Reviewer #1 (Public review):

Summary:

The authors address the role of the centromere histone core in force transduction by the kinetochore.

Strengths:

They use a hybrid DNA sequence that combines CDEII and CDEIII as well as Widom 601 so they can make stable histones for biophysical studies (provided by the Widom sequence) and maintain features of the centromere (CDE II and III).

Weaknesses:

The main results are shown in one figure (Figure 2). Indeed the Centromere core of Widom and CDE II and III contribute to strengthening the binding force for the OA-beads. The data are very nicely done and convincingly demonstrate the point. The weakness is that this is the entire paper. It is certainly of interest to investigators in kinetochore biology, but beyond that, the impact is fairly limited in scope.

Reviewer #2 (Public review):

Summary:

This paper provides a valuable addendum to the findings described in Hamilton et al. 2020 (https://doi.org/ 10.7554/eLife.56582). In the earlier paper, the authors reconstituted the budding yeast centromeric nucleosome together with parts of the budding yeast kinetochore and tested which elements are required and sufficient for force transmission from microtubules to the nucleosome. Although budding yeast centromeres are defined by specific DNA sequences, this earlier paper did not use centromeric DNA but instead the generic Widom 601 DNA. The reason is that it has so far been impossible to stably reconstitute a budding yeast centromeric nucleosome using centromeric DNA.

In this new study, the authors now report that they were able to replace part of the Widom 601 DNA with centromeric DNA from chromosome 3. This makes the assay more closely resemble the in vivo situation. Interestingly, the presence of the centromeric DNA fragment makes one type of minimal kinetochore assembly, but not the other, withstand stronger forces.

Which kinetochore assembly turned out to be affected was somewhat unexpected, and can currently not be reconciled with structural knowledge of the budding yeast centromere/kinetochore. This highlights that, despite recent advances (e.g. Guan et al., 2021; Dendooven et al., 2023), aspects of budding yeast kinetochore architecture and function remain to be understood and that it will be important to dissect the contributions of the centromeric DNA sequence.

Given the unexpected result, the study would become yet more informative if the authors were able to pinpoint which interactions contribute to the enhanced force resistance in the presence of centromeric DNA.

Strength:

The paper demonstrates that centromeric DNA can increase the attachment strength between budding yeast microtubules and centromeric nucleosomes.

Weakness:

How centromeric DNA exerts this effect remains unclear.

Author response:

Reviewer #1:

Summary:

The authors address the role of the centromere histone core in force transduction by the kinetochore.

Strengths:

They use a hybrid DNA sequence that combines CDEII and CDEIII as well as Widom 601 so they can make stable histones for biophysical studies (provided by the Widom sequence) and maintain features of the centromere (CDE II and III).

Weaknesses:

The main results are shown in one figure (Figure 2). Indeed the Centromere core of Widom and CDE II and III contribute to strengthening the binding force for the OA-beads. The data are very nicely done and convincingly demonstrate the point. The weakness is that this is the entire paper. It is certainly of interest to investigators in kinetochore biology, but beyond that, the impact is fairly limited in scope.

This reviewer might have missed that this is a Research Advance, not an article.  Research Advances are limited in scope by definition and provide a new development that builds on research reported in a prior paper.  They can be of any length.  Our Research Advance builds on our prior work, Hamilton et al., 2020 and provides the new result that native centromere sequences strengthen the attachment of the kinetochore to the nucleosome.

Reviewer #2:

Summary:

This paper provides a valuable addendum to the findings described in Hamilton et al. 2020 (https://doi.org/ 10.7554/eLife.56582). In the earlier paper, the authors reconstituted the budding yeast centromeric nucleosome together with parts of the budding yeast kinetochore and tested which elements are required and sufficient for force transmission from microtubules to the nucleosome. Although budding yeast centromeres are defined by specific DNA sequences, this earlier paper did not use centromeric DNA but instead the generic Widom 601 DNA. The reason is that it has so far been impossible to stably reconstitute a budding yeast centromeric nucleosome using centromeric DNA.

In this new study, the authors now report that they were able to replace part of the Widom 601 DNA with centromeric DNA from chromosome 3. This makes the assay more closely resemble the in vivo situation. Interestingly, the presence of the centromeric DNA fragment makes one type of minimal kinetochore assembly, but not the other, withstand stronger forces.

We thank the reviewer for their careful and positive assessment of our work.

Which kinetochore assembly turned out to be affected was somewhat unexpected, and can currently not be reconciled with structural knowledge of the budding yeast centromere/kinetochore. This highlights that, despite recent advances (e.g. Guan et al., 2021; Dendooven et al., 2023), aspects of budding yeast kinetochore architecture and function remain to be understood and that it will be important to dissect the contributions of the centromeric DNA sequence.

We couldn’t agree more.

Given the unexpected result, the study would become yet more informative if the authors were able to pinpoint which interactions contribute to the enhanced force resistance in the presence of centromeric DNA.

Strength:

The paper demonstrates that centromeric DNA can increase the attachment strength between budding yeast microtubules and centromeric nucleosomes.

Weakness:

How centromeric DNA exerts this effect remains unclear.

eLife Assessment

In this work, the authors use a Drosophila melanogaster adult ventral nerve cord injury model extending and confirming previous observations. This important study reveals key aspects of adult neural plasticity. Taking advantage of several genetic reporter and fate tracing tools, the authors provide solid evidence for different forms of glial plasticity, that are increased upon injury. The significance of the generated cell types under homeostatic conditions and in response to injury remains to be further explored and open up new avenues of research.

Reviewer #2 (Public review):

Summary:

Casas-Tinto et al., provide new insight into glial plasticity using a crush injury paradigm in the ventral nerve cord (VNC) of adult Drosophila. The authors find that both astrocyte-like glia (ALG) and ensheating glia (EG) divide under homeostatic conditions in the adult VNC and identify ALG as the glial population that specifically ramps up proliferation in response to injury, whereas the number of EGs decreases following the insult. Using lineage-tracing tools, the authors interestingly observe interconversion of glial subtypes, especially of EGs into ALGs, which occurs independent of injury and is dependent on the availability of the transcription factor Prospero in EGs, adding to the plasticity observed in the system. Finally, when tracing the progeny of glia, Casas-Tinto and colleagues detect cells of neuronal identity and provide evidence that such glia-derived neurogenesis is favored following ventral nerve cord injury, which puts forward a remarkable way in which glia can respond to neuronal damage.

Strengths:

This study highlights a new facet of adult nervous system plasticity at the level of the ventral nerve cord, supporting the view that proliferative capacity is maintained in the mature CNS and stimulated upon injury.

The injury paradigm is well chosen, as the organization of the neuromeres allows specific targeting of one segment, compared to the remaining intact and with the potential to later link observed plasticity to behavior such as locomotion.

Numerous experiments have been carried out in 7-day old flies, showing that the observed plasticity is not due to residual developmental remodeling or a still immature VNC.

Different techniques are used to observe proliferation in the VNC.

By elegantly combining different methods, the authors show glial divisions including with mitotic-dependent tracing and find that the number of generated glia is refined by apoptosis later on.

The work identifies prospero in glia as important coordinator of glial cell fate, from development to the adult context, which draws further attention to the upstream regulatory mechanisms.

Weaknesses:

The authors do not discuss their results on gliogenesis or neurogenesis in the adult VNC to previous findings made in the context of the injured adult brain.

The authors speculate about the role of glial inter-conversion for tissue homeostasis or regeneration, but no supportive evidence is cited or provided. Further experiments will be required to test the function of the described glial plasticity.

Elav+ cells originating from glia do not express markers for mature neurons at the analysed time-point. If they will eventually differentiate<br /> or what type of structure is formed by them will have to be followed up in future studies.

Context/Discussion

Highlighting some differences in the reactiveness of glia in the VNC compared to the brain could reveal important differences in repair strategies in different areas of the CNS.

Reviewer #3 (Public review):

In this manuscript, Casas-Tintó et al. explore the role of glial cell in the response to a neurodegenerative injury in the adult brain. They used Drosophila melanogaster as a model organism, and found that glial cells are able to generate new neurons through the mechanism of transdifferentiation in response to injury. This paper provides a new mechanism in regeneration, and gives an understanding to the role of glial cells in the process.

The authors have now addressed all my concerns.

Author response:

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

eLife Assessment

In this work, the authors use a Drosophila adult ventral nerve cord injury model extending and confirming previous observations; this important study reveals key aspects of adult neural plasticity. Taking advantage of several genetic reporter and fate tracing tools, the authors provide solid evidence for different forms of glial plasticity, that are increased upon injury. The data on detected plasticity under physiologic conditions and especially the extent of cell divisions and cell fate changes upon injury would benefit from validation by additional markers. The experimental part would improve if strengthened and accompanied by a more comprehensive integration of results regarding glial reactivity in the adult CNS.

Thank you very much for your thoughtful comments and constructive feedback regarding our manuscript. We appreciate all the positive remarks on the significance of our findings on neural plasticity in this Drosophila adult ventral nerve cord injury model.

In response to your suggestion, we fully agree that the continuation of this project should address in detail cell fate changes with additional markers if available, or an “omic” approach such as scRNAseq. Unfortunately, these further experiments are beyond the scope of this paper to describe the in vivo phenomena of cell reprogramming, and the cellular events that take glial cells to convert into neurons or neuronal precursors.

Additionally, we agree that the experimental part can be further improved by providing a more comprehensive integration of our results with current knowledge on glial reactivity in the adult CNS. We will revise the manuscript accordingly to include a deeper discussion of the broader implications of our findings and their alignment with existing literature.

Thank you again for your valuable input, which will undoubtedly enhance the quality of our work. We look forward to submitting the revised manuscript for your consideration.

Public Reviews:

Reviewer #1 (Public review):

Summary:

Casas-Tinto et al. present convincing data that injury of the adult Drosophila CNS triggers transdifferentiation of glial cell and even the generation of neurons from glial cells. This observation opens up the possibility to get an handle on the molecular basis of neuronal and glial generation in the vertebrate CNS after traumatic injury caused by Stroke or Crush injury. The authors use an array of sophisticated tools to follow the development of glial cells at the injury site in very young and mature adults. The results in mature adults reveal a remarkable plasticity in the fly CNS and dispels the notion that repair after injury may be only possible in nerve cords which are still developing. The observation of so called VC cells which do not express the glial marker repo could point to the generation of neurons by former glial cells.

Conclusion:

The authors present an interesting story which is technically sound and could form the basis for an in depth analysis of the molecular mechanism driving repair after brain injury in Drosophila and vertebrates.

Strengths:

The evidence for transdifferentiation of glial cells is convincing. In addition, the injury to the adult CNS shows an inherent plasticity of the mature ventral nerve cord which is unexpected.

Weaknesses:

Traumatic brain injury in Drosophila has been previously reported to trigger mitosis of glial cells and generation of neural stem cells in the larval CNS and the adult brain hemispheres. Therefore this report adds to but does not significantly change our current understanding. The origin and identity of VC cells is still unclear. The authors show that VC cells are not GABA- or glutamergic. Yet, there are many other neurotransmitter or neuropetides. It would have been nice to see a staining with another general neuronal marker such as anti-Syt1 to confirm the neuronal identity of Syt1.

We thank the reviewer for the constructive comments and positive feedback. We concur that previous studies have demonstrated glial cell proliferation in response to CNS injury. In contrast, our study focuses on glial transdifferentiation that emerges as a novel phenomenon, particularly in response to injury. We found that neuropile glia lose their glial identity and express the pan-neuronal marker Elav. To investigate the identity of these newly observed elav-positive cells, we employed anti-ChAT, antiGABA and anti-GluRIIA antibodies to determine the functional identity of these cells, besides we stained them with other neuronal markers such Enabled, Gigas or Dac (not shown); however, our attempts yielded limited success. To address this, we have now included a discussion section exploring the potential identity of these cells, considering the possibility that they may represent immature neurons.

Reviewer #2 (Public review):

Summary:

Casas-Tinto et al., provide new insight into glial plasticity using a crush injury paradigm in the ventral nerve cord (VNC) of adult Drosophila. The authors find that both astrocyte-like glia (ALG) and ensheating glia (EG) divide under homeostatic conditions in the adult VNC and identify ALG as the glial population that specifically ramps up proliferation in response to injury, whereas the number of EGs decreases following the insult. Using lineage-tracing tools, the authors interestingly observe interconversion of glial subtypes, especially of EGs into ALGs, which occurs independent of injury and is dependent on the availability of the transcription factor Prospero in EGs, adding to the plasticity observed in the system. Finally, when tracing the progeny of glia, Casas-Tinto and colleagues detect cells of neuronal identity and provide evidence that such gliaderived neurogenesis is specifically favoured following ventral nerve cord injury, which puts forward a remarkable way in which glia can respond to neuronal damage.

Strengths:

This study highlights a new facet of adult nervous system plasticity at the level of the ventral nerve cord, supporting the view that proliferative capacity is maintained in the mature CNS and stimulated upon injury.

The injury paradigm is well chosen, as the organization of the neuromeres allows specific targeting of one segment, compared to the remaining intact and with the potential to later link observed plasticity to behaviour such as locomotion.

Numerous experiments have been carried out in 7-day old flies, showing that the observed plasticity is not due to residual developmental remodelling or a still immature VNC.

By elegantly combining different methods, the authors show glial divisions including with mitotic-dependent tracing and find that the number of generated glia is refined by apoptosis later on.

The work identifies prospero in glia as an important coordinator of glial cell fate, from development to the adult context, which draws further attention to the upstream regulatory mechanisms.

We would like to thank the reviewer for his/her comments and the positive analysis of this work.

Weaknesses:

The authors observe consistent inter-conversion of EG to ALG glial subtypes that is further stimulated upon injury. The authors conclude that these findings have important consequences for CNS regeneration and potentially for memory and learning. However, it remains somewhat unclear how glial transformation could contribute to regeneration and functional recovery.

This is an ongoing question in the laboratory and in the field. We know that glial cells contribute to the regenerative program in the nervous system, and molecular signalling in glial cells is determinant for the functional recovery (Losada-Perez et al 2021). Therefore, we include this concept in the discussion as the evidence indicates that glial cells participate in these programs. However, further investigation is required to clarify and determine the mechanisms underlying this glial contribution. To determine if glial to neuron transformation contributes to functional recovery, we would need to compare the recovery of animals with new VC to animals without VC, however, the  molecular mechanism that produces this change of identity is still unknown, and therefore we are not able to generate injured flies with no new VC

The signal of the Fucci cell cycle reporter seems more complex to interpret based on the panels provided compared to the other methods employed by the authors to assess cell divisions.

We agree that Fly Fucci is a genetic reporter that might be more complex to interpret than EdU staining or other markers. However, glial cells proliferation is a milestone of this manuscript, and we used different available tools to confirm our results. We have revised this specific section to ensure that the text is clear and straightforward.

Elav+ cells originating from glia do not express markers for mature neurons at the analysed time-point. If they will eventually differentiate or what type of structure is formed by them will have to be followed up in future studies.

We fully agree with the reviewer, and we will analyze later days to study neuronal fate and contribution to VNC function.

Context/Discussion

There is some lack of connecting or later comparing the observed forms of glial plasticity in the VNC with respect to plasticity described in the fly brain.

Highlighting some differences in the reactiveness of glia in the VNC compared to the brain could point to relevant differences in repair capacity in different areas of the CNS.

Based on the assays employed, the study points to a significant amount of glial "identity" changes or interconversions under homeostatic conditions. The potential significance of this rather unexpected "baseline" plasticity in adult tissues is not explicitly pointed out and could improve the understanding of the findings.

Some speculations if "interconversion" of glia is driven by the needs in the tissue could enrich the discussion.

We would like to thank the reviewer for these suggestions. We have changed the discussion to introduce these concepts.

Reviewer #3 (Public review):

In this manuscript, Casas-Tintó et al. explore the role of glial cell in the response to a neurodegenerative injury in the adult brain. They used Drosophila melanogaster as a

model organism, and found that glial cells are able to generate new neurons through the mechanism of transdifferentiation in response to injury. This paper provides a new mechanism in regeneration, and gives an understanding to the role of glial cells in the process.

Comments on revisions:

In the previous version of the manuscript, I had suggested several recommendations for the authors. Unfortunately, none of these were addressed in the author's revision.

We are sorry for this error. We apologize but we never received these comments. We have now found them, and we have incorporated these comments in the new version of the manuscript.

(1) Have you tried screening for other markers for the EdU+ Repo+ Pros- cells?

We have identified these cells as glial cells (Repo +), and not astrocyte-like glia (pros-). But we have not further characterized  the identity of these cells. Our aim was to identify these proliferating glial cells as NPG (Neuropile glia), which are Astrocyte-Like Glia (ALG), as previous works suggest in larvae (Kato et al., 2020; Losada-Perez et al., 2016), or Ensheathing Glia (EG). To discard the ALG identity, we used prospero as the best marker. The results indicate that there are ALG among the proliferating population, but in addition, we also found pros- glial cells that were EdU positive. These cells are located in the interface between cortex and neuropile, where the neuropile glia position is described. The anti-pros staining indicated they were no ALG which suggest that they are EG.

There is no specific nuclear marker for EG cells, therefore we used FLY_FUCCI under the control of a EG specific promoter (R56F03-Gal4) to determine if the other dividing cells were EG. These results indicate that EG glia divide although their proliferation does not increase upon injury.

The R56F03 Gal4 construct is described as ensheathing glia specific by previous publications, including:

(1) Kremer M. C., Jung C., Batelli S., Rubin G. M. and Gaul U. (2017). The glia of the adult Drosophila nervous system. Glia 65, 606-638. 10.1002/glia.23115

(2) Qingzhong Ren, Takeshi Awasaki, Yu-Chun Wang, Yu-Fen Huang, Tzumin Lee. Lineage-guided Notch-dependent gliogenesis by Drosophila multi-potent progenitors. Development. 2018 Jun 11;145(11):dev160127. doi: 10.1242/dev.160127   

To summarize, our results suggest that part of these proliferating glial cells are ALG and EG. Our results can not discard that a residual part of these proliferating cells are not AG nor EG.

(2) You mentioned that ALG are heterogenous in size and shape, does that mean that you may have different subpopulations of ALG? Would that also mean that only a portion of them responds to injury?

Yes, as in Astrocytes in vertebrates this population is highly heterogeneous. Currently there are no molecular tools to specifically identify these subpopulations and characterize their distinct roles. However, emerging research suggests that differences in size, shape, and potentially molecular markers could correlate with functional diversity. This implies that certain subpopulations of ALG may be more specialized or primed to respond to injury, while others may play roles in homeostasis or other processes. Understanding this heterogeneity will require advanced techniques such as single-cell RNA sequencing, spatial transcriptomics, or live imaging to unravel how these subpopulations contribute to injury responses and overall tissue dynamics.

(3) You mentioned that NP-like cells have similar nuclear shape and size to ALG and EG, while Ventral cortex cells have larger nuclei. Can you please show a quantification of the NP-like cells and Ventral cortex cells size, and show a direct comparison with ALG and EG cells to support those claims (images, quantification and analysis)?

We added a new supplementary figure with a graph showing nuclei size differences between VC and NP-like cells, and a diagram showing VC cell localization. Images in figure 2A-A’ and 2B-B’ show both types of cells with the same scale, additionally, NPG cells are shown in red (current expression of the specific Gal4 line). A direct comparison between EG and NP-like glia can be observed in Figure 3 as well.

Besides of size and localization, we conclude  that VC and N-like cells present different molecular markers as VC are elav-positive and reponegative whereas NP-like cells are repo-positive elav-negative

(4) In Figure 2B, the repo expression is not very clear. I suggest using a different example to support the claim that NP cells are Repo+.

We have changed the color of anti-elav staining to facilitate visualisation

(5) Again, in Figure 2C, you need quantification and analysis to support the claim that you used nuclear shape and size to identify VC vs. NP like cells.

Quantification in point 3, criteria in Figure S1

(6) What is the identity of the newly formed neurons? Other than Elav, have you tried using other markers of neurons that are typically found in this area?

This question is of great interest and relevance. We have done great efforts to solve this open question and so far, our data suggest that these neurons might be in an immature state. In this last version of the manuscript, we included the results (Figure S1) with several different markers. 

The molecular identity of these cell populations, glia and neurons, is currently under investigation.

Minor comments:

(1) In the abstract, EG and ALG abbreviations are not introduced properly.

Thank you very much for noticing this missing information, we have now included it in the abstract.

(2) Please include a representation of the NPG somata location in Figure 1A.

We have included this information in the figure

(3) A schematic showing the differences between ALG and EG cells would be helpful as well.

We have included in the introduction references and reviews where other authors describe in detail the differences.

(4) In Figure 1 E, G, H- please indicated the genotype of the fly used in the panel as well as the cell type studied.

The complete genotype is included in the corresponding figure legend. We have added a simplified genotype in the figure for clarity.

(5) Please show the genotype used for images in Figure 2: ALG or EG specific drivers.

This information is included in the corresponding figure legend. We believe that it is better to keep the figure clean so we decided to keep the complete genotype, which is considerably long, only in the figure legend.

eLife Assessment

This study presents valuable findings by using Fmr1 knockout mice as a model to investigate the role of Fmr1 in sleep regulation. These mice exhibited clear evidence of sleep and circadian disturbances, including abnormal retinal innervation of the SCN, which may provide a potential mechanistic explanation for the observed behavioral deficits. Interestingly, the results suggest that a scheduled feeding approach could improve sleep and circadian rhythms while enhancing social interactions and reducing repetitive behaviors in a mouse model of Fragile X syndrome. The topic is both intriguing and highly significant; however, while the evidence supporting the authors' claims is solid, several issues hinder the manuscript's clarity and impact.

Reviewer #1 (Public review):

Summary:

The authors investigated sleep and circadian rhythm disturbances in Fmr1 KO mice. Initially, they monitored daily home cage behaviors to assess sleep and circadian disruptions. Next, they examined the adaptability of circadian rhythms in response to photic suppression and skeleton photic periods. To explore the underlying mechanisms, they traced retino-suprachiasmatic connectivity. The authors further analyzed the social behaviors of Fmr1 KO mice and tested whether a scheduled feeding strategy could mitigate sleep, circadian, and social behavior deficits. Finally, they demonstrated that scheduled feeding corrected cytokine levels in the plasma of mutant mice.

Strengths:

(1) The manuscript addresses an important topic-investigating sleep deficits in an FXS mouse model and proposing a potential therapeutic strategy.

(2) The study includes a comprehensive experimental design with multiple methodologies, which adds depth to the investigation.

Weaknesses:

(1) The first serious issue in the manuscript is the lack of a clear description of how they performed the experiments and the missing definitions of various parameters in the results. Given that monitoring and analyzing sleep behaviors are the key experiments of this manuscript, I use the "Immobility-Based Sleep Behavior" section of Methods as an example to elaborate:

Incomplete or Incorrect Description of Tracking Threshold:<br /> o The phrase "tracked the (40 sec or greater as previously described" is incomplete and does not clarify what is being tracked. This appears to be an error in writing or editing.<br /> Unclear Relationship Between Threshold and EEG Validation:<br /> o The threshold "40 sec or greater" is mentioned without context or explanation of what it represents (e.g., sleep bout duration, inactivity, or another parameter). The reference to Fisher et al. (2016) and "99% correlation with EEG-defined sleep" seems misaligned with the paragraph's content.

Confusing Definition of Sleep Bout:<br /> o The definition of a sleep bout is unclear. Sleep bouts should logically be based on periods of inactivity, not activity. The sentence suggesting sleep is measured by "activity staying above the threshold" is confusing. The phrase "3 counts of sleep per minute for longer than one minute" requires clarification.

Unclear Data Selection for Analysis:<br /> o The phrase "2 days with the best recording quality" is vague and does not specify how "best" was determined or why only two days out of five were analyzed.

Awkward Grammar and Structure:<br /> o Phrases like "Acquiring data were exported in 1-min bins" are grammatically awkward. "Acquiring" should be "Acquired." Some sentences are overly long and lack clarity, making the text harder to follow.<br /> In addition to this section, the authors should review all paragraphs in the Methods section to improve readability.

(2) Although the manuscript has a relatively long Methods section, some essential information is missing. For instance, the definition of sleep bout, as described above, is unclear. Additional missing information includes:

Figure 2: "Rhythmic strength (%)" and "Cycle-to-cycle variability (min)."<br /> Figure 3: "Activity suppression."<br /> Figure 4: "Rhythmic power (V%)" (is this different from rhythmic strength (%)?) and "Subjective day activity (%)."<br /> Figure 5: Clear labeling of the SCN's anatomical features and an explanation for quantifying only the ventral part instead of the entire SCN. Alternatively, the authors should consider quantifying the whole SCN.<br /> Figure 6: Inconsistencies in terms like "Sleep frag. (bout #)" and "Sleep bouts (#)." Consistent terminology throughout the manuscript is essential.

(3) Figure 1A shows higher mouse activity during ZT13-16. It is unclear why the authors scheduled feeding during ZT15-21, as this seems to disturb the rhythm. Consistent with this, the body weights of WT and Fmr1 KO mice decreased after scheduled feeding. The authors should explain the rationale for this design clearly.

(4) The interpretation of social behavior results in Figure 6 is questionable. The authors claim that Fmr1 KO mice cannot remember the first stranger in a three-chamber test, writing, "The reduced time in exploring and staying in the novel-mouse chamber suggested that the Fmr1 KO mutants were not able to distinguish the second novel mouse from the first now-familiar mouse." However, an alternative explanation is that Fmr1 KO mice do remember the first stranger but prefer to interact with it due to autistic-like tendencies. Data in Table 5 show that Fmr1 KO mice spent more time interacting with the first stranger in the 3-chamber social recognition test, which support this possibility. Similarly, in the five-trial social test, Fmr1 KO mice's preference for familiar mice might explain the reduced interaction with the second stranger.

In Figure 6C (five-trial social test results), only the fifth trial results are shown. Data for trials 1-4 should be provided and compared with the fifth trial. The behavioral features of mice in the 5-trial test can then be shown completely. In addition, the total interaction times for trials 1-4 (154 {plus minus} 15.3 for WT and 150 {plus minus} 20.9 for Fmr1 KO) suggest normal sociability in Fmr1 KO mice (it is different from the results of 3-chamber). Thus, individual data for trials 1-4 are required to draw reliable conclusions.

In Table 6 and Figure 6G-6J, the authors claim that "Sleep duration (Figures 6G, H) and fragmentation (Figures 6I, J) exhibited a moderate-strong correlation with both social recognition and grooming." However, Figure 6I shows a p-value of 0.077, which is not significant. Moreover, Table 6 shows no significant correlation between SNPI of the three-chamber social test and any sleep parameters. These data do not support the authors' conclusions.

(5) Figure 7 demonstrates the effect of scheduled feeding on circadian activity and sleep behaviors, representing another critical set of results in the manuscript. Notably, the WT+ALF and Fmr1 KO+ALF groups in Figure 7 underwent the same handling as the WT and Fmr1 KO groups in Figures 1 and 2, as no special treatments were applied to these mice. However, the daily patterns observed in Figures 7A, 7B, 7F, and 7G differ substantially from those shown in Figures 2B and 1A, respectively. Additionally, it is unclear why the WT+ALF and Fmr1 KO+ALF groups did not exhibit differences in Figures 7I and 7J, especially considering that Fmr1 KO mice displayed more sleep bouts but shorter bout lengths in Figures 1C and 1D.

Furthermore, it is not specified whether the results in Figure 7 were collected after two weeks of scheduled feeding (for how many days?) or if they represent the average data from the two-week treatment period.

The rationale behind analyzing "ZT 0-3 activity" in Figure 7D instead of the parameters shown in Figures 2C and 2D is also unclear.

In Figure 7F, some data points appear to be incorrectly plotted. For instance, the dark blue circle at ZT13 connects to the light blue circle at ZT14 and the dark blue circle at ZT17. This is inconsistent, as the dark blue circle at ZT13 should link to the dark blue circle at ZT14. Similarly, it is perplexing that the dark blue circle at ZT16 connects to both the light blue and dark blue circles at ZT17. Such errors undermine confidence in the data. The authors need to provide a clear explanation of how these data were processed.

Lastly, in the Figure 7 legend, Table 6 is cited; however, this appears to be incorrect. It seems the authors intended to refer to Table 7.

(6) Similar to the issue in Figure 7F, the data for day 12 in Supplemental Figure 2 includes two yellow triangles but lacks a green triangle. It is unclear how the authors constructed this chart, and clarification is needed.

(7) In Figure 8, a 5-trial test was used to assess the effect of scheduled feeding on social behaviors. It is essential to present the results for all trials (1 to 4). Additionally, it is unclear whether the results for familial mice in Figure 8A correspond to trials 1, 2, 3, or 4.<br /> The legend for Figure 8 also appears to be incorrect: "The left panels show the time spent in social interactions when the second novel stranger mouse was introduced to the testing mouse in the 5-trial social interaction test. The significant differences were analyzed by two-way ANOVA followed by Holm-Sidak's multiple comparisons test with feeding treatment and genotype as factors." This description does not align with the content of the left panels. Moreover, two-way ANOVA is not the appropriate statistical analysis for Figure 8A. The authors need to provide accurate details about the analysis and revise the figure legend accordingly.

(8) The circadian activity and sleep behaviors of Fmr1 KO mice have been reported previously, with some findings consistent with the current manuscript, while others contradict it. Although the authors acknowledge this discrepancy, it seems insufficiently thorough to simply state that the reasons for the conflicts are unknown. Did the studies use the same equipment for behavior recording? Were the same parameters used to define locomotor activity and sleep behaviors? The authors are encouraged to investigate these details further, as doing so may uncover something interesting or significant.

(9) Some subtitles in the Results section and the figure legends do not align well with the presented data. For example, in the section titled "Reduced rhythmic strength and nocturnality in the Fmr1 KOs," it is unclear how the authors justify the claim of altered nocturnality in Fmr1 KO mice. How do the authors define changes in nocturnality? Additionally, the tense used in the subtitles and figure legends is incorrect. The authors are encouraged to carefully review all subtitles and figure legends to correct these errors and enhance readability.

Reviewer #2 (Public review):

Summary:

In the present study, the authors, using a mouse model of Fragile X syndrome, explore the very interesting hypothesis that restricting food access over a daily schedule will improve sleep patterns and, subsequently, behavioral capacities. By restricting food access from 12h to 6h over the nocturnal period (active period for mice), they show, in these KO mice, an improvement of the sleep pattern accompanied by reduced systemic levels of inflammatory markers and improved behavior. Using a classical mouse model of neurodevelopmental disorder (NDD), these data suggest that eating patterns might improve sleep quality, reduce inflammation and improve cognitive/behavioral capacities in children with NDD.

Strengths:

Overall, the paper is very well-written and easy to follow. The rationale of the study is generally well-introduced. The data are globally sound. The provided data support the interpretation overall.

Weaknesses:

(1) The introduction part is quite long in the Abstract, leaving limited space for the data provided by the present study.

(2) A couple of points are not totally clear for a non-expert reader:<br /> - The Fmr1/Fxr2 double KO mice are not well described.<br /> - What is the rationale for performing both LD and DD measures?

(3) The data on cytokines and chemokines are interesting. However, the rationale for the selection of these molecules is not given. In addition, these measures have been performed in the systemic blood. Measures in the brain could be very informative.

(4) An important question is the potential impact of fasting vs the impact of the food availability restriction. Indeed fasting has several effects on brain functioning including cognitive functions.

(5) How do the authors envision the potential translation of the present study to human patients? How to translate the 12 to 6 hours of food access in mice to children with Fragile X syndrome?

eLife Assessment

This study presents an important discovery regarding the diversity and evolution of gall-forming microbial effectors. Supported by convincing computational structural predictions and analyses, the research provides insights into the unique mechanisms by which gall-forming microbes exert their pathogenicity in plants. This study also offers guidance that is of value for future studies on pathogen effector function and co-evolution with host plants.

Reviewer #1 (Public review):

Summary:

This manuscript presents a comprehensive structure-guided secretome analysis of gall-forming microbes, providing valuable insights into effector diversity and evolution. The authors have employed AlphaFold2 to predict the 3D structures of the secretome from selected pathogens and conducted a thorough comparative analysis to elucidate commonalities and unique features of effectors among these phytopathogens.

Strengths:

The discovery of conserved motifs such as 'CCG' and 'RAYH' and their central role in maintaining the overall fold is an insightful finding. Additionally, the discovery of a nucleoside hydrolase-like fold conserved among various gall-forming microbes is interesting.

Weaknesses:

Important conclusions are not verified by experiments.

Reviewer #2 (Public review):

Summary:

Soham Mukhopadhyay et al. investigated the protein folding of the secretome from gall-forming microbes using the AI-based structure modeling tool AlphaFold2. Their study analyzed six gall-forming species, including two Plasmodiophorid species and four others spanning different kingdoms, along with one non-gall-forming Plasmodiophorid species, Polymyxa betae. The authors found no effector fold specifically conserved among gall-forming pathogens, leading to the conclusion that their virulence strategies are likely achieved through diverse mechanisms. However, they identified an expansion of the Ankyrin repeat family in two gall-forming Plasmodiophorid species, with a less pronounced presence in the non-gall-forming Polymyxa betae. Additionally, the study revealed that known effectors such as CCG and AvrSen1 belong to sequence-unrelated but structurally similar (SUSS) effector clusters.

Strengths:

(1) The bioinformatics analyses presented in this study are robust, and the AlphaFold2-derived resources deposited in Zenodo provide valuable resources for researchers studying plant-microbe interactions. The manuscript is also logically organized and easy to follow.

(2) The inclusion of the non-gall-forming Polymyxa betae strengthens the conclusion that no effector fold is specifically conserved in gall-forming pathogens and highlights the specific expansion of the Ankyrin repeat family in gall-forming Plasmodiophorids.

(3) Figure 4a and 4b effectively illustrate the SUSS effector clusters, providing a clear visual representation of this finding.

(4) Figure 1 is a well-designed, comprehensive summary of the number and functional annotations of putative secretomes in gall-forming pathogens. Notably, it reveals that more than half of the analyzed effectors lack known protein domains in some pathogens, yet some were annotated based on their predicted structures, despite the absence of domain annotations.

Weaknesses:

(1) The effector families discussed in this paper remain hypothetical in terms of their functional roles, which is understandable given the challenges of demonstrating their functions experimentally. However, this highlights the need for experimental validation as a next step.

(2) Some analyses, such as those in Figure 4e, emphasize motifs derived from sequence alignments of SUSS effector clusters. Since these effectors are sequence-unrelated, sequence alignments might be unreliable. It would be more rigorous to perform structure-based alignments in addition to sequence-based ones for motif confirmation. For instance, methods described in Figure 3E of de Guillen et al. (2015, https://doi.org/10.1371/journal.ppat.1005228) or tools like Foldseek (https://search.foldseek.com/foldmason) could be useful for aligning structures of multiple sequences.

(3) When presenting AlphaFold-generated structures, it is essential to include confidence scores such as pLDDT and PAE. For example, in Figure 1D of Derbyshire and Raffaele (2023, https://doi.org/10.1038/s41467-023-40949-9), the structural representations were colored red due to their high pLDDT scores, emphasizing their reliability.

Author response:

We appreciate the constructive feedback provided by the reviewers and the editorial board. We are delighted by the positive reception of our work and the thoughtful insights shared.

Regarding the validation of our predicted interactions, we are currently conducting yeast two-hybrid (Y2H) assays using a commercially available Arabidopsis thaliana cDNA library to screen for interacting partners of the ANK putative effector PBTT_00818 from Plasmodiophora brassicae. Following this initial screening, we will validate positive interactions through targeted 1-to-1 Y2H assays. In particular, we aim to confirm the AlphaFold Multimer-predicted interaction between PBTT_00818 and MPK3, a key immunity-related kinase in Arabidopsis. 

We are grateful for the reviewers’ thoughtful suggestions regarding clustering visualization, sequence vs. structure-based motif alignments, and structural confidence assessments. We will carefully incorporate these improvements in our planned revisions.

Once again, we thank the editors and reviewers for their rigorous and constructive assessment. We look forward to implementing these refinements and submitting an updated version that further enhances the impact of our study.

eLife Assessment

This important study reports a detailed computational analysis of the CFTR ion channel's permeation mechanism, advancing our understanding of its structure-function relationship. The conclusions are based on extensive molecular dynamics simulations and thorough analysis, but the use of an approximate chloride ion model, known to underestimate key ion-protein interactions, leaves them incomplete without experimental or alternative computational validation. The work will be of interest to biophysicists working on CFTR and cystic fibrosis.

Reviewer #1 (Public review):

Summary:

The goal of this study was to overcome the apparent difficulty in constructing structural models of the open state of the CFTR chloride channel. While several CFTR structural models at near-atomic resolution have been published under a variety of conditions, none of them have demonstrated a pore open across the full dimension of the plasma membrane. Instead, these have routinely been referred to as "near-open" models. In the present study, the authors extended their findings from a prior paper from their group that investigated a series of brief MD simulations, a small number of which exhibited permeation events where chloride ions permeated the pore. This study included massively repeated simulations initiated from these aforementioned Cl permeable conformations. Extensive analysis of the data identified a novel penta-helical structure that comprises the channel pore. This comprehensive study attempted to explain several features of conducting CFTR channels, including single-channel conductance, selectivity, and the mechanisms linking the ATP-induced dimerization of the cytosolic nucleotide-binding domains (NBDs) to the opening of the channel pore (a.k.a., "pore-gating".

Strengths:

The major strength of this study is its comprehensive nature. The approaches applied are cutting-edge and beyond, and are used to explain many different aspects of channel function in CFTR. The strength of evidence is very strong. The paper is extremely well-written, and the arguments are well-supported.

Weaknesses:

The major weakness is that none of the novel conclusions (i.e., those arising solely from this study and not previously published (have been supported by experimental confirmation. That is typical of computational studies such as this.

Reviewer #2 (Public review):

Although recent cryo-EM structures of the CFTR ion channel were reported in a putative open state (ATP-bound, NBD-dimerized), it remains unclear whether these structures explain the conductive properties of the open channel observed in functional experiments. To investigate this, the authors conducted extensive molecular dynamics simulations at different voltages. The simulations are started from snapshots of their prior work, based on the experimental putative open state and including conditions with high negative voltage. Their analysis reveals that the cryo-EM structure represents a near-open metastable state, with most trajectories transitioning to either more closed or more open conformations, leading to the identification of a potential new open state. Permeation rate analysis shows that, unlike the other states, the proposed open state exhibits functional conductive properties of the open channel, although a strong inward rectification, inconsistent with experimental data, is also noted. Further structural analysis and simulations of ATP-unbound closed states offer additional mechanistic insights.

Overall, this work tackles key questions about CFTR: What is the true open conductive state? Does the ATP-bound cryo-EM structure reflect an actual open state? What is the ion permeation mechanism, and what structural changes occur during the closed-to-open transition? Which residues are critical, particularly those linked to diseases like CF? The study, based on a comprehensive set of all-atom molecular dynamics simulations, including a range of physiologically relevant voltages, provides important insights in this regard. It identifies key structural states, permeation pathways, critical residues, and conductance properties that can be directly compared to functional data. Notably, the analysis identifies a new open state of the channel, which, systematic analysis convincingly demonstrates is a conductive conformation of the channel, in line with experimental data at negative voltages. The authors carefully address some of the limitations of their results, exploring and discussing discrepancies with functional experiments, such as inward rectification. The work is also very well written, with a clear and logical presentation of key findings.

The main weakness of this study is that the simulation data rely on the conventional CHARMM36 force field for Cl− ions, which has been shown to significantly underestimate the interaction between Cl− and proteins (J. Chem. Theory Comput. 2021, 17, 6240-6261). For example, the conventional CHARMM36 force field destabilizes the Cl-binding site in CLC-ec1. The latter ion unbinds irreversibly during microseconds-long simulations which is at odds with the experimental binding affinity.

This imbalance in Cl−/protein/water interactions could significantly impact the CFTR simulations, potentially altering state populations and Cl− permeability. Notably, recent work by Levring and Chen (Proc Natl Acad Sci U S A. 2024) identifies a likely Cl− binding site in the bottleneck region of the channel, which contradicts the simulation results showing low occupancy Cl− ions in this region (Fig. 1B and Fig. 6A). This discrepancy may be due to the underestimation of Cl−/protein interactions. Indeed, Orabi et al. have proposed corrections that specifically tune these interactions, including those with aromatic residues, in line with the binding site geometry suggested by Levring and Chen. This imbalance in interactions may also lead to an underestimation of the conductance in the experimental near-open state.<br /> Balanced Cl−/protein interactions could also influence voltage/current relationships, potentially affecting the degree of inward rectification. For example, higher Cl− occupancy in the bottleneck region may stabilize the down state of R334, along with other measured interactions, thereby increasing conductance as the authors have shown.

The experimental evidence reported and discussed by the authors in support of the proposed open state is largely qualitative. For instance, in Figure 4 Supplement 2 there is a significant overlap in the distances and SASA distributions of open and near-open states for the reported residues (are those residues water accessible in the simulations?).

Given the known limitations of the standard CHARMM36 Cl− force field and in the absence of robust experimental validation of the proposed open state, I recommend validating at least part of the results using an independent set of simulations (not started from the previous ones) with an updated Cl− force field. It would be especially important to reassess whether the experimental near-open state is truly metastable and less probable than the new open state, and confirm that the near-open state exhibits negligible conductance.

A minor point worth discussing is whether the observed inward rectification may be influenced by hysteresis or incomplete equilibration, as many simulations were started from prior trajectories at large negative voltages and may not have fully relaxed. For instance, is not uncommon that small structural changes in backbone and sidechains occur in several microseconds (Shaw et al., Science, 2010). That said, discrepancies in current-voltage relationships are not unexpected due to challenges in simulation sampling and force field accuracy (J Gen Physiol 2013 May;141(5):619-32) as the authors stated.

Another minor point to address is the preparation of the simulation setup for the ATP-free structure of the protein. It would be helpful to specify whether any particular controls or steps were taken, given that the structure is based on a relatively low resolution (3.87 Å) model.

Reviewer #3 (Public review):

Background:

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride channel whose dysfunction underlies cystic fibrosis, a life-limiting condition caused by thick, sticky mucus buildup in the lungs and other organs. Despite multiple high-resolution structures of CFTR, these snapshots have all captured the channel in a non-conducting or "closed" conformation - even when the protein was prepared under conditions that should favor channel opening. This discrepancy has posed a key challenge: how can a channel be experimentally observed as closed while physiological tests demonstrate it conducts chloride ions?

Key Findings:

(1) Stable Open Conformation

Through repeated molecular dynamics (MD) simulations of human CFTR in lipid bilayers, researchers observed a reproducible, stable open state. Unlike previous transient openings seen in single-run or short simulations, this conformation remains consistently permeable over extended timescales.

(2) Penta-Helical Arrangement

The authors highlight a "penta-helical" pore-lining arrangement in which five transmembrane helices symmetrically organize to create a clear ion-conduction pathway. This novel configuration resolves the previously puzzling hydrophobic bottleneck found in cryo-EM structures.

(3) Conductance Close to Experimental Values

By analyzing chloride ion flow under near-physiological voltages, they calculate a channel conductance aligning well with electrophysiological measurements. This alignment provides strong support that the observed structure is functionally relevant.

(4) Roles of Key Residues

Several positively charged (cationic) residues in the pore appear crucial for guiding and stabilizing chloride ions. Simultaneously, small kinks in certain helices may act as structural "hinges," allowing or blocking chloride passage.

How to Interpret These Results:

(1) Bridging a Major Gap: The study tackles the mismatch between static "closed" CFTR structures and their known open-channel function. Successfully capturing a stable open state in MD simulations is a significant step toward reconciling what cryo-EM data shows versus what physiological experiments have long told us.

(2) Strength in Multiple Replicas: Running many simulation repeats (rather than relying on a single trajectory) lends credibility. Only if a phenomenon is reproducible across multiple runs can it be considered robust.

(3) Consistency with Mutational Data: Observing that known functional hotspots (e.g., specific charged residues) play a key role in the new pore model further validates these findings.

Important Caveats and Limitations:

(1) Simulation Timescales vs. Biology<br /> Even extended MD (on the microsecond scale) is still much faster, simpler, and more controlled than real cellular processes.

(2) Physiological existence of the penta-helical pore<br /> Although the simulations and results are highly compelling, several factors leave open the possibility of a physiological open conformation differing from the observed penta-helical pore. These factors include ATP hydrolysis, interactions with physiological binding partners, the native membrane environment, and regions not modeled in the CFTR structures, such as the R domain. Most importantly, the transmembrane voltage is very high (500mV).

Bottom Line:

This work delivers a long-awaited, near-physiological view of CFTR's open conformation. It provides a foundational structure against which future experimental and computational studies can be compared. By demonstrating reliable chloride conduction and matching established biophysical data, these simulations bring us closer to understanding - and potentially targeting - CFTR's gating mechanism in health and disease. Readers should applaud the breakthroughs while recognizing that further exploration (including more complex in vitro and in vivo experiments) will still be necessary to capture the full dynamism of CFTR in the living cell environment.

Reviewer #4 (Public review):

Summary:

The structural mechanism of anion permeation through the open CFTR pore has remained unresolved and is subject to ongoing debate. That is because even in CFTR structures obtained under conditions that normally maximally activate the channel (phosphorylation + ATP + non-hydrolytic mutations + potentiator drugs) a bottleneck region in the pore, too narrow to allow passage of hydrated chloride ions, is observed.

The present study uses molecular dynamics (MD) simulations initiated from such "quasi-open" states to address local conformational dynamics of the pore. The authors conclude that the quasi-open structure stably relaxes to a fully open conformation on the sub-microsecond time scale. They provide a detailed analysis of this fully open structure and of the mechanism of chloride permeation. They conclude that two major exit pathways (a central and a peripheral) exist for chloride ions, and that the ions remain near-fully hydrated throughout the pore: chloride-protein interactions displace only 1-2 waters from the first solvation shell. Furthermore, the simulations provide some hints for conformational changes involved in gating.

Strengths:

The findings are interpreted in the context of the large body of published functional studies on CFTR permeation properties, and caveats are adequately discussed.

Weaknesses:

The conclusions on gating would benefit from further discussions. In particular, a fair comparison of the timescale at which channel gating happens, and that of the MD simulations would strengthen the manuscript.

eLife Assessment

Rennert et al. developed a valuable thermodynamic framework to study the force response of branched actin networks from the crucial and unexplored perspective of energetic cost. They used the fact that the entropy production rate must be positive to derive inequalities that set limits on the maximum force produced by branched actin networks, and speculate that the dissipative cost beyond that required to move the load may be necessary to maintain an adaptive steady state. This work is highly innovative, but remains incomplete until the hypotheses of the model are better justified and the conclusions about the dissipative cost of the system are better established.

Reviewer #1 (Public review):

Summary:

This paper investigated the dynamic self-assembly of branched actin networks and the relation between the nonequilibrium features of the dynamics with the thermodynamic cost. The authors constructed a chain model to describe the self-assembly process of a branched actin network, including events like nucleation, polymerization, and capping. The forward and backward transition rates associated with the events allowed them to investigate the entropy production rate of the dynamics. They then used the fact that the entropy production rate has to be greater than zero to derive inequalities that set bounds for the maximum force produced by the branched actin network. The idea is similar to estimating the polymerization force of actin filament via the equation F_{max} = dG/delta, which sets a bound on the maximum force by the thermodynamic potential dG which is the chemical energy associated with ATP hydrolysis and delta is the length increment upon monomer insertion. Furthermore, they speculated the dissipative cost beyond what is necessary to move the load may be necessary to maintain an adaptive steady state.

Strengths:

The authors developed a simple model that is capable of qualitatively reproducing some mechanical phenomena for a branched actin network. The model has captured the essential dynamic elements in the branched actin network and built connections between the maximum load and the adaptation behavior with the energetic cost. It is an interesting study that provides a new perspective to look at the mechanical response of the branched actin network.

Weaknesses:

The text needs to be improved, particularly in the model introduction part. It is unclear to me what happens to the state when the reverse reaction in Figure 2 occurs.

Furthermore, what the authors have done is similar to estimate the polymerization force of actin filaments but in a more complicated scenario. Their conclusion that "dissipative cost in the system beyond what is necessary to move the load may be necessary to maintain an adaptive steady state" is skeptical. The branched actin network is a nonequilibrium system driven by active processes like ATP hydrolysis that converts chemical energy into mechanical work. There has to be a gap between the actual E-C_f curve and that when dissipation rate dot{S} = 0. If the authors want to make the claim, they have to decompose the dissipation into different parts and show that a particular part is associated with adaption. Otherwise, the conclusion about the gap is baseless.

Reviewer #2 (Public review):

Summary:

Rennert et al. developed a thermodynamic framework for the assembly of branched networks to calculate the entropy dissipation associated with this process. They base their model on the simplest possible experimental system consisting of four proteins: actin, Arp2/3, capping protein, and NPF. They decompose the network assembly into a linear model where the order of events (polymerization, capping, and nucleation) is recorded sequentially. Polymerization and capping are sensitive to load and affected by Brownian ratchet effects, while nucleation is not. This simplified model provides an analytical solution that describes the load sensitivity of actin networks and agrees well with experimental data for a given set of transition rates.

Strengths:

(1) These thermodynamic approaches are original and fundamental to our understanding of these non-equilibrium systems.

(2) The fact that the model fits experimental data is encouraging.

Weaknesses:

(1) The possibility of describing branched actin assembly as a Markov process is not well justified.

(2) The choice of parameters controlling the system is open to question. Some parameters are probably completely negligible, while other ignored effects are potentially significant.

(3) The main conclusion of the manuscript, linked to the existence of a dissipation gap, is quite expected. The manuscript would have been more valuable if the authors had been able to decompose dissipation into different components in order to prove that a particular fraction is associated with adaptation.

eLife Assessment

This study presents a potentially fundamental analysis of the original color of a fossil feather from the crest of a 125-million-year-old enantiornithine bird, using sophisticated 3D microscopic and numerical methods to conclude that the feather was iridescent and brightly colored, possibly indicating that this was a male bird that used its crest in sexual displays. At present, the strength of evidence supporting the authors' conclusions is considered incomplete based on methodological incompleteness and questions about taphonomy.

Reviewer #1 (Public review):

Summary:

Li et al describe a novel form of melanosome based iridescence in the crest of an Early Cretaceous enantiornithine avialan bird from the Jehol Group.

Strengths:

Novel set of methods applied to the study of fossil melanosomes.

Weaknesses:

(1) Firstly, several studies have argued that these structures are in fact not a crest, but rather the result of compression. Otherwise, it would seem that a large number of Jehol birds have crests that extend not only along the head but the neck and hindlimb. It is more parsimonious to interpret this as compression as has been demonstrated using actuopaleontology (Foth 2011).<br /> (2) The primitive morphology of the feather with their long and possibly not interlocking barbs also questions the ability of such feathers to be erected without geologic compression.<br /> (3) The feather is not in situ and therefore there is no way to demonstrate unequivocally that it is indeed from the head (it could just as easily be a neck feather)<br /> (4) Melanosome density may be taphonomic; in fact, in an important paper that is notably not cited here (Pan et al. 2019) the authors note dense melanosome packing and attribute it to taphonomy. This paper describes densely packed (taphonomic) melanosomes in non-avian avialans, specifically stating, "Notably, we propose that the very dense arrangement of melanosomes in the fossil feathers (Fig. 2 B, C, and G-I, yellow arrows) does not reflect in-life distribution, but is, rather, a taphonomic response to postmortem or postburial compression" and if this paper was taken into account it seems the conclusions would have to change drastically. If in this case the density is not taphonomic, this needs to be justified explicitly (although clearly these Jehol and Yanliao fossils are heavily compressed).<br /> (5) Color in modern birds is affected by the outer keratin cortex thickness which is not preserved but the authors note the barbs are much thicker (10um) than extant birds; this surely would have affected color so how can the authors be sure about the color in this feather?<br /> (6) Authors describe very strange shapes that are not present in extant birds: "...different from all other known feather melanosomes from both extant and extinct taxa in having some extra hooks and an oblique ellipse shape in cross and longitudinal sections of individual melanosome" but again, how can it be determined that this is not the result of taphonomic distortion?<br /> (7) The authors describe the melanosomes as hexagonally packed but this does not appear to be in fact the case, rather appearing quasi-periodic at best, or random. If the authors could provide some figures to justify this hexagonal interpretation?<br /> (8) One way to address these concerns would be to sample some additional fossil feathers to see if this is unique or rather due to taphonomy<br /> (9) On a side, why are the feet absent in the CT scan image?

Reviewer #2 (Public review):

Summary:

The authors reconstructed the three-dimensional organization of melanosomes in fossilized feathers belonging to a spectacular specimen of a stem avialan from China. The authors then proceed to infer the original coloration and related ecological implications.

Strengths:

I believe the study is well executed and well explained. The methods are appropriate to support the main conclusions. I particularly appreciate how the authors went beyond the simple morphological inference and interrogated the structural implications of melanosome organization in three dimensions. I also appreciate how the authors were upfront with the reliability of their methods, results, and limitations of their study. I believe this will be a landmark study for the inference of coloration in extinct species and how to interrogate its significance in the future.

Weaknesses:

I have a few minor comments.<br /> Introduction: I would suggest the authors move the paragraph on coloration in modern birds (lines 75-97) before line 64, as this is part of the reasoning behind the study. I believe this change would improve the flow of the introduction for the general reader.<br /> Melanosome organization: I was surprised to find little information in the main text regarding this topic. As this is one of the major findings of the study, I would suggest the authors include more information regarding the general geometry/morphology of the single melanosomes and their arrangement in three dimensions.<br /> Keratin: the authors use such a term pretty often in the text, but how is this inference justified in the fossil? Can the authors extend on this? Previous studies suggested the presence of degradation products deriving from keratin, rather than immaculated keratin per se.<br /> Ontogenetic assessment: the authors infer a sub-adult stage for the specimen, but no evidence or discussion is reported in the SI. Can the authors describe and discuss their interpretations?<br /> CT scan data: these data should be made freely available upon publication of the study.

Reviewer #3 (Public review):

Summary:

The paper presents an in-depth analysis of the original colour of a fossil feather from the crest of a 125-million-year-old enantiornithine bird. From its shape and location, it would be predicted that such a feather might well have shown some striking colour and pattern. The authors apply sophisticated microscopic and numerical methods to determine that the feather was iridescent and brightly coloured and possibly indicates this was a male bird that used its crest in sexual displays.

Strengths:

The 3D micro-thin-sectioning techniques and the numerical analyses of light transmission are novel and state-of-the-art. The example chosen is a good one, as a crest feather is likely to have carried complex and vivid colours as a warning or for use in sexual display. The authors correctly warn that without such 3D study feather colours might be given simply as black from regular 2D analysis, and the alignment evidence for iridescence could be missed.

Weaknesses: Trivial.

eLife Assessment

This fundamental manuscript comprehensively examines the roles of nine structural proteins in herpes simplex virus 1 (HSV-1) assembly and nuclear egress. By integrating cryo-light microscopy and soft X-ray tomography, the study presents an innovative approach to investigating viral assembly within cells. The research is thoroughly executed, yielding compelling data that explain previously unknown functions of these structural proteins. This work is of broad interest to virologists, cellular biologists, and structural biologists, offering a robust, contextually rich methodology for studying large protein complex assembly within the cellular environment, serving as an excellent starting point for high-resolution techniques.

Reviewer #1 (Public review):

Summary:

Nahas et al. investigated the roles of herpes simplex virus 1 (HSV-1) structural proteins using correlative cryo-light microscopy and soft X-ray tomography. The authors generated nine viral variants with deletions or mutations in genes encoding structural proteins. They employed a chemical fixation-free approach to study native-like events during viral assembly, enabling observation of a wider field of view compared to cryo-ET. The study effectively combined virology, cell biology, and structural biology to investigate the roles of viral proteins in virus assembly and budding.

Strengths:

(1) The study presented a novel approach to studying viral assembly in cellulo.

(2) The authors generated nine mutant viruses to investigate the roles of essential proteins in nuclear egress and cytoplasmic envelopment.

(3) The use of correlative imaging with cryoSIM and cryoSXT allowed for the study of viral assembly in a near-native state and in 3D.

(4) The study identified the roles of VP16, pUL16, pUL21, pUL34, and pUS3 in nuclear egress.

(5) The authors demonstrated that deletion of VP16, pUL11, gE, pUL51, or gK inhibits cytoplasmic envelopment.

(6) The manuscript is well-written, clearly describing findings, methods, and experimental design.

(7) The figures and data presentation are of good quality.

(8) The study effectively correlated light microscopy and X-ray tomography to follow virus assembly, providing a valuable approach for studying other viruses and cellular events.

(9) The research is a valuable starting point for investigating viral assembly using more sophisticated methods like cryo-ET with FIB-milling.

(10) The study proposes a detailed assembly mechanism and tracks the contributions of studied proteins to the assembly process.

(11) The study includes all necessary controls and tests for the influence of fluorescent proteins.

Weaknesses:

Overall, the manuscript does not have any major weaknesses, just a few minor comments:

(1) The gel quality in Figure 1 is inconsistent for different samples, with some bands not well resolved (e.g., for pUL11, GAPDH, or pUL20).

(2) The manuscript would benefit from a summary figure or table to concisely present the findings for each protein. It is a large body of manuscript, and a summary figure showing the discovered function would be great.

(3) Figure 2 lacks clarity on the type of error bars used (range, standard error, or standard deviation). It says, however, range, and just checking if this is what the authors meant.

(4) The manuscript could be improved by including details on how the plasma membrane boundary was estimated from the saturated gM-mCherry signal. An additional supplementary figure with the data showing the saturation used for the boundary definition would be helpful.

(5) Additional information or supplementary figures on the mask used to filter the YFP signal for Figure 4 would be helpful.

(6) The figure legends could include information about which samples are used for comparison for significance calculations. As the color of the brackets is different from the compared values (dUL34), it would be great to have this information in the figure legend.

(7) In Figure 5B, the association between YFP and mCherry signals is difficult to assess due to the abundance of mCherry signal; single-channel and combined images might improve visualization.

(8) In Figure 6D, staining for tubulin could help identify the cytoskeleton structures involved in the observed virus arrays.

(9) It is unclear in Figure 6D if the microtubule-associated capsids are with the gM envelope or not, as the signal from mCherry is quite weak. It could be made clearer with the split signals to assess the presence of both viral components.

(10) The representation of voxel intensity in Figure 8 is somewhat confusing. Reversion of the voxel intensity representation to align brighter values with higher absorption, which would simplify interpretation.

(11) The visualization in panel I of Figure 8 might benefit from a more divergent colormap to better show the variation in X-ray absorbance.

(12) Figure 9 would be enhanced by images showing the different virus sizes measured for the comparative study, which would help assess the size differences between different assembly stages.

Overall, this is an excellent manuscript and an enjoyable read. It would be interesting to see this approach applied to the study of other viruses, providing valuable insights before progressing to high-resolution methods.

Reviewer #2 (Public review):

Summary:

For centuries, humans have been developing methods to see ever smaller objects, such as cells and their contents. This has included studies of viruses and their interactions with host cells during processes extending from virion structure to the complex interactions between viruses and their host cells: virion entry, virus replication and virion assembly, and release of newly constructed virions. Recent developments have enabled simultaneous application of fluorescence-based detection and intracellular localization of molecules of interest in the context of sub-micron resolution imaging of cellular structures by electron microscopy.

The submission by Nahas et al., extends the state-of-the-art for visualization of important aspects of herpesvirus (HSV-1 in this instance) virion morphogenesis, a complex process that involves virus genome replication, and capsid assembly and filling in the nucleus, transport of the nascent nucleocapsid and some associated tegument proteins through the inner and outer nuclear membranes to the cytoplasm, orderly association of several thousand mostly viral proteins with the capsid to form the virion's tegument, envelopment of the tegumented capsid at a virus-tweaked secretory vesicle or at the plasma membrane, and release of mature virions at the plasma membrane.

In this groundbreaking study, cells infected with HSV-1 mutants that express fluorescently tagged versions of capsid (eYFP-VP26) and tegument (gM-mCherry) proteins were visualized with 3D correlative structured illumination microscopy and X-ray tomography. The maturation and egress pathways thus illuminated were studied further in infections with fluorescently tagged viruses lacking one of nine viral proteins.

Strengths:

This outstanding paper meets the journal's definitions of Landmark, Fundamental, Important, Valuable, and Useful. The work is also Exceptional, Compelling, Convincing, and Solid. The work is a tour de force of classical and state-of-the-art molecular and cellular virology. Beautiful images accompanied by appropriate statistical analyses and excellent figures. The numerous complex issues addressed are explained in a clear and coordinated manner; the sum of what was learned is greater than the sum of the parts. Impacts go well beyond cytomegalovirus and the rest of the herpesviruses, to other viruses and cell biology in general.

Weaknesses:

I have a few suggestions for minor adjustments in the text.

Reviewer #3 (Public review):

Summary:

Kamal L. Nahas et al. demonstrated that pUL16, pUL21, pUL34, VP16, and pUS3 are involved in the egress of the capsids from the nucleous, since mutant viruses ΔpUL16, ΔpUL21, ΔUL34, ΔVP16, and ΔUS3 HSV-1 show nuclear egress attenuation determined by measuring the nuclear:cytoplasmic ratio of the capsids, the dfParental, or the mutants. Then, they showed that gM-mCherry+ endomembrane association and capsid clustering were different in pUL11, pUL51, gE, gK, and VP16 mutants. Furthermore, the 3D view of cytoplasmic budding events suggests an envelopment mechanism where capsid budding into spherical/ellipsoidal vesicles drives the envelopment.

Strengths:

The authors employed both structured illumination microscopy and cellular ultrastructure analysis to examine the same infected cells, using cryo-soft-X-ray tomography to capture images. This combination, set here for the first time, enabled the authors to obtain holistic data regarding a biological process, as a viral assembly. Using this approach, the researchers studied various stages of HSV-1 assembly. For this, they constructed a dual-fluorescently labelled recombinant virus, consisting of eYFP-tagged capsids and mCherry-tagged envelopes, allowing for the independent identification of both unenveloped and enveloped particles. They then constructed nine mutants, each targeting a single viral protein known to be involved in nuclear egress and envelopment in the cytoplasm, using this dual-fluorescent as the parental one. The experimental setting, both the microscopic and the virological, is robust and well-controlled. The manuscript is well-written, and the data generated is robust and consistent with previous observations made in the field.

Weaknesses:

It would be helpful to find out what role the targeted proteins play in nuclear egress or envelopment acquisition in a different orthoherpesvirus, like HSV-2. This would confirm the suitability of the technical approach set and would also act as a way to validate their mechanism at least in one additional herpesvirus beyond HSV-1. So, using the current manuscript as a starting point and for future studies, it would be advisable to focus on the protein functions of other viruses and compare them.

eLife Assessment

This study provides important insights into the regulation of type-I interferon signaling and anti-tumor immunity, demonstrating that ORMDL3 promotes RIG-I degradation to suppress immune responses. The evidence is convincing, with well-executed mechanistic experiments and in vivo validation in syngeneic tumor models. These findings have significant implications for cancer immunotherapy, highlighting ORMDL3 as a potential therapeutic target.

Reviewer #2 (Public review):

Summary:

The authors identified ORMDL3 as a negative regulator of the RLR pathway and anti-tumor immunity. Mechanistically, ORMDL3 interacts with MAVS and further promotes RIG-I for proteasome degradation. In addition, the deubiquitinating enzyme USP10 stabilizes RIG-I and ORMDL3 disturbs this process. Moreover, in subcutaneous syngeneic tumor models in C57BL/6 mice, they showed that inhibition of ORMDL3 enhances anti-tumor efficacy by augmenting the proportion of cytotoxic CD8-positive T cells and IFN production in the tumor microenvironment (TME).

Strengths:

The paper has a clearly arranged structure and the English is easy to understand. It is well written. The results clearly support the conclusion.

Comments on revisions:

All questions have been answered.

Author response:

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

Reviewer #1 (Recommendations for the authors):

Minor Points:

• HEK293T cells are not typically Type 1 IFN-producing cells; it is recommended to use other immune cell lines to validate results obtained with ORMDL3 overexpression in 293T cells. The same applies to A549 alveolar basal epithelial cells.

Thanks for the reviewer’s insightful comment. In Figure 1C, we overexpressed ORMDL3 in mouse primary BMDM cell and stimulated it with poly(I:C) or poly(dG:dC), which suggests that ORMDL3 inhibits IFN expression in primary cell BMDM.

• Clarify whether TLR3 is expressed in the cell lines used in Figure 1 and whether TLR3 is present in mouse BMDMs.

Thanks for your suggestions. We identified whether TLR3 is expressed in HEK293T, A549 and BMDM. We designed primers of human TLR3 and murine Tlr3, and the results showed that Tlr3 is expressed in BMDM but not in HEK293T and A549. As it shown in Author response image 1.

Author response image 1.

PCR amplification of human TLR3 was conducted on cDNA derived from HEK293T and A549 cells (lanes 1 and 2, respectively), and PCR amplification of murine Tlr3 was performed on cDNA from BMDM (lane 3). Human spleen cDNA (lane 4, TAKARA Human MTCTM Panel I, Cat# 636742) served as a positive control, and 18s rRNA was used as an internal control.

primer sequences:

human TLR3: forward TTGCCTTGTATCTACTTTTGGGG   reverse TCAACACTGTTATGTTTGTGGGT

murine Tlr3: forward GTGAGATACAACGTAGCTGACTG   reverse TCCTGCATCCAAGATAGCAAGT

18s (human/mice): forward GTAACCCGTTGAACCCCATT   reverse CCATCCAATCGGTAGTAGCG

• Specify the type of luciferase reporter assay used in Figure 1E.

Thanks for the reviewer’s insightful comment. The Dual-Luciferase® Reporter (DLR™) Assay System efficiently measures two luciferase signals. In brief, the IFN-reporter luciferase is derived from firefly (Photinus pyralis), while the internal control luciferase is from Renilla (Renilla reniformis or sea pansy). These dual luciferases are measured sequentially from a single sample. In Figure 1E, we measured the luciferase activity of IFN (firefly) and internal control gene TK (Renilla), and their ratio is shown in Figure 1E.

• Clarify what was knocked down in the A549 stable KD cell line and whether HSV-1 infects and replicates in A549 cells.

We sincerely appreciate the reviewer’s concern and apologize for any ambiguous descriptions. In Figure 1H, we knocked down ORMDL3 and infected the cell with HSV-1, which shows that ORMDL3 does not affect the infection and replication of HSV-1 in A549.

• In Figure 2E, provide the rationale for using the same tag (Flag) in overexpression experiments with different molecules such as Flag-ORDML3 and Flag-RIG-I.

We thank the reviewer’s concern. We tried to co-express different tags of ORMDL3 and innate immunity proteins, and we got the same results as before. ORMDL3-Myc overexpression can only promote the degradation of Flag-RIG-I-N, as shown in current Figure 2E.

• Address the low knockdown efficiency shown in Figure 2D and consider whether it is sufficient for drawing conclusions.

Thanks for the reviewer’s concern. Because ORMDL3 antibody (Abcam 107639) can recognize all ORMDL family members (ORMDL1, 2 and 3), this may explain why the knockdown efficiency of ORMDL3 is not apparent in Figure2D. We also detect the knockdown efficiency of ORMDL3 at mRNA level, which showed that ORMDL3 was silenced efficiently and specifically (Figure S2C).

• Replace the Tubulin/β-Actin WB control with a more distinguishable band.

Thanks for the suggestion. Owing to different gel concentration, sometimes the protein bands appear fused, but it is distinguishable that the internal controls are consistent.

• In Figures 3D/E, the expression level of the Lysine mutant of RIG-I-N is too low. Please provide an explanation or repeat the experiment to achieve comparable expression levels and update the figure accordingly.

Thanks for the question. The expression of lysine mutant of RIG-I-N is low, we have increased the amount of plasmid in transfection, but this still hasn't increased its expression level. Though its abundance is low, we provided evidence to show that it would not be degraded by ORMDL3. In some literatures (for example: RNF122 suppresses antiviral type I interferon production by targeting RIG-I CARDs to mediate RIG-I degradation. Proc Natl Acad Sci U S A. 2016 Aug 23;113(34):9581-6; TRIM4 modulates type I interferon induction and cellular antiviral response by targeting RIG-I for K63-linked ubiquitination. J Mol Cell Biol. 2014 Apr;6(2):154-63.), it has also been reported that lysine mutant can affect RIG-I stability. In addition, we speculate that the 4KR mutant (K146R, K154R, K164R, K172R) may change RIG-I conformation, so its expression is lower.

• Explain why there is no difference in MAVS expression levels despite binding with MAVS.

Thanks for the question. In our experiment, ORMDL3 has no effect on MAVS expression. Our results showed that ORMDL3 interacts with MAVS and promotes the degradation of RIG-I, so only RIG-I level has a significant difference.

• Verify if Flag-tagged ORMDL3 is present in the IP sample in Figure 3G.

Thanks for the comment. We reloaded the samples and blot flag, and we found that ORMDL3 cannot be pulled down by RIG-I. We have added the results in Figure 3G.

• Reload the samples in Figure 4C to clearly identify the correct band for GFP-tagged ORMDL3.

Thanks for the question. As ORMDL3 is small molecular protein, we fused it and its fragments to GFP to increase its molecular weight. In our GFP vector, for some unknown reason, the 26kDa band always exists. This is actually a technical difficulty. Although the GFP-fused protein and GFP band are very close, they can still be distinguished as two bands.

• Rerun the Western blot for Actin IB in Figure 4E, as the ORMDL3-GFP (1-153) full-length appears abnormal.

Thanks for the question. As we first blot GFP and then blot actin on the same membrane, so it appears abnormal. We reloaded the previous sample and blotted the actin again.

• Clarify in which figure RIG-I ubiquitination is shown and whether ORMDL3 has E3 ubiquitin ligase activity. Explain how ORMDL3 facilitates USP10 transfer to RIG-I despite no direct interaction.

Thank you for your question. In Figure 3B we showed the ubiquitination of RIG-I and ORMDL3 does not have an E3 ubiquitin ligase activity. Our results showed that although ORMDL3 does not directly interacted with RIG-I, it forms complex with USP10 (Figure 5B, 5C) and disrupt USP10 induced RIG-I stabilization by decreasing the interaction between USP10 and RIG-I (Figure 6A). The detailed mechanism needs further investigation.

• Provide quantification for Figure 5D. Explain why the bands are not degraded by RIG-I and USP10.

Thanks for the concern. We quantified the bands and found that overexpression of USP10 increased RIG-I protein abundance. The quantitative gray values are added into the image. USP10 functions to stabilize RIG-I rather than promoting its degradation.

• Explain the decrease in RIG-I levels in Figure 5E when USP10 levels decrease.

Thanks for the concern. As shown in the working model (Supplementary Figure 8), USP10 is a deubiquitinase that stabilizes RIG-I by decreasing its K48-linked ubiquitination. So, in Figure 5E, we knocked down USP10 and found a decrease in RIG-I levels, which is consistent with Figure 5D.

• Clarify whether K48 ubiquitination on RIG-I has decreased in Figure 5F, as this is not clear from the image.

Thanks for the question. In Figure 5F it is shown that the K48 ubiquitination level of RIG-I significantly decreased (please see the density of the bands in the IP samples).

• Address whether ORMDL3 reduces RIG-I-N degradation in Figure 5H, as the results do not clearly support this claim.

Thanks for the concern. We quantified the bands and the results showed that ORMDL3 promotes the degradation of RIG-I-N. The quantitative gray values are added into the image.

• Reload Flag-ORMDL3 in Figure 6C to determine whether RIG-I-N is restored in the MG132-treated samples.

Thank you for your question. We quantified the bands and the results showed that RIG-I-N is restored in the MG132-treated samples. The quantitative gray values are added into the image.

• Correct numerous typos and errors, especially in the Discussion section, to improve readability

Thanks for the suggestion. We have revised the manuscript carefully to correct these errors.

Reviewer #2 (Recommendations for the authors):

(1) In Figure 1G and H, The number of virus-infected cells was observed using a fluorescence microscope. In addition, can the author use other techniques to detect the impact of ORMDL3 on virus replication?

Thanks for the question. Except for using a fluorescence microscope, we also used RT-PCR to quantify the amount of viral mRNA, and results were added in Figure 1G and H.

(2) In Figure 3C, ORMDL3 overexpression promotes the degradation of RIG-I-N. ORMDL3 is one of three ORMDL proteins with similar amino acid sequences, does ORMDL1/2 also have this function?

Thanks for the suggestion. We compared the function between ORMDLs and found that only ORMDL3 overexpression facilitated RIG-I-N degradation. The results were shown in Figure S2D.

(3) In Figure 5A, USP10 is not the top protein in the Mass spec assay. Does the author verified the interaction between ORMDL3 and other protein (for example CAND1)?

Thanks for your suggestion. We verified that ORMDL3 has no interaction with CAND1 and UFL1 but only interacts with USP10, as Figure S5 shows.

(4) A scale bar to be added to the images in Figure 1 G, H and Figure 7K.

Thanks for the suggestion. We have added the scale bars.

(5) The annotations in Figure 4B, C and E should be aligned.

Thanks for the suggestion. We have aligned the annotations.

(6) Provide Statistical methods

Thanks for the suggestion. We have provided the statistical methods in the materials and methods part.

eLife Assessment

This study addresses an important and longstanding question regarding the molecular mechanism of protein misfolding in Ig light chain (LC) amyloidosis (AL), a life-threatening condition. By combining advanced techniques, including small-angle X-ray scattering, molecular dynamics simulations, and hydrogen-deuterium exchange mass spectrometry, the authors provide convincing evidence that the "H state" distinguishes amyloidogenic from non-amyloidogenic LCs. These findings not only offer novel insights into LC structural dynamics but also hold promise for guiding therapeutic strategies in amyloidosis and will be of particular interest to structural biologists, biophysicists, and many others working on amyloid diseases.

Reviewer #1 (Public review):

The study investigates light chains (LCs) using three distinct approaches, with a focus on identifying a conformational fingerprint to differentiate amyloidogenic light chains from multiple myeloma light chains. The study's major contribution is the identification of a low-populated "H state," which the authors propose as a unique marker for AL-LCs. While this finding is promising, the review highlights several strengths and weaknesses. Strengths include the valuable contribution of identifying the H state and the use of multiple approaches, which provide a comprehensive understanding of LC structural dynamics. Weaknesses include a lack of physical insights explaining the changes.

Reviewer #2 (Public review):

Summary:

This well-written manuscript addresses an important but recalcitrant problem - molecular mechanism of protein misfolding in Ig light chain (LC) amyloidosis (AL), a major life-threatening form of systemic human amyloidosis. The authors use expertly recorded and analyzed small-angle X-ray scattering (SAXS) data as a restraint for molecular dynamics simulations (called M&M). Six patient-based LC proteins are explored, including four AL and two non-AL. The authors report a partially populated "H-state" determined computationally, wherein the two domains in an LC molecule acquire a straight rather than bent conformation, with an extended interdomain linker; this H-state distinguishes AL from non-AL LCs. H-D exchange mass spectrometry is used to support this conclusion. This is a novel and interesting finding with potentially important translational implications.

Strengths:

Expertly recorded and analyzed SAXS data combined with clever M&M simulations lead to a novel and interesting conclusion, which is supported by limited H-D exchange data.<br /> Stabilization of the CL-CL interface is a good idea that may help protect a subset of AL LCs from misfolding in amyloid.

Computational M&M evidence is convincing and is supported by SAXS data, which are used as restraints for simulations. Although Kratky plots reported in the main MS Fig. 1 show significant differences between the data and the structural model for only one AL protein, AL-55, H-state is also inferred for other AL proteins.

Apparent limitations:

HDX MS results show that residues 35-50 from VL-VL and VL-CL dimerization interface are less protected in AL vs. non-AL proteins, which is consistent with the H-state. However, the small number of proteins yielding useful HDX data (three AL and one non-AL) suggests that this conclusion should be treated with caution. It is unclear whether the conformational heterogeneity depicted in M&M simulations is consistent with HDX results, and whether prior HDX studies of AL and MM LCs are consistent with the conclusions that a particular domain-domain interface is weakened in AL vs. non-AL LCs. The butterfly plots in Fig. 5 could benefit from the X-axis labeling with the peptide fragments.

Reviewer #3 (Public review):

Summary:

This study identifies confirmational fingerprints of amylodogenic light chains, that set them apart from the non-amylodogenic ones.

Strengths:

The research employs a comprehensive combination of structural and dynamic analysis techniques, providing evidence that conformational dynamics at VL-CL interface and structural expansion are distinguished features of amylodogenic LCs.

Weaknesses:

The sample size is limited, which may affect the generalizability of the findings. Additionally, the study could benefit from deeper analysis of specific mutations driving this unique conformation to further strengthen therapeutic relevance.

Furthermore. p-value (statistical significance) of Rg difference should be computer. Finally, significance of mutations (SHM?) at the interface, such as A40G should be compared with previous observations. (Garofalo et al., 2021)

Author response:

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

eLife Assessment

This important study identifies the "H-state" as a potential conformational marker distinguishing amyloidogenic from non-amyloidogenic light chains, addressing a critical problem in protein misfolding and amyloidosis. By combining advanced techniques such as small-angle X-ray scattering, molecular dynamics simulations, and H-D exchange mass spectrometry, the authors provide convincing evidence for their novel findings. However, incomplete experimental descriptions, limitations in SAXS data interpretation, and the way HDX MS data is presented aHect the strength and generalizability of the conclusions. Strengthening these aspects would enhance the impact of this work for researchers in amyloidosis and protein misfolding.

We thank eLife editors and reviewers for their constructive feedback. The manuscript has been improved to provide a more complete description of the experiments and to strengthen the interpretation and presentation of all data. Updated Figures (Figure 2 and Figure 5) and a new Table (Table 2) in the main text provide a more complete and clearer comparison of the SAXS data with MD simulations as well as a clearer representation of the HDX MS data. Additional figures have been added in SI. The text has been extended accordingly and complete materials and methods are now included in the main text. Abstract, introduction and discussion have been revised to improve the overall readability of the manuscript.

Public Reviews:

Reviewer #1 (Public review):

The study investigates light chains (LCs) using three distinct approaches, with a focus on identifying a conformational fingerprint to diHerentiate amyloidogenic light chains from multiple myeloma light chains. The study's major contribution is identifying a low-populated "H state," which the authors propose as a unique marker for AL-LCs. While this finding is promising, the review highlights several strengths and weaknesses. Strengths include the valuable contribution of identifying the H state and using multiple approaches, which provide a comprehensive understanding of LC structural dynamics. However, the study suHers from weaknesses, particularly in interpreting SAXS data, lack of clarity in presentation, and methodological inconsistencies. Critical concerns include high error margins between SAXS profiles and MD fits, unclear validation of oligomeric species in SAXS measurements, and insuHicient quantitative cross-validation between experimental (HDX) and computational data (MD). This reviewer calls for major revisions including clearer definitions, improved methodology, and additional validation, to strengthen the conclusions.

We thank the reviewer for the supportive comments, in the revised version of the manuscript we have focused on improving the clarity and completeness of our work. We are sorry for example to not have made previously clear enough that the comparison of SAXS with MD simulation was not that shown in the main text in Figure 1 and Table 1 (this is the comparison with single structures) but that reported in the SI (previously Figure S1 and Table S2, showing very good fits). These data have been moved in the main text in the reworked Figure 2 and new Table 2.  We have also improved the presentation of the HDX MS data in Figure 5 and in the text adding also additional analysis in SI. Materials and methods are now completely moved in the main text. We generally revised the manuscript for clarity.

Reviewer #2 (Public review):

Summary:

This well-written manuscript addresses an important but recalcitrant problem - the molecular mechanism of protein misfolding in Ig light chain (LC) amyloidosis (AL), a major life-threatening form of systemic human amyloidosis. The authors use expertly recorded and analyzed smallangle X-ray scattering (SAXS) data as a restraint for molecular dynamics simulations (called M&M) and to explore six patient-based LC proteins. The authors report that a highly populated "H-state" determined computationally, wherein the two domains in an LC molecule acquire a straight rather than bent conformation, is what distinguishes AL from non-AL LCs. They then use H-D exchange mass spectrometry to verify this conclusion. If confirmed, this is a novel and interesting finding with potentially important translational implications.

We thank the reviewer for the supportive comments.

Strengths:

Expertly recorded and analyzed SAXS data combined with clever M&M simulations lead to a novel and interesting conclusion. Regardless of whether or not the CL-CL domain interface is destabilized in AL LCs explored in this (Figure 6) and other studies, stabilization of this interface is an excellent idea that may help protect at least a subset of AL LCs from misfolding in amyloid. This idea increases the potential impact of this interesting study.

We thank the reviewer for the supportive comments.

Weaknesses:

The HDX analysis could be strengthened.

We have extended the analysis and improved the presentation of the HDX data. Figure 5 has been reworked, text has been improved accordingly and additional analysis have been reported in SI.

Reviewer #3 (Public review):

Summary:

This study identifies conformational fingerprints of amyloidogenic light chains, that set them apart from the non-amyloidogenic ones.

We thank the reviewer for the supportive comments.

Strengths:

The research employs a comprehensive combination of structural and dynamic analysis techniques, providing evidence that conformational dynamics at the VL-CL interface and structural expansion are distinguished features of amyloidogenic LCs.

We thank the reviewer for the supportive comments.

Weaknesses:

The sample size is limited, which may aHect the generalizability of the findings. Additionally, the study could benefit from deeper analysis of specific mutations driving this unique conformation to further strengthen therapeutic relevance.

We agree, we tried to maximise the size of the sample and this was the best we could do. With respect to the analysis of the mutations, while we tried to discuss some of them also in view of previous works, because our set covers multiple germlines instead than focusing on a single one, this limit our ability to discuss single point mutations systematically, at the same time the discussion of single points mutations has been the focus of many recent works, while our approach provide a diNerent point of view.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

This study provides an investigation of light chains (LCs) using three distinct approaches, focusing primarily on identifying a conformational fingerprint to distinguish amyloidogenic light chains (AL-LCs) from multiple myeloma light chains (MM-LCs). The authors propose that the presence of a low-populated "H state," characterized by an extended quaternary structure and a perturbed CL-CL interface, is unique to AL-LCs. This finding is validated through hydrogendeuterium exchange mass spectrometry (HDX-MS). The study makes a valuable contribution to understanding the structural dynamics of light chains, particularly with the identification of the H state in AL-LCs. However, significant concerns regarding the interpretation of the SAXS data, clarity in presentation, and methodological rigor must be addressed. I recommend major revisions and resubmission of the work.

Major concerns:

(1) A critical concern is how the authors ensure that the SAXS profiles represent only dimeric species, given the high propensity of LCs to aggregate. If higher-order aggregates or monomers were present, this would significantly impact the SAXS data and SAXS-MD integration. Some measurements are bulk SAXS, while others are SEC-SAXS, making the study questionable. The authors need to clarify how only dimeric species were measured for the SEC-SAXS analysis, and all assessments of the dimeric state should be shown in the SI. Additionally, complementary techniques such as DLS or SEC-MALS should be used to verify the oligomeric state of the samples. Without this validation, the SAXS profiles may not be reliable.

We added SEC-MALS and SEC-SAXS data in the SI (Figures S20 and S21) as well the SAXS curves shown in log-log plot (Figure S1) that display a flat trend at low q that exclude aggregation. SAXS is very sensitive to oligomers and aggregates and our data do not indicate the presence of those species. When we had indication of possible aggregation in the sample we used SEC-SAXS.

(2) A major problem with the paper is that the claim of the "H state," which is the novelty of the study and serves as a marker of aggregation, is derived from samples where the error between the SAXS profiles and MD fits is extremely high. This casts doubt on whether the structure is indeed resolved by MD. The main conclusion of the paper is derived from weak consistency between experiment and simulation. In AL55, the error between experiment and simulation is greater than 5; for H7, it is higher than 2.8. The residuals show significant error at mid-q values, suggesting that long-range distance correlations (20-10 Å, CL, VL positioning) are not consistent between simulation and experiment. Furthermore, the FES plots of two independent replicas show deviation in the existence of the H state. One shows a minimum in that region, while the other does not. So, how robust is this conclusion? What is the chi-squared value if each replica is used independently? A separate experimental cross-validation is necessary to claim the existence of the H state.

We apologise for the misunderstanding underlying this reviewer comment. The poor agreement mentioned is not between the SAXS and MD simulations, but with the individual structures, and this disagreement led us to perform MD simulations that are in much better agreement with the data (previously Fig. S1 and Table S2). To avoid this misunderstanding, which would indeed weaken our work, we have now moved both the figure and the table in the main text to the updated Figure 2 and the new Table 2.

Regarding the robustness of the sampling, we believe that Table 3 (previously Table 2) clearly shows the statistical convergence of the data, diNerences in the presentation of the free energy are purely interpolation issues. The chi-squares of each replicate are reported in Table 2 (previously Table S2).

(3) There is insuHicient discussion about SAXS computations from MD trajectories. The accuracy of these calculations is crucial to deriving the existing conclusions, and the study's reliance on the PLUMED plugin, which is known to give inaccurate results for SAXS computations, raises concerns. How the solvent is treated in the SAXS computations needs to be explained. Alternative methods like WAXSiS or Crysol should be explored to check whether the SAXS profiles derived from the MD trajectory are consistent across other SAXS computation methods for the major conformers of the proteins.

We have now clarified that while the SAXS calculation to perform Metainference MD were done using PLUMED (that to our knowledge is as accurate as crysol) SAXS curves used for analysis were calculated using crysol.

(4) The HDX and MD results do not seem to correlate well, and there is a disconnect between Figure 2 (SAXS profiles) and Figure 5 (HDX structural interpretation). The authors should quantitatively assess residue-level dynamics by comparing HDX signals with MD-derived HDX signals for each protein. This would provide a cross-validation between the experimental and computational data.

In our opinion our SAXS, MD and HDX MS data provide a consistent picture. Our HDX-MS do not provide per residue data, making a quantitative comparison out of scope. RMSF data do not necessarily need to correlate with the deuterium uptake.

(5) MD simulations are only used to refine the structure of AlphaFold predictions, but the trajectories could help explain why these structures diHer, what stabilizes the dimer, or what leads to the conformational transition of the H state. A lack of analysis regarding the physical mechanism behind these structural changes is a weakness of the study. The authors should dedicate more eHort to analyzing their data and provide physical insights into why these changes are observed.

Our aim was to identify a property that could discriminate between AL and MM LCs. We used MD simulations, not to refine structures, but to explore the conformational dynamics of LCs (starting from either X-ray structures, homology or AlphaFold models), because SAXS data suggested that conformational dynamics could discriminate between AL- and MM-LCs. Simulations allowed us to propose a hypothesis, which we tested by HDX MS. While more insight is always welcome, we believe that we have achieved our goal for now. In the discussion, we present additional analysis of the simulations to connect with previous literature, we agree that more analysis can be done, and also for this reason, all our data are publicly available.

Minor concerns

(6) The abstract leans heavily on describing the problem and methods but lacks a clear presentation of key results. Providing a concise summary of the main findings (e.g., the identification of the H state) would better balance the abstract.

We agree with the reviewer and we rewrote the abstract.

(7) In the abstract, the term "experimental structure" is used ambiguously. Since SAXS also provides an experimental structure, it is unclear what the authors are referring to. This should be clarified.

We agree with the reviewer and we rewrote the abstract.

(8) Abbreviations such as VL (variable domain) and CL (constant domain) are not defined, making it harder for readers unfamiliar with the field to follow. Abbreviations should be defined when first mentioned.

We agree with the reviewer and we rewrote the abstract.

(9) The introduction provides a good general context but fails to explicitly define the knowledge gap. Specifically, the structural and dynamic determinants of LC amyloidogenicity are not well established, and this study could be framed as addressing that gap.

We thank the reviewer and we agree this could be better framed, we improved the introduction accordingly.

(10) The introduction does not present the novel discovery of the H state early enough. The unique contribution of identifying this state as a marker for AL-LCs should be mentioned upfront to guide the reader through the significance of the study.

We thank the reviewer and we have now made more explicit what we found.

(11) The therapeutic implications of this research should be highlighted more clearly in the discussion. Examples of how these findings could be utilized in drug design or therapeutic approaches would enhance the study's impact.

We thank the reviewer, but while we think that the H-state could be targeted for drug design, since we do not have data yet we do not want to stress this point more than what we are already doing.

(12) There is an overwhelming use of abbreviations such as H3, H7, H18, M7, and M10 without proper introduction. This makes it diHicult for readers to follow the results, and the average reader may become lost in the details. An introductory figure summarizing the sequences under study, along with a schematic of the dimeric structure defining VL and CL domains, would significantly aid comprehension.

We agree and we tried to better introduce the systems and simplify the language without adding a figure that we think would be redundant.

(13) In Figure 1, add labels to each SAXS curve to indicate which protein they correspond to. Also, what does online SEC-SAXS mean?

Done

(14) The caption of Figure 3 is unclear, particularly with abbreviations like Lb, Ls, G, and H, which are not mentioned in the captions. The authors should define these terms for clarity.

Done

(15) The study claims that the dominant structure of the dimer changes between diHerent LCs. However, Figure 5 shows identical structures for all proteins, raising questions about the consistency between the SAXS and HDX data. This inconsistency is a general problem between the MD and HDX sections, where cross-communication and comparisons are not properly addressed.

We do not claim that the dominant structure of the dimer changes between diNerent LCs, this would also be in contradiction with current literature. We claim a diNerence in a low-populated state. From this point of view using always the same structure is consistent and should simplify the representation of the results. We agree that the manuscript may be not always easy to follow and we thank the reviewer in helping us improving it.

(16) The authors show I(q) vs q and residuals for each protein. The Kratky plots are not suHicient to compare the SAXS computations with the measured profile.

Showing Kratky and residuals is a standard and complementary way to present and compare SAXS data to structures. Chi-square values are also reported. Log-log plots have been added to SI in response to previous comments.

(17) The authors need to explain how they estimate the Rg values (from simulation or SAXS profiles). If they are using simulations, they should compute the Rg values from the simulations for comparison.

Rg values reported in Table 1 are derived from SAXS. Rg from simulations have been added in Table 2.

(18) The evolution of the sampling is unclear. The authors need to show the initial starting conformation in each case and the most likely conformation after M&M in the SI, to demonstrate that their approach indeed caused changes in the initial predictions.

Our approach is not structure refinement and as such the proposed analysis would be misleading. Metainference is meant to generate a statistical ensemble representing the equilibrium conformations that as whole reproduce the data. DiNerences (or not) between initial and selected configurations will not be particularly informative in this context.

(19) The authors should also provide a running average of chi-squared values over time to demonstrate that the conformational ensemble converged toward the SAXS profile.

Our simulations are not driven to improve the agreement with SAXS over time, this is not structure refinement. Metainference is meant to generate a statistical ensemble representing the equilibrium conformations that as whole reproduce the data. The suggested analysis would be a misinterpretation of our simulations. The comparison with SAXS is provided in Figure 2 and Table 2 as mentioned above.

(20) The aggregate simulation time of 120 microseconds is misleading, as each replica was only run for 2-3 microseconds. This should be clarified.

The number reported in the text is accurate and represent the aggregated sampling. The number of replicas for each metainference simulation and their length is reported in Table 2 now moved for clarity from the SI to main text.

(21) It is not clear how the replicas were weighted to compute the SAXS profiles and FES. There are two independent runs in each case, and each run has about 30 replicas. How these replicas are weighted needs to be discussed in the SI.

Done

(22) The methods section is unevenly distributed, with detailed explanations of LC production and purification, while other key methodologies like SAXS+MD integration and HDX are not even mentioned in the main text (they are in the Supporting Information). The authors should provide a brief overview of all methodologies in the main text or move everything to the SI for consistency.

We agree with the reviewer, all methods are now in main text. 

Reviewer #2 (Recommendations for the authors):

(1) Computational M&M evidence is strong (Figure 3) and is supported by SAXS (used as restraints). However, Kratky plots reported in the main MS Figure 1 show significant diHerences between the data and the structural model only for one protein, AL-55. It is hard for the general reader to see how these SAXS data support a clear diHerence between AL and non-AL proteins. If possible, please strengthen the evidence; if not, soften the conclusions.

We thank the reviewer for the comments. The chi-square (Table 1) and the residuals (Figure 1) are a strong indication of the diNerence. To strengthen the evidence, following also the comment from reviewer 3 we calculated the p-value (<10^-5) on the significance of the radius of gyration to discriminate AL and MM LCs. We agree that SAXS alone was not enough and this is indeed what prompted us to perform MD simulations.

(2) HDX MS results are cursory and not very convincing as presented. The butterfly plots in Figure 5 are too small to read and are unlabeled so it is unclear which protein is which.  

Figure 5 has been reworked for readability. More data have been added in SI. 

(3) What labeling time was selected to construct these plots and why?

The deuterium uptakes at 30 min HDX time showed the most pronounced diNerences between diNerent proteins, which were chosen to illustrate the key structural features in the main figure panel (Figure 5).

How diHerent are the results at other labeling times? Showing uptake curves (with errors) for more than just two peptides in the supplement Figure S12 might be helpful. 

We found a continuous increase in deuterium uptake as we increased the exchange time from 0.5 to 240 min, which reached saturation at 120 min. Therefore, the exchange follows the same pattern at all time points. Butterfly plots at diNerent HDX times of 0.5 to 240 min are shown in gradient of light blue to dark blue which clearly shows the pattern of deuterium uptake at increasing incubation times (Figure 5). The HDX uptake kinetics of selected peptides with corresponding error bars are shown in Figure S12.

How redundant are the data, i.e. how good is the peptide coverage/resolution in key regions at the domain-domain interface that the authors deem important? Mapping the maximal deuterium uptake on the structures in Figure 5 is not very helpful. Perhaps mapping the whole range of uptake using a gradient color scheme would be more informative.

Overall coverage and redundancy for all four proteins are> 90% and > 4.0, respectively, with an average error margin in fractional uptake among all peptides is 0.04-0.05 Da, which suggests that our data is reliable (Table S3). We modified the main panel figures showing the gradient of deuterium uptake in blue-white-red for 0 to 30% of deuterium uptake on the chain A of the dimeric LCs.

(3) Is the conformational heterogeneity depicted in M&M simulations consistent with HDX results? The authors may want to address this by looking at the EX1/EX2 exchange kinetics for AL vs. non-AL proteins. Do AL proteins show more EX1?

No, we don’t see any EX1 exchange kinetics in our analysis. This is compatible with the prediction of the H-state that is a native like state and not an unfolded/partially folded state. 

(4) Perhaps the main conclusion could be softened given the small number of proteins (six), esp. since only four (3 AL and 1 non-AL) could be explored by HDX. Are other HDX MS data of AL LCs from the same Lambda6 family (e.g. PMID: 34678302) consistent with the conclusions that a particular domain-domain interface is weakened in AL vs. non-AL LCs?

We thank the reviewer for this suggestions. A diNerence in HDX MS data is indeed visible between AL and MM proteins for peptide 33-47 in the suggested paper (Figures 4, S5 and S8). The diNerence is reduced by the mutation identified in the paper as driving the aggregation in that specific case. We now mention this in the discussion.

(5) Please clarify if the H* state is the same for a covalent vs. non-covalent LC dimer.

We do not know because our data are only for covalent dimers. But, interestingly, the state is very similar to what was observed for a model kappa light-chain in Weber, et al., we have better highlighted this point in the discussion.

(6) Please try and better explain why a smaller distance between CL domains in H7 protein and a larger distance in other AL proteins both promote protein misfolding.

We do not have elements to discuss this point in more detail.

(7) Please comment on the Kratky plots data vs. model agreement (see comments above).

Done.

(8) Please find a better way to display, describe, and interpret the HD exchange MS data.

We have generated new main text (new Figure 5) and SI figures that we think allow the reader to better appreciated our observations. Corresponding results sections have been also improved.

Minor points:

(9) Is the population of the H-state with perturbed CL-CL domain interface, which was obtained in M&M simulations, suHicient to be observable by HDX MS?

While populations alone are not enough to determine what is observable by HDX MS, a 10% population correspond roughly to 6 kJ/mol of ΔG and is compatible with EX2 kinetics. Previous works suggested that HDX-MS data should be sensitive to subpopulations of the order of 10%, (https://doi.org/10.1016/j.bpj.2020.02.005, https://doi.org/10.1021/jacs.2c06148)

(10) Typically, an excited intermediate in protein unfolding is a monomer, while here it is an LC dimer. Is this unusual?

This is a good point, we think that intermediates have mostly been studied on monomeric proteins because these are more commonly used as model systems, but we do not feel like discussing this point.

(11) Low deuterium uptake is consistent with a rigid structure but may also reflect buried structure and/or structure that moves on a time scale greater than the labeling time.

We agree.

Reviewer #3 (Recommendations for the authors):

(1) The p-value (statistical significance) of Rg diHerence should be computed.

We thank the reviewer for the suggestion, we calculated the p-value that resulted quite significant.

(2) The significance of mutations (SHM?) at the interface, such as A40G should be compared with previous observations. (Garrofalo et al., 2021).

We thank the reviewer for the suggestion, a sentence has been added in the discussion.

eLife Assessment

The authors present three transgenic models carrying three representative exon deletions of the dystrophin gene. The findings presented are valuable to the field of muscle diseases, particularly muscular dystrophies. The evidence provided in the manuscript is convincing, with rigorous biochemical assays and state-of-the-art microscopy methods.

Reviewer #2 (Public review):

Miyazaki et al. established three distinct BMD mouse models by deleting different exon regions of the dystrophin gene, observed in human BMD. The authors demonstrated that these models exhibit pathophysiological changes, including variations in body weight, muscle force, muscle degeneration, and levels of fibrosis, alongside underlying molecular alterations such as changes in dystrophin and nNOS levels. Notably, these molecular and pathological changes progress at different rates depending on the specific exon deletions in dystrophin gene. Additionally, the authors conducted extensive fiber typing, revealing a site-specific decline in type IIa fibers in BMD mice, which they suggest may be due to muscle degeneration and reduced capillary formation around these fibers.

Strengths:

The manuscript introduces three novel BMD mouse models with different dystrophin exon deletions, each demonstrating varying rates of disease progression similar to the human BMD phenotype. The authors also conducted extensive fiber typing across different muscles and regions within the muscles, effectively highlighting a site-specific decline in type IIa muscle fibers in BMD mice.

Comments on revisions:

The authors did an excellent job addressing all or most of the concerns I raised in my previous review and have incorporated the necessary changes into the manuscript.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this article the authors described mouse models presenting with backer muscular dystrophy, they created three transgenic models carrying three representative exon deletions: ex45-48 del., ex45-47 19 del., and ex45-49 del. This article is well written but needs improvement in some points.

Strengths:

This article is well written. The evidence supporting the authors' claims is robust, though further implementation is necessary. The experiments conducted align with the current state-of-the-art methodologies.

Weaknesses:

This article does not analyze atrophy in the various mouse models. Implementing this point would improve the impact of the work

We thank the reviewer for their constructive suggestions and comments on this work. Muscle hypertrophy is shown with growth in dystrophin-deficient skeletal muscle in mdx mice; thus, we did not pay attention to the factors associated with muscle atrophy in BMD mice. As the reviewer suggested, the examination of the association between type IIa fiber reduction and muscle atrophy is important, and the result is considered to be helpful in resolving the cause of type IIa fiber reduction in BMD mice.

In response, we reviewed the following.

(1) The cross-sectional areas (CSAs) of muscles. We confirmed that the CSAs in BMD and mdx mice were rather high at 3 months, in accordance with muscle hypertrophy, compared with those of WT mice. The data is presented in Fig. 4–figure supplement 1B.

(2) The mRNA expression levels of Murf1 and atrogin-1. We confirmed that these muscle atrophy inducing factors did not differ among WT, BMD, and mdx mice. The data is presented in Fig. 4–figure supplements 1C and 1D.

Reviewer #2 (Public review):

Summary:

Miyazaki et al. established three distinct BMD mouse models by deleting different exon regions of the dystrophin gene, observed in human BMD. The authors demonstrated that these models exhibit pathophysiological changes, including variations in body weight, muscle force, muscle degeneration, and levels of fibrosis, alongside underlying molecular alterations such as changes in dystrophin and nNOS levels. Notably, these molecular and pathological changes progress at different rates depending on the specific exon deletions in the dystrophin gene. Additionally, the authors conducted extensive fiber typing, revealing a site-specific decline in type IIa fibers in BMD mice, which they suggest may be due to muscle degeneration and reduced capillary formation around these fibers.

Strengths:

The manuscript introduces three novel BMD mouse models with different dystrophin exon deletions, each demonstrating varying rates of disease progression similar to the human BMD phenotype. The authors also conducted extensive fiber typing across different muscles and regions within the muscles, effectively highlighting a site-specific decline in type IIa muscle fibers in BMD mice.

Weaknesses:

The authors have inadequate experiments to support their hypothesis that the decay of type IIa muscle fibers is likely due to muscle degeneration and reduced capillary formation. Further investigation into capillary density and histopathological changes across different muscle fibers is needed, which could clarify the mechanisms behind these observations.

We thank the reviewer for these positive comments and the very important suggestion about type IIa fiber reduction and capillary change around muscle fibers in BMD mice. From the results of the cardiotoxin-induced muscle degeneration and regeneration model, type IIa and IIx fibers showed delayed recovery compared with that of type-IIb fibers. However, this delayed recovery of type IIa and IIx could not explain the cause of the selective muscle fiber reduction limited to type IIa fibers in BMD mice. Therefore, we considered vascular dysfunction as the reason for the selective type IIa fiber reduction, and we found morphological capillary changes from a “ring pattern” to a “dot pattern” around type IIa fibers in BMD mice. However, the association between selective type IIa fiber reduction and the capillary change around muscle fibers in BMD mice remains unclear due to the lack of information about capillaries around type IIx and IIb fibers. The reviewer pointed out this insufficient evaluation of capillaries around other muscle fibers (except for type IIa fibers), and this suggestion is very helpful for explaining the association between selective type IIa fiber reduction and vascular dysfunction in BMD mice.

In response, we reviewed the following.

(1) The capillary formation around type IIx, IIb, and I fibers, in addition to that around type IIa fibers. We found that capillaries contacting around type IIx, IIb, and I fibers were poor in WT mice compared with that around type IIa fibers, with ‘incomplete ring-patterns’ around type IIx fibers, and ‘dot-patterns’ around type IIb and I fibers in WT mice. Morphological capillary changes around muscle fibers from WT to d45-49 and mdx mice were ‘incomplete dot-pattern’ to ‘dot-pattern’ around type IIx fibers, and ‘dot-pattern’ to ‘dot-pattern’ around type IIb and I fibers. This was in contrast to those around type IIa fibers: remarkable ‘ring-pattern’ to ‘dot-pattern’. These data are presented in Fig. 6B.

(2) The endothelial area in contact with type IIx, IIb, and I fibers, and additionally that in contact with type IIa fibers. The endothelial area in contact with both type IIa and IIx fibers was less in d45-49 and mdx mice than in WT mice, but the reduction was larger around type IIa fibers than around type IIx fibers, reflecting the difference between the ‘ring-pattern’ around the former and the ‘incomplete ring-pattern’ around the latter in WT mice. These data are presented in Fig. 6C.

(3) Transversely interconnected branches and capillary loops, using longitudinal muscle sections. We confirmed that there were fewer interconnected capillaries in BMD and mdx mice than in WT mice. These data are presented in Fig. 6E.

(4) The mRNA expression levels of neuronal nitric oxide synthase (nNOS). We confirmed that nNOS protein expression levels were decreased in BMD and mdx mice in spite of adequate levels of nNOS mRNA expression. The data on nNOS mRNA expression levels is presented in Fig. 3–figure supplement 1C.

(5) We added a sentence in the Abstract about the potential utility of BMD mice in developing vascular targeted therapies.

Recommendation for the authors:

Reviewer #1 (Recommendation for the authors):

Abstract:

Abstract: more emphasis should be on the pathological implications of Becker muscular dystrophy (BMD). Furthermore, should be emphasized the findings made in this article and the conclusions. Abbreviations such as DMD and MDX should be written in full and only then with the acronym.

We appreciate the reviewers’ comments, and we apologize for the confusion over abbreviations. DMD is the gene name encoding dystrophin, and mdx is the strain name of mouse lacking dystrophin.

In the Abstract and the Figure legends we changed:

(1) DMD to DMD;

(2) mdx mice to mdx mice.

Results:

Line 95: in this line, authors evaluated serum creatinine kinase (CK) levels at 1, 3, 6 and 12 months in WT mice and mdx mice. Why did you decide to study it? This part should be described in more detail. Serum CK is one of the main markers of muscle necrosis; therefore, I would report this data alongside the description of the muscle histology and necrotic fibers.

We thank the reviewers for the important remarks. In this study, serum creatine kinase (CK) levels were two-fold to four-fold higher in BMD mice than in WT mice, but its rate of increase was less than that of mdx mice. We consider that the lesser changes in serum CK levels in BMD mice may be due to the smaller area of muscle degeneration because of focal and uneven muscle degeneration compared with that in mdx mice, which showed diffuse muscle degeneration.

In response, we have moved the description of serum CK levels in the Results, from the section about the establishment of BMD mice to the section about site-specific muscle degeneration in BMD mice.

In addition, we added a description in the Discussion about the possible association between the lesser changes in serum CK levels in BMD mice and its uneven distribution of muscle degeneration.

Line 192-202: In these lines, authors observed a decrease in type IIa fibers after 3 months in BMD mice. I suggest evaluating also atrophy through evaluating cross-sectional areas (CSA) and expression of Murf1 and Atrogin1

We thank the reviewer for the point about the association between type IIa fiber reduction and muscle atrophy. We evaluated the CSAs and the mRNA expression levels of Murf1 and atrogin-1. We confirmed that the CSAs in BMD and mdx mice were rather high at 3 months, in accordance with muscle hypertrophy, compared with those of WT mice, and that Murf1 and atrogin-1 mRNA expression levels did not differ among WT, BMD, and mdx mice. These data are presented in Fig. 4–figure supplements 1B, 1C, and 1D. We added a sentence about the changes in CSA and muscle atrophy inducing factors in the Discussion.

Methods and material

Line 342-348: authors have described animals, but not specified sex and number of mice in each group. This part should be improved.

We apologize for our insufficient information about the sex and number of mice in the Materials and methods.

We added a sentence specifying the sex, number, and evaluation period of each mouse group in the section on the generation of BMD mice.

Line 426-433: authors described qPCR. It is necessary that the authors also describe primer sequences.

We apologize for any lack of information about the primer sequences used in qPCR analysis. Supplemental Table 1 lists the primer sequences.

We also added a sentence about the information in the primer list in the section on RNA isolation and RT-PCR in the Materials and methods.

Reviewer #2 (Recommendation for the authors):

Miyazaki et al. established three distinct BMD mouse models by removing different exon regions of the dystrophin gene. The authors demonstrated that the pathophysiological and molecular changes in these models progress at varying rates. Additionally, they observed a site-specific decline in type IIa fibers in BMD mice, while the proportions of other fiber types, such as type I and type IIx, remained consistent with those in wild-type mice. They proposed that the selective decay of type IIa fibers in BMD mice could be due to two primary factors: 1) muscle degeneration and regeneration, supported by their findings in cardiotoxin-treated mouse models, and 2) reduced capillary formation around type IIa fibers. However, the authors also presented evidence that type IIx fibers exhibited delayed recovery, similar to type IIa fibers, as demonstrated in cardiotoxin-induced regeneration models. Additionally, dot-patterned capillary formations were observed around both type IIa and type IIx fibers. Despite these findings, BMD mice did not show any changes in the proportion of type IIx fibers in inner BMD muscles. The authors should consider adding further analysis to strengthen their hypothesis and to disclose any possible mechanisms that led to these discrepancies.

If the authors hypothesize that reduced capillary density around type IIa fibers contribute to their site-specific decay in BMD mice, they should consider measuring and statistically analyzing the endothelial area around all fiber types. By plotting and comparing these measurements across different fiber types between wild-type, BMD, and mdx mice, the authors could provide more robust evidence to support their hypothesis. This approach would help clarify whether reduced capillary density is a contributing factor to the site-specific decay of type IIa fibers in BMD mice and the more diffuse, non-specific muscle changes observed in mdx mice.

The authors reported in the first part of the manuscript that histopathological changes, including muscle degeneration in BMD mice, are predominantly restricted to the inner part of the muscles. In the second part, they noted a decline in type IIa fibers specifically in the inner muscle region. To strengthen the hypothesis that the decay of type IIa fibers in the inner muscle is linked to muscle degeneration, the authors should consider performing histopathological measurements across different fiber types within the inner muscle. Reporting the correlations between these measurements would provide more compelling evidence to support their hypothesis.

We thank the reviewer for these important suggestions about the association between type IIa fiber reduction and capillary change around muscle fibers in BMD mice. We prepared an additional evaluation about the capillary formation (in Fig. 6B) and endothelial area (in Fig. 6C) around type IIx, IIb, and I fibers. We found that capillaries contacting around type IIx, IIb, and I fibers were poor in WT mice compared with those around type IIa fibers, and showed an ‘incomplete ring-pattern’ around type IIx fibers and a ‘dot-pattern’ around type IIb and I fibers in WT mice, in contrast with type IIa fibers, which showed remarkable ‘ring-pattern’ capillaries. Reflecting this, the changes in endothelial area around type IIx, IIb, and I fibers between WT and BMD mice were less than those around type IIa fibers. These results suggest that type IIa fibers may require numerous capillaries and maintained blood flow compared with type IIx, IIb, and I fibers, and this high requirement for blood flow might be associated with the type IIa fiber-specific decay in BMD mice.

We added the following.

(1) Sentences in the Results about the capillary changes around type IIx, IIb, and I fibers in WT, d45-49, and mdx mice.

(2) Sentences in the Results about the changes in endothelial area around type IIx, IIb, and I fibers in WT, d45-49, and mdx mice.

(3) Sentences in the Discussion about the association between the type IIa fiber-specific decay in BMD mice and the differences in capillary changes of each muscle fiber from WT to BMD mice.

We changed a sentence in the Discussion about the delayed recovery of type IIa and IIx fibers after CTX injection, to make it clear that the recovery of type IIx fibers was slower than that of type IIa fibers after CTX injection, and that therefore the type IIa fiber-specific decay in BMD mice might not be explained by this vulnerability and delayed recovery during muscle degeneration and regeneration.

Minor Issues:

Line 103: The word "mice" is duplicated and should be corrected.

We apologize that “mice” was duplicated. We have corrected it.

Line 120: Revise for clarity: "The proportion of opaque fibers is significantly different between d45-48 mice and WT at 3 months, with an increased tendency observed only in 1-month-old mice."

We apologize for the confusion about the proportion of opaque fibers. We revised this sentence as follows.

“Opaque fibers, which are thought to be precursors of necrotic fibers, increased at an earlier age of 1 month in d45–49 mice compared with WT mice; in contrast, the proportion of opaque fibers differs significantly between d45–47 and WT mice at 3 months, with an increased tendency only in 1-month-old mice (Fig. 2C).”

Line 152: Clarify the statement regarding utrophin levels, as it currently contradicts the Western blot data. The sentence reads: "The increased levels of utrophin are 8-fold higher at 1 month and 30-fold higher at 3 months." This should be verified against the data, as the band densities in the Western blots suggest otherwise.

We apologize for the confusion about utrophin expression levels. We revised this sentence as follows.

“By western blot analysis, the utrophin expression levels showed only an increased tendency in all BMD mice at 3 months, whereas there was a significant increase in mdx mice (8-fold at 1 month, and 30-fold at 3 months) compared to WT mice (Figs. 3C and F).”

Line 235: Correct the sentence to accurately reflect the findings: "BMD mice showed reduced muscle weakness."

We apologize for our incorrect wording. We have removed the word “reduced” in this sentence.

eLife Assessment

This valuable work provides solid evidence that a neuronal metallothionein, GIF/MT-3, incorporates metal-persulfide clusters. A variety of well-designed assays support the authors' hypothesis, revealing that sulfane sulfur is released from MT-3. The biological role of the persulfidated form is not yet clearly defined. There are caveats to the findings that limit the study, but the work will nevertheless prompt major follow-up work.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors reveal that GIF/MT-3 regulates the zinc homeostasis depending on the cellular redox status. The manuscript technically sounds, and their data concretely suggest that the recombinant MTs, not only GIF/MT-3 but also canonical MTs such as MT-1 and MT-2, contain sulfane sulfur atoms for the Zn-binding. The scenario proposed by the authors seems to be reasonable to explain the Zn homeostasis by the cellular redox balance.

Strengths:

The data presented in the manuscript solidly reveal that recombinant GIF/MT-3 contains sulfane sulfur.

Weaknesses:

It remains unclear whether native MTs, in particular induced MTs in vivo contain sulfane sulfur or not.

Comments on revisions:

Although the authors have revealed the sulfane sulfur content in native MT-3, my question, namely, whether canonical MT-1 and MT-2 contained sulfane sulfur after the induction has been left.<br /> The authors argue that the biological significance of sulfane sulfur in MTs lies in its ability to contribute to metal binding affinity, provide a sensing mechanism against oxidative stress, and aid in the regulation of the protein. Due to their biological roles, induced MT-1 and MT-2 could contain sulfane sulfur in their molecules. Thus, I expect the authors to evaluate or explain the sulfane sulfur content in induced MT-1 and MT-2.

Reviewer #3 (Public review):

Summary:

The authors were trying to show that a novel neuronal metallothionein of poorly defined function, GIF/MT3, is actually heavily persulfidated in both the Zn-bound and apo (metal-free) forms of the molecule as purified from a heterologous (bacterial) or native host. Evidence in support of this conclusion is strong, with both spectroscopic and mss spectrometry evidence strongly consistent with this general conclusion. The authors would appear to have achieved their aims.

Strengths:

The analytical data in support of the author's primary conclusions are strong. The authors also provide some modeling evidence that supports the contention that MT3 (and other MTs) can readily accommodate a sulfane sulfur on each of the 20 cysteines in the Zn-bound structure, with little perturbation of the overall structure. This is not the case with Cys trisulfides, which suggests that the persulfide-metallated state is clearly positioned at lower energy relative to the immediately adjacent thiolate- or trisulfidated metal coordination complexes.

Weaknesses:

The biological significance of the findings is not entirely clear. On the one hand, the analytical data are solid (albeit using a protein derived from a bacterial over-expression experiment), and yes, it's true that sulfane S can protect Cys from overoxidation, but everything shown in the summary figure (Fig. 9D) can be done with Zn release from a thiol by ROS, and subsequent reduction by the Trx/TR system. In addition, it's long been known that Zn itself can protect Cys from oxidation. I view this as a minor shortcoming that will motivate follow-up studies.

Impact:

The impact will be high since the finding is potentially disruptive to the MT field for sure. The sulfane sulfur counting experiment (the HPE-IAM electrophile trapping experiment) may well be widely adopted by the field. Those in the metals field always knew that this was a possibility, and it will interesting to see the extent to which metal binding thiolates broadly incorporate sulfane sulfur into their first coordination shells.

Comments on revisions:

The revised manuscript is only slightly changed from the original, with the inclusion of a supplementary figure (Fig. S2) and minor changes in the text. The authors did not choose to carry out the quantitative Zn binding experiment (which I really wanted to see), but given the complexities of the experiment, I'll let it go.

Fig. 9: the authors imply in the mechanistic "redox-switch" figure that Trx/TR can not reduce persulfide linkages. A number of groups have shown this to be the case. I recommend modifying the figure legend or text to make this clear to the reader,

Author response:

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

Reviewer #1 (Public Review):

The manuscript by Dr. Shinkai and colleagues is about the posttranslational modification of a highly important protein, MT3, also known as the growth inhibitory factor. Authors postulate that MT3, or generally all MT isoforms, are sulfane sulfur binding proteins. The presence of sulfane sulfur at each Cys residue has, according to the authors, a critical impact on redox protein properties and almost does not affect zinc binding. They show a model in which 20 Cys residues with sulfane sulfur atoms can still bind seven zinc ions in the same clusters as unmodified protein. They also show that recombinant MT3 (but also MT1 and MT2) protein can react with HPE-IAM, an efficient trapping reagent of persulfides/polysulfides. This reaction performed in a new approach (high temperature and high reagent concentration) resulted in the formation of bis-S-HPE-AM product, which was quantitatively analyzed using LC-MS/MS. This analysis indicated that all Cys residues of MT proteins are modified by sulfane sulfur atoms. The authors performed a series of experiments showing that such protein can bind zinc, which dissociates in the reaction with hydrogen peroxide or SNAP. They also show that oxidized MT3 is reduced by thioredoxin. It gives a story about a new redox-dependent switching mechanism of zinc/persulfide cluster involving the formation of cystine tetrasulfide bridge.

The whole story is hard to follow due to the lack of many essential explanations or full discussion. What needs to be clarified is the conclusion (or its lack) about MT3 modification proven by mass spectrometry. Figure 1B shows the FT-ICR-MALDI-TOF/MS spectrum of recombinant MT3. It clearly shows the presence of unmodified MT3 protein without zinc ions. Ions dissociate in acidic conditions used for MALDI sample preparation. If the protein contained all Cys residues modified, its molecular weight would be significantly higher. Then, they show the MS spectrum (low quality) of oxidized protein (Fig. 1C), in which new signals (besides reduced apo-MT3) are observed. They conclude that new signals come from protein oxidation and modification with one or two sulfur atoms. If the conclusion on Cys residue oxidation is reasonable, how this protein contains sulfur is unclear. What is the origin of the sulfur if apo-MT does not contain it? Oxidized protein was obtained by acidification of the protein, leading to zinc dissociation and subsequent neutralization and air oxidation. Authors should perform a detailed isotope analysis of the isotopic envelope to prove that sulfur is bound to the protein. They say that the +32 mass increase is not due to the appearance of two oxygen donors. They do not provide evidence. This protein is not a sulfane sulfur binding protein, or its minority is modified. Moreover, it is unacceptable to write that during MT3 oxidation are "released nine molecules of H2". How is hydrogen molecule produced? Moreover, zinc is not "released", it dissociates from protein in a chemical process.

Thank you for your comment. According to your suggestion, we have rewritten the corresponding sentences below, together with addition of new Fig.1D.

First, the sentence “which corresponded to the mass of zinc-free apo-GIF/MT3 and indicated that zinc was removed during MS analysis.” was changed to “which corresponded to the mass of zinc-free apo-GIF/MT3 and indicated that zinc dissociates from protein in acidic conditions used for MALDI sample preparation.” in the introduction section. Second, we have added the following sentence “However, FT-ICR-MALDI-TOF/MS analysis failed to detect sulfur modifications in GIF/MT-3 (Fig. 1B), suggesting that sulfur modifications in the protein were dissociated during laser desorption/ionization. Therefore, we postulate that the small amount of sulfur detected in oxidized apo-GIF/MT-3 is derived from the effect of laser desorption/ionization rather than any actual modification of the minority component.” in the discussion section. Third, we have added new Fig. 1D and the corresponding citation in the introduction. Fourth, the sentence “An increase in mass of 32 Da can also result from addition of two oxygen atoms, but we attributed it to one sulfur atom for reasons described later.” was changed to “Note that an increase in mass of 32 Da can also result from addition of two oxygen atoms.”.

Another important point is a new approach to the HPE-IAM application. Zinc-binding MT3 was incubated with 5 mM reagent at 60°C for 36 h. Authors claim that high concentration was required because apoMT3 has stable conformation. Figure 2B shows that product concentration increases with higher temperature, but it is unclear why such a high temperature was used. Figure 1D shows that at 37°C, there is almost no reaction at 5 mM reagent. Changing parameters sounds reasonable only when the reaction is monitored by mass spectrometry. In conclusion, about 20 sulfane sulfur atoms present in MT3 would be clearly visible. Such evidence was not provided. Increased temperature and reagent concentration could cause modification of cysteinyl thiol/thiolates as well, not only persulfides/polysulfides. Therefore, it is highly possible that non-modified MT3 protein could react with HPE-IAM, giving false results. Besides mass spectrometry, which would clearly prove modifications of 20 Cys, authors should use very important control, which could be chemically synthesized beta- or alfa-domain of MT3 reconstituted with zinc (many protocols are present in the literature). Such models are commonly used to test any kind of chemistry of MTs. If a non-modified chemically obtained domain would undergo a reaction with HPE-IAM under such rigorous conditions, then my expectation would be right.

Thank you for your comments. Although we have already confirmed that no false-positive results were observed using this method in Fig. 5 (previously Fig. 4), we have conducted additional experiments by preparing chemically synthesized α- and β-domains of GIF/MT-3, as well as recombinant α- and β-domains of GIF/MT-3. As shown in the new Fig. S2A, the chemically synthesized α- and β-domains of GIF/MT-3 detected almost no sulfane sulfur (less than 1 molecule per protein), whereas the recombinant α- and β-domains detected several molecules of sulfane sulfur (more than 5 molecules per protein) (Fig. S2A). Therefore, I would like to emphasize here that the cysteine residue itself cannot be the source of the bis-S-HPE-AM product (sulfane sulfur derivative).

Accordingly, we have added the following sentence in the results section: “Because this assay was performed at relatively high temperatures (60°C), we also examined the sulfane sulfur levels of several mutant proteins using chemically synthesized α- and β-domains of GIF/MT-3 to eliminate false-positive results. As shown in Fig. S2A, sulfane sulfur (less than 1 molecule per protein) was undetectable in chemically synthesized α- and β-domains of GIF/MT-3, whereas several molecules of sulfane sulfur per protein were detected in recombinant α- and β-domains exhibited (Fig. S2B, left panel). These findings indicated that the sulfane sulfur detected in our assay was derived from biological processes executed during the production of GIF/MT-3 protein. We further analyzed mutant proteins with β-Cys-to-Ala and α-Cys-to-Ala substitutions and found that their sulfane sulfur levels were comparable with those of the α- and β-domains of GIF/MT-3, respectively (Fig. S2B, left panel). Additionally, Ser-to-Ala mutation did not affect the sulfane sulfur levels of GIF/MT-3. The zinc content of each mutant protein was also determined under these conditions (Fig. S2B, right panel).”

- The remaining experiments provided in the manuscript can also be applied for non-modified protein (without sulfane sulfur modification) and do not provide worthwhile evidence. For instance, hydrogen peroxide or SNAP may interact with non-modified MTs. Zinc ions dissociate due to cysteine residue modification, and TCEP may reduce oxidized residue to rescue zinc binding. Again, mass spectrometry would provide nice evidence.

Thank you for your comment. We understand that such experiments can also be applied to non-modified proteins (without sulfane sulfur modification). However, the experiments shown in Fig. 4 and Fig. 6 were conducted to investigate the role of sulfane sulfur under oxidative stress conditions, rather than to examine sulfur modification in the protein itself. As mentioned previously, it is difficult to detect sulfur modifications directly in the protein using MALDI-TOF/MS (Fig. 1), as sulfur modifications appear to dissociate during the laser desorption/ionization process.

- The same is thioredoxin (Fig. 7) and its reaction with oxidized MT3. Nonmodified and oxidized MT3 would react as well.

Thank you for your comment. We understand that such experiments can also be applied to non-modified MT-3 protein. However, to the best of our knowledge, this is the first report demonstrating that apo-MT-3 can serve as a good substrate for the Trx system. In fact, this experiment is not intended to prove that MT-3 is sulfane sulfur-binding protein. Rather, it demonstrates the novel finding that apo-MT3 serves as an excellent substrate for Trx and that the sulfane sulfur (persulfide structure) remains intact throughout the reduction process.

- If HPE-IAM reacts with Cys residues with unmodified MT3, which is more likely the case under used conditions, the protein product of such reaction will not bind zinc. It could be an explanation of the cyanolysis experiment (Fig. 6).

Thank you for your comment. As you pointed out, HPE-IAM reacts with cysteine residues in unmodified MT-3, thereby preventing zinc from binding to the protein. However, we did not use HPE-IAM prior to measuring zinc binding. Instead, HPE-IAM was used solely for determining the sulfane sulfur content in the protein, and thus it cannot explain the results of the cyanolysis experiment.

- Figure 4 shows the reactivity of (pol)sulfides with TCEP and HPE-IAM. What are redox potentials? Do they correlate with the obtained results?

Thank you for your comment. However, we must apologize as we do not fully understand the rationale behind determining redox potentials in this experiment. We believe the data itself to be very clear and presenting convincing results.

- Raman spectroscopy experiments would illustrate the presence of sulfane sulfur in MT3 only if all Cys were modified.

Yes, that is correct. Since approximately 20 sulfane sulfur atoms are detected in the protein with 20 cysteine residues, we believe that nearly all cysteine residues are modified by sulfane sulfur. Therefore, Raman spectroscopy is considered applicable to our current study.

- The modeling presented in this study is very interesting and confirms the flexibility of metallothioneins. MT domains are known to bind various metal ions of different diameters. They adopt in this way to larger size the ions. The same mechanism could be present from the protein site. The presence of 9 or 11 sulfur atoms in the beta or alfa domain would increase the size of the domains without changing the cluster structure.

We truly appreciate your positive evaluation of this work.

- Comment to authors. Apo-MT is not present in the cell. It exists as a partially metallated species. The term "apo-MT" was introduced to explain that MTs are not fully saturated by metals and function as a metal buffer system. Apo-MT comes from old ages when MT was considered to be present only in two forms: apo-form and fully saturated forms.

Thank you for your insightful comments. We find it reasonable to understand that apo-MT exists as a partially metallated species within the cell.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors reveal that GIF/MT-3 regulates zinc homeostasis depending on the cellular redox status. The manuscript technically sounds, and their data concretely suggest that the recombinant MTs, not only GIF/MT-3 but also canonical MTs such as MT-1 and MT-2, contain sulfane sulfur atoms for the Zn-binding. The scenario proposed by the authors seems to be reasonable to explain the Zn homeostasis by the cellular redox balance.

Strengths:

The data presented in the manuscript solidly reveal that recombinant GIF/MT-3 contains sulfane sulfur.

Weaknesses:

It is still unclear whether native MTs, in particular, induced MTs in vivo contain sulfane sulfur or not.

Thank you for pointing out the strengths and weaknesses of this manuscript. Based on your suggestions, we have determined the sulfane sulfur content in the native GIF/MT-3 protein, as explained in our response to "Recommendations for the Authors #2."

Reviewer #3 (Public Review):

Summary:

The authors were trying to show that a novel neuronal metallothionein of poorly defined function, GIF/MT3, is actually heavily persulfidated in both the Zn-bound and apo (metal-free) forms of the molecule as purified from a heterologous or native host. Evidence in support of this conclusion is compelling, with both spectroscopic and mass spectrometry evidence strongly consistent with this general conclusion. The authors would appear to have achieved their aims.

Strengths:

The analytical data are compelling in support of the author's primary conclusions are strong. The authors also provide some modeling evidence that strongly supports the contention that MT3 (and other MTs) can readily accommodate sulfane sulfur on each of the 20 cysteines in the Zn-bound structure, with little perturbation of the structure. This is not the case with Cys trisulfides, which suggests that the persulfide-metallated state is clearly positioned at lower energy relative to the immediately adjacent thiolate- or trisulfidated metal coordination complexes.

Weaknesses:

The biological significance of the findings is not entirely clear. On the one hand, the analytical data are clearly solid (albeit using a protein derived from a bacterial over-expression experiment), and yes, it's true that sulfane S can protect Cys from overoxidation, but everything shown in the summary figure (Fig. 8D) can be done with Zn release from a thiol by ROS, and subsequent reduction by the Trx/TR system. In addition, it's long been known that Zn itself can protect Cys from oxidation. I view this as a minor weakness that will motivate follow-up studies. Fig. 1 was incomplete in its discussion and only suggests that a few S atoms may be covalently bound to MT3 as isolated. This is in contrast to the sulfate S "release" experiment, which I find quite compelling.

Impact:

The impact will be high since the finding is potentially disruptive to the metals in the biology field in general and the MT field for sure. The sulfane sulfur counting experiment (the HPE-IAM electrophile trapping experiment) may well be widely adopted by the field. Those of us in the metals field always knew that this was a possibility, and it will interesting to see the extent to which metal-binding thiolates broadly incorporate sulfate sulfur into their first coordination shells.

Thank you for pointing out the strengths and weaknesses of this manuscript. As you noted, the explanations and discussions regarding Fig. 1 were missing. To address this, we have added the following sentences to the discission section: “However, FT-ICR-MALDI-TOF/MS analysis failed to detect sulfur modifications in GIF/MT-3 (Fig. 1B), suggesting that sulfur modifications in the protein were dissociated during laser desorption/ionization. Therefore, we postulate that the small amount of sulfur detected in oxidized apo-GIF/MT-3 is derived from the effect of laser desorption/ionization rather than any actual modification of the minority component.”

Reviewer #1 (Recommendations For The Authors):

Overall, the topic of the study is interesting, but the provided evidence is insufficient to claim that MT3 is a sulfane sulfur-binding protein. Indeed, some recent studies showed that natural and recombinant MT proteins can be modified, but only one or a few cysteine residues were modified. Authors should follow my suggestion and apply mass spectrometry to all performed reactions and, first of all, to freshly obtained protein. I strongly suggest using chemically synthesized and reconstituted domains to test whether the home-developed approach is appropriate. Moreover, native MS and ICP-MS analysis of MT3 would support their claims.

Thank you for your insightful comments. Following your suggestions, we have prepared chemically synthesized proteins of the α- and β-domains of GIF/MT-3 and conducted additional experiments, as explained in response comments to “Public Review #1”. Regarding the MS analysis, we have also added a discussion on the difficulty of detecting sulfur modifications in the protein.

Reviewer #2 (Recommendations For The Authors):

I have some minor points which should be considered by the authors.

(1) Table 1: In the simulation by MOE, the authors speculated 7 atoms of metal bound to GIF/MT-3. Although a total of 7 atoms of Zn or Cd are actually bound to MTs as a divalent ion, the number of Cu and Hg bound to MTs as a monovalent ion is scientifically controversial. Several ideas have been proposed in the literature, however, "7 atoms of Cu or Hg" could be inappropriate as far as I know. The authors should simulate again using a more appropriate number of Cu or Hg in MTs.

Thank you for providing this valuable information. We reviewed several papers by the Stillman group and found that the relative binding constants of Cu4-MT, Cu6-MT, and Cu10-MT were determined after the addition of Cu(I) to apo MT-1A, MT-2, and MT-3 (Melenbacher and Stillman, Metallomics, 2024). However, incorporating these copper numbers into our GIF/MT-3 simulation model proved challenging. Therefore, we decided to omit the score value for copper in Table 1.

On the other hand, some researchers have reported that mercury binds to MT as a divalent ion, and the formation of Hg₇MT is possible (not just other forms). Therefore, we decided to continue using the score value for mercury shown in Table 1.

(2) If possible, native MT samples isolated from an experimental animal should be evaluated for the sulfane sulfur content. Canonical MTs, MT-1 and MT-2, are highly inducible by not only heavy metals but also oxidative stress. Under the oxidative stress condition such as the exposure of hydrogen peroxide, it is questionable whether the induced Zn-MTs contain sulfane sulfur or not.

According to your suggestion, we evaluated the sulfane sulfur content in native GIF/MT-3 samples isolated from mouse brain cytosol (Fig. 10). The measured amount was 3.3 per protein. This suggests that sulfane sulfur in GIF/MT-3 could be consumed under oxidative conditions, as you anticipated. Another possible explanation for the discrepancy between the native form and recombinant protein is likely related to metal binding in the protein. It is generally understood that both zinc and copper bind to GIF/MT-3 in approximately equal proportions in vivo. When we prepared recombinant copper-binding GIF/MT-3 protein, the sulfane sulfur content in the protein was significantly different (approximately 4.0 per protein) compared to the Zn₇GIF/MT-3 form. Further studies are needed to clarify the relationship between sulfane sulfur binding and the types of metals in the future.

(3) The biological significance of sulfane sulfur in MTs is still unclear to me.

Thank you for your comments. To address this question, we have added the following sentence to the discussion section: “The biological significance of sulfane sulfur in MTs lies in its ability to 1) contribute to metal binding affinity, 2) provide a sensing mechanism against oxidative stress, and 3) aid in the regeneration of the protein.”

(4) According to the widely accepted nomenclature of MT, "MT3" should be amended to "MT-3".

According to your suggestion, we have amended from MT3 to MT-3 throughout the manuscript.

Reviewer #3 (Recommendations For The Authors):

Most of my comments are editorial in nature, largely focused on what I perceive as overinterpretation or unnecessary speculation.

The authors state in the abstract that the intersection of sulfane sulfur and Zn enzymes "has been overlooked." This is not actually true - please tone down to "under investigated" or something like this.

Based on your suggestion, we have replaced the term “has been overlooked” with “has been under investigated” in the abstract.

Line 228: The discussion of Fig. 6C involved too much speculation. I cannot see a quantitative experiment that supports this.

Based on your suggestion, we have removed Fig. 6C (currently referred to as Fig. 7C). Additionally, we have revised the sentence from “implying that the sulfane sulfur is an essential zinc ligand in apo-GIF/MT3 and that an asymmetric SSH or SH ligand is insufficient for native zinc binding (Fig. 6C)” to “implying the contribution of sulfane sulfur to zinc binding in GIF/MT-3”.

Line 247 "persulfide in apo-GIF/MT3 seems.." I think the authors mean that the Zn form of the protein is resistant to Trx or TCEP.

Thank you for pointing this out. We realized that the term “persulfide in apo-GIF/MT3” might be confusing. Therefore, we have replaced it with “persulfide formation derived from apo-GIF/MT3” in the corresponding sentence.

Molecular modeling: We need more details- were these structures energy-minimized in any way? Can the authors comment on the plethora of S-S dihedral angles in these structures, and whether they are consistent with expectations of covalent geometry? Please add text to explain or even a table that compiles these data.

Thank you for your comment. Yes, energy minimization calculations for structural optimization were conducted during homology modeling in MOE. In fact, we have already stated in the Methods section that “Refinement of the model with the lowest generalized Born/volume integral (GBVI) score was achieved through energy minimization of outlier residues in Ramachandran plots generated within MOE.” In this model, covalent geometry, including the S-S dihedral angles, is also taken into consideration.

What is a thermostability score? Perhaps a bit more discussion here and what relationship this has to an apparent (or macroscopic) metal affinity constant.

The thermostability score is used to compare the thermal stability between the wild-type and mutant proteins. As shown in Equation (1) in the method section, it is calculated by subtracting the energy of the hypothetical unfolded state from the energy of the folded state. Since obtaining the structure of the unfolded state requires extensive computational effort, MOE employs an empirical formula based on two-dimensional structural features to estimate it. The ΔΔG values represent the difference between ΔGf(WT) and ΔGf(Mut). However, because it is difficult to directly determine ΔGf(Mut) and ΔGf(WT), MOE calculates ΔΔG using the thermodynamic cycle equivalence: ΔΔGs =ΔGsf (WT→Mut) - ΔGsu (WT→Mut), as expressed in Equation (1).

On the other hand, the affinity score represents the interaction energy between the target ligand and the protein. In this study, we calculated the affinity score by selecting metal atoms as the ligands. The interaction energy (E int) is defined as:

E int = E complex − E receptor − E ligand

where each term is as follows:

E complex : Potential energy of the complex.

E receptor : Potential energy of the receptor alone.

E ligand : Potential energy of the ligand alone.

Each potential energy term includes contributions from bonded interactions such as bond lengths and bond angles. However, since there is no structural difference among E receptor, and E ligand, the bonded energy components cancel out. Consequently, E int is determined as:

E int = ΔEele +ΔEvdW +ΔE sol

Here, a negative E int indicates that the complex is more stable, while a positive E int implies that the receptor and ligand are more stable in their dissociated states.

We have revised the sentence "The affinity score was also calculated using MOE software as the difference between the ΔΔGs values of the protein, free zinc, and metal–protein complex” to "The affinity score was also calculated using MOE software as the difference between the potential energy values of the protein, free zinc, and metal–protein complex” to correct the misdescription.

Lines 278-280: The authors state that they observe a "marked enhancement of metal binding affinity, and rearrangement of zinc ions." I don't see support for this rather provocative conclusion. This is the expectation of course. I would love to see actual experimental data on this point, direct binding titrations with metals performed before and after the release of the sulfate sulfur atoms.

Thank you for your comments. Although this statement is based on the 3D modeling simulation, we have also experimentally observed that the diminishment of sulfane sulfur in GIF/MT-3 resulted in a decrease in zinc binding levels, as shown in Fig. 7. However, conducting direct binding titration experiments was difficult for us due to the difficulty in preparing pure GIF/MT-3 protein with or without sulfane sulfur. Therefore, we have revised the sentence "marked enhancement of metal binding affinity, and rearrangement of zinc ions" to simply "enhancement of metal binding affinity" to avoid over-speculation.

Table I- quantitatively lower stability for the Cu complex- the stoichiometry is clearly wrong in this simulation- please redo this simulation with the right stoichiometry or Cu to MT3- consult a Stillman paper.

Thank you for providing this valuable information. We reviewed several papers by the Stillman group and found that the relative binding constants of Cu4-MT, Cu6-MT, and Cu10-MT were determined after the addition of Cu(I) to apo MT-1A, MT-2, and MT-3 (Melenbacher and Stillman, Metallomics, 2024). However, incorporating these copper numbers into our GIF/MT-3 simulation model proved challenging. Therefore, we decided to omit the score value for copper in Table 1.

I like the model for reversible metal release mediated by the thioredoxin system (Fig. 8D)- but you can also do this with thiols- nothing really novel here. Has it been generally established that tetraulfides are better substrates for the Trx/TR system? The data shown in Fig. 7B seems to suggest this, but is this broadly true, from the literature?

There are reports describing that persulfides and polysulfides are reduced by the thioredoxin system. However, it is not well-established that tetraulfides are better substrates for the Trx/TR system. To the best of our knowledge, this is the first report demonstrating that apo-MT-3 can serve as a good substrate for the Trx/TR system. Further research is required to compare the catalytic efficiency between proteins containing disulfide and those with tetraulfide moieties.

Line 380: Many groups have reported that many proteins are per- or polysulfidated in a whole host of cells using mass spectrometry workflows, and that terminal persulfides can be readily reduced by general or specific Trx/TR systems. This work could be better acknowledged in the context of the authors' demonstration of the reduction of the tetrasulfides, which itself would appear to be novel (and exciting!).

We truly appreciate your positive evaluation of this work.

eLife Assessment

This fundamental article significantly advances our understanding of FGF signalling, and in particular, highlights the complex modifications affecting this pathway. The evidence for the authors' claims is convincing, combining state-of-the-art conditional gene deletion in the mouse lens with histological and molecular approaches. This work should be of great interest to molecular and developmental biologists beyond the lens community.

Reviewer #1 (Public review):

Summary:

This manuscript uses the eye lens as a model to investigate basic mechanisms in the Fgf signaling pathway. Understanding Fgf signaling is of broad importance to biologists as it is involved in the regulation of various developmental processes in different tissues/organs and is often misregulated in disease states. The Fgf pathway has been studied in embryonic lens development, namely with regards to its involvement in controlling events such as tissue invagination, vesicle formation, epithelium proliferation and cellular differentiation, thus making the lens a good system to uncover the mechanistic basis of how the modulation of this pathway drives specific outcomes. Previous work has suggested that proteins, other than the ones currently known (e.g., the adaptor protein Frs2), are likely involved in Fgfr signaling. The present study focuses on the role of Shp2 and Shc1 proteins in the recruitment of Grb2 in the events downstream of Fgfr activation.

Strengths:

The findings reveal that the juxtamembrane region of the Fgf receptor is necessary for proper control of downstream events such as facilitating key changes in transcription and cytoskeleton during tissue morphogenesis. The authors conditionally deleted all four Fgfrs in the mouse lens that resulted in molecular and morphological lens defects, most importantly, preventing the upregulation of the lens induction markers Sox2 and Foxe3 and the apical localization of F-actin, thus demonstrating the importance of Fgfrs in early lens development, i.e. during lens induction. They also examined the impact of deleting Fgfr1 and 2, on the following stage, i.e. lens vesicle development, which could be rescued by expressing constitutively active KrasG12D. By using specific mutations (e.g. Fgfr1ΔFrs lacking the Frs2 binding domain and Fgfr2LR harboring mutations that prevent binding of Frs2), it is demonstrated that the Frs2 binding site on Fgfr is necessary for specific events such as morphogenesis of lens vesicle. Further, by studying Shp2 mutations and deletions, the authors present a case for Shp2 protein to function in a context-specific manner in the role of an adaptor protein and a phosphatase enzyme. Finally, the key surprising finding from this study is that downstream of Fgfr signaling, Shc1 is an important alternative pathway - in addition to Shp2 - involved in the recruitment of Grb2 and in the subsequent activation of Ras. The methodologies, namely, mouse genetics and state-of-the-art cell/molecular/biochemical assays are appropriately used to collect the data, which are soundly interpreted to reach these important conclusions. Overall, these findings reveal the flexibility of the Fgf signaling pathway and it downstream mediators in regulating cellular events. This work is expected to be of broad interest to molecular and developmental biologists.

Weaknesses:

A weakness that needs to be discussed is that Le-Cre depends on Pax6 activation, and hence its use in specific gene deletion will not allow evaluation of the requirement of Fgfrs in the expression of Pax6 itself. But since this is the earliest Cre available for deletion in the lens, mentioning this in the discussion would make the readers aware of this issue.

Reviewer #2 (Public review):

Summary

I have reviewed the revised manuscript submitted by Wang et al., which is entitled "Shc1 cooperates with Frs2 and Shp2 to recruit Grb2 in FGF-induced lens development". In this paper, the authors first examined lens phenotypes in mice with Le-Cre-mediated knockdown (KD) of all four FGFR (FGFR1-4), and found that pERK signals, Jag1 and foxe3 expression are absent or drastically reduced, indicating that FGF signaling is essential for lens induction. Next, the authors examined lens phenotypes of FGFR1/2-KD mice and found that lens fiber differentiation is compromised and that proliferative activity and cell survival are also compromised in lens epithelium. Interestingly, Kras activation rescues defects in lens growth and lens fiber differentiation in FGFR1/2-KD mice, indicating that Ras activation is a key step for lens development, downstream of FGF signaling. Next, the authors examined the role of Frs2, Shp2 and Grb2 in FGF signaling for lens development. They confirmed that lens fiber differentiation is compromised in FGFR1/3-KD mice combined with Frs2-dysfunctional FGFR2 mutants, which is similar to lens phenotypes of Grb2-KD mice. However, lens defects are milder in mice with Shp2YF/YF and Shp2CS mutant alleles, indicating that involvement of Shp2 is limited for the Grb2 recruitment for lens fiber differentiation. Lastly, the authors showed new evidence on the possibility that another adapter protein, Shc1, promotes Grb2 recruitment independent of Frs2/Shp2-mediated Grb2 recruitment.

Strength

Overall, the manuscript provides valuable data on how FGFR activation leads to Ras activation through the adapter platform of Frs2/Shp2/Grb2, which advances our understanding on complex modification of FGF signaling pathway. The authors applied a genetic approach using mice, whose methods and results are valid to support the conclusion. The discussion also well summarizes the significance of their findings.

Weakness

The authors found that the new adaptor protein Shc1 is involved in Grb2 recruitments in response to FGF receptor activation. However, the main data on Shc1 are only histological sections and statistical evaluation of lens size. In the revised manuscript, the authors did not answer my major concern that cellular-level data are missing, which is not fully enough to support their main conclusion on the involvement of Shc1 in Grb2 recruitment of FGF signaling for lens development. Since the title of this manuscript is that Shc1 cooperates with Frs2 and Shp2 to recruit Grb2 in FGF-induced lens development, it is important to provide the cellular-level evidence on Shc1.

Reviewer #3 (Public review):

Summary:

The manuscript entitled "Shc1 cooperates with Frs2 and Shp2 to recruit Grb2 in FGF-induced lens development" by Wang et al., investigates the molecular mechanism used by FGFR signaling to support lens development. The lens has long been known to depend on FGFR-signaling for proper development. Previous investigations have demonstrated the FGFR signaling is required for embryonic lens cell survival and for lens fiber cell differentiation. The requirement of FGFR signaling for lens induction has remained more controversial as deletion of both Fgfr1 and Fgfr2 during lens placode formation does not prevent the induction of definitive lens markers such as FOXE3 or αA-crystallin. Here the authors have used the Le-Cre driver to delete all four FGFR genes from the developing lens placode demonstrating a definitive failure of lens induction in the absence of FGFR-signaling. The authors focused on FGFR1 and FGFR2, the two primary FGFRs present during early lens development and demonstrated that lens development could be significantly rescued in lenses lacking both FGFR1 and FGFR2 by expressing a constitutively active allele of KRAS. They also showed that the removal of pro-apoptotic genes Bax and Bak could also lead to a substantial rescue of lens development in lenses lacking both FGFR1 and FGFR2. In both cases, the lens rescue included both increased lens size and the expression of genes characteristic of lens cells.

Significantly the authors concentrated on the juxtamembrane domain, a portion of the FGFRs associated with FRS2. Previous investigations have demonstrated the importance of FRS2 activation for mediating a sustained level of ERK activation. FRS2 is known to associate both with GRB2 and SHP2 to activate RAS. The authors utilized a mutant allele of Fgfr1, lacking the entire juxtamembrane domain (Fgfr1ΔFrs) and an allele of Fgfr2 containing two-point mutations essential for Frs2 binding (Fgfr2LR). When combining three floxed alleles and leaving only one functional allele (Fgfr1ΔFrs or Fgfr2LR) the authors got strikingly different phenotypes. When only the Fgfr1ΔFrs allele was retained, the lens phenotype matched that of deleting both Fgfr1 and Fgfr2. However, when only the Fgfr2LR allele was retained the phenotype was significantly milder, primarily affecting lens fiber cell differentiation, suggesting that something other than FRS2 might be interacting with the juxtamembrane domain to support FGFR signaling in the lens. The authors also deleted Grb2 in the lens and showed that the phenotype was similar to that of the lenses only retaining the Fgfr2LR allele, resulting a failure of lens fiber cell differentiation and decreased lens cell survival. However, mutating the major tyrosine phosphorylation site of GRB2 did not affect lens development. The authors additionally investigated the role of SHP2 in lens development by either deleting SHP2 or by making mutations in the SHP2 catalytic domain. The deletion of the SHP2 phosphatase activity did not affect lens development as severely as total loss of SHP2 protein, suggesting a function for SHP2 outside of its catalytic activity. Although the loss of Shc1 alone has only a slight effect on lens size and pERK activation in the lens, the authors showed that the loss of Shc1 exacerbated the lens phenotype in lenses lacking both Frs2 and Shp2. The authors suggest that SHC1 binds to the FGFR juxtamembrane domain allowing for the recruitment of GRB2 in independently of FRS2.

Strengths:

(1) The authors used a variety of genetic tools to carefully dissect the essential signals downstream of FGFR signaling during lens development.

(2) The authors made a convincing case that something other than FRS2 binding mediates FGFR signaling in the juxtamembrane domain.

(3) The authors demonstrated that despite the requirement of both the adaptor function and phosphatase activity of SHP2 are required for embryonic survival, neither of these activities is absolutely required for lens development.

(4) The authors provide more information as to why FGFR loss has a phenotype much more severe than the loss of FRS2 alone during lens development.

(5) The authors followed up their work analyzing various signaling molecules in the context of lens development with biochemical analyses of FGF-induced phosphorylation in murine embryonic fibroblasts (MEFs).

(6) In general, this manuscript represents a Herculean effort to dissect FGFR signaling in vivo with biochemical backing with cell culture experiments in vitro.

Weaknesses:

(1) The authors demonstrate that the loss of FGFR1 and FGFR2 can be compensated by a constitutive active KRAS allele in the lens and suggest that FGFRs largely support lens development only by driving ERK activation. However, the authors also saw that lens development was substantially rescued by preventing apoptosis through the deletion of BAK and BAX. To my knowledge, the deletion of BAK and BAX should not independently activate ERK. The authors do not show whether ERK activation is restored in the BAK/BAX deficient lenses. Do the authors suggest the FGFR3 and/or FGFR4 provide sufficient RAS and ERK activation for lens development when apoptosis is suppressed? Alternatively, is it the survival function of FGFR-signaling as much as a direct effect on lens differentiation?

(2) Do the authors suggest that GRB2 is required for RAS activation and ultimately ERK activation? If so, do the authors suggest that ERK activation is not required for FGFR-signaling to mediate lens induction? This would follow considering that the GRB2 deficient lenses lack a problem with lens induction.

(3) The increase in p-Shc is only slightly higher in the Cre FGFR1f/f FGFR2r/LR than in the FGFR1f/Δfrs FGFR2f/f. Can the authors provide quantification?

(4) The authors have not shown directly that Shc1 binds to the juxtamembrane region of either Fgfr1 or Fgfr2.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

This manuscript uses the eye lens as a model to investigate basic mechanisms in the Fgf signaling pathway. Understanding Fgf signaling is of broad importance to biologists as it is involved in the regulation of various developmental processes in different tissues/organs and is often misregulated in disease states. The Fgf pathway has been studied in embryonic lens development, namely with regards to its involvement in controlling events such as tissue invagination, vesicle formation, epithelium proliferation, and cellular differentiation, thus making the lens a good system to uncover the mechanistic basis of how the modulation of this pathway drives specific outcomes. Previous work has suggested that proteins, other than the ones currently known (e.g., the adaptor protein Frs2), are likely involved in Fgfr signaling. The present study focuses on the role of Shp2 and Shc1 proteins in the recruitment of Grb2 in the events downstream of Fgfr activation.

Strengths:

The findings reveal that the juxtamembrane region of the Fgf receptor is necessary for proper control of downstream events such as facilitating key changes in transcription and cytoskeleton during tissue morphogenesis. The authors conditionally deleted all four Fgfrs in the mouse lens that resulted in molecular and morphological lens defects, most importantly, preventing the upregulation of the lens induction markers Sox2 and Foxe3 and the apical localization of F-actin, thus demonstrating the importance of Fgfrs in early lens development, i.e. during lens induction. They also examined the impact of deleting Fgfr1 and 2, on the following stage, i.e. lens vesicle development, which could be rescued by expressing constitutively active KrasG12D. By using specific mutations (e.g. Fgfr1ΔFrs lacking the Frs2 binding domain and Fgfr2LR harboring mutations that prevent binding of Frs2), it is demonstrated that the Frs2 binding site on Fgfr is necessary for specific events such as morphogenesis of lens vesicle. Further, by studying Shp2 mutations and deletions, the authors present a case for Shp2 protein to function in a context-specific manner in the role of an adaptor protein and a phosphatase enzyme. Finally, the key surprising finding from this study is that downstream of Fgfr signaling, Shc1 is an important alternative pathway - in addition to Shp2 - involved in the recruitment of Grb2 and in the subsequent activation of Ras. The methodologies, namely, mouse genetics and state-of-the-art cell/molecular/biochemical assays are appropriately used to collect the data, which are soundly interpreted to reach these important conclusions. Overall, these findings reveal the flexibility of the Fgf signaling pathway and its downstream mediators in regulating cellular events. This work is expected to be of broad interest to molecular and developmental biologists.

Weaknesses:

A weakness that needs to be discussed is that Le-Cre depends on Pax6 activation, and hence its use in specific gene deletion will not allow evaluation of the requirement of Fgfrs in the expression of Pax6 itself. But since this is the earliest Cre available for deletion in the lens, mentioning this in the discussion would make the readers aware of this issue. Referring to Jag1 among "lens-specific markers" (page 5) is debatable, suggesting changing to the lines of "the expected upregulation of Jag1 in lens vesicle". The Abstract could be modified to clearly convey the existing knowledge gap and the key findings of the present study. As it stands now, it is a bit all over the place. Some typos in the manuscript need to be fixed, e.g. "...yet its molecular mechanism remains largely resolved" - unresolved? "...in the development lens" - in the developing lens? In Figure 4 legend, "(B) Grb2 mutants Grb2 mutants displayed...", etc.

We thank the reviewer for the thoughtful and constructive feedback. We have added the caveat regarding the Le-Cre dependency on Pax6 expression to the discussion, removed the reference to Jag1 as a “lens-specific marker” and corrected the typographical errors noted by the reviewer.

Reviewer #2 (Public review):

Summary:

I have reviewed a manuscript submitted by Wang et al., which is entitled "Shc1 cooperates with Frs2 and Shp2 to recruit Grb2 in FGF-induced lens development". In this paper, the authors first examined lens phenotypes in mice with Le-Cre-mediated knockdown (KD) of all four FGFR (FGFR1-4), and found that pERK signals, Jag1, and foxe3 expression are absent or drastically reduced, indicating that FGF signaling is essential for lens induction. Next, the authors examined lens phenotypes of FGFR1/2-KD mice and found that lens fiber differentiation is compromised and that proliferative activity and cell survival are also compromised in lens epithelium. Interestingly, Kras activation rescues defects in lens growth and lens fiber differentiation in FGFR1/2-KD mice, indicating that Ras activation is a key step for lens development. Next, the authors examined the role of Frs2, Shp2, and Grb2 in FGF signaling for lens development. They confirmed that lens fiber differentiation is compromised in FGFR1/3-KD mice combined with Frs2-dysfunctional FGFR2 mutants, which is similar to lens phenotypes of Grb2-KD mice. However, lens defects are milder in mice with Shp2YF/YF and Shp2CS mutant alleles, indicating that the involvement of Shp2 is limited for the Grb2 recruitment for lens fiber differentiation. Lastly, the authors showed new evidence on the possibility that another adapter protein, Shc1, promotes Grb2 recruitment independent of Frs2/Shp2-mediated Grb2 recruitment.

Strengths:

Overall, the manuscript provides valuable data on how FGFR activation leads to Ras activation through the adapter platform of Frs2/Shp2/Grb2, which advances our understanding of complex modification of the FGF signaling pathway. The authors applied a genetic approach using mice, whose methods and results are valid to support the conclusion. The discussion also well summarizes the significance of their findings.

Weaknesses:

The authors eventually found that the new adaptor protein Shc1 is involved in Grb2 recruitments in response to FGF receptor activation. however, the main data for Shc1 are histological sections and statistical evaluation of lens size. So, my major concern is that the authors need to provide more detailed data to support the involvement of Shc1 in Grb2 recruitment of FGF signaling for lens development.

We thank the reviewer for the positive comments and valuable suggestions. We have addressed the concerns in detail in the response to the recommendation outlined below.

Reviewer #3 (Public review):

Summary:

The manuscript entitled "Shc1 cooperates with Frs2 and Shp2 to recruit Grb2 in FGF-induced lens development" by Wang et al., investigates the molecular mechanism used by FGFR signaling to support lens development. The lens has long been known to depend on FGFR signaling for proper development. Previous investigations have demonstrated that FGFR signaling is required for embryonic lens cell survival and for lens fiber cell differentiation. The requirement of FGFR signaling for lens induction has remained more controversial as deletion of both Fgfr1 and Fgfr2 during lens placode formation does not prevent the induction of definitive lens markers such as FOXE3 or αA-crystallin. Here the authors have used the Le-Cre driver to delete all four FGFR genes from the developing lens placode demonstrating a definitive failure of lens induction in the absence of FGFR signaling. The authors focused on FGFR1 and FGFR2, the two primary FGFRs present during early lens development, and demonstrated that lens development could be significantly rescued in lenses lacking both FGFR1 and FGFR2 by expressing a constitutively active allele of KRAS. They also showed that the removal of pro-apoptotic genes Bax and Bak could also lead to a substantial rescue of lens development in lenses lacking both FGFR1 and FGFR2. In both cases, the lens rescue included both increased lens size and the expression of genes characteristic of lens cells.

Significantly the authors concentrated on the juxtamembrane domain, a portion of the FGFRs associated with FRS2. Previous investigations have demonstrated the importance of FRS2 activation for mediating a sustained level of ERK activation. FRS2 is known to associate both with GRB2 and SHP2 to activate RAS. The authors utilized a mutant allele of Fgfr1, lacking the entire juxtamembrane domain (Fgfr1ΔFrs), and an allele of Fgfr2 containing two-point mutations essential for Frs2 binding (Fgfr2LR). When combining three floxed alleles and leaving only one functional allele (Fgfr1ΔFrs or Fgfr2LR) the authors got strikingly different phenotypes. When only the Fgfr1ΔFrs allele was retained, the lens phenotype matched that of deleting both Fgfr1 and Fgfr2. However, when only the Fgfr2LR allele was retained the phenotype was significantly milder, primarily affecting lens fiber cell differentiation, suggesting that something other than FRS2 might be interacting with the juxtamembrane domain to support FGFR signaling in the lens. The authors also deleted Grb2 in the lens and showed that the phenotype was similar to that of the lenses only retaining the Fgfr2LR allele, resulting in a failure of lens fiber cell differentiation and decreased lens cell survival. However, mutating the major tyrosine phosphorylation site of GRB2 did not affect lens development. The author additionally investigated the role of SHP2 lens development by making by either deleting SHP2 or by making mutations in the SHP2 catalytic domain. The deletion of the SHP2 phosphatase activity did not affect lens development as severely as the total loss of SHP2 protein, suggesting a function for SHP2 outside of its catalytic activity. Although the loss of Shc1 alone has only a slight effect on lens size and pERK activation in the lens, the authors showed that the loss of Shc1 exacerbated the lens phenotype in lenses lacking both Frs2 and Shp2. The authors suggest that SHC1 binds to the FGFR juxtamembrane domain allowing for the recruitment of GRB2 independently of FRS2.

Strengths:

(1) The authors used a variety of genetic tools to carefully dissect the essential signals downstream of FGFR signaling during lens development.

(2) The authors made a convincing case that something other than FRS2 binding mediates FGFR signaling in the juxtamembrane domain.

(3) The authors demonstrated that despite the requirement of both the adaptor function and phosphatase activity of SHP2 are required for embryonic survival, neither of these activities is absolutely required for lens development.

(4) The authors provide more information as to why FGFR loss has a phenotype much more severe than the loss of FRS2 alone during lens development.

(5) The authors followed up their work analyzing various signaling molecules in the context of lens development with biochemical analyses of FGF-induced phosphorylation in murine embryonic fibroblasts (MEFs).

(6) In general, this manuscript represents a Herculean effort to dissect FGFR signaling in vivo with biochemical backing with cell culture experiments in vitro.

We thank the reviewer for the thorough review of our paper and positive comments.

Weaknesses:

(1) The authors demonstrate that the loss of FGFR1 and FGFR2 can be compensated by a constitutive active KRAS allele in the lens and suggest that FGFRs largely support lens development only by driving ERK activation. However, the authors also saw that lens development was substantially rescued by preventing apoptosis through the deletion of BAK and BAX. To my knowledge, the deletion of BAK and BAX should not independently activate ERK. The authors do not show whether ERK activation is restored in the BAK/BAX deficient lenses. Do the authors suggest the FGFR3 and/or FGFR4 provide sufficient RAS and ERK activation for lens development when apoptosis is suppressed? Alternatively, is it the survival function of FGFR-signaling as much as a direct effect on lens differentiation?

Our interpretation is that at the lens induction stage, where FGFR1 and FGFR2 are crucial, their primary function operates through Ras signaling to promote cell survival. Thus, either constitutively active KRAS or the direct suppression of apoptosis by deleting Bak and Bax is sufficient to rescue lens induction. This rescue enables the subsequent differentiation of lens progenitor cells, a process for which FGFR3 and FGFR4 are sufficient to support.

(2) The authors make the argument that deleting all four FGFRs prevented lens induction but that the deletion of only FGFR1 and FGFR2 did not. Part of this argument is the retention of FOXE3 expression, αA-crystallin expression, and PROX1 expression in the FGFR1/2 double mutants. However, in Figure 1E, and Figure 1F, the staining of the double mutant lens tissue with FOXE3, αA-crystallin, and PROX1 is unconvincing. However, the retention of FOXE3 expression in the FGFR1/FGFR2 double mutants was previously demonstrated in Garcia et al 2011. Also, there needs to be an enlargement or inset to demonstrate the retention of pSMAD in the quadruple FGFR mutants in Figure 1D.

We have updated Figure 1E with a clearer image of FOXE3 staining to better illustrate FOXE3 expression in the FGFR1/2 double mutants. It seems there may have been a misunderstanding regarding our claims about αA-crystallin and PROX1. To clarify, our observation is that both αA-crystallin and PROX1 are lost in the FGFR1/2 double mutants, which we believe is clearly demonstrated in Figure 1F. Additionally, we have added inserts to Figure 1D to highlight the retention of pSMAD.

(3) Do the authors suggest that GRB2 is required for RAS activation and ultimately ERK activation? If so, do the authors suggest that ERK activation is not required for FGFR-signaling to mediate lens induction? This would follow considering that the GRB2 deficient lenses lack a problem with lens induction.

We do believe that GRB2 is required for RAS-ERK signaling activation; however, ERK activation is not absolutely required for lens induction. This conclusion is consistent with our previous study, which showed that deletion of ERK1/2 did not prevent lens induction (Garg et al. eLife 2020;9:e51915), as well as with our current findings demonstrating that the GRB2-deficient mutant is still capable of supporting lens induction.

(4) The increase in p-Shc is only slightly higher in the Cre FGFR1f/f FGFR2r/LR than in the FGFR1f/Δfrs FGFR2f/f. Can the authors provide quantification?

pShc quantification is now provided in Fig. 7B.

(5) The authors have not shown directly that Shc1 binds to the juxtamembrane region of either Fgfr1 or Fgfr2.

It is not yet clear whether Shc1 directly binds to the juxtamembrane region of FGFR1 or FGFR2, as it may also be recruited indirectly. We acknowledge this as an important question that warrants further investigation in future studies.

(6) The authors have used the Le-Cre strain for all of their lens deletion experiments. Previous work has documented that the Le-Cre transgene can cause lens defects independent of any floxed alleles in both homozygous and hemizygous states on some genetic backgrounds (Dora et al., 2014 PLoS One 9:e109193 and Lam et al., Human Genomics 2019 13(1):10. Are the controls used in these experiments Le-Cre hemizygotes?

As stated in the Method section, Le-Cre only or Le-Cre and heterozygous flox mice were used as controls.  

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Weaknesses

There are only a few minor weaknesses that need to be addressed.

(1) The point could be made in the Discussion that since Le-Cre depends on Pax6 placodal expression, it is challenging to evaluate the impact of deletion of the four Fgfrs on the expression of Pax6 (since Pax6 needs to be activated prior to achieving Fgfr deletion). A different Cre line (e.g. a Cre which is expressed in the surface ectoderm prior to lens placode formation) could help partially address this question, although it may not be able to comment on the requirement of the Fgfrs specifically in the lens ectoderm. Thus, it will be prudent to mention this in the discussion.

We have added the caveat regarding the Le-Cre dependency on Pax6 expression to the discussion.

(2) Referring to Jag1 among "lens-specific markers" (page 5) is debatable, I suggest changing it along the lines of "the expected upregulation of Jag1 in lens vesicle".

The wording has been changed as suggested.  

(3) The Abstract could be modified to clearly convey the existing knowledge gap and the key findings of the present study. As it stands now, it is a bit all over the place.

The abstract has been revised.  

(4) Some typos in the manuscript need to be fixed.

e.g. "...yet its molecular mechanism remains largely resolved" - unresolved?, "...in the development lens" - in the developing lens?, In Fig. 4 legend, "(B) Grb2 mutants Grb2 mutants displayed...", etc.

These typos have been corrected.

Reviewer #2 (Recommendations for the authors):

My specific suggestions are shown below.

(1) The authors need to describe the role of Shc1 in FGF signaling and vertebrate lens development, by citing previous publications in the introduction.

We have detailed previous studies on the role of Shc in FGF signaling in the Introduction and discussed its function in the vertebrate lens in the Discussion section.

(2) Figure 1B bottom panels: Inset images seem to be missing, although frames and arrowheads are there. Please check them.

The inset images were correctly placed.

(3) Results (page 5, line 13): The authors mentioned "Sox2 expression remained at basal levels". Since Figure 1B indicates that Sox2 expression fails to be upregulated in FGFR1/2 mutant lens placode in contrast to Pax6, it is better to clearly mention the failure in upregulation of Sox2 expression in the FGFR1/2 mutants.

This sentence has been rewritten as suggested.  

(4) Results (page 6, line 8): The authors mentioned "we observed .... expression of Foxe3 in ...mutant lens cells (Figure 1E, arrows). However, Foxe3-expressing lens cells are a very small population in Figure 1E. It is important to state the decreased number of Foxe3-expressing lens cells in FGFR1/2 mutants. In addition, I would like to request the authors to show histograms indicating sample size and statistical analysis for marker expression: Foxe3 (Figure 1E), Prox1 and aA-crystallin (Fig. 1F), cyclin D1 and TUNEL (Fig. 1G) and pmTOR and pS6 (Supplementary figure 1B).

We added a statement indicating that the number of Foxe3-expressing cells is reduced in FGFR1/2 mutants, which is now quantified in Fig. 1H. Quantifications for Cyclin D1 and TUNEL are now shown in Fig. 1I and J, respectively. However, we chose not to quantify Prox1, αA-crystallin, pmTOR, and pS6, as the FGFR1/2 mutants showed no staining for these markers.

(5) Results (page 6, line 19- page 7, line 6): The authors showed that inducible expression of constitutive active Kras, KrasG12D, using Le-Cre, recovered lens size to the half level of wild-type control. However, in the lens of mice with Le-Cre; FGFR1/2f/f; LSL-KrasG12D, pERK was detected in the most posterior edge of the lens fiber core, whereas pERK was detected in the broader area of the lens in control. Furthermore, pMEK was detected in the whole lens of mice with Le-Cre; FGFR1/2f/f; and LSL-KrasG12D, whereas pMEK was detected only in the lens epithelial cells at the equator. So, the spatial profile of pERK and pMEK expression was different from those of wild-type, although the authors observed that Prox1 and Crystallin expression are normally induced in the lens of mice with Le-Cre; FGFR1/2f/f; LSL-KrasG12D. I wonder whether the lens normally develops in mice with Le-Cre; LSL-KrasG12D? Is the lens growth enhanced in mice with Le-Cre; LSL-KrasG12D? Please add the panels of mice with Le-Cre; LSL-KrasG12D in Figure 2B and 2C. In addition, I wonder whether apoptosis is suppressed in the lens of mice with Le-Cre; FGFR1/2f/f; LSL-KrasG12D?

As we previously reported (Developmental Biology 355, 2011, 12–20), Le-Cre; LSL-KrasG12D did not lead to enhanced lens growth. While we agree that including images of Le-Cre; LSL-KrasG12D as controls in Fig. 2B and C and evaluating apoptosis in Le-Cre; FGFR1/2f/f; LSL-KrasG12D mutants would be appropriate, we regretfully no longer have these animals available to conduct these experiments.

(6) Results (page 11, line 15): the PCR genotyping image of Fig. 6C seems to be missing.

The PCR genotyping image was correctly placed below Fig. 6B. 

(7) Results (page 11, lines 15-20): there is no citation of Figure 6D in the results section.

The citation for Fig. 6D is added in the results section.

(8) Figures 5H, 6H, and 7A: Western blotting of some of the pERK, ERK lanes is missing.

These western blots all have pERK/ERK overlay images.

(9) Figure 7A, western blotting data on pShc levels are important to suggest the involvement of Shc1 in Frs2-independent Grb2 activation by FGF stimulation. Please provide the histogram for statistical analysis.

pShc quantification is now provided in Fig. 7B.

(10) There is no citation of Figure 7D, E, and F in the results section. Please add them.

These citations have been added.

(11) Figures 7E, and 7F: The authors showed that lens morphology and lens size evaluation in genetic combinations: control, Frs2/Shc1 KD, Frs2/Shp2 KD, and Frs2/Shp2/Shc1 KD. However, I would like to request the authors to show more detailed data in these genetic combinations, for example, pERK, foxe3, Maf, Prox1, Jag1, p57, cyclin D3, g-crystallin, and TUNEL.

Unfortunately, we no longer have these mutant mice to perform these detailed staining.  

Reviewer #3 (Recommendations for the authors):

(1) The figure legend for Figure 2 lists (G) twice. The second (G) should be (H). Also, in Figures 2G and H there is no indication as to what stage lenses were used for the TUNEL and size analyses. I assume that it was E13.5, but it should be explicitly stated.

The figure labeling has been corrected and the stage added to the figure legend.

(2) In Figure 4 A the label should be gamma-crystallin rather than r-crystallin.

The figure labeling has been corrected.

(3) In Figure 6 D, I believe that the immunolabeling for Maf and Foxe3 are reversed. The Maf should be red as it is in the fibers and the Foxe3 should be green as it is epithelial.

The figure labeling has been corrected.

(4) In Figure 6C I believe that the labels for the WT and YF alleles on the western blot are reversed.

The YF PCR band was designed to be larger than WT, so the labeling was correct as is.

(5) In Figure 6F I believe that the labels for WT and CS on the western blot are reversed.

The figure labeling has been corrected.

(6) In Supplemental figure 2 there are no genotype labels for the TUNEL bar graph.

The figure labeling has been added.

eLife Assessment

In this valuable report, the authors investigated the effect of mitochondrial transplantation on post-cardiac arrest myocardial dysfunction (PAMD), which is associated with mitochondrial dysfunction. They convincingly demonstrated that mitochondrial transplantation enhanced cardiac function and increased survival rates after the return of spontaneous circulation (ROSC). They have also shown that myocardial tissues with transplanted mitochondria exhibited increased mitochondrial complex activity, higher ATP levels, reduced cardiomyocyte apoptosis, and lower myocardial oxidative stress post-ROSC.

Reviewer #1 (Public review):

Summary:

In this study, the authors investigate the effect of mitochondrial transplantation on post-cardiac arrest myocardial dysfunction (PAMD), which is associated with mitochondrial dysfunction. The authors demonstrate that mitochondrial transplantation enhances cardiac function and increases survival rates after the return of spontaneous circulation (ROSC). Mechanistically, they found that myocardial tissues with transplanted mitochondria exhibit increased mitochondrial complex activity, higher ATP levels, reduced cardiomyocyte apoptosis, and lower myocardial oxidative stress post-ROSC.

Strengths:

Previous studies have reported that mitochondrial transplantation can improve myocardial recovery after regional ischemia, but its potential for treating myocardial injury following cardiac arrest has not been tested yet. Therefore, the findings are somewhat novel. Remarkably, the increased survival in mitochondria treated group post ROSC is very promising and highlights its translational potential.

Comments on revisions:

My concerns are adequately addressed.

Reviewer #3 (Public review):

In this manuscript titled "Transplantation of exogenous mitochondria mitigates myocardial dysfunction after cardiac arrest", Zhen Wang et al. report that exogenous mitochondrial transplantation can enhance myocardial function and survival rates. It limits mitochondrial morphology impairment, boosts complexes II and IV activity, and increases ATP levels. Additionally, mitochondrial therapy reduces oxidative stress, lessens myocardial injury, and improves PAMD after cardiopulmonary resuscitation. The results of this manuscript clearly demonstrate that mitochondrial transplantation can effectively improve PAMD after cardiopulmonary resuscitation, highlighting its significant scientific and clinical value. The findings shown in this manuscript are interesting to the readers. However, further experiments are needed to confirm this conclusion. In addition, the results should be rewritten to describe and discuss the relevant data in detail.

Major comments from the original round of review:

(1) Can isolated mitochondria be transported to cultured cardiomyocytes, such as H9C2 cells, in vitro?

(2) The description of results in the manuscript is too simple. It lacks detail on the rationale behind the experiments and the significance of the data.

(3) The authors demonstrate that mitochondrial transplantation reduces cardiomyocyte apoptosis. Therefore, Western blot analysis of apoptosis-related caspases could be provided for further confirmation.

(4) Do donor mitochondria fuse with recipient mitochondria? Relevant experiments and data should be provided to address this question.

(5) In Figure 5A, the histograms are not labeled with the specific experimental groups.

Comments on revisions:

The revised manuscript quality has been improved, and most of my concerns were addressed and resolved.

Author response:

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

Reviewer 3 (Public review):

Major comments:

(1) Can isolated mitochondria be transported to cultured cardiomyocytes, such as H9C2 cells, in vitro?

Thank you for this insightful question. Mitochondria are highly dynamic organelles that play a crucial role in cellular energy metabolism. When cells encounter various stressors and increased energy demands, they can benefit from the incorporation of exogenous mitochondria. In 2013, Masuzawa et al. (Masuzawa, et al.,2013) were the first to demonstrate that transplanted mitochondria are internalized by cardiomyocytes 2 to 8 hours after transplantation, significantly contributing to the preservation of myocardial energetics. Ali et al. (Ali, et al.,2020) discovered that exogenous mitochondria could be internalized by H9C2 cardiomyocytes as quickly as 5 minutes after co-incubation, resulting in an acute enhancement of normal cellular bioenergetics following mitochondrial transplantation. Pacak et al. (Pacak, et al.,2015) established that the internalization of mitochondria into cardiomyocytes is time-dependent and occurs through actin-dependent endocytosis.

Collectively, these evidences illustrate that exogenous mitochondria can be effectively internalized by H9C2 cells and other cardiomyocytes, our experiments further confirmed that mitochondrial transplantation can be incorporated by the myocardium in vivo.

(2) The description of results in the manuscript is too simple. It lacks detail on the rationale behind the experiments and the significance of the data.

Thank you for this suggestion. We have realized that the results in the submitted manuscript have not been adequately interpreted. We have added necessary details on the rationale behind the experiments and the significance of the data to the results section (Lines 57~59, 69~73, 81~88, 91~98, 100~102, 103~104,  10⁹~115, 124~129, 135~146, 149~157, 159~161, 168~169, 178~179). We would like to express our gratitude to the reviewers once again and hope that our modifications will meet their requirements.

(3) The authors demonstrate that mitochondrial transplantation reduces cardiomyocyte apoptosis. Therefore, Western blot analysis of apoptosis-related caspases could be provided for further confirmation.

Thank you for this constructive comment. We fully agree with the reviewer's perspective on the detection of apoptosis-related caspases and have conducted a Western blot assay to investigate the impact of mitochondria on myocardial tissue. Our new evidence indicates that rats receiving mitochondrial transplantation exhibited reduced expression of cleaved caspase-3 compared with those in the NS and Vehicle groups (Fig. 6G, 6H, Lines 168~169), suggesting that mitochondrial transplantation decreased the level of apoptosis in the myocardium.

(4) Do donor mitochondria fuse with recipient mitochondria? Relevant experiments and data should be provided to address this question.

This is a very helpful comment. Investigating the fate of transplanted mitochondria in myocardial cells after CA is of great significance. The internalization of exogenous mitochondria has been observed across various cell types (Liu, et al.,2021; Shanmughapriya, et al.,2020). Notably, a recent study indicated that after being incorporated into host cells, isolated mitochondria are transported to endosomes and lysosomes. Subsequently, most of these mitochondria escape from these compartments and fuse with the endogenous mitochondrial network (Cowan, et al.,2017). We have discussed this in the manuscript. (Lines 217~220)

Oxidative stress, a pathophysiological phenomenon common to cells suffering from ischemia/reperfusion insults after CA/CPR, was implicated to promote internalization and survival of exogenous mitochondria (Aharoni-Simon, et al.,2022). In our study, we confirmed that mitochondrial transplantation can enhance the metabolism of cardiomyocytes, increase ATP level, and reduce reactive oxygen species (ROS). Our results indirectly confirm that isolated mitochondria can successfully fuse with myocardial mitochondria.

(5) In Figure 5A, the histograms are not labeled with the specific experimental groups.

We apologize for this oversight. We have labeled the specific experimental groups in the histograms presented in Figure 6B and 6C (originally Figure 5A).

Reviewer #1 (Recommendations For The Authors):

(1) The age, gender, and strain of the donor rats should be specified in the Methods section. Additionally, it is not obvious what doses of mitochondria were injected into the rats and how the dosage was initially determined.

Thanks for your suggestion. We have included relevant information about the donor rats in the Methods section（Lines 361~362）.

In Mito group, each animal received 0.5 mL of 1× 10⁹/mL mitochondrial suspension. (Lines 342~345). Considerable amounts of data have demonstrated the efficacy of mitochondrial transplantation in cellular, animal, and human research (Alemany, et al.,2024; Kaza, et al.,2017; Liu, et al.,2023). However, there is currently no evidence to determine the optimal dosage for transplantation. In previous research, isolated mitochondria (1 ×  10⁹) were delivered to the left coronary ostium in pigs, and can be a viable treatment modality in cardiac ischemia-reperfusion injury (Blitzer, et al.,2020; Guariento, et al.,2020). Additionally, the dose of 1× 10⁹ mitochondria achieve the maximal hyperemic effect when administered via intracoronary injection (Shin, et al.,2019). Considering that Sprague-Dawley (SD) rats are smaller than pigs and that there is a loss of mitochondria during pulmonary circulation, we adopted a mitochondrial transplantation dose of 5× 10⁸. We will explore the optimal dosage in our future research.

(2) In Figure 4a, the number of transplanted mitochondria appears to be very low. Considering the high number of mitochondria present in cardiomyocytes, it is unclear whether this small amount of transplanted mitochondria can significantly impact complex II activity and ATP levels in myocardial tissues, as shown in Figures 4b-d, or improve survival post-ROSC, as shown in Figure 2d. Could the observed benefits of mitochondrial transplantation be due to the indirect effects of the injected mitochondria, such as the release of mitochondrial contents, rather than the mitochondria themselves, as discussed by Bertero et al. (2021, Circ. Research)? This issue should be addressed in the manuscript.

Thanks for this wonderful comment. As presented in Fig. 4 (originally Figure 4A), our results indicated the internalization of mitochondria by myocardium, shown by colocalization of Mito-tracker and myocardium marker. We would like to make our points here regrading to Fig. 4:

(1) Significant left ventricular systolic and diastolic dysfunction that occurs in the myocardium shortly after the return of ROSC is referred to post-cardiac arrest myocardial dysfunction (PAMD) (Laurent, et al.,2002). It has demonstrated the efficacy of mitochondrial transplantation for the heart following ischemia-reperfusion injury in cellular, animal, and human studies, despite inadequate mitochondrial internalization (Liu, et al.,2023). A low number of transplanted mitochondria may improve cardiac function.

(2) Only biologically active mitochondria can be specifically labeled with Mito-tracker. Therefore, cardiomyocytes uptake mitochondria that possess complete functionality. Previous results have demonstrated that mitochondrial contents, such as nonviable mitochondria, mitochondrial fractions, mitochondrial deoxyribonucleic acid, ribonucleic acid, exogenous adenosine diphosphate and ATP, do not provide protection to the ischemic heart (McCully, et al.,2017; McCully, et al.,2009).

(3) The specific mechanism for mitochondrial internalization has yet to be fully elucidated. We totally agree with reviewer’s opinion pertaining the presence of other mechanisms of mitochondria transplantation that play a role in cardiac protection. Multiple mechanism may involve in the cardiac protection effect of mitochondria transplantation, and we are actively seeking reasonable approach to verify these hypotheses in an underway study (Lines 236~246).

(3) In Figure 4g, the claims regarding sarcomere length, mitochondrial structure, the number of cristae, accumulated calcium etc. seem to rely on the visual interpretation of representative images. To ensure a reliable interpretation of the data, a blinded quantification of each image in each group should be conducted. The same applies to the claims made in Figure 5E.

Thanks for this suggestion. We have quantitatively evaluated the electron microscope images and HE images of the myocardium to ensure reliable interpretation. Corresponding supplements have been added to the methods (Lines 433~441, 494~496), results sections (Lines  10⁹~115, 178~179), and Figures 5C, 5D, 6K and 6H (originally Figures 4G and 5E).

(4) In line 69, it is unclear why the authors claim that MAP and HR decrease at 1, 2, 3, and 4 hours after ROSC in all groups compared to the Sham group, despite stating in line 72 that "MAP and HR did not differ at any observational time points (P>0.05, Figure 2C)."

We apologize for our inaccurate phrasing. In the presented study, there was no statistically significant difference between MAP and HR at any observational timepoints (P>0.05, Figure 2C). In the NS, Vehicle and Mito groups, the MAP and HR decreased at 1, 2, 3, and 4 hours after ROSC, reaching their nadir at 1 hour. Subsequently, MAP and HR increased gradually but did not show any statistically significant differences compared with the Sham group.  (Lines 69~73).

(5) The absence of increased mitochondrial content in the mito-groups should be discussed further in the manuscript.

Thank you for your suggestion. We discussed the reasons why the mass of isolated mitochondria did not increase in Lines 224~235.

(6) The N in Figure 5d should be provided.

Thanks for your suggestion. We have revised the figure legend to include N of Figure 6F (originally Figures 5D).

(7) Figure 6 demonstrates content beyond the findings in this manuscript. This reviewer recommends limiting the graphical abstract to the findings specifically in this paper.

Thanks for your great advice. We have revised Figure 7 (originally Figure 6) and restricted the graphical abstract to the findings presented in this paper.

Minor issues:

(8) The order of data in Figure 4 should be consistent with the text in the manuscript. Figures 4E-F-G are described before Figures 4B-C-D in the text. Similarly, Figure 5F was described before Figure 5E in the text.

Thanks for your great advice. We have rearranged the order of the pictures to align with the text. Thank you for your proposal.

(9) In Figure 4A, the locations of the epicardium, muscle, and endocardium should be indicated for clarity. Also, it is not obvious where the close-up box refers to in the actual image.

Thank you for your suggestion. We primarily seek evidence of mitochondrial internalization within the endocardium, as injury occurs first during myocardial ischemia (Kuwada and Takenaka,2000). The close-up box in Fig. 4 refers to the endocardium.

(10) In Figure 5A, the group annotations are missing from the MDA and SOD graphs. The standard deviation bars for the SOD vehicle and SOD mito groups (3rd and 4th columns) appear to overlap. Can the authors provide the actual p-values?

We apologize for the mission of group annotations in the MDA and SOD graphs. The p-value between the Vehicle group and the Mito group was 0.004. The SOD activity level of myocardial samples in the groups are presented in Table 1.

Author response table 1.

The SOD activity levels of myocardial samples in groups (U/mgprot)

(11) In line 58, NS abbreviation is used without defining what NS is.

We apologize for not including the full name of NS. NS is the abbreviation of normal. It has now been marked in the manuscript. (Line 58)

(12) In line 118, what MDA stands for is not described until line 348. MDA should be defined in the text for the general audience.

We apologize for this. We have defined it in the manuscript. (Lines 156~157)

(13) In line 192, the authors state that "mitochondrial transplantation... increased the expression of antioxidant enzymes after four hours of ROSC," while only SOD activity levels were assessed in the manuscript. Increased activity levels do not necessarily imply an increase in expression levels. This discrepancy should be addressed in the Discussion section.

Sorry for confusing the ‘activity’ with ‘expression’. Although mitochondrial transplantation has been shown to be involved in the restoration of manganese superoxide dismutase levels after ischemic insults, the changes in antioxidant enzyme expression level were not evaluated at the protein level in this paper (Tashiro, et al.,2022). To avoid misunderstandings, we have replaced the term ‘expression’ with ‘activity’ as appropriate. (Lines 268~271)

(14) Mitochondria from non-ischemic gastrocnemius muscle of health donor animals were isolated and a manner that maximized their healing potential. This sentence is not clear.

We apologize for the confusing sentence in the original manuscript. To improve clarity, we have revised that sentence. We isolated mitochondria from allogeneic gastrocnemius muscle tissue of healthy rats and maintained optimal mitochondrial activity and therapeutic effects. (Lines 199~201)

Minor grammar issues:

In line 153, mitochondrial should be mitochondria.

Figure 2D: Percent servival should be percent survival.

There should be a blank in complex IIactivity Figure 4B, and complex IV activity in Figure 4C.

In line 134, Four hours of ROSC, Tissue samples from. Tissue is capital.

In line 190, Similaerly should be similarly.

Thank you for your valuable comments. We apologize for the grammatical issues caused by our oversight. We have made the necessary corrections in the manuscript and figures. (Lines 198, 179, and 268), Figure 2D, Figure 5E (originally Figure 4B); Figure 5F (originally Figure 4C).

Reviewer #2 (Recommendations For The Authors):

Some details are lacking clarity, such as the rationale behind choosing certain doses or time points for interventions.

Thank you for this valuable suggestion. We have explained the rationale behind the selection of the dosage and the timing of the intervention. (Lines 201~212)

I would suggest verifying mitochondrial function using the seahorse experiment oxygen consumption, and to check mitochondrial oxidative stress. I would also suggest checking the mitochondrial permeability transition pore opening, using for example calcein cobalt quenching or simply a kit to examine this further.

Thank you for your valuable advice. In our manuscript, we added results regarding mitochondrial reactive oxygen species (ROS) and the mitochondrial permeability transition pore (mPTP) opening. As anticipated, mitochondrial transplantation reduced the increase in mitochondrial ROS and the mPTP opening in ischemic myocardium. (Lines 135~146, 149~157, 442~455, 460~476, Figure 5H, 5I, 6A)

We agree that seahorse experiment oxygen consumption would be beneficial for understanding the intricacies of their interactions and enhancements. Additionally, Ali et al. (Ali, et al.,2020) have demonstrated that introducing non-autologous mitochondria from healthy skeletal muscle cells into normal cardiomyocytes results in a short-term improvement in bioenergetics, as measured using a Seahorse Extracellular Flux Analyzer. In our results, we have not yet conducted cellular experiments, The process of isolating cells from the myocardial tissue of adult SD rats for Seahorse analysis can lead to secondary damage to the myocardial cells (Jacobson, et al.,1985). In this experiment, we measured ATP content and the activity of mitochondrial complexes to evaluate energy changes after mitochondrial transplantation. We will conduct cell experiments and utilize Seahorse measurements to further clarify the alterations in myocardial energy in future.

For Figure 3B, it would be beneficial to include the relative quantification of the mitochondrial marker COX-IV. Additionally, if feasible, I suggest verifying the representation of the mitochondria outer membrane TOM20 or VDAC.

Thank you for your great suggestion. As suggested, we added TOM20 to assess the purity of the isolated mitochondria and reached the same conclusion: the isolated mitochondria exhibited high purity (Figure 3B). TOM20 was expressed in both muscle lysates and isolated mitochondria, whereas GAPDH was exclusively found in the muscle lysate. (We re-validated the purity of the mitochondria by using relative quantification of TOM20 and COX VI.)

In Figure 2C, the clarity of the graphs depicting both arterial pressure (MAP) and heart rate (HR) is lacking and could potentially confuse the reader. I recommend incorporating color coding instead of relying solely on symbols, or by presenting the data in a more comprehensible format and that aligns with graph B as well.

Thank you for your constructive comments. We have color-coded the diagrams in Figure 2B and 2C.

In Figure 4A, please include high-magnification of the mitochondria to provide a more detailed examination.

Thank you for this insightful comment. We have provided a high-magnification image of the mitochondria in Figure 4.

Regarding lines 81-82, I recommend specifying the sentence more precisely for better clarity and understanding.

Thank you for your comments. We have revised the sentences in lines 83~86 to enhance their clarity for readers.

In the Materials and Methods section, it is crucial to provide precise details. For instance, when staining the exogenous mitochondria with MitoTracker Red, it is important to specify the duration of staining, such as the standard 20 minutes for example. Additionally, it is advisable to mention the number of times these mitochondria were washed with the respiratory solution to ensure thorough removal of excess MitoTracker, thus preventing unintended staining of endogenous mitochondria with MitoTracker red upon injection of pre-labeled mitochondria.

Thank you for your suggestion. We have added the necessary details regarding Mito-Tracker Red dyeing. (Lines 373~376) In addition, we also added other details in necessary (Lines 373~376, 379~382, 395~396, 397~400, 487~488). We appreciate your suggestion once again.

The sensitivity of JC-1 dye to temperature and pH fluctuations underscores the necessity for meticulous experimental conditions. It is crucial for the authors to elucidate why they chose to maintain the samples at 4 {degree sign} C for 60 minutes, especially considering the dye's optimal operating temperature of 25 {degree sign} C. Providing a rationale behind this deviation from standard protocol would enhance the scientific rigor and reproducibility of the study. Please add more information on the objectives used in the fluorescence microscope (BX53, OLYMPUS, Tokyo, Japan) and the software used.

We sincerely apologize for the mistake in this sentence. The purified mitochondria, which are stained with JC-1, should be stored at 4°C and examined using a fluorescence microscope within 60 minutes. Purified mitochondria were incubated with JC-1 staining solution at 37°C for 20 minutes. The fluorescence microscope used in our experiment is equipped with a WHN 10/22 eyepiece, and the software version is OLYMPUS cellSens Standard 3.2. (Lines 379~382)

Moreover, in the context of immunoblotting, it is imperative for the authors to furnish detailed information regarding the preparation of muscle tissue homogenates. Specifically, clarification is needed regarding the solution utilized for tissue grinding. Did the authors employ ice-cold RIPA lysis buffer or an alternative lysis buffer, supplemented with a protease inhibitor cocktail? Such details are pivotal for methodological transparency.

Thanks for this wonderful comment. In the methods section, we added detailed information about protein extraction. (Lines 383~385)

Furthermore, it would be beneficial for the authors to specify the instrument employed for scanning the immunoblots, as well as the software utilized for subsequent analysis of the immunoblot images. Providing this information would not only enhance the reproducibility of the findings but also facilitate the evaluation of the experimental results.

Thank you for your suggestion. We have included the instrument used for scanning the Western blot, as well as the software used for image analysis in the manuscript. (Lines 397~400)

Authors must exercise caution against copy-pasting. In line 282, there's a query regarding how the mitochondria were isolated. It is recommended to cite a specific reference and offer more comprehensive details. Despite the authors referencing a number within the text, the absence of numbered references makes it challenging to cross-reference.

Thank you for pointing this out; we have updated the citation accordingly (Line 361).

Figure 5C please double check some misspelling label errors (e.g: Vehicle and not Vehucle).

We apologize for the misspelling in Figure 6E (originally Figure 5C) and have corrected it. Additionally, we have thoroughly reviewed the text for spelling errors and sincerely apologize once again for the previous mistakes. (Lines 249~252, 322)

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eLife Assessment

These useful findings assigned a novel functional implication of histone acylation, crotonylation. Although the mechanistic insights have been provided in great detail regarding the role of the YEATS2-GCDH axis in modulating EMT in HNC, the strength of evidence for the manuscript is incomplete. The patient cohort is very small, with just 10 patients; to establish a significant result the cohort size should be increased. Furthermore, the functional implication of p300 is also to be looked into.

Reviewer #1 (Public review):

Summary:

This manuscript investigates a mechanism between the histone reader protein YEATS2 and the metabolic enzyme GCDH, particularly in regulating epithelial-to-mesenchymal transition (EMT) in head and neck cancer (HNC).

Strengths:

Great detailing of the mechanistic aspect of the above axis is the primary strength of the manuscript.

Weaknesses:

Several critical points require clarification, including the rationale behind EMT marker selection, the inclusion of metastasis data, the role of key metabolic enzymes like ECHS1, and the molecular mechanisms governing p300 and YEATS2 interactions.

Major Comments:

(1) The title, "Interplay of YEATS2 and GCDH mediates histone crotonylation and drives EMT in head and neck cancer," appears somewhat misleading, as it implies that YEATS2 directly drives histone crotonylation. However, YEATS2 functions as a reader of histone crotonylation rather than a writer or mediator of this modification. It cannot itself mediate the addition of crotonyl groups onto histones. Instead, the enzyme GCDH is the one responsible for generating crotonyl-CoA, which enables histone crotonylation. Therefore, while YEATS2 plays a role in recognizing crotonylation marks and may regulate gene expression through this mechanism, it does not directly catalyse or promote the crotonylation process.

(2) The study suggests a link between YEATS2 and metastasis due to its role in EMT, but the lack of clinical or pre-clinical evidence of metastasis is concerning. Only primary tumor (PT) data is shown, but if the hypothesis is that YEATS2 promotes metastasis via EMT, then evidence from metastatic samples or in vivo models should be included to solidify this claim.

(3) There seems to be some discrepancy in the invasion data with BICR10 control cells (Figure 2C). BICR10 control cells with mock plasmids, specifically shControl and pEGFP-C3 show an unclear distinction between invasion capacities. Normally, we would expect the control cells to invade somewhat similarly, in terms of area covered, within the same time interval (24 hours here). But we clearly see more control cells invading when the invasion is done with KD and fewer control cells invading when the invasion is done with OE. Are these just plasmid-specific significant effects on normal cell invasion? This needs to be addressed.

(4) In Figure 3G, the Western blot shows an unclear band for YEATS2 in shSP1 cells with YEATS2 overexpression condition. The authors need to clearly identify which band corresponds to YEATS2 in this case.

(5) In ChIP assays with SP1, YEATS2 and p300 which promoter regions were selected for the respective genes? Please provide data for all the different promoter regions that must have been analysed, highlighting the region where enrichment/depletion was observed. Including data from negative control regions would improve the validity of the results.

(6) The authors establish a link between H3K27Cr marks and GCDH expression, and this is an already well-known pathway. A critical missing piece is the level of ECSH1 in patient samples. This will clearly delineate if the balance shifted towards crotonylation.

(7) The p300 ChIP data on the SPARC promoter is confusing. The authors report reduced p300 occupancy in YEATS2-silenced cells, on SPARC promoter. However, this is paradoxical, as p300 is a writer, a histone acetyltransferase (HAT). The absence of a reader (YEATS2) shouldn't affect the writer (p300) unless a complex relationship between p300 and YEATS2 is present. The role of p300 should be further clarified in this case. Additionally, transcriptional regulation of SPARC expression in YEATS2 silenced cells could be analysed via downstream events, like Pol-II recruitment. Assays such as Pol-II ChIP-qPCR could help explain this.

(8) The role of GCDH in producing crotonyl-CoA is already well-established in the literature. The authors' hypothesis that GCDH is essential for crotonyl-CoA production has been proven, and it's unclear why this is presented as a novel finding. It has been shown that YEATS2 KD leads to reduced H3K27cr, however, it remains unclear how the reader is affecting crotonylation levels. Are GCDH levels also reduced in the YEATS2 KD condition? Are YEATS2 levels regulating GCDH expression? One possible mechanism is YEATS2 occupancy on GCDH promoter and therefore reduced GCDH levels upon YEATS2 KD. This aspect is crucial to the study's proposed mechanism but is not addressed thoroughly.

(9) The authors should provide IHC analysis of YEATS2, SPARC alongside H3K27cr and GCDH staining in normal vs. tumor tissues from HNC patients.

Reviewer #2 (Public review):

Summary:

The manuscript emphasises the increased invasive potential of histone reader YEATS2 in an SP1-dependent manner. They report that YEATS2 maintains high H3K27cr levels at the promoter of EMT-promoting gene SPARC. These findings assigned a novel functional implication of histone acylation, crotonylation.

Concerns:

(1) The patient cohort is very small with just 10 patients. To establish a significant result the cohort size should be increased.

(2) Figure 4D compares H3K27Cr levels in tumor and normal tissue samples. Figure 1G shows overexpression of YEATS2 in a tumor as compared to normal samples. The loading control is missing in both. Loading control is essential to eliminate any disparity in protein concentration that is loaded.

(3) Figure 4D only mentions 5 patient samples checked for the increased levels of crotonylation and hence forms the basis of their hypothesis (increased crotonylation in a tumor as compared to normal). The sample size should be more and patient details should be mentioned.

(4) YEATS2 maintains H3K27Cr levels at the SPARC promoter. The p300 is reported to be hyper-activated (hyperautoacetylated) in oral cancer. Probably, the activated p300 causes hyper-crotonylation, and other protein factors cause the functional translation of this modification. The authors need to clarify this with a suitable experiment.

(5) I do not entirely agree with using GAPDH as a control in the western blot experiment since GAPDH has been reported to be overexpressed in oral cancer.

(6) The expression of EMT markers has been checked in shControl and shYEATS2 transfected cell lines (Figure 2A). However, their expression should first be checked directly in the patients' normal vs. tumor samples.

(7) In Figure 3G, knockdown of SP1 led to the reduced expression of YEATS2 controlled gene Twist1. Ectopic expression of YEATS2 was able to rescue Twist1 partially. In order to establish that SP1 directly regulates YEATS2, SP1 should also be re-introduced upon the knockdown background along with YEATS2 for complete rescue of Twist1 expression.

(8) In Figure 7G, the expression of EMT genes should also be checked upon rescue of SPARC expression.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

This manuscript investigates a mechanism between the histone reader protein YEATS2 and the metabolic enzyme GCDH, particularly in regulating epithelial-to-mesenchymal transition (EMT) in head and neck cancer (HNC).

Strengths:

Great detailing of the mechanistic aspect of the above axis is the primary strength of the manuscript.

Weaknesses:

Several critical points require clarification, including the rationale behind EMT marker selection, the inclusion of metastasis data, the role of key metabolic enzymes like ECHS1, and the molecular mechanisms governing p300 and YEATS2 interactions.

We would like to sincerely thank the reviewer for the detailed, in-depth, and positive response. We are committed to implementing constructive revisions to the manuscript to address the reviewer’s concerns effectively.

Major Comments:

(1) The title, "Interplay of YEATS2 and GCDH mediates histone crotonylation and drives EMT in head and neck cancer," appears somewhat misleading, as it implies that YEATS2 directly drives histone crotonylation. However, YEATS2 functions as a reader of histone crotonylation rather than a writer or mediator of this modification. It cannot itself mediate the addition of crotonyl groups onto histones. Instead, the enzyme GCDH is the one responsible for generating crotonyl-CoA, which enables histone crotonylation. Therefore, while YEATS2 plays a role in recognizing crotonylation marks and may regulate gene expression through this mechanism, it does not directly catalyse or promote the crotonylation process.

We thank the reviewer for raising this concern. As stated by the reviewer, YEATS2 functions as a reader protein, capable of recognizing histone crotonylation marks and assisting in the addition of this mark to nearby histone residues, possibly by assisting the recruitment of the writer protein for crotonylation. Our data indicates the involvement of YEATS2 in the recruitment of writer protein p300 on the promoter of the SPARC gene, making YEATS2 a regulatory factor responsible for the addition of crotonyl marks in an indirect manner. Thus, we have decided to make changes in the title by replacing the word “mediates” with “regulates”. Therefore, the updated title can be read as: “Interplay of YEATS2 and GCDH regulates histone crotonylation and drives EMT in head and neck cancer”.

(2) The study suggests a link between YEATS2 and metastasis due to its role in EMT, but the lack of clinical or pre-clinical evidence of metastasis is concerning. Only primary tumor (PT) data is shown, but if the hypothesis is that YEATS2 promotes metastasis via EMT, then evidence from metastatic samples or in vivo models should be included to solidify this claim.

We appreciate the reviewer’s suggestion. Here, we would like to state that the primary aim of this study was to delineate the molecular mechanisms behind the role of YEATS2 in maintaining histone crotonylation at the promoter of genes that favour EMT in head and neck cancer. We have dissected the importance of histone crotonylation in the regulation of gene expression in head and neck cancer in great detail, having investigated the upstream and downstream molecular players involved in this process that promote EMT. Moreover, with the help of multiple phenotypic assays, such as Matrigel invasion, wound healing, and 3D invasion assays, we have shown the functional importance of YEATS2 in promoting EMT in head and neck cancer cells. Since EMT is known to be a prerequisite process for cancer cells undergoing metastasis(1), the evidence of YEATS2 being associated with EMT demonstrates a potential correlation of YEATS2 with metastasis. However, as part of the revision, we will use publicly available patient data to investigate the direct association of YEATS2 with metastasis by checking the expression of YEATS2 between different grades of head and neck cancer, as an increase in tumor grade is often correlated with the incidence of metastasis(2).

(3) There seems to be some discrepancy in the invasion data with BICR10 control cells (Figure 2C). BICR10 control cells with mock plasmids, specifically shControl and pEGFP-C3 show an unclear distinction between invasion capacities. Normally, we would expect the control cells to invade somewhat similarly, in terms of area covered, within the same time interval (24 hours here). But we clearly see more control cells invading when the invasion is done with KD and fewer control cells invading when the invasion is done with OE. Are these just plasmid-specific significant effects on normal cell invasion? This needs to be addressed.

We appreciate the reviewer for the thorough evaluation of the manuscript. The figure panels in question, Figure 2B and 2C, represent two different experiments performed independently, the invasion assay performed after knockdown and overexpression of YEATS2, respectively. We would like to clarify that both panels represent results that are distinct and independent of each other and that the method used to knockdown or overexpress YEATS2 is also different. As stated in the Materials and Methods section, the knockdown is performed using lentivirus-mediated transfection (transduction) of cells, on the other hand, the overexpression is done using standard method of transfection by directly mixing transfection reagent and the respective plasmids, prior to the addition of this mix to the cells. The difference in the experimental conditions in these two experiments might have attributed to the differences seen in the controls as observed previously(3). Hence, we would like to state that the results of figure panels Figure 2B and Figure 2C should be evaluated independently of each other.

(4) In Figure 3G, the Western blot shows an unclear band for YEATS2 in shSP1 cells with YEATS2 overexpression condition. The authors need to clearly identify which band corresponds to YEATS2 in this case.

The two bands seen in the shSP1+pEGFP-C3-YEATS2 condition correspond to the endogenous YEATS2 band (lower band, indicated by * in the shControl lane) and YEATS2-GFP band (upper band, corresponding to overexpressed YEATS2-GFP fusion protein, which has a higher molecular weight). To avoid confusion, the endogenous band will be highlighted (marked by *) in the lane representing the shSP1+pEGFP-C3-YEATS2 condition in the revised version of the manuscript.

(5) In ChIP assays with SP1, YEATS2 and p300 which promoter regions were selected for the respective genes? Please provide data for all the different promoter regions that must have been analysed, highlighting the region where enrichment/depletion was observed. Including data from negative control regions would improve the validity of the results.

Throughout our study, we have performed ChIP-qPCR assays to check the binding of SP1 on YEATS2 and GCDH promoter, and to check YEATS2 and p300 binding on SPARC promoter. Using transcription factor binding prediction tools and luciferase assays, we selected multiple sites on the YEATS2 and GCDH promoter to check for SP1 binding. The results corresponding to the site that showed significant enrichment were provided in the manuscript. The region of SPARC promoter in YEATS2 and p300 ChIP assay was selected on the basis of YEATS2 enrichment found in the YEATS2 ChIP-seq data. We will provide data for all the promoter regions investigated (including negative controls) in the revised version of the manuscript.

(6) The authors establish a link between H3K27Cr marks and GCDH expression, and this is an already well-known pathway. A critical missing piece is the level of ECSH1 in patient samples. This will clearly delineate if the balance shifted towards crotonylation.

We thank the reviewer for their valuable suggestion. To support our claim, we had checked the expression of GCDH and ECHS1 in TCGA HNC RNA-seq data (provided in Figure 4—figure supplement 1A and B) and found that GCDH showed increase while ECHS1 showed decrease in tumor as compared to normal samples. We hypothesized that higher GCDH expression and decreased ECHS1 expression might lead to an increase in the levels of crotonylation in HNC. To further substantiate our claim, we will check the abundance of ECHS1 in HNC patient samples as part of the revision.

(7) The p300 ChIP data on the SPARC promoter is confusing. The authors report reduced p300 occupancy in YEATS2-silenced cells, on SPARC promoter. However, this is paradoxical, as p300 is a writer, a histone acetyltransferase (HAT). The absence of a reader (YEATS2) shouldn't affect the writer (p300) unless a complex relationship between p300 and YEATS2 is present. The role of p300 should be further clarified in this case. Additionally, transcriptional regulation of SPARC expression in YEATS2 silenced cells could be analysed via downstream events, like Pol-II recruitment. Assays such as Pol-II ChIP-qPCR could help explain this.

Using RNA-seq and ChIP-seq analyses, we have shown that YEATS2 affects the expression of several genes by regulating the level of histone crotonylation at gene promoters globally. The histone writer p300 is a promiscuous acyltransferase protein that has been shown to be involved in the addition of several non-acetyl marks on histone residues, including crotonylation(4). Our data provides evidence for the dependency of the writer p300 on YEATS2 in mediating histone crotonylation, as YEATS2 downregulation led to decreased occupancy of p300 on the SPARC promoter (Figure 5F). However, the exact mechanism of cooperativity between YEATS2 and p300 in maintaining histone crotonylation remains to be investigated. To address the reviewer’s concern, we will perform various experiments to delineate the molecular mechanism pertaining to the association of YEATS2 with p300 in regulating histone crotonylation. Following are the experiments that will be performed:

(a) Co-immunoprecipitation experiments to check the physical interaction between YEATS2 and p300.

(b) We will check H3K27cr levels on the SPARC promoter and SPARC expression in p300-depleted HNC cells.

(c) Rescue experiments to check if the decrease in p300 occupancy on the SPARC promoter can be compensated by overexpressing YEATS2.

(d) As suggested by the reviewer, Pol-II ChIP-qPCR at the promoter of SPARC will be performed in YEATS2-silenced cells to explain the mode of transcriptional regulation of SPARC expression by YEATS2.

(8) The role of GCDH in producing crotonyl-CoA is already well-established in the literature. The authors' hypothesis that GCDH is essential for crotonyl-CoA production has been proven, and it's unclear why this is presented as a novel finding. It has been shown that YEATS2 KD leads to reduced H3K27cr, however, it remains unclear how the reader is affecting crotonylation levels. Are GCDH levels also reduced in the YEATS2 KD condition? Are YEATS2 levels regulating GCDH expression? One possible mechanism is YEATS2 occupancy on GCDH promoter and therefore reduced GCDH levels upon YEATS2 KD. This aspect is crucial to the study's proposed mechanism but is not addressed thoroughly.

The source for histone crotonylation, crotonyl-CoA, can be produced by several enzymes in the cell, such as ACSS2, GCDH, ACOX3, etc(5). Since metabolic intermediates produced during several cellular pathways in the cell can act as substrates for epigenetic factors, we wanted to investigate if such an epigenetic-metabolism crosstalk existed in the context of YEATS2. As described in the manuscript, we performed GSEA using publicly available TCGA RNA-seq data and found that patients with higher YEATS2 expression also showed a high correlation with expression levels of genes involved in the lysine degradation pathway, including GCDH. Since the preferential binding of YEATS2 with H3K27cr and the role of GCDH in producing crotonyl-CoA was known(6,7), we hypothesized that higher H3K27cr in HNC could be a result of both YEATS2 and GCDH. We found that the presence of GCDH in the nucleus of HNC cells is correlated to higher H3K27cr abundance, which could be a result of excess levels of crotonyl-CoA produced via GCDH. We also found a correlation between H3K27cr levels and YEATS2 expression, which could arise due to YEATS2-mediated preferential maintenance of crotonylation. This states that although being a reader protein, YEATS2 is affecting the promoter H3K27cr levels, possibly by helping in the recruitment of p300 (as shown in Figure 5F). Thus, YEATS2 and GCDH are both responsible for the regulation of histone crotonylation-mediated gene expression in HNC.

We did not find any evidence of YEATS2 regulating the expression of GCDH in HNC cells. However, we found that YEATS2 downregulation reduced the nuclear pool of GCDH in head and neck cancer cells (Figure 7F). This suggests that YEATS2 not only regulates histone crotonylation by affecting promoter H3K27cr levels (with p300), but also by affecting the nuclear localization of crotonyl-CoA producing GCDH. Also, we observed that the expression of YEATS2 and GCDH are regulated by the same transcription factor SP1 in HNC. We found that the transcription factor SP1 binds to the promoter of both genes, and its downregulation led to a decrease in their expression (Figure 3 and Figure 7).

We would like to state that the relationship between YEATS2 and the nuclear localization of GCDH, as well as the underlying molecular mechanism, remains unexplored and presents an open question for future investigation.

(9) The authors should provide IHC analysis of YEATS2, SPARC alongside H3K27cr and GCDH staining in normal vs. tumor tissues from HNC patients.

We thank the reviewer for their suggestion. We are consulting our clinical collaborators to assess the feasibility of including this IHC analysis in our revision and will make every effort to incorporate it.

Reviewer #2 (Public review):

Summary:

The manuscript emphasises the increased invasive potential of histone reader YEATS2 in an SP1-dependent manner. They report that YEATS2 maintains high H3K27cr levels at the promoter of EMT-promoting gene SPARC. These findings assigned a novel functional implication of histone acylation, crotonylation.

We thank the reviewer for the constructive comments. We are committed to making beneficial changes to the manuscript in order to alleviate the reviewer’s concerns.

Concerns:

(1) The patient cohort is very small with just 10 patients. To establish a significant result the cohort size should be increased.

We thank the reviewer for this suggestion. We will increase the number of patient samples to assess the levels of YEATS2 and H3K27cr in normal vs. tumor samples.

(2) Figure 4D compares H3K27Cr levels in tumor and normal tissue samples. Figure 1G shows overexpression of YEATS2 in a tumor as compared to normal samples. The loading control is missing in both. Loading control is essential to eliminate any disparity in protein concentration that is loaded.

In Figures 1G and 4D, we have used Ponceau S staining as a control for equal loading. Ponceau S staining is frequently used as an alternative for housekeeping genes like GAPDH as a control for protein loading(8). It avoids the potential for variability in housekeeping gene expression. However, it may be less quantitative than using housekeeping proteins. To address the reviewer’s concern, we will probe with an antibody against a house keeping gene as a loading control in the revised figures, provided its expression remains stable across the conditions tested.

(3) Figure 4D only mentions 5 patient samples checked for the increased levels of crotonylation and hence forms the basis of their hypothesis (increased crotonylation in a tumor as compared to normal). The sample size should be more and patient details should be mentioned.

A total of 9 samples were checked for H3K27cr levels (5 of them are included in Figure 4D and rest included in Figure 4—figure supplement 1D). However, as a part of the revision, we will check the H3K27cr levels in more patient samples.

(4) YEATS2 maintains H3K27Cr levels at the SPARC promoter. The p300 is reported to be hyper-activated (hyperautoacetylated) in oral cancer. Probably, the activated p300 causes hyper-crotonylation, and other protein factors cause the functional translation of this modification. The authors need to clarify this with a suitable experiment.

In our study, we have shown that p300 is dependent on YEATS2 for its recruitment on the SPARC promoter. As a part of the revision, we propose the following experiments to further substantiate the role of p300 in YEATS2-mediated gene regulation:

(a) Co-immunoprecipitation experiments to check the physical interaction between YEATS2 and p300.

(b) We will check H3K27cr levels on the SPARC promoter and SPARC expression in p300-depleted HNC cells.

(c) Rescue experiments to check if the decrease in p300 occupancy on the SPARC promoter can be compensated by overexpressing YEATS2.

(d) Pol-II ChIP-qPCR at the promoter of SPARC will be performed in YEATS2-silenced cells to explain the mode of transcriptional regulation of SPARC expression by YEATS2.

(5) I do not entirely agree with using GAPDH as a control in the western blot experiment since GAPDH has been reported to be overexpressed in oral cancer.

We would like to clarify that GAPDH was not used as a loading control for protein expression comparisons between normal and tumor samples. GAPDH was used as a loading control only in experiments using head and neck cancer cell lines where shRNA-mediated knockdown or overexpression was employed. These manipulations specifically target the genes of interest and are not expected to alter GAPDH expression, making it a suitable loading control in these instances.

(6) The expression of EMT markers has been checked in shControl and shYEATS2 transfected cell lines (Figure 2A). However, their expression should first be checked directly in the patients' normal vs. tumor samples.

We thank the reviewer for the suggestion. To address this, we will check the expression of EMT markers alongside YEATS2 expression in normal vs. tumor samples.

(7) In Figure 3G, knockdown of SP1 led to the reduced expression of YEATS2 controlled gene Twist1. Ectopic expression of YEATS2 was able to rescue Twist1 partially. In order to establish that SP1 directly regulates YEATS2, SP1 should also be re-introduced upon the knockdown background along with YEATS2 for complete rescue of Twist1 expression.

To address the reviewer’s concern regarding the partial rescue of Twist1 in SP1 depleted-YEATS2 overexpressed cells, we will perform the experiment as suggested by the reviewer. In brief, we will overexpress both SP1 and YEATS2 in SP1-depleted cells and then assess the expression of Twist1.

(8) In Figure 7G, the expression of EMT genes should also be checked upon rescue of SPARC expression.

We thank the reviewer for the suggestion. We will check the expression of EMT markers on YEATS2/ GCDH rescue and update Figure 7G in the revised version of the manuscript.

References

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(2) P. Pisani, M. Airoldi, A. Allais, P. Aluffi Valletti, M. Battista, M. Benazzo, R. Briatore, S. Cacciola, S. Cocuzza, A. Colombo, B. Conti, A. Costanzo, L. Della Vecchia, N. Denaro, C. Fantozzi, D. Galizia, M. Garzaro, I. Genta, G. A. Iasi, M. Krengli, V. Landolfo, G. V. Lanza, M. Magnano, M. Mancuso, R. Maroldi, L. Masini, M. C. Merlano, M. Piemonte, S. Pisani, A. Prina-Mello, L. Prioglio, M. G. Rugiu, F. Scasso, A. Serra, G. Valente, M. Zannetti and A. Zigliani, Acta Otorhinolaryngol Ital, 2020, 40, S1–S86.

(3) J. Lin, P. Zhang, W. Liu, G. Liu, J. Zhang, M. Yan, Y. Duan and N. Yang, Elife, 2023, 12, RP87510.

(4) X. Liu, W. Wei, Y. Liu, X. Yang, J. Wu, Y. Zhang, Q. Zhang, T. Shi, J. X. Du, Y. Zhao, M. Lei, J.-Q. Zhou, J. Li and J. Wong, Cell Discov, 2017, 3, 17016.

(5) G. Jiang, C. Li, M. Lu, K. Lu and H. Li, Cell Death Dis, 2021, 12, 703.

(6) D. Zhao, H. Guan, S. Zhao, W. Mi, H. Wen, Y. Li, Y. Zhao, C. D. Allis, X. Shi and H. Li, Cell Res, 2016, 26, 629–632.

(7) H. Yuan, X. Wu, Q. Wu, A. Chatoff, E. Megill, J. Gao, T. Huang, T. Duan, K. Yang, C. Jin, F. Yuan, S. Wang, L. Zhao, P. O. Zinn, K. G. Abdullah, Y. Zhao, N. W. Snyder and J. N. Rich, Nature, 2023, 617, 818–826.

(8) I. Romero-Calvo, B. Ocón, P. Martínez-Moya, M. D. Suárez, A. Zarzuelo, O. Martínez-Augustin and F. S. de Medina, Anal Biochem, 2010, 401, 318–320.

eLife Assessment

In this important study, the authors advance our understanding of copper uptake by chalkophores and their targeted metalloproteins in Mycobacterium tuberculosis. These convincing data demonstrate that chalkophore-acquired copper is solely incorporated into the Mtb bcc:aa3 copper-iron respiratory oxidase under low copper conditions, and that chalkophore-mediated protection of the respiratory chain is critical to Mtb virulence. These findings may be leveraged for drug discovery and will be of broad interest to those studying bacterial pathogenesis.

Reviewer #1 (Public review):

Summary:

It is essential for Mycobacterium tuberculosis (Mtb) to scavenge trace metals from its host to survive. In this study, the authors explore the effects of copper limitation on Mtb. Mtb synthesizes small molecular diisonitrile lipopeptides termed chalkophores, that chelate host copper for import, whereby the copper is incorporated into Mtb metalloproteins. However, the role of chalkophores in Mtb biology and their targeted metalloproteins are unknown. This study investigates Mtb proteins that require chalkophores for copper incorporation and their effect on Mtb virulence. It is known that the nrp operon is induced by copper deprivation and encodes the synthesis of chalkophores. A genetic analysis revealed transcriptional differences for WT and Mtb∆nrp when exposed to the copper chelator tetrathiomolybdate (TTM). The authors found that copper chelation results in upregulation of genes in the chalkophore cluster as well as genes involved in the respiratory chain: specifically, components of the heme-dependent oxidase CytBD and subunits of the bcc:aa3 heme-copper oxidase. Interestingly, treatment of Mtb∆nrp with an inhibitor of the QcrB subunit of the bcc:aa3 oxidase (Q203) resulted in similar transcriptional changes. The bcc:aa3 oxidase and CytBD are functionally redundant, and while both utilize heme as a cofactor, only the first utilizes heme and copper. Utilizing Mtb∆nrp, Mtb∆cydAB and MtbΔnrpΔcydAB along with single gene complementation, the authors showed that copper starvation survival requires diisonitrile chalkophore synthesis and that copper starvation results in dysfunctional bcc:aa3 oxidase. Further genetic analysis combined with inhibitor studies indicate that bcc:aa3 oxidase is the only target impacted by copper starvation. By monitoring oxygen consumption for mutants in combination with inhibitors, the authors show that copper deprivation inhibits respiration through the bcc:aa3 oxidase. Similarly, they show that TTM or Q203 treatment inhibits ATP production in MtbΔnrpΔcydAB, but not in WT, showing that chalkophores maintain oxidative phosphorylation. Lastly, the authors compare the virulence of WT Mtb, Mtb∆nrp and MtbΔnrpΔcydAB strains in mice spleen and lung. The Mtb∆nrp strain showed mild attenuation, but virulence in MtbΔnrpΔcydAB was severely attenuated, and complementation with the chalkophore biosynthetic pathway restored Mtb virulence. These results suggest that chalkophore mediated protection of the respiratory chain is critical to Mtb virulence, and the that redundant respiratory oxidases within Mtb provides respiratory chain flexibility that may promote host adaptation.

Strengths:

Overall, the paper is very clear and well-written, with thorough and well-thought-out experimentation.

The methods are all quite standard, so there are no weaknesses identified with regard to methodology.

Reviewer #2 (Public review):

Summary:

This is a well-written manuscript that clearly demonstrates that the nrp encoded diisonitrile chalkophore is necessary for the function of the bcc-aa3 oxidase supercomplex under low copper conditions. In addition, the study demonstrates that the chlakophore is important early during infection when copper sequestration is employed by the host as a method of nutritional immunity.

Strengths:

The authors use genetic approaches including single and double mutants of chalkophore biosynthesis, and both the Mtb oxidases. They use copper chelators to restrict copper in vitro. A strength of the work was the use of a synthesized a Mtb chalkophore analogue to show chemical complementation of the mutant nrp locus. Oxphos metabolic activity was measuered by oxygen consumption and ATP levels. Importantly, the study demonstrated that chalkophore, especially in a strain lacking the secondary oxidase, was necessary for early infection and ruled out a role for adaptive immunity in the chalkophore lacking Mtb by use of SCID mice. It is interesting that after two weeks of infection and onset of adaptive immunity, the chalkophore is not required, which is consistent with the host environment switching from a copper-restricted to copper overload in phagosomes.

Weaknesses:

Most claims in the manuscript are soundly justified. The one exception is the claim that "maintenance of respiration is the only cellular target of chalkophore mediated copper acquisition." While under the in vitro conditions tested this does appear to be the case; however, it can't be ruled out that the chalkophore is important in other situations. In particular, for maintenance of the periplasmic superoxide dismustase, SodC, which is the other M. tuberculosis enzyme known to require copper.

Reviewer #3 (Public review):

Summary:

In this manuscript, the group of Glickman expands on their previous studies on the function of chalkophores during the growth of and infection by Mycobacterium tuberculosis. Previously, the group had shown that chalkophores, which are metallophores specific for the scavenging of copper, are induced by M. tuberculosis under copper deprivation conditions. Here, they show that chalkophores, under copper limiting conditions, are essential for the uptake of copper and maturation of a terminal oxidase, the heme-copper oxidase, cytochrome bcc:aa3. As M. tuberculosis has two redundant terminal oxidases, growth of and infection by M. tuberculosis is only moderated if both the chalkophores and the second terminal oxidase, cytochrome bd, are inhibited.

Strengths:

A strength of this work is that the lab-culture experiments are expanded upon with mice infection models, providing strong indications that host-inflicted copper deprivation is a condition that M. tuberculosis has adapted to for virulence.

Weaknesses:

Because the phenotype of M. tuberculosis lacking chalkophores is similar, if not identical, to using Q203, an inhibitor of cytochrome bcc:aa3, the authors propose that the copper-containing cytochrome bcc:aa3 is the only recipient of copper-uptake by chalkophores. A minor weakness of the work is that this latter conclusion is not verified under infection conditions and other copper-enzymes might still be functionally required during one or more stages of infection.

Author response:

We thank the reviewers for their careful evaluation of our manuscript and appreciate the suggestions for improvement. We will outline our planned revisions in response to these reviews.

Reviewer 2:

“The one exception is the claim that "maintenance of respiration is the only cellular target of chalkophore mediated copper acquisition." While under the in vitro conditions tested this does appear to be the case; however, it can't be ruled out that the chalkophore is important in other situations. In particular, for maintenance of the periplasmic superoxide dismutase, SodC, which is the other M. tuberculosis enzyme known to require copper.”

And

Reviewer 3:

“Because the phenotype of M. tuberculosis lacking chalkophores is similar, if not identical, to using Q203, an inhibitor of cytochrome bcc:aa3, the authors propose that the copper-containing cytochrome bcc:aa3 is the only recipient of copper-uptake by chalkophores. A minor weakness of the work is that this latter conclusion is not verified under infection conditions and other copper-enzymes might still be functionally required during one or more stages of infection.

Both comments concern the question of whether the bcc:aa3 respiratory oxidase supercomplex is the only target of chalkophore delivered copper. In culture, our experiments suggest that bcc:aa3 is the only target. The evidence for this claim is in Figure 2E and F. In 2E, we show that M. tuberculosis DctaD (a subunit of bcc:aa3) is growth impaired, copper chelation with TTM does not exacerbate that growth defect, and that a DctaDDnrp double mutant is no more sensitive to TTM than DctaD. These data indicate that role of the chalkophore in protecting against copper deprivation is absent when the bcc:aa3 oxidase is missing. Similar results were obtained with Q203 (Figure 2F). Q203 or TTM arrest growth of M. tuberculosis Dnrp, but the combination has no additional effect, indicating that when Q203 is inhibiting the bcc:aa3 oxidase, the chalkophore has no additional role. However, we agree with the reviewers that we cannot exclude the possibility that during infection, there is an additional target of chalkophore mediated Cu acquisition. We will add this caveat to the revised version of this manuscript.

eLife Assessment

This manuscript reports fundamental discoveries on how necrotic cells contribute to organ regeneration through apoptotic signalling to produce cells with non-lethal apoptotic caspase activity that contribute to the regenerated tissue. These findings will be of broad interest to those who study wound repair and tissue regeneration. The strength of the evidence is solid and has been improved in the revised version.

Reviewer #2 (Public review):

In this revised manuscript, Klemm et al., build on top of past published findings (Klemm et al., 2021) to characterize caspase activation in distal cells following necrotic tissue damage within the Drosophila wing imaginal disc. Previously in Klemm et al., 2021, the authors describe necrosis-induced-apoptosis (NiA) following the development of a genetic system to study necrosis that is caused by the expression of a constitutive active GluR1 (Glutamate/Ca2+ channel), and they discovered that the appearance of NiA cells were important for promoting regeneration.

In this manuscript, the authors investigate how tissues regenerate following necrotic cell death. They find that:

(1) the cells of the wing pouch are more likely to have non-autonomous caspase activation than other regions within the wing imaginal disc (hinge and notum),

(2) two signaling pathways that are known to be upregulated during regeneration, Wnt (wingless) and JAK/Stat signaling, act to prevent additional NiA in pouch cells, and may partially explain the region specificity,

(3) the presence of NiA (and/or NiCP) cells promotes regenerative proliferation in the late stages of regeneration,

(4) not all caspase-positive cells are cleared from the epithelium (these cells are then referred to as Necrosis-induced Caspase Positive (NiCP) cells), these NiCP cells continue to live and promote proliferation in adjacent cells,

(5) the initiator caspase Dronc is important for creating NiA/NiCP cells and for these cells to promote proliferation. Animals heterozygous for a Dronc null allele show a decrease in regeneration following necrotic tissue damage. In the revised manuscript, the authors provide improvements through additional data quantifications and text changes to better explain NiA/NiCP lineage tracing methods.

The study has the potential to be broadly interesting due to the insights into how tissues differentially respond to necrosis as compared to apoptosis to promote regeneration. The paper raises many interesting questions for future investigation, including what is the nature of the signaling between the damaged tissue and the NiA/NiCP responsive areas (such as the identity of the DAMPs)? What determines if these cells at a distance undergo apoptosis or remain viable in the tissue as caspase-positive cells? And since the authors have data that indicates that the phenomenon is distinct from 'undead cells', what are the mechanisms by which these cells promote local proliferation?

Reviewer #3 (Public review):

The manuscript "Regeneration following tissue necrosis is mediated by non-apoptotic caspase activity" by Klemm et al. is an exploration of what happens to a group of cells that experience caspase activation after necrosis occurs some distance away from the cells of interest. These experiments have been conducted in the Drosophila wing imaginal disc, which has been used extensively to study the response of a developing epithelium to damage and stress. The authors revise and refine their earlier discovery of apoptosis initiated by necrosis, here showing that many of those presumed apoptotic cells do not complete apoptosis. Thus, the most interesting aspect of the paper is the characterization of a group of cells that experience mild caspase activation in response to an unknown signal, followed by some effector caspase activation and DNA damage, but that then recover from the DNA damage, avoid apoptosis, and proliferate instead.

The authors have addressed the concerns raised, including those about drawing conclusions from RNAi knockdown without evaluating the efficacy of the knockdown, and in doing so they revised their conclusions after ascertaining that the Zfh2 RNAi was not effective.

The authors have added quantification of the imaging data throughout, which strengthens their conclusions.

In addition, the authors have revised some of the text describing the changes in EdU signal and added explanations of reagents such as the caspase sensors to clarify the experimental approaches, results, and interpretation of those results.

The authors have also addressed the minor concerns and questions about the figures and text.

A few questions remain, which the authors may choose to address.

(1) The hh>Stat92ERNAi was assessed by the 10xSTAT-GFP reporter, as shown in Fig 2 Supp1 F. The authors point out the marked reduction in GFP in the ventral part of the hinge but do not comment on the lack of change in GFP in the dorsal part of the hinge. However, the open arrowhead in Figure 2H indicating the lack of cDcp-1 signal in the hinge in the same experiment points to the dorsal hinge, where the reporter suggests no difference in JAK-STAT signaling.

(2) The data used to conclude that DRONC-DN and UAS-DIAP1 do not affect regenerative proliferation were normalized EdU intensities. As discussed in the prior review round, normalized EdU may not be a good comparison across experimental conditions given that the remainder of the disc may also have altered EdU incorporation, so this measurement may not be enough by itself to draw conclusions about regenerative proliferation. To strengthen the conclusion that regenerative proliferation is unaffected under these conditions, the authors may want to consider using a second measure such as adult wing size, PCNA, or quantitate mitoses via anti-phospho histone H3 staining.

Author response:

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

Reviewer #1 (Public Review):

Summary:

In previous work, the authors described necrosis-induced apoptosis (NiA) as a consequence of induced necrosis. Specifically, experimentally induced necrosis in the distal pouch of larval wing imaginal discs triggers NiA in the lateral pouch. In this manuscript, the authors confirmed this observation and found that while necrosis can kill all areas of the disc, NiA is limited to the pouch and to some extent to the notum, but is excluded from the hinge region. Interestingly and unexpectedly, signaling by the Jak/Stat and Wg pathways inhibits NiA. Further characterization of NiA by the authors reveals that NiA also triggers regenerative proliferation which can last up to 64 hours following necrosis induction. This regenerative response to necrosis is significantly stronger compared to discs ablated by apoptosis. Furthermore, the regenerative proliferation induced by necrosis is dependent on the apoptotic pathway because RNAi targeting the RHG genes is sufficient to block proliferation. However, NiA does not promote proliferation through the previously described apoptosis-induced proliferation (AiP) pathway, although cells at the wound edge undergo AiP. Further examination of the caspase levels in NiA cells allowed the authors to group these cells into two clusters: some cells (NiA) undergo apoptosis and are removed, while others referred to as Necrosis-induced Caspase Positive (NiCP) cells survive despite caspase activity. It is the NiCP cells that repair cellular damage including DNA damage and that promote regenerative proliferation. Caspase sensors demonstrate that both groups of cells have initiator caspase activity, while only the NiA cells contain effector caspase activity. Under certain conditions, the authors were also able to visualize effector caspase activity in NiCP cells, but the level was low, likely below the threshold for apoptosis. Finally, the authors found that loss of the initiator caspase Dronc blocks regenerative proliferation, while inhibiting effector caspases by expression of p35 does not, suggesting that Dronc can induce regenerative proliferation following necrosis in a non- apoptotic manner. This last finding is very interesting as it implies that Dronc can induce proliferation in at least two ways in addition to its requirement in AiP.

Strengths:

This is a very interesting manuscript. The authors demonstrate that epithelial tissue that contains a significant number of necrotic cells is able to regenerate. This regenerative response is dependent on the apoptotic pathway which is induced at a distance from the necrotic cells. Although regenerative proliferation following necrosis requires the initiator caspase Dronc, Dronc does not induce a classical AiP response for this type of regenerative response. In future work, it will be very interesting to dissect this regenerative response pathway genetically.

Weaknesses:

No weaknesses were identified.

We thank the reviewer for their positive evaluation and kind words.

Reviewer #2 (Public Review):

Summary / Strengths:

In this manuscript, Klemm et al., build on past published findings (Klemm et al., 2021) to characterize caspase activation in distal cells following necrotic tissue damage within the Drosophila wing imaginal disc. Previously in Klemm et al., 2021, the authors describe necrosis-induced-apoptosis (NiA) following the development of a genetic system to study necrosis that is caused by the expression of a constitutive active GluR1 (Glutamate/Ca2+ channel), and they discovered that the appearance of NiA cells were important for promoting regeneration.

In this manuscript, the authors aim to investigate how tissues regenerate following necrotic cell death. They find that the cells of the wing pouch are more likely to have non-autonomous caspase activation than other regions within the wing imaginal disc (hinge and notum),two signaling pathways that are known to be upregulated during regeneration, Wnt (wingless) and JAK/Stat signaling, act to prevent additional NiA in pouch cells, and may explain the region specificity, the presence of NiA cells promotes regenerative proliferation in late stages of regeneration, not all caspase-positive cells are cleared from the epithelium (these cells are then referred to as Necrosis-induced Caspase Positive (NiCP) cells), these NiCP cells continue to live and promote proliferation in adjacent cells, the caspase Dronc is important for creating NiA/NiCP cells and for these cells to promote proliferation. Animals heterozygous for a Dronc null allele show a decrease in regeneration following necrotic tissue damage.

The study has the potential to be broadly interesting due to the insights into how tissues differentially respond to necrosis as compared to apoptosis to promote regeneration.

Weaknesses:

However, here are some of my current concerns for the manuscript in its current version:

The presence of cells with activated caspase that don't die (NiCP cells) is an interesting biological phenomenon but is not described until Figure 5. How does the existence of NiCP cells impact the earlier findings presented? Is late proliferation due to NiA, NiCP, or both? Does Wg and JAK/STAT signaling act to prevent the formation of both NiA and NiCP cells or only NiA cells? Moreover, the authors are able to specifically manipulate the wound edge (WE) and lateral pouch cells (LP), but don't show how these manipulations within these distinct populations impact regeneration. The authors provide evidence that driving UAS-mir(RHG) throughout the pouch, in the LP or the WE all decrease the amount of NiA/NiCP in Figure 3G-O, but no data on final regenerative outcomes for these manipulations is presented (such as those presented for Dronc-/+ in Fig 7M). The manuscript would be greatly enhanced by quantification of more of the findings, especially in describing if the specific manipulations that impacted NiA /NiCP cells disrupt end-point regeneration phenotypes.

We have added a line to the results to clarify that we believe the finding that some NiA likely persist as NiCP does not affect our conclusions up to this point.

We have added a statement emphasizing the results from our first paper, which demonstrate that LP>miRHG expression reduces the overall capacity to regenerate.

Quantification of the change in posterior NiA number have been added to Figure 2L to strengthen the evidence. Likewise, we have included quantification of the E2F time course presented in Figure 3A (Figure 3 – Figure supplement 1C), and quantification of the change in GC3Ai signal over time has been added to Figure 5 - Figure supplement 1D) to emphasize the perdurance of GC3Ai-positive NiA/NiCP.

How fast does apoptosis take within the wing disc epithelium? How many of the caspase(+) cells are present for the whole 48 hours of regeneration? Are new cells also induced to activate caspase during this time window? The author presented a number of interesting experiments characterizing the NiCP cells. For the caspase sensor GC3Ai experiments in Figure 5, is there a way to differentiate between cells that have maintained fluorescent CG3Ai from cells that have newly activated caspase? What is the timeline for when NiA and NiCP are specified? In addition, what fraction of NiCP cells contribute to the regenerated epithelium? Additional information about the temporal dynamics of NiA and NiCP specification/commitment would be greatly appreciated.

We have included more information concerning the kinetics of apoptotic cell removal, and how this compares to the observations we have made with NiA/NiCP in our GC3Ai experiments. Additionally, we have included a quantification of the percent of the whole wing pouch with GC3Ai signal over time (Figure 5F) as well as the distal wing pouch with GC3Ai signal over time (Figure 5 – Figure supplement 1D) to further support the idea that NiCP persist over time.

We acknowledge that our GC3Ai time course unfortunately cannot confirm whether the increase in GC3Ai signal over time is due to cells with new caspase activity or proliferating NiCP and have included this point in the discussion.

We attempted to track the lineage of NiA/NiCP into the pupal and adult wings with CasExpress and DBS, however the results of these experiments were inconsistent, and therefore we did not feel confident to include these data or draw conclusions in either direction. We are currently designing variations of these lineage trace tools in order to better track the lineage of these cells that we hope to include in a future paper.

The notum also does not express developmental JAK/STAT, yet little NiA was observed within the notum. Do the authors have any additional insights into the differential response between the pouch and notum? What makes the pouch unique? Are NiA/NiCP cells created within other imaginal discs and other tissues? Are they similarly important for regenerative responses in other contexts?

We have added a brief mention of these points to the appropriate results section to avoid further increasing the length of the discussion.

Data on the necrosis of other imaginal discs through FLP/FRT clone formation in haltere and leg discs has been added to Figure 1 Figure supplement 1J, and described in the text.

Reviewer #3 (Public Review):

The manuscript "Regeneration following tissue necrosis is mediated by non- apoptotic caspase activity" by Klemm et al. is an exploration of what happens to a group of cells that experience caspase activation after necrosis occurs some distance away from the cells of interest. These experiments have been conducted in the Drosophila wing imaginal disc, which has been used extensively to study the response of a developing epithelium to damage and stress. The authors revise and refine their earlier discovery of apoptosis initiated by necrosis, here showing that many of those presumed apoptotic cells do not complete apoptosis. Thus, the most interesting aspect of the paper is the characterization of a group of cells that experience mild caspase activation in response to an unknown signal, followed by some effector caspase activation and DNA damage, but that then recover from the DNA damage, avoid apoptosis, and proliferate instead. Many questions remain unanswered, including the signal that stimulates the mild caspase activation, and the mechanism through which this activation stimulates enhanced proliferation.

The authors should consider answering additional questions, clarifying some points, and making some minor corrections:

Major concerns affecting the interpretation of experimental results:

Expression of STAT92E RNAi had no apparent effect on the ability of hinge cells to undergo NiA, leading the authors to conclude that other protective signals must exist. However, the authors have not shown that this STAT92E RNAi is capable of eliminating JAK/STAT signaling in the hinge under these experimental conditions. Using a reporter for JAK/STAT signaling, such as the STAT-GFP, as a readout would confirm the reduction or elimination of signaling. This confirmation would be necessary to support the negative result as presented.

We have included data demonstrating our ability to knock down JAK/STAT activity in the hinge with UAS-Stat92E^RNAi (Figure 2 – Figure supplement 1E and F). Additionally, we have included a quantification of posterior NiA/NiCP with the Stat92E^RNAi (as well as wg^RNAi and Zfh-2^RNAi, Figure 2L) to strengthen our conclusion that JAK/STAT and WNT signaling acts to regulate NiA formation within the pouch.

Similarly, the authors should confirm that the Zfh2 RNAi is reducing or eliminating Zfh2 levels in the hinge under these experimental conditions, before concluding that Zfh2 does not play a role in stopping hinge cells from undergoing NiA.

We have repeated this experiment with a longer knockdown using a GAL4 driver that expresses from early larval stages until our evaluation at L3, but were unable to demonstrate a loss of Zfh-2 with IF labeling. Additionally, we have quantified posterior NiA/NiCP with a Zfh-2RNAi (Figure 2L) and do find a slight increase in NiA/NiCP number, however this change is not significant. We have altered our conclusions to reflect these new data.

EdU incorporation was quantified by measuring the fluorescence intensity of the pouch and normalizing it to the fluorescence intensity of the whole disc. However, the images show that EdU fluorescence intensity of other regions of the disc, especially the notum, varied substantially when comparing the different genetic backgrounds (for example, note the substantially reduced EdU in the notum of Figure 3 B' and B'). Indeed, it has been shown that tissue damage can lead to suppression of proliferation in the notum and elsewhere in the disc, unless the signaling that induces the suppression is altered. Therefore, the normalization may be skewing the results because the notum EdU is not consistent across samples, possibly because the damage-induced suppression of proliferation in the notum is different across the different genetic backgrounds.

To more accurately reflect the observations that we have made with the EdU assay, we have changed our terminology to indicate that the EdU signal is more localized to the damaged tissue in ablated discs, thus taking into account the relative changes across the disc, rather than referring to it as an increase in the pouch. To further strengthen our observation that damage results in a localized proliferation, we have included a quantification of the E2F time course presented in Figure 3A (Figure 3 – Figure supplement 1C), which underscores the trend observed in our EdU experiments.

The authors expressed p35 to attempt to generate "undead cells". They take an absence of mitogen secretion or increased proliferation as evidence that undead cells were not generated. However, there could be undead cells that do not stimulate proliferation non-autonomously, which could be detected by the persistence of caspase activity in cells that do not complete apoptosis. Indeed, expressing p35 and observing sustained effector caspase activation could help answer the later question of what percentage of this cell population would otherwise complete apoptosis (NiA, rescued by p35) vs reverse course and proliferate (NiCP, unaffected by p35).

In our previous work, we showed that P35 expression impairs our ability to detect effector caspases with IF-based tools. This can also be seen in Figure 4 of this work (Figure 4C and F). Given that P35 expression precludes our ability to label and assay effector caspase activity visually, and thus address the concerns outlined above, we relied on other tools such as reporters of AiP mitogens (wg-lacZ & dpp-lacZ) to assay whether NiA participate in AiP. As a functional readout, we also paired P35 expression with the EdU assay to test whether proliferation was altered by the presence of undead cells. The results discussed in Figure 4 lead us to conclude that NiA likely do not participate in the canonical AiP feedforward loop, although it is possible that these experiments generate another type of undead cell – one that utilizes a different mechanism to promote proliferation.

It is unclear if the authors' model is that the NiCP cells lead to autonomous or non-autonomous cell proliferation, or both. Could the lineage-tracing experiments and/or the experiments marking mitosis relative to caspase activity answer this question?

We have added further details to the discussion on the potential for NiA/NiCP to induce cell autonomous/non-autonomous proliferation.

Many of the conclusions rely on single images. Quantification of many samples should be included wherever possible.

We have added quantification to strengthen the results of Figures 2, 3 and 5.

Why does the reduction of Dronc appear to affect regenerative growth in females but not males?

We have repeated this regeneration scoring experiments and have increased the N for control versus droncI29 mutant males, however the results of the analysis for male wing size remain not significant, although the general trend that droncI29 wings are slightly smaller. While there could be sex-specific differences in the capacity to regenerate that contribute to this observation, it is unclear what the underlying mechanism could be.

Reviewer #1 (Recommendations for the authors):

The work in this paper is already very complete and very well worked out. The conclusions are well supported by the data in this manuscript. I do not have any experimental requests, only a few minor and formal requests/questions.

(1) Why does Diap1 overexpression not affect regenerative proliferation, whereas mir(RHG) and dronc[I29] do, given that Diap1 acts between RHG and Dronc?

We speculate on this point in the discussion section but have adjusted some of the phrasing for clarity.

(2) I assume that the authors used the cleaved Dcp-1 antibody from Cell Signaling Technologies. I recommend that the authors refer to this antibody as cDcp-1 in text and figures as this antibody specifically detects the cleaved, and thus activated form of Dcp-1, and not the uncleaved, inactive form of Dcp-1 which has a uniform expression in the discs.

Changed to cDcp-1.

(3) Line 299: Hay et al. 1994 did not show that p35 inhibits Drice and Dcp-1 (in fact, both genes were not even cloned yet). This was shown by Meier et al. 2000 and Hawkins et al. 2000. Please correct references.

Corrected.

(4) Line 574/575. Meier et al. 2000 did not show that Dronc is mono-ubiquitylated. This was shown by Kamber-Kaya et al., 2017. Please correct.

Corrected.

Reviewer #2 (Recommendations for the authors):

(1) Does domeless knockdown cause apoptosis without tissue ablation (Figures 2C-E)? Currently, the non-ablation control is not shown.

Domeless knockdown does not cause apoptosis in the absence of ablation (Added Figure 2 – Figure supplement 1A).

(2) The supplemental experiment with zfh2-RNAi is hard to interpret because there is no evidence of RNAi knockdown based on the staining with the anti-Zfh2 antibody.

As noted above, a longer zfh-2 knockdown does not appear to alter Zfh-2 protein levels. A quantification of posterior NiA/NiCP following knockdown shows a slight (non-significant) increase in posterior NiA/NiCP. Considering these new results, we have altered our interpretation within the appropriate results and discussion sections.

(3) The authors should consider adding a diagram showing where mir(RHG) and DIAP1 are in the apoptotic/caspase activation pathway (Figure 7N).

Completed, Figure 7N and 7O.

Reviewer #3 (Recommendations for the authors):

(1) Figure 2 I -The purported increase in NiA should be quantitated relative to the NiA in G across many discs.

Completed (Figure 2L)

(2) Figure 2 M - contrary to the conclusion drawn, the posterior Dcp1 does not appear different from that in the control (K). This conclusion that the NiA does not occur in the margin could be better supported with more images/quantification.

We have exchanged the image for a representative one that more clearly shows the lack of margin NiA and highlighted with an arrowhead (Figure 2K)

(3) Figure 2 supp 1 E - the "slight increase" in NiA in the pouch is relative to which control? Can this conclusion be supported by quantification?

Figure 2L now quantifies this change.

(4) Figure 2 Supp 1 D, E - these discs supposedly have Zfh2 RNAi expressed, but there appears to be no reduction in Zfh2.

We were unable to demonstrate a reduction of Zfh2, even with a longer knockdown. Considering these new data, we have altered our conclusions from the Zfh2 experiments.

(5) Figure 2 Supp 1 I - please quantitate the Dcp-1 across many discs to support the conclusion.

This is the UAS-wg experiment, which we decided to remove from the quantification given the non-specific increase in cDcp-1 throughout the disc (likely as a result from ectopic Wg expression).

(6) Figure 4 legend M - The authors conclude that the experiment indicates that "NiA promote proliferation independent of AiP". It would be more precise to say that NiA cells do not secrete AiP mitogens and do not increase the proliferation of surrounding cells when prevented from completing apoptosis. To say that the NiA-induced proliferation does not require AiP would require eliminating AiP, perhaps through reaper hid grim knockdown or mitogen knockdown.

Corrected.

Minor concerns and clarification needed:

(7) Line 61 - consider the distinction between a feed-forward loop and a positive feedback loop.

Corrected.

(8) Line 338 - it would be helpful to have a brief explanation of what the GC3Ai consists of and how it reports caspase activity.

Corrected.

(9) Line 343 - the authors should clarify by what they mean when they state GC3Ai-positive cells are "associated with" mitotic cells. Are the GC3Ai cells undergoing mitosis? Or is the increase in mitosis non-autonomous?

Adjusted. “associated with adjacent proliferative cells”.

(10) Lines 392-394 - the authors should add brief descriptions of how the Drice-Based sensor and the CasExpress function, so the readers can better understand the distinctions between these sensors and the previously mentioned sensors (anti-Dcp1 and GC3Ai). In addition, please clarify how the Gal80ts modulates the sensitivity of the CasExpress.

Descriptions of DBS and CasExpress and additional clarification provided.

(11) Line 413: How does Gal80ts suppress the background developmental caspase signal, and how does this suppression lead to NiCP cells expressing GFP?

This section has been reworded to clarify.

(12) Line 417 - which GFP label is referred to here?

This section has been reworded to clarify.

(13) Line 445 is the first mention of the CARD domain - it could be introduced more fully and explained why the DroncDN's lack of effect on proliferation excludes the CARD domain as being important.

Clarified. See also the discussion for the significance of the CARD domain as dispensable for regenerative proliferation following necrosis.

(14) Line 452 - "As mentioned" - the manuscript has not previously mentioned DIAP1 modification of the CARD domain and what that modification does. Perhaps the previous explanatory text was inadvertently removed?

Corrected.

(15) The Discussion is a lengthy list of experiments that the authors did not do or observations they were unable to make. This section could benefit from a more in-depth discussion of necrosis and the possibility that NiCP cells contribute to repair after injury across contexts and species.

We have made several changes to the discussion that elaborate on some of the points listed in the public reviews.

(16) All figures: Consider making single-channel panels grayscale to aid visualization. Also consider using color combinations that can be distinguished by color-blind readers.

We appreciate these suggestions and will consider them for future manuscripts.

(17) All figure legends - are error bars SD or SEM?

Standard deviation. Added to appropriate legends.

(18) Figure 1A,C - it would be helpful in the diagrams to note when the necrosis occurs/completes.

The endpoint of necrosis is not well defined, given the simultaneous changes that occur with regeneration. Thus, we opted to not include an indicator of when necrotic ablation ends.

(19) Figure 1B - it would be helpful to name the GAL4 drivers whose expression domain is depicted to correlate with the terms used in the text.

Completed.

(20) Figure 1 legend- what do the different colors of the arrowheads denote? The dotted lines are in R' and S', not N' and O'.

Completed.

(21) Figure 2G - the yellow dashed line is not in the same place in the two images.

Corrected.

(22) Figure 2I - what is the open arrowhead?

Completed (Figure 2I legend).

(23) Figure 3 legend - please describe what the time course is observing (EdU).

Completed.

(24) Figure 4 - please include the yellow boxes in the Dcp-1 channels.

Completed.

(25) Figure 5 F' - add the arrowheads to all the panels. The yellow arrowhead appears to be pointing to nothing.

Completed.

(27) Figure 5 legend - what is a "cytoplasmic undisturbed cell"? What is the arrowhead in G? J and J' should show the same view at different time points or different views at the same time point.

Figure legend has been corrected.

(28) Figure 5 Supp 1 would be especially helped by having more single-channel panels in grayscale.

For clarity and consistency, we chose to maintain the different color channels.

(29) Figure 5 Supp 1 D and E - It would be helpful to have higher magnification and arrows pointing to the cells of interest. Why are there TUNEL+ cells that do not have caspase activation (green)?

We have added arrowheads as suggested. We believe the disparity in TUNEL and GC3Ai signals are a result of the different sensitivities of the IF staining and the TUNEL assay.

(30) Figure 5 Supp 1 F - perhaps the arrowheads should be in all panels - they point to empty spaces with no H2Av staining in the final panel. Perhaps a higher magnification image would make the "strong overlap" of the two signals more apparent?

We have added arrowheads where appropriate.

(31) Figure 6 D-E - does the widespread GFP lineage tracing signal suggest that most cells in the repaired tissue originated from cells that once had caspases activity?

Possibly, however given that CasExpress leads to significant developmental labeling, we were unable to determine to what extent the signal in this experiment comes from NiA/NiCP activity versus developmental labeling. Note that tubGAL80ts is not present in this experiment.

(32) Writing corrections:

Line 343 "positive" is misspelled.

Completed

Line 429 - a word may be missing.

Completed

Line 639 - the word "day" may be missing.

Completed

Line 658 - what temperature was the recovery?

Completed

Lines 706-708 - were the discs incubated in 55 mL and 65 mL of liquid, or a smaller volume?

Completed

eLife Assessment

This manuscript establishes a mathematical model to estimate the key parameters that control the repopulation of planarian stem cells after sublethal irradiation as they undergo fate-switching as part of their differentiation and self-renewal process. The findings are valuable for future investigation of stem cell division in planarians. The methods are solid, integrating modeling with perturbations of key transcription factors known to be critical for cell fate decisions, but the authors have only shown that this is the case for a small number of stem cell types.

Reviewer #1 (Public review):

Summary:

This is a very creative study using modeling and measurement of neoblast dynamics to gain insight into the mechanism that allows these highly potent cells to undergo fate-switching as part of their differentiation and self-renewal process. The authors estimate growth equation parameters for expanding neoblast clones based on new and prior experimental observations. These results indicate neoblast likely undergo much more symmetric self-amplifying division than loss of the population through symmetric differentiation, in the case of clone expansion assays after sublethal irradiation. Neoblasts take on multiple distinct transcriptional fates related to their terminally differentiated cell types, and prior work indicated neoblasts have a high plasticity to switch fates in a way linked to cell cycle progression and possibly through a random process. Here, the authors explore the impact of inhibition of key transcription factors defining such states (ie "fate specifying transcription factors", FSTFs) plus measurement and modeling in the clone expansion assay, to find that inhibition of factors like zfp1 likely cause otherwise zfp1-fated neoblasts to fail to proliferate and differentiation without causing compensatory gains in other lineages. A mathematical model of this process assuming that neoblasts do not retain a memory of prior states while they proliferate, and transition across specified states can mimic the experimentally determined decreased sizes of clones following inhibition of zfp1. Complementary approaches to inhibit more than one lineage (muscle plus intestine) supports the idea that this is a more general process in planarian stem cells. These results provide an important advance for understanding the fate-switching process and its relationship to neoblast growth.

Overall I find the evidence very well presented and the study compelling. It offers an important new perspective on the key properties of neoblasts. I do have some comments to clarify the presentation and significance of the work.

Reviewer #2 (Public review):

Summary:

Cell cycle duration and cell fate choice are critical to understanding the cellular plasticity of neoblasts in planarians. In this study, Tamar et al. integrated experimental and computational approaches to simulate a model for neoblast behaviors during colony expansion.

Strengths:

The finding that "arresting differentiation into specific lineages disrupts neoblast proliferative capacities without inducing compensatory expression of other lineages" is particularly intriguing. This concept could inspire further studies on pluripotent stem cells and their application for regenerative biology.

Weaknesses:

However, the absence of a cell-cell feedback mechanism during colony growth and the likelihood of the difference needs to be clarified. Is there any difference in interpreting the results if this mechanism is considered? More explanation and discussion should be included to distinguish the stages controlled by the one-step model from those discussed in this study. Although hnf-4 and foxF have been silenced together to validate the model, a deeper understanding of the tgs-1+ cell type and the non-significant reduction of tgs-1+ neoblasts in zfp-1 RNAi colonies is necessary, considering a high neural lineage frequency.

Author response:

Reviewer #1:

Overall I find the evidence very well presented and the study compelling. It offers an important new perspective on the key properties of neoblasts. I do have some comments to clarify the presentation and significance of the work.

We thank the reviewer for the positive feedback and plan to improve the presentation of the work.

Reviewer #2:

However, the absence of a cell-cell feedback mechanism during colony growth and the likelihood of the difference needs to be clarified. Is there any difference in interpreting the results if this mechanism is considered?

We will improve the description of the model assumptions and the interpretation of the data on the basis of these assumptions.

Although hnf-4 and foxF have been silenced together to validate the model, a deeper understanding of the tgs-1+ cell type and the non-significant reduction of tgs-1+ neoblasts in zfp-1 RNAi colonies is necessary, considering a high neural lineage frequency.

We will improve the analysis of this result in light of the experimentally determined frequency of the tgs-1+ neoblast population.

eLife Assessment

This study provides evidence that single-cell multi-omics profiling can reveal key regulators of HIV-1 persistence and early immune dysregulation, particularly implicating KLF2 and Th17 cells as major players in viral reservoir dynamics. The findings are solid, supported by rigorous integration of scRNA-seq and scATAC-seq data, but are limited by sample size and lack of validation with external datasets. Overall, this work makes a valuable contribution to understanding HIV-1 immune evasion and highlights potential therapeutic targets for reservoir eradication.

Reviewer #1 (Public review):

Summary:

The authors aimed to elucidate the molecular mechanisms underlying HIV-1 persistence and host immune dysfunction in CD4+ T cells during early infection (<6 months). Using single-cell multi-omics technologies-including scRNA-seq, scATAC-seq, and single-cell multiome analyses-they characterized the transcriptional and epigenomic landscapes of HIV-1-infected CD4+ T cells. They identified key transcription factors (TFs), signaling pathways, and T cell subtypes involved in HIV-1 persistence, particularly highlighting KLF2 and Th17 cells as critical regulators of immune suppression. The study provides new insights into immune dysregulation during early HIV-1 infection and reveals potential epigenetic regulatory mechanisms in HIV-1-infected T cells.

Strengths:

The study excels through its innovative integration of single-cell multi-omics technologies, enabling detailed analysis of gene regulatory networks in HIV-1-infected cells. Focusing on early infection stages, it fills a crucial knowledge gap in understanding initial immune responses and viral reservoir establishment. The identification of KLF2 as a key transcription factor and Th17 cells as major viral reservoirs, supported by comprehensive bioinformatics analyses, provides robust evidence for the study's conclusions. These findings have immediate clinical relevance by identifying potential therapeutic targets for HIV-1 reservoir eradication.

Weaknesses:

Despite its strengths, the study has several limitations. By focusing exclusively on CD4+ T cells, the study overlooks other relevant immune cells such as CD14+ monocytes, NK cells, and B cells. Additionally, while the authors generated their own single-cell datasets, they need to validate their findings using other publicly available single-cell data from HIV-1-infected PBMCs.

Reviewer #2 (Public review):

Summary:

The authors observed gene ontologies associated with upregulated KLF2 target genes in HIV-1 RNA+ CD4 T Cells using scRNA-seq and scATAC-seq datasets from the PBMCs of early HIV-1-infected patients, showing immune responses contributing to HIV pathogenesis and novel targets for viral elimination.

Strengths:<br /> The authors carried out detailed transcriptomics profiling with scRNA-seq and scATAC-seq datasets to conclude upregulated KLF2 target genes in HIV-1 RNA+ CD4 T Cells.

Weaknesses:

This key observation of up-regulation KLF2 associated genes family might be important in the HIV field for early diagnosis and viral clearance. However, with the limited sample size and in-vivo study model, it will be hard to conclude. I highly recommend increasing the sample size of early HIV-1-infected patients.

Reviewer #3 (Public review):

Summary:

This manuscript studies intracellular changes and immune processes during early HIV-1 infection with an additional focus on the small CD4+ T cell subsets. The authors used single-cell omics to achieve high resolution of transcriptomic and epigenomic data on the infected cells which were verified by viral RNA expression. The results add to understanding of transcriptional regulation which may allow progression or HIV latency later in infected cells. The biosamples were derived from early HIV infection cases, providing particularly valuable data for the HIV research field.

Strengths:

The authors examined the heterogeneity of infected cells within CD4 T cell populations, identified a significant and unexpected difference between naive and effector CD4 T cells, and highlighted the differences in Th2 and Th17 cells. Multiple methods were used to show the role of the increased KLF2 factor in infected cells. This is a valuable finding of a new role for the major transcription factor in further disease progression and/or persistence.

The methods employed by the authors are robust. Single-cell RNA-Seq from PBMC samples was followed by a comprehensive annotation of immune cell subsets, 16 in total. This manuscript presents to the scientific community a valuable multi-omics dataset of good quality, which could be further analyzed in the context of larger studies.

Weaknesses:

Methods and Supplementary materials<br /> Some technical aspects could be described in more detail. For example, it is unclear how the authors filtered out cells that did not pass quality control, such as doublets and cells with low transcript/UMI content. Next, in cell annotation, what is the variability in cell types between donors? This information is important to include in the supplementary materials, especially with such a small sample size. Without this, it is difficult to determine, whether the differences between subsets on transcriptomic level, viral RNA expression level, and chromatin assessment are observed due to cell type variations or individual patient-specific variations. For the DEG analysis, did the authors exclude the most variable genes?

The annotation of 16 cell types from PBMC samples is impressive and of good quality, however, not all cell types get attention for further analysis. It's natural to focus primarily on the CD4 T cells according to the research objectives. The authors also study potential interactions between CD4 and CD8 T cells by cell communication inference. It would be interesting to ask additional questions for other underexplored immune cell subsets, such as: 1) Could viral RNA be detected in monocytes or macrophages during early infection? 2) What are the inferred interactions between NK cells and infected CD4 T cells, are interactions similar to CD4-CD8 results? 3) What are the inferred interactions between monocytes or macrophages and infected CD4 T cells?

Discussion<br /> It would be interesting to see more discussion of the observation of how naïve T cells produce more viral RNA compared to effector T cells. It seems counterintuitive according to general levels of transcriptional and translational activity in subsets.<br /> Another discussion block could be added regarding the results and conclusion comparison with Ashokkumar et al. paper published earlier in 2024 (10.1093/gpbjnl/qzae003). This earlier publication used both a cell line-based HIV infection model and primary infected CD4 T cells and identified certain transcription factors correlated with viral RNA expression.

eLife Assessment

This valuable study describes a software package in R for visualizing metabolite ratio pairs. The evidence supporting the claims of the authors is solid and broadly supports the authors' conclusions. This work would be of interest to the mass spectrometry community.

Reviewer #2 (Public review):

Summary:

In the article, the authors describe their software package in R for visualizing metabolite ratio pairs. I think the work would be of interest to the mass spectrometry community.

Strengths:

The authors describe a software that would be of use to those performing MALDI MSI. This software would certainly add to the understanding metabolomics data and enhance the identification of critical metabolites.

Weaknesses:

The figures are difficult to interpret/ analyze in their current state but are significantly better in the revision.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Cheng et al explore the utility of analyte ratios instead of relative abundance alone for biological interpretation of tissue in a MALDI MSI workflow. Utilizing the ratio of metabolites and lipids that have complimentary value in metabolic pathways, they show the ratio as a heat map which enhances the understanding of how multiple analytes relate to each other spatially. Normally, this is done by projecting each analyte as a unique color but using a ratio can help clarify visualization and add to biological interpretability. However, existing tools to perform this task are available in open-source repositories, and fundamental limitations inherent to MALDI MSI need to be made clear to the reader. The study lacks rigor and controls, i.e. without quantitative data from a variety of standards (internal isotopic or tissue mimetic models for example), the potential delta in ionization efficiencies of different species subtracts from the utility of pathway analysis using metabolite ratios.

We thank the reviewer for comments on the availability of four other commercial and open-source tools for performing ratio imaging: ENVI® Geospatial Analysis Software, MATLAB image processing toolbox, Spectral Python (SPy) and QGIS. We now highlight these in the introduction (page 3 line 80-86). However, in contrast to these target ratio imaging methods, our approach uniquely enables the untargeted discovery of correlated (or anti-correlated) ratios of molecular features, whether the species are structurally known or unknown.

ENVI® Geospatial Analysis Software and MATLAB image processing toolbox for hyperspectral imaging are both paid programs, limiting free access and software evaluation for the potential application of untargeted ratio-metric imaging. We are able to evaluate the application of MATLAB RatioImage since Weill Cornell Medicine has an institutional subscription for Mathwork-MATLAB. Notably, MATLAB RatioImage computes and displays an individual intensity modulated ratiometric image by choosing a numerator and denominator image. This software tool only images the ratios of selected metabolites from an input list of multiple species and does not allow for the possibility of untargeted ratiometric images of all metabolite pairs.

While Spectral Python (SPy) and QGIS are both freely-available software packages, and both can perform individual metabolite ratio images, neither allows for untargeted ratiometric imaging of all pairs from a multiple metabolite input list. Table S1 (below) provides a comparison of the ratio imaging tool that we offer in comparison with other previously available tools.

We appreciate the reviewer’s insightful comments on differential ionization efficiency among metabolites and the importance of using stable isotope internal standard to gain absolute quantification.

A fundamental advantage of our ratiometric imaging tool is to provide better image contrast for tissue regions with differential ionization efficiency, with the potential to discover new “metabolic” regions that can be revealed by metabolite ratio. Note that comparison for ratio image abundance is limited to tissue groups in the equivalent region which is expected to have similar ionization efficiency for given metabolites. Furthermore, the power of our strategy is to provide untargeted (and targeted) ratio imaging as a hypothesis generation tool and this use does not require absolute quantification. If cost was not an issue, an extensive group of stable isotope standards could theoretically be used for absolute metabolite quantification of target metabolites with known identity.

Using the tissue mimetic model, we generate calibration curve for stable isotope standards spiked in carboxymethylcellulose (CMC)-embedded brain homogenate cryosections and quantify the concentration of brain glucose, lactate and ascorbate concentrations. Similar ratio images among these metabolites are obtained from abundance data compared to quantified concentration data (Fig S3). While stable isotope standards are often used to obtain quantitative concentration of metabolite/lipid of interest, it is not applicable for untargeted metabolite ratios that include an assessment of structurally undefined species. Nevertheless, our data indicates that absolute quantification is not necessary for the targeted and untargeted ratio imaging described here (Page 6, line 196-205).

Reviewer #2 (Public Review):

Summary:

In the article, "Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging" the authors describe their software package in R for visualizing metabolite ratio pairs. I think the novelty of this manuscript is overstated and there are several notable issues with the figures that prevent detailed assessment but the work would be of interest to the mass spectrometry community.

Strengths:

The authors describe a software that would be of use to those performing MALDI MSI. This software would certainly add to the understanding of metabolomics data and enhance the identification of critical metabolites.

Weaknesses:

The authors are missing several references and discussion points, particularly about SIMS MSI, where ratio imaging has been previously performed.

There are several misleading sentences about the novelty of the approach and the limitations of metabolite imaging.

Several sentences lack rigor and are not quantitative enough.

The figures are difficult to interpret/ analyze in their current state and lack some critical components, including labels and scale bars.

We thank reviewer for very helpful comments. The tone of the manuscript has been adjusted to highlight the real novelty of this method in the ease of computing and application to MS specific projects (abstract line 26-30 ). All figures have been updated to include labels and scale bars with improved resolution. References for ratio imaging use of SIMS MSI has been added in the introduction (Page 3, line 80-89).

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Major Comments:

In the Abstract it is stated that: "the research community lacks a discovery tool that images all metabolite abundance ratio pairs." However, the following tools exist that perform this fundamental task.

A "pixel by pixel" data frame in .csv form has a very similar data structure to many instruments like satellite imaging or other hyperspectral tools. It is true this does not exist in the MALDI-specific context, but it would not be difficult to perform this task on the following programs. Highlight the novelty here is not ratios but the ease of computing them and the application in the specific project. Also, describe the available tools and what shortcomings others lack that this package provides. A supplemental table of MSI data analysis tools and the function of each would be a good addition.

List of tools to perform band ratio computation with minimal modification:

(1) ENVI IDL: geospatial imaging tool that allows ratio computation between spectral bands.

(2) MATLAB image processing toolbox for hyperspectral imaging.

(3) Spectral Python package (SPy).

(4) QGIS with plugins can be used for hyperspectral image analysis with a ratio between bands.

We revised the abstract and introduction to include novelty and comparison to other existing methods listed in Table S1.

"untargeted R package workflow" - If there are functions used outside the SCiLS Lab API client then write it up and include a GitHub link for open access to fit the mission of eLife.

As shown in Scheme I. We develop two types of codes for untargeted ratio imaging. The first type uses Scils lab API client to extend the function of targeted and targeted ratio imaging and all related spatial image analysis. This is suitable for Scils lab users. The second type does not require Scils lab API, it allows extracting pixel data from imzml file then proceed targeted and untargeted imaging and analysis. Both codes are now deposit in Github via public access (https://github.com/qic2005/Untargeted-massspectrometry-ratio-imaging.git).

"across cells and tissue subregions" The value in reporting cell type and tissue type-specific differences in any metric is powerful, but not done in this paper. Only whole samples are compared such as "KO vs WT" and the annotations in Figure 3 are not leveraged for increased biological relevance. This paper treats each image as a homogenization experiment in a practical sense beyond just visually inspecting each image. Remove this claim or do the calculations on region/tissue/cell-type specific differences with the appropriate tools to show the data beyond simple heat map images.

We have deleted the sentence containing across cells and tissue subregions from the abstract.

"enhances spatial image resolution" Clarify. The resolution in MALDI is set by the raster size of the pixels which is an instrument parameter and cannot be changed post-acquisition. Image-specific methods to increase resolution exist, but dividing the value in one peak column by another does not change functional resolution in the context of the instruments here.

We thank reviewer for pointing out this typo. We have changed it to enhance spatial image contrast in the abstract (line 34).

"pixel-by-pixel imaging of the ratio of an enzyme's substrate to its derived product offers an opportunity to view the distribution of functional activity for a given metabolic pathway across tissue" - Appropriately calibrate the impact of this work and correct this statement to better reflect the capabilities of this approach. Do not oversell the exploration of pathway activity since the raw quantity reported as relative abundance does not provide biologically interpretable pathway information. This is due to unaccounted differences in ionization efficiencies between analytes in a pathway and lack of determination of rate. Without a calibration curve and more techniques on the analytical chemistry side of the project, it is possible a relative abundance of one analyte (like the product of a pathway) could be higher than the relative abundance of another analyte (a precursor), but due to structural differences, the actual quantity of the higher relative abundance species could be significantly different or even lower than its counterpart. Secondly, "functional activity" cannot be assessed in this manner without isotopic labeling or additional techniques. This does not subtract from the overall validity and impact of the work, but highlighting these shortcomings and slight alterations to the claim are important for a multidisciplinary audience.

Although we show that abundance ratio results in similar image to concentration ratio for brain metabolites such as lactate, glucose and ascorbate, we agree with the reviewer that abundance ratio is different from the absolute concentration ratio in numerical value due to difference in ionization efficiency. We delete the sentence “pixel-by-pixel imaging of the ratio of an enzyme's substrate to its derived product offers an opportunity to view the distribution of functional activity for a given metabolic pathway across tissue" from the abstract. We apologize for not clarifying this application more clearly. We meant to compare pathway activity among the equivalent and similar pixel/regions of tissues from different biological groups, given the assumption that ionization efficiency is identical for equivalent pixel from different tissue sections ( i.e. same cell type and microenvironment), especially for metabolites with similar functional structure in the same pathway. For example, fatty acids with different chain length and phospholipid with same head groups are expected to have similar ionization efficiency in the same tissue pixel/region. We have thereby rewritten this section (Page 7, line 239-247).

"We further show that ratio imaging minimizes systematic variations in MSI data by sample handling and instrument drift, improves image resolution, enables anatomical mapping of metabotype heterogeneity, facilitates biomarker discovery, and reveals new spatially resolved tissue regions of interest (ROIs) that are metabolically distinct but otherwise unrecognized."

Instrument drift is not accounted for by ratios as it impacts the process before ratio computation. "metabotype" - spelling?

Instrument drift here refers to individual ion abundance changes during long data acquisition. Ratio may offer a better read-out than individual metabolite abundance alone. However, for acquired data after total ion normalization, ratio data would not have difference from non-ratio data. Therefore, we delete instrument drift from the sentence (Page 2, line 33, and Page 3, line 99)

Metabotype is a term widely used for metabolomics field. It is categorized by similar metabolic profiles, which are based on combinations of specific metabolites. https://nutritionandmetabolism.biomedcentral.com/articles/10.1186/s12986-020-00499-z

Results 3: Justify the claim that the ratio reduces artifacts. A ratio is the value from one m/z area over another and would seem that the quality of the ratio would be always lower than the individually higher quality pixel signal of the two analytes that compose a ratio.

Ratio images are indeed the heatmaps of pixel-by-pixel ratio data, set by the scale of all ratio values. For very abundant ion pairs, their individual image may not be better than the ratio image, depending on the abundance changes among pixels within tissue sections. Similarly, the quality of ratio image may not be higher than the individual image if distribution of ratios does not change much among pixels in tissue sections. For example, metabolite or lipids in Figures 2 and 5 are abundant, but non-ratio images do not have better quality than ratio images. Furthermore, ratio image provides additional information on how the ratio of the two metabolite pair changes pixel-by pixel in all tissue sections, such additional information could be useful for data interpretation.

Results 4: The metabolite pairs are biologically sensible but should be clearly stated that they do not account for differences in ionization efficiency between metabolites and cannot provide quantitative pathway analysis with a high degree of biological confidence.

We apologize for not clarifying this application more clearly. We meant to compare pathway activity among the equivalent and similar pixel/regions of tissues from different biological groups, given the assumption that ionization efficiency is identical for equivalent pixel from different tissue sections ( i.e. same cell type and microenvironment), especially for metabolites with similar functional structure in the same pathway. For example, fatty acids with different chain length and phospholipid with same head groups are expected to have similar ionization efficiency in the same tissue pixel/region. We have thereby rewritten this section (Page 7, 239-247, 254-255).

Results 4: "cell-type specific metabolic activity at cellular (10 µm) spatial resolution" Prove the cell type differences with IHC coregistration or MALDI IHC if you want to make claims about them. Just visually determining a tissue type of a scan of a slide is inadequate to support this claim.

We agree with reviewer’s comments. We meant to provide additional information on cellular level metabolic activity such as adenosine nucleotide phosphorylation status (ATP/AMP) ratio at 10µm resolution. Hippocampus neurons provide a good example for depicting this utility. We have rewritten the claim to highlight the role of ratio imaging in providing additional metabolic information (Page 8, line 288-290).

Minor Comments:

Table 2 "Aspartiate" spelling

We have corrected it.

Describe the process and mathematical background for ratio computation in the Methods section. As this paper introduces a package, describing its underlying functions has value.

We have added R-script comments to illustrate the untargeted ratio calculation using the R-mathematical function of combination and division between any two metabolite pairs in a data matrix (Page 4, line 139-141)

"we annotate missing values with 1/5 the minimum value quantified in all pixels in which it was detected" This is explicit (ie only values with exactly 1/5 the value are annotated" - make it clear this is a threshold.

We apologize for misunderstanding. Missing values are either have no value or have solid zero in their abundance. We first calculate the minimum abundance of a particular m/z among all pixels with detectable abundance ( i.e. excluding non-missing values), then use 1/5 this minimum value as a threshold to annotate missing value (Page 4, 133-139).

Figure 1: legend scils is branded SCiLS and EXCEL does not need caps lock (Excel).

Figure 1 legend has been corrected.

Conflicts of interest "None" - there are Bruker employees on a paper about MALDI method development in a field they dominate.

We added Joshua Fischer as a Bruker employee.

Figure 3: The legend does not describe the purple arrow in J.

Purple arrow description is added to figure legend.

Figure 5: Fix orientation inconsistencies in G, H, I, and J. Especially in J - they are opposite directions. This is arbitrary and determined in SCiLS lab with simple rotation.

Orientation has been made consistent in G,H, I and J.

Figure S8: Provide exact number of biological and technical replicates used to generate this figure.

Figure S8, now Figure S9, was generated from 4 biological replicates of KO and 4 biological replicates of WT brain section in the ROI7 region. This information has been added to the figure legend.

Figure S9: Make consistent orientation of all brains

We have made brain orientations consistent.

In addition to ionization efficiencies impacting the value of the numeric relative abundance where ratio computation originates from, it should be mentioned how different classes of metabolites are differentially impacted by the euthanasia and collection methods used for various tissue types. For example, it is well established the ATP/AMP ratio can change drastically from tissue collection.

We have added this to page 8, line 315-319.

Perform standards to adjust for ionization efficiency between different m/z features.

Untargeted ratio imaging serves as an add-on MSI data analysis tool with primary use in comparing ratio among equivalent regions/pixels with similar ionization efficiencies. It is a hypothesis generation tool. Standards adjust for ionization efficiency would be a great idea for a more accurate assessment of ratio values. Due to the cost and availability of stable isotope standards for different m/z, we chose glucose, lactate and ascorbate to showcase that abundance ratio and concentration ratio result in similar images among example brain metabolite lactate, glucose and ascorbate (page 6, 196-205).

Add more controls to support the claims.

We have 4 biological replicates for each genotype of brain. We have added the number of controls in all figure legends.

Significantly tone down the claims, it is unclear how knowledgeable the authors are about the current literature of SW regarding MALDI.

The tone has been significantly tuned down throughout the revised manuscript.

Reviewer #2 (Recommendations For The Authors):

Abstract:

"relative abundance of structurally identified and yet-undefined metabolites across tissue cryosections" is misleading, since tandem MS can be performed in an imaging context and is often also compatible with the same instrument.

We have deleted this sentence in the abstract.

Intro:

Paragraph 1: The authors mention MALDI and DESI, but I would argue that SIMS is more abundantly used than DESI within single-cell applications.

We have added SIMS to the introduction Page 3, line 67.

Paragraph 2: While it may not be all detected pairs, there are many examples of ratio imaging in the MALDI MSI and SIMS communities, particularly for bacterial signaling. These would be important examples to reference.

We have added the application of SIMS ratio imaging to the introduction, page 3, line 74-75.

Materials :

Paragraph 1: More specificity on sample size is required. 3 or 4 per group is not specific. Which has four and which has three? Why are they different?

We have corrected sample numbers for specific genotype in the text and figure legends. The number of sections per group is different due to the availability of fresh-frozen tissues (Page 4, line 115-117).

Results:

Paragraph 1: Am I correct in reading that an .imzml can't be used directly? Why not?

Imaging Mass Spectrometry Markup Language (imzml) is a common data format for mass spectrometry imaging. It was developed to allow the flexible and efficient exchange of large MS imaging data between different instruments and data analysis software (Schramm et al, 2012). It contains two sets of data: the mass spectral data which is stored in a binary file (.ibd file) to ensure efficient storage and the XML metadata (.imzml file) which stores instrumental parameters, sample details. Therefore, it can’t be used directly. We have added this to result 1(Page 5, line 160-169).

Paragraph 4: "Additionally, nonlipid small molecule metabolites suffer from smearing and/or diffusion during cryosection processing, including over the course of matrix deposition for MALDI-MSI." This is misleading. There are several examples of MALDI MSI of small metabolites that are nonlipids, where smearing or diffusion have not occurred. It would be beneficial to have a more accurate discussion of this instead. The authors should also provide some evidence of this, since they continue to focus on it for the full paragraph and don't provide references.

We initially meant the poor image quality of small molecule metabolites is due to its interaction with aqueous phase of spraying solution, rapid degradation rate and matrix interference. We have deleted this sentence in the revised version.

Section 5 Paragraph 2; "However, ratio imaging revealed a much greater aspartate to glutamate ratio in an unusual "moon arc" region across the amygdala and hypothalamus relative to the rest of the coronal brain." Much greater isn't scientifically accurate or descript. Use real numbers and be quantitative.

We used pixel data from all 8 sections to obtain quantitative changes in the ratio-generated “moon arc” region compared to the rest of coronal brain (page 8, line 331-337). Ratio imaging revealed a average of 1.59-fold increase in aspartate to glutamate ratio in an unusual “moon arc” region across the amygdala and hypothalamus (mean abundance 0.563 in 6345 pixels) relative to the rest of the coronal brain (mean abundance 0.353 in 45742 pixels, Figure 5D). Similar but different arc-like structures are encompassed within the ventral thalamus and hypothalamus, wherein glutamate to glutamine ratio show a 1.63-fold increase in intensity compared to the rest of the brain (mean abundance of 0.695 in 7108 pixels vs 0.428 in 44979 pixels, Figure 5E).

Section 8 Paragraph 2: "UMAPing" is not scientifically written.

We have replaced UMAPing with UMAP.

Figure 2 is difficult to interpret, given the small sizes of the images. Align the images, reduce the white space, clearly label the different tissues, add scale bars, increase size, etc. This applies to all figures, except for 3. This will make it possible to review.

All figures have been resized by removing extra space between sections.

Figure 3. There seems to be a change in tissue after section I, so a different diagram would be helpful. SCD has a high abundance in an area that seems to be off of the tissue. Can the authors explain this? Some of the images also appear to be low signal-to-noise. Example spectra in the SI would be helpful, so I can more accurately judge the quality of the data.

We apologize for the discrepancy. All images are from the same sample. We initially cropped the individual image from multiple page PDF plot, then inserted it in Figure 3. Resizing and cropping inconsistency may lead to the small difference in image size. In the revised version, we plot all images in one page, which eliminates the inconsistency.

Figure 3 example pixel data, ratio pixel data, mass spectra and ratio images can be downloaded below:

https://wcm.box.com/s/2d5jch45ar8upjzytljnylt6doewcsqc

eLife Assessment

This study provides valuable information on the single nucleus RNA sequencing transcriptome, pathways, and cell types in pig skeletal muscle in response to conjugated linoleic acid (CLA) supplementation. Based on the comprehensive data analyses, the data are considered compelling and provide new insight into the mechanisms underlying intramuscular fat deposition and muscle fiber remodeling. The study contributes significantly to the understanding of nutritional strategies for fat infiltration in pig muscle.

Joint Public Review:

This study comprehensively presents data from single nuclei sequencing of Heigai pig skeletal muscle in response to conjugated linoleic acid supplementation. The authors identify changes in myofiber type and adipocyte subpopulations induced by linoleic acid at depth previously unobserved. The authors show that linoleic acid supplementation decreased the total myofiber count, specifically reducing type II muscle fiber types (IIB), myotendinous junctions, and neuromuscular junctions, whereas type I muscle fibers are increased. Moreover, the authors identify changes in adipocyte pools, specifically in a population marked by SCD1/DGAT2. To validate the skeletal muscle remodeling in response to linoleic acid supplementation, the authors compare transcriptomics data from Laiwu pigs, a model of high intramuscular fat, to Heigai pigs. The results verify changes in adipocyte subpopulations when pigs have higher intramuscular fat, either genetically or diet-induced. Targeted examination using cell-cell communication network analysis revealed associations with high intramuscular fat with fibro-adipogenic progenitors (FAPs). The authors then conclude that conjugated linoleic acid induces FAPs towards adipogenic commitment. Specifically, they show that linoleic acid stimulates FAPs to become SCD1/DGAT2+ adipocytes via JNK signaling. The authors conclude that their findings demonstrate the effects of conjugated linoleic acid on skeletal muscle fat formation in pigs, which could serve as a model for studying human skeletal muscle diseases.

[Editors' note: the authors have responded to the previous rounds of review: https://doi.org/10.7554/eLife.99790.1.sa1 and https://doi.org/10.7554/eLife.99790.2.sa1]

Author response:

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

Reviewer #1 (Public review):

In this revised manuscript, the authors aim to elucidate the cytological mechanisms by which conjugated linoleic acids (CLAs) influence intramuscular fat deposition and muscle fiber transformation in pig models. They have utilized single-nucleus RNA sequencing (snRNA-seq) to explore the effects of CLA supplementation on cell populations, muscle fiber types, and adipocyte differentiation pathways in pig skeletal muscles. Notably, the authors have made significant efforts in addressing the previous concerns raised by the reviewers, clarifying key aspects of their methodology and data analysis.

Strengths:

(1) Thorough validation of key findings: The authors have addressed the need for further validation by including qPCR, immunofluorescence staining, and western blotting to verify changes in muscle fiber types and adipocyte populations, which strengthens their conclusions.

(2) Improved figure presentation: The authors have enhanced figure quality, particularly for the Oil Red O and Nile Red staining images, which now better depict the organization of lipid droplets (Figure 7A). Statistical significance markers have also been clarified (Figure 7I and 7K).

Thanks!

Weaknesses:

(1) Cross-species analysis and generalizability of the results: Although the authors could not perform a comparative analysis across species due to data limitations, they acknowledged this gap and focused on analyzing regulatory mechanisms specific to pigs. Their explanation is reasonable given the current availability of snRNA-seq datasets on muscle fat deposition in other human and mouse.

Thanks for your suggestion!

(2) Mechanistic depth in JNK signaling pathway: While the inclusion of additional experiments is a positive step, the exploration of the JNK signaling pathway could still benefit from deeper analysis of downstream transcriptional regulators. The current discussion acknowledges this limitation, but future studies should aim to address this gap fully.

Thanks! As we discussed in discussion part, further studies should focus on the downstream transcriptional regulators of JNK signaling pathway on IMF deposition.

(3) Limited exploration of other muscle groups: The authors did not expand their analysis to additional muscle groups, leaving some uncertainty regarding whether other muscle groups might respond differently to CLA supplementation. Further studies in this direction could enhance the understanding of muscle fiber dynamics across the organism.

Thanks for your suggestion! In this study, we mainly focused on the adipocytes, muscles and FAPs subpopulations, which play important roles in lipid deposition. As you suggested, our further study will focus on other subpopulations such as endothelial cells and immune cells.

Reviewer #2 (Public review):

Summary:

This study comprehensively presents data from single nuclei sequencing of Heigai pig skeletal muscle in response to conjugated linoleic acid supplementation. The authors identify changes in myofiber type and adipocyte subpopulations induced by linoleic acid at depth previously unobserved. The authors show that linoleic acid supplementation decreased the total myofiber count, specifically reducing type II muscle fiber types (IIB), myotendinous junctions, and neuromuscular junctions, whereas type I muscle fibers are increased. Moreover, the authors identify changes in adipocyte pools, specifically in a population marked by SCD1/DGAT2. To validate the skeletal muscle remodeling in response to linoleic acid supplementation, the authors compare transcriptomics data from Laiwu pigs, a model of high intramuscular fat, to Heigai pigs. The results verify changes in adipocyte subpopulations when pigs have higher intramuscular fat, either genetically or diet-induced. Targeted examination using cell-cell communication network analysis revealed associations with high intramuscular fat with fibro-adipogenic progenitors (FAPs). The authors then conclude that conjugated linoleic acid induces FAPs towards adipogenic commitment. Specifically, they show that linoleic acid stimulates FAPs to become SCD1/DGAT2+ adipocytes via JNK signaling. The authors conclude that their findings demonstrate the effects of conjugated linoleic acid on skeletal muscle fat formation in pigs, which could serve as a model for studying human skeletal muscle diseases.

Strengths:

The comprehensive data analysis provides information on conjugated linoleic acid effects on pig skeletal muscle and organ function. The notion that linoleic acid induces skeletal muscle composition and fat accumulation is considered a strength and demonstrates the effect of dietary interactions on organ remodeling. This could have implications for the pig farming industry to promote muscle marbling. Additionally, these data may inform the remodeling of human skeletal muscle under dietary behaviors, such as elimination and supplementation diets and chronic overnutrition of nutrient-poor diets. However, the biggest strength resides in thorough data collection at the single nuclei level, which was extrapolated to other types of Chinese pigs.

Weaknesses:

Although the authors compiled a substantial and comprehensive dataset, the scope of cellular and molecular-level validation still needs to be expanded. For instance, the single nuclei data suggest changes in myofiber type after linoleic acid supplementation, but these findings need more thorough validation. Further histological and physiological assessments are necessary to address fiber types and oxidative potential. Similarly, the authors propose that linoleic acid alters adipocyte populations, FAPs, and preadipocytes; however, there are limited cellular and molecular analyses to confirm these findings. The identified JNK signaling pathways require additional follow-ups on the molecular mechanism or transcriptional regulation. However, these issues are discussed as potential areas for future exploration. While various individual studies have been conducted on mouse/human skeletal muscle and adipose tissues, these have only been briefly discussed, and further investigation is warranted. Additionally, the authors incorporate two pig models into their results, but they only examine one muscle group. Exploring whether other muscle groups respond similarly or differently to linoleic acid supplementation would be valuable. Furthermore, the authors should discuss how their results translate to human and pig nutrition, such as the desirability and cost-effectiveness for pig farmers and human diets high in linoleic acid. Notably, while the single nuclei data is comprehensive, there needs to be a statement on data deposition and code availability, allowing others access to these datasets.

Thanks for your suggestion!

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

The authors have discussed and provided some experimental evidence to address the related issues to help justify their conclusions. The reviewer believes that authors should deposit their single-cell sequencing data and code for the broader research community.

Thank you! We have uploaded our raw dataset in the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2021) in National Genomics Data Center (Nucleic Acids Res 2022), China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences and data availability part has been updated (line 575-579).

eLife Assessment

This important study reveals that disrupting fatty acid metabolism in macrophages significantly restricts the growth of Mycobacterium tuberculosis, showing that impaired lipid processing triggers various antimicrobial responses. Overall, the approach is robust, utilizing CRISPR-Cas9 knockout of multiple genes involved in lipid metabolism which yielded convincing data. This work highlights how host lipid metabolism affects the ability of tubercle bacilli to thrive intracellularly, pointing to potential new therapeutic targets.

Reviewer #1 (Public review):

Summary:

This study investigates the role of macrophage lipid metabolism in the intracellular growth of Mycobacterium tuberculosis. By using a CRISPR-Cas9 gene-editing approach, the authors knocked out key genes involved in fatty acid import, lipid droplet formation, and fatty acid oxidation in macrophages. Their results show that disrupting various stages of fatty acid metabolism significantly impairs the ability of Mtb to replicate inside macrophages. The mechanisms of growth restriction included increased glycolysis, oxidative stress, pro-inflammatory cytokine production, enhanced autophagy, and nutrient limitation. The study demonstrates that targeting fatty acid homeostasis at different stages of the lipid metabolic process could offer new strategies for host-directed therapies against tuberculosis.

The work is convincing and methodologically strong, combining genetic, metabolic, and transcriptomic analyses to provide deep insights into how host lipid metabolism affects bacterial survival.

Strengths:

The study uses a multifaceted approach, including CRISPR-Cas9 gene knockouts, metabolic assays, and dual RNA sequencing, to assess how various stages of macrophage lipid metabolism affect Mtb growth. The use of CRISPR-Cas9 to selectively knock out key genes involved in fatty acid metabolism enables precise investigation of how each step-lipid import, lipid droplet formation, and fatty acid oxidation-affects Mtb survival. The study offers mechanistic insights into how different impairments in lipid metabolism lead to diverse antimicrobial responses, including glycolysis, oxidative stress, and autophagy. This deepens the understanding of macrophage function in immune defense.<br /> The use of functional assays to validate findings (e.g., metabolic flux analyses, lipid droplet formation assays, and rescue experiments with fatty acid supplementation) strengthens the reliability and applicability of the results.<br /> By highlighting potential targets for HDT that exploit macrophage lipid metabolism to restrict Mtb growth, the work has significant implications for developing new tuberculosis treatments.

Weaknesses:

The experiments were primarily conducted in vitro using CRISPR-modified macrophages. While these provide valuable insights, they may not fully replicate the complexity of the in vivo environment where multiple cell types and factors influence Mtb infection and immune responses. Yet, I agree that the Hoxb8 in vitro model provides a powerful genetic tool to interrogate host-Mtb interactions using primary macrophages that represent the bone marrow-derived macrophage lineage, instead of using cell lines.

Comments on revisions: The authors have addressed my comment satisfactorily.

Reviewer #2 (Public review):

Summary:

Host-derived lipids are an important factor during Mtb infection. In this study, using CRISPR knockouts of genes involved in fatty acid uptake and metabolism, the authors claim that a compromised uptake, storage or metabolism of fatty acid in the hosts restricts Mtb growth upon infection. The mechanism involves increased glycolysis, autophagy, oxidative stress, pro-inflammatory cytokines and nutrient limitation. The study may be useful for developing novel host-directed approaches against TB.

Strengths:

The study's strength is the use of clean HOXB8-derived primary mouse macrophage lines for generating CRISPR knockouts.

Weaknesses:

The strength of evidence on autophagy and redox stress remains incomplete.

Comments on revisions:

The authors have revised the manuscript and addressed some of the earlier concerns. However, some of the interpretations and responses are incorrect.

Overall, the level of evidence to state the following in the abstract- "Our analyzes demonstrate that macrophages which cannot either import, store or catabolize fatty acids restrict Mtb growth by both common and divergent anti-microbial mechanisms, including increased glycolysis, increased oxidative stress, production of pro-inflammatory cytokines, enhanced autophagy and nutrient limitation" is incomplete.

There is an increase in glycolysis and pro-inflammatory cytokines and, to some extent, oxidative stress. The same can not be said about autophagy. Unfortunately, the authors did not try to establish a direct role of any of these pathways in restricting bacterial growth in the absence of any of the three genes studied.

Major concern:

Autophagy: The LC3 WB does not, by any stretch of the imagination, convince that there is an increase in autophagy flux, as inferred by the authors. Authors correctly cite the "Guidelines to autophagy" paper. Unfortunately, they cite it only selectively to justify their assessment. The LC3II/LC3I ratio indicates the number of autophagosomes present. This ratio can also increase if there is an active block of autophagosome maturation. That's why having BafA1 or CQ controls is important to assess the active autophagosome maturation. However, the authors sidestep this serious consideration by claiming some "pleiotropic impact on Mtb". With BafA1 and CQ, the only assay one needs is to measure the impact on LC3II levels. In the absence of this assay, the evidence supporting the role of autophagy is incomplete.

The main concern regarding autophagy results is that autophagy induction can typically bring down oxidative stress and classically has anti-inflammatory outlay. Thus, increased glycolysis, inflammatory cytokine production and redox stress indicate more towards a potential block in autophagy at the maturation step. This necessitates validation using autophagy flux assays.

Oxidative stress: Showing a representative image for the corresponding representative groups would be more convincing. For example, there is no clarity on whether, in the infected group, there was any staining for Mtb to analyse only the infected cells.

Reviewer #3 (Public review):

Summary:

This study provides significant insights into how host metabolism, specifically of lipids, influences the pathogenesis of Mycobacterium tuberculosis (Mtb). It builds on existing knowledge about Mtb's reliance on host lipids and emphasizes the potential of targeting fatty acid metabolism for therapeutic intervention.

Strengths:

To generate the data, the authors use CRISPR technology to precisely disrupt the genes involved in lipid import (CD36, FATP1), lipid droplet formation (PLIN2) and fatty acid oxidation (CPT1A, CPT2) in mouse primary macrophages. The Mtb Erdman strain is used to infect the macrophage mutants. The study, revealsspecific roles of different lipid-related genes. Importantly, results challenge previous assumptions about lipid droplet formation and show that macrophage responses to lipid metabolism impairments are complex and multifaceted. The experiments are well-controlled and the data is convincing.

Overall, this well-written paper makes a meaningful contribution to the field of tuberculosis research, particularly in the context of host-directed therapies (HDTs). It suggests that manipulating macrophage metabolism could be an effective strategy to limit Mtb growth.

Weaknesses:

None noted. The manuscript provides important new knowledge that will lead mpvel to host-directed therapies to control Mtb infections.

Comments on revisions: The authors have addressed the concerns of the reviewers.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

This study investigates the role of macrophage lipid metabolism in the intracellular growth of Mycobacterium tuberculosis. By using a CRISPR-Cas9 gene-editing approach, the authors knocked out key genes involved in fatty acid import, lipid droplet formation, and fatty acid oxidation in macrophages. Their results show that disrupting various stages of fatty acid metabolism significantly impairs the ability of Mtb to replicate inside macrophages. The mechanisms of growth restriction included increased glycolysis, oxidative stress, pro-inflammatory cytokine production, enhanced autophagy, and nutrient limitation. The study demonstrates that targeting fatty acid homeostasis at different stages of the lipid metabolic process could offer new strategies for host-directed therapies against tuberculosis.

The work is convincing and methodologically strong, combining genetic, metabolic, and transcriptomic analyses to provide deep insights into how host lipid metabolism affects bacterial survival.

Strengths:

The study uses a multifaceted approach, including CRISPR-Cas9 gene knockouts, metabolic assays, and dual RNA sequencing, to assess how various stages of macrophage lipid metabolism affect Mtb growth. The use of CRISPR-Cas9 to selectively knock out key genes involved in fatty acid metabolism enables precise investigation of how each step-lipid import, lipid droplet formation, and fatty acid oxidation affect Mtb survival. The study offers mechanistic insights into how different impairments in lipid metabolism lead to diverse antimicrobial responses, including glycolysis, oxidative stress, and autophagy. This deepens the understanding of macrophage function in immune defense.

The use of functional assays to validate findings (e.g., metabolic flux analyses, lipid droplet formation assays, and rescue experiments with fatty acid supplementation) strengthens the reliability and applicability of the results.

By highlighting potential targets for HDT that exploit macrophage lipid metabolism to restrict Mtb growth, the work has significant implications for developing new tuberculosis treatments.

Weaknesses:

The experiments were primarily conducted in vitro using CRISPR-modified macrophages. While these provide valuable insights, they may not fully replicate the complexity of the in vivo environment where multiple cell types and factors influence Mtb infection and immune responses.

We thank the reviewer for pointing this out. We acknowledge that our in vitro system may indeed not fully replicate the complex in vivo environment given of what is becoming to light of macrophage heterogenous responses to Mtb infection in whole animal models. We do believe, however, that the Hoxb8 in vitro model provides a powerful genetic tool to interrogate host-Mtb interactions using primary macrophages that represent the bone marrow-derived macrophage lineage.

Reviewer #2 (Public review):

Summary:

Host-derived lipids are an important factor during Mtb infection. In this study, using CRISPR knockouts of genes involved in fatty acid uptake and metabolism, the authors claim that a compromised uptake, storage, or metabolism of fatty acid restricts Mtb growth upon infection. Further, the authors claim that the mechanism involves increased glycolysis, autophagy, oxidative stress, pro-inflammatory cytokines, and nutrient limitation. The authors also claim that impaired lipid droplet formation restricts Mtb growth. However, promoting lipid droplet biogenesis does not reverse/promote Mtb growth.

Strengths:

The strength of the study is the use of clean HOXB8-derived primary mouse macrophage lines for generating CRISPR knockouts.

Weaknesses:

There are many weaknesses of this study, they are clubbed into four categories below

(1) Evidence and interpretations: The results shown in this study at several places do not support the interpretations made or are internally contradictory or inconsistent. There are several important observations, but none were taken forward for in-depth analysis.

a) The phenotypes of PLIN2^-/-, FATP1^-/-, and CPT-/- are comparable in terms of bacterial growth restriction; however, their phenotype in terms of lipid body formation, IL1B expression, etc., are not consistent. These are interesting observations and suggest additional mechanisms specific to specific target genes; however, clubbing them all as altered fatty acid uptake or catabolism-dependent phenotypes takes away this important point.

We thank the reviewer for highlighting this. Our focus was on assessing the impact of manipulating lipid homeostasis in macrophages at several stages and the consequences this has on the intracellular growth of Mtb. Throughout the manuscript (abstract, results and discussion), we have continuously emphasized that interfering with lipid handling at several stages in macrophages results in both conserved and divergent antimicrobial responses against intracellular Mtb.

b) Finding the FATP1 transcript in the HOXB8-derived FATP1^-/- CRISPR KO line is a bit confusing. There is less than a two-fold decrease in relative transcript abundance in the KO line compared to the WT line, leaving concerns regarding the robustness of other experiments as well using FATP1^-/- cells.

CRISPR-Cas9 targeting of genes with single sgRNAs as is the case with our mutants generates insertions and deletions (INDELs) at the CRISPR cut site. These INDELs do not block mRNA transcription totally, and this is widely reported in the field.  Because of this, quantitative RT-PCR or RNA-seq methods are not routinely used to verify CRISPR knockouts as they are not sensitive enough to identify INDELs. We provide INDEL quantification and knockout efficiencies by ICE analysis in supplemental file 1 for all the mutants used in the study. We also demonstrate protein depletion by western blot and flow cytometry for all the mutants (Figure 1 - figure supplement 1). Only mutants with greater than >90% protein depletion were used for subsequent characterization.

c) No gene showing differential regulation in FATP^-/- macrophages, which is very surprising.

We assume the reviewer is referring to the Mtb transcriptome response in FATP1^-/- macrophages, which we agree was unexpected.  However, we saw a significant compensatory response in the host cell (at transcriptional level) in FATP1^-/- macrophages as evidenced by an upregulation of other fatty acid transporters (Figure 5 - figure supplement 1, now Figure 6 - figure supplement 1). We believe that these compensatory responses could, in part, alleviate the stresses the bacteria experience within the cell. We discuss this point in the manuscript.

d) ROS measurements should be done using flow cytometry and not by microscopy to nail the actual pattern.

We thank the reviewer for the suggestion. However, confocal imaging is also widely used to measure ROS with similar quantitative power and individual cell resolution (PMID: 32636249, 35737799).

(2) Experimental design: For a few assays, the experimental design is inappropriate

a) For autophagy flux assay, immunoblot of LC3II alone is not sufficient to make any interpretation regarding the state of autophagy. This assay must be done with BafA1 or CQ controls to assess the true state of autophagy.

We would like to point out that monitoring LC3I to LC3II conversion by western blot, confocal imaging of LC3 puncta and qPCR analysis of autophagy related genes are all validated assays for monitoring autophagic flux in a wide variety of cells. We refer the reviewer to the latest extensive guidelines on the subject (PMID: 33634751). Furthermore, Bafilomycin A and chloroquine are not specific inhibitors of autophagy and therefore are of limited value as controls. BafA is an inhibitor of the proton-ATPase apparatus and can indirectly impact autophagy through activity on the Ca-P60A/SERCA pathway. Chloroquine impacts vacuole acidification, autophagosome/lysosome fusion and slows phagosome maturation. So, while BafA and chloroquine will reduce autophagy; their effects are pleotropic and their impact on Mtb is unknown.

b) Similarly, qPCR analyses of autophagy-related gene expression do not reflect anything on the state of autophagy flux.

See our response above.

(3) Using correlative observations as evidence:

a) Observations based on RNAseq analyses are presented as functional readouts, which is incorrect.

We are not entirely sure where we used our RNA-seq data sets as functional readouts. We used our transcriptome data to provide a preliminary identification of anti-microbial responses in the mutant macrophages infected with Mtb and we mention this at the beginning of the RNA-seq results sections. Where applicable, we followed up and confirmed the more compelling RNA-seq data either by metabolic flux analyzes, qPCR, ROS measurements, and quantitative imaging.

b) Claiming that the inability to generate lipid droplets in PLIN2^-/- cells led to the upregulation of several pathways in the cells is purely correlative, and the causal relationship does not exist in the data presented.

It was not our intention to infer causality. We have re-written the beginning of the sentence, and it now starts with “Meanwhile, Mtb infection of PLIN2^-/- macrophages led to upregulation” which hopefully eliminates any association to causality.

(4) Novelty: A few main observations described in this study were previously reported. That includes Mtb growth restriction in PLIN2 and FATP1 deficient cells. Similarly, the impact of Metformin and TMZ on intracellular Mtb growth is well-reported. While that validates these observations in this study, it takes away any novelty from the study.

To the best of our knowledge, Mtb growth restrictions in PLIN2 and FATP1 deficient macrophages have not been reported elsewhere. To the contrary, PLIN2 knockout macrophages obtained from PLIN2 deficient mice have been reported to robustly support Mtb replication (PMID: 29370315). We extensively discuss these discrepancies in the manuscript. We also discuss and cite appropriate references where Mtb growth restriction for similar macrophage mutants have been reported (CD36^-/- and CPT2^-/-). Our aim was to carry out a systematic myeloid specific genetic interference of fatty acid import, storage and catabolism to assess the effect on Mtb growth at all stages of lipid handling instead of focusing on one target. In the chemical approach, we used TMZ and Metformin deliberately because they had already been reported as being active against intracellular Mtb and we wished to place our data in the context of existing literature.  These studies have been referenced extensively in the text.

(5) Manuscript organisation: It will be very helpful to rearrange figures and supplementary figures.

New figures have been added, and existing ones have been re-arranged where necessary. See our responses to recommendations for authors.

Reviewer #3 (Public review):

Summary:

This study provides significant insights into how host metabolism, specifically lipids, influences the pathogenesis of Mycobacterium tuberculosis (Mtb). It builds on existing knowledge about Mtb's reliance on host lipids and emphasizes the potential of targeting fatty acid metabolism for therapeutic intervention.

Strengths:

To generate the data, the authors use CRISPR technology to precisely disrupt the genes involved in lipid import (CD36, FATP1), lipid droplet formation (PLIN2), and fatty acid oxidation (CPT1A, CPT2) in mouse primary macrophages. The Mtb Erdman strain is used to infect the macrophage mutants. The study, reveals specific roles of different lipid-related genes. Importantly, results challenge previous assumptions about lipid droplet formation and show that macrophage responses to lipid metabolism impairments are complex and multifaceted. The experiments are well-controlled and the data is convincing.

Overall, this well-written paper makes a meaningful contribution to the field of tuberculosis research, particularly in the context of host-directed therapies (HDTs). It suggests that manipulating macrophage metabolism could be an effective strategy to limit Mtb growth.

Weaknesses:

None noted. The manuscript provides important new knowledge that will lead mpvel to host-directed therapies to control Mtb infections.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

The study presents compelling and well-supported conclusions based on a solid body of evidence. However, the clarity of several figures could be improved for better understanding.

(1) In Figure 1, panels B and C are referenced incorrectly in the text.

We thank the reviewer for identifying the error. This has now been corrected

(2) Figures 2 and S2 would benefit from being combined or reorganized to display the data related to infected and uninfected cells together, making it easier for the reader to interpret.

We thank the reviewer for the suggestion. However, we believe that combining the two figures would further complicate the merged figure making it even more difficult to interpret. We decided to highlight the mutant macrophage’s responses upon Mtb infection in Figure 2 and put the uninfected data sets in supplementary information given that the OCR and ECAR trends were similar and as expected in both infected and uninfected states.

(3) Figure 3 is mislabeled, with four panels shown in the figure, but only panels A and B are mentioned in both the text and the figure legend.

We thank the reviewer for the observation. Figure 3 has been extensively revised. We have included new blots, statistical comparisons and a corresponding new supplementary figure (Figure 3 - figure supplement 1). We have verified that the figure panels are labelled correctly and appropriately referenced in the manuscript text.

(4) Figure 5 is overly complex and difficult to interpret. Simplifying the figure, possibly by reducing the amount of data or breaking it into more digestible parts, would enhance its readability.

We thank the reviewer for the suggestion. We have separated the figure into two parts which are now Figure 5 for the PCA and Venn diagrams and Figure 6 for the pathway enrichment figure panels. We have increased the resolution of both figures in the revised manuscript to improve readability.

(5) Panel 6A is not particularly informative and could either be omitted with a more detailed explanation provided in the text, or replaced with a clearer visual representation, such as Venn diagrams, to improve data visualization.

We thank the reviewer for the suggestion. We have removed Figure 6A given that detailed explanation of the panel is already available in the manuscript text.

(6) Additionally, on line 309, the word "to" is missing before "generate".

We thank the reviewer for identifying this. This sentence has now been re-written to address some unintended inferences of causation in line with recommendations from reviewer 2.

Reviewer #2 (Recommendations for the authors):

(1) Manuscript Organisations: The manuscript is very poorly organised. Supplemental figures are labelled very unconventionally, and that creates much confusion in following the manuscript. Some of the results in the supplementary figures could be easily kept in the main figures, as it is difficult to compare plots between the main figures and the supple figures. The results of RNAseq experiments are impossible to follow with very small fonts. Overall, the figures are very casually organised and can certainly be improved.

We would like to clarify that supplemental figures are labelled and organized as is in line with the eLife formatting of supplemental figures. We deliberately put some redundant figures like Figure 2 - figure supplement 1 in supplementary information (see our response to reviewer 1 recommendations on the same). We have split the RNA-seq Figure 5 into two separate figures (now Figure 5 and 6) and increased their resolution to improve readability.

(2) Figure 3: Among the KO lines, only PLIN2^-/- had a higher HIF1a level before infection. Infection surely leads to higher levels across the three cases.

We have generated replicate western blots and provide statistical quantitation for both HIF1a, AMPK and pAMPK. Figure 3 has now been revised extensively, replicate blots are in Figure 3 - figure supplement 1. We have updated the text to reflect the reviewer observation which was also consistent with our statistical quantification.

(3) pAMPK blots are of very poor quality. Without quantification, the trend mentioned in the text is not clearly visible.

We have provided two more replicate blots for AMPK/pAMPK and provide statistical quantification as described above.

(4) Line 230: Regarding autophagy flux, neither the data suggest what is interpreted nor is this experiment correctly done. LC3 WB and autophagy gene qPCR: Unfortunately, LC3 WB, the way it was done, does not tell anything about the state of autophagy in these cells. A very mild LC3II increase is noted in CPT2^-/- cells upon infection; the rest of the others do not show any change. This assay is not done correctly. To interpret LC3II WB, one needs to include the Bafilomycin A1 control, usually +Baf and -Baf run in the adjacent wells in the gel. Similarly, qPCR results are not indicative of any increase in autophagy. Regulation of ATG7, MAP1LC3B, and ULK1 is more at the post-translational level than the transcriptional level.

We have provided an additional replicate blot together with statistical quantification of LC3II/LC3I ratios in the revised Figure 3 - figure supplement 2. Our quantifications remain consistent with our prior assertations in the manuscript text. See our response in the public review section concerning autophagy assays and the use of Baf or chloroquine as controls.

(5) Exogenous oleate fails to rescue the Mtb icl1-deficient mutant in FATP1^-/-, PLIN2^-/- and CPT2^-/- macrophages: this result is confusing. Lipid uptake and metabolism have been the central players so far; however, here, the phenotypes of FATP1 and CPT2 in terms of lipid body accumulation are very distinct. Therefore, the assessment that Mtb growth inhibition is due to factors other than limited access to fatty acid is not consistent with the theme of the study.

Nutrient limitation is a distinct transcriptional signature of Mtb, at least in PLIN2^-/- macrophages (Figure 7). We used the oleate supplementation assay with the Mtb Dicl1 mutant to assess whether nutrient restriction was the sole anti-microbial pathway against Mtb in the knockout macrophages. This would have been the case (to a certain extent) if the growth of the Mtb Dicl1 mutant was rescuable upon addition of exogenous oleate in the knockout macrophages. Our data clearly shows that this is not the case and that in addition to nutrient limitation, interference with lipid processing results in several other macrophage anti-microbial responses against the bacteria. We extensively discuss these points in the abstract, results and discussion sections of the manuscript.

(6) Line 309: "Meanwhile, inability generate lipid droplets in Mtb infected PLIN2^-/- macrophages led to upregulation in pathways involved in ribosomal biology, MHC class 1 antigen presentation, canonical glycolysis, ATP metabolic processes and type 1 interferon responses (Figure 5C, Supplementary file 3)." This is just a correlative observation. However, it is mentioned here as a causal mechanism.

We have revised this sentence to remove any unintended inference of causation.

(7) IL-1b is upregulated in FATP-/- macrophages, no effect in CPT2^-/- macrophages, but downregulated in PLIN2^-/- macrophages. Moreover, this effect is very transient, and by 24 hours, all these differences are lost. This suggests the mechanism of action, as their pro-bacterial function shown in Figure 1, is very distinct for different proteins, and FA metabolism is probably not the common denominator across these phenotypes.

We agree with the reviewer, and we extensively discuss this in the manuscript text (results and discussion). Clearly, they are shared anti-microbial responses across the mutants, but they are also points of divergence. We would like to further clarify that pro-inflammatory responses (IL-1b or IFN-B) in Mtb infected macrophages show a biphasic early upregulation (up to 8 hours of infection) followed by a rapid resolution phase (24-48 hours post infection). This is well reported in the literature (PMID: 30914513). It is common for pro-inflammatory gene expression differences to be temporary lost during the resolution phase (PMID: 30914513, 39472457). IL-1b expression profiles return to the 4-hour equivalent profile in Mtb infected FATP1^-/- and PLIN2^-/- macrophages 4 days post infection (Figure 6A, Figure 6 - figure supplement 2B, Supplementary file 2)

(8) It is very surprising that FATP-/- macrophages do not show any change in Mtb gene expression. The robustness of this experiment and analysis appears doubtful, given that the phenotype in terms of bacterial growth was clean.

See our response to this comment in the public reviews section

(9) Figure 5, Supplementary Figure 1: Among the FA transporters, authors also show data for FATP1. I am surprised to see FATP1 expression levels in the FATP1^-/- cells. This puts into doubt every dataset using FATP-/- cells in this study.

See our response to this comment in the public reviews section

(10) Unfortunately, with the kind of evidence presented, it is far-fetched to claim that PLIN2^-/- macrophages restrict Mtb growth by increasing ROS production. There is no evidence for this statement. The MFI units in Figure 6, Supplementary 1 are too small to extract meaningful interpretations. Moreover, the data appears to be arrived at by combining multiple technical replicates. Usually, flow cytometry data are more reliable for CellROX assays. Microscopy is not the technique of choice for this assay.

We would like to point out that MFIs are arbitrary units set to predetermined reference points. In our case, the reference was background fluorescence in CellROX unstained cells and cells stained with CellROX equivalent fluorophore conjugated isotype antibodies. We are not entirely sure what the reviewer means by “small” in these contexts. And the data is not entirely from technical replicates. Reported MFIs are from three independent repeats with MFI reads of at least 30 cells per replicate. We have added this clarification in Figure 6 - figure supplement 1 legend, now Figure 7 - figure supplement 1. See our response in the public reviews section on the use of confocal microcopy to image and quantify ROS. Furthermore, the Mtb transcriptional response in PLIN2^-/- and CPT2^-/- macrophages is clearly indicative of increased oxidative stresses (Figure 7).

(11) The CFU results with Metformin and TMZ are on the expected lines, as published earlier by others. FATP1 In data is good and aligned with the knockout phenotype.

We thank the reviewer for the note.

(12) Western blots, when interpreted for quantitative differences, must be quantified, and data should be represented as plots with statistical analysis.

Replicate blots have been provided and statistical quantifications performed.

eLife Assessment

This manuscript establishes a mathematical model to estimate the key parameters that control the repopulation of planarian stem cells after sublethal irradiation as they undergo fate-switching as part of their differentiation and self-renewal process. The findings are important for future investigation of stem cell division in planarians and have implications for analyzing stem cell biology in other systems. The methods are convincing, integrating modeling with perturbations of key transcription factors known to be critical for cell fate decisions, but the authors have only shown that this is the case for a small number of stem cell types.

Reviewer #1 (Public review):

Summary:

This is a very creative study using modeling and measurement of neoblast dynamics to gain insight into the mechanism that allows these highly potent cells to undergo fate-switching as part of their differentiation and self-renewal process. The authors estimate growth equation parameters for expanding neoblast clones based on new and prior experimental observations. These results indicate neoblast likely undergo much more symmetric self-amplifying division than loss of the population through symmetric differentiation, in the case of clone expansion assays after sublethal irradiation. Neoblasts take on multiple distinct transcriptional fates related to their terminally differentiated cell types, and prior work indicated neoblasts have a high plasticity to switch fates in way linked to cell cycle progression and possibly through a random process. Here, the authors explore the impact of inhibition of key transcription factors defining such states (ie "fate specifying transcription factors", FSTFs) plus measurement and modeling in the clone expansion assay, to find that inhibition of factors like zfp1 likely cause otherwise zfp1-fated neoblasts to fail to proliferate and differentiation, without causing compensatory gains in other lineages. A mathematical model of this process assuming that neoblasts do not retain a memory of prior states while they proliferate and transition across specified states can mimic the experimentally determined decreased sizes of clones following inhibition of zfp1. Complementary approaches to inhibit more than one lineage (muscle plus intestine) supports the idea that this is a more general process in planarian stem cells. These results provide an important advance for understanding the fate-switching process and its relationship to neoblast growth.

Overall I find the evidence very well presented and the study compelling, and offers an important new perspective on the key properties of neoblasts. I have some comments to clarify the presentation and significance of the work.

Comments on revisions:

In this revised version, the authors nicely address all of my comments and I find the work makes a strong case for its main conclusions.

Reviewer #2 (Public review):

Summary:

Cell cycle duration and cell fate choice are critical to understanding the cellular plasticity of neoblasts in planarians. In this study, Tamar et al. integrated experimental and computational approaches to simulate a model for neoblast behaviors during colony expansion.

Strengths:

The finding that "arresting differentiation into specific lineages disrupts neoblast proliferative capacities without inducing compensatory expression of other lineages" is particularly intriguing. This concept could inspire further studies on pluripotent stem cells and their application for regenerative biology.

Comments on revisions:

The authors have addressed all of my comments and concerns.

Author response:

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

Public reviews

Reviewer #1 (Public review):

Overall I find the evidence very well presented and the study compelling. It offers an important new perspective on the key properties of neoblasts. I do have some comments to clarify the presentation and significance of the work.

We thank the reviewer for the positive feedback and plan to improve the presentation of the work.

Reviewer #2 (Public review):

However, the absence of a cell-cell feedback mechanism during colony growth and the likelihood of the difference needs to be clarified. Is there any difference in interpreting the results if this mechanism is considered?

We will improve the description of the model assumptions and the interpretation of the data on the basis of these assumptions.

Although hnf-4 and foxF have been silenced together to validate the model, a deeper understanding of the tgs-1+ cell type and the non-significant reduction of tgs-1+ neoblasts in zfp-1 RNAi colonies is necessary, considering a high neural lineage frequency.

We will improve the analysis of this result in light of the experimentally determined frequency of the tgs-1+ neoblast population.

Recommendations for the authors

Reviewing Editor Comments:

After consultation, we have compiled a list of the key changes to be made to the manuscript, along with reviewer-specific recommendations to follow.

(1) Include a section that explicitly describes the assumptions and limitations of the study, particularly with respect to the following assumptions:

We thank the reviewers for the comment. We added a description of the model assumptions in the methods section “Assumptions underlying neoblast colony growth model”.

a) All known types of specialized neoblasts cycle at the same rate (see points from Reviewer 1).

We thank the reviewers for the comment. The current data used to estimate τ (Lei et al., Dev Cell, 2016) does not allow the direct estimation of individual cycling behaviors. Consequently, we assume that all specialized neoblasts cycle at the same average rate, a simplification supported by the model's accurate prediction of colony growth.

b) The assumption that any FSTF-like gene would behave like zfp1 or foxF and hnfA genes. The manuscript does not mention that there may be fundamental differences among these different FSTFs that could be uncovered by future work. A strong addition to the paper would be to test other epithelial genes (e.g. p53, chd4, egr5) to show reproducible behavior within a single lineage.

We thank the reviewers for the comment. Colony size reduction following inhibition of Smed-p53 and failure to produce epidermal progenitors is strongly supported by previous analysis (Wagner et al., Cell Stem Cell, 2012). We refer to this observation in the paper in the section titled: “Inhibition of zfp-1 does not induce overexpression of other lineages in homeostasis”. We added the following sentence to the discussion (Line 460-462): Interestingly, suppression of Smed-p53, a TF expressed in neoblasts and required for epidermal cell production, has resulted in a similar reduction in colony size (Wagner et al., Cell Stem Cell, 2012).

Of note, Chd4 expression is not limited to specialized neoblasts or to a specific lineage (Scinome et al., Development, 2010), and therefore its inhibition likely has a more complex outcome than an effect on a single lineage. Furthermore, egr-5 is not expressed in neoblasts (Tu et al, eLife, 2015), making this experimental condition more challenging to examine in the context of neoblast colonies at the time points assessed in this study.

c) The fact that the data used to feed the model relies on radiated animals which are likely to have altered cell cycle rates compared to unirradiated animals (see comment by Reviewer 1). Of note, the model predicts a steady increase in colony size, but colony size does not change between 9dpi and 12dpi.

We thank the reviewers for the comment. The colony size in control animals increased between 9 and 12 dpi (Fig 3B), as predicted by the model. In zfp-1 (RNAi) animals, the median colony size has also increased over this period, at a slower rate, which we attribute to the increase in q. We attribute the unchanged average colony size to an increase in the frequency of cells failing to proliferate, because of selection of a fate they cannot fully differentiate into.

d) In light of both reviewers' comments about colony expansion vs. feedback, the authors should discuss how predicted changes to division frequencies might change as homeostasis is reached, or explain how their model accounts for the predicted rate differences under homeostatic conditions in which overall neoblast numbers do not change. Can the model estimate when this transition might occur?

We thank the reviewers for the comment. Our colony assays are constrained by the animals survival following sub-total irradiation (16 to 20 days). In this timeframe, the neoblast population is overwhelmingly smaller in comparison to non-irradiated animals. Therefore, the animals do not reach homeostasis during the experiment, and the model does not allow to estimate the time the system would need to return to homeostasis.

(2) In Figure 2D, the assumption is that these adjacent smedwi-1+ cells are sisters. Previous data analyzing this relied on EdU or H3P staining to show a shared division history. When these images were collected is therefore extremely critical to include (the methods suggest 7, 9, or 12 days). The authors should justify why they believe that these adjacent cells are derived from a single neoblast that has divided only once.

We thank the reviewers for the comment. The images were collected at 7 dpi. We modified the figure legend and the associated methods to include this information. At this early time point, smedwi-1+ cell dyads are spatially separated from other neighboring cells, suggesting that they are the product of a single cell division. Importantly, our data is in complete agreement with previous estimates of symmetric renewal division rate (Raz et al., Cell Stem Cell, 2021; Lei et al, Developmental Cell, 2016).

(3) Clarify the wording 'pre-selected' in the abstract as described by Reviewer 1.

We thank the reviewers for the comment, and for clarity we replaced the wording “pre-select” with “select”. 

(4) Experimental details that are important to the interpretation should be added. For example, how is belonging to a colony defined? This is important because some of the data (e.g. Figure S1A: similar numbers of smedwi-1+ cells are observed at 2dpi and 4dpi, but 4dpi is considered a colony whereas 2dpi is not). The timing of quantification should be included in each figure (it is missing in Figure S2, and Figure 3C and 3D). How the authors distinguish biological vs technical replicates is not mentioned.

We thank the reviewers for the comment. Subtotal irradiation may result in formation of a spatially-isolated cluster of neoblasts that is not distributed throughout the animal (Wagner et al., Science, 2011). This localized cluster of neoblasts is defined as a neoblast colony (Wagner et al., Science, 2011; Wagner et al., Cell Stem Cell, 2012). The small number of high smedwi-1+ cells observed at 4 dpi in our experiments aligns with this definition (Fig S1A). By contrast, the low smedwi-1 expression detected across the animal 2 dpi does not fit this definition and likely reflects remnants of dying neoblasts resulting from irradiation. The following text was added to the figure legend: “isolated cells expressing low levels of smedwi-1+ were scattered in the planarian parenchyma, likely reflecting remnants of dying neoblasts”.

(5) Figure 5F appears to use SMEDWI-1 antibody (based on capital letters and increased signal in the brain). Is this the case? The methods do not mention the use of a SMEDWI-1 antibody, and the text indicates that these are progenitors, but SMEDWI-1 protein is well known to not mark neoblasts. If the antibody was used, the authors should not claim that these are neoblasts.

We thank the reviewers for the comment. The SMEDWI-1 antibody used in the experiments described in Figure 5F indeed labels neoblasts and their progeny (Guo et al., Developmental cell, 2006). The methods section “Immunofluorescence combined with FISH” details the labeling procedure, which combines FISH and IF using this antibody.

All microscopy images are difficult to see. Perhaps this is because they are formatted as CMYK images. They should be converted to RGB format to make them appear less dull.

We thank the reviewer for the comment. Improved version of the figures has now been uploaded.

The terminology used in Figure 5 to describe upregulation should not be "overexpression".  We thank the reviewers for the comment.

We changed the terminology to “upregulated”.

Reviewer #1 (Recommendations for the authors):

I think the authors should include a section that explicitly lays out the assumptions and limitations of the study. For example, I believe that determining tau requires assuming that all different types of specialized neoblasts cycle at the same rates. Also there is the assumption that any FSTF-like gene would behave like zfp1 or foxF and hnfA genes. It seems to remain possible that a future study could find that a subset of FSTFs might indeed exert "either/or" decisions in fating, just not the particular genes under investigation here.

We thank the reviewer for the comment. We added a description of the model assumptions in the methods section.

In the abstract, the wording "pre-selected" is somewhat puzzling to me. I would interpret a preselection as a process that defines the next specified state prior to its manifestation. Instead, and as I understand the authors argue this as well, the study provides good evidence that the determination mechanism is random in that subsequent neoblast choices do not likely depend on prior states. So I would suggest changing that wording.

We thank the reviewer for the comment. We replaced “pre-select” with “select”

Is it possible to determine the uncertainty in measuring tau the cell cycle time and would this have an impact on subsequent modeling?

We thank the reviewers for the comment. The current data that was used to estimate tau (Lei et al., Dev Cell, 2016) does not allow us to directly estimate the uncertainty in measuring τ.

For lines 154-164 I would suggest doing a little more to explicitly write out the logic of determining the growth constants within the main text and not just in methods, for ease of reading.

We thank the reviewer for the comment, and added explanations for how we determined the growth constant in the text. The text now reads (lines 160-166): “Considering an average cell cycle length of 29.7 hours, we calculated the value of q using the following approach: the probabilities of all cell division outcomes must sum to 1. Our experimental data showed that symmetric renewal (p) and asymmetric division (a) occur at equal rates (i.e., p = a). By fitting these parameters to the experimental data, we determined that the difference between the probabilities of symmetric renewal and symmetric differentiation (i.e., p - q) was = 0.345 (Fig 2E, S1D-E). Therefore, with these criteria, we estimated the probabilities of cell division outcomes in the colony as p = 0.45, a = 0.45, and q = 0.1 (Fig 2G; Methods).”

Line 192 why does post-mitotic progeny number linearly relate to neoblast number? In clones, a change in q has an exponential effect. I feel like I am missing something.

We thank the reviewer for the comment. In colonies, 50% of cell divisions result in the production of post-mitotic progeny (asymmetric division). Therefore, the number of produced progenitors in a given cell cycle is linearly correlated with the number of neoblasts. This statement is in line with previous analysis of planarian colony size (Wagner et al., Cell Stem Cell, 2012).

Line103 it also seems possible, although less likely, that the specified state is not fixed within a given cell cycle and could be that cells that try to switch into zeta-neoblasts mid-cell cycle arrest in proliferation etc just for that time.

We thank the reviewer for the comment and agree that this is a possibility. However, our observations suggest that incorporating this factor into the model is unnecessary for accurately predicting colony size.

In terms of the feedback mechanism proposed to operate in homeostasis, I think in the case of zfp-1 it is quite likely that loss of epidermal differentiation results in wound responses (this phenomenon has been documented in egr-5 RNAi in Tu et al 2015 I believe). This could play out differently in the clone assay because the effects of sublethal irradiation on this process would predominate in both control versus zfp1(RNAi) conditions.

We thank the reviewer for the comment. Our RNA-seq analysis following zfp-1 inhibition did not show overexpression of injury-induced genes at an early time point (6 days; Fig. 5B-C). However, an increase in cycling cells was detected much earlier via EdU labeling (3 days; Fig. 5D). In the case of egr-5 suppression, Tu et al. analyzed injury-induced gene expression at a later stage (21 days of RNAi), where they found significant epidermal defects (see Fig. 5C in Tu et al.). We agree that sublethal irradiation effects likely predominate in colony analysis for both control and zfp-1 (RNAi) animals. In homeostasis, additional factors likely influence cell proliferation and differentiation.

It seems likely that some of the differences noted between homeostasis versus clone growth could ultimately arise from the different growth parameters under each setting. Could the rate parameters be estimated from prior data in homeostasis as well? It seems to me that with the framework the authors use, homeostasis must involve a net zero change to neoblast abundance (also shown by Wagner 2011 by the sigmoidal curve of neoblast abundance at the endpoint of clone expansion). Therefore, in these conditions p=q by definition. Experimental evidence from Lei 2016 (Figure S7M) suggests asymmetric divisions and symmetric renewing divisions are about equally abundant (5/12 41% sym renewing vs 7/12 69% asymmetric renewing). Therefore, under homeostasis, there would be an estimated p=q=0.3 and a=0.4. Compared to clone growth conditions then, in homeostasis, it seems that roughly the rate of symmetric renewal decreases and the rate of symmetric differentiation also increases. I wonder, could this kind of difference potentially account for the differences between homeostasis versus clone expansion settings? It is also worth noting that the clone expansion context has been used as a sensitized genetic background for identifying effects of gene inhibition on neoblast self-renewal, so perhaps the reason this works is that the rates of selfrenewal are relatively less in homeostasis so that clone expansion represents a case where there is greater demand for self-renewal.

We thank the reviewer for the comment. We agree that under homeostatic conditions, where the population size remains stable, the average probability of symmetric renewal matches the average probability of symmetric differentiation or elimination. By contrast, during colony expansion, the probability of symmetric renewal exceeds that of symmetric differentiation or elimination. The differences in response to a lineage block between homeostasis and colony expansion can have multiple interpretations. However, data from homeostatic animals does not permit the analysis of individual neoblasts or their specific responses to a lineage block. Consequently, we cannot determine whether the proliferative response following the lineage block during homeostasis is a direct response to the lineage block or an indirect effect resulting from changes in other neoblasts. We discuss these possibilities further in lines 472 - 484.

In terms of the memory effect, I recall some arguments presented in the Raz 2021 study that were consistent with a slight memory for neoblast specification being retained. I believe this was a minor point from detecting a slightly higher likelihood of identifying 2-cell clones that both took on prog1+ identity compared to the population average. If this is the case, it may be worth the authors commenting on reconciling those observations with their model.

We thank the reviewer for their comment. Raz et al. (Cell Stem Cell, 2021) reported that in the asymmetric division of a zeta-neoblast, which generates a prog-2+ cell and a neoblast, there was a slightly higher observed frequency of zfp-1 expression in the neoblast compared to the expected rate (Expected: 32%, Observed: 44%). This small increase may reflect a mild memory effect, experimental variability, or both. However, statistical analysis using Fisher's exact test yielded a non-significant p-value (p = 0.1), suggesting that this difference could be attributed to experimental variability. Other data from Raz et al., such as lineage representation in early colonies, also did not show significant memory effects, indicating that any such effects, if present, are minimal and difficult to detect. Therefore, while we do not, and cannot, rule out the presence of minor memory effects, we expect that effects of this magnitude will have minimal impact on our model.

Reviewer #2 (Recommendations for the authors):

Figure 2C and 2D:

Please provide the specific time points for the data presented.

We thank the reviewer for the comment. The information was added to the figure legend.

Colony growth and homeostasis:

It would be beneficial to estimate a time point at which colony growth transitions to a model with a cell-cell feedback mechanism, similar to that observed in homeostasis. This would help in understanding the dynamics and timing of these processes.

We thank the reviewers for the comment. Our colony assays were constrained by the animals survival following sub-total irradiation (16 to 20 days). Neoblast numbers are substantially reduced compared to unirradiated animals, preventing us from determining the time point at which homeostasis is achieved.

Methods:

μl should be μL  

The text was changed accordingly.

Line 526: H2O should be H2O

The text was changed accordingly.

eLife Assessment

This important and well-written study uses functional neuroimaging in human observers to provide compelling evidence that activity in the early visual cortex is suppressed at locations that are frequently occupied by a task-irrelevant but salient item. This suppression appears to be general to any kind of stimulus and also occurs in advance of any item actually appearing. The work will be of great interest to psychologists and neuroscientists examining attention, perception, learning and prediction.

Reviewer #1 (Public review):

Summary:

The authors investigated if/how distractor suppression derived from statistical learning may be implemented in early visual cortex. While in a scanner, participants conducted a standard additional singleton task in which one location more frequently contained a salient distractor. The results showed that activity in EVC was suppressed for the location of the salient distractor as well as for neighbouring neutral locations. This suppression was not stimulus specific - meaning it occurred equally for distractors, targets and neutral items - and it was even present in trials in which the search display was omitted. Generally, the paper was clear, the experiment was well-designed, and the data are interesting.

The authors addressed all of my concerns and the revised manuscript will make a beautiful addition to the literature.

Reviewer #2 (Public review):

The authors of this work set out to test ideas about how observers learn to ignore irrelevant visual information. Specifically, they used fMRI to scan participants who performed a visual search task. The task was designed in such a way that highly salient but irrelevant search items were more likely to appear at a given spatial location. With a region-of-interest approach, the authors found that activity in visual cortex that selectively responds to that location was generally suppressed, in response to all stimuli (search targets, salient distractors, or neutral items), as well as in the absence of an anticipated stimulus.

Strengths of the study include: A well-written and well-argued manuscript; clever application of a region of interest approach to fMRI design, which allows articulating clear tests of different hypotheses; careful application of follow-up analyses to rule out alternative, strategy-based accounts of the findings; tests of the robustness of the findings to detailed analysis parameters such as ROI size; and exclusion of the role of regional baseline differences in BOLD responses. The main findings are enhanced by supplementary analyses that distinguish between the responses of early visual areas.

The study provides an advance over previous studies, which identified enhancement or suppression in visual cortex as a function of search target/distractor predictability, but in less spatially-specific way. It also speaks to open questions about whether such suppression/enhancement is observed only in response to the arrival of visual information, or instead is preparatory, favouring the latter view. These questions have been at the heart of theoretical debates in this literature on how distractor suppression unfolds in the context of visual search.

Author response:

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

eLife Assessment

This well-written report uses functional neuroimaging in human observers to provide convincing evidence that activity in the early visual cortex is suppressed at locations that are frequently occupied by a task-irrelevant but salient item. This suppression appears to be general to any kind of stimulus, and also occurs in advance of any item actually appearing. The work in its present form will be valuable to those examining attention, perception, learning and prediction, but with a few additional analyses could more informatively rule out potential alternative hypotheses. Further discussion of the mechanistic implications could clarify further the broad extent of its significance. 

We thank the editor and the reviewers for the positive evaluation of our manuscript and the thoughtful comments. Below we provide a detailed point-by-point reply to the reviewers’ comments.

In addition to addressing the reviewers' comments, we have improved the figure legends by explicitly describing the type of error bars depicted in the figures, information which was previously only listed in the Materials and Methods section. Specifically, the statement: “Error bars denote within-subject SEM” was added to several figures, as applicable. We believe that briefly reiterating this information in the figure legends enhances clarity and enables readers to interpret the results more accurately and efficiently. We also updated our code and data sharing statement, as well as opened the repository for the public: “Analysis and experiment code, as well as data required to replicate the results reported in this manuscript are available here: https://doi.org/10.17605/OSF.IO/G4RXV. Raw MRI data is available upon request.”

Public Reviews

Reviewer #1 (Public review): 

Summary: 

The authors investigated if/how distractor suppression derived from statistical learning may be implemented in early visual cortex. While in a scanner, participants conducted a standard additional singleton task in which one location more frequently contained a salient distractor. The results showed that activity in EVC was suppressed for the location of the salient distractor as well as for neighbouring neutral locations. This suppression was not stimulus specific - meaning it occurred equally for distractors, targets and neutral items - and it was even present in trials in which the search display was omitted. Generally, the paper was clear, the experiment was well-designed, and the data are interesting. Nevertheless, I do have several concerns mostly regarding the interpretation of the results. 

(1) My biggest concern with the study is regarding the interpretation of some of the results. Specifically, regarding the dynamics of the suppression. I appreciate that there are some limitations with what you might be able to say here given the method but I do feel as if you have committed to a single interpretation where others might still be at play. Below I've listed a few alternatives to consider. 

We agree with the reviewer that there are important alternatives to consider. Adequately addressing these alternatives will substantially increase the inferences we can draw from our data. Therefore, we address each alternative interpretation in detail below.

(a) Sustained Suppression. I was wondering if there is anything in your results that would speak for or against the suppression being task specific. That is, is it possible that people are just suppressing the HPDL throughout the entire experiment (i.e., also through ITI, breaks, etc., rather than just before and during the search). Since the suppression does not seem volitional, I wonder if participants might apply a blanket suppression to HPDL un l they learn otherwise. Since your localiser comes a er the task you might be able to see hints of sustained suppression in the HPDL during these trials.  

It is indeed possible that participants suppressed the HPDL throughout the entire experiment, instead of proactively instantiating suppression on each trial. While possible, we believe that this account is less likely to explain the present results, given the utilized analysis approach, a voxel-wise GLM fit to the BOLD data per run (see Materials and Methods for details). Specifically, we derived parameter estimates from this GLM per location to estimate the relative suppression. Sustained suppression would modulate BOLD responses throughout the run, i.e. presumably also during the implicit baseline period used to estimate the contrast parameter estimates per location. Hence, sustained suppression should not result in a differential modulation between locations, as the BOLD response at the HPDL during the baseline period would be equally suppressed as during the trial. Inspired by the reviewer’s comment, we now clarify this critical point in the manuscript’s Discussion section:

“Third, participants might have suppressed the HPDL consistently throughout the experiment. This sustained suppression account differs from the proactive suppression proposed here. While this alternative is plausible, we believe that it is less likely to account for the present results, given the analysis conducted. Specifically, we computed voxel-wise parameter estimates and contrasted the obtained betas between locations. Under a sustained suppression account, the HPDL would show suppression even during the implicit baseline period, which would obscure the observed BOLD suppression at and near the HPDL.” 

(b) Enhancement followed by suppression. Another alternative that wasn't discussed would be an initial transient enhancement of the HPDL which might be brought on by the placeholders followed by more sustained suppression through the search task. Of course, on the whole this would look like suppression, but this still seems like it would hold different implications compared to simply "proactive suppression". This would be something like search and destroy however could be on the location level before the actual onset of the search display.  

R1 correctly points out that BOLD data, given the poor temporal resolution, do not allow for the detection of potential transient enhancements at the HPDL followed by a later and more pronounced suppression (akin to “search and destroy”). We fully agree with this assessment. However, we also argue that a transient enhancement followed by sustained suppression before search display onset constitutes proactive suppression in line with our interpretation, because suppression would still arise proactively (i.e., before search, and hence distractor, onset). Whether transient enhancement precedes suppression cannot be elucidated by our data, but we believe that it constitutes an interesting avenue for future studies using me-resolved and spatially specific recording methods. We now clarify this important implementational variation in the updated manuscript.

“Finally, due to the limited temporal resolution of BOLD data, the present data do not elucidate whether the present suppression is preceded by a brief attentional enhancement of the HPDL, as implied by some prior work (Huang et al., 2024). On this account the HPDL would see transient enhancement, followed by sustained suppression, akin to a ‘search and destroy’ mechanism. Critically, we believe that this variation would nonetheless constitute proactive distractor suppression as the suppression would still arise before search onset. Using temporally and spatially resolved methods to explore potential transient enhancements preceding suppression is a promising avenue for future research charting the neural mechanisms underlying distractor suppression.”

(2) I was also considering whether your effects might be at least partially attributable to priming type effects. This would be on the spatial (not feature) level as it is clear that the distractors are switching colours. Basically, is it possible that on trial n participants see the HPDL with the distractor in it and then on trial n+1 they suppress that location. This would be something distinct from the statistical learning framework and from the repetition suppression discussion you have already included. To test for this, you could look at the trials that follow omission or trials. If there is no suppression or less suppression on these trials it would seem fair to conclude that the suppression is at least in part due to the previous trial. 

We agree with the reviewer that it is plausible that participants particularly suppress locations which on previous trials contained a distractor. To address this possibility, we conducted a new analysis and adjusted the manuscript accordingly:

“Second, participants may have suppressed locations that contained the distractor on the previous trial, reflecting a spatial priming effect. This account constitutes a complementary but different perspective than statistical learning, which integrates implicit prior knowledge across many trials. We ruled out that spatial priming explains the present results by contrasting BOLD suppression magnitudes on trials with the distractor at the HPDL and trials where the distractor was not at the HPDL on the previous trial. Results, depicted in Supplementary Figure 4 showed that distractor suppression was statistically significant across both trial types, including trials without a distractor at the HPDL on the preceding trial. This indicates that the observed BOLD suppression is unlikely to be driven by priming and is instead more consistent with statistical learning. Moreover, results did not yield a statistically significant difference between trial types based on the distractor location in the preceding trial. However, these results should not be taken to suggest that spatial priming cannot contribute to distractor suppression; for details see: Supplementary Figure 4.” (p. 13).

We note that this analysis approach slightly differs from the reviewer’s suggestion, which considered omission trials. However, we decided to exclude trials immediately following an omission to ensure that both conditions were matched as closely as possible. In particular, omission trials represent extended rest periods, which could alter participants’ state and especially modulate the visually evoked BOLD responses (e.g., potentially increasing the dynamic range) compared to trials that did not follow omissions. Our analysis approach avoids this difference while still addressing the hypothesis put forward by the reviewer. We now provide the full explanation and results figure of this priming analysis in the figure text of Supplementary Figure 4: 

Reviewer #2 (Public review): 

The authors of this work set out to test ideas about how observers learn to ignore irrelevant visual information. Specifically, they used fMRI to scan participants who performed a visual search task. The task was designed in such a way that highly salient but irrelevant search items were more likely to appear at a given spatial location. With a region-of-interest approach, the authors found that activity in visual cortex that selectively responds to that location was generally suppressed, in response to all stimuli (search targets, salient distractors, or neutral items), as well as in the absence of an anticipated stimulus. 

Strengths of the study include: A well-written and well-argued manuscript; clever application of a region of interest approach to fMRI design, which allows articulating clear tests of different hypotheses; careful application of follow-up analyses to rule out alternative, strategy-based accounts of the findings; tests of the robustness of the findings to detailed analysis parameters such as ROI size; and exclusion of the role of regional baseline differences in BOLD responses. 

We thank the reviewer for the positive evaluation of our manuscript.

The report might be enhanced by analyses (perhaps in a surface space) that distinguish amongst the multiple "early" retinotopic visual areas that are analysed in the aggregate here. 

We agree with the reviewer that an exploratory analysis separating early visual cortex (EVC) into its retinotopic areas could be an interesting addition. Our reasoning to combine early visual areas into one mask in the original analyses was two-fold: First, we did not have an a priori reason to expected distinct neural suppression between these early ROIs. Therefore, we did not acquire retinotopy data to reliably separate early visual areas (e.g. V1, V2 and V3), instead opting to increase the number of search task trials. The lack of retinotopy data inherently limits the reliability of the resulting cortical segmentation. However, we now performed an analysis separating early visual cortex into V1 and V2 and report the details as Supplementary Text 1:

“In an exploratory analysis we investigated whether subdivisions of EVC exhibit different representations of priority signals. In brief, we used FreeSurfer to reconstruct brain surfaces (recon-all) from each subject’s anatomical scan. From these reconstructions we derived V1_exvivo and V2_exvivo labels, which were transformed into volume space using ‘mri_label2vol’ and merged into a bilateral mask for each ROI. We then selected the voxels within each ROI that were most responsive to the four stimulus locations, based on independent localizer data. This voxel selection followed the procedure outlined in the Materials and Methods: Region of Interest (ROI) Definition. To accommodate the subdivision into two ROIs (V1 and V2) compared to the single EVC ROI in the main analysis, we halved the number of voxels selected per location. Finally, we applied the same ROI analysis to investigate distractor suppression during search and omission trials, following the procedure described in Materials and Methods: Statistical Analysis. 

Results of this more fine-grained ROI analyses are depicted in Supplementary Figure 1. First, the results from V2 qualitatively mirrored our primary ROI analysis. BOLD responses in V2 differed significantly between stimulus types (main effect of stimulus type: F_(2,54) = 31.11, p < 0.001, 𝜂 = 0.54). Targets elicited larger BOLD responses compared to distractors (t₍₂₇₎ = 3.05, p_holm = 0.004, d = 0.06) and neutral stimuli (t₍₂₇₎ = 7.82, p_holm < 0.001, d = 0.14). Distractors also evoked larger responses than neutral stimuli (t₍₂₇₎ = 4.78, p_holm < 0.001, d = 0.09). These results likely reflect top-down modulation due to target relevance and bo om-up effects of distractor salience. Consistent with the primary ROI analysis, the manipula on of distractor predictability showed a distinct pattern of location specific BOLD suppression in V2 (main effect of location: F_(1.1,52.8) = 5.01, p = 0.030, 𝜂 = 0.16). Neural populations with receptive fields at the HPDL showed significantly reduced BOLD responses compared to the diagonally opposite neutral location (NL-far; post hoc test HPDL vs NL-far: t₍₂₇₎ = 2.69, p_holm = 0.022, d = 0.62). Again, this suppression was not confined to the HPDL but also extended to close by neutral locations (NL-near vs NL-far: t₍₂₇₎ = 2.79, p_holm = 0.022, d = 0.65). BOLD responses did not differ between HPDL and NL-near locations (HPDL vs NL-near: t₍₂₇₎ = 0.11, p_holm = 0.915, d = 0.03; BF₁₀ = 0.13). As in the EVC ROI analysis, this suppression pattern was consistent across distractor, target, and neutral stimuli presented at the HPDL and NL-near locations compared to NL-far. In sum, neural responses in V2 were significantly modulated by the distractor contingencies, evident as reduced BOLD responses in neural populations with receptive fields at the HPDL and neutral locations near the location of the frequent distractor (NL-near), relative to the neutral location diagonally across the HPDL (NL-far). 

In V1, BOLD responses also differed significantly between stimulus types (main effect of stimulus type: F_(1.3,35.6) = 6.69, p = 0.009, 𝜂 = 0.20). Targets elicited larger BOLD responses compared neutral stimuli (t₍₂₇₎ = 3.52, p_holm = 0.003, d = 0.12) and distractors evoked larger responses than neutral stimuli (t₍₂₇₎ = 2.62, p_holm = 0.023, d = 0.09). However, no difference between targets and distractors was observed (t₍₂₇₎ = 0.90, p_holm = 0.375, d = 0.03; BF₁₀ = 0.17), suggesting reduced sensitivity to task-related effects in V1. Indeed, analyzing the effect of distractor predictability for BOLD responses in V1 showed a different result than in V2 and the combined EVC ROI. There was no significant main effect of location (F_(2,54) = 2.20, p = 0.120, 𝜂 = 0.08; BF₁₀ = 0.77). BOLD responses at NL-near and NL-far were similar (BF₁₀ = 0.171), with the only reliable difference found between target stimuli at the HPDL and NL-far locations (W = 94, p_holm = 0.012, r = 0.54).”  

We include the new result figure as Supplementary Figure 5

We now include reference to these results in the manuscript’s Discussion section:

“Are representations of priority signals uniform across EVC? A priori we did not have any hypotheses regarding distinct neural suppression profiles across different early visual areas, hence our primary analyses focused stimulus responses neural populations in EVC, irrespective of subdivision. However, an exploratory analysis suggests that distractor suppression may show different patterns in V1 compared to V2 (Supplementary Figure 5 and Supplementary Text 1). In brief, results in V2 mirrored those reported for the combined EVC ROI (Figure 4). In contrast, results in V1 appeared to be only partially modulated by distractor contingencies, and if so, the modulation was less robust and not as spatially broad as in V2. This suggests the possibility of different effects of distractor predictability across subdivisions of early visual areas. However, these results should be interpreted with caution. First, our design did not optimize the delineation of early visual areas (e.g., no functional retinotopy), limiting the accuracy of V1 and V2 segmentation. Additionally, analyses were conducted in volumetric space, which further reduces spatial precision. Future studies could improve this by including retinotopy runs to accurately delineate V1, V2, and V3, and by performing analyses in surface space. Higher-resolution functional and anatomical MRI sequences would also help elucidate how distractor suppression is implemented across EVC with greater precision.”

Furthermore, the study could benefit from an analysis that tests the correlation over observers between the magnitude of their behavioural effects and their neural responses. 

R2 highlights that behavioral facilitation and neural suppression could be correlated across participants. The rationale is that if neural suppression in EVC is related to the facilitation of behavioral responses, we should expect a positive relationship between neural suppression at the HPDL and RTs across participants. In this analysis we focused on the contrast between HPDL and NL-far, as this contrast was statistically significant in both the RT (Figure 2) and the neural suppression analysis (Figure 4). First, we computed for each participant the behavioural benefit of distractor suppression as: RT_facilitation = RT_NL-far – RT_HPDL. Thereby RT facilitation reflects the response speeding due to a distractor appearing at the high probability distractor location compared to the far neutral location. Next, we computed neural suppression as: BOLD_suppression = BOLD_NL-far – BOLD_HPDL Thus, positive values reflect the suppression of BOLD responses at the HPDL comparted to the NL-far location. The BOLD suppression index was computed for each stimulus type separately, as in the main ROI analysis (i.e. for Targets, Neutrals and Distractors). Finally, we correlated RT_facilitation with BOLD_suppression across participants using Pearson correlation. Results showed a small, but not statistically significant correlation between RT facilitation and BOLD suppression for distractor (r₍₂₆₎ = 0.22, p = 0.257), target (r₍₂₆₎ = 0.10, p = 0.598) and neutral (r₍₂₆₎ = 0.13, p = 0.519) stimuli. Thus, while the direc on of the correlation was in line with the specula on by the reviewer in the “ Recommendations for the authors”, results were not statistically reliable and therefore inconclusive. As also noted in our preliminary reply to the reviewer comments, it was a priori unlikely that this analysis would yield a statistically significant correlation. An a priori power analysis suggested that, to reach a power of 0.8 at a standard alpha of 0.05, given the present sample size of n=28, the effect size would need to exceed r > 0.75, which seemed unlikely for the correlation of behavioural and neural difference scores. Given the inconclusive nature of the results, we prefer to not include this additional analysis in the manuscript, as we believe that it does not add to the main message of the paper but have it accessible to the interested reader in the public “peer review process”.

The study provides an advance over previous studies, which iden fied enhancement or suppression in visual cortex as a function of search target/distractor predictability, but in less spatially-specific way. It also speaks to open questions about whether such suppression/enhancement is observed only in response to the arrival of visual information, or instead is preparatory, favouring the la er view. The theoretical advance is moderate, in that it is largely congruent with previous frameworks, rather than strongly excluding an opposing view or providing a major step change in our understanding of how distractor suppression unfolds. 

We agree with the reviewer that our results are an advancement of prior work, particularly with respect to narrowing down the role of sensory areas and the proactive nature of distractor suppression. However, we argue that this represents a significant step forward for several reasons. First, to our knowledge, the literature on distractor suppression, and visual search in general, is by no means unanimous with respect to the conclusion that distractor suppression is instantiated proactively (Huang et al., 2021, 2022). Indeed, there are several studies suggesting the opposite account; reactive suppression (Chang et al., 2023) or contributions by both proactive and reactive mechanisms (Sauter et al., 2021; Wang et al., 2019). Moreover, studies in support of proactive distractor suppression did not investigate the involvement of (early) sensory areas during suppression. Conversely, to our knowledge most studies investigating the involvement of sensory cortex during distractor suppression did not address the question whether suppression arises proactive or reactively.

Recommendations for the authors: 

Reviewer #1 ( Recommendations for the authors): 

Minor Points: 

(1) There are several disconnects between the behaviour and the MR results - i.e. not stimulus specific yet there are no deficits for targets appearing the HPDL, also no behavioural suppression for the NLNear but neural suppression found. Nevertheless, the behaviour is used as a way to rule out potential attentional strategies when considering whether there is enhancement in the NL-Far condition. I realise you have a few other points here, but I think it's worth addressing what could be seen as a double standard.

The reviewer points out an important concern, which we feel could have better been addressed in the manuscript. From our point of view a partial dissociation between neural modulations in EVC and eventual behavioural facilitation is not surprising, given the extensive neural processing beyond EVC required for behaviour. However, this assessment may differ, if one stresses an explicit volitional attentional strategy over an implicit statistical learning account. That said, we clearly do not want to create the impression of using a double standard. The lack of behavioural facilitation for targets at NLfar is not a critical part of our argument against explicit attentional strategies. Therefore, we rephrased the relevant paragraph in the Discussion section to now emphasize the importance of the control analysis excluding participants who reported the correct HPDL in the questionnaire (Figure 5), but nonetheless yielded qualitatively identical results to the main ROI analysis (Figure 4). In our opinion, this control analysis provides more compelling evidence against a volitional attentional strategy account without the risk of crea ng the impression of applying a double standard in the interpretation of behavioural data. Additionally, we now acknowledge the limitation of relying on behavioral data in ruling out volitional attentional strategies in the updated manuscript:

“It is well established that attention enhances BOLD responses in visual cortex (Maunsell, 2015; Reynolds & Chelazzi, 2004; Williford & Maunsell, 2006). If participants learned the underlying distractor contingencies, they could deploy an explicit strategy by directing their attention away from the HPDL, for example by focusing attention on the diagonally opposite neutral location. This account provides an alternative explanation for the observed EVC modulations. However, while credible, the current findings are not consistent with such an interpretation. First, there was no behavioral facilitation for target stimuli presented at the far neutral location, contrary to what one might expect if participants employed an explicit strategy. However, given the partial dissociation between neural suppression in EVC and behavioral facilitation, additional neural data analyses are required to rule out volitional attention strategies. Thus, we performed a control analysis that excluded all participants that indicated the correct HPDL location in the questionnaire, thereby possibly expressing explicit awareness of the contingencies. This control analysis yielded qualitatively identical results to the full sample, showing significant distractor suppression in EVC. Therefore, it is unlikely that explicit attentional strategies, and the enhancement of locations far from the HPDL, drive the results observed here. Instead the current finding are consistent with an account emphasizing the automa c deployment of spatial priors (He et al., 2022) based on implicitly learned statistical regularities.”

(2) Does the level of suppression change in any way through the experiment? I.e., does it get stronger in the second vs. first half of the experiment? 

The reviewer askes an interesting question, whether BOLD suppression may change across the experiment. To address this question, we performed an additional analysis testing BOLD suppression in EVC during the first compared to second half of the MRI experiment. Here we defined BOLD suppression as: BOLD_suppression = ((BOLD_NL-far – BOLD_HPDL) + (BOLD_NL-far – BOLD_NL-near)) / 2. Thus, in this formula on of BOLD suppression we summarize the two primary BOLD suppression effects observed in our main results (Figure 4). Additionally, as we previously did not observe any significant differences in BOLD suppression magnitudes between different stimulus types (i.e. suppression was similar for target, distractor and neutral stimuli), we collapsed across stimulus types in this analysis.

Results, depicted below, showed that during both the initial (Run 1+2) and later part (Run 4+5) of the MRI experiment BOLD suppression was statistically significant (BOLD suppression Run 1+2: W = 331, p = 0.003, r = 0.63; BOLD suppression Run 4+5: W = 320, p = 0.007, r= 0.58) , confirming our main results of reliable distractor suppression even in this subset of trials. However, we did not observe any statistically significant differences between early and late runs of the experiment (t₍₂₇₎ = -0.21, p = 0.835, d = -0.04). In fact, a Bayesian paired t-test provided evidence for the absence of a difference in BOLD suppression between early compared to later runs (BF₁₀ = 0.205), suggesting that distractor suppression in EVC was stable throughout the experiment. A qualitatively similar, pattern was evident during omission trials, with significant distractor suppression during early runs (t₍₂₇₎ = 2.70, p = 0.012, d = 0.51), but not quite a statistically significant modulation for later runs (t₍₂₇₎ = 1.97, p = 0.059, d = 0.37). Again, there was no evidence for a difference in suppression magnitudes across the experiment (W = 198, p = 0.920, d = -0.025) and support for the absence of a difference in BOLD suppression between early and late runs (BF₁₀ = 0.278).

Author response image 1.

Analysis of BOLD suppression magnitudes in EVC across the MRI experiment phases. BOLD suppression was comparable between early (Run 1+2) and late (Run 4+5) phases of the MRI experiment, suggesting consistent suppression in EVC following statistical learning. Error-bars denote within-subject SEM. * p < 0.05, ** p < 0.01, = BF₁₀ < 1/3.

In sum, results suggest that distractor suppression in EVC was stable across runs and did not change significantly throughout the experiment. This result was a priori likely, given that participants already underwent behavioral training before entering the MRI. This enabled them to establish modified spatial priority maps, containing the high probability distractor location contingencies, already before the first MRI run. While specula ve, it is possible that participants may still have consolidated the spatial priority maps during the initial runs, but that this additional consolation is not evident in the data, as later runs may see less engagement by participants due to increasing fa gue towards the end of the MRI experiment. Indeed, rapid learning and stable suppression throughout the remainder of the experiment is also reported by prior work (Lin et al., 2021). We believe that it is highly interesting for future studies to investigate the development of distractor suppression across learning, with initial exposure to the contingencies inside the MRI. However, as the present results are inconclusive, we prefer to not include this analysis in the main manuscript, as it may not provide significant additional insight into the neural mechanisms underlying distractor suppression. 

(3) In the methods vs. results you have reported the probabili es slightly differently. In the methods you say the HPDL was 6x more likely to contain a distractor whereas in the results you say 4x. Based on the reported trial numbers I think it should be 4, but probably you want to double check that this is consistent and correct throughout. 

We thank the reviewer for bringing this inconsistency to our attention. We have corrected this oversight in the adjusted manuscript: 

“One of the four locations of interest was designated the high probability distractor location (HPDL), which contained distractor stimuli (unique color) four mes more o en than any of the remaining three locations of interest. In other words, if a distractor was present on a given trial (42 trials per run), the distractor appeared 57% (24 trials per run) at the HPDL and at one of the other three locations with equal probability (i.e., 14% or 6 trials per run per location).” 

Reviewer #2 ( Recommendations for the authors): 

The authors have performed their analyses in the volume rather than the surface, and have grouped together V1, V2, and V3 as "early visual cortex". As the authors' claims lean heavily on the idea that they are measuring "early" visual responses, the study would be improved by delinea ng the ROIS within these different retinotopic regions. Such an approach might be facilitated by analysing data on the reconstructed surface. 

Please refer to our reply to this analysis suggested in the Public review.

The authors rightly tread carefully on the causal link between their neural findings and the behavioural outcomes. The picture might be clarified somewhat further by testing for a positive relationship between behavioural effect sizes and neural effect sizes across participants. e.g. to what extent is the search advantage when distractors are presented at the "HPDL" linked to greater suppression of BOLD at the HDPL region of early visual cortex? 

Please refer to our reply to this analysis suggested in the Public review.

Some of the claims based on null hypotheses would be better supported by Bayesian tests e.g. page 6 "This pattern of results was the same regardless whether the distractor, target, or a neutral stimulus presented at the HPDL and NL-near locations compared to NL-far ..." and "BOLD responses between HPDL and NL-near locations did not reliably differ ..." This is similar to the approach that the authors adopted later in the section "Ruling out attentional modulation".

We agree with the reviewer that our ROI analyses would benefit from providing evidence for the absence of a modulation. Accordingly, we updated our results by adding equivalent Bayesian tests. Bayes Factors were computed using JASP 0.18.2 (JASP Team, 2024; RRID:SCR_015823) with default settings; i.e. for Bayesian paired t-tests with a Cauchy prior width of 0.707. Qualitative interpretations of BFs were based on Lee and Wagenmakers (2014). We now report the obtained BF in the Results section. 

“BOLD responses between HPDL and NL-near locations did not reliably differ (HPDL vs NL-near: t₍₂₇₎ = 0.47, p_holm = 0.643, d = 0.08; BF₁₀ = 0.19).”

And:

“Neural responses at HPDL and NL-near did not reliably differ (t₍₂₇₎ = 0.21, p_holm = 0.835 d = 0.04; BF₁₀ = 0.21).”

Moreover, we now denote any equivalent results (defined as BF₁₀<1/3) in Fig. 4 and Fig. 5, and included the descrip on of the associated symbol in the figure text (“ = BF₁₀ < 1/3”).

Additionally, we now also report the BF for all paired t-tests reported in Supplementary Table 1.

Finally, we addressed the statement: “This pattern of results was the same regardless whether the distractor, target, or a neutral stimulus presented at the HPDL and NL-near locations compared to NLfar”. Our inten on was to emphasize that the pattern of results reported in the sentence preceding it was evident for distractor, target, or neutral stimulus, and not to suggest that the magnitude of the effect is the same. Hence, to more accurate reflect the results, we changed this sentence to:  “This pattern of results was present regardless whether the distractor, target, or a neutral stimulus presented at the HPDL and NL-near locations compared to NL-far”

eLife Assessment

This valuable work presents how PRDM16 plays a critical role during colloid plexus development, through regulating BMP signaling. Solid evidence supports the context-dependent gene regulatory mechanisms both in vivo and in vitro. The work will be of broad interest to researchers working on growth factor signaling mechanisms and vertebrate development.

Reviewer #1 (Public review):

Summary:

This manuscript describes the role of PRDM16 in modulating BMP response during choroid plexus (ChP) development. The authors combine PRDM16 knockout mice and cultured PRDM16 KO primary neural stem cells (NSCs) to determine the interactions between BMP signaling and PRDM16 in ChP differentiation.

They show PRDM16 KO affects ChP development in vivo and BMP4 response in vitro. They determine genes regulated by BMP and PRDM16 by ChIP-seq or CUT&TAG for PRDM16, pSMAD1/5/8, and SMAD4. They then measure gene activity in primary NSCs through H3K4me3 and find more genes are co-repressed than co-activated by BMP signaling and PRDM16. They focus on the 31 genes found to be co-repressed by BMP and PRDM16. Wnt7b is in this set and the authors then provide evidence that PRDM16 and BMP signaling together repress Wnt activity in the developing choroid plexus.

Strengths:

Understanding context-dependent responses to cell signals during development is an important problem. The authors use a powerful combination of in vivo and in vitro systems to dissect how PRDM16 may modulate BMP response in early brain development.

Main weaknesses of the experimental setup:

(1) Because the authors state that primary NSCs cultured in vitro lose endogenous Prdm16 expression, they drive expression by a constitutive promoter. However, this means the expression levels are very different from endogenous levels (as explicitly shown in Supplementary Figure 2B) and the effect of many transcription factors is strongly dose-dependent, likely creating differences between the PRDM16-dependent transcriptional response in the in vitro system and in vivo.

(2) It seems that the authors compare Prdm16_KO cells to Prdm16 WT cells overexpressing flag_Prdm16. Aside from the possible expression of endogenous Prdm16, other cell differences may have arisen between these cell lines. A properly controlled experiment would compare Prdm16_KO ctrl (possibly infected with a control vector without Prdm16) to Prdm16_KO_E (i.e. the Prdm16_KO cells with and without Prdm16 overexpression.)

Other experimental weaknesses that make the evidence less convincing:

(1) The authors show in Figure 2E that Ttr is not upregulated by BMP4 in PRDM16_KO NSCs. Does this appear inconsistent with the presence of Ttr expression in the PRDM16_KO brain in Figure1C?

(2) Figure 3: The authors use H3K4me3 to measure gene activity. This is however, very indirect, with bulk RNA-seq providing the most direct readout and polymerase binding (ChIP-seq) another more direct readout. Transcription can be regulated without expected changes in histone methylation, see e.g. papers from Josh Brickman. They verify their H3K4me3 predictions with qPCR for a select number of genes, all related to the kinetochore, but it is not clear why these genes were picked, and one could worry whether these are representative.

(3) Line 256: The overlap of 31 genes between 184 BMP-repressed genes and 240 PRDM16-repressed genes seems quite small.

(4) The Wnt7b H3K4me3 track in Fig. 3G is not discussed in the text but it shows H3K4me3 high in _KO and low in _E regardless of BMP4. This seems to contradict the heatmap of H3K4me3 in Figure 3E which shows H3K4me3 high in _E no BMP4 and low in _E BMP4 while omitting _KO no BMP4. Meanwhile CDKN1A, the other gene shown in 3G, is missing from 3E.

(5) The authors use PRDM16 CUT&TAG on dissected dorsal midline tissues to determine if their 31 identified PRDM16-BMP4 co-repressed genes are regulated directly by PRDM16 in vivo. By manual inspection, they find that "most" of these show a PRDM16 peak. How many is most? If using the same parameters for determining peaks, how many genes in an appropriately chosen negative control set of genes would show peaks? Can the authors rigorously establish the statistical significance of this observation? And why wasn't the same experiment performed on the NSCs in which the other experiments are done so one can directly compare the results? Instead, as far as I could tell, there is only ChIP-qPCR for two genes in NSCs in Supplementary Figure 4D.

(6) In comparing RNA in situ between WT and PRDM16 KO in Figure 7, the authors state they use the Wnt2b signal to identify the border between CH and neocortex. However, the Wnt2b signal is shown in grey and it is impossible for this reviewer to see clear Wnt2b expression or where the boundaries are in Figure 7A. The authors also do not show where they placed the boundaries in their analysis. Furthermore, Figure 7B only shows insets for one of the regions being compared making it difficult to see differences from the other region. Finally, the authors do not show an example of their spot segmentation to judge whether their spot counting is reliable. Overall, this makes it difficult to judge whether the quantification in Figure 7C can be trusted.

(7) The correlation between mKi67 and Axin2 in Figure 7 is interesting but does not convincingly show that Wnt downstream of PRDM16 and BMP is responsible for the increased proliferation in PRDM16 mutants.

Weaknesses of the presentation:

Overall, the manuscript is not easy to read. This can cause confusion.

Reviewer #2 (Public review):

Summary:

This article investigates the role of PRDM16 in regulating cell proliferation and differentiation during choroid plexus (ChP) development in mice. The study finds that PRDM16 acts as a corepressor in the BMP signaling pathway, which is crucial for ChP formation.

The key findings of the study are:<br /> (1) PRDM16 promotes cell cycle exit in neural epithelial cells at the ChP primordium.<br /> (2) PRDM16 and BMP signaling work together to induce neural stem cell (NSC) quiescence in vitro.<br /> (3) BMP signaling and PRDM16 cooperatively repress proliferation genes.<br /> (4) PRDM16 assists genomic binding of SMAD4 and pSMAD1/5/8.<br /> (5) Genes co-regulated by SMADs and PRDM16 in NSCs are repressed in the developing ChP.<br /> (6) PRDM16 represses Wnt7b and Wnt activity in the developing ChP.<br /> (7) Levels of Wnt activity correlate with cell proliferation in the developing ChP and CH.

In summary, this study identifies PRDM16 as a key regulator of the balance between BMP and Wnt signaling during ChP development. PRDM16 facilitates the repressive function of BMP signaling on cell proliferation while simultaneously suppressing Wnt signaling. This interplay between signaling pathways and PRDM16 is essential for the proper specification and differentiation of ChP epithelial cells. This study provides new insights into the molecular mechanisms governing ChP development and may have implications for understanding the pathogenesis of ChP tumors and other related diseases.

Strengths:

(1) Combining in vitro and in vivo experiments to provide a comprehensive understanding of PRDM16 function in ChP development.

(2) Uses of a variety of techniques, including immunostaining, RNA in situ hybridization, RT-qPCR, CUT&Tag, ChIP-seq, and SCRINSHOT.

(3) Identifying a novel role for PRDM16 in regulating the balance between BMP and Wnt signaling.

(4) Providing a mechanistic explanation for how PRDM16 enhances the repressive function of BMP signaling. The identification of SMAD palindromic motifs as preferred binding sites for the SMAD/PRDM16 complex suggests a specific mechanism for PRDM16-mediated gene repression.

(5) Highlighting the potential clinical relevance of PRDM16 in the context of ChP tumors and other related diseases. By demonstrating the crucial role of PRDM16 in controlling ChP development, the study suggests that dysregulation of PRDM16 may contribute to the pathogenesis of these conditions.

Weaknesses:

(1) Limited investigation of the mechanism controlling PRDM16 protein stability and nuclear localization in vivo. The study observed that PRDM16 protein became nearly undetectable in NSCs cultured in vitro, despite high mRNA levels. While the authors speculate that post-translational modifications might regulate PRDM16 in NSCs similar to brown adipocytes, further investigation is needed to confirm this and understand the precise mechanism controlling PRDM16 protein levels in vivo.

(2) Reliance on overexpression of PRDM16 in NSC cultures. To study PRDM16 function in vitro, the authors used a lentiviral construct to constitutively express PRDM16 in NSCs. While this approach allowed them to overcome the issue of low PRDM16 protein levels in vitro, it is important to consider that overexpressing PRDM16 may not fully recapitulate its physiological role in regulating gene expression and cell behavior.

(3) Lack of direct evidence for AP1 as the co-factor responsible for SMAD relocation in the absence of PRDM16. While the study identified the AP1 motif as enriched in SMAD binding sites in Prdm16 knockout cells, they only provided ChIP-qPCR validation for c-FOS binding at two specific loci (Wnt7b and Id3). Further investigation is needed to confirm the direct interaction between AP1 and SMAD proteins in the absence of PRDM16 and to rule out other potential co-factors.

Reviewer #3 (Public review):

Summary:

Bone morphogenetic protein (BMP) signaling instructs multiple processes during development including cell proliferation and differentiation. The authors set out to understand the role of PRDM16 in these various functions of BMP signaling. They find that PRDM16 and BMP co-operate to repress stem cell proliferation by regulating the genomic distribution of BMP pathway transcription factors. They additionally show that PRDM16 impacts choroid plexus epithelial cell specification. The authors provide evidence for a regulatory circuit (constituting of BMP, PRDM16, and Wnt) that influences stem cell proliferation/differentiation.

Strengths:

I find the topics studied by the authors in this study of general interest to the field, the experiments well-controlled and the analysis in the paper sound.

Weaknesses:

I have no major scientific concerns. I have some minor recommendations that will help improve the paper (regarding the discussion).

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

This manuscript describes the role of PRDM16 in modulating BMP response during choroid plexus (ChP) development. The authors combine PRDM16 knockout mice and cultured PRDM16 KO primary neural stem cells (NSCs) to determine the interactions between BMP signaling and PRDM16 in ChP differentiation.

They show PRDM16 KO affects ChP development in vivo and BMP4 response in vitro. They determine genes regulated by BMP and PRDM16 by ChIP-seq or CUT&TAG for PRDM16, pSMAD1/5/8, and SMAD4. They then measure gene activity in primary NSCs through H3K4me3 and find more genes are co-repressed than co-activated by BMP signaling and PRDM16. They focus on the 31 genes found to be co-repressed by BMP and PRDM16. Wnt7b is in this set and the authors then provide evidence that PRDM16 and BMP signaling together repress Wnt activity in the developing choroid plexus.

Strengths:

Understanding context-dependent responses to cell signals during development is an important problem. The authors use a powerful combination of in vivo and in vitro systems to dissect how PRDM16 may modulate BMP response in early brain development.

Main weaknesses of the experimental setup:

(1) Because the authors state that primary NSCs cultured in vitro lose endogenous Prdm16 expression, they drive expression by a constitutive promoter. However, this means the expression levels are very different from endogenous levels (as explicitly shown in Supplementary Figure 2B) and the effect of many transcription factors is strongly dose-dependent, likely creating differences between the PRDM16-dependent transcriptional response in the in vitro system and in vivo.<br />

We acknowledge that our in vitro experiments may not ideally replicate the in vivo situation, a common limitation of such experiments, our primary aim was to explore the molecular relationship between PRDM16 and BMP signaling in gene regulation. Such molecular investigations are challenging to conduct using in vivo tissues. In vitro NSCs treated with BMP4 has been used a model to investigate NSC proliferation and quiescence, drawing on previous studies (e.g., Helena Mira, 2010; Marlen Knobloch, 2017). Crucially, to ensure the relevance of our in vitro findings to the in vivo context, we confirmed that cultured cells could indeed be induced into quiescence by BMP4, and this induction necessitated the presence of PRDM16. Furthermore, upon identifying target genes co-regulated by PRDM16 and SMADs, we validated PRDM16's regulatory role on a subset of these genes in the developing Choroid Plexus (ChP) (Fig. 7 and Suppl.Fig7-8). Only by combining evidence from both in vitro and in vivo experiments could we confidently conclude that PRDM16 serves as an essential co-factor for BMP signaling in restricting NSC proliferation.

(2) It seems that the authors compare Prdm16_KO cells to Prdm16 WT cells overexpressing flag_Prdm16. Aside from the possible expression of endogenous Prdm16, other cell differences may have arisen between these cell lines. A properly controlled experiment would compare Prdm16_KO ctrl (possibly infected with a control vector without Prdm16) to Prdm16_KO_E (i.e. the Prdm16_KO cells with and without Prdm16 overexpression.)

We agree that Prdm16 KO cells carrying the Prdm16-expressing vector would be a good comparison with those with KO_vector. However, despite more than 10 attempts with various optimization conditions, we were unable to establish a viable cell line after infecting Prdm16 KO cells with the Prdm16-expressing vector. The overall survival rate for primary NSCs after viral infection is low, and we observed that KO cells were particularly sensitive to infection treatment when the viral vector was large (the Prdm16 ORF is more than 3kb).

As an alternative oo assess vector effects, we instead included two other control cell lines, wt and KO cells infected with the 3xNLS_Flag-tag viral vector, and presented the results in supplementary Fig 2.  When we compared the responses of the four lines — wt, KO, wt infected with the Flag vector, KO infected with the Flag vector — to the addition and removal of BMP4, we confirmed that the viral infection itself has no significant impacts on the responses of these cells to these treatments regarding changes in cell proliferation and Ttr induction.

Given that wt cells and the KO cells, with or without viral backbone infection behave quite similarly in terms of cell proliferation, we speculate that even if we were successful in obtaining a cell line with Prdm16-expressing vector in the KO cells, it may not exhibit substantial differences compared to wt cells infected with Prdm16-expressing vector.

Other experimental weaknesses that make the evidence less convincing:

(1) The authors show in Figure 2E that Ttr is not upregulated by BMP4 in PRDM16_KO NSCs. Does this appear inconsistent with the presence of Ttr expression in the PRDM16_KO brain in Figure1C?<br />

The reviwer’s point is that there was no significant increase in Ttr expression in Prdm16_KO cells after BMP4 treatment (Fig. 2E), but there remained residule Ttr mRNA signals in the Prdm16 mutant ChP (Fig. 1C). We think the difference lies in the measuable level of Ttr expression between that induced by BMP4 in NSC culture and that in the ChP. This is based on our immunostaining expreriment in which we tried to detect Ttr using a Ttr antibody. This antibody could not detect the Ttr protein in BMP4-treated Prdm16_expressing NSCs but clearly showed Ttr signal in the wt ChP. This means that although Ttr expression can be significantly increased by BMP4 in vitro to a level measurable by RT-qPCR, its absolute quantity even in the Prdm16_expressing condition is much lower compared to that in vivo. Our results in Fig 1C and Fig 2E, as well as Fig 7B, all consistently showed that Prdm16 depletion significantly reduced Ttr expression in in vitro and in vivo.

(2) Figure 3: The authors use H3K4me3 to measure gene activity. This is however, very indirect, with bulk RNA-seq providing the most direct readout and polymerase binding (ChIP-seq) another more direct readout. Transcription can be regulated without expected changes in histone methylation, see e.g. papers from Josh Brickman. They verify their H3K4me3 predictions with qPCR for a select number of genes, all related to the kinetochore, but it is not clear why these genes were picked, and one could worry whether these are representative.

H3K4me3 has widely been used as an indicator of active transcription and is a mark for cell identity genes. And it has been demonstrated that H3K4me3 has a direct function in regulating transciption at the step of RNApolII pausing release. As stated in the text, there are advantages and disadvantages of using H3K4me3 compared to using RNA-seq. RNA-seq profiles all gene products, which are affected by transcription and RNA stability and turnover. In contrast, H3K4me3 levels at gene promoter reflects transcriptional activity. In our case, we aimed to identify differential gene expression between proliferation and quiescence states. The transition between these two states is fast and dynamic. RNA-seq may not be able to identify functionally relevant genes but more likely produces false positive and negative results. Therefore, we chose H3K4me3 profiling.

We agree that transcription may change without histone methylation changes. This may cause an under-estimation of the number of changed genes between the conditions. 

We validated 7 out of 31 genes (Wnt7b, Id3, Mybl2, Spc24, Spc25, Ndc80 and Nuf2). We chose these genes based on two critira: 1) their function is implicated in cell proliferation and cell-cycle regulation based on gene ontology analysis; 2) their gene products are detectable in the developing ChP based on the scRNA-seq data. Three of these genes (Wnt7b, Id3, Mybl2) are not related to the kinetochore. We now clarify this description in the revised text.

(3) Line 256: The overlap of 31 genes between 184 BMP-repressed genes and 240 PRDM16-repressed genes seems quite small.

This indicates that in addition to co-repressing cell-cycle genes, BMP and PRDM16 have independent fucntions. For example, it was reported that BMP regulates neuronal and astrocyte differentiation (Katada, S. 2021), while our previous work demonstrated that Prdm16 controls temporal identity of NSCs (He, L. 2021).

(4) The Wnt7b H3K4me3 track in Fig. 3G is not discussed in the text but it shows H3K4me3 high in _KO and low in _E regardless of BMP4. This seems to contradict the heatmap of H3K4me3 in Figure 3E which shows H3K4me3 high in _E no BMP4 and low in _E BMP4 while omitting _KO no BMP4. Meanwhile CDKN1A, the other gene shown in 3G, is missing from 3E.

The track in Fig 3G shows the absolute signal of H3K4me3 after mapping the sequencing reads to the genome and normaliz them to library size. Compare the signal in Prdm16_E with BMP4 and that in Prdm16_E without BMP4, the one with BMP4 has a lower peak. The same trend can be seen for the pair of Prdm16_KO cells with or without BMP4.  The heatmap in Fig. 3E shows the relative level of H3K4me3 in three conditions. The Prdm16_E cells with BMP4 has the lowest level, while the other two conditions (Prdm16_KO with BMP4 and Prdm16_E without BMP4) display a higher level. These two graphs show a consistent trend of H3K4me3 changes at the Wnt7b promoter across these conditions.

(5) The authors use PRDM16 CUT&TAG on dissected dorsal midline tissues to determine if their 31 identified PRDM16-BMP4 co-repressed genes are regulated directly by PRDM16 in vivo. By manual inspection, they find that "most" of these show a PRDM16 peak. How many is most? If using the same parameters for determining peaks, how many genes in an appropriately chosen negative control set of genes would show peaks? Can the authors rigorously establish the statistical significance of this observation? And why wasn't the same experiment performed on the NSCs in which the other experiments are done so one can directly compare the results? Instead, as far as I could tell, there is only ChIP-qPCR for two genes in NSCs in Supplementary Figure 4D.

In our text, we indicated the genes containing PRDM16 binding peaks in the figures and described them as “Text in black in Fig. 6A and Supplementary Fig. 5A”. We will add the precise number “25 of these genes” in the main text to clarify it. To define a negative control set of genes, we will use BMP-only repressed 184-31 =153 genes (excluding PRDM16-BMP4 co-repressed), and of these 153 genes, we will determine how many have PRDM16 peaks in the E12.5 ChP data, say X. Then we will use binomial test to calculate p-value binom_test(25, 31, X/153, alternative=“greater).

We are confused with the second part of the comment “And why wasn't the same experiment performed on the NSCs in which the other experiments are done so one can directly compare the results? Instead, as far as I could tell, there is only ChIP-qPCR for two genes in NSCs in Supplementary Figure 4D.” If the reviewer meant why we didn’t sequence the material from sequential-ChIP or validate more taget genes, the reason is the limitation of the material. Sequential ChIP requires a large quantity of the antibodies, and yields little material barely sufficient for a few qPCR after the second round of IP. This yielded amount was far below the minimum required for library construction. The PRDM16 antibody was a gift, and the quantity we have was very limited. We made a lot of efforts to optimize all available commercial antibodies in ChIP and Cut&Tag, but none of them worked.

(6) In comparing RNA in situ between WT and PRDM16 KO in Figure 7, the authors state they use the Wnt2b signal to identify the border between CH and neocortex. However, the Wnt2b signal is shown in grey and it is impossible for this reviewer to see clear Wnt2b expression or where the boundaries are in Figure 7A. The authors also do not show where they placed the boundaries in their analysis. Furthermore, Figure 7B only shows insets for one of the regions being compared making it difficult to see differences from the other region. Finally, the authors do not show an example of their spot segmentation to judge whether their spot counting is reliable. Overall, this makes it difficult to judge whether the quantification in Figure 7C can be trusted.

To address these questions, in the revised manuscript we will include an individal channel of Wnt2b and mark the boundaries. We will also provide full-view images and examples of spot segmentation in supplementary figures as space limitation in the main figures.

(7) The correlation between mKi67 and Axin2 in Figure 7 is interesting but does not convincingly show that Wnt downstream of PRDM16 and BMP is responsible for the increased proliferation in PRDM16 mutants.

We agree that this result (the correlation between mKi67 and Axin2) alone only suggests that Wnt signaling is related to the proliferation defect in the Prdm16 mutant, and does not necessarily mean that Wnt is downstream of PRDM16 and BMP. Our concolusion is backed up by two additional lines of evidences:  the Cut&Tag data in which PRDM16 binds to regulatory regions of Wnt7b and Wnt3a; BMP and PRDM16 co-repress Wnt7b in vitro.

An ideal result is that down-regulating Wnt signaling in Prdm16 mutant can rescue Prdm16 mutant phenotype. Such an experiment is technically challenging. Wnt plays diverse and essential roles in NSC regulation, and one would need to use a celltype-and stage-specific tool to down-regulate Wnt in the background of Prdm16 mutation. Moreover, Wnt genes are not the only targets regulated by PRDM16 in these cells, and downregulating Wnt may not be sufficient to rescue the phenotype. 

Weaknesses of the presentation:

Overall, the manuscript is not easy to read. This can cause confusion.

We will revise the text to improve the clarity.

Reviewer #2 (Public review):

Summary:

This article investigates the role of PRDM16 in regulating cell proliferation and differentiation during choroid plexus (ChP) development in mice. The study finds that PRDM16 acts as a corepressor in the BMP signaling pathway, which is crucial for ChP formation.

The key findings of the study are:

(1) PRDM16 promotes cell cycle exit in neural epithelial cells at the ChP primordium.

(2) PRDM16 and BMP signaling work together to induce neural stem cell (NSC) quiescence in vitro.

(3) BMP signaling and PRDM16 cooperatively repress proliferation genes.

(4) PRDM16 assists genomic binding of SMAD4 and pSMAD1/5/8.

(5) Genes co-regulated by SMADs and PRDM16 in NSCs are repressed in the developing ChP.

(6) PRDM16 represses Wnt7b and Wnt activity in the developing ChP.

(7) Levels of Wnt activity correlate with cell proliferation in the developing ChP and CH.

In summary, this study identifies PRDM16 as a key regulator of the balance between BMP and Wnt signaling during ChP development. PRDM16 facilitates the repressive function of BMP signaling on cell proliferation while simultaneously suppressing Wnt signaling. This interplay between signaling pathways and PRDM16 is essential for the proper specification and differentiation of ChP epithelial cells. This study provides new insights into the molecular mechanisms governing ChP development and may have implications for understanding the pathogenesis of ChP tumors and other related diseases.

Strengths:

(1) Combining in vitro and in vivo experiments to provide a comprehensive understanding of PRDM16 function in ChP development.

(2) Uses of a variety of techniques, including immunostaining, RNA in situ hybridization, RT-qPCR, CUT&Tag, ChIP-seq, and SCRINSHOT.

(3) Identifying a novel role for PRDM16 in regulating the balance between BMP and Wnt signaling.

(4) Providing a mechanistic explanation for how PRDM16 enhances the repressive function of BMP signaling. The identification of SMAD palindromic motifs as preferred binding sites for the SMAD/PRDM16 complex suggests a specific mechanism for PRDM16-mediated gene repression.

(5) Highlighting the potential clinical relevance of PRDM16 in the context of ChP tumors and other related diseases. By demonstrating the crucial role of PRDM16 in controlling ChP development, the study suggests that dysregulation of PRDM16 may contribute to the pathogenesis of these conditions.

Weaknesses:

(1) Limited investigation of the mechanism controlling PRDM16 protein stability and nuclear localization in vivo. The study observed that PRDM16 protein became nearly undetectable in NSCs cultured in vitro, despite high mRNA levels. While the authors speculate that post-translational modifications might regulate PRDM16 in NSCs similar to brown adipocytes, further investigation is needed to confirm this and understand the precise mechanism controlling PRDM16 protein levels in vivo.

While mechansims controlling PRDM16 protein stability and nuclear localization in the developing brain are interesting, the scope of this paper is revealing the function of PRDM16 in the choroid plexus and its interaction with BMP signaling. We will be happy to pursuit this direction in our next study.

(2) Reliance on overexpression of PRDM16 in NSC cultures. To study PRDM16 function in vitro, the authors used a lentiviral construct to constitutively express PRDM16 in NSCs. While this approach allowed them to overcome the issue of low PRDM16 protein levels in vitro, it is important to consider that overexpressing PRDM16 may not fully recapitulate its physiological role in regulating gene expression and cell behavior.

As stated above, we acknowledge that findings from cultured NSCs may not directly apply to ChP cells in vivo. We are cautious with our statements. The cell culture work was aimed to identify potential mechanisms by which PRDM16 and SMADs interact to regulate gene expression and target genes co-regulated by these factors. We expect that not all targets from cell culture are regulated by PRDM16 and SMADs in the ChP, so we validated expression changes of several target genes in the developing ChP and now included the new data in Fig. 7 and Supplementary Fig. 7. Out of the 31 genes identified from cultured cells, four cell cycle regulators including Wnt7b, Id3, Spc24/25/nuf2 and Mybl2, showed de-repression in Prdm16 mutant ChP. These genes can be relevant downstream genes in the ChP, and other target genes may be cortical NSC-specific or less dependent on Prdm16 in vivo.

(3) Lack of direct evidence for AP1 as the co-factor responsible for SMAD relocation in the absence of PRDM16. While the study identified the AP1 motif as enriched in SMAD binding sites in Prdm16 knockout cells, they only provided ChIP-qPCR validation for c-FOS binding at two specific loci (Wnt7b and Id3). Further investigation is needed to confirm the direct interaction between AP1 and SMAD proteins in the absence of PRDM16 and to rule out other potential co-factors.

We agree that the finding of the AP1 motif enriched at the PRDM16 and SMAD co-binding regions in Prdm16 KO cells can only indirectly suggest AP1 as a co-factor for SMAD relocation. That’s why we used ChIP-qPCR to examine the presence of C-fos at these sites. Although we only validated two targets, the result confirms that C-fos binds to the sites only in the Prdm16 KO cells but not Prdm16_expressing cells, suggesting AP1 is a co-factor.  We results cannot rule out the presence of other co-factors.

Reviewer #3 (Public review):

Summary:

Bone morphogenetic protein (BMP) signaling instructs multiple processes during development including cell proliferation and differentiation. The authors set out to understand the role of PRDM16 in these various functions of BMP signaling. They find that PRDM16 and BMP co-operate to repress stem cell proliferation by regulating the genomic distribution of BMP pathway transcription factors. They additionally show that PRDM16 impacts choroid plexus epithelial cell specification. The authors provide evidence for a regulatory circuit (constituting of BMP, PRDM16, and Wnt) that influences stem cell proliferation/differentiation.

Strengths:

I find the topics studied by the authors in this study of general interest to the field, the experiments well-controlled and the analysis in the paper sound.

Weaknesses:

I have no major scientific concerns. I have some minor recommendations that will help improve the paper (regarding the discussion).

We will revise the discussion according the suggestions.

eLife Assessment

The authors utilize a valuable computational approach to exploring the mechanisms of memory-dependent klinotaxis, with a hypothesis that is both plausible and testable. Although they provide a solid hypothesis of circuit function based on an established model, the model's lack of integration of newer experimental findings, its reliance on predefined synaptic states, and oversimplified sensory dynamics, make the investigation incomplete for both memory and internal-state modulation of taxis.

Reviewer #1 (Public review):

Summary:

This research focuses on C. elegans klinotaxis, a chemotactic behavior characterized by gradual turning, aiming to uncover the neural circuit mechanism responsible for the context-dependent reversal of salt concentration preference. The phenomenon observed is that the preferred salt concentration depends on the difference between the pre-assay cultivation conditions and the current environmental salt levels.

The authors propose that a synaptic-reversal plasticity mechanism at the primary sensory neuron, ASER, is critical for this memory- and context-dependent switching of preference. They build on prior findings regarding synaptic reversal between ASER and AIB, as well as the receptor composition of AIY neurons, to hypothesize that similar "plasticity" between ASER and AIY underpins salt preference behavior in klinotaxis. This plasticity differs conceptually from the classical one as it does not rely on any structural changes but rather synaptic transmission is modulated by the basal level of glutamate, and can switch from inhibitory to excitatory.

To test this hypothesis, the study employs a previously established neuroanatomically grounded model [4] and demonstrates that reversing the ASER-AIY synapse sign in the model agent reproduces the observed reversal in salt preference. The model is parameterized using a computational search technique (evolutionary algorithm) to optimize unknown electrophysiological parameters for chemotaxis performance. Experimental validity is ensured by incorporating constraints derived from published findings, confirming the plausibility of the proposed mechanism.

Finally. the circuit mechanism allowing C. elegans to switch behaviour to an exploration run when starved is also investigated. This extension highlights how internal states, such as hunger, can dynamically reshape sensory-motor programs to drive context-appropriate behaviors.

Strengths and weaknesses:

The authors' approach of integrating prior knowledge of receptor composition and synaptic reversal with the repurposing of a published neuroanatomical model [4] is a significant strength. This methodology not only ensures biological plausibility but also leverages a solid, reproducible modeling foundation to explore and test novel hypotheses effectively.

The evidence produced that the original model has been successfully reproduced is convincing.

The writing of the manuscript needs revision as it makes comprehension difficult.

One major weakness is that the model does not incorporate key findings that have emerged since the original model's publication in 2013, limiting the support for the proposed mechanism. In particular, ablation studies indicate that AIY is not critical for chemotaxis, and other interneurons may play partially overlapping roles in positive versus negative chemotaxis. These findings challenge the centrality of AIY and suggest the model oversimplifies the circuit involved in klinotaxis.

Reference [1] also shows that ASER neurons exhibit complex, memory- and context-dependent responses, which are not accounted for in the model and may have a significant impact on chemotactic model behaviour.

The hypothesis of synaptic reversal between ASER and AIY is not explicitly modeled in terms of receptor-specific dynamics or glutamate basal levels. Instead, the ASER-to-AIY connection is predefined as inhibitory or excitatory in separate models. This approach limits the model's ability to test the full range of mechanisms hypothesized to drive behavioral switching.

While the main results - such as response dependence on step inputs at different phases of the oscillator - are consistent with those observed in chemotaxis models with explicit neural dynamics (e.g., Reference [2]), the lack of richer neural dynamics could overlook critical effects. For example, the authors highlight the influence of gap junctions on turning sensitivity but do not sufficiently analyze the underlying mechanisms driving these effects. The role of gap junctions in the model may be oversimplified because, as in the original model [4], the oscillator dynamics are not intrinsically generated by an oscillator circuit but are instead externally imposed via $z_\text{osc}$. This simplification should be carefully considered when interpreting the contributions of specific connections to network dynamics. Lastly, the complex and context-dependent responses of ASER [1] might interact with circuit dynamics in ways that are not captured by the current simplified implementation. These simplifications could limit the model's ability to account for the interplay between sensory encoding and motor responses in C. elegans chemotaxis.

Appraisal:

The authors show that their model can reproduce memory-dependent reversal of preference in klinotaxis, demonstrating that the ASER-to-AIY synapse plays a key role in switching chemotactic preferences. By switching the ASER-AIY connection from excitatory to inhibitory they indeed show that salt preference reverses. They also show that the curving/turn rate underlying the preference change is gradual and depends on the weight between ASER-AIY. They further support their claim by showing that curving rates also depend on cultivated (set-point).

Thus within the constraints of the hypothesis and the framework, the model operates as expected and aligns with some experimental findings. However, significant omissions of key experimental evidence raise questions on whether the proposed neural mechanisms are sufficient for reversal in salt-preference chemotaxis.

Previous work [1] has shown that individually ablating the AIZ or AIY interneurons has essentially no effect on the Chemotactic Index (CI) toward the set point ([1] Figure 6). Furthermore, in [1] the authors report that different postsynaptic neurons are required for movement above or below the set point. The manuscript should address how this evidence fits with their model by attempting similar ablations. It is possible that the CI is rescued by klinokinesis but this needs to be tested on an extension of this model to provide a more compelling argument.

The investigation of dispersal behaviour in starved individuals is rather limited to testing by imposing inhibition of the SMB neurons. Although a circuit is proposed for how hunger states modulate taxis in the absence of food, this circuit hypothesis is not explicitly modelled to test the theory or provide novel insights.

Impact :

This research underscores the value of an embodied approach to understanding chemotaxis, addressing an important memory mechanism that enables adaptive behavior in the sensorimotor circuits supporting C. elegans chemotaxis. The principle of operation - the dependence of motor responses to sensory inputs on the phase of oscillation - appears to be a convergent solution to taxis. Similar mechanisms have been proposed in Drosophila larvae chemotaxis [2], zebrafish phototaxis [3], and other systems. Consequently, the proposed mechanism has broader implications for understanding how adaptive behaviors are embedded within sensorimotor systems and how experience shapes these circuits across species.

Although the reported reversal of synaptic connection from excitatory to inhibitory is an exciting phenomenon of broad interest, it is not entirely new, as the authors acknowledge similar reversals have been reported in ASER-to-AIB signaling for klinokinesis ( Hiroki et al., 2022). The proposed reversal of the ASER-to-AIY synaptic connection from inhibitory to excitatory is a novel contribution in the specific context of klinotaxis. While the ASER's role in gradient sensing and memory encoding has been previously identified, the current paper mechanistically models these processes, introducing a hypothesis for synaptic plasticity as the basis for bidirectional salt preference in klinotaxis.

The research also highlights how internal states, such as hunger, can dynamically reshape sensory-motor programs to drive context-appropriate behaviors.

The methodology of parameter search on a neural model of a connectome used here yielded the valuable insight that connectome information alone does not provide enough constraints to reproduce the neural circuits for behaviour. It demonstrates that additional neurophysiological constraints are required.

Additional Context

Oscillators with stimulus-driven perturbations appear to be a convergent solution for taxis and navigation across species. Similar mechanisms have been studied in zebrafish phototaxis [3], Drosophila larvae chemotaxis [2], and have even been proposed to underlie search runs in ants. The modulation of taxis by context and memory is a ubiquitous requirement, with parallels across species. For example, Drosophila larvae modulate taxis based on current food availability and predicted rewards associated with odors, though the underlying mechanism remains elusive. The synaptic reversal mechanism highlighted in this study offers a compelling framework for understanding how taxis circuits integrate context-related memory retrieval more broadly.

As a side note, an interesting difference emerges when comparing C. elegans and Drosophila larvae chemotaxis. In Drosophila larvae, oscillatory mechanisms are hypothesized to underlie all chemotactic reorientations, ranging from large turns to smaller directional biases (weathervaning). By contrast, in C. elegans, weathervaning and pirouettes are treated as distinct strategies, often attributed to separate neural mechanisms. This raises the possibility that their motor execution could share a common oscillator-based framework. Re-examining their overlap might reveal deeper insights into the neural principles underlying these maneuvers.

(1) Luo, L., Wen, Q., Ren, J., Hendricks, M., Gershow, M., Qin, Y., Greenwood, J., Soucy, E.R., Klein, M., Smith-Parker, H.K., & Calvo, A.C. (2014). Dynamic encoding of perception, memory, and movement in a C. elegans chemotaxis circuit. Neuron, 82(5), 1115-1128.

(2) Antoine Wystrach, Konstantinos Lagogiannis, Barbara Webb (2016) Continuous lateral oscillations as a core mechanism for taxis in Drosophila larvae eLife 5:e15504.

(3) Wolf, S., Dubreuil, A.M., Bertoni, T. et al. Sensorimotor computation underlying phototaxis in zebrafish. Nat Commun 8, 651 (2017).

(4) Izquierdo, E.J. and Beer, R.D., 2013. Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis. PLoS computational biology, 9(2), p.e1002890.

Reviewer #2 (Public review):

Summary:

This study explores how a simple sensorimotor circuit in the nematode C. elegans enables it to navigate salt gradients based on past experiences. Using computational simulations and previously described neural connections, the study demonstrates how a single neuron, ASER, can change its signaling behavior in response to different salt conditions, with which the worm is able to "remember" prior environments and adjust its navigation toward "preferred" salinity accordingly.

Strengths:

The key novelty and strength of this paper is the explicit demonstration of computational neurobehavioral modeling and evolutionary algorithms to elucidate the synaptic plasticity in a minimal neural circuit that is sufficient to replicate memory-based chemotaxis. In particular, with changes in ASER's glutamate release and sensitivity of downstream neurons, the ASER neuron adjusts its output to be either excitatory or inhibitory depending on ambient salt concentration, enabling the worm to navigate toward or away from salt gradients based on prior exposure to salt concentration.

Weaknesses:

While the model successfully replicates some behaviors observed in previous experiments, many key assumptions lack direct biological validation. As to the model output readouts, the model considers only endpoint behaviors (chemotaxis index) rather than the full dynamics of navigation, which limits its predictive power. Moreover, some results presented in the paper lack interpretation, and many descriptions in the main text are overly technical and require clearer definitions.

Author response:

eLife Assessment 

The authors utilize a valuable computational approach to exploring the mechanisms of memorydependent klinotaxis, with a hypothesis that is both plausible and testable. Although they provide a solid hypothesis of circuit function based on an established model, the model's lack of integration of newer experimental findings, its reliance on predefined synaptic states, and oversimplified sensory dynamics, make the investigation incomplete for both memory and internal-state modulation of taxis.  

We would like to express our gratitude to the editor for the assessment of our work. However, we respectfully disagree with the assessment that our investigation is incomplete, if the negative assessment is primarily due to the impact of AIY interneuron ablation on the chemotaxis index (CI) which was reported in Reference [1]. It is crucial to acknowledge that the CI determined through experimental means incorporates contributions from both klinokinesis and klinotaxis [1]. It is plausible that the impact of AIY ablation was not adequately reflected in the CI value. Consequently, the experimental observation does not necessarily diminish the role of AIY in klinotaxis. Anatomical evidence provided by the database (http://ims.dse.ibaraki.ac.jp/ccep-tool/) substantiates that ASE sensory neurons and AIZ interneurons, which have been demonstrated to play a crucial role in klinotaxis [Matsumoto et al., PNAS 121 (5) e2310735121], have the highest number of synaptic connections with AIY interneurons. These findings provide substantial evidence supporting the validity of the presented minimal neural network responsible for salt klinotaxis.

Public Reviews: 

Reviewer #1 (Public review): 

Summary: 

This research focuses on C. elegans klinotaxis, a chemotactic behavior characterized by gradual turning, aiming to uncover the neural circuit mechanism responsible for the context-dependent reversal of salt concentration preference. The phenomenon observed is that the preferred salt concentration depends on the difference between the pre-assay cultivation conditions and the current environmental salt levels. 

We would like to express our gratitude for the time and consideration you have dedicated to reviewing our manuscript.

The authors propose that a synaptic-reversal plasticity mechanism at the primary sensory neuron, ASER, is critical for this memory- and context-dependent switching of preference. They build on prior findings regarding synaptic reversal between ASER and AIB, as well as the receptor composition of AIY neurons, to hypothesize that similar "plasticity" between ASER and AIY underpins salt preference behavior in klinotaxis. This plasticity differs conceptually from the classical one as it does not rely on any structural changes but rather synaptic transmission is modulated by the basal level of glutamate, and can switch from inhibitory to excitatory. 

To test this hypothesis, the study employs a previously established neuroanatomically grounded model [4] and demonstrates that reversing the ASER-AIY synapse sign in the model agent reproduces the observed reversal in salt preference. The model is parameterized using a computational search technique (evolutionary algorithm) to optimize unknown electrophysiological parameters for chemotaxis performance. Experimental validity is ensured by incorporating constraints derived from published findings, confirming the plausibility of the proposed mechanism. 

Finally. the circuit mechanism allowing C. elegans to switch behaviour to an exploration run when starved is also investigated. This extension highlights how internal states, such as hunger, can dynamically reshape sensory-motor programs to drive context-appropriate behaviors.  

We would like to thank the reviewer for the appropriate summary of our work. 

Strengths and weaknesses: 

The authors' approach of integrating prior knowledge of receptor composition and synaptic reversal with the repurposing of a published neuroanatomical model [4] is a significant strength.

This methodology not only ensures biological plausibility but also leverages a solid, reproducible modeling foundation to explore and test novel hypotheses effectively.

The evidence produced that the original model has been successfully reproduced is convincing.

The writing of the manuscript needs revision as it makes comprehension difficult.  

We would like to thank the reviewer for recognizing the usefulness of our approach. In the revised version, we will improve the explanation.  

One major weakness is that the model does not incorporate key findings that have emerged since the original model's publication in 2013, limiting the support for the proposed mechanism. In particular, ablation studies indicate that AIY is not critical for chemotaxis, and other interneurons may play partially overlapping roles in positive versus negative chemotaxis. These findings challenge the centrality of AIY and suggest the model oversimplifies the circuit involved in klinotaxis.

We would like to express our gratitude for the constructive feedback we have received. We concur with some of your assertions. In fact, our model is the minimal network for salt klinotaxis, which includes solely the interneurons that are connected to each other via the highest number of synaptic connections. It is important to note that our model does not consider redundant interneurons that exhibit overlapping roles. Consequently, the model is not applicable to the study of the impact of interneuron ablation. In the reference [1], the influence of interneuron ablations on the chemotaxis index (CI) has been investigated. The experimentally determined CI value incorporates the contributions from both klinokinesis and klinotaxis. Consequently, it is plausible that the impact of AIY ablation was not significantly reflected in the CI value. The experimental observation does not necessarily diminish the role of AIY in klinotaxis. 

Reference [1] also shows that ASER neurons exhibit complex, memory- and context-dependent responses, which are not accounted for in the model and may have a significant impact on chemotactic model behaviour. 

As pointed out by the reviewer, our model does not incorporate the context-dependent response of the ASER. Instead, the salt concentration-dependent glutamate release from the ASRE [S. Hiroki et al. Nat Commun 13, 2928 (2022)] as the result of the ASER responses is considered in the present study.

The hypothesis of synaptic reversal between ASER and AIY is not explicitly modeled in terms of receptor-specific dynamics or glutamate basal levels. Instead, the ASER-to-AIY connection is predefined as inhibitory or excitatory in separate models. This approach limits the model's ability to test the full range of mechanisms hypothesized to drive behavioral switching.  

We would like to thank the reviewer for the helpful comments. In the revised version, we will mention the limitation.

While the main results - such as response dependence on step inputs at different phases of the oscillator - are consistent with those observed in chemotaxis models with explicit neural dynamics (e.g., Reference [2]), the lack of richer neural dynamics could overlook critical effects. For example, the authors highlight the influence of gap junctions on turning sensitivity but do not sufficiently analyze the underlying mechanisms driving these effects. The role of gap junctions in the model may be oversimplified because, as in the original model [4], the oscillator dynamics are not intrinsically generated by an oscillator circuit but are instead externally imposed via $z_¥text{osc}$. This simplification should be carefully considered when interpreting the contributions of specific connections to network dynamics. Lastly, the complex and contextdependent responses of ASER [1] might interact with circuit dynamics in ways that are not captured by the current simplified implementation. These simplifications could limit the model's ability to account for the interplay between sensory encoding and motor responses in C. elegans chemotaxis. 

We might not understand the substance of your assertions. However, we understand that the oscillator dynamics were not generated by an oscillator neural circuit in our modeling. On the other hand, the present study focuses on how the sensory input and resulting interneuron dynamics regulate the oscillatory activity of SMB motor neurons to generate klinotaxis. 

Appraisal: 

The authors show that their model can reproduce memory-dependent reversal of preference in klinotaxis, demonstrating that the ASER-to-AIY synapse plays a key role in switching chemotactic preferences. By switching the ASER-AIY connection from excitatory to inhibitory they indeed show that salt preference reverses. They also show that the curving/turn rate underlying the preference change is gradual and depends on the weight between ASER-AIY. They further support their claim by showing that curving rates also depend on cultivated (set-point).  

We would like to thank the reviewer for assessing our work.

Thus within the constraints of the hypothesis and the framework, the model operates as expected and aligns with some experimental findings. However, significant omissions of key experimental evidence raise questions on whether the proposed neural mechanisms are sufficient for reversal in salt-preference chemotaxis.  

We agree with your opinion. The present hypothesis should be verified by experiments.

Previous work [1] has shown that individually ablating the AIZ or AIY interneurons has essentially no effect on the Chemotactic Index (CI) toward the set point ([1] Figure 6). Furthermore, in [1] the authors report that different postsynaptic neurons are required for movement above or below the set point. The manuscript should address how this evidence fits with their model by attempting similar ablations. It is possible that the CI is rescued by klinokinesis but this needs to be tested on an extension of this model to provide a more compelling argument.  

We would like to express our gratitude for the constructive feedback we have received. In the reference [1], the influence of interneuron ablations on the chemotaxis index (CI) has been investigated. It is important to acknowledge that the experimentally determined CI value encompasses the contributions of both klinokinesis and klinotaxis. It is plausible that the impact of AIY ablation was not reflected in the CI value. Consequently, these experimental observations do not necessarily diminish the role of AIY in klinotaxis. The neural circuit model employed in the present study constitutes a minimal network for salt klinotaxis, encompassing solely interneurons that are connected to each other via the highest number of synaptic connections. Anatomical evidence provided by the database (http://ims.dse.ibaraki.ac.jp/cceptool/) substantiates that ASE sensory neurons and AIZ interneurons, which have been demonstrated to play a crucial role in klinotaxis [Matsumoto et al., PNAS 121 (5) e2310735121], have the highest number of synaptic connections with AIY interneurons. Our model does not take into account redundant interneurons with overlapping roles, thus rendering it not applicable to the study of the effects of interneuron ablation.

The investigation of dispersal behaviour in starved individuals is rather limited to testing by imposing inhibition of the SMB neurons. Although a circuit is proposed for how hunger states modulate taxis in the absence of food, this circuit hypothesis is not explicitly modelled to test the theory or provide novel insights.  

As pointed out by the reviewer, the neural circuit that inhibits the SMB motor neurons was not explicitly incorporated in our model. We then examined whether our minimal network model could reproduce dispersal behavior under starvation conditions solely due to the experimentally identified inhibitory effect of SMB motor neurons.

Impact : 

This research underscores the value of an embodied approach to understanding chemotaxis, addressing an important memory mechanism that enables adaptive behavior in the sensorimotor circuits supporting C. elegans chemotaxis. The principle of operation - the dependence of motor responses to sensory inputs on the phase of oscillation - appears to be a convergent solution to taxis. Similar mechanisms have been proposed in Drosophila larvae chemotaxis [2], zebrafish phototaxis [3], and other systems. Consequently, the proposed mechanism has broader implications for understanding how adaptive behaviors are embedded within sensorimotor systems and how experience shapes these circuits across species.

We would like to express our gratitude for useful suggestion. We will add the argument that the reviewer mentioned in the revised version.  

Although the reported reversal of synaptic connection from excitatory to inhibitory is an exciting phenomenon of broad interest, it is not entirely new, as the authors acknowledge similar reversals have been reported in ASER-to-AIB signaling for klinokinesis ( Hiroki et al., 2022). The proposed reversal of the ASER-to-AIY synaptic connection from inhibitory to excitatory is a novel contribution in the specific context of klinotaxis. While the ASER's role in gradient sensing and memory encoding has been previously identified, the current paper mechanistically models these processes, introducing a hypothesis for synaptic plasticity as the basis for bidirectional salt preference in klinotaxis.  

The research also highlights how internal states, such as hunger, can dynamically reshape sensory-motor programs to drive context-appropriate behaviors.  

The methodology of parameter search on a neural model of a connectome used here yielded the valuable insight that connectome information alone does not provide enough constraints to reproduce the neural circuits for behaviour. It demonstrates that additional neurophysiological constraints are required.  

We would like to acknowledge the appropriate recognition of our work.

Additional Context 

Oscillators with stimulus-driven perturbations appear to be a convergent solution for taxis and navigation across species. Similar mechanisms have been studied in zebrafish phototaxis [3],

Drosophila larvae chemotaxis [2], and have even been proposed to underlie search runs in ants.

The modulation of taxis by context and memory is a ubiquitous requirement, with parallels across species. For example, Drosophila larvae modulate taxis based on current food availability and predicted rewards associated with odors, though the underlying mechanism remains elusive. The synaptic reversal mechanism highlighted in this study offers a compelling framework for understanding how taxis circuits integrate context-related memory retrieval more broadly.  

We would like to express our gratitude for the insightful commentary. In the revised version, we will incorporate the discussion that the similar oscillator mechanism with stimulus-driven perturbations has been observed for zebrafish phototaxis [3] and Drosophila larvae chemotaxis [2].

As a side note, an interesting difference emerges when comparing C. elegans and Drosophila larvae chemotaxis. In Drosophila larvae, oscillatory mechanisms are hypothesized to underlie all chemotactic reorientations, ranging from large turns to smaller directional biases (weathervaning). By contrast, in C. elegans, weathervaning and pirouettes are treated as distinct strategies, often attributed to separate neural mechanisms. This raises the possibility that their motor execution could share a common oscillator-based framework. Re-examining their overlap might reveal deeper insights into the neural principles underlying these maneuvers. 

We would like to acknowledge your thoughtfully articulated comment. As pointed out by the reviewer, from the anatomical database (http://ims.dse.ibaraki.ac.jp/ccep-tool/), we found that the neural circuits underlying weathervaning and pirouettes in C. elegans are predominantly distinct but exhibit partial overlap. When we restrict our search to the neurons that are connected to each other with the highest number of synaptic connections, we identify the projections from the neural circuit of weathervaning to the circuit of pirouettes; however we observed no reversal projections. This finding suggests that the neural circuit of weathervaning, namely, our minimal neural network, is not likely to be affected by that of pirouettes, which consists of AIB interneurons and interneurons and motor neurons the downstream. 

(1) Luo, L., Wen, Q., Ren, J., Hendricks, M., Gershow, M., Qin, Y., Greenwood, J., Soucy, E.R., Klein, M., Smith-Parker, H.K., & Calvo, A.C. (2014). Dynamic encoding of perception, memory, and movement in a C. elegans chemotaxis circuit. Neuron, 82(5), 1115-1128. 

(2) Antoine Wystrach, Konstantinos Lagogiannis, Barbara Webb (2016) Continuous lateral oscillations as a core mechanism for taxis in Drosophila larvae eLife 5:e15504. 

(3) Wolf, S., Dubreuil, A.M., Bertoni, T. et al. Sensorimotor computation underlying phototaxis in zebrafish. Nat Commun 8, 651 (2017). 

(4) Izquierdo, E.J. and Beer, R.D., 2013. Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis. PLoS computational biology, 9(2), p.e1002890. 

Reviewer #2 (Public review): 

Summary: 

This study explores how a simple sensorimotor circuit in the nematode C. elegans enables it to navigate salt gradients based on past experiences. Using computational simulations and previously described neural connections, the study demonstrates how a single neuron, ASER, can change its signaling behavior in response to different salt conditions, with which the worm is able to "remember" prior environments and adjust its navigation toward "preferred" salinity accordingly.  

We would like to express our gratitude for the time and consideration the reviewer has dedicated to reviewing our manuscript.

Strengths: 

The key novelty and strength of this paper is the explicit demonstration of computational neurobehavioral modeling and evolutionary algorithms to elucidate the synaptic plasticity in a minimal neural circuit that is sufficient to replicate memory-based chemotaxis. In particular, with changes in ASER's glutamate release and sensitivity of downstream neurons, the ASER neuron adjusts its output to be either excitatory or inhibitory depending on ambient salt concentration, enabling the worm to navigate toward or away from salt gradients based on prior exposure to salt concentration.

We would like to thank the reviewer for appreciating our research. 

Weaknesses: 

While the model successfully replicates some behaviors observed in previous experiments, many key assumptions lack direct biological validation. As to the model output readouts, the model considers only endpoint behaviors (chemotaxis index) rather than the full dynamics of navigation, which limits its predictive power. Moreover, some results presented in the paper lack interpretation, and many descriptions in the main text are overly technical and require clearer definitions.  

We would like to thank the reviewer for the constructive feedback. As the reviewer noted, the fundamental assumptions posited in the study have yet to be substantiated by biological validation. Consequently, these assumptions must be directly assessed by biological experimentation. The model performance for salt klinotaxis is evaluated by multiple factors, including not only a chemotaxis index but also the curving rate vs. bearing (Fig. 4a, the bearing is defined in Fig. A3) and the curving rate vs. normal gradient (Fig. 4c). The subsequent two parameters work to characterize the trajectory during salt klinotaxis. In the revised version, we will meticulously revise the manuscript according to the suggestions by the reviewer. We would like to express our sincere gratitude for your insightful review of our work.

eLife Assessment

This important study examines the role of pericytes in patterning the zebrafish blood-brain barrier (BBB) and controlling its permeability. Using pdgfrb mutant zebrafish models lacking brain pericytes, the authors report that pericyte-deficient cerebrovasculatures are ill-patterned, yet display unaltered restrictive BBB permeability properties at larval and juvenile stages. More severe phenotypes are detected in adults, with focal leakage sites associated with hemorrhages and aneurysms. Using solid and beautifully documented imaging, the authors suggest that, contrary to the situation described in rodent models, pdgfrb-dependent pericytes are not required to maintain the BBB in the zebrafish brain; these unexpected and intriguing findings reshape our understanding of BBB permeability regulation in vertebrates.

Reviewer #1 (Public review):

Summary:

The study investigates the role of vascular mural cells, specifically pericytes and vascular smooth muscle cells (vSMCs), in maintaining blood-brain barrier (BBB) integrity and regulating vascular patterning. Analyzing zebrafish pdgfrb mutants that lack brain pericytes and vSMCs, they show that mural cell deficiency does not impair BBB establishment or maintenance during larval and early juvenile stages. However, mural cells seem to be crucial for preventing vascular aneurysms and hemorrhage in adulthood as focal leakage, basement membrane disruption, and increased caveolae formation are observed in adult zebrafish at aneurysm hotspots. The authors challenge the paradigm that mural cells are essential for BBB regulation in early development while highlighting their importance for long-term vascular stability.

Strengths:

Previous studies have established that the zebrafish BBB shares molecular and morphological homology with e.g. the mammalian BBB and therefore represents a suitable model. By examining mural cell roles across different life stages - from larval to adult zebrafish - the study provides an unprecedented comprehensive developmental analysis of brain vascular development and of how mural cells influence BBB integrity and vascular stability over time. The use of live imaging, whole-brain clearing, and electron microscopy offers high-resolution insights into cerebrovascular patterning, aneurysm development, and structural changes in endothelial cells and basement membranes. By analyzing "leakage hotspots" and their association with structural endothelial defects in adults the presented findings add novel insights into how mural cell loss may lead to vascular instability.

Weaknesses:

The study uses quantitative tracer assays with multiple molecular weight dyes to evaluate blood-brain barrier (BBB) permeability. The study normalizes the intensity of tracer signals (e.g., 10 kDa, 70 kDa dextrans) in the brain parenchyma to the vascular signal of a 2000 kDa dextran tracer (assumed to remain within vessels). Intensity normalization is used to control for variations in tracer injection efficiency or vascular density. This method doesn't directly assess the absolute amount of tracer present in the parenchyma, potentially underestimating leakage severity. As the lack of BBB impairment is a "negative" finding, more rigorous controls or other methods might be needed to corroborate it.

Reviewer #2 (Public review):

Summary:

The authors generated a zebrafish mutant of the pdgfrb gene. The presented analyses and data confirm previous studies demonstrating that Pdgfrb signaling is necessary for mural cell development in zebrafish. In addition, the data support previously published studies in zebrafish showing that mural cell deficiency leads to hemorrhages later in life. The authors presented quantified data on vessel density and branching, assessed tracer extravasation, and investigated the vasculature of adult mice using electron microscopy.

Strengths:

The strength of this article is that it provides independent confirmation of the important role of Pdgfrb signaling for the development of mural cells in the zebrafish brain. In addition, it confirms previous literature on zebrafish that provides evidence that, in the absence of pericytes/VSMC, hemorrhages appear (Wang et al, 2014, PMID: 24306108 and Ando et al 2021, PMID: 3431092). The study by Ando et al, 2021 did not report experiments assessing BBB leakage in pdgfrb mutants but in the review article by Ando et al (PMID: 34685412) it is stated that "indicating that endothelial cells can produce basic barrier integrity without pericytes in zebrafish".

Weaknesses:

(1) The authors should avoid using violin plots, which show distribution. Instead, they should replace all violin plots in the figures with graphs showing individual data points and standard deviation. For Figure 2f specifically, the standard deviation in the analyzed cohort should be shown.

(2) The authors have not shown the reduced PDGFRB protein or the effect of mutation on mRNA level in their zebrafish mutant.

(3) Statistical data analysis: Did the authors perform analyses to investigate whether the data has a normal distribution (e.g., Figures 1d, e)?

(4) Analysis of tracer extravasation. The use of 2000 kDa dextran intensity as an internal reference is problematic because the authors have not provided data demonstrating that the 2000 kDa dextran signal remains consistent across the entire vasculature. The authors have not provided data demonstrating that the 2000 kDa dextran signal in vessels exhibits acceptable variance across the vasculature to serve as a reliable internal reference. The variability of this signal within a single animal remains unknown. The presented data do not address this aspect.

Additionally, it's intriguing that the signal intensity in the parenchyma of the tested tracers presents a substantial range, varying by 20-30% in the analysed cohort (Figure 1g, Extended Figure 1e). Such large variability raises the question of its origin. Could it be a consequence of the normalization to 2000 kDa dextran intensity which differs between different fish? Or is it due to the differences in the parenchymal signal intensity while the baseline 2000 kDa intensity is stable? Or is the situation mixed?

An alternative and potentially more effective approach would be to cross the pdgfrb mutant line with a line where endothelial cells are genetically labeled to define vessels (e.g. the line kdrl used in acquiring data presented in Figure 2a). Non-injected controls could then be used as a baseline to assess tracer extravasation into the parenchyma.

How is the data presented in Figure 3e generated? How was the dextran intensity calculated? It looks like the authors have used the kdrl line to define vessels. Was the 2000 kDa still used as in previous figures? If not, please describe this in the Materials and Methods section.

(5) The authors state that both controls and mutants show extravasation of 1 kDa NHS-ester into the parenchyma. However, the presented images do not illustrate this; it is not obvious from these images (Extended Data Figure 1c). Additionally, the presented quantification data (Extended Data Figure 1e) do not show that, at 7 dpf, the vasculature is permeable to this tracer. Note that the range of signal intensity of the 1 kDa NHS-ester is similar to the 70 kDa dextran (Figure 1g and Extended Figure 1e). Would one expect an increase in the ratio in case of extravasation, considering that the 2000 kDa dextran has the same intensity in all experiments? Please explain.

(6) The study would be strengthened by a more detailed temporal analysis of the phenotype. When do the aneurysms appear? Is there an additional loss of VSMC?

(7) The authors intended to analyze the BBB at later stages (line 128), but there is not a significant time difference between 2 months (Figure 2) and 3 months (Figure 3) considering that zebrafish live on average 3 years. Therefore, the selection of only two time-points, 2 and 3 months, to analyze BBB changes does not provide a comprehensive overview of temporal changes throughout the zebrafish's lifespan. How long do the pdgfb mutants live?

(8) Why is there a difference in tracer permeability between 2 and 3 months (Figures 2 and 3)? Are hemorrhages not detected in 2-month-old zebrafish?

(9) Figure 3: The capillary bed should be presented in magnified images as it is not clearly visible. Figure 3e shows that in the pdgfb mutant the dextran intensity is higher also in regions 6-10. How do the authors explain this?

(10) In general, the manuscript would benefit from a more detailed description of the performed experiments. How long did the tracer circulate in the experiments presented in Figures 2, 3, and 4?

(11) How do the authors explain the poor signal of the 70 kDa dextran from the vasculature of 5-month-old zebrafish presented in Extended Data Figure 3?

(12) The study would benefit from a clear separation of the phenotypes caused by the loss of VSMC. The title eludes that also capillaries present hemorrhages which is not the case. How do vascular mural cells differ from mural cells? Are there any other mural cells?

(13) I have a few comments about how the authors have interpreted the literature and why, in my opinion, they should revise their strong statements (e.g., the last sentence in the abstract).

Scientists have their own insights and interpretations of data. However, when citing published data, it should be clearly indicated whether the statement is a direct quote from the original publication or an interpretation. In the current manuscript, the authors have not correctly cited the data presented in the two published papers (references 5 and 6). These papers do not propose a model where pericytes suppress "adsorptive transcytosis" (lines 73-76). While increased transcytosis is observed in pericyte-deficient mice, the specific type of vesicular transport that is increased or induced remains unknown.

Similarly, lines 151-152 refer to references 5 and 6 and use the term "adsorptive transcytosis," but the authors of both papers did not use this term. Attributing this term to the original authors is inaccurate. Additionally, lines 152-153 do not accurately represent the findings of references 5 and 6. These papers do not state that there is an induction of "caveolae" in endothelial cells in pericyte-deficient mice. In the absence of pericytes, many vesicles can be observed in endothelial cells, but these vesicles are relatively large. It is more likely that there is some form of uncontrolled transcytosis, perhaps micropinocytosis. Please refer to the original papers accurately.

Also, the authors have missed the fact that in mice, the extent of pericyte loss correlates with the extent of BBB leakage. To a certain extent, the remaining pericytes, can compensate for the loss by making longer processes and so ensure the full longitudinal coverage of the endothelium. This was shown in the initial work of Armulik et al (reference 5) and later in other studies.

The bold assertion on lines 183 -187 that a lack of specific BBB phenotype in pdgfrb zebrafish mutant invalidates mouse model findings is unfounded. Despite the notion that zebrafish endothelium possesses a BBB, I present a few examples highlighting the differences in brain vascular development and why the authors' expectation of a straightforward extrapolation of mouse BBB phenotypes to zebrafish is untenable.

In mice Pdgfrb knockout is lethal, but in zebrafish, this is not the case. In marked contrast to mice, however, zebrafish pdgfrb null mutants reach adulthood despite extensive cerebral vascular anomalies and hemorrhage. Following the authors' argumentation about the unlikely divergence of zebrafish and mice evolution, does it mean that the described mouse phenotype warrants a revisit and that the Pdgfrb knockout in mice perhaps is not lethal? Another example where the role of a gene product is not one-to-one, which relates to pericyte development, is Notch3. Notch3-null mice do not show significant changes in pericyte numbers or distribution, suggesting a less prominent role in pericyte development compared to zebrafish.

Although many aspects of development are conserved between species, there are significant differences during brain vascular development between zebrafish and mice. These differences could reveal why the BBB is not impaired in zebrafish pdgfrb mutants. There is a difference in the temporal aspect when various cellular players emerge. The timing of microglia colonization in the brain differs. In mice, microglia colonization starts before the first vessel sprouts enter the brain, while in zebrafish, microglia enter after. Additionally, microglia in zebrafish and mice have a different ontogeny. In mice, astrocytes specialize postnatally and form astrocyte endfeet postnatally. In zebrafish, radial glia/astrocytes form at 48 hpf, and as early as 3 dpf, gfap+ cells have a close relationship with blood vessels. Thus, these radial glia/astrocyte-like cells could play an important role in BBB induction in zebrafish. It's worth noting that in Drosophila, the blood-brain barrier is located in glial cells. While speculative, these cells might still play a role in zebrafish, while the role of pericytes does not seem to be crucial. Pericytes enter the brain and contact with developing vasculature (endothelium) relatively late in zebrafish (60 hpf). In mice, the situation is different, as there is no such lag between endothelium and pericyte entry into the brain. I suggest that the authors approach the observed data with curiosity and ask: Why are these differences present? Are all aspects of the BBB induced by neural tissue in zebrafish? What is the contribution of microglia and astrocytes?"

Another interesting aspect to consider is the endothelial-pericyte ratio and longitudinal coverage of pericytes in the zebrafish brain, and how this relates to what is observed in mice. How similar is the zebrafish vasculature to the mouse vasculature when it comes to the average length of pericytes in the zebrafish brain? Does the longitudinal coverage of pericytes in the zebrafish brain reach nearly 100%, as it does in mice?

Based on the preceding arguments, it is recommended that the authors present a balanced discussion that provides insightful discussion and situates their work within a broader framework.

Reviewer #3 (Public review):

This manuscript examines the role of pdgfrb-positive pericytes in the establishment and maintenance of the blood-brain barrier (BBB) in the zebrafish. Previous studies in PDGFB- or PDGFRB-deficient mice have suggested that loss of pericytes results in disruption of the BBB. The authors show that zebrafish pdgfrb mutant larvae have an intact BBB and that pdgfrb mutant adult fish show large vessel defects and hemorrhage but do not exhibit substantial leakage from brain capillaries, suggesting loss of pericytes is not sufficient to "open" the BBB. The authors use beautiful and compelling images and rigorous quantification to back up most of their conclusions. The imaging of the adult brain is particularly nice. The authors rigorously document the lack of BBB leakage in pdgfrbuq30bh mutant larvae and large vessel phenotypes (eg, enlargement and rupture) in pdgfrbuq30bh mutant adults. A few points would help the authors to further strengthen their findings contradicting the current dogma from rodent models.

Major point:

The authors document pericyte loss using a single TgBAC(pdgfrb:egfp)ncv22 transgenic line driven by the promoter of the same gene mutated in their pdgfrbuq30bh mutants. Given their findings on the consequences of pericyte loss directly contradict current dogma from rodent studies, it would be useful to further validate the absence of brain pericytes in these mutants using one of several other transgenic lines marking pericytes currently available in the zebrafish. This could be done using pdgfrb crispants, which the authors show nicely phenocopy the germline mutants, at least in larvae. This would help nail down the absence of any currently identifiable pericyte population or sub-population in the loss of pdgfrb animals and substantially strengthen the authors' conclusions.

Other issues:

The authors should provide more information about the pdgfrbuq30bh mutant and how it was generated (including a diagram in a supplemental figure would be useful).

It would be helpful to show some data on whether mutants show morphological phenotypes or developmental delay at 7 and 14 dpf, to provide some context to better assess the reduced branching and vessel length vascular phenotypes (see Figures 1c-e).

If available, it would be helpful to have a positive control for the tracer leakage experiments - a genetic manipulation that does cause disruption of the BBB and leakage at 2 hours post-tracer injection (see Figures 1f and g).

Quantification of the findings in Figure 4c,d would be useful, as would the use of germline fish for these experiments if these are now available. If this is not possible, it would be helpful to document that the crispants used in these experiments lack pdgfrb:egfp pericytes at adult stages (this is only shown for 5 dpf larvae, in Extended Data Figure 4b).

Adult mutants clearly show less dye leakage in the more superficial capillary regions than WT siblings, but dextran intensity is a bit higher, although this could well be diffusion from more central brain regions where overt hemorrhage is occurring. Along similar lines though, the authors' TEM data in Extended Data Figure 4d hints that there may be more caveolae in mutant brain capillaries, although the N number was lower here than for the measurements from TEM of larger central vessels (Figure 4g). It would be useful to carry out additional measurements to increase the N number in Figure 4d to see whether the difference between wild-type sibling and mutant capillary caveolae numbers remains as not significant.

It might be helpful to include some orienting labels and/or additional descriptions in the figure legends to help readers who are not used to looking at zebrafish brain vessels have an easier time figuring out what they are looking at and where it is in the brain.

Author response:

We thank all the reviewers for their detailed comments. In response, we will address the comments with further analysis, experiments and an expanded discussion.

In terms of each specific reviewer's comments:

Reviewer 1 was positive overall but had several suggestions and requested further rigorously controls. These are highly constructive technical concerns and will be addressed through additional experimentation and methods for quantification.

Reviewer 2 summarised the strengths of the study as being largely confirmatory. They have perhaps not fully appreciated that this is the first published functional assessment of cerebral vascular permeability in a pericyte deficient zebrafish model.

The reviewer has made a number of very helpful suggestions to improve technical aspects of the analysis. Many align with the suggestions of Reviewer 1. Additional experiments that include more rigorous controls and further methods to quantify vessel permeability will address these concerns in revision.

We also note that the reviewer calls for a more nuanced and careful discussion section. We take the reviewers point and do appreciate their concerns. We were limited by wordcount in the initial submission in short report format, but in response will expand and provide a more thorough discussion.

Reviewer 3 was positive overall but has suggested additional controls and experiments to further strengthen the findings and support our conclusions. Some align with the suggestions of Reviewers 1 and 2. We agree and aim to address them through additional work in revision.

eLife Assessment

This important manuscript proposes a new strategy for the identification of new mechanisms of drug resistance based on SAturated Transposon Analysis in Yeast (SATAY), a powerful transposon sequencing method in Saccharomyces cerevisiae. This method allows us to uncover loss- and gain-of-function mutations conferring resistance to 20 different antifungal compounds. The method is convincing, allowing the authors to identify a novel interaction of chitosan with the cell wall mannosylphosphate, and show that the transporter Hol1 concentrates the novel antifungal ATI-2307 within yeast.

Reviewer #1 (Public review):

Summary:

In this study, the authors employed Saturated Transposon Analysis in Yeast (SATAY) in the model yeast Saccharomyces cerevisiae to uncover mutations conferring resistance to 20 different antifungal compounds. These screens revealed novel resistance mechanisms and the modes of action for the antifungal compounds Chitosan and HTI-2307. The authors discovered that Chitosan electrostatically interacts with cell wall mannosylphosphate and identified Hol1 as the transporter of HTI-2307.

Strengths:

The study highlights the power of SATAY in uncovering drug-resistance mechanisms, modes of action, and cellular processes influencing fungal responses to drugs. Identifying novel resistance mechanisms and modes of action for various compounds in this model yeast provides valuable insights for further investigating these compounds in fungal pathogens and developing antifungal strategies. This study thus represents a significant resource for exploring cellular responses to chemical stresses.

The manuscript is well-written and highly clear.

Weaknesses:

As the study was conducted using highly modified non-pathogenic laboratory yeast strains, verification of the findings in fungal pathogens would greatly enhance its relevance and applicability.

Reviewer #2 (Public review):

The study begins by exposing wild-type yeast libraries to some well-understood antifungals (amphotericin B, caspofungin, myriocin) to illustrate the complexity and power of the analytical method. These toxins are positively selected for loss-of-function transposon (CDS) insertions in many of the genes identified previously in earlier studies. The outlier genes were visually evident in scatter plots (Figure 1A, 1B, 1C) but the magnitude and statistical significance of the effects were not presented in tables. There were some unexplained and unexpected findings as well. For example, caspofungin targets the product of the GSC2 gene, and yet transposon insertions in this gene were positively selected rather than negatively selected (seemingly discordant from other studies).

Interestingly, transposon insertions immediately upstream of toxin targets (Figure 1D) and toxin efflux transporters or their regulators (Figure 1E) were visibly selected by exposure to the toxins, suggesting gain-of-expression. Most of these findings are convincing, even without statistical tests. However, some were not (for example, Soraphen A on YOR1). A relevant question emerges here: Do both ends of the transposon confer the same degree of cryptic enhancer/promoter activity? If one end contains strong activity on downstream gene expression while the other does not, the effects of one may be obscured by the other. The directionality of transposon insertions (not provided) would then be important to consider when interpreting the raw data.

A masterful rationalization of transposon insertion selection in the YAP1 and FLR1 genes was presented wherein loss of C-terminal auto-inhibitory domain of the Yap1 transcription factor resulted in FLR1 overexpression and resistance to Cerulenin. Transposon insertions in the CDS of YAP1 and FLR1 were negatively selected in Chlorothalonil while the gain-of-function and -expression insertions (enriched in Cerulenin) were not. The rationalization of these findings - that Chlorothalonil activates Yap1 while Cerulenin does not - was much less convincing and should be tested directly with a simple experiment such as Q-PCR.

Moving to specially engineered yeast strains (Figure 2) where multiple efflux transporters were eliminated (for Prochloraz testing) or new drug targets were inserted (for Fludioxonil and Iprodione), numerous interesting observations were obtained. For instance, transposon insertions in totally different sets of genes were enriched by prochloraz depending on the strain background. Conversely, almost the exact same genes were selected in Fludioxonil and Iprodione, including genes in the well-known HOG pathway. Because several candidate receptors of these compounds were not significant in the Tn-seq dataset, the authors add new evidence to the field suggesting that the introduced gene (BdDRK1) represents the direct, or near-direct, target of these compounds.

Chitosan effectiveness was studied by Tn-seq in yet another specialized strain of yeast that is uniquely susceptible to the toxin. Once again, the authors masterfully rationalize the complex effects, leading to a simple model where chitosan interacts with mannosyl-phosphate in the cell wall and membrane, which is deposited by Mnn4 and Mnn6 and masked by Mnn1 enzymes in the Golgi complex (themselves regulated or dependent on a number of additional gene products such as YND1. This research compellingly adds to our understanding of an industrial antifungal.

Finally, the effects of a preclinical antifungal ATI-2307 were studied for the first time. Remarkably, ATI-2307 efficacy greatly depended on HOL1 coding sequences and an upstream enhancer (Figure 4). After engineering hol1∆ strains, uptake of the compound and sensitivity to the compound were lost and then restored by heterologous expression of CaHOL1 from a pathogenic yeast. HOL1 also conferred susceptibility to polyamines with related structures (Pentamidine, Iminoctadine). Remarkably, separation-of-function mutations were obtained in HOL1 that abolished the uptake of the toxins while preserving the uptake of nutrient polyamines in low nitrogen conditions, which strongly suggests that HOL1 encodes a direct transporter of the toxins. The implications are important for ATI-2307 efficacy in patients, where resistance mutations could arise spontaneously and produce poor clinical outcomes.

Additional comments:

The experiments presented here are often convincing and serve to illustrate the power of Tn-seq approaches in elucidating drug resistance mechanisms in eukaryotic microbes. The gain-of-expression effects (upstream of CDS), gain-of-function effects (elimination of auto-inhibitory domains), and loss-of-function effects were all carefully exposed and discussed, leading to numerous new insights on the action of diverse toxins.

On the other hand, several deficiencies and weaknesses (in addition to the minor ones described above) limit the utility of the data that has been generated.

(1) There was no summary table of Tn-seq data for different genes in the different conditions, so readers could not easily access data for genes and pathways not mentioned in the text. This is especially important because transposon insertions that were negatively selected (of great interest to the community) were barely mentioned. Additionally, the statistical significance of outlier genes was not reported. The same is true for insertions within the DNA segments upstream of CDSs. Users of these data are therefore restricted to visually inspecting insertion sites on a genome browser.

(2) Only one dose of each toxin was studied, which therefore produces a limited perspective on the genetic mechanisms of resistance in each case.

(3) No Tn-seq experiments were performed in diploid yeast strains. The gain-of-expression and gain-of-function insertions under positive selection in haploid strains in the different conditions are expected to be dominant in diploid strains as well, while loss-of-function insertions in CDS are expected to be recessive. Do these expectations hold? Could such experiments potentially confirm the models for Cerulenin and Chlorothalonil effects on YAP1 and FLR1? Pathogenic Candida species are usually diploid where gain-of-function/expression mutants most frequently lead to poor clinical outcomes. Resistance to ATI-2307 through loss of HOL1 may not be as significant for diploid C. albicans with two functional copies of all genes. On a related note, is it possible that transposon insertions in the 3' untranslated region produce anti-sense transcripts that lowers the expression of the upstream gene from both alleles in diploids, thereby producing a strong selective advantage in ATI-2307? This study already touches on exciting new applications of the Tn-seq method but could easily go a bit further.

Reviewer #3 (Public review):

Summary:

This manuscript describes an extensive application of the Yeast (SATAY) transposon mutagenesis and sequencing method to explore loss- and gain-of-function mutations conferring resistance to 20 different antifungal compounds. Impressively, the authors demonstrate that SATAY can be used to identify mutations that lead to antifungal resistance, including promoter mutations that include the direct targets of antifungal compounds and drug efflux pumps. Because SATAY is not tied to a specific genetic background, the sensitivity of an S. cerevisiae strain, AD1-8, that specifically displays Chitosan susceptibility was examined in detail, and the results suggest that Chitosan acts through interactions with the fungal cell wall. Through a series of experiments that expand upon SATAY analysis, the novel antifungal ATI-2307, the authors clearly show that the transporter Hol1 concentrates this compound within yeast.

General Comments:

This is a very impressive application of SATAY, highlighting many different strategies for exploring the mechanism of action of various antifungal compounds. It's clear from the findings presented that SATAY is a powerful and potentially highly productive approach for chemical-genetic analysis.

eLife Assessment

This important study seeks to examine the relationship between pupil size and information gain, showing opposite effects dependent upon whether the average uncertainty increases or decreases across trials. Given the broad implications for learning and perception, the findings will be of broad interest to researchers in cognitive neuroscience, decision-making, and computational modelling. Nevertheless, the evidence in support of the particular conclusion is at present incomplete - the conclusions would be strengthened if the authors could both clarify the differences between model-updating and prediction error in their account and clarify the patterns in the data.

Reviewer #1 (Public review):

Summary:

This study investigates whether pupil dilation reflects prediction error signals during associative learning, defined formally by Kullback-Leibler (KL) divergence, an information-theoretic measure of information gain. Two independent tasks with different entropy dynamics (decreasing and increasing uncertainty) were analyzed: the cue-target 2AFC task and the letter-color 2AFC task. Results revealed that pupil responses scaled with KL divergence shortly after feedback onset, but the direction of this relationship depended on whether uncertainty (entropy) increased or decreased across trials. Furthermore, signed prediction errors (interaction between frequency and accuracy) emerged at different time windows across tasks, suggesting task-specific temporal components of model updating. Overall, the findings highlight that pupil dilation reflects information-theoretic processes in a complex, context-dependent manner.

Strengths:

This study provides a novel and convincing contribution by linking pupil dilation to information-theoretic measures, such as KL divergence, supporting Zénon's hypothesis that pupil responses reflect information gained during learning. The robust methodology, including two independent datasets with distinct entropy dynamics, enhances the reliability and generalisability of the findings. By carefully analysing early and late time windows, the authors capture the temporal dynamics of prediction error signals, offering new insights into the timing of model updates. The use of an ideal learner model to quantify prediction errors, surprise, and entropy provides a principled framework for understanding the computational processes underlying pupil responses. Furthermore, the study highlights the critical role of task context - specifically increasing versus decreasing entropy - in shaping the directionality and magnitude of these effects, revealing the adaptability of predictive processing mechanisms.

Weaknesses:

While this study offers important insights, several limitations remain. The two tasks differ significantly in design (e.g., sensory modality and learning type), complicating direct comparisons and limiting the interpretation of differences in pupil dynamics. Importantly, the apparent context-dependent reversal between pupil constriction and dilation in response to feedback raises concerns about how these opposing effects might confound the observed correlations with KL divergence. Finally, subjective factors such as participants' confidence and internal belief states were not measured, despite their potential influence on prediction errors and pupil responses.

Reviewer #2 (Public review):

Summary:

The authors proposed that variability in post-feedback pupillary responses during the associative learning tasks can be explained by information gain, which is measured as KL divergence. They analysed pupil responses in a later time window (2.5s-3s after feedback onset) and correlated them with information-theory-based estimates from an ideal learner model (i.e., information gain-KL divergence, surprise-subjective probability, and entropy-average uncertainty) in two different associative decision-making tasks.

Strength:

The exploration of task-evoked pupil dynamics beyond the immediate response/feedback period and then associating them with model estimates was interesting and inspiring. This offered a new perspective on the relationship between pupil dilation and information processing.

Weakness:

However, disentangling these later effects from noise needs caution. Noise in pupillometry can arise from variations in stimuli and task engagement, as well as artefacts from earlier pupil dynamics. The increasing variance in the time series of pupillary responses (e.g., as shown in Figure 2D) highlights this concern.

It's also unclear what this complicated association between information gain and pupil dynamics actually means. The complexity of the two different tasks reported made the interpretation more difficult in the present manuscript.

Reviewer #3 (Public review):

Summary:

This study examines prediction errors, information gain (Kullback-Leibler [KL] divergence), and uncertainty (entropy) from an information-theory perspective using two experimental tasks and pupillometry. The authors aim to test a theoretical proposal by Zénon (2019) that the pupil response reflects information gain (KL divergence). In particular, the study defines the prediction error in terms of KL divergence and speculates that changes in pupil size associated with KL divergence depend on entropy. Moreover, the authors examine the temporal characteristics of pupil correlates of prediction errors, which differed considerably across previous studies that employed different experimental paradigms. In my opinion, the study does not achieve these aims due to several methodological and theoretical issues.

Strengths:

(1) Use of an established Bayesian model to compute KL divergence and entropy.

(2) Pupillometry data preprocessing, including deconvolution.

Weaknesses:

(1) Definition of the prediction error in terms of KL divergence:

I'm concerned about the authors' theoretical assumption that the prediction error is defined in terms of KL divergence. The authors primarily refer to a review article by Zénon (2019): "Eye pupil signals information gain". It is my understanding that Zénon argues that KL divergence quantifies the update of a belief, not the prediction error: "In short, updates of the brain's internal model, quantified formally as the Kullback-Leibler (KL) divergence between prior and posterior beliefs, would be the common denominator to all these instances of pupillary dilation to cognition." (Zénon, 2019).

From my perspective, the update differs from the prediction error. Prediction error refers to the difference between outcome and expectation, while update refers to the difference between the prior and the posterior. The prediction error can drive the update, but the update is typically smaller, for example, because the prediction error is weighted by the learning rate to compute the update. My interpretation of Zénon (2019) is that they explicitly argue that KL divergence defines the update in terms of the described difference between prior and posterior, not the prediction error.

The authors also cite a few other papers, including Friston (2010), where I also could not find a definition of the prediction error in terms of KL divergence. For example [KL divergence:] "A non-commutative measure of the non-negative difference between two probability distributions." Similarly, Friston (2010) states: Bayesian Surprise - "A measure of salience based on the Kullback-Leibler divergence between the recognition density (which encodes posterior beliefs) and the prior density. It measures the information that can be recognized in the data." Finally, also in O'Reilly (2013), KL divergence is used to define the update of the internal model, not the prediction error.

The authors seem to mix up this common definition of the model update in terms of KL divergence and their definition of prediction error along the same lines. For example, on page 4: "KL divergence is a measure of the difference between two probability distributions. In the context of predictive processing, KL divergence can be used to quantify the mismatch between the probability distributions corresponding to the brain's expectations about incoming sensory input and the actual sensory input received, in other words, the prediction error (Friston, 2010; Spratling, 2017)."

Similarly (page 23): "In the current study, we investigated whether the pupil's response to decision outcome (i.e., feedback) in the context of associative learning reflects a prediction error as defined by KL divergence."

This is problematic because the results might actually have limited implications for the authors' main perspective (i.e., that the pupil encodes prediction errors) and could be better interpreted in terms of model updating. In my opinion, there are two potential ways to deal with this issue:

a) Cite work that unambiguously supports the perspective that it is reasonable to define the prediction error in terms of KL divergence and that this has a link to pupillometry. In this case, it would be necessary to clearly explain the definition of the prediction error in terms of KL divergence and dissociate it from the definition in terms of model updating.

b) If there is no prior work supporting the authors' current perspective on the prediction error, it might be necessary to revise the entire paper substantially and focus on the definition in terms of model updating.

(2) Operationalization of prediction errors based on frequency, accuracy, and their interaction:

The authors also rely on a more model-agnostic definition of the prediction error in terms of stimulus frequency ("unsigned prediction error"), accuracy, and their interaction ("signed prediction error"). While I see the point here, I would argue that this approach offers a simple approximation to the prediction error, but it is possible that factors like difficulty and effort can influence the pupil signal at the same time, which the current approach does not take into account. I recommend computing prediction errors (defined in terms of the difference between outcome and expectation) based on a simple reinforcement-learning model and analyzing the data using a pupillometry regression model in which nuisance regressors are controlled, and results are corrected for multiple comparisons.

(3) The link between model-based (KL divergence) and model-agnostic (frequency- and accuracy-based) prediction errors:

I was expecting a validation analysis showing that KL divergence and model-agnostic prediction errors are correlated (in the behavioral data). This would be useful to validate the theoretical assumptions empirically.

(4) Model-based analyses of pupil data:

I'm concerned about the authors' model-based analyses of the pupil data. The current approach is to simply compute a correlation for each model term separately (i.e., KL divergence, surprise, entropy). While the authors do show low correlations between these terms, single correlational analyses do not allow them to control for additional variables like outcome valence, prediction error (defined in terms of the difference between outcome and expectation), and additional nuisance variables like reaction time, as well as x and y coordinates of gaze.

Moreover, including entropy and KL divergence in the same regression model could, at least within each task, provide some insights into whether the pupil response to KL divergence depends on entropy. This could be achieved by including an interaction term between KL divergence and entropy in the model.

(5) Major differences between experimental tasks:

More generally, I'm not convinced that the authors' conclusion that the pupil response to KL divergence depends on entropy is sufficiently supported by the current design. The two tasks differ on different levels (stimuli, contingencies, when learning takes place), not just in terms of entropy. In my opinion, it would be necessary to rely on a common task with two conditions that differ primarily in terms of entropy while controlling for other potentially confounding factors. I'm afraid that seemingly minor task details can dramatically change pupil responses. The positive/negative difference in the correlation with KL divergence that the authors interpret to be driven by entropy may depend on another potentially confounding factor currently not controlled.

(6) Model validation:

My impression is that the ideal learner model should work well in this case. However, the authors don't directly compare model behavior to participant behavior ("posterior predictive checks") to validate the model. Therefore, it is currently unclear if the model-derived terms like KL divergence and entropy provide reasonable estimates for the participant data.

(7) Discussion:

The authors interpret the directional effect of the pupil response w.r.t. KL divergence in terms of differences in entropy. However, I did not find a normative/computational explanation supporting this interpretation. Why should the pupil (or the central arousal system) respond differently to KL divergence depending on differences in entropy?

The current suggestion (page 24) that might go in this direction is that pupil responses are driven by uncertainty (entropy) rather than learning (quoting O'Reilly et al. (2013)). However, this might be inconsistent with the authors' overarching perspective based on Zénon (2019) stating that pupil responses reflect updating, which seems to imply learning, in my opinion. To go beyond the suggestion that the relationship between KL divergence and pupil size "needs more context" than previously assumed, I would recommend a deeper discussion of the computational underpinnings of the result.

eLife Assessment

This important study analyzes a large dataset of Salmonella gallinarum whole-genome sequences and provides findings regarding the population structure of this avian-specific pathogen. The convincing results indicate regional adaptation of the mobilome-driven resistome and a role in the evolutionary trajectory of this pathogen that will interest microbiologists and researchers working on genomics, evolution, and antimicrobial resistance.

Reviewer #1 (Public review):

Summary:

The investigators in this study analyzed the dataset assembly from 540 Salmonella isolates, and those from 45 recent isolates from Zhejiang University of China. The analysis and comparison of the resistome and mobilome of these isolates identified a significantly higher rate of cross-region dissemination compared to localized propagation. This study highlights the key role of the resistome in driving the transition and evolutionary history of S. Gallinarum.

Strengths:

The isolates included in this study were from 16 countries in the past century (1920 to 2023). While the study uses S. Gallinarun as the prototype, the conclusion from this work will likely apply to other Salmonella serotypes and other pathogens.

Reviewer #2 (Public review):

Summary:

The authors sequence 45 new samples of S. Gallinarum, a commensal Salmonella found in chickens, which can sometimes cause disease. They combine these sequences with around 500 from public databases, determine the population structure of the pathogen, and coarse relationships of lineages with geography. The authors further investigate known anti-microbial genes found in these genomes, how they associate with each other, whether they have been horizontally transferred, and date the emergence of clades.

Strengths:

- It doesn't seem that much is known about this serovar, so publicly available new sequences from a high burden region are a valuable addition to the literature.<br /> - Combining these sequences with publicly available sequences is a good way to better contextualise any findings.<br /> - The genomic analyses have been greatly improved since the first version of the manuscript, and appropriately analyse the population and date emergence of clades.<br /> - The SNP thresholds are contextualised in terms of evolutionary time.<br /> - The importance and context of the findings are fairly well described.

Author response:

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

Public Reviews: 

Reviewer #1 (Public review):

Summary:

The investigators in this study analyzed the dataset assembly from 540 Salmonella isolates, and those from 45 recent isolates from Zhejiang University of China. The analysis and comparison of the resistome and mobilome of these isolates identified a significantly higher rate of cross-region dissemination compared to localized propagation. This study highlights the key role of the resistome in driving the transition and evolutionary history of S. Gallinarum.

Strengths:

The isolates included in this study were from 16 countries in the past century (1920 to 2023). While the study uses S. Gallinarun as the prototype, the conclusion from this work will likely apply to other Salmonella serotypes and other pathogens.

Thank you very much for your positive feedback. We recognize, as you noted, that emphasizing Salmonella enterica Serovar Gallinarum in the title may lead readers to perceive our methods and conclusions as overly restrictive. In light of your evaluation of our work, we have revised the title to: “Avian-specific Salmonella transition to endemicity is accompanied by localized resistome and mobilome interaction” We believe this final version not only reflects the applicability of our conclusions, as you appreciated, but also addresses your previous suggestion to highlight the resistome and mobilome.

Revisions in the manuscript Lines: 1-3

Weaknesses:

While the isolates came from 16 countries, most strains in this study were originally from China.

We believe that this issue was discussed in detail in our previous response. Although potential bias exists, we have minimized its impact by constructing the largest global S. Gallinarum genome dataset to date. In addition, we have further emphasized these limitations in the manuscript.

Comments on revisions:

This reviewer is happy with the detailed responses from the authors regarding revising this manuscript. I do not have further comments.

We greatly appreciate your positive feedback and are pleased that our responses have addressed your concerns.

Reviewer #2 (Public review):

Summary:

The authors sequence 45 new samples of S. Gallinarum, a commensal Salmonella found in chickens, which can sometimes cause disease. They combine these sequences with around 500 from public databases, determine the population structure of the pathogen, and coarse relationships of lineages with geography. The authors further investigate known anti-microbial genes found in these genomes, how they associate with each other, whether they have been horizontally transferred, and date the emergence of clades.

Strengths:

- It doesn't seem that much is known about this serovar, so publicly available new sequences from a high burden region are a valuable addition to the literature.

- Combining these sequences with publicly available sequences is a good way to better contextualise any findings.

- The genomic analyses have been greatly improved since the first version of the manuscript, and appropriately analyse the population and date emergence of clades.

- The SNP thresholds are contextualised in terms of evolutionary time.

- The importance and context of the findings are fairly well described.

Thank you so much for your thorough review and constructive comments on the manuscript.

Weaknesses:

-  There are still a few issues with the genomic analyses, although they no longer undermine the main conclusions:

We are grateful for the valuable time and effort you have dedicated to improving our manuscript. In this revision, we have provided a point-by-point response to each of your concerns. Moreover, with the addition of new supplementary materials and modifications to the figures, we have re-examined and adjusted the numbering of figures and supplementary materials in the text to ensure they appear correctly in the manuscript.

(1) Although the SNP distance is now considered in terms of time, the 5 SNP distance presented still represents ~7yrs evolution, so it is unlikely to be a transmission event, as described. It would be better to use a much lower threshold or describe the interpretation of these clusters more clearly. Bringing in epidemiological evidence or external references on the likely time interval between transmissions would be helpful.

We sincerely thank you for highlighting this issue. We appreciate your concern regarding the use of a 5-SNP threshold to define a transmission event, especially given the approximate 7-year evolutionary timeframe. Considering our updated estimate for the evolutionary rate of S. Gallinarum (approximately 0.74 SNPs per year, with a 95% HPD range of 0.42 to 1.06), we have revised the manuscript to use a 2-SNP threshold (approximately representing less than two years of evolution) to better control the temporal span of transmission events. In addition, we have updated the manuscript to reflect this new threshold and demonstrated that the use of a more stringent SNP threshold does not affect the overall conclusions of the study.

Specifically, we adopted the newly established 2-SNP threshold to update Figure 3a and corresponding Supplementary Figure 8. The heatmap on the far right of New Figure 3a illustrates the SNP distances among 45 newly isolated S. Gallinarum strains from two locations in Zhejiang Province (Taishun and Yueqing). New Supplementary Figure 8 simulates potential transmission events between the bvSP strains isolated from Zhejiang Province (n=95) and those from other regions of China with available provincial information (n=435). These analyses collectively demonstrate the localized transmission patterns of bvSP within China.

For New Figure 3a, we found that even with the 2-SNP threshold, the number of potential transmission events among the 45 newly isolated S. Gallinarum strains from the two Zhejiang locations (Taishun and Yueqing) remains unchanged. In fact, we observed that the results from SNP tracing using an SNP threshold of less than 5 are consistent (see Author response image 1). 

Author response image 1.

Clustering results of 45 newly isolated S. Gallinarum strains using different SNP thresholds of 1, 2, 3, 4, and 5 SNPs. The five subplots represent the clustering results under each threshold. Each point corresponds to an individual strain, and lines connect strains with potential transmission relationships.

For New Supplementary Figure 8, we employed the 2-SNP threshold and found that the number of transmission events between the bvSP strains isolated from Zhejiang Province (n=95) and those from other Chinese provinces (n=435) decreased from 91 to 53. The names of the strains involved in these potential transmission events are listed in Supplementary Table 5.

Revisions in the manuscript

Lines: 352-357

Figures: Figure 3; Supplementary Figure 8

Table: Supplementary Table 5

(2) The HGT definition has not fundamentally been changed and therefore still has some issues, mainly that vertical evolution is still not systematically controlled for. 

We sincerely thank you for highlighting this issue. We hope the following explanation will help clarify and improve our manuscript, as well as address your concerns.

In bacteria, mobile genetic elements (MGEs) such as plasmids, transposons, integrons, and prophages, as mentioned in our manuscript, are segments of DNA that encode enzymes and proteins responsible for mediating the movement of genetic material between bacterial genomes (commonly referred to as “jumping genes”). These MGEs contribute to the mechanisms of horizontal gene transfer (HGT) in Salmonella, including transduction (via prophages), conjugation (via plasmids), and transposition (via integrons and transposons) (Nat Rev Microbiol. 2005 Sep;3(9):722-32). These “jumping genes” can enable Salmonella to acquire additional antimicrobial resistance genes (ARGs), which may not only originate from other Salmonella strains but also from distantly related species.

To further address your concern regarding the systematic control of vertical evolution, we employed the HGTphyloDetect pipeline developed by Le Yuan et al. (Brief Bioinform. 2023 Mar 19;24(2):bbad035) to control for vertical evolution in the ARG sequences mentioned in our manuscript. We chose HGTphyloDetect because, as noted, "jumping genes" often occur among evolutionarily distant species, rendering the use of Gubbins potentially unsuitable for these distant HGT events.

Using the HGTphyloDetect pipeline, we extracted base sequences for the eight ARGs shown in Figure 6b with an HGT frequency greater than zero (bla^TEM-1B, sul1, dfrA17, aadA5, sul2, aph(3’’)-Ib, tet(A), aph(6)-Id). For bla^TEM-1B, sul1, dfrA17, aadA5, and sul2, the HGT frequency reached 100% across different isolates, indicating that these ARG sequences have a unique sequence type. In contrast, due to the ResFinder settings requiring both similarity and coverage to meet a minimum value of 90%, the base sequences for aph(3’’)-Ib, tet(A), and aph(6)-Id are not unique. Consequently, we applied the HGTphyloDetect pipeline individually to each sequence type of ARGs to verify their association with HGT events. Specifically, among 436 bvSP isolates collected in China, we identified two sequence types of aph(3’’)-Ib, four sequence types of tet(A), and three sequence types of aph(6)-Id.

Subsequently, to identify potential ARGs horizontally acquired from evolutionarily distant organisms, we queried the translated amino acid sequences of each ARG against the National Center for Biotechnology Information (NCBI) non-redundant protein database. We then evaluated whether these sequences were products of HGT by calculating Alien Index (AI) scores and out_perc values.

The calculation of AI score is as follows:

In this study, bbhG and bbhO represent the E-values of the best blast hit in ingroup and outgroup lineages, respectively. The outgroup lineage is defined as all species outside of the kingdom, while the ingroup lineage encompasses species within the kingdom but outside of the subphylum. An AI score ≥ 45 is considered a strong indicator that the gene in question is likely derived from an HGT event.

Regarding the calculation method for out_perc:

Finally, according to the definition provided by the HGTphyloDetect pipeline, ARGs with AI score ≥ 45 and out_perc ≥ 90% are presumed to be potential candidates for HGT from evolutionarily distant species. We have compiled the calculation results for the aforementioned genes in New Supplementary Table 9. The results indicate that all ARGs presented in Figure 6b, which exhibited a HGT frequency greater than zero, were acquired horizontally by S. Gallinarum. Based on these findings, we have revised the manuscript accordingly.

Revisions in the manuscript

Lines: 302-307; 616-650; 955-957

Table: Supplementary Table 9

Using a 5kb window is not sufficient, as LD may extend across the entire genome.

We agree with your point that linkage disequilibrium (LD) could influence the transmission of genes within chromosomal regions. LD can lead to the non-random cooccurrence of alleles at different loci within a population. Considering that horizontal gene transfer (HGT) events involving more distantly related ARGs may be accompanied by vertical propagation on chromosomes, and to simultaneously assess the impact of LD, we conducted two evaluations.

It is important to note that the following assessments are based on the assumption that plasmid replicons detected by PlasmidsFinder are part of self-replicating, extrachromosomal DNA.

(1) In the revised pipeline used to calculate ARG HGT frequencies, we categorized a total of 621 ARGs carried by 436 bvSP isolates collected in China and found that 415 of these ARGs were located on MGEs. We further investigated the distribution of these 415 ARGs across different MGEs, taking into account the complex nesting relationships among them. We observed that 90% of the ARGs (372/415) were located on plasmid contigs. It is important to clarify that this finding does not contradict our statement in the manuscript regarding plasmids and transposons as the primary reservoirs for resistome geo-temporal dissemination. This is because transposons, integrons, and prophages carrying ARGs can also be found on plasmids. Additionally, only 25 bvSG isolates from China contained ARGs, which were likely acquired via transposons or integrons located on the chromosome.  

(2) In our manuscript, we searched for ARGs within a 5kb upstream and downstream region (a total of 10kb) of transposons and integrons (The BLASTn parameters used in the Bacant pipeline to identify transposons and integrons were set to a coverage threshold of 60%, rather than 100%). However, in light of the potential impact of LD on vertical transmission, we expanded our search to include a 10kb upstream and downstream range (a total of 20kb)  for these 25 isolates. The decision to expand the search range to 10kb upstream and downstream range is based on the following two considerations: 1) Based on literature, we determined the overall lengths of the integrons and transposons carried by the 25 isolates (Tn801, Tn6205, Tn1721, In498, In1440, In473, and In282), and found that the maximum length of these elements is ~13.5 kb. Using a 10kb upstream and downstream threshold effectively covers these integrons/transposons. 2) The limitation posed by genomic fragmentation due to next-generation sequencing, which restrict the search range. We present the results of this expanded search for colocalization of ARGs with transposons and integrons at: Figshare:  https://doi.org/10.6084/m9.figshare.28129130.v1

We found that these results were consistent with those obtained using the previous search range.

Taken together, these results suggest that although linkage disequilibrium may influence genetic processes within chromosomal regions—particularly for the few chromosomeassociated antibiotic resistance genes linked to integrons and transposons—the overall impact in our study is likely minimal. This conclusion is supported by the observation that 90% of the ARGs in our dataset are located on plasmids, and even an expanded search range does not alter this outcome. Additionally, by incorporating Alien Index scores and calculating out_perc, we can further confirm the occurrence of horizontal gene transfer events.

However, it is undeniable that other studies using our current pipeline may be affected. As a temporary remedial measure, we have included a note in the "README" file  as below (https://github.com/tjiaa/Cal_HGT_Frequency):

“Note: Considering that ARGs located on the chromosome and carried by mobile genetic elements—such as integrons and transposons—may introduce potential computational errors, we recommend evaluating the number of ARGs associated with these elements on the chromosome during your analysis. If a majority of ARGs in your dataset fall into this category, we suggest using additional methods to evaluate the potential impact of linkage disequilibrium. Additionally, by modifying the “MGE_start” and “MGE_end” parameters in the “eLife_MGE_ARG_Co_location.ipynb” script, you can assess the distance between different ARGs and integrons or transposons on the chromosome. This approach will further aid in evaluating the impact of linkage disequilibrium on the genetic process.”

We believe this approach will assist researchers in further assessing the potential impact of vertical evolution and help other users determine whether additional methods are necessary to account for such effects.

As the authors have now run gubbins correctly, they could use the results from this existing analysis to find recent HGT.

We sincerely thank you for your valuable suggestion. Utilizing additional methods to predict potential horizontal gene transfer (HGT) events could indeed enhance the robustness of the results. However, "jumping genes" often occur among evolutionarily distant species, rendering the use of Gubbins potentially unsuitable for these distant HGT events.

Furthermore, the primary focus of our study is to identify HGT of antimicrobial resistance genes (ARGs) in the Salmonella genome driven by mobile genetic elements. Therefore, we employed the HGTphyloDetect pipeline developed by Le Yuan et al. (Brief Bioinform. 2023 Mar 19;24(2):bbad035) to control for vertical evolution in the ARG sequences. The specific computational methods and conclusions have been detailed above.

To definite mobilisation, perhaps a standard pipeline such (e.g. https://github.com/EBIMetagenomics/mobilome-annotation-pipeline) would be more convincing.

Thank you for your valuable suggestion. We agree that defining mobilization using a standardized pipeline can add rigor and clarity to our analysis. The pipeline you referenced (https://github.com/EBI-Metagenomics/mobilome-annotation-pipeline) is an excellent resource and provides a robust approach to the identification and annotation of mobile genetic elements.

We have examined and run this pipeline, which uses “IntegronFinder” and “ICEfinder” to detect integrons, “geNomad” to identify plasmids, and “geNomad” and “VIRify” to detect prophages. Our initial checks revealed that the numbers of integrons, plasmids, and prophages identified using this pipeline were consistent with those detected in our study. However, due to the significantly different output formats, the results from this pipeline could not be integrated with the pipeline we used for calculating HGT frequency.

We will incorporate the standardized pipeline you suggested in future studies to further improve the reliability of our findings.

(3) The invasiveness index is better described, but the authors still did not provide convincing evidence that the small difference is actually biologically meaningful (there was no statistical difference between the two strains provided in response Figure 6). What do other Salmonella papers using this approach find, and can their links be brought in? If there is still no good evidence, a better description of this difference would help make the conclusions better supported.

We sincerely appreciate your thoughtful feedback. The initial introduction of the invasiveness index in our manuscript aimed to quantitatively assess the differences in invasiveness between two geographically distinct strains of S. Gallinarum (isolated from Taishun and Yueqing) by comparing the degradation of 196 top predicted genes associated with invasiveness in their genomes. We found a highly significant statistical difference (P < 0.0001) in the invasiveness index between them.

Several studies have also employed the invasiveness index to predict biological relevance in Salmonella strains, and we believe these examples provide further context for our approach:

(1) Caisey V. Pulford et al, Nat Microbiol, 2021, used the same method to calculate the invasiveness index for Salmonella Typhimurium and employed it to characterize the invasiveness of different lineage strains. They found that Salmonella in Lineage-3 exhibited the highest invasiveness index, suggesting an adaptation from an intestinal to a systemic lifestyle. The authors noted, "Although the invasiveness index cannot yet be experimentally validated, Salmonella isolates with different invasiveness indices produce distinct clinical symptoms in a human population (BMC Med. 2020 Jul 17; 18(1):212)". They emphasized the necessity of developing more robust methods to measure Salmonella invasiveness.

(2) Sandra Van Puyvelde et al, Nat Commun, 2019, reported that Salmonella Typhimurium sequence type 313 (ST313) lineage II.1 exhibited a higher invasiveness index compared to lineage II, suggesting that the two lineages might have distinct adaptations to an invasive lifestyle. Further experiments demonstrated significant differences between these lineages in terms of biofilm formation (A red dry and rough (RDAR) assay) and metabolic capacity for carbon compounds.

(3) Wim L. Cuypers et al, Nat Commun, 2023, calculated the invasiveness index for 284 global Salmonella Concord strains across different lineages and found that Lineage-4 potentially exhibited the highest invasiveness.

Given these evidences, we acknowledge that no significant difference in mortality was observed between the L2b and L3b S. Gallinarum strains in 16-day-old SPF chicken embryos. Existing literature suggests that strains with higher invasiveness indices may still exhibit differences in biofilm formation and metabolic capacities, reflecting their adaptation to different host environments. As such, we maintain that the invasiveness index remains a valuable metric for evaluating the genomic differences between S. Gallinarum strains from Taishun and Yueqing. We plan to further investigate these differences through phenotypic experiments in our next research.

In the revised manuscript, we have added the following discussion along with additional references:

Lines 358-365: “Moreover, the invasiveness index of bvSP from Taishun and Yueqing suggests that different lineages of S. Gallinarum recovered from distinct regions may exhibit biological differences. Previous studies have shown that strains with higher invasiveness indexes tend to be more virulent in hosts (30, 31), potentially causing neurological or arthritic symptoms in S. Gallinarum infections. Furthermore, strains with varying invasiveness indexes have been confirmed to differ in their biofilm formation abilities and metabolic capacities for carbon compounds (32).”

Revisions in the manuscript:

Lines: 358-365, 806-827.

In summary, the analysis is broadly well described and feels appropriate. Some of the conclusions are still not fully supported, although the main points and context of the paper now appear sound.

Thank you so much for your positive evaluation of our work. We hope that the revised manuscript meets your expectations and offers a more accurate interpretation of our findings.

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

This is a great improvement over the first version and I thank the authors for a thorough response, as well as changing their conclusions in response to their improvements.

Other small remaining issues:

Figure 3: Heatmap of SNPs is hard to read in grayscale. It also just represents the between clade distances already shown by the tree. It would be more useful to present intraclade distances only to see the SNP resolution _within_ each lineage. Using a better colour scheme would also help.

Thank you for your insightful comments and suggestions regarding Figure 3. We agree that the grayscale heatmap may present challenges in terms of visual clarity. To address this, we have updated the heatmap with a more distinct color gradient, ensuring better contrast and easier interpretation (New Figure 3). 

Regarding your second suggestion: "It would be more useful to present intraclade distances only to see the SNP resolution within each lineage," we believe it is already addressed in the current version of New Figure 3. Specifically, the heatmap on the right side of New Figure 3 illustrates the SNP distances between S. Gallinarum isolates from Taishun and Yueqing, with the goal of demonstrating that genomic variation within isolates from a single region is generally smaller compared to those from different regions. In this figure, 45 newly isolated S. Gallinarum strains are categorized into two lineages: L2b and L3b. The heatmap on the right side of Figure 3 displays the SNP distances between all pairwise combinations of these 45 strains, where the intraclade distances are represented by the red regions (highlighting the pairwise distances within each lineage, specifically L3b and L2b, which are indicated by two triangles). The between-clade distances are shown by the blue regions.

We also believe in further exploring the intraclade distances across the entire dataset of 580 S. Gallinarum strains, as it could provide additional insights. However, this analysis would extend beyond the scope of the current section.

Revisions in the manuscript Line: 998

Figure: Figure 3

Please remove Figure 6c, it does not add anything to the paper and raises questions about performing this regression.

Thank you for pointing out this issue. We have removed Figure 6c and the corresponding description in the "Results" section from the manuscript (New Figure 6).

Revisions in the manuscript Lines: 316, 319, 1035-1041.

Figure: Figure 6

Again, thank you all for your time and efforts in reviewing our work. We believe the improved manuscript meets the high standards of the journal.

eLife Assessment

In this valuable study, Tutak and colleagues set out to identify factors that mediate Repeat Associated Non-AUG (RAN) translation of CGG repeats in the FMR1 mRNA which are implicated in toxic protein accumulation that underpins ensuing neurological pathologies. The authors provide solid evidence that RPS26 may be implicated in mediating the RAN translation of FMR1 mRNA. This article should be of broad interest to researchers in the variety of disciplines including post-transcriptional regulation of gene expression and neurobiology.

Reviewer #2 (Public review):

Summary:

Translation of CGG repeats leads to accumulation of poly G, which is associated with neurological disorders. This is an important paper in which the authors sought out proteins that modulate RAN translation. They determined which proteins in Hela cells were enriched on CGG repeats and affected levels of polyG encoded in the 5'UTR of the FMR1 mRNA. They then showed that siRNA depletion of ribosomal protein RPS26 results in less production of FMR1polyG than in control. Experiments were performed in several cell lines and with several reporters with differences in repeats and transfection methods to increase confidence that changes were occurring. New data and details of the methods increase confidence that reporter translation but not global translation is diminished by RPS26 knockdown as concluded. The manuscript has been improved by data showing that new proteins are being synthesized in cells following RPS26 knockdown, and that near-cognate start codon usage is diminished in lines when RPS26 is knocked down, but the mechanism by which RPS26 depletion affects translation is still unclear.

Strengths:

- The authors have proteomics data that show enrichment of a set of proteins on FMR1-polyG RNA but not a related RNA.<br /> - Knockdown of RPS26, which was enriched on the FMR1 RNA, led to decreases in cell growth, but surprisingly did not strongly affect global translation, as assessed by puromycin incorporation<br /> - There is some new evidence that near-cognate start codon selection is affected by RPS26 knockdown

Weaknesses:

- The mechanism for RPS26 knockdown affecting translation of the polyG sequences is unclear, whether knockdown is affecting ribosome levels, extra ribosomal RPS26 or ribosome composition is not known.

Reviewer #3 (Public review):

Tutak et al provide intriguing findings demonstrating that insufficiency of RPS26 and related proteins, such as TSR2 and RPS25, downregulates RAN translation from CGG repeat RNA in fragile X-associated conditions. Using RNA-tagging system and mass spectrometry-based screening, the authors identified RPS26 as a potential regulator of RAN translation. They further confirmed its regulatory effects on RAN translation by siRNA-based knockdown experiments in multiple cellular disease models. Quantitative mass spectrometry analysis revealed that the expression of some ribosomal proteins is sensitive to RPS26 depletion, while approximately 80% of proteins, including FMRP, were not influenced. Given the limited understanding of the roles of ribosomal proteins in RAN translation regulation, this study provides novel insights into this research field. However, certain data do not fully support the authors' critical conclusions.

(1) While the authors substituted the ACG near-cognate initiation codon with other near-cognate codons, such as GTG and CTG, in the luciferase assay (Figure 4F), substitution of the ACG codon with an ATG codon should also be performed. Although they evaluated RPS26 knockdown effect on AUG-dependent FMRP translation in Figure 3C, investigating its effect on AUG-dependent repeat-associated translation (e.g., AUG-CGG-repeat) is necessary to substantiate their claim that ACG codon selection is important for RAN translation downregulation by RPS26 knockdown.

(2) The results of the ASO-based ACG codon-blocking experiment in Figure 4G are difficult to interpret. While RPS knockdown reduces FMRpolyG expression, the effect appears attenuated by the ASO-ACG treatment compared to the control. However, this does not conclusively demonstrate that the regulatory effect is directly due to ACG codon selection during translation initiation for some reasons. For example, ASO-ACG treatment possibly interferes with ribosomal scanning rather than ACG-codon selection, or alters the expression of template CGG repeat RNA. To validate the effect of RPS26 knockdown on ACG codon selection, experiments using the ACG-to-ATG substituted CGG repeat reporter are recommended, as suggested in comment 1.

(3) The regulatory effects of RPS26 and other molecules on RAN translation have been investigated as effects on the expression levels of FMRpolyG proteins upon knockdown of these molecules in disease model cells expressing CGG repeat sequences (Figures 1C, 1D, 3B, 3C, 3E, 4F, 4G, 5A, 5C, 6A, 6D）. However, FMRpolyG expression levels can be influenced by factors other than RAN translation in these cellular experiments, such as template RNA level, template RNA localization, and FMRpolyG protein degradation. Although the authors evaluated the effect on the expression levels of template CGG repeat RNA, it would be better to confirm the direct effect of these regulators on RAN translation by other experiments. In vitro translation assay that can directly evaluate RAN translation is preferable, but experiments using the ACG-to-ATG substituted CGG repeat reporter, as suggested in comment 1, would also provide valuable insights.

Author response:

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

We thank Reviewers for highlighting the strengths of our work along with suggestions for future directions.

We agree with the Reviewers that RPS26 depletion may impact not only RAN translation initiation and codon selection (as showed in the experiments in Figure 4G), but also other mechanisms, such as speed of PIC scanning, as we stated in the discussion. Although, we did provide the data showing that mRNA of exogenous FMR1-GFP does not change upon RPS26 depletion (Figure 3B&C), hence observed effect most likely stems from translation regulation. In addition, an experiment with ASO-ACG treatment (Figure 4G) suggests that near cognate start codon selection or speed of PIC scanning may be a part of the regulation of RAN translation sensitive to RPS26 depletion. In addition, our latest unpublished results (Niewiadomska D. et al., in revision), indicate that FMRpolyG in fusion with GFP is fairly stable, in particular, while derived from long repeats (>90xCGG), suggesting that the protein stability is not at play in RPS26-dependent regulation.

We would like to stress that in order to avoid bias in result interpretation and to mimic the natural situation, the majority of experiments concerning levels of FMRpolyG were performed in cell models with stable expression of ACG-initiated FMRpolyG. Currently, we do not possess a cell model with stable expression of AUG-initiated FMRpolyG, and the experiments based on transient transfection system would not necessarily be comparable to the results obtained in stable expression system. However, we believe that the experiment presented in Figure 2B serves as a good control for overall translation level upon RPS26 depletion indicating that RPS26 insufficiency does not affect global translation and the observed regulation is specific to some mRNAs including the one encoding FMRpolyG frame. We also show that the level of ca. 80% of identified canonical proteins, including FMRP, did not change upon RPS26 silencing (SILAC-MS, Figure 4A). Indeed, we did not explore the ribosome composition upon RPS26 and TSR2 depletion, although, most likely the pool of functional ribosomes in the cell is sufficient enough to support the basal translation level (SUnSET assays, Figure 2B & 5C). However, we cannot exclude possibility that for some mRNAs, including one encoding for FMRpolyG, the observed effect can be partially caused by lowering the number of fully active ribosomes, especially in experiments with transient transfection experiments where transgene expression is hundreds times higher than for average native mRNA.

Finally, we agree with the Reviewer that in vitro translation assay would provide the evidence of direct effect of RPS26 on FMRpolyG level, however, we did not manage to overcome technical difficulties in obtaining cellular lysate devoid of RPS26 from vendor companies.

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

General Comments

We thank Reviewers for the critical comments and experimental suggestions. We considered most of the advices in the revised version of the manuscript, which allowed for a more balanced interpretation of the results presented, and further supported major statement of the manuscript that insufficiency of the RPS26 and RPS25 plays a role in modulating the efficiency of noncanonical RAN translation from FMR1 mRNA, which results in the production of toxic polyglycine protein (FMRpolyG). Firstly, performing new experiments, we showed that silencing of the RPS26 and its chaperone protein TSR2, which regulates loading/exchange of RPS26 in maturing small ribosome subunit, did not elicit global translation inhibition. Secondly, we demonstrated that in contrary to RPS26 and RPS25 depletion, silencing the RPS6 protein, a core component of 40S subunit, did not affect FMRpolyG production, further supporting the specific effect of RPS26 and RPS25 on RAN translation regulation of mutant FMR1 mRNA. We also observed that depletion of RPS26, RPS25 and RPS6 had significant negative effect on cells proliferation which is in line with previously published results indicating that insufficiencies of ribosomal proteins negatively affect cell growth. Moreover, we showed that FMRpolyG production is significantly affected by RPS26 depletion while initiated at ACG, but not other near cognate start codons. Importantly, translation of FMRP initiated at canonical AUG codon of the same mRNA upstream the CGGexp was not affected by RPS26 silencing, similarly to vast majority of the human proteome. This implies that RAN translation of FMR1 mRNA mediated by RPS26 insufficiency is likely to be dependent on start codon selection/fidelity. In essence, we provide a series of evidences indicating that cellular amount of 40S ribosomal proteins RPS26 and RPS25 is important factor of CGGrelated RAN translation regulation. Finally, we also decided to tone down our claims. Now, we state that the RPS26/25/TSR2 insufficiency or depletion, affects RAN translation, rather than composition of 40S ribosomal subunit per se influences RAN translation. We have addressed all specific concerns below and made changes to the new version of manuscript.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, Tutak et al use a combination of pulldowns, analyzed by mass spectrometry, reporter assays, and fluorescence experiments to decipher the mechanism of protein translation in fragile X-related diseases. The topic is interesting and important.

Although a role for Rps26-deficient ribosomes in toxic protein translation is plausible based on already available data, the authors' data are not carefully controlled and thus do not support the conclusions of the paper.

We sincerely appreciate your rigorous, insightful, and constructive feedback throughout the revision process. We believe your guidance has been instrumental in significantly enhancing the quality of our research. Below, we have addressed your comments pointby-point.

Strengths:

The topic is interesting and important.

Weaknesses:

In particular, there is very little data to support the notion that Rps26-deficient ribosomes are even produced under the circumstances. And no data that indicate that they are involved in the RAN translation. Essential controls (for ribosome numbers) are lacking, no information is presented on the viability of the cells (Rps26 is an essential protein), and the differences in protein levels could well arise from block in protein synthesis, and cell division coupled to differential stability of the proteins.

We agree that data presented in the first version of the manuscript did not directly address the following processes: ribosome content, global translation rate and cell viability upon RPS26 depletion. Therefore we addressed some of the issues in the revised version of the manuscript. In particular, we showed that RPS26 and TSR2 knock down did not inhibit global translation (new Figure 2B & 4C), hence we concluded that the changes of FMRpolyG level did not arise from general translational shut down. On the other hand, RPS26, RPS25 and RPS6 depletion negatively affected cells proliferation (new Figure 2A,5D,6C), which is in line with a number of previously published researches (e.g. Cheng et al, 2019; Havkin-Solomon et al, 2023). However, the rate of proliferation abnormalities is limited. We agree that observed effects on RAN translation from mutant FMR1 mRNA may stem from the combination of altered protein synthesis, conditions of the cells but also cis-acting factors of mRNA sequence/structure. In new experiments we showed that single nucleotide substitution of ACG by other near cognate start codons change sensitivity of RAN translation to insufficiency of RPS26 (new Figure 4F). Also the inhibitory effect of antisense oligonucleotide binding to the region of 5’UTR containing ACG initiation codon (ASO_ACG) is different in cells differing in amount of RPS26 (new Figure 4G).

We also agree that our data only partially supports the role of RPS26-defficient ribosomes in RAN translation. Therefore, we have toned down our claims. Now, we state that the RPS26/25/TSR2 insufficiency or depletion affects RAN translation. We also changed the title of the manuscript to: “Insufficiency of 40S ribosomal proteins, RPS26 and RPS25, negatively affects biosynthesis of polyglycine-containing proteins in fragile-X associated conditions” (Previously it was: “Ribosomal composition affects the noncanonical translation and toxicity of polyglycine-containing proteins in fragile X-associated conditions”.

Specific points:

(1) Analysis of the mass spec data in Supplemental Table S3 indicates that for many of the proteins that are differentially enriched in one sample, a single peptide is identified. So the difference is between 1 peptide and 0. I don't understand how one can do a statistical analysis on that, or how it would give out anything of significance. I certainly do not think it is significant. This is exacerbated by the fact that the contaminants in the assay (keratins) are many, many-fold more abundant, and so are proteins that are known to be mitochondrial or nuclear, and therefore likely not actual targets (e.g. MCCC1, PC, NPM1; this includes many proteins "of significance" in Table S1, including Rrp1B, NAF1, Top1, TCEPB, DHX16, etc...).

The data in Table S6/Figure 3A suffer from the same problem.

I am not convinced that the mass spec data is reliable.

We thank Reviewer for the comment concerning MS data; however, we believe that it may stem from misunderstanding of the data presented in Table S3 and S6. Both tables represent the output from MaxQuant analysis (so-called ProteinGroup) of MS .raw files, without any filtering. As stated in the Material&Methods, we applied default parameters suggested by MaxQuant developers to analyze MS data, these include identification of proteins based on at least 1 unique peptide, and thus some of the proteins with only 1 unique peptide are shown in Tables S1 and S3. Reviewer is also right that in this output table common contaminants, such as keratins are included. However, these identifications are denoted as “CON_”, and are further filtered out during statistical analysis in Perseus software. During the statistical analysis we first filtered out irrelevant protein groups identifications, such as contaminants, or only identified by site modifications.

We have changed the names of Supplementary Table files, giving more detailed description. We hope this will help to avoid misunderstanding for broader public. Secondly, when comparing the data presented in Table S3 and volcano plot presented in Figure 1B, one can notice that indeed the majority of identified proteins are not statistically significant (grey points), thus not selected for further stratification. Lack of significance of these proteins may be partially due to poor MS identification, however, they are not included in the following parts of the manuscript. Further, we selected only eight proteins (out of over 150) for stratification by orthogonal techniques, thus we argue that this step validates the biological relevance of chosen candidate RAN-translation modifiers. One should also keep in mind that pull down samples analyzed by MS often yield lower intensity and identification rates, when comparing to whole cell analysis, as a result of lower protein input or stringent washes used during sample preparation.

Regarding the data presented in Table S6 (SILAC data), we argue that these data are of very good quality. More than 2,000 proteins were identified in a 125min gradient, with over 80% of proteins that were identified with at least 2 unique peptides. Each of three biological replicates was analyzed three times (technical replicates), giving total of 9 high resolution MS runs. Together, we strongly believe that this data is of high confidence.

(2) The mass-spec data however claims to identify Rps26 as a factor binding the toxic RNA specifically. The rest of the paper seeks to develop a story of how Rps26-deficient ribosomes play a role in the translation of this RNA. I do not consider that this makes sense.

Indeed, we identified RPS26 as a protein that co-precipitated with FMR1 containing expanded CGG repeats (Supplementary Figure 1G) and found that depletion of RPS26 hindered RAN translation of FMRpolyG, suggesting that RPS26 positively affects RAN translation. However, we did not state that RPS26 directly interacts with toxic RNA. In order to confirm the specificity of RAN translation regulation by RPS26 insufficiency, we tested whether depletion of other 40S ribosomal protein, RPS6, affects FMRpolyG synthesis. Our experiments showed that there was no any significant effect on RAN translation efficiency post RPS6 silencing (new Figure 5C). Importantly, we showed that RPS26 depletion did not inhibit global translation (new Figure 2B). In addition, mutagenesis of near-cognate start codon (new Figure 4F) and ASO_ACG treatment (new Figure 4G) provided the evidences that modulation of FMRpolyG biosynthesis by RPS26 level may depend on start codon selection. In essence, our data suggest that RPS26 depletion specifically affects synthesis of FMRpolyG, but not FMRP derived from the same FMR1 mRNA with CGGexp. However, we do not claim that the observed effect is the consequence of a direct interaction between RPS26 and 5’UTR of FMR1 mRNA. Downregulation of FMRpolyG biosynthesis could be an outcome of the alteration of ribosomal assembly, decrease of efficiency and fidelity of PIC scanning/initiation or impeded elongation or a combination of all these processes. In the manuscript we presented the results of experiments which tested many of these possibilities.

(3) Rps26 is an essential gene, I am sure the same is true for DHX15. What happens to cell viability? Protein synthesis? The yeast experiments were carefully carried out under experiments where Rps26 was reduced, not fully depleted to give small growth defects.

We agree with the Reviewer that RPS26 and DHX15 are essential proteins, similarly to all RNA binding proteins, and caution should be taken during experimental design. To address this, we titrated different concentrations of siRPS26, and found that administration of 5 nM siRPS26, which just partially silenced RPS26, decreased FMRpolyG by around 50% (new Figure 1D). This impact was even greater with 15 nM siRPS26, as we observed around 80% decrease of FMRpolyG.

Havkin-Solomon et al. (2023), showed that proliferation rate is decreased in cells with mutated C-terminus of RPS26, which is required for contacting mRNA. In accordance with this study, we showed that cells with knocked down RPS26 proliferate less efficiently (new Figure 2A), but depletion of RPS26 did not impact the global translation (new Figure 2B). In addition, our SILAC-MS data indicates that ~80% of proteins with determined expression level were not affected by RPS26 insufficiency, and ~20% of the proteins turned out to be sensitive to RPS26 decrease. Although, these data do not take into account the protein stability.

(4) Knockdown efficiency for all tested genes must be shown to evaluate knockdown efficiency.

The current version of the manuscript contains representative western blots with validation of knock-down efficiency (for example in Figure 3B, C, E, Figure 6A) and we included knock-down validations where applicable (Figures 1D, 2B, 4G and 5C).

(5) The data in Figure 1E have just one mock control, but two cell types (control si and Rps26 depletion).

Mock control corresponds to the cells treated with lipofectamine reagent and was included in the study to determine the “background” signal from cells treated with delivery agent and reagents used to measure the apoptosis process. These cells were neither expressing FMRpolyG, nor siRNAs. Luminescence signals were normalized to the values obtained from mock control. We added more details describing this assay in the Figure 1 legend.

(6) The authors' data indicate that the effects are not specific to Rps26 but indeed also observed upon Rps25 knockdown. This suggests strongly that the effects are from reduced ribosome content or blocked protein synthesis. Additional controls should deplete a core RP to ascertain this conclusion.

We agree that observed effects may stem from reduced ribosome content, however, we argue that this is the only possibility and explanation. Previously, it was shown that RPS25 regulates G4C2-related RAN translation, but knock out of RPS25 does not affect global translation (Yamada S, 2019, Nat. Neuroscience). Similarly, we showed that KD of RPS26 or TSR2 did not reduce significantly global translation rate (SUnSET assay; new Figure 2B and 5C, respectively).

Moreover, in a new version of manuscript we included a control experiment, where we silenced core ribosomal protein (RPS6) and found that RPS6 depletion did not affect RAN translation from mutant FMR1 mRNA (new Figure 5C), thus strengthening our conclusion about specific RAN translation regulation by the level of RPS26 and RPS25.

Finally, our observation aligns well with current knowledge about how deficiency of different ribosomal proteins alters translation of some classes of mRNAs (Luan Y, 2022, Nucleic Acids Res; Cheng Z, 2019, Mol Cell). It was shown that depletion of RPS26 affects translation rate of different mRNAs compared to depletion of other proteins of small ribosomal subunit.

(7) Supplemental Figure S3 demonstrates that the depletion of S26 does not affect the selection of the start codon context. Any other claim must be deleted. All the 5'-UTR logos are essentially identical, indicating that "picking" happens by abundance (background).

Supplementary Figure 3D represents results indicating that the mutation in -4 position (from G to A) did not affect the RAN translation regardless of RPS26 presence or depletion. However, this result does not imply that RPS26 does not affect the selection of start codon of sequence- or RNA structure-context. We verified this particular -4 position, as it was suggested previously as important RPS26-sensitive site in yeasts (Ferretti M, 2017, Nat Struct Mol Biol). We agree with Reviewer that all 5’UTR logos presented in our paper did not show statistical significance for neither tested position for human mRNAs. On the contrary, we observed that regulation sensitive to RPS26 level depends on the selection of start codon of RAN translation, in particular ACG initiation (new Figure 4F&G). RPS26 depletion affected ACG-initiated but not GTG- or CTG-initiated RAN translation.

In the previous version of the manuscript, we wrote that we did not identify any specific motifs or enrichment within analyzed transcripts in comparison to the background. On the other hand, we found that the GC-content among analyzed transcripts is higher within 5’UTRs and in close proximity to ATG in coding sequences (Figure 4D), what suggests the importance of RNA stable structures in this region. In addition, we showed that mRNAs encoding proteins responding to RPS26 depletion have shorter than average 5’UTRs (new Figure 4E).

(8) Mechanism is lacking entirely. There are many ways in which ribosomes could have mRNA-specific effects. The authors tried to find an effect from the Kozak sequence, unsuccessfully (however, they also did not do the experiment correctly, as they failed to recognize that the Kozak sequence differs between yeast, where it is A-rich, and mammalian cells, where it is GGCGCC). Collisions could be another mechanism.

Indeed, collisions as well as other mechanisms such as skewed start codon fidelity may have an effect on efficiency of FMRpolyG biosynthesis. In the current version of the manuscript, we show that RPS26 amount-sensitive regulation seems to be start codonselection dependent (new Figure 4F&G).

Reviewer #2 (Public Review):

Summary:

Translation of CGG repeats leads to the accumulation of poly G, which is associated with neurological disorders. This is a valuable paper in which the authors sought out proteins that modulate RAN translation. They determined which proteins in Hela cells bound to CGG repeats and affected levels of polyG encoded in the 5'UTR of the FMR1 mRNA. They then showed that siRNA depletion of ribosomal protein RPS26 results in less production of FMR1polyG than in control. There are data supporting the claim that RPS26 depletion modulates RAN translation in this RNA, although for some results, the Western results are not strong. The data to support increased aggregation by polyG expression upon S26 KD are incomplete.

We thank the Reviewer for critical comments and suggestions. We sincerely appreciate your rigorous, insightful, and constructive feedback throughout the revision process.

Below each specific point, we addressed the mentioned issues.

Strengths:

The authors have proteomics data that show the enrichment of a set of proteins on FMR1 RNA but not a related RNA.

We thank Reviewer for appreciation of provided MS-screening results, which identified proteins enriched on FMR1 RNA with expanded CGG repeats.

Weaknesses:

- It is insinuated that RPS26 binds the RNA to enhance CGG-containing protein expression. However, RPS26 reduction was also shown previously to affect ribosome levels, and reduced ribosome levels can result in ribosomes translating very different RNA pools.

In previous version of the manuscript we did not state that RPS26 binds directly to RNA with expanded CGG repeats and we did not show the experiment indicating direct interaction between studied RNA and RPS26. What we showed is that RPS26 was enriched on FMR1 RNA MS samples, however, we did not verify whether it is direct or indirect interaction. We also tried to test hypothesis that lack of RPS26 in PIC complex may affect efficiency of RAN translation initiation via specific, previously described in yeast Kozak context (Ferretti M, 2017, Nat Struct Mol Biol). As we described this hypothesis was negatively validated. However, we showed that other features of 5’UTR sequences (e.g. higher GC-content or shorter leader sequence) are potentially important for translation efficiency in cells with depleted RPS26.

Indeed, RPS26 is involved in 40S maturation steps (Plassart L, 2021, eLife) and its insufficiency or mutations or blocking its inclusion to 40S ribosome may result in incomplete 40S maturation, which subsequently might negatively affect translation per se. However, we did not observe global translation inhibition after RPS26 depletion or depletion of TSR2, the chaperon involved in incorporation/exchange RPS26 to small ribosomal subunit (new Figure 2B and 5C). In addition, our SILAC-MS data indicates that majority of studied proteins (including FMRP, the main product of FMR1 gene) were not affected by RPS26 depletion which can be carefully extrapolated to global translation. In revised manuscript we also showed that relatively low silencing of RPS26 also decreased FMRpolyG production in model cells (new Figure 1D).

We agree that reduced ribosome levels can result in different efficiency of translation of different RNA pools. We enhance this statement in revised manuscript. However, we also showed that the same mRNA containing different near cognate start codons (single/two nucleotide substitution) specific to RAN translation, or targeting this codon with antisense oligonucleotides resulted in altered sensitivity of FMR1 mRNA translation to RPS26 depletion (new Figure 4F).

- A significant claim is that RPS26 KD alleviates the effects of FMRpolyG expression, but those data aren't presented well.

We thank the Reviewer for this comment. In the new version of the manuscript, we have added new microscopic images and improved the explanation of Figure 1E. We have also completed the interpretation of Figure 1F in the main text, figure image as well as figure legend, and we hope that these changes will ameliorate understanding of our data.

Recommendations For The Authors:

- A significant claim is that RPS26 KD alleviates the effects of FMR polyG expression, but those data aren't presented well:

Figure 1D (supporting data in S2) and 2D - the authors need to show representative images of a control that has aggregation and indicate aggregates being counted on an image. The legend states that there are no aggregates, but the quantification of aggregates/nucleus is ~1, suggesting there are at least 1 per cell. It is preferred to show at least a representative of what is quantified in the main figure instead of a bar graph.

The representative images of control and siRPS26-treated cells are now shown in revised version of Figure 1E. Additionally, we completed the Figure legend concerning this part, as well as extended description of the experiment in Materials&Methods section.

Figure 1E - it is unclear what luminescence signal is being measured. Is this a dye for an apoptotic marker? More information is needed in the legend.

This information was added to the legend of modified Figure 1F (previously 1E) as suggested.

- Some of the Western blots are not very convincing. Better evidence for the changes in bar graphs would improve how convincing the data are:

Fig 2B. The western for FMR95G in the first model is not very convincing. The difference by eye for the second siRNA seems to give a larger effect than the first for 95G construct but they appear almost the same on the graph. More supporting information for the quantification is needed.

We provided better explanation for WB quantification in M&M section in the manuscript. Alos, we provided additional blot demonstrating independent biological replicate of the mentioned experiment in supplementary materials (Supplementary Figure S2E).

Figure 4A, the blots for RPS26 and FMR95G are not convincing. They are quite smeary compared to all of the others shown for these proteins in other figures. Could a different replicate be shown?

We provided additional blot demonstrating the effect on transiently expressed FMRpolyG affected by depletion of TSR2 in COS7 cell line (Supplementary Figure S4A).

Figure 5A and 5B blots are not ideal. Could a different replicate be shown? Or show multiple replicates in the supplemental figure?

We provided additional blots from the same experiment, although data is not statistically significant, most likely due to low quality of normalization factor, which is Vinculin (Supplementary Figure S5A). Nevertheless, the level of FMRpolyG is decreased by ~70% after RPS25 silencing in SH-SY5Y cells.

Figure 2C. Please use the same y axes for all four Westerns in B and C. One would like to compare 95 and 15 repeats, but it is difficult when the y axes are different.

Thank you for this comment. The y axis was adjusted as suggested by the Reviewer.

Figure 3D-The text suggests a significant difference between positive and negative responders that is not clear in the figure.

In the main body of the manuscript we state that: “We did not observe any significant differences in the frequency of individual nucleotide positions in the 20-nucleotide vicinity of the start codon relative to the expected distribution in the BG”, which is in line with the graph showed in Figure 4D (previously 3D).

Reviewer #3 (Public Review):

Tutak et al provide interesting data showing that RPS26 and relevant proteins such as TSR2 and RPS25 affect RAN translation from CGG repeat RNA in fragile X-associated conditions. They identified RPS26 as a potential regulator of RAN translation by RNAtagging system and mass spectrometry-based screening for proteins binding to CGG repeat RNA and confirmed its regulatory effects on RAN translation by siRNA-based knockdown experiments in multiple cellular disease models and patient-derived fibroblasts. Quantitative mass spectrometry analysis found that the expressions of some ribosomal proteins are sensitive to RPS26 depletion while approximately 80% of proteins including FMRP were not influenced. Since the roles of ribosomal proteins in RAN translation regulation have not been fully examined, this study provides novel insights into this research field. However, some data presented in this manuscript are limited and preliminary, and their conclusions are not fully supported.

(1) While the authors emphasized the importance of ribosomal composition for RAN translation regulation in the title and the article body, the association between RAN translation and ribosomal composition is apparently not evaluated in this work. They found that specific ribosomal proteins (RPS26 and RPS25) can have regulatory effects on RAN translation (Figures 1C, 2B, 2C, 2E, 4A, 5A, and 5B), and that the expression levels of some ribosomal proteins can be changed by RPS26 knockdown (Figure 3B, however, the change of the ribosome compositions involved in the actual translation has not been elucidated). Therefore, their conclusive statement, that is, "ribosome composition affects RAN translation" is not fully supported by the presented data and is misleading.

We thank the Reviewer for critical comments and suggestions. We agree that the initial title and some statements in the text were misleading and the presented data did not fully support the aforementioned statement regarding ribosomal composition affecting FMRpolyG synthesis. Therefore, in the revised version of the manuscript we included a control experiment indicating that depletion of another core 40S ribosomal protein (RPS6) did not impact the FMRpolyG synthesis (new Figure 5C), which supports our hypothesis that RPS26 and RPS25 are specific CGG-related RAN translation modifiers. To precisely deliver a main message of our work, we changed the title that will indicate the specific effect of RPS26 and RPS25 insufficiency on RAN translation of FMRpolyG. Proposed title: “Insufficiency of 40S ribosomal proteins, RPS26 and RPS25 negatively affects biosynthesis of polyglycine-containing proteins in fragile-X associated conditions”. We also changed all statements regarding “ribosomal composition” in main text of the new version of manuscript.

(2) The study provides insufficient data on the mechanisms of how RPS26 regulates RAN translation. Although authors speculate that RPS26 may affect initiation codon fidelity and regulate RAN translation in a CGG repeat sequence-independent manner (Page 9 and Page 11), what they really have shown is just identification of this protein by the screening for proteins binding to CGG repeat RNA (Figure 1A, 1B), and effects of this protein on CGG repeat-RAN translation. It is essential to clarify whether the regulatory effect of RPS26 on RAN translation is dependent on CGG repeat sequence or near-cognate initiation codons like ACG and GUG in the 5' upstream sequence of the repeat. It would be better to validate the effects of RPS26 on translation from control constructs, such as one composed of the 5' upstream sequence of FMR1 with no CGG repeat, and one with an ATG substitution in the 5' upstream sequence of FMR1 instead of near-cognate initiation codons.

We agree that the data presented in the manuscript implies that insufficiency of RPS26 plays a pivotal role in the regulation of CGG-related RAN translation and in the revised version of the manuscript we included a series of experiments indicating that ACG codon selection seems to be an important part of RPS26 level-dependent regulation of polyglycine production (new Figure 4F&G; see point 3 below for more details). Importantly, in the luciferase assay showed on Figure 4F we used the AUG-initiated firefly luciferase reporter as normalization control.

Moreover, to verify if FMRpolyG response to RPS26 deficiency depends on the type of reporter used, we repeated many experiments using FMRpolyG fused with different tags. The luciferase-based assays were in line with experiments conducted on constructs with GFP tag (new Figure 1D), thus strengthening our previous data. Moreover, in the series of experiments, we show that FMRP synthesis which is initiated from ATG codon located in FMR1 exon 1, was not affected by RPS26 depletion (Figure 3E & 4C), even though its translation occurs on the same mRNA as FMRpolyG. This indicates a specific RPS26 regulation of polyglycine frame initiated from ACG near cognate codon.

(3) The regulatory effects of RPS26 and other molecules on RAN translation have all been investigated as effects on the expression levels of FMRpolyG-GFP proteins in cellular models expressing CGG repeat sequences Figures 1C, 2B, 2C, 2E, 4A, 5A, and 5B). In these cellular experiments, there are multiple confounding factors affecting the expression levels of FMRpolyG-GFP proteins other than RAN translation, including template RNA expression, template RNA distribution, and FMRpolyG-GFP protein degradation. Although authors evaluated the effect on the expression levels of template CGG repeat RNA, it would be better to confirm the effect of these regulators on RAN translation by other experiments such as in vitro translation assay that can directly evaluate RAN translation.

We agree that there are multiple factors affecting final levels of FMRpolyG-GFP proteins including aforementioned processes. We evaluated the level of FMR1 mRNA, which turned out not to be decreased upon RPS26 depletion (Figure 3B&C), therefore, we assumed that what we observed, was the regulation on translation level, especially that RPS26 is a ribosomal protein contacting mRNA in E-site. We believe that direct assays such as in vitro translation may be beneficial, however, depletion of RPS26 from cellular lysate provided by the vendor seems technically challenging, if not completely impossible. Instead, we focused on sequence/structure specific regulation of RAN translation with the emphasis on start-codon initiation selection. It resulted in generating the valuable results pointing out the RPS26 role in start codon fidelity (Figure 4F&G). These new results showed that translation from mRNAs differing just in single or two nucleotide substitution in near cognate start codon (ACG to GUG or ACG to CUG), although results in exactly the same protein, is differently sensitive to RPS26 silencing (new Figure 4F). Similar differences were observed for translation efficiency from the same mRNA targeted or not with antisense oligonucleotide complementary to the region of RAN translation initiation codon (new Figure 4G). These results also suggest that stability of FMRpolyG is not affected in cells with decreased level of RPS26.

(4) While the authors state that RPS26 modulated the FMRpolyG-mediated toxicity, they presented limited data on apoptotic markers, not cellular viability (Figure 1E), not fully supporting this conclusion. Since previous work showed that FMRpolyG protein reduces cellular viability (Hoem G, 2019,Front Genet), additional evaluations for cellular viability would strengthen this conclusion.

We thank the Reviewer for this suggestion. We addressed the apoptotic process in order to determine the effect of RPS26 depletion on RAN translation related toxicity (Figure 1F). In revised version of the manuscript, we also added the evaluation on how cells proliferation was affected by RPS26, RPS25, RPS6 and TSR2 depletion. Our data indicate that TSR2 silencing slightly impacted the cellular fitness (new Figure 5D), whereas insufficiencies of RPS26, RPS25 and RPS6 had a much stronger negative effect on proliferation (new Figure 2A, 5D, 6C), which is in line with previous data (Cheng Z 2019, Mol Cell; Luan Y, 2022, Nucleic Acids Res). The difference in proliferation rate after treatment with siRPS26 makes proper interpretation of cellular viability assessment very difficult.

Recommendations For The Authors:

(1) It would be nice to validate the effects of overexpression of RPS26 and other regulators on RAN translation, not limited to knockdown experiments, to support the conclusion.

We did not performed such experiments because we believed that RPS26 overexpression may have no or marginal effect on translation or RAN translation. It is likely impossible to efficiently incorporate overexpressed RPS26 into 40S subunits, because the concentration of all ribosomal proteins in the cells is very high.

(2) It would be better to explain how authors selected 8 proteins for siRNA-based validation (Figure 1C, 1D, S1D) from 32 proteins enriched in CGG repeat RNA in the first screening.

We selected those candidates based on their functions connected to translation, structured RNA unwinding or mRNA processing. For example, we tested few RNA helicases because of their known function in RAN translation regulation described by other researchers. This explanation was added to the revised version of the manuscript.

(3) Original image data showing nuclear FMRpolyG-GFP aggregates should be presented in Figure 1D.

The representative images of control and siRPS26-treated cells are now shown in modified version of Figure 1E and described with more details in the legend.

(4) Image data in Figure 2A and 2D have poor signal/noise ratio and the resolution should be improved. In addition, aggregates should be clearly indicated in Figure 2D in an appropriate manner.

The stable S-FMR95xG cellular model is characterized by very low expression of RANtranslated FMR95xG, therefore, it is challenging to obtain microscopic images of better quality with higher GFP signal. In the L-99xCGG model expression of transgene is higher. Therefore, we provided new image in the new version of Figure 3D (former 2D). Moreover, we showed aggregates on the image obtained using confocal microscopy (new Supplementary Figure 2D).

(5) The detailed information on patient-derived fibroblast (age and sex of the patient, the number of CGG repeats, etc.) in Figure 2F needed to be presented.

This information was added to the figure legend (Figure 3F; previously 2F) and in the Material and Methods section as suggested.

(6) It would be better to normalize RNA expression levels of FMR1 and FMR1-GFP by the housekeeping gene in Figure S2C, like other RT-qPCR experimental data such as Figure 2B.

Normalization of FMR1-GFP to GAPDH is now shown in modified version of Figure S2C (right graph) as requested by the Reviewer.

(7) It would be better to add information on molecular weight on all Western blotting data.

(8) Marks corresponding to molecular weight ladder were added to all images.

Full blots, including protein ladders were deposited in Zenodo repository, under doi: 10.5281/zenodo.13860370

References

Cheng Z, Mugler CF, Keskin A, Hodapp S, Chan LYL, Weis K, Mertins P, Regev A, Jovanovic M & Brar GA (2019) Small and Large Ribosomal Subunit Deficiencies Lead to Distinct Gene Expression Signatures that Reflect Cellular Growth Rate. Mol Cell 73: 36-47.e10

Havkin-Solomon T, Fraticelli D, Bahat A, Hayat D, Reuven N, Shaul Y & Dikstein R (2023) Translation regulation of specific mRNAs by RPS26 C-terminal RNA-binding tail integrates energy metabolism and AMPK-mTOR signaling. Nucleic Acids Res 51: 4415–4428

Hoem,G., Larsen,K.B., Øvervatn,A., Brech,A., Lamark,T., Sjøttem,E. and Johansen,T. (2019) The FMRpolyGlycine protein mediates aggregate formation and toxicity independent of the CGG mRNA hairpin in a cellular model for FXTAS. Front. Genet., 10, 1–18.

Luan Y, Tang N, Yang J, Liu S, Cheng C, Wang Y, Chen C, Guo YN, Wang H, Zhao W, et al (2022) Deficiency of ribosomal proteins reshapes the transcriptional and translational landscape in human cells. Nucleic Acids Res 50: 6601–6617

Plassart L, Shayan R, Montellese C, Rinaldi D, Larburu N, Pichereaux C, Froment C, Lebaron S, O’donohue MF, Kutay U, et al (2021) The final step of 40s ribosomal subunit maturation is controlled by a dual key lock. Elife 10

eLife Assessment

This valuable study uses a massive and long-term experimental data set to provide solid evidence on how tree diversity affects host-parasitoid communities of insects in forests. The work will be of interest to ecologists working on biodiversity conservation, community ecology, and food webs.

Reviewer #2 (Public review):

Summary

The authors use a tree biodiversity experiment to evaluate the effects of tree community and canopy cover on communities of cavity-nesting Hymenoptera and their parasitoids and the interactions between these two guilds. They find that multiple measures of tree diversity influence the hosts, parasitoids, and their interactions. In addition, host-parasitoid interactions show a phylogenetic signal.

Strength

The authors use a massive, long-term data set, meaningful community descriptors, and a solid set of analyses to explore the impacts of tree communities on host-parasitoid networks. It is rare to have such detailed data from multiple different trophic levels.

Weakness

Even though the data expands over several seasons, this is not considered in the analyses, but communities sampled at different years are pooled at the plot level. A more detailed analysis of the variations between years could reveal underlaying patterns as currently the differences in the communities and their structure between the years are ignored (e.g., when estimating the phylogenetic compositions not all the species pooled together actually coexist in time).<br /> Also, the precision of the writing should be improved as it was not always easy to follow the text and the thoughts.

Author response:

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

It would be great if the authors could add clarification about the NMDS analyses and the associated results (Fig. 1, Table 1 and Tables S2-4). The overall aim of these analyses was to see how plot characteristics (e.g. canopy cover) and composition of one taxonomic group were related to the composition of another taxonomic group. The authors quantified species composition by two axes from NMDS. (1) This analysis may yield an interpretation problem: if we only find one of the axes, but not the other, was significantly related to one variable, it would be difficult to determine whether that specific variable is important to the species composition because the composition is co-determined by two axes. (2) It is unclear how the authors did the correlation analyses for Tables S2-4. If correlation coefficients were presented in these tables, then these coefficients should be the same or very similar if we switch the positions of y vs. x. That is, the correlation between host vs. parasite phylogenetic composition would be very close to the correlation between parasite vs. phylogenetic composition, but not as the author found that these two relationships were quite different, leading to the interpretation of bottom-up or top-down processes. It is also unclear which correlation coefficient was significant or not because only one P value was provided per row in these tables. (3) In addition to the issues of multiple axes (point 1), NMDS axes simply define the relative positions of the objects in multi-dimensional space, but not the actual dissimilarities. Other methods, such as generalized dissimilarity modeling, redundancy analysis and MANOVA, can be better alternatives.

Thank you for the thorough and constructive review. We have taken the concerns and questions raised by the editors and reviewers into account and provided clarification about the NMDS analyses as well as additional analyses to confirm our results. First, we have now added a brief explanation in the manuscript regarding the interpretation of the two NMDS axes and how they relate to species composition. Specifically, we clarified that while NMDS defines the relative positions of objects in multi-dimensional space, the two axes together provide a more comprehensive representation of the community composition, which is not solely determined by either axis independently. Second, we acknowledge that alternative approaches could help further strengthen our conclusions. To address this, we incorporated Mantel tests and PERMANOVA (with ‘adonis2’) as additional validation methods. These analyses allowed us to summarize compositional patterns while testing our hypotheses within the framework of the plot characteristics and taxonomic relationships. We have added these analyses and their results in the manuscript to reinforce our findings.

In methods: L478-481 “To strengthen the robustness of our findings based on NMDS, we further validated the results using Mantel test and PERMANOVA (with ‘adonis2’) for correlation between communities and relationships between communities and environmental variables.”

L469-475 “NMDS was used to summarize the variation in species composition across plots. The two axes extracted from the NMDS represent gradients in community composition, where each axis reflects a subset of the compositional variation. These axes should not be interpreted in isolation, as the overall species composition is co-determined by their combined variation. For clarity, results were interpreted based on the relationships of variables with the compositional gradients captured by both axes together."

In results: L172-177 “The PERMANOVA analysis also highlighted the important role of canopy cover for host and parasitoid community (Table S6-9). The Mantel test revealed a consistent pattern with the NMDS analysis, highlighting a pronounced relationship between the species composition of hosts and parasitoids (Table S10). However, the correlation between the phylogenetic composition of hosts and parasitoids was not significant.”

In discussion: L257-261 “However, this significant pattern was observed only in the NMDS analysis and not in the Mantel test, suggesting that the non-random interactions between hosts and parasitoids could not be simply predicted by their community similarity and associations between the phylogenetic composition of hosts and parasitoids are more complex and require further investigation in the future.”

-- One additional minor point: "site" would be better set as a fixed rather than random term in the linear mixed-effects models, because the site number (2) is too small to make a proper estimate of random component.

Now we treated “site” as a fixed factor in our models, interacting with tree species richness/tree MPD and tree functional diversity to reflect the variation of spatial and tree composition between the two sites. We found the main results did not change, as both sites showed consistent patterns for effects of tree richness/MPD on network metrics, which is more pronounced in one site.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The authors analyzed how biotic and abiotic factors impact antagonistic host-parasitoid interaction systems in a large BEF experiment. They found the linkage between the tree community and host-parasitoid community from the perspective of the multi-dimensionality of biodiversity. Their results revealed that the structure of the tree community (habitat) and canopy cover influence host-parasitoid compositions and their interaction pattern. This interaction pattern is also determined by phylogenetic associations among species. This paper provides a nice framework for detecting the determinants of network topological structures.

Strengths:

This study was conducted using a five-year sampling in a well-designed BEF experiment. The effects of the multi-dimensional diversity of tree communities have been well explained in a forest ecosystem with an antagonistic host-parasitoid interaction.

The network analysis has been well conducted. The combination of phylogenetic analysis and network analysis is uncommon among similar studies, especially for studies of trophic cascades. Still, this study has discussed the effect of phylogenetic features on interacting networks in depth.

Weaknesses:

(1) The authors should examine species and interaction completeness in this study to confirm that their sampling efforts are sufficient.

(2) The authors only used Rao's Q to assess the functional diversity of tree communities. However, multiple metrics of functional diversity exist (e.g., functional evenness, functional dispersion, and functional divergence). It is better to check the results from other metrics and confirm whether these results further support the authors' results.

(3) The authors did not elaborate on which extinction sequence was used in robustness analysis. The authors should consider interaction abundance in calculating robustness. In this case, the author may use another null model for binary networks to get random distributions.

(4) The causal relationship between host and parasitoid communities is unclear. Normally, it is easy to understand that host community composition (low trophic level) could influence parasitoid community composition (high trophic level). I suggest using the 'correlation' between host and parasitoid communities unless there is strong evidence of causation.

Thank you very much for your thoughtful and constructive review of our manuscript. We have carefully addressed your comments and made several revisions to improve the clarity and robustness of our work.1) We appreciate your suggestion regarding species and interaction completeness. To confirm that our sampling efforts were sufficient, we have now included a figure (Fig. S1) showing the species accumulation curve and the coverage of interactions in our study. This ensures that the data collected provide a comprehensive representation of the system. 2) Regarding the use of only Rao’s Q to assess functional diversity, we acknowledge that multiple metrics of functional diversity exist. However, due to the large number of predictors in our analysis, we decided to streamline our approach and focus on Rao’s Q as it provides a robust measure for our research objectives. We have discussed this decision in the revised manuscript and clarified that, while additional metrics could be informative, we believe Rao’s Q sufficiently captures the key aspects of functional diversity in our study. 3) We have elaborated on the robustness analysis and the null model used in our study. Specifically, we now clarified which extinction sequence (random extinction) was used in our manuscript, and explained interaction abundance was incorporated into the robustness calculations (networklevel function, weighted=TURE; see L506). 4) We have revised the text to clarify the relationship between host and parasitoid communities. As you correctly pointed out, while it is intuitive that host community composition influences parasitoid community composition, we have reframed our analysis to emphasize the correlation between the two communities rather than implying causation without strong evidence. We have revised the manuscript to reflect this distinction.

Reviewer #2 (Public Review):

Summary:

In their manuscript, Multi-dimensionality of tree communities structure host-parasitoid networks and their phylogenetic composition, Wang et al. examine the effects of tree diversity and environmental variables on communities of reed-nesting insects and their parasitoids. Additionally, they look for the correlations in community composition and network properties of the two interacting insect guilds. They use a data set collected in a subtropical tree biodiversity experiment over five years of sampling. The authors find that the tree species, functional, and phylogenetic diversity as well as some of the environmental factors have varying impacts on both host and parasitoid communities. Additionally, the communities of the host and parasitoid showed correlations in their structures. Also, the network metrices of the host-parasitoid network showed patterns against environmental variables.

Strengths:

The main strength of the manuscript lies in the massive long-term data set collected on host-parasitoid interactions. The data provides interesting opportunities to advance our knowledge on the effects of environmental diversity (tree diversity) on the network and community structure of insect hosts and their parasitoids in a relatively poorly known system.

Weaknesses:

To me, there are no major issues regarding the manuscript, though sometimes I disagree with the interpretation of the results and some of the conclusions might be too far-fetched given the analyses and the results (namely the top-down control in the system). Additionally, the methods section (especially statistics) was lacking some details, but I would not consider it too concerning. Sometimes, the logic of the text could be improved to better support the studied hypotheses throughout the text. Also, the results section cannot be understood as a stand-alone without reading the methods first. The study design and the rationale of the analyses should be described somewhere in the intro or presented with the results.

Thank you very much for your valuable comments and suggestions on our manuscript! We appreciate your feedback and have made revisions accordingly. Specifically, we have rephrased the interpretation of the results and conclusions to better align with the analyses and avoid overstatements, particularly concerning the top-down control in the system. In addition, we have expanded the methods section by providing more details, especially regarding the statistical approaches, to address the points you raised. To enhance the clarity of the manuscript, we have also ensured that the logic of the text better supports the hypotheses throughout. Please see our point-by-point responses below for additional clarifications.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Line 120: "... and large ecosystems susceptible to global change (add citation here)": Citation(s)?

Now we provided the missed citations.

Line 141: Add sampling completeness information.

Now we provide a new figure about sampling completeness (Fig. S1) in the supplementary materials, showing the adequate sampling effort for our study.

Line 151: use more metrics in the evaluation of functional diversity

We used tree functional diversity Rao’s Q, which is an integrated and wildly used metric to represent functional dissimilarity of trees. As our study focus on multiple diversity indices of trees, it would be better to do not pay more attention to one type of diversity. Thank you for your suggestion!

Line 164: host vulnerability. Although generality and vulnerability are commonly used in network analysis, it is better to link these metrics with the trophic level, like the 'host vulnerability' you used. Thus, you can use 'parasitoid generality' instead of 'generality'.

Thanks for your suggestion. Now the metrics were labeled with the trophic levels in the full text.

Line 169: two'.'

Corrected.

Line 173: 'parasitoid robustness' Or 'robustness of parasitoids'?

Now changed it to ‘robustness of parasitoid’.

Lines 173, 468: For the robustness estimations, maybe use null model for binary networks to get random distributions?

Thanks for the suggestion. Actually, we have used Patefield null models to compare the randomized robustness and observed, helping to assess whether the robustness of the observed network is significantly different compared to expected by chance. All robustness indices across plots were significantly different from a random distribution, See results section L197-201.

Line 184: modulating interacting communities of hosts and parasitoids.

Changed accordingly.

Line 186: determined host-parasitoid interaction patterns

Changed accordingly.

Line 191: Biodiversity loss in this study refers to low trophic levels.

Now we clarified this point.

Line 190: understand

Changed accordingly.

Lines 215-216: Reorganize these sentences

Line 227: indirectly influenced by...

Changed accordingly.

Line 238: Be more specific. Which type of further study?

Rephased it more specific.

Lines 297-299: rewrite this sentence to make it more transparent.

Now we rewrote the sentence accordingly.

Line 302: Certain

Changed accordingly.

Line 453: effective

Changed accordingly.

Finally, the authors should check the text carefully to avoid grammatical errors.

Thanks, now we have checked the full text to avoid grammatical errors.

Reviewer #2 (Recommendations For The Authors):

I feel that the authors have very interesting data and have a solid set of analyses. I do not have major issues regarding the manuscript, though sometimes I disagree with the interpretation of the results and some of the conclusions might be too far-fetched given the analyses and the results. Additionally, the methods section (especially statistics) was lacking some details, but I would not consider it too concerning at this point.

I feel that the largest caveat of the manuscript remains in the representation of the rationale of the study. I felt the introduction could be more concise and be better focused to back up the study questions and hypotheses. Many times, the sentences were too vague and unspecific, and thus, it was difficult to understand what was meant to be said. The authors could mention something more about how community composition of hosts and parasitoids are expected to change with the studied experimental design regarding the metrices you mention in the introduction (stronger hypotheses). The results section cannot be understood as a stand-alone without reading the methods first. The study design and the rationale of the analyses must be described somewhere in the intro or results, if the journal/authors want to keep the methods last structure. Also, the results and discussion could be more focused around the hypotheses. Naturally, these things can be easily fixed.

I also disagree with the interpretation of results finding top-down control in the system (it might well be there, but I do not think that the current methods and tests are suitable in finding it). First, the used methodology cannot distinguish parasitoids if the hosts are not there and the probability to detect parasitoid likely depends on the abundance of the host. Thus, the top-down regulation is difficult to prove (is it the parasitoids that have driven the host population down). Secondly, I would be hesitant to say anything about the top-down and bottom-up control in the systems as the data in the manuscript is pooled across five years while the top-down/bottom-up regulation in insect systems usually spans only one season/generation in time (much shorter than five years). Consequently, the analyses are comparing the communities of species that some of most likely do not co-exist (they were found in the same space but not during the same time). Luckily, the top-down/bottom-up effects could potentially be explored by using separately the time steps of the now pooled community data: e.g., does the population of the host decrease in t if the parasitoids are abundant in t-1? There are also other statistical tests to explore these patterns.

In the manuscript "Phylogenetic composition" refers to Mean Pairwise Distance. I would use "phylogenetic diversity" instead throughout the text. Also, to my understanding, in trees both "phylogenetic composition" and "phylogenetic diversity" are used even though based on their descriptions, they are the same.

Detailed comments:

Punctuation needs to be checked and edited at some point (I think copy-pasting had left things in the wrong places). Please check that "-" instead of "-" is used in host-parasitoid.

1-2 The title is not very matching with the content. "Multi-dimensionality" is not mentioned in the text. "phylogenetic composition" -> "phylogenetic diversity"

We didn’t find the role of functional diversity of trees in host-parasitoid interactions, but we still have tree richness and phylogenetic diversity. I also disagree with that using phylogenetic diversity to replace phylogenetic composition, because diversity highlights higher or lower phylogenetic distance among communities, while the later highlights the phylogenetic dissimilarity across communities.

53-57 This sentence is quite vague and because of it, difficult to follow. Consider rephrasing and avoiding unspecified terms such as "tree identity", "genetic diversity", and "overall community composition of higher trophic levels" (at least, I was not sure what taxa/level you meant with them).

Rephased.

L58-61 “Especially, we lack a comprehensive understanding of the ways that biotic factors, including plant richness, overall community phylogenetic and functional composition of consumers, and abiotic factors such as microclimate, determining host–parasitoid network structure and host–parasitoid community dynamics.”

56 I would remove "interact" as no interactions were tested.

Removed accordingly.

59-60 This needs rephrasing. I feel "taxonomic and phylogenetic composition should be just "species composition". To better match, what was done: "taxonomic, phylogenetic, and network composition of both host and parasitoid communities" -> "species and phylogenetic diversity of both host and parasitoid communities and the composition their interaction networks"

Changed accordingly.

62 Remove "tree composition".

Done.

62 Replace "taxonomic" with "species". Throughout the text.

Done.

63-64 "Generally, top-down control was stronger than bottom-up control via phylogenetic association between hosts and parasitoids" I disagree, see my comments elsewhere.

Now we rephased the sentence.

L68-70 “Generally, phylogenetic associations between hosts and parasitoids reflect non-randomly structured interactions between phylogenetic trees of hosts and parasitoids.”

68 "habitat structure and heterogeneity" This is too strong and general of a statement based on the results. You did not really measure habitat structure or heterogeneity.

Now we rephased the statement to avoid strong and general description.

L71-73 “Our study indicates that the composition of higher trophic levels and corresponding interaction networks are determined by plant diversity and canopy cover especially via trophic phylogenetic links in species-rich ecosystems.”

69 Specify "phylogenetic links". Trophic links?

Specified to “trophic phylogenetic links”.

75-77 The sentence is a bit difficult to follow. Consider rephrasing.

Now we rephased it.

L79-82 “Changes in network structure of higher trophic levels usually coincide with variations in their diversity and community, which could be in turn affected by the changes in producers via trophic cascades”

76 Be more specific about what you mean by "community of trophic levels".

Specified to “community composition”.

79 Remove "basal changes of", it only makes the sentence heavier.

Done.

81 What is "species codependence"?

We sim to describe the species co-occurrence depending on their closely relationships. For clarity, now we changed to “species coexistence”

82 What do you mean by "complex dynamics"?

Rephased to “mechanisms on dynamics of networks”.

83 onward: I would not focus so much on top-down/bottom-up as I feel that your current analyses cannot really say anything too strong about these causalities but are rather correlative.

Thanks, we now removed the relevant contents from the discussion. However, we kept one sentence in the Introduction, because it should be highlighted to make reviewers aware of this (the other text on about this were removed).

89 Remove "environmental".

Done.

90 Specify what you mean by "these forces".

Done.

98-99 I have difficulties following the logic here "potential specialization of their hosts may cascade up to impact the parasitoids' presence or absence". Consider rephrasing.

Now we rephased it.

L101-102 “…and their host fluctuations may cascade up to impact the parasitoids’ presence or absence.”

100 Be more specific with "habitat-level changes".

Specified to “community-level changes”

100 I do not see why host-parasitoid systems would be ideal to study "species interactions". There are much simpler and easier systems available.

Changed to “… one of ideal…”

101-103 "influence of" on what?

Now we rephased the sentence.

L104-105 “Previous studies mainly focused on the influence of abiotic factors on host-parasitoid interactions”

104 Be more specific in "the role of multiple components of plant diversity".

Now we specified "the role of multiple components of plant diversity".

L107-108 “…the role of multiple components of plant diversity (i.e. taxonomic, functional and phylogenetic diversity)…”

106 "diversity associations" of what?

“diversity associations between host and parasitoids”.

108 Specify the "direct and indirect effects".

Now we specified it to “…direct and indirect effects (i.e. one pathway and more pathways via other variables)…”

110-113 A bit heavy sentence to follow. Consider rephrasing.

Now we rephased the sentence to make it more readable.

114 Give an example of "phylogenetic dependences".

Done. Phylogenetic dependences (e.g. phylogenetic diversity)

117 Move the "e.g. taxonomic, phylogenetic, functional" within brackets in 117 after "dimensions of biodiversity".

Done.

120 "(add citation here)" Yes please!

Done.

120-121 Specify "such relationships".

Done. Specified to “multiple dimensions of biodiversity”

128-130 This is difficult to follow. Please rephrase.

Now we rephased the sentence.

L135-137 “We aimed to discern the primary components of the diversity and composition of tree communities that affect higher trophic level interactions via quantifying the strength and complexity of associations between hosts and parasitoid.”

131-132 Remove "phylogenetic and". It is redundant to phylogenetic diversity.

Done.

128 Tested robustness does not really capture "stability of associations".

Yes, we agree. Now we rephased the sentence and exclude the “stability” description.

133 Specify "phylogenetic processes".

Now we specified “phylogenetic processes”.

L140-141 “…especially via phylogenetic processes (e.g. lineages of trophic levels diverge and evolve over time)…”

141 I would like to have more details on the data set somewhere in the results. How many individuals and species were found in each plot (on average)? Was there a lot of temporal variation (e.g. between the seasons)? On how many sites were the insect species found?

Thanks for your suggestion. Now we provide more details on the data set in the results (L153-156), including mean values of individuals and species in each plot. However, the temporal variation should be studied for another relative independent topic, as our study focus on the general patter of interactions between hosts and parasitoids. Therefore, we would not put more information on temporal changes to make readers get lost in the text.

153-156 “Among them, we found 56 host species (12 bees and 44 wasps, mean abundance and richness are 400.05 and 45.14, respectively, for each plot) and 50 parasitoid species (38 Hymenoptera and 12 Diptera, mean abundance and richness are 14.07 and 9.05, respectively, for each plot).”

149 tree -> trees

Done.

149 Should there read also some else than "NMDS scores"?

Thanks! Now we provided more details about “NMDS scores”.

L161-162 “(NMDS axis scores; i.e. preserving the rank order of pairwise dissimilarities between samples)”

149 You could mention the amount of variation explained by the first two axes of the NMDSs. Now it is difficult to estimate how much the models actually explain.

Thanks for your comments! However, we could not directly provide the explanatory power of the two axes, because NMDS is based on rank-order distances rather than linear relationships like in PCA. However, the goodness of fit for the NMDS solution is typically evaluated using the stress value. We provide the stress value in the figure caption.

150 "tree MPD" is mentioned for the first time. Spell it out.

Done.

150 Explain "eastness".

Done.

L163-164 “…eastness (sine-transformed radian values of aspect) )”

151 How was "tree functional diversity" quantified?

Please see methods. L437-L438.

160 Specify that you talk about phylogenetic compositions of the host and parasitoid communities here.

We would keep it refined here, keeping consistent with species composition here. Phylogenetic composition just represents the dissimilarities of phylogenetic linages within a community.

161 Describe "parafit" test here when first mentioned.

Done, see methods L485-487.

182 Keep on referring to tables and figures in the discussion! Also, more clearly discuss your hypotheses. There are lots of discussions on top-down/bottom-up control. It could be good to form a hypothesis on them and predict what kind of patterns would suggest either one and what would you expect to find regarding them.

Now we referred figures and tables in the discussion. As the contents on top-down and bottom-up control were not fit very well with our study (as also suggested by reviewers), so we rephased the discussion and also clearly discuss our hypotheses in the discussion. See L218, L226, and L237 etc.

186 "partly determined host-parasitoid networks" Be more specific.

Done.

L206-207 “…partly determined host-parasitoid network indices, including vulnerability, linkage density, and interaction evenness.”

195 Tell what you mean by "other biotic factors".

Specified it: “…other biotic factors such as elevation and slope…”

197-198 "It seems likely that these results are based on bee linkages to pollen resources" I would be hesitant to conclude this as the bees most likely forage way beyond the borders of the 30m by 30m study plots.

Thanks for your concern about this problem. While it is true that bees can forage beyond 30 x 30m, the study focuses on their nesting behavior and activity within this defined area, rather than their entire foraging range. Existing literature shows bees often forage locally when resources are available (e.g. Ebeling et al., 2012 Oecologia; Guo et al., year, Basic and Applied Ecology). Therefore, we are confident that this pattern could be associated with the resources around the trap nests.

223 "This could be further tested by collecting the food directly used by the wasps (caterpillars)" A bit unnecessary addition.

Thanks for your suggestion. Yes, this definitely is a good point, but currently we don’t have enough data of caterpillars, but we will follow this in the future.

232-238 I disagree with the authors on the interpretation of the causality of the results here. I think that the community of parasitoids simply indicates which host species are available, while the host community does not have an as strong effect on parasitoid community as parasitoids do not utilise the whole species pool of the hosts. (Presence of parasitoid tells that the host is around while the presence of the host does not necessarily tell about the presence of the parasitoid.) To me, this would rather indicate a bottom-up than top-down regulation. Similar patterns are also visible in species communities of hosts and parasites.

Thank you for your suggestion. We agree with you that parasitoids are more depended on hosts, as host could not be always attacked by parasitoids. Now we rephased our explanation to follow this argument.

L254-256 “Such pattern could be further confirmed by the significant association between host phylogenetic composition and parasitoid phylogenetic composition (Fig. 1c), which suggested that their interactions are phylogenetically structured to some extent.”

247-266 The logic in this section is difficult to follow. Try rephrasing.

Now we rephased the section for a clearer logic.

L270-287 “Tree community species richness did not significantly influence the diversity of hosts targeted by parasitoids (parasitoid generality), but caused a significant increase in the diversity of parasitoids per host species (host vulnerability) (Fig. 3a; Table 2). This is likely because niche differentiation often influences network specialization via potential higher resource diversity in plots with higher tree diversity (Lopez-Carretero et al. 2014). Such positive relationship between host vulnerability and tree species richness suggested that host-parasitoid interactions could be driven through bottom-up effects via benefit from tree diversity. For example, parasitoid species increases more than host diversity with increasing tree species richness (Guo et al. 2021), resulting increasing of host vulnerability at community level. According to the enemies hypothesis (Root 1973), which posits a positive effects of plant richness on natural enemies, the higher trophic levels in our study (e.g. predators and parasitoids) would benefit from tree diversity and regulate herbivores thereby (Staab and Schuldt 2020). Indeed, previous studies at the same site found that bee parasitoid richness and abundance were positively related to tree species richness, but not their bee hosts (Fornoff et al. 2021, Guo et al. 2021). Because our dataset considered all hosts and reflects an overall pattern of host-parasitoid interactions, the effects of tree species richness on parasitoid generality might be more complex and difficult to predict, as we found that neither tree species richness nor tree MPD were related to parasitoid generality.”

249 "This is likely because niche differentiation often influences network specialization via potential higher resource diversity in plots with higher tree diversity" This is a bit contradicting your vulnerability results as niche differentiation should increase specialization and diversity and specialization should decrease vulnerability (less host per parasitoid).

Thanks! We understand that the concepts of “generality” and “vulnerability” can be a bit confusing. To clarify, “fewer hosts per parasitoid” actually corresponds to lower generality at the community level.

332-337 How did you select the species growing on your plots? Or was only species number considered? What was the pool of tree species growing on the selected plots? Was the selection similar at both sites?

Now we provided more information on the experiment design.

L354-356 “The species pools of the two plots are nonoverlapping (16 species for each site). The composition of tree species within the study plots is based on a “broken-stick” design (see Bruelheide et al. 2014).”

342 Remove "centrally per plot"?

Done.

346-347 Was the selection of different reed diameters similar in all the plots?

Diameters and the relative distribution of diameters was similar in all trap nests.

399 & 432 Are "phylogenetic diversity of the tree communities" and "phylogenetic composition of trees" the same? They are both described as mean pairwise distance.

These two are actually different, as we use this to distinguish the phylogenetic diversity with communities and rank order of dissimilarities between tree communities. Here, the phylogenetic diversity of the tree communities is mean pairwise phylogenetic distance of species for tree communities. Tree phylogenetic composition is the rank order of pairwise dissimilarities between tree communities based on NMDS.

400 Do you think that MPD makes any sense with the monocultures (value is always 0)? Does this have a potential to bias your analyses and result?

We agree your point. However, we do not think that this is a major problem in the analyses. We followed the experimental design and considered low phylogenetic relatedness of tree species in a plot (Likewise in monocultures, the tree species richness is always 1).

402-405 MNTD is not mentioned before or after this. Consider removing this section.

We tested the potential effects of MNTD in our models. Now we mentioned it in our results.

L194-195 “Tree mean nearest taxon distance (MNTD) was unrelated to any network indices.”

405 "Phylogenetic metrics of trees" Which ones?

Both tree MPD and MNTD. Now we have noted it in the manuscript. (L432)

410 Further details on "Rao's Q" and how the functional diversity of the communities was calculated are needed.

Now more details were provided.

L435-438 “Specifically, seven leaf traits were used for calculation of tree functional diversity, which was calculated as the mean pairwise distance in trait values among tree species, weighted by tree wood volume, and expressed as Rao's Q”

413 Specify "higher trophic levels".

Now we specified the trophic levels.

L440-441 “…higher trophic levels in our study area, such as herbivores and predators”

417-424 What about the position of the plots within study sites? Is there potential for edge effects (e.g. bees finding easier the trap nest close to the edge of the experimental forest)? Were there any differences between the two sites? What is the elevation range of the plots?

Thanks for concerning the details of our study. First, all the plots were randomly distributed within the study sites (see Fig. S2). Admittedly, there are several plots are located in the edges of the site. However, we did not consider the potential edge effects in our analysis. Of course, this will be a good point in our future studies. Moreover, the biggest difference between the two is the non-overlapping tree species pool, and the two study sites are apart from 5 km in the same town. Finally, there is not too distinct elevation gradient across the plots (112 m - 260 m).

432-434 "The species and phylogenetic composition of trees, hosts, and parasitoids were quantified at each plot with nonmetric multidimensional scaling (NMDS) analysis based on Morisita-Horn distances" This section needs to be more specific and detailed. Did you do the NMDS separately for each plot as suggested in the text?

We provided more details of the section.

L462-465 “The minimum number of required dimensions in the NMDS based on the reduction in stress value was determined in the analysis (k = 2 in our case). We centred the results to acquire maximum variance on the first dimension, and used the principal components rotation in the analysis.”

435 Specify how picante was used (function and arguments)!

Now we specified the function.

L465-467 “The phylogenetic composition was calculated by mean pairwise distance among the host or parasitoid communities per plot with the R package “picante” with ‘mpd’ function.”

436 "standardized values" Of what? How was the standardisation done?

Now we citied a supplementary table (Table S2) to specify it (see L469). For the standardization, we used ‘scale’ function in R, which standardizes data by centering and scaling data. Specifically, it subtracts the mean and divides by the standard deviation for each variable.

443 Provide more details on parafit.

Actually, we have provided the reason why we use the parafit test and the usage.

L483-486 “We used a parafit test (9,999 permutations) with the R package “ape” to test whether the associations were non-random between hosts and parasitoids. This is widely used to assess host-parasite co-phylogeny by analyzing the congruence between host and parasite phylogenies using a distance-based matrix approach.”

449-451 Rephrase the sentence.

Rephased.

L490-491 “We constructed quantitative host-parasitoid networks at community level with the R package “bipartite” for each plot of the two sites.”

451 "six" Should this be five?

Yes, should be five, thanks.

470-481 What package and function were used for the LMMs?

As we now used linear models, we do no longer use a R package for LMMs.

470 "mix" -> mixed

Changed to linear models.

472 "six" Should this be five?

Again, we changed it to five.

479-481 How did you treat the variables from the two different sites when testing for the correlations to avoid two geographic clusters of data points?

Now we considered the two study sites as fixed factor in our linear models. Moreover, tree-based variables were additionally included as interaction terms with the study sites.

501 "mix" -> mixed

Changed to linear models.

The panel selection for figures 3 and 4 seems random. Justify it!

Thank you. To avoid including too many figures in the main text, which could potentially confuse readers, we have selected the key results that are of primary interest. The remaining figures are provided in the appendix for reference.

533 "Note that axes are on a log scale for tree species richness." Why the log-scale if the analyses were performed with linear fit? Also, the drawn regression lines do not match the model description (non-linear, while a linear model is described in the text). The models should probably be described in more detail.

We used log-transformed to promote the normality of the data. The drawn regression lines are linear lines, which fit our models.

539 "Values were adjusted for covariates of the final regression model." How?

We used residual plot to directly visualizes the relationship between the predictor and the response variable with the fitted regression line, making it easier to assess the model's fit.

Fig. S4 text does not match the figure.

Thanks! We now deleted the unmatched text in the figure.

eLife Assessment

This important study provides new insights into the mechanisms that underlie perceptual and attentional impairments of conscious access. The paper presents convincing evidence of a dissociation between the early stages of low-level perception, which are impermeable to perceptual or attentional impairments, and subsequent stages of visual integration which are susceptible to perceptual impairment but resilient to attentional manipulations. This study will be of interest to scientists working on visual perception and consciousness.

Reviewer #1 (Public review):

Summary:

In this work, Noorman and colleagues test the predictions of the "four-stage model" of consciousness by combining psychophysics and scalp EEG in humans. The study relies on an elegant experimental design to investigate the respective impact of attentional and perceptual blindness on visual processing.

The study is very well summarised, the text is clear and the methods seem sound. Overall, a very solid piece of work. I haven't identified any major weaknesses. Below I raise a few questions of interpretation that may possibly be the subject of a revision of the text.

(1) The perceptual performance on Fig1D appears to show huge variation across participants, with some participants at chance levels and others with performance > 90% in the attentional blink and/or masked conditions. This seems to reveal that the procedure to match performance across participants was not very successful. Could this impact the results? The authors highlight the fact that they did not resort to post-selection or exclusion of participants, but at the same time do not discuss this equally important point.

(2) In the analysis on collinearity and illusion-specific processing, the authors conclude that the absence of a significant effect of training set demonstrates collinearity-only processing. I don't think that this conclusion is warranted: as the illusory and non-illusory share the same shape, so more elaborate object processing could also be occuring. Please discuss.

(3) Discussion, lines 426-429: It is stated that the results align with the notion that processes of perceptual segmentation and organization represent the mechanism of conscious experience. My interpretation of the results is that they show the contrary: for the same visibility level in the attentional blind or masking conditions, these processes can be implicated or not, which suggests a role during unconscious processing instead.

(4) The two paradigms developed here could be used jointly to highlight non-idiosyncratic NCCs, i.e. EEG markers of visibility or confidence that generalise regardless of the method used. Have the authors attempted to train the classifier on one method and apply it to another (e.g. AB to masking and vice versa)? What perceptual level is assumed to transfer?

(4) How can the results be integrated with the attentional literature showing that attentional filters can be applied early in the processing hierarchy?

Comments on revisions:

I'm very pleased with the responses to my previous comments, and congratulate the authors on this excellent piece of work.

Reviewer #2 (Public review):

Summary:

This is a very elegant and important EEG study that unifies within a single set of behaviorally equated experimental conditions conscious access (and therefore also conscious access failures) during visual masking and attentional blink (AB) paradigms in humans. By a systematic and clever use of multivariate pattern classifiers across conditions, they could dissect, confirm, and extend a key distinction (initially framed within the GNWT framework) between 'subliminal' and 'pre-conscious' unconscious levels of processing. In particular, the authors could provide strong evidence to distinguish here within the same paradigm these two levels of unconscious processing that precede conscious access : (i) an early (< 80ms) bottom-up and local (in brain) stage of perceptual processing ('local contrast processing') that was preserved in both unconscious conditions, (ii) a later stage and more integrated processing (200-250ms) that was impaired by masking but preserved during AB. On the basis of preexisting studies and theoretical arguments, they suggest that this later stage could correspond to lateral and local recurrent feedback processes. Then, the late conscious access stage appeared as a P3b-like event.

Strengths:

The methodology and analyses are strong and valid. This work adds an important piece in the current scientific debate about levels of unconscious processing and specificities of conscious access in relation to feed-forward, lateral, and late brain-scale top-down recurrent processing.

Comments on revisions:

I congratulate the authors for the quality of their revised ms. They convincingly addressed each of the issues raised in my previous review.

Reviewer #3 (Public review):

Summary:

This work aims to investigate how perceptual and attentional processes affect conscious access in humans. By using multivariate decoding analysis of electroencephalography (EEG) data, the authors explored the neural temporal dynamics of visual processing across different levels of complexity (local contrast, collinearity, and illusory perception). This is achieved by comparing the decidability of an illusory percept in matched conditions of perceptual (i.e., degrading the strength of sensory input using visual masking) and attentional impairment (i.e., impairing top-down attention using attentional blink, AB). The decoding results reveal three distinct temporal responses associated with the three levels of visual processing. Interestingly, the early stage of local contrast processing remains unaffected by both masking and AB. However, the later stage of collinearity and illusory percept processing are impaired by the perceptual manipulation but remained unaffected by the attentional manipulation. These findings contribute to the understanding of the unique neural dynamics of perceptual and attentional functions and how they interact with the different stages of conscious access.

Strengths:

The study investigates perceptual and attentional impairments across multiple levels of visual processing in a single experiment. Local contrast, collinearity, and illusory perception were manipulated using different configurations of the same visual stimuli. This clever design allows for the investigation of different levels of visual processing under similar low-level conditions.

Moreover, behavioural performance was matched between perceptual and attentional manipulations. One of the main problems when comparing perceptual and attentional manipulations on conscious access is that they tend to impact performance at different levels, with perceptual manipulations like masking producing larger effects. The study utilizes a staircasing procedure to find the optimal contrast of the mask stimuli to produce a performance impairment to the illusory perception comparable to the attentional condition, both in terms of perceptual performance (i.e., indicating whether the target contained the Kanizsa illusion) and metacognition (i.e., confidence in the response).

The results show a clear dissociation between the three levels of visual processing in terms of temporal dynamics. Local contrast was represented at an early stage (~80 ms), while collinearity and illusory perception were associated with later stages (~200-250 ms). Furthermore, the results provide clear evidence in support of a dissociation between the effects of perceptual and attentional processes on conscious access: while the former affected both neuronal correlates of collinearity and illusory perception, the latter did not have any effect on the processing of the more complex visual features involved in the illusion perception.

Weaknesses:

The design of the study and the results presented are very similar to those in Fahrenfort et al. (2017), reducing its novelty. Similar to the current study, Fahrenfort et al. (2017) tested the idea that if both masking and AB impact perceptual integration, they should affect the neural markers of perceptual integration in a similar way. They found that behavioural performance (hit/false alarm rate) was affected by both masking and AB, even though only the latter was significant in the unmasked condition. In contrast, an early classification peak was exclusively affected by masking. A later classification peak mirrored the behavioural findings, with classification performance impacted by both masking and AB.

The interpretation of the results primarily relies on the recurrent processing theory of consciousness (Lamme, 2020), which lead to the assumption that local contrast and illusory perception reflect feedforward and (lateral and feedback) recurrent connections, respectively. It should be mentioned, however, that this theoretical prediction is not directly tested in the study. Moreover, the evidence for the dissociation between illusion and collinearity in terms of lateral and feedback connections seems at least limited. For instance, Kok et al. (2016) found that, whereas bottom-up stimulation activated all cortical layers, feedback activity induced by illusory figures led to a selective activation of the deep layers. Lee & Nguyen (2001), instead, found that V1 neurons respond to illusory contours of the Kanizsa figures, particularly in the superficial layers. Although both studies reference feedback connections, neither provides clear evidence for the involvement of lateral connections.

The evidence in favour of primarily lateral connections driving collinearity seems mixed as well. On one hand, Liang et al. (2017) showed that feedback and lateral connections closely interact to mediate image grouping and segmentation. On the other hand, Stettler et al. (2002) showed that, whereas the intrinsic connections link similarly oriented domains in V1, V2 to V1 feedback displays no such specificity. Additionally, the other studies cited in the manuscript focused solely on lateral connections without examining feedback pathways, making it challenging to draw definitive conclusions.

Comments on revisions:

The authors have thoroughly addressed all my comments and provided comprehensive responses to each point raised.

Author response:

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

Reviewer #1 (Public Review): 

Summary: 

In this work, Noorman and colleagues test the predictions of the "four-stage model" of consciousness by combining psychophysics and scalp EEG in humans. The study relies on an elegant experimental design to investigate the respective impact of attentional and perceptual blindness on visual processing. 

The study is very well summarised, the text is clear and the methods seem sound. Overall, a very solid piece of work. I haven't identified any major weaknesses. Below I raise a few questions of interpretation that may possibly be the subject of a revision of the text. 

We thank the reviewer for their positive assessment of our work and for their extremely helpful and constructive comments that helped to significantly improve the quality of our manuscript.

(1) The perceptual performance on Fig1D appears to show huge variation across participants, with some participants at chance levels and others with performance > 90% in the attentional blink and/or masked conditions. This seems to reveal that the procedure to match performance across participants was not very successful. Could this impact the results? The authors highlight the fact that they did not resort to postselection or exclusion of participants, but at the same time do not discuss this equally important point. 

Performance was indeed highly variable between observers, as is commonly found in attentional-blink (AB) and masking studies. For some observers, the AB pushes performance almost to chance level, whereas for others it has almost no effect. A similar effect can be seen in masking. We did our best to match accuracy over participants, while also matching accuracy within participants as well as possible, adjusting mask contrast manually during the experimental session. Naturally, those that are strongly affected by masking need not be the same participants as those that are strongly affected by the AB, given the fact that they rely on different mechanisms (which is also one of the main points of the manuscript). To answer the research question, what mattered most was that at the group-level, performance was well matched between the two key conditions. As all our statistical inferences, both for behavior and EEG decoding, rest on this group level. We do not think that variability at the individualsubject level detracts from this general approach.  

In the Results, we added that our goal was to match performance across participants:

“Importantly, mask contrast in the masked condition was adjusted using a staircasing procedure to match performance in the AB condition, ensuring comparable perceptual performance in the masked and the AB condition across participants (see Methods for more details).”

In the Methods, we added:

“Second, during the experimental session, after every 32 masked trials, mask contrast could be manually updated in accordance with our goal to match accuracy over participants, while also matching accuracy within participants as well as possible.”

(2) In the analysis on collinearity and illusion-specific processing, the authors conclude that the absence of a significant effect of training set demonstrates collinearity-only processing. I don't think that this conclusion is warranted: as the illusory and nonillusory share the same shape, so more elaborate object processing could also be occurring. Please discuss. 

We agree with this qualification of our interpretation, and included the reviewer’s account as an alternative explanation in the Discussion section:  

“It should be noted that not all neurophysiological evidence unequivocally links processing of collinearity and of the Kanizsa illusion to lateral and feedback processing, respectively (Angelucci et al., 2002; Bair et al., 2003; Chen et al., 2014), so that overlap in decoding the illusory and non-illusory triangle may reflect other mechanisms, for example feedback processes representing the triangular shapes as well.”

(3) Discussion, lines 426-429: It is stated that the results align with the notion that processes of perceptual segmentation and organization represent the mechanism of conscious experience. My interpretation of the results is that they show the contrary: for the same visibility level in the attentional blind or masking conditions, these processes can be implicated or not, which suggests a role during unconscious processing instead. 

We agree with the reviewer that the interpretation of this result depends on the definition of consciousness that one adheres to. If one takes report as the leading metric for consciousness (=conscious access), one can indeed conclude that perceptual segmentation/organization can also occur unconsciously. However, if the processing that results in the qualitative nature of an image (rather than whether it is reported) is taken as leading – such as the processing that results in the formation of an illusory percept – (=phenomenal) the conclusion can be quite different. This speaks to the still ongoing debate regarding the existence of phenomenal vs access consciousness, and the literature on no-report paradigms amongst others (see last paragraph of the discussion). Because the current data do not speak directly to this debate, we decided to remove  the sentence about “conscious experience”, and edited this part of the manuscript (also addressing a comment about preserved unconscious processing during masking by Reviewer 2) by limiting the interpretation of unconscious processing to those aspects that are uncontroversial:

“Such deep feedforward processing can be sufficient for unconscious high-level processing, as indicated by a rich literature demonstrating high-level (e.g., semantic) processing during masking (Kouider & Dehaene, 2007; Van den Bussche et al., 2009; van Gaal & Lamme, 2012). Thus, rather than enabling deep unconscious processing, preserved local recurrency during inattention may afford other processing advantages linked to its proposed role in perceptual integration (Lamme, 2020), such as integration of stimulus elements over space or time.”

(4) The two paradigms developed here could be used jointly to highlight nonidiosyncratic NCCs, i.e. EEG markers of visibility or confidence that generalise regardless of the method used. Have the authors attempted to train the classifier on one method and apply it to another (e.g. AB to masking and vice versa)? What perceptual level is assumed to transfer? 

To avoid issues with post-hoc selection of (visible vs. invisible) trials (discussed in the Introduction), we did not divide our trials into conscious and unconscious trials, and thus did not attempt to reveal NCCs, or NCCs generalizing across the two paradigms. Note also that this approach alone would not resolve the debate regarding the ‘true’ NCC as it hinges on the operational definition of consciousness one adheres to; also see our response to the previous point the reviewer raised. Our main analysis revealed that the illusory triangle could be decoded with above-chance accuracy during both masking and the AB over extended periods of time with similar topographies (Fig. 2B), so that significant cross-decoding would be expected over roughly the same extended period of time (except for the heightened 200-250 ms peak). However, as our focus was on differences between the two manipulations and because we did not use post-hoc sorting of trials, we did not add these analyses.

(5) How can the results be integrated with the attentional literature showing that attentional filters can be applied early in the processing hierarchy? 

Compared to certain manipulations of spatial attention, the AB phenomenon is generally considered to represent an instance of  “late” attentional filtering. In the Discussion section we included a paragraph on classic load theory, where early and late filtering depend on perceptual and attentional load. Just preceding this paragraph, we added this:  

“Clearly, these findings do not imply that unconscious high-level (e.g., semantic) processing can only occur during inattention, nor do they necessarily generalize to other forms of inattention. Indeed, while the AB represents a prime example of late attentional filtering, other ways of inducing inattention or distraction (e.g., by manipulating spatial attention) may filter information earlier in the processing hierarchy (e.g., Luck & Hillyard, 1994 vs. Vogel et al., 1998).”

Reviewer #2 (Public Review): 

Summary: 

This is a very elegant and important EEG study that unifies within a single set of behaviorally equated experimental conditions conscious access (and therefore also conscious access failures) during visual masking and attentional blink (AB) paradigms in humans. By a systematic and clever use of multivariate pattern classifiers across conditions, they could dissect, confirm, and extend a key distinction (initially framed within the GNWT framework) between 'subliminal' and 'pre-conscious' unconscious levels of processing. In particular, the authors could provide strong evidence to distinguish here within the same paradigm these two levels of unconscious processing that precede conscious access : (i) an early (< 80ms) bottom-up and local (in brain) stage of perceptual processing ('local contrast processing') that was preserved in both unconscious conditions, (ii) a later stage and more integrated processing (200-250ms) that was impaired by masking but preserved during AB. On the basis of preexisting studies and theoretical arguments, they suggest that this later stage could correspond to lateral and local recurrent feedback processes. Then, the late conscious access stage appeared as a P3b-like event. 

Strengths: 

The methodology and analyses are strong and valid. This work adds an important piece in the current scientific debate about levels of unconscious processing and specificities of conscious access in relation to feed-forward, lateral, and late brain-scale top-down recurrent processing. 

Weaknesses: 

- The authors could improve clarity of the rich set of decoding analyses across conditions. 

- They could also enrich their Introduction and Discussion sections by taking into account the importance of conscious influences on some unconscious cognitive processes (revision of traditional concept of 'automaticity'), that may introduce some complexity in Results interpretation 

- They should discuss the rich literature reporting high-level unconscious processing in masking paradigms (culminating in semantic processing of digits, words or even small group of words, and pictures) in the light of their proposal (deeper unconscious processing during AB than during masking). 

We thank the reviewer for their positive assessment of our study and for their insightful comments and helpful suggestions that helped to significantly strengthen our paper. We provide a more detailed point-by-point response in the “recommendations for the authors” section below. In brief, we followed the reviewer’s suggestions and revised the Results/Discussion to include references to influences on unconscious processes and expanded our discussion of unconscious effects during masking vs. AB.  

Reviewer #3 (Public Review): 

Summary: 

This work aims to investigate how perceptual and attentional processes affect conscious access in humans. By using multivariate decoding analysis of electroencephalography (EEG) data, the authors explored the neural temporal dynamics of visual processing across different levels of complexity (local contrast, collinearity, and illusory perception). This is achieved by comparing the decidability of an illusory percept in matched conditions of perceptual (i.e., degrading the strength of sensory input using visual masking) and attentional impairment (i.e., impairing topdown attention using attentional blink, AB). The decoding results reveal three distinct temporal responses associated with the three levels of visual processing. Interestingly, the early stage of local contrast processing remains unaffected by both masking and AB. However, the later stage of collinearity and illusory percept processing are impaired by the perceptual manipulation but remain unaffected by the attentional manipulation. These findings contribute to the understanding of the unique neural dynamics of perceptual and attentional functions and how they interact with the different stages of conscious access. 

Strengths: 

The study investigates perceptual and attentional impairments across multiple levels of visual processing in a single experiment. Local contrast, collinearity, and illusory perception were manipulated using different configurations of the same visual stimuli. This clever design allows for the investigation of different levels of visual processing under similar low-level conditions. 

Moreover, behavioural performance was matched between perceptual and attentional manipulations. One of the main problems when comparing perceptual and attentional manipulations on conscious access is that they tend to impact performance at different levels, with perceptual manipulations like masking producing larger effects. The study utilizes a staircasing procedure to find the optimal contrast of the mask stimuli to produce a performance impairment to the illusory perception comparable to the attentional condition, both in terms of perceptual performance (i.e., indicating whether the target contained the Kanizsa illusion) and metacognition (i.e., confidence in the response). 

The results show a clear dissociation between the three levels of visual processing in terms of temporal dynamics. Local contrast was represented at an early stage (~80 ms), while collinearity and illusory perception were associated with later stages (~200-250 ms). Furthermore, the results provide clear evidence in support of a dissociation between the effects of perceptual and attentional processes on conscious access: while the former affected both neuronal correlates of collinearity and illusory perception, the latter did not have any effect on the processing of the more complex visual features involved in the illusion perception. 

Weaknesses: 

The design of the study and the results presented are very similar to those in Fahrenfort et al. (2017), reducing its novelty. Similar to the current study, Fahrenfort et al. (2017) tested the idea that if both masking and AB impact perceptual integration, they should affect the neural markers of perceptual integration in a similar way. They found that behavioural performance (hit/false alarm rate) was affected by both masking and AB, even though only the latter was significant in the unmasked condition. An early classification peak was instead only affected by masking. However, a late classification peak showed a pattern similar to the behavioural results, with classification affected by both masking and AB. 

The interpretation of the results mainly centres on the theoretical framework of the recurrent processing theory of consciousness (Lamme, 2020), which lead to the assumption that local contrast, collinearity, and the illusory perception reflect feedforward, local recurrent, and global recurrent connections, respectively. It should be mentioned, however, that this theoretical prediction is not directly tested in the study. Moreover, the evidence for the dissociation between illusion and collinearity in terms of lateral and feedback connections seems at least limited. For instance, Kok et al. (2016) found that, whereas bottom-up stimulation activated all cortical layers, feedback activity induced by illusory figures led to a selective activation of the deep layers. Lee & Nguyen (2001), instead, found that V1 neurons respond to illusory contours of the Kanizsa figures, particularly in the superficial layers. They all mention feedback connections, but none seem to point to lateral connections. 

Moreover, the evidence in favour of primarily lateral connections driving collinearity seems mixed as well. On one hand, Liang et al. (2017) showed that feedback and lateral connections closely interact to mediate image grouping and segmentation. On the other hand, Stettler et al. (2002) showed that, whereas the intrinsic connections link similarly oriented domains in V1, V2 to V1 feedback displays no such specificity. Furthermore, the other studies mentioned in the manuscript did not investigate feedback connections but only lateral ones, making it difficult to draw any clear conclusions. 

We thank the reviewer for their careful review and positive assessment of our study, as well as for their constructive criticism and helpful suggestions. We provide a more detailed point-by-point response in the “recommendations for the authors” section below. In brief, we addressed the reviewer’s comments and suggestions by better relating our study to Fahrenfort et al.’s (2017) paper and by highlighting the limitations inherent in linking our findings to distinct neural mechanisms (in particular, to lateral vs. feedback connections).

Recommendations for the authors:  

Reviewer #1 (Recommendations For The Authors): 

-  Methods: it states that "The distance between the three Pac-Man stimuli as well as between the three aligned two-legged white circles was 2.8 degrees of visual angle". It is unclear what this distance refers to. Is it the shortest distance between the edges of the objects? 

It is indeed the shortest distance between the edges of the objects. This is now included in the Methods.

-  Methods: It's unclear to me if the mask updating procedure during the experimental session was based on detection rate or on the perceptual performance index reported on Fig1D. Please clarify. 

It was based on accuracy calculated over 32 trials. We have included this information in the Methods.

-  Methods and Results: I did not understand why the described procedure used to ensure that confidence ratings are not contaminated by differences in perceptual performance was necessary. To me, it just seems to make the "no manipulations" and "both manipulations" less comparable to the other 2 conditions. 

To calculate accurate estimates of metacognitive sensitivity for the two matched conditions, we wanted participants to make use of the full confidence scale (asking them to distribute their responses evenly over all ratings within a block). By mixing all conditions in the same block, we would have run the risk of participants anchoring their confidence ratings to the unmatched very easy and very difficult conditions (no and both manipulations condition). We made this point explicit in the Results section and in the Methods section:

“To ensure that the distribution of confidence ratings in the performancematched masked and AB condition was not influenced by participants anchoring their confidence ratings to the unmatched very easy and very difficult conditions (no and both manipulations condition, respectively), the masked and AB condition were presented in the same experimental block, while the other block type included the no and both manipulations condition.”

“To ensure that confidence ratings for these matched conditions (masked, long lag and unmasked, short lag) were not influenced by participants anchoring their confidence ratings to the very easy and very difficult unmatched conditions (no and both manipulations, respectively), one type of block only contained the matched conditions, while the other block type contained the two remaining, unmatched conditions (masked, short lag and unmasked, long lag).”

- Methods: what priors were used for Bayesian analyses? 

Bayesian statistics were calculated in JASP (JASP Team, 2024) with default prior scales (Cauchy distribution, scale 0.707). This is now added to the Methods.

- Results, line 162: It states that classifiers were applied on "raw EEG activity" but the Methods specify preprocessing steps. "Preprocessed EEG activity" seems more appropriate. 

We changed the term to “preprocessed EEG activity” in the Methods and to “(minimally) preprocessed EEG activity (see Methods)” in the  Results, respectively.

- Results, line 173: The effect of masking on local contrast decoding is reported as "marginal". If the alpha is set at 0.05, it seems that this effect is significant and should not be reported as marginal. 

We changed the wording from “marginal” to “small but significant.”  

- Fig1: The fixation cross is not displayed. 

Because adding the fixation cross would have made the figure of the trial design look crowded and less clear, we decided to exclude it from this schematic trial representation. We are now stating this also in the legend of figure 1.  

- Fig 3A: In the upper left panel, isn't there a missing significant effect of the "local contrast training and testing" condition in the first window? If not, this condition seems oddly underpowered compared to the other two conditions. 

Thanks for the catch! The highlighting in bold and the significance bar were indeed lacking for this condition in the upper left panel (blue line). We corrected the figure in our revision.

- Supplementary text and Fig S6: It is unclear to me why the two control analyses (the black lines vs. the green and purple lines) are pooled together in the same figure. They seem to test for different, non-comparable contrasts (they share neither training nor testing sets), and I find it confusing to find them on the same figure. 

We agree that this may be confusing, and deleted the results from one control analysis from the figure (black line, i.e., training on contrast, testing on illusion), as the reviewer correctly pointed out that it displayed a non-comparable analysis. Given that this control analysis did not reveal any significant decoding, we now report its results only in the Supplementary text.  

- Fig S6: I think the title of the legend should say testing on the non-illusory triangle instead of testing on the illusory triangle to match the supplementary text. 

This was a typo – thank you! Corrected.  

Reviewer #2 (Recommendations For The Authors): 

Issue #1: One key asymmetry between the three levels of T2 attributes (i.e.: local contrast; non-illusory triangle; illusory Kanisza triangle) is related to the top-down conscious posture driven by the task that was exclusively focusing on the last attribute (illusory Kanisza triangle). Therefore, any difference in EEG decoding performance across these three levels could also depend to this asymmetry. For instance, if participants were engaged to report local contrast or non-illusory triangle, one could wonder if decoding performance could differ from the one used here. This potential confound was addressed by the authors by using decoders trained in different datasets in which the main task was to report one the two other attributes. They could then test how classifiers trained on the task-related attribute behave on the main dataset. However, this part of the study is crucial but not 100% clear, and the links with the results of these control experiments are not fully explicit. Could the author better clarity this important point (see also Issue #1 and #3). 

The reviewer raises an important point, alluding to potential differences between decoded features regarding task relevance. There are two separate sets of analyses where task relevance may have been a factor, our main analyses comparing illusion to contrast decoding, and our comparison of collinearity vs. illusion-specific processing.  

In our main analysis, we are indeed reporting decoding of a task-relevant feature (illusion) and of a task-irrelevant feature (local contrast, i.e., rotation of the Pac-Man inducers). Note, however, that the Pac-Man inducers were always task-relevant, as they needed to be processed to perceive illusory triangles, so that local contrast decoding was based on task-relevant stimulus elements, even though participants did not respond to local contrast differences in the main experiment. However, we also ran control analyses testing the effect of task-relevance on local contrast decoding in our independent training data set and in another (independent) study, where local contrast was, in separate experimental blocks, task-relevant or task-irrelevant. The results are reported in the Supplementary Text and in Figure S5. In brief, task-relevance did not improve early (70–95 ms) decoding of local contrast. We are thus confident that the comparison of local contrast to illusion decoding in our main analysis was not substantially affected by differences in task relevance. In our previous manuscript version, we referred to these control analyses only in the collinearity-vs-illusion section of the Results. In our revision, we added the following in the Results section comparing illusion to contrast decoding:

“In the light of evidence showing that unconscious processing is susceptible to conscious top-down influences (Kentridge et al., 2004; Kiefer & Brendel, 2006; Naccache et al., 2002), we ran control analyses showing that early local contrast decoding was not improved by rendering contrast task-relevant (see Supplementary Information and Fig. S5), indicating that these differences between illusion and contrast decoding did not reflect differences in task-relevance.”

In addition to our main analysis, there is the concern that our comparison of collinearity vs. illusion-specific processing may have been affected by differences in task-relevance between the stimuli inducing the non-illusory triangle (the “two-legged white circles”, collinearity-only) and the stimuli inducing the Kanizsa illusion (the PacMan inducers, collinearity-plus-illusion). We would like to emphasize that in our main analysis classifiers were always used to decode T2 illusion presence vs. absence (collinearity-plus-illusion), and never to decode T2 collinearity-only. To distinguish collinearity-only from collinearity-plus-illusion processing, we only varied the training data (training classifiers on collinearity-only or collinearity-plus-illusion), using the independent training data set, where collinearity-only and collinearity-plus-illusion (and rotation) were task-relevant (in separate blocks). As discussed in the Supplementary Information, for this analysis approach to be valid, collinearity-only processing should be similar for the illusory and the non-illusory triangle, and this is what control analyses demonstrated (Fig. S7). In any case, general task-relevance was equated for the collinearity-only and the collinearity-plus-illusion classifiers.  

Finally, in supplementary Figure 6 we also show that our main results reported in Figure 2 (discussed at the top of this response) were very similar when the classifiers were trained on the independent localizer dataset in which each stimulus feature could be task-relevant.  

Together, for the reasons described above, we believe that differences in EEG decoding performance across these three stimulus levels did  are unlikely to depend also depend on a “task-relevance” asymmetry.

Issue #2: Following on my previous point the authors should better mention the concept of conscious influences on unconscious processing that led to a full revision of the notion of automaticity in cognitive science [1 , 2 , 3 , 4]. For instance, the discovery that conscious endogenous temporal and spatial attention modulate unconscious subliminal processing paved the way to this revision. This concept raises the importance of Issue#1: equating performance on the main task across AB and masking is not enough to guarantee that differences of neural processing of the unattended attributes of T2 (i.e.: task-unrelated attributes) are not, in part, due to this asymmetry rather than to a systematic difference of unconscious processing strengtsh [5 , 6-8]. Obviously, the reported differences for real-triangle decoding between AB and masking cannot be totally explained by such a factor (because this is a task-unrelated attribute for both AB and masking conditions), but still this issue should be better introduced, addressed, clarified (Issue #1 and #3) and discussed. 

We would like to refer to our response to the previous point: Control analyses for local contrast decoding showed that task relevance had no influence on our marker for feedforward processing. Most importantly, as outlined above, we did not perform real-triangle decoding – all our decoding analyses focused on comparing collinearity-only vs. collinearity-plus-illusion were run on the task-relevant T2 illusion (decoding its presence vs. absence). The key difference was solely the training set, where the collinearity-only classifier was trained on the (task-relevant) real triangle and the collinearity-plus-illusion classifier was trained on the (task-relevant) Kanizsa triangle. Thus, overall task relevance was controlled in these analyses.  

In our revision, we are now also citing the studies proposed by the reviewer, when discussing the control analyses testing for an effect of task-relevance on local contrast decoding:

“In the light of evidence showing that unconscious processing is susceptible to conscious top-down influences (Kentridge et al., 2004; Kiefer & Brendel, 2006; Naccache et al., 2002), we ran control analyses showing that early local contrast decoding was not improved by rendering contrast task-relevant (see Supplementary Information and Fig. S5), indicating that these differences between illusion and contrast decoding did not reflect differences in task-relevance.”

Issue #3: In terms of clarity, I would suggest the authors to add a synthetic figure providing an overall view of all pairs of intra and cross-conditions decoding analyses and mentioning main task for training and testing sets for each analysis (see my previous and related points). Indeed, at one point, the reader can get lost and this would not only strengthen accessibility to the detailed picture of results, but also pinpoint the limits of the work (see previous point). 

We understand the point the reviewer is raising and acknowledge that some of our analyses, in particular those using different training and testing sets, may be difficult to grasp. But given the variety of different analyses using different training and testing sets, different temporal windows, as well as different stimulus features, it was not possible to design an intuitive synthetic figure summarizing the key results. We hope that the added text in the Results and Discussion section will be sufficient to guide the reader through our set of analyses.  

In our revision, we are now more clearly highlighting that, in addition to presenting the key results in our main text that were based on training classifiers on the T1 data, “we replicated all key findings when training the classifiers on an independent training set where individual stimuli were presented in isolation (Fig. 3A, results in the Supplementary Information and Fig. S6).” For this, we added a schematic showing the procedure of the independent training set to Figure 3, more clearly pointing the reader to the use of a separate training data set.  

Issue #4: In the light of these findings the authors should discuss more thoroughly the question of unconscious high-level representations in masking versus AB: in particular, a longstanding issue relates to unconscious semantic processing of words, numbers or pictures. According to their findings, they tend to suggest that semantic processing should be more enabled in AB than in masking. However, a rich literature provided a substantial number of results (including results from the last authors Simon Van Gaal) that tend to support the notion of unconscious semantic processing in subliminal processing (see in particular: [9 , 10 , 11 , 12 , 13]). So, and as mentioned by the authors, while there is evidence for semantic processing during AB they should better discuss how they would explain unconscious semantic subliminal processing. While a possibility could be to question the unconscious attribute of several subliminal results, the same argument also holds for AB studies. Another possible track of discussion would be to differentiate AB and subliminal perception in terms of strength and durability of the corresponding unconscious representations, but not necessarily in terms of cognitive richness. Indeed, one may discuss that semantic processing of stimuli that do not need complex spatial integration (e.g.: words or digits as compared to illusory Kanisza tested here) can still be observed under subliminal conditions. 

We thank the reviewer for pointing us to this shortcoming of our previous Discussion. Note that our data does not directly speak to the question of high-level unconscious representations in masking vs AB, because such conclusions would hinge on the operational definition of consciousness one adheres to (also see response to Reviewer 1). Nevertheless, we do follow the reviewer’s suggestions and added the following in the Discussion (also addressing a point about other forms of attention raised by Reviewer 1):

“Clearly, these findings do not imply that unconscious high-level (e.g., semantic) processing can only occur during inattention, nor do they necessarily generalize to other forms of inattention. Indeed, while the AB represents a prime example of late attentional filtering, other ways of inducing inattention or distraction (e.g., by manipulating spatial attention) may filter information earlier in the processing hierarchy (e.g., Luck & Hillyard, 1994 vs. Vogel et al., 1998).”

And, in a following paragraph in the Discussion:

“Such deep feedforward processing can be sufficient for unconscious high-level processing, as indicated by a rich literature demonstrating high-level (e.g., semantic) processing during masking (Kouider & Dehaene, 2007; Van den Bussche et al., 2009; van Gaal & Lamme, 2012). Thus, rather than enabling high-level unconscious processing, preserved local recurrency during inattention may afford other processing advantages linked to its proposed role in perceptual integration (Lamme, 2020), such as integration of stimulus elements over space or time.  

Reviewer #3 (Recommendations For The Authors): 

(1) The objective of Fahrenfort et al., 2017 seems very similar to that of the current study. What are the main differences between the two studies? Moreover, Fahrenfort et al., 2017 conducted similar decoding analyses to those performed in the current study.

Which results were replicated in the current study, and which ones are novel? Highlighting these differences in the manuscript would be beneficial. 

We now provide a more comprehensive coverage of the study by Fahrenfort et al., 2017. In the Introduction, we added a brief summary of the key findings, highlighting that this study’s findings could have reflected differences in task performance rather than differences between masking and AB:

“For example, Fahrenfort and colleagues (2017) found that illusory surfaces could be decoded from electroencephalogram (EEG) data during the AB but not during masking. This was taken as evidence that local recurrent interactions, supporting perceptual integration, were preserved during inattention but fully abolished by masking. However, masking had a much stronger behavioral effect than the AB, effectively reducing task performance to chance level. Indeed, a control experiment using weaker masking, which resulted in behavioral performance well above chance similar to the main experiment’s AB condition, revealed some evidence for preserved local recurrent interactions also during masking. However, these conditions were tested in separate experiments with small samples, precluding a direct comparison of perceptual vs. attentional blindness at matched levels of behavioral performance. To test …”

In the Results , we are now also highlighting this key advancement by directly referencing the previous study:

“Thus, whereas in previous studies task performance was considerably higher during the AB than during masking (e.g., Fahrenfort et al., 2017), in the present study the masked and the AB condition were matched in both measures of conscious access.” When reporting the EEG decoding results in the Results section, we continuously cite the Fahrenfort et al. (2017) study to highlight similarities in the study’s findings. We also added a few sentences explicitly relating the key findings of the two studies:

“This suggests that the AB allowed for greater local recurrent processing than masking, replicating the key finding by Fahrenfort and colleagues (2017). Importantly, the present result demonstrates that this effect reflects the difference between the perceptual vs. attentional manipulation rather than differences in behavior, as the masked and the AB condition were matched for perceptual performance and metacognition.”

“This similarity between behavior and EEG decoding replicates the findings of Fahrenfort and colleagues  (2017) who also found a striking similarity between late Kanizsa decoding (at 406 ms) and behavioral Kanizsa detection. These results indicate that global recurrent processing at these later points in time reflected conscious access to the Kanizsa illusion.”  

We also more clearly highlighted where our study goes beyond Fahrenfort et al.’s (2017), e.g., in the Results:

“The addition of this element of collinearity to our stimuli was a key difference to the study by Fahrenfort and colleagues (2017), allowing us to compare non-illusory triangle decoding to illusory triangle decoding in order to distinguish between collinearity and illusion-specific processing.”

And in the Discussion:

“Furthermore, the addition of line segments forming a non-illusory triangle to the stimulus employed in the present study allowed us to distinguish between collinearity and illusion-specific processing.”

Also, in the Discussion, we added a paragraph “summarizing which results were replicated in the current study, and which ones are novel”, as suggested by the reviewer:

“This pattern of results is consistent with a previous study that used EEG to decode Kanizsa-like illusory surfaces during masking and the AB (Fahrenfort et al., 2017). However, the present study also revealed some effects where Fahrenfort and colleagues (2017) failed to obtain statistical significance, likely reflecting the present study’s considerably larger sample size and greater statistical power. For example, in the present study the marker for feedforward processing was weakly but significantly impaired by masking, and the marker for local recurrency was significantly impaired not only by masking but also by the AB, although to a lesser extent. Most importantly, however, we replicated the key findings that local recurrent processing was more strongly impaired by masking than by the AB, and that global recurrent processing was similarly impaired by masking and the AB and closely linked to task performance, reflecting conscious access. Crucially, having matched the key conditions behaviorally, the present finding of greater local recurrency during the AB can now unequivocally be attributed to the attentional vs. perceptual manipulation of consciousness.”

Finally, we changed the title to “Distinct neural mechanisms underlying perceptual and attentional impairments of conscious access despite equal task performance” to highlight one of the crucial differences between the Fahrenfort et al., study and this study, namely the fact that we equalized task performance between the two critical conditions (AB and masking).

(2) It is not clear from the text the link between the current study and the literature on the role of lateral and feedback connections in consciousness (Lamme, 2020). A better explanation is needed. 

To our knowledge, consciousness theories such as recurrent processing theory by Lamme make currently no distinction between the role of lateral and feedback connections for consciousness. The principled distinction lies between unconscious feedforward processing and phenomenally conscious or “preconscious” local recurrent processing, where local recurrency refers to both lateral (or horizontal) and feedback connections. We added a sentence in the Discussion:

“As current theories do not distinguish between the roles of lateral vs. feedback connections for consciousness, the present findings may enrich empirical and theoretical work on perceptual vs. attentional mechanisms of consciousness …”

(3) When training on T1 and testing on T2, EEG data showed an early peak in local contrast classification at 75-95 ms over posterior electrodes. The authors stated that this modulation was only marginally affected by masking (and not at all by AB); however, the main effect of masking is significant. Why was this effect interpreted as nonrelevant? 

Following this and Reviewer 1’s comment, we changed the wording from “marginal” to “weak but significant.” We considered this effect “weak” and of lesser relevance, because its Bayes factor indicated that the alternative hypothesis was only 1.31 times more likely than the null hypothesis of no effect, representing only “anecdotal” evidence, which is in sharp contrast to the robust effects of the consciousness manipulations on illusion decoding reported later. Furthermore, later ANOVAs comparing the effect of masking on contrast vs. illusion decoding revealed much stronger effects on illusion decoding than on contrast decoding (BFs>3.59×10⁴).

(4) The decoding analysis on the illusory percept yielded two separate peaks of decoding, one from 200 to 250 ms and another from 275 to 475 ms. The early component was localized occipitally and interpreted as local sensory processing, while the late peak was described as a marker for global recurrent processing. This latter peak was localized in the parietal cortex and associated with the P300. Can the authors show the topography of the P300 evoked response obtained from the current study as a comparison? Moreover, source reconstruction analysis would probably provide a better understanding of the cortical localization of the two peaks. 

Figure S4 now shows the P300 from electrode Pz, demonstrating a stronger positivity between 375 and 475 ms when the illusory triangle was present than when it was absent. We did not run a source reconstruction analysis.  

(5) The authors mention that the behavioural results closely resembled the pattern of the second decoding peak results. However, they did not show any evidence for this relationship. For instance, is there a correlation between the two measures across or within participants? Does this relationship differ between the illusion report and the confidence rating? 

This relationship became evident from simply eyeballing the results figures: Both in behavior and EEG decoding performance dropped from the both-manipulations condition to the AB and masked conditions, while these conditions did not differ significantly. Following a similar observation of a close similarity between behavior and the second/late illusion decoding peak in the study by Fahrenfort et al. (2017), we adopted their analysis approach and ran two additional ANOVAs, adding “measure” (behavior vs. EEG) as a factor. For this analysis, we dropped the both-manipulations condition due to scale restrictions (as noted in footnote 1: “We excluded the bothmanipulations condition from this analysis due to scale restrictions: in this condition, EEG decoding at the second peak was at chance, while behavioral performance was above chance, leaving more room for behavior to drop from the masked and AB condition.”). The analysis revealed that there were no interactions with condition:

“The pattern of behavioral results, both for perceptual performance and metacognitive sensitivity, closely resembled the second decoding peak: sensitivity in all three metrics dropped from the no-manipulations condition to the masked and AB conditions, while sensitivity did not differ significantly between these performancematched conditions (Fig. 2C). Two additional rm ANOVAs with the factors measure (behavior, second EEG decoding peak) and condition (no-manipulations, masked, AB)¹ for perceptual performance and metacognitive sensitivity revealed no significant interaction (performance: F</iv>_2,58=0.27, P\=0.762, BF₀₁=8.47; metacognition: F</iv><sub>2,58</sub=0.54, P\=0.586, BF_2,58=6.04). This similarity between behavior and EEG decoding replicates the findings of Fahrenfort and colleagues  (2017) who also found a striking similarity between late Kanizsa decoding (at 406 ms) and behavioral Kanizsa detection. These results indicate that global recurrent processing at these later points in time reflected conscious access to the Kanizsa illusion.”

eLife Assessment

This important manuscript sets out to identify sleep/arousal phenotypes in larval zebrafish carrying mutations in Alzheimer's disease (AD)-associated genes. The authors provide detailed phenotypic data for F0 knockouts of each of 7 AD-associated genes and then compare the resulting behavioral fingerprints to those obtained from a large-scale chemical screen to generate new hypotheses about underlying molecular mechanisms. The data presented are solid, although extensive interpretation of pharmacological screen data does not necessarily reflect the limited mechanistic data. Nonetheless, the authors address most reviewer concerns in their revised version, providing invaluable new analyses. Phenotypic characterization presented is comprehensive, and the authors develop a well-designed behavioral analysis pipeline that will provide considerable value for zebrafish neuroscientists.