eLife assessment

The work is interesting in its characterization of a large number of antibiotic persisters from a wild-type strain. Previous work was typically limited to directly observe either high persister strains or a smaller number of wt persisters. Therefore, it sheds new light on the elusive non-dormant persisters present in exponentially growing cultures and should help resolve previous conflicting observations.

Reviewer #1 (Public Review):

The work of Umetani et al. monitors the death of about 100,000 cells caused by lethal antibiotic treatments in a microfluidic device. They observe that the surviving bacteria are either in a dormant or in a non-dormant state prior to the antibiotic treatment. They then study the relative abundances of these different persister cells when varying the physiological state of the culture. In agreement with previous observations, they observe that late stationary phase cultures harbor a high number of dormant persister cells and that this number goes down as the culture is more exponential but remains non-zero, suggesting that cultures at the exponential phase contain different types of persister bacteria. These results were qualitatively similar in a rich and poor medium. Further characterization of the growing persister bacteria shows that they often form L-forms, have low RpoS-mcherry expression levels and grow only slightly more slowly than the non-persister bacteria. Taken together, these results draw a detailed view of persister bacteria and the way they may survive extensive antibiotic treatments. However, in order to represent a substantial advance on previous knowledge, a deeper analysis of the persister bacteria should be done.

Reviewer #2 (Public Review):

The main question asked by Umenati et al. is whether persister cells to ampicillin arise preferentially from dormant, non-dividing cells or from cells that are actively growing before antibiotic exposure. The authors tracked persister cells generated from populations at different growth phases and culture media using a microfluidic device coupled to fluorescence microscopy, which is a challenge due to the low frequency of these persister cells. One of the main conclusions is that the majority of persisters arising in exponentially-growing populations originated from actively-dividing cells before the antibiotic treatment, reinforcing the idea that dormancy is not a prerequisite for persister formation. The authors made use of a fluorescent reporter monitoring RpoS activity (RpoS-mCherry fusion) and observed that RpoS levels in these persister cells were low. In the few lineages that exhibited no growth before the ampicillin treatment, RpoS levels were low as well, indicating that RpoS is not a predictive marker for persistence. By performing the same experiment with early and late stationary phase cultures, the authors observed that the proportion of persister cells that originated from dormant cells before the ampicillin treatment is significantly increased under these conditions. In the late stationary phase condition, dormant cells were expressing high levels of RpoS. The authors suggested that RpoS-mCherry proteins form aggregates which were suggested by the authors to be a characteristic of 'deep dormancy'. These cells were mostly unable to restart growth after the antibiotic removal while others with the lowest levels of RpoS tended to be persister. Confirming that these cells indeed contain protein aggregates as well as determining the physiological state of these cells appears to be crucial.

Reviewer #3 (Public Review):

In their manuscript, Umetani, et al. address the question of the origin of persister bacteria using single-cell approaches. Persistence refers to a physiological state where bacteria are less sensitive to antibiotherapy, although they have not acquired a resistance mutation; importantly, the concept of persistence has been refined in the past decade to distinguish it from tolerance where bacteria are only transiently insensitive. Since persister cells are very rare in growing populations (typically 1e-5 or 1e-6), it is very challenging to observe them directly. It had been proposed that individual cells surviving antibiotics are not growing at the start of the treatment, but recent studies (nicely reviewed in the introduction) where persister bacteria were observed directly do not support this link. Following a similar line, the authors nonetheless still aim at "investigating whether non-growing cells are predominantly responsible for bacterial persistence". Based on new experimental data, they claim the contrary that most surviving cells were "actively growing before drug exposure" and that their work "reveals diverse survival pathways underlying antibiotic persistence".

The main strengths of the manuscript are in my opinion:

- To report on direct observation of E. coli persisters to ampicillin (200µg/mL) in 5 different growth media (typically 20 persisters or more per condition, one condition with 12 only), which constitutes without a doubt an experimental tour de force.

- To aim at bridging the population level and the single-cell level by measuring relevant variables for each and analyzing them jointly.

- To demonstrate that in most conditions a large fraction of surviving cells was actively growing before drug exposure.

In addition, although it is well-known that E. coli doesn't need to maintain its rod shape for surviving and dividing, I found very remarkable in their data the extent to which morphology can be affected in persister cells and their progeny, since this really challenges our understanding of E. coli's "lifestyle" (these swimming amoeba-like cells in Supp Video 11 are mind-blowing!).

Unfortunately, these positive aspects are counter-balanced by several shortcomings in the way experiments are analyzed and interpreted, which I explain below. Moreover, the manuscript is written in a way that makes it very hard to find important information on how experiments are done and is likely to leave the reader with an impression of confusion about what the main findings actually are.

My major concerns are the following:

(1) The main interpretation framework proposed by the authors is to assess whether cells not growing before drug exposure (so-called "dormant") are more or less likely to survive the treatment than growing ones ("non-dormant"). Fig 2A and Fig 3G show the main conclusions of the article from this perspective, that growing cells can survive the treatment and that the fraction of persisters in a given condition is not explained by the fraction of "dormant" cells, respectively. With this analysis, the authors essentially assume that "dormant" cells are of the same type in their different conditions, which ignores the progress in this field over the last decade (Balaban et al. 2019). I argue on the contrary that the observation of "diverse modes of survival in antibiotic persistence" is expected from their experimental design. In particular, the sensitivity of E. coli to beta-lactams such as ampicillin is expected to be much lower during the lag out of the stationary phase, a phenomenon which has been coined "tolerance"; hence in the Late Stationary condition, two subpopulations coexist for which different response to ampicillin is expected. I propose steps toward a more compelling interpretation of the experimental data. Should this point be taken seriously by the authors, it, unfortunately, implies a major rewriting of the article, including its title.

(2) The way the authors describe their experiments with bacteria in the stationary phase is very problematic. For instance, they write that they "sampled cells from early and late stationary phases (...) and exposed them to 200 μg/mL of Amp in both batch and single-cell cultures." For any reader in a hurry (hence skipping methods and/or supplementary figure), this leads to believe that bacteria sampled in the stationary phase were exposed to the drug right away (either by adding the drug to the stationary phase sample, or more classically by transferring cells to fresh media with antibiotics). However, it turns out that, after sampling and loading in the microfluidic device, bacteria are grown 2 h in LB (or 4 h in M9) - I don't know what to think of such a blatant omission. The names chosen for each condition should reflect their most important aspects, here "stationary" is simply not appropriate - maybe something like "post early stationary" instead. In any case, I believe that this point highlights further the misconception pointed out in 1 and implies that the average reader will be at best confused, and probably misled.

(3) Figures 4 and 5 are of very minor significance, and the methodology used in Fig 4 is questionable. The authors measure the abundance of an Rpos-mCherry translational fusion because its "high expression has been suggested to predict persistence". The rationale for this (that an RpoS-mCherry fusion would be a proxy for intracellular ppGpp levels, and in turn predict persistence) has never been firmly established, and the standards used in the article where this reporter was introduced (Maisonneuve, Castro-Camargo, and Gerdes 2013) are notoriously low (which eventually led to its retraction) - I don't know what to think of the fact that the authors cite a review by this group rather than their retracted article. While transcriptional fusions of promoters regulated by RpoS have been proposed to measure its regulatory activity (Patange et al. 2018), the combination of self-regulation and complex post-translational regulation of rpoS makes the physical meaning of the reporter used here completely unclear. Moreover, this translational fusion is introduced without doing any of the necessary controls to demonstrate that the activity of RpoS is not impaired by the addition of the fluorescent protein. Fig 5 simply reports the existence of persisters to ciprofloxacin growing before the treatment. This might be a new observation but it is not unexpected given that a similar observation has been made with a similar drug, ofloxacin (Goormaghtigh and van Melderen 2019), as pointed out in the introduction. There is no further quantitative claim on this.

(4) The authors don't mention the dead volume nor the speed of media exchange in their device. Hopefully, it is short compared to the duration of the treatment; however, it is challenging to remove all antibiotics after the treatment and only 1e-3 or 1e-4 of the treatment concentration is already susceptible to affecting regrowth in fresh media. If this is described in another article, it would be worth adding a comment in the main text.

(5) Fig 2A supports the main finding that a significant fraction of bacteria surviving the treatment are growing before drug exposure, but it uses a poorly chosen representation.<br /> - In order to compare between conditions, one would like to see the fraction of each type in the population.<br /> - The current representation (of a fraction of each type among surviving cells) requires a side-by-side comparison with a random sample (which will practically be equivalent to the fraction of each type among killed cells) in order to be informative.

Author response:

Reviewer #1 (Public Review):

The work of Umetani et al. monitors the death of about 100,000 cells caused by lethal antibiotic treatments in a microfluidic device. They observe that the surviving bacteria are either in a dormant or in a non-dormant state prior to the antibiotic treatment. They then study the relative abundances of these different persister cells when varying the physiological state of the culture. In agreement with previous observations, they observe that late stationary phase cultures harbor a high number of dormant persister cells and that this number goes down as the culture is more exponential but remains non-zero, suggesting that cultures at the exponential phase contain different types of persister bacteria. These results were qualitatively similar in a rich and poor medium. Further characterization of the growing persister bacteria shows that they often form Lforms, have low RpoS-mcherry expression levels and grow only slightly more slowly than the non-persister bacteria. Taken together, these results draw a detailed view of persister bacteria and the way they may survive extensive antibiotic treatments. However, in order to represent a substantial advance on previous knowledge, a deeper analysis of the persister bacteria should be done.

We thank the reviewer for suggesting the addition of more detailed analyses of persister cells. As we wrote in our response to Essential Revision 1, we now include a new section titled “Response of growing persisters to Amp exposure is heterogeneous” (Page 11-12) and present the results of the detailed analyses of single-cell dynamics of growth and cell morphology over the course of the pre-exposure, exposure, and post-exposure periods (Fig. 2D and H, Fig. 4B and D, Fig. 4 – figure supplement 1 and 2, Fig. 5B and D, Fig. 5 – figure supplement 1, Fig. 8B and D, and Figure 8 – figure supplement 1). The new results characterize differential responses to Amp treatment among growing persister cells (Fig. 4A-D, Fig. 4 – figure supplement 1, Fig. 4 – figure supplement 2A, Fig. 5A-D, and Fig. 5 – figure supplement 1), comparable division rates of MG1655 between non-surviving cells and persister cells growing prior to antibiotic treatments (Fig. 4E and Fig. 8E), except for the post-exponential phase cell populations of MF1 to Amp treatment in the LB medium and the post-exponential phase cell populations of MG1655 to Amp treatment in the M9 medium (Fig. 4 – figure supplement 2B and Fig. 5E) and the presence of persister cells to CPFX that avoid filamentation after the treatment (Fig. 8C and D, and Fig. 8 – figure supplement 1). We believe that these new analyses would provide new insights into the diverse dynamics and survival modes of antibiotic persistence at the single-cell level and represent important contributions to the field.

Reviewer #2 (Public Review):

The main question asked by Umenati et al. is whether persister cells to ampicillin arise preferentially from dormant, non-dividing cells or from cells that are actively growing before antibiotic exposure. The authors tracked persister cells generated from populations at different growth phases and culture media using a microfluidic device coupled to fluorescence microscopy, which is a challenge due to the low frequency of these persister cells. One of the main conclusions is that the majority of persisters arising in exponentially-growing populations originated from actively-dividing cells before the antibiotic treatment, reinforcing the idea that dormancy is not a prerequisite for persister formation. The authors made use of a fluorescent reporter monitoring RpoS activity (RpoS-mCherry fusion) and observed that RpoS levels in these persister cells were low. In the few lineages that exhibited no growth before the ampicillin treatment, RpoS levels were low as well, indicating that RpoS is not a predictive marker for persistence. By performing the same experiment with early and late stationary phase cultures, the authors observed that the proportion of persister cells that originated from dormant cells before the ampicillin treatment is significantly increased under these conditions. In the late stationary phase condition, dormant cells were expressing high levels of RpoS. The authors suggested that RpoS-mCherry proteins form aggregates which were suggested by the authors to be a characteristic of 'deep dormancy'. These cells were mostly unable to restart growth after the antibiotic removal while others with the lowest levels of RpoS tended to be persister. Confirming that these cells indeed contain protein aggregates as well as determining the physiological state of these cells appears to be crucial.

We thank reviewer #2 for pointing out the critical issue with the RpoS-mCherry fusion that we used to quantify RpoS expression levels in single cells in the original manuscript. As explained in our reply to the comments below, we performed a suggested experiment and confirmed that the RpoS function was impaired by tagging it with mCherry. To resolve this issue, we repeated almost all the experiments using the wild-type strain MG1655 and confirmed the reproducibility of the main results (Fig. 3, Fig. 3 – figure supplement 1, and Fig. 7). Due to this change of the main strain used in this study, we removed the results on the correlation between RpoS expression and the persistence trait in the revised manuscript because it may not reflect the relationship of intact RpoS. However, we decided to still keep and show some of the results with the MF1 strain, such as the population killing curves and the survival mode analyses, because they also provide insight into the role of RpoS in antibiotic persistence. In particular, we found both beneficial and detrimental effects of RpoS on antibiotic persistence, depending on culture conditions and duration of antibiotic treatment (Fig. 1 – figure supplement 3 and Fig. 6 – figure supplement 1). Therefore, we have included these results and related discussions in the revised manuscript.

Reviewer #3 (Public Review):

In their manuscript, Umetani, et al. address the question of the origin of persister bacteria using single-cell approaches. Persistence refers to a physiological state where bacteria are less sensitive to antibiotherapy, although they have not acquired a resistance mutation; importantly, the concept of persistence has been refined in the past decade to distinguish it from tolerance where bacteria are only transiently insensitive. Since persister cells are very rare in growing populations (typically 1e-5 or 1e-6), it is very challenging to observe them directly. It had been proposed that individual cells surviving antibiotics are not growing at the start of the treatment, but recent studies (nicely reviewed in the introduction) where persister bacteria were observed directly do not support this link. Following a similar line, the authors nonetheless still aim at "investigating whether non-growing cells are predominantly responsible for bacterial persistence". Based on new experimental data, they claim the contrary that most surviving cells were "actively growing before drug exposure" and that their work "reveals diverse survival pathways underlying antibiotic persistence".

We thank the reviewer for this helpful comment, which suggested to us that some revisions in our Introduction would better place our study in the context of previous understanding of antibiotic persistence. As mentioned in our response to Essential Revision 4 and the second comment of Reviewer 1's Recommendations for the authors, we have modified the Introduction to more appropriately place our study in the context of the field.

The main strengths of the manuscript are in my opinion:

- To report on direct observation of E. coli persisters to ampicillin (200µg/mL) in 5 different growth media (typically 20 persisters or more per condition, one condition with 12 only), which constitutes without a doubt an experimental tour de force.

- To aim at bridging the population level and the single-cell level by measuring relevant variables for each and analyzing them jointly.

- To demonstrate that in most conditions a large fraction of surviving cells was actively growing before drug exposure.

In addition, although it is well-known that E. coli doesn't need to maintain its rod shape for surviving and dividing, I found very remarkable in their data the extent to which morphology can be affected in persister cells and their progeny, since this really challenges our understanding of E. coli's "lifestyle" (these swimming amoeba-like cells in Supp Video 11 are mind-blowing!).

We are grateful to the reviewer for the articulation of the strength of this study. 

Unfortunately, these positive aspects are counter-balanced by several shortcomings in the way experiments are analyzed and interpreted, which I explain below. Moreover, the manuscript is written in a way that makes it very hard to find important information on how experiments are done and is likely to leave the reader with an impression of confusion about what the main findings actually are.

We thank the reviewer for pointing out these important issues regarding the original manuscript. Please see our replies below regarding how we corresponded to each specific comment to resolve the issue. To make the experimental methods and procedures more accessible and interpretable, we have added more explanations of the experimental details to the Results and Methods sections. Furthermore, since we understood that some of the confusions came from the insufficient explanation of the preculture procedures for the microfluidic experiments, we have modified the schematic illustration of the method shown in Fig. S1 in the original manuscript and moved it as the first main figure in the revised manuscript (Fig. 1C and D). We have also added an illustration that explains the cultivation procedures for the batch culture experiments as Fig.

6A. 

My major concerns are the following:

(1) The main interpretation framework proposed by the authors is to assess whether cells not growing before drug exposure (so-called "dormant") are more or less likely to survive the treatment than growing ones ("non-dormant"). Fig 2A and Fig 3G show the main conclusions of the article from this perspective, that growing cells can survive the treatment and that the fraction of persisters in a given condition is not explained by the fraction of "dormant" cells, respectively. With this analysis, the authors essentially assume that "dormant" cells are of the same type in their different conditions, which ignores the progress in this field over the last decade (Balaban et al. 2019). I argue on the contrary that the observation of "diverse modes of survival in antibiotic persistence" is expected from their experimental design. In particular, the sensitivity of E. coli to beta-lactams such as ampicillin is expected to be much lower during the lag out of the stationary phase, a phenomenon which has been coined "tolerance"; hence in the Late Stationary condition, two subpopulations coexist for which different response to ampicillin is expected. I propose steps toward a more compelling interpretation of the experimental data. Should this point be taken seriously by the authors, it, unfortunately, implies a major rewriting of the article, including its title.

We thank the reviewer for bringing to our attention the point that may have caused confusion in the original manuscript. 

The primary purpose of this manuscript was not to assess whether non-growing cells prior to drug exposure are more or less likely to survive treatment than growing cells. Rather, we wanted to examine how different persister cell dynamics emerge at the single-cell level depending on previous cultivation history, growth media, and antibiotic types. We believe that this point is clearer in the revised manuscript with the newly added single-cell dynamics data (Fig. 2D, 2H, 4B, 4D, Fig. 4 – figure supplement 1 and 2A, Fig. 5B, 5D, Fig. 5 – figure supplement 1, Fig. 8B, 8D, and Fig. 8 – figure supplement 1). 

We also did not mean to imply that "dormant cells" were of the same type under different conditions, as we were aware of the diversity of cellular states of non-growing cells, as well as the reduced sensitivity of cells to antibiotics during the lag out of stationary phase. We believe that one of the reasons this point may have been unclear is that in the previous version we had referred to all cells that were not growing prior to antibiotic treatment as "dormant cells", a term that is often used in a more restricted way to refer to cells under prolonged growth arrest. Therefore, in the revised manuscript, we have avoided the term "dormant cells" and instead simply referred to these as "non-growing cells". Accordingly, we have changed the title of the paper from "Observation of non-dormant persister cells reveals diverse modes of survival in antibiotic persistence" to "Observation of persister cell histories reveals diverse modes of survival in antibiotic persistence".

To further address these points, we have improved the description of the experimental procedures for the single-cell measurements (see the reviewer's next comment as well). The nongrowing persisters of the MF1 strain found in the post-exponential phase cell populations must be of a different type than those found in the post-early and post-late stationary phase cell populations due to the experimental design. All early and late stationary phase cells were maintained in a non-growing state by flowing conditioned media prepared from the early and late stationary phase cultures until the start of the time-lapse measurements. Thus, aside from potential physiological heterogeneity, the non-growing cells prior to drug treatment are all long lagging cells. On the other hand, for the post-exponential phase condition, we maintained exponential growth conditions during the period from the start of the second pre-culture to the start of antibiotic treatment, including the period during sample preparation for time-lapse measurements. Given the exponential dilution by growth of cell populations, the non-growing persisters are unlikely to be long lagging cells (see our response to Reviewer 2's third comment  in "Recommendations for the authors"). We now describe these experimental procedures in more detail in the Results section (L161-178, L287-297). In addition, we discuss the diversity of cellular states of both non-growing and growing cells in Discussion, citing literature (L545-557).

(2) The way the authors describe their experiments with bacteria in the stationary phase is very problematic. For instance, they write that they "sampled cells from early and late stationary phases (...) and exposed them to 200 μg/mL of Amp in both batch and single-cell cultures." For any reader in a hurry (hence skipping methods and/or supplementary figure), this leads to believe that bacteria sampled in the stationary phase were exposed to the drug right away (either by adding the drug to the stationary phase sample, or more classically by transferring cells to fresh media with antibiotics). However, it turns out that, after sampling and loading in the microfluidic device, bacteria are grown 2 h in LB (or 4 h in M9) - I don't know what to think of such a blatant omission. The names chosen for each condition should reflect their most important aspects, here "stationary" is simply not appropriate - maybe something like "post early stationary" instead. In any case, I believe that this point highlights further the misconception pointed out in 1 and implies that the average reader will be at best confused, and probably misled.

We again thank the reviewer for pointing out the insufficient explanation of the method for the single-cell measurements and the helpful recommendation regarding our nomenclature for different conditions. As mentioned above, we now present the previous supplementary figure that schematically explains the experimental procedure as the first main figure to clarify how we prepared the cells loaded into the microfluidic device for single-cell measurements (Fig. 1C and D). Also, following the reviewer's suggestion, we now refer to the conditions as "post-exponential phase," "post-early stationary phase," and "post-late stationary phase" in the revised manuscript. 

We included a 2-hour (or 4-hour in M9) cultivation period in fresh medium in batch cultures for measuring killing curves to make the cultivation conditions prior to antibiotic treatment as similar as possible between batch and microfluidic experiments. We have clarified the presence of preexposure cultivation of post-early stationary and post-late stationary phase cell populations in the fresh medium before treating them with antibiotics (L264-269, Fig. 6A), so that readers can more easily recognize the experimental conditions.

(3) Figures 4 and 5 are of very minor significance, and the methodology used in Fig 4 is questionable. The authors measure the abundance of an Rpos-mCherry translational fusion because its "high expression has been suggested to predict persistence". The rationale for this (that an RpoS-mCherry fusion would be a proxy for intracellular ppGpp levels, and in turn predict persistence) has never been firmly established, and the standards used in the article where this reporter was introduced (Maisonneuve, Castro-Camargo, and Gerdes 2013) are notoriously low (which eventually led to its retraction) - I don't know what to think of the fact that the authors cite a review by this group rather than their retracted article. While transcriptional fusions of promoters regulated by RpoS have been proposed to measure its regulatory activity (Patange et al. 2018), the combination of self-regulation and complex post-translational regulation of rpoS makes the physical meaning of the reporter used here completely unclear. Moreover, this translational fusion is introduced without doing any of the necessary controls to demonstrate that the activity of RpoS is not impaired by the addition of the fluorescent protein. Fig 5 simply reports the existence of persisters to ciprofloxacin growing before the treatment. This might be a new observation but it is not unexpected given that a similar observation has been made with a similar drug, ofloxacin (Goormaghtigh and van Melderen 2019), as pointed out in the introduction. There is no further quantitative claim on this.

We thank the reviewer for pointing out the issue of the RpoS-mCherry fusion. As we mentioned in our response to Essential Revision 2 and also to the comment from reviewer #2, we have tested the sensitivity of this fluorescent reporter strain to oxidative stress and confirmed that it is as sensitive as the rpoS strain (Fig. 1 – figure supplement 1C). Therefore, the RpoS function seems to be defective in this strain, as now explained in Results (L69-79). After confirming the problem with the RpoS-mCherry fusion, we removed all analyses and related arguments that relied on the RpoS expression level (previous Figure 4). In addition, we repeated almost all the experiments with the original MG1655 strain to confirm that the observed results are not specific to the problematic reporter strain. 

Regarding the experiments with CPFX, we have added a more detailed analysis of single cell dynamics and found that, contrary to the reported results for ofloxacin, not all persistent cells show filamentation after drug withdrawal (Fig. 8C and D, Fig. 8 – figure supplement 1). In addition, we performed new microfluidic experiments in which we treated post-late stationary phase cells with CPFX (Fig. 3). In contrast to the Amp treatment result and the previous study that reported the persistence of post-stationary phase cell populations to ofloxacin (ref. 20), all the persisters for which we identified the pre-exposure growth traits in this condition grew normally prior to CPFX treatment. These newly added analyses and experiments clarify the significance of the CPFX experiments. 

(4) The authors don't mention the dead volume nor the speed of media exchange in their device. Hopefully, it is short compared to the duration of the treatment; however, it is challenging to remove all antibiotics after the treatment and only 1e-3 or 1e-4 of the treatment concentration is already susceptible to affecting regrowth in fresh media. If this is described in another article, it would be worth adding a comment in the main text.

We thank the reviewer for bringing up this important point. We have added the perfusion chamber volume and medium flow rate information in the Methods section (L809-817).   

In the study in which two of the authors participated, the medium exchange rate across the semipermeable membrane was evaluated in a similar device with similar microchamber dimensions (ref. 26). There, we confirmed that the medium exchange was completed within 5 min, which is much shorter than the period of antibiotic treatment and post-antibiotic treatment periods for observing regrowth. We have also included this information in the main text with the reference (L58-63).

Despite the relatively high medium exchange rate, we cannot formally exclude the possibility that a small amount of antibiotic may remain in the device, e.g. due to non-specific adsorption on the internal surface of the microchambers. In such cases, the residual antibiotics may influence the physiological states of the cells and the regrowth kinetics in the post-exposure periods, as suggested by the reviewer. However, the frequencies of persister cells in the cell populations in our single-cell measurements are comparable to those in the batch culture measurements. Therefore, the removal of antibiotic drugs in our device is at least as efficient as in the batch culture assay. To clarify this point, we have added a paragraph to the Discussion with a reference that reviews the influence of antibiotics at concentrations significantly lower than the MICs (L482-

489).    

(5) Fig 2A supports the main finding that a significant fraction of bacteria surviving the treatment are growing before drug exposure, but it uses a poorly chosen representation.

- In order to compare between conditions, one would like to see the fraction of each type in the population.

- The current representation (of a fraction of each type among surviving cells) requires a side-byside comparison with a random sample (which will practically be equivalent to the fraction of each type among killed cells) in order to be informative.

We have changed the style of the previous Fig. 2A to show the fraction of each type in the population instead of the fraction of each type among surviving cells (Fig. 3 and Fig. 3-figure supplement 1).

eLife Assessment

This important study compares the cortical projections to primary motor and sensory areas originating from the ipsilateral and contralateral hemispheres. Results show that, while there is substantial symmetry between the two hemispheres regarding the areas sending projections to these primary cortical areas, contra-hemispheric projections had more inputs from layer 6 neurons than ipsi-projecting ones. The evidence is compelling and the conclusions are supported by rigorous analyses.

Reviewer #1 (Public review):

Weiler, Teichert, and Margrie systematically analyzed long-range cortical connectivity, using a retrograde viral tracing strategy to identify layer and region-specific cortical projections onto the primary visual, primary somatosensory, and primary motor cortices. Their analysis revealed several hundred thousand inputs into each region, with inputs originating from almost all cortical regions but dominated in number by connections within cortical sub-networks (e.g. anatomical modules). Generally, the relative areal distribution of contralateral inputs followed the distribution of corresponding ipsilateral inputs. The largest proportion of inputs originated from layer 6a cells, and this layer 6 dominance was more pronounced for contralateral than ipsilateral inputs, which suggests that these connections provide predominantly feedback inputs. The hierarchical organization of input regions was similar between ipsi- and contralateral regions, except for within-module connections, where ipsilateral connections were much more feed-forward than contralateral. These results contrast earlier studies which suggested that contralateral inputs only come from the same region (e.g. V1 to V1) and from L2/3 neurons. The conclusions of this paper are well-supported by the data and analysis, and useful follow-up analyses and discussions are present in the supplemental figures. Taken together, these results provide valuable data supporting a view of interhemispheric connectivity in which layer 6 neurons play an important role in providing modulatory feedback.

Reviewer #2 (Public review):

Summary:

Weiler et al use retrograde tracers, two-photon tomography, and automatic cell detection to provide a detailed quantitative description of the laminar and area sources of ipsi- and contralateral cortico-cortical inputs to two primary sensory areas and a primary motor area. They found considerable bilateral symmetry in the areas providing cortico-cortical inputs. However, although the same regions in both hemispheres tended to supply inputs, a larger proportion of inputs from contralateral areas originated from deeper layers (L5 and L6).

Strengths:

The study applies state-of-the-art anatomical methods, and the data is very effectively presented and carefully analyzed. The results provide many novel insights on the similarities and differences of inputs from the two hemispheres. While over the past decade there has been many studies quantitively and comprehensively describing cortico-cortical connections, by directly comparing inputs from the ipsi and contralateral hemispheres, this study fills in an important gap in the field. It should be of great utility and an important reference for future studies on inter hemispheric interactions.

Weaknesses:

Overall, I do not find any major weakness in the analyses or their interpretation. However, one must keep in mind that the study only analyses inputs projecting to three areas. This is not an inherent flaw of the study; however, it warrants caution when extrapolating the results to callosal projections terminating in other areas. As inputs to two primary sensory areas and one is the primary motor cortex are studied, some of the conclusions could potentially be different for inputs terminating in high-order sensory and motor areas. Given that primary areas were injected, there are few instances of feedforward connections sampled in the ipsilateral hemisphere. The study finds that while ipsi- projections from visual cortex to barrel cortex are feedforward given its fILN values, those from the contralateral visual cortex are feedback instead. This is now acknowledged in the revised discussion.

Another issue that is left unexplored is that, in the current analyses the barrel and primary visual cortex are analyzed as a uniform structure. It is well established that both the laminar sources of callosal inputs and their terminations differ in the monocular and binocular areas of the visual cortex (border with V2L). Similarly, callosal projections differ when terminating the border of S1 (A row of whiskers ) then in other parts of S1. Thus, some of the conclusions regarding the laminar sources of callosal inputs might depend on whether one is analyzing inputs terminating or originating in these border regions. This is now acknowledged in the revised version.

Author response:

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

Reviewer #1 (Public review):

Weiler, Teichert, and Margrie systematically analyzed long-range cortical connectivity, using a retrograde viral tracing strategy to identify layer and region-specific cortical projections onto the primary visual, primary somatosensory, and primary motor cortices. Their analysis revealed several hundred thousand inputs into each region, with inputs originating from almost all cortical regions but dominated in number by connections within cortical sub-networks (e.g. anatomical modules). Generally, the relative areal distribution of contralateral inputs followed the distribution of corresponding ipsilateral inputs. The largest proportion of inputs originated from layer 6a cells, and this layer 6 dominance was more pronounced for contralateral than ipsilateral inputs, which suggests that these connections provide predominantly feedback inputs. The hierarchical organization of input regions was similar between ipsi- and contralateral regions, except for within-module connections, where ipsilateral connections were much more feed-forward than contralateral. These results contrast earlier studies which suggested that contralateral inputs only come from the same region (e.g. V1 to V1) and from L2/3 neurons. Thus, these results provide valuable data supporting a view of interhemispheric connectivity in which layer 6 neurons play an important role in providing modulatory feedback.

The conclusions of this paper are mostly well-supported by the data and analysis, but additional consideration of possible experimental biases is needed.

We thank the reviewer for their positive feedback on our manuscript.

Further discussion or analysis is needed about possible biases in uptake efficiency for different cell types. Is it possible that the nuclear retro-AAV has a tropism for layer 6 axons? Quantitative comparisons with results obtained with alternative methods such as rabies virus (Yao et al., 2023) or anterograde tracing (Harris et al., 2019) may be helpful for this.

We appreciate this technical comment. For the reasons indicated below we are confident that our AAV approach successfully and rather comprehensively labels inputs to the three target areas. Firstly, in the brains in which we injected our retrograde nuclear-AAV tracer into VISp, SSp-bfd or MOp we found several instances where layer 5 and/or layer 2/3 as was the dominant cortical projection layer (please see e.g. Figure 3 heatmaps). This was true for both ipsilateral and contralateral projection. 

Secondly, by way of comparison Yao et al., 2023 injected rabies virus into VISp (but not in SSp-bfd or MOp) and their results show notable similarities to ours: 1) They show that contralateral inputs to VISp (and higher visual areas) were mainly located in Layers 5 and 6. 2) Retrogradely labelled neurons in higher visual areas revealed anatomical hierarchy that reflects the known functional hierarchy of the mouse cortical visual system and that shown by our retro-AAV approach. Thus, as AAV and rabies based tracing lead to similar results, this is further evidence against bias via tropism of our AAV tracer. That said, direct comparisons of the results between our study and the Yao et al., 2023 study should be viewed with some caution since Yao et. al.  injected rabies virus into specific Cre-driver lines in which the rabies virus targets individual genetically defined cell types in specific layers. Importantly, because of the lack of a specific cre-driver line, L6 cortico-cortical (L6 CC) cells could not be targeted by their approach. Thus, the dataset in Yao et al., overlook the contribution of L6 CCs due to the lack of available Cre-lines. 

Thirdly, in a recent study (Weiler et al., 2024) we found that in a specific pathway (SSp-bfd→ VISp) both retro-AAV and the more traditional non-viral tracer cholera toxin subunit B (CTB) identified neurons in Layer 6 as the main source of projection neurons. The same results for the same pathway was shown by Bieler et al., 2019 (Bieler et al., 2017) using Fluorogold for retrograde tracing. Thus, the described dominance of Layer 6 projection neurons in specific pathways is likely not the result of a tropism of retro-AAV tracers. 

Please also see that we have now further extended the summary of these points in our revised manuscript in the discussion section (e.g. lines 457-463): 

Quantitative analysis of the injection sites should be included to account for possible biases. For example, L6 neurons are known to be the main target of contralateral inputs into the visual cortex (Yao et al., 2023). Thus, if the injections are biased towards or against layer 6 neurons, this may change the layer distribution of retrogradely labeled input cells. Comparison across biological replicates may help reveal sensitivity to particular characteristics of the injections.

In response to the reviewers' feedback, please see we have now quantified the injection volume per cortical layer, as shown in the revised Fig. S3D. Our results indicate that the injections were not biased toward Layer 6. Instead, the injected tracer volumes in Layers 1, 4, 5, and 6 were similar across all animals and injected areas. However, we observed that the injected tracer volume in Layer 2/3 tended to be higher than in other layers. Although the tracer volumes in Layers 2/3 appeared to be higher, the proportion of input neurons located in Layers 2/3 for most of the cortical projection areas was consistently lower than that from Layer 6. These findings provide strong evidence against injection bias towards L6 inputs.

The possibility of labelling axons of passage within the white matter should be addressed. This could potentially lead to false positive connections, contributing to the broad connectivity from most cortical regions that were observed.

For clarification, please see Fig.S2B in our revised manuscript. In this panel we plot the average percentage volume of the viral boli in the target areas and in all other nearby structures including the white matter. The percentage of virus injected into the white matter (WM) was 0.0824 ± 0.0759% for VISp and 0.0650 ± 0.0481 for SSp-bfd injections. Notably, injections into MOp showed no leakage into white matter (0%). These minimal volumes of virus in the white matter are unlikely to significantly influence the observed profile of widespread connectivity. Please see we have added a sentence to the Results section (lines 84-86) where we state that we only used brains that had a transduction of the white matter below 0.1%.

Reviewer #2 (Public review):

Summary:

Weiler et al use retrograde tracers, two-photon tomography, and automatic cell detection to provide a detailed quantitative description of the laminar and area sources of ipsi- and contralateral cortico-cortical inputs to two primary sensory areas and a primary motor area. They found considerable bilateral symmetry in the areas providing cortico-cortical inputs. However, although the same regions in both hemispheres tended to supply inputs, a larger proportion of inputs from contralateral areas originated from deeper layers (L5 and L6).

Strengths:

The study applies state-of-the-art anatomical methods, and the data is very effectively presented and carefully analyzed. The results provide many novel insights into the similarities and differences of inputs from the two hemispheres. While over the past decade there have been many studies quantitatively and comprehensively describing cortico-cortical connections, by directly comparing inputs from the ipsi and contralateral hemispheres, this study fills in an important gap in the field. It should be of great utility and an important reference for future studies on inter-hemispheric interactions.

We thank the reviewer for this encouraging feedback on our manuscript.

Weaknesses:

Overall, I do not find any major weakness in the analyses or their interpretation. However, one must keep in mind that the study only analyses inputs projecting to three areas. This is not an inherent flaw of the study; however, it warrants caution when extrapolating the results to callosal projections terminating in other areas. As inputs to two primary sensory areas and one is the primary motor cortex are studied, some of the conclusions could potentially be different for inputs terminating in high-order sensory and motor areas. Given that primary areas were injected, there are few instances of feedforward connections sampled in the ipsilateral hemisphere. The study finds that while ipsi-projections from the visual cortex to the barrel cortex are feedforward given its fILN values, those from the contralateral visual cortex are feedback instead. One is left to wonder whether this is due to the cross-modal nature of these particular inputs and whether the same rule (that contralateral inputs consistently exhibit feedback characteristics regardless of the hierarchical relationship of their ipsilateral counterparts with the target area,) would also apply to feedforward inputs within the same sensory cortices.

We acknowledge that what we find for primary sensory and motor target areas may not hold for other functionally different areas such as anterior cingulate cortex, retrosplenial cortex or frontal lobe that might be expected to receive strong feedforward cortical input. To begin to understand the organization of the global cortical input we have however first explored with primary sensory and motor areas. Please see that we have now added a sentence to the Discussion section of our manuscript that highlights the importance of investigating the hierarchical organization of intra and interhemispheric input onto higher cortical areas or within subregions of a given sensory area.

Another issue that is left unexplored is that, in the current analyses the barrel and primary visual cortex are analyzed as a uniform structure. It is well established that both the laminar sources of callosal inputs and their terminations differ in the monocular and binocular areas of the visual cortex (border with V2L). Similarly, callosal projections differ when terminating the border of S1 (a row of whiskers), and then in other parts of S1. Thus, some of the conclusions regarding the laminar sources of callosal inputs might depend on whether one is analyzing inputs terminating or originating in these border regions.

The aim of the present study was to analyse the global projectome to the VISp, SSp-bfd and MOp, irrespective of which subregions were included. Importantly, we purposely injected rather large bolus volumes to achieve large sample sizes of target neurons in each cortical layer.  For SSp-bfd, we utilised our previously reconstructed barrel map (Weiler et al., 2024) to precisely map our viral injection sites onto the barrels (Author response image 1). Analysis revealed that the six injection sites consistently encompassed 7–13 barrels (Author response image 1, three exemplary injection sites). Additionally, we determined the centres of mass for each injection site and mapped them onto the barrel map. Four of the injection sites were located in the lateral part of SSp-bfd, two in the central region, and none in the medial part. Notably, the injection sites within SSp-bfd exhibited significant overlap. As a result, a selective analysis of callosal projections targeting these injection sites would likely not yield distinct projection patterns, as the projectomes would inevitably include projections to surrounding barrels, leading to contamination.

Author response image 1.

Left: exemplary Injection sites mapped onto the 3D barrel map of SSp-bfd within the Mouse Allen Brain Atlas. Barrels were reconstructed using a specialized software as described previously (Weiler et al., 2024) Right: Centres of mass of all SSp-bfd injection sites mapped onto the 3D barrel map.

Due to the fact we covered a significant proportion of the respective target primary sensory area any further subdivision of these data is not possible and requires more tailored injections into clearly defined subareas. Investigating the separate projectomes onto these subregions (e.g. onto V1M and V1B) remains an important interesting research question that we, at least in part, will address in a future study.

Finally, while the paper emphasizes that projections from L6 "dominate" intra and contralateral cortico-cortical inputs, the data shows a more nuanced scenario. While it is true that the areas for which L6 neurons are the most common source of cortico-cortical projections are the most abundant, the picture becomes less clear when considering the number of neurons sending these connections. In fact, inputs from L2/3 and L5 combined are more abundant than those from L6 (Figure 3B), challenging the view that projections from L6 dominate ipsi- and contralateral projecting cortico-cortical inputs.

We agree in the case of the barrel cortex, layer 5 significantly contributes in terms of the number of brain areas projecting from within the ipsilateral and contralateral hemispheres. Please see we have replaced the term “dominates” in the title, abstract and in the manuscript where relevant.

Recommendations for the authors:  

Reviewer #1 (Recommendations for the authors):

The sections analyzing the role of L6 towards feedback (pg. 11-13, Figure 6) were a bit verbose and confusing to me. Three possible models are proposed:

(1) a decrease in L23 projections, (2) an increase in L56 projections, or (3) both.

However, what is being quantified appears to be the fractions inputs, with L23. L5, and L6 summing to 1. Thus, a decrease in L23 would necessarily result in an increase in L56 projections. It seems like it would make more sense to quantify the percent change in the total number of inputs (rather than fractional) from each layer so that the 3 models are actually independent possibilities.

The issue with the suggested analysis is that, with one exception (one area projecting to MOp), the number of projection neurons in contralateral areas is always ~60-80% lower compared to their ipsilateral counterparts. Consequently, this is also true for the number of projection neurons in the different cortical layers. Thus, quantifying the percentage change from the ipsilateral to the contralateral hemisphere in the total number of inputs from each layer will always result in negative values. 

Nevertheless, we addressed the reviewer’s issue by calculating the preservation index (1(ipsi-contra)/(ipsi+contra)) for the sensory-motor areas independently for the absolute number of neurons within L2/3, 5 and 6 for the cortical areas projecting to VISp, SSp-bfd and MOp (see Author response image 2). When analysing the shift from the ipsilateral to the contralateral hemisphere, we observed that significantly more projection neurons were preserved in L6 compared to L2/3 for VISp and SSp-bfd. This shows that the number of L6 projection neurons declines less from the ipsilateral to the contralateral hemisphere compared to L2/3. However, our focus was on the fraction of projection neurons within each layer relative to the other layers per hemisphere (see Fig.6 of our manuscript). This measure is critical for distinguishing between feedforward and feedback connectivity. Calculating the change for each layer independently unfortunately does not provide insights into this comparison, as it does not capture the relative distribution of projection neurons across layers, which is central to our analysis. Therefore, we chose to present the data as layer fractions normalised within each hemisphere separately, enabling a comparison of relative changes between hemispheres, as shown in Fig.6 in the manuscript. We agree that with our approach a decrease in the fraction of L2/3 neurons would necessarily lead to an increase in the fraction of L5+6 neurons. However, as we analysed the fractional change for L5 and L6 separately, we found that the fraction of projection neurons in L5 generally showed only minor changes, while the fraction of L6 projection neurons increased substantially (Fig.6C). In addition, excluding L5 from the ipsi- or contralateral default network had significant effects on the fILN in only a relatively small number of projection areas. Excluding L6 resulted in significant changes in many more projection areas than layer 5.

Author response image 2.

Preservation index for L2/3, L5 and L6 of the 24 sensory-motor areas projecting onto the three target areas VISp, SSp-bfd and MOp.

Reviewer #2 (Recommendations for the authors):

I feel that there are a few conclusions that could be strengthened in the paper:

(1) The laminar sources of callosal inputs and their terminations differ in the monocular and binocular areas of the visual cortex (border with V2L. Similarly, callosal inputs are different close to the border of S1 with S2 than in the rest of the barrel cortex. From the methods sections and Figure S2, it seems that some injections targeted the V1 binocular zone while others were aimed at the monocular zone. Thus, it would be of interest to compare the laminar distribution and fILM of the contra inputs in inputs to the binocular and monocular zones (and S1 border vs the rest, if possible within this dataset).

Please see the answer for the reviewer’s second point in the public review (above).

(2) The results are currently a bit unclear on whether the contra inputs reflect the cortical hierarchy. Figure 4E-F makes it clear that the ipsi and contra fILMs do not always match. However, it seems from the plots in Figure 4D and Figure S6 that, while the contra fILM values are always higher, there might be a correlation between the ipsi and contra fILM. This could be addressed by directly plotting contra vs ipsi fILM.

Similarly, it would be useful to directly address if there is any hint of the visual hierarchy, as calculated in Figure S5 for the contra inputs.

Regarding the first point of the reviewer: We appreciate this comment. We do indeed find a positive correlation between the fILN ipsilateral and fILN contralateral across the individual cortical areas for all three targets. (please see Author response image 3 below). This is indeed an interesting observation that indicates a high degree of preservation concerning the rank order of the anatomical hierarchy within the input arising from both hemispheres. Please see we have included this new figure 4F into the manuscript and added a sentence in the results (lines 282-288): 

Regarding the second point of the reviewer: For visual hierarchy, although weaker, we find that the hierarchical ranking of the higher cortical visual areas is preserved for the contralateral hemisphere (see Author response image 3 below). 

Author response image 3.

Rank ordered average fILN values (± sem) of higher visual cortical areas of the ventral and dorsal visual stream for the ipsilateral and contralateral hemisphere.

(3) I find the emphasis in the title and other parts of the paper on Layer 6 corticocortical cells dominating the anatomical organization of intra and interhemispheric feedback a bit of an overstatement. While it is true that the areas for which L6 is the most abundant source of cortico-cortical projections are the most abundant (Figure 3C), when just focusing on the number of neurons sending corticocortical connections (Figure 3B), this is less clear. Ipsi connections are roughly divided 1/3, 1/3 , 1/3 between L2/3 , L5 and L6. In the contra, while projections from L6 neurons are the most abundant, there are not a majority and are less than those of L2/3 and L5 together. I suggest revising the statement about L6 cells dominating cortico-cortical connections to more accurately reflect these nuances.

(4) The observations from Figure 3 discussed above suggest that L6 inputs dominate in areas with less abundant projections to the injected areas. Is this the case? Is the fraction of L6 inputs inversely correlated with the number of inputs from that area?

Please see the following correlation plots for the total number of inputs versus the fraction of L6 inputs per area for both the ipsilateral and contralateral hemisphere. We do find on the ipsilateral hemisphere a negative correlation between the total number of inputs and the L6 input fraction for VISp and to a lesser degree for SSp-bfd. Interestingly, we find the opposite correlation for the ipsilateral MOp, contralateral VISp, SSp-bfd and MOp (Author response image 4, Author response table 1). While this is an interesting finding, the correlations often appeared to be weak and often absent within the individual animals and across the three target areas (Author response table 1). Thus, these correlations are seemingly not a general feature of cortical connectivity.

Author response image 4.

Total number of cells versus fraction of cells within L6 per cortical brain area (average across animals) for the ipsilateral (top) and contralateral (bottom) hemisphere for the three target areas VISp, SSp-bfd and MOp.

Author response table 1: Respective correlations between total numbers of cells and fraction of cells within L6 per cortical brain area for the ipsilateral and contralateral hemisphere for the three target areas (significant correlations highlighted with green).

Minor issues:

(5) Where was the mouse in Figure 3A injected?

In this exemplary mouse the retrograde tracer was injected into VISp. We added this information in the Figure legend of Figure 3A1. 

(6) Clarify in panel 4F that the position of the circle corresponds to the area location.

Done as suggested. 

References

Bieler M, Sieben K, Cichon N, Schildt S, Röder B, Hanganu-Opatz IL. 2017. Rate and Temporal Coding Convey Multisensory Information in Primary Sensory Cortices. eNeuro 4. doi:10.1523/ENEURO.0037-17.2017

Weiler S, Rahmati V, Isstas M, Wutke J, Stark AW, Franke C, Graf J, Geis C, Witte OW, Hübener M, Bolz J, Margrie TW, Holthoff K, Teichert M. 2024. A primary sensory cortical interareal feedforward inhibitory circuit for tacto-visual integration. Nat Commun 15:3081. doi:10.1038/s41467-024-47459-2

Yao S, Wang Q, Hirokawa KE, Ouellette B, Ahmed R, Bomben J, Brouner K, Casal L, Caldejon S, Cho A, Dotson NI, Daigle TL, Egdorf T, Enstrom R, Gary A, Gelfand E, Gorham M, Griffin F, Gu H, Hancock N, Howard R, Kuan L, Lambert S, Lee EK, Luviano J, Mace K, Maxwell M, Mortrud MT, Naeemi M, Nayan C, Ngo N-K, Nguyen T, North K, Ransford S, Ruiz A, Seid S, Swapp J, Taormina MJ, Wakeman W, Zhou T, Nicovich PR, Williford A, Potekhina L, McGraw M, Ng L, Groblewski PA, Tasic B, Mihalas S, Harris JA, Cetin A, Zeng H. 2023. A whole-brain monosynaptic input connectome to neuron classes in mouse visual cortex. Nat Neurosci 26:350–364. doi:10.1038/s41593-022-01219-x

eLife Assessment

This study aims to identify the proteins that compose the electrical synapse, which are much less understood than those of the chemical synapse. The study is useful in terms of both method development and biological advances, as the authors identified more than 50 new proteins and used immunoprecipitation and immunostaining to validate their interaction. However, the current experimental data are considered incomplete, as many key experimental details are missing.

Reviewer #1 (Public review):

Summary:

This study aims to identify the proteins that compose the electrical synapse, which are much less understood than those of the chemical synapse. Identifying these proteins is important to understand how synaptogenesis and conductance are regulated in these synapses. The authors identified more than 50 new proteins and used immunoprecipitation and immunostaining to validate their interaction of localization. One new protein, a scaffolding protein, shows particularly strong evidence of being an integral component of the electrical synapse. However, many key experimental details are missing (e.g. mass spectrometry), making it difficult to assess the strength of the evidence.

Strengths:

One newly identified protein, SIPA1L3, has been validated both by immunoprecipitation and immunohistochemistry. The localization at the electrical synapse is very striking.<br /> A large number of candidate interacting proteins were validated with immunostaining in vivo or in vitro.

Weaknesses:

There is no systematic comparison between the zebrafish and mouse proteome. The claim that there is "a high degree of evolutionary conservation" was not substantiated.

No description of how mass spectrometry was done and what type of validation was done.

The threshold for enrichment seems arbitrary.

Inconsistent nomenclature and punctuation usage.

The description of figures is very sparse and error-prone (e.g. Figure 6).

In Figure 1B, there is very broad non-specific labeling by avidin in zebrafish (In contrast to the more specific avidin binding in mice, Figure 2B). How are the authors certain that the enrichment is specific at the electrical synapse?

In Figure 1E, there is very little colocalization between Cx35 and Cx34.7. More quantification is needed to show that it is indeed "frequently associated."

Expression of GFP in HCs would potentially be an issue, since GFP is fused to Cx36 (regardless of whether HC expresses Cx36 endogenously) and V5-TurboID-dGBP can bind to GFP and biotinylate any adjacent protein.

Figure 7: the description does not match up with the figure regarding ZO-1 and ZO-2.

Reviewer #2 (Public review):

Summary:

This study aimed to uncover the protein composition and evolutionary conservation of electrical synapses in retinal neurons. The authors employed two complementary BioID approaches: expressing a Cx35b-TurboID fusion protein in zebrafish photoreceptors and using GFP-directed TurboID in Cx36-EGFP-labeled mouse AII amacrine cells. They identified conserved ZO proteins and endocytosis components in both species, along with over 50 novel proteins related to adhesion, cytoskeleton remodeling, membrane trafficking, and chemical synapses. Through a series of validation studies¬-including immunohistochemistry, in vitro interaction assays, and immunoprecipitation - they demonstrate that novel scaffold protein SIPA1L3 interacts with both Cx36 and ZO proteins at electrical synapse. Furthermore, they identify and localize proteins ZO-1, ZO-2, CGN, SIPA1L3, Syt4, SJ2BP, and BAI1 at AII/cone bipolar cell gap junctions.

Strengths:

The study demonstrates several significant strengths in both experimental design and validation approaches. First, the dual-species approach provides valuable insights into the evolutionary conservation of electrical synapse components across vertebrates. Second, the authors compare two different TurboID strategies in mice and demonstrate that the HKamac promoter and GFP-directed approach can successfully target the electrical synapse proteome of mouse AII amacrine cells. Third, they employed multiple complementary validation approaches - including retinal section immunohistochemistry, in vitro interaction assays, and immunoprecipitation-providing evidence supporting the presence and interaction of these proteins at electrical synapses.

Weaknesses:

The conclusions of this paper are supported by data; however, some aspects of the quantitative proteomics analysis require clarification and more detailed documented. The differential threshold criteria (>3 log2 fold for mouse vs >1 log2 fold for zebrafish) will benefit from biological justification, particularly given the cross-species comparison. Additionally, providing details on the number of biological or technical replicates used in this study, along with analyses of how these replicates compare to each other, would strengthen the confidence in the identification of candidate proteins. Furthermore, including negative controls for the histological validation of proteins interacting with Cx36 could increase the reliability of the staining results.

While the study successfully characterized the presence of candidate proteins at the electrical synapses between AII amacrine cells and cone bipolar cells, it did not compare protein compositions between the different types of electrical synapses within the circuit. Given that AII amacrine cells form both homologous (AII-AII) and heterologous (AII-cone bipolar cell) electrical synapses-connections that serve distinct functional roles in retinal signaling processing-a comparative analysis of their molecular compositions could have provided important insights into synapse specificity.

Reviewer #3 (Public review):

Summary:

This study by Tetenborg S et al. identifies proteins that are physically closely associated with gap junctions in retinal neurons of mice and zebrafish using BioID, a technique that labels and isolates proteins proximal to a protein of interest. These proteins include scaffold proteins, adhesion molecules, chemical synapse proteins, components of the endocytic machinery, and cytoskeleton-associated proteins. Using a combination of genetic tools and meticulously executed immunostaining, the authors further verified the colocalizations of some of the identified proteins with connexin-positive gap junctions. The findings in this study highlight the complexity of gap junctions. Electrical synapses are abundant in the nervous system, yet their regulatory mechanisms are far less understood than those of chemical synapses. This work will provide valuable information for future studies aiming to elucidate the regulatory mechanisms essential for the function of neural circuits.

Strengths:

A key strength of this work is the identification of novel gap junction-associated proteins in AII amacrine cells and photoreceptors using BioID in combination with various genetic tools. The well-studied functions of gap junctions in these neurons will facilitate future research into the functions of the identified proteins in regulating electrical synapses.

Weaknesses:

I do not see major weaknesses in this paper. A minor point is that, although the immunostaining in this study is beautifully executed, the quantification to verify the colocalization of the identified proteins with gap junctions is missing. In particular, endocytosis component proteins are abundant in the IPL, making it unclear whether their colocalization with gap junction is above chance level (e.g. EPS15l1, HIP1R, SNAP91, ITSN in Figure 3B).

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

This study aims to identify the proteins that compose the electrical synapse, which are much less understood than those of the chemical synapse. Identifying these proteins is important to understand how synaptogenesis and conductance are regulated in these synapses. The authors identified more than 50 new proteins and used immunoprecipitation and immunostaining to validate their interaction of localization. One new protein, a scaffolding protein, shows particularly strong evidence of being an integral component of the electrical synapse. However, many key experimental details are missing (e.g. mass spectrometry), making it difficult to assess the strength of the evidence.

Strengths:

One newly identified protein, SIPA1L3, has been validated both by immunoprecipitation and immunohistochemistry. The localization at the electrical synapse is very striking.<br /> A large number of candidate interacting proteins were validated with immunostaining in vivo or in vitro.

Weaknesses:

There is no systematic comparison between the zebrafish and mouse proteome. The claim that there is "a high degree of evolutionary conservation" was not substantiated.

We agree that we should have included a comprehensive comparison of proteins captured in the different species.  We are assembling this table and it will be included in the revised manuscript.  There is, indeed, significant conservation of many of the proteins enriched in both species.

No description of how mass spectrometry was done and what type of validation was done.

Since the mass spec was outsourced to a core facility, we had not included methodological details.  We have requested these and will include full details in the revised version of the manuscript.  In terms of “validation,” enrichment of proteins at electrical synapses was determined based on capture relative to control samples (non-transgenic zebrafish retinas or non-transgenic mouse retinas infected with the dGBP-TurboID virus) captured and processed at the same time.  Actual validations based on protein co-localization and pull-downs is the subject of the rest of the manuscript, and could only be done for a fraction of the identified proteins.  This type of validation can be pursued in many future studies. 

The threshold for enrichment seems arbitrary.

Yes, the thresholds are somewhat arbitrary.  This is due to the fact that experiments that captured larger total amounts of protein (mouse retina samples) had higher signal-to-noise ratio than those that captured smaller total amounts of protein (zebrafish retina).  This allowed us to use a more stringent threshold in the mouse dataset to focus on high probability captured proteins. 

Inconsistent nomenclature and punctuation usage.

We have scanned through the manuscript and updated terms that were used inconsistently in the interim revision of the manuscript.

To describe the mass spec procedure, we will get in touch with the mass spec facility and provide the details in the next round of submission.

The description of figures is very sparse and error-prone (e.g. Figure 6).

In Figure 1B, there is very broad non-specific labeling by avidin in zebrafish (In contrast to the more specific avidin binding in mice, Figure 2B). How are the authors certain that the enrichment is specific at the electrical synapse?

The enrichment of the proteins we identified is specific for electrical synapses because we compared the abundance of all candidates between Cx35b-V5-TurboID and wildtype retinas. Proteins that are components of electrical synapses, will only show up in the Cx35b-V5-TurboID condition. The western blot (Strep-HRP) in figure 1C shows the differences in the streptavidin labeling and hence the enrichment of proteins that are part of electrical synapses. Moreover, while the background appears to be quite abundant in sections, biotinylation is a rare posttranslational modification and mainly occurs in carboxylases: The two intense bands that show up above 50 and 75 kDa.  The background mainly originates from these two proteins.

In Figure 1E, there is very little colocalization between Cx35 and Cx34.7. More quantification is needed to show that it is indeed "frequently associated."

We agree that “frequently associated” is too strong as a statement. We corrected this and instead wrote “that Cx34.7 was only expressed in the outer plexiform layer (OPL) where it was associated with Cx35b at some gap junctions” in line 150. There are many gap junctions at which Cx35b is not colocalized with Cx34.7. 

Expression of GFP in HCs would potentially be an issue, since GFP is fused to Cx36 (regardless of whether HC expresses Cx36 endogenously) and V5-TurboID-dGBP can bind to GFP and biotinylate any adjacent protein.  

Thank you for this suggestion! There should be no Cx36-GFP expression in horizontal cells, which means that the nanobody cannot bind to anything in these cells. Moreover, to recognize specific signals from non-specific background, we included wild type retinas throughout the entire experiments. This condition controls for non-specific biotinylation.

Figure 7: the description does not match up with the figure regarding ZO-1 and ZO-2.

It appears that a portion of the figure legend was left out of the submitted version of the manuscript.  We have put the legend for panels A through C back into the manuscript in the interim revision.

Reviewer #2 (Public review):

Summary:

This study aimed to uncover the protein composition and evolutionary conservation of electrical synapses in retinal neurons. The authors employed two complementary BioID approaches: expressing a Cx35b-TurboID fusion protein in zebrafish photoreceptors and using GFP-directed TurboID in Cx36-EGFP-labeled mouse AII amacrine cells. They identified conserved ZO proteins and endocytosis components in both species, along with over 50 novel proteins related to adhesion, cytoskeleton remodeling, membrane trafficking, and chemical synapses. Through a series of validation studies¬-including immunohistochemistry, in vitro interaction assays, and immunoprecipitation - they demonstrate that novel scaffold protein SIPA1L3 interacts with both Cx36 and ZO proteins at electrical synapse. Furthermore, they identify and localize proteins ZO-1, ZO-2, CGN, SIPA1L3, Syt4, SJ2BP, and BAI1 at AII/cone bipolar cell gap junctions.

Strengths:

The study demonstrates several significant strengths in both experimental design and validation approaches. First, the dual-species approach provides valuable insights into the evolutionary conservation of electrical synapse components across vertebrates. Second, the authors compare two different TurboID strategies in mice and demonstrate that the HKamac promoter and GFP-directed approach can successfully target the electrical synapse proteome of mouse AII amacrine cells. Third, they employed multiple complementary validation approaches - including retinal section immunohistochemistry, in vitro interaction assays, and immunoprecipitation-providing evidence supporting the presence and interaction of these proteins at electrical synapses.

Weaknesses:

The conclusions of this paper are supported by data; however, some aspects of the quantitative proteomics analysis require clarification and more detailed documented. The differential threshold criteria (>3 log2 fold for mouse vs >1 log2 fold for zebrafish) will benefit from biological justification, particularly given the cross-species comparison. Additionally, providing details on the number of biological or technical replicates used in this study, along with analyses of how these replicates compare to each other, would strengthen the confidence in the identification of candidate proteins. Furthermore, including negative controls for the histological validation of proteins interacting with Cx36 could increase the reliability of the staining results.

While the study successfully characterized the presence of candidate proteins at the electrical synapses between AII amacrine cells and cone bipolar cells, it did not compare protein compositions between the different types of electrical synapses within the circuit. Given that AII amacrine cells form both homologous (AII-AII) and heterologous (AII-cone bipolar cell) electrical synapses-connections that serve distinct functional roles in retinal signaling processing-a comparative analysis of their molecular compositions could have provided important insights into synapse specificity.

Reviewer #3 (Public review):

Summary:

This study by Tetenborg S et al. identifies proteins that are physically closely associated with gap junctions in retinal neurons of mice and zebrafish using BioID, a technique that labels and isolates proteins proximal to a protein of interest. These proteins include scaffold proteins, adhesion molecules, chemical synapse proteins, components of the endocytic machinery, and cytoskeleton-associated proteins. Using a combination of genetic tools and meticulously executed immunostaining, the authors further verified the colocalizations of some of the identified proteins with connexin-positive gap junctions. The findings in this study highlight the complexity of gap junctions. Electrical synapses are abundant in the nervous system, yet their regulatory mechanisms are far less understood than those of chemical synapses. This work will provide valuable information for future studies aiming to elucidate the regulatory mechanisms essential for the function of neural circuits.

Strengths:

A key strength of this work is the identification of novel gap junction-associated proteins in AII amacrine cells and photoreceptors using BioID in combination with various genetic tools. The well-studied functions of gap junctions in these neurons will facilitate future research into the functions of the identified proteins in regulating electrical synapses.

Thank you for these comments.

Weaknesses:

I do not see major weaknesses in this paper. A minor point is that, although the immunostaining in this study is beautifully executed, the quantification to verify the colocalization of the identified proteins with gap junctions is missing. In particular, endocytosis component proteins are abundant in the IPL, making it unclear whether their colocalization with gap junction is above chance level (e.g. EPS15l1, HIP1R, SNAP91, ITSN in Figure 3B).

eLife Assessment

This study presents a valuable finding on the importance of the plasma metabolome in glaucoma risk prediction. The evidence supporting the claims of the authors is solid and the work offers insights for the design of protective therapeutic strategies for glaucoma. The authors have addressed the concerns of the reviewers and reported on the limitations of the study.

Reviewer #1 (Public review):

Summary:

The Authors explore associations between plasma metabolites and glaucoma, a primary cause of irreversible vision loss worldwide. The study relies on measurements of 168 plasma metabolites in 4,658 glaucoma patients and 113,040 controls from the UK Biobank. The Authors show that metabolites improve the prediction of glaucoma risk based on polygenic risk score (PRS) alone, albeit weakly. The Authors also report a "metabolomic signature" that is associated with a reduced risk (or "resilience") for developing glaucoma among individuals in the highest PRS decile (reduction of risk by an estimated 29%). The Authors highlight the protective effect of pyruvate, a product of glycolysis, for glaucoma development and show that this molecule mitigates elevated intraocular pressure and optic nerve damage in a mouse model of this disease.

Strengths:

This work provides additional evidence that glycolysis may play a role in the pathophysiology of glaucoma. Previous studies have demonstrated the existence of an inverse relationship between intraocular pressure and retinal pyruvate levels in animal models (Hader et al. 2020, PNAS 117(52)) and pyruvate supplementation is currently being explored for neuro-enhancement in patients with glaucoma (De Moraes et al. 2022, JAMA Ophthalmology 140(1)). The study design is rigorous and relies on validated standard methods. Additional insights gained from a mouse model are valuable.

Weaknesses:

Caution is warranted when examining and interpreting the results of this study. Among all participants (cases and controls) glaucoma status was self-reported, determined on the basis of ICD codes or previous glaucoma laser/surgical therapy. This is problematic as it is not uncommon for individuals in the highest PRS decile to have undiagnosed glaucoma (as shown in previous work by some of the authors of this article). The Authors acknowledge a "relatively low glaucoma prevalence in the highest decile group" but do not explore how undiagnosed glaucoma may affect their results. This also applies to all controls selected for this study. The Authors state that "50 to 70% of people affected [with glaucoma] remain undiagnosed". Therefore, the absence of self-reported glaucoma does not necessarily indicate that the disease is not present. Validation of the findings from this study in humans is, therefore, critical. This should ideally be performed in a well-characterized glaucoma cohort, in which case and control status has been assessed by qualified clinicians.

The authors indicate that within the top decile of PRS participants with glaucoma are more likely to be of white ethnicity, while they are more likely to be of Black and Asian ethnicity if they are in the bottom half of PRS. Have the Authors explored how sensitive their predictions are to ethnicity? Since their cohort is predominantly of European ancestry (85.8%), would it make sense to exclude other ethnicities to increase the homogeneity of the cohort and reduce the risk for confounders that may not be explicitly accounted for?

The authors discuss the importance of pyruvate, and lactate for retinal ganglion cell survival along with that of several lipoproteins for neuroprotection. However, there is a distinction to be made between locally produced/available glycolysis end products and lipoproteins and those circulating in the blood. It may be useful to discuss this in the manuscript, and for the Authors to explore if plasma metabolites may be linked to metabolism that takes place past the blood-retinal barrier.

Comments on revisions:

The Authors have addressed all of my concerns.

Reviewer #2 (Public review):

Summary

The authors have used the UK Biobank data to interrogate the association between plasma metabolites and glaucoma.

(1) They initially assessed plasma metabolites as predictors of glaucoma: The addition of NMR-derived metabolomic data to existing models containing clinical and genetic data was marginal.<br /> (2) They then determined whether certain metabolites might protect against glaucoma in individuals at high genetic risk: Certain molecules in bioenergetic pathways (lactate, pyruvate and citrate) conferred protection.<br /> (3) They provide support for protection conferred by pyruvate in a murine model.

Weaknesses

(1) Although it is an invaluable treasure trove of data, selection bias and self-reporting are inescapable problems when using the UK Biobank data for glaucoma research. The high-impact glaucoma-related GWAS publications (Ref 26 and 27) referenced in support of the method suffer the same limitations. This doesn't negate the conclusions but must be taken into consideration. The authors might note that it is somewhat reassuring that the proportion of glaucoma cases (4%) is close to what would be expected in a population-based study of 40-69-year-olds of predominantly white ethnicity.<br /> (2) As noted by the authors, a limitation is the predominantly white ethnicity profile that comprises the UK Biobank.<br /> (3) Also as noted by the authors, the study is cross-sectional and is limited by the "correlation does not imply causation" issue.<br /> (4) The optimal collection, transport and processing of the samples for NMR metabolite analysis is critical for accurate results. Strict policies were in place for these procedures, but deviations from protocol remain an unknown influence on the data.<br /> (5) In addition, all UK Biobank blood samples had unintended dilution during the initial sample storage process at UK Biobank facilities. (Julkunen, H. et al. Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank. Nat Commun 14, 604 (2023) Samples from aliquot 3, used for the NMR measurements, suffered from 5-10% dilution. (Allen, Naomi E., et al. Wellcome Open Research 5 (2021): 222.) Julkunen et al. report that "The dilution is believed to come from mixing of participant samples with water due to seals that failed to hold a system vacuum in the automated liquid handling systems. While this issue is likely to have an impact on some of the absolute biomarker concentration values, it is expected to have limited impact on most epidemiological analyses."

Strengths

The huge sample size supports a powerful statistical analysis and the opportunity for the inclusion of multiple covariates and interactions without overfitting the models.<br /> The authors have constructed a robust methodology and statistical design.<br /> The manuscript is well-written, and the study is logically presented.<br /> The Figures are of good quality.

Broadly, the conclusions are justified by the findings.

Impact<br /> The findings advance personalized prognostics for glaucoma that combine metabolomic and genetic data. In addition, the protective effect of certain metabolites influences further research on novel therapeutic strategies.

Comments on revisions:

The authors have thoughtfully and comprehensively addressed my comments. I have no further comments.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors explore associations between plasma metabolites and glaucoma, a primary cause of irreversible vision loss worldwide. The study relies on measurements of 168 plasma metabolites in 4,658 glaucoma patients and 113,040 controls from the UK Biobank. The authors show that metabolites improve the prediction of glaucoma risk based on polygenic risk score (PRS) alone, albeit weakly. The authors also report a "metabolomic signature" that is associated with a reduced risk (or "resilience") for developing glaucoma among individuals in the highest PRS decile (reduction of risk by an estimated 29%). The authors highlight the protective effect of pyruvate, a product of glycolysis, for glaucoma development and show that this molecule mitigates elevated intraocular pressure and optic nerve damage in a mouse model of this disease.

Strengths:

This work provides additional evidence that glycolysis may play a role in the pathophysiology of glaucoma. Previous studies have demonstrated the existence of an inverse relationship between intraocular pressure and retinal pyruvate levels in animal models (Hader et al. 2020, PNAS 117(52)) and pyruvate supplementation is currently being explored for neuro-enhancement in patients with glaucoma (De Moraes et al. 2022, JAMA Ophthalmology 140(1)). The study design is rigorous and relies on validated, standard methods. Additional insights gained from a mouse model are valuable.

We thank the reviewer for these supportive comments.

Weaknesses:

Caution is warranted when examining and interpreting the results of this study. Among all participants (cases and controls) glaucoma status was self-reported, determined on the basis of ICD codes or previous glaucoma laser/surgical therapy. This is problematic as it is not uncommon for individuals in the highest PRS decile to have undiagnosed glaucoma (as shown in previous work by some of the authors of this article). The authors acknowledge a "relatively low glaucoma prevalence in the highest decile group" but do not explore how undiagnosed glaucoma may affect their results. This also applies to all controls selected for this study. The authors state that "50 to 70% of people affected [with glaucoma] remain undiagnosed". Therefore, the absence of self-reported glaucoma does not necessarily indicate that the disease is not present. Validation of the findings from this study in humans is, therefore, critical. This should ideally be performed in a well-characterized glaucoma cohort, in which case and control status has been assessed by qualified clinicians.

We appreciate the comment regarding the challenges of glaucoma ascertainment in UK Biobank. This is a valid limitation, as glaucoma in UK Biobank is based on self-reports and hospital records rather than comprehensive ophthalmologic examinations for all participants. To the best of our knowledge, there is no comparably sized dataset where all participants have undergone standardized glaucoma assessments, comprehensive metabolomic profiling, and high-throughput genotyping. Work is currently ongoing to link UK Biobank data to ophthalmic EMR data, which will help confirm self-reported diagnoses. This work is not complete, and the coverage of the cohort from such linkage is uncertain at present. Nonetheless, several factors speak to the validity of our findings. The top members of the metabolomic signature associated with resilience in the top decile of glaucoma polygenic risk score (PRS) decile—lactate (P=8.8E-12) and pyruvate (P=1.9E-10) —had robust values for statistical significance after appropriate adjustment for multiple comparisons, with additional validation for pyruvate in a human-relevant, glaucoma mouse model. Strikingly, the glaucoma odds ratio (OR) for subjects in the highest quartile of glaucoma PRS and metabolic risk score (MRS) was 25-fold, using participants in the lowest quartile of glaucoma PRS and MRS as the reference group. An effect size this large for a putative glaucoma determinant has only been seen for intraocular pressure (IOP), which is now largely accepted to be in the causal pathway of the disease.

The Discussion now contains the following statement: “A second limitation is that glaucoma ascertainment in the UK Biobank is based on self-reported diagnoses and hospital records rather than comprehensive ophthalmologic examinations. Nonetheless, it is reassuring that the prevalence of glaucoma in our sample (~4%) is similar to a directly performed disease burden estimate in a comparable, albeit slightly older, United Kingdom sample (2.7%)(79)”. (Lines 379-382)

The authors indicate that within the top decile of PRS participants with glaucoma are more likely to be of white ethnicity, while they are more likely to be of Black and Asian ethnicity if they are in the bottom half of PRS. Have the authors explored how sensitive their predictions are to ethnicity? Since their cohort is predominantly of European ancestry (85.8%), would it make sense to exclude other ethnicities to increase the homogeneity of the cohort and reduce the risk for confounders that may not be explicitly accounted for?

Comparing data in Tables 3 and 4 of the manuscript, we observe that, on a percentage basis, more individuals have glaucoma in the highest 10th percentile of risk compared to the lowest 50th percentile of risk across all ancestral groups.  We recently reported that the risk of glaucoma increases with each standard deviation increase in the glaucoma PRS across ancestral groups in the UK Biobank, utilizing a slightly different sample size (see Author response table 1 below). (1)Since the PRS is applicable across ancestral groups, we aim to make our results as generalizable as possible; therefore, we prefer to report our findings for all ethnic groups and not restrict our results to Europeans.

Author response table 1.

Performance of the mtGPRS Across Ancestral Groups in the UK Biobank

Abbreviations: mtGPRS, multitrait analysis of GWAS polygenic risk score; OR, odds ratio; CI, confidence interval.(1)

UK Biobank ancestry was genetically inferred based on principal component analysis. The OR represents the risk associated with each standard deviation change in mtGRS and is adjusted for multiple covariates including age, sex, and medical comorbidities.

In the discussion, we stated that “... we chose to analyze Europeans and non-Europeans together to make the results as generalizable as possible.” (Lines 378-379)

The authors discuss the importance of pyruvate, and lactate for retinal ganglion cell survival, along with that of several lipoproteins for neuroprotection. However, there is a distinction to be made between locally produced/available glycolysis end products and lipoproteins and those circulating in the blood. It may be useful to discuss this in the manuscript, and for the authors to explore if plasma metabolites may be linked to metabolism that takes place past the blood-retinal barrier.

As the reviewer points out, it is crucial to interpret the results for lipoproteins within the context of their access to the blood-retinal barrier. Even for smaller metabolites like pyruvate and lactate, it is essential to consider local production versus serum-derived molecules in mediating any neuroprotective effects. Our murine data suggest that exogenous pyruvate contributed to neuroprotection. However, for the other glycolysis-related metabolites (lactate and citrate), we cannot rule out the possibility that locally produced metabolites may also contribute to neuroprotection. None of the lipoproteins identified as potential resilience biomarkers had an adjusted P-value of less than 0.05. Nevertheless, HDL analytes can cross blood-ocular barriers to enter the aqueous humor.(2) Therefore, it is also possible for serum-derived HDL to influence retinal ganglion cell homeostasis. Overall, much more research is needed to clarify the roles of locally produced versus serum-derived factors in conferring resilience to genetic predisposition to glaucoma.

We have added the following sentences to the discussion:

“Notably, although our validation data confirm the neuroprotective effects of exogenous pyruvate, it remains possible that endogenously produced pyruvate within ocular tissues may also contribute to RGC protection.” (Lines 329-331)

“Furthermore, as HDL analytes can cross blood-ocular barriers,(78) there is a plausible route for serum-derived HDL to influence RGC homeostasis. Nonetheless, the relative contributions of circulating lipoproteins versus local synthesis within ocular tissues remain unclear and warrant further investigation.” (Lines 355-358)

“Incorporating ocular physiology and blood-retinal barrier considerations when interpreting lipoproteins as potential resilience biomarkers will be critical for future studies aimed at understanding and therapeutically targeting increased glaucoma risk.” (Lines 360-363)

Reviewer #2 (Public review):

Summary

The authors have used the UK Biobank data to interrogate the association between plasma metabolites and glaucoma.

(1) They initially assessed plasma metabolites as predictors of glaucoma: The addition of NMR-derived metabolomic data to existing models containing clinical and genetic data was marginal.

(2) They then determined whether certain metabolites might protect against glaucoma in individuals at high genetic risk: Certain molecules in bioenergetic pathways (lactate, pyruvate, and citrate) conferred protection.

(3) They provide support for protection conferred by pyruvate in a murine model.

Strengths

(1) The huge sample size supports a powerful statistical analysis and the opportunity for the inclusion of multiple covariates and interactions without overfitting the models.

(2) The authors have constructed a robust methodology and statistical design.

(3) The manuscript is well written, and the study is logically presented.

(4) The figures are of good quality.

(5) Broadly, the conclusions are justified by the findings.

We thank the reviewer for these supportive comments.

Weaknesses

(1) Although it is an invaluable treasure trove of data, selection bias and self-reporting are inescapable problems when using the UK Biobank data for glaucoma research. The high-impact glaucoma-related GWAS publications (references 26 and 27) referenced in support of the method suffer the same limitations. This doesn't negate the conclusions but must be taken into consideration. The authors might note that it is somewhat reassuring that the proportion of glaucoma cases (4%) is close to what would be expected in a population-based study of 40-69-year-olds of predominantly white ethnicity.

While there are limitations when open-angle glaucoma (OAG) is ascertained by self-report, as discussed above, we agree with the reviewer that the prevalence of glaucoma is consistent with data from population-based studies of Europeans who are 40-69 years of age. 

We also want to point out that references 26 and 27 indicate glaucoma self-reports can be an acceptable surrogate for OAG that is ascertained by clinical evaluation. Consider the methodologic details for each study:

Reference 26 is a 4-stage genome-wide meta-analysis to identify loci for OAG from 21 independent populations. The phenotypic definition of OAG was based on clinical assessment in the discovery stage, and 7286 glaucoma self-reports from the UK Biobank served as an effective replication set.  It is also important to note that 120 out of the 127 discovered OAG loci were nominally replicated in 23andMe, where glaucoma was ascertained entirely by self-report.

Reference 27 is a genome-wide meta-analysis to identify IOP genetic loci, an important endophenotype for OAG. The study identified 112 loci for IOP. These loci were incorporated into a glaucoma prediction model in the NEIGHBORHOOD study and the UK Biobank. The area under the receiver operator curve was 0.76 and 0.74, respectively, in these studies. While the AUCs were similar, OAG was ascertained clinically in NEIGHBORHOOD and largely by self-report in UK Biobank. 

Finally, a strength of the UK Biobank is that selection bias is minimized. Patients need not be insured or aligned to the study for any reason aside from being a UK resident. There is indeed a healthy bias in the UK Biobank. Ambulatory patients who tend to be health conscious and willing to donate their time and provide biological specimens tend to participate. We agree with the reviewer that the use of self-reported cases does not negate the conclusions, and hopefully, future iterations of the UK Biobank where clinical validation of self-reports are performed will confirm these findings, which already have some validation in a preclinical glaucoma model.

We add the following sentence to the first action item above regarding our case ascertainment method. “Nonetheless, it is reassuring that the prevalence of glaucoma in our sample (~4%) is similar to a directly performed disease burden estimate in a comparable, albeit slightly older, United Kingdom sample (2.7%)..”(3) (Lines 381-383)

(2) As noted by the authors, a limitation is the predominantly white ethnicity profile that comprises the UK Biobank. 

(3) Also as noted by the authors, the study is cross-sectional and is limited by the "correlation does not imply causation" issue.

While the epidemiological arm of our study was cross-sectional, the studies testing the ability of pyruvate to mitigate the glaucoma phenotype in mice with the Lmxb1 mutation were prospective.

We already pointed out in the discussion that pyruvate supplementation reduced glaucoma incidence in a human-relevant genetic mouse model.

(4) The optimal collection, transport, and processing of the samples for NMR metabolite analysis is critical for accurate results. Strict policies were in place for these procedures, but deviations from protocol remain an unknown influence on the data.

Comments 4 and 5 are related and will be addressed after comment 5.

(5) In addition, all UK Biobank blood samples had unintended dilution during the initial sample storage process at UK Biobank facilities. (Julkunen, H. et al. Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank. Nat Commun 14, 604 (2023) Samples from aliquot 3, used for the NMR measurements, suffered from 5-10% dilution. (Allen, Naomi E., et al. Wellcome Open Research 5 (2021): 222.) Julkunen et al. report that "The dilution is believed to come from mixing of participant samples with water due to seals that failed to hold a system vacuum in the automated liquid handling systems. While this issue is likely to have an impact on some of the absolute biomarker concentration values, it is expected to have limited impact on most epidemiological analyses."

We thank the reviewer for making us aware of the unintended sample dilution issue from aliquot 3, used for NMR metabolomics in UK Biobank participants. While ~98% of samples experienced a 5-10% dilution, this would not affect our reported results, which did not rely on absolute biomarker concentrations. All metabolites in the main tables were probit transformed and used as continuous variables per 1 standard deviation increase.  Nonetheless, in supplemental material, we show the unadjusted median levels of pyruvate (in mmol/L) were higher in participants without glaucoma vs those with glaucoma, both in the population overall and in those in the top 10 percentile of glaucoma risk. 

Furthermore, we see no evidence in the literature that unidentified protocol deviations might impact metabolite results in UK Biobank participants. For example, a recent study evaluated the relationship between a weighted triglyceride-raising polygenic score (TG.PS) and type 3 hyperlipidemia (T3HL) in the Oxford Biobank (OBB) and the UK Biobank. In both biobanks, metabolomics was performed on the Nightingale NMR platform. A one standard deviation increase in TG.PS was associated with a 13% and 15.2% increased risk of T3HL in the OBB and UK Biobank, respectively.(4) Replication of the OBB result in the UK Biobank suggests there are no additional concerns regarding the processing of the UK Biobank for NMR metabolomics. Of course, we remain vigilant for protocol deviations that might call our results into question and will seek to validate our findings in other biobanks in future research.

Impact

The findings advance personalized prognostics for glaucoma that combine metabolomic and genetic data. In addition, the protective effect of certain metabolites influences further research on novel therapeutic strategies.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Given the uncertainty in the proportion of controls with undiagnosed glaucoma, it may be appropriate to include a sensitivity analysis in the manuscript. The authors could then provide the readers with an estimate of how sensitive their predictions are to the proportion of undiagnosed individuals among controls.

Since UK Biobank participants did not undergo standardized clinical assessments, it is not possible to perform sensitivity analyses as we don’t know which controls might have glaucoma, although we can offer the following comments.

We are performing a cross-sectional, prospective, detailed glaucoma assessment of participants in the top and bottom 10 percent of genetic predisposition recruited from BioMe at Icahn School of Medicine at Mount Sinai and Mass General Brigham Biobank at Harvard Medical School. We find that 21% of people in the top decile of genetic risk have glaucoma,(5) which compares reasonably well to the 15% of people in the top 10% of genetic risk in the UK Biobank. This underscores the assertion that our definition of glaucoma in the UK Biobank, while not ideal, is a reasonable surrogate for a detailed clinical assessment.

Currently, 10,077 subjects in the top decile of glaucoma genetic predisposition did not meet our definition of glaucoma. If we assume that the glaucoma prevalence is 3% and 50% of people with glaucoma are undiagnosed, then that would translate to an additional 150 cases misclassified as controls, which could either drive our result to the null, have no impact on our current result or contribute to a false positive result, depending on their pyruvate (and other metabolite) levels.   

We have already addressed the issue of a lack of standardized exams in the UK Biobank and the need for more studies to confirm our findings.

Reviewer #2 (Recommendations for the authors):

(1) I am curious about the proposed reason for some individuals having metabolic profiles conferring resilience. Plasma pyruvate levels are normally distributed. Is it simply the case that some individuals with naturally high levels of pyruvate are fortuitously protected against glaucoma? Some sort of self-regulation mechanism seems unlikely.

Thank you for your insightful question regarding the potential mechanism underlying the association between pyruvate levels and glaucoma resilience. There may be modest inter-individual differences which can have significant physiological implications, particularly in the context of neurodegeneration and metabolic stress. One possibility is that individuals with naturally higher pyruvate levels may benefit from pyruvate's known neuroprotective and metabolic support functions(6–8), which could confer resilience against the oxidative and bioenergetic challenges associated with glaucoma. Pyruvate is important for cellular metabolism, redox balance, and mitochondrial function - processes that are increasingly implicated in glaucomatous neurodegeneration. (9)Elevated pyruvate levels support mitochondrial ATP production(10), buffer oxidative stress,(11) and impact metabolic flux(12,13) through pathways such as the tricarboxylic acid cycle and NAD+/NADH homeostasis. This is consistent with prior studies suggesting that mitochondrial dysfunction contributes to retinal ganglion cell vulnerability in glaucoma.(14–17) While a direct self-regulation mechanism may seem unlikely, both genetic and environmental factors can influence pyruvate metabolism, which could lead to subtle but clinically meaningful variations in its levels. Our findings are supported by validation in a mouse model, which suggests that the association is less likely fortuitous, but there may be an underlying biological process that merits further mechanistic investigation. Future studies incorporating longitudinal metabolic profiling and functional validation in human-derived models will help better understand this relationship.

(2) Conceivably, the higher levels of pyruvate and lactate may have resulted from recent exercise and may reflect individuals with high levels of exercise that confers resilience against glaucoma by independent mechanisms such as improved blood flow. Any way to rule that out from the UK Biobank data?

Thank you for raising this important point. To account for the potential confounding effects of physical activity, we adjusted for metabolic equivalents of task (METs) in our models, a standardized measure of physical activity available in the UK Biobank. By incorporating METs as a covariate, we aimed to minimize the influence of individual exercise levels on plasma pyruvate and lactate levels. This helps us ascertain that the observed associations are not solely attributable to differences in physical activity. However, we do acknowledge that longitudinal analysis of exercise patterns would provide further clarity on this relationship. 

(3) It may be worth mentioning that the retinal ganglion cells contain a plasma membrane monocarboxylate transporter that supports pyruvate and lactate uptake from the extracellular space.

Thank you for this extremely insightful suggestion on retinal ganglion cell (RGC) expression of monocarboxylate transporters, which can facilitate the uptake of pyruvate and lactate from the extracellular space. This is relevant for our study, given the high metabolic demands of RGCs and their reliance on both glycolytic and oxidative metabolism for neuroprotection and survival.

We acknowledged this in the discussion section of the manuscript by adding the following statement: "RGCs express monocarboxylate transporters, which facilitate the uptake of extracellular pyruvate and lactate, improving energy homeostasis, neuronal metabolism, and survival.” (Lines 309-311)

(4) The mechanism of protection in the mice, at least in part, is likely due to the lower IOP in the pyruvate-treated animals. Did the authors investigate the influence of pyruvate on IOP in the UK Biobank data (about 110,000 individuals had IOP measurements)?

Thank you for your suggested investigation. We ran the suggested analysis among 68,761 individuals with IOP measurements and metabolomic profiling. Imputed pretreatment IOP values for participants using ocular hypotensive agents were calculated by dividing the measured IOP by 0.7, based on the mean IOP.

We plotted the relationship between IOP and pyruvate levels (probit transformed). We compared participants with pyruvate levels +2 standard deviations, above the mean (red dashed line), which has a probit-transformed value of 2 and an absolute concentration of 0.15 mmol/L. We found a statistically significant difference between the groups (p=0.017) using the Welch two-sample t-test. We have not added this analysis to the manuscript, but readers can find the data here as the reviews are public. We acknowledge and addressed the dilutional issue above, where we utilized probit-transformed metabolite levels analyzed as continuous variables per 1 SD increase, rather than absolute concentrations.

Author response image 1.

(5) Line 88: I suggest changing "patients" to "affected individuals". The term "patients" tends to imply that the individual has already been diagnosed, but the idea being conveyed is about underdiagnosis in the population.

Thank you for your suggestion.

We have added the change from "patients" to "affected individuals" in the introduction. (Line 90)

(6) Line 93: "However, glaucoma is also significantly affected by environmental and lifestyle factors,10-14". Although lifestyle risk factors such as caffeine intake, alcohol, smoking, and air pollution have been reported, the associations are generally weak and inconsistently reported. Consider modifying this notion to stress the emerging evidence around gene-environment interactions (reference 14) rather than environmental factors per se, with the implication that genes + metabolism may be greater than the sum of the parts.

Thank you for this thoughtful suggestion to highlight gene-environment interactions, where genetic susceptibility may amplify or mitigate the impact of metabolic and environmental influences on glaucoma progression. We have revised the statement to better reflect the synergistic effects of genetics and metabolism rather than considering environmental factors in isolation.

Revised sentence for inclusion in the introduction of the manuscript: "Glaucoma risk is influenced by both genetic and metabolic factors, with emerging evidence suggesting that gene-environment interactions may play a greater role in conferring disease risk than independent exposures alone.” (Lines 95-97)

(7) Lines 156-161: In model 4, rather than stating that the very small increase in AUC with the addition of metabolic data compared to clinical and genetic data alone, "modestly enhances the prediction of glaucoma", it may be better interpreted as a marginal difference that was statistically significant due to the very large sample size but not clinically significant.

Thank you for your suggested comment.

We have adjusted the wording by changing “modestly” to “marginally” to address that the statistical significance is in the context of the study’s large sample size in the results section (Line 162) and throughout the manuscript.

NB: We made other minor edits to correct minor grammatical errors, improve clarity, and streamline the revised manuscript. Furthermore, the paragraph regarding slit lamp examination in the Methods was inadvertently omitted but is added back in the revised manuscript (Lines 571-579).

References:

(1) Kim J, Kang JH, Wiggs JL, et al. Does Age Modify the Relation Between Genetic Predisposition to Glaucoma and Various Glaucoma Traits in the UK Biobank? Invest Ophthalmol Vis Sci. 2025;66(2):57. doi:10.1167/iovs.66.2.57

(2) Cenedella RJ. Lipoproteins and lipids in cow and human aqueous humor. Biochim Biophys Acta BBA - Lipids Lipid Metab. 1984;793(3):448-454. doi:10.1016/0005-2760(84)90262-5

(3) Minassian DC, Reidy A, Coffey M, Minassian A. Utility of predictive equations for estimating the prevalence and incidence of primary open angle glaucoma in the UK. Br J Ophthalmol. 2000;84(10):1159-1161. doi:10.1136/bjo.84.10.1159

(4) Pieri K, Trichia E, Neville MJ, et al. Polygenic risk in Type III hyperlipidaemia and risk of cardiovascular disease: An epidemiological study in UK Biobank and Oxford Biobank. Int J Cardiol. 2023;373:72-78. doi:10.1016/j.ijcard.2022.11.024

(5) Zhao H, Pasquale LR, Zebardast N, et al. Screening by glaucoma polygenic risk score to identify primary open-angle glaucoma in two biobanks: An updated report. ARVO 2025 meeting. Published online 2025.

(6) Zilberter Y, Gubkina O, Ivanov AI. A unique array of neuroprotective effects of pyruvate in neuropathology. Front Neurosci. 2015;9. doi:10.3389/fnins.2015.00017

(7) Quansah E, Peelaerts W, Langston JW, Simon DK, Colca J, Brundin P. Targeting energy metabolism via the mitochondrial pyruvate carrier as a novel approach to attenuate neurodegeneration. Mol Neurodegener. 2018;13(1):28. doi:10.1186/s13024-018-0260-x

(8) Gray LR, Tompkins SC, Taylor EB. Regulation of pyruvate metabolism and human disease. Cell Mol Life Sci. 2014;71(14):2577-2604. doi:10.1007/s00018-013-1539-2

(9) Harder JM, Guymer C, Wood JPM, et al. Disturbed glucose and pyruvate metabolism in glaucoma with neuroprotection by pyruvate or rapamycin. Proc Natl Acad Sci. 2020;117(52):33619-33627. doi:10.1073/pnas.2014213117

(10) Kim MJ, Lee H, Chanda D, et al. The Role of Pyruvate Metabolism in Mitochondrial Quality Control and Inflammation. Mol Cells. 2023;46(5):259-267. doi:10.14348/molcells.2023.2128

(11) Wang X, Perez E, Liu R, Yan LJ, Mallet RT, Yang SH. Pyruvate Protects Mitochondria from Oxidative Stress in Human Neuroblastoma SK-N-SH Cells. Brain Res. 2007;1132(1):1-9. doi:10.1016/j.brainres.2006.11.032

(12) Tilton WM, Seaman C, Carriero D, Piomelli S. Regulation of glycolysis in the erythrocyte: role of the lactate/pyruvate and NAD/NADH ratios. J Lab Clin Med. 1991;118(2):146-152.

(13) Li X, Yang Y, Zhang B, et al. Lactate metabolism in human health and disease. Signal Transduct Target Ther. 2022;7(1):305. doi:10.1038/s41392-022-01151-3

(14) Zhang ZQ, Xie Z, Chen SY, Zhang X. Mitochondrial dysfunction in glaucomatous degeneration. Int J Ophthalmol. 2023;16(5):811-823. doi:10.18240/ijo.2023.05.20

(15) Ju WK, Perkins GA, Kim KY, Bastola T, Choi WY, Choi SH. Glaucomatous optic neuropathy: Mitochondrial dynamics, dysfunction and protection in retinal ganglion cells. Prog Retin Eye Res. 2023;95:101136. doi:10.1016/j.preteyeres.2022.101136

(16) Jassim AH, Inman DM, Mitchell CH. Crosstalk Between Dysfunctional Mitochondria and Inflammation in Glaucomatous Neurodegeneration. Front Pharmacol. 2021;12. doi:10.3389/fphar.2021.699623

(17) Yang TH, Kang EYC, Lin PH, et al. Mitochondria in Retinal Ganglion Cells: Unraveling the Metabolic Nexus and Oxidative Stress. Int J Mol Sci. 2024;25(16):8626. doi:10.3390/ijms25168626

eLife Assessment

The authors examine the role of Numb, a Notch inhibitor, in intestinal stem cell self-renewal in Drosophila during homeostasis and regeneration. The significance is important as the authors demonstrate the ISC maintenance is reduced when both BMP signaling and Numb expression is reduced. The strength of evidence is convincing as large sample sizes and statistical analyses are provided.

Reviewer #1 (Public review):

Summary:

By way of background, the Jiang lab has previously shown that loss of the type II BMP receptor Punt (Put) from intestinal progenitors (ISCs and EBs) caused them to differentiate into EBs, with a concomitant loss of ISCs (Tian and Jiang, eLife 2014). The mechanism by which this occurs was activation of Notch in Put-deficient progenitors. How Notch was upregulated in Put-deficient ISCs was not established in this prior work. In the current study, the authors test whether a very low level of Dl was responsible. But co-depletion of Dl and Put led to a similar phenotype as depletion of Put alone. This result suggested that Dl was not the mechanism. They next investigate genetic interactions between BMP signaling and Numb, an inhibitor of Notch signaling. Prior work from Bardin, Schweisguth and other labs has shown that Numb is not required for ISC self-renewal. But the authors wanted to know whether loss of both the BMP signal transducer Mad and Numb would cause ISC loss. This result was observed for RNAi depletion from progenitors and for mad, numb double mutant clones. Of note, ISC loss was observed in 40% of mad, numb double mutant clones, whereas 60% of these clones had an ISC. They then employed a two-color tracing system called RGT to look at the outcome of ISC divisions (asymmetric (ISC/EB) or symmetric (ISC/ISC or EB/EB)). Control clones had 69%, 15% and 16%, respectively, whereas mad, numb double mutant clones had much lower ISC/ISC (11%) and much higher EB/EB (37%). They conclude that loss of Numb in moderate BMP loss of function mutants increased symmetric differentiation which lead caused ISC loss. They also reported that numb15 and numb4 clones had a moderate but significant increase in ISC-lacking clones compared to control clones, supporting the model that Numb plays a role in ISC maintenance. Finally, they investigated the relevance of these observation during regeneration. After bleomycin treatment, there was a significant increase in ISC-lacking clones and a significant decrease in clone size in numb4 and numb15 clones compared to control clones. Because bleomycin treatment has been shown to cause variation in BMP ligand production, the authors interpret the numb clone under bleomycin results as demonstrating an essential role of Numb in ISC maintenance during regeneration.

Strengths

i. Data are quantified with statistical analysis<br /> ii. Experiments have appropriate controls and large numbers of samples<br /> iii. Results demonstrate an important role of Numb in maintaining ISC number during regeneration and a genetic interaction between Mad and Numb during homeostasis.

Weaknesses

None noted in the revised manuscript.

Reviewer #2 (Public review):

Summary:

This work assesses the genetic interaction between the Bmp signaling pathway and the factor Numb, which can inhibit Notch signalling. It follows up on the previous studies of the group (Tian, eLife, 2014; Tian, PNAS, 2014) regarding BMP signaling in controlling stem cell fate decision as well as on the work of another group (Sallé, EMBO, 2017) that investigated the function of Numb on enteroendocrine fate in the midgut. This is an important study providing evidence of a Numb-mediated back up mechanism for stem cell maintenance.

Strengths:

(1) Experiments are consistent with these previous publications while also extending our understanding of how Numb functions in the ISC.<br /> (2) Provides an interesting model of a "back up" protection mechanism for ISC maintenance.

Weaknesses:<br /> (1) Aspects of the experiments could be better controlled or annotated:<br /> (a) As they "randomly chose" the regions analyzed, it would be better to have all from a defined region (R4 or R2, for example) or to at least note the region as there are important regional differences for some aspects of midgut biology.<br /> (b) It is not clear to me why MARCM clones were induced and then flies grown at 18{degree sign}C? It would help to explain why they used this unconventional protocol.

(2) There are technical limitations with trying to conclude from double-knockdown experiments in the ISC lineage, such as those in Figure 1 where Dl and put are both being knocked down: depending on how fast both proteins are depleted, it may be that only one of them (put, for example) is inactivated and affects the fate decision prior to the other one (Dl) being depleted. Therefore, it is difficult to definitively conclude that the decision is independent of Dl ligand.

(3) Additional quantification of many phenotypes would be desired.<br /> (a) It would be useful to see esg-GFP cells/total cells and not just field as the density might change (2E for example).<br /> (b) Similarly, for 2F and 2G, it would be nice to see the % of ISC/ total cell and EB/total cell and not only per esgGFP+ cell.<br /> (c) Fig1: There is no quantification - specifically it would be interesting to know how many esg+ are su(H)lacZ positive in Put- Dl- condition compared to WT or Put- alone. What is the n?<br /> (d) Fig2: Pros + cells are not seen in the image? Are they all DllacZ+?<br /> (e) Fig3: it would be nice to have the size clone quantification instead of the distribution between groups of 2 cell 3 cells 4 cell clones.<br /> (f) How many times were experiments performed?

(4) The authors do not comment on the reduction of clone size in DSS treatment in Figure 6K. How do they interpret this? Does it conflict with their model of Bleo vs DSS?

(5) There is probably a mistake on sentence line 314 -316 "Indeed, previous studies indicate that endogenous Numb was not undetectable by Numb antibodies that could detect Numb expression in the nervous system".

Comments on revisions:

The authors have by and large addressed my main points.

Reviewer #3 (Public review):

Summary:

The authors provide an in-depth analysis of the function of Numb in adult Drosophila midgut. Based on RNAi combinations and double mutant clonal analyses, they propose that Numb has a function in inhibiting Notch pathway to maintain intestinal stem cells, and is a backup mechanism with BMP pathway in maintaining midgut stem cell mediated homeostasis.

Strengths:

Overall, this is a carefully constructed series of experiments, and the results and statistical analyses provides believable evidence that Numb has a role, albeit weak compared to other pathways, in sustaining ISC and in promoting regeneration especially after damage by bleomycin, which may damage enterocytes and therefore disrupt BMP pathway more. The results overall support their claim.

The data are highly coherent, and support a genetic function of Numb, in collaborating with BMP signaling, to maintain the number and proliferative function of ISCs in adult midguts. The authors used appropriate and sophisticated genetic tools of double RNAi, mutant clonal analysis and dual marker stem cell tracing approaches to ensure the results are reproducible and consistent. The statistical analyses provide confidence that the phenotypic changes are reliable albeit weaker than many other mutants previously studied.

Weaknesses:

In the absence of Numb itself, the midgut has a weak reduction of ISC number (Fig. 3 and 5), as well as weak albeit not statistically significant reduction of ISC clone size/proliferation. I think the authors published similar experiments with BMP pathway mutants. The mad1-2 allele used here as stated below may not be very representative of other BMP pathway mutants. Therefore, it could be beneficial to compare the number of ISC number and clone sizes between other BMP experiments to provide the readers a clearer picture how these two pathways individually contribute (stronger/weaker effects) to the ISC number and gut homeostasis.

The main weakness of this manuscript is the analysis of the BMP pathway components, especially the mad1-2 allele. The mad RNAi and mad1-2 alleles (P insertion) are supposed to be weak alleles and that might be suitable for genetic enhancement assays here together with numb RNAi. However, the mad1-2 allele, and sometime the mad RNAi, showed weakly increased ISC clone size. This is kind of counter-intuitive that they should have a similar ISC loss and ISC clone size reduction.

A much stronger phenotype was observed when numb mutants were subject to treatment of tissue damaging agents Bleomycin, which causes damage in different ways than DSS. Bleomycin as previously shown to be causing mainly enterocyte damage, and therefore disrupt BMP signaling from ECs more likely. Therefore, this treatment together with loss of numb led to highly significant reduction of ISC in clones and reduction of clone size/proliferation. One improvement is that it is not clear whether the authors discussed the nature of the two numb mutant alleles used in this study and the comparison to the strength of the RNAi allele. Because the phenotypes are weak, and more variable, the use of specific reagents is important.

Furthermore, the use of possible activating alleles of either or both pathways to test genetic enhancement or synergistic activation will provide strong support for the claims.

For the revision, the authors have provided detailed responses, comments, and a revised manuscript that together satisfactorily answer all my questions. The manuscript read well and the flow of information is quite clear. I do not have further concerns and support the manuscript moving forward.

Author response:

The following is the authors’ response to the original reviews

Reviewer #1 (Public review):

Summary:

By way of background, the Jiang lab has previously shown that loss of the type II BMP receptor Punt (Put) from intestinal progenitors (ISCs and EBs) caused them to differentiate into EBs, with a concomitant loss of ISCs (Tian and Jiang, eLife 2014). The mechanism by which this occurs was activation of Notch in Put-deficient progenitors. How Notch was upregulated in Put-deficient ISCs was not established in this prior work. In the current study, the authors test whether a very low level of Dl was responsible. But co-depletion of Dl and Put led to a similar phenotype as depletion of Put alone. This result suggested that Dl was not the mechanism. They next investigate genetic interactions between BMP signaling and Numb, an inhibitor of Notch signaling. Prior work from Bardin, Schweisguth and other labs has shown that Numb is not required for ISC self-renewal. However the authors wanted to know whether loss of both the BMP signal transducer Mad and Numb would cause ISC loss. This result was observed for RNAi depletion from progenitors and for mad, numb double mutant clones. Of note, ISC loss was observed in 40% of mad, numb double mutant clones, whereas 60% of these clones had an ISC. They then employed a two-color tracing system called RGT to look at the outcome of ISC divisions (asymmetric (ISC/EB) or symmetric (ISC/ISC or EB/EB)). Control clones had 69%, 15% and 16%, respectively, whereas mad, numb double mutant clones had much lower ISC/ISC (11%) and much higher EB/EB (37%). They conclude that loss of Numb in moderate BMP loss of function mutants increased symmetric differentiation which lead caused ISC loss. They also reported that numb¹⁵ and numb⁴ clones had a moderate but significant increase in ISC-lacking clones compared to control clones, supporting the model that Numb plays a role in ISC maintenance. Finally, they investigated the relevance of these observation during regeneration. After bleomycin treatment, there was a significant increase in ISC-lacking clones and a significant decrease in clone size in numb⁴ and numb¹⁵ clones compared to control clones. Because bleomycin treatment has been shown to cause variation in BMP ligand production, the authors interpret the numb clone under bleomycin results as demonstrating an essential role of Numb in ISC maintenance during regeneration.

Strengths:

(i) Most data is quantified with statistical analysis

(ii) Experiments have appropriate controls and large numbers of samples

(iii) Results demonstrate an important role of Numb in maintaining ISC number during regeneration and a genetic interaction between Mad and Numb during homeostasis.

Weaknesses:

(i) No quantification for Fig. 1

Quantification of Fig.1 has been added. 

(ii) The premise is a bit unclear. Under homeostasis, strong loss of BMP (Put) leads to loss of ISCs, presumably regardless of Numb level (which was not tested). But moderate loss of BMP (Mad) does not show ISC loss unless Numb is also reduced. I am confused as to why numb does not play a role in Put mutants. Did the authors test whether concomitant loss of Put and Numb leads to even more ISC loss than Put-mutation alone.

We have tested the genetic interaction between put and numb using Put RNAi and Numb RNAi driven by esg^ts. According to the results in this study and our previously published data, put mutant clone or esg^ts > Put-RNAi induced a rapid loss of ISC (whin 8 days). We did not observe further enhancement of stem cell loss phenotype in Put and Numb double RNAi guts.

(iii) I think that the use of the word "essential" is a bit strong here. Numb plays an important role but in either during homeostasis or regeneration, most numb clones or mad, numb double mutant clones still have ISCs. Therefore, I think that the authors should temper their language about the role of Numb in ISC maintenance.

We have revised the language and changed “essential” to important”.

Reviewer #2 (Public review):

Summary:

This work assesses the genetic interaction between the Bmp signaling pathway and the factor Numb, which can inhibit Notch signalling. It follows up on the previous studies of the group (Tian, Elife, 2014; Tian, PNAS, 2014) regarding BMP signaling in controlling stem cell fate decision as well as on the work of another group (Sallé, EMBO, 2017) that investigated the function of Numb on enteroendocrine fate in the midgut. This is an important study providing evidence of a Numb-mediated back up mechanism for stem cell maintenance.

Strengths:

(1) Experiments are consistent with these previous publications while also extending our understanding of how Numb functions in the ISC.

(2) Provides an interesting model of a "back up" protection mechanism for ISC maintenance.

Weaknesses:

(1) Aspects of the experiments could be better controlled or annotated:

(a) As they "randomly chose" the regions analyzed, it would be better to have all from a defined region (R4 or R2, for example) or to at least note the region as there are important regional differences for some aspects of midgut biology.

Thank you for the suggestion. In fact, we conducted all the analyses in region 4, we have added statement to clarify this in the revised manuscript.

(b) It is not clear to me why MARCM clones were induced and then flies grown at 18{degree sign}C? It would help to explain why they used this unconventional protocol.

We kept the flies at 18°C to avoid spontaneous clone.

(2) There are technical limitations with trying to conclude from double-knockdown experiments in the ISC lineage, such as those in Figure 1 where Dl and put are both being knocked down: depending on how fast both proteins are depleted, it may be that only one of them (put, for example) is inactivated and affects the fate decision prior to the other one (Dl) being depleted. Therefore, it is difficult to definitively conclude that the decision is independent of Dl ligand.

In our hand, Dl-RNAi is very effective and exhibited loss of N pathway activity (as determined by the N pathway reporter Su(H)-lacZ ) after RNAi for 8 days (Fig. 1D). Therefore, the ectopic Su(H)-lacZ expression in Punt Dl double RNAi (fig. 1E) is unlikely due to residual Dl expression. Nevertheless, we have changed the statement “BMP signaling blocks ligand-independent N activity” to” Loss of BMP signaling results in ectopic N pathway activity even when Dl is depleted”

(3) Additional quantification of many phenotypes would be desired.

(a) It would be useful to see esg-GFP cells/total cells and not just field as the density might change (2E for example).

We focused on R4 region for quantification where the cell density did not exhibit apparent change in different experimental groups. In addition, we have examined many guts for quantification. It is very unlikely that the difference in the esg-GFP+ cell number is caused by change in cell density.

(b) Similarly, for 2F and 2G, it would be nice to see the % of ISC/ total cell and EB/total cell and not only per esgGFP+ cell.

Unfortunately, we didn’t have the suggested quantification. However, we believe that quantification of the percentage of ISC or EB among all progenitor cells, as we did here, provides a meaningful measurement of the self-renewal status of each experimental group.

(c) Fig1: There is no quantification - specifically it would be interesting to know how many esg+ are su(H)lacZ positive in Put- Dl- condition compared to WT or Put- alone. What is the n?

Quantification of Fig.1 has been added. 

(d) Fig2: Pros + cells are not seen in the image? Are they all DllacZ+?

Anti-Pros and anti-E(spl)mβ-CD2 were stained in the same channel (magenta).  Pros+ exhibited “dot-like” nuclear staining while CD2 staining outlined the cell membrane of EBs. We have clarified this in the revised figure legend.

(e) Fig3: it would be nice to have the size clone quantification instead of the distribution between groups of 2 cell 3 cells 4 cell clones.

Because of the heterogeneity of clone size for each genotype, we chose to group clones based on their sizes ( 2, 3-6, 6-8, >8 cells) and quantified the distribution of individual groups for each genotype, which clearly showed an overall reduction in clone size for mad numb double mutant clones. We and others have used the same clone size analysis in previous studies (e.g., Tian and Jiang, eLife 2014).

(f) How many times were experiments performed?

All experiments were performed at least 3 times.

(4) The authors do not comment on the reduction of clone size in DSS treatment in Figure 6K. How do they interpret this? Does it conflict with their model of Bleo vs DSS?

Guts containing numb⁴ clones treated with DSS exhibited a slight reduction of clone size, evident by a higher percentage of 2-cell clones and lower percentage of > 8 cell clones. This reduction is less significant in guts containing numb¹⁵ clones. However, the percentage of Dl⁺-containing clones is similar between DSS and mock-treated guts. It is possible that ISC proliferation is lightly reduced due to numb⁴ mutation or the genetic background of this stock.

(5) There is probably a mistake on sentence line 314 -316 "Indeed, previous studies indicate that endogenous Numb was not undetectable by Numb antibodies that could detect Numb expression in the nervous system".

We have modified the sentence.

Reviewer #3 (Public review):

Summary:

The authors provide an in-depth analysis of the function of Numb in adult Drosophila midgut. Based on RNAi combinations and double mutant clonal analyses, they propose that Numb has a function in inhibiting Notch pathway to maintain intestinal stem cells, and is a backup mechanism with BMP pathway in maintaining midgut stem cell mediated homeostasis.

Strengths:

Overall, this is a carefully constructed series of experiments, and the results and statistical analyses provides believable evidence that Numb has a role, albeit weak compared to other pathways, in sustaining ISC and in promoting regeneration especially after damage by bleomycin, which may damage enterocytes and therefore disrupt BMP pathway more. The results overall support their claim.

The data are highly coherent, and support a genetic function of Numb, in collaborating with BMP signaling, to maintain the number and proliferative function of ISCs in adult midguts. The authors used appropriate and sophisticated genetic tools of double RNAi, mutant clonal analysis and dual marker stem cell tracing approaches to ensure the results are reproducible and consistent. The statistical analyses provide confidence that the phenotypic changes are reliable albeit weaker than many other mutants previously studied.

Weaknesses:

In the absence of Numb itself, the midgut has a weak reduction of ISC number (Fig. 3 and 5), as well as weak albeit not statistically significant reduction of ISC clone size/proliferation. I think the authors published similar experiments with BMP pathway mutants. The mad^1-2 allele used here as stated below may not be very representative of other BMP pathway mutants. Therefore, it could be beneficial to compare the number of ISC number and clone sizes between other BMP experiments to provide the readers with a clearer picture of how these two pathways individually contribute (stronger/weaker effects) to the ISC number and gut homeostasis.

Thanks for the comment. We have tested other components of BMP pathway in our previously study (Tian et al., 2014). More complete loss of BMP signaling (for example, Put clones, Put RNAi, Tkv/Sax double mutant clones or double RNAi) resulted in ISC loss regardless the status of numb, suggesting a more predominant role of BMP signaling in ISC self-renewal compared with Numb. We speculate that the weak stem cell loss phenotype associated with numb mutant clones in otherwise wild type background could be due to fluctuation of BMP signaling in homeostatic guts.

The main weakness of this manuscript is the analysis of the BMP pathway components, especially the mad^1-2 allele. The mad RNAi and mad^1-2 alleles (P insertion) are supposed to be weak alleles and that might be suitable for genetic enhancement assays here together with numb RNAi. However, the mad^1-2 allele, and sometimes the mad RNAi, showed weakly increased ISC clone size. This is kind of counter-intuitive that they should have a similar ISC loss and ISC clone size reduction.

We used mad^1-2 and mad RNAi here to test the genetic interaction with numb because our previous studies showed that partial loss of BMP signaling under these conditions did not cause stem cell loss, therefore, may provide a sensitized background to determine the role of Numb in ISC self-renewal. The increased proliferation of ISC/ clone size associated with mad^1-2 and mad RNAi is due to the fact that reduction of BMP signaling in either EC or EB non-autonomously induces stem cell proliferation. However, in mad numb double mutant clones, there was a reduction in clone size due to loss of ISC in many clones.

A much stronger phenotype was observed when numb mutants were subject to treatment of tissue damaging agents Bleomycin, which causes damage in different ways than DSS. Bleomycin as previously shown to be causing mainly enterocyte damage, and therefore disrupt BMP signaling from ECs more likely. Therefore, this treatment together with loss of numb led to a highly significant reduction of ISC in clones and reduction of clone size/proliferation. One improvement is that it is not clear whether the authors discussed the nature of the two numb mutant alleles used in this study and the comparison to the strength of the RNAi allele. Because the phenotypes are weak and more variable, the use of specific reagents is important.

We have included information about the two numb alleles in the “Materials and Methods”. numb¹⁵ is a null allele, and the nature of numb⁴ has not been elucidated. According to Domingos, P.M. et al., numb¹⁵ induced a more severe phenotype than numb⁴ did. Consistently, we also found that more numb¹⁵ mutant clones were void of stem cell than numb⁴ mutant clones.

Furthermore, the use of possible activating alleles of either or both pathways to test genetic enhancement or synergistic activation will provide strong support for the claims.

Activation of BMP (esgts>Tkv^CA) alone induced stem cell tumor (Tian et al., 2014) whereas overexpression of Numb did not induce increase stem cell number although overexpression of Numb in wing discs produced phenotypes indictive of inhibition of N (our unpublished observation), making it difficult to test the synergistic effect of activating both BMP and Numb.

Reviewer #1 (Recommendations for the authors):

- Cartoon of RGT in Fig 4 needs to be improved. We need to know what chromosome harbors the esgts. It is not sufficient to simply put the location of the ubi-GFP and ubi-RFP (on 19A) and not show the location of other components of the RGT system.

Thank you for the suggestion. We have revised the cartoon in Fig. 4 to include all three pairs of chromosomes and indicate where the esgts driver and UAS-RNAi are located. In addition, we have included the genotypes for all the genetic experiments in the Method section.

- Quantification of the results in Fig. 1

Quantification of Fig.1 has been added. 

- The authors need to explain the premise more carefully (see above) and explain whether or not they tested put, numb double knockdowns.

We have explained why not testing put numb double RNAi (see above).

Reviewer #2 (Recommendations for the authors):

The number of times the experiments have been performed would be useful to include.

This information has been added in the figure legends.

eLife Assessment

This valuable study shows that an odorant that is typically thought of as a repellant actually activates both attractant and repellant olfactory neurons in C. elegans. Solid evidence is provided that nematode worms can integrate signals using different pathways to drive different behavioral responses to the same cue. These findings will be of interest to scientists interested in combinatorial coding in sensory systems.

Reviewer #1 (Public review):

The authors investigated the response of worms to the odorant 1-octanol (1-oct) using a combination of microfluidics-based behavioral analysis and whole-network calcium imaging. They hypothesized that 1-oct may be encoded through two simultaneous, opposing afferent pathways: a repulsive pathway driven by ASH, and an attractive pathway driven by AWC. And the ultimate chemotactic outcome is likely determined by the balance between these two pathways.

It is not surprising that 1-octanol is encoded as attractive at low concentrations and repulsive at higher concentrations. However, the novel aspect of this study is the discovery of the combinatorial coding of 1-oct in the periphery, where it serves as both an attractant and a repellent. Furthermore, the study uses this dual encoding as a model to explore the neural basis of sensory-driven behaviors at a whole-network scale in this organism. The basic conclusions of this study are well supported by the behavioral and imaging experiments, though there are certain aspects of the manuscript that would benefit from further clarification.

A key issue is that several previous studies have demonstrated a combinatorial and concentration-dependent coding of odorant sensing in the nematode peripheral nervous system. Specifically, ASH and AWC are the primary receptors for repellent and attractive responses, respectively. However, other neurons such as AWB, AWA, and ADL are also involved in the coding process. These neurons likely communicate with different interneurons to contribute to 1-oct-induced outputs. The authors' conclusion that loss of tax-4 reduces attractive responses and that osm-9 mutants reduce repulsive responses is not entirely convincing. TAX-4 is required for both AWC (an attractive neuron) and AWB (a repulsive neuron), and osm-9 is essential for ASH, ADL, and AWA (attraction-associated). Therefore, the observed effects on the attractive and repulsive responses could be more complex. Additionally, the interpretation of results involving the use of IAA to reduce the contribution of AWC at lower concentrations lacks clarity. A more effective approach might involve using transgenically expressed miniSOG or histamine (HisCl1) to specifically inhibit AWC neurons.

The authors did not observe any increased correlation between motor command interneurons and sensory neurons, which is consistent with the absence of a consistent relationship between state transitions and 1-oct application. Furthermore, they did not observe significant entrainment of AIB activity with the 2.2 mM 1-oct application. This might be due to the animals being anesthetized with 1 mM tetramisole hydrochloride, which could affect neural activity and/or feedback from locomotion. It is unclear whether subtracting AVA activity from AIB activity provides a valid measure. Similarly, it is unclear how the behavioral data from freely moving worms compares to the whole-network calcium imaging results obtained from immobilized worms.

Reviewer #2 (Public review):

Summary:

The authors used whole-network imaging to identify sensory neurons that responded to the repellant 1-octanol. While several olfactory neurons responded to the initial onset of odor pulses, two neurons consistently responded to all the pulses, ASH and AWC. ASH typically activates in response to repellants, and AWC typically activates in response to the removal of attractants. However, in this case, AWC activated in response to the removal of 1-octanol, which was unexpected because 1-octanol is a harmful repellant to the worm. The authors further investigated this phenomenon by testing different concentrations of 1-octanol in a chemotaxis assay and found that at lower (less harmful) concentrations the odor is actually an attractant, but becomes repulsive at higher concentrations. The amplitude of the ASH response appeared to be modulated by concentration, but this was not true for AWC. The authors propose a model where the behavioral response of the worm is the result of integrating these two opposing drives, where repulsion is a result of the increased ASH activity overriding the positive drive from AWC. The authors further tested this theory by testing mutants that ablated the AWC response (tax-4) or ASH response (osm-9), which produced results consistent with their hypothesis. While the interneuron(s) that integrate these signals to influence behavior were not identified, the authors did find that increasing concentrations of 1-octanol did increase the likelihood of AVA activity, a neuron that drives reversals (and hence, behavioral repulsion).

Strengths:

This was simple and elegant work that identified specific neurons of interest which generated a hypothesis, which was further tested with mutants that altered neuronal activity. The authors performed both neuronal imaging and behavioral experiments to verify their claims.

Weaknesses:

tax-4, but not osm-9 mutants were used in chemotaxis and imaging assays. It would have been nice to have osm-9 results as well for these assays. The mutants are not specific to AWC and ASH. Cell-specific rescue of these neurons would have strengthened the proposed model.

Reviewer #3 (Public review):

Summary:

This work describes how two chemosensory neurons in C. elegans drive opposite behaviors in response to a volatile cue. Because they have different concentration dependencies, this leads to different behavioral responses (attraction at low concentration and repulsion at high concentration). It has been known that many odorants that are attractive at low concentrations are aversive at high concentrations, and the implicated neurons (at least AWC for attraction and ASH for repulsion) have been well established. Nonetheless, studying behavior and neural responses in a common context (odor pulses, as opposed to gradients) provides a clear picture of how these sensory neurons may guide the dose-dependent response by separately modulating odor entry and odor exit behaviors.

Strengths:

(1) There is good evidence that worms are attracted to low concentrations and repelled by high concentrations of 1-oct. Calcium imaging also makes it clear that dose dependence is stronger for ASH than AWC.

(2) There is good evidence for conc. dependent responses via ASH (Figure 4E) and attractive inhibition via tonic IAA (Figure 7A).

(3) This work presents calcium imaging and behavior with the same stimulus (sudden pulses in volatile odor concentration), while previous studies often focus on using neuronal responses to pulses to understand the navigation of gentle gradients.

Weaknesses:

(1) It is not clear precisely how important AWC is (compared to other cells) for the attractive response, though the presence of odor-off behavior implicates it. This could be resolved by looking at additional mutants (tax-4 is broad).

(2) Relatedly, dose-dependent chemotaxis data (Figure 4C, D) should be provided for osm-9 animals to get a sense of the degree to which dose-dependence is explained by ASH.

(3) Figure 4A, B should include average traces with errors, as there are several ways the responses can vary across conditions.

(4) The data in Figure 6G does not appear to have error bars. Also, it would help to include a more conventional demonstration of AIB responding to stimuli (e.g. averaging stimulus-aligned responses as a percent of the fluorescence value at stimulus onset to perform the desired subtraction). Subtracted calcium traces are harder to interpret. As it stands, the evidence that sensory signals are persisting in AIB and not being shunted by proprioceptive feedback in microfluidic devices is not strong.

Author response:

We thank the reviewers for their thoughtful comments on our submitted manuscript.

The major point from all three reviewers was that the sensory inputs may be more complex than simply ASH and AWC, since mutations in osm-9 and tax-4 will affect many more sensory neurons. We fully agree. The differential effects of osm-9 and ta_x-_4 allowed us to recognize that there were two distinct afferent pathways operating simultaneously, mediating repulsion and attraction separately. However, it remains to be determined which sensory neurons are contributing to each pathway. We have planned a full analysis of the sensory inputs, not limited to just ASH and AWC, using neuron-specific rescue and neuron-specific chemogenetic inactivation (using HisCl1). While this analysis falls outside the scope of the present study, we will perform the inactivations of ASH and AWC and include the data for the revised version of this study. We expect to demonstrate whether ASH and AWC inputs are sufficient or whether other sensory neurons make significant contributions. Additionally, we will include chemotaxis dose-response data for osm-9 mutants as part of this analysis and make the minor corrections in data presentation requested.

eLife Assessment

This valuable study sets new standards in analyzing the ultrastructure of insect eyes, which have long served as models for understanding how vision works. The way it describes an entire eye with the resolution of electron microscopy is convincing. On top of this, a miniaturized visual system provides additional, remarkable insights towards understanding optimized solutions.

eLife Assessment

This valuable study sets new standards in analyzing the ultrastructure of insect eyes, which have long served as models for understanding how vision works. The way it describes an entire eye with the resolution of electron microscopy is convincing. On top of this, a miniaturized visual system provides additional, remarkable insights towards understanding optimized solutions.

Reviewer #2 (Public review):

Summary:

Makarova et al. provide the first complete cellular-level reconstruction of an insect eye. They use the extremely miniaturized parasitoid wasp, Megaphragma viggiani and apply improved and optimized volumetric EM methods they can describe, the size, volume and position of every single cell in the insect compound eye.

This data has previously only been inferred from TEM cross-sections taken in different parts of the eye, but in this study and in the associated 3d datasets video and stacks, one can observe the exact position and orientation in 3D space.<br /> The authors have made a very rigorous effort to describe and assess the variation in each cell type and have also compared two different classes of dorsal rim and non-dorsal rim ommatidia and the associated visual apparatus for each, confirming previous known findings about the distribution and internal structure that assists in polarization detection in these insects.

Strengths:

The paper is well written and strives to compare the data with previous literature wherever possible and goes beyond cell morphology, calculating the optical properties of the different ommatidia and estimating light sensitivity and spatial resolution limits using rhabdom diameter, focal length and showing how this varies across the eye.

Finally, the authors provide very informative and illustrative videos showing how the cones, lenses, photoreceptors, pigment cells, and even the mitochondria are arranged in 3D space, comparing the structure of the dorsal rim and non-dorsal rim ommatidia. They also describe three 'ectopic' photoreceptors in more anatomical detail providing images and videos of them.

Comments on revisions:

The updates improve the manuscript.

Reviewer #3 (Public review):

Summary:

The article presents a meticulous and quantitative anatomical reconstruction of the compound eye of a tiny wasp at the level of subcellular structures, cellular and optical organization of the ommatidia and reveals the ectopic photoreceptors, which are decoupled from the eye's dioptrical apparatus.

Strengths:

The graphic material is of very high quality, beautifully organized and presented in a logical order. The anatomical analysis is fully supported by quantitative numerical data at all scales, from organelles to cells and ommatidia, which should be a valuable source for future studies in cellular biology and visual physiology. The 3D renders are highly informative and a real eye candy.

Weaknesses:

The claim that the large dorsal part of the eye is the dorsal rim area (DRA), supported by anatomical data on rhabdomere geometry and connectomics in authors' earlier work, would eventually greatly benefit from additional evidence, obtained by other methods.

Comments on revisions:

Thank you for considering my remarks and advice. All is fine.

Author response:

The following is the authors’ response to the original reviews

Public reviews:

Reviewer #1:

Weaknesses:

As this paper only uses anatomical analyses, no functional interpretations of cell function are tested.

The aim of this paper was to describe the ultrastructural organization of compound eyes in the extremely small wasp Megaphragma viggianii. The authors successfully achieved this aim and provided an incredibly detailed description of all cell types with respect to their location, volume, and dimensions. As this is the first of its kind, the results cannot easily be compared with previous work. The findings are likely to be an important reference for future work that uses similar techniques to reconstruct the eyes of other insect species. The FIB-SEM method used is being used increasingly often in structural studies of insect sensory organs and brains and this work demonstrates the utility of this method.

We thank you for your high assessment of our work. Unfortunately, it is hard to test our functional interpretations and check them with electrophysiological methods due to the extremely small size of the animal. Studies on three-dimensional ultrastructural datasets obtained using vEM have just started to appear, and we hope that a lot of data will become available for comparison in the nearest future.

Reviewer #2:

Thank you for your work and for your high assessment of our manuscript.

Reviewer #3:

Weaknesses:

The claim that the large dorsal part of the eye is the dorsal rim area (DRA), supported by anatomical data on rhabdomere geometry and connectomics in authors' earlier work, would eventually greatly benefit from additional evidence, obtained by immunocytochemical staining, that could also reveal a putative substrate for colour vision. The cell nuclei that are located in the optical path in the DRA crystalline cone have only a putative optical function, which may be either similar to pore canals in hymenopteran DRA cornea (scattering) or to photoreceptor nuclei in camera-type eyes (focussing), both explanations being mutually exclusive.

We thank the Reviewer for high assessment of our study and for detailed analysis of our manuscript. Your comments and recommendations are very valued and helped us to improve the text. We understand that immunocytochemical methods could improve our findings and supply additional evidence, but there is no technical possibility for this in present. Megaphragma is a very complicated model organism for such methods. We are currently working on the optimization of the protocol for staining, which is needed because of the high level of autoluminescence and because of insufficient penetration of dyes into the samples.

Recommendations for the authors:

Reviewer #1:

I do not have any major concerns about the content of the paper.

There are some minor spelling and grammatical errors throughout the text but these can be identified most readily using a spelling/grammar check.

We have revised the text, checked the spelling, and fixed the grammatical errors throughout the text.

I suggest consistency when referring to the capitalization of the term 'non-DRA' as it is sometimes 'Non-DRA' in the text.

We have fixed the term “non-DRA” throughout the text. Thank you.

Also, check carefully the spelling of headings in the tables as there are a few mistakes in Table 1 and 5 in particular.

The grammar errors have been fixed.

Figure 7 legend: an explanation of the abbreviation RPC should be added.

We have done so.

Reviewer #2:

(1) The paper presents the data in great detail, however, since this is the first time the technique has been applied to get whole insect eyes, even if on a small insect, it would be worth outlining in the methods section what innovations in the staining/ scanning or sample preparation allowed these improvements and a roadmap for extending this method to larger insects if possible.

The whole method, including sample preparation, staining, and scanning, was described in our previous paper (Polilov et al., 2021), where it was presented in every detail. Due to the complicated methodology we suppose that it is not necessary to include all the stages of the technique in the present paper, and thus described it more briefly.

(2) The optical modelling needs a statement in the discussion providing a disclaimer on parameters like sensitivity, anatomical measurements can provide limits and some measure, but the inherent optics are also key and it is worth qualifying these as only estimates and measurements that give a sense of the variation in morphology, only coupled with optical and potentially neural measurements could one confirm the true sensitivity and acceptance angle.

In the absence of experimental data or precise computational models of Megaphragma vision, we try to discuss rather carefully the functions of structures based on their morphology, ultrastructure, first-order visual connectome, and analogies with other species. This is reflected in the methods and those sections of our paper that contain functional interpretations.

Reviewer #3

(1) The finding that the CNS neurons are enucleated, while the compound eye contains cell nuclei, deserves another word. I would confidentially say that the optical demands of a miniaturized compound eye (the minimal size of the optics due to diffraction, the rhabdomere size, and the minimal thickness of optically insulating granules) are such that further cellular miniaturization is not possible, and the minimal sizes even render the cells that build the eye sufficiently large to accommodate cell nuclei. This is in my opinion a parsimonious explanation, yet speculative and I leave it up to you to embrace it or not.

We agree with the Reviewer and understand the limiting factors and the optical demands of a miniaturized compound eye. According to our data, nuclei occupy a considerable volume in the eye (in the cells of compound eye there are more nuclei than in the whole brain), and on average the cell volume is larger than in Trichogramma, which is minute, but larger than Megaphragma. But as the Reviewer rightly assumed, it is speculative; therefore, we would like to avoid it.

(2) Our current understanding of DRA optics and function is limited and I claim that your interpretation of the cell nuclei in the DRA dioptrical apparatuses is inappropriate. Please consider a few articles on hymenopteran DRA, starting with the one below and the citing literature:

Meyer, E.P., Labhart, T. Pore canals in the cornea of a functionally specialized area of the honey bee's compound eye. Cell Tissue Res. 216, 491-501 (1981). https://doi.org/10.1007/BF00238646

Honebyee DRA has a milky appearance under a stereomicroscope and can be discerned from the outside. This is due to pore canals in the cornea. I happen to be studying this exact structure and its function right now. I found that the result of those canals is not so much the extended receptor acceptance angles, but rather a minimized light gain. This is counterintuitive, but think of the following. The DRA photoreceptors must encode the limited range of polarization contrasts with a maximal working dynamic range (= voltage) of the photoreceptors, which results in a very steep stimulus-response curve.

Physiologically such a curve is due to very high transduction gain and a high cell input resistance. In most of the retina, small contrasts are transcoded by LMC neurons, but DRA receptors are long visual fibres and must do the job themselves. The skylight intensity (especially antisolar, where the polarized pattern is maximal) varies little during the day. Hence, the DRA receptors work almost at a fixed intensity range. In order to prevent receptor saturation and keep steep contrast coding, the corneal lenses in DRA have a built-in diffusor ring, which diminishes the light influx. Unfortunately, I have yet to publish this and I may be wrong, of course. But if I look into your data, I see consistently smaller corneal lenses and crystalline cones in the DRA, plus the cell nuclei obstructing the incident light. I think this is similar to the optics of honeybee DRA.

You do not support your claim that the nuclei additionally focus light by optical calculations, but cite literature on camera-type eyes, which is not OK.

In any case, I think it is fair to limit the discussion by saying that the nuclei may have an optical role. Further evidence from hymenopteran and vertebrate literature is controversial. “so that the nuclei act as extra collecting lenses, as was reported for rod cells of nocturnal vertebrates (Solovei et al., 2009; Błaszczak et al., 2014)” - please consider omitting this.

We thank the Reviewer for this piece of advice. And we have rewritten the text, to omit the comparison with vertebrates, but left the citation as an illustration of the fact that nuclei could perform the optical role.

“Since the nuclei in DRA and non-DRA ommatidia are arranged differently in cone cells, we suggest that the nuclei of the cone cells of DRA ommatidia in M. viggianii perform some optical role, facilitating the specialization of this group of ommatidia. The optical function for nuclei was described for rod cells of nocturnal vertebrates, where chromatin inside the cell nucleus has a direct effect on light propagation (Solovei et al., 2009; Błaszczak et al., 2014; Feodorova et al., 2020).”

(3) Please consider comparing the structure and function of ectopic receptors with the eyelet in Drosophila (i.e. https://doi.org/10.1523/JNEUROSCI.22-21-09255.2002 )

We thank the Reviewer for this advice and have included the comparison fragment into the text:

“The position of ePR, their morphology and synaptic targets look similar to the eyelet (extraretinal photoreceptor cluster) discovered in Drosophila (Helfrich-Förster et al., 2002). Eyelets are remnants of the larval photoreceptors, Bolwig’s organs in Drosophila (Hofbauer, Buchner, 1989). Unlike Drosophila, Trichogrammatidae are egg parasitoids and their central nervous system differentiation is shifted to the late larva and even early pupa (Makarova et al., 2022). According to the available data on the embryonic development of Trichogrammatidae, no photoreceptors cells were found during the larval stages (Ivanova-Kazas, 1954, 1961).”

According to this, the analogy question remains open.

(4) Minor remarks:

“but also to trace the pathways that connect the analyzer with the brain.” - I find the word analyzer a bit stretched here; sure, the DRA is polarization analyzer, but if the main retina was monochromatic, it would only be a detector, not an analyzer.

The sentence was changed according to the Reviewer’s advice.

Table I: thikness -> thickness, wigth -> width

We have fixed these misprints.

“The cross-section of Non-DRA ommatidia has a strongly spherical shape” - perhaps circular, not spherical. And not necessary to say “strongly”

The spelling was changed according to the Reviewer’s advice.

“which can be rarely visualized in the cell's projections not far from the basement membrane.” - I'd suggest saying “which are nearly absent in retinula axons”

The spelling was changed according to the Reviewer’s advice.

“The pigment granules of the retinula cells have an elongated nearly oval shape” - please consider replacing 'elongated nearly oval' with 'prolate' (try googling for “prolate” or “oblate spheroids”; the adjective describes precisely what you wanted to say)

We thank the Reviewer for this piece of advice but prefer to leave our original phrasing, because it is more readily understandable.

“The results of our morphological analysis of all ommatidia in Megaphragma are consistent with the light-polarization related features in Hymenoptera and other insects” - please add citations, see my comment on the DRA above.

We have added the citations according to the Reviewer’s advice.

“The group of short PRs (R1-R6)” - please consider renaming into “short visual fibre photoreceptors” (as opposed to “long visual fibre PRs”; hence SVFs and LVFs). This naming is quite common.

The naming was changed according to the Reviewer’s advice.

“The total rhabdom shortening in M. viggianii ommatidia probably favors polarization and absolute sensitivity,” - please see comments on DRA. Wide rhabdom means also a wider acceptance angle.

Shortening of DRA rhabdoms does not result in their widening compared to other rhabdoms, so it is difficult to say how this may be related to sensitivity. The comments on DRA given earlier have been taken into account.

“Ommatidia located across the diagonal area of the eye are more sensitive to light” - I don't understand what is diagonal area.

We have deleted the sentence.

“Estimated optical sensitivity of the eyes very close to those reported for diurnal hymenopterans with apposition eyes (Greiner et al., 2004; Gutiérrez et al., 2024) and possess around 0.19 {plus minus} 0.04 μm2 sr. M. viggianii have reasonably huge values of acceptance angle Δρ, and thus should result in a low spatial resolution” - please correct English here. “eyes IS very close”, “should result in a low”

The grammatical errors were fixed.

Table 6 legend: “SPC - secondary pigment cells.” -> “SPC – secondary pigment cells.”

Citation “(Makarova et al., 2025).” - probably 2015

The typos were fixed.

Methods, FIB-SEM: I can't understand the sentence “The volumetric data of lenses and cones, some linear measurements (lens thickness, cone length, cone width, curvature radius) and to visualize the complete 3D-model of eye we use (measure or reconstruct) the elements from another eye (left).”

The sentence is a continuation of the previous one. We have rewritten it as follows to clarify the meaning and move it to the 3D reconstruction section:

“The right eye, on which the reconstruction was performed, has several damaged regions from milling (see Appendix 1С), which hinder the complete reconstructions of lenses and cones on a few ommatidia. According to this, for the volumetric data on lenses and cones, some linear measurements (lens thickness, cone length, cone width, curvature radius), we use (measure or reconstruct) the corresponding elements from the other (left) eye.”

“The cells of single interfacet bristles were not reconstructed, because of damaging on right eye and worst quality of section on the left.” - please change to “The cells of the single interfacet bristle were not reconstructed, because of damage to the right eye and inferior quality of the sections of the left eye.”

The text has been changed as follows:

“The cells of single interfacet bristles were not reconstructed, because of the damage present in the right eye and because of the generally lower quality of this region on the left eye.”

“Morphometry. Each ommatidia was” -> “Morphometry. Each ommatidium was”

The grammatical error has been fixed.

eLife Assessment

This important study combines convincing evolution experiments with molecular and genetic techniques to study how a genetic lesion in MreB that causes rod-shaped cells to become spherical, with concomitant deleterious fitness effects, can be rescued by natural selection. The detailed mechanistic investigation increases our understanding of how mreB contributes to cell wall synthesis and shows how compensatory mutations may reestablish its homogeneity.

Reviewer #1 (Public review):

Summary:

The authors performed experimental evolution of MreB mutants that have a slow growing round phenotype and studied the subsequent evolutionary trajectory using analysis tool from molecular biology. It was remarkable and interesting that they found that the original phenotype was not restored (most common in these studies) but that the round phenotype was maintained.

Strengths:

The finding that the round phenotype was maintained during evolution rather than that the original phenotype, rod shape cells, was recovered is interesting. The paper extensively investigates what happens during adaptation with various different techniques. Also the extensive discussion of the findings at the end of the paper is well thought through and insightful.

Reviewer #3 (Public review):

This paper addresses a long-standing problem in microbiology: the evolution of bacterial cell shape. Bacterial cells can take a range of forms, among the most common being rods and spheres. The consensus view is that rods are the ancestral form and spheres the derived form. The molecular machinery governing these different shapes is fairly well understood but the evolutionary drivers responsible for the transition between rods and spheres is not. Enter Yulo et al.'s work. The authors start by noting that deletion of a highly conserved gene called MreB in the Gram-negative bacterium Pseudomonas fluorescens reduces fitness but does not kill the cell (as happens in other species like E. coli and B. subtilis) and causes cells to become spherical rather than their normal rod shape. They then ask whether evolution for 1000 generations restores the rod shape of these cells when propagated in a rich, benign medium.

The answer is no. The evolved lineages recovered fitness by the end of the experiment, growing just as well as the unevolved rod-shaped ancestor, but remained spherical. The authors provide an impressively detailed investigation of the genetic and molecular changes that evolved. Their leading results are:

(1) The loss of fitness associated with MreB deletion causes high variation in cell volume among sibling cells after cell division;<br /> (2) Fitness recovery is largely driven by a single, loss-of-function point mutation that evolves within the first ~250 generations that reduces the variability in cell volume among siblings;<br /> (3) The main route to restoring fitness and reducing variability involves loss of function mutations causing a reduction of TPase and peptidoglycan cross-linking, leading to a disorganized cell wall architecture characteristic of spherical cells.

The inferences made in this paper are on the whole well supported by the data. The authors provide a uniquely comprehensive account of how a key genetic change leads to gains in fitness and the spectrum of phenotypes that are impacted and provide insight into the molecular mechanisms underlying models of cell shape.

Author response:

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

As to the exceptionally minor issue, namely, correction for multiple statistical tests (minor because the data and the error are presented in the text). We have now conducted one-way ANOVA to back the data displayed in Fig 4A., and Supp. Figs 19 and 21. In each case ANOVA revealed a highly significant difference among means: Dunnett’s post hoc test was then used to test each result against SBW25, with the multiple comparisons corrected for in the analysis.

This resulted in changes to the description of the statistical analysis in the following captions:

To Figure 4.

Where we previously referred to paired t-tests we now state:  ANOVA revealed a highly significant difference among means [F_7,16 = 8.19, p < 0.001] with Dunnett’s post-hoc test adjusted for multiple comparisons showing that five genotypes (*) differ significantly (p < 0.05) from SBW25.

To Supplementary Figure 19.

Where we previously referred to paired t-tests we now state: ANOVA revealed a highly significant difference among means [F_7,16 = 16.74, p < 0.001] with Dunnett’s post-hoc test adjusted for multiple comparisons showing that three genotypes (*) differ significantly (p < 0.05) from SBW25.

To Supplementary Figure 21.

Where we previously referred to paired t-tests we now state:  ANOVA revealed a highly significant difference among means [F_7,89 = 9.97, p < 0.0001] with Dunnett’s post-hoc test adjusted for multiple comparisons showing that SBW25 ∆mreB and SBW25 ∆PFLU4921-4925 are significantly different (*) from SBW25 (p < 0.05).

---

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

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

The authors performed experimental evolution of MreB mutants that have a slow-growing round phenotype and studied the subsequent evolutionary trajectory using analysis tools from molecular biology. It was remarkable and interesting that they found that the original phenotype was not restored (most common in these studies) but that the round phenotype was maintained. 

Strengths: 

The finding that the round phenotype was maintained during evolution rather than that the original phenotype, rod-shaped cells, was recovered is interesting. The paper extensively investigates what happens during adaptation with various different techniques. Also, the extensive discussion of the findings at the end of the paper is well thought through and insighXul. 

Weaknesses: 

I find there are three general weaknesses: 

(1) Although the paper states in the abstract that it emphasizes "new knowledge to be gained" it remains unclear what this concretely is. On page 4 they state 3 three research questions, these could be more extensively discussed in the abstract. Also, these questions read more like genetics questions while the paper is a lot about cell biological findings. 

Thank you for drawing attention to the unnecessary and gratuitous nature of the last sentence of the Abstract. We are in agreement. It has been modified, and we have taken  advantage of additional word space to draw attention to the importance of the two competing (testable) hypotheses laid out in the Discussion. 

As to new knowledge, please see the Results and particularly the Discussion. But beyond this, and as recognised by others, there is real value for cell biology in seeing how (and whether) selection can compensate for effects that are deleterious to fitness. The results will very o_en depart from those delivered from, for example, suppressor analyses, or bottom up engineering. 

In the work recounted in our paper, we chose to focus – by way of proof-of principle – on the most commonly observed mutations, namely, those within pbp1A.  But beyond this gene, we detected mutations  in other components of the cell shape / division machinery whose connections are not yet understood and which are the focus of on-going investigation.  

As to the three questions posed at the end of the Introduction, the first concerns whether selection can compensate for deleterious effects of deleting mreB (a question that pertains to evolutionary aspects); the second seeks understanding of genetic factors; the third aims to shed light on the genotype-to-phenotype map (which is where the cell biology comes into play).  Given space restrictions, we cannot see how we could usefully expand, let alone discuss, the three questions raised at the end of the Introduction in restrictive space available in the Abstract.   

(2) It is not clear to me from the text what we already know about the restoration of MreB loss from suppressors studies (in the literature). Are there suppressor screens in the literature and which part of the findings is consistent with suppressor screens and which parts are new knowledge?  

As stated in the Introduction, a previous study with B. subtilis (which harbours three MreB isoforms and where the isoform named “MreB” is essential for growth under normal conditions), suppressors of MreB lethality were found to occur in ponA, a class A penicillin binding protein (Kawai et al., 2009). This led to recognition that MreB plays a role in recruiting Pbp1A to the lateral cell wall. On the other hand, Patel et al. (2020) have shown that deletion of classA PBPs leads to an up-regulation of rod complex activity. Although there is a connection between rod complex and class A PBPs, a further study has shown that the two systems work semi-autonomously (Cho et al., 2016). 

Our work confirms a connection between MreB and Pbp1A, and has shed new light on how this interaction is established by means of natural selection, which targets the integrity of cell wall. Indeed, the Rod complex and class A PBPs have complementary activities in the building of the cell wall with each of the two systems able to compensate for the other in order to maintain cell wall integrity. Please see the major part of the Discussion. In terms of specifics, the connection between mreB and pbp1A (shown by Kawai et al (2009)) is indirect because it is based on extragenic transposon insertions. In our study, the genetic connection is mechanistically demonstrated.  In addition, we capture that the evolutionary dynamics is rapid and we finally enriched understanding of the genotype-to-phenotype map.

(3) The clarity of the figures, captions, and data quantification need to be improved.  

Modifications have been implemented. Please see responses to specific queries listed below.

Reviewer #2 (Public Review): 

Yulo et al. show that deletion of MreB causes reduced fitness in P. fluorescens SBW25 and that this reduction in fitness may be primarily caused by alterations in cell volume. To understand the effect of cell volume on proliferation, they performed an evolution experiment through which they predominantly obtained mutations in pbp1A that decreased cell volume and increased viability. Furthermore, they provide evidence to propose that the pbp1A mutants may have decreased PG cross-linking which might have helped in restoring the fitness by rectifying the disorganised PG synthesis caused by the absence of MreB. Overall this is an interesting study. 

Queries: 

Do the small cells of mreB null background indeed have have no DNA? It is not apparent from the DAPI images presented in Supplementary Figure 17. A more detailed analysis will help to support this claim. 

It is entirely possible that small cells have no DNA, because if cell division is aberrant then division can occur prior to DNA segregation resulting in cells with no DNA. It is clear from microscopic observation that both small and large cells do not divide. It is, however, true, that we are unable to state – given our measures of DNA content – that small cells have no DNA. We have made this clear on page 13, paragraph 2.

What happens to viability and cell morphology when pbp1A is removed in the mreB null background? If it is actually a decrease in pbp1A activity that leads to the rescue, then pbp1A- mreB- cells should have better viability, reduced cell volume and organised PG synthesis. Especially as the PG cross-linking is almost at the same level as the T362 or D484 mutant.  

Please see fitness data in Supp. Fig. 13. Fitness of ∆mreB ∆pbp1A is no different to that caused by a point mutation. Cells remain round.  

What is the status of PG cross-linking in ΔmreB Δpflu4921-4925 (Line 7)? 

This was not analysed as the focus of this experiment was PBPs. A priori, there is no obvious reason to suspect that ∆4921-25 (which lacks oprD) would be affected in PBP activity.

What is the morphology of the cells in Line 2 and Line 5? It may be interesting to see if PG cross-linking and cell wall synthesis is also altered in the cells from these lines. 

The focus of investigation was restricted to L1, L4 and L7. Indeed, it would be interesting to look at the mutants harbouring mutations in :sZ, but this is beyond scope of the present investigation (but is on-going). The morphology of L2 and L5 are shown in Supp. Fig. 9.

The data presented in 4B should be quantified with appropriate input controls. 

Band intensity has now been quantified (see new Supp. Fig .20). The controls are SBW25, SBW25∆pbp1A, SBW25 ∆mreB and SBW25 ∆mreBpbp1A as explained in the paper.

What are the statistical analyses used in 4A and what is the significance value? 

Our oversight. These were reported in Supp. Fig. 19, but should also have been presented in Fig. 4A. Data are means of three biological replicates. The statistical tests are comparisons between each mutant and SBW25, and assessed by paired t-tests.  

A more rigorous statistical analysis indicating the number of replicates should be done throughout. 

We have checked and made additions where necessary and where previously lacking. In particular, details are provided in Fig. 1E, Fig. 4A and Fig. 4B. For Fig. 4C we have produced quantitative measures of heterogeneity in new cell wall insertion. These are reported in Supp. Fig. 21 (and referred to in the text and figure caption) and show that patterns of cell wall insertion in ∆mreB are highly heterogeneous.

Reviewer #3 (Public Review): 

This paper addresses an understudied problem in microbiology: the evolution of bacterial cell shape. Bacterial cells can take a range of forms, among the most common being rods and spheres. The consensus view is that rods are the ancestral form and spheres the derived form. The molecular machinery governing these different shapes is fairly well understood but the evolutionary drivers responsible for the transition between rods and spheres are not. Enter Yulo et al.'s work. The authors start by noting that deletion of a highly conserved gene called MreB in the Gram-negative bacterium Pseudomonas fluorescens reduces fitness but does not kill the cell (as happens in other species like E. coli and B. subtilis) and causes cells to become spherical rather than their normal rod shape. They then ask whether evolution for 1000 generations restores the rod shape of these cells when propagated in a rich, benign medium. 

The answer is no. The evolved lineages recovered fitness by the end of the experiment, growing just as well as the unevolved rod-shaped ancestor, but remained spherical. The authors provide an impressively detailed investigation of the genetic and molecular changes that evolved. Their leading results are: 

(1) The loss of fitness associated with MreB deletion causes high variation in cell volume among sibling cells a_er cell division. 

(2) Fitness recovery is largely driven by a single, loss-of-function point mutation that evolves within the first ~250 generations that reduces the variability in cell volume among siblings. 

(3) The main route to restoring fitness and reducing variability involves loss of function mutations causing a reduction of TPase and peptidoglycan cross-linking, leading to a disorganized cell wall architecture characteristic of spherical cells. 

The inferences made in this paper are on the whole well supported by the data. The authors provide a uniquely comprehensive account of how a key genetic change leads to gains in fitness and the spectrum of phenotypes that are impacted and provide insight into the molecular mechanisms underlying models of cell shape. 

Suggested improvements and clarifications include: 

(1) A schematic of the molecular interactions governing cell wall formation could be useful in the introduction to help orient readers less familiar with the current state of knowledge and key molecular players. 

We understand that this would be desirable, but there are numerous recent reviews with detailed schematics that we think the interested reader would be better consulting. These are referenced in the text.

(2) More detail on the bioinformatics approaches to assembling genomes and identifying the key compensatory mutations are needed, particularly in the methods section. This whole subject remains something of an art, with many different tools used. Specifying these tools, and the parameter sesngs used, will improve transparency and reproducibility, should it be needed. 

We overlooked providing this detail, which has now been corrected by provision of more information in the Materials and Methods. In short we used Breseq, the clonal option, with default parameters. Additional analyses were conducted using Genieous. The BreSeq output files are provided https://doi.org/10.17617/3.CU5SX1 (which include all read data).

(3) Corrections for multiple comparisons should be used and reported whenever more than one construct or strain is compared to the common ancestor, as in Supplementary Figure 19A (relative PG density of different constructs versus the SBW25 ancestor). 

The data presented in Supp Fig 19A (and Fig 4A) do not involve multiple comparisons. In each instance the comparison is between SBW25 and each of the different mutants. A paired t-test is thus appropriate.

(4) The authors refrain from making strong claims about the nature of selection on cell shape, perhaps because their main interest is the molecular mechanisms responsible. However, I think more can be said on the evolutionary side, along two lines. First, they have good evidence that cell volume is a trait under strong stabilizing selection, with cells of intermediate volume having the highest fitness. This is notable because there are rather few examples of stabilizing selection where the underlying mechanisms responsible are so well characterized. Second, this paper succeeds in providing an explanation for how spherical cells can readily evolve from a rod-shaped ancestor but leaves open how rods evolved in the first place. Can the authors speculate as to how the complex, coordinated system leading to rods first evolved? Or why not all cells have lost rod shape and become spherical, if it is so easy to achieve? These are important evolutionary questions that remain unaddressed. The manuscript could be improved by at least flagging these as unanswered questions deserving of further attention. 

These are interesting points, but our capacity to comment is entirely speculative. Nonetheless, we have added an additional paragraph to the Discussion that expresses an opinion that has yet to receive attention:

“Given the complexity of the cell wall synthesis machinery that defines rod-shape in bacteria, it is hard to imagine how rods could have evolved prior to cocci. However, the cylindrical shape offers a number of advantages. For a given biomass (or cell volume), shape determines surface area of the cell envelope, which is the smallest surface area associated with the spherical shape. As shape sets the surface/volume ratio, it also determines the ratio between supply (proportional to the surface) and demand (proportional to cell volume). From this point of view, it is more efficient to be cylindrical (Young 2006). This also holds for surface attachment and biofilm formation (Young 2006). But above all, for growing cells, the ratio between supply and demand is constant in rod shaped bacteria, whereas it decreases for cocci. This requires that spherical cells evolve complex regulatory networks capable of maintaining the correct concentration of cellular proteins despite changes in surface/volume ratio. From this point of view, rod-shaped bacteria offer opportunities to develop unsophisticated regulatory networks.”

why not all cells have lost rod shape and become spherical.

Please see Kevin Young’s 2006 review on the adaptive significance of cell shape

The value of this paper stems both from the insight it provides on the underlying molecular model for cell shape and from what it reveals about some key features of the evolutionary process. The paper, as it currently stands, provides more on which to chew for the molecular side than the evolutionary side. It provides valuable insights into the molecular architecture of how cells grow and what governs their shape. The evolutionary phenomena emphasized by the authors - the importance of loss-of-function mutations in driving rapid compensatory fitness gains and that multiple genetic and molecular routes to high fitness are o_en available, even in the relatively short time frame of a few hundred generations - are wellunderstood phenomena and so arguably of less broad interest. The more compelling evolutionary questions concern the nature and cause of stabilizing selection (in this case cell volume) and the evolution of complexity. The paper misses an opportunity to highlight the former and, while claiming to shed light on the latter, provides rather little useful insight. 

Thank you for these thoughts and comments. However, we disagree that the experimental results are an overlooked opportunity to discuss stabilising selection. Stabilising selection occurs when selection favours a particular phenotype causing a reduction in underpinning population-level genetic diversity. This is not happening when selection acts on SBW25 ∆mreB leading to a restoration of fitness. Driving the response are biophysical factors, primarily the critical need to balance elongation rate with rate of septation. This occurs without any change in underlying genetic diversity.  

Recommendations for the authors:  

Reviewer 1 (Recommendations for the Authors): 

Hereby my suggestion for improvement of the quantification of the data, the figures, and the text. 

-  p 14, what is the unit of elongation rate?  

At first mention we have made clear that the unit is given in minutes^-1

-  p 14, please give an error bar for both p=0.85 and f=0.77, to be able to conclude they are different 

Error on the probability p is estimated at the 95% confidence interval by the formula:1.96 , where N is the total number of cells. This has been added in the paragraph p »probability » of the Image Analysis section in the Material and Methods. 

We also added errors on p measurement in the main text.

-  p 14, all the % differences need an errorbar 

The error bars and means are given in Fig 3C and 3D.

-  Figure 1B adds units to compactness, and what does it represent? Is the cell size the estimated volume (that is mentioned in the caption)? Shouldn't the datapoints have error bars? 

Compactness is defined in the “Image Analysis” section of the Material and Methods. It is a dimensionless parameter. The distribution of individual cell shapes / sizes are depicted in Fig 1B. Error does arise from segmentation, but the degree of variance (few pixels) is much smaller than the representations of individual cells shown.

-  Figure 1C caption, are the 50.000 cells? 

Correct. Figure caption has been altered.

-  Figure 1D, first the elongation rate is described as a volume per minute, but now, looking at the units it is a rate, how is it normalized? 

Elongation rate is explained in the Materials and Methods (see the image analysis section) and is not volume per minute. It is dV/dt = r*V (the unit of r is min^-1). Page 9 includes specific mention of the unit of r.

-  Figure 1E, how many cells (n) per replicate? 

Our apologies. We have corrected the figure caption that now reads:

“Proportion of live cells in ancestral SBW25 (black bar) and ΔmreB (grey bar) based on LIVE/DEAD BacLight Bacterial Viability Kit protocol. Cells were pelleted at 2,000 x g for 2 minutes to preserve ΔmreB cell integrity. Error bars are means and standard deviation of three biological replicates (n>100).”

-  Figure 1G, how does this compare to the wildtype 

The volume for wild type SBW25 is 3.27µm^3 (within the “white zone”). This is mentioned in the text.

-  Figure 2B, is this really volume, not size? And can you add microscopy images? 

The x-axis is volume (see Materials and Methods, subsection image analysis). Images are available in Supp. Fig. 9.

-  Figure 3A what does L1, L4 and L7 refer too? Is it correct that these same lines are picked for WT and delta_mreB 

Thank you for pointing this out. This was an earlier nomenclature. It was shorthand for the mutants that are specified everywhere else by genotype and has now been corrected. 

-  Figure 3c: either way write out p, so which probability, or you need a simple cartoon that is plotted. 

The value p is the probability to proceed to the next generation and is explained in Materials and Methods  subsection image analysis.  We feel this is intuitive and does not require a cartoon. We nonetheless added a sentence to the Materials and Methods to aid clarity.

-  Figure 4B can you add a ladder to the gel? 

No ladder was included, but the controls provide all the necessary information. The band corresponding to PBP1A is defined by presence in SBW25, but absence in SBW25 ∆pbp1A.

-  Figure 4c, can you improve the quantification of these images? How were these selected and how well do they represent the community? 

We apologise for the lack of quantitative description for data presented in Fig 4C. This has now been corrected. In brief, we measured the intensity of fluorescent signal from between 10 and 14 cells and computed the mean and standard deviation of pixel intensity for each cell. To rule out possible artifacts associated with variation of the mean intensity, we calculated the ratio of the standard deviation divided by the square root of the mean. These data reveal heterogeneity in cell wall synthesis and provide strong statistical support for the claim that cell wall synthesis in ∆mreB is significantly more heterogeneous than the control. The data are provided in new Supp. Fig. 21. 

Minor comments: 

-  It would be interesting if the findings of this experimental evolution study could be related to comparative studies (if these have ever been executed).  

Little is possible, but Hendrickson and Yulo published a portion of the originally posted preprint separately. We include a citation to that paper. 

-  p 13, halfway through the page, the second paragraph lacks a conclusion, why do we care about DNA content? 

It is a minor observation that was included by way of providing a complete description of cell phenotype.  

-  p 17, "suggesting that ... loss-of-function", I do no not understand what this is based upon. 

We show that the fitness of a pbp1A deletion is indistinguishable from the fitness of one of the pbp1A point mutants. This fact establishes that the point mutation had the same effects as a gene deletion thus supporting the claim that the point mutations identified during the course of the selection experiment decrease (or destroy) PBP1A function.

-  p 25, at the top of the page: do you have a reference for the statement that a disorganized cell wall architecture is suited to the topology of spherical cells? 

The statement is a conclusion that comes from our reasoning. It stems from the fact that it is impossible to entirely map the surface of a sphere with parallel strands.

eLife Assessment

This study presents useful data on sex differences in gene expression across organs of four mice taxa. While the methods and analysis are largely sound, the strength of evidence is solid only in parts and the conclusions drawn from the results are not always appropriate.

Reviewer #2 (Public review):

Summary:

The manuscript by Xie and colleagues presents transcriptomic experiments that measure gene expression in eight different tissues taken from adult female and male mice from four species. These data are used to make inferences regarding the evolution of sex-biased gene expression across these taxa.

Strengths:

The experimental methods and data analysis appear appropriate. The authors promote their study as unprecedented in its size and technical precision.

Weaknesses:

The manuscript does not present a clear set of novel evolutionary conclusions. The major findings recapitulate many previous comparative transcriptomics studies - gene expression variation is prevalent between individuals, sexes, and species; and genes with sex-biased expression evolve more rapidly than genes with unbiased expression - but it is not clear how the study extends our understanding of gene expression or its evolution.

Many gene expression differences between individual animals are selectively neutral, because these differences in mRNA concentration are buffered at the level of translation, or differences in protein abundance have no effect on cellular or organismal function. The hypothesis that sex-biased genes are enriched for selectively neutral expression differences is supported by the excess of inter-individual expression variance and inter-specific expression differences in sex-biased genes. A higher rate of adaptive coding evolution is inferred among sex-biased genes as a group, but it is not clear whether this signal is driven by many sex-biased genes experiencing a little positive selection, or a few sex-biased genes experiencing a lot of positive selection, so the relationship between expression and protein-coding evolution remains unclear. It is likely that only a subset of the gene expression differences detected here will have phenotypic effects relevant for fitness or medicine, but without some idea of how many or which genes comprise this subset, it is difficult to interpret the results in this context.

Throughout the paper the concepts of sexual selection and sexually antagonistic selection are conflated; while both modes of selection can drive the evolution of sexually dimorphic gene expression, the conditions promoting and consequence of both kinds of selection are different, and the manuscript is not clear about the significance of the results for either mode of selection.

The manuscript's conclusion that "most of the genetic underpinnings of sex-differences show no long-term evolutionary stability" is not supported by the data, which measured gene expression phenotypes but did not investigate the underlying genetic variation causing these differences between individuals, sexes, or species. Furthermore, most of the gene expression differences are observed between sex-specific organs such as testes and ovaries, which are downstream of the sex-determination pathway that is conserved in these four mouse species, so these conclusions are limited to gene expression phenotypes in somatic organs shared by the sexes.

The differences between sex-biased expression in mice and humans are attributed to differences in the two species effective population sizes; but the human samples have significantly more environmental variation than the mouse samples taken from age-matched animals reared in controlled conditions, which could also explain the observed pattern.

The smoothed density plots in Figure 5 are confusing and misleading. Examining the individual SBI values in Table S9 reveals that all of the female and male SBI values for each species and organ are non-overlapping, with the exception of the heart in domesticus and mammary gland in musculus, where one male and one female individual fall within the range of the other sex. The smoothed plots therefore exaggerate the overlap between the sexes; in particular, the extreme variation shown in the SBI in the mammary glands in spretus females and spicilegus males is hard to understand given the normalized values in Table S3. The R code used to generate the smoothed plots is not included in the Github repository, so it is not possible to independently recreate those plots from the underlying data.

The correlations provided in Table S9 are confusing - most of the reported correlations are 1.0, which are not recovered when using the SBI values in Table S9, and which does not support the manuscript's assertion that sex-biased gene expression can vary between organs within an individual. Indeed, using the SBI values in Table S9, many correlations across organs are negative, which is expected given the description of the result in the text.

Reviewer #3 (Public review):

This manuscript reports interesting data on sex differences in expression across several somatic and reproductive tissues among 4 mice species or subspecies. The focus is on sex-biased expression in the somatic tissues, where the authors report high rates of turnover such that the majority of sex-biased genes are only sex-biased in one or two taxa. The authors show sex-biased genes have higher expression variance than unbiased genes but also provide some evidence that sex-bias is likely to evolve from genes with higher expression variance. The authors find that sex-biased genes (both female- and male-biased) experience more adaptive evolution (i.e., higher alpha values) than unbiased genes. The authors develop a summary statistic (Sex-Bias Index, SBI) of each individual's degree of sex-bias for a given tissue. They show that the distribution of SBI values often overlap considerably for somatic (but not reproductive) tissues and that SBI values are not correlated across tissues, which they interpret as indicating an individual can be relatively "male-like" in one tissue and relatively "female-like" in another tissue.

Though the data are interesting, there are some disappointing aspects to how the authors have chosen to present the work. For example, their criteria for sex-bias requires an expression ratio of one sex to the other of 1.25. A reasonably large fraction of the "sex-biased genes" have ratios just beyond this cut-off (Fig. S1). A gene which has a ratio of 1.27 in taxa 1 can be declared as "sex-biased" but which has a ratio of 1.23 in taxa 2 will not be declared as "sex-biased". It is impossible to know from how the data are presented in the main text the extent to which the supposed very high turnover represents substantial changes in dimorphic expression. A simple plot of the expression sex ratio of taxa 1 vs taxa 2 would be illuminating but the authors declined this suggestion.

I was particularly intrigued by the authors' inference of the proportion of adaptive substitutions ("alpha") in different gene sets. The show alpha is higher for sex-biased than unbiased genes and nicely shows that the genes that are unbiased in focal taxa but sex-biased in the sister taxa also have low alpha. It would be even stronger that sex-bias is associated with adaptive evolution to estimate alpha for only those genes that are sex-biased in the focal taxa but not in the sister taxa (the current version estimates alpha on all sex-biased genes within the focal taxa, both those that are sex-biased and those that are unbiased in the sister taxa).

The author's Sex Bias Index is measured in an individual sample as: SBI = median(TPM of female-biased genes) - median(TPM of male-biased genes). This index has some strange properties when one works through some toy examples (though any summary statistic will have limitations). The authors do little to jointly discuss the merits and limitations of this metric. It would have been interesting to examine their two key points (degree of overlapping distributions between sexes and correlation across tissues) using other individual measures of sex-bias.

Figure 5 shows symmetric gaussian-looking distributions of SBI but it makes me wonder to what extent this is the magic of model fitting software as there are only 9 data points underlying each distribution. Whereas Figure 5 shows many broadly overlapping distributions for SBI, Figure 6 seems to suggest the sexes are quite well separated for SBI (e.g., brain in MUS, heart in DOM).

Fig. S1 should be shown as the log(F/M) ratio so it is easier to see the symmetry, or lack thereof, of female and male-biased genes.<br /> It is important to note that for the variance analysis that IQR/median was calculated for each gene within each sex for each tissue. This is a key piece of information that should be in the methods or legend of the main figure (not buried in Supplemental Table 17).

Author response:

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

We are disappointed that the reviewers do not acknowledge that our data constitute a major step forward for the field. We will prepare a revised version that takes care of the remaining small issues concerning the technical descriptions and a detailed response to the current round of comments. We will also add a summary of the major new findings of our study.

---

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

We appreciate the time of the reviewers and their detailed comments, which have helped to improve the manuscript.

Our study presents the largest systematic dataset so far on the evolution of sex-biased gene expression in animals. It is also the first that explores the patterns of individual variation in sex-biased gene expression and the SBI is an entirely new procedure to directly visulize these variance patterns in an intuitive way.

Also, we should like to point out that our study contradicts recent conclusions that had suggested that a substantial set of sex-biased genes has conserved functions between humans and mice and that mice can therefore be informative for gender-specific medicine studies. Our data suggest that only a very small set of genes are conserved in their sex-biased expression between mice and humans in more than one organ.

In the revised version we have made the following major updates:

- added a rate comparison of gene regulation turnover between sex-biased and non-sex-biased genes

- added additional statistics to the variance comparisons and selection tests

- added a regulatory module analysis that shows that much of the gene turnover happens within modules

- added a mosaic pattern analysis that shows the individual complexity of sex-biased patterns

- extended introduction and discussion

Reviewer #1 (Public Review):<br /> The authors describe a comprehensive analysis of sex-biased expression across multiple tissues and species of mouse. Their results are broadly consistent with previous work, and their methods are robust, as the large volume of work in this area has converged toward a standardized approach.

I have a few quibbles with the findings, and the main novelty here is the rapid evolution of sex-biased expression over shorter evolutionary intervals than previously documented, although this is not statistically supported. The other main findings, detailed below, are somewhat overstated.

(1) In the introduction, the authors conflate gametic sex, which is indeed largely binary (with small sperm, large eggs, no intermediate gametic form, and no overlap in size) with somatic sexual dimorphism, which can be bimodal (though sometimes is even more complicated), with a large variance in either sex and generally with a great deal of overlap between males and females. A good appraisal of this distinction is at . This distinction in gene expression has been recognized for at least 20 years, with observations that sex-biased expression in the soma is far less than in the gonad.

For example, the authors frame their work with the following statement:

"The different organs show a large individual variation in sex-biased gene expression, making it impossible to classify individuals in simple binary terms. Hence, the seemingly strong conservation of binary sex-states does not find an equivalent underpinning when one looks at the gene-expression makeup of the sexes"

The authors use this conflation to set up a straw man argument, perhaps in part due to recent political discussions on this topic. They seem to be implying one of two things. a) That previous studies of sex-biased expression of the soma claim a binary classification. I know of no such claim, and many have clearly shown quite the opposite, particularly studies of intra-sexual variation, which are common - see https://doi.org/10.1093/molbev/msx293, https://doi.org/10.1371/journal.pgen.1003697, https://doi.org/10.1111/mec.14408, https://doi.org/10.1111/mec.13919, https://doi.org/10.1111/j.1558-5646.2010.01106.x for just a few examples. Or b) They are the first to observe this non-binary pattern for the soma, but again, many have observed this. For example, many have noted that reproductive or gonad transcriptome data cluster first by sex, but somatic tissue clusters first by species or tissue, then by sex (https://doi.org/10.1073/pnas.1501339112, https://doi.org/10.7554/eLife.67485)

Figure 4 illustrates the conceptual difference between bimodal and binary sexual conceptions. This figure makes it clear that males and females have different means, but in all cases the distributions are bimodal.

I would suggest that the authors heavily revise the paper with this more nuanced understanding of the literature and sex differences in their paper, and place their findings in the context of previous work.

We are sorry that our introduction seems to have been too short to make our points sufficiently clear. Of course, overlapping somatic variation has been shown for morphological characters, but we were aiming to assess this at the sex-biased transcriptome level. Previous studies looking at sex-biased genes were usually limited by the techniques that were available at their times, resulting in a focus on gonads in most studies and almost all have too few individuals included to study within-group variation. We detail this below for the papers that are mentioned by the referee. In view of this, we cite them now as examples for the prevalent focus on gonadal comparisons in most studies. Only Scharmann et al. 2021 on plant leaf dimorphism is indeed relevant for our study with respect to its general findings and we make now extensive reference to it. In addition, we have generally modified the introduction and substantially extended the discussion to make our points clear.

Snell-Rood 2010: the paper focuses on sex-specific morphological structures in beetles. It samples six somatic tissues for four individuals each of each class. Analysis is done via microarray hybridizations. While categorial differences were traced, variability between individuals was not discussed. By today´s standards, microarrays have anyway too much technical variability to even consider such a discussion.

Pointer et al. 2013: this paper studies three sexual phenotypes in a bird species, females, dominant males and subordinate males. Tissues include telencephalon, spleen and left gonad. The focus of the analysis is on the gonads, since only few sex-biased genes were found in spleen and brain (according to suppl. Table S1, 0 for the spleen and 2 for the brain). No inferences could be made on somatic variation.

Harrison 2015: this paper focuses on gonads plus spleen in six bird species with between 2-6 individuals for each sex collected. In the spleen, only one female biased gene and no male biased gene was detected. Hence, the data do not allow to infer patterns of somatic variation.

Dean et al. 2016: this paper compares four categories of fish caught around nests, with four to seven individuals per category. Only gonads were analyzed, hence no inferences could be made about somatic variability between individuals.

Cardoso et al. 2017: this paper test categories of fish with alternative reproductive tactics based on brain transcriptomes. While it uses 9-10 individuals per category, it uses pools for sequencing with two pools per category. This does not allow to make any inference on individual variation.

Todd et al 2017: this paper focuses on three categories of a fish species, females and dominant and sneaker males. It uses brain and gonads as samples with five individuals each for each category. For the brain, more different genes were found between the two types of males, rather than between females and males (3 and 9 respectively). The paper focuses on individual gene descriptions and does not mention somatic variation.

Scharmann 2021: the paper focuses on 10 species of plants with sexually dimorphic leafs. 5-6 individuals were sampled per sex. The major finding is that sex-biased gene expression does not correlate with the degree of sexual dimorphism of the leafes. The study shows also a fast evolution of sex-biased expression and states that signatures of adaptive evolution are weak. But it does not discuss variance patterns within populations.

(2) The authors also claim that "sexual conflict is one of the major drivers of evolutionary divergence already at the early species divergence level." However, making the connection between sex-biased genes and sexual conflict remains fraught. Although it is tempting to use sex-biased gene expression (or any form of phenotypic dimorphism) as an indicator of sexual conflict, resolved or not, as many have pointed out, one needs measures of sex-specific selection, ideally fitness, to make this case (https://doi.org/10.1086/595841, 10.1101/cshperspect.a017632). In many cases, sexual dimorphism can arise in one sex only without conflict (e.g. 10.1098/rspb.2010.2220). As such, sex-biased genes alone are not sufficient to discriminate between ongoing and resolved conflict.

We imply sexual conflict as a driver of genomic divergence patterns in a similar way as it has been done by many authors before (e.g. Mank 2017a, Price et al. 2023, Tosto et al. 2023). While we fully appreciate the point of the referee, we do not really see where we deviate from the standard wording that is used in the context of genomic data. In such data, it is of course usually assumed that they represent solved conflicts (Figure 1D in Cox and Calsbeek) where selection differentials would not be measurable anyway. (Please note also that the phylogenetic approach used in Oliver and Monteiro 2010 becomes rather problematic in view of introgressive hybridization patterns in butterflies), We have extended the discussion to address this.

(3) To make the case that sex-biased genes are under selection, the authors report alpha values in Figure 3B. Alpha value comparisons like this over large numbers of genes often have high variance. Are any of the values for male- female- and un-biased genes significantly different from one another? This is needed to make the claim of positive selection.

Sorry, we had accidentally not included the statistics in the final version of the figure. We have added this now in the supplementary table but have also generally changed the statistical approach and the design of the figure.

Reviewer #2 (Public Review):

The manuscript by Xie and colleagues presents transcriptomic experiments that measure gene expression in eight different tissues taken from adult female and male mice from four species. These data are used to make inferences regarding the evolution of sex-biased gene expression across these taxa. The experimental methods and data analysis are appropriate; however, most of the conclusions drawn in the manuscript have either been previously reported in the literature or are not fully supported by the data.

We are not aware of any study that has analyzed somatic sex-biased expression in such a large and taxonomically well resolved closely related taxa of animals. Only the study by Scharman et al. 2021 on plant leaves comes close to it, but even this did not specifically analyze the intragroup variation aspects. Of course, some of our results confirm previous conclusions, but we should still like to point out that they go far beyond them.

There are two ways the manuscript could be modified to better strengthen the conclusions.

First, some of the observed differences in gene expression have very little to no effect on other phenotypes, and are not relevant to medicine or fitness. Selectively neutral gene expression differences have been inferred in previous studies, and consistent with that work, sex-biased and between-species expression differences in this study may also be enriched for selectively neutral expression differences. This idea is supported by the analysis of expression variance, which indicates that genes that show sex-biased expression also tend to show more inter-individual variation. This perspective is also supported by the MK analysis of molecular evolution, which suggests that positive selection is more prevalent among genes that are sex-biased in both mus and dom, and genes that switch sex-biased expression are under less selection at the level of both protein-coding sequence and gene expression.

We have now revisited these points by additional statistical analysis of the variance patterns and an extended discussion under the heading "Neutral or adaptive?". 

As an aside, I was confused by (line 176): "implying that the enhanced positive selection pressure is triggered by their status of being sex-biased in either taxon." - don't the MK values suggest an excess of positive selection on genes that are sex-biased in both taxa?

There are different sets of genes that are sex-biased in these two taxa - hence this observation is actually a strong argument for selection on these genes. We have changed the correspondiung text to make this clearer.

Without an estimate of the proportion of differentially expressed genes that might be relevant for broader physiological or organismal phenotypes, it is difficult to assess the accuracy and relevance of the manuscript's conclusions. One (crude) approach would be to analyze subsets of genes stratified by the magnitude of expression differences; while there is a weak relationship between expression differences and fitness effects, on average large gene expression differences are more likely to affect additional phenotypes than small expression differences.

We agree that it remains a challenge to show functional effects for the sex-biased genes. The argument that they should have a function is laid out above (and stated in many reviews on the topic). To use the expression level as a proxy of function does not seem justified, given the current literature. For example, genes that are highly conected in modules are not necessrily highly expressed (e.g. transcription factors). Also, genes may be highly expressed in a rare cell type of an organ and have an important funtion there, but this would not show up across the RNA of the whole organ. The most direct functional relationship between sex-biased expression and phenotype comes from the human data in Naqvi et al. 2019 - which we had cited.

Another perspective would be to compare the within-species variance to the between-species variance to identify genes with an excess of the latter relative to the former (similar logic to an MK test of amino acid substitutions).

Such an analysis was actually our intial motivation for this study. However, the new (and surprising!) result is that the status of being sex-biased shows such a high turnover that not many genes are left per organ where one could even try to make such a test. However, we have extended the variance analysis with reciprocal gene sets (as we had done it for the MK test) and extended the discussion on the topic, including citation of our prior work on these questions.

Second, the analysis could be more informative if it distinguished between genes that are expressed across multiple tissues in both sexes that may show greater expression in one sex than the other, versus genes with specialized function expressed solely in (usually) reproductive tissues of one sex (e.g. ovary-specific genes). One approach to quantify this distinction would be metrics like those used defined by [Yanai I, et al. 2005. Genome-wide midrange transcription profiles reveal expression-level relationships in human tissue specification. Bioinformatics 21:650-659.] These approaches can be used to separate out groups of genes by the extent to which they are expressed in both sexes versus genes that are primarily expressed in sex-specific tissue such as testes or ovaries. This more fine-grained analysis would also potentially inform the section describing the evolution/conservation of sex-biased expression: I expect there must be genes with conserved expression specifically in ovaries or testes (these are ancient animal structures!) but these may have been excluded by the requirement that genes be sex-biased and expressed in at least two organs.

Given that our study focuses on somatic sex-biased genes, we refrain from a comparative analysis of genes that are only expressed in the sex-organs in this paper. With respect to sharing of sex-biased gene expresssion between the somatic tissues, we show in Figure 8 that there are only very few of them (8 female-biased and 3 male-biased). A separate statistical treatment is not possible for this small set of genes.

There are at least three examples of statements in the discussion that at the moment misinterpret the experimental results.

The discussion frames the results in the context of sexual selection and sexually antagonistic selection, but these concepts are not synonymous. Sexual selection can shape phenotypes that are specific to one sex, causing no antagonism; and fitness differences between males and females resulting from sexually antagonistic variation in somatic phenotypes may not be acted on by sexual selection. Furthermore, the conditions promoting and consequence of both kinds of selection can be different, so they should be treated separately for the purposes of this discussion.

We cannot make such a distinction for gene expression patterns - and we are not aware that this was done before in the literature (except gene expression was directly linked to a morphological structure). We have updated this discussion accordingly.

The discussion claims that "Our data show that sex-biased gene expression evolves extremely fast" but a comparison or expectation for the rate of evolution is not provided. Many other studies have used comparative transcriptomics to estimate rates of gene expression evolution between species, including mice; are the results here substantially and significantly different from those previous studies? Furthermore, the experimental design does not distinguish between those gene expression phenotypes that are fixed between species as compared to those that are polymorphic within one or more species which prevents straightforward interpretation of differences in gene expression as interspecific differences.

Our statement was in relation to the comparison between somatic and gondadal gene turnover, as well as the comparison to humans. We have now included an additional analysis for a direct comparison with non-sex-biased genes in the same populations (Figure 2B). Note that gene expression variances cannot get fixed anyway, they can only become different in average and magnitude.

The conclusion that "Our results show that most of the genetic underpinnings of sex differences show no long-term evolutionary stability, which is in strong contrast to the perceived evolutionary stability of two sexes" - seems beyond the scope of this study. This manuscript does not address the genetic underpinnings of sex differences (this would involve eQTL or the like), rather it looks at sex differences in gene expression phenotypes.

This comes back to the points discussed above about the validity to infer function from sex-biased expression. We have updated the text to clarify this.

Simply addressing the question of phenotypic evolutionary stability would be more informative if genes expressed specifically in reproductive tissues were separated from somatic sex-biased genes to determine if they show similar patterns of expression evolution.

Our study is generally focused on somatic gene expression. The comparison with reproductive tissues serves merely as a reference. Since they are of course very different tissues, they should not be compared with each other in the same way. We have now specifically addressed this point in the discussion.

Reviewer #3 (Public Review):

This manuscript reports some interesting and important patterns. The results on sex-bias in different tissues and across four taxa would benefit from alternative (or additional) presentation styles. In my view, the most important results are with respect to alpha (fraction of beneficial amino acid changes) in relation to sex-bias (though the authors have made this as a somewhat minor point in this version).

The part that the authors emphasize I don't find very interesting (i.e., the sexes have overlapping expression profiles in many nongonadal tissues), nor do I believe they have the appropriate data necessary to convincingly demonstrate this (which would require multiple measures from the same individual).

This is the first study that reports such overlaps and we show that this is not always the case (e.g. liver and kidney data in mice). We are not aware of any preditions of how such patterns would look like and how they would evolve - why should such a new finding not be interesting? Concerning the appropriateness of the data we do not agree with the point the referee makes - see response below.

This study reports several interesting patterns with respect to sex differences in gene expression across organs of four mice taxa. An alternative presentation of the data would yield a clearer and more convincing case that the patterns the authors claim are legitimate.

I recommend that the authors clarify what qualifies as "sex-bias".

This is defined by the statistical criteria that we have applied, following the general standard of papers on this topic.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

(1) "However, already Darwin has pointed out that the phenotypes of the sexes should evolve fast". I think the authors mean that Darwin was quick to point out that sex-specific phenotypes evolve quickly".

We have modified this text part.

(2) Non-gonadal is more often referred to as somatic. I would encourage the authors to use this more common term for accessibility.

We have adopted this term

(3) Figure 5 is interesting, however, it is difficult to know whether the decreased bimodality in humans compared to mice is biological or technical due to the differences in the underlying data. For example, the mouse samples tightly controlled age and environmental conditions within each species. It is not possible to do that with human samples, and there are very good reasons to think that these factors will affect variance in both sexes.

Yes, this is certainly true and we know this also from other comparative data between mice and humans. Still, this is human reality vs mouse artificialness. We pick this now up in the discussion.

(4) Line 273. The large numbers of cells needed for single-cell analysis require that most studies pool multiple samples, however these pools are helpful in themselves. This approach was used by https://doi.org/10.1093/evlett/qrad013 to quantify the degree of sex-bias within cell types across multiple tissues and to compare how bulk and single-cell sex-bias measures compare. Sex-bias in some somatic cell types was very high, even when bulk sex-bias in those tissues was not. This suggests that the bulk data the authors use in this study may in fact obscure the pattern of sex-bias.

Yes, we agree, and this is exactly how we did the analysis and interpretation, based on the cited paper.

(5)- Line 379 "Total RNAs were" should be "Total RNA was"

Corrected

References cited in this review and which should be included in the manuscript :

Sam L Sharpe, Andrew P Anderson, Idelle Cooper, Timothy Y James, Alexandra E Kralick, Hans Lindahl, Sara E Lipshutz, J F McLaughlin, Banu Subramaniam, Alicia Roth Weigel, A Kelsey Lewis, Sex and Biology: Broader Impacts Beyond the Binary, Integrative, and Comparative Biology, Volume 63, Issue 4, October 2023, Pages 960-967.

Included

Masculinization of Gene Expression Is Associated with Exaggeration of Male Sexual Dimorphism Pointer MA, Harrison PW, Wright AE, Mank JE (2013) Masculinization of Gene Expression Is Associated with Exaggeration of Male Sexual Dimorphism. PLOS Genetics 9(8): e1003697.

Included

Erica V Todd, Hui Liu, Melissa S Lamm, Jodi T Thomas, Kim Rutherford, Kelly C Thompson, John R Godwin, Neil J Gemmell, Female Mimicry by Sneaker Males Has a Transcriptomic Signature in Both the Brain and the Gonad in a Sex-Changing Fish, Molecular Biology and Evolution, Volume 35, Issue 1, January 2018, Pages 225-241.

Included

Cardoso SD, Gonçalves D, Goesmann A, Canário AVM, Oliveira RF. Temporal variation in brain transcriptome is associated with the expression of female mimicry as a sequential male alternative reproductive tactic in fish. Mol Ecol. 2018; 27: 789-803.

Included

Dean, R., Wright, A.E., Marsh-Rollo, S.E., Nugent, B.M., Alonzo, S.H. and Mank, J.E. (2017), Sperm competition shapes gene expression and sequence evolution in the ocellated wrasse. Mol Ecol, 26: 505-518.

Included

Emilie C. Snell‐Rood, Amy Cash, Mira V. Han, Teiya Kijimoto, Justen Andrews, Armin P. Moczek, DEVELOPMENTAL DECOUPLING OF ALTERNATIVE PHENOTYPES: INSIGHTS FROM THE TRANSCRIPTOMES OF HORN‐POLYPHENIC BEETLES, Evolution, Volume 65, Issue 1, 1 January 2011.

Not included, since its technical approach is not really comparable

Harrison PW, Wright AE, Zimmer F, Dean R, Montgomery SH, Pointer MA, Mank JE (2015) Sexual selection drives evolution and rapid turnover of male gene expression. Proceedings of the National Academy of Sciences, USA 112: 4393-4398.

Included

Mathias Scharmann, Anthony G Rebelo, John R Pannell (2021) High rates of evolution preceded shifts to sex-biased gene expression in Leucadendron, the most sexually dimorphic angiosperms eLife 10:e67485.

Included

Sexually Antagonistic Selection, Sexual Dimorphism, and the Resolution of Intralocus Sexual Conflict. Robert M. Cox and Ryan Calsbeek , The American Naturalist 2009 173:2, 176-187.

Included

Ingleby FC, Flis I, Morrow EH. Sex-biased gene expression and sexual conflict throughout development. Cold Spring Harb Perspect Biol. 2014 Nov 6;7(1):a017632.

Included

Oliver JC, Monteiro A 2011. On the origins of sexual dimorphism in butterflies. Proc Biol Sci 278: 1981-1988.

Included

Iulia Darolti, Judith E Mank, Sex-biased gene expression at single-cell resolution: cause and consequence of sexual dimorphism, Evolution Letters, Volume 7, Issue 3, June 2023, Pages 148-156.

Included

Reviewer #2 (Recommendations For The Authors):

I am concerned the smoothed density plots in Figure 4 may be providing a misleading sense of the distributions since each distribution is inferred from only 9 values. A boxplot might better represent the data to the reader.

Boxplots with 9 values are much more difficult to interpret for a reader, this is the very reason why one tends to smoothen them. In this way, they also become similar to the standard plots that are used for showing morphological variation between the sexes. Note that the original data are availble for the individual values, if these are of special interest in some cases. In addition, our new “mosaic” analysis (Figure 6) provides another presentation for readers.

Line 235: "the overall numbers are lower" I assume this is the number of genes included in the analyses, but this should be explicitly stated.

Clarified in the text

The analysis of gene expression from different brain regions in control individuals from the Alzheimer's study (line 273) suffers from low power and it is not clear to me how much taking samples from different brain regions eliminates the issue of different cell types within a sample (the stated motivation for this analysis). While I support publishing negative results, this section does not feel like it adds much to the manuscript and could be cut in my opinion.

This is actually a study on single cell types, differentiating each of them. We are sorry that the text was apparently unclear about this. Given that there are studies that show the importance of looking at single cell data, we still think that is a suitable analysis. We have updated the text to make it clearer.

It might be useful to separate out X-linked genes from autosomal genes to see if they show consistent patterns with regard to sex-bias.

We have added this information in suppl. Table S2 and include some description in the text.

Reviewer #3 (Recommendations For The Authors):

Comments follow the order of the Results section:

(1) The latter half of this line in the Methods is too vague to be helpful: "We have explored a range of cutoffs and found that a sex-bias ratio of 1.25-fold difference of MEDIAN expression values combined with a Wilcoxon rank sum test and Benjamini-Hochberg FDR correction (using FDR <0.1 as cutoff) (Benjamini & Hochberg, 1995) yields the best compromise between sensitivity and specificity". What precisely is meant by "the best compromise between sensitivity and specificity"?

We explain now that this was based on pre-tests with comparing randomized with actual data. However, we agree that this is in the end a subjective decision, but there is no single standard used in the literature, especially when somatic organs are included. We consider our criteria as rather stringent.

(2) The 1.25 number for sex bias is, ultimately, an arbitrary cut-off. It is common in this literature to choose some arbitrary level and, in this sense, the authors are following common practice. The choice of 1.25 should be stated in the main text as it is a lower (but not reasonable) value than has been used in many other papers.

It is not only the cutoff, but also the Wilcoxon test and FDR correction that defines the threshold. See also comment above.

(3) In truth, dimorphism is continuous rather than discrete (i.e, greater or less than 1.25 fold different). Thus, where possible it would be useful to present results in a fashion that allows readers to see the continuous range of ratios rather than having to worry about whether the patterns are due to the rather arbitrary choices of how genes were binned into sex-bias categories.

It is necessary to work with cutoffs in such cases - and this is the usual practice for any such paper. But we provide now in Figure 1 Figure supplement 1 plots with the female/male ratio distributions.

a) Number of genes that are female- / male-biased. I would like to be able to see a version of Figure 1 showing the full distribution of TPM ratios rather than bar graphs of the numbers of (arbitrarily defined) female- and male-biased genes. This will be, of course, a larger figure (a full distribution rather than 2 bars for each species for each organ) and so could be relegated to Supplementary Material (assuming the message of that figure is the same as the current Figure 1).

This is a very unusual request, given that no other paper has done this either. It would indeed result in a non-managable figure size, or many separate figures that would be difficult to scrutinize. Note that there would be one plot of two (female and male) TPM distributions for each sex-biased gene in each organ and each taxon, leading to hundreds of thousands of plots. We think that by providing the general distributions as plots (see above), and the original data as supplements is sufficient.

b) Turnover of genes with sex bias. This important issue is addressed in Figure 2. First, it is not precisely clear what "percentages of sums of shared genes for any pairwise comparison" in Figure 2 legend means and no further detail is given in the Methods; this must be made clearer or the info in Figure 2 is meaningless. Regardless, this approach again relies heavily on the arbitrary criterion of defining sex-bias. Thus, I would like to see correlation plots of the log(TPM ratio) between taxa as done in the classic multispecies fly paper of Zhang et al. 2007. In Figure 2 it is quite clear that male-biased genes evolve with respect to sex bias more rapidly than female-biased genes.

We have provided a better explanation of this analysis. Note that the Zhang et al. 2007 paper was not focussing on somatic expression and covers a much broader evolutionary spectrum. Hence, the results are not comparable. Also, we doubt that it would be so helpful to generate a huge figure with all these plots.

(4) Is there a simpler explanation for the results in the "Variance patterns" section? The total variance for any variable can be decomposed into the variance within and among "groups". If we use "sex" as the group, then there are genes - labelled sex-biased genes - that were identified as such, in essence, because they have high among-group variance. Given that we then know a priori at the start of this section of sex-biased genes have high among-group variance, is it at all surprising that they have higher total variance than the unbiased genes (which we know a priori have low among-group variance)? Perhaps I misunderstood the point of this section. Maybe it would be more meaningful to examine the WITHIN-SEX variance (averaged across the two sexes) instead.

We did calculate IQR/median (“normalized variance”) with the nine mice for each gene and each sex in each organ, hence sex is not a variance factor in this calculation. The algorithm steps are outlined in suppl. Table S17. We have now also added a variance calculation for reciprocal gene sets and added an extended discussion of these results.

(5) Analysis of alpha for sex-biased genes. This was the most interesting part of this manuscript to me.

(a) More information about what SNVs were used is required.

i. Were only sites where SPR was fixed used? (If not, how was polarization done?)

ii. Were sites only considered diverged if they were fixed for different bases in DOM and MUS? (If not, what was the criteria?)

iii. Using, say, DOM as the focal species, a site must be polymorphic in DOM. But did its status (polymorphic/fixed) in MUS matter?

We have added a more detailed description on this in the Methods section. For the direct answers of the three questions: (i) yes; (ii) yes; (iii) no, considering that DOM and MUS are two subspecies of Mus musculus separating recently, a variant might occur before separating and there might be gene flow between them.

(b) A particularly interesting part of the analysis is the investigation of alpha for genes that are NOT sex-biased in one taxa but are sex-biased in the other. At the moment (as I understand it), alpha is only calculated for these genes in the taxa where they are NOT sex-biased (and this alpha value can be compared to the alpha of sex-biased genes and of unbiased genes in that taxa). I would like to see both sets of genes (set 1: those sex-biased in MUS and not in DOM; set 2: those sex-biased DOM and not in MUS) analyzed in each of the 2 species, with results presented in a 2x2 table.

By definition of these categories, these genes are sex-biased in the respective other taxon, hence the values are already in the table. They are named as “reciprocal”.

(c) No confidence intervals are given for the alpha values, despite the legend of Figure 3 referring to them.

These were accidentally omitted - we now included the full table in suppl. Table S6; Figure 3 was modified to show violin plots of the bootstrap distributions

The author's creation and use of a "sex-bias index" (SBI). My greatest skepticism of this manuscript is with respect to the value of their manufactured index, SBI. Of course, it is possible to create such an index but does this literature really need this index or does this just add to the "clutter" in the literature for this field? Is it helping to illuminate important patterns? This index is presumably some attempt to quantify how "male-like" or "female-like" overall expression is for a given individual (for a given organ). It is calculated as SBI = (MEDIAN of all female-biased tpm) - (MEDIAN of all male-biased tpm).

(6) A main result that comes from this is that the sexes tend to overlap for these values for most nongonad tissues but are clearly distinct for gonadal tissues. I do not think this result would come as a surprise to almost anyone and I'm far from convinced that this metric is a good way to quantify that point. Let's consider testes vs. ovaries. Compared to non-gonadal tissues, I am reasonably certain that not only are there many more genes that are classified as "sex-biased" in gonads but also the magnitude of sex-bias among these genes is typically much greater than it is for the so-called sex-biased genes in nongonadal tissue (density plots requested in #3a would make this clear). In other words, males and females are, on average, very different with respect to expression in gonads so even allowing for variation within each sex will still result in a clear separation of all individuals of the two sexes. In contrast, males and females are, on average, much less different in, say, heart so when we consider the variation within each sex, there is overlap. One could imagine a variety of different metrics which could be used to make this point. The merits of "SBI" are unclear. It is a novel metric and its properties are poorly understood. (A simple alternative would be looking at individual scores along the axis separating mean/median males and females; almost certainly, for gonads, this would be very similar to PC scores for PC1.)

As throughout the text, we use gonadal comparisons only as general reference, not as the main result. The main result that we are stressing is the fast turnover of these patterns, including from binary to overlapping for kidney and liver in mouse. We consider this as a new finding. If it comes "not to a surprise to anyone", isn´t it great that one does not have to guess anymore but has finally real data on this?

We have now also added a mosaic analysis to show that the SBI can be used as summary measure in different presentations.

The use of a single PC axis is no good alternative, since it throws away the information from the other axis.

We have now included an explicit discussion on the usefulness of the SBI.

(7) For simplicity, let's assume all males are identical and all females are identical. Let's imagine that heart and kidney have the exact same set of sex-biased genes. There are 20 female-biased genes; they all happen to be identical in expression level (within tissue) and look like this:

Female TPM Male TPM TPM ratio (F:M)

Heart 4 2 2

Kidney 40 20 2

And there are 20 male-biased genes that look like this:

Female TPM Male TPM TPM ratio (F:M)

Heart 1 3 1/3

Kidney 10 30 1/3

Most people would describe these two tissues as equally sex-biased.

However, the SBIs would be:

Female SBI Male SBI Sex difference (F - M)

Heart 4-1 = 3 2 - 3 = -1 4

Kidney 40-10 =30 20-30 = -10 40

Is it a desirable property that by this metric these two tissues have wildly different SBI values for each sex as well as for the difference between sexes? (At the very least, shouldn't you make readers aware of these strange properties of SBI so they can decide how much value they put into them?)

Actually, in this example the simple ratio between the expression levels has a strange property, since it does not reflect a much higher expression of the relevant genes in the kidney. The SBI is actually more suitable for making such cases clear. Of course, this is under the assumption that expression level has a meaning for the phenotype, but this is the general assumption for all RNA-Seq experiment comparisons.

(8) With respect to Figure 4, why do females often have mean SBI values close to zero or even negative (e.g., kidney, mammary glands)? Is this simply because the female-biased genes tend to have lower TPM than the male-biased genes? It seems that the value zero for this metric is really not very biologically meaningful because this metric is a difference of two things that are not necessarily expected to be equal.

This is the extra information about the expression levels that is gained via the SBI values (see comment above). However, we noticed that people can get confused about this. We have now added a re-scaling step to focus completely on the variance information in these plots.

(9) Interpreting variances. A substantial fraction of the latter half of the manuscript focuses on interpreting variances among individual samples. This is problematic because there is no replication within individuals (i.e.., "repeatability"), thus it is impossible to infer the extent of observed variance among individuals of a given group (e.g., among females) is due to true biological differences among individuals or is simply due to noise (i.e., "measurement error" in the broad sense). Is the larger variance for mammary glands than liver or gonads just due to measurement error? What is the evidence?

This point was of course a major issue during the times where microarrays were used for transcriptome studies. However, the first systematic RNA-Seq studies showed already that the technical replicability is so high, that technical replicates are not required. In fact, practically all RNA-Seq studies are done without technical replicates for this reason.

(10) Because I have little confidence in the SBI metric (#7-8) and in interpreting within sex variances (#9), I found little value in the human results and how SBI distributions (and degree of overlap between sexes) compare between humans and mice.

We disagree - the current published status is that there are thousands of sex-biased gene in humans and this has implications for gender-specific medicine (Oliva et al. 2020). Our results show a much more nuanced picture in this respect.

(11) I found even less value in the single-cell data. It too suffers from the issues above. Further, as the authors more or less state, the data are too limited to say much of value here. It is impossible to tell to what extent the results are simply due to data limitations.

We have pointed out that it is still valuable to have them. They are good enough to exclude the possibility that only a small set of cells drives the overall pattern across an organ. We have further clarified this in the text.

(12) The code for data analysis should be posted on GitHub or some other repository.

The code for the sex-biased gene detection and analysis has been posted on GitHub (see Code availability in the manuscript).

eLife Assessment

This valuable study unravels the mechanisms underlying mammalian sperm-oocyte recognition and penetration, shedding light on cross-species interactions. It provides solid evidence that exposure of sperm to oviductal fluid or OVGP1 proteins from bovine, murine, or human sources imparts species-specific zona pellucida (ZP) recognition, ensuring that only sperm from the corresponding species can penetrate the ZP, regardless of its origin. These findings hold significant potential for reproductive biology, offering insights to enhance porcine in vitro fertilization (IVF), which frequently suffers from polyspermy, as well as advancing human IVF through improved intrinsic sperm selection.

Reviewer #1 (Public review):

Summary:

This interesting manuscript first shows that human, murine, and feline sperm penetrate the zona pellucida (ZP) of bovine oocytes recovered directly from the ovary, although first cleavage rates are reduced. Similarly, bovine sperm can penetrate superovulated murine oocytes recovered directly from the ovary. However, bovine oocytes incubated with oviduct fluid (30 min) are generally impenetrable by human sperm.

Thereafter, the cytoplasm was aspirated from murine oocytes - obtained from the ovary or oviduct. Binding and penetration by bovine and human sperm was reduced in both groups relative to homologous (murine) sperm. However, heterologous (bovine and human) sperm penetration was further reduced in oviduct vs. ovary derived empty ZP. These data show that outer (ZP) not inner (cytoplasmic) oocyte alterations reduce heterologous sperm penetration as well as homologous sperm binding.

This was repeated using empty bovine ZP incubated, or not, with bovine oviduct fluid. Prior oviduct fluid exposure reduced non-homologous (human and murine) empty ZP penetration, polyspermy, and sperm binding. This demonstrates that species-specific oviduct fluid factors regulate ZP penetrability.

To test the hypothesis that OVGP1 is responsible, the authors obtained histidiine-tagged bovine and murine OVGP1 and DDK-tagged human OVGP1 proteins. Tagging was to enable purification following over-expression in BHK-21 or HEK293T cells. The authors confirm these recombinant OVGP1 proteins bound to both murine and bovine oocytes. Moreover, previous data using oviduct fluid was mirrored using bovine oocytes supplemented with homologous (bovine) recombinant OVGP1, or not. This confirms the hypothesis, at least in cattle.

Next, the authors exposed bovine and murine empty ZP to bovine, murine, and human recombinant OVGP1, in addition to bovine, murine, or human sperm. Interestingly, both species-specific ZP and OVGP1 seem to be required for optimal sperm binding and penetration.

Lastly, empty bovine and murine ZP were treated with neuraminidase, or not, with or without pre-treatment with homologous OVGP1. In each case, neuraminidase reduced sperm binding and penetration. This further demonstrates that both ZP and OVGP1 are required for optimal sperm binding and penetration.

In summary, the authors demonstrate that two mechanisms seem to underpin mammalian sperm recognition and penetration, the first being specific (ZP-mediated) and the second non-specific (OVGP1 mediated).

Reviewer #2 (Public review):

Summary:

In the manuscript entitled "Oviductin sets the species-specificity of the mammalian zona pellucida", de la Fuente et al analyze the species specificity of sperm-egg recognition by looking at sperm binding and penetration of zonae pellucidae from different mammalian species and find a role for the oviductal protein OVGP1 in determining species specificity.

Strengths:

By combining sperm, oocytes, zona pellucida (ZP), and oviductal fluid from different mammalian species, they elucidate the essential role of OVGP1 in conferring species-specific fertilization.

Weaknesses:

Mice with OVGP1 deletion are viable and fertile. It would be quite interesting to investigate the species-specificity of sperm-ZP binding in this model. That would indicate whether OVGP1 is the only glycoprotein involved in determining species-specificity. Alternatively, the authors could immunodeplete OVGP1 from oviductal fluid and then ascertain whether this depleted fluid retains the ability to impede cross-species fertilization.

Comments on revisions:

This resubmission addresses most of my comments and concerns.

Reviewer #3 (Public review):

Summary:

The authors submitted a second revised manuscript that reports findings from a series of experiments suggesting that bovine oviductal fluid and species-specific oviductal glycoprotein (OVGP1 or oviductin) from bovine, murine, or human sources modulate the species specificity of bovine and murine oocytes.

Strengths:

The study reported in the manuscript deals with an important topic of interest in reproductive biology.

Weaknesses:

The authors submitted a second revised manuscript. Some of the previous questions are considered inadequate. There are still several problematic issues that require the authors' attention.

Author response:

The following is the authors’ response to the original reviews

Reviewer #3 (Recommendations for the authors):

Major concerns:

P.6, lines 223-224: The sentence sounds like the authors produced all the OVGP1s by themselves in their laboratories, which is not completely true. The recombinant human and mouse OVGP1s were purchased from OriGene. It is suggested that the authors should state and explain clearly here which OVGP1 is produced by their laboratories and that recombinant human and mouse OVGP1s were obtained and purchased from Origene.

It is already clearly included in the M&M.

P6, lines 227-229: The authors stated that "Western blots of the three OVGP1recombinants indicated expected sizes based on those of the proteins: 75 kDa for human and murine OVGP1 and around 60 kDa for bovine OVGP1 (Fig. 4B and S6)." I pointed out in my last review report that the size of the recombinant human OVGP1shown by the authors in their manuscript is not in agreement with what has been published previously in literature regarding the molecular weight of native human OVGP1 as well as that of recombinant human OVGP1. The authors did not address the above concern adequately. In fact, recombinant human OVGP1 has been produced a few years ago (Reproduction (2016) 152:561-573) and it has been previously demonstrated that a single protein band of approximately 110-130 kDa was detected for both native human OVGP1 (see Microscopy Research and Technique (1995) 32:57-69) and recombinant human OVGP1 (Reproduction (2016) 152:561-573; Carbohydrate Research (2012) 358:47-55) using antibodies specific for human OVGP1. Molecular weight of the protein core or polypeptide of human OVGP1 is approximately 75 kDa, but the glycosylated form of native human OVGP1 and recombinant human OVGP1 is approximately 110-130 kDa. Therefore, the authors might have been using the recombinant core protein of human OVGP1 instead of the fully glycosylated recombinant OVGP1 in their study. The same concern also applies to the commercially obtained mouse recombinant OVGP1 used by the authors in their study. I would also like to mention that the mature and fully glycosylated OVGP1s in mammals vary in molecular weight (90-95 kDa in domestic animals; 110-150 kDa in primates; 160-350 kDa in rodents). Again, the 75kDa of mouse OVGP1 detected by the authors could be the core protein or polypeptide of mouse OVGP1 instead of the fully glycosylated mouse OVGP1.

In our study, as previously mentioned, we included commercially available recombinant proteins from Origene for human and murine OVGP1, which are produced in mammalian cells, and we also produced and purified bovine OVGP1 in mammalian cells. Therefore, these proteins should be properly glycosylated. Moreover, we performed Western blot assays favouring the blotting of higher molecular weight proteins, ensuring the optimal conditions for the assay. Additionally, we tested the size of OVGP1 from murine and bovine oviductal fluids on the same blot. During oestrus, the size of OVGP1 from oviductal fluids matches that of the recombinant proteins, and this band is downregulated during anoestrus, confirming the proper size of recombinant protein.

P.7, lines 236 and 237: Please provide a figure or source to support the statement "...as confirmed by proteomics of the bands along with PEAKS Studio v11.5 search engine peptide identification software."

It is included in the text the amount of unique peptides obtained by Proteomics for OVGP1 identification over all protein groups identified.

P.7, lines 243 to 245: The statement "...using rabbit polyclonal antibody to human OVGP1 for bOVGP1 and endogenous OVGP1, and mouse monoclonal antibody against Flag (DDK)-tag for hOVGP1 and mOVGP1." is confusing and might be inaccurate. First of all, I wondered why the authors did not use an antibody against bovine OVGP1 for the recombinant bOVGP1 instead of using a rabbit polyclonal antibody to human OVGP1. Secondly, what does the "endogenous OVGP1" refer to in the statement? Thirdly, the authors in their study used the commercially available recombinant human OVGP1 and recombinant mouse OVGP1 purchased from Origene. Based on the data sheet provided by Origene, the tag used for both recombinant human OVGP1 and recombinant mouse is C-Myc/DDK-tag and not Flag-tag. Can the authors explain these discrepancies?

Firstly, for the recombinant protein of bOVGP1 we used the same antibody that we used in the Western blot for all the proteins and oviductal fluids because we do not have anti-His tag working for Immunofluorescence (the one we had only worked for Western blot) and neither we do not have any antibody against bovine OVGP1. In the case of human and murine since we had anti-Flag antibody that worked for Western blot and for immunofluorescence, we used this one. However, as has been shown in our figure and supplementary material, the antibody against human OVGP1 works properly for both techniques (Western blot and Immunofluorescence). Secondly, endogenous OVGP1 is referred to the OVGP1 present in the oviductal fluid. Thirdly, as you can see in the datasheet of the protein, the recombinant proteins purchased from Origene contains a c-myc tag (EQKLISEEDL) some amino acids and a ddk-tag (DYKDDDDK). The sequence of ddk is the same of Flag-tag (DYKDDDDK). Since the proteins have both tags we used the antibody against Flag (or ddk) epitope.

P12, lines 429-432: The newly added statement at the end of the Discussion saying "Additionally, future studies would be valuable to investigate whether incubating oocytes with oviductal fluid (or OVGP1) could reduce polyspermy in porcine IVF and whether ZPs could be leveraged to naturally enhance sperm selection in human ICSI" is very concerning and requires further attention. The statement reflects that the authors do not keep pace with and do not pay attention to what has been published in literature regarding porcine and human OVGP1s. In fact, porcine oviduct-specific glycoprotein (OVGP1) has already been reported to reduce the incidence of polyspermy in pig oocytes (Biology of Reproduction (2000) 63:242-250). Porcine oviductal fluid, used in porcine IVF, has also been found to exert a beneficial effect on oocytes by reducing the incidence of polyspermy without decreasing the penetration rate. (Theriogenology (2016) 86:495-502). Therefore, the studies deemed valuable by the authors to be investigated in the future have, in fact, already been carried out two decades ago by several other laboratories. I am surprised the authors were not aware of these published work in literature. All the above should have been incorporated in the Discussion.

This sentence is modified in the discussion and the references are included.

Furthermore, as mentioned earlier, recombinant human OVGP1 has also been produced (Reproduction (2016) 152:561-573), and recombinant human OVGP1 has been found to increase tyrosine phosphorylation of sperm proteins, a biochemical hallmark of sperm capacitation, and potentiate the subsequent acrosome reaction (Reproduction (2016) 152:561-573) as well as increase sperm-zona binding (Journal of Assisted Reproduction and Genetics (2019) 36:1363-1377). These earlier findings should be incorporated into the Discussion.

Thank you for your comment, but in this work we had not performed any experimental setting related to tyrosine phosphorylation and despite is a very interesting topic is not directly related to this work.

P.19, lines 678-683: Since the human and mouse recombinant oviductin proteins were purchased from Origene, the authors should be aware of the fact that these commercially available recombinant OVGP1s might not be fully glycosylated. While I appreciate the fact that the authors wanted to briefly describe how the human and mouse recombinant OVGP1s were prepared by the manufacturer, I strongly suggest that the authors should contact Origene, the manufacturer, for all information regarding the procedures for producing the human and mouse recombinant oviductin proteins. For example, the authors stated on lines 680-681 that "A sequence expressing FLAG-tagged epitope proteins (DYKDDDDK) was cloned into an expression vector." According to the data sheet provided by Origene, it appears that both human and recombinant oviductin proteins are C-Myc/DDK-tagged and not FLAG-tagged.

Thank you for your comment, as according to the sequence of Flag-tag it is matching with the sequence of the tag in the datasheet corresponding to DDK (this is in detail in previous comment). Besides, the protein is tagged also by C-Myc tag. Among both tags, the antibody selected to detect it was anti-Flag tag.

P.19, lines 692-697: The description of the primary and secondary antibodies used for detection of the various recombinant OVGP1s is also very confusing and not clearly presented. For example, it is mentioned here that "...membranes were...incubated with anti-OVGP1 rabbit monoclonal antibody for OVGP1,..". What specifically does "OVGP1" refer to here? The authors then stated that anti-Histamine Tag antibody was used to detect bOVGP1 and mOVGP1 and anti-Flag antibody was used to detect hOVGP1. As pointed out earlier, the human and mouse recombinant OVGP1s were produced using C-Myc/DDK tag and not His-tag or Flag-tag. Can the authors clarify these discrepancies?

We apologise for the complexity of the antibodies, we included in this paragraph the ones used to Western blot for both figures: anti- human OVGP1 was used for the principal figure that contains the three recombinant proteins and oviductal fluids; and the anti-Histidine and anti-Flag antibodies that are included in supplementary figure, specifically for recombinant bovine OVGP1 (Histidine tag) and for recombinant murine and human OVGP (DDK tag). A clarifying sentence has been included in the text.

P.31, lines 1143-1149: Figure 10 is not mentioned anywhere in the main text of the manuscript. Rewrite the second half of the sentence "...; being this specificity lost when OVGP1 is heterologous to the ZP (right diagram)." Which sounds awkward and grammatically not correct.

The figure is already mentioned in the text, thank you for your comment. The sentence is also corrected.

Other comments: P.1, the statement of "All authors contributed equally to this work" on line 14 can be deleted because detailed and specific contributions from each authors are listed in lines 1009-1017 on page 27.

Both authors contributed equally to this work, now is clear in authors contribution section.

P.2, lines 43 and 44: Do the authors mean "sperm-oocyte binding protein" instead of "sperm-oocyte fusion protein" in the sentence? "Fusion protein" is a protein composed of two or more domains encoded by different genes, or a hybrid molecule created by combining two different proteins for various purposes. I believe the term "fusion protein" is wrongly used in the sentence which should be rephrased with a proper term.

Done.

P2, line 73: Remove the comma after the word "Both".

Done.

P.5, line 179: "...mice ZP..." should be written as "...mouse ZP...".  

Done.

P.6, heading of 3rd paragraph on line 207: The term "binding" will be a better term than "fusion" used in the heading because the results do not actually show the fusion of the OVGP1 proteins with the ZP glycoprotein. Instead, binding of the OVGP1 proteins to the ZP occurred.

Done.

P.6, lines 215-217: Authors, please provide a reference or references to support the statement "Region A, corresponding to the amino acid end, shows high identity among monotremes, marsupials and placentals."

In the text was indicated a review (29) which includes the supporting idea of this statement for Figure 4. Moreover, we have included some if the references used for the description of the domains when performing the sequence alignment of Figure S5.

P.6, line 230 and line 233 on P.7: Authors, please be consistent in the use of either American English or British English. The word "oestrus" is British English whereas "estrus" is American English.

Done.

P.7, line 264: The word "sticking" used here means non-specific binding. I believe the author means specific binding here. If so, a more appropriate word should be used here instead of "sticking".

Done.

P.7, lines 267-269: This newly added sentence sounds very awkward and should be completely rewritten.

Done.

P.8, line 288: This reviewer finds it difficult to understand the meaning of the heading. The heading should be rephrased to bring out exactly what the authors want to say in well-written English.

Done.

P.8, line 290: The word "would" should be replaced by "could" in the sentence.

Done.

P.13, line 437: Authors, please provide the location of Sigma-Aldrich.

Done.

P.13, line 457: Here, the authors used "1800 rpm" to indicate the centrifugation speed but used the g-force elsewhere in the Materials and Methods. Please be consistent. The g-force is preferred.

Done.

P.14, lines 483-485: The procedure of sacrificing the cats should be provided in the Materials and Methods

Cats weren’t sacrificed they were vasectomized. It is now included in the text.

P.17, line 628: "...the ZPs were exposed or no exposed to..." should be written as "...the ZPs were either exposed or not exposed to...".

Done.

P.17, line 629: "...each groups were incubated with..." should be "...each group was incubated with...".

Done.

P.19, line 700: "As loading control, was used the primary antibody....." is not a complete sentence and it needs to be rewritten.

Done.

P.20, lines 744-754: For scanning electron microscopy and image processing, the procedures of prior treatment of the oocytes with and without oviductal fluid and OVGP1 should be included here.

Done.

P.21, line 756: It is stated here that "Two hundred isolated ZPs were treated with Clostridium perfringens neuraminidase....". However, it is not clear whether two hundred isolated ZPs of both porcine and murine ZPs were treated. Authors, please clarify.

We used 200 isolated ZPs of each specie, bovine and murine. It is classified in the text.

P.28, lines 1039 and 1040: The author only mentioned the use of bovine and murine sperm here. What about human sperm?

Done.

P.29, line 1076: "...in mammalian cells..." is very vague. Be specific what exactly the mammalian cells were.

Done.

P.29, line 1079: "Oviductal fluid from ovulated cows or anoestrus cows." is not a complete sentence and it needs to be rewritten.

Done.

eLife Assessment

This is a convincing study of the morphological properties of Purkinje cell dendrites and dendritic spines in adult humans and mice, and the anatomical determinants of multi-innervation by climbing fibers. The data will provide an important resource for the field of cerebellar computation.

Reviewer #1 (Public review):

Summary:

Busch and Hansel present a morphological and histological comparison between mouse and human Purkinje cells (PCs) in the cerebellum. The study reveals species-specific differences that have not previoulsy been reported despite numerous observations in these species. While mouse PCs show morphological heterogeneity and occasional multi-innervation by climbing fibers (CFs), human PCs exhibit a widespread, multi-dendritic structure that exceeds expectations based on allometric scaling. Specifically, human PCs are significantly larger, exhibit increased spine density, with a unique cluster-like morphology not found in mice.

Strengths:

The manuscript provides an exceptionally detailed analysis of PC morphology across species, surpassing any prior publication. Major strengths include a systematic and thorough methodology, rigorous data analysis, and clear presentation of results. This work is likely to become the go-to resource for quantitation in this field. The authors have largely achieved their aims, with the results effectively supporting their conclusions.

Weaknesses:

There are a few concerns that need to be addressed, specifically related to details of the methodolology as well as data interpretation based on the limits of some experimental approaches. Overall, these weaknesses are minor.

Comments on revisions:

The authors addressed my concerns in the revised manuscript. One bit of clarification, the defraction limit calculation involves the wavelength of light used for excitation not emission ("...for the minimum resolvable distance (R) given the fluorophore emission wavelength [l; 570nm for the Cy3 probe] and numerical aperture of the objective (NA) as follows:"). This is why a 2p system has less resolving power than a confocal system as it uses much longer wavelengths for excitation.

Reviewer #2 (Public review):

Summary:

This manuscript follows up on a previously published paper (Busch and Hansel 2023) which proposed that the morphological variation of dendritic bifurcation in Purkinje cells in mouse and human is indicative of the number of climbing fiber inputs, with dendritic bifurcation at the level of the soma resulting in a proportion of these neurons being multi-innervated. The functional and anatomical climbing fiber data was obtained solely from mice, since all human tissue was embalmed and fixed, and the extension of these findings to human Purkinje cells was indirect. The current comparative anatomy study aims to resolve this question in human tissue more directly and to further analyse in detail the properties of adult human Purkinje cell dendritic morphology.

Strengths:

The authors have carried out a meticulous anatomical quantification of human Purkinje cell dendrites, in tissue preparations with better signal to noise ratio than their previous study, comparing them with those from mice. They show that human PC dendrites are much larger than would be expected from straightforward scaling to brain size and, importantly, they now present immunolabelling results that trace climbing fiber axons innervating human PCs in a subset of the data. As well as providing detailed analyses of spine properties and interesting and unexpected new findings of human PC dendritic length and spine types, the work suggests that human PCs that have two clearly distinct dendritic branches have an approximately 80% chance of receiving more than one CF input, segregated across the two branches. Albeit entirely observational, the data will be of widespread interest to the cerebellar field, in particular those building computational models of Purkinje cells.

Weaknesses:

The work is, by necessity, purely anatomical. It remains to be seen whether there are any functional differences in ion channel expression or functional mapping of granule inputs to human PCs compared with the mouse that might mitigate the major differences in electronic properties suggested.

Comments on revisions:

I am happy with the updated manuscript in response to my suggestions and I have no further comments.

Author response:

The following is the authors’ response to the original reviews

Reviewer #1 (Public review):

Summary:

Busch and Hansel present a morphological and histological comparison between mouse and human Purkinje cells (PCs) in the cerebellum. The study reveals species- specific differences that have not previously been reported despite numerous observations of these species. While mouse PCs show morphological heterogeneity and occasional multi-innervation by climbing fibers (CFs), human PCs exhibit a widespread, multi-dendritic structure that exceeds expectations based on allometric scaling. Specifically, human PCs are significantly larger, and exhibit increased spine density, with a unique cluster-like morphology not found in mice.

Strengths:

The manuscript provides an exceptionally detailed analysis of PC morphology across species, surpassing any prior publication. Major strengths include a systematic and thorough methodology, rigorous data analysis, and clear presentation of results. This work is likely to become the go-to resource for quantitation in this field. The authors have largely achieved their aims, with the results effectively supporting their conclusions.

We are grateful to this reviewer for their thoughtful assessment that this work will be a go-to resource for the field.

Weaknesses:

There are a few concerns that need to be addressed, specifically related to details of the methodology as well as data interpretation based on the limits of some experimental approaches. Overall, these weaknesses are minor.

We thank this reviewer for their careful reading of the manuscript and for highlighting limitations and weaknesses in the methodology. We are in full agreement that while interpretation is somewhat limited, there is still value in their description. As detailed below in response to this reviewer’s recommendations, we provide more description of our imaging resolution. This additional detail clarifies that our quantitation is appropriate for the scale of the objects being measured and provides critical information to help readers assess the findings as they may pertain to their own work.

Reviewer #2 (Public review):

Summary:

This manuscript aims to follow up on a previously published paper (Busch and Hansel 2023) which proposed that the morphological variation of dendritic bifurcation in Purkinje cells in mice and humans is indicative of the number of climbing fiber inputs, with dendritic bifurcation at the level of the soma resulting in a proportion of these neurons being multi-innervated. The functional and anatomical climbing fiber data was obtained solely from mice since all human tissue was embalmed and fixed, and the extension of these findings to human Purkinje cells was indirect. The current comparative anatomy study aims to resolve this question in human tissue more directly and to further analyse in detail the properties of adult human Purkinje cell dendritic morphology.

Strengths:

The authors have carried out a meticulous anatomical quantification of human Purkinje cell dendrites, in tissue preparations with a better signal-to-noise ratio than their previous study, comparing them with those from mice. Importantly, they now present immunolabelling results that trace climbing fiber axons innervating human PCs. As well as providing detailed analyses of spine properties and interesting new findings of human PC dendritic length and spine types, the work confirms that human PCs that have two clearly distinct dendritic branches have an approximately x% chance of receiving more than one CF input, segregated across the two branches. Albeit entirely observational, the data will be of widespread interest to the cerebellar field, in particular, those building computational models of Purkinje cells.

We thank this reviewer for their positive and considered assessment of our work. We enthusiastically agree that while these data are descriptive in nature, they may be of interest across modalities of cerebellar research and will provide a more detailed framework for cross-species comparisons and single cell computational modeling, which remains a critical tool to explore the human case given the inaccessibility of physiological experimentation.

Weaknesses:

The work is, by necessity, purely anatomical. It remains to be seen whether there are any functional differences in ion channel expression or functional mapping of granule inputs to human PCs compared with the mouse that might mitigate the major differences in electronic properties suggested.

We are in full agreement with the reviewer that the focused anatomical description of this manuscript could not make strong assertions about function given that cellular and circuit physiology is determined by many additional factors that remain unexamined. We appreciate that the reviewer acknowledges that this is out of necessity as those factors are inaccessible to experimentation at the current time; however, we are enthusiastic that our current findings will motivate future work that will shed light on these critical additional features of the system, both in rodents and humans.

Reviewer 1 (Recommendations for the authors):

PCs are now known to be genetically diverse, with unique PC types found only in humans. Could this cellular diversity contribute to the differences observed between species in this study? This possibility should be at least discussed in the context of the findings.

We agree that this is a fascinating possibility. The perhaps most detailed recent study (Sepp et al., Nature 625, 2024) – in a conservative assessment – describes four developmental PC subtypes in mice that are identical in humans. The study points out that the subtype ratio changes over the course of development, though. Taken together with the possibility of additional human-specific subtypes, a genetic basis for morphological as well as physiological diversity arises. This is now discussed on p. 7. It needs to be kept in mind, however, that other factors, such as push-pull influences during tissue growth, might also play a role.

The human tissue used in this study was obtained from elderly individuals, while the mouse tissue was not. It is unclear whether the age difference might influence the findings, and this warrants further discussion or control.

We share this concern, in particular regarding the spine / spine cluster analysis as here tissue quality and or degenerative effects might play a role. We additionally analyzed a tissue sample from a 37 year-old human, and observed the same spine clusters as in the other human brains. This is now described on p. 4 of the revised manuscript.

The study includes spine size comparisons, but it is not clear if the point spread function (PSF) of the microscope provides the necessary resolution for these quantitative assessments. For instance, are multi-headed spines truly multi-headed, or could this be an artifact of limited resolution?

This is an important point. We addressed it by calculating the Rayleigh limit (more conservative than the Abbe limit) as 248.4nm for the equipment and conditions used (Methods, p. 22). On pages 3-5, we updated our Results section accordingly to point out what quantifications are well supported and discuss the limitations (p. 3-5).

Reviewer 2 (Recommendations for the authors):

This is nice work which must have been very time-consuming. It would be good to make sure that the technical details are properly discussed, to quantify the data properly. Please include details of how you measured the resolution of the microscope used to evaluate spine size.

See our response to the last comment of Referee 1 above.

The figure panels are mostly satisfactory, but they are exceptionally crowded and will probably be difficult to read at the final size. Some work tidying these would be worth it. In Figure 3B, include mention of open and blue triangles in legend. In 3E, the dendritic branches are shown at a different gray scale. You have not done this elsewhere, so probably good to mention it in the legend.

Figure 3 and its legend have been updated / improved accordingly.

The definition of horizontal and vertical is not absolutely clear. Perhaps re-assess this bit of the text. Does it mean that you did not include cells that were neither vertical nor horizontal?

We categorized those PCs as ‘vertical’ that have a >30° angle relative to the PC layer, and those as ‘horizontal’ that have a <30° angle relative to the PC layer. All PCs are covered by these categories. This is now described on p. 5.

eLife Assessment

This important study shows that the Nora virus, a natural Drosophila pathogen that also persistently infects many laboratory fly stocks, infects intestinal stem cells (ISCs), leading to a shorter life span and increased sensitivity to intestinal infection with the Pseudomonas bacterium. The authors provide convincing data to support their conclusions. The paper provides new insights into virus-host interactions in the Drosophila gut and serves as a warning for scientists who use the fruit fly as a model to study gut physiology.

Reviewer #1 (Public review):

Summary:

This important article reveals that the Nora virus can colonize the intestinal cells of Drosophila melanogaster, where it persists with minimal immediate impact on its host. However, upon aging, infection, or exposure to toxicants, stem cell activation induces Nora virus proliferation, enabling it to colonize enterocytes. This colonization disrupts enterocyte function, leading to increased gut permeability and a significant reduction in lifespan. Results are convincing with an important impact on the Drosophila community.

Strengths:

(1) Building on previous studies by Habayeb et al. (2009) and Hanson et al. (2023), this study highlights cryptic Nora virus infection as a crucial factor in aging and gut homeostasis in Drosophila melanogaster.

(2) Consistent with the oral route of Nora virus transmission, the study demonstrates that the virus resides in intestinal stem cells, with its replication directly linked to stem cell proliferation. This process facilitates the colonization of enterocytes, ultimately disrupting intestinal function.

(3) The study establishes a clear connection between stem cell proliferation and virus replication, suggesting that various factors - such as microbiota, aging, diet, and injury - can influence Nora virus dynamics and associated pathology.

(4) The experimental design is robust, comparing infected flies with virus-cured controls to validate findings.

Weaknesses:

(1) The study does not explore or discuss how oral ingestion of Nora virus leads to the colonization of stem cells, which are located basally in the gut. This mechanism should be discussed.

(2) The authors fail to detect Dicer-GFP fusion protein expression in stem cells, a finding that could explain why the virus persists in these cells. Further investigation is needed to determine whether RNAi functions are effective in stem cells compared to enterocytes. For clarification, the authors could cross esg-Gal4 UAS-GFP and Myo-Gal4 UAS-GFP with UAS GFP-RNAi and/or express a Dicer-GFP construct under a stem cell-specific driver.

(3) The presentation of experimental parameters (e.g., pathogen type, temperature, time points) should be improved in the results section and at the top of the figures to enhance clarity. Additionally, details regarding the mode of oral infection (continuous exposure vs. single feeding on a filter) should be specified. Given that fly stock flipping frequency influences microbiota load (as noted in Broderick et al.), this should be reported, especially for lifespan studies.

(4) To confirm that enterocyte colonization requires stem cell proliferation and differentiation, the authors should analyze Nora virus localization in JAK-STAT-deficient flies infected with bacteria or toxicants. This would help determine whether the virus can infect enterocytes in the absence of enterocyte differentiation, but stimulation of stem cells.

(5) The study does not discuss the spatial distribution of Nora virus infection along the gut. Specifically, it remains unclear whether viral colonization is higher in gut regions R2 and R3, which contain proliferative stem cells. Addressing this could provide valuable insights into the virus's infection dynamics.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors report that Nora virus, a natural Drosophila pathogen that also persistently infects many laboratory fly stocks, infects intestinal stem cells (ISCs), leading to a shorter life span and increased sensitivity to intestinal infection with the Pseudomonas bacterium. Nora virus infection was associated with an increased proliferation of ISC and disrupted gut barrier function. Genetically, the authors show that increased ISC division in Nora virus and Pseudomonas coinfected flies is driven by signaling through the JAK-STAT pathway and apoptosis.

Accordingly, blocking apoptosis and JAK-STAT signaling reduces viral load, suggesting that in this context the JAK-STAT pathway is proviral in contrast to other previous observations in systemically infected flies. This work adds to the findings of another recent paper showing that another persistent fruit fly virus, Drosophila A virus, also increases ISC proliferation and decreases gut barrier function. Intestinal viruses should therefore be considered confounders in studies of fly intestinal physiology.

Strengths:

Overall, the data are convincing and robust, starting with two wildtype fly stocks (Ore-R strain) that differ in their Nora virus infection status, followed by experiments in which cleared stocks are reinfected with a purified Nora virus stock preparation. The conclusions of the paper will be of interest to scientists working on insect physiology, virology, and immunology, but should also serve as a warning for scientists that use the fly as a model to study gut physiology.

Weaknesses:

The title does not seem to be fully supported by the data. While the authors convincingly show the increased sensitivity to Pseudomonas infection, effects on another tested bacterium, Serratia marcescens, were not significantly different between Nora-virus-infected and non-infected flies. Thus effects of 'intestinal infection' seem to be too broad a claim. Also, whether the Nora virus increases sensitivity to oxidative stress is not so clear to me: the figure that supports this claim is the survival assay of Figure 5F. However, the difference in survival between control and paraquat-treated Nora (-) flies seems to be in the same order as between control and paraquat-treated Nora (+) flies. Rather, cause and effect seem to be the reverse: paraquat increases ISC proliferation, higher viral loads, and consequently shorter survival. I suggest rephrasing the title and conclusions accordingly.

Quantification of immunofluorescence microscopy is missing, rendering the images somewhat anecdotal. Quantification should be provided. It will then also be of interest to quantify the number of Nora(+) cells and the Nora virus levels per infected cell (e.g. Figure 5H). Also, the claim that the Nora virus initially infects ISC and later (upon stress) infects enterocytes requires quantification.

Genetic support for the role of the JAK-STAT pathway in driving ISC proliferation and supporting Nora virus replication is convincing. It would also be of interest to analyze other pathways implicated in ISC proliferation (e.g. JNK, EGFR), especially given the observations of Nigg et al, showing an involvement of STING/NF-kB and EGFR pathway in driving intestinal phenotypes of Drosophila A virus-infected flies (doi: 10.1016/j.cub.2024.05.009).

Figure 5E: An intriguing observation is that GFP:Dicer2 seems to be unstable in Nora virus-infected cells. Here, GFP control driven by the same driver line would be required to confidently conclude that this is due to an effect on Dicer-2 specifically.

Legends are mostly conclusive, and essential information about the experimental setup is missing in the captions of multiple figures, making the interpretation of the data difficult. See my private recommendations for suggestions to improve the data presentation.

Reviewer #3 (Public review):

Summary:

Franchet et al. sought to characterize the impact of Nora virus on host lifespan and sensitivity to a variety of infectious or stressful treatments. Through careful and rigorous analyses, they provide evidence that the Nora virus greatly impacts fly survival to infection, overall lifespan, and intestinal integrity. The authors have been thorough and rigorous, and the experimental evidence including proper isolation of the virus and Koch's Postulate reinoculation of the organism is excellent. The additional work is valuable and to the gold standard of the field, characterizing the pathology of the gut, including data showing gut leakage, the presence of the virus in the intestinal stem cells, and the importance of stem cell proliferation for virus replication and spread using elegant genetic tools to block stem cell proliferation or enterocyte death.

Strengths:

The authors have been rigorous and careful. The initial finding is presented through the lens of two related strains differing in virus infection. From there, the authors characterized the virus and isolated a purified culture, which they used to reinoculate a cleared strain to demonstrate proper Koch's Postulate satisfaction. The authors have also probed various parameters in terms of dietary importance in relevant conditions for many experiments. The additional work to characterize the pathology of the gut is compelling, using genetic tools to block or allow intestinal stem cell proliferation and enterocyte death through JAK-STAT and JNK signalling alongside the tracing of virus presence using a Nora virus antibody. JAK-STAT and JNK are previously described as regulators of these processes, making these tools appropriate and convincing. It is also interesting to see good evidence that the virus itself is damaging, rather than simply permitting coinfection by gut microbes (which does happen).

Weaknesses:

The claim that Dcr2 is not abundant in ISCs because the protein is not stable is logically consistent and reasonable. Perhaps I missed this, but the authors could additionally knock down or use somatic CRISPR to delete Dcr2 in ISCs to test whether a lack of Dcr2 underlies sensitivity. In this experiment, the expectation would be that depleting Dcr2 in ISCs genetically would make little difference to susceptibility overall compared to controls. This is not an essential experiment request.

eLife Assessment

This important research addresses the effects of subjective control and task difficulty on experienced stress using a novel behavioral task in two, large online samples. Convincing evidence is provided, establishing internal and external task validity and a relationship with individual differences in relevant mental health constructs. Evidence for the core claims could be strengthened by disentangling the effects of controllability from those of reward rate and adjusting data parcellation for computing internal consistency. This work will be of interest to psychologists and clinicians studying controllability, stress, and psychopathology.

Reviewer #1 (Public review):

Summary:

This work investigated how the sense of control influences perceptions of stress. In a novel "Wheel Stopping" task, the authors used task variations in difficulty and controllability to measure and manipulate perceived control in two large cohorts of online participants. The authors first show that their behavioral task has good internal consistency and external validity, showing that perceived control during the task was linked to relevant measures of anxiety, depression, and locus of control. Most importantly, manipulating controllability in the task led to reduced subjective stress, showing a direct impact of control on stress perception. However, this work has minor limitations due to the design of the stressor manipulations/measurements and the necessary logistics associated with online versus in-person stress studies.

Nevertheless, this research adds to our understanding of when and how control can influence the effects of stress and is particularly relevant to mental health interventions.

Strengths:

The primary strength of this research is the development of a unique and clever task design that can reliably and validly elicit variations in beliefs about control. Impressively, higher subjective control in the task was associated with decreased psychopathology measures such an anxiety and depression in a non-clinical sample of participants. In addition, the authors found that lower control and higher difficulty in the task led to higher perceived stress, suggesting that the task can reliably manipulate perceptions of stress. Prior tasks have not included both controllability and difficulty in this manner and have not directly tested the direct influence of these factors on incidental stress, making this work both novel and important for the field.

Weaknesses:

One minor weakness of this research is the validity of the online stress measurements and manipulations. In this study, the authors measure subjective stress via self-report both during the task and also after either a Trier Social Stress Test (high-stress condition) or a memory test (low-stress condition). One concern is that these stress manipulations were really "threats" of stress, where participants never had to complete the stress tasks (i.e., recording a speech for judgment). While this is not unusual for an in-lab study and can reliably elicit substantial stress/anxiety, in an online study, there is a possibility for communication between participants (via online forums dedicated to such communication), which could weaken the stress effects. That said, the authors did find sensible increases and decreases of perceived stress between relevant time points, but future work could improve upon this design by including more complete stress manipulations and measuring implicit physiological signs of stress.

Reviewer #2 (Public review):

Summary:

The authors have developed a behavioral paradigm to experimentally manipulate the sense of control experienced by the participants by changing the level of difficulty of a wheel-stopping task. In the first study, this manipulation is tested by administering the task in a factorial design with two levels of controllability and two levels of stressor intensity to a large number of participants online while simultaneously recording subjective ratings on perceived control, anxiety, and stress. In the second study, the authors used the wheel-stopping task to induce a high sense of controllability and test whether this manipulation buffers the response to a subsequent stress induction when compared to a neutral task, like looking at pleasant videos.

Strengths:

(1) The authors validate a method to manipulate stress.<br /> (2) The authors use an experimental manipulation to induce an enhanced sense of controllability to test its impact on the response to stress induction.<br /> (3) The studies involved big sample sizes.

Weaknesses:

(1) The study was not preregistered.

(2) The control manipulation is conflated with task difficulty, and, therefore the reward rate. Although the authors acknowledge this limitation at the end of the discussion, it is a very important limitation, and its implications are not properly discussed. The discussion states that this is a common limitation with previous studies of control but omits that many studies have controlled for it using yoking.

(3) The methods are not always clear enough, and it is difficult to know whether all the manipulations are done within-subjects or some key manipulations are done between subjects.

(4) The analysis of internal consistency is based on splitting the data into odd/even sliders. This choice of data parcellation may cause missed drifts in task performance due to learning, practice effects, or tiredness, thus potentially inflating internal consistency.

(5) Study 2 manipulates the effect of domain (win versus loss WS task), but the interaction of this factor with stressor intensity is not included in the analysis.

This study will be of interest to psychologists and cognitive scientists interested in understanding how controllability and its subjective perception impact how people respond to stress exposure. Demonstrating that an increased sense of control buffers/protects against subsequent stress is important and may trigger further studies to characterize this phenomenon better. However, beyond the highlighted weaknesses, the current study only studied the effect of stress induction consecutive to the performance of the WS task on the same day and its generalizability is not warranted.

Reviewer #3 (Public review):

Summary:

This is an interesting investigation of the benefits of perceiving control and its impact on the subjective experience of stress. To assess a subjective sense of control, the authors introduce a novel wheel-stopping (WS) task where control is manipulated via size and speed to induce low and high control conditions. The authors demonstrate that the subjective sense of control is associated with experienced subjective stress and individual differences related to mental health measures. In a second experiment, they further show that an increased sense of control buffers subjective stress induced by a trier social stress manipulation, more so than a more typical stress buffering mechanism of watching neutral/calming videos.

Strengths:

There are several strengths to the manuscript that can be highlighted. For instance, the paper introduces a new paradigm and a clever manipulation to test an important and significant question. Additionally, it is a well-powered investigation that allows for confidence in replicability and the ability to show both high internal consistency and high external validity with an interesting set of individual difference analyses. Finally, the results are quite interesting and support prior literature while also providing a significant contribution to the field with respect to understanding the benefits of perceiving control.

Weaknesses:

There are also some questions that, if addressed, could help our readership.

(1) A key manipulation was the high-intensity stressor (Anticipatory TSST signal), which was measured via subjective ratings recorded on a sliding scale at different intervals during testing. Typically, the TSST conducted in the lab is associated with increases in cortisol assessments and physiological responses (e.g., skin conductance and heart rate). The current study is limited to subjective measures of stress, given the online nature of the study. Since TSST online may also yield psychologically different results than in the lab (i.e., presumably in a comfortable environment, not facing a panel of judges), it would be helpful for the authors to briefly discuss how the subjective results compare with other examples from the literature (either online or in the lab). The question is whether the experienced stress was sufficiently stressful given that it was online and measured via subjective reports. The control condition (low intensity via reading recipes) is helpful, but the low-intensity stress does not seem to differ from baseline readings at the beginning of the experiment.

(2) The neutral videos represent an important condition to contrast with WS, but it raises two questions. First, the conditions are quite different in terms of experience, and it is interesting to consider what another more active (but not controlled per se) condition would be in comparison to the WS performance. That is, there is no instrumental action during the neutral video viewing (even passive ratings about the video), and the active demands could be an important component of the ability to mitigate stress. Second, the subjective ratings of the stress of the neutral video appear equivalent to the win condition. Would it have been useful to have a high arousal video (akin to the loss condition) to test the idea that experience of control will buffer against stress? That way, the subjective stress experience of stress would start at equivalent points after WS3.

(3) For the stress relief analysis, the authors included time points 2 and 3 (after the stressor and debrief) but not a baseline reading before stress. Given the potential baseline differences across conditions, can this decision be justified in the manuscript?

(4) Is the increased control experience during the losses condition more valuable in mitigating experienced stress than the win condition?

(5) The subjective measure of control ("how in control do you feel right now") tends to follow a successful or failed attempt at the WS task. How much is the experience of control mediated by the degree of experienced success/schedule of reinforcement? Is it an assessment of control or, an evaluation of how well they are doing and/or resolution of uncertainty? An interesting paper by Cockburn et al. 2014 highlights the potential for positive prediction errors to enhance the desire for control.

(6) While the authors do a very good job in their inclusion and synthesis of the relevant literature, they could also amplify some discussion in specific areas. For example, operationalizing task controllability via task difficulty is an interesting approach. It would be useful to discuss their approach (along with any others in the literature that have used it) and compare it to other typically used paradigms measuring control via presence or absence of choice, as mentioned by the authors briefly in the introduction.

(7) The paper is well-written. However, it would be useful to expand on Figure 1 to include a) separate figures for study 1 (currently not included) and 2, and b) a timeline that includes the measurements of subjective stress (incorporated in Figure 1). It would also be helpful to include Figure S4 in the manuscript.

Author response:

Conflation of control, difficulty and reward rate

In response to the comment of control being conflated with task difficulty (and thus reward rate) that the reviewer feels is not adequately discussed in the paper, we will add more to this point in our discussion, especially in relation to previous literature. It is important to note, however, that our measure of perceived difficulty was included in analyses assessing the fluctuations in stress and control. Subjective control still had a unique effect on the experience of stress over and above perceived difficulty, suggesting that subjective control explains variance in stress beyond what is accounted for by perceived difficulty. We will also include additional analyses in which we include the win rate (i.e. percentage of all trials won) as a covariate when assessing the relationship between subjective control, perceived difficulty and subjective stress, which shows that win rate does not predict stress, but subjective control and perceived difficulty still uniquely predict subjective stress. The results of this will be added and elaborated further in the discussion.

Neutral video condition

In response to the comment of the neutral video condition not being active enough, we believe that any task with action-outcome contingencies would have a degree of controllability. To better distinguish experiences of control (WS task) to an experience of no/neutral control (i.e., neither high nor low controllability), we decided to use a task in which no actions were required during the task itself, although concentration was still required (attention checks regarding the content of the videos and ratings of the videos).

The suggestion of having a high arousal video condition would indeed be interesting to test how experiencing ‘neutral’ control and high(er) stress levels preceding the stressor task influences stress buffering and stress relief. This is a good suggestion for future work that we can include in the discussion section.

The TSST version (online and anticipatory)

We will add more information regarding prior literature that the Trier Social Anticipatory Stress test has found physiological and psychological correlates (e.g. Nasso et al., 2019, Schlatter et al., 2021, Steinbeis et al., 2015), suggesting that the anticipation is still a valid stress manipulation despite participants not performing the actual speech task. Further, the TSST had a significant impact on subjective stress in the expected direction demonstrating that it was effective at eliciting subjective stress.

Internal consistency

We will parcellate the timepoints differently (not just odd/even sliders) to test the internal consistency, for example a random split or first half/second half.

Effect of win-loss domain in Study 2

We will run additional analyses testing the interaction of Domain (win or loss) with stressor intensity when predicting the stress buffering and stress relief effects. To test whether the loss domain is more valuable at mitigating experiences of stress than the win condition, we will run additional analyses with just the high control conditions (WS task) to test for a Domain*Time interaction, as we cannot test a Control*Domain*Time interaction in the full model given that we do not have ‘Domain’ for the video (neutral control) condition.

Stress relief analyses

Regarding the stress relief analyses (timepoints 2 and 3) and ‘baseline’ stress (timepoint 1), we will add to the manuscript that there is no significant difference in stress ratings between the high control and neutral control (collapsed across stress and domain) after the WS/video task, hence why we do not think it’s necessary to include in the stress relief model. Nevertheless, we will include a sensitivity analysis in the supplementary material to test the Timepoint*Control interaction (of stress relief – timepoints 2 and 3) when including timepoint 1 stress as a covariate.

Clarity

We will add more clarity in the methods section regarding within- and between-subject manipulations. We will also add Figure S4 to the main manuscript and expand Figure 1 to include both Studies 1 and 2 and a timeline of when subjective stress was assessed throughout the experiment.

eLife Assessment

The authors study the context of the skeletal remains of three individuals and associated sediment samples to conclude that the hominin species Homo naledi intentionally buried their dead. Demonstration of the earliest known instance of intentional funerary practice - with a relatively small-brained hominin engaging in a highly complex behavior that has otherwise been observed from Homo sapiens and Homo neanderthalensis - would represent a landmark finding. The authors have revised their manuscript extensively in light of the reviews of their initial submission, with improved illustration, context, discussion, and theoretical frameworks, leading to an improved case supporting their conclusion that Homo naledi intentionally buried their dead. One of the reviewers concludes that the findings convincingly demonstrate intentional burial practices, while another considers evidence for such an unambiguous conclusion to be incomplete given a lack of definitive knowledge around how the hominins got into the chamber. We look forward to seeing the continued development and assessment of this hypothesis. It is worth noting that the detailed reviews (both rounds) and comprehensive author response are commendable and consequential parts of the scientific record of this study. The editors note that the authors' response repeatedly invokes precedent from previous publications to help justify the conclusions in this paper. While doing so is helpful, the editors also note that scientific norms and knowledge are constantly evolving, and that any study has to rest on its own scientific merit.

Reviewer #1 (Public review):

Thank you for allowing me to review the paper "Evidence for deliberate burial of the dead by Homo naledi". This remains a very important site for paleoanthropology. I appreciate the work that the crew, especially the junior members of the team, put into this massive project. I appreciate that the authors did revise the paper since that is not a requirement of eLife. Extensive reviews by peer-reviewers have been provided for this paper, as well as professionally published replies (Martinón-Torres et al., 2023; Foecke et al., 2023). The composition, and citations of this version are much improved, though important information, some requested by reviewers, are buried in the supplementary section. It seems important that the authors make these sections more easily accessible to the general reader. The length of the paper is also unnecessary and impedes the readability of the work. Concise clarity is an expectation of most journals. The Netflix documentary was made to appeal to a mass audience, I would hope that the goal of the accompanying publication would be to enable readers to fully comprehend the work behind the claims.

This version of the paper considers at great length many possibilities for how the H. naledi skeletal material came to rest in the cave system with some additional figures and data provided. However, quite a lot is still unclear. In my original review I stated, "The authors have repeatedly described how incredibly challenging it is to get into and out of this cave system and all of its chambers." This was a point emphasized in the Netflix documentary. In this version of the paper the authors have included within the supplementary section a brief discussion of other entrances. The work by Robbins et al. 2021 (a peer-reviewed paper in the impact factor rated journal Chemical Geology) is extremely relevant here. In this revision it is noted in the supplementary section that if the Postbox chamber was used as an opening, it would have reduced the length of the access to the system by 80 m. This fact seems important. This section should be moved out of the supplementary material and expanded because the conclusions published by Robbins et al. (2021) indicate a completely different route by which H. naledi accessed the cave, but this is hardly mentioned in the revision and deserves attention. To quote the Robbins et al.'s (2021) discussion section 6.3:

"We acknowledge that additional data is required in order to confidently assess the relative timing of the Dragon's Back collapse and entry of H. naledi. Nonetheless, the stratigraphic and geochronologic observations presented here, together with those previously published (Dirks et al., 2017) are consistent with the following scenario. Prior to the collapse of the Dragon's Back, sometime before 241 ka (new minimum age for H. naledi from RS68), the cave could be entered by H. naledi via a shaft in the roof of the Postbox Chamber. From there H. naledi could walk along a straight passage that follows a gently descending, SW trending fracture into the Dragon's Back Chamber and, with the Dragon's Back block still attached to the roof, would have only needed to climb over a ~5 m high sill to access the Dinaledi Subsystem behind it. This sill and narrow fracture system behind the Dragon's Back block would have been a major impediment to any flood waters and most other fauna into the Dinaledi Subsystem, but it would have been a more accessible route than that today."

The paper's conclusion continues, "The new dates further constrain the minimum age of H. naledi to 241 ka. Thus, H. naledi entered the subsystem between 241 ka and 335 ka, during a glacial period, when clastic sediment along the access route into the Dinaledi Subsystem experienced erosion. H. naledi would have probably entered the cave in the same way as the clastic sediments did, through an opening in the roof of the Postbox Chamber and may have entered via the Dragon's Back Chamber by climbing a 5 m high sill and passing below the Dragon's Back Block that was then still attached to the roof, to enter the Dinaledi Subsystem. In this context it is important to emphasize that it was not the Dragon's Back Block that prevented high-energy transport of coarse siliciclastic sediment from the Dragon's Back Chamber into the Dinaledi Subsystem, but rather the in situ floor block in the back wall of the Dragon's Back Chamber, against which the Dragon's Back Block slumped after it fell." This conclusion is very different from the complex pathway suggested by Berger et al. Martinón-Torres et al., 2023 also requested elaboration on this point in their reply by stating, "Moreover, recent studies by the Rising Star Cave team also point to a possible different and easier accesses for H. naledi into the fossil-bearing cave chambers than the current restricted access chute used by the research team, making clear that the degree of accessibility remains an open question (Robbins et al., 2021). Based on extensive dating studies of speleothem, this research (Robbins et al., 2021) implies that prior to 241 ka and the collapse of the Dragon's Back block hominins and other species could have more easily entered the cave via the Post Box Chamber and beneath the Dragon's Back Block before it fell. This gives access to a series of rifts that allow easier entry to the Dinaledi and other chambers beyond the present-day chute."

Because this paper introduces very different sets of possibilities, it seems impossible to derive an understanding of the processes that occurred 335-241 ka throughout the cave system without going into detail on these other openings, especially openings that are hypothesized to have been used by the hominins in question.

The world cares deeply about the H. naledi hominins and their story. I hope that in the coming years these issues are addressed, and perhaps other independent teams are allowed to do a full analysis since science is about replication. In any case, the excavation team has contributed important fossils to paleoanthropology.

Literature cited:

Foecke, Kimberly K., Queffelec, Alain, & Pickering, Robyn. (2023). No Sedimentological Evidence for Deliberate Burial by Homo naledi - A Case Study Highlighting the Need for Best Practices in Geochemical Studies Within Archaeology and Paleoanthropology. PaleoAnthropology, 2024. https://doi.org/10.48738/202x.issx.xxx

Martinón-Torres, M., Garate, D., Herries, A. I. R., & Petraglia, M. D. (2023). No scientific evidence that Homo naledi buried their dead and produced rock art. Journal of Human Evolution, 103464. https://doi.org/10.1016/j.jhevol.2023.103464

Robbins, J. L., Dirks, P. H. G. M., Roberts, E. M., Kramers, J. D., Makhubela, T. V., HilbertWolf, H. L., Elliott, M., Wiersma, J. P., Placzek, C. J., Evans, M., & Berger, L. R. (2021). Providing context to the Homo naledi fossils: Constraints from flowstones on the age of sediment deposits in Rising Star Cave, South Africa. Chemical Geology, 567, 120108. https://doi.org/10.1016/j.chemgeo.2021.120108

Reviewer #2 (Public review):

Before providing my review of the revised version of this study by Berger et al., which explores potential deliberate burials of Homo naledi within the Rising Star Cave System, I would like to briefly summarize the key points from my previous review of the earlier version (in 2023). Summarizing my previous review will provide context for assessing how effectively the revised study addresses the concerns I raised previously (in 2023).

In my earlier comments, I highlighted significant methodological and analytical shortcomings that, in my view, undermined the authors' claim of intentional burials by Homo naledi. While the study presented detailed geological and fossil data, I found the evidence for intentional burials unconvincing due to insufficient application of archaeothanatological principles and other methodological gaps.

My key concerns included:

(1) The absence of a comprehensive archaeothanatological analysis, particularly with respect to taphonomic changes, bone articulations, and displacement patterns such as the collapse of sediments and bone remains into voids created by decomposition.

(2) Missing or unclear illustrations of bone arrangements, which are critical for interpreting burial positions and processes.

(3) A lack of detailed discussion on the sequence of decomposition, joint disarticulation, sediment infill, and secondary bone displacement.

To convincingly support claims of deliberate burial, I argued that the study must reconstruct the timeline and processes surrounding death and deposition while clearly distinguishing natural taphonomic changes from intentional human actions. I emphasized the importance of integrating established archaeothanatological frameworks, such as those outlined by Duday et al. or Boulestin et al., to provide the necessary analytical rigor.

I will now explain how the revised version of this study has successfully addressed all the concerns raised in my previous review and why I now think that the authors provide sufficient evidence for the presence of "repeated and patterned" deliberate burials (referred to as "cultural burials" by the authors) by Homo naledi within the Rising Star Cave System.

In their revised manuscript, the authors have implemented substantial improvements in methodology, analytical depth, and overall presentation, which have effectively resolved the critical issues I previously highlighted. These revisions greatly strengthen their argument for intentional funerary practices. Importantly, the authors remain cautious in their interpretation of the evidence, explicitly refraining from inferring "symbolic" behavior or complex cognitive motivations behind these burials. Instead, they focus on presenting clear evidence for deliberate, patterned practices while leaving the broader implications for Homo naledi's cultural and cognitive capacities open for further investigation. This cautious approach adds to the credibility of their conclusions and avoids overextending the interpretation of the data.

The authors' enhanced application of archaeothanatological principles now offers a more comprehensive and convincing interpretation of the burial features. Key gaps in the earlier version, such as the absence of detailed reconstructions of taphonomic processes, bone articulations, and displacement patterns, have been addressed with thorough analyses and clearer illustrations. The study also now includes a well-structured timeline of events surrounding death and deposition, demonstrating an improved ability to differentiate between natural processes and deliberate human actions. These additions lend greater clarity and rigor to the evidence, making the argument for intentional burials both robust and persuasive.

Furthermore, the revised study presents detailed data on skeletal arrangements, decomposition sequences, and spatial patterns. This information is now relatively well illustrated and contextualized, enabling readers to better understand the complex processes involved in these burial practices. Importantly, the authors provide a stronger theoretical framework, integrating established archaeothanatological methodologies and taphonomic studies that situate their findings within broader archaeological and anthropological discussions of funerary behavior.

That being said, there remain relatively minor issues that could be refined further. Addressing these would help ensure the study is as clear and accessible as possible to the reader. Such adjustments would enhance the overall readability and reinforce the study's impact within the scientific community.

A - Suggested changes:

While the revised version of this study marks a significant improvement, successfully addresses my previous major concerns and provides a convincing argument for deliberate burials by Homo naledi, I believe that including both one summary table + one summary figure for each of the three main locations and the-Hill Antechamber, and Dinaledi Chamber (Feature 1 and Puzzle Box)-would further enhance the clarity and accessibility of the findings. Such tables and figures would serve as a valuable reference, allowing readers to more easily follow how the detailed patterns observed at each site fit the criteria for distinguishing intentional from natural processes.

The summary tables should consolidate key information for each location, such as:

(1) Bone articulations: A comprehensive list of articulated skeletal elements, categorized by their anatomical relationships (e.g., labile vs. stable articulations).

(2) Displacement patterns: Documentation of any spatial shifts in bone positions, noting directions and extents of disarticulation.

(3) Sequence of decomposition: Observations regarding the sequence of decomposition, joint disarticulation and associated changes in bone arrangements.

(4) Sediment interaction: Notes on sediment infill and its timing relative to decomposition, including evidence of secondary voids or delayed sediment deposition.

(5) Distinguishing criteria: Clear indications of how each observed pattern supports intentional burial (e.g., structured placement, lack of natural transport mechanisms) versus natural processes (e.g., random dispersal, sediment-driven bone displacement).<br /> Including such tables would not only summarize the complex taphonomic and archaeothanatological data but also allow readers to quickly assess how the evidence supports the authors' conclusions. This approach would bridge the gap between the detailed narrative descriptions and the criteria necessary to differentiate deliberate funerary practices from natural occurrences.

To streamline the main text further, many of the detailed descriptions of individual bones, specific displacement measurements, and other intricate observations could be moved to the supplementary data. This reorganization would maintain the richness of the data for those who wish to explore it in depth, while the summary tables would present the key findings concisely in the main text. This balance between accessibility and detail would ensure that the study appeals to both specialists requiring comprehensive data and readers looking for an overarching understanding of the findings.

In addition to these structural changes, it is crucial to ensure that evidence is consistently illustrated throughout the text.

Importantly the skeletal part representation is provided for Dinaledi Feature 1 in Figure 14, but similar data is not presented for the other burial features, such as those in the Hill Antechamber or Puzzle Box. This inconsistency could make it more challenging for readers to compare the features and fully appreciate the patterns of burial behavior across the different locations. Ensuring that similar types of evidence and analyses are presented uniformly for all features would strengthen the study and make its conclusions more cohesive and compelling.

Adding supplementary figures to represent the skeletal part distribution (as in Figure 14) within each excavated area (i.e., not only for Dinaledi Feature 1 but also for Hill Antechamber and Puzzle Box) would significantly enhance the study's clarity and accessibility. These figures could provide a visual summary of skeletal part representation, allowing readers to easily understand the nature of human remains within each burial context.

Specifically, such figures could:

(1) Illustrate Skeletal Part Representation: By visually mapping the presence and location of various skeletal elements, the figures would make it easier for readers to assess the completeness and arrangement of remains in each feature. This is particularly important for interpreting patterns of bone articulation and disarticulation.<br /> For example, it is quite challenging to determine the exact number and characteristics of the human skeletal remains identified within the Puzzle Box and those recovered through the "subsurface collection" in its surrounding area. The authors state that "at least six individuals" were identified in this area (during "subsurface collection") but provide no further clarification. They simply mention that "most elements" were described previously, without specifying which elements or where this prior description can be found.

(2) Highlight Articulations and Displacements: Figures could indicate which bones are articulated and their relative positions, as well as the spatial distribution of disarticulated elements. This would provide a clear visual context to support interpretations of taphonomic processes.

(3) Facilitate Comparisons Across Locations: By presenting skeletal part representation consistently for each location, the figures would enable readers to directly compare features, reinforcing the argument for "repeated and patterned" behavior.

(4) Simplify Complex Data: Instead of relying solely on textual descriptions, the visual format would allow readers to quickly grasp the key findings, making the study more accessible to a broader audience

By including such figures alongside the proposed summary tables in the main text, the study would achieve a balance between detailed narrative descriptions and concise, visual representation of the data. This approach would strengthen the overall presentation and support the authors' conclusions effectively.

Again, by presenting the data in a structured and comparative format, the new tables + figures could also highlight the differences and similarities between the three locations. This would reinforce the argument for "repeated and patterned" behavior, as the tables would make it easier to observe consistent burial practices across different contexts within the Rising Star Cave System.

Adding these summary tables + figures, ensuring consistent presentation of evidence, and reallocating detailed descriptions to supplementary materials would not require significant new analysis. However, these organizational adjustments would greatly enhance the study's clarity, readability, and overall impact.

B - A few additional changes are needed:

Figure 8: This figure is critical but lacks clarity. Specifically:

Panels 8a-c suffer from low contrast, making details difficult to discern.<br /> Panel 8d (sediment profile) is too small and lacks annotations that would aid interpretation.<br /> Figure S7: While this figure has significantly better contrast than Figures 8a-c, I am unable to identify the "articulated foot ... at right of frame," as mentioned in the caption. Please clarify this by adding annotations directly to the figure.

Page 4, 2nd paragraph: In the sentence "Researchers thus have diverse opinions about how to test whether ...," the word "opinions" should be replaced with a more precise term, such as "approaches."

C - In conclusion, I am impressed by the significant effort and meticulous work that has gone into this revised version of the study. The quality of the new evidence presented is commendable, and the findings now convincingly demonstrate not only clear evidence of intentional burial practices by Homo naledi but also compelling indications of post-depositional reworking. These advancements reflect a major improvement in the study's analytical rigor and the robustness of its conclusions, making it a valuable contribution to the understanding of early hominin funerary behavior.

Author response:

The following is the authors’ response to the original reviews

We extend our sincere thanks to the editor, referees for eLife, and other commentators who have written evaluations of this manuscript, either in whole or in part. Sources of these comments were highly varied, including within the bioRxiv preprint server, social media (including many comments received on X/Twitter and some YouTube presentations and interviews), comments made by colleagues to journalists, and also some reviews of the work published in other academic journals. Some of these are formal and referenced with citations. Others were informal but nonetheless expressed perspectives that helped enable us to revise the manuscript with the inclusion of broader perspectives than the formal review process. It is beyond the scope of this summary to list every one of these, which have often been brought to the attention of different coauthors, but we begin by acknowledging the very wide array of peer and public commentary that have contributed to this work. The reaction speaks to a broad interest in open discussion and review of preprints. 

As we compiled this summary of changes to the manuscript, we recognized that many colleagues made comments about the process of preprint dissemination and evaluation rather than the data or analyses in the manuscript. Addressing such comments is outside the scope of this revised manuscript, but we do feel that a broader discussion of these comments would be valuable in another venue. Many commentators have expressed confusion about the eLife system of evaluation of preprints, which differs from the editorial acceptance or rejection practiced in most academic journals. As authors in many different nations, in varied fields, and in varied career stages, we ourselves are still working to understand how the academic publication landscape is changing, and how best to prepare work for new models of evaluation and dissemination. 

The manuscript and coauthor list reflect an interdisciplinary collaboration. Analyses presented in the manuscript come from a wide range of scientific disciplines. These range from skeletal inventory, morphology, and description, spatial taphonomy, analysis of bone fracture patterns and bone surface modifications, sedimentology, geochemistry, and traditional survey and mapping. The manuscript additionally draws upon a large number of previous studies of the Rising Star cave system and the Dinaledi Subsystem, which have shaped our current work. No analysis within any one area of research stands alone within this body of work: all are interpreted in conjunction with the outcomes of other analyses and data from other areas of research. Any single analysis in isolation might be consistent with many different hypotheses for the formation of sediments and disposition of the skeletal remains. But testing a hypothesis requires considering all data in combination and not leaving out data that do not fit the hypothesis. We highlight this general principle at the outset because a number of the comments from referees and outside specialists have presented alternative hypotheses that may arguably be consistent with one kind of analysis that we have presented, while seeming to overlook other analyses, data, or previous work that exclude these alternatives. In our revision, we have expanded all sections describing results to consider not only the results of each analysis, but how the combination of data from different kinds of analysis relate to hypotheses for the deposition and subsequent history of the Homo naledi remains. We address some specific examples and how we have responded to these in our summary of changes below. 

General organization

The referee and editor comments are mostly general and not line-by-line questions, and we have compiled them and treated them as a group in this summary of changes, except where specifically noted. 

The editorial comments on the previous version included the suggestion that the manuscript should be reorganized to test “natural” (i.e. noncultural) hypotheses for the situations that we examine. The editorial comment suggested this as a “null hypothesis” testing approach. Some outside comments also viewed noncultural deposition as a null hypothesis to be rejected. We do not concur that noncultural processes should be construed as a null hypothesis, as we discuss further below. However, because of the clear editorial opinion we elected to revise the manuscript to make more explicit how the data and analyses test noncultural depositional hypotheses first, followed by testing of cultural hypotheses. This reorganization means that the revised manuscript now examines each hypothesis separately in turn. 

Taking this approach resulted in a substantial reorganization of the “Results” section of the manuscript. The “Results” section now begins with summaries of analyses and data conducted on material from each excavation area. After the presentation of data and analyses from each area, we then present a separate section for each of several hypotheses for the disposition and sedimentary context of the remains. These hypotheses include deposition of bodies upon a talus (as hypothesized in some previous work), slow sedimentary burial on a cave floor or within a natural depression, rapid burial by gravity-driven slumping, and burial of naturally mummified remains. We then include sections to test the hypothesis of primary cultural burial and secondary cultural burial. This approach adds substantial length to the Results. While some elements may be repeated across sections, we do consider the new version to be easier to take piece by piece for a reader trying to understand how each hypothesis relates to the evidence. 

The Results section includes analyses on several different excavation areas within the Dinaledi Subsystem. Each of these presents somewhat different patterns of data. We conceived of this manuscript combining these distinct areas because each of them provides information about the formation history of the Homo naledi-associated sediments and the deposition of the Homo naledi remains. Together they speak more strongly than separately. In the previous version of the manuscript, two areas of excavation were considered in detail (Dinaledi Feature 1 and the Hill Antechamber Feature), with a third area (the Puzzle Box area) included only in the Discussion and with reference to prior work. We now describe the new work undertaken after the 2013-2014 excavations in more detail. This includes an overview of areas in the Hill Antechamber and Dinaledi Chamber that have not yielded substantial H. naledi remains and that thereby help contextualize the spatial concentration of H. naledi skeletal material. The most substantial change in the data presented is a much expanded reanalysis of the Puzzle Box area. This reanalysis provides greater clarity on how previously published descriptions relate to the new evidence. The reanalysis also provides the data to integrate the detailed information on bone identification fragmentation, and spatial taphonomy from this area with the new excavation results from the other areas. 

In addition to Results, the reorganization also affected the manuscript’s Introduction section. Where the previous version led directly from a brief review of Pleistocene burial into the description of the results, this revised manuscript now includes a review of previous studies of the Rising Star cave system. This review directly addresses referee comments that express some hesitation to accept previous results concerning the structure and formation of sediments, the accessibility of the Dinaledi Subsystem, the geochronological setting of the H. naledi remains, and the relation of the Dinaledi Subsystem to nearby cave areas. Some parts of this overview are further expanded in the Supplementary Information to enable readers to dive more deeply into the previous literature on the site formation and geological configuration of the Rising Star cave system without needing to digest the entirety of the cited sources. 

The Discussion section of the revised manuscript is differentiated from Results and focuses on several areas where the evidence presented in this study may benefit from greater context. One new section addresses hypothesis testing and parsimony for Pleistocene burial evidence, which we address at greater length in this summary below. The majority of the Discussion concerns the criteria for recognizing evidence for burial as applied in other studies. In this research we employ a minimal definition but other researchers have applied varied criteria. We consider whether these other criteria have relevance in light of our observations and whether they are essential to the recognition of burial evidence more broadly. 

Vocabulary

We introduce the term “cultural burial” in this revised manuscript to refer to the burial of dead bodies as a mortuary practice. “Burial” as an unmodified term may refer to the passive covering of remains by sedimentary processes. Use of the term “intentional burial” would raise the question of interpreting intent, which we do not presume based on the evidence presented in this research. The relevant question in this case is whether the process of burial reflects repeated behavior by a group. As we received input from various colleagues it became clear that burial itself is a highly loaded term. In particular there is a common assumption within the literature and among professionals that burial must by definition be symbolic. We do not take any position on that question in this manuscript, and it is our hope that the term “cultural burial” may focus the conversation around the extent that the behavioral evidence is repeated and patterned. 

Sedimentology and geochemistry of Dinaledi Feature 1

Reviewer 4 provided detailed comments on the sedimentological and geochemical context that we report in the manuscript. One outside review (Foecke et al. 2024) included some of the points raised by reviewer 4, and additionally addressed the reporting of geochemical and sedimentological data in previous work that we cite. 

To address these comments we have revised the sedimentary context and micromorphology of sediments associated with Dinaledi Feature 1. In the new text we demonstrate the lack of microstratigraphy (supported by grain size analysis) in the unlithified mud clast breccia (UMCB), while such a microstratigraphy is observed in the laminated orange-red mudstones

(LORM) that contribute clasts to the UMCB. Thus, we emphasize the presence and importance

of a laterally continuous layer of LORM nature occurring at a level that appears to be the maximum depth of fossil occurrence. This layer is severely broken under extensive accumulation of fossils such as Feature 1 and only evidenced by abundant LORM clasts within and around the fossils. 

We have completely reworked the geochemical context associated with Feature 1 following the comments of reviewer 4. We described the variations and trends observed in the major oxides separate from trace and rare-earth elements. We used Harker variations plots to assess relationships between these element groups with CaO and Zn, followed by principal component analysis of all elements analyzed. The new geochemical analysis clearly shows that Feature 1 is associated with localized trace element signatures that exist in the sediments only in association with the fossil bones, which suggests lack of postdepositional mobilization of the fossils and sediments. We additionally have included a fuller description of XRF methods. 

To clarify the relation of all results to the features described in this study, we removed the geochemical and sedimentological samples from other sites within the Dinaledi Subsystem. These localities within the fissure network represent only surface collection of sediment, as no excavation results are available from those sites to allow for comparison in the context of assessing evidence of burial. These were initially included for comparison, but have now been removed to avoid confusion.  

Micromorphology of sediments

Some referees (1, 3, and 4) and other commentators (including Martinón-Torres et al. 2024) have suggested that the previous manuscript was deficient due to an insufficient inclusion of micromorphological analysis of sediments. Because these commentators have emphasized this kind of evidence as particularly important, we review here what we have included and how our revision has addressed this comment. Previous work in the Dinaledi Chamber (Dirks et al., 2015; 2017) included thin section illustrations and analysis of sediment facies, including sediments in direct association with H. naledi remains within the Puzzle Box area. The previous work by Wiersma and coworkers (2020) used micromorphological analysis as one of several approaches to test the formation history of Unit 3 sediments in the Dinaledi Subsystem, leading to the interpretation of autobrecciation of earlier Unit 1 sediment. In the previous version of this manuscript we provided citations to this earlier work. The previous manuscript also provided new thin section illustrations of Unit 3 sediment near Dinaledi Feature 1 to place the disrupted layer of orange sediment (now designated the laminated orange silty mudstone unit) into context. 

In the new revised manuscript we have added to this information in three ways. First, as noted above in response to reviewer 4, we have revised and added to our discussion of

micromorphology within and adjacent to the Dinaledi Feature 1. Second, we have included more discussion in the Supplementary Information of previous descriptions of sediment facies and associated thin section analysis, with illustrations from prior work (CC-BY licensed) brought into this paper as supplementary figures, so that readers can examine these without following the citations. Third, we have included Figure 10 in the manuscript which includes six panels with microtomographic sections from the Hill Antechamber Feature. This figure illustrates the consistency of sub-unit 3b sediment in direct contact with H. naledi skeletal material, including anatomically associated skeletal elements, with previous analyses that demonstrate the angular outlines and chaotic orientations of LORM clasts. It also shows density contrasts of sediment in immediate contact with some skeletal elements, the loose texture of this sediment with air-filled voids, and apparent invertebrate burrowing activity. To our knowledge this is the first application of microtomography to sediment structure in association with a Pleistocene burial feature. 

To forestall possible comments that the revised manuscript does not sufficiently employ micromorphological observations, or that any one particular approach to micromorphology is the standard, we present here some context from related studies of evidence from other research groups working at varied sites in Africa, Europe, and Asia. Hodgkins et al. (2021) noted: “Only a handful of micromorphological studies have been conducted on human burials and even fewer have been conducted on suspected burials from Paleolithic or hunter-gatherer contexts.” In that study, one supplementary figure with four photomicrographs of thin sections of sediments was presented. Interpretation of the evidence for a burial pit by Hodgkins et al. (2021) noted the more open microstructure of sediment but otherwise did not rely upon the thin section data in characterizing the sediments associated with grave fill. Martinón-Torres et al. (2021) included one Extended Data figure illustrating thin sections of sediments and bone, with two panels showing sediments (the remainder showing bone histology). The micromorphological analysis presented in the supplementary information of that paper was restricted to description of two microfacies associated with the proposed “pit” in that study. That study did carry out microCT scanning of the partially-prepared skeletal remains but did not report any sediment analysis from the microtomographic results. Maloney et al. (2022) reported no micromorphological or thin section analysis. Pomeroy et al. (2020a) included one illustration of a thin section; this study may be regarded as a preliminary account rather than a full description of the work undertaken. Goldberg et al. (2017) analyzed the geoarchaeology of the Roc de Marsal deposits in which possible burial-associated sediments had been fully excavated in the 1960s, providing new morphological assessments of sediment facies; the supplementary information to this work included five scans (not microscans) of sediment thin sections and no microphotographs. Fewlass et al. (2023) presented no thin section or micromorphological illustrations or methods. In summary of this research, we note that in one case micromorphological study provided observations that contributed to the evidence for a pit, in other cases micromorphological data did not test this hypothesis, and many researchers do not apply micromorphological techniques in their particular contexts. 

Sediment micromorphology is a growing area of research and may have much to provide to the understanding of ancient burial evidence as its standards continue to develop (Pomeroy et al. 2020b). In particular microtomographic analysis of sediments, as we have initiated in this study, may open new horizons that are not possible with more destructive thin-section preparation. In this manuscript, the thin section data reveals valuable evidence about the disruption of sediment structure by features within the Dinaledi Chamber, and microtomographic analysis further documents that the Hill Antechamber Feature reflects similar processes, in addition to possible post-burial diagenesis and invertebrate activity. Following up in detail on these processes will require further analysis outside the scope of this manuscript. 

Access into the Dinaledi Subsystem

Reviewer 1 emphasizes the difficulty of access into the Dinaledi Subsystem as a reason why the burial hypothesis is not parsimonious. Similar comments have been made by several outside commentators who question whether past accessibility into the Dinaledi Subsystem may at one time have been substantially different from the situation documented in previous work. Several pieces of evidence are relevant to these questions and we have included some discussion of them in the Introduction, and additionally include a section in the Supplementary Information (“Entrances to the cave system”) to provide additional context for these questions. Homo naledi remains are found not only within the Dinaledi Subsystem but also in other parts of the cave system including the Lesedi Chamber, which is similarly difficult for non-expert cavers to access. The body plan, mass, and specific morphology of H. naledi suggest that this species would be vastly more suited to moving and climbing within narrow underground passages than living people. On this basis it is not unparsimonious to suggest that the evidence resulted from H. naledi activity within these spaces. We note that the accessibility of the subsystem is not strictly relevant to the hypothesis of cultural burial, although the location of the remains does inform the overall context which may reflect a selection of a location perceived as special in some way. 

Stuffing bodies down the entry to the subsystem

Reviewer 3 suggests that one explanation for the emplacement of articulated remains at the top of the sloping floor of the Hill Antechamber is that bodies were “stuffed” into the chute that comprises the entry point of the subsystem and passively buried by additional accumulation of remains. This was one hypothesis presented in earlier work (Dirks et al. 2015) and considered there as a minimal explanation because it did not entail the entry of H. naledi individuals into the subsystem. The further exploration (Elliott et al. 2021) and ongoing survey work, as well as this manuscript, all have resulted in data that rejects this hypothesis. The revised manuscript includes a section in the results “Deposition upon a talus with passive burial” that examines this hypothesis in light of the data. 

Recognition of pits

Referee 3 and 4 and several additional commentators have emphasized that the recognition of pit features is necessary to the hypothesis of burial, and questioned whether the data presented in the manuscript were sufficient to demonstrate that pits were present. We have revised the manuscript in several ways to clarify how all the different kinds of evidence from the subsystem test the hypothesis that pits were present. This includes the presentation of a minimal definition of burial to include a pit dug by hominins, criteria for recognizing that a pit was present, and an evaluation of the evidence in each case to make clear how the evidence relates to the presence of a pit and subsequent infill. As referee 3 notes, it can be challenging to recognize a pit when sediment is relatively homogeneous. This point was emphasized in the review by Pomeroy and coworkers (2020b), who reflected on the difficulty seeing evidence for shallow pits constructed by hominins, and we have cited this in the main text. As a result, the evidence for pits has been a recurrent topic of debate for most Pleistocene burial sites. However in addition to the sedimentological and contextual evidence in the cases we describe, the current version also reflects upon other possible mechanisms for the accumulation of bones or bodies. The data show that the sedimentary fill associated with the H. naledi remains in the cases we examine could not have passively accumulated slowly and is not indicative of mass movement by slumping or other high-energy flow. To further put these results into context, we added a section to the Discussion that briefly reviews prior work on distinguishing pits in Pleistocene burial contexts, including the substantial number of sites with accepted burial evidence for which no evidence of a pit is present. 

Extent of articulation and anatomical association

We have added significantly greater detail to the descriptions of articulated remains and orientation of remains in order to describe more specifically the configuration of the skeletal material. We also provide 14 figures in main text (13 of them new) to illustrate the configuration of skeletal remains in our data. For the Puzzle Box area, this now includes substantial evidence on the individuation of skeletal fragments, which enables us to illustrate the spatial configuration of remains associated with the DH7 partial skeleton, as well as the spatial position of fragments refitted as part of the DH1, DH2, DH3, and DH4 crania. For Dinaledi Feature 1 and the Hill Antechamber Feature we now provide figures that key skeletal parts as identified, including material that is unexcavated where possible, and a skeletal part representation figure for elements excavated from Dinaledi Feature 1. 

Archaeothanatology

Reviewer 2 suggests that a greater focus on the archaeothanatology literature would be helpful to the analysis, with specific reference to the sequence of joint disarticulation, the collapse of sediment and remains into voids created by decomposition, and associated fragmentation of the remains. In the revised manuscript we have provided additional analysis of the Hill Antechamber Feature with this approach in mind. This includes greater detail and illustration of our current hypothesis for individuation of elements. We now discuss a hypothesis of body disposition, describe the persistent joints and articulation of elements, and examine likely decomposition scenarios associated with these remains. Additionally, we expand our description and illustration of the orientation of remains and degree of anatomical association and articulation within Dinaledi Feature 1. For this feature and for the Hill Antechamber Feature we have revised the text to describe how fracturing and crushing patterns are consistent with downward pressure from overlying sediment and material. In these features, postdepositional fracturing occurred subsequent to the decomposition of soft tissue and partial loss of organic integrity of the bone. We also indicate that the loss by postdepositional processes of most long bone epiphyses, vertebral bodies, and other portions of the skeleton less rich in cortical bone, poses a challenge for testing the anatomical associations of the remaining elements. This is a primary reason why we have taken a conservative approach to identification of elements and possible associations. 

A further aspect of the site revealed by our analysis is the selective reworking of sediments within the Puzzle Box area subsequent to the primary deposition of some bodies. The skeletal evidence from this area includes body parts with elements in anatomical association or articulation, juxtaposed closely with bone fragments at varied pitch and orientation. This complexity of events evidenced within this area is a challenge for approaches that have been developed primarily based on comparative data from single-burial situations. In these discussions we deepen our use of references as suggested by the referee.   

Burial positions

Reviewer 2 further suggests that illustrations of hypothesized burial positions would be valuable. We recognize that a hypothesized burial position may be an appealing illustration, and that some recent studies have created such illustrations in the context of their scientific articles. However such illustrations generally include a great deal of speculation and artist imagination, and tend to have an emotive character. We have added more discussion to the manuscript of possible primary disposition in the case of the Hill Antechamber Feature as discussed above. We have not created new illustrations of hypothesized burial positions for this revision. 

Carnivore involvement

Referee 1 suggests that the manuscript should provide further consideration of whether carnivore activity may have introduced bones or bodies into the cave system. The reorganized Introduction now includes a review of previous work, and an expanded discussion within the Supplementary Information (“Hypotheses tested in previous work”). This includes a review of literature on the topic of carnivore accumulation and the evidence from the Dinaledi and Lesedi Chamber that rejects this hypothesis. 

Water transport and mud

The eLife referees broadly accepted previous work showing that water inundation or mass flow of water-saturated sediment did not occur within the history of Unit 2 and 3 sediments, including those associated with H. naledi remains. However several outside commentators did refer specifically to water flow or mud flow as a mechanism for slumping of deposits and possible sedimentary covering of the remains. To address these comments we have added a section to the

Supplementary Information (“Description of the sedimentary deposits of the Dinaledi Subsystem”) that reviews previous work on the sedimentary units and formation processes documented in this area. We also include a subsection specifically discussing the term “mud” as used in the description of the sedimentology within the system, as this term has clearly been confusing for nonspecialists who have read and commented on the work. We appreciate the referees’ attention to the previous work and its terminology.  

Redescription of areas of the cave system

Reviewer 1 suggests that a detailed reanalysis of all portions of the cave system in and around the Dinaledi Subsystem is warranted to reject the hypothesis that bodies entered the space passively and were scattered from the floor by natural (i.e. noncultural) processes. The referee suggests that National Geographic could help us with these efforts. To address this comment we have made several changes to the manuscript. As noted above, we have added material in Supplementary Information to review the geochronology of the Dinaledi Subsystem and nearby Dragon’s Back Chamber, together with a discussion of the connections between these spaces. 

Most directly in response to this comment we provide additional documentation of the possibility of movement of bodies or body parts by gravity within the subsystem itself. This includes detailed floor maps based on photogrammetry and LIDAR measurement, where these are physically possible, presented in Figures 2 and 3. In some parts of the subsystem the necessary equipment cannot be used due to the extremely confined spaces, and for these areas our maps are based on traditional survey methods. In addition to plan maps we have included a figure showing the elevation of the subsystem floor in a cross-section that includes key excavation areas, showing their relative elevation. All figures that illustrate excavation areas are now keyed to their location with reference to a subsystem plan. These data have been provided in previous publications but the visualization in the revised manuscript should make the relationship of areas clear for readers. The Introduction now includes text that discusses the configuration of the Hill Antechamber, Dinaledi Chamber, and nearby areas, and also discusses the instances in which gravity-driven movement may be possible, at the same time reviewing that gravity-driven movement from the entry point of the subsystem to most of the localities with hominin skeletal remains is not possible. 

Within the Results, we have added a section on the relationship of features to their surroundings in order to assist readers in understanding the context of these bone-bearing areas and the evidence this context brings to the hypothesis in question. We have also included within this new section a discussion of the discrete nature of these features, a question that has been raised by outside commentators. 

Passive sedimentation upon a cave floor or within a natural depression

Reviewer 3 suggests that the situation in the Dinaledi Subsystem may be similar to a European cave where a cave bear skeleton might remain articulated on a cave floor (or we can add, within a hollow for hibernation), later to be covered in sediment. The reviewer suggests that articulation is therefore no evidence of burial, and suggests that further documentation of disarticulation processes is essential to demonstrating the processes that buried the remains. We concur that articulation by itself is not sufficient evidence of cultural burial. To address this comment we have included a section in the Results that tests the hypothesis that bodies were exposed upon the cave floor or within a natural depression. To a considerable degree, additional data about disarticulation processes subsequent to deposition are provided in our reanalysis of the Puzzle Box area, including evidence for selective reworking of material after burial. 

Postdepositional movement and floor drains

Reviewer 3 notes that previous work has suggested that subsurface floor drains may have caused some postdepositional movement of skeletal remains. The hypothesis of postdepositional slumping or downslope movement has also been discussed by some external commentators (including Martinón-Torres et al. 2024). We have addressed this question in several places within the revised manuscript. As we now review, previous discussion of floor drains attempted to explain the subvertical orientation of many skeletal elements excavated from the Puzzle Box area. The arrangement of these bones reflects reworking as described in our previous work, and without considering the possibility of reworking by hominins, one mechanism that conceivably might cause reworking was downward movement of sediments into subsurface drains. Further exploration and mapping, combined with additional excavation into the sediments beneath the Puzzle Box area provided more information relevant to this hypothesis. In particular this evidence shows that subsurface drains cannot explain the arrangement of skeletal material observed within the Puzzle Box area. As now discussed in the text, the reworking is selective and initiated from above rather than below. This is best explained by hominin activity subsequent to burial. 

In a new section of the Results we discuss slumping as a hypothesis for the deposition of the remains. This includes discussion of downslope movement within the Hill Antechamber and the idea that floor drains may have been a mechanism for sediment reworking in and around the Puzzle Box area and Dinaledi Feature 1. As described in this section the evidence does not support these hypotheses. 

Hypothesis testing and parsimony

Referees 1 and 3 and the editorial guidance all suggested that a more appropriate presentation would adopt a null hypothesis and test it. The specific suggestion that the null hypothesis should be a natural sedimentary process of deposition was provided not only by these reviewers but also by some outside commentators. To address this comment, we have edited the manuscript in two ways. The first is the addition of a section to the Discussion that specifically discusses hypothesis testing and parsimony as related to Pleistocene evidence of cultural burial. This includes a brief synopsis of recent disciplinary conversations and citation of work by other groups of authors, none of whom adopted this “null hypothesis” approach in their published work. 

As we now describe in the manuscript, previous work on the Dinaledi evidence never assumed any role for H. naledi in the burial of remains. Reading the reviewer reports caused us to realize that this previous work had followed exactly the “null hypothesis” approach that some suggested we follow. By following this null hypothesis approach, we neglected a valuable avenue of investigation. In retrospect, we see how this approach impeded us from understanding the pattern of evidence within the Puzzle Box area. Thus in the revised manuscript we have mentioned this history within the Discussion and also presented more of the background to our previous work in the Introduction. Hopefully by including this discussion of these issues, the manuscript will broaden conversation about the relation of parsimony to these issues. 

Language and presentation style

Reviewer 4 criticizes our presentation, suggesting that the text “gives the impression that a hypothesis was formulated before data were collected.” Other outside commentators have mentioned this notion also, including Martinón-Torres et al. (2024) who suggest that the study began from a preferred hypothesis and gathered data to support it. The accurate communication of results and hypotheses in a scientific article is a broader issue than this one study. Preferences about presentation style vary across fields of study as well as across languages. We do not regret using plain language where possible. In any study that combines data and methods from different

scientific disciplines, the use of plain language is particularly important to avoid misunderstandings where terms may mean different things in different fields. 

The essential question raised by these comments is whether it is appropriate to present the results of a study in terms of the hypothesis that is best supported. As noted above, we read carefully many recent studies of Pleistocene burial evidence. We note that in each of these studies that concluded that burial is the best hypothesis, the authors framed their results in the same way as our previous manuscript: an introduction that briefly reviews background evidence for treatment of the dead, a presentation of results focused on how each analysis supports the hypothesis of burial for the case, and then in some (but not all) cases discussion of why some alternative hypotheses could be rejected. We do not infer from this that these other studies started from a presupposition and collected data only to confirm it. Rather, this is a simple matter of presentation style. 

The alternative to this approach is to present an exhaustive list of possible hypotheses and to describe how the data relate to each of them, at the end selecting the best. This is the approach that we have followed in the revised manuscript, as described above under the direction of the reviewer and editorial guidance. This approach has the advantage of bringing together evidence in different combinations to show how each data point rejects some hypotheses while supporting others. It has the disadvantage of length and repetition. 

Possible artifact

We have chosen to keep the description of the possible artifact associated with the Hill Antechamber Feature in the Supplementary Information. We do this while acknowledging that this is against the opinion of reviewer 4, who felt the description should be removed unless the object in question is fully excavated and physically analyzed. The previous version of the manuscript did not rely upon the stone as positive evidence of grave goods or symbolic content, and it noted that the data do not test whether the possible artifact was placed or was intentionally modified. However this did not satisfy reviewer 4, and some outside commentators likewise asserted that the object must be a “geofact” and that it should be removed. 

We have three arguments against this line of thinking. First, we do not omit data from our reporting. Whether Homo naledi shaped the rock or not, used it as a tool or not, whether the rock was placed with the body or not, it is unquestionably there. Omitting this one object from the report would be simply dishonest. Second, the data on this rock are at 16 micron resolution. While physical inspection of its surface may eventually reveal trace evidence and will enable better characterization of the raw material, no mode of surface scanning will produce better evidence about the object’s shape. Third, the position of this possible artifact within the feature provides significant information about the deposition of the skeletal material and associated sediments. The pitch, orientation, and position of the stone is not consistent with slow deposition but are consistent with the hypothesis that the surrounding sediment was rapidly emplaced at the same time as the articulated elements less than 2 cm away. 

In the current version, we have redoubled our efforts to provide information about the position and shape of this stone while not presupposing the intentionality of its shape or placement. We add here that the attitude expressed by referee 4 and other commentators, if followed at other sites, would certainly lead to the loss or underreporting of evidence, which we are trying to avoid.  

Consistency versus variability of behavior

As described in the revised manuscript, different features within the Dinaledi Subsystem exhibit some shared characteristics. At the same time, they vary in positioning, representation of individuals and extent of commingling. Other localities within the subsystem and broader cave system present different evidence. Some commentators have questioned whether the patterning is consistent with a single common explanation, or whether multiple explanations are necessary. To address this line of questioning, we have added several elements to the manuscript. We created a new section on secondary cultural burial, discussing whether any of the situations may reflect this practice. In the Discussion, we briefly review the ways in which the different features support the involvement of H. naledi without interpreting anything about the intentionality or meaning of the behavior. We further added a section to the Discussion to consider whether variation among the features reflects variation in mortuary practices by H. naledi. One aspect of this section briefly cites variation in the location and treatment of skeletal remains at other sites with evidence of burial. 

Grave goods

Some commentators have argued that grave goods are a necessary criterion for recognizing evidence of ancient burial. We added a section to the Discussion to review evidence of grave goods at other Pleistocene sites where burial is accepted. 

References

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eLife Assessment

This study offers valuable insights into the conformational dynamics of the nucleic acid recognition lobe of GeoCas9, a thermophilic Cas9 from Geobacillus stearothermophilus. The authors investigate the influence of local dynamics and allosteric regulation on guide RNA binding affinity and DNA cleavage specificity through advanced NMR techniques and mutagenesis. The revised manuscript incorporates new experimental data, including molecular dynamics simulations and additional RNA binding studies, which provide convincing support for the findings. While the mutations studied do not lead to significant changes in GeoCas9 cleavage activity, the study contributes to a better understanding of the allosteric mechanisms and interdomain communication in Cas9 enzymes, and will be of great interest to biochemists and biophysicists exploring these complex systems.

Reviewer #1 (Public review):

Summary:

In this study from Belato, Knight and co-workers, the authors investigated the Rec domain of a thermophilic Cas9 from Geobacillus stearothermophilus (GeoCas9). The authors investigated three constructs, two individual subdomains of Rec (Rec1 and Rec2) and the full Rec domain. This domain is involved in binding to the guide RNA of Cas9, as well as the RNA-DNA duplex that is formed upon target binding. The authors performed RNA binding and relaxation experiments using NMR for the wild-type domain as well as two-point mutants. They observed differences in RNA binding activities as well as the flexibility of the domain. The authors also performed molecular dynamics and functional experiments on full-length GeoCas9 to determine whether these biophysical differences affect the RNA binding or cleavage activity. Although the authors observed some changes in the thermal stability of the mutant GeoCas9-gRNA complex, they did not observe substantial differences in the guide RNA binding or cleavage activities of the mutant GeoCas9 variants.

Overall, this manuscript provides a detailed biophysical analysis of the GeoCas9 Rec domain. The NMR assignments for this construct should prove very useful, and can serve as the basis for future similar studies of GeoCas9 Rec domain mutants. While the two mutants tested in the study did not produce significant differences from wild-type GeoCas9, the study rules out the possibility that analogous mutations can be translated between type II-A and II-C Cas9 orthologs. Together, these findings may provide the grounds for future engineering of higher fidelity variants of GeoCas9

Reviewer #2 (Public review):

The manuscript from Belato et al., used advanced NMR approaches and a mutagenesis campaign probe the conformational dynamics of the recognition lobe (Rec) of the CRISPR Cas9 enzyme from G. stearothermophilus (GeoCas9). Using truncated and full-length constructs they assess the impacts of two different point mutations have on the redistribution and timescale of these motions and assess gRNA recognition and specificity. Single point mutations in the Rec domain in a Cas9 from a related species had profound impacts on- and off-target DNA editing, therefore the authors reasoned analogous mutations in GeoCas9 would have similar effects. However, despite a redistribution of local motions and changes in global stability, their chosen mutations had little impact on DNA editing in the context of the full-length enzyme.

In their revised manuscript, the authors were highly responsive to the reviewer's comments incorporating new experimental results including molecular dynamics simulations and RNA binding data using full-length GeoCas9, as well as reframing their discussion and conclusions in consideration of the new data. They were receptive to suggestions for clarification in both the text and methods section. With these changes, the manuscript has been significantly improved.

Their studies highlight the species-specific complexity of interdomain communication and allosteric mechanisms used by these multi-domain endonucleases. The noted strengths of the article remain, and despite the negative results, their approach will garner interest from investigators interested in understanding how the activity and specificity of these enzymes can be engineered to tune activity and limit off-target cleavage by these enzymes. Generally, the manuscript highlights the challenges of studying the effect of allosteric networks on protein function, particularly in multidomain proteins, and thus will be of broad interest to the community.

Reviewer #3 (Public review):

The authors explore the role of Rec domains in a thermophilic Cas9 enzyme. They report on the crystal structure of part of the recognition lobe, its dynamics from NMR spin relaxation and relaxation-dispersion data, its interaction mode with guide RNA, and the effect of two single-point mutations hypothesised to enhance specificity. They find that mutations have small effects on Rec domain structure and stability but lead to significant rearrangement of micro- to milli-second dynamics which does not translate into major changes in guide RNA affinity or DNA cleavage specificity, illustrating the inherent tolerance of GeoCas9. The work can be considered as a first step towards understanding motions in GeoCas9 recognition lobe, although no clear hotspots were discovered with potential for future rational design of enhanced Cas9 variants.

Strengths:

- Detailed biophysical and structural investigation, despite a few technical limitations inherent with working with complex targets, provides converging evidence that molecular dynamics embedded in the recognition lobes allow GeoCas9 to operate on a broad range of substrates.<br /> - Since the authors and others have shown that substrate specificity is dictated by equivalent hotspot mutations in other Cas9 variants, we are one step closer to understanding this phenomenon.

Weaknesses:

- Since the mutations investigated here do not significantly affect substrate binding or enzymatic activity, it is difficult to rationalize anything for enzyme engineering at this point.<br /> - Further investigation of the determinants of the observed dynamic modes, and follow-up with rationally designed mutations would hopefully allow to create a real model of the mechanism, but I do understand that this goes beyond the scope of this study.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this study from Belato, Knight, and co-workers, the authors investigated the Rec domain of a thermophilic Cas9 from Geobacillus stearothermophilus (GeoCas9). The authors investigated three constructs, two individual subdomains of Rec (Rec1 and Rec2) and the full Rec domain. This domain is involved in binding to the guide RNA of Cas9, as well as the RNA-DNA duplex that is formed upon target binding. The authors performed RNA binding and relaxation experiments using NMR for the wild-type domain as well as two-point mutants. They observed differences in RNA binding activities as well as the flexibility of the domain. The authors also performed experiments on fulllength GeoCas9 to determine whether these biophysical differences affect the RNA binding or cleavage activity. Although the authors observed some changes in the thermal stability of the mutant GeoCas9-gRNA complex, they did not observe substantial differences in the cleavage activities of the mutant GeoCas9 variants.

Overall, this manuscript provides a detailed biophysical analysis of the GeoCas9 Rec domain. The NMR assignments for this construct should prove very useful, and the results may provide the grounds for future engineering of higher fidelity variants of GeoCas9. While the NMR results are generally well presented, it is unclear how the results on the isolated Rec domain related to the overall function of full-length GeoCas9. In addition, some conclusions are overstated and not fully supported by the evidence provided. The following major points should be addressed by the authors.

(1) Many of the results rely on the backbone resonance assignments of the three constructs that were used, and the authors have done an excellent job of assigning the Rec1 and Rec2 constructs. However, it is unclear from the descriptions in the text how the full-length Rec construct was assigned. Were these assignments made based on assignments for the individual domains? The authors state that the spectra of individual domains and RecFL overlay very well, but there appear to be many resonances that have chemical shift differences or are only present in one construct. As it stands, it is unclear how the resonances were assigned for residues whose chemical shifts were perturbed, making it difficult to interpret many of the results.

The Reviewer raises an important oversight. In Lines 491-493, we clarify that we were able to transfer the assignments using spectral overlays of the individual domains with GeoRec (i.e. careful analysis of the data in Figure S3). We also cite two new references where a similar approach was applied to Cas9.

(2) The minimal gRNA that was used for the Rec-gRNA binding experiments is unlikely to be a good mimic for the full-length gRNA, as it lacks any of the secondary structure that is most specifically recognized by the REC lobe and the rest of the Cas9 protein. The majority of this RNA is a "spacer" sequence, but spacers are variable, so this sequence is arbitrary. Thus, the interactions that the authors are observing most likely represent non-specific interactions between the Rec domains and RNA. The authors also map chemical shift perturbations and line broadening on structural models with an RNA-DNA duplex bound, but this is not an accurate model for how the Rec domain binds to a single-stranded RNA (for which there is no structural model). Thus, many of the conclusions regarding the RNA binding interface are overstated.

The Reviewer again raises an important point. We have added a section of text explaining the rationale for truncating the gRNA for binding experiments with NMR (Lines 223-235). We chose the 5’end of the gRNA containing the spacer sequence based on crystal structures of NmeCas9 and SpCas9 that show the Rec lobe interacting with this section of nucleic acid. The newly published GeoCas9 cryo-EM structure bound to gRNA, which overlaid well with the NmeCas9 structure, also suggested that this portion of the gRNA could interact with Rec.

Figures S11 and S12 show our gradual truncation of the gRNA and Rec construct to achieve useful atomic detail. Ultimately, a 39nt gRNA containing a 23 base pair spacer sequence was chosen for this study to retain the NMR signal of the complex and because several structures suggested this 39nt sequence would be long enough to interact with the entire Rec lobe.

To investigate the effect of the spacer sequence, we have now measured binding affinities via MST between GeoRec and a 39nt Tnnt2 gRNA and a 39nt gRNA from PDB: 8UZA, containing a different spacer sequence used in the very recent GeoCas9 cryo-EM structure. The observed trends for each gRNA are consistent across the samples. We also measured WT, K267E, and R332A GeoCas9 affinity for the full-length Tnnt2 and PDB:8UZA gRNAs.

Lastly, we used a new cryo-EM structure of GeoCas9 bound to gRNA (PDB: 8JTR) to better define the interface for NMR CSPs and line broadening and have adjusted the language in this section.

(3) The authors include microscale thermophoresis (MST) data for the Rec constructs binding to the minimal gRNA. These data suggest that all three Rec variants have very similar Kd's for the RNA. Given these similarities, it is unclear why the RNA titration experiments by NMR yielded such different results. Moreover, in the Discussion, the authors state that the NMR titration data are consistent with the MST-derived Kd values. This conclusion appears to be overstated given the very small differences in affinities measured by MST.

MST and NMR experiments describing the weakened binding affinity of GeoRec and GeoRec2 for the Tnnt2 gRNA agree with each other (Figure 5). However, additional MST experiments with a different gRNA sequence (from PDB: 8UZA) and with fulllength GeoCas9 (new Figure 7) have provided new insight for us to soften and reframe the Discussion to avoid overstatement. See Lines 263-282 and 375-385.

(4) While the authors have performed some experiments to help place their findings on the isolated Rec domain in the context of the full-length protein, these experiments do not fully support the conclusions that the authors draw about the meaning of their NMR results. The two Cas9 variants that were explored via NMR have no effect on Cas9 cleavage activity, and it is unclear from the data provided whether they have any effect on GeoCas9 binding to the full sgRNA. This makes it difficult to determine whether the observed differences in RNA binding and dynamics of the isolated Rec domain have any consequence in the context of the full protein.

We have since measured the binding affinities of full-length GeoCas9 to full-length gRNA. (new Figure 7) We have also added a comment in the Discussion section describing how both GeoRec and GeoRec2 domain variants bind the truncated RNA with weaker affinity than the WT, but this biophysical effect does not translate to GeoCas9 with its full-length gRNA. We describe this finding as an explanation for why the single-point mutants have minimal effect of GeoCas9 cleavage activity. See Lines 375-385.

(5) The authors state in multiple places that the K267E/R332A mutant enhanced GeoCas9 specificity. Improved specificity refers to a situation in which the efficiency of cleavage of a perfectly matched target improves in comparison to a mismatched target. This is not what the authors observed for the double mutant. Instead, the cleavage of the perfect target was drastically reduced, in some cases to a larger degree than for the mismatched target. The double mutant does not appear to have improved specificity, it has simply decreased cleavage efficiency of the enzyme.

The conclusion has been reframed to suggest that the K267E/R332A double mutant has decreased cleavage efficiency of the enzyme but does not enhance GeoCas9 specificity. We discuss an interesting contrast, namely that mutations in the SpCas9 Rec lobe alter its specificity, which is at times accompanied by a loss of overall activity. We also speculate on why this may not be the case in GeoCas9, considering some very recent (unpublished at the time of initial submission) structural and biochemical data. See Lines 414-418.

Reviewer #2 (Public Review):

Summary:

The manuscript from Belato et al. used advanced NMR approaches and a mutagenesis campaign to probe the conformational dynamics of the recognition lobe (Rec) of the CRISPR Cas9 enzyme from G. stearothermophilus (GeoCas9). Using truncated and full-length constructs they assess the impacts of two different point mutations have on the redistribution and timescale of these motions and assess gRNA recognition and specificity. Single point mutations in the Rec domain in a Cas9 from a related species had profound impacts on- and off-target DNA editing, therefore the authors reasoned analogous mutations in GeoCas9 would have similar effects. However, despite a redistribution of local motions and changes in global stability, their chosen mutations had little impact on DNA editing in the context of the full-length enzyme. Their studies highlight the species-specific complexity of interdomain communication and allosteric mechanisms used by these multi-domain endonucleases. Despite these negative results, their study is highly rigorous, and their approach will broadly support understanding how the activity and specificity of these enzymes can be engineered to tune activity and limit off-target cleavage by these enzymes.

Strengths:

(1) Atomistic investigation of the conformational dynamics of the GeoCas9 gRNA recognition lobe (GeoRec), probing dynamics on a broad range of timescales from ps to ms using advanced NMR approaches will be broadly interesting to both the structural biology and CRISPR engineering communities.

(2) Highly rigorous biophysical studies that push the boundaries of current techniques, provide insight into local dynamics of the GeoRec domain that serve to propagate allosteric information and potentially regulate enzymatic activity.

(3) The study highlights the complexities of understanding interdomain communication in Cas9 enzymes since analogous mutations in different species have different effects on target recognition and cleavage.

(4) The type of structural and dynamic insights derived from this study design could serve as foundational information to guide a rational design strategy aimed at improving the selectivity and reducing the off-target effects of Cas9 enzymes.

Weaknesses:

(1) Despite the rigor of the experiments, the mutations chosen by the authors do not have a profound effect on the overall substrate affinity or activity of GeoCas9 rendering little mechanistic insight into allosteric communication in this particular Cas9. However, the double mutant K267E/R332A has a more pronounced effect on the cleavage of WT and mismatched (at nucleotides 19 and 20) DNA substrates while minimally affecting the cleavage of mismatched (at nucleotides 5 and 6), suggesting more could be learned about the allosteric mechanism from the detailed characterization of this mutant.

We thank the Reviewer for this comment. While we have included new binding experiments with full-length GeoCas9 and gRNAs (new Figure 7), the addition of new MD simulations (new Figure 6) better address this point. MD examined our single and double mutants, as well as the recently published high-specificity iGeoCas9, and reported the degree of conformational sampling and nucleic acid contacts and binding energies.

The simulations show that our mutations induce some, but not the full extent of the effect of iGeoCas9 (with one mutation in GeoRec and many others in the adjacent WED domain), implying that further engineering of GeoRec to mimic iGeoCas9’s properties can have profound functional outcomes. Future efforts to mutate GeoRec will be leverage this strategy. See Lines 309-342.

(2) Follow-up experiments with other residues that were identified as being highly dynamic might affect substrate recognition and cleavage activity in different ways providing additional insight.

The Reviewer is correct. While beyond this initial scope, new MD simulations (see the response directly above) and NMR resonances distally affect by gRNA (via CSP or relaxation dispersion) will be used identify the primary targets for this analysis.

(3) Details regarding the authors' experimental approach are incomplete such as a description of the model used to fit the CD data, a detailed explanation of the global fitting of the relaxation dispersion data describing how the best-fit model was selected, and the description of the ModelFree fitting of fast timescale dynamics is incomplete.

We thank the Reviewer for pointing out these oversights. We have now included the fitting equation in the CD Methods section.

We included new Figures S8-S10 with the individual relaxation dispersion curves and note in the Methods that global fits were deemed superior based on the Akaike Information Criterion. For WT, the AIC showed the global fit to be ~10-fold better. For K267E, the global model was 4-fold better, and for R332A, the global model was 6-fold better.

We have included a more detailed description of CPMG and Model-free fitting. See Lines 520-526.

Reviewer #3 (Public Review):

The authors explore the role of Rec domains in a thermophilic Cas9 enzyme. They report on the crystal structure of part of the recognition lobe, its dynamics from NMR spin relaxation and relaxation-dispersion data, its interaction mode with guide RNA, and the effect of two single-point mutations hypothesised to enhance specificity. They find that mutations have small effects on Rec domain structure and stability but lead to significant rearrangement of micro- to milli-second dynamics which does not translate into major changes in guide RNA affinity or DNA cleavage specificity, illustrating the inherent tolerance of GeoCas9. The work can be considered as a first step towards understanding motions in GeoCas9 recognition lobe, although no clear hotspots were discovered with potential for future rational design of enhanced Cas9 variants.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Suggestions for improved or additional experiments, data, or analyses

(1) Please update the sentences on lines 100-105 and the Methods to clarify how the RecFL assignments were obtained. If RecFL was assigned based on the assignments for Rec1 and Rec2, please describe in the Methods how the shifted resonances were handled. Please also provide chemical shift perturbation profiles for the truncated constructs versus the full-length Rec construct.

We have now added text (Lines 491-493) and two new references explaining the GeoRec (full-length) assignment.

We appreciate this point. We have now provided a new Figure S9 with analysis of CSPs and line broadening in truncated constructs (GeoRec2 only). See also Lines 263-282. We also show a similar structural response to mutation in full-length GeoRec and GeoRec2 NMR CSPs (Figure 2 and Figure S5).

We have provided the CSPs for each construct, relative to the full-length GeoRec domain, Author response image 1. In most cases, the largest CSPs occur at resonances on the periphery of the spectra, retaining the ability to unambiguously assign it.

Author response image 1.

 

(2) It is unclear whether the differences in Kd's for the Rec-gRNA interactions are statistically significant, given the errors associated with the values. Can the authors further analyze these data to determine statistical significance? If they are not found to be significantly different, the authors should soften all conclusions related to the observed differences.

Statistical significance was calculated for all MST data and Figures 5 and 7 have been updated to reflect this

(3) As mentioned above, it seems likely that the Rec-RNA binding that is observed is non-specific. Have the authors tried MST with another 39 nt RNA? Are there differences in affinities for the Rec constructs?

We have done MST with another 39nt RNA. The affinity for each gRNA (Tnnt2 vs 8UZA) is similar for WT and K267E, and a factor of ~4 weaker for R332A with 8UZA gRNA. The trend is the same, that WT Rec has a (statistically significant) stronger affinity for the gRNA compared to the mutants.

(4) Have the authors tried MST with full-length GeoCas9 and the sgRNA? The current data on the thermal stability of the RNP's is interesting, but a more direct measurement of the affinity of the Cas9-sgRNA complexes would provide stronger evidence of the effects of the mutations.

The Reviewer makes an excellent suggestion. We have now generated Cy5-labeled full-length gRNAs and conducted MST with full-length GeoCas9 (new Figure 7). The binding affinities to multiple guides do not vary significantly. We have discussed this, and its implications, in Lines 376-385.

(5) One potential issue with not observing differences between the three Cas9 variants' cleavage activity is that the activity of these purified proteins appears to be very low in comparison to previous studies of GeoCas9. There are significant differences in the expression protocol used by the authors of the current study and previous studies. Have the authors attempted to replicate the expression and purification protocol of previous reports? This may improve the enzymatic activity and allow for a more detailed investigation of cleavage between the three variants (e.g. by performing time-course cleavage assays).

The expression protocol of GeoCas9 is identical to those of previous studies. This was a written mistake on our part, which has now been corrected in the methods section. We apologize for this oversight.

Recommendations for improving the writing and presentation

The introduction of the manuscript is reasonable for specialists who are very familiar with Cas9 function, but it does not contain important details that may be unknown to most readers. The authors do not introduce the domains of Cas9 in the Introduction section. A brief description of the domains that are important to this work should be provided. For example, what is the role of the Rec lobe? This is not introduced until lines 110-111, after some discussion of the authors' initial work on these domains. For a broad audience, it would also be helpful to define the two catalytic domains of the protein. A paragraph describing the general architecture of Cas9 and the overall mechanism of Cas9, including allostery and domain movement, would be very helpful to a general audience. There are elements of this throughout the manuscript, but it would be better to have everything described in a single location at the beginning of the Introduction.

The Reviewer makes an excellent point. We have added significant clarifying text to the Introduction (Lines 42-47, 52-58, and 61-66). We have also amended Figure 1 to highlight the domain arrangement of GeoCas9 and construct domain boundaries.

Minor corrections to the text

(1) Lines 37-38: The statement about GeoCas9 activity should reference citation.

We have added two references here.

(2) Line 39-40: "The widely-studied SpCas9, as well as GeoCas9, are Type-II CRISPR systems". Cas9 is only a single component of a larger system that contains other proteins and DNA elements, so it would be more appropriate to say "are effectors of type II CRISPR systems" or "are signature proteins of type II CRISPR systems". Also, please define the organism from which SpCas9 is derived. It may be more appropriate to use the three-letter abbreviation "SpyCas9" to be consistent with the abbreviation used for GeoCas9.

We have revised the initial suggestion and specified the organisms. We have, however, chosen to keep “SpCas9” for consistency with our prior work and the work of many several others, including Doudna et al and Zhang et al.

(3) Lines 39-42: "only the Type II-C class to which GeoCas9 belongs has been rigorously validated for mammalian genome editing". SpCas9 is from a type II-A system and is by far the most commonly used ortholog for genome editing, including in ongoing clinical trials. It is unlikely that any of the type II-C Cas9 orthologs have been more rigorously validated than SpCas9. The reference cited in this sentence also does not support this statement and is a review written in 2017, so would be unlikely to reflect the current state of the art. Please revise this sentence.

We have softened and revised this text (Lines 42-47).

(4) Lines 48-52: It would be helpful to describe the dynamic movement of the HNH domain (and cite appropriate references) prior to describing the authors' previous work. As it stands, it is unclear how this sentence would be understood by a non-specialist.

We have added text in Lines 61-68

(5) Lines 44-45: The wording is a little unclear, as it sounds like the guide RNA, rather than the nuclease domains, is responsible for dsDNA cleavage. The sentence could be adjusted to remove "and cleave". Cleavage by the HNH and RuvC domains could be described in a separate sentence.

We have revised this text. See Lines 49-50.

(6) Lines 46-48: This segment of the sentence suggests that PAM recognition triggers the allosteric events that result in the movement of the nuclease domain (HNH). This is misleading, as HNH movement is triggered by the complete formation of an R-loop, rather than initial PAM recognition. Please revise this sentence.

We have revised the text in Lines 52-58.

(7) Lines 62-65: The first sentence is unclear. The specificity of many protein-nucleic acid complexes is well understood and is also readily quantified by several wellestablished methods. Are the authors specifically referring to the structural basis for Cas9 specificity? Although Cas9 specificity is highly complex, it has been studied structurally in great detail and should not be described as "poorly understood" without some discussion of what is already known. These sentences also elide the fact that Cas9 specificity has been successfully altered via rational design, based on our general framework for understanding protein-nucleic acid interactions. Please clarify these statements.

The Reviewer makes an important point. We have softened this statement (Lines 8081). We have clarified that we intended to refer to structural characterization of large, multidomain proteins and nucleic acid complexes via NMR. We agree that many critical structural studies comment on Cas9 dynamics and specificity in great detail, including at the domain-level.

(8) Lines 62-68: It seems like the citations do not match up with the references in this section. The references for citations 8-10 are not about DNA repair complexes, references 11-14 are not papers about the directed evolution of Cas9 (should these be 16-17?), and the references for the HNH domain movements should be for citations 1821.

We apologize for the confusion, and the references have been updated

(9) Lines 116-119: The description of the RNAs used is unclear, as the segments that are described add up to 141 not 101. Also, what is meant by "110-nt guide sequence intrinsic to GeoCas9"? Is this referring to the tracrRNA segment? It may be helpful if the RNA sequences shown in the accompanying figures were replaced with cartoons of the RNAs that were used, with the different segments labeled.

We now describe the gRNA sequences in detail in new Table S4. We also expanded a bit in the text (Lines 224-235).

(10) Line 121-123: This sentence should contain reference(s).

We have changed the sentence.

(11) Line 156-158: Reference 19 did not report or investigate any higher specificity SpCas9 variants, is this citation correct?

We have removed the reference from this line. Ref. 19 (now Ref 23, Slaymaker et al) should be correct.

(12) Lines 162-166: Please provide a sequence and structural alignment for SpCas9 and GeoCas9 to support the claim that the amino acid substitutions are equivalent between the two orthologs.

We have updated Figure 1 to display the similarity in domain arrangement between SpCas9 and GeoCas9 and have noted similarity in structure and sequence of these proteins in Figure S1.

(13) Lines 234-236: There is insufficient evidence to conclude that the alterations in protein dynamics caused the changes in gRNA interaction. The substitutions are charge swap substitutions, and it is equally (if not more) feasible that these substitutions decrease the potential for favorable electrostatic interactions.

(14) Lines 261-265: While the RNP stability for R332A is clearly decreased in comparison to WT, the authors' conclusions regarding K267E seem overstated. The difference in Tm for the K267E mutant and WT RNPs is not very large and may be within error, especially given that the CD data are noisy. Similarly, on lines 321-322, only one of the mutations really impacted the stability of the full-length RNP.

We have softened this text in Lines 303-305.

(15) Lines 336-338: HiFi-SpCas9 does not contain four mutations, it is a single R691A point mutation, as reported in reference 17. This sentence and subsequent sentences should be updated.

Here, the “final form” of HiFi SpCas9 contains the R691A and three additional mutations. The Reviewer is correct, though, that the R691A mutation alone was enough to enhance the specificity of WT SpCas9. We have clarified this point on Line 156.

Minor corrections to the figures

(16) The cryo-EM structures of GeoCas9 have recently been released on the PDB. The authors may now update figures to include the experimentally determined structure, rather than an AlphaFold model and update the text accordingly.

We have made this change.

(17) For Figure S4, please describe what the red dashed lines are in the top three graphs. Are these the Tm values determined for the two individual Rec domains? How do these compare to the inflection points for the two transitions in the full Rec construct (could be determined by plotting the first derivative data)? Please provide information in the Methods on how the temperature-dependent CD spectral data were fit and Tm's were determined.

We have made these changes in the Figure S4 caption and Methods section.

(18) The blue box denoting the unassigned region is missing from Figure 2C-D, although it is mentioned in the figure legend.

We have added the blue box denoting the unassigned linker.

Reviewer #2 (Recommendations For The Authors):

The manuscript is well-written and generally clear and concise. The following recommendations will help improve the readability and include details important for interpreting the results.

(1) In general, the figures are too small and difficult to interpret, it was hard to discern the differences described in the text (e.g. Figure 1A, E, 4A, etc.), the text labels are illegible in several panels (e.g. Figure 4A, S8B, C, etc.), the chosen colors were difficult to interpret in the structures (Figure 4C, S8G, H, etc.), as well as residues with motion (as balls) were difficult to make out due to size and color usage. Similar story for the dispersion curves (Fig 3A), the plots are chaotically crowded, and it is impossible to interpret (or see) the undelaying data.

We apologize for these difficulties. We have now revised the Figures in several ways. First, we greatly simplified Figure 1, such that it now includes only the domain arrangement, structure, and initial NMR details for GeoRec (essentially A-B of the old Figure 1).

Second, we have reformatted Figure 3 to make the structure maps a bit easier to see.

We certainly appreciate the point made by the Reviewer about the dispersion curves. Our intent here is to illustrate the number of curves that can be fit globally, which substantially increase for K267E and R332A GeoRec3, versus WT. As a compromise, we have included the individual dispersion curves in the SI for each variant. We have also thinned the line weights for each fit, and added NMR order parameters to the main figure to round out the discussion of dynamics.

Third, we have compiled the gRNA titration into Figure 4, removing the CD analysis (to SI), MST data (new Fig 5), and unclear structure maps to focus only on the NMR spectra here.

Fourth, we have created a new Figure 5 focusing on MST studies of two gRNAs with GeoRec, which now include bar charts of affinities with appropriate statistics.

Much of the data trimmed from the prior version of the manuscript figures has been moved to Supporting Information. We have also created two new main text Figures (6 & 7) based on MD simulations and MST studies of full-length GeoCas9 and gRNAs to provide additional context for interpreting the results in prior figures.

(2) Line 39 - this sentence is awkward, could you rephrase it?

We have rephrased this sentence.

(3) There is inconsistent labeling, in Figure S2 the full-length construct is referred to as GeoRecFL while in other places in the text and in Figure 1 it is called GeoRec.

We have changed all references to the intact Rec lobe to “GeoRec.”

(4) It would be helpful to include a cartoon of the domain organization of GeoCas9 and indicate the truncation mutants that were studied in this manuscript.

We included the domain organization in Figure 1A and indicated the amino acid boundaries for each construct on the figure and in the Methods section.

(5) There is significant line broadening that occurs during the titration, not all line broadening is due to changes in rotational correlation time, and differential line broadening may reveal interactions of residues that are in the intermediate regime, certainly, uM affinities measured by the authors, would suggest this, therefore, a plot of I/Io might inform on binding sites, and it might be useful to look at differential broadening as a function of titrant added.

The Reviewer makes a very good point. In addition to the data in Figure 4, which show a clear reduction in gRNA-induced line broadening in larger GeoRec constructs, we included new titration data on smaller GeoRec2 domains (Figure S12). Here, we conducted an I/I0 analysis and added some clarifying language about the possible nature of line broadening in these samples. See new Figure S12 and Lines 268-274.

(6) Line 126 "Importantly, many resonances are also minimally impacted." This statement is unclear since from the plots shown in Figure 1D, it seems that many of the residues are impacted by RNA titration, see the point about differential broadening above, this sort of plot may help pick apart residues that broaden due to RNA contacts (rather than changing rotational correlation).

We have removed this statement, in addition to our revisions above regarding the line broadening.

(7) Line 137 - I am not sure that a max chemical shift of 0.15 ppm constitutes "strong chemical shift perturbations"

The Reviewer makes a good point. We have changed “strong” to “significant” which refers to 1 standard deviation above the 10% trimmed mean of the data. See Line 237.

(8) Line 144 - change to "...experimentally determined structure...".

We have added new lines 135-136 to make this point clear. We reinforced that initial predictions were based on the Alphafold2, since an experimental structure was lacking, but we have now discussed the mutations in context of the new structural data.

(9) The section from lines 150 - 166, comparison of the effect of different mutations in different Cas9 seems more appropriate for the discussion section.

We have added additional text on this point in the Discussion section, within several new paragraphs.

(10) In Figure S6, chemical shifts are observed at the distal site away from the mutations, could the authors discuss?

The Reviewer makes an important observation. Indeed, the CSPs caused by K267E and R332A extend beyond the mutation site. These shifts are mostly close in 3D space to the mutation, and consistent in Figures 2 and S5. New titrations of gRNA into isolated GeoRec2 also activate some distal sites, and new MD simulations suggests the mutations disrupt RNA and DNA contacts, where these distal effects may play a role with full-length gRNAs.

We agree it would be worth mutating distal sites undergoing CSPs to examine their impact on function, but two complicating factors are 1) the lack of substantial gRNA affinity differences in experiments with full-length GeoCas9 and 2) the lack of functional changes in the mutants. In this initial study, it appears difficult to assign an effect to these distal sites in GeoCas9 (beyond speculation). We do have a brief discussion of the distal sites (Lines 293-298) and will follow up this work with more comprehensive mutagenesis studies of these sites.

(11) It appears that the authors fitted the Tm data to some model although this is not mentioned in the text, figure captions, or methods. In the caption for Figure 4D the authors refer to "Fitted thermal denaturation profiles...".

We have added the relevant Equation in the Methods and referenced it in Figure S6 and S14 captions.

(12) Details of the ModelFree fitting are needed, how many residues fit with the minimal models, and how many invoked Rex and other terms? How does the statement in line 191 about the elevated S2 values arising from global tumbling compare with an experimental estimation of rotational correlation eg. from R2/R1 ratios?

We have included an expanded description of the Model-free protocol (Lines 521-527). The best diffusion tensor was an ellipsoid model. The number of residues utilizing Rex was 81, though Rex contribution was very small. The mean and errors for the fast motion (S²_f), slow motion (S²_z) and generalized order parameter were 0.97 ± 0.15, 0.84 ± 0.14, and 0.91 ± 0.20, respectively.

R2/R1 ratios for each of the samples (relaxation conducted on GeoRec2 in isolation) corresponded to an estimated tc of 16.3 ns for all data sets. This value is a bit larger than would be expected for a compact globular protein of 25 kDa, though our X-ray structure of GeoRec2 shows a somewhat elongated domain.

(13) Line 221 - referring to two different figures at the end of the sentence is confusing, maybe place the figure references immediately after the referral in the sentence.

We have resolved due to reshuffling of the Figures.

(14) Line 234 - Fig 4E is mentioned before fig 4D, in fact Fig 4D is not mentioned in the text.

We have reordered and edited many of the Figures, this is now resolved.

(15) Line 243 - what is the saturating concentration to which the authors are referring?

We have amended the Results section to more clearly discuss the effect of gRNA on the GeoRec and (now) GeoRec2 domains. We meant 3-fold excess gRNA-to-protein by “saturating” in the prior version. At that point, CSPs held stable and the degree of line broadening at certain sites had completely obscured the resonance from view.

(16) Fig 4E caption - mentions error of 1.34 while the figure is labeled 1.1 for the R332A GeoRec mutant.

This has been resolved due to additional MST trails as well as the editing and reordering of many Figures.

(17) Line 253 - the authors are discussing regions of allosteric hotspots, how do the motions of these predicted hotspots compare with the relaxation dispersion data? There seems to be some overlap.

The Reviewer makes a keen observation. Yes, there is overlap in these data. For example, hotspot residue R269 is bracketed by L268 and L270 with relaxation dispersion. Also, hotspot L279 surrounded by C275, A276, R277, and D281 with dispersion in both variants. Further, D403 and E408 reside in a stretch of ms timescale flexibility comprised of N404, L406, N412, and L413. We have yet to fully understand the functional significance of this overlap, but have added a note in Line 298 to draw the reader’s attention to it.

Reviewer #3 (Recommendations For The Authors):

Although the scope of the manuscript is rather limited due to the minor effects observed for the selected mutations, it is clear that a lot of work was done in spearheading the investigation of dynamic modes in GeoCas9 Rec2. In my view, the data will still be of relevance and interest to the general structural and chemical biology communities.

However, there are a few technical shortcomings that need to be addressed and some statements that are poorly supported by data, necessitating either more experimental proofs or rephrasing of the conclusions.

Major points:

X-ray structure - No PDB ID, structural statistics, or validation report is given for the structure, so it is impossible to judge of the quality. Please provide these. Furthermore, it would be commendable to determine the structure of the point mutant Rec2 domains, this would greatly strengthen the claim that mutations affect only dynamics and do not change structure.

We apologize for this oversight. We absolutely had these data at the time of submission but must have forgotten to upload them. The validation report is now attached.

Regarding the mutant structures, the Reviewer’s point is well taken. In the absence of these structures, we have adjusted the language to include the possibility of structural change. We have also included new MD simulations (new Figure 6 and associated text) that provide comment on possible structural and dynamic changes due to mutation. We note that NMR spectral changes are quite modest, beyond the site of mutation. Further, the new binding data with full-length GeoCas9 (new Figure 7) shows very little change in gRNA affinity with mutations, implying that a profound structural rearrangement does not take place.

Translating isolated Rec2 findings to FL GeoCas9 - This is an important point and I do appreciate that the authors discuss this. I agree that working on FL samples for NMR would not be feasible, but I am not convinced by the statement that "GeoRec2 in isolation represents the structure of the subdomain within full-length GeoCas9 very well". The chemical shift perturbations observed between isolated Rec2 and FL Cas9 are relatively sizable. This should be discussed in further detail. Figure 1B should showcase peaks having the highest perturbations. Are they located at termini or interaction interfaces?

We have provided the combined ¹H-¹⁵N combined CSPs for each construct, relative to the full-length GeoRec domain, Author response image 1. In most cases, the largest CSPs occur at resonances on the periphery of the spectra, retaining the ability to unambiguously assign it. The largest CSPs do appear to exist at the termini.

The Rec1 and Rec2 subdomains are connected by a short, but flexible unstructured linker in full-length GeoRec. Thus, the two subdomains do not form a particularly tight non-covalent interface and behave somewhat independently (see Figure S4, for example).

Regarding the statement of “GeoRec2 in isolation...,” we apologize for this confusion.

We were referring to our solved crystal structure in relation to the AlphaFold model. With the new cryo-EM structure of GeoCas9 having been recently published, our X-ray structure of GeoRec2 is still in excellent agreement, but we have clarified our intent on Line 111.

Dynamics and effect of mutations - K267E is more destabilizing and leads to more spread chemical shift perturbations throughout Rec2 and to faster-correlated dynamics but not in significantly lower affinity or cleavage. How do the authors explain this?

The Reviewer raises an interesting question. Regarding the impact of the K267E mutation, new MD simulations also suggest K267E to be quite disruptive of the GeoCas9 structure and dynamics, modulating contacts with the nucleic acids. However, further MD analysis of the recently published (bona fide high specificity) iGeoCas9 variant shows that K267E only imparts a portion of the effect of iGeoCas9, suggesting that even further modulation of GeoRec would be require for substantial functional impact. In addition, new MST binding studies with full-length variants and gRNAs show K267E does not dramatically alter gRNA binding, suggesting that the lack of functional impact, despite biophysical change, is suppressed by the surrounding GeoCas9 domains. We comment on this in the Discussion.

Moreover, the time regime for the fit of the CPMG curves is surprisingly slow given the profiles, how were the minor state populations? Were the dynamics really correlated? Please provide numbers (also see minor points below). In that regime CEST experiments should work, was that done?

The minor state populations were very low in the analysis, <1%.

To examine the correlated dynamics, we compared the global fits to those of the individual fits for each residue and found them to be better for the global fit, based on the Akaike Information Criterion. For WT, the AIC showed the global fit to be ~10-fold better. For K267E, the global model was 4-fold better, and for R332A, the global model was 6-fold better. We have added language clarifying the use of AIC to the Methods section.

We have done CEST experiments on _Geo_HNH (we did not see overly clear evidence for a minor state), but we did not perform these experiments on GeoRec. However, we strongly agree that a detailed follow-up study focusing on CEST and new GeoRec variants should investigate this further.

Since the binding effects with gRNAs differ in the isolated domain and the full-length protein, we have tried not to over-analyze the impact of the relaxation data in this specific context. These data still provide useful information regarding the impact of point mutants on GeoCas9 domain biophysics, and MD simulations support the enhanced dynamics seen in CPMG and other relaxation data. However, the functional implication is clearly more complicated and requires further study.

Mutations affect gRNA affinity - I am not convinced that affinity itself is significantly affected based on the MST data. This data could be reproduced as technical replicates to reduce the error bars, or another technique with less intrinsic noise (ITC, SPR) could be used to better support this claim. However, a 3-fold difference seen from NMR titrations could indicate a change in binding mode, for instance in koff. It would be interesting to obtain SPR or BLI data quantifying the kinetics of the interactions. Anyhow, this point should be more carefully discussed.

We agree with the Reviewer on this point. We conducted additional replicates of MST trials, as well as new MST with a different gRNA sequence. Our updated analysis, including statistics, provides a better measure for “significance” in these data, which is now reported. We have also added some text discussing a possible change in binding mode, see Lines 256-259.

We also carried out MST on full-length GeoCas9 with full-length gRNAs (the same two RNAs used as truncated constructs). We report these data in new Figure 7 and note there is essentially no difference between the gRNAs or the GeoCas9 variants under these conditions.

Further, MD simulations suggest a change in binding energy associated with the gRNA interaction in the context of full-length GeoCas9. Since experimental studies are not able to parse these differences, collectively, we describe a scenario where the highly stable structure of GeoCas9 resists substantial mutation-induced change seen for analogous perturbations in SpCas9. See Lines 309-342, 414-418, and 448-461.

Minor points:

• Please detail how the error on R1 and R2 rates was calculated.

We have included new text in Lines 514-518.

• Please detail how hetNOE values were calculated (simply Isat/Iref?) and what values were used for Model Free.

Yes, the Reviewer is correct. We have added specifically that we used Isat/Iref on Line 518.

• Please elaborate on the Model Free analysis. What tensor was used for tumbling? What was the correlation time? This is needed to judge the trustworthiness of S2 parameters.

We have included new text on Lines 520-526. The diffusion tensor used was an ellipsoid and the correlation time was 15.4 ns. The correlation time estimated from R2/R1 ratios was 16.3 ns.

• Figure 1: Please indicate where Rec1 and Rec2 are located on panel A and indicate the residue assignments for each peak showcased in panel B.

We have indicated the boundary of Rec1 and Rec2 in the new cartoon of Figure 1A. We have also noted the exact amino acids used for each construct in the Methods. We also added resonance labels to the spectral overlays in Figure 1B. We have done the same

• Line 187: I believe this should refer to Figure S8C rather than Figure 3A.

We have made this change.

• Some fits of the CPMG curves look strange, e.g. R343 in Fig. 3B WT definitely does not contain significant us-ms dynamics and should be excluded from the analysis. Please double-check each profile. Were other models besides CR72 not providing better fits?

The Reviewer has made a very careful observation. Our intent was to highlight these sites on purpose to show differences in CPMG relaxation dispersion between WT and variant samples. This was provided as some evidence for the redistribution of dynamics between samples, as many different sites found to be “rigid” on the ms timescale in WT GeoRec2 were flexible in GeoRec2 variants. We agree, however, that this Figure panel was confusing and have therefore removed it in favor of simple discussion in the text.

• To what degree are the CPMG dynamics correlated, can you provide statistical measures for the global fits?

We compared the global fits to those of the individual fits for each residue and found them to be better for the global fit, based on the Akaike Information Criterion. For WT, the AIC showed the global fit to be ~10-fold better. For K267E, the global model was 4fold better, and for R332A, the global model was 6-fold better.

We have added language clarifying the use of AIC to the Methods section.

• Error measured from replicates and p-values should be reported for DNA cleavage assays.

We thank the Reviewer for pointing out this omission. We have included error bars on these plots.

eLife Assessment

This important study aims to understand the role of endothelial cell differentiation into pericytes in the restoration of blood-brain barrier function after ischemic stroke. Identification of pericytes derived from endothelial cells and the involvement of myeloid cell-derived TGFβ1 signaling are compelling new findings, but the evidence supporting the origin and nature of these pericytes is incomplete and would benefit from more rigorous approaches demonstrating reproducibility. The work will be of interest to researchers whose work focuses on the blood-brain barrier and basic and translational stroke.

Reviewer #1 (Public review):

Summary:

Using lineage tracing and single-cell RNA sequencing, Li et al. reported brain ECs can differentiate into pericytes after stroke. This finding is novel and important to the field.

Strengths:

Detailed characterization of each time point and genetic manipulation of genes for study role of ECs and E-pericyte.

Weaknesses:

Genetic evidence for lineage tracing of ECs and E-pericytes requires more convincing data that includse staining, FACS, and scRNA-seq analysis.

Reviewer #2 (Public review):

Summary:

In this manuscript, Li and colleagues study the fate of endothelial cells in a mouse model of ischemic stroke. Using genetic lineage tracing approaches, they found that endothelial cells give rise to non-endothelial cells, which they term "E-pericytes." They further show that depleting these cells exacerbates blood-brain barrier leakage and worsens functional recovery. The authors also provide evidence that endothelial-to-mesenchymal transition, myeloid cell-derived TGFβ1, and endothelial TGFβRII are involved in this process. These are potentially interesting findings, however, the experimental evidence that endothelial cells undergo transdifferentiation to non-endothelial cells is weak, as is the evidence that these cells are pericytes. Addressing this foundational weakness will facilitate the interpretation of the other findings.

Strengths:

(1) The authors address an important question about blood vessel function and plasticity in the context of stroke.

(2) The authors use a variety of genetic approaches to understand cell fate in the context of stroke. Particularly commendable is the use of several complementary lineage tracing strategies, including an intersectional strategy requiring both endothelial Cre activity and subsequent mural cell NG2 promoter activity.

(3) The authors address upstream cellular and molecular mechanisms, including roles for myeloid-derived TGFβ.

Weaknesses:

(1) The authors use Cdh5-CreERT2; Ai47 mice to permanently label endothelial cells and their progeny with eGFP. They then isolate eGFP+ cells from control and MCAO RP7D and RP34D brains, and use single-cell RNA-seq to identify the resulting cell types. Theoretically, all eGFP+ cells should be endothelial cells or their progeny. This is a very powerful and well-conceived experiment. The authors use the presence of a pericyte cluster as evidence that endothelial-to-pericyte transdifferentiation occurs. However, pericytes are also present in the scRNA-seq data from sham mice, as are several other cell types such as fibroblasts and microglia. This suggests that pericytes and these other cell types might have been co-purified (e.g., as doublets) with eGFP+ endothelial cells during FACS and may not themselves be eGFP+. Pericyte-endothelial doublets are common in scRNA-seq given that these cell types are closely and tightly associated. Additionally, tight association (e.g., via peg-socket junctions) can cause fragments of endothelial cells to be retained on pericytes (and vice-versa) during dissociation. Finally, it is possible that after stroke or during the dissociation process, endothelial cells lyse and release eGFP that could be taken up by other cell types. All of these scenarios could lead to the purification of cells that were not derived (transdifferentiated) from endothelial cells. The authors note that the proportion of pericytes increased in the stroke groups, but it does not appear this experiment was replicated and thus this conclusion is not supported by statistical analysis. The results of pseudotime and trajectory analyses rely on the foundation that the pericytes in this dataset are endothelial-derived, which, as discussed above, has not been rigorously demonstrated.

(2) I have the same concern regarding the inadvertent purification of cells that were not derived from endothelial cells in the context of the bulk RNA-seq experiment (Figure S4), especially given the sample-to-sample variability in gene expression in the RP34D, eGFP+ non-ECs-group (e.g., only 2/5 samples are enriched for mesenchymal transcription factor Tbx18, only 1/5 samples are enriched for mural cell TF Heyl). If the sorted eGFP+ non-ECs were pericytes, I would expect a strong and consistent pericyte-like gene expression profile.

(3) The authors use immunohistochemistry to understand localization, morphology, and marker expression of eGFP+ cells in situ. The representative "E-pericytes" shown in Figure 3A-D are not associated with blood vessels, and the authors' quantification also shows that the majority of such cells are not vessel-associated ("avascular"). By definition, pericytes are a component of blood vessels and are embedded within the vascular basement membrane. Thus, concluding that these cells are pericytes ("E-pericytes") may be erroneous.

(4) CD13 flow cytometry and immunohistochemistry are used extensively to identify pericytes. In the context of several complementary lineage tracing strategies noted in Strength #2, CD13 immunohistochemistry is the only marker used to identify putative pericytes (Figure S3J-M). In stroke, CD13 is not specific to pericytes; dendritic cells and other monocyte-derived cells express CD13 (Anpep) in mouse brain after stroke (PMID: 38177281, https://anratherlab.shinyapps.io/strokevis/).

(5) The authors conclude that "EC-specific overexpression of the Tgfbr2 protein by a virus (Tgfbr2) decreases Evans blue leakage, promotes CBF recovery, alleviates neurological deficits and facilitates spontaneous behavioral recovery after stroke by increasing the number of E-pericytes." All data in Figure 10, however, compare endothelial Tgfbr2 overexpression to a DsRed overexpression control. There is no group in which Tgfbr2 is overexpressed but "E-pericytes" are eliminated with DTA (this is done in Figure 9B, but this experiment lacks the Tgfbr2 overexpression-only control). Thus, the observed functional outcomes cannot be ascribed to "E-pericytes"; it remains possible that endothelial Tgfbr2 overexpression affects EB leakage, CBF, and behavior through alternative mechanisms.

(6) Single-cell and bulk RNA-seq data are not available in a public repository (such as GEO). Depositing these data would facilitate their independent reevaluation and reuse.

Reviewer #3 (Public review):

Summary:

The data and experiments presented in that study convincingly show that a subpopulation of endothelial cells undergo transformation into pericyte-like cells after stroke in mice. These so-called "E-pericytes" are protective and might present a new target for stroke recovery. The authors used a huge battery of different techniques and modified signaling pathways and cellular interactions using several genetic and pharmacological tools to show that TGFbeta and EndoMT are causes of this transformation.

Strengths:

The amount of different genetic and pharmacological approaches in combination with sophisticated techniques such as single-cell RNAseq is impressive and convincing. The results support their conclusions and the authors achieved their aims. The findings will strongly impact the field of cerebrovascular recovery after stroke and might open up new therapeutic targets.

Weaknesses:

The written and graphic presentation of the findings needs substantial improvement. Language editing is strongly recommended (there are a lot of spelling and grammatical errors in the text and illustrations, including legends).

eLife Assessment

This work is of fundamental significance and has an exceptional level of evidence for the role of a mutant p53 in regulation of tumorigenesis using an in vivo mouse model. The study is well-conducted and will be of interest to a broad audience including those interested in p53, transcription factors and cancer biology.

Reviewer #1 (Public review):

Summary:

This manuscript by Toledo and colleagues describes the generation and characterization of Y220C mice (Y217C in the mouse allele). The authors make notable findings: Y217C mice that have been backcrossed to C57Bl/6 for five generations show decreased female pup births due to exencephaly, a known defect in p53 -/- mice, and they show a correlation with decreased Xist expression, as well as increased female neonatal death. They also noted similar tumor formation in Y217C/+ and p53 +/- mice, suggesting that Y217C may not function as a dominant negative. Notably, the authors find that homozygous Y217C mice die faster than p53 -/- mice, and that the lymphomas in the Y217C mice were more aggressive and invasive. The authors then perform RNA seq on thymi of Y217C homozygotes compared to p53 -/-, and they suggest that these differentially expressed genes may explain the increased tumorigenesis in Y217C mice.

Strengths:

Overall, the study is well controlled and quite well done and will be of interest to a broad audience, particularly given the high frequency of the Y220C mutation in cancer (1% of all cancers, 4% of ovarian cancer).

Weaknesses:

None noted

Comments on revisions:

The authors have done a superb job on this very interesting work.

Reviewer #2 (Public review):

Summary:

Jaber et al. describe the generation and characterization of a knock-in mouse strain expressing the p53 Y217C hot-spot mutation. While the homozygous mutant cells and mice reflect the typical loss-of-p53 functions, as expected, the Y217C mutation also appears to display gain-of function (GOF) properties, exemplified by elevated metastasis in the homozygous context (as noted with several hot-spot mutations). Interestingly, this mutation does not appear to exhibit any dominant-negative effects associated with most hot-spot p53 mutations, as determined by absence of differences in overall survival and tumor predisposition of the heterozygous mice, as well as target gene activation upon nutlin treatment.

In addition, the authors noted a severe reduction in the female 217/217 homozygous progeny, significantly more than that observed with the p53 null mice, due to exencephaly, leading them to conclude that the Y217C mutation also has additional, non-cancer related GOFs. Thought this property has been well described and attributed to p53 functional impairment, the authors conclude that the Y217C has additional properties in accelerating the phenotype.<br /> Transcriptomic analyses of thymi found additional gene signature differences between p53 null and the Y217C strains, indicative of novel target gene activation, associated with inflammation.

Strengths:

Overall, the characterisation of the mice highlights the expected typical outcomes associated with most hot-spot p53 mutations published earlier. The quality of the work presented is well done and good, and the conclusions and reasonably well justified.

Comments on revisions:

Revised version has addressed most of our queries and is acceptable.

Author response:

The following is the authors’ response to the original reviews

Reviewer #2 suggested the addition of new data to address the following points:

Reviewer #2: 

(1) Oncogenic GOF - the main data shown for GOF are the survival curve and enhanced metastasis. Often, GOF is exemplified at the cellular level as enhanced migration and invasion, which are standard assays to support the GOF. As such, the authors should perform these assays using either tumor cells derived from the mice or transformed fibroblasts from these mice. This will provide important and confirmatory evidence for GOF for Y217C. 

We thank the referee for this comment. Our previous data indicated accelerated tumor progression and increased metastasis in Trp53^Y217C/Y217C mice, which provided in vivo evidence of an oncogenic gain of function (GOF) for the p53^Y217C mutant. However, we agree that it was important to provide additional evidence of GOF at the cellular level. 

Many cellular assays were previously used to evaluate the GOF of p53 mutants, including those listed by the referee. Importantly, Zhao et al. recently showed that a common property of several p53 mutants proposed to have oncogenic GOF is their capacity to promote chromosomal instability (Zhao et al. (2024) Nat. Commun. 15, 180). For the revision of our manuscript, we compared the frequencies of chromosomal alterations occurring spontaneously in WT, Trp53^Y217C/Y217C and Trp53^-/- mouse embryonic fibroblasts (MEFs). Chromosome breaks, radial chromosomes and DMs were more frequent in Trp53^Y217C/Y217C MEFs than in WT or Trp53^-/- MEFs, providing clear evidence of a GOF promoting chromosomal instability. This new result is presented in Figure 2G and mentioned in the revised abstract. 

Furthermore, as pointed out by referee #1 in a confidential comment, increased NF-kB signaling provides evidence of p53 GOF. Accordingly, Zhao et al. proposed that the capacity of p53^G245D and p53^R273H to promote chromosomal instability ultimately led to activation of a noncanonical NF-kB signaling that would promote tumor cell invasion and metastasis. Consistent with their work, we now report that the GSEA of Trp53^Y217C/Y217C and Trp53^-/- thymocytes revealed an upregulation of non-canonical NF-kB signaling in Trp53^Y217C/Y217C thymic cells (a new result presented in Figure 5F and Supplementary Figure S13).  These new data lead us to mention in the revised discussion that “similar mechanisms might underlie the oncogenic properties of the p53^Y217C, p53^G245D and p53^R273H mutants”.

(2) Novel target gene activation - while a set of novel targets appears to be increased in the Y217C cells compared to the p53 null cells, it is unclear how they are induced. The authors should examine if mutant p53 can bind to their promoters through CHIP assays, and, if these targets are specific to Y217C and not the other hot-spot mutations. This will strengthen the validity of the Y217C's ability to promote GOF. 

We respectfully disagree with the referee when he/she considers that the validity of p53^Y217C’s ability to promote a GOF would be strengthened by showing that p53^Y217C binds to the promoters of genes upregulated in Trp53^Y217C/Y217C cells. In fact, Pal et al. recently performed the experiment proposed by the referee, by integrating RNAseq and ChIPseq data from MCF10A cells expressing p53^Y220C, the human equivalent of p53^Y217C,  and found that 95% of the genes upregulated upon p53^Y220C expression were upregulated indirectly, without p53^Y220C binding to their promoters (Pal et al. (2023) NPJ Breast Cancer 9, 78). Consistent with our data, Pal et al. notably found that the expression of p53^Y220C increased cell migration and invasion, which correlated with an increased expression of S100A8 and S100A9. They found that the promoters of S100A8 and S100A9 were however not bound by p53^Y220C, indicating an indirect mechanism for their upregulated expression. Furthermore, the study by Zhao et al. mentioned above also suggested an indirect mechanism of GOF, because the upregulation of inflammation-related genes by a mutant p53 protein was proposed to result from signaling cascades triggered by chromosomal instability. Our data appear consistent with both studies, because p53^Y217C was undetectable or barely detectable in the chromatin fraction of Trp53^Y217C/Y217C cells, and because Trp53^Y217C/Y217C cells exhibited increased chromosome instability and increased NFB signaling compared to Trp53^-/- cells, which may suggest indirect mechanisms for p53^Y217C GOF. 

Nevertheless, we agree with the referee that it was important to provide stronger evidence of p53^Y217C GOF in the revised manuscript.  In that regard, we were intrigued by the perinatal death of most Trp53^Y217C/Y217C females, which provided evidence of unexpected teratogenic effects of the mutant. We had proposed that these female-specific teratogenic effects likely resulted from pro-inflammatory GOF of p53^Y217C. This hypothesis relied on the RNAseq pro-inflammatory signature in Trp53^Y217C/Y217C thymic cells, and on the fact that the glycoprotein CD44, known to drive inflammation, had been identified as a key gene in open neural tube defects. However, we had not tested this hypothesis experimentally. In the revised version of the manuscript, we tested this hypothesis. We mated Trp53^+/Y217C female mice with Trp53^Y217C/Y217C males, then administered supformin (LCC-12), a potent CD44 inhibitor known to attenuate inflammation in vivo, to pregnant mice by oral gavage. The administration of subformin led to a five-fold increase in the proportion of weaned Trp53^Y217C/Y217C females in the progeny, suggesting that reducing inflammation in utero rescued some of the Trp53^Y217C/Y217C female embryos. This new result is presented in Figure 5G and Supplementary Table S6, and mentioned in the abstract. 

We believe that these new results, as well as the additional GSEA analyses revealing increased NFkB signaling in Trp53^Y217C/Y217C cells, further emphasize the importance of inflammation in the GOF of the p53^Y217C mutant. Accordingly, we slightly modified the title of our article, to include the notion that Trp53^Y217C is an inflammation-prone mouse model. We also end the article by summarizing the effects of p53^Y217C in vivo, in a new Supplementary Table S7 that compares the LOF effects of a p53 KO with the (LOF+GOF) effects of the p53^Y217C mutant. 

(3) Dominant negative effect - the authors' claim of lack of DN effect needs to be strengthened further, as most p53 hot-spot mutations do exhibit DN effect. At the minimum, the authors should perform additional treatment with nutlin and gamma irradiation (or cytotoxic/damaging agents) and examine a set of canonical p53 target genes by qRT-PCR to strengthen their claim. 

Our previous data indicated identical tumor onset and survival in Trp53^+/Y217C and Trp53^+/- mice, leading us to conclude that, at least for spontaneous tumorigenesis, there was no evidence of a Dominant Negative Effect (DNE) in vivo. Here, we followed the referee’s suggestion and evaluated the possibility of a DNE in response to stress, by comparing WT, Trp53^+/Y217C and Trp53^+/- MEFs or thymocytes. We analyzed different types of stress (Nutlin, Doxorubicin, girradiation) and different types of cellular responses (transactivation of classical p53 target genes, cell cycle arrest, apoptosis), and the results lead us to conclude that there is little if any DNE also in response to various stresses. These new data are mentioned in a paragraph evaluating the possibility of DNE or GOF at the cellular level, and presented in a new Supplementary Figure S6.

eLife Assessment

The manuscript provides valuable findings in the field for understanding the RNAi regulation in plants at the molecular level with a model of how DRB7.2 and DRB4 form a heterodimer and protect dsRNA from DICER activity. The presented data provide a solid basis for the model, but certain measurements could benefit from replicates for robust statistics.

Reviewer #1 (Public review):

Summary:

In this manuscript, Paturi et.al. presents a detailed structural and mechanistic study of the DRB7.2:DRB4 complex in plants, focusing on its role in sequestering endogenous inverted-repeat dsRNA precursors and inhibiting Dicer-like protein 3 (DCL3) activity. By truncating the two proteins, they systematically identify the domains involved in direct interaction between DRB7.2 and DRB4 and study the interactions between the two using biophysical techniques (ITC and NMR). They show using NMR that the interacting domains between the two proteins are likely partially unfolded or aggregated in the absence of the binding partner and determining the NMR structure of the individual interacting domains in the presence of the isotopically unlabelled partner using sparse restrain data combined with Rosetta. They also determine the complex structure of the interacting DRB7.2 dsRBD domain and the DRB4 D3 domain using X-ray crystallography.

Strengths:

Overall, the manuscript is well written, provides molecular details at high resolution between the interaction of DRB7.2 and DRB4 and the data in the manuscript strongly supports the proposed model where DRB7.2:DRB4 complex sequesters the DCL3 substrates inhibiting its function of producing epigenetically activated siRNAs.

Weaknesses:

Major comments:

(1) The manuscript unfortunately completely lacks functional validation of the determined DRB7.2:DRB4 complex structure which is required for the rigorous validation of the proposed model. For functional validation of the determined structures, the author should at least present the mutational analysis (impact on complex formation, RNA affinity) of the point mutants derived from the structure of the DRB7.2:DRB4 complex.

(2) The proposed model shows the DRB7.2M and DRB4D3 as partially folded/aggregated proteins in the absence of the complex, understandably from the presented NMR data of the individual domains. However, in the cellular context, when the RNAs are present, especially DRB7.2M might be properly folded/not aggregated. Could the authors support or negate this by showing the 15N HSQC spectrum of DRB7.2M in complex with the 13 bp dsRNA?

(3) It remains unclear from the manuscript if DRB7.1 will have a similar or different mechanism of interaction with DRB4. Based on the sequence comparisons of the two proteins, the authors should comment on this in the discussion section.

Minor comments:

(1) There are no errors for the N, dH and dS values of the ITC measurements in Table 1. Also, it seems that the measurements are done only once. Values derived from at least triplicates should be presented. This would be helpful to increase confidence in the values derived from ITC especially for the titration between DRB7.2, DRB4C, and DRB4D3 as the N value there is substantially lower than 1 which does not agree with the other data.

Reviewer #2 (Public review):

Summary:

The manuscript by Paturi and colleagues uses an approach that combines structural biology and biochemistry to probe protein-protein and protein-RNA interactions for two protein factors related to the dsRNA pathway in plants.

Strengths:

A key finding in the research is the direct demonstration of the ability of the single dsRBD (double-strand RNA binding domain) of DRB7.2 to interact simultaneously with dsRNA as well as the C-terminal domain of DRB4. The heterodimerization of DRB7.2 and DRB4 is demonstrated to make a high-affinity complex with dsRNA and it is proposed that this atypical use of the dsRBD domain to bridge the protein and RNA may contribute to the ability to prevent cleavage that would otherwise occur for dsRNA. The primary results for the interactions are generally well-supported by the data, and the conclusions are taken from the available results without excessive speculation.

Weaknesses:

There is a need for some statistical repeats, as well as a suggested movement of many protein characterization findings in the solution state to support data or to better indicate how these properties could play a role in the final proposed mechanism. There is also the need for certain measurement replicates, such as for the ITC data which are derived from single measurements and lack sufficient estimates of error.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this manuscript, Paturi et.al. presents a detailed structural and mechanistic study of the DRB7.2:DRB4 complex in plants, focusing on its role in sequestering endogenous inverted-repeat dsRNA precursors and inhibiting Dicer-like protein 3 (DCL3) activity. By truncating the two proteins, they systematically identify the domains involved in direct interaction between DRB7.2 and DRB4 and study the interactions between the two using biophysical techniques (ITC and NMR). They show using NMR that the interacting domains between the two proteins are likely partially unfolded or aggregated in the absence of the binding partner and determining the NMR structure of the individual interacting domains in the presence of the isotopically unlabelled partner using sparse restrain data combined with Rosetta. They also determine the complex structure of the interacting DRB7.2 dsRBD domain and the DRB4 D3 domain using X-ray crystallography.

Strengths:

Overall, the manuscript is well written, provides molecular details at high resolution between the interaction of DRB7.2 and DRB4, and the data in the manuscript strongly supports the proposed model where DRB7.2:DRB4 complex sequesters the DCL3 substrates inhibiting its function of producing epigenetically activated siRNAs.

Weaknesses:

Major comments:

(1) The manuscript, unfortunately, completely lacks functional validation of the determined DRB7.2:DRB4 complex structure, which is required for the rigorous validation of the proposed model. For functional validation of the determined structures, the author should at least present the mutational analysis (impact on complex formation, RNA affinity) of the point mutants derived from the structure of the DRB7.2:DRB4 complex.

We thank the reviewer for pointing out a crucial aspect that is missed out in our manuscript. With the inputs and experiments proposed above, we would certainly like to perform additional mutational analysis to determine the impact on the heterodimeric complex formation and identify the key essential residues involved in the RNA binding.

We expect that we can accomplish this study in the next ~ 4-6 months as we may have to create a combination of mutations for residues involved in the dimerization interface, namely, T131, V132, E134, F136, W156, and V161 on DRB7.2M. Having said that, the disruption of the heterodimer interface would probably lead to DRB7.2M and DRB4D3 returning to their fast-intermediate timescale exchanging native homo-oligomeric state/partially folded state.

For dsRNA binding, six residues (i.e., A85 and K86 (a1), H112 and K114 (b1-b2 loop), and K142 and K144 (a2)) involved in the RNA binding interface and a few other residues based on the mutational data will be considered.

(2) The proposed model shows the DRB7.2M and DRB4D3 as partially folded/aggregated proteins in the absence of the complex, understandably from the presented NMR data of the individual domains. However, in the cellular context, when the RNAs are present, especially DRB7.2M might be properly folded/not aggregated. Could the authors support or negate this by showing the ¹⁵N HSQC spectrum of DRB7.2M in complex with the 13 bp dsRNA?

While we have no direct proof that the DRB7.2M might be folded/not aggregated in the presence of RNAs in the cellular context, the in vitro NMR-based titration studies of alone DRB7.2 (Author response image 1A) with two molar equivalence of 13 bp dsRNA (Author response image 1B and R1C) indicate that there is no change in overall spectral pattern (except for the apparent chemical shift perturbations as expected from fast-intermediate exchange timescale binding of DRB7.2M with 13 bp dsRNA), implying that the dsRNA alone is neither necessary nor sufficient to disrupt the native fast exchange oligomeric states sampled by individual DRB7.2 and DRB7.2M.

Author response image 1.

DRB7.2M binding interaction with 13bp dsRNA (A) 1H-15N TROSY-HSQC of U[15N, 2H] DRB7.2M. (B) 1H-15N TROSY-HSQC of U[15N, 2H] DRB7.2M in the presence of 13 bp dsRNA with 1:2 molar equivalence. (C) An overlay of (A) and (B) indicates no evident changes in the broadening of resonances. (D) The 15N linewidth analysis of unbound (red) and bound (green) forms of U[15N, 2H] DRB7.2M resonances for which the assignment could be traced from the assignments of the DRB7.2M:DRB4D3 complex.

Furthermore, the line-width analysis, shown in Author response image 1D, implies that the ~R₂ rates are roughly identical in the presence of dsRNA, indicating that the native oligomeric state of DRB7.2M remains unperturbed by the presence of dsRNA. Our observation also corroborates with the crystal structure presented in the manuscript, where we have observed that the hetero-dimeric interface lies on the opposite side of the dsRNA binding interface of the DRB7.2M:DRB4D3 complex.

Therefore, the dsRNA substrate does not have any role in the native partially folded/oligomeric state of DRB7.2M.

(3) It remains unclear from the manuscript if DRB7.1 will have a similar or different mechanism of interaction with DRB4. Based on the sequence comparisons of the two proteins, the authors should comment on this in the discussion section.

Pairwise sequence alignment of full-length DRB7.2 and DRB7.1 reveals 50.7% similarity and a 33.2% identity derived from EMBOSS Needle (Author response image 2).

Author response image 2.

ClustalW alignment of full-length DRB7.2 and DRB7.1. The secondary structure elements are derived from the crystal structure of DRB7.2M (PDB ID: 8IGD). Identical residues are marked with red highlights, whereas similar residues are marked with yellow highlights, and the consensus residues (> 50%) are annotated below the sequence alignment.

As expected, for the dsRBD region (corresponding to DRB7.2M), we observe a much higher degree of alignment with a 76.7% similarity with a 54.7% identity (Author response image 3).

Author response image 3.

ClustalW alignment of the dsRBD region of DRB7.2 and DRB7.1. The secondary structure elements are derived from the crystal structure of DRB7.2M (PDB ID: 8IGD). Identical residues are marked with red highlights, whereas similar residues are marked with yellow highlights, and the consensus residues (> 50%) are annotated below the sequence alignment.

Moreover, the residues involved in the heterodimerization interface in DRB7.2M are identical to those in DRB7.1. As a matter of fact, the residues involved in the dimerization interface, namely, T131, V132, E134, F136, W156, and V161 in DRB7.2M are unchanged in DRB7.1, suggesting that DRB7.1M may interact with DRB4D3 using a similar manner as illustrated for DRB7.2M:DRB4D3 in the manuscript.

Future studies will shed more light on the binding preference of DRB4D3 with DRB7.1 versus DRB7.2. One interesting thing to note is that DRB7.2 is exclusively present in the nucleus, whereas DRB7.1 is observed to localize in the nucleus as well as the cytoplasm. Therefore, spatial restriction may be one of the mechanisms that bring exclusivity to the interaction partner despite having a conserved interaction interface.

Minor comments:

(1) There are no errors for the N, dH, and dS values of the ITC measurements in Table 1. Also, it seems that the measurements are done only once. Values derived from at least triplicates should be presented. This would be helpful to increase confidence in the values derived from ITC, especially for the titration between DRB7.2, DRB4C, and DRB4D3, as the N value there is substantially lower than 1, which does not agree with the other data.

We plan to estimate the errors as proposed by the reviewer in the revised manuscript to ensure that the presented data is of high confidence.

Reviewer #2 (Public review):

Summary:

The manuscript by Paturi and colleagues uses an approach that combines structural biology and biochemistry to probe protein-protein and protein-RNA interactions for two protein factors related to the dsRNA pathway in plants.

Strengths:

A key finding in the research is the direct demonstration of the ability of the single dsRBD (double-strand RNA binding domain) of DRB7.2 to interact simultaneously with dsRNA as well as the C-terminal domain of DRB4. The heterodimerization of DRB7.2 and DRB4 is demonstrated to make a high-affinity complex with dsRNA, and it is proposed that this atypical use of the dsRBD domain to bridge the protein and RNA may contribute to the ability to prevent cleavage that would otherwise occur for dsRNA. The primary results for the interactions are generally well-supported by the data, and the conclusions are taken from the available results without excessive speculation.

Weaknesses:

There is a need for some statistical repeats, as well as a suggested movement of many protein characterization findings in the solution state to support data or to better indicate how these properties could play a role in the final proposed mechanism. There is also the need for certain measurement replicates, such as for the ITC data, which are derived from single measurements and lack sufficient estimates of error.

We plan to restructure the manuscript on the lines proposed by the reviewer in the revised version. Moreover, as mentioned in the response to the comments of Reviewer 1, we suggest estimating the errors to ensure that the presented data is of high confidence in the revised version.

eLife Assessment

In this manuscript, Franco and colleagues describe valuable findings about the chemotactic response of Salmonella to serine and indole, conflicting chemotactic signals. Although the evidence presented is solid, concerns were raised about the novelty of the chemotactic phenomena observed with these two compounds. Also, although the induction of invasion by feces is a novel and interesting finding, the lack of follow-up to this observation was also noted.

Reviewer #1 (Public review):

Summary:

The study shows, perhaps surprisingly, that human fecal homogenates enhance the invasiveness of Salmonella typhimurium into cells of a swine colonic explant. This effect is only seen with chemotactic cells that express the chemoreceptor Tsr. However, two molecules sensed by Tsr that are present at significant concentrations in the fecal homogenates, the repellent indole and the attractant serine, do not, either by themselves or together at the concentrations in which they are present in the fecal homogenates, show this same effect. The authors then go on to study the conflicting repellent response to indole and attractant response to serine in a number of different in vitro assays.

Strengths:

The demonstration that homogenates of human feces enhance the invasiveness of chemotactic Salmonella Typhimurium in a colonic explant is unexpected and interesting. The authors then go on to document the conflicting responses to the repellent indole and the attractant serine, both sensed by the Tsr chemoreceptor, as a function of their relative concentration and the spatial distribution of gradients.

Weaknesses:

The authors do not identify what is the critical compound or combination of compounds in the fecal homogenate that gives the reported response of increased invasiveness. They show it is not indole alone, serine alone, or both in combination that have this effect, although both are sensed by Tsr and both are present in the fecal homogenates. Some of the responses to conflicting stimuli by indole and serine in the in vitro experiments yield interesting results, but they do little to explain the initial interesting observation that fecal homogenates enhance invasiveness.

Reviewer #2 (Public review):

Summary:

The manuscript presents experiments using an ex vivo colonic tissue assay, clearly showing that fecal material promotes Salmonella cell invasion into the tissue. It also shows that serine and indole can modulate the invasion, although their effects are much smaller. In addition, the authors characterized the direct chemotactic responses of these cells to serine and indole using a capillary assay, demonstrating repellent and attractant responses elicited by indole and serine, respectively, and that serine can dominate when both are present. These behaviors are generally consistent with those observed in E. coli, as well as with the observed effects on cell invasion.

Strengths:

The most compelling finding reported here is the strong influence of fecal material on cell invasion. Also, the local and time-resolved capillary assay provides a new perspective on the cell's responses.

Weaknesses:

The weakness is that indole and serine chemotaxis does not seem to control the fecal-mediated cell invasion and thus the underlying cause of this effect remains unclear.

In addition, the fact that serine alone, which clearly acts as a strong attractant, did not affect cell invasion (compared to buffer) is somewhat puzzling. Additionally, wild-type cells showed nearly a tenfold advantage even without any ligand (in buffer), suggesting that factors other than chemotaxis might control cell invasion in this assay, particularly in the serine and indole conditions. These observations should probably be discussed.

Final comment. As shown in reference 12, Tar mediates attractant responses to indole, which appear to be absent here (Figure 3J). Is it clear why? Could it be related to receptor expression?

Reviewer #3 (Public review):

Summary:

In this manuscript, Franco and colleagues describe careful analyses of Salmonella chemotactic behavior in the presence of conflicting environmental stimuli. By doing so, the authors describe that this human pathogen integrates signals from a chemoattractant and a chemorepellent into an intermediate "chemohalation" phenotype.

Strengths:

The study was clearly well-designed and well-executed. The methods used are appropriate and powerful. The manuscript is very well written and the analyses are sound. This is an interesting area of research and this work is a positive contribution to the field.

Weaknesses:

Although the authors do a great job in discussing their data and the observed bacterial behavior through the lens of chemoattraction and chemorepulsion to serine and indole specifically, the manuscript lacks, to some extent, a deeper discussion on how other effectors may play a role in this phenomenon. Specifically, many other compounds in the mammalian gut are known to exhibit bioactivity against Salmonella. This includes compounds with antibacterial activity, chemoattractants, chemorepellers, and chemical cues that control the expression of invasion genes. Therefore, authors should be careful when making conclusions regarding the effect of these 2 compounds on invasive behavior. It is important that the word invasion is used in the manuscript only in its strictest sense, the ability displayed by Salmonella to enter non-phagocytic host cells. With that in mind, authors should discuss how other signals that feed into the control of Salmonella invasion can be at play here.

Author response:

We thank the reviewers of this manuscript for their thoughtful and detailed feedback, and agree that they bring up valid points. We also thank them for their suggestions on how to improve this study. We intend to revise this manuscript to help address these concerns and in the future will submit a revised version that will hopefully be improved in terms of the clarity of the text and rigor of the experimental findings.

eLife Assessment

This solid work, a Research Advance linked to Buchwalter et al., 2019, demonstrates that epitope tagging influences protein fate, serving as a cautionary example of how different tagging and imaging strategies may alter the pattern of endogenous protein trafficking. The information presented will be useful for researchers in the field of membrane trafficking, particularly in guiding their experimental designs. That being said, the study offers limited new insights into the biogenesis or disposal of endogenous Emerin.

Reviewer #1 (Public review):

Summary:

The authors revisit the specific domains/signals required for the redirection of an inner nuclear membrane protein, emerin, to the secretory pathway. They find that epitope tagging influences protein fate, serving as a cautionary tale for how different visualisation methods are used. Multiple tags and lines of evidence are used, providing solid evidence for the altered fate of different constructs.

Strengths:

This is a thorough dissection of domains and properties that confer INM retention vs secretion to the PM/lysosome, and will serve the community well as a caution regarding the placement of tags and how this influences protein fate.

Weaknesses:

Biogenesis pathways are not explored experimentally: it would be interesting to know if the lysosomal pool arrives there via the secretory pathway (eg by engineering a glycosylation site into the lumenal domain) or by autophagy, where failed insertion products may accumulate in the cytoplasm and be degraded directly from cytoplasmic inclusions.

It would be helpful if the topology of constructs could be directly demonstrated by pulse-labelling and protease protection. It's possible that there are mixed pools of both topologies that might complicate interpretation.

Reviewer #2 (Public review):

In this manuscript, Mella et al. investigate the effect of GFP tagging on the localization and stability of the nuclear-localized tail-anchored (TA) protein Emerin. A previous study from this group showed that C-terminally GFP-tagged Emerin protein traffics to the plasma membrane and reaches lysosomes for degradation. It is suggested that the C-terminal tagging of tail-anchored proteins shifts their insertion from the post-translational TRC/GET pathway to the co-translational SRP-mediated pathway. The authors of this paper found that C-terminal GFP tagging causes Emerin to localize to the plasma membrane and eventually reach lysosomes. They investigated the mechanism by which Emerin-GFP moves to the secretory pathway. By manipulating the cytosolic domain and the hydrophobicity of the transmembrane domain (TMD), the authors identify that an ER retention sequence and strong TMD hydrophobicity contribute to Emerin trafficking to the secretory pathway. Overall, the data are solid, and the knowledge will be useful to the field. However, the authors do not fully answer the question of why C-terminally GFP-tagged Emerin moves to the secretory pathway. Importantly, the authors did not consider the possible roles of GFP in the ER lumen influencing Emerin trafficking to the secretory pathway.

eLife Assessment

This study shows that a peptide called galanin can decrease or increase seizure activity in experimental models of seizures depending on the model. The authors use zebrafish and several methods to address the effects of galanin. The study will be useful to researchers who use zebrafish as experimental animals and who are interested in how peptides like galanin regulate seizures. However, the strength of evidence was considered incomplete at the present time due to several limitations of the results.

Reviewer #1 (Public review):

Summary:

In this study, authors explored how galanin affects whole-brain activity in larval zebrafish using wide-field Ca2+ imaging, genetic modifications, and drugs that increase brain activity. The authors conclude that galanin has a sedative effect on the brain under normal conditions and during seizures, mainly through the galanin receptor 1a (galr1a). However, acute "stressors(?)" like pentylenetetrazole (PTZ) reduce galanin's effects, leading to increased brain activity and more seizures. Authors claim that galanin can reduce seizure severity while increasing seizure occurrence, speculated to occur through different receptor subtypes. This study confirms galanin's complex role in brain activity, supporting its potential impact on epilepsy.

Strengths:

The overall strength of the study lies primarily in its methodological approach using whole-brain Calcium imaging facilitated by the transparency of zebrafish larvae. Additionally, the use of transgenic zebrafish models is an advantage, as it enables genetic manipulations to investigate specific aspects of galanin signaling. This combination of advanced imaging and genetic tools allows for addressing galanin's role in regulating brain activity.

Weaknesses:

The weaknesses of the study also stem from the methodological approach, particularly the use of whole-brain Calcium imaging as a measure of brain activity. While epilepsy and seizures involve network interactions, they typically do not originate across the entire brain simultaneously. Seizures often begin in specific regions or even within specific populations of neurons within those regions. Therefore, a whole-brain approach, especially with Calcium imaging with inherited limitations, may not fully capture the localized nature of seizure initiation and propagation, potentially limiting the understanding of Galanin's role in epilepsy.

Furthermore, Galanin's effects may vary across different brain areas, likely influenced by the predominant receptor types expressed in those regions. Additionally, the use of PTZ as a "stressor" is questionable since PTZ induces seizures rather than conventional stress. Referring to seizures induced by PTZ as "stress" might be a misinterpretation intended to fit the proposed model of stress regulation by receptors other than Galanin receptor 1 (GalR1).

The description of the EAAT2 mutants is missing crucial details. EAAT2 plays a significant role in the uptake of glutamate from the synaptic cleft, thereby regulating excitatory neurotransmission and preventing excitotoxicity. Authors suggest that in EAAT2 knockout (KO) mice galanin expression is upregulated 15-fold compared to wild-type (WT) mice, which could be interpreted as galanin playing a role in the hypoactivity observed in these animals.

However, the study does not explore the misregulation of other genes that could be contributing to the observed phenotype. For instance, if AMPA receptors are significantly downregulated, or if there are alterations in other genes critical for brain activity, these changes could be more important than the upregulation of galanin. The lack of wider gene expression analysis leaves open the possibility that the observed hypoactivity could be due to factors other than, or in addition to, galanin upregulation.

Moreover, the observation that in double KO mice for both EAAT2 and galanin there was little difference in seizure susceptibility compared to EAAT2 KO mice alone further supports the idea that galanin upregulation might not be the reason to the observed phenotype. This indicates that other regulatory mechanisms or gene expressions might be playing a more pivotal role in the manifestation of hypoactivity in EAAT2 mutants.

These methodological shortcomings and conceptual inconsistencies undermine the perceived strengths of the study, and hinders understanding of Galanin's role in epilepsy and stress regulation.

Comments on revisions:

The revised manuscript and the answers of the authors is appreciated. However, the criticisms were addressed only partially and main weaknesses of the manuscript are still remaining.

Reviewer #2 (Public review):

This revised study is an investigation of galanin and galanin receptor signaling on whole-brain activity in the context of recurrent seizure activity or under homeostatic basal conditions. The authors primarily use calcium imaging to observe whole-brain neuronal activity accompanied by galanin qPCR to determine how manipulations of galanin or the galr1a receptor affect the activity of the whole-brain under non-ictal conditions or when seizure activity occurs. The authors use their eaat2a-/- model (introduced in their Glia 2022 paper, PMID 34716961) that shows recurrent seizure activity as well as suppression of neuronal activity and locomotion interictally. It is compared to the well-known pentylenetetrazole (PTZ) pharmacological model of seizures in zebrafish. Given the literature cited in their Introduction, the authors hypothesize that galanin will exert a net inhibitory effect on brain activity in models of seizures/epilepsy. They were surprised to find that this hypothesis was only moderately supported in their eaat2a-/- model. In contrast, after PTZ, fish with galanin overexpression showed increased seizure number and reduced duration while fish with galanin KO showed reduced seizure number and increased duration.

Previous concerns about sex or developmental biological variables were addressed, as their model's seizure phenotype emerges rapidly and long prior to the establishment of zebrafish sexual maturity. However, in the course of re-review, some additional concerns (below) were detected that, if addressed, could further improve the manuscript. These concerns relate to how seizures were defined from the measurement of fluorescent calcium imaging data. Overall, this study is important and convincing, and carries clear value for understanding the multifaceted functions that neuronal galanin can perform under homeostatic and disease conditions.

Additional Concerns:

- The authors have validated their ability to measure behavioral seizures quantitatively in their 2022 Glia paper but the information provided on defining behavioral seizures was limited. The definition of behavioral seizure activity is not expanded upon in this paper, but could provide detail about how the behavioral seizures relate to a seizure detected via calcium imaging.

- Related to the previous point, for the calcium imaging, the difference between an increase in fluorescence that the authors think reflects increased neuronal activity and the fluorescence that corresponds to seizures is not very clear. This detail is necessary because exactly when the term "seizure" describes a degree of increased activity can be difficult to distinguish objectively.

- The supplementary movies that were added were very useful, but raised some questions. For example, what brain regions were pulsating? What areas seemed to constantly exhibit strong fluorescence and was this an artifact? It seemed that sometimes there was background fluorescence in the body. Perhaps an anatomical diagram could be provided for the readers. In addition, there were some movies with much greater fluorescence changes - are these the seizures? These are some reasons for our request for clarified definitions of the term "seizure".

Reviewer #3 (Public review):

Summary:

The neuropeptide galanin is primarily expressed in the hypothalamus and has been shown to play critical roles in homeostatic functions such as arousal, sleep, stress, and brain disorders such as epilepsy. Previous work in rodents using galanin analogs and receptor-specific knockout have provided convincing evidence for anti-convulsant effects of galanin.

In the present study, the authors sought to determine the relationship between galanin expression and whole-brain activity. The authors took advantage of the transparent nature of larval zebrafish to perform whole-brain neural activity measurements via widefield calcium imaging. Two models of seizures were used (eaat2a-/- and pentylenetetrazol; PTZ). In the eaat2a-/- model, spontaneous seizures occur and the authors found that galanin transcript levels were significantly increased and associated with reduced frequency of calcium events. Similarly, two hours after PTZ galanin transcript levels roughly doubled and the frequency and amplitude of calcium events were reduced.

The authors also used a heat shock protein line (hsp70I:gal) where galanin transcripts levels are induced by activation of heat shock protein, but this line also shows higher basal transcript levels of galanin. Due to problems with whole-brain activity in wild-type larvae, the authors used the line without heat shock. They found higher level of galanin in hsp70I:gal larval zebrafish resulted in a reduction of calcium events and a reduction in amplitude of events. In contrast, galanin knockout (gal-/-) increased calcium activity, indicated by an increased number of calcium events, but a reduction in amplitude and duration. New data in the supplementary figure 2 used antibody staining to confirm the absence of galanin expression in gal-/- knockouts. Knockout of the galanin receptor subtype galr1a via crispants also increased the frequency of calcium events. New data in the revised manuscript reports that galr1aKO did not cause an upregulation of galanin, thereby ruling out genetic compensation effects.

In subsequent experiments in eaat2a-/- mutants were crossed with hsp70I:gal or gal-/- to increase or decrease galanin expression, respectively. These experiments showed modest effects, with eaat2a-/- x gal-/- knockouts showing an increased normalized area under the curve and seizure amplitude.

Lastly, the authors attempted to study the relationship between galanin and brain activity during a PTZ challenge. The hsp70I:gal larva showed increased number of seizures and reduced seizure duration during PTZ. In contrast, gal-/- mutants showed increased normalized area under the curve and a stark reduction in number of detected seizures, a reduction in seizure amplitude, but an increase in seizure duration. The authors then ruled out the role of Galr1a in modulating this effect during PTZ, since the number of seizures was unaffected, whereas the amplitude and duration of seizures was increased.

Strengths:

(1) The gain- and loss-of function galanin manipulations provided convincing evidence that galanin influences brain activity (via calcium imaging) during interictal and/or seizure-free periods. In particular, the relationship between galanin transcript levels and brain activity in figures 1 & 2 was convincing. New antibody staining confirms the absence of galanin in gal-/- mutants. New data also shows galanin transcript levels were unchanged in galr1ako brains.

(2) The authors use two models of epilepsy (eaat2a-/- and PTZ).

(3) Focus on the galanin receptor subtype galr1a provided good evidence for an important role of this receptor in controlling brain activity during interictal and/or seizure-free periods.

(4) The authors have added supplementary video files for calcium imaging to support their observations.

Weaknesses:

(1) Although the relationship between galanin and brain activity during interictal or seizure-free periods was clear, the revised manuscript still lacks mechanistic insight in the role of galanin during seizure-like activity induced by PTZ.

(2) The revised manuscript continues to heavily rely on calcium imaging of different mutant lines. Confirmation of knockouts has been provided with immunostaining in a new supplementary figure. Additional methods could strengthen the data, translational relevance, and interpretation (e.g., acute pharmacology using galanin agonists or antagonists, brain or cell recordings, biochemistry, etc).

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this study, the authors explored how galanin affects whole-brain activity in larval zebrafish using wide-field Ca2+ imaging, genetic modifications, and drugs that increase brain activity. The authors conclude that galanin has a sedative effect on the brain under normal conditions and during seizures, mainly through the galanin receptor 1a (galr1a). However, acute "stressors(?)" like pentylenetetrazole (PTZ) reduce galanin's effects, leading to increased brain activity and more seizures. The authors claim that galanin can reduce seizure severity while increasing seizure occurrence, speculated to occur through different receptor subtypes. This study confirms galanin's complex role in brain activity, supporting its potential impact on epilepsy.

Strengths:

The overall strength of the study lies primarily in its methodological approach using whole-brain Calcium imaging facilitated by the transparency of zebrafish larvae. Additionally, the use of transgenic zebrafish models is an advantage, as it enables genetic manipulations to investigate specific aspects of galanin signaling. This combination of advanced imaging and genetic tools allows for addressing galanin's role in regulating brain activity.

Weaknesses:

The weaknesses of the study also stem from the methodological approach, particularly the use of whole-brain Calcium imaging as a measure of brain activity. While epilepsy and seizures involve network interactions, they typically do not originate across the entire brain simultaneously. Seizures often begin in specific regions or even within specific populations of neurons within those regions. Therefore, a whole-brain approach, especially with Calcium imaging with inherited limitations, may not fully capture the localized nature of seizure initiation and propagation, potentially limiting the understanding of Galanin's role in epilepsy.

Furthermore, Galanin's effects may vary across different brain areas, likely influenced by the predominant receptor types expressed in those regions. Additionally, the use of PTZ as a "stressor" is questionable since PTZ induces seizures rather than conventional stress. Referring to seizures induced by PTZ as "stress" might be a misinterpretation intended to fit the proposed model of stress regulation by receptors other than Galanin receptor 1 (GalR1).

The description of the EAAT2 mutants is missing crucial details. EAAT2 plays a significant role in the uptake of glutamate from the synaptic cleft, thereby regulating excitatory neurotransmission and preventing excitotoxicity. Authors suggest that in EAAT2 knockout (KO) mice galanin expression is upregulated 15-fold compared to wild-type (WT) mice, which could be interpreted as galanin playing a role in the hypoactivity observed in these animals.

Indeed, our observation of the unexpected hypoactivity in EAAT2a mutants, described in our description of this mutant (Hotz et al., 2022), prompted us to initiate this study formulating the hypothesis that the observed upregulation of galanin is a neuroprotective response to epilepsy.

However, the study does not explore the misregulation of other genes that could be contributing to the observed phenotype. For instance, if AMPA receptors are significantly downregulated, or if there are alterations in other genes critical for brain activity, these changes could be more important than the upregulation of galanin. The lack of wider gene expression analysis leaves open the possibility that the observed hypoactivity could be due to factors other than, or in addition to, galanin upregulation.

We have performed a transcriptome analysis that we are still evaluation. We can already state that AMPA receptor genes are not significantly altered in the mutant.

Moreover, the observation that in double KO mice for both EAAT2 and galanin, there was little difference in seizure susceptibility compared to EAAT2 KO mice alone further supports the idea that galanin upregulation might not be the reason for the observed phenotype. This indicates that other regulatory mechanisms or gene expressions might be playing a more pivotal role in the manifestation of hypoactivity in EAAT2 mutants.

We agree that upregulation of galanin transcripts is at best one of a suite of regulatory mechanisms that lead to hypoactivity in EAAT2 zebrafish mutants.

These methodological shortcomings and conceptual inconsistencies undermine the perceived strengths of the study, and hinders understanding of Galanin's role in epilepsy and stress regulation.

Reviewer #2 (Public Review):

Summary:

This study is an investigation of galanin and galanin receptor signaling on whole-brain activity in the context of recurrent seizure activity or under homeostatic basal conditions. The authors primarily use calcium imaging to observe whole-brain neuronal activity accompanied by galanin qPCR to determine how manipulations of galanin or the galr1a receptor affect the activity of the whole-brain under non-ictal or seizure event conditions. The authors' Eaat2a-/- model (introduced in their Glia 2022 paper, PMID 34716961) that shows recurrent seizure activity alongside suppression of neuronal activity and locomotion in the time periods lacking seizures is used in this paper in comparison to the well-known pentylenetetrazole (PTZ) pharmacological model of epilepsy in zebrafish. Given the literature cited in their Introduction, the authors reasonably hypothesize that galanin will exert a net inhibitory effect on brain activity in models of epilepsy and at homeostatic baseline, but were surprised to find that this hypothesis was only moderately supported in their Eaat2a-/- model. In contrast, under PTZ challenge, fish with galanin overexpression showed increased seizure number and reduced duration while fish with galanin KO showed reduced seizure number and increased duration. These results would have been greatly enriched by the inclusion of behavioral analyses of seizure activity and locomotion (similar to the authors' 2022 Glia paper and/or PMIDs 15730879, 24002024). In addition, the authors have not accounted for sex as a biological variable, though they did note that sex sorting zebrafish larvae precludes sex selection at the younger ages used. It would be helpful to include smaller experiments taken from pilot experiments in older, sex-balanced groups of the relevant zebrafish to increase confidence in the findings' robustness across sexes. A possible major caveat is that all of the various genetic manipulations are non-conditional as performed, meaning that developmental impacts of galanin overexpression or galanin or galr1a knockout on the observed results have not been controlled for and may have had a confounding influence on the authors' findings. Overall, this study is important and solid (yet limited), and carries clear value for understanding the multifaceted functions that neuronal galanin can have under homeostatic and disease conditions.

Strengths:

- The authors convincingly show that galanin is upregulated across multiple contexts that feature seizure activity or hyperexcitability in zebrafish, and appears to reduce neuronal activity overall, with key identified exceptions (PTZ model).

- The authors use both genetic and pharmacological models to answer their question, and through this diverse approach, find serendipitous results that suggest novel underexplored functions of galanin and its receptors in basal and disease conditions. Their question is well-informed by the cited literature, though the authors should cite and consider their findings in the context of Mazarati et al., 1998 (PMID:982276). The authors' Discussion places their findings in context, allowing for multiple interpretations and suggesting some convincing explanations.

- Sample sizes are robust and the methods used are well-characterized, with a few exceptions (as the paper is currently written).

- Use of a glutamatergic signaling-based genetic model of epilepsy (Eaat2a-/-) is likely the most appropriate selection to test how galanin signaling can alter seizure activity, as galanin is known to reduce glutamatergic release as an inhibitory mechanism in rodent hippocampal neurons via GalR1a (alongside GIRK activation effects). Given that PTZ instead acts through GABAergic signaling pathways, it is reasonable and useful to note that their glutamate-based genetic model showed different effects than did their GABAergic-based model of seizure activity.

Weaknesses:

- The authors do not include behavioral assessments of seizure or locomotor activity that would be expected in this paper given their characterizations of their Eaat2a-/- model in the Glia 2022 paper that showed these behavioral data for this zebrafish model. These data would inform the reader of the behavioral phenotypes to expect under the various conditions and would likely further support the authors' findings if obtained and reported.<br />

We agree that a thorough behavioral assessment would have strengthened the study, but we deemed it outside of the scope of this study.

- No assessment of sex as a biological variable is included, though it is understood that these specific studied ages of the larvae may preclude sex sorting for experimental balancing as stated by the authors.

The study was done on larval zebrafish (5 days post fertilization). The first signs of sexual differentiation become apparent at about 17 days post fertilization (reviewed in Ye and Chen, 2020). Hence sex is no biological variable at the stage studied. 

- The reported results may have been influenced by the loss or overexpression of galanin or loss of galr1a during developmental stages. The authors did attempt to use the hsp70l system to overexpress galanin, but noted that the heat shock induction step led to reduced brain activity on its own (Supplementary Figure 1). Their hsp70l:gal model shows galanin overexpression anyways (8x fold) regardless of heat induction, so this model is still useful as a way to overexpress galanin, but it should be noted that this galanin overexpression is not restricted to post-developmental timepoints and is present during development.

The developmental perspective is an important point to consider. Due to the rapid development of the zebrafish it is not trivial to untangle this. In the zebrafish we first observe epileptic seizures as early as 3 days post fertilization (dpf), where the brain is clearly not well developed yet (e.g. behaviroal response to light are still minimal). Even the 5 dpf stage, where most of our experiments have been conducted, cannot by far not be considered post-development.  

Reviewer #3 (Public Review):

Summary:

The neuropeptide galanin is primarily expressed in the hypothalamus and has been shown to play critical roles in homeostatic functions such as arousal, sleep, stress, and brain disorders such as epilepsy. Previous work in rodents using galanin analogs and receptor-specific knockout has provided convincing evidence for the anti-convulsant effects of galanin.

In the present study, the authors sought to determine the relationship between galanin expression and whole-brain activity. The authors took advantage of the transparent nature of larval zebrafish to perform whole-brain neural activity measurements via widefield calcium imaging. Two models of seizures were used (eaat2a-/- and pentylenetetrazol; PTZ). In the eaat2a-/- model, spontaneous seizures occur and the authors found that galanin transcript levels were significantly increased and associated with a reduced frequency of calcium events. Similarly, two hours after PTZ galanin transcript levels roughly doubled and the frequency and amplitude of calcium events were reduced. The authors also used a heat shock protein line (hsp70I:gal) where galanin transcript levels are induced by activation of heat shock protein, but this line also shows higher basal transcript levels of galanin. Again, the higher level of galanin in hsp70I:gal larval zebrafish resulted in a reduction of calcium events and a reduction in the amplitude of events. In contrast, galanin knockout (gal-/-) increased calcium activity, indicated by an increased number of calcium events, but a reduction in amplitude and duration. Knockout of the galanin receptor subtype galr1a via crispants also increased the frequency of calcium events.

In subsequent experiments in eaat2a-/- mutants were crossed with hsp70I:gal or gal-/- to increase or decrease galanin expression, respectively. These experiments showed modest effects, with eaat2a-/- x gal-/- knockouts showing an increased normalized area under the curve and seizure amplitude.

Lastly, the authors attempted to study the relationship between galanin and brain activity during a PTZ challenge. The hsp70I:gal larva showed an increased number of seizures and reduced seizure duration during PTZ. In contrast, gal-/- mutants showed an increased normalized area under the curve and a stark reduction in the number of detected seizures, a reduction in seizure amplitude, but an increase in seizure duration. The authors then ruled out the role of Galr1a in modulating this effect during PTZ, since the number of seizures was unaffected, whereas the amplitude and duration of seizures were increased.

Strengths:

(1) The gain- and loss-of function galanin manipulations provided convincing evidence that galanin influences brain activity (via calcium imaging) during interictal and/or seizure-free periods. In particular, the relationship between galanin transcript levels and brain activity in Figures 1 & 2 was convincing.

(2) The authors use two models of epilepsy (eaat2a-/- and PTZ).

(3) Focus on the galanin receptor subtype galr1a provided good evidence for the important role of this receptor in controlling brain activity during interictal and/or seizure-free periods.

Weaknesses:

(1) Although the relationship between galanin and brain activity during interictal or seizure-free periods was clear, the manuscript currently lacks mechanistic insight in the role of galanin during seizure-like activity induced by PTZ.

We completely agree and concede that this study constitutes only a first attempt to understand the (at least for us) perplexing complexity of galanin function on the brain.

(2) Calcium imaging is the primary data for the paper, but there are no representative time-series images or movies of GCaMP signal in the various mutants used.

We have now added various movies in supplementary data.

(3) For Figure 3, the authors suggest that hsp70I:gal x eaat2a-/-mutants would further increase galanin transcript levels, which were hypothesized to further reduce brain activity. However, the authors failed to measure galanin transcript levels in this cross to show that galanin is actually increased more than the eaat2a-/- mutant or the hsp70I:gal mutant alone.

After a couple of unsuccessful mating attempts with our older mutants, we finally decided not to wait for a new generation to grow up, deeming the experiment not crucial (but still nice to have).

(4) Similarly, transcript levels of galanin are not provided in Figure 2 for Gal-/- mutants and galr1a KOs. Transcript levels would help validate the knockout and any potential compensatory effects of subtype-specific knockout.

To validate the gal-/- mutant line, we decided to show loss of protein expression (Suppl. Figure 2), which we deem to more relevant to argue for loss of function. Galanin transcript levels in galr1a KOs were also added into the same Figure. However, validation of the galr1a KO could not be performed due to transcript levels being close to the detection limit and lack of available antibodies.

(5) The authors very heavily rely on calcium imaging of different mutant lines. Additional methods could strengthen the data, translational relevance, and interpretation (e.g., acute pharmacology using galanin agonists or antagonists, brain or cell recordings, biochemistry, etc).

Again, we agree and concede that a number of additional approaches are needed to get more insight into the complex role of galanin in regulation overall brain activity. These include, among others, also behavioral, multiple single cell recordings and pharmacological interventions.

Recommendations for the authors:

Reviewer #2 (Recommendations For The Authors):

Minor issues:

(1) "Sedative" effect of galanin is somewhat vague and seems overapplied without the inclusion of behavioral data showing sedation effects. I would replace "sedative" with something clearer, like the phrase "net inhibitory effect" or similar.

We have modified the wording as deemed appropriate.

(2) Include new data that is sufficiently powered to detect or rule out the effects of sex as a biological variable within the various experiments.

At this stage sex is not a biological variable. Sex determination starts a late larval stage around 14dpf. Our analysis is based on 5pdf larvae.

(3) Attempt to perform some experiments with galanin/galr1a manipulations that have been induced after the majority of development without using heat shock induction if possible (unknown how feasible this is in current model systems).

In the current model this is not feasible, but an excellent suggestion for future studies that would then also address more longterm effects in the model.

(4) Figure 2 should include qPCR results for galanin or galr1a mRNA expression to match Figure 1C, F, and Figure 2C and to confirm reductions in the respective RNA transcript levels of gal or galr1a. It could be useful to perform qPCR for galanin in all galr1aKO mice to ascertain whether compensatory elevations in galanin occur in response to galr1aKO.

(5) Axes should be made with bolder lines and bolder/larger fonts for readability and consistency throughout.

Indeed, an excellent suggestion. We have adjusted the axes significantly improving the readability of the graphs.

(6) The bottom o,f the image for Figure 2 appears to have been cut off by mistake (page 5).

(7) The ending of the legend text for Figure 3 appears to have been cut off by mistake (page 6).

Both regrettable mistakes have been corrected (already in the initial posted version)

Reviewer #3 (Recommendations For The Authors):

(1) The introduction or first paragraph of the results should be revised to more directly state the hypotheses. Several critical details were only clear after reading the discussion.

We added some words to the introduction, hoping that the critical points are now more apparent to the reader.

(2) Galanin is known to be rapidly depleted by seizures (Mazarati et al., 1998; Journal of Neuroscience, PMID #9822761) but this paper did not appear to be cited or considered. Could the rapid depletion of galanin during seizures help explain the confusing effects of galanin manipulations during PTZ?

We have added a sentence and the reference to the discussion.

(3) Figure 1 panels are incorrect. For example, Panel 'F' is used twice and the figure legend is also incorrect due to the labeling errors. In-text references to the figure should also be updated accordingly.

(4) In Figure 2 N-P, the delta F/F threshold wording is partially cropped. The figure should be updated.

Thank you for pointing out this mistake. Both figures have now been updated (already in the initial posted version)

(5) The naming and labeling of groups in the manuscript and figures should be updated to more accurately reflect the fish used for each experiment. As it currently stands, I found the labeling confusing and sometimes misleading. For example, Figure 3 'controls' are actually eaat2a-/- mutants, whereas the other group is hsp70I:gal x eaat2a-/- crosses or gal-/- x eaat2a-/- crosses. In other Figures, 'controls' are eaat2a+/+larva, or wild-type siblings (sometimes unclear).

We have made appropriate changes to the manuscript to make this point clearer to the reader, especially when the controls are eaat2a mutants.

(6) Figure 4J and 4K only show 5 data points, when the authors clearly indicate that 6 fish had seizures. Continuation of this data in Figure 4L shows 6 data points.

Indeed the 6 data points in Figure 4J and K are hard to see due to their nearly complete overlap. On larger magnification all six data points become distinguishable. We will try some different plotting approaches for the revision.

eLife Assessment

This potentially important model-based study seeks to mimic bat echolocation behavior and flight under high-density conditions. The simulations convincingly suggest that the problem of acoustic jamming in these situations may be less severe than previously thought, a finding that would be of broad interest to scientists working in the fields of bat biology and collective behaviour. However, some aspects of the manuscript were found to lack clarity and concerns were raised about some of the assumptions underlying the parameters used for the simulations, which impact both the modeling results and the conclusions that can be made from the data.

Reviewer #1 (Public review):

Summary:

Mazer & Yovel 2025 dissect the inverse problem of how echolocators in groups manage to navigate their surroundings despite intense jamming using computational simulations.

The authors show that despite the 'noisy' sensory environments that echolocating groups present, agents can still access some amount of echo-related information and use it to navigate their local environment. It is known that echolocating bats have strong small and large-scale spatial memory that plays an important role for individuals. The results from this paper also point to the potential importance of an even lower-level, short-term role of memory in the form of echo 'integration' across multiple calls, despite the unpredictability of echo detection in groups. The paper generates a useful basis to think about the mechanisms in echolocating groups for experimental investigations too.

Strengths:

(1) The paper builds on biologically well-motivated and parametrised 2D acoustics and sensory simulation setup to investigate the various key parameters of interest

(2) The 'null-model' of echolocators not being able to tell apart objects & conspecifics while echolocating still shows agents successfully emerge from groups - even though the probability of emergence drops severely in comparison to cognitively more 'capable' agents. This is nonetheless an important result showing the direction-of-arrival of a sound itself is the 'minimum' set of ingredients needed for echolocators navigating their environment.

(3) The results generate an important basis in unraveling how agents may navigate in sensorially noisy environments with a lot of irrelevant and very few relevant cues.

(4) The 2D simulation framework is simple and computationally tractable enough to perform multiple runs to investigate many variables - while also remaining true to the aim of the investigation.

Weaknesses:

There are a few places in the paper that can be misunderstood or don't provide complete details. Here is a selection:

(1) Line 61: '... studies have focused on movement algorithms while overlooking the sensory challenges involved' : This statement does not match the recent state of the literature. While the previous models may have had the assumption that all neighbours can be detected, there are models that specifically study the role of limited interaction arising from a potential inability to track all neighbours due to occlusion, and the effect of responding to only one/few neighbours at a time e.g. Bode et al. 2011 R. Soc. Interface, Rosenthal et al. 2015 PNAS, Jhawar et al. 2020 Nature Physics.

(2) The word 'interference' is used loosely places (Line 89: '...took all interference signals...', Line 319: 'spatial interference') - this is confusing as it is not clear whether the authors refer to interference in the physics/acoustics sense, or broadly speaking as a synonym for reflections and/or jamming.

(3) The paper discusses original results without reference to how they were obtained or what was done. The lack of detail here must be considered while interpreting the Discussion e.g. Line 302 ('our model suggests...increasing the call-rate..' - no clear mention of how/where call-rate was varied) & Line 323 '..no benefit beyond a certain level..' - also no clear mention of how/where call-level was manipulated in the simulations.

Reviewer #2 (Public review):

This manuscript describes a detailed model of bats flying together through a fixed geometry. The model considers elements that are faithful to both bat biosonar production and reception and the acoustics governing how sound moves in the air and interacts with obstacles. The model also incorporates behavioral patterns observed in bats, like one-dimensional feature following and temporal integration of cognitive maps. From a simulation study of the model and comparison of the results with the literature, the authors gain insight into how often bats may experience destructive interference of their acoustic signals and those of their peers, and how much such interference may actually negatively affect the groups' ability to navigate effectively. The authors use generalized linear models to test the significance of the effects they observe.

In terms of its strengths, the work relies on a thoughtful and detailed model that faithfully incorporates salient features, such as acoustic elements like the filter for a biological receiver and temporal aggregation as a kind of memory in the system. At the same time, the authors' abstract features are complicating without being expected to give additional insights, as can be seen in the choice of a two-dimensional rather than three-dimensional system. I thought that the level of abstraction in the model was perfect, enough to demonstrate their results without needless details. The results are compelling and interesting, and the authors do a great job discussing them in the context of the biological literature.

The most notable weakness I found in this work was that some aspects of the model were not entirely clear to me. For example, the directionality of the bat's sonar call in relation to its velocity. Are these the same? If so, what is the difference between phi_target and phi_tx in the model equations? What is a bat's response to colliding with a conspecific (rather than a wall)? From the statistical side, it was not clear if replicate simulations were performed. If they were, which I believe is the right way due to stochasticity in the model, how many replicates were used, and are the standard errors referred to throughout the paper between individuals in the same simulation or between independent simulations, or both?

Overall, I found these weaknesses to be superficial and easily remedied by the authors. The authors presented well-reasoned arguments that were supported by their results, and which were used to demonstrate how call interference impacts the collective's roost exit as measured by several variables. As the authors highlight, I think this work is valuable to individuals interested in bat biology and behavior, as well as to applications in engineered multi-agent systems like robotic swarms.

Reviewer #3 (Public review):

Summary:

The authors describe a model to mimic bat echolocation behavior and flight under high-density conditions and conclude that the problem of acoustic jamming is less severe than previously thought, conflating the success of their simulations (as described in the manuscript) with hard evidence for what real bats are actually doing. The authors base their model on two species of bats that fly at "high densities" (defined by the authors as colony sizes from tens to tens of thousands of individuals and densities of up to 33.3 bats/m2), Pipistrellus kuhli and Rhinopoma microphyllum. This work fits into the broader discussion of bat sensorimotor strategies during collective flight, and simulations are important to try to understand bat behavior, especially given a lack of empirical data. However, I have major concerns about the assumptions of the parameters used for the simulation, which significantly impact both the results of the simulation and the conclusions that can be made from the data. These details are elaborated upon below, along with key recommendations the authors should consider to guide the refinement of the model.

Strengths:

This paper carries out a simulation of bat behavior in dense swarms as a way to explain how jamming does not pose a problem in dense groups. Simulations are important when we lack empirical data. The simulation aims to model two different species with different echolocation signals, which is very important when trying to model echolocation behavior. The analyses are fairly systematic in testing all ranges of parameters used and discussing the differential results.

Weaknesses:

The justification for how the different foraging phase call types were chosen for different object detection distances in the simulation is unclear. Do these distances match those recorded from empirical studies, and if so, are they identical for both species used in the simulation? What reasoning do the authors have for a bat using the same call characteristics to detect a cave wall as they would for detecting a small insect? Additionally, details on the signal creation are also absent, but based on the sample spectrogram in Figure 2A, it appears that the authors used a synthetic linear FM chirp characterized by the call parameters. This simplification of the echolocation signals for these species is not representative of the true emitted signals, which are nonlinear FM for not only the species used within this simulation--PK (Schnitzler et al., 1987; Kalko and Schnitzler 1993 and RM (Schmidt and Joermann 1986)-but also for many other bat species that form large aggregations and undergo dense emergence. Furthermore, echolocation calls of bats emitted during dense emergence flights (see Gillam et al 2010) can be very much different from those emitted during foraging calls, so limiting the simulation to foraging calls may not be valid. Why did the authors not use actual waveforms of calls produced by these species during dense emergence to use biologically relevant signals in their simulation?

The two species modeled have different calls. In particular, the bandwidth varies by a factor of 10, meaning the species' sonars will have different spatial resolutions. Range resolution is about 10x better for PK compared to RM, but the authors appear to use the same thresholds for "correct detection" for both, which doesn't seem appropriate. Also, the authors did not mention incorporating/correcting for/exploiting Doppler, which leads me to assume they did not model it.

The success of the simulation may very well be due to variation in the calls of the bats, which ironically enough demonstrates the importance of a jamming avoidance response in dense flight. This explains why the performance of the simulation falls when bats are not able to distinguish their own echoes from other signals. For example, in Figure C2, there are calls that are labeled as conspecific calls and have markedly shorter durations and wider bandwidths than others. These three phases for call types used by the authors may be responsible for some (or most) of the performance of the model since the correlation between different call types is unlikely to exceed the detection threshold. But it turns out this variation in and of itself is what a jamming avoidance response may consist of. So, in essence, the authors are incorporating a jamming avoidance response into their simulation.

The authors claim that integration over multiple pings (though I was not able to determine the specifics of this integration algorithm) reduces the masking problem. Indeed, it should: if you have two chances at detection, you've effectively increased your SNR by 3dB.

They also claim - although it is almost an afterthought - that integration dramatically reduces the degradation caused by false echoes. This also makes sense: from one ping to the next, the bat's own echo delays will correlate extremely well with the bat's flight path. Echo delays due to conspecifics will jump around kind of randomly. However, the main concern is regarding the time interval and number of pings of the integration, especially in the context of the bat's flight speed. The authors say that a 1s integration interval (5-10 pings) dramatically reduces jamming probability and echo confusion. This number of pings isn't very high, and it occurs over a time interval during which the bat has moved 5-10m. This distance is large compared to the 0.4m distance-to-obstacle that triggers an evasive maneuver from the bat, so integration should produce a latency in navigation that significantly hinders the ability to avoid obstacles. Can the authors provide statistics that describe this latency, and discussion about why it doesn't seem to be a problem?

The authors are using a 2D simulation, but this very much simplifies the challenge of a 3D navigation task, and there is an explanation as to why this is appropriate. Bat densities and bat behavior are discussed per unit area when realistically it should be per unit volume. In fact, the authors reference studies to justify the densities used in the simulation, but these studies were done in a 3D world. If the authors have justification for why it is realistic to model a 3D world in a 2D simulation, I encourage them to provide references justifying this approach.

The focus on "masking" (which appears to be just in-band noise), especially relative to the problem of misassigned echoes, is concerning. If the bat calls are all the same waveform (downsweep linear FM of some duration, I assume - it's not clear from the text), false echoes would be a major problem. Masking, as the authors define it, just reduces SNR. This reduction is something like sqrt(N), where N is the number of conspecifics whose echoes are audible to the bat, so this allows the detection threshold to be set lower, increasing the probability that a bat's echo will exceed a detection threshold. False echoes present a very different problem. They do not reduce SNR per se, but rather they cause spurious threshold excursions (N of them!) that the bat cannot help but interpret as obstacle detection. I would argue that in dense groups the mis-assignment problem is much more important than the SNR problem.

The criteria set for flight behavior (lines 393-406) are not justified with any empirical evidence of the flight behavior of wild bats in collective flight. How did the authors determine the avoidance distances? Also, what is the justification for the time limit of 15 seconds to emerge from the opening? Instead of an exit probability, why not instead use a time criterion, similar to "How long does it take X% of bats to exit?" What is the empirical justification for the 1-10 calls used for integration? The "average exit time for 40 bats" is also confusing and not well explained. Was this determined empirically? From the simulation? If the latter, what are the conditions? Does it include masking, no masking, or which species?

Author response:

Public Reviews:

Reviewer #1 (Public review):

We thank the reviewer for his valuable input and careful assessment, which have significantly improved the clarity and rigor of our manuscript.

Summary:

Mazer & Yovel 2025 dissect the inverse problem of how echolocators in groups manage to navigate their surroundings despite intense jamming using computational simulations.

The authors show that despite the 'noisy' sensory environments that echolocating groups present, agents can still access some amount of echo-related information and use it to navigate their local environment. It is known that echolocating bats have strong small and large-scale spatial memory that plays an important role for individuals. The results from this paper also point to the potential importance of an even lower-level, short-term role of memory in the form of echo 'integration' across multiple calls, despite the unpredictability of echo detection in groups. The paper generates a useful basis to think about the mechanisms in echolocating groups for experimental investigations too.

Strengths:

(1) The paper builds on biologically well-motivated and parametrised 2D acoustics and sensory simulation setup to investigate the various key parameters of interest

(2) The 'null-model' of echolocators not being able to tell apart objects & conspecifics while echolocating still shows agents successfully emerge from groups - even though the probability of emergence drops severely in comparison to cognitively more 'capable' agents. This is nonetheless an important result showing the direction-of-arrival of a sound itself is the 'minimum' set of ingredients needed for echolocators navigating their environment.

(3) The results generate an important basis in unraveling how agents may navigate in sensorially noisy environments with a lot of irrelevant and very few relevant cues.

(4) The 2D simulation framework is simple and computationally tractable enough to perform multiple runs to investigate many variables - while also remaining true to the aim of the investigation.

Weaknesses:

There are a few places in the paper that can be misunderstood or don't provide complete details. Here is a selection:

(1) Line 61: '... studies have focused on movement algorithms while overlooking the sensory challenges involved' : This statement does not match the recent state of the literature. While the previous models may have had the assumption that all neighbours can be detected, there are models that specifically study the role of limited interaction arising from a potential inability to track all neighbours due to occlusion, and the effect of responding to only one/few neighbours at a time e.g. Bode et al. 2011 R. Soc. Interface, Rosenthal et al. 2015 PNAS, Jhawar et al. 2020 Nature Physics.

We appreciate the reviewer's comment and the relevant references. We have revised the manuscript accordingly to clarify the distinction between studies that incorporate limited interactions and those that explicitly analyze sensory constraints and interference. We have refined our statement to acknowledge these contributions while maintaining our focus on sensory challenges beyond limited neighbor detection, such as signal degradation, occlusion effects, and multimodal sensory integration (see lines 61-64):

While collective movement has been extensively studied in various species, including insect swarming, fish schooling, and bird murmuration (Pitcher, Partridge and Wardle, 1976; Partridge, 1982; Strandburg-Peshkin et al., 2013; Pearce et al., 2014; Rosenthal, Twomey, Hartnett, Wu, Couzin, et al., 2015; Bastien and Romanczuk, 2020; Davidson et al., 2021; Aidan, Bleichman and Ayali, 2024), as well as in swarm robotics agents performing tasks such as coordinated navigation and maze-solving (Faria Dias et al., 2021; Youssefi and Rouhani, 2021; Cheraghi, Shahzad and Graffi, 2022), most studies have focused on movement algorithms , often assuming full detection of neighbors (Parrish and Edelstein-Keshet, 1999; Couzin et al., 2002, 2005; Sumpter et al., 2008; Nagy et al., 2010; Bialek et al., 2012; Gautrais et al., 2012; Attanasi et al., 2014). Some models have incorporated limited interaction rules where individuals respond to one or a few neighbors due to sensory constraints (Bode, Franks and Wood, 2011; Jhawar et al., 2020). However, fewer studies explicitly examine how sensory interference, occlusion, and noise shape decision-making in collective systems (Rosenthal et al., 2015).

(2) The word 'interference' is used loosely places (Line 89: '...took all interference signals...', Line 319: 'spatial interference') - this is confusing as it is not clear whether the authors refer to interference in the physics/acoustics sense, or broadly speaking as a synonym for reflections and/or jamming.

To improve clarity, we have revised the manuscript to distinguish between different types of interference:

· Acoustic interference (jamming): Overlapping calls that completely obscure echo detection, preventing bats from perceiving necessary environmental cues.

· Acoustic interference (masking): Partial reduction in signal clarity due to competing calls.

· Spatial interference: Physical obstruction by conspecifics affecting movement and navigation.

We have updated the manuscript to use these terms consistently and explicitly define them in relevant sections (see lines 87-94 and 329-330). This distinction ensures that the reader can differentiate between interference as an acoustic phenomenon and its broader implications in navigation.

(3) The paper discusses original results without reference to how they were obtained or what was done. The lack of detail here must be considered while interpreting the Discussion e.g. Line 302 ('our model suggests...increasing the call-rate..' - no clear mention of how/where call-rate was varied) & Line 323 '..no benefit beyond a certain level..' - also no clear mention of how/where call-level was manipulated in the simulations.

All tested parameters, including call rate dynamics and call intensity variations, are detailed in the Methods section and Tables 1 and 2. Specifically:

· Call Rate Variation: The Inter-Pulse Interval (IPI) was modeled based on documented echolocation behavior, decreasing from 100 msec during the search phase to 35 msec (~28 calls per second) at the end of the approach phase, and to 5 msec (200 calls per second) during the final buzz (see Table 2). This natural variation in call rate was not manually manipulated in the model but emerged from the simulated bat behavior.

· Call Intensity Variation: The tested call intensity levels (100, 110, 120, 130 dB SPL) are presented in Table 1 under the “Call Level” parameter. The effect of increasing call intensity was analyzed in relation to exit probability, jamming probability, and collision rate. This is now explicitly referenced in the Discussion.

We have revised the manuscript to explicitly reference these aspects in the Results and Discussion sections.

Reviewer #2 (Public review):

We are grateful for the reviewer’s insightful feedback, which has helped us clarify key aspects of our research and strengthen our conclusions.

This manuscript describes a detailed model of bats flying together through a fixed geometry. The model considers elements that are faithful to both bat biosonar production and reception and the acoustics governing how sound moves in the air and interacts with obstacles. The model also incorporates behavioral patterns observed in bats, like one-dimensional feature following and temporal integration of cognitive maps. From a simulation study of the model and comparison of the results with the literature, the authors gain insight into how often bats may experience destructive interference of their acoustic signals and those of their peers, and how much such interference may actually negatively affect the groups' ability to navigate effectively. The authors use generalized linear models to test the significance of the effects they observe.

In terms of its strengths, the work relies on a thoughtful and detailed model that faithfully incorporates salient features, such as acoustic elements like the filter for a biological receiver and temporal aggregation as a kind of memory in the system. At the same time, the authors' abstract features are complicating without being expected to give additional insights, as can be seen in the choice of a two-dimensional rather than three-dimensional system. I thought that the level of abstraction in the model was perfect, enough to demonstrate their results without needless details. The results are compelling and interesting, and the authors do a great job discussing them in the context of the biological literature.

The most notable weakness I found in this work was that some aspects of the model were not entirely clear to me.

For example, the directionality of the bat's sonar call in relation to its velocity. Are these the same?

For simplicity, in our model, the head is aligned with the body, therefore the direction of the echolocation beam is the same as the direction of the flight.

Moreover, call directionality (directivity) is not directly influenced by velocity. Instead, directionality is estimated using the piston model, as described in the Methods section. The directionality is based on the emission frequency and is thus primarily linked to the behavioral phases of the bat, with frequency shifts occurring as the bat transitions from search to approach to buzz phases. During the approach phase, the bat emits calls with higher frequencies, resulting in increased directionality. This is supported by the literature (Jakobsen and Surlykke, 2010; Jakobsen, Brinkløv and Surlykke, 2013). This phase is also associated with a natural reduction in flight speed, which is a well-documented behavioral adaptation in echolocating bats (Jakobsen et al., 2024).

To clarify this in the manuscript, we have updated the text to explicitly state that directionality follows phase-dependent frequency changes rather than being a direct function of velocity, see lines 460-465.

If so, what is the difference between phi_target and phi_tx in the model equations?

represents the angle between the bat and the reflected object (target).

the angle [rad], between the masking bat and target (from the transmitter’s perspective)

refers to the angle between the transmitting conspecific and the receiving focal bat, from the transmitter’s point of view.

represents the angle between the receiving bat and the transmitting bat, from the receiver’s point of view.

These definitions have been explicitly stated in the revised manuscript to prevent any ambiguity (lines 467-468). Additionally, a Supplementary figure demonstrating the geometrical relations has been added to the manuscript.

Author response image 1.

What is a bat's response to colliding with a conspecific (rather than a wall)?

In nature, minor collisions between bats are common and typically do not result in significant disruptions to flight (Boerma et al., 2019; Roy et al., 2019; Goldstein et al., 2024).Given this, our model does not explicitly simulate the physical impact of a collision event. Instead, during the collision event the bat keeps decreasing its velocity and changing its flight direction until the distance between bats is above the threshold (0.4 m). We assume that the primary cost of such interactions arises from the effort required to avoid collisions, rather than from the collision itself. This assumption aligns with observations of bat behavior in dense flight environments, where individuals prioritize collision avoidance rather than modeling post-collision dynamics.

From the statistical side, it was not clear if replicate simulations were performed. If they were, which I believe is the right way due to stochasticity in the model, how many replicates were used, and are the standard errors referred to throughout the paper between individuals in the same simulation or between independent simulations, or both?

The number of repetitions for each scenario is detailed in Table 1, but we included it in a more prominent location in the text for clarity. Specifically, we now state (Lines 274-275):

"The number of repetitions for each scenario was as follows: 1 bat: 240; 2 bats: 120; 5 bats: 48; 10 bats: 24; 20 bats: 12; 40 bats: 12; 100 bats: 6."

Regarding the reported standard errors, they are calculated across all individuals within each scenario, without distinguishing between different simulation trials.

We clarified in the revised text (Lines 534-535 in Statistical Analysis)

Overall, I found these weaknesses to be superficial and easily remedied by the authors. The authors presented well-reasoned arguments that were supported by their results, and which were used to demonstrate how call interference impacts the collective's roost exit as measured by several variables. As the authors highlight, I think this work is valuable to individuals interested in bat biology and behavior, as well as to applications in engineered multi-agent systems like robotic swarms.

Reviewer #3 (Public review):

We sincerely appreciate the reviewer’s thoughtful comments and the time invested in evaluating our work, which have greatly contributed to refining our study.

We would like to note that in general, our model often simplifies some of the bats’ abilities, under the assumption that if the simulated bats manage to perform this difficult task with simpler mechanisms, real better adapted bats will probably perform even better. This thought strategy will be repeated in several of the answers below.

Summary:

The authors describe a model to mimic bat echolocation behavior and flight under high-density conditions and conclude that the problem of acoustic jamming is less severe than previously thought, conflating the success of their simulations (as described in the manuscript) with hard evidence for what real bats are actually doing. The authors base their model on two species of bats that fly at "high densities" (defined by the authors as colony sizes from tens to tens of thousands of individuals and densities of up to 33.3 bats/m2), Pipistrellus kuhli and Rhinopoma microphyllum. This work fits into the broader discussion of bat sensorimotor strategies during collective flight, and simulations are important to try to understand bat behavior, especially given a lack of empirical data. However, I have major concerns about the assumptions of the parameters used for the simulation, which significantly impact both the results of the simulation and the conclusions that can be made from the data. These details are elaborated upon below, along with key recommendations the authors should consider to guide the refinement of the model.

Strengths:

This paper carries out a simulation of bat behavior in dense swarms as a way to explain how jamming does not pose a problem in dense groups. Simulations are important when we lack empirical data. The simulation aims to model two different species with different echolocation signals, which is very important when trying to model echolocation behavior. The analyses are fairly systematic in testing all ranges of parameters used and discussing the differential results.

Weaknesses:

The justification for how the different foraging phase call types were chosen for different object detection distances in the simulation is unclear. Do these distances match those recorded from empirical studies, and if so, are they identical for both species used in the simulation?

The distances at which bats transition between echolocation phases are identical for both species in our model (see Table 2). These distances are based on well-documented empirical studies of bat hunting and obstacle avoidance behavior (Griffin, Webster and Michael, 1958; Simmons and Kick, 1983; Schnitzler et al., 1987; Kalko, 1995; Hiryu et al., 2008; Vanderelst and Peremans, 2018). These references provide extensive evidence that insectivorous bats systematically adjust their echolocation calls in response to object proximity, following the characteristic phases of search, approach, and buzz.

To improve clarity, we have updated the text to explicitly state that the phase transition distances are empirically grounded and apply equally to both modeled species (lines 430-447).

What reasoning do the authors have for a bat using the same call characteristics to detect a cave wall as they would for detecting a small insect?

In echolocating bats, call parameters are primarily shaped by the target distance and echo strength. Accordingly, there is little difference in call structure between prey capture and obstacles-related maneuvers, aside from intensity adjustments based on target strength (Hagino et al., 2007; Hiryu et al., 2008; Surlykke, Ghose and Moss, 2009; Kothari et al., 2014). In our study, due to the dense cave environment, the bats are found to operate in the approach phase nearly all the time, which is consistent with natural cave emergence, where they are navigating through a cluttered environment rather than engaging in open-space search. For one of the species (Rhinopoma M.), we also have empirical recordings of individuals flying under similar conditions (Goldstein et al., 2024). Our model was designed to remain as simple as possible while relying on conservative assumptions that may underestimate bat performance. If, in reality, bats fine-tune their echolocation calls even earlier or more precisely during navigation than assumed, our model would still conservatively reflect their actual capabilities.

We actually used logarithmically frequency modulated (FM) chirps, generated using the MATLAB built-in function chirp(t, f0, t1, f1, 'logarithmic'). This method aligns with the nonlinear FM characteristics of Pipistrellus kuhlii (PK) and Rhinopoma microphyllum (RM) and provides a realistic approximation of their echolocation signals. We acknowledge that this was not sufficiently emphasized in the original text, and we have now explicitly highlighted this in the revised version to ensure clarity (sell Lines 447-449 in Methods).

The two species modeled have different calls. In particular, the bandwidth varies by a factor of 10, meaning the species' sonars will have different spatial resolutions. Range resolution is about 10x better for PK compared to RM, but the authors appear to use the same thresholds for "correct detection" for both, which doesn't seem appropriate.

The detection process in our model is based on Saillant’s method using a filter bank, as detailed in the paper (Saillant et al., 1993; Neretti et al., 2003; Sanderson et al., 2003). This approach inherently incorporates the advantages of a wider bandwidth, meaning that the differences in range resolution between the species are already accounted for within the signal-processing framework. Thus, there is no need to explicitly adjust the model parameters for bandwidth variations, as these effects emerge from the applied method.

Also, the authors did not mention incorporating/correcting for/exploiting Doppler, which leads me to assume they did not model it.

The reviewer is correct. To maintain model simplicity, we did not incorporate the Doppler effect or its impact on echolocation. The exclusion of Doppler effects was based on the assumption that while Doppler shifts can influence frequency perception, their impact on jamming and overall navigation performance is minor within the modelled context.

The maximal Doppler shifts expected for the bats in this scenario are of ~ 1kHz. These shifts would be applied variably across signals due to the semi-random relative velocities between bats, leading to a mixed effect on frequency changes. This variability would likely result in an overall reduction in jamming rather than exacerbating it, aligning with our previous statement that our model may overestimate the severity of acoustic interference. Such Doppler shifts would result in errors of 2-4 cm in localization (i.e., 200-400 micro-seconds) (Boonman, Parsons and Jones, 2003). 

We have now explicitly highlighted this in the revised version (see Lines 468-470).

The success of the simulation may very well be due to variation in the calls of the bats, which ironically enough demonstrates the importance of a jamming avoidance response in dense flight. This explains why the performance of the simulation falls when bats are not able to distinguish their own echoes from other signals. For example, in Figure C2, there are calls that are labeled as conspecific calls and have markedly shorter durations and wider bandwidths than others. These three phases for call types used by the authors may be responsible for some (or most) of the performance of the model since the correlation between different call types is unlikely to exceed the detection threshold. But it turns out this variation in and of itself is what a jamming avoidance response may consist of. So, in essence, the authors are incorporating a jamming avoidance response into their simulation.

We fully agree that the natural variations in call design between the phases contribute significantly to interference reduction (see our discussion in a previous paper in Mazar & Yovel, 2020). However, we emphasize that this cannot be classified as a Jamming Avoidance Response (JAR). In our model, bats respond only to the physical presence of objects and not to the acoustic environment or interference itself. There is no active or adaptive adjustment of call design to minimize jamming beyond the natural phase-dependent variations in call structure. Therefore, while variation in call types does inherently reduce interference, this effect emerges passively from the modeled behavior rather than as an intentional strategy to avoid jamming.

The authors claim that integration over multiple pings (though I was not able to determine the specifics of this integration algorithm) reduces the masking problem. Indeed, it should: if you have two chances at detection, you've effectively increased your SNR by 3dB.

The reviewer is correct. Indeed, integration over multiple calls improves signal-to-noise ratio (SNR), effectively increasing it by approximately 3 dB per doubling of observations. The specifics of the integration algorithm are detailed in the Methods section, where we describe how sensory information is aggregated across multiple time steps to enhance detection reliability.

They also claim - although it is almost an afterthought - that integration dramatically reduces the degradation caused by false echoes. This also makes sense: from one ping to the next, the bat's own echo delays will correlate extremely well with the bat's flight path. Echo delays due to conspecifics will jump around kind of randomly. However, the main concern is regarding the time interval and number of pings of the integration, especially in the context of the bat's flight speed. The authors say that a 1s integration interval (5-10 pings) dramatically reduces jamming probability and echo confusion. This number of pings isn't very high, and it occurs over a time interval during which the bat has moved 5-10m. This distance is large compared to the 0.4m distance-to-obstacle that triggers an evasive maneuver from the bat, so integration should produce a latency in navigation that significantly hinders the ability to avoid obstacles. Can the authors provide statistics that describe this latency, and discussion about why it doesn't seem to be a problem?

As described in the Methods section, the bat’s collision avoidance response does not solely rely on the integration process. Instead, the model incorporates real-time echoes from the last calls, which are used independently of the integration process for immediate obstacle avoidance maneuvers. This ensures that bats can react to nearby obstacles without being hindered by the integration latency. The slower integration on the other hand is used for clustering, outlier removal and estimation wall directions to support the pathfinding process, as illustrated in Supplementary Figure 1.

Additionally, our model assumes that bats store the physical positions of echoes in an allocentric coordinate system (x-y). The integration occurs after transforming these detections from a local relative reference frame to a global spatial representation. This allows for stable environmental mapping while maintaining responsiveness to immediate changes in the bat’s surroundings.

See lines 518-523 in the revied version.

The authors are using a 2D simulation, but this very much simplifies the challenge of a 3D navigation task, and there is an explanation as to why this is appropriate. Bat densities and bat behavior are discussed per unit area when realistically it should be per unit volume. In fact, the authors reference studies to justify the densities used in the simulation, but these studies were done in a 3D world. If the authors have justification for why it is realistic to model a 3D world in a 2D simulation, I encourage them to provide references justifying this approach.

We acknowledge that this is a simplification; however, from an echolocation perspective, a 2D framework represents a worst-case scenario in terms of bat densities and maneuverability:

· Higher Effective Density: A 2D model forces all bats into a single plane rather than distributing them through a 3D volume, increasing the likelihood of overlap in calls and echoes and making jamming more severe. As described in the text: the average distance to the nearest bat in our simulation is 0.27m (with 100 bats), whereas reported distances in very dense colonies are 0.5m, as observed in Myotis grisescens and Tadarida brasiliensis (Fujioka et al., 2021; Sabol and Hudson, 1995; Betke et al., 2008; Gillam et al, 2010)

· Reduced Maneuverability: In 3D space, bats can use vertical movement to avoid obstacles and conspecifics. A 2D constraint eliminates this degree of freedom, increasing collision risk and limiting escape options.

Thus, our 2D model provides a conservative difficult test case, ensuring that our findings are valid under conditions where jamming and collision risks are maximized. Additionally, the 2D framework is computationally efficient, allowing us to perform multiple simulation runs to explore a broad parameter space and systematically test the impact of different variables.

To address the reviewer’s concern, we have clarified this justification in the revised text and will provide supporting references where applicable: (see Methods lines 407-412)

The focus on "masking" (which appears to be just in-band noise), especially relative to the problem of misassigned echoes, is concerning. If the bat calls are all the same waveform (downsweep linear FM of some duration, I assume - it's not clear from the text), false echoes would be a major problem. Masking, as the authors define it, just reduces SNR. This reduction is something like sqrt(N), where N is the number of conspecifics whose echoes are audible to the bat, so this allows the detection threshold to be set lower, increasing the probability that a bat's echo will exceed a detection threshold. False echoes present a very different problem. They do not reduce SNR per se, but rather they cause spurious threshold excursions (N of them!) that the bat cannot help but interpret as obstacle detection. I would argue that in dense groups the mis-assignment problem is much more important than the SNR problem.

There is substantial literature supporting the assumption that bats can recognize their own echoes and distinguish them from conspecific signals (Schnitzler and Bioscience, 2001‏; Kazial, Burnett and Masters, 2001; Burnett and Masters, 2002; Kazial, Kenny and Burnett, 2008; Chili, Xian and Moss, 2009; Yovel et al., 2009; Beetz and Hechavarría, 2022). However, we acknowledge that false echoes may present a major challenge in dense groups. To address this, we explicitly tested the impact of the self-echo identification assumption in our study see Results Figure 4: The impact of confusion on performance, and lines 345-355 in the Discussion.

Furthermore, we examined a full confusion scenario, where all reflected echoes from conspecifics were misinterpreted as obstacle reflections (i.e., 100% confusion). Our results show that this significantly degrades navigation performance, supporting the argument that echo misassignment is a critical issue. However, we also explored a simple mitigation strategy based on temporal integration with outlier rejection, which provided some improvement in performance. This suggests that real bats may possess additional mechanisms to enhance self-echo identification and reduce false detections. See lines XX in the manuscript for further discussion.

The criteria set for flight behavior (lines 393-406) are not justified with any empirical evidence of the flight behavior of wild bats in collective flight. How did the authors determine the avoidance distances? Also, what is the justification for the time limit of 15 seconds to emerge from the opening? Instead of an exit probability, why not instead use a time criterion, similar to "How long does it take X% of bats to exit?"

While we acknowledge that wild bats may employ more complex behaviors for collision avoidance, we chose to implement a simplified decision-making rule in our model to maintain computational tractability.

The avoidance distances (1.5 m from walls and 0.4 m from other bats) were selected as internal parameters to ensure coherent flight trajectories while maintaining a reasonable collision rate. These distances provide a balance between maneuverability and stability, preventing erratic flight patterns while still enabling effective obstacle avoidance. In the revised paper, we have added supplementary figures illustrating the effect of model parameters on performance, specifically focusing on the avoidance distance.

The 15-second exit limit was determined as described in the text (Lines 403-404): “A 15-second window was chosen because it is approximately twice the average exit time for 40 bats and allows for a second corrective maneuver if needed.” In other words, it allowed each bat to circle the ‘cave’ twice to exit even in the most crowded environment. This threshold was set to keep simulation time reasonable while allowing sufficient time for most bats to exit successfully.

We acknowledge that the alternative approach suggested by the reviewer—measuring the time taken for a certain percentage of bats to exit—is also valid. However, in our model, some outlier bats fail to exit and continue flying for many minutes, Such simulations would lead to excessive simulation times making it difficult to generate repetitions and not teaching us much – they usually resulted from the bat slightly missing the opening (see video S1. Our chosen approach ensures practical runtime constraints while still capturing relevant performance metrics.

What is the empirical justification for the 1-10 calls used for integration?

The "average exit time for 40 bats" is also confusing and not well explained. Was this determined empirically? From the simulation? If the latter, what are the conditions? Does it include masking, no masking, or which species?

Previous studies have demonstrated that bats integrate acoustic information received sequentially over several echolocation calls (2-15), effectively constructing an auditory scene in complex environments (Ulanovsky and Moss, 2008; Chili, Xian and Moss, 2009; Moss and Surlykke, 2010; Yovel and Ulanovsky, 2017; Salles, Diebold and Moss, 2020). Additionally, bats are known to produce echolocation sound groups when spatiotemporal localization demands are high (Kothari et al., 2014). Studies have documented call sequences ranging from 2 to 15 grouped calls (Moss et al., 2010), and it has been hypothesized that grouping facilitates echo segregation.

We did not use a single integration window - we tested integration sizes between 1 and 10 calls and presented the results in Figure 3A. This range was chosen based on prior empirical findings and to explore how different levels of temporal aggregation impact navigation performance. Indeed, the results showed that the performance levels between 5-10 calls integration window (Figure 3A)

Regarding the average exit time for 40 bats, this value was determined from our simulations, where it represents the mean time for successful exits under standard conditions with masking.

We have revised the text to clarify these details see, lines 466.

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eLife Assessment

In this article, García-Vázquez et al. report valuable findings demonstrating that G2 and S phases expressed protein 1 (GTSE1), is a previously unappreciated non-pocket substrate of the cyclin D/cyclin-dependent kinase (CDK) 4/6 axis. The authors provide convincing evidence showing that this mechanism is triggered in pathological states in which cyclin D levels are elevated (e.g., cancer). Overall, this study holds a promise to improve understanding of the mechanisms underpinning cell cycle progression including its dysregulation in neoplasia and may thus be of broad interest to researchers belonging to diverse biomedical disciplines ranging from cancer research to cell biology.

Reviewer #1 (Public review):

Summary:

García-Vázquez et al. identify GTSE1 as a novel target of the cyclin D1-CDK4/6 kinases. The authors show that GTSE1 is phosphorylated at four distinct serine residues and that this phosphorylation stabilizes GTSE1 protein levels to promote proliferation. This regulatory link appears to be particularly important in pathological conditions such as cancer, where cyclin D levels are elevated.

Strengths:

The authors support their findings with several previously published results, including databases. In addition, the authors perform a wide range of experiments to support their findings.

Impact:

The authors reveal a mechanism by which elevated levels of cyclin D1-CDK4 can stabilize GTSE1 throughout the cell cycle via phosphorylation. This provides insight into the role of cyclin D1-CDK4 in regulating the cell cycle and promoting cancer growth.

Comments on revisions:

The authors have addressed all my concerns, and I would like to thank them for their efforts on this great study.

Reviewer #2 (Public review):

Summary:

The manuscript by García-Vázquez et al identifies the G2 and S phases expressed protein 1(GTSE1) as a substrate of the CycD-CDK4/6 complex. CycD-CDK4/6 is a key regulator of the G1/S cell cycle restriction point, which commits cells to enter a new cell cycle. This kinase is also an important therapeutic cancer target by approved drugs including Palbocyclib. Identification of substrates of CycD-CDK4/6 can therefore provide insights into cell cycle regulation and the mechanism of action of cancer therapeutics. A previous study identified GTSE1 as a target of CycB-Cdk1 but this appears to be the first study to address the phosphorylation of the protein by Cdk4/6.

The authors identified GTSE1 by mining an existing proteomic dataset that are elevated in AMBRA1 knockout cells. The AMBRA1 complex normally targets D cyclins for degradation. From this list they then identified proteins that contain a CDK4/6 consensus phosphorylation site and were responsive to treatment with Palbocyclib.

The authors show CycD-CDK4/6 overexpression induces a shift in GTSE1 on phostag gels that can be reversed by Palbocyclib. In vitro kinase assays also showed phosphorylation by CDK4. The phosphorylation sites were then identified by mutagenizing the predicted sites and phostag gets to see which eliminated the shift.

The authors go on to show that phosphorylation of GTSE1 affects the steady state level of the protein. Moreover, they show that expression and phosphorylation of GTSE1 confer growth advantage on tumor cells and correlate with poor prognosis in patients.

Strengths:

The biochemical and mutagenesis evidence presented convincingly show that the GTSE1 protein is indeed a target of the CycD-CDK4 kinase. The follow-up experiments begin to show that the phosphorylation state of the protein affect function and have an impact on patient outcome.

Weaknesses:

It is not clear at which stage in the cell cycle GTSE1 is being phosphorylated and how this is affecting the cell cycle. Considering that the protein is also phosphorylated during mitosis by CycB-Cdk1, it is unclear which phosphorylation events may be regulating the protein.

Additional comments for the revised manuscript

The authors have made many modifications to the manuscript in response to the reviewer comments, including the addition of new data that have clarified some of the conclusions. Some of the questions regarding the phase of the cell cycle affected have been addressed with flow cytometry.

There is one issue raised in the first review that can be better addressed. As the authors mentioned in their rebuttal letter, all the reviewers and editor concluded from the original manuscript that GTSE1 was being proposed as a physiological target of CycD-Cdk4 even in non-transformed cells. The authors believe that GTSE1 is likely only a target in cancerous cells that overexpress CycD and have made alterations in the abstract and main text making this point more clear.

Some additional evidence that GTSE1 phosphorylation is occurring in CycD overexpressing tumor cells would strengthen this argument beyond the overexpression experiments presented in the manuscript. For example, in Supplemental Fig 4A of the revised manuscript, bubble plots from CPTAC data is used to show that total protein levels of GTSE1 correlate with proteins associated with proliferation and metastasis. Do levels of GTSE1 correlate with CycD in this data set?

Reviewer #3 (Public review):

Summary:

This paper identifies GTSE1 as a substrate of cyclin D1-CDK4/6 complexes when cyclin D1 is significantly over-expressed (as is common in cancers) rather than its endogenous level. GTSE is stabilized by phosphorylation and GTSE1 correlates with cancer prognosis, probably through an effect on cell proliferation.

Strengths:

There are few bonafide cyclin D1-Cdk4/6 substrates identified to be important in vivo so GTSE1 represents a potentially important finding for the field. Currently, the only cyclin D1 substrates involved in proliferation are the Rb family proteins.

Weaknesses:

GTSE1 is not a 'normal' target of cyclin D1-Cdk4/6, but rather only a target in a pathological situation.

Author response:

The following is the authors’ response to the original reviews

eLife Assessment

In this valuable study, García-Vázquez et al. provide solid evidence suggesting that G2 and S phases expressed protein 1 (GTSE1), is a previously unappreciated non-pocket substrate of cyclin D1-CDK4/6 kinases. To this end, this study holds a promise to significantly contribute to an improved understanding of the mechanisms underpinning cell cycle progression. Notwithstanding these clear strengths of the article, it was thought that the study may benefit from establishing the precise role of cyclin D1-CDK4/6 kinase-dependent GTSE1 phosphorylation in the context of cell cycle progression, …

We do not claim, as editors and reviewers appear to have interpreted, that GTSE1 is phosphorylated by cyclin D1-CDK4 in the G1 phase of the cell cycle under normal physiologic conditions.  Indeed, we agree with the existing literature indicating that in cells that do not express high levels of cyclin D1, GTSE1 is expressed predominantly during S and G2 phase (hence the name GTSE1, which stands for G-Two and S phases expressed protein 1) and is phosphorylated by mitotic cyclins in early mitosis.  Even during G1, when the levels of cyclin D1 peak, GTSE1 is not phosphorylated in normal cells.  This could be due to either a higher affinity between GTSE1 and mitotic cyclins as compared to D-type cyclins or to a higher concentration of mitotic cyclins compared to D-type cyclins.  In the current manuscript, we show that higher levels of cyclin D1 can drive the sustained phosphorylation of GTSE1 across all cell cycle points. To reach this conclusion, we do not rely only on the overexpression of exogenous cyclin D1. In fact, we observe similar effect when we deplete endogenous AMBRA1, resulting in the stabilization of endogenous cyclin D1 in all cell cycle phases (see Figure 2G and Figure supplement 3B).  As we had already mentioned in the Discussion section, we propose that GTSE1 is phosphorylated by CDK4 and CDK6 particularly in pathological states, such as cancers displaying overexpression of D-type cyclins (i.e., it is possible that the overexpression overcomes the lower affinity of the cyclin D-GTSE1 complex). In turn, phosphorylation of GTSE1 induces its stabilization, leading to increased levels that, as expected based on the existing literature, contribute to enhanced cell proliferation.  So, the role of the cyclin D1-CDK4/6 kinase-dependent GTSE1 phosphorylation is to stabilize GTSE1 independently of the cell cycle.  In sum, our study suggests that overexpression of cyclin D1, which is often observed in cancers cells beyond the G1 phase, induces phosphorylation of GTSE1 at all points in the cell cycle. 

… obtaining more direct evidence that cyclin D1-CDK4/6 kinase phosphorylate indicated sites on GTSE1 (e.g., S454) …

We show that treatment of cells with palbociclib completely abolished the effect of cyclin D1-CDK4 on the GTSE1 shift observed using Phos-tag gels (Figure 2H).  Moreover, mutagenesis analysis shows that S91, S262, and S724 are phosphorylated in a cyclin D1-CDK4-dependent manner (Figure 2F and Figure supplement 3A). Compared to wild-type GTSE1, a triple mutant (S91A/S262A/S724A) displayed loss of slower-migrating bands upon co-expression of cyclin D1-CDK4, suggesting diminished phosphorylation. Nevertheless, a residual slow-migrating band persisted, prompting further mutations of the triple GTSE1 mutant in S331 and S454 (individually), which do not have a CDK-phosphorylation consensus, but were identified in several published phospho-proteomics studies. From these two quadruple mutants, only the that containing the S454A mutation demonstrated a complete abrogation of any shift in phos-tagTM gels (Figure 2F). These studies suggest that four major sites (S91, S262, S454, and S724) are phosphorylated (either directly and/or indirectly) in a cyclin D1-CDK4-dependent manner.

… and mapping a degron in GTSE1 whose function may be blocked by cyclin D1-CDK4/6 kinase-dependent phosphorylation.

We show that stabilization or overexpression of cyclin D1, which is often observed in human cancers, promotes GTSE1 phosphorylation on S91, S262, S454, and S724, resulting in GTSE1 stabilization.  Similarly, a phospho-mimicking mutant with the 4 serine residues replaced with an aspartate at positions 91, 261, 454, and 724 display increased half-life. While we appreciate the editor’s suggestion and agree on these being interesting questions, we would like to respectfully point out that mapping the GTSE1 degron and understanding how it is affected by cyclin D1-CDK4/6-dependent phosphorylation is outside the scope of the current project and will require an extensive set of experiments and tools. Accordingly, the three reviewers did not ask to map the GTSE1 degron.  We plan on addressing these interesting questions as part of a follow-up study.

Reviewer #1 (public review):

Summary:

García-Vázquez et al. identify GTSE1 as a novel target of the cyclin D1-CDK4/6 kinases. The authors show that GTSE1 is phosphorylated at four distinct serine residues and that this phosphorylation stabilizes GTSE1 protein levels to promote proliferation.

Strengths:

The authors support their findings with several previously published results, including databases. In addition, the authors perform a wide range of experiments to support their findings.

Weaknesses:

I feel that important controls and considerations in the context of the cell cycle are missing. Cyclin D1 overexpression, Palbociclib treatment and apparently also AMBRA1 depletion can lead to major changes in cell cycle distribution, which could strongly influence many of the observed effects on the cell cycle protein GTSE1. It is therefore important that the authors assess such changes and normalize their results accordingly.

We have approached the question of GTSE1 phosphorylation to account for potential cell cycle effects from multiple angles: 

(i) We conducted in vitro experiments with purified, recombinant proteins and shown that GTSE1 is phosphorylated by cyclin D1-CDK4 in a cell-free system (Figure 2A-C). These experiments provide direct evidence of GTSE1 phosphorylation by cyclin D1-CDK4 without the influence of any other cell cycle effectors. 

(ii) We present data using synchronized AMBRA1 KO cells (new Figure 2G and Figure supplement 3B).  In agreement with what we had shown previously (Simoneschi et al., Nature 2021, PMC8875297), AMBRA1 KO cells progress faster in the cell cycle but they are still synchronized as shown, for example, by the mitotic phosphorylation of Histone H3, peaking at 32 hours after serum readdition like in parental cells. Under these conditions we observed that while phosphorylation of GTSE1 in parental cells is evident in the last two time points, AMBRA1 KO cells exhibited sustained phosphorylation of GTSE1 across all cell cycle phases.  This was evident enough when using Phos-tag gels as in the top panel of the old Figure 2G. We now re-run one the biological triplicates of the synchronized cells using higher concentration of Zn⁺²-Phos-tag reagent and lower voltage to allow better separation of the phosphorylated bands.  Under these conditions, GTSE1 phosphorylation is better appreciable (top panel of the new Figure 2G). This experiment provides evidence that high levels of cyclin D1 in AMBRA1 KO cells affect GTSE1 phosphorylation independently of the specific points in the cell cycle. 

(iii) The relative short half-life of GTSE1 (<4 hours) makes its levels sensitive to acute treatments such as Palbociclib or acute AMBRA1 depletion. The effects of these treatments on GTSE1 levels are measurable within a time frame too short to significantly affect cell cycle progression. For example, we used cells with fusion of endogenous AMBRA1 to a mini-Auxin Inducible Degron (mAID) at the N-terminus. This system allows for rapid and inducible degradation of AMBRA1 upon addition of auxin, thereby minimizing compensatory cellular rewiring. Again, we observed an increase in GTSE1 levels upon acute ablation of AMBRA1 (i.e., in 8 hours) (Figure 3B), when no significant effects on cell cycle distribution are observed (please see Simoneschi et al., Nature 2021, PMC8875297 and Rona et al., Mol. Cell 2024, PMC10997477).

Altogether, the above lines of evidence support our conclusion that GTSE1 is a target of cyclin D1-CDK4, independent of cell cycle effects.

In conclusion, we do not claim that GTSE1 is phosphorylated by cyclin D1-CDK4 in the G1 phase of the cell cycle under normal physiologic conditions.  Indeed, we agree with the existing literature indicating that in cells that do not express high levels of cyclin D1, GTSE1 is expressed predominantly during S and G2 phase (hence the name GTSE1, which stands for G-Two and S phases expressed protein 1) and is phosphorylated by mitotic cyclins in early mitosis.  Even during G1, when the levels of cyclin D1 peak, GTSE1 is not phosphorylated in normal cells. This could be due to either a higher affinity between GTSE1 and mitotic cyclins as compared to D-type cyclins or to a higher concentration of mitotic cyclins compared to D-type cyclins.  In the current manuscript, we show that higher levels of cyclin D1 can drive the sustained phosphorylation of GTSE1 across all cell cycle points. To reach this conclusion, we do not rely only on the overexpression of exogenous cyclin D1. In fact, we observe similar effect when we deplete endogenous AMBRA1, resulting in the stabilization of endogenous cyclin D1 in all cell cycle phases (see Figure 2G and Figure supplement 3B).  As we had already mentioned in the Discussion section of the original submission, we propose that GTSE1 is phosphorylated by CDK4 and CDK6 particularly in pathological states, such as cancers displaying overexpression of D-type cyclins (i.e., it is possible that the overexpression overcomes the lower affinity of the cyclin D1-GTSE1 complex). In turn, phosphorylation of GTSE1 induces its stabilization, leading to increased levels that, as expected based on the existing literature, contribute to enhanced cell proliferation.  In sum, our study suggests that overexpression of cyclin D1, which is often observed in cancers cells beyond the G1 phase, induces phosphorylation of GTSE1 at all points in the cell cycle.    

Reviewer #2 (public review):

Summary:

The manuscript by García-Vázquez et al identifies the G2 and S phases expressed protein 1(GTSE1) as a substrate of the CycD-CDK4/6 complex. CycD-CDK4/6 is a key regulator of the G1/S cell cycle restriction point, which commits cells to enter a new cell cycle. This kinase is also an important therapeutic cancer target by approved drugs including Palbocyclib. Identification of substrates of CycD-CDK4/6 can therefore provide insights into cell cycle regulation and the mechanism of action of cancer therapeutics. A previous study identified GTSE1 as a target of CycB-Cdk1 but this appears to be the first study to address the phosphorylation of the protein by Cdk4/6.

The authors identified GTSE1 by mining an existing proteomic dataset that is elevated in AMBRA1 knockout cells. The AMBRA1 complex normally targets D cyclins for degradation. From this list, they then identified proteins that contain a CDK4/6 consensus phosphorylation site and were responsive to treatment with Palbocyclib.

The authors show CycD-CDK4/6 overexpression induces a shift in GTSE1 on phostag gels that can be reversed by Palbocyclib. In vitro kinase assays also showed phosphorylation by CDK4. The phosphorylation sites were then identified by mutagenizing the predicted sites and phostag got to see which eliminated the shift.

The authors go on to show that phosphorylation of GTSE1 affects the steady state level of the protein. Moreover, they show that expression and phosphorylation of GTSE1 confer a growth advantage on tumor cells and correlate with poor prognosis in patients.

Strengths:

The biochemical and mutagenesis evidence presented convincingly show that the GTSE1 protein is indeed a target of the CycD-CDK4 kinase. The follow-up experiments begin to show that the phosphorylation state of the protein affects function and has an impact on patient outcomes.

Weaknesses:

It is not clear at which stage in the cell cycle GTSE1 is being phosphorylated and how this is affecting the cell cycle. Considering that the protein is also phosphorylated during mitosis by CycB-Cdk1, it is unclear which phosphorylation events may be regulating the protein.

Please see point (ii) and the last paragraph in the response to Reviewer #1.  Moreover, we show that, compared to the amino acids phosphorylated by cyclin D1-CDK4, cyclin B1-CDK1 phosphorylates GTSE1 on either additional residues or different sites (Figure 2H). We also show that expression of a phospho-mimicking GTSE1 mutant leads to accelerated growth and an increase in the cell proliferative index (Figure 4B,C and new Figure supplement 4D-E).  Finally, we have evaluated also the cell cycle distributions by flow cytometry (new Figure supplement 4F). These analyses show that the expression of a phospho-mimicking GTSE1 mutant induces a decrease in the percentage of cells in G1 and an increase in the percentage of cells in S, similarly to what observed in AMBRA1 KO cells.

Reviewer #3 (public review)

Summary:

This paper identifies GTSE1 as a potential substrate of cyclin D1-CDK4/6 and shows that GTSE1 correlates with cancer prognosis, probably through an effect on cell proliferation. The main problem is that the phosphorylation analysis relies on the over-expression of cyclin D1. It is unclear if the endogenous cyclin D1 is responsible for any phosphorylation of GTSE1 in vivo, and what, if anything, this moderate amount of GTSE1 phosphorylation does to drive proliferation.

Strengths:

There are few bonafide cyclin D1-Cdk4/6 substrates identified to be important in vivo so GTSE1 represents a potentially important finding for the field. Currently, the only cyclin D1 substrates involved in proliferation are the Rb family proteins.

Weaknesses:

The main weakness is that it is unclear if the endogenous cyclin D1 is responsible for phosphorylating GTSE1 in the G1 phase. For example, in Figure 2G there doesn't seem to be a higher band in the phos-tag gel in the early time points for the parental cells. This experiment could be redone with the addition of palbociclib to the parental to see if there is a reduction in GTSE1 phosphorylation and an increase in the amount in the G1 phase as predicted by the authors' model. The experiments involving palbociclib do not disentangle cell cycle effects. Adding Cdk4 inhibitors will progressively arrest more and more cells in the G1 phase and so there will be a reduction not just in Cdk4 activity but also in Cdk2 and Cdk1 activity. More experiments, like the serum starvation/release in Figure 2G, with synchronized populations of cells would be needed to disentangle the cell cycle effects of palbociclib treatment.   

Please see last paragraph in the response to Reviewer #1.  Concerning the experiments involving palbociclib, we limited confounding effects on the cell cycle by treating cells with palbociclib for only 4-6 hours. Under these conditions, there is simply not enough time for S and G2 cells to arrest in G1.

It is unclear if GTSE1 drives the G1/S transition. Presumably, this is part of the authors' model and should be tested.

We are not claiming that GTSE1 drives the G1/S transition (please see last paragraph in the response to Reviewer #1). GTSE1 is known to promote cell proliferation, but how it performs this task is not well understood.  Our experiments indicate that, when overexpressed, cyclin D1 promotes GTSE1 phosphorylation and its consequent stabilization.  In agreement with the literature, we show that higher levels of GTSE1 promote cell proliferation.  To measure cell cycle distribution upon expressing various forms of GTSE1, we have now performed FACS analyses (new Figure supplement 4F). These analyses show that the expression of a phospho-mimicking GTSE1 mutant induces a decrease in the percentage of cells in G1 and an increase in the percentage of cells in S, similarly to what observed in AMBRA1 KO cells shown in the same panel and in Simoneschi et al. (Nature 2021, PMC8875297).

The proliferation assays need to be more quantitative. Figure 4B should be plotted on a log scale so that the slope can be used to infer the proliferation rate of an exponentially increasing population of cells. Figure 4c should be done with more replicates and error analysis since the effects shown in the lower right-hand panel are modest.

In Figure 4B, we plotted data in a linear scale as done in the past (Donato et al. Nature Cell Biol. 2017, PMC5376241) to better underline the changes in total cell number overtime.  The experiments in Figure 4B were performed in triplicate, statistical significance was determined using unpaired T-tests with p-values<0.05, and error bars represent the mean +/- SEM.  In Figure 4C, error analysis was not included for simplicity, given the complexity of the data.  We have now included the other two sets of experiments (new Figure supplement 4D,E).  While the effects shown in the lower right-hand panel of Figure 4C are modest, they demonstrate the same trend as those observed in the AMBRA KO cells (Figure 4C and Simoneschi et al., Nature 2021, PMC8875297). It's important to note that this effect is achieved through the stable expression of a single phospho-mimicking protein, whereas AMBRA KO cells exhibit changes in numerous cell cycle regulators. Moreover, these effects are obtained by growing cells in culture for only 5 days. A similar impact on cell growth in vivo over an extended period could pose significant risks in the long term.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Figure 1E is referenced before 1D. The authors should consider switching D and E.

Done.

Figure 1D-E: The authors correctly note in the introduction that GTSE1 is encoded by a cell cycle-dependently expressed gene. Given that cell cycle genes are often associated with poor prognosis (e.g., see Whitfield et al., 2006 Nat. Rev. Cancer), this would be expected to correlate with poor prognosis. This should be mentioned in the results section.

We agree that the overexpression of certain (but not all) cell cycle-regulated genes are prognostically unfavorable across various cancer types, and we cited Whitfield et al., 2006 Nat. Rev. Cancer.  However, our data indicate that phosphorylation of GTSE1 induces its stabilization and, consequently, its levels do not oscillate during the cell cycle any longer (new Figure 2G and Figure supplement 3B).  Moreover, analyzing data from the Clinical Proteomic Tumor Analysis Consortium, we observed an enrichment of GTSE1 phospho-peptides (normalized to total protein) within a pan-cancer cohort as opposed to adjacent, corresponding normal tissues (Figure 2I).

Figure 2F: Contrast is too high. Blot images should not contain fully saturated black or white.

We corrected the contrast.

Figure 2G and Figure Supplement 3B: It looks like AMBRA1 KO cells do not synchronize properly in response to serum withdrawal. The cell cycle distribution should be checked by FACS. Otherwise, it is unclear whether changes in GTSE1 (phosphor) levels are only due to indirect changes in the cell cycle distribution.

Synchronization of both parental and AMBRA1 KO cells is demonstrated by the fact that the phosphorylation of Histone H3 peaks at 32 hours after serum readdition in both cases (Figure supplement 3B). 

Figure 2I: It is important that phosphor-GTSE1 levels are normalized to total GTSE1 levels to understand the distinct contribution of changes in GTSE1 levels and from CCND1-CDK4 driven phosphorylation.

Done.

Figure 3A-B: These experiments should also be controlled for cell cycle distribution. Is this effect specific to GTSE1 and other AMBRA1 targets or are other G2/M cell cycle proteins also affected?

The relative short half-life of GTSE1 (<4 hours) makes its levels sensitive to acute treatments such as Palbociclib or acute AMBRA1 depletion. The effects of these treatments on GTSE1 levels are measurable within a time frame too short to significantly affect cell cycle progression. For example, we used cells with fusion of endogenous AMBRA1 to a mini-Auxin Inducible Degron (mAID) at the N-terminus. This system allows for rapid and inducible degradation of AMBRA1 upon addition of auxin, thereby minimizing compensatory cellular rewiring. Again, we observed an increase in GTSE1 levels upon acute ablation of AMBRA1 (i.e., in 8 hours) (Figure 3B), when no significant effects on cell cycle distribution are observed (please see Simoneschi et al., Nature 2021, PMC8875297 and Rona et al., Mol. Cell 2024, PMC10997477).

Figure 4: It should be noted that the correlation with cell proliferation and cell cycle protein expression is expected for any cell cycle protein, including GTSE1.

Actually, the main point of Figure 4 is to show that expression of the phospho-mimicking mutant of GTSE1 promotes cell proliferation. Comparative analysis revealed that cells overexpressing either wild-type GTSE1 or its phospho-deficient form exhibited significantly reduced proliferation rates compared to those expressing the phospho-mimicking mutant (Figure 4B,C). 

The two-decades-old references 33 and 34 are not well suited to support the notion for Cyclin D1 that "the full spectrum of substrates and their impact on cellular function and oncogenesis remain poorly explored." More recent references should be used to show that this is still the case.

We added more recent references.

The authors conclude that their "data indicate that cyclin D1-CDK4 is responsible for the phosphorylation of GTSE1 on four residues (S91, S262, S454, and S724)." However, the authors' data do not exclude a role for their siblings cyclin D2, cyclin D3, and CDK6. Reflecting this, the conclusions should be toned down.

The analysis of the sites phosphorylated in GTSE1 was performed by experimentally co-expressing cyclin D1-CDK4 (Figure 2F, Figure 2H, and Figure supplement 3A), hence our statement.  Yet, we agree that in cells, cyclin D2, cyclin D3, and CDK6 can contribute to GTSE1 phosphorylation. 

The authors claim that they "observed that in human cells, when D-type cyclins are stabilized in the absence of AMBRA1, GTSE1 becomes phosphorylated also in G1." However, the G1-specific data presented by the authors are not controlled for, and it is unclear whether these phosphorylation events actually occur in G1 cells.

We now provide a WB in which GTSE1 phosphorylation is more evident (top panel of the new Figure 2G) (please see point (ii) in the response to the public review of Reviewer #1).  This experiment clearly shows that in AMBRA1 KO cells, GTSE1 is phosphorylated at all points in the cell cycle. Synchronization of both parental and AMBRA1 KO cells is demonstrated by the fact that phosphorylation of Histone H3 peaks at 32 hours after serum re-addition in both cases (Figure supplement 3B). 

Reviewer #2 (Recommendations for the authors):

(1) It is not clear from the presented data at which point in the cell cycle that phosphorylation of GTSE1 may be affecting the steady state level of the protein. The implication that GTSE1 is a target of CycD-CDK4 would suggest that the protein is stabilized at G1/S. Can this effect be observed?

Please see the last paragraph in the response to the public review of Reviewer #1.

(2) Considering the previous study showing that GTSE1 is also phosphorylated during mitosis by CycB-Cdk1, do levels of GTSE1 protein change during the cell cycle? Do changes in GTSE1 levels correlate with phosphorylation during the cell cycle? Cell synchronization experiments such as double thymidine and subsequent phostag analysis could shed some light on these questions.

Please see the last paragraph in the response to the public review of Reviewer #1.

(3) The authors show that the phosphomimetic mutants of GTSE1 confer a growth advantage on cells. The mechanism of this growth advantage is unclear. Is this effect due to a shorter cell cycle, enhanced survival, or another mechanism?

We did not observe increased cell survival when the phosphomimetic mutants of GTSE1 is expressed.  We show that phosphorylation of GTSE1 induces its stabilization, leading to increased levels that, as expected based on the existing literature, contribute to enhanced cell proliferation.  So, the role of the cyclin D1-CDK4/6 kinase-dependent phosphorylation of GTSE1 is to stabilize GTSE1. 

(4) Other minor points - all of the presented immunoblots do not show molecular weight markers. The IF images require scale bars.

To prevent overcrowding of the Figures, the sizes of blotted proteins are indicated in the uncropped scans of each blot. Uncropped scans have been deposited in Mendeley at:  https://data.mendeley.com/datasets/xzkw7hrwjr/1. Scale bars have been added to the IF images.

eLife Assessment

This is an important study demonstrating the importance of S100A4+ alveolar macrophages in the earlier stages of tumour development and suggesting a role in angiogenesis. As such this convincing study is of interest to cancer biologists focused on early tumour development and those interested in the development of therapeutics that may specifically target early cancers.

Reviewer #1 (Public review):

Summary:

In this paper, the authors have leveraged Single-cell RNA sequencing of the various stages of evolution of lung adenocarcinoma to identify the population of macrophages that contribute to tumor progression. They show that S100a4+ alveolar macrophages, active in fatty acid metabolic activity, such as palmitic acid metabolism, seem to drive atypical adenomatous hyperplasia (AAH) stage. These macrophages also seem to induce angiogenesis promoting tumor growth. Similar types of macrophage infiltration were demonstrated in the progression of the human lung adenocarcinomas.

Comments on revised version:

The authors have satisfactorily addressed my main concerns.

The only weakness is that infusion of S100a4+ macrophages seem not to affect tumor growth when introduced to the intratracheal route. This negative result somewhat diminishes the significance of the study.

Overall, the revised manuscript is significantly improved.

Reviewer #2 (Public review):

Summary:

The work aims to further understand the role of macrophages in lung precancer/lung cancer evolution

Strengths:

(1) The use of single-cell RNA seq to provide comprehensive characterisation.

(2) Characterisation of cross-talk between macrophages and the lung precancerous cells.

(3) Functional validation of the effects of S100a4+ cells on lung precancerous cells using in vitro assays.

(4) Validation in human tissue samples of lung precancer / invasive lesions.

Weaknesses identified previously:

(1) The authors need to provide clarification of several points in the text.

(2) The authors need to carefully assess their assumptions regarding the role of macrophages in angiogenesis in precancerous lesions.

(3) The authors should discuss more broadly the current state of anti-macrophage therapies in the clinic.

Comments on revised version:

The authors have adequately addressed all of my comments.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this paper, the authors have leveraged Single-cell RNA sequencing of the various stages of the evolution of lung adenocarcinoma to identify the population of macrophages that contribute to tumor progression. They show that S100a4+ alveolar macrophages, active in fatty acid metabolic activity, such as palmitic acid metabolism, seem to drive the atypical adenomatous hyperplasia (AAH) stage. These macrophages also seem to induce angiogenesis promoting tumor growth. Similar types of macrophage infiltration were demonstrated in the progression of the human lung adenocarcinomas.

Strengths:

Identification of the metabolic pathways that promote angiogenesis-dependent progression of lung adenocarcinomas from early atypical changes to aggressive invasive phenotype could lead to the development of strategies to abort tumor progression.

We are grateful for your constructive comments. These comments are very helpful for revising and improving our paper and have provided important guiding significance to our study. We have made revisions according to your comments and have provided point-by-point responses to your concerns.

Weaknesses:

(1) Can the authors demonstrate what are the functional specialization of the S100a4+ alveolar macrophages that promote the progression of the AAH to the more aggressive phenotype? What are the factors produced by these unique macrophages that induce tumor progression and invasiveness?

Thank you for your comments. To more comprehensively characterize the functional specialization of the S100a4⁺ alveolar macrophages, we expanded the macrophage functional gene sets based on relevant literature and databases and performed enrichment analysis. The results showed that all stages of precancerous progression presented activated states of angiogenesis, M2-like and immunosuppressive functions relative to the normal stage (Figure 4B). As we have demonstrated, S100a4⁺ alveolar macrophages predominantly exert pro-angiogenic functions during the AAH phase and may be more biased towards M2-like polarization and immunosuppression during further disease progression. Consistently, S100A4⁺ subset population of macrophages has been proved to exhibit a M2-like phenotype with immunosuppressive properties in tumor progression [PMID: 34145030]. In addition, S100A4 has been reported to be associated with macrophage M2 polarization, angiogenesis, and tumorigenesis [PMID: 39664586, 36895491, 30221056, 32117590]. The functional status of human S100A4⁺ alveolar macrophages is basically the same. The relevant description was added to the Results section as follows: “It was revealed that the capacities for angiogenesis, M2-like polarization, and immunosuppression were found to be stronger in AAH or other precancerous stages relative to the normal stage (Figure 4B). The pro-angiogenic function predominated in the AAH stage, while M2-like and immunosuppressive functions were more prominent in the subsequent precancerous progression.” (page 11, line 262). Our study puts more attention on the functional phenotypic changes of S100a4⁺ alveolar macrophages during the progression from normal to AAH to explain the role of this subpopulation in tumor initiation, and similarly, preliminary coculture experiments could only indicate its role in the early malignant transformation of epithelial cells. In further experimental validation, we will confirm the above functions of the S100a4⁺ alveolar macrophages promoting the progression of AAH to the more aggressive phenotype by in vitro and in vivo experiments. We have extended the limitations and potential experimental designs to the Discussion section as follows: “It is worth noting that our mining of S100a4⁺ alv-macro remains at the precancerous initiation stage, and further experimental designs are needed to verify its specific contribution at more aggressive stages. For example, FACS sorting of the subpopulation at different stages of disease progression, respectively, for precise functional characterization;” (page 19, line 468).

For the factors produced by these unique macrophages during induction of malignant transformation, we assayed culture supernatant of S100a4-OE alveolar macrophages for secreted functional cytokines. The results showed up-regulation of MIP-2, HGF, TNFα, IL-1a, CD27, CT-1, MMP9, 4-1BB, and CD40, and GO enrichment showed angiogenesis and tumorigenesis-related processes (Figure 5L and 5M). We have added the detailed content to the Results section as follows: “Next, we detected tumor-inducing factors secreted by these unique macrophages using Cytokine Antibody Array. We noted the production of macrophage inflammatory protein (MIP)-2, hepatocyte growth factor (HGF), tumor necrosis factor α (TNF-α), IL-1α, MMP9, and CD40, and these cytokine-related biological processes were mainly involved in the regulation of angiogenesis and immune response (Figure 5L and 5M).” (page 13, line 319). Furthermore, changes in these cytokines during subsequent invasive tumor progression will also be continuously monitored. The description in the Discussion section have been added as: “Furthermore, TGF-β and HGF activate vascular endothelial cells and promote proliferation and migration, as well as induce the expression of pro-angiogenic factors such as VEGF (Vimalraj, 2022; Watabe, Takahashi, Pietras, & Yoshimatsu, 2023). Macrophage-derived TNF-α and IL-1α lead tumor cells to produce potent angiogenic factors IL-8 and VEGF, which affect angiogenesis and tumor growth (Torisu et al., 2000). MIP2 and CD40 were also identified as pro-tumor factors associated with angiogenesis (Kollmar, Scheuer, Menger, & Schilling, 2006; Murugaiyan, Martin, & Saha, 2007)…continuous monitoring of the fluctuation of the above factors in bronchoalveolar lavage fluid at corresponding periods;” (page 19, line 461).

All method details covered in this section have been updated in the Materials and methods.

(2) Angiogenic factors are not only produced by the S100a4+ cells but also by pericytes and potentially by the tumor cells themselves. Then, how do these factors aberrantly trigger tumor angiogenesis that drives tumor growth?

Thank you for your comment. In our study, we detected up-regulation of angiogenic factors HIF-1α, VEGF, MMP9, and TGF-β (Figure 5K), and elevation of secreted HGF, IL-1α, and TNF-α (Figure 5L). We provide a detailed description of how these factors are involved in angiogenesis-related tumorigenesis to varying degrees in the Discussion section: “Precancerous lesions of LUAD are angiogenic, and pro-angiogenic factors secreted by cells, including S100a4⁺ alv-macro, induce endothelial cell sprouting and chemotaxis, leaving the angiogenic switch activated, prompting the formation of new blood vessels on the basis of the original ones to supply oxygen and nutrients to sustain tumor initiation (Chen et al., 2024; Kayser et al., 2003; van Hinsbergh & Koolwijk, 2008). Under hypoxic conditions, HIF-1α activates numerous factors that contribute to the angiogenic process, including VEGF, which promotes vascular permeability, and MMP9, which breaks down the ECM, promotes endothelial cell migration, and recruits pericytes to provide structural support (Raza, Franklin, & Dudek, 2010; Sakurai & Kudo, 2011). Cytokines secreted into the microenvironment activate macrophages, which subsequently produce angiogenic factors, further promoting angiogenesis (Sica, Schioppa, Mantovani, & Allavena, 2006). Furthermore, TGF-β and HGF activate vascular endothelial cells and promote proliferation and migration, as well as induce the expression of pro-angiogenic factors such as VEGF (Vimalraj, 2022; Watabe, Takahashi, Pietras, & Yoshimatsu, 2023). Macrophage-derived TNF-α and IL-1α lead tumor cells to produce potent angiogenic factors IL-8 and VEGF, which affect angiogenesis and tumor growth (Torisu et al., 2000)…” (page 19, line 449).

(3) It is not clear how abnormal fatty acid uptake by the macrophages drives the progression of tumors.

Thank you for your comment, which coincides with our mechanistic exploration. The metabolic status of macrophages influences their pro-tumor properties, and lipid metabolism has been shown to determine the functional polarization of macrophages [PMID: 29111350]. In this study, we observed more accumulation of lipid droplets in S100a4-OE MH-S, demonstrating enhanced cellular fatty acid uptake (Figure 6A). The pro-angiogenic ability of S100a4⁺ alv-macro was confirmed by tube formation assay and cytokine assay (Figure 6B and 5M). Cpt1a was thought to play a crucial role in the metabolic paradigm shift of S100a4⁺ alv-macro, we therefore performed functional rescue experiments by inhibiting CPT1A expression in S100a4-OE MH-S by addition of etomoxir (ETO). After culture with conditioned medium of MH-S, the proliferation, migration, and ROS production of MLE12 cells were all restored to lower levels (Figure 6E-G). In addition, ETO treatment significantly reversed the angiogenesis, which supported the regulation of fatty acid metabolism on macrophage function (Figure 6H). Immunoblotting also revealed restoration of expression in related proteins (Figure 6I and 6J), these findings reinforced previous analyses of the association of fatty acid metabolism with pro-angiogenesis and M2-like function in S100a4⁺ alv-macro. The involvement of PPAR-γ in the regulation of metabolic state was also confirmed. Taken together, we suggest that S100a4⁺ alv-macro promotes fatty acid metabolism through the CPT1A-PPAR-γ axis, enhances its ability to promote angiogenesis, and thus drives tumor occurrence. The corresponding contents were added in the Results section S100a4⁺ alv-macro drove angiogenesis by promoting Cpt1a-mediated fatty acid metabolism (page 13, line 327) and Discussion section: “We demonstrated the regulation of fatty acid metabolism by CPT1A in S100a4⁺ alv-macro as well as the involvement of PPAR-γ. Nevertheless, the molecular mechanism that drives the acquisition of metabolic and functional switching properties specific to this cell state still requires further characterization in the context of precancerous lesions. It has been reported that CD36 is the main effector of the S100A4/PPAR-γ pathway, and its mediated fatty acid uptake plays an important role in the tumor-promoting function of macrophages (S. Liu et al., 2021).” (page 18, line 433).

All method details covered in this section have been supplemented in the Materials and methods.

(4) Does infusion or introduction of S100a4+ polarized macrophages promote the progression of AAH to a more aggressive phenotype?

Thank you for your comment. We performed intratracheal instillation of lentivirus-infected S100a4-OE MH-S and culture supernatant in A/J and BALB/c mice, respectively, but no aggressive pathological phenotype was observed so far, possibly due to the lack of time required for lesions or the imperfection of experimental conditions. We will continue to explore the instillation dose and frequency for long-term monitoring and will simultaneously evaluate the availability of primary alveolar macrophages. We have discussed as follows: “It is worth noting that our mining of S100a4⁺ alv-macro remains at the precancerous initiation stage, and further experimental designs are needed to verify its specific contribution at more aggressive stages…and intratracheal instillation of primary S100a4⁺ alv-macro to observe the pathological progression of precancerous lesions.” (page 19, line 468).

(5) How does Anxa and Ramp1 induction in inflammatory cells induce angiogenesis and tumor progression?

Thank you for your comment. ANXA2 is an important member of annexin family of proteins expressed on surface of endothelial cells, macrophages, and tumor cells [PMID: 30125343]. ANXA2 was reported to regulate neoangiogenesis in the tumor microenvironment and most likely due to overproduction of plasmin. As a well-established receptor for plasminogen (PLG) and tissue plasminogen activator (tPA) on the cell surface, ANXA2 converts PLG into plasmin. Plasmin plays a critical role in the activation of cascade of inactive proteolytic enzymes such as metalloproteases (pro-MMPs) and latent growth factors (VEGF and bFGF) [PMID: 12963694, 11487021]. Activated forms of MMPs and VEGF then induce extracellular matrix remodeling facilitating angiogenesis and tumor development [PMID: 15788416]. Sharma et al. suggested administration of ANXA2-antibody inhibited tumor angiogenesis and growth concurrent with plasmin generation [PMID: 22044461], the role of ANXA2 in plasmin activation thus explains it’s importance in tumor-related angiogenesis. We verified the simultaneous upregulation of ANXA2 and PLG in S100a4-OE MH-S and cocultured HUVEC and MLE12 by immunoblotting (Figure 6D). The relevant description was added to the Results section as follows: “ANXA2 is considered to be a cellular receptor for plasminogen (PLG), often expressed on the surface of endothelial cells, macrophages, and tumor cells, which activates a cascade of pro-angiogenic factors by promoting the conversion of PLG to plasmin, thereby promoting angiogenesis and tumor progression (Semov et al., 2005; Sharma, 2019). We found synergistic upregulation of ANXA2 and PLG expression in S100a4-OE MH-S and cocultured HUVEC and MLE12, which may help explain how ANXA2 induction was involved in angiogenesis and malignant transformation (Figure 6D).” (page 14, line 338).

Recent studies showed that S100A4 is associated with tumor angiogenesis and progression by the interaction with ANXA2. ANXA2 is the endothelial receptor for S100A4 and that their interaction triggers the functional activity directly related to pathological properties of S100A4, including angiogenesis [PMID: 18608216]. It has been proved that S100A4 induces angiogenesis through interaction with ANXA2 and accelerated plasmin formation [PMID: 15788416, 25303710]. In addition, it is generally believed that ANXA2 participates in malignant cell transformation [PMID: 28867585]. Therefore, we speculate that ANXA2 may promote plasmin production by binding to S100A4, thus promoting angiogenesis and tumor initiation, and we have discussed accordingly: “The role of ANXA2 in angiogenesis has been widely recognized, and it may facilitate plasmin production by binding to S100A4 and then trigger angiogenesis and malignant cell transformation (Grindheim, Saraste, & Vedeler, 2017; Y. Liu, Myrvang, & Dekker, 2015).” (page 18, line 446).

In our study, the primary target of our validation was ANXA2 rather than RAMP1, even though its relationship with angiogenesis had been established [PMID: 20596610], so we weakened the relevant description in the manuscript.

(6) For the in vitro studies the authors might consider using primary tumor cells and not cell lines.

Thank you for your suggestion, which was in our initial experimental plan. However, since S100A4 is not expressed on the cell surface, FACS sorting of primary subset of alveolar macrophages presents technical limitations. We have also attempted overexpression in primary macrophages, but the current overexpression efficiency and cell status are not sufficient to support a subsequent series of experiments. For all these reasons, the alveolar macrophage cell line MH-S and the lung epithelial cell line MLE12 were selected to ensure the consistency and stability of the coculture system.

In addition, we are optimizing the experimental conditions to achieve coculture of primary macrophages and epithelial cells, and will also establish transgenic mouse models for simultaneous validation. The Discussion has been added as: “Besides, as our previous in vitro results were obtained based on cell lines, we will optimize the experimental conditions to achieve coculture of primary macrophage subset and epithelial cells and establish transgenic mouse models for in vivo validation.” (page 19, line 475).

Reviewer #2 (Public review):

Summary:

The work aims to further understand the role of macrophages in lung precancer/lung cancer evolution

Strengths:

(1) The use of single-cell RNA seq to provide comprehensive characterisation.

(2) Characterisation of cross-talk between macrophages and the lung precancerous cells.

(3) Functional validation of the effects of S100a4+ cells on lung precancerous cells using in vitro assays.

(4) Validation in human tissue samples of lung precancer / invasive lesions.

We are grateful for your constructive comments. These comments are very helpful for revising and improving our paper and have provided important guiding significance to our study. We have made revisions according to your comments and have provided point-by-point responses to your concerns.

Weaknesses:

(1) The authors need to provide clarification of several points in the text.

Thank you for your comment. We have clarified these points in the manuscript and responded to all your concerns in detail. Please see the responses to Recommendations for the authors.

(2) The authors need to carefully assess their assumptions regarding the role of macrophages in angiogenesis in precancerous lesions.

Thank you for your comment. We have cited relevant literature to support the occurrence of angiogenesis in precancerous lesions, and demonstrated the contribution of S100a4⁺ alveolar macrophages by tube formation assay and cytokine assay. In addition, we have discussed the relevant limitations of this study and aimed to provide more robust evidence. Please see the responses to Recommendations for the authors.

(3) The authors should discuss more broadly the current state of anti-macrophage therapies in the clinic.

Thank you for your suggestion. We have provided extensive discussion of the clinical state of anti-macrophage therapies. Please see the responses to Recommendations for the authors.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

The text has grammatical and syntax errors that need to be corrected accordingly.

Thank you for your suggestion. We have corrected the grammatical and syntactic errors and asked a native English speaker in the field to help polish the full text.

Reviewer #2 (Recommendations for the authors):

This work provides an important contribution to our further understanding of the role of macrophages in lung precancer/lung cancer evolution. I have several comments regarding how the manuscript could be improved:

Introduction:

The authors may consider citing the following work to enhance their work:

(1) At line 78, where they talk about precancerous lesions being reversible, they should cite recent work on this in lung cancer: Teixeria et al 2019 PMID: 30664780, and Pennycuik et al 2020 PMID: 32690541.

Thank you for your suggestion. We have cited the above references in the corresponding paragraph (page 4, line 76).

(2) At line 96, where they talk about developing medicines for precancerous lesions, the authors should cite comprehensive review articles where this concept has been discussed in depth, for example: Reynolds et al 2023 PMID: 37067191, and Asad et al 2012 PMID: 23151603.

Thank you for your suggestion. We have cited the above references in the corresponding paragraph (page 5, line 94).

Results:

(1) Line 142, the authors say "mice were feed for 12-16 months" - do they mean the mice were maintained for 12-16 months?

Thank you for your comment. To best mimic the process of human lung cancer development, A/J mice with the highest incidence of spontaneous lung tumors, which increases substantially with age, were selected. The corresponding description has been modified as: “A/J mice have the highest incidence of spontaneous lung tumors among various mouse strains, and this probability significantly increased with age (Landau, Wang, Yang, Ding, & Yang, 1998). To more comprehensively mirror the tumor initiation and progression process of human lung cancer, A/J mice were maintained for 12-16 months for spontaneous lesions, which resulted in three recognizable precancerous lesions in the lung.” (page 7, line 138).

(2) Line 143, the authors claim to have seen "three recognizable precancerous and cancerous lesions in the lung" but then, they only go on to describe AAH, adenoma, and AIS, lesions which are all commonly recognized as precancers. What was the cancerous (i.e. invasive) lesion they identified?

Thank you for your comment. We apologize for this misstatement and will include cancerous lesions from mice for simultaneous analysis in subsequent study. The corresponding description has been revised as: “To more comprehensively mirror the tumor initiation and progression process of human lung cancer, A/J mice were maintained for 12-16 months for spontaneous lesions, which resulted in three recognizable precancerous lesions in the lung.” (page 7, line 140).

(3) Line 172, the authors say that the "proportion of cell types across the four stages showed a dynamic trend" ... what does this mean? A trend towards what exactly?

Thank you for your comment. Our intention was to highlight heterogeneous changes, and the description has been corrected: “The proportion of cell types across the four stages showed irregular changes, while transcriptional homogeneity was reduced with precancerous progression, illustrating the importance of heterogeneity in tumorigenesis and also proving the reliability of the sampling in this study.” (page 8, line 169).

(4) Line 193, the authors say cell communication "showed a tendency to malignant transformation." What does this statement mean? If they mean more cell communication occurred in the malignant lesions than the precancerous, then there is a flaw in the logic because AAH, adenoma, and AIS are all precancerous lesions. What is the sequence of evolution to malignancy the authors are assuming? Do they mean AIS is a more advanced stage of precancerous malignancy than adenoma, and adenoma is more advanced than AAH (albeit they are all precancerous lesions).

Thank you for your comments. The malignant transformation process involves multiple stages, and histological AAH is regarded as the beginning of this process. Precancerous lesions of LUAD in mice are believed to develop stepwise from AAH, adenoma, to AIS, even if the process is not necessarily completely consistent [PMID: 11235908, 32707077]. What we meant to describe was a gradual increase in the frequency of cell communication during this process. The corresponding description has been modified as: “At the evolutionary stages of precancerous LUAD, despite possible sample heterogeneity and other interference, we observed increased interactions between epithelial cells and surrounding stromal and immune cells in the microenvironment, indicating gradually frequent cell-cell communication during this process” (page 8, line 187).

(5) Immunofluorescence images in Figure 3G and Figure 4F are captured at low magnification, making it very difficult to evaluate the colocalisation data. Suggest authors provide higher magnification images.

Thank you for your suggestion. We have replaced the immunofluorescence images in Figure 3G and Figure 4F with higher magnification images.

(6) Line 284 when referencing the cell line here, the author should make it clear in the text that cells were transfected with a construct expressing S100A4. If possible, would be good to understand if the level of S100A4 expression achieved is less, similar, or greater than that seen in these cells in vivo.

Thank you for your suggestion. We have amended the text to make it clear: “S100a4-overexpressed (OE) alveolar macrophages were established by transfection of the mS100a4 vector into the murine MH-S cell line, and empty vector was transfected as negative control (NC) cells” (page 12, line 284), and it will be clarified in the following exploration whether the level of S100a4 expression achieved is less, similar, or greater than that seen in these cells in vivo.

(7) Line 285 - when the authors first refer to OE cells that have been transfected, they should also inform the reader what NC cells are i.e. negative control cells?

Thank you for your suggestion. We have revised the relevant content as follows: “S100a4-overexpressed (OE) alveolar macrophages were established by transfection of the mS100a4 vector into the murine MH-S cell line, and empty vector was transfected as negative control (NC) cells” (page 12, line 284).

(8) Line 324 - the authors claim they have demonstrated that the macrophages promote angiogenesis through upregulation of fatty acid metabolism. Whilst they may have demonstrated changes in fatty acid metabolism, no experiments assessing the effect of the macrophages in angiogenesis assays are included in the paper, so the authors should modify this statement.

Thank you for your comments. The relevant experiments have been added based on your suggestions. Firstly, we demonstrated in vitro the up-regulation of fatty acid metabolism in S100a4⁺ alv-macro and uncovered the contribution of CPT1A to angiogenesis and cell transformation through rescue experiments; Then, HUVEC tube formation assay and cytokine assay confirmed the pro-angiogenic effect of S100a4⁺ alv-macro. We have added the Results section S100a4⁺ alv-macro drove angiogenesis by promoting Cpt1a-mediated fatty acid metabolism (page 13, line 327) and added the Discussion as: “We demonstrated the regulation of fatty acid metabolism by CPT1A in S100a4⁺ alv-macro as well as the involvement of PPAR-γ. Nevertheless, the molecular mechanism that drives the acquisition of metabolic and functional switching properties specific to this cell state still requires further characterization in the context of precancerous lesions. It has been reported that CD36 is the main effector of the S100A4/PPAR-γ pathway, and its mediated fatty acid uptake plays an important role in the tumor-promoting function of macrophages (S. Liu et al., 2021).” (page 18, line 433).

All method details covered in this section have been supplemented in the Materials and methods.

(9) Regarding angiogenesis in precancerous lesions and the role of macrophages in this process: is there even any evidence that precancerous LUAD lesions are angiogenic? Don't these lesions typically have a lepidic pattern, wherein the cancer cells merely co-opt pre-existing alveolar capillaries without the need to generate new vessels?

Thank you for your comments. As you mentioned, pathologically, precancerous LUAD lesions mainly show a lepidic growth pattern, characterized by the growth of type II alveolar epithelial cells along pre-existing alveolar walls [PMID: 29690599], but this does not mean that this process does not require the formation of new blood vessels. There are multiple patterns of tumor angiogenesis. Some studies have shown that increased angiogenesis can be observed in certain precancerous lesions, which suggests that angiogenesis may play an important role in the early stages of lung cancer development. Microvessel density (MVD) was increased in AAH and AIS compared to normal lung tissue, indicating that new blood vessels are forming to provide essential nutrients and oxygen to tumor cells to support their growth. The expression level of pro-angiogenic factors such as VEGF is usually upregulated, which promotes the formation of new blood vessels by stimulating endothelial cell proliferation and migration. [PMID: 39570802, 14568684] In addition, the infiltration of macrophages into precancerous areas in response to cytokines has been shown to trigger a tumor angiogenic switch and maintain tumor-associated continuous angiogenesis [PMID: 35022204]. Our in vitro tube formation assay and cytokine assay also demonstrated angiogenesis induced by S100a4⁺ alv-macro. We have discussed the relevant content (page 19, line 449) and will provide more sufficient evidence in future work.

Discussion:

Perhaps the authors can cite any literature pertaining to the current wave of anti-macrophage therapies currently being tested in the clinic. Moreover, have these therapies been tested in lung cancer, and if so, what were the results?

Thank you for your suggestion. At present, the clinical trials of anti-macrophage therapies mainly involve Gaucher's disease and hematological malignancies, and the two tests related to lung cancer have no valid data posted. Nevertheless, there are some preclinical studies worth learning from. We have cited the relevant literature and discussed in detail: “With the elaborate resolution of TME, macrophage-related therapy is considered to be promising. So far, macrophage-targeted therapy has demonstrated clinical efficacy in Gaucher's disease and advanced hematological malignancies (Barton et al., 1991; Ossenkoppele et al., 2013). In lung cancer, an attempt to enhance anti-PD-1 therapy in NSCLC by depleting myeloid-derived suppressor cells with gemcitabine was prematurely terminated because of insufficient data collected; another clinical trial of TQB2928 monoclonal antibody promoting macrophage phagocytosis of tumor cells in combination with a third-generation EGFR TKI for advanced NSCLC is now recruiting. Moreover, preclinical studies on macrophage-targeted therapy combined with immune checkpoint inhibitors are being extensively conducted in NSCLC, and it was suggested that blockade of purine metabolism can reverse macrophage immunosuppression, and a synergetic effect can be achieved when combined with anti-PD-L1 therapy, which inspired the direction of our early intervention strategies (H. Wang, Arulraj, Anbari, & Popel, 2024; Yang et al., 2025).” (page 20, line 479).

Methods:

Further description of how lesions were classified as precancerous (AAH, adenoma, AIS) or cancerous by the pathologist should be defined (or cite appropriate reference where this is described).

Thank you for your suggestion. We have cited relevant references in the Methods section (page 21, line 528) on how lesions were classified by the pathologists [PMID: 21252716, 28951454, 32707077, 24811831].

eLife Assessment

How misfolded proteins are segregated and cleared is a significant question in cell biology, since clearance of these aggregates can protect against pathologies that may otherwise arise. The authors discover a cell cycle stage-dependent clearing mechanism that involves the ER chaperone BiP, the proteosome, and CDK inactivation, but is curiously independent of the anaphase promoting complex (APC). These are valuable and interesting new observations, but the evidence supporting these claims is partially incomplete. New experiments and/or toning down the conclusions and highlighting what has not been learned may be appropriate and can then spur more work in the field.

Reviewer #1 (Public review):

Du et al. address the cell cycle-dependent clearance of misfolded protein aggregates mediated by the endoplasmic reticulum (ER) associated Hsp70 chaperone family and ER reorganisation. The observations are interesting and impactful to the field.

Strength:

The manuscript addresses the connection between the clearance of misfolded protein aggregates and the cell cycle using a proteostasis reporter targeted to ER in multiple cell lines. Through imaging and some biochemical assays, they establish the role of BiP, an Hsp70 family chaperone, and Cdk1 inactivation in aggregate clearance upon mitotic exit. Furthermore, the authors present an initial analysis of the role of ER reorganisation in this clearance. These are important correlations and could have implications for ageing-associated pathologies. Overall, the results are convincing and impactful to the field.

Weakness:

The manuscript still lacks a mechanistic understanding of aggregate clearance. Even though the authors have provided the role of different cellular components, such as BiP, Cdk1 and ATL2/3 through specific inhibitors, at least an outline establishing the sequence of events leading to clearance is missing. Moreover, the authors show that the levels of ER-FlucDM-eGFP do not change significantly throughout the cell cycle, indicating that protein degradation is not in play. Therefore, addressing/elaborating on the mechanism of disassembly can add value to the work. Also, the physiological relevance of aggregate clearance upon mitotic exit has not been tested, nor have the cellular targets of this mode of clearance been identified or discussed.

Reviewer #2 (Public review):

This paper describes an interesting observation that ER-targeted misfolded proteins are trapped within vesicles inside nucleus to facilitate quality control during cell division. This work supports the concept that transient sequestration of misfolded proteins is a fundamental mechanism of protein quality control. The authors satisfactorily addressed several points asked in the review of first submission. The manuscript is improved but still unable to fully address the mechanisms.

Strengths:

The observations in this manuscript are very interesting and open up many questions on proteostasis biology.

Weaknesses:

Despite inclusions of several protein-level experiments, the manuscript remained a microscopy-driven work and missed the opportunity to work out the mechanisms behind the observations.

Reviewer #3 (Public review):

This paper describes a new mechanism for the clearance of protein aggregates associated to endoplasmic reticulum re-organization that occurs during mitosis.

Experimental data showing clearance of protein aggregates during mitosis is solid, statistically significant, and very interesting. The authors made several new experiments included in the revised version to address the concerns raised by reviewers. A new proteomic analysis, co-localization of the aggregates with the ER membrane Sec61beta protein, expression of the aggregate-prone protein in the nucleus does not result in accumulation of aggregates, detection of protein aggregates in the insoluble faction after cell disruption and mostly importantly knockdown of ATL proteins involved in the organization of ER shape and structure impaired the clearance mechanism. This last observation addresses one of the weakest points of the original version which was the lack of experimental correlation between ER structure capability to re-shape and the clearance mechanism.

In conclusion, this new mechanism of protein aggregate clearance from the ER was not completely understood in this work but the manuscript presented, particularly in the revised version, an ensemble of solid observations and mechanistic information to scaffold future studies that clarify more details of this mechanism. As stated by the authors: "How protein aggregates are targeted and assembled into the intranuclear membranous structure waits for future investigation". This new mechanism of aggregate clearance from the ER is not expected to be fully understood in a single work but this paper may constitute one step to better comprehend the cell capability to resolve protein aggregates in different cell compartments.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:  

Reviewer #1 (Public Review):

Strengths:

The manuscript utilizes a previously reported misfolding-prone reporter to assess its behaviour in ER in different cell line models. They make two interesting observations:

(1) Upon prolonged incubation, the reporter accumulates in nuclear aggregates.

(2) The aggregates are cleared during mitosis. They further provide some insight into the role of chaperones and ER stressors in aggregate clearance. These observations provide a starting point for addressing the role of mitosis in aggregate clearance. Needless to say, going ahead understanding the impact of aggregate clearance on cell division will be equally important.

Weaknesses:

The study almost entirely relies on an imaging approach to address the issue of aggregate clearance. A complementary biochemical approach would be more insightful. The intriguing observations pertaining to aggregates in the nucleus and their clearance during mitosis lack mechanistic understanding. The issue pertaining to the functional relevance of aggregation clearance or its lack thereof has not been addressed. Experiments addressing these issues would be a terrific addition to this manuscript.

We have performed protein blotting and proteomics to characterize ER-FlucDM-eGFP expressing cells. We have also provided evidence to support the role of ER reorganization in regulating aggregate clearance. Our proteomic analysis provided a global view of the cellular state of cells expressing ER-FlucDM-eGFP, which potentially revealed functional relevance of ER-FlucDM-eGFP. Details are explained in the following comments. 

Reviewer #2 (Public Review):

Summary:

The authors provide an interesting observation that ER-targeted excess misfolded proteins localize to the nucleus within membrane-entrapped vesicles for further quality control during cell division. This is useful information indicating transient nuclear compartmentalization as a quality control strategy for misfolded ER proteins in mitotic cells, although endogenous substrates of this pathway are yet to be identified.

Strengths:

This microscopy-based study reports unique membrane-based compartments of ERtargeted misfolded proteins within the nucleus. Quarantining aggregating proteins in membrane-less compartments is a widely accepted protein quality control mechanism. This work highlights the importance of membrane-bound quarantining strategies for aggregating proteins. These observations open up multiple questions on proteostasis biology. How do these membrane-bound bodies enter the nucleus? How are the singlelayer membranes formed? How exactly are these membrane-bound aggregates degraded? Are similar membrane-bound nuclear deposits present in post-mitotic cells that are relevant in age-related proteostasis diseases? Etc. Thus, the observations reported here are potentially interesting.

Weaknesses:

This study, like many other studies, used a set of model misfolding-prone proteins to uncover the interesting nuclear-compartment-based quality control of ER proteins. The endogenous ER-proteins that reach a similar stage of overdose of misfolding during ER stress remain unknown.

We have included a previous study that showed accumulation of BiP aggregates in the nucleus upon overexpression of BiP (Morris et al., 1997; DOI: 10.1074/jbc.272.7.4327) in the discussion (Line 299).

The mechanism of disaggregation of membrane-trapped misfolded proteins is unclear. Do these come out of the membrane traps? The authors report a few vesicles in living cells. This may suggest that membrane-untrapped proteins are disaggregated while trapped proteins remain aggregates within membranes.

We initially made mStayGold-Sec61β to image the ER structures and ER-FlucDM-eGFP aggregates. However, we could not obtain convincing time-lapse images to show the release of ER-FlucDM-eGFP aggregates from the ER membrane as there are abundant ER structures present close to the aggregates during mitosis, preventing the differentiation of the membrane encapsulating aggregates from the ER structures. 

The authors figure out the involvement of proteasome and Hsp70 during the disaggregation process. However, the detailed mechanisms including the ubiquitin ligases are not identified. Also, is the protein ubiquitinated at this stage?

We performed cycloheximide chase experiments in cells released from the G2/M and found that ER-FlucDM-eGFP protein level did not fluctuate significantly when cells progressed through mitosis and cytokinesis. Thus, we did not consider protein ubiquitination and degradation of ER-FlucDM-eGFP as a major mechanism for its clearance. We have included this observation in the results (Figure S7A; Line 266) and in the discussion (Line 324) of the revised manuscript.

This paper suffers from a lack of cellular biochemistry. Western blots confirming the solubility and insolubility of the misfolded proteins are required. This will also help to calculate the specific activity of luciferase more accurately than estimating the fluorescence intensities of soluble and aggregated/compartmentalized proteins. 

We performed solubility test in cells expressing ER-FlucDM-eGFP and detected insoluble ERFlucDM-eGFP after heat stress (Figure S1E; Line 102). We have also performed protein blotting to detect ER-FlucDM-eGFP to normalize the luciferase activity (Line 609). We have updated the method section for luciferase measurement (Line 494).   

Microscopy suggested the dissolution of the membrane-based compartments and probably disaggregation of the protein. This data should be substantiated using Western blots. Degradation can only be confirmed by Western blots. The authors should try time course experiments to correlate with microscopy data. Cycloheximide chase experiments will be useful.

We performed cycloheximide chase experiments in cells released from the G2/M and found that ER-FlucDM-eGFP protein level did not fluctuate significantly when cells progressed through mitosis and cytokinesis (Figure S7A to S7C). Also, live-cell imaging of cells released from the G2/M indicated no significant change of total fluorescence intensity of ER-FlucDMeGFP (Figure S7D). Thus, we do not think that protein degradation of ER-FlucDM-eGFP is the major mechanism for its clearance. 

The cell models express the ER-targeted misfolded proteins constitutively that may already reprogram the proteostasis. The authors may try one experiment with inducible overexpression.

We have re-transduced fresh MCF10A cells with lentiviral particles to induce expression of ER-FlucDM-eGFP. The aggregates started to form after 24 h post-transduction. We made similar observations as described in the manuscript (e.g. aggregate clearance) two days after re-transduction.

It is clear that a saturating dose of ER-targeted misfolded proteins activates the pathway.

The authors performed a few RT-PCR experiments to indicate the proteostasis-sensitivity.

Proteome-based experiments will be better to substantiate proteostasis saturation.

We have performed proteomic analysis in cells expressing ER-FlucDM-eGFP and observed up-regulation of multiple proteins involved in the ER stress response, indicating that cells expressing ER-FlucDM-eGFP experience proteostatic stress (Figure S4A; Line 179).  

The authors should immunostain the nuclear compartments for other ER-membrane resident proteins that span either the bilayer or a single layer. The data may be discussed.

We have co-expressed ER-FlucDM-mCherry and mStayGold-Sec61β and detected mStayGold- Sec61β around ER-FlucDM-mCherry aggregates (Figure 1B).  

All microscopy figures should include control cells with similarly aggregating proteins or without aggregates as appropriate. For example, is the nuclear-targeted FlucDM-EGFP similarly entrapped? A control experiment will be interesting. Expression of control proteins should be estimated by western blots.

We targeted FlucDM-eGFP to the nucleus by expressing NLS-FlucDM-eGFP (Figure S1A). We found that the nuclear FlucDM-eGFP did not co-localize with the ER-FlucDM-mCherry aggregates (Figure S1B; Line 96). We have also determined the expression levels of NLSFlucDM-eGFP and ER-FlucDM-mCherry (Figure S1C and S1D).

There are few more points that may be out of the scope of the manuscript. For example, how do these compartments enter the nucleus? Whether similar entry mechanisms/events are ever reported? What do the authors speculate? Also, the bilayer membrane becomes a single layer. This is potentially interesting and should be discussed with probable mechanisms. Also, do these nuclear compartments interfere with transcription and thereby deregulate cell division? What about post-mitotic cells? Similar deposits may be potentially toxic in the absence of cell division. All these may be discussed.

Thank you for interesting suggestions for our study. We speculated that ER-FlucDM-eGFP aggregates may derive from the invagination of the inner nuclear membrane given that the aggregates are in close proximity to the inner nuclear membrane in interpase cells (Line 299). We have included a previous study that reported a similar aggregate upon BiP overexpression (Morris et al., 1997; DOI: 10.1074/jbc.272.7.4327; Line 300). Our proteomic analysis showed that cells expressing ER-FlucDM-eGFP have several up-regulated proteins related to cell cycle regulation (Figure S4A; Line 346).  

Reviewer #3 (Public Review):

Summary:

This paper describes a new mechanism of clearance of protein aggregates occurring during mitosis.

The authors have observed that animal cells can clear misfolded aggregated proteins at the end of mitosis. The images and data gathered are solid, convincing, and statistically significant. However, there is a lack of insight into the underlying mechanism. They show the involvement of the ER, ATPase-dependent, BiP chaperone, and the requirement of Cdk1 inactivation (a hallmark of mitotic exit) in the process. They also show that the mechanism seems to be independent of the APC/C complex (anaphase-promoting complex). Several points need to be clarified regarding the mechanism that clears the aggregates during mitosis:

• What happens in the cell substructure during mitosis to explain the recruitment of BiP towards the aggregates, which seem to be relocated to the cytoplasm surrounded by the ER membrane.

We have included images to show that BiP co-localizes with ER-FlucDM-eGFP aggregates in interphase cells (Figure S5C). We think that BiP participates in the formation of ER-FlucDMeGFP during interphase instead of getting recruited to the aggregates during mitosis.  

• How the changes in the cell substructure during mitosis explain the relocation of protein aggregates during mitosis.

We provided evidence to show that clearance of ER-FlucDM-eGFP aggregates involves the ER remodeling process. We depleted ER membrane fusion proteins ATL2 and ATL3 to perturb the distribution of ER sheets or tubules and found that cells were defective in clearing the aggregates (Figure 7A and B; Line 278). 

• Why BiP seems to be the main player of this mechanism and not the cyto Hsp70 first described to be involved in protein disaggregation.

In our proteomic analysis, we found that BiP (HSPA5) but not other Hsp70 family members were up-regulated in cells expressing ER-FlucDM-eGFP (Line 352; Figure S4A). This explains why BiP is the main player of the ER-FlucDM-eGFP aggregate clearance.  

Strengths:

Experimental data showing clearance of protein aggregates during mitosis is solid, statistically significant, and very interesting.

Weaknesses:

Weak mechanistic insight to explain the process of protein disaggregation, particularly the interconnection between what happens in the cell substructure during mitosis to trigger and drive clearance of protein aggregates.

In our revised manuscript, we now provided evidence to show that ER-FlucDM-eGFP aggregate clearance involved remodeling of the ER structures during mitotic exit. This is added as a new Figure 7 in the revised manuscript and is described in the result section (Line 278) and in the discussion section (Line 323). We believe that this addition has provided mechanistic insights into ER-FlucDM-eGFP aggregate clearance.

Recommendations for the authors:

Reviewing Editor comments:

I have read these reviews in detail and would like to recommend that the authors perform the experiments according to the reviewers' suggestions, as well as provide the appropriate controls raised by the reviewers.

I think there are not that many requests and they all seem very reasonable and easily doable. I would recommend that the authors carry out the suggested experiments to develop a stronger story where the evidence transitions from being incomplete presently to a "more complete" standard.

We have addressed questions raised by three reviewers and updated our manuscript (labeled in red in the main text).

Reviewer #1 (Recommendations For The Authors):

The manuscript makes exciting observations about the accumulation of reporter protein aggregates in the nucleus and its clearance during mitosis. It also provides some insight into the role of chaperons in aggregate clearance. These observations provide a good platform to perform in-depth analysis of the underlying mechanism and its functional relevance which perhaps the authors will plan over the long term. However, the below suggestions will help improve the current version of the manuscript:

(1) Although it is assumed that the aggregates are cleared by the protein degradation mechanism, clear evidence supporting this assumption in the author's experiments is lacking and needs to be provided. Is it possible that mitosis induces disassembly of these aggregates instead of degradation?

We performed two experiments to verify whether ER-FlucDM-eGFP aggregates are cleared by the protein degradation mechanism. In the first experiment, we treated cells expressing ER-FlucDM-eGFP released from the G2/M boundary with cycloheximide (CHX) and found that ER-FlucDM-eGFP did not decrease in protein abundance in cells progressing through mitosis (Figure S7A to S7C). In the second experiment, we measured the intensity of ERFlucDM-eGFP in early dividing cells and late dividing cells after release from the G2/M boundary and found that there was no significant difference between early and late dividing cells (Figure S7D). Thus, we concluded that protein degradation of ER-FlucDM-eGFP is not the primary mechanism of its clearance during cell division (Line 324). Furthermore, we included new data to show that the ER-FlucDM-eGFP aggregate clearance depends on ER reorganization during cell division, so mitotic exit induces disassembly of the aggregates instead of protein degradation.

(2) It is intriguing that the aggregates are nuclear. Is the nuclear localization mediated by localization to ER? A time course analysis would reveal this and would provide credence to the idea that the reporter was originally expressed in the ER. It is currently unclear if the reporter ever gets expressed in ER.

We showed that in interphase cells, ER-FlucDM-eGFP co-localizes with mStayGold-Sec61β, which labels the ER structures (Figure 1B). So, ER-FlucDM-eGFP is expressed and present in the ER network and invaginates into the inner nuclear membrane as aggregates. We attempted to image ER-FlucDM-eGFP for its formation; however it was technically challenging as the aggregates appeared very small and not too visible after clearance under our microscopy system.  

(3) It would be expected that the persistence of these aggregates would impact cell division and cellular health. An experiment addressing this hypothesis would be very useful in establishing the functional relevance of this observation in the context of the current study.

We have performed proteomic analysis on cell expressing ER-FlucDM-eGFP and found that multiple proteins involved in the ER stress response were up-regulated (Figure S4A). Additionally, proteins related to cell cycle regulation were up-regulated upon expression of ER-FlucDM-eGFP (Figure S4A). The increase of these proteins may indicate a perturbed cellular health (Line 344). 

(4) A recent report (PMID: 34467852) identified the role of ER tubules in controlling the size of certain misfolded condensates. Would specific ER substructures affect the nuclear localization and/or clearance of the FlucDM aggregates? This is tied to point#2 and would provide insights into the connection between ER and the nuclear aggregates.

Thank you for your suggestions. We perturbed the ER remodeling process by knocking down ATL2 and ATL3, which are ER membrane fusion proteins, and found that clearance of ER-FlucDM-eGFP aggregates was affected (Figure 7A and B). Hence, perturbation of the distribution of ER tubules and ER sheets affects ER-FlucDM-eGFP aggregate clearance. We have also added the recent paper about ER tubule size in regulating the sizes of misfolded condensates in the discussion (Line 321)

Reviewer #2 (Recommendations For The Authors):

I expect that the images indicate z-sections. Should be indicated in legends as applicable.

We have indicated whether the images are Z-stack or single Z-slices in the figure legends.  

Small point: the control region (outside inclusion) that was bleached in 2c may be clearly indicated. 

We have added the explanation in the figure legend of Figure 2C.

eLife Assessment

Cardiolipin is known to play an important role in modulating the assembly and function of membrane proteins in bacterial and mitochondrial membranes. Here, authors convincingly define the molecular determinants of cardiolipin binding on de novo-designed and native membrane proteins combining the coarse-grained molecular dynamics simulation with the state-of-the-art experimental approaches such as native mass spectrometry and cryogenic electron microscopy. The major findings in this study, which are the identification of degenerate cardiolipin binding motifs, the characterization of their dynamic features, and the role in membrane protein stability and activity, will provide much needed insight into the still poorly understood nature of protein-cardiolipin interactions.

Reviewer #1 (Public review):

Summary:

The study combines predictions from MD simulations with sophisticated experimental approaches including native mass spectrometry (nMS), cryo-EM, and thermal protein stability assays to investigate the molecular determinants of cardiolipin (CDL) binding and binding-induced protein stability/function of an engineered model protein (ROCKET), as well as of the native E. coli intramembrane rhomboid protease, GlpG.

Strengths:

State-of-the-art approaches and sharply focused experimental investigation lend credence to the conclusions drawn. Stable CDL binding is accommodated by a largely degenerate protein fold that combines interactions from distant basic residues with greater intercalation of the lipid within the protein structure. Surprisingly, there appears to be no direct correlation between binding affinity/occupancy and protein stability.

Overall, using both model and native protein systems, this study convincingly underscores the molecular and structural requirements for CDL binding and binding-induced membrane protein stability. This work provides much-needed insight into the poorly understood nature of protein-CDL interactions.

Reviewer #3 (Public review):

Summary:

The relationships of proteins and lipids: it's complicated. This paper illustrates how cardiolipins can stabilize membrane protein subunits - and not surprisingly, positively charged residues play an important role here. But more and stronger binding of such structural lipids does not necessarily translate to stabilization of oligomeric states, since many proteins have alternative binding sites for lipids which may be intra- rather than intermolecular. Mutations which abolish primary binding sites can cause redistribution to (weaker) secondary sites which nevertheless stabilize interactions between subunits. This may be at first sight counterintuitive but actually matches expectations from structural data and MD modelling. An analogous cardiolipin binding site between subunits is found in E.coli tetrameric GlpG, with cardiolipin (thermally) stabilizing the protein against aggregation.

Strengths:

The use of the artificial scaffold allows testing of hypothesis about the different roles of cardiolipin binding. It reveals effects which are at first sight counterintuitive and are explained by the existence of a weaker, secondary binding site which unlike the primary one allows easy lipid-mediated interaction between two subunits of the protein. Introducing different mutations either changes the balance between primary and secondary binding sites or introduced a kink in a helix - thus affecting subunit interactions which are experimentally verified by native mass spectrometry.

[Editors' note: The reviewers agreed that the authors addressed all reviewer comments adequately and rigorously.]

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

The study combines predictions from MD simulations with sophisticated experimental approaches including native mass spectrometry (nMS), cryo-EM, and thermal protein stability assays to investigate the molecular determinants of cardiolipin (CDL) binding and binding-induced protein stability/function of an engineered model protein (ROCKET), as well as of the native E. coli intramembrane rhomboid protease, GlpG.

Strengths:

State-of-the-art approaches and sharply focused experimental investigation lend credence to the conclusions drawn. Stable CDL binding is accommodated by a largely degenerate protein fold that combines interactions from distant basic residues with greater intercalation of the lipid within the protein structure. Surprisingly, there appears to be no direct correlation between binding affinity/occupancy and protein stability.

Weaknesses:

(i) While aromatic residues (in particular Trp) appear to be clearly involved in the CDL interaction, there is no investigation of their roles and contributions relative to the positively charged residues (R and K) investigated here. How do aromatics contribute to CDL binding and protein stability, and are they differential in nature (W vs Y vs F)?

Based on the simulations in Corey et al (Sci Adv 2021), aromatic residues, especially tryptophan, appear to help provide a binding platform for the glycerol moiety of CDL which is quite flat. This interaction is likely why we generally see the tryptophan slightly further into the plane of the membrane than the basic residues, where it may help to orient the lipid. Unlike charge interactions with lipid head groups, such subtle contributions are likely distorted by the transfer to the gas phase, making it difficult to confidently assign changes in stability or lipid occupancy to interactions with tryptophan. We have added an explanation of these considerations to the Discussion section (page 13, last paragraph).

(ii) In the case of GlpG, a WR pair (W136-R137) present at the lipid-water on the periplasmic face (adjacent to helices 2/3) may function akin to the W12-R13 of ROCKET in specifically binding CDL. Investigation of this site might prove to be interesting if it indeed does.

Thank you for the suggestion. In our CG simulations, we don’t see significant CDL binding at this site, likely because there is just a single basic residue. We note that there is a periplasmic site nearby with two basic residues (K132+K191+W125) with a higher occupancy, however still far lower than the identified cytoplasmic site. In general, periplasmic sites are less common and/or have lower affinity which may be related to leaflet asymmetry (Corey et al, Sci Adv 2021). We added the CDL density plot for the periplasmic side to Figure S7 and noted this on page 9, next-to-last paragraph.

(iii) Examples of other native proteins that utilize combinatorial aromatic and electrostatic interactions to bind CDL would provide a broader perspective of the general applicability of these findings to the reader (for e.g. the adenine nucleotide translocase (ANT/AAC) of the mitochondria as well as the mechanoenzymatic GTPase Drp1 appear to bind CDL using the common "WRG' motif.)

Several confirmed examples are presented in Corey et al (Sci Adv 2021), the dataset which we used to identify the CDL site in GlpG. So essentially, our broader perspective is that we test the common features observed in native proteins in an artificial system. While it is not clear how a peripheral membrane protein like Drp1 fits into this framework, the CDL binding sites in ANTs indeed have the same hallmarks as the one in GlpG (Hedger et al, Biochemistry 2016). We recently contributed to a study demonstrating that the tertiary structure of ANT Aac2 is stabilized by co-purified CDL molecules, underscoring the general validity of our findings (Senoo et al, EMBO J 2024).  We have added this information to the discussion, pg 12, third paragraph, and added a figure (S8, see below) to highlight the architecture of the Aac2-CDL complex.

Overall, using both model and native protein systems, this study convincingly underscores the molecular and structural requirements for CDL binding and binding-induced membrane protein stability. This work provides much-needed insight into the poorly understood nature of protein-CDL interactions.

We thank the reviewer for the positive assessment!

Reviewer #2 (Public review):

Summary:

The work in this paper discusses the use of CG-MD simulations and nMS to describe cardiolipin binding sites in a synthetically designed, that can be extrapolated to a naturally occurring membrane protein. While the authors acknowledge their work illuminates the challenges in engineering lipid binding they are able to describe some features that highlight residues within GlpG that may be involved in lipid regulation of protease activity, although further study of this site is required to confirm it's role in protein activity.

Comments

Discrepancy between total CDL binding in CG simulations (Fig 1d) and nMS (Fig 2b,c) should be further discussed. Limitations in nMS methodology selecting for tightest bound lipids?

We thank the reviewer for pointing out that this needs to be clarified. We analyze proteins in detergent, which is in itself delipidating, because detergent molecules compete with the lipids for binding to the protein, an effect that can be observed in MS (Bolla et al, Angew Chemie Int. Ed. 2020). Native MS of membrane proteins requires stripping of the surrounding lipid vesicle or detergent micelle in the vacuum region of the mass spectrometer, which is done through gentle thermal activation in the form of high-energy collisions with gas molecules. Detergent molecules and lipids not directly in contact with the protein generally dissociate easier than bound lipids (Laganowsky et al, Nature 2014), however, the even loosely bound lipids can readily dissociate with the detergent, artificially reducing occupancy. The nMS data is therefore likely biased towards lipids bound tightly (e.g. via electrostatic headgroup interactions), however, these are the lipids we are interested in, meaning that the use of MS is suitable here. We have noted this in the Discussion, last paragraph on page 12.

Mutation of helical residues to alanine not only results in loss of lipid binding residues but may also impact overall helix flexibility, is this observed by the authors in CG-MD simulations? Change in helix overall RMSD throughout simulation? The figures shown in Fig.1H show what appear to be quite significant differences in APO protein arrangement between ROCKET and ROCKET AAXWA.

For most of the study, we use CG with fixed backbone bead properties as well as an elastic network to maintain tertiary structure. This means that a mutation to alanine will have essentially no impact on the stability of the helix or protein in general in the CG simulations in the bilayer. It should be noted that Figure 1H shows snapshots from atomistic gas phase simulations with pulling force applied (see schematic in Figure 1F, as well as Figure S1 for ends-point structures), where we naturally expect large structural changes due to unfolding. We have analyzed the helix content in the gas-phase simulations and see that helix 1 in ROCKET unwinds within 10 ns but stays helical ca. 10 ns longer when bound to CDL. The AAWXA mutation stabilizes the helical conformation independently of CDL binding, but CDL tethers the folded helix closer to the core (see Figure 1 G and H). We have added this information to the results section and the plot below to Figure S2.

CG-MD force experiments could be corroborated experimentally with magnetic tweezer unfolding assays as has been performed for the unfolding of artificial protein TMHC2. Alternatively this work could benefit to referencing Wang et al 2019 "On the Interpretation of Force-Induced Unfolding Studies of Membrane Proteins Using Fast Simulations" to support MD vs experimental values.

We apologize for the confusion here. The force experiments are gas-phase all-atom MD. The simulations show that the protein-lipid complex has a more stable tertiary structure in the gas phase. Since these are gas-phase simulations, they cannot be corroborated using in-solution measurements. Similarly, the paper by Wang et al is a great reference for solution simulations, however, to date the only validations for gas-phase unfolding come from native MS.

Did the authors investigate if ROCKET or ROCKETAAXWA copurifies with endogenous lipids? Membrane proteins with stabilising CDL often copurify in detergent and can be detected by MS without the addition of CDL to the detergent solution. Differences in retention of endogenous lipid may also indicate differences in stability between the proteins and is worth investigation.

We have investigated the co-purification of the ROCKET variants and did not observe any co-purified lipids (see Figure S4) which we clarified in the results section (page 5, third paragraph) now. We previously showed that long residence times in CG-MD are linked to the observation of co-purified lipids, because they are not easily outcompeted by the detergent (Bolla et al, Angew Chemie Int. Ed. 2020). In CG-MD of ROCKET, we see that although the CDL sites are nearly constantly occupied, the CDL molecules are in rapid exchange with free CDL from the bulk membrane. For MS, all ROCKET proteins were extracted from the E. coli membrane fraction with DDM, which likely outcompetes CDL. This interpretation would explain why we see significant CDL retention when the protein is released from liposomes, but not when the protein is first extracted into detergent. For GlpG, CDL residence times in CG-MD  are longer, which agrees with CDL co-purification. Similarly, there is clearly an enrichment of CDL when the protein is extracted into nanodiscs (Sawczyc et al, Nature Commun 2024).

Do the AAXWA and ROCKET have significantly similar intensities from nMS? The AAXWA appears to show slightly lower intensities than the ROCKET.

We did not observe a significant difference, however, in most spectra, the AAXWA peaks have a lower intensity than those of the other variants (see e.g. Figure S5). While this could be batch-to-batch variations, there may be a small contribution from the lower number of basic residues (see Abramsson et al, JACS au 2021). However, there is an excess of basic residues in the soluble domain of ROCKET, so this interpretation is speculative.

Can the authors extend their comments on why densities are observed only around site 2 in the cryo-em structures when site 1 is the apparent preferential site for ROCKET.

We base the lipid preference of Site 1 > Site 2 on the CG MD data, where we see a higher occupancy for site 1. At the same time, as noted in the text, CDL at both sites have rather short residence times. When the protein is solubilized in detergent, these times can change, and lipids in less accessible sites (such as cavities and subunit interfaces) may be subject to a slower exchange than those that are fully exposed to the micelle (Bolla et al, Angew Chemie Int. Ed. 2020). We speculate that this effect may favor retaining a lipid at site 2. Furthermore, site 1 is flexible, with CDL attaching in various angles while site 2 has more uniform CDL orientations (see CDL density plot in Figure 1D). EM is likely biased towards the less flexible site. Notably, the density is still poorly defined, so it is possible that a more variable lipid position in site 1 would not yield a notable density at all. We have added this information to the Results section (page 5, second paragraph).

The authors state that nMS is consistent with CDL binding preferentially to Site 1 in ROCKET and preferentially to Site 2 in the ROCKET AAXWA variant, yet it unclear from the text exactly how these experiments demonstrate this.

As outlined in the previous answer, we base our assessment of the sites on the CG MD simulations. There, we note that CDL binds predominantly to site 1 in ROCKET and predominantly to site 2 in AAXWA, however, the overall occupancy is lower in AAXWA than in Rocket, meaning fewer lipids will be bound simultaneously in that variant. The nMS data show CDL retention by both variants when released from liposomes, but the AAXWA has lower-intensity CDL adduct peaks (Figure 2B, C). We interpret this that both have CDL sites, but in the AAXWA variant, the sites have lower occupancy. We agree that this observation does not demonstrate that the CG MD data are correct, however, it is the outcome one expects based on the simulations, so we described it as “consistent with the simulations”. We have rephrased the section to make this clear.

As carried out for ROCKET AAXWA the total CDL binding to A61P and R66A would add to supporting information of characterisation of lipid stabilising mutations.

We considered this possibility too. Unfortunately, the mass differences between A61P / R66A and AAXWA are slightly too high to unambiguously resolve CDL adducts of each variant, as the 1st CDL peak of AAWXA partially overlaps with the apo peak of A61P or R66A.

Did the authors investigate a double mutation to Site 2 (e.g. R66A + M16A)?

While designing mutants, we tested several double mutants involving the basic residues that bind the CDL headgroups (e.g. R66 + AAWXA) but found that they could not be purified, probably because a minimum of positive residues at the N-terminus is required for proper membrane insertion and folding. M16 is an interesting suggestion, but wasn’t considered because the more subtle effects of non-charged amino acids on CDL binding may be lost during desolvation (see also our response to Comment (i) from reviewer 1).

Was the stability of R66A ever compared to the WT or only to AAXWA?

Some of the ROCKET mutants have very similar masses that cannot be resolved well enough on the ToF instrument. While the R66-WT comparison is possible, we would not be able to compare it to R61P or D7A/S8R. To avoid three-point comparisons, we selected AAXWA as the common point of reference for all variants.

How many CDL sites in the database used are structurally verified?

At the time, 1KQF was the only verified E. coli protein with a CDL resolved in a high-resolution structure. The complex was predicted accurately, see Figure 6A in Corey et al (Sci Adv 2021), as were several non-E. coli complexes.

The work on GlpG could benefit from mutagenesis or discussion of mutagenesis to this site. The Y160F mutation has already been shown to have little impact on stability or activity (Baker and Urban Nat Chem Biol. 2012).

We thank the referee for their excellent suggestion. While Y160F did not have a pronounced effect, the other 3 positions of the predicted CDL binding site in GlpG have not been covered by Baker and Urban. Looking at sequence conservation in GlpG orthologs, manually sampling down to 50% identity (~1300 sequences in Uniprot) shows that Y160 and K167 are conserved, R92 varies between K/R/Q, whereas W98 is not conserved. The other (weak) site cited above (K132 and K191) is not conserved. A detailed investigation of how the conserved residues impact CDL binding and activity is already planned for a follow up study focusing on GlpG biology.

Reviewer #3 (Public review):

Summary:

The relationships of proteins and lipids: it's complicated. This paper illustrates how cardiolipins can stabilize membrane protein subunits - and not surprisingly, positively charged residues play an important role here. But more and stronger binding of such structural lipids does not necessarily translate to stabilization of oligomeric states, since many proteins have alternative binding sites for lipids which may be intra- rather than intermolecular. Mutations which abolish primary binding sites can cause redistribution to (weaker) secondary sites which nevertheless stabilize interactions between subunits. This may be at first sight counterintuitive but actually matches expectations from structural data and MD modelling. An analogous cardiolipin binding site between subunits is found in E.coli tetrameric GlpG, with cardiolipin (thermally) stabilizing the protein against aggregation.

“It’s complicated” We could not have phrased the main conclusions of our study better.

Strengths:

The use of the artificial scaffold allows testing of hypothesis about the different roles of cardiolipin binding. It reveals effects which are at first sight counterintuitive and are explained by the existence of a weaker, secondary binding site which unlike the primary one allows easy lipid-mediated interaction between two subunits of the protein. Introducing different mutations either changes the balance between primary and secondary binding sites or introduced a kink in a helix - thus affecting subunit interactions which are experimentally verified by native mass spectrometry.

Weaknesses:

The artificial scaffold is not necessarily reflecting the conformational dynamics and local flexibility of real, functional membrane proteins. The example of GlpG, while also showing interesting cardiolipin dependency, illustrates the case of a binding site across helices further but does not add much to the main story. It should be evident that structural lipids can be stabilizing in more than one way depending on how they bind, leading to different and possibly opposite functional outcomes.

We share the reviewer’s concern, as we clearly observe that TMHC4_R does not have the same type of flexibility as a natural protein. We find that by introducing flexibility, we start to see CDL-mediated effects. To test the valIdity of our findings from the artificial system, we apply them to GlpG. In response to a suggestion from Reviewer 1, we compared the findings to Aac2, and found that its stabilizing CDL site closely resembles that in GlpG (see new Figure S8).

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Minor comments:

There are a number of typos/uncorrected statements in the text.

i) The last sentence of the Abstract appears to be an uncorrected mishmash of two.

ii) Line 66: "protects" should be just "protect"

iii) Line 75: Sentence appears to be incomplete. "...associated changes in protein stability." The word "stability" is missing.

We have made these changes.

iv) Fig. 2E. Are the magenta and blue colors inverted for variants 1 and 2?

No, the color is correct. greater stabilization of the blue tetramer (AAXAW) compared to WT (purple) will lead to fewer blue monomoers than purple monomers in the mass spectrum.

v) Line 274: the salt bridge should be between R8-E68.

We have corrected this.

vi) Lines 350-354 (final sentence of the paragraph): The sentence does not read well (especially with the double negative element). Please reconstruct the sentence and/or break it into two. 

We have split the sentence in two.

Suggestions:

(i) While aromatic residues (in particular Trp) appear to be clearly involved in the CDL interaction, there is no investigation of their roles and contributions relative to the positively charged residues (R and K) investigated here. How do aromatics contribute to CDL binding and protein stability, and are they differential in nature (W vs Y vs F)?

See our response to comment (i) from reviewer 1. In short, subtle contribution to lipid interactions (such as pi stacking with Trp or Tyr) will likely be lost during transfer to the gas phase. However, see also our response to the last comment from reviewer 2, we plan to use solution-phase activity assays to investigate the effect of Trp on CDL binding to Glp. However, this is beyond thes cope oif the current study.

(ii) In the case of GlpG, a WR pair (W136-R137) present at the lipid-water on the periplasmic face (adjacent to helices 2/3) may function akin to the W12-R13 of ROCKET in specifically binding CDL. Investigation of this site might prove to be interesting if it indeed does.

We added the CDL density plot for the periplasmic side to Figure S7 and discuss further sites in GlpG in the Discussion section. See response to point (ii) above for details.

Reviewer #2 (Recommendations for the authors):

Minor comments

- Typo in abstract line 39-40

- Typo in figure legend of Fig 1 line 145

- Typo in line 149, missing R66 in residues shown as sticks description

- Lines 165-167 could benefit from describing what residues are represented as sticks

We have made these changes.

- Line 263 should refer to the figure where the tetrameric state was not affected by this mutation.

The full spectrum of the A61P mutant is not included in the figure, hence there is no reference,

- Addition of statistics to Fig. 4F ?

We have added significance indicators to the graph and information about the statistics to the legend.

Reviewer #3 (Recommendations for the authors):

Minor issues

l39: rewrite

We have made these changes.

l60: provide evidence for what is presented as a general statement - cardiolipins might also regulate function without affecting oligomeric state, e.g. MgtA

This is a good point, we have added references to two examples where CDL work without affecting oligomerization (MtgA, Weikum et al BBA 2024, and Aac2, Senoo et al, EMBO J 2024).

l74: not every functional interaction comes with a thermal shift

We use thermal shift as a proxy because it indicates tight interactions, even if they may not be functional. We have made this distinction clearer in the text.

l78: this is true for electrostatic interactions such as are at play here, but not necessarily for hydrophobic ones

l133: in what direction is the pulling force applied - the figure seems to suggest diagonally?

The pull coordinate is defined as the distance between the centers of mass of the two helices. The direction of the pull coordinate in Cartesian coordinate space is thus not fixed.

fig 1f, l159: "dissociating" meaning separation of subunits? the placement of the lipid within one subunit would not suggest that intermolecular interactions are properly represented here, please clarify

The lipid placement in the schematic is not representative since the lipid occupies different spaces in WT and AAXWA, we have noted this in the legend. Regarding line 159, “Dissociation” is not strictly correct, since the measure the force to separate helix 1 and 2, i.e. unfolding. We have changed the wording to “unfolding”.

l173: was there any evidence in EM data for monomers or smaller oligomers?

No smaller particles were identified by visual inspection or in the particle classes. We have noted this in the methods section.

l203: were tetramer peaks isolated separately for CID?

C8E4 can cause some activation-dependent charge reduction, which could allow some tetramers to “sneak out” of the isolation window. We used global activation without precursor selection which subjects all ions to activation.

fig 2c: can you indicate the 3rd lipid binding as it seems to be in the noise

We can unambiguously assign the retention of three CDL molecules for 17+ charge state only, and clarified this in the legend to Figrue 2.

fig3: can you pls clarify what is meant by stabilization here - less monomer in case A means a more stable oligomer, but "A > B" should lead to ratios < 50%. This does not help with understanding what "stabilization" means in panels c-f, please define what the y axis means for these. Please also explain the bottom panels (side view) in each case, what do the dots represent?

We apologize for the oversight of not explaining the side views, we have added a legend. The schematic in panel A is correct (compare the schematic in Figure 2 E). If tetramer A (blue) is stabilized by CDL more than tetramer B  “CDL stabilization A>B”), there will be fewer monomers ejected from A. If there is less A in the presence of CDL, then the ratio of B/(B+A) will go up.

It is not very clear what consequences the kink introduced by proline has for intra- vs. intermolecular interactions - the cartoons don't help much here

We agree, the A61P impact on the structure is subtle. The small kink it introduces is not really visible in the top view, and hence, we tried to emphasize this in the side view. We have clarified the meaning of the side view schematics in the legend.

l360: is that an assumption made here or is there evidence for displacement? native MS could potentially prove this.

This is an assumption based on the fact that we see very little binding of POPG in the mixed bilayer CG-MD. We have clarified this in the text. Measuring this with MS is an interesting idea, but we have no direct measurement of displacement, since addition of CDL and POPG to the protein in detergent would result in binding to other sites as well.

fig 4d: there is not much POPG density visible at all - why is that?

Both plots use the same absolute scale. There is simply much less POPG binding compared to CDL.

fig 4e: is this released protein already dissociated into monomers due to denaturation or excessive energy (CID product) - please comment.

The CID energy for the spectrum in Figure 4E was selected to show partial dissociation and monomer release at higher voltages (220V in this case). At lower voltages (150V-170V) we do not observe dissociation in C8E4, see Figure S4A.

l363: pls comment on the apparent discrepancy between single lipid binding and double density

We added a clarifying sentence regarding the double lipids. The density seen in the published structure is of four lipid tails next to each other, which is what one would expect for a CDL. Since the CDL could not be resolved unambiguously, two phospholipids with two acyl chains each were modeled into the density instead. Our MS and MD data strongly suggests that the density stems from a single CDL.

eLife Assessment

This important study provides insights into the role of maternal behavior in the learning and ontogeny of vocalization. It finds evidence that the maternal behavior of sac-winged bats (Saccopteryx bilineata) can influence the learned territorial songs of their pups. The behavioral analyses are convincing, using longitudinal acoustic recordings and behavioral monitoring of individual mother-pup pairs across development and multiple wild bat colonies. The work will be relevant to a broad audience interested in the evolution and development of social behavior as well as sensory-motor learning.

Reviewer #1 (Public review):

Summary:

Fernandez et al. investigate the influence of maternal behavior on bat pup vocal development in Saccopteryx bilineata, a species known to exhibit vocal production learning. The authors performed detailed longitudinal observations of wild mother-pup interactions to ask whether non-vocal maternal displays during juvenile vocal practice, or 'babbling', affect vocal production. Specifically, the study examines the durations of pup babbling events and the developmental babbling phase, in relation to female display rates, as well as pup age and the number of nearby singing adult males. Furthermore, the authors examine pup vocal repertoire size and maturation in relation to maternal display rates encountered during babbling. Statistical models identify female display behavior as a predictor of i) babbling bout duration, ii) the length of the babbling phase, iii) song composition and iv) syllable maturation. Notably, these outcomes were not influenced by the number of nearby adult males (the pups' source of song models) and were largely independent of general maturation (pup age). These findings highlight the impact of non-vocal aspects of social interactions in guiding mammalian vocal development.

Strengths:

Historically, work on developmental vocal learning has focused on how juvenile vocalizations are influenced by the sounds produced by nearby adults (often males). In contrast, this study takes the novel approach of examining juvenile vocal ontogeny in relation to non-vocal maternal behavior, in one of the few mammals known to exhibit vocal production learning. The authors collected an impressive dataset from multiple wild bat colonies in two Central American countries. This includes longitudinal acoustic recordings and behavioral monitoring of individual mother-pup pairs, across development.

The identified relationships between maternal behavior and bat pup vocalizations have intriguing implications for understanding the mechanisms that enable vocal production learning in mammals, including human speech acquisition. As such, these findings are likely be relevant to a broad audience interested in the evolution and development of social behavior as well as sensory-motor learning.

Weaknesses:

The authors qualitatively describe specific patterns of female displays during pup babbling, however, subsequent quantitative analyses are based on aggregate measures of female behavior that pool across display types. Consequently, it remains unclear how certain maternal behaviors might differentially influence pup vocalizations (e.g. through specific feedback contingencies or more general modulation of pup behavioral states).

Comments on revisions:

(1) More detailed analyses of female behavior may be beyond the scope of this study, given the nature of the dataset/recordings. I look forward to the authors' future work on this aspect.

By addressing the important distinction between display number vs. display rate, the authors have provided more direct support for the claim that babbling behavior is related to female displays.

(2) The additional information regarding exposure to adult male song is appreciated.

(3) Added discussion of pup sex differences provides useful context and intriguing speculation about the role of female pup babbling.

(4) The authors' additions have significantly improved the clarity of their acoustic terminology and syllable analyses.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

Fernandez et al. investigate the influence of maternal behavior on bat pup vocal development in Saccopteryx bilineata, a species known to exhibit vocal production learning. The authors performed detailed longitudinal observations of wild mother-pup interactions to ask whether non-vocal maternal displays during juvenile vocal practice or 'babbling', affect vocal production. Specifically, the study examines the durations of pup babbling events and the developmental babbling phase, in relation to the amount of female display behavior, as well as pup age and the number of nearby singing adult males. Furthermore, the authors examine pup vocal repertoire size and maturation in relation to the number of maternal displays encountered during babbling. Statistical models identify female display behavior as a predictor of i) babbling bout duration, ii) the length of the babbling phase, iii) song composition, and iv) syllable maturation. Notably, these outcomes were not influenced by the number of nearby adult males (the pups' source of song models) and were largely independent of general maturation (pup age). These findings highlight the impact of non-vocal aspects of social interactions in guiding mammalian vocal development.

We thank Reviewer 1 for the time and effort dedicated to the revision of our study. The suggestions for the revision of our manuscript were very helpful and have improved our manuscript considerably. 

Strengths:

Historically, work on developmental vocal learning has focused on how juvenile vocalizations are influenced by the sounds produced by nearby adults (often males). In contrast, this study takes the novel approach of examining juvenile vocal ontogeny in relation to non-vocal maternal behavior, in one of the few mammals known to exhibit vocal production learning. The authors collected an impressive dataset from multiple wild bat colonies in two Central American countries. This includes longitudinal acoustic recordings and behavioral monitoring of individual mother-pup pairs, across development.

The identified relationships between maternal behavior and bat pup vocalizations have intriguing implications for understanding the mechanisms that enable vocal production learning in mammals, including human speech acquisition. As such, these findings are likely to be relevant to a broad audience interested in the evolution and development of social behavior as well as sensory-motor learning.

We thank reviewer 1 for this assessment. 

Weaknesses:

The authors qualitatively describe specific patterns of female displays during pup babbling, however, subsequent quantitative analyses are based on two aggregate measures of female behavior that pool across display types. Consequently, it remains unclear how certain maternal behaviors might differentially influence pup vocalizations (e.g. through specific feedback contingencies or more general modulation of pup behavioral states).

In analyzing the effects of maternal behavior on song maturation, the authors focus on the most common syllable type produced across pups. This approach is justified based on the syllable variability within and across individuals, however, additional quantification and visual presentation of categorized syllable data would improve clarity and potentially strengthen resulting claims.

We agree that our analysis of maternal behaviour does not investigate potential contingencies between particular maternal behavioural displays and pup vocalizations (e.g. particular syllable types). Our data collected for this study on maternal behaviour includes direct observations, field notes and/or video recordings. In the future, it will be necessary to work with high-speed cameras for the analysis of potential contingencies between particular maternal behavioural displays and specific pup vocalizations, which allow this kind of fine-detailed analysis. We have planned future studies investigating whether pup vocalizations elicit contingent maternal responses or vice versa. In the revision of our manuscript, we have included a comment pointing out that this special behaviour will be investigated in greater detail in the future. 

As suggested by reviewer 1, in our revised manuscript we have included more information on methods to improve understandability. In particular, we have:

-presented more information on different steps of our acoustic analyses

-provided additional and clearer spectrogram figures representing the different syllable types and categorizations 

-changed the figures accompanying our GLMM analyses following the suggestion of Reviewer 1

Reviewer #2 (Public review):

Summary:

This study explores how maternal behaviors influence vocal learning in the greater sac-winged bat (Saccopteryx bilineata). Over two field seasons, researchers tracked 19 bat pups from six wild colonies, examining vocal development aspects such as vocal practice duration, syllable repertoire size, and song syllable acquisition. The findings show that maternal behaviors significantly impact the length of daily babbling sessions and the overall babbling phase, while the presence of adult male tutors does not.

The researchers conducted detailed acoustic analyses, categorizing syllables and evaluating the variety and presence of learned song syllables. They discovered that maternal interactions enhance both the number and diversity of learned syllables and the production of mature syllables in the pups' vocalizations. A notable correlation was found between the extent of acoustic changes in the most common learned syllable type and maternal activity, highlighting the key role of maternal feedback in shaping pups' vocal development.

In summary, this study emphasizes the crucial role of maternal social feedback in the vocal development of S. bilineata. Maternal behaviors not only increase vocal practice but also aid in acquiring and refining a complex vocal repertoire. These insights enhance our understanding of social interactions in mammalian vocal learning and draw interesting parallels between bat and human vocal development.

We thank reviewer 2 for his/her time and effort dedicated to the revision of our study. The suggestions were very helpful in improving our manuscript. 

Strengths:

This paper makes significant contributions to the field of vocal learning by looking at the role of maternal behaviors in shaping the vocal learning phenotype of Saccopteryx bilineata. The paper uses a longitudinal approach, tracking the vocal ontogeny of bat pups from birth to weaning across six colonies and two field seasons, allowing the authors to assess how maternal interactions influence various aspects of vocal practice and learning, providing strong empirical evidence for the critical role of social feedback in non-human mammalian vocal learners. This kind of evidence highlights the complexity of the vocal learning phenotype and shows that it goes beyond the right auditory experience and having the right circuitry.

The paper offers a nuanced understanding of how specific maternal behaviors impact the acquisition and refinement of the vocal repertoire, while showing the number of male tutors - the source of adult song - did not have much of an effect. The correlation between maternal activity and acoustic changes in learned syllable types is a novel finding that underscores the importance of non-vocal social interactions in vocal learning. In vocal learning research, with some notable exceptions, experience is often understood as auditory experience. This paper highlights how, even though that is one important piece of the puzzle, other kinds of experience directly affect the development of vocal behavior. This is of particular importance in the case of a mammalian species such as Saccopteryx bilineata, as this kind of result is perhaps more often associated with avian species.

Moreover, the study's findings have broader implications for our understanding of vocal learning across species. By drawing parallels between bat and human vocal development (and in some ways to bird vocal development), the paper highlights common mechanisms that may underlie vocal practice and learning in both humans and other mammals. This interdisciplinary perspective enriches the field and encourages further comparative studies, ultimately advancing our knowledge of the evolutionary and developmental processes that shape vocal productive learning in all its dimensions.

We thank reviewer 2 for this assessment. 

Weaknesses:

Some weaknesses can be pointed out, but in fairness, the authors acknowledge them in one way or another. As such, these are not flaws per se, but gaps that can be filled with further research.

Experimental manipulations, such as controlled playback experiments or controlled environments, could strengthen the causal claims by directly testing the effects of specific maternal behaviors on vocal development. Certainly, the strengths of the paper will be consolidated after such work is performed.

The reliance on the number of singing males as a proxy for social acoustic input. This measure does not account for the variability in the quality, frequency, or duration of the male songs to which the pups are exposed. A more detailed analysis of the acoustic environment, including direct measurements of song exposure and its impact on vocal learning, would provide a clearer understanding of the role of male tutors.

Finally, and although it would be unlikely that these results are unique to Saccopteryx bilineata, the study's focus on a single species limits at present the generalizability of some of its findings to other vocal learning mammals. While the parallels drawn between bat and human vocal development are intriguing, the conclusions will be more robust when supported by comparative studies involving multiple species of vocal learners. This will help to identify whether the observed maternal influences on vocal development reported here are unique to Saccopteryx bilineata or represent a broader phenomenon in chiropteran, mammalian, or general vocal learning. Expanding the scope of research to include a wider range of species and incorporating cross-species comparisons will significantly enhance the contribution of this study to the field of vocal learning.

Thank you for your suggestions and comments. 

Regarding your main comment 1: In the future, we plan to implement temporary captivity experiments to investigate how maternal behaviours affect pup vocal development. This study provides the necessary basis for conducting future playback studies investigating specific behaviours in a controlled environment.

Regarding your main comment 2: We completely agree that the number of singing males only represents a proxy for acoustic input that pups receive during ontogeny. In the future, we plan to investigate in detail how the acoustic landscape influences pup vocal development and learning. This will include quantifying how long pups are exposed to song during ontogeny and assessing the influence of different tutors, including a detailed analysis of song syllables of the adult tutors to compare it to vocal trajectories of song syllables in pups. 

Regarding your main comment 3: We also fully agree that it is unlikely that these results are unique to Saccopteryx bilineata. We are certain that other mammalian vocal learners show parallels to the vocal development and learning processes of S. bilineata. Especially bats are a promising taxon for comparative studies because their vocal production and perception systems are highly sophisticated (due to their ability to echolocate). The high sociability of this taxon also includes a variety of social systems and vocal capacities (e.g. regarding vocal repertoire size, vocal learning capacities, information content, etc.) which support social learning and social feedback – as shown in our study. 

As suggested, in our revised manuscript we have includes information on the validation of the ethogram. Furthermore, we have corrected all the spelling mistakes – thank you very much for pointing them out!

Recommendations for the authors:  

Reviewer #1 (Recommendations for the authors):

The following comments and suggestions are offered to improve clarity and strengthen support for the paper's main claims.

(1) Female displays as feedback:

a) The authors rather broadly describe maternal behavior as feedback based on its occurrence during pup babbling. Feedback typically entails some degree of response contingency, which is not explicitly established here. Although the authors qualitatively describe a variety of female displays that only occur within the babbling context, they also state that "all these behaviors could occur singly or in an interactive way" (Line 102). The authors go on to use aggregate counts of these diverse female displays in their analyses. It would of course be interesting to know whether distinct female displays are evoked differentially by pup behavior and whether specific female behaviors, in turn, predict subsequent pup vocalizations. A display-specific approach might also reveal more about the mechanisms by which the female behavior shapes babbling (e.g. specific reinforcement signals vs. more graded social facilitation or 'audience effect'). However, even without identifying such finegrained contingencies, the main text should at least mention the results shown in Figure 1A. Namely, that pups initiate ~80% of interactive behavioral sequences, suggesting that subsequent maternal displays are likely to be pup-contingent responses (i.e. feedback) and not simply co-occurring behavior.

We fully agree with Reviewer 1 that it would be very informative to investigate whether distinct female displays are evoked differentially by pup behavior, such as specific syllables within babbling. Or conversely, whether specific female behaviors precede particular pup vocalizations. For this study, we documented maternal behavior through direct observations, field notes, and/or video recordings. However, to capture potential contingencies between specific maternal behavioral displays and vocalization occurring in the millisecond range, other data collection methods (e.g. high-speed camera) will be required in the future. 

Related to this, we have included the following statements (see below). Statement 1 also cites a very recent study in zebra finches, demonstrating that female calls can promote song learning success (Bistere et al. 2024, line 57, lines 304-305). 

Lines 297-305: This finding serves as an initial indication that non-vocal interactions with the mother may influence a pup´s individual learning trajectories. Future studies will focus on the relationship between acoustic change, maternal feedback, and learning success, specifically investigating contingencies between particular pup vocalizations and maternal displays in natural settings. Playback experiments are an additional approach to test the impact of contingency on vocal learning. For example, one study in zebra finches demonstrated that contingent non-vocal maternal feedback affects imitation success (Carouso-Peck & Goldstein, 2019), while another recent study found that female calls can promote song learning but the role of contingency remains to be determined (Bistere et al., 2024).  

Lines: 332-334: This might also apply to S. bilineata where pups initiated ~ 80% of social interactions, suggesting that maternal feedback is likely influenced by the pup´s vocal practice.  

b) The authors claim that the number of maternal displays during babbling predicts the duration of babbling bouts (Figure 1D). I find this analysis - and others based on the raw number of behaviors during babbling - difficult to interpret given that the raw number of displays may depend upon the duration of the babbling bout over which they are counted. In other words, might the number of displays reflect the fact that more displays can occur within the interval of longer babbling bouts? It would be relatively straightforward to minimize this potential confound by testing whether female display *rates* predict longer bouts.

We calculated the display rates (maternal displays per bout duration) and conducted a GLMM (the same analysis after log-transformation and scaling) like in our original manuscript (model 1).  

GLMM

summary(vocpracf)

Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) ['glmerMod']  Family: Gamma  ( log )

Formula: bout_dur ~ age.z + behavioural_quotient.log.z + nomales.z + (1 | ID) Data: set1

Author response table 1.

Author response table 2.

Author response table 3.

Author response table 4.

Author response table 5.

Interpretation: Our analysis in the original manuscript shows that the bout duration increases with number of maternal displays. As reviewer 1 points out: more time offers more opportunities for the mother to show displays. The number of displays in longer bouts could just reflect that more displays are possible in a longer period. This could be a potential confounding factor. However, our analysis of display rates as an explaining factor shows that the relationship between bout duration and display rate is negative. This means that in longer bouts the displays increase (as seen in the first scenario), but they happen less frequently per time unit. This could indicate that in longer bouts, the mother takes breaks or longer periods of time between each display, which decreases the frequency of displays. This minimizes the risk of a potential confound, as it shows that the rate of displays tends to decrease rather than increase in longer bouts. In summary: The display rate does not appear to ‘favour’ longer bouts, as longer bouts are associated with a lower display rate. This speaks against the hypothesis that the number of displays only increases due to the longer bout duration. This also means that our analyses, which show that maternal displays influence song syllable production, are not biased or confounded by the bout duration. This suggests that maternal behaviour is targeted and selective, and represents a potentially contingent reaction to the pup´s vocal production, and is not simply determined by the duration of a bout.

We added this analysis in our supplementary material (Table S2) and pointed this out in the revision of our main manuscript (lines 136-138). 

c) The introduction states that "Pup babbling is not tied to a specific function." (Lines 75-78). This may be an important point worth exploring with this unique data set. For example, the termination of a babbling bout is defined in some cases by the onset of nursing. Have the authors (or others) tested whether babbling elicits nursing behavior? If so, this may represent a reinforcement mechanism that affects babbling rates and subsequent song outcomes. Similar functional shifts in developing vocal behavior have been reported in male chipping sparrows, in which juvenile begging calls - which initially elicit parental feeding behavior - can later be incorporated into 'sub-song' (i.e. babbling) during the development of courtship song (Lui, Wada, Nottebohm, PLOS ONE, 2009).

Thank you for pointing out this interesting study on chipping sparrows! 

To address your question: Strauss et al. (2010) conducted a study on pup and maternal behaviors, demonstrating that babbling did not consistently result in nursing.  When denied care, pups often returned to resting or grooming, a pattern we also observed in our study. While nursing might provide an additional reinforcement mechanisms, it is not the cause that evokes babbling – this is what we mean by stating “pup babbling is not tied to a specific function”. Babbling is not a begging behavior as described by Lui et al. 2009. As mentioned in the review of ter Haar et al. 2021, babbling differs structurally from begging in that it is composed of both adult-like and juvenile syllables and lacks context specificity. To solicit care (i.e. begging) pups produce several isolation calls in a fast repetitive manner. We added a more detailed explanation to make this distinction clear (lines 79-83).

Another interesting fact and probably more comparable to the study of the chipping sparrows – in which begging calls are incorporated into subsong practice – might be the isolation call syllables of S. bilineata. Directly after birth, S. bilineata pups produce multisyllabic isolation calls (see Knörnschild & von Helversen 2008, Knörnschild et al. 2012, Fernandez & Knörnschild 2017) that serve to solicit maternal care. For the first 2.5 weeks, pups only produce innate vocalizations, including echolocation and isolation calls (Fernandez et al. 2021). During the babbling phase, the syllables encoding the individual (and group) signature of the isolation call are also incorporated into babbling bouts. The production of isolation calls might also mark an initial step in the vocal learning process. However, in contrast to the subsong of chipping sparrows, babbling bouts in S. bilineata also include syllables acquired through vocal imitation. Thus, although we find similarities in vocal practice and development between chipping sparrows and S. bilineata, there are also distinct differences. 

(2) Are pups exposed to more male songs when the mother is present?

The number of singing males in each colony was used as a reasonable proxy for the amount of social acoustic input. However, I wonder if pups are exposed to more adult male songs when the mother is present and, relatedly, if females tend to remain present for longer if a pup is babbling (potentially increasing its exposure to male songs during the babbling phase).

The mother is always present when males are singing. In S. bilineata, males predominantly engage in territorial song twice daily: at dusk and dawn. After foraging at night, territorial singing males are the first to return to the roost, and females will only return when they hear male song. Pups are either attached to the mother´s belly or – when growing older – will fly into the roost followed by the mother. In the evening, males sing approximately half an hour before leaving for foraging. Females will usually leave first, followed by their pups, and males leave last. Hence, females/mothers are always present when pups are exposed to male acoustic input.  

(3) Pup sex differences:

The authors test for sex differences within a subset of pups and briefly mention that vocal development is considered in both males and females. This presumably means that female pups also exhibit vocal imitation of adult male territorial songs, even though they only produce these vocalizations during the babbling phase, after which they stop singing entirely. If so, this would, to my knowledge, be a unique phenomenon among vocal learners and would be interesting to discuss in greater detail.

We followed your recommendation and discussed this topic in greater detail. We included the following part in our discussion (lines 257-269): An intriguing aspect of this species is that, unlike most song-learning songbird species, female pups show no differences from males in babbling behavior and vocal development (Fernandez et al. 2021). This study corroborated this finding: female pups received the same maternal feedback, and their song syllable imitation did not differ in any way from male pups (as observed as well in Knörnschild et al. 2010). This phenomenon is rare among vocal learners and raises the question of why female pups match male vocal development despite not using the learned vocalizations later in life. One potential explanation might lie in the function of the territorial song for adult females: it serves as an acoustic signal to help females locate new suitable colonies after dispersal. The territorial song exhibits different dialects, with females showing a preference for local over foreign dialects (Knörnschild et al., 2017). The own early practice and production of song might enhance the ability to evaluate male song and support mating decisions.

(4) Characterization of song syllables:

The authors explain their acoustic analyses in detail within the methods, however, descriptions of the syllable classification procedures and acoustic movement analyses need to be presented more clearly in the main text, so readers unfamiliar with bioacoustics or previous work can follow the logic. Also, given the qualitative descriptions of the data and the two spectrogram examples provided (Figures 2 and S1), it is difficult for the reader to fully evaluate the suitability and output of these critical procedures.

Suggestions:  

- Qualitative descriptions of syllable characteristics (i.e. buzz, pulse, trill, ripple, gap, smeared noisy, precursor syllable, mature syllable, adult-like syllable, early vs. late babbling phase, syllable name, etc) should all be clearly-labeled in example spectrograms and used consistently, without using different terms interchangeably (e.g. mature vs. adult-like).

We understand that we should provide a clearer description of the various terms essential to understanding this study. We added a “Terminology” box (line 158) to the main manuscript, defining the acoustic terms we are using throughout our study. Additionally, we enhanced Figure S1 by providing more detailed information on the spectrogram that displays the five distinct song syllable types. Moreover, we included an additional spectrogram in the supplementary material (Fig. S2) displaying examples of precursor and mature syllables for syllable B2. In the method section, “The acoustic movement during ontogeny”, we added a sentence clarifying the terms “early” and “late babbling phase” (Lines 605-606). 

- Show as you tell. Plot the data, at least from a representative pup, for each major step in the analyses (labeled spectrogram, PCA plots with distinct syllable clusters, high vs. low versatility, precursor vs. mature variants, early vs. late syllables with Euclidean distances between centroids and relation to "generic" adult male syllables, etc.)

To illustrate the acoustic analysis more comprehensively, we have made the following additions:

-we included a Figure (Fig. S3) in the supplementary materials showing an excerpt of a babbling bout with labelled syllables to illustrate how we analyzed a) total song syllable count per bout, b) versatility per bout, and c) the number of precursor versus mature B2 syllables (the most common syllable type).

-Additionally, we included a spectrogram with three exemplary B2 syllables to illustrate the acoustic parameter extraction with Avisoft SASLab Pro software for subsequent analysis of vocal change during development (Fig. S4 A).

Lastly, we included a DFA for one of the colonies with three exemplary pups to illustrate how we calculated each pup's acoustic change during ontogeny (Fig. S4 B). 

(5) Minor Comments and Corrections:

- Modeled data are log-transformed, however, the raw data are plotted on linear scales, and in most cases, data points are densely clustered and overlapping at lower values. Plotting the data on log scales would likely aid visibility.

We appreciate this suggestion and changed the plots accordingly. 

- Figure 1E displays 18 data points, (legend says n=19).

The legend is correct; the figure includes 19 data points. Two mothers have the same activity score, so their points are at the same location and it looks like there are only 18 data points. 

- Line 482: Is "VCL" media player meant to refer to "VLC" player?

Yes, thank you for spotting that. We corrected it.  

Reviewer #2 (Recommendations for the authors):

I have only a couple of comments:

- Perhaps it would be useful to briefly go over the validation used for the ethogram in Table S1.

The behaviors listed in the ethogram were defined based on Strauss et al. (2010) and expanded based on our own observations. For consistency, we developed these definitions and trained the students analyzing behavioral data for this study. During the training phase, we validated their analyses until the inter-observer-reliability reached 100% (lines 507-508).  

- The paper seems to be generally written in American English, yet there are some instances of British English spelling, e.g. "standardised"/"standardisation": table 1, table 2, lines 143, 228, 524, 525, 531, 546, 547, 554, 560, 561.

Thank you for spotting these errors, we corrected them.  

- Line 343: "at libitum" should be "ad libitum".

Thank you for spotting this error. We corrected it.

eLife Assessment

This valuable contribution to the field evaluated the function of the cytoskeletal protein ABBA in mediating key aspects of mitosis of neuronal precursor cells. The authors provide compelling evidence that ABBA interactions with its signaling partners is related to the development of at least some cases of microcephaly — a developmental anomaly associated with intellectual disability and other neurological findings.

Reviewer #1 (Public review):

The manuscript investigates the role of the membrane-deforming cytoskeletal regulator protein Abba in cortical development and its potential implications for microcephaly. It is a valuable contribution to the understanding of Abba's role in cortical development. The strengths and weaknesses identified in the manuscript are outlined below:

Clinical Relevance:

The authors identified a patient with microcephaly and intellectual disability patient harboring a mutation in the Abba variant (R671W), adding a clinically relevant dimension to the study.

Mechanistic Insights:

The study offers valuable mechanistic insights into the development of microcephaly by elucidating the role of Abba in radial glial cell proliferation, radial fiber organization, and the migration of neuronal progenitors. The identification of Abba's involvement in the cleavage furrow during cell division, along with its interaction with Nedd9 and positive influence on RhoA activity, adds depth to our understanding of the molecular processes governing cortical development.

In Vivo Validation:

The overexpression of mutant Abba protein (R671W), which results in phenotypic similarities to Abba knockdown effects, supports the significance of Abba in cortical development.

Weaknesses:

The findings in the study suggest that heterozygous expression of the R671W variant may exert a dominant-negative effect on ABBA's role, disrupting normal brain development and leading to microcephaly and cognitive delay. However, evidence also points to a possible gain-of-function effect, as the mutation does not decrease RhoA activity or PH3 expression in vivo. Additionally, the impact of ABBA depletion on cell fate is not fully addressed. While abnormal progenitor accumulation in the ventricular and subventricular zones is observed, the transition of progenitors to neuroblasts and their ability to support neuroblast migration remains unclear. Impaired cleavage furrow ingression and disrupted Nedd9 and RhoA signaling could lead to structural abnormalities in radial glial progenitors, affecting their scaffold function and neuroblast progression. The manuscript lacks an exploration of the loss or decrease in interaction between Abba and NEDD9 in the case of the pathogenic patient-derived mutation in Abba. Furthermore, addressing the changes in localization and ineraction in for NEDD9 following over-expression of the mutant are important to further mehcanistically characterizxe this interaction in future studies. These gaps suggest the need for further exploration of ABBA's role in progenitor cell fate and neuroblast migration to clarify its mechanistic contributions to cortical development.

Reviewer #2 (Public review):

Summary:

Carabalona and colleagues investigated the role of the membrane-deforming cytoskeletal regulator protein Abba (MTSS1L/MTSS2) in cortical development to better understand the mechanisms of abnormal neural stem cell mitosis. The authors used short hairpin RNA targeting Abba20 with a fluorescent reporter coupled with in utero electroporation of E14 mice to show changes to neural progenitors. They performed flow cytometry for in-depth cell cycle analysis of Abba-shRNA impact to neural progenitors and determined an accumulation in S phase. Using culture rat glioma cells and live imaging from cortical organotypic slides from mice in utero electroporated with Abba-shRNA, the authors found Abba played a prominent role in cytokinesis. They then used a yeast-two-hybrid screen to identify three high confidence interactors: Beta-Trcp2, Nedd9, and Otx2. They used immunoprecipitation experiments from E18 cortical tissue coupled with C6 cells to show Abba requirement for Nedd9 localization to the cleavage furrow/cytokinetic bridge. The authors performed an shRNA knockdown of Nedd9 by in utero electroporation of E14 mice and observed similar results as with the Abba-shRNA. They tested a human variant of Abba using in utero electroporation of cDNA and found disorganized radial glial fibers and misplaced, multipolar neurons, but lacked the impact of cell division seen in the shRNA-Abba model.

Strengths:

Fundamental question in biology about the mechanics of neural stem cell division.<br /> Directly connecting effects in Abba protein to downstream regulation of RhoA via Nedd9.<br /> Incorporation of human mutation in ABBA gene.<br /> Use of novel technologies in neurodevelopment and imaging.

Weaknesses:

Unexplored components of the pathway (such as what neurogenic populations are impacted by Abba mutation) and unleveraged aspects of their data (such as the live imaging) limit the scope of their findings and left significant questions about the effect of ABBA on radial glia development.

(1) Claim of disorganized radial glial fibers lacks quantifications.<br /> -On page 11, the authors claim that knockdown of Abba lead to changes in radial glial morphology observed with vimentin staining. Here they claim misoriented apical processes, detached end feet, and decreased number of RGP cells in the VZ. However, they no not provide quantification of process orientation to better support their first claim. Measurements of radial glia fiber morphology (directionality, length) and of angle of division would be metrics that can be applied to data. Some of these analysis could be done in their time-lapse microscopy images, such as to quantify the number of cell division during their period of analysis (though that is short-15 hours).

(2) Unclear where effect is:<br /> -in RG or neuroblasts? Is it in cell cleavage that results in accumulation of cells at VZ (as sometimes indicated by their data like in Fig 2A or 4D)? Interrogation of cell death (such as by cleaved caspase 3) would also help. Given their time lapse, can they identify what is happening to the RG fiber? The authors describe a change in "migration" but do not show evidence for this for either progenitor or neuroblast populations. Given they have nice time-lapse imaging data, could they visualize progenitor versus young neuron migration? Analysis of neuroblasts (such as with doublecortin expression in the tissue) would also help understand any issues in migration (of neurons v stem cells).<br /> -at cleaveage furrow? In abscission? There is high resolution data that highlights the cleavage furrow as the location of interest (fig 3A), however there is also data (fig 3B) to suggest Abba is expressed elsewhere as well and there is an overall soma decrease. More detail of the localization of Abba during the division process would be helpful-for example, could cleavage furrow proteins, such as Aurora B, co-localization (and potentially co-IP) help delineate subpopulations of Abba protein? Furthermore, the FRET imaging is unique way to connect their mutation with function-could they measure/quantify differences at furrow compared to rest of soma to further corroborate that Abba-associated RhoA effect was furrow-enriched?<br /> -The data highlights nicely that a furrow doesn't clearly form when ABBA expression and subsequent RhoA activity are decreased (in Fig 3 or 5A). Does this lead to cells that can't divide because of poor abscission, especially since "rounding" still occurs? Or abnormal progenitors (with loss of fiber or inability to support neuroblast migration)? Or abnormal progression of progenitors to neuroblasts?

(3) Limited to a singular time point of mouse cortical development<br /> On page 13, the authors outline the results of their Y2H screen with the identification of three high confidence interactors. Notably, they used a E10.5-E12.5 mouse brain embryo library rather than one that includes E14, the age of their in utero electroporation mice. Many of the authors' claims focus on in utero electroporation of shRNA-Abba of E14 mice that are then evaluated at E16-18. Justification for the focus on this age range should be included to support that their findings can then be applied to all of mouse corticogenesis.

(4) Detail of the effect of the human variant of the ABBA mutation in mouse is lacking.<br /> Their identification of the R671W mutation is interesting and the IUE model warrants more characterization, as they did with their original KD experiments.<br /> -Could they show that Abba protein levels are decreased (in either cell lines or electroporated tissue)?<br /> -While time-lapse morphology might not have been performed, more analysis on cell division phenotype (such as plane of division and radial glia morphology) would be helpful.

The resubmission has addressed many of the questions raised.

I have a few comments that should be addressed:

(1) The authors maintain a deficit in "migration of immature neurons" which remains unsubstantiated. In their resonse, they state: "we believe that the data showing the accumulation of migrating electroporated cells in the ventricular (V) and subventricular (SV) zones provide compelling evidence of abnormal migration in ABBA-shRNA electroporated cells. "<br /> -Firstly, they do not demonstrate that it's immature neurons, not RGs, that are affected. Secondly, accumulation of cells at the V-SVZ could be due to soley the inability for the RGC to undergo mitosis, therefore remaining stuck"<br /> The commentary of migration, especially of neurons, should be modified.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

The manuscript investigates the role of the membrane-deforming cytoskeletal regulator protein Abba in cortical development and its potential implications for microcephaly. It is a valuable contribution to the understanding of Abba's role in cortical development. The strengths and weaknesses identified in the manuscript are outlined below:

Clinical Relevance:

The authors identified a patient with microcephaly and a patient with an intellectual disability harboring a mutation in the Abba variant (R671W) adding a clinically relevant dimension to the study.

Mechanistic Insights:

The study offers valuable mechanistic insights into the development of microcephaly by elucidating the role of Abba in radial glial cell proliferation, radial fiber organization, and the migration of neuronal progenitors. The identification of Abba's involvement in the cleavage furrow during cell division, along with its interaction with Nedd9 and positive influence on RhoA activity, adds depth to our understanding of the molecular processes governing cortical development. Though the reported results establish the novel interaction between Abba and Nedd9, the authors have not addressed whether the mutant protein loses this interaction and whether that results in the observed effects.

We appreciate the reviewer’s observation and fully agree that our study does not provide direct evidence that the phenotypes induced by the R671W mutant are mediated through NEDD9. We sincerely apologize if the manuscript inadvertently conveyed this impression.

While we show that the interaction with NEDD9 plays a role in the action of ABBA, our findings suggest that NEDD9 and RhoA activation have a minor influence on the phenotypes induced by this mutation, as highlighted by the evidence we presented.

We would like to point out that we have previously addressed this point in the discussion section of the manuscript. For clarity, below is an excerpt from that section:

“heterozygous expression of the human R671W variant would exert a dominant negative effect on ABBA's role in brain development, leading to microcephaly and cognitive delay. This notion is supported by recent work disclosing additional patient carrying the R671W variant42. In the same study the significant neurological phenotypes were observed in a drosophila model where the ortholog of human MTSS2 and MTSS1 mim was deleted.   However, from a clinical genetics’ standpoint, it is unlikely to find patients with the recurrent R671W mutation without any homozygous or compound heterozygous loss-of-function mutations elsewhere in the ABBA gene. This could also suggest a gain-of-function effect of the R671W mutation. Supporting this notion, overexpressing ABBA-R671W in cells expressing the wild-type Abba in this study did not result in a dominant-negative decrease in RhoA activation, nor did it affect the expression of PH3 in vivo. These findings make it plausible to suggest that a mechanism responsible for the phenotype associated with overexpression of the human variant may primarily involve post-cell division processes, such as cell migration. “

We have made corrections to the new version of the manuscript to emphasize this further.

In Vivo Validation:

The overexpression of mutant Abba protein (R671W) resulting in phenotypic similarities to Abba knockdown effects supports the significance of Abba in cortical development.

Reviewer #2 (Public Review):

Summary:

Carabalona and colleagues investigated the role of the membrane-deforming cytoskeletal regulator protein Abba (MTSS1L/MTSS2) in cortical development to better understand the mechanisms of abnormal neural stem cell mitosis. The authors used short hairpin RNA targeting Abba20 with a fluorescent reporter coupled with in-utero electroporation of E14 mice to show changes to neural progenitors. They performed flow cytometry for in-depth cell cycle analysis of Abba-shRNA impact on neural progenitors and determined an accumulation in the S phase. Using culture rat glioma cells and live imaging from cortical organotypic slides from mice in utero electroporated with Abba-shRNA, the authors found Abba played a prominent role in cytokinesis. They then used a yeast-two-hybrid screen to identify three high-confidence interactors: Beta-Trcp2, Nedd9, and Otx2. They used immunoprecipitation experiments from E18 cortical tissue coupled with C6 cells to show Abba's requirement for Nedd9 localization to the cleavage furrow/cytokinetic bridge. The authors performed a shRNA knockdown of Nedd9 by in-utero electroporation of E14 mice and observed similar results as with the Abba-shRNA. They tested a human variant of Abba using in-utero electroporation of cDNA and found disorganized radial glial fibers and misplaced, multipolar neurons, but lacked the impact of cell division seen in the shRNA-Abba model.

Strengths:

A fundamental question in biology about the mechanics of neural stem cell division.

Directly connecting effects in Abba protein to downstream regulation of RhoA via Nedd9.

Incorporation of human mutation in ABBA gene.

Use of novel technologies in neurodevelopment and imaging.

Weaknesses:

Unexplored components of the pathway (such as what neurogenic populations are impacted by Abba mutation) and unleveraged aspects of their data (such as the live imaging) limit the scope of their findings and leave significant questions about the effect of ABBA on radial glia development.

(1) The claim of disorganized radial glial fibers lacks quantifications.

On page 11, the authors claim that knockdown of Abba leads to changes in radial glial morphology observed with vimentin staining. Here they claim misoriented apical processes, detached end feet, and decreased number of RGP cells in the VZ. However, they do not provide quantification of process orientation to better support their first claim. Measurements of radial glia fiber morphology (directionality, length) and angle of division would be metrics that can be applied to data.

In the corrected version of the manuscript, we provide new qualification of changes in dispersion of vimentin immunostaining (Supplementary Figure 1).

Some of these analyses could be done in their time-lapse microscopy images, such as to quantify the number of cell divisions during their period of analysis (though that is short-15 hours).

This is indeed a very good idea. We have reanalyzed the recordings to follow cell division. Unfortunately, the number of cells that we were able to follow was low, making statistical analysis of the data unreliable.  As the reviewer alluded in the comment longer recording times than 15h are required to make reliable conclusion. Instead, we have performed live-cell imaging using Aniling-GFP coelectroporeted with RFP as a marker of mitotic progression . We monitored the distribution of cells showing accumulation of Anillin-GFP in control (Scramble) and ABBA-shRNA3 conditions (this data was added to new Supplementary Figure 3). Anillin has been shown to be an efficient tool to monitor cell division in vivo as in particular as it displays accumulation and correlated increase intensity of Anillin-GFP ((Hesse et al Nature Com. 2012, DOI: 10.1038/ncomms2089).

(2) It is unclear where the effect is:

-In RG or neuroblasts? Is it in cell cleavage that results in the accumulation of cells at VZ (as sometimes indicated by their data like in Figure 2A or 4D)?

The data suggest that radial glial (RG) cells are indeed blocked prior to abscission. This phenomenon might contribute to the accumulation of cells at the ventricular zone (VZ), as indicated by observations such as those in Figure 2A and 4D. The interruption in cell cleavage likely prevents the proper progression of division, causing RG cells to remain at the VZ rather than proceeding with their normal differentiation or migration processes. This finding highlights a potential mechanistic link between disrupted abscission and cell accumulation in the VZ.

Interrogation of cell death (such as by cleaved caspase 3) would also help.  

Caspase-3 cleavage is widely used as a marker for apoptosis; however, it may not be the most reliable tool for monitoring apoptosis during brain cortical development. The developing brain is a highly dynamic environment where caspase-3 activation can be transient and involved in non-apoptotic processes, such as synaptic pruning and neuronal remodeling. This makes it challenging to distinguish caspase-3 activity associated with apoptosis from its roles in physiological processes.

In contrast, monitoring overall cell survival provides a more reliable measure of developmental outcomes, as it reflects the net balance of cell death and survival mechanisms. By focusing on cell survival e.g. quantification of number of RGP, we can better assess the functional consequences of apoptosis and its interplay with neurogenesis and other developmental processes.  In line with this we have added more data on the quantification of RGPC as well as their distribution in new Supplementary Figure 3. 

Given their time-lapse, can they identify what is happening to the RG fiber?

Both apical and basal endfeet appear to detach and retract prior to radial glial (RG) cell death. This is evident in Figure 1D, as well as from our observation of cellular bodies located far from the ventricular surface (VS), as demonstrated in the new Supplementary Figure 3.

The authors describe a change in "migration" but do not show evidence for this for either progenitor or neuroblast populations. Given they have nice time-lapse imaging data, could they visualize progenitor versus young neuron migration? Analysis of neuroblasts (such as with doublecortin expression in the tissue) would also help understand any issues in migration (of neurons v stem cells).

This is an excellent question that arises from the extensive data presented in this study. Addressing it would require repeating a significant portion of the experiments. We fully agree with the reviewer that these are important and obvious questions that warrant a dedicated study to answer them thoroughly. Additionally, we believe that the data showing the accumulation of migrating electroporated cells in the ventricular (V) and subventricular (SV) zones provide compelling evidence of abnormal migration in ABBA-shRNA electroporated cells.

-At cleavage furrow? In abscission? There is high-resolution data that highlights the cleavage furrow as the location of interest (Figure 3A), however, there is also data (Figure 3B) to suggest Abba is expressed elsewhere as well and there is an overall soma decrease. More detail of the localization of Abba during the division process would be helpful for example, could cleavage furrow proteins, such as Aurora B, co-localization (and potentially co-IP) help delineate subpopulations of Abba protein? Furthermore, the FRET imaging is a unique way to connect their mutation with function - could they measure/quantify differences at furrow compared to the rest of soma to further corroborate that the Abba-associated RhoA effect was furrow-enriched?

In the corrected version of the manuscript, we include new quantification of RhoA activity in the region corresponding to the cleavage furrow (New Figure 5), This new data show similar results as the previous and indicate that the changes observed are primarily derived from the cleavage furrow region. In the future a detailed dissection of the molecules involved in the mechanism would be highly desirable. These notions are now included in the discussion. 

-The data highlights nicely that a furrow doesn't clearly form when ABBA expression and subsequent RhoA activity are decreased (in Figure 3 or 5A). Does this lead to cells that can't divide because of poor abscission, especially since "rounding" still occurs? Or abnormal progenitors (with loss of fiber or inability to support neuroblast migration)? Or abnormal progression of progenitors to neuroblasts?

Our findings, combined with previous results, suggest multiple mechanisms through which ABBA depletion and subsequent Nedd9 and RhoA signaling disruptions could impact progenitor cells and neuroblasts. Below is a detailed response to each question: 

(1) Do cells fail to divide due to poor abscission?

Nedd9 is a key regulator of RhoA signaling, which could be essential for cleavage furrow ingression and abscission. Reduced Nedd9 expression may leads to non-activation of RhoA, thereby impairing cleavage furrow ingression. Furthermore, since RhoA deactivation is critical for successful abscission, any disruption in this signaling pathway could compromise the final stages of cytokinesis. While we do not directly observe failed abscission, the impaired furrow formation in Figure 3 and 5A aligns with the hypothesis that some cells may struggle to complete division due to defects in RhoA-mediated abscission. 

(2) Are abnormal progenitors generated (e.g., loss of fiber or inability to support neuroblast migration)?

Disrupted Nedd9 expression not only affects cell cycle progression but also influences the structural integrity of radial glial progenitors (RGPs). RGPs with impaired cleavage furrow ingression may exhibit detachment of apical and basal endfeet (Supplementary Figure 3), leading to abnormalities in their scaffold function. This structural disruption likely contributes to the accumulation of electroporated cells in the ventricular (V) and subventricular (SV) zones (Figure 5A), supporting the idea that abnormal progenitors fail to support proper neuroblast migration. 

(3) Is there abnormal progression of progenitors to neuroblasts?

Given that Nedd9 triggers cells to enter mitosis, its impaired function may prevent progenitors from properly progressing through the cell cycle, causing cell cycle arrest and eventual decrease survival. This would directly impact the ability of progenitors to transition into neuroblasts. Moreover, the abnormal membrane composition and PI(4,5)P2 enrichment we hypothesize during cytokinesis could disrupt ABBA recruitment and its interaction with Nedd9. This disruption would impair RhoA activation, further compromising the progression of progenitors to neuroblasts. 

In conclusion, our findings suggest that impaired ABBA expression disrupts Nedd9 and RhoA signaling, leading to poor cleavage furrow ingression, abnormal progenitor structure, and defective neuroblast migration. These processes collectively contribute to developmental defects in the cortex. Future studies focusing on live imaging of cytokinesis and cell fate mapping will help elucidate better these mechanisms further.

(3) Limited to a singular time point of mouse cortical development

On page 13, the authors outline the results of their Y2H screen with the identification of three high-confidence interactors. Notably, they used an E10.5-E12.5 mouse brain embryo library rather than one that includes E14, the age of their in-utero electroporation mice. Many of the authors' claims focus on in-utero electroporation of shRNA-Abba of E14 mice that are then evaluated at E16-18. Justification for the focus on this age range should be included to support that their findings can then be applied to all mouse corticogenesis.

We thank the reviewer to point this out. Indeed, the data suggest that the interaction between ABBA and Nedd9 occurs before E14. The reason to address the questions at E14 is that in earlier work, we have shown that ABBA is mainly expressed through E10.5-12.5 in the floorplate structure formed by radial glia. The radial glia-specific expression was confirmed through double staining with radial glial (RC2) and neuronal (Tuj1) markers at E12.5 (see Saarikangas et al. J. Cell Sci. 121:1444-1454, 2008). Thus, we consider the Y2H library relevant for identifying ABBA's interactors within radial glia. We have specified this better in the corrected manuscript.

(4) Detail of the effect of the human variant of the ABBA mutation in mice is lacking.

Their identification of the R671W mutation is interesting and the IUE model warrants more characterization, as they did with their original KD experiments.

We have now included addition data in the corrected manuscript showing R671W dependent changes in INM (Supplementary Figure 3 )

Could they show that Abba protein levels are decreased (in either cell lines or electroporated tissue)?

Estimation of ABBA expression in cell expressing ABBA R671W as in Supplemental Figure 5 did not show significant change.

-While time-lapse morphology might not have been performed, more analysis on cell division phenotype (such as plane of division and radial glia morphology) would be helpful. 

This would be indeed very informative, but we were not able to perform these analysis in the existing dataset.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Here are some suggestions for targeting some of the weaknesses by additional experiments:

Regional Demarcation in Radial Glial Cell Population:

While the authors demonstrate a decrease in overall RFP-positive cells in response to Abba knockdown, the distinction between different regions should be demarcated using cortical layer-specific markers (e.g., CUX1/BRN2 for the upper layer and CTIP2/FOXP2). Quantification based on regional markers would enhance accuracy and meaningful interpretation.

In order to harmonize the quantification during the different developmental stages we have used a broader definition of the cortical regions that may not be entirely fitting with the regions identified with the staining of Cux1 and CTIP2. We have now however included in the supplementary figure 1 with the staining for Cux1 and CTIP2 showing the corresponding regions defined in the manuscript. Supplementary Figure 1.

Mitotic Stage Marker and BrdU Staining:<br /> The discrepancy between no changes in staining with the mitotic stage marker PH3 and a reported decrease in Ki67 staining calls for further clarification. Additionally, the use of BrdU staining could distinguish the effects on dividing cells after Abba knockdown. The authors are encouraged to explore these aspects further, including their applicability to NEDD9 knockdown and Abba mutant overexpression.

As suggested by the reviewer elsewhere, we made use of life imaging. We monitored the distribution of cells showing accumulation of Anillin-GFP in control (Scramble) and ABBA-shRNA3 conditions (this data has been added to the new Supplementary Figure 3). Anillin has been shown to be an efficient tool for monitoring cell cycle stages in vivo (Hesse et al Nature Com. 2012, DOI: 10.1038/ncomms2089). Interestingly, we observed an increase in cells displaying accumulated Anillin in ABBA-shRNA3 treated cells, which is consistent with an arrest of progression of mitosis.  

Quantification of Cytokinesis Effects:

The brain slices illustrating the effects of Abba knockdown on cytokinesis would benefit from a quantification depicting changes in interkinetic nuclear migration and the number of successful mitosis events. This would enhance the clarity and interpretation of the observed effects.

In the revised manuscript we have included new data in Supplementary Figure 3 were we report the quantification of the distance of the RGC from the ventricle to address the reviewer’s comments. We were not entirely sure about comment about quantification of successful mitosis events, but as specified above, we have included new data from the monitoring of anillin. We hope to perform more detailed experiments and analysis in future studies. 

Loss of Interaction and NEDD9 Localization:

The manuscript lacks an exploration of the loss or decrease in interaction between Abba and NEDD9 in the case of the pathogenic patient-derived mutation in Abba. Addressing this aspect is crucial, as it may shed light on the underlying causes of the observed effects. Furthermore, investigating changes in NEDD9 localization following overexpression of the Abba mutant would provide additional insights.

We fully agree with the reviewer’s comment. Unfortunately the anti NEDD9 antibody had a poor performance in slice immunohistochemistry, which hampered further reliable investigation of expression and distribution changes in vivo. Resolving this issue and providing a more detailed characterization of the mechanism of Abba-NEDD9 interaction will be important in future studies.

Overall, I believe that with minor revisions and additional contextualization, the manuscript has the potential to make a significant contribution to the field. I recommend acceptance pending the incorporation of the suggested revisions.

Reviewer #2 (Recommendations For The Authors):

The manuscript is generally well-organized. We hope that given their nice experimental systems, many of the comments and questions can be addressed with their data already on hand.

Minor Comments

• For Figure 6E A closeup of the vimentin would be helpful - hard to visualize radial glia morphology at the current magnification.

This has been corrected in the new version of the manuscript

• For the in utero electroporation what was their rationale for 2-4 day interval before evaluation? For example, waiting for more cortical plate development to be able to manifest long-term effects.

We observed a massive cell death at E18, in only few of those brains we were able to still observe RFP cells. We have also tried P6 animals but none of them had significant reminding electroporated cells that’s why we have decided to focus at E17, 3 days after the electroporation to have still enough expression of the shRNA.

• Figure 4E-F lacks images of controls for comparison of effect.

This has been corrected in the revised version of the manuscript

eLife Assessment

This important Research Advance presents compelling evidence on the neuroprotective effects of reserpine in a well-established model of retinitis pigmentosa (P23H-1). This study builds on previous work establishing reserpine as a neuroprotectant in models of Leber congenital amaurosis. Here authors show reserpine's disease gene-independent influence on photoreceptor survival and emphasizes the importance of considering biological sex in understanding inherited retinal degeneration and the impact of drug treatments on mutant retinas. The work will be of interest to vision researchers as well as a broad audience in translational research.

Reviewer #1 (Public review):

Summary:

The authors investigate the neuroprotective effect of reserpine in a retinitis pigmentosa (P23H-1) model, characterized by a mutation in the rhodopsin gene. Their results reveal that female rats show better preservation of both rod and cone photoreceptors following reserpine treatment compared to males.

Strengths:

This study effectively highlights the neuroprotective potential of reserpine and underscores the value of drug repositioning as a strategy for accelerating the development of effective treatments. The findings are significant for their clinical implications, particularly in demonstrating sex-specific differences in therapeutic response.

Weaknesses:

The main limitation is the lack of precise identification of the specific pathway through which reserpine prevents photoreceptor death.

Comments on revisions:

Thank you for your thorough revisions. I appreciate the effort you have put into addressing all the concerns I previously raised. Upon reviewing your responses and the updated manuscript, I find that you have adequately clarified the issues and incorporated the necessary modifications. Your revisions have strengthened the paper, and I have no further concerns at this stage.

Author response:

The following is the authors’ response to the previous reviews

Reviewer #1 (Public review):

Summary:

The authors investigate the neuroprotective effect of reserpine in a retinitis pigmentosa (P23H-1) model, characterized by a mutation in the rhodopsin gene. Their results reveal that female rats show better preservation of both rod and cone photoreceptors following reserpine treatment compared to males.

Strengths:

This study effectively highlights the neuroprotective potential of reserpine and underscores the value of drug repositioning as a strategy for accelerating the development of effective treatments. The findings are significant for their clinical implications, particularly in demonstrating sex-specific differences in therapeutic response.

We sincerely appreciate the reviewer’s comments.

Weaknesses:

The main limitation is the lack of precise identification of the specific pathway through which reserpine prevents photoreceptor death.

We acknowledge that the exact pathway through which reserpine exerts its protective effects on photoreceptors remains undetermined, yet our findings provide critical insights into potential mechanisms. Together with our previous report [PMID: 36975211], the studies being presented here validate proteostasis (including autophagy) and p53 signaling as the key pathways underlying reserpine-mediated survival of photoreceptors in retinal disease models. We also go a step further by showing an influence of the biological sex.

We emphasize that the primary aim of this study was to demonstrate the effectiveness of reserpine in a different retinal degeneration model—specifically, the autosomal dominant RP model—which shares a retinal disease phenotype with the model used for initial screening but involves different genetic and molecular mechanisms of degeneration.

Reviewer #2 (Public review):

Summary:

In the manuscript entitled "Sex-specific attenuation of photoreceptor degeneration by reserpine in a rhodopsin P23H rat model of autosomal dominant retinitis pigmentosa" by Beom Song et al., the authors explore the transcriptomic differences between male and female wild-type (WT) and P23H retinas, highlighting significant gene expression variations and sex-specific trends. The study emphasizes the importance of considering biological sex in understanding inherited retinal degeneration and the impact of drug treatments on mutant retinas.

Strengths:

(1) Relevance to Clinical Challenges: The study addresses a critical limitation in inherited retinal degeneration (IRD) therapies by exploring a gene-agnostic approach. It emphasizes sex-specific responses, which aligns with recent NIH mandates on sex as a biological variable.

(2) Multi-dimensional Methodology: Combining electroretinography (ERG), optical coherence tomography (OCT), histology, and transcriptomics strengthens the study's findings.

(3) Novel Insights: The transcriptomic analysis uncovers sex-specific pathways impacted by reserpine, laying the foundation for personalized approaches to retinal disease therapy.

We are grateful for highlighting the strengths of our work.

Weaknesses:

Dose Optimization

The study uses a fixed dose (40 µM), but no dose-response analysis is provided. Sex-specific differences in efficacy might be influenced by suboptimal dosing, particularly considering potential differences in metabolism or drug distribution.

We acknowledge the limitation of using a fixed dose (40 µM) of reserpine in this study without conducting a comprehensive dose-response analysis. In the primary screens, the EC₅₀ of reserpine was approximately 20 µM. We doubled the concentration for injection to account for the potential loss of reserpine during the in vivo procedures. As we observed the rescue effect of reserpine in mice, we used the same concentration for rats. The fixed-dose approach was chosen to maintain consistency with previous studies evaluating reserpine in retinal degeneration models and to facilitate comparison across studies. Efforts to identify optimal dosing were deprioritized, as the primary goal was different and this information cannot be directly translated to clinical applications.

We also agree that sex-specific differences in efficacy might be influenced by suboptimal dosing, particularly given potential variations in metabolism, drug distribution, and pharmacokinetics between male and female rats. However, recent pharmacokinetic studies on systemically administered reserpine in rats reported no statistically significant covariates, including body weight, age, breed, or sex, affecting pharmacokinetic (PK) or pharmacodynamic (PD) parameters (Alfosea-Cuadrado, G. M., Zarzoso-Foj, J., Adell, A., Valverde-Navarro, A. A., González-Soler, E. M., Mangas-Sanjuán, V., & Blasco-Serra, A. (2024). Population Pharmacokinetic–Pharmacodynamic Analysis of a Reserpine-Induced Myalgia Model in Rats. Pharmaceutics, 16(8), 1101. https://doi.org/10.3390/pharmaceutics16081101). Furthermore, no evidence of sex-specific differences in reserpine pharmacokinetics has been previously identified in available databases (National Center for Biotechnology Information (2025). PubChem Compound Summary for CID 5770, Reserpine. Retrieved January 13, 2025 from https://pubchem.ncbi.nlm.nih.gov/compound/Reserpine). Importantly, the drug in this study was administered intravitreally, where the ocular compartments are relatively isolated from systemic metabolism or excretion. Under these conditions, where absorption, distribution, metabolism, and excretion have minimal impact, we observed sex differences in efficacy using the same dose of drug.

Nonetheless, we agree with the reviewer and plan to pursue dose-response and other studies in future investigations.

Statistical Analysis

In my opinion, there is room for improvement. How were the animals injected? Was the contralateral eye used as control? (no information in the manuscript about it!, line 390 just mentions the volume and concentration of injections). If so, why not use parametric paired analysis? Why use a non-parametric test, as it is the Mann-Whitney U? The Mann-Whitney U test is usually employed for discontinuous count data; is that the case here?<br /> Therefore, please specify whether contralateral eyes or independent groups served as controls. If contralateral controls were used, paired parametric tests (e.g., paired t-tests) would be statistically appropriate. Alternatively, if independent cohorts were used, non-parametric Mann-Whitney U tests may suffice but require clear justification.

We apologize for the lack of clarity. In line 124, we described the injection as “bilateral intravitreal injections of 5 µL of either vehicle or 40 µM reserpine,” and in Figure 1A, we annotated the bilateral injection as DMSO for both eyes and RSP for both eyes. To address this uncertainty, we added the clarification, “with each group receiving bilateral injections of either vehicle or reserpine” (lines 404–405). Since the results are not paired and involve continuous data for which the normality assumption cannot be confidently met or verified, we used the Mann-Whitney U test for statistical analysis.

Sex-Specific Pathways

The authors do identify pathways enriched in female vs. male retinas but fail to explicitly connect these to the changes in phenotype analysed by ERG and OCT. The lack of mechanistic validation weakens the argument.

The study does not explore why female rats respond better to reserpine. Potential factors such as hormonal differences, retinal size, or differential drug uptake are not discussed.

It remains open, whether observed transcriptomic trends (e.g., proteostasis network genes) correlate with sex-specific functional outcomes.

We acknowledge that, while we identified pathways enriched in female versus male retinas, we did not explicitly connect these findings to the functional phenotypes measured by ERG and OCT. Although our transcriptomic data suggest that reserpine differentially influences pathways such as proteostasis and p53 signaling, we did not conduct mechanistic experiments to validate a causal relationship between these pathways and the observed outcomes.

In practice, designing a study to validate the mechanisms of a small molecule modulating multiple pathways presents significant challenges. If the pathways cannot be specifically modulated or if modulation could result in irreversible outcomes, the mechanistic validation becomes difficult to achieve. Drugs demonstrating mutation-agnostic efficacy are often investigated primarily through outcome measures and the analysis of affected pathways rather than through direct mechanistic validation (Leinonen, H., Zhang, J., Occelli, L. M., Seemab, U., Choi, E. H., L P Marinho, L. F., Querubin, J., Kolesnikov, A. V., Galinska, A., Kordecka, K., Hoang, T., Lewandowski, D., Lee, T. T., Einstein, E. E., Einstein, D. E., Dong, Z., Kiser, P. D., Blackshaw, S., Kefalov, V. J., Tabaka, M., … Palczewski, K. (2024). A combination treatment based on drug repurposing demonstrates mutation-agnostic efficacy in pre-clinical retinopathy models. Nature communications, 15(1), 5943. https://doi.org/10.1038/s41467-024-50033-5).

As recommended, we added potential factors that might influence the differential response to reserpine, based on other studies (lines 353–362) highlighting differences in dopamine storage capacity and estrogen independence. We also added a discussion on the possibility of sex-related differences in basal ERG response levels (lines 363–366).

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

The study presents compelling findings on the neuroprotective effects of reserpine in a well-established model of retinitis pigmentosa (P23H-1). The use of ERG, optomotor assays, OCT, immunohistochemistry, and transcriptomic techniques provides a good exploration of the treatment's effects, particularly highlighting the differential response in females. The study underscores the potential of drug repurposing to expedite the availability of therapeutic interventions for patients.

Thanks for your generous comments.

While the manuscript presents an important contribution, I would like to highlight a few points that need clarification or further elaboration to strengthen the work:

(1) Please include the photopic a-wave data in your analysis or provide a justification for its omission. Specifically, it would be valuable to know whether there is an improvement in this parameter under reserpine treatment.

We appreciate the reviewer’s suggestion to include photopic a-wave data in our analysis and acknowledge the importance of this parameter in evaluating cone photoreceptor function. However, we did not analyze the photopic a-wave amplitude in our study because we found the photopic a-wave has low amplitude and high variability, consistent with findings in other studies with P23H-1 rats (Orhan E, Dalkara D, Neuillé M, Lechauve C, Michiels C, et al. (2015) Genotypic and Phenotypic Characterization of P23H Line 1 Rat Model. PLOS ONE 10(5): e0127319. https://doi.org/10.1371/journal.pone.0127319) or even with wild type rats (V.L. Fonteille, J. Racine, S. Joly, A.L. Dorfman, S. Rosolen, P. Lachapelle; Do Rats Generate a Photopic a–Wave? . Invest. Ophthalmol. Vis. Sci. 2005;46(13):2246). We added the description (lines 435-437) explaining why the photopic a-wave was not analyzed. Studies with P23H-1 did not analyze the photopic a-wave, probably for similar reasons.

(2) In Figure 1, it would be helpful to include data from normal control animals to provide a benchmark for retinal degeneration in P23H-1 animals and to better contextualize the effects of reserpine treatment.

Thanks. As suggested, we have included data from normal control animals to Figure 1.

(3) The manuscript states that "Treated female retinas have significantly higher expression of the gene for P62 (SQSTM1), indicating a potential key route for reserpine's activity" (Line 331). Please explain how this difference in expression might translate into a better photoreceptor response in females compared to males.

The difference in P62 (SQSTM1) expression between treated female and male retinas could have important implications for the photoreceptor response. We have identified in our previous study that reserpine increased P62 that mediates proteome balance between ubiquitin-proteasome system (UPS) and autophagy. Together with the role of P62 in the regulation of oxidative stress, P62 might be important for photoreceptor survival and function. Higher expression of P62 in treated females could suggest more efficient cellular maintenance and a better ability to cope with stress, leading to improved photoreceptor survival and function.

(4) Numerous studies have shown that animal models of Parkinson's disease (e.g., those treated with MPTP or rotenone) or retinal tissue from Parkinson's patients exhibit dopaminergic cell death and associated vision loss. Please discuss how these findings relate to your results. Can you hypothesize how dopamine depletion by reserpine may lead to improved photoreceptor responses in your model?

We appreciate the reviewer’s insightful comments. Both MPTP and rotenone act via inhibition of complex I of the respiratory chain, causing cell death and leading to dopamine depletion. In contrast, reserpine acts by inhibiting the vesicular monoamine transporter, depleting catecholamines by preventing their storage and facilitating their metabolism by monoamine oxidase. Although reserpine and other agents can induce animal models of Parkinson's disease, reserpine differs from the others in several aspects: (i) reserpine do not induce neurodegeneration and protein aggregation; (ii) motor performance, monoamine content, and TH staining are partially restored after treatment interruption; and (iii) reserpine lacks specificity regarding dopaminergic neurotransmission (Leão, A. H., Sarmento-Silva, A. J., Santos, J. R., Ribeiro, A. M., & Silva, R. H. (2015). Molecular, Neurochemical, and Behavioral Hallmarks of Reserpine as a Model for Parkinson's Disease: New Perspectives to a Long-Standing Model. Brain pathology (Zurich, Switzerland), 25(4), 377–390. https://doi.org/10.1111/bpa.12253). We have discussed the various effects of catecholamine depletion on retinal diseases (lines 331–337). Both dopamine receptor antagonists and agonists, as well as catecholamine depletion, can exert protective effects on the retina. The reduction in scotopic b-wave amplitude observed at P54, followed by a lack of further progression in degeneration, may support the hypothesis that reduced neuronal activity due to catecholamine depletion could have mitigated damage to retinal neurons.

(5) For readers who may not be familiar with the P23H-1 mutation, it would be beneficial to include a brief description of the timeline and progression of retinal degeneration in this model.

As the progression varies among studies, we have provided our description on observations from the same facility where the animals were housed. The timeline and progression of retinal degeneration are briefly described in the results section (lines 112–115) and Supplementary Figure 1.

(6) Do you have any data on the effects of reserpine treatment in older animals? If available, this could provide additional insight into the potential applicability of reserpine in later stages of disease progression.

Unfortunately, we do not have data from older animals. As described in the results section (lines 116–124), we set the timepoint for interventions before functional impairment peaked, aiming to harness the remaining potential for rescue and promote functional improvement. Our approach focused on developing a gene-agnostic therapy that can delay disease progression and be delivered at an earlier stage than AAV-based therapies, using FDA-approved drugs.

(7) Molecular Basis of Sex Differences: The molecular mechanisms underlying the differential responses in males and females should be elaborated upon. If possible, include a discussion or hypothesis that addresses these sex-specific differences at the molecular level.

We thank the reviewer for highlighting the importance of addressing the molecular basis of sex-specific differences. In our study, we observed distinct transcriptomic responses to reserpine between male and female rats, particularly in molecular pathways related to proteostasis and p53 signaling. While the sex-specific differences in these molecular pathways remain to be fully evaluated, we have added a discussion on sex differences in reserpine responses, incorporating findings from other studies (lines 353–366).

Reviewer #2 (Recommendations for the authors):

(1) There is no mention in the manuscript about the fact that the transgene rats have several copies of rhodopsin and how this can affect these sex differences. Would it be the same in the P23H KO mouse? Or in other models with a single copy of the mutation?

We have described in the Materials and Methods section how they were bred, but we did not specifically mention the allele status in the manuscript. Hemizygous P23H-1 rats used in this study carry a single P23H transgene allele with a transgene copy number of 9, in addition to the normal two wild-type opsin alleles. We added this description to clear the uncertainty (lines 384-387.

(2) This sentence: in abstract lines 26 to 29: "Recently, we identified reserpine as a lead molecule for maintaining rod survival in mouse and human retinal organoids as well as in the rd16 mouse, which phenocopy Leber congenital amaurosis caused by mutations in the cilia-centrosomal gene CEP290 (Chen et al. eLife 2023;12:e83205. DOI: https://doi.org/10.7554/eLife.83205)", to my vew, does not belong to the abstract, maybe in the introduction as stage of art.

Thank you for asking. According to the guidelines for the research advance articles (that follow previously published studies), a reference to the original eLife article should be included in the abstract. As specified in the guidelines, we have updated the citation format to (author, year) for referencing eLife articles (line 29).

(3) Lines 167-170: "Histologic evaluation of the retinas also demonstrated more prominent ONL thinning in the dorsal retina and increased ONL thickness in the dorsal retina measured at 1,000, 1,250, and 1,500 µm distant from the optic nerve head in reserpine-treated group compared with control group (Figure 3C)". I do not understand this sentence. Is it a more prominent thinning or an increased thickness?

We apologize for the confusion caused by this sentence. The histological evaluation showed that ONL thinning was more pronounced in the dorsal retina of control group, which was consistent with OCT findings in Figure 3A. Reserpine treatment increased the ONL thickness in the dorsal retina at specific distances from the optic nerve head (1,000, 1,250, and 1,500 µm). We have revised the sentence for clarity (lines 165-168).

(4) Lines 182-185 and Figure 4B: FL is not the best approach to quantify rhodopsin levels. Since the DAPI staining is overexposed, it is hard to evaluate the staining of RHO in the ONL. From the visible staining in the OS, it is only possible to affirm that the OS are longer in RSP-treated retinas... more is not to be affirmed based on these figures. I suggest using WB.

We acknowledge the reviewer’s concern regarding the use of fluorescence imaging to quantify rhodopsin levels. While our current data highlight structural preservation, such as the length of the outer segments, we agree that drawing conclusions about rhodopsin levels from fluorescence staining is limited. As we do not have samples for WB and fluorescence imaging cannot quantify rhodopsin, we have revised the description (lines 180-184).

(5) Lines 188-190 and Figure 4C: The images in 4C showed an extreme divergence between treated and untreated retina concerning the amount of stained cones, which is not observed at the quantification at 1000µm statistic. Are the images not representative?

We agree with the reviewer that the images in Figure 4C may not adequately represent the quantified data. To address this, we have changed the figure to reflect the quantification results accurately.

(6) Figures 6C-6D and 6G. Why do the authors not use any statistical analysis? Or are the differences not statistically significant? Why do authors use only WT and DMSO controls? What about untreated P23H controls (no DMSO)?

Thanks for checking, and we apologize for the oversight. We have updated figures 5, 6 and S5 to include adjusted p-value in relevant plots. In addition, details of significance threshold are available in supplementary tables. Regarding controls, untreated P23H retinas (without DMSO) were not included in the current analysis, as our experience shows that DMSO injection itself does not cause functional or structural changes. The key data demonstrating the effect of reserpine involve a comparison between the group treated with reserpine and the control group treated with DMSO, as the only difference between these groups is the involvement of the drug.

(7) Validation of findings by testing key genes (e.g., p62/SQSTM1, Nrf2) using qPCR or immunohistochemistry will strengthen the findings.

We appreciate the reviewer’s suggestion to validate key findings using qPCR or immunohistochemistry, as such experiments are crucial for further strengthening our conclusions. While this was not feasible in the current study due to various constraints, we fully recognize their importance and plan to incorporate these in our follow-up studies.

eLife Assessment

In this valuable study, the authors integrate several datasets to describe how the genome interacts with nuclear bodies across distinct cell types and in Lamin A and LBR knockout cells. They provide convincing evidence to support their claims and particularly find that specific genomic regions segregate relative to the equatorial plane of the cell when considering their interaction with various nuclear bodies.

Reviewer #3 (Public review):

Summary:

Golamalamdari, van Schaik, Wang, Kumar Zhang, Zhang and colleagues study interactions between the speckle, nucleolus and lamina in multiple cell types (K562, H1, HCT116 and HFF). Their datasets define how interactions between the genome and the different nuclear landmarks relate to each other and change across cell types. They also identify how these relationships change in K562 cells in which LBR and LMNA are knocked out.

Strengths:

Overall, there are a number of datasets that are provided, and several "integrative" analyses performed. This is a major strength of the paper, and I imagine the datasets will be of use to the community to further probed and the relationships elucidated here further studied. An especially interesting result was that specific genomic regions (relative to their association with the speckle, lamina, and other molecular characteristics) segregate relative to the equatorial plane of the cell.

Weaknesses:

The experiments are primarily descriptive, and the cause-and-effect relationships are limited (though the authors do study the role of LMNA/LBR knockdown with their technologies).

Comments on revisions:

I have no additional comments. I appreciate the authors responding to my previous comments. I anticipate the datasets and concepts raised will be helpful to many investigators in the field.

Author response:

The following is the authors’ response to the previous reviews

Response to Public Reviews:

We would like to thank the reviewers and editors once more for their time and effort in reviewing our manuscript. Below we discuss specifically our response to the recommendations of Reviewer 2, which were the only substantial changes we made to the manuscript.

Reviewer 2 recommendation:

"My only remaining suggestion is that the authors acknowledge and cite the work of other groups which have similarly found different subsets of LADs based on various molecular/epigenetic features:

(1) doi.org/10.1101/2024.12.20.629719

(2) PMID: 25995381

(3) PMID: 36691074

(4) PMID: 23124521 (fLADs versus cLADs, as described by the authors themselves) The exact subtypes of LADs might be different based on the features examined, but others have found/implicated the existence of different types of LADs. Hence, the pwv-LAD should be contextualized within these findings (which they do relative to v-fiLADs)."

We thank the reviewer for this suggestion and for these references. We think that the best place to go into depth about how our work relates to these references would be in an appropriate review article.

However, we did read these references carefully and responded, as described below, by adding additional clarifying text in the manuscript as well as mention of articles specifically relevant to our description of our results.

(1) Reviewer 2 wrote specifically, "Hence, the pwv-LAD should be contextualized within these findings (which they do relative to v-fiLADs)"

We are not sure exactly what Reviewer 2 means here. In this manuscript we defined p-w-v iLADs, not LADs. So, it would be inappropriate to compare a subset of iLAD regions with different types of LADs.

If this was the meaning of Reviewer 2, then other readers might have similar confusion. Therefore, we added the following clarifying text in red:

"Several previous studies have used varying approaches to subdivide LADs further into distinct subsets of LADs with different biochemical and/or functional properties (Martin et al., 2024; Meuleman et al., 2013; Shah et al., 2023; Zheng et al., 2015). However, in this Section we focused instead on asking whether regions specifically within iLADs might show differential localization relative to the lamina and/or nucleoli and, if so, whether these regions would show different levels of gene expression. More specifically, analogously to how gene expression hot-zones appeared as local maxima in speckle TSA-seq with early DNA replication timing, we asked whether iLAD regions that appeared as local maxima in lamina proximity mapping signals would correspond to iLAD regions with locally reduced gene expression levels and later DNA replication timing relative to their flanking iLAD sequences. Our rationale was that these iLAD regions might represent chromatin domains that together with their flanking iLAD regions would typically localize well within the nuclear interior but in a fraction of the cell population would loop back and attach at the nuclear periphery."

(2) We also added the following text near the end of the section about p-w-v iLADs to place them in the context of one class of "LADs" identified by ChIP-seq rather than DamID. We use quotation marks since the approach used produced a segmentation that included a nearly 50/50 mix of iLAD and LAD regions, as identified by DamID, for this class of domains.

"We note that in a previous study a three-state Hidden Markov Model (HMM) segmented lamin B ChIP-seq data into two chromatin domain states with extensive overlap with LADs defined by lamina DamID (Shah et al., 2023). Whereas the late replicating, low gene density/expression "T1 LAD" state showed very high overlap (98%) with LADs defined by DamID, the intermediate replicating, intermediate gene expression "T2 LAD" state showed only 47% overlap with LADs defined by DamID. This was partly a result of the HMM segmentation algorithm but also due to substantial differences between the lamina ChIPseq versus DamID signals for reasons that remain unclear. The subset of p-w-v iLADs included in T2 comprise only a small percentage of the total T2 LAD coverage, which includes both other iLAD and LAD regions. Thus, the p-w-v iLADs we identified here represent a novel and distinct class of iLAD chromatin domains, not previously described."

(3) Alternatively, what Reviewer 2 might be suggesting implicitly is that we should start with the regions identified as p-w-v iLADs in one cell type and then identify all of those p-w-v iLADs which instead exist as LADs in a second cell type. Once we have identified their LAD equivalents in a second cell type we could then ask whether they possess special characteristics such that they correspond to a specific type of LAD subset. Finally, we could then ask how that specific type of LAD subset compared to the different subtypes of LADs identified by other groups and, in particular, the references Reviewer 2 provided.

We agree that would be an interesting future direction, but we consider that as outside the scope of this current manuscript. We note that we did no such analysis of the characteristics of LADs which existed as p-w-v iLADs in a different cell line. We save that for a possible future analysis, ideally in the same cell types as used in the cited references to allow a more direct comparison.

(4) Finally, we added text in the Discussion that relates our analysis of the differential SON and LMNB1 TSA-seq signals for different LAD regions, and how these correlate with different histone modifications, with results from the recent preprint cited by Reviewer 2. Note that we could not directly correlate our results from human cells with the three classes of LADs described in MEFs by this preprint.

"Fourth, we show how LAD regions showing different histone marks- either enriched in H3K9me3, H3K9me2 plus H2A.Z, H3K27me3, or none of these marks- can differentially segregate within nuclei. These results support the previous suggestion of different "flavors" of LAD regions, based on the sensitivity of the autonomous targeting of BAC transgenes to the lamina to different histone methyltransferases (Bian et al., 2013). Differential nuclear localization also was recently inferred by the appearance of different Hi-C Bsubcompartments, which similarly were differentially enriched in either H3K9m3, H3K27me3, or the combination of H3K9me2 and H2A.Z (Spracklin et al., 2023). More recently, and while this paper was in revision, a new study described segmenting mouse embryonic fibroblast LADs into three clusters using histone modification profiling (Martin et al., 2024). Interestingly, these three LAD clusters also most notably differed by their dominant enrichment of either H3K9me3, H3K9me2, or H3K27me3. Thus, three orthogonal approaches have converged on identifying different LAD regions showing differential enrichment either of H3K9me3, H3K9me2, or H3K27me3. Here, our use of TSA-seq directly measures and assigns the intranuclear localization of these different LAD regions to different nuclear locales."

eLife Assessment

Using multiple techniques previously validated by the authors, this study identified INTS12, a component of the Integrator complex involved in 3' processing of small nuclear RNAs U1 and U2, as a factor promoting HIV-1 latency. The work is valuable, based on a sound strategy for screening targets to activate HIV latency and the solid mechanistic insights it provides on INTS12 repression of transcriptional elongation. Future studies are needed to explore INTS12 as a drug target against HIV/AIDS.

Reviewer #1 (Public review):

Gray and colleagues describe the identification of Integrator complex subunit 12 (INTS12) as a contributor to HIV latency in two different cell lines and in cells isolated from the blood of people living with HIV. The authors employed a high-throughput CRISPR screening strategy to knock down genes and assess their relevance in maintaining HIV latency. They had used a similar approach in two previous studies, finding genes required for latency reactivation or genes preventing it and whose knockdown could enhance the latency-reactivating effect of the NFκB activator AZD5582. This work builds on the latter approach by testing the ability of gene knockdowns to complement the latency-reactivating effects of AZD5582 in combination with the BET inhibitor I-BET151. This drug combination was selected because it has been previously shown to display synergistic effects on latency reactivation.

The finding that INTS12 may play a role in HIV latency is novel, and the effect of its knock down in inducing HIV transcription in primary cells, albeit in only a subset of donors, is intriguing.

In this revised version, the authors have included new data and clarifications which help strengthen their conclusions.

Reviewer #2 (Public review):

Summary:

Identifying an important role for Integrator complex in repressing HIV transcription and suggesting that by targeting subunits of this complex specifically, INTS12, reversal of latency with and without latency reversal agents can be enhanced.

Strengths:

The strengths of the paper include the general strategy for screening targets that may activate HIV latency and the rigor of exploring the mechanism of INTS12 repression of HIV transcriptional elongation.

Weaknesses:

Minor point-there was an opportunity to examine a larger panel of latency reversal agents that reactivate by different mechanisms to determine whether INTS12 and transcriptional elongation are limiting for a broad spectrum of latency reversal agents.

Comments on revisions:

I feel the authors have adequately addressed the original questions and concerns.

Reviewer #3 (Public review):

Summary:

Transcriptionally silent HIV-1 genomes integrated in the host`s genome represent the main obstacle for an HIV-1 cure. Therefore, agents aimed at promoting HIV transcription, the so-called latency reactivating agents (LRAs) might represent useful tools to render these hidden proviruses visible to the immune system. The authors successfully identified, through multiple techniques, INTS12, a component of the Integrator complex involved in 3' processing of small nuclear RNAs U1 and U2, as a factor promoting HIV-1 latency and hindering elongation of the HIV RNA transcripts. This factor hinders the activity of a previously identified combination of LRAs, one of which, AZD5582, has been validated in the macaque model for HIV persistence during therapy (https://pubmed.ncbi.nlm.nih.gov/37783968/). The other compound, I-BET151, is known to synergize with AZD5582, and is a inhibitor of BET, factors counteracting elongation of RNA transcripts.<br /> Therefore, INTS12 maight represent a target for future LRAs-

Strengths:

Findings were confirmed through multiple screens and multiple techniques. The authors successfully mapped the identified HIV silencing factor at the HIV promoter, Silencing of INTS12 increases the activity of small-molecule HIV latency-reversing agents such as the histone deacetylase inhibitor vorinostat. Knockdown of INTS12 does not induce toxic effects in the cells, thus rendering it a candidate a drug discovery campaign aimed at finding new agents for an HIV/AIDS cure.

Weaknesses:

A caveat is that the impact of INTS12 in diverse T cell functions or other in vivo functions is not yet known, but the authors acknowledge this in the revised discussion.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Gray and colleagues describe the identification of Integrator complex subunit 12 (INTS12) as a contributor to HIV latency in two different cell lines and in cells isolated from the blood of people living with HIV. The authors employed a high-throughput CRISPR screening strategy to knock down genes and assess their relevance in maintaining HIV latency. They had used a similar approach in two previous studies, finding genes required for latency reactivation or genes preventing it and whose knockdown could enhance the latency-reactivating effect of the NFκB activator AZD5582. This work builds on the latter approach by testing the ability of gene knockdowns to complement the latency-reactivating effects of AZD5582 in combination with the BET inhibitor I-BET151. This drug combination was selected because it has been previously shown to display synergistic effects on latency reactivation.

The finding that INTS12 may play a role in HIV latency is novel, and the effect of its knockdown in inducing HIV transcription in primary cells, albeit in only a subset of donors, is intriguing. However, there are some data and clarifications that would be important to include to complement the information provided in the current version of the manuscript.

We have now added the requested data and clarifications. In particular, we show that knockout of INTS12 has no effect on cell proliferation (new data added in Figure 2—figure supplement 3)), we clarify how the degree of knockout and the complementation were accomplished, we clarify the differences between the RNA-seq and the activation scores, and we have bolstered the claim that INTS12 affected transcription elongation by performing CUT&Tag on Ser2 phosphorylation of the C-terminal tail of RNAPII along the length of the provirus (new data added in Figure 5C) Please see detailed responses below.

Reviewer #2 (Public review):

Summary:

Identifying an important role for the Integrator complex in repressing HIV transcription and suggesting that by targeting subunits of this complex specifically, INTS12, reversal of latency with and without latency reversal agents can be enhanced.

Strengths:

The strengths of the paper include the general strategy for screening targets that may activate HIV latency and the rigor of exploring the mechanism of INTS12 repression of HIV transcriptional elongation. I found the mechanism of INTS12 interesting and maybe even the most impactful part of the findings.

Weaknesses:

I have two minor comments:

There was an opportunity to examine a larger panel of latency reversal agents that reactivate by different mechanisms to determine whether INTS12 and transcriptional elongation are limiting for a broad spectrum of latency reversal agents.

I felt the authors could have extended their discussion of how exquisitely sensitive HIV transcription is to pausing and transcriptional elongation and the insights this provides about general HIV transcriptional regulation.

We have now added data on latency reversal agents of different mechanisms of action. We show that INTS12 affects HIV latency reversal from agents that affect the non-canonical NF-kB pathway (AZD5582), the canonical NF-kB pathway (TNF-alpha), activation via the T-cell receptor (CD3/CD28 antibodies), through bromodomain inhibition (I-BET151), and through a histone deacetylase inhibitor (SAHA). This additional data has been added to the manuscript in Figure 7, panels B and C as well as adding text to the discussion.

We appreciate the suggestion to extend the discussion to emphasize how important pausing and elongation are to HIV transcription. Additionally, to further support our claim that INTS12KO with AZD5582 & I-BET151 leads to an increase in elongation, that we previously showed with CUT&Tag data showing an increase in total RNAPII seen in within HIV (Figure 5B), we measured RNAPII Ser2 phosphorylation (Figure 5C) and RNAPII Ser5 phosphorylation (Figure 5—figure supplement 2) and added these findings to the manuscript. Upon measuring Ser2 phosphorylation, a marker associated with elongation, we observed evidence of elongation-competent RNAPII in our AZD5582 & I-BET151 condition as well as our INTS12 KO with AZD5582 & I-BET151 condition, as we saw an increase of Ser2 phosphorylation within HIV. Despite seeing elongation-competent RNAPII in both conditions, we only saw a dramatic increase in total RNAPII for our INTS12 KO and AZD5582 & I-BET151 condition (Figure 5B), which supports that there are more elongation events and that an elongation block is overcome specifically with INTS12 KO paired with AZD5582 & I-BET151. This claim is further supported by our data showing an increase in virus in the supernatant only with the INTS12 KO with AZD5582 & I-BET151 condition in cells from PLWH (Figure 6C). We did not observe any statistically significant differences between RNAPII Ser5 phosphorylation, which might be expected as this mark is not associated with elongation (Figure 5—figure supplement 2).

Reviewer #3 (Public review):

Summary:

Transcriptionally silent HIV-1 genomes integrated into the host`s genome represent the main obstacle to an HIV-1 cure. Therefore, agents aimed at promoting HIV transcription, the so-called latency reactivating agents (LRAs) might represent useful tools to render these hidden proviruses visible to the immune system. The authors successfully identified, through multiple techniques, INTS12, a component of the Integrator complex involved in 3' processing of small nuclear RNAs U1 and U2, as a factor promoting HIV-1 latency and hindering elongation of the HIV RNA transcripts. This factor synergizes with a previously identified combination of LRAs, one of which, AZD5582, has been validated in the macaque model for HIV persistence during therapy (https://pubmed.ncbi.nlm.nih.gov/37783968/). The other compound, I-BET151, is known to synergize with AZD5582, and is a inhibitor of BET, factors counteracting the elongation of RNA transcripts.

Strengths:

The findings were confirmed through multiple screens and multiple techniques. The authors successfully mapped the identified HIV silencing factor at the HIV promoter.

Weaknesses:

(1) Initial bias:

In the choice of the genes comprised in the library, the authors readdress their previous paper (Hsieh et al.) where it is stated: "To specifically investigate host epigenetic regulators involved in the maintenance of HIV-1 latency, we generated a custom human epigenome specific sgRNA CRISPR library (HuEpi). This library contains sgRNAs targeting epigenome factors such as histones, histone binders (e.g., histone readers and chaperones), histone modifiers (e.g., histone writers and erasers), and general chromatin associated factors (e.g., RNA and DNA modifiers) (Fig 1B and 1C)".

From these figure panels, it clearly appears that the genes chosen are all belonging to the indicated pathways. While I have nothing to object to on the pertinence to HIV latency of the pathways selected, the authors should spend some words on the criteria followed to select these pathways. Other pathways involving epigenetic modifications and containing genes not represented in the indicated pathways may have been left apart.

(2) Dereplication:

From Figure 1 it appears that INTS12 alone reactivates HIV -1 from latency alone without any drug intervention as shown by the MACGeCk score of DMSO-alone controls. If INTS12 knockdown alone shows antilatency effects, why, then were they unable to identify it in their previous article (Hsieh et al., 2023)? The authors should include some words on the comparison of the results using DMSO alone with those of the previous screen that they conducted.

(3) Translational potential:

In order to propose a protein as a drug target, it is necessary to adhere to the "primum non nocere" principle in medicine. It is therefore fundamental to show the effects of INTS12 knockdown on cell viability/proliferation (and, advisably, T-cell activation). These data are not reported in the manuscript in its current form, and the authors are strongly encouraged to provide them.

Finally, as many readers may not be very familiar with the general principles behind CRISPR Cas9 screening techniques, I suggest addressing them in this excellent review: https://pmc.ncbi.nlm.nih.gov/articles/PMC7479249/.

(1) The CRISPR library used was more completely described in a previous publication (Hsieh et al, PLOS Pathogens, 2023). However, we now more explicitly refer the reader to information about the pathways targeted in the library. We also point out how initial hits in the library lead to finding genes outside of the starting library as in the follow-up screen in Figure 7 where each of the members of the INT complex are interrogated even though only INTS12 was the only member in the initial library.

(2) We understand the confusion between the hits in this paper and a previous publication. Indeed, INTS12 was observed in Hsieh et al., PLOS Pathogens, 2023 as a hit in the Venn diagram of Figure 3B of that paper, and in Figure 5A, right panel of that paper. However, it was not followed up on in the previous paper since that paper focused on a hit that was unique to increasing the potency of one particular LRA. We added text to the present manuscript to make it clear that the screens identified many of the same hits. We have also added additional data here on hit validation to underscore the reliability of the CRISPR screen. In one of the cell lines (5A8), EZH2 was a strong hit (Figure 1B). We have now added data that shows that an inhibitor to EZH2 augments the latency reversal of AZD5582/I-BET151 as predicted from the screen. This data has been added to Figure 1, figure supplement 1.

(3) We appreciate the concern that for INTS12 to be a drug target, it should not be essential to cell viability. We now show that knockout of INTS12 has no effect on cell proliferation (new data added in Figure 2—figure supplement 3). In addition, the discussion now adds additional literature references that describe how knockout of INTS12 has relatively minor effects on cell functions in comparison to knockout of other INT members which supports that the proposal that modulation of INTS12 may be more specific than targeting the catalytic modules of Integrator. Nonetheless, we completely agree with the reviewer that many other aspects of how INTS12 affects T cell functions have not been addressed as well as other potential detrimental effect of INTS12 as a drug target in vivo. We now more explicitly describe these caveats in the discussion but feel that the present manuscript is a first step with a long path ahead before the translational potential might be realized.

(4) We now cite the review of CRISPR screens suggested by the reviewer.

Responses to recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) The authors report in the legend of Figure 2 (and similarly in other figures) that there was "a calculated INTS12 knockout score of 76% (for the one guide used) and 69% (for one of three guides used), respectively." However, it would be helpful to show representative data on the efficiency of INTS12 knockdown in cell lines and primary cells, as well as data on the efficiency of the complementation (Figure 2C).

The knockout scores cited are the genetic assays for the efficiency based on sequence files. As the knockouts are done with multiple guides the knockout for each guide is an underestimate of the total knockout. The complementation, however, was done by adding back INTS12 in a lentiviral vector that also contains a drug resistance marker (puromycin). Cells were then selected for puromycin resistance, and therefore, all of them contain the complemented gene. What one would ideally like is a Western blot to quantify the amount of INTS12 remaining in the knockout pools. Unfortunately, despite obtaining multiple different commercial sources of INTS12 antibodies, we were unable to identify one that was suitable for Western blotting (as opposed to two that did work for CUT&Tag). Nonetheless, the functional data in primary T cells from PLWH and in J-Lat cells lines does show the even if the knockout is suboptimal, we find activation after INTS12 knockout (e.g., Figure 6).

(2) Flow cytometry methods are not reported, but was a viability dye included when testing GFP reactivation (Figure S2)? More broadly, showing data on the viability of cells post-knockdown and drug treatments would help, as cell mortality is inherently associated with latency reactivation in J-Lat cells. For the same reason, reporting viability data would be important for primary cells, as the electroporation procedure can lead to significant mortality.

We did not include viability dyes in the data for GFP activation. However, as described in the public response, we have done growth curves in J-Lat 10.6 cells with and without INTS12 knockout and find no effects on cell proliferation (Figure 2—figure supplement 3). As the reviewer points out, it is not possible to do these experiments in primary cells since the electroporation itself causes a degree of cell death. Nonetheless, we do see effects on HIV activation in these primary cells (Figure 6).

(3) Figure S2 shows a relatively high baseline expression (approximately 15%) of HIV-GFP, which is not unusual for the J-Lat 10.6 clone. However, Figure 3 appears to show no HIV RNA reads in the control condition of this same cell clone. How do the authors reconcile this discrepancy?

We believe that the discrepancies in the flow cytometry versus RNA-seq assays are due to differences in the sensitivity of the assays, the linear range of the assays especially at the lower end, and the different half-lives of RNA versus protein. We now clarify that Figure 3 does not show “no” HIV RNA at baseline, but rather values of ~30 copies per million read counts. This increases to ~800 copies per million read counts when INTS12 knockout cells are treated with AZD5582/I-BET151. These values have the same fold change predicted in Figure 4, and more closely resemble the trend in Figure 2—figure supplement 1.

(4) The combination of AZD5582 and I-BET151 consistently reactivates HIV latency (including GFP protein expression), as previously reported and as shown here by the authors. However, in Figure 5B, RPB3/RNAPII occupancy in the DMSO control appears higher than in the AAVS1KO + AZD5582 and I-BET151 samples. This should be discussed, as it could raise concerns about the robustness of RPB3/RNAPII occupancy results as a proxy for provirus elongation.

As addressed in the public comments, in order to strengthen our claims about transcriptional elongation control, we measured RNAPII Ser2 and Ser5 phosphorylation levels. We see evidence of elongation with Ser2 in the condition of concern (AAVS1 KO + AZD5582 & I-BET151) as well as our main condition of interest (INTS12 KO + AZD5582 & I-BET151) and no change in Ser5 for any condition. With both the Ser2 phosphorylation and total RNAPII as well as our virus release and transcription data we believe that we are seeing evidence of increased elongation with INTS12 KO with AZD5582 & I-BET151. One potential nuance that may not be gathered from the CUT&Tag data is the turnover rate of the polymerase. Despite the levels of RNAPII appearing lower in the condition of concern (AAVS1 KO + AZD5582 & I-BET151) compared to DMSO it is possible that low levels of elongation are occurring but that in our INTS12 KO + AZD5582 & I-BET151 condition there is more rapid elongation and this is why we can observe more RNAPII within HIV. This new data is added in Figure 5C and Figure 5—supplement 2 and its implications are now described in more detail in the discussion.

(5) The authors write that "Degree of reactivation was correlated with reservoir size as donors PH504 (star symbol) and PH543 (upside down triangle) have the largest HIV reservoirs (supplemental Figure S2)." I could not find mention of the reservoir size of these donors in the figure provided.

This confusion was caused by mislabeling of the supplement number, which we fixed, and we added additional labeling to make finding the reservoir size even more clear as this is an important part of the manuscript. This is now found in Supplemental file S4.

Reviewer #3 (Recommendations for the authors):

(1) The MAGeCK gene score is a feature that is essential for the interpretation of the results in Figure 1. The authors do quote the Li et al. paper where this score was described for the first time (https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0554-4), however, they may understand that not all readers may be familiar with this score. Therefore a didactic short description of this score should be done when introducing the results in Figure 1.

We have added a short description to the paper to address this.

(2) Figure 4. The authors write: "Among the host genes most prominently affected by INTS12 knockout with AZD5582 & I-BET151 are MAFA, MAFB, and ID2 (full list of genes in supplemental file S3)." I am a bit confused. In the linked Excel file there is only a list of a few genes. The differentially expressed genes appear to be many more from Figure 4. The full list should be uploaded.

We believe there was a mistake in our original uploading and naming of the supplements. We have now double-checked numbering on the supplements and added in text clarification of which excel tabs hold the desired information.

(3) Figure 6: The authors are right in highlighting that there is a high level of variability in viral RNA in supernatants in the early stages of viral reactivation. It is therefore advisable to repeat measurements at Day 7, at which variability decreases and data are more reliable (please, see: https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(23)00443-7/fulltext).

While it would have been nice to prolong these measurements, our current assay conditions are not optimal for longer term growth of the cells. We note that the measurements were all done in biological triplicates (independent knockouts) and in different individuals. Because the number of activatable latent proviruses is variable and the number of cells tested is limiting, the variability in the assays is expected.

(4) Figure 7: The main genes outside the INTS family should be identified, also.

We include the full list in supplemental file S5 and sort by most enriched.

(5) Methods: A statistical paragraph should be added in the Methods section, detailing the data analysis procedures and the key parameters utilized (for example, which is the MAGeCK gene score threshold that they used to consider knockdown efficacy on HIV latency?).

There is no MAGeCK score threshold that we use to determine efficacy on HIV latency. In a previous publication using CRISPR screens for HIV Dependency Factors (Montoya et al, mBio 2023), we showed that there is a relationship between the MAGeCK and the effect of that gene knockout on HIV replication (Figure 5 that paper). However, it is a continuum rather than a strict threshold and we believe that the effects on HIV latency would respond similarly. In the current paper, we have focused on the top hits rather than a comprehensive analysis of all the entire list. In case the reviewer is referring to the average and standard deviation of the non-targeting controls, we have added this to the figure legend and methods.

eLife Assessment

This valuable study investigates both online responses to, and offline replay of, visual motion sequences. Sophisticated EEG analyses provide convincing evidence for both feature-specific and non-specific sequence representations. These intriguing findings will be of interest to perception and learning researchers alike.

Reviewer #1 (Public review):

Summary:

The study identifies two types of activation: one that is cue-triggered and non-specific to motion directions, and another that is specific to the exposed motion directions but occurs in a reversed manner. The finding that activity in the medial temporal lobe (MTL) preceded that in the visual cortex suggests that the visual cortex may serve as a platform for the manifestation of replay events, which potentially enhance visual sequence learning.

Evaluations:

Identifying the two types of activation after exposure to a sequence of motion directions is very interesting. The experimental design, procedures and analyses are solid. The findings are interesting and novel.

In the original submission, it was not immediately clear to me why the second type of activation was suggested to occur spontaneously. The procedural differences in the analyses that distinguished between the two types of activation need to be a little better clarified. However, this concern has been satisfactorily addressed in the revision.