Author response:

We thank both reviewers for their feedback and for underlying the potential of our new tool and experimental approach to identify signalling molecules that can improve the in vitro derivation of specific cell types from human pluripotent stem cells. To address the reviewers' points we plan to carry out further analysis that should solidify our conclusions. We will also edit the text to temper conclusions where appropriate.

Reviewer #2 (Public Review):

To enable robust production of hematopoietic progenitors in-vitro, Petazzi et al examined the role of transcription factors in the arterial hemogenic endothelium. They use IGFBP2 as a candidate gene to increase the directed differentiation of iPSCs into hematopoietic progenitors. They have established a novel induced-CRISPR mediated activation strategy to drive the expression of multiple endogenous transcription factors and show enhanced production of hematopoietic progenitors through expansion of the arterial endothelial cells. Further, upregulation of IGFBP2 in the arterial cells facilitates the metabolic switch from glycolysis to oxidative phosphorylation, inducing hematopoietic differentiation. While the overall study and resources generated are good, assertions in the manuscript are not entirely supported by the experimental data and some claims need further experimental validation.

eLife assessment

This study presents useful findings to inform and improve the in vitro differentiation of hematopoietic progenitor cells from human induced pluripotent stem cells. However, while relying on a well-characterized technical approach, the data analysis is overall incomplete and only partially supports the main conclusions.

Reviewer #1 (Public Review):

Summary:

The work from Petazzi et al. aimed at identifying novel factors supporting the differentiation of human hematopoietic progenitors from induced pluripotent stem cells (iPSCs). The authors developed an inducible CRISPR-mediated activation strategy (iCRISPRa) to test the impact of newly identified candidate factors on the generation of hematopoietic progenitors in vitro. They first compared previously published transcriptomic data of iPSC-derived hemato-endothelial populations with cells isolated ex vivo from the aorta-gonad-mesonephros (AGM) region of the human embryo and they identified 9 transcription factors expressed in the aortic hemogenic endothelium that were poorly expressed in the in vitro differentiated cells. They then tested the activation of these candidate factors in an iPSC-based culture system supporting the differentiation of hematopoietic progenitors in vitro. They found that the IGF binding protein 2 (IGFBP2) was the most upregulated gene in arterial endothelium after activation and they demonstrated that IGFBP2 promotes the generation of functional hematopoietic progenitors in vitro.

Strengths:

The authors developed an extremely useful doxycycline-inducible system to activate the expression of specific candidate genes in human iPSC. This approach allows us to simultaneously test the impact of 9 different transcription factors on in vitro differentiation of hematopoietic cells, and the system appears to be very versatile and applicable to a broad variety of studies.

The system was extensively validated for the expression of 1 transcription factor (RUNX1) in both HeLa cells and human iPSC, and a detailed characterization of this test experiment was provided.

The authors exhaustively demonstrated the role of IGFBP2 in promoting the generation of functional hematopoietic progenitors in vitro from iPSCs. Even though the use of IGFBP2-interacting proteins IGF1 and IGF2 have been previously reported in human iPSC-derived hematopoietic differentiation in vitro (Ditadi and Sturgeon, Methods 2016; Ng et al., Nature Biotechnology 2016), and IGFBP-2 itself has been shown to promote adult HSC expansion ex vivo (Zhang et al., Blood 2008), its role on supporting in vitro hematopoiesis was demonstrated here for the first time.

Weaknesses:

Although the authors performed a very thorough characterization of the system in proof-of-principle experiments activating a single transcription factor, the data provided when 9 independent factors were used is not sufficient to fully validate the experimental strategy. Indeed, in the current version of the manuscript, it is not clear whether the results presented in both the scRNAseq analysis and the functional assays are the consequence of the simultaneous activation of all 9 TF or just a subset of them. This is essential to establish whether all the proposed factors play a role during embryonic hematopoiesis, and a more complete analysis of the scRNAseq dataset could help clarify this aspect.

Similarly, the data presented in the manuscript are not sufficient to clarify at what stage of the endothelial-to-hematopoietic transition (EHT) the TF activation has an impact. Indeed, even though the overall increase of functional hematopoietic progenitors is fully demonstrated, the assays proposed in the manuscript do not clarify whether this is due to a specific effect at the endothelial level or to an increased proliferation rate of the generated hematopoietic progenitors. Similar conclusions can be applied to the functional validation of IGFBP2 in vitro.

The overall conclusions are sometimes vague and not always supported by the data. For instance, the authors state that the CRISPR activation strategy resulted in transcriptional remodeling and a steer in cell identity, but they do not specify which cell types are involved and at what level of the EHT process this is happening. In the discussion, the authors also claim that they provided evidence to support that RUNX1T1 could regulate IGFBP2 expression. However, this is exclusively based on the enrichment of RUNX1T1 gRNA in cells expressing higher levels of IGFBP2 and it does not demonstrate any direct or indirect association of the two factors.

Reviewer #2 (Public Review):

In their manuscript entitled "BEND2 is a crucial player in oogenesis and reproductive aging", the authors present their findings that full-length BEND2 is important for repair of meiotic double strand break repair in spermatocytes, regulation of LINE-1 elements in spermatocytes, and proper oocyte meiosis and folliculogenesis in females. The manuscript utilizes an elegant system to specifically ablate the full-length form of BEND2 which has been historically difficult to study due to its location on the X chromosome and male sterility of global knockout animals.

While the manuscript is an overall excellent addition to the field, it would significantly benefit from a few additional experiments, as well as some additional clarification/elaboration.

The claim that BEND2 is required for ovarian reserve establishment is not supported, as the authors only look at folliculogenesis and oocyte abundance starting at one week of age, after the reserve is formed. Analysis of earlier time points would be much more convincing and would parse the role of BEND2 in the establishment vs. maintenance of this cell population. In spermatocytes, the authors demonstrate a loss of nuclear BEND2 in their mutant but do not comment on the change in localization (which is now cytoplasmic) of the remaining protein in these animals. This may have true biological significance and a discussion of this should be more thoroughly explored.

eLife assessment

This study provides valuable information on a novel gene that regulates meiotic progression in both male and female meiosis, but the evidence supporting the conclusions of the authors on the role of BEND2 in oogenesis and reproductive aging is incomplete. This study will be of interest to developmental and reproductive biologists.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors investigate the role of BEND2, a novel regulator of meiosis, in both male and female fertility. Huang et al have created a mouse model where the full-length BEND2 transcript is depleted but the truncated BEND2 version remains. This mouse model is fertile, and the authors used it to study the role of BEND2 on both male and female meiosis. Overall, the full-length BEND2 appears dispensable for male meiosis. The more interesting phenotype was observed in females. Females exhibit a lower ovarian reserve suggesting that full-length BEND2 is involved in the establishment of the primordial follicle pool.

Strengths:

The authors generated a mouse model that enabled them to study the role of BEND2 in meiosis. The role of BEND2 in female fertility is novel and enhances our knowledge of genes involved in the establishment of the primordial follicle pool.

Weaknesses:

The manuscript extensively explores the role of BEND2 in male meiosis; however, a more interesting result was obtained from the study of female mice. Only a few experiments were performed using female mice, therefore, more experiments should be performed to complete the story of the role of BEND2 on female fertility. In addition, the title and abstract of the manuscript do not align with the story, as female fertility is only a small portion of the data compared to the male fertility section.

Reviewer #3 (Public Review):

Summary:

Huang et al. investigated the phenotype of Bend2 mutant mice which expressed a truncated isoform. This mutant male showed increasing apoptosis due to unrepaired double-strand breaks. However, this mutant male has fertility, and this enabled them to analyze Bend2 function in females. They revealed that Bend2 mutation in females showed decreasing follicle numbers which leads to loss of ovarian reserve.

Strengths:

Since their Bend2 mutant males were fertile, they were able to analyze the function of Bend2 in females and they revealed that loss of Bend2 causes less follicle formation.

Weaknesses:

Why the phenotype of their mutant male is different from previous work (Ma et al.) is not clear enough although they discuss it.

Reviewer #3 (Public Review):

Summary:

The authors conducted a time-resolved EEG decoding study where they presented sequences of dot locations (4 locations onscreen) or single elements of those sequences, presented at the correct temporal epoch for if they had been presented in the full sequence. They were interested in examining whether presenting single items would activate representations of the anticipated following events that were never presented. Stimuli were presented for 100 ms and separated by 200 ms ISIs. They also had pattern estimation blocks with 600 ms ISIs. They found indeed, that anticipated events could be decoded at their correct moment in time, although future anticipated elements could not.

The decoding of presented dots was fairly confined to the diagonal of the decoding matrix (training time x testing time), suggesting little temporal generalisation. This was in contrast with successor representations which were temporally more diffuse. The subsequent successor could be decoded but not future successors.

Strengths:

I liked this paper. The design was simple and clean and the implications of the findings are clear. The authors achieved their aims with this design, with the results supporting the conclusions. The findings will be of interest to a range of researchers studying learning and perception mechanisms, as well as the more generic role of prediction in the brain.

Weaknesses:

The sample size is fairly low for an EEG study. The authors justify it according to a previous Hogendoorn study, but not according to effect sizes in that study and particular power values.

For understandable reasons, the long ISI blocks were presented before the main test blocks (I would have made the same decision) but there is the risk that participants then come to expect stimuli at larger temporal separations in the main blocks. I do wonder whether this is part of the reason for the greater temporal generalisation for anticipated event representations.

Additional context:

My memory of Ekman et al. 2017 is that single events (presented at position 1) elicited predictive activation of anticipated future events, but that there was a temporal compression. The present study appears to show no temporal compression but that the representations are activated at the correct moment in time. This seems like a potentially interesting difference and one with mechanistic implications for the field.

eLife assessment

This valuable study investigates how a predicted - but not presented - stimulus within a sequence is represented in the brain using time-resolved EEG decoding. The results demonstrate that when the predicted stimulus is omitted, it is still represented at the expected space and time, although at present they provide only incomplete support given some alternative explanations. The findings will have implications for researchers across domains who are interested in learning and perception.

Reviewer #1 (Public Review):

Summary:

Li and colleagues describe an experiment whereby sequences of dots in different locations were presented to participants while electroencephalography (EEG) was recorded. By presenting fixed sequences of dots in different locations repeatedly to participants, the authors assumed that participants had learned the sequences during the experiment. The authors also trained classifiers using event-related potential (ERP) data recorded from separate experimental blocks of dots presented in a random (i.e., unpredictable) order. Using these trained classifiers, the authors then assessed whether patterns of brain activity could be detected that resembled the neural response to a dot location that was expected, but not presented. They did this by presenting an additional set of sequences whereby only one of the dots in the learned sequence appeared, but not the other dots. They report that, in these sequences with omitted stimuli, patterns of EEG data resembled the visual response evoked by a dot location for stimuli that could be expected, but were not presented. Importantly, this only occurred for an omitted dot stimulus that would be expected to appear immediately after the dot that was presented in these partial sequences.

This exciting finding complements previous demonstrations of the ability to decode expected (but not presented) stimuli in Blom et al. (2020) and Robinson et al. (2020) that are cited in this manuscript. It suggests that the visual system is able to generate patterns of activity that resemble expected sensory events, approximately at times at which an observer would expect them.

Strengths:

The experiment was carefully designed and care was taken to rule out some confounding factors. For example, gaze location was tracked over time, and deviations from fixation were marked, in order to minimise the contributions of saccades to above-chance decoding of dot position. The use of a separate block of dots (with unpredictable locations) to train the classifiers was also useful in isolating visual responses evoked by each dot location independently of any expectations that might be formed during the experiment. A large amount of data was also collected from each participant, which is important when using classifiers to decode stimulus features from EEG data. This careful approach is commendable and draws on best practices from existing work.

Weaknesses:

While there was clear evidence of careful experiment design, there are some aspects of the data analysis and results that significantly limit the inferences that can be drawn from the data. Both issues raised here relate to the use of pre-stimulus baselines and associated problems. As these issues are somewhat technical and may not be familiar to many readers, I will try to unpack each line of reasoning below. Here, it should be noted that these problems are complex, and similar issues often go undetected even by highly experienced EEG researchers.

Relevant to both issues, the authors derived segments of EEG data relative to the time at which each dot was presented in the sequences (or would have appeared when the stimuli were omitted in the partial sequences). Segments were derived that spanned -100ms to 300ms relative to the actual or expected onset of the dot stimulus. The 300ms post-stimulus time period corresponds to the duration of each dot in the sequence (100ms) plus the inter-stimulus interval (ISI) that was 200ms in duration before the next dot appeared (or would be expected to appear in the partial sequences). Importantly, a pre-stimulus baseline was applied to each of these segments of data, meaning that the average amplitude at each electrode between -100ms and 0ms relative to (actual or expected) stimulus onset was subtracted from each segment of data (i.e., each epoch in common EEG terminology). While this type of baseline subtraction procedure is commonplace in EEG studies, in this study design it is likely to cause problematic effects that could plausibly lead to the patterns of results reported in this manuscript.

First of all, the authors compare event-related potentials (ERPs) evoked by dots in the full as compared to partial sequences, to test a hypothesis relating to attentional tuning. They reported ERP amplitude differences across these conditions, for epochs corresponding to when a dot was presented to a participant (i.e., excluding epochs time-locked to omitted dots). However, these ERP comparisons are complicated by the fact that, in the full sequences, dot presentations are preceded by the presentation of other dots in the sequence. This means that ERPs evoked by the preceding dots in the full sequences will overlap in time with the ERPs corresponding to the dots presented at the zero point in the derived epochs. Importantly, this overlap would not occur in the partial sequence conditions, where only one dot was presented in the sequence. This essentially makes any ERP comparisons between full and partial sequences very difficult to interpret, because it is unclear if ERP differences are simply a product of overlapping ERPs from previously presented dots in the full sequence conditions. For example, there are statistically significant differences observed even in the pre-stimulus baseline period for this ERP analysis, which likely reflects the contributions ERPs evoked by the preceding dots in the full sequences, which are absent in the partial sequences.

The problems with interpreting this data are also compounded by the use of pre-stimulus baselines as described above. Importantly, the use of pre-stimulus baselines relies on the assumption that the ERPs in the baseline period (here, the pre-stimulus period) do not systematically differ across the conditions that are compared (here, the full vs. partial sequences). This assumption is violated due to the overlapping ERPs issue described just above. Accordingly, the use of the pre-stimulus baseline subtraction can produce spurious effects in the time period after stimulus onset (for examples see Feuerriegel & Bode, 2022, Neuroimage). This also makes it very difficult to meaningfully compare the ERPs following dot stimulus onset in these analyses.

The second issue relates to the use of pre-stimulus baselines and concerns the key finding reported in the paper: that EEG patterns corresponding to expected but omitted events can be decoded in the partial sequences. In the partial sequences, there are two critical epochs that were derived: One time-locked to the presentation of the dot, and another that was time-locked to 300ms after the dot was presented (i.e. when the next dot would be expected to appear). The latter epoch was used to test for representations of expected, but omitted, stimulus locations.

For the epochs in which the dots were presented, above-chance decoding can be observed spanning a training time range from around 100-300ms and a testing time range of a similar duration (see the plot in Figure 4b). This plot indicates that, during the time window of around 200-300ms following dot stimulus onset, the position of the dot can be decoded not only from trained classifiers using the same time windows spanning 200-300ms, but also using classifiers trained using earlier time windows of around 100-200ms.

This is important because the 200-300ms time period after dot onset in the partial sequences is the window used for pre-stimulus baseline subtraction when deriving epochs corresponding to the first successor representation (i.e., the first stimulus that might be expected to follow from the presented dot, but did not actually appear). In other words, the 200-300ms time window from dot onset corresponds to the -100 to 0 ms time window in the first successor epochs. Accordingly, the pattern that is indicative of the preceding, actually presented dot position would be subtracted from the EEG data used to test for the successor representation. Notably, the first successor condition would always be in another visual field quadrant (90-degree rotated or the opposite quadrant) as stated in the methods. In other words, the omitted stimulus would be expected to appear in the opposite vertical and/or horizontal visual hemifield as compared to the previously presented dot in these partial sequences.

This is relevant because ERPs tend to show reversed polarity across hemifields. For example, a stimulus presented in the right hemifield will have reversed polarity patterns at the same electrode as compared to an equivalent stimulus presented in the left hemifield (e.g., Supplementary Figure 3 in the comparable study of Blom et al., 2020). By subtracting the ERP patterns evoked by the presented dot in the partial sequences during the time period of 200-300ms (corresponding to the -100 to 0ms baseline window), this would be expected to bias patterns of EEG data in the first successor epochs to resemble stimulus positions in opposite hemifields. This could plausibly produce above-chance decoding accuracy in the time windows identified in Figure 5a, where the training time windows broadly correspond to the periods of above-chance decoding during 200-300ms from dot stimulus onset in Figure 4b.

In other words, the above-chance decoding of the first successor representation may plausibly be an artefact of the pre-stimulus baseline subtraction procedure used when deriving the epochs. This casts some doubt as to whether genuine successor representations were actually detected in the study. Additional tests for successor representations using ERP baselines prior to the presented dot in the partial sequences may be able to get around this, but such analyses were not presented, and the code and data were not accessible at the time of this review.

Although the study is designed well and a great amount of care was taken during the analysis stage, these issues with ERP overlap and baseline subtraction raise some doubts regarding the interpretability of the findings in relation to the analyses currently presented.

Reviewer #2 (Public Review):

Summary:

The authors investigated how predicted stimuli are represented in posterior regions of the brain by recording electroencephalography during a visual sequence learning task. After learning the spatial order in which four stimuli were presented within a fixed sequence, participants were shown partial sequences - i.e., sequences in which only one element of the sequence was presented. By examining the decoding accuracy of the omitted stimuli, the authors aimed to investigate whether anticipated stimuli are (pro)actively represented in the expected spatial location at the expected time.

Strengths and Weaknesses:

The study successfully replicated previous findings on omitted stimuli within a predicted sequence (Ekman et al., 2023), while providing novel information regarding the temporal dynamics of predictive representation. Nevertheless, this outcome is not entirely surprising, as similar temporal dynamics were observed in a previous study employing a different task (Kok et al., 2017). The high level of scientific rigor is evident, as demonstrated by the numerous control analyses. Additionally, the results are particularly intriguing in terms of discerning the nature of the prepared representation, spanning from early perceptual to late attentional representations. Unfortunately, this distinction is not investigated in detail, thus allowing for alternative interpretations of the results.

The connection between the findings and the literature on priority maps could benefit from further clarification. There is room for a clearer delineation of how much of the representation can be ascribed to a perceptual prediction mechanism versus an attentional (post-perceptual) spatial cueing process. Although the latter can be readily connected to the concept of a priority map guiding spatial attention, the relationship between the priority map and perceptual prediction remains somewhat ambiguous. Noteworthy, an explanation of the results in terms of spatial cueing does not necessarily require a perceptual predictive mechanism. The significant decoding of the location of the omitted stimulus might be attributed to the preceding stimulus orienting attention towards the following location. While this potential explanation was not explicitly addressed in the study, it presents an intriguing avenue for further investigation.

The study provides valuable insight into how omitted, yet predicted stimuli are represented in the brain and its dynamics. While the research is commendable, addressing the outlined limitations would enhance its impact in the field. Specifically, the spatial location decoding results do not disentangle between perceptual prediction (i.e., the features of the expected stimulus) and attentional processes (i.e., the cueing of the to-be-attended location),

Reviewer #2 (Public Review):

Summary:

In this manuscript, Shah et al. explore the function of an understudied neural circuitry from the dLS -> LHA -> RVM in mediating stress-induced analgesia. They initially establish this neural circuitry through a series of intersectional tracings. Subsequently, they conduct behavioral tests, coupled with optogenetic or chemogenetic manipulations, to confirm the involvement of this pathway in promoting analgesia. Additionally, fiber photometry experiments are employed to investigate the activity of each brain region in response to stress and pain.

Strengths:

Overall, the study is comprehensive, and the findings are compelling.

Weaknesses:

One noteworthy concern arises regarding the overarching hypothesis that restrained-induced stress promotes analgesia. A more direct interpretation suggests that intense struggling, rather than stress per se, activates the dLS -> LHA -> RVM pathway that may drive analgesic responses.

eLife assessment

This important work explores the modulation of pain by intense stress. The authors employed a series of cutting-edge techniques and provided convincing evidence suggesting that the dorsal lateral septum-> lateral hypothalamus-> rostral ventromedial medulla circuit is responsible for mediating stress-induced analgesia. This work will be of interest to neuroscientists interested in the neural circuits of behavior, and scientists interested in stress or pain.

Reviewer #1 (Public Review):

The manuscript entitled "A septo-hypothalamic-medullary circuit directs stress-induced analgesia" by Shah et al., showed that the dLS-to-LHA circuit is sufficient and necessary for stress-induced analgesia (SIA), which is mediated by the rostral ventromedial medulla (RVM) in a opioid-dependent manner. This study is interesting and important and the conclusions are largely supported by the data. I have a few concerns as follows:

(1) The present data show that activation of dLS neurons produces SIA, however, this manipulation is non-specific. It may be better to see the effect of specific manipulation of stress-activated c-Fos positive neurons in the dLS using a combination of the Tet-Off system and chemogenetic/optogenetic tools.

(2) Depending on its duration, and intensity, stress can exert potent and bidirectional modulatory effects on pain, either reducing pain (SIA) or exacerbating it (stress-induced hyperalgesia, SIH). Is the circuit in the manuscript involved in SIH?

(3) It is well-accepted that opioid and cannabinoid receptors participate in the SIA, and the evidence is especially strong for the RVM endocannabinoid system. Given this, why did the authors focus their study on the opioid system?

(4) Does silencing of the dLS neurons affect stress-induced anxiety-like behaviors? Alternatively, what is the relationship between SIA and the level of stress-induced anxiety?

(5) Direct electrophysiological evidence should be provided to confirm the efficacy of the MP-CNO.

(6) Is the LHA a specific downstream target for SIA, and is the LHA involved in stress-induced anxiety-like behaviors?

(7) Do LHA neurons have direct projections to the RVM? If yes, what is its role in the SIA?

Author response:

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

We sincerely appreciate the reviewer’s dedication to evaluating our manuscript and raising essential considerations regarding the classification of the migration behavior we described. While the reviewer suggests that this behavior aligns with the concept of itinerancy, we contend that it represents a distinct phenomenon, albeit with similarities, as both involve the non-breeding movements of birds. We acknowledge that our manuscript did not adequately address this distinction and have considered the reviewer’s feedback. In our response, we clarify the difference between the described phenomenon and itinerancy. Our revised manuscript will include a new section in the Discussion to address this issue comprehensively.

In the first part of the review, the reviewer emphasizes that the pattern we are describing is consistent with itinerancy. Regardless of the terminology used, we want to highlight the existence of two different types of migratory behavior, both of which involve movement in non-breeding areas.

The first type, called itinerancy, was first described by Moreau in 1972 in “The Palaearctic-African Bird Migration Systems.” As noted by the reviewer, this behavior involves an alternation of stopovers and movements between different short-term non-breeding residency areas. They usually occur in response to food scarcity in one part of the non-breeding range, causing birds to move to another part of the same range. These movements typically cover distances of 10 to 100 kilometers but are neither continuous nor directional. Moreau (1972) defined itinerancy as prolonged stopovers, normally lasting several months, primarily in tropical regions. He noted observations of certain species disappearing from his study areas in sub-Saharan Africa in December and others appearing, suggesting they may have multiple home ranges during the non-breeding season. Subsequent research, as mentioned by the reviewer, has confirmed itinerancy in many species, particularly among Palaearctic-African migrants in sub-Saharan Africa. In particular, the Montagu’s Harrier has been extensively studied in this regard. The reviewer rightly points out that our study does not include recent findings on this species. In our revised version, we will include references to recent studies, such as those by Trierweiler et al. (2013, Journal of Animal Ecology, 82:107-120) and Schlaich et al. (2023, Ardea, 111:321-342), which show that Montagu’s Harrier has an average of 3-4 home ranges separated by approximately 200 kilometers. These studies suggest that the species spends approximately 1.5 months at each site, with the most extended period typically observed at the last site before migrating to the breeding grounds.

In the second type, birds undertake a post-breeding migration, arrive in their non-breeding range, and then gradually move in a particular direction throughout the season. This continuous directional movement covers considerable distances and continues throughout the non-breeding period. In our study, this movement covered about 1000 km, comparable to the total migration distance of Rough-legged Buzzards of about 1500 km. As observed in our research, these movements are influenced by external factors such as snow cover. In such cases, the progression of snow cover in a south-westerly direction during winter can prevent birds from finding food, forcing them to continue migrating in the same direction. In essence, this movement represents a prolonged phase of the migration process but at a slower pace. Similar behavior has been documented in buzzards, as reported by Strandberg et al. (2009, Ibis 151:200-206). Although several transmitters in their study stopped working in mid-winter, the authors observed a phenomenon they termed ‘prolonged autumn migration.’

In the second part of the review, the reviewer questions the need to distinguish between the two behaviors we have discussed. However, we believe these behaviors differ in their structure (with the first being intermittent and often non-directional, whereas the second is continuous and directional) and in their causes (with the first being driven by seasonal food resource cycles and the second by advancing snow cover). We therefore argue that it is worth distinguishing between them. To differentiate these forms of non-breeding movement, we propose to use ‘itinerancy’ for the first type, as described initially by Moreau in 1972, and introduce a separate term for the second behavior. Although ‘slow directional itinerancy’ could be considered, we find it too cumbersome.

Moreover, ‘itinerancy’ in the literature refers not only to non-breeding movements but also to the use of different nesting sites, e.g., Lislevand et al. (2020, Journal of Avian Biology: e02595), reinforcing its association with movements between multiple sites within habitats. We, therefore, propose that the second behavior be given a distinct name. We acknowledge the reviewer’s point that we did not adequately address this distinction in the Discussion and plan to include a separate section in our paper’s revised version. In the third part of his review, the reviewer suggests an alternative title. Another reviewer, Dr Theunis Piersma, suggested the current title during the first round of reviewing, and we have chosen his version.

In the fourth part of the review, the reviewer questions whether it is appropriate to discuss the conservation aspect of this study. This type of non-breeding movement raises concerns about accurately determining non-breeding ranges and population dynamics for species that exhibit this behavior. We believe that accurate determination of range and population dynamics is critical to conservation efforts. While this may be less important for species breeding in Europe and migrating to Africa, for which monitoring breeding territories is more feasible, it’s essential for Arctic and sub-Arctic breeding species. Large-scale surveys in these regions have historically been challenging and have become even more so with the end of Arctic cooperation following Russia’s war with Ukraine (Koivurova, Shibata, 2023). For North America and Europe, non-breeding abundance is typically estimated once per season in mid-winter. In North America, these are the so-called Christmas counts (which take place once at the end of December), and in Europe, they are the IWC counts mentioned by the reviewer (as follows from their official website - “The IWC requires a single count at each site, which should be repeated each year. The exact dates vary slightly from region to region, but take place in January or February”). Because of such a single count in mid-winter, non-breeding habitats occupied in autumn and spring will be listed as ‘uncommon’ at best, while south-western habitats where birds are only present in mid-winter will be listed as ‘common.’ However, the situation will be reversed if we consider the time birds spend in these habitats.

The reviewer also highlights the introduction’s unconventional structure and information redundancy at the beginning. We have chosen this structure and provided basic explanations to improve readability for a wider audience, given eLife’s readership. At the same time, we will certainly take the reviewers’ feedback into account in the revised version. We plan to include the references to modern itinerancy research mentioned above and to add a section on itinerancy to the Discussion.

We appreciate the reviewer’s input and sincerely thank them for their time and effort in reviewing our paper. While we may not fully agree on the classification of the behavior we describe, we value the opportunity to engage in discussion and believe that presenting arguments and counterarguments to the reader is beneficial to scientific progress.

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

Reviewer #1 (Recommendations For The Authors):

I much enjoyed reading this manuscript, that is, once I understood what it is about. Titles like "Conserving bird populations in the Anthropocene: the significance of non-breeding movements" are a claim to so-called relevance, they have NOTHING to do with the content of the paper, so once I understood that this paper was about the "Quick quick slow: the foxtrot migration of rough-legged buzzards is a response to habitat and snow" (an alternative title), it was becoming very interesting. So the start of the abstract as well as the introduction is very tedious, as clearly much trouble is taken here to establish reputability. In my eyes this is unnecessary: eLife should be interested in publishing such a wonderful description of such a wonderful migrant in a study that comes to grips with limiting factors on a continental scale!

We sincerely appreciate your time and effort in reviewing our manuscript. Thank you for your appreciation of our study.

We agree that the focus of the article should be changed from conservation to migration patterns. We have rewritten the Introduction and Discussion as suggested. We have added the application of this pattern including conservation at the end of the Discussion by completely changing Figure 5. We have also changed the title to the suggested one.

Not sure that the first paragraph statements that seek to downplay what we know about wintering vs breeding areas are valid (although I see what purpose they serve). Migratory shorebirds have extensively been studied in the nonbreeding areas, for example, including movement aspects (see, as just one example, Verhoeven, M.A., Loonstra, A.H.J., McBride, A.D., Both, C., Senner, N.R. & Piersma, T. (2020) Migration route, stopping sites, and non breeding destinations of adult Black tailed Godwits breeding in southwest Fryslân, The Netherlands. Journal of Ornithology 162, 61-76) and there are very impressive studies on the winter biology of migrants across large scale (for example in Zwarts' Living on the Edge book on the Sahel wetlands). Think also about geese and swans and about seabirds!

We have rewritten the first paragraph and it now talks about patterns of migratory behavior. We have also rewritten the second paragraph, now it is devoted to studies of movements in the non-breeding period. We explain how our pattern differs from those already studied and give references to the papers you mentioned.

Directional movements in nonbreeding areas as a function of food (in this case locusts) have really beautifully been described by Almut Schlaich et al in JAnimEcol for Montagu's harriers.

We have added Montagu's harrier example in the second paragraph of the Introduction and the Discussion. We have added a reference to Schlaich and to Garcia and Arroyo, who suggested that Montagu's harriers have long directional migrations during the non-breeding period.

Once the paper starts talking buzzards, and the analyses of the wonderful data, all is fine. It is a very competent analysis with a description of a cool pattern.

Thank you for your appreciation of our study. We hope the revised version is better and clearer.

However, i would say that it is all a question of spatial scale. The buzzards here respond to changes in food availability, but there is not an animal that doesn't. The question is how far they have to move for an adequate response: in some birds movements of 100s of meters may be enough, and then anything to the scale of rough-legged buzzards.

In the new version of the manuscript, we emphasize that this is a large distance (about 1000 km), comparable to the distance of the fall and spring migrations (about 1400 km) in lines 70-72 of the Introduction and 379-383 of the Discussion.

And actually, several of the shorebirds I know best also do a foxtrot, such as red knots and bar-tailed godwits moulting in the Wadden Sea, then spending a few months in the UK estuaries, before returning to the Wadden Sea before the long migrations to Arctic breeding grounds. The publication of the rough-legged buzzard story may help researchers to summarize patterns such as this too. Mu problem with this paper is the framing. A story on the how and why of these continental movements in response to snow and other habitat features would be a grand contribution. Drop Anthropocene, and rethink whether foxtrot should be introduced as a hypothesis or a summary of cool descriptions. I prefer the latter, and recommend eLife to go with that too, rather than encourage "disconnected frames that seek 'respectability'" Good luck, theunis piersma

We thank the reviewer again for his valuable comments and suggestions. We have changed the framing to the suggested one and removed the Anthropocene from the article.

Reviewer #2 (Recommendations For The Authors):

We sincerely appreciate the time and effort you have taken to review our manuscript. We have carefully considered all of your comments, including both public and author comments, and provided detailed responses to each of them below. In addition, we would like to address the most important public comments.

We agree with the suggestion to shift the focus of the article from conservation to migration patterns. Accordingly, we have rewritten both the Introduction and Discussion sections to focus on migration behavior rather than conservation.

However, we respectfully disagree with the suggestion that the migration patterns we describe are synonymous with itinerancy. We acknowledge that our original presentation may have been unclear and may have hindered full understanding. In the revised version, we provide a detailed analysis of migratory behavior in the Introduction that describes how our pattern differs from itinerancy. We also revisit this distinction in the Discussion section. We have also carefully revised Figure 1 to improve clarity and avoid potential misunderstandings.

Regarding the applicability of the described migration pattern, we acknowledge that the Rough-legged Buzzard is not listed as an endangered species. However, we believe that our findings have practical implications. We have moved our discussion of this issue to the end of the Discussion section and have completely revised Figure 5. While the overall population of Rough-legged Buzzards is not declining, certain regions within its range are experiencing declines. We show that this decline does not warrant listing the species as endangered. Instead, it may represent a redistribution within the non-breeding range - a shift in range dynamics. We use the example of the Rough-legged Buzzard to illustrate this concept and emphasize the importance of considering such dynamics when assessing the conservation status of species in the future.

We also acknowledge that the hypothesis of this form of behavior has been proposed previously for Montagu's Harrier, and we have included this information in the revised manuscript. In addition, we agree that the focus on the Anthropocene is unnecessary in this context and have therefore removed it.

We believe that these revisions significantly improve the clarity and robustness of the manuscript, and we are grateful for your insightful comments and suggestions.

As a general comment, please note that including line numbers (as it is the standard in any manuscript submission) would facilitate reviewers providing more detailed comments on the text.

We apologize for this oversight and have added line numbers to our revised manuscript.

Dataset: unclear what is the frequency of GPS transmissions. Furthermore, information on relative tag mass for the tracked individuals should be reported.

We have included this information in our manuscript (L 157-163). We also refer to the study in which this dataset was first used and described in detail (L 164).

Data pre-processing: more details are needed here. What data have been removed if the bird died? The entire track of the individual? Only the data classified in the last section of the track? The section also reports on an 'iterative procedure' for annotating tracks, which is only vaguely described. A piecewise regression is mentioned, but no details are provided, not even on what is the dependent variable (I assume it should be latitude?).

Regarding the deaths. We only removed the data when the bird was already dead. We have corrected the text to make this clear (L 170).

Regarding the iterative procedure. We have added a detailed description on lines 175-188.

Data analysis: several potential issues here:

(1) Unclear why sex was not included in all mixed models. I think it should be included.

Our dataset contains 35 females and eight males. This ratio does not allow us to include sex in all models and adequately assess the influence of this factor. At the same time, because adult females disperse farther than males in some raptor species, we conducted a separate analysis of the dependence of migration distance on sex (Table S8) and found no evidence for this in our species. We have written a separate paragraph about this. This paragraph can be found on lines 356-360 of the new manuscript.

(2) Unclear what is the rationale of describing habitat use during migration; is it only to show that it is a largely unsuitable habitat for the species? But is a formal analysis required then? Wouldn't be enough to simply describe this?

Habitat use and snow cover determine the two main phases (quick and slow) of the pattern we describe. We believe that habitat analysis is appropriate in this case and that a simple description would be uninformative and would not support our conclusions.

(3) Analysis of snow cover: such a 'what if' analysis is fine but it seems to be a rather indirect assessment of the effect of snow cover on movement patterns. Can a more direct test be envisaged relating e.g. daily movement patterns to concomitant snow cover? This should be rather straightforward. The effectiveness of this method rests on among-year differences in snow cover and timing of snowfall. A further possibility would be to demonstrate habitat selection within the entire non-breeding home range of an individual in relation snow cover. Such an analysis would imply associating presence-absence of snow to every location within the non-breeding range and testing whether the proportion of locations with snow is lower than the proportion of snow of random locations within the entire non-breeding home range (95% KDE) for every individual (e.g. by setting a 1/10 ratio presence to random locations).

The proposed analysis will provide an opportunity to assess whether the Rough-legged Buzzard selects areas with the lowest snow cover, but will not provide an opportunity to follow the dynamics and will therefore give a misleading overall picture. This is especially true in the spring months. In March-April, Rough-legged Buzzards move northeast and are in an area that is not the most open to snow. At this time, areas to the southwest are more open to snow (this can be seen in Figure 4b). If we perform the proposed analysis, the control points for this period would be both to the north (where there is more snow) and to the south (where there is less snow) from the real locations, and the result would be that there is no difference in snow cover.

A step-selection analysis could be used, as we did in our previous work (Curk et al 2020 Sci Rep) with the same Rough-legged Buzzard (but during migration, not winter). But this would only give us a qualitative idea, not a quantitative one - that Rough-legged Buzzards move from snow (in the fall) and follow snowmelt progression (in the spring).

At the same time, our analysis gives a complete picture of snow cover dynamics in different parts of the non-breeding range. This allows us to see that if Rough-legged Buzzards remained at their fall migration endpoint without moving southwest, they would encounter 14.4% more snow cover (99.5% vs. 85.1%). Although this difference may seem small (14.4%), it holds significance for rodent-hunting birds, distinguishing between complete and patchy snow cover. Simultaneously, if Rough-legged Buzzards immediately flew to the southwest and stayed there throughout winter, they would experience 25.7% less snow cover (57.3% vs. 31.6%). Despite a greater difference than in the first case, it doesn't compel them to adopt this strategy, as it represents the difference between various degrees of landscape openness from snow cover.

We write about this in the new manuscript on lines 385-394.

Results: it is unclear whether the reported dispersion measures are SDs or SEs. Please provide details.

For the date and coordinates of the start and end of the different phases of migration, we specified the mean, sd, and sample size. We wrote this in line 277. For the values of the parameters of the different phases of the migration (duration, distance, speed, and direction), we used the mean, the standard error of the mean, and the confidence interval (obtained using the ‘emmeans’ package). We have indicated this in lines 302-303 and the caption of Table 1 (L 315) and Figure 2 (L 293-294). For the values of habitat and snow cover experienced by the Rough-legged Buzzards, we used the mean and the error of the mean. We reported this on lines 322 and 337 and in Figures 3 (L 332-333) and 4 (L 355-356).

Discussion: in general, it should be reshaped taking into account the comments. It is overlong, speculative and quite naive in several passages. Entire sections can be safely removed (I think it can be reduced by half without any loss of information). I provide some examples of the issues I have spotted below. For instance, the entire paragraph starting with 'Understanding....' is not clear to me. What do you mean by 'prohibited management' options? Without examples, this seems a rather general text, based on unclear premises when related to the specific of this study. Some statements are vague, derive from unsubstantiated claims, and unclear. E.g. "Despite their scarcity in these habitats, forests appear to hold significant importance for Rough-legged buzzards for nocturnal safety". I could not find any day-night analysis showing that they actually roost in forests during nighttime. Being a tundra species, it may well be possible that rough-legged buzzards perceive forests as very dangerous habitats and that they prefer instead to roost in open habitats. Analysing habitat use during day and night during the non-breeding period may be of help to clarify this. Furthermore, considering the fast migration periods, what is the flight speed during day and night above forests? Do these birds also migrate at night or do they roost during the night? Perhaps a figure visualizing day and night track segments could be of help (or an analysis of day vs. night flight speed) (there are several R packages to annotate tracks in relation to day and night). This is an example of another problematic statement: "The progression of snow cover in the wintering range of Rough-legged buzzards plays a significant role in their winter migration pattern." The manuscript does not contain any clear demonstration of this, as I wrote in my previous comments. Without such evidence, you must considerably tone down such assertions. But since providing a direct link is certainly possible, I think that additional analyses would clearly strengthen your take-home message.

The paragraph starting with "The quantification of environmental changes that could prove fatal to bird species presents yet another challenge for conservation efforts in an era of rapid global change." is quite odd. Take the following statement "For instance, the presence of small patches of woodland in the winter range might appear crucial to the survival of the Rough-legged buzzard. Elimination of these seemingly minor elements of vegetation cover through management actions could have dire consequences for the species.". It is based on the assumption that minor vegetation elements play a key role in the ecology of the species, without any evidence supporting this. Does it have any sense? I could safely say exactly the opposite and I would believe it might even be more substantiated.

We agree with these comments.

We have completely rewritten this section. As suggested, we have shortened it by removing statements that were not supported by the research. We have completely removed the statements about "prohibited management". We have also removed the statement that "forests appear to be of significant importance to Rough-legged buzzards for nocturnal safety" and everything associated with that statement, e.g. the statement about "small elements of vegetation cover", etc. We do believe that this statement is true in substance, but we also agree that it is not supported by the results and requires separate analysis. At the same time, we believe that this is a topic for a separate study and would be redundant here. Therefore, we leave it for a separate publication.

Conclusion paragraph: I believe this severely overstates the conservation importance of this study. That the results have "crucial implications for conservation efforts in the Anthropocene, where rapidly changing environmental factors can severely impact bird migration" seems completely untenable to me. What is the evidence for such crucial implications? For instance, these results may suggest that climate change, because global warming is predicted to reduce snow cover in the non-breeding areas, might well be beneficial for populations of this species, by reducing non-breeding energy expenditure and improving non-breeding survival. I think statements like these are simply not necessary, and that the study should be more focused on the actual results and evidence provided.

We have completely rewritten this section. We removed the reference to the Anthropocene and focused on migratory behavior and migration patterns.

eLife assessment

This work presents a useful finding on non-breeding itinerant behavior of a migratory raptor. With its extensive dataset and analytical framework, this work is of interest to researchers investigating the ecological drivers of bird migration. However, the main claim on a novel migration pattern (so-called 'fox-trot migration') is incomplete in light of current knowledge on bird migratory behavior.

Reviewer #2 (Public Review):

This preprint by Pokrovsky and coworkers is a descriptive study reporting on non-breeding itinerant behaviour of an intrapalearctic migratory raptor, the rough-legged buzzard, and relating such non-breeding movements to snow cover across the European non-breeding range. The article is based on long-term GPS tracking data from a relatively large (n=43) sample of individuals that were equipped with state-of-the-art tracking devices in the Russian Arctic during 2013-2019. The results show that, upon breeding, buzzards migrated rapidly to southern non-breeding areas, located in open areas north of the Black and Caspian seas, where they perform continuous directional movements at a slower pace, initially moving SW (Oct to Jan) and then progressively moving NE (Feb to Apr) before embarking on rapid spring migration. It is suggested that such itinerant behaviour follows variation (expansion and retreat) of snow cover across the non-breeding range.

The results are potentially useful for researchers investigating the ecological drivers of bird movement patterns. The analytical framework appears solid, although some details on the analyses (requested during the previous review round) are still unclear and have not been modified despite explicit requests. Significant weaknesses in the theoretical framework persist in the revised version, including unwarranted claiming of novelty, overselling of importance of the study, and overinterpretation of the data. Below are key points that the authors did not consider when revising their manuscript.

(1) The authors underemphasize the fact that what they term 'fox-trot' migration is actually a well-known patterns for many other migratory species, both in the Nearctic and in the Afro-Palearctic migration systems. Such behaviour has previously been identified as 'itinerant' or 'non-breeding itinerancy', involving an alternation of stopovers and movements between different short-term non-breeding residency areas, or even slow continuous movements, and it seems that the pattern the authors report for this particular species is perfectly in line with such previous evidence. For instance, this is well-documented among migratory raptors, such as the Montagu's harrier, lesser kestrels or black kites, that exploit Sahelian savannahs, where large spatio-temporal variation in greenness and hence resource availability occurs. And, besides the mentioned cuckoos and nightingales, there are studies of red-backed shrikes suggesting the same, as well as of tree swallows in the Nearctic. Therefore, the authors should avoid claiming novelty for this study and introducing unnecessary and confusing new terms in the literature (i.e. the 'fox-trot' migration patterns) when these are definitely not strictly needed as they have been previously observed and defined otherwise. Sentences such as 'We used the rough-legged buzzard as a model..." are also similarly unwarranted. This is simply a descriptive studies reporting on such behaviour in yet another migratory species. The whole introduction is pervaded by a faulty logic. The authors first introduce a new (unwarranted) term based on previous evidence from other studies (none of which felt any need to introduce and describe it); then they assume, for unclear reasons, that the species they are studying should behave in that way; even more worryingly, based on these assumptions, they make specific predictions on how this species should behave, without any sound biological reason for these predictions. I admit I hardly see any scientific logic in this approach.

(2) The species has a very standard migration for a short-distance migrant, by all means. It moves to non-breeding areas, and once there it slowly moves towards the south in autumn and back again in spring, until it departs for pre-breeding migration. This is no different from other trans-Saharan migratory raptor species that spend the non-breeding period in the Sahel. Whether the species perform any short/medium term stopover (frequenting the same are for some days) during the non-breeding stage (between end of autumn migration and onset of spring migration), as is the case of most species showing non-breeding itinerancy, is not reported. The authors only show a slower pace of movement during the non-breeding period compared to autumn and spring migration, without providing any further details. This hinders comparisons with other previous studies.

(3) The current title is unnecessarily general (it may recall rather a review or meta-analysis) and not adequately describing the content of the manuscript. In order to be informative, the title should more tightly reflect the content of the article. A valid alternative would be 'Itinerant non-breeding behaviour of an intra-Palaearctic migratory raptor', as it would be far more adequate and informative.

(4) The text, particularly the Introduction and the Discussion, would greatly benefit from profound reframing in light of the above comments. Upon reading the first sentence of the introduction, it looks surprising that the authors based their suggestion for 'fox-trot' migration based on a very outdated article on the migration of Montagu's harrier based on sparse ring recovery data which merely suggests the existence of 'movements' within the non-breeding areas (i.e. non-breeding itinerancy), while subsequent large scale satellite tracking studies of this species provided compelling evidence for non-breeding area itinerancy (and again, no mention of 'fox-trot' whatsoever). The discussion is entirely framed around potential issues related to accurate monitoring of population size and trends, which the author surprisingly refer to 'conservation implications'. As I already mentioned in my previous review, the 'conservation implications' of this study are nearly negligible. At best, it suggests that caution should be applied when interpreting population trends of migratory species based on non-breeding area counts only, a pattern that is already well known for decades (consider the long-running IWC coordinated by Wetlands International!). In addition, Christmas Bird Count, a long-term monitoring program of AOS, is mentioned without any accurate reference to what it actually is, assuming that any reader would be familiar with a very peculiar monitoring scheme of the Nearctic region.

The final paragraph epitomizes how authors are overstating the importance of this study, claiming for non-existent novelty and even 'discovery': "Our study has identified and characterized a new pattern of migratory behavior, the 'foxtrot migration', along with the associated concept of 'dynamic range'. This discovery has significant implications for conservation strategies and adequate representation of non-breeding habitats".

eLife assessment

In this important study, Castello-Serrano and colleagues describe, model and quantify the role of transmembrane domains in protein sorting in the secretory pathway, first at the ER and subsequently at the Golgi. Convincing data support the role of a cytoplasmic motif in ER exit, while further experiments are necessary to support a direct connection between the phase partitioning capability of the transmembrane regions and the sorting potential of domains at the Golgi/TGN.

Joint Public Review:

In their revised manuscript additional experiments have been conducted competently, and the interpretation of experiments regarding exit from the ER are convincing. They collectively indicate that the phase partitioning behaviour of the TMDs do not have a significant effect on exit from the ER; they all exit the ER very slowly unless they carry a short cytoplasmic domain from LAT which is sufficient to accelerate ER exit. This data is consistent with available literature supporting a role for a ER-exit signal. Along with new experiments in their revision, they have also toned down the assertion that their data rule out a phase partitioning mechanism at the ER.

The authors, however, continue to interpret their experiments regarding Golgi exit of the transmembrane peptides (with luminal and cytoplasmic domains) as conclusive evidence of the role of lipid rafts in exit from the Golgi. This is once again based on correlation of the phase partitioning behaviour of these proteins in GPMVs, phase separated at low temperatures. They argue that this represents very strong evidence that trafficking out of the Golgi is driven by phase separation. The reviewers consider that there are a number of potential issues with the final model that need to be addressed.

We reiterate that:

(1) the phase segregation in the GPMV at low temperatures is dictated by thermodynamics given its composition and the measurement temperature. However at physiological temperatures at which membrane trafficking is taking place these GPMVs will not exhibit phase separation. Hence it is difficult to argue that a sorting mechanism based solely on the partitioning of the synthetic TM constructs into liquid ordered domain detected at low temperatures in GPMVs provide an explanation of the explanation of the differential kinetics of traffic of the LAT TMD and the allL-TMD constructs, although there is a strong correlation with its phase partitioning behaviour.

(2) The fluctuations of lipid composition resembling lo-domains if persisting at higher temperatures and its conversion into a sorting domain will require a cellular mechanism, that may or may not retain similar properties of these lipidic environments. Additionally, TMDs from TfR/VsVG and GPI prefer different domains in the GPMV assays (Table S1) yet they traffic to the cell surface equally rapidly.

(3) The authors fail to discuss the point raised about the relatively high colocalization of TfR with the GPI probe (seen in Fig 5E) in the Golgi. This is inconsistent with their explanation of traffic correlating with partitioning into distinct domains in the Golgi, since TfR and GPI probes show an opposite preference for lo versus ld domains in cooled GPMVs. TMD-allL and the LAT-allL are segregated from TfR in the Golgi, and end up in a different final destination (ie lysosomes). This could represent yet another membrane specialisation in the Golgi for lysosomal traffic. The segregation that the authors report in the Golgi is therefore not a convincing argument for phase preferences in GPMVs dictating the trafficking behaviour of these molecules towards the plasma membrane.

(4) Despite the authors' claim in their rebuttal that 'we feel that GPMVs are a useful tool for quantifying protein preference for ordered (raft) membrane domains and that this preference is a useful proxy for the raft-associated behavior ... biological membrane with a relevant and measurable cellular outcome, specifically inter-organelle trafficking rates." -several caveats for these observations need to be addressed before they constitute strong evidence for the raft model of membrane trafficking proposed. Phase partitioning in GPMVs is just another operational definition and while more refined (ie the data is derived from the membrane of interest, ie, the plasma membrane) it is not very different conceptually from quantitative measurements of detergent-insolubility.

(5) Further work is necessary to establish that ordered domains are formed at the Golgi at physiological temperatures, into which these proteins may partition; subsequently, there must be a mechanism that selectively traffics these proteins towards the cell surface.

(6) The authors continue to conflate thermodynamic phase separation mechanisms with the real possibility of the formation of functional sorting domains by cellular mechanisms that likely involve lipidic interactions, adding to the confusion in the literature.

eLife assessment

This manuscript presents useful findings on several phage from deep sea isolates of Lentisphaerae strains WC36 and zth2 that further our understanding of deep sea microbial life. The manuscript's primary claim is that phage isolates augment polysaccharide use in Pseudomonas bacteria via auxiliary metabolic genes (AMGs). However, the strength of the evidence is incomplete and does not support the primary claims. Namely, there are not data presented to rule out phage contamination in the polysaccharide stock solution, AMGs are potentially misidentified, and there is missing evidence of successful infection.

Reviewer #1 (Public Review):

Summary:

This manuscript describes the identification and isolation of several phage from deep sea isolates of Lentisphaerae strains WC36 and zth2. The authors observe induction of several putative chronic phages with the introduction of additional polysaccharides to the media. The authors suggest that two of the recovered phage genomes encode AMGs associated with polysaccharide use. The authors also suggest that adding the purified phage to cultures of Pseudomonas stutzeri 273 increased the growth of this bacteria due to augmented polysaccharide use genes from the phage.

While the findings were of interest and relevance to the field, it is my opinion that several of the analysis fall short of supporting the key assertions presented.

Strengths:

Interesting isolate pf deep sea Lentisphaerae strains which will undoubtedly further our understanding of deep sea microbial life.

Weaknesses:

Many of the findings are consistent with a phage contamination in the polysaccharide stock solution.

The genes presented as AMGs are largely well known and studied phage genes which play a role in infection cycles.

The evidence that the isolated phage can infect Pseudomonas stutzeri 273 is lacking, putting into question the dependent results.

Reviewer #2 (Public Review):

Summary:

This paper investigates virus-host interactions in deep-sea bacteriophage systems which employ a seemingly mutualistic approach to viral replication in which the virus aids host cell polysaccharide import and utilization via metabolic reprogramming. The hypothesis being tested is supported with solid and convincing evidence and the findings are potentially generalizable with implications for our understanding of polysaccharide-mediated virus-host interactions and carbon cycles in marine ecosystems more broadly.

Strengths:

This paper synthesizes sequencing and phylogenic analyses of two Lentisphaerae bacteria and three phage genomes; electron microscopy imaging of bacterial/phage particles; differential gene expression analyses; differential growth curve analyses, and differential phage proliferation assays to extract insights into whether laminarin and starch can induce both host growth and phage proliferation. The data presented convincingly demonstrate that both host culture density and phage proliferation increase as a result having host, phage, and polysaccharide carbon source together in culture.

Weaknesses (suggestions for improvement):

The article would be strengthened by the following additional experiment: providing the phage proteins hypothesized to be aiding host cell growth (red genes from Figure 5...TonB system energizer ExbB, glycosidases, etc) individually or in combination on plasmids rather than within the context of the actual phage itself to see if such additional genes are necessary and sufficient to realize the boosts in host cell growth/saturation levels observed in the presence of the phages tested.

The paper would also benefit from additional experiments focused on determining how the polysaccharide processing, transport, and metabolism genes are being used by the phages to either directly increase viral infection/replication or else to indirectly do so by supporting the growth of the host in a more mutualistic manner (i.e. by improving their ability to import, degrade, and metabolize polysaccharides).

The introduction would benefit from a discussion of what is known regarding phage and/or viral entry pathways that utilize carbohydrate anchors during host entry. The discussion could also be improved by linking the work presented to the concept of "selfishness" in bacterial systems (see for instance Giljan, G., Brown, S., Lloyd, C.C. et al. Selfish bacteria are active throughout the water column of the ocean. ISME COMMUN. 3, 11 (2023) https://doi.org/10.1038/s43705-023-00219-7). The bacteria under study are gram negative and it was recently demonstrated (https://www.nature.com/articles/ismej201726) that "selfish" bacteria sequester metabolizable polysaccharides in their periplasm to advantage. It is plausible that the phages may be hijacking this "selfishness" mechanism to improve infectivity and ENTRY rather than helping their hosts to grow and profilerate so they can reap the benefits of simply having more hosts to infect. The current work does not clearly distinguish between these two distinct mechanistic possibilities. The paper would be strengthened by at least a more detailed discussion of this possibility as well as the author's rationale for interpreting their data as they do to favor the "mutualistic" interpretation. In the same light, the paper would benefit from a more careful choice of words which can also help to make such a distinction more clear/evident/intentional. As currently written the authors seem to be actively avoiding giving insights wrt this question.

Finally, I would be interested to know if the author's sequencing datasets might be used to inform the question raised above by using bacterial immunity systems such as CRISPR/Cas9. For example, if the phage systems studied are truly beneficial/mutualistic for the bacteria then it's less likely that there would be evidence of targeted immunity against that particular phage that has the beneficial genes that support polysaccharide metabolism.

eLife assessment

In this small-scale study, Fawaz et al. report a significant prevalence of somatic mutations such as Clonal Hematopoiesis of Indeterminate Potential (CHIP) and mosaic loss of Y chromosome (mLOY), but lack of their association with a history of myocardial infarction (MI). The study utilized sensitive techniques, including targeted high-throughput sequencing and digital PCR. The valuable findings by the authors present a contrast to earlier reports, yet they align somewhat with some studies that have demonstrated little or no link between clonal hematopoiesis and atherothrombotic events. Although the study offers convincing results, its limited sample size and brief follow-up period preclude drawing definitive conclusions.

Reviewer #1 (Public Review):

This manuscript examines the individual and dual effects of CHIP and LOY in MI employing a cohort of ~460 individuals. CHIP is assessed by NGS and LOY is assessed by PCR. The threshold for CHIP is set at 2% (an arbitrary cutoff that is often used) and LOY at 9% (according to the Discussion text - this reviewer may have missed the section that describes why this threshold was employed). The investigation assessed whether LOY could modulate inflammation, atherosclerotic burden, or MI risk associated with CHIP. Neither CHIP nor LOY independently affected hsCRP, atherosclerotic burden, or MI incidence, nor did LOY presence diminish these outcomes in CHIP+ male subjects.

This study represents the first dual analysis of CHIP and LOY on CVD outcomes. The results are largely negative, contradictory to other studies (many with much larger sample sizes). I would attribute the limitation of sample size as a major contributor to the negative data. While the negative data are suspect, the "positive" finding that LOY abolishes the prognostic significance of CHIP on MI is of interest (and consistent with what is understood from mechanistic studies).

Overall, I enjoyed reading the paper, and it is of interest to the research community. However, I disagree with some of the authors' interpretations of the data. Generally, many conclusions on CHIP interpretation are based on the comparison of findings from very large datasets that have been evaluated by shallow NGS DNA sequencing. These studies lack sensitivity and accuracy, but this is counterbalanced by their very large sample sizes. Thus, they draw conclusions from the sickest individuals (ICD codes) with the largest clones (explaining the 10% VAF threshold). Here, the study has a well-phenotyped cohort, but as far as this reviewer can tell, the DNA sequencing is "shallow" NGS. Typically, to assess smaller datasets, investigators employ an error-correction method (DNA barcodes, duplex sequencing, etc.) for the sensitivity and accuracy of calling variants. Thus, the current study appears to suffer from this limitation (small sample sizes combined with NGS).

While the "negative" data from this study are inconclusive, the positive data (i.e. CHIP being prognostic for MI in the absence but not presence of MI) is of interest. Thus, the investigators may want to consider a shorter report that largely focuses on this finding.

Reviewer #2 (Public Review):

Summary:

The preprint by Fawaz et al. presents the findings of a study that aimed to assess the relationship between somatic mutations associated with clonal hematopoiesis (CHIP) and the prevalence of myocardial infarction (MI). The authors conducted targeted DNA sequencing analyses on samples from 149 MI patients and 297 non-MI controls from a separate cohort. Additionally, they investigated the impact of the loss of the Y chromosome (LOY), another somatic mutation frequently observed in clonally expanded blood cells. The results of the study primarily demonstrate no significant associations, as neither CHIP nor LOY were found to be correlated with an increased prevalence of MI. Of note, the null findings regarding CHIP are in conflict with several larger studies in the literature.

Strengths:

Overall, this is a useful research work on an emerging risk factor for cardiovascular disease (CVD). The use of a targeted sequencing approach is a strength, as it offers higher sensitivity than the whole exome sequencing approaches used in many previous studies.

Weaknesses:

Reporting null findings is definitely relevant in an emerging field such as the role of somatic mutations in cardiovascular disease. Nevertheless, the study suffers from severe limitations, which casts doubts on the authors' conclusions, as detailed below:

(1) The small sample size of the study population is a critical limitation, particularly when reporting null findings that conflict (partly) with positive findings in much larger studies, totaling hundreds of thousands of individuals (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024). The authors claim that they have 90% power to detect an effect size of CHIP on MI comparable to that in a previous report (Jaiswal et al, NEJM 2017). However, the methodology used to estimate statistical power is not described. Furthermore, the work by Jaiswal et al (NEJM 2017) showed a hazard ratio of approx. 2.0, but more recent work in much larger populations suggests that the overall effect of CHIP on atherosclerotic CVD is smaller, most likely due to the heterogeneity of effects of different mutated genes (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024). In addition, several analyses in the current manuscript are conducted separately in MI(+) (n= 149) and MI(-) (N=297) individuals, further limiting statistical power. Power is still lower in the investigation of the effects of LOY and its interaction with CHIP, as only men are included in these analyses. Overall, I believe the study is severely underpowered, which calls into question the validity of the reported null findings.

(2) Related to the above, it is widely accepted that the effects of CHIP on CVD are highly heterogeneous, as some mutated genes appear to have a strong impact on atherosclerosis, whereas the effect of others is negligible (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023, among others). TET2 mutations are frequently considered a "positive control", given the multiple lines of evidence suggesting that these mutations confer a higher risk of atherosclerotic disease. However, no association with MI or related variables was found for TET2 mutations in the current work. Reporting the statistical power specifically for assessing the effect of TET2 mutations would enhance the interpretation of these results.

(3) One of the most essential features of CHIP is the tight correlation with age. In this study, the effect of age on CHIP (Supplementary Tables S5, S6) seems substantially milder than in previous studies. Given the relatively weak association with age here, it is not surprising that no association with MI or atherosclerotic disease was found, considering that this association would have a much smaller effect size. In addition, there are previous reports of sex-related differences in the prevalence of CHIP, is there an association between CHIP and age after adjusting for sex?

(4) The mutated genes included in the definition of "CHIP" here are markedly different than those in most previous studies, particularly when considering specifically the studies that demonstrated an association between CHIP and atherosclerotic CVD. For instance, the definition of CHIP in this manuscript includes genes such as ANKRD26, CALR, CCND2, and DDX41... that are not prototypical CHIP genes. This is unlikely to have a major impact on the main results, as the vast majority of mutations detected are indeed in bona fide CHIP genes, but it should be at least acknowledged. Furthermore, the strategy used here for the CHIP variant calling and curation seems substantially different than that used in previous studies, which precludes a direct comparison. This is important because such differences in the definition of CHIP and the curation of variants are the basis of most conflicting findings in the literature regarding the effects of this condition. Ideally, the authors should conduct sensitivity analyses restricted to prototypical CHIP genes, using the criteria that have been previously established in the field (e.g. Vlasschaert et al, Blood 2023).

(5) An important limitation of the current study is the cross-sectional design of most of the analyses. For instance, it is not surprising that no association is found between CHIP and prevalent atherosclerosis burden by ultrasound imaging, considering that many individuals may have developed atherosclerosis years or decades before the expansion of the mutant clones, limiting the possible effect of CHIP on atherosclerosis burden. Similarly, the analysis of the relationship between CHIP and a history of MI may be confounded by the potential effects of MI on the expansion of mutant clones. In this context, it is noteworthy that the only positive results here are found in the analysis of the relationship between CHIP at baseline and incident MI development over follow-up. Increasing the sample size for these longitudinal analyses would provide deeper insights into the relationship between CHIP and MI.

(6) The description of some analyses lacks detail, but it seems that statistical analyses were exclusively adjusted for age or age and sex. The lack of adjustment for conventional cardiovascular risk factors in statistical analyses may confound results, particularly given the marked differences in several variables observed between groups.

(7) The variant allele fraction (VAF) threshold for identifying clinically relevant clonal hematopoiesis is still a subject of debate. The authors state that subjects without any detectable mutation or with mutations with a VAF below 2% were considered non-CHIP carriers. While this approach is frequent in the field, it likely misses many impactful mutations with lower VAFs. Such false negatives could contribute to the null findings reported here. Ideally, the authors should determine the lower detection limit of their sequencing approach (either computationally or through serial dilution experiments) and identify the threshold of VAF that can be detected reliably with their sequencing assay. The association between CHIP and MI should then be evaluated considering all mutations above this VAF threshold, in addition to sensitivity analyses with other thresholds frequent in the literature, such as 1% VAF, 2% VAF, and 10% VAF.

(8) The authors should justify the use of 3D vascular ultrasound imaging exclusively in the supra-aortic trunk. I am not familiar with this technique, but it seems to be most typically used to evaluate atherosclerosis burden in superficial vascular beds such as carotids or femorals. I am concerned about the potential impact of tissue depth on the accurate quantification of atherosclerosis burden in the current study (e.g. https://doi.org/10.1016/j.atherosclerosis.2016.03.002). It is unclear whether the carotids or femorals were imaged in the study population.

(9) The specific criteria used to define LOY need to be justified. LOY is stated to be defined based on a "A cut off of 9% of cells with mLOY defined the detection of a mLOY based on the study of 30 men of less than 40 years who had a normal karyotype as assessed by conventional cytogenetic study." As acknowledged by the authors, this definition of LOY is substantially different than that used in recent studies employing the same technique to detect LOY (Mas-Peiro et al, EHJ 2023). In addition, it seems essential to provide more detailed information on the ddPCR assay used to determine LOY, including the operating range and, more importantly, the lower limit of detection (%LOY) of the assay. A dilution series of a control DNA with no LOY would be helpful in this context.

(10) Our understanding of the relationship between CHIP and CVD is evolving fast, and the manuscript should be considered in the context of recent literature in the field. For instance, the recent work by Zhao et al (JAMA Cardio 2024, doi:10.1001/jamacardio.2023.5095) should be considered, as it used a similar targeted DNA sequencing approach as the one used here, but found a clear association between CHIP and coronary heart disease (in a population of 6181 individuals).

(11) The use of subjective terms like "comprehensive" or "thorough" in the title of the manuscript does not align with the objective nature of scientific reporting.

eLife assessment

This small-sized clinical trial comparing nebulized dornase-alfa to the best available care in patients hospitalized with COVID-19 pneumonia is valuable, but in its present form the paper is incomplete.

Reviewer #1 (Public Review):

This study by Porter et al reports on outcomes from a small, open-label, pilot randomized clinical trial comparing dornase-alfa to best available care in patients hospitalized with COVID-19 pneumonia. As the number of randomized participants is small, investigators describe also a contemporary cohort of controls and the study concludes with decrease of inflammation (reflected by CRP levels) after 7 days of treatment but no other statistically significant clinical benefit.

I read with interest this manuscript and I find the idea about treatment of COVID-19 patients with dornase-alfa novel and inspiring. I have some major concerns about the methodology the authors followed in this RCT.

My major concerns are:

(1) The authors have chosen a primary outcome that cannot be at least considered as clinically relevant or interesting. After 3 years of the pandemic with so much research, why investigate if a drug reduces CRP levels as we already have marketed drugs that provide beneficial clinical outcomes such as dexamethasone, anakinra, tocilizumab and baricitinib.

(2) ΙΤΤ analysis is not followed

Reviewer #2 (Public Review):

Interesting work with an original and appealing hypothesis. The authors performed an open-label trial comparing nebulized dornase alfa to best available care in COVID-19, reaching the primary outcome of CRP reduction over the first week of intervention. The main weaknesses of the study are the small sample size, the lack of randomization for the majority of the participants, and the lack of blinding. The authors have sufficiently addressed the issues raised, provided that these weaknesses are highlighted in the limitations section.

eLife assessment

The manuscript presents potentially valuable findings of bone remodeling by chronic unpredictable mild stress (CUMS). This is an interesting topic on mental stress on bone health and osteoporosis, and the authors offer solid evidence of decreased bone mass by micro-CT. However, to strengthen the work, the validation should be conducted in vivo, and the mechanism behind this should be investigated further.

Reviewer #1 (Public Review):

I have reviewed, with interest, the manuscript "Psychological stress disturbs bone metabolism via miR-335-3p/Fos signaling in osteoclast". The described findings are relevant and useful for daily practice in periodontology. The paper is concise, professionally written, and easy to read. In this study, Jiayao et al. revealed the role of miR-335-3p in psychological stress-induced osteoporosis. CUMS mice were constructed to observe the femur phenotype, osteoclasts were identified as the primary research object, and miRNA-seq was used to find the key miRNAs linking the brain and peripheral tissues. This study showed that the expression of miR-335-3p was simultaneously reduced in mice's NAC, serum, and bone under psychological stress. The miR-335-3p/Fos/NFATC1 signaling pathway was validated in osteoclasts to reveal the potential mechanism of enhanced osteoclast activity under psychological stress. From a new perspective of miRNAs, this study indicates a possible cause of disturbed bone metabolism due to psychological stress and may suggest a new approach to treating osteoporosis.

Reviewer #2 (Public Review):

Zhang et al. established chronic unpredictable mild stress (CUMS) mouse model, which displayed osteoporosis phenotype, suggesting a potential correlation between psychological stress and bone metabolism. They found that miRNA candidate miR-335-3p is downregulated in the long bone of CUMS mice through microRNA sequencing and qRT-PCR experiments. They further demonstrated that miR-335-3p attenuates osteoclast activity via inhibiting Fos signaling, which can induce NFATC1 expression and regulate osteoclast activity.

Strengths:

The authors established CUMS mouse model and confirmed the osteoporosis phenotype through careful characterization of bone and analysis of osteoclast activity. They performed microRNA sequencing to identify the miRNA candidate regulating the bone loss in the CUMS mouse model. They also validated the expression of miR-335-3p and interfered with the function of miR-335-3p through an in vitro assay. Overall, the findings from this study provide important hints for the correlation between psychological stress and bone metabolism.

Weakness:

The data provided by the authors are preliminary, especially the mechanistic insight, which needs to be enhanced. The authors have shown that miR-335-3p expression was altered in the CUMS mouse model and the change of its expression regulated osteoclast activity. The validation should be conducted in vivo, and the mechanism behind this should be investigated further.

eLife assessment

In this work, the authors make a valuable contribution based on convincing evidence that children 6-to-7-years-old improve in 2 years of development towards utilising more optimal value-based decision-making strategies while performing a reinforcement learning task. They found that delayed feedback learning was associated with volume in the hippocampus while immediate feedback learning was not. Striatal volume was associated with both forms of learning, in contrast to prior research funding in adults. Brain-behaviour correlations were stable across the 2-year period, despite the hippocampus increasing in volume and striatal volume remaining stable.

Reviewer #1 (Public Review):

Existing literature suggests that brain structures implicated in memory such as the hippocampus, and reward/punishment processing such as the striatal regions are also engaged in learning and value-based decision-making. However, how the contributions of these regions to learning and value-based decision-making change over time, particularly in children where these neural systems show protracted maturation was not studied systematically. This is the question the authors are aiming to address in this work in which children 6-to-7-years-old were recruited for a neuroimaging study that involves taking structural scans from this cohort to investigate how they correlate with changes in the way children approach a reinforcement learning task in which they learn to identify the better shape between 2 options through trial-and-error.

Particular strengths of the paper are longitudinally following up a cohort of small children and engaging them in a value-based decision-making task so that the relationship between neural maturation and improvements in reinforcement learning can be studied reliably. Towards this end, the authors make use of well-established computational modelling approaches to extract key parameters such as learning rates (which designate the speed of learning from expected versus actual outcomes) or choice stochasticity (which designate the inherent variation in people's decisions and the tendency to explore between the options) from children's choices so that their structural neural correlates can be established. As a part of this endeavour, the authors rely on methodological choices which do not warrant much criticism. Their data visualization choices are particularly spot-on and highly informative about the details of the raw data.

Also considering the importance of the hippocampal system in human memory, the key contribution of the paper is that the volumetric increases in hippocampus size between 2 assessment points correlated selectively with the delayed, but not immediate, learning score which refers to the learning condition in which the outcome feedback is given to the children after a 5-seconds delay. Although the authors also demonstrate evidence to suggest that changes in the striatal volume are also implicated in learning performance, this was more general as associations were found for both immediate and delayed feedback conditions. Thus, the paper makes an important contribution to the fields of developmental and decision neuroscience. An important question arising from the authors' findings could be that, whether the hippocampus maintains this selective role in value-based learning during the course of neuronal development, for example, whether a similar association would be found in children 8-to-9 years old. A better understanding of how these developmental trajectories map onto changes in learning and decision-making can inform fields outside neuroscience, for example tailoring educational approaches onto neural development pathways to boost learning efficiency in young children.

Reviewer #2 (Public Review):

Summary:

This is an interesting and impressive study that provides a rare opportunity to learn about brain-behaviour links of learning systems at a relatively early stage of development.

The main strengths are that the authors followed a relatively large group of children over 2 years and used a reinforcement learning task aimed at assessing learning that depends on both the striatum and the hippocampus. The authors also included a thorough overview of the computational models and the choices they made. I think this paper would be of considerable interest and contributes to knowledge about how learning and memory systems change with development.

eLife assessment

This study presents important novel findings on how heterosynaptic plasticity can transform a weak associative memory into a stronger one, or produce a memory when stimuli were not paired. This work expands our views on the role of temporal- and input-specific plasticity in shaping learning and memory processes. The evidence, based on state-of-the-art in vivo manipulations, activity recordings, and behavioral analysis, is convincing. Findings will be of broad interest to neuroscience community, and especially those studying synaptic plasticity and associative memory.

Reviewer #1 (Public Review):

Summary:

The authors goal here was to explore how a non hebbian form of plasticity, heterosynaptic LTP, could shape neuronal responses and learning. They used several conceptually and technically innovative approaches to answer this. First, they identified a behavioral paradigm that was a subthreshold training paradigm (stimulation of thalamic inputs with a footshock), which could be 'converted' to a memory via homosynaptic LTP (HFS of thalamic inputs). They then find that stimulation of 'cortical' inputs could also convert the subthreshold stimulation to a lasting memory, and that this was associated with a change in neuronal response, akin to LTP. Finally, they provide some slice work which demonstrated that stimulation of cortical inputs could stabilize LTP at thalamic inputs.

Strengths:

(1) The approach was innovative and asked an important question in the field.

(2) The studies are, for the most part, quite rigorous, using a novel dual opsin approach to probe multiple inputs in vivo.

(3) The authors explore neural responses both in vivo and ex vivo, as well as leveraging a 'simple' behavior output of freezing.

Reviewer #2 (Public Review):

Summary

Faress et al. address how synaptic plasticity (i.e. potentiation induced by high frequency stimulation, HFS) induced at different time points and pathways relative to those active during initial learning can transform memories. They adopt an experimental design developed by Nabavi et al, 2014 to optogenetically induce a weak fear memory by pairing an optical conditioned stimulus (CS) at thalamo-LA synapses with a footshock unconditioned stimulus (US) in male mice. Homosynaptic HFS delivered in the same pathway before or after conditioning transforms the weak memory into a stronger one. Leveraging a new dual wavelength optogenetic approach in vivo, they also show that heterosynaptic (cortico-LA) HFS directly following the opto-conditioning can transform the thalamo-LA induced fear memory, or create a memory when directly delivered after unpaired conditioning. Lastly, they demonstrate that heterosynaptic potentiation of the thalamo-LA pathway accompanies the strengthening of fear memory in freely moving mice. The authors conclude that a transient experience (i.e. weak memory) can be transformed into a stable one by non-Hebbian forms of plasticity.

Strengths

This study uses well-defined and elegant optogenetic manipulations of distinct neural pathways in awake behaving mice combined with in vivo recordings, which allows to directly manipulate and monitor synaptic strength and memory. It addresses an interesting, timely, and important question.

Weaknesses

A key experiment with in vivo monitoring of LFPs and behavior (Fig. 5a-c) seems a bit underpowered and input-output curves (extended data 5c) not entirely convincing.<br /> Ex vivo slice experiments (Fig. 5d-f) are not well aligned with in vivo experimental conditions. While they provide proof of principle, this is not entirely novel (see Fonseca et al, 2013).

Significance and impact

The conclusions are well supported by the data. The significance of the study lies in showing in vivo, that plasticity induced at different times or synaptic pathways than those engaged during learning can modify a memory and the synaptic strength in the neural pathway related to that memory. While heterosynaptic and timing-dependent effects in synaptic plasticity have been described largely ex vivo on shorter time scales, the discovery of lasting behavioral effects on memory is novel. The study was enabled by a combination of clever approaches: creation of a "synthetic" pathway-specific association and a novel dual opsin approach in vivo to probe the role of plasticity in a converging second pathway at the same time.<br /> This work broadens our understanding of how Hebbian and non-Hebbian forms of plasticity shape neural activity and associative memory and is of broad interest to the neuroscience community.

eLife assessment

This study establishes a two distinct feature-encoding visual projection neurons in Drosophila as a model for the development of synaptic specificity. The comprehensive description of connectivity development in this system is valuable to a more general understanding of principles that underlie neural circuit development. The high-quality supporting evidence is convincing.

Reviewer #1 (Public Review):

Summary:

This is a strong paper that sets the foundation for future work that will explore the innervation of the giant fiber, allowing experiments that will link molecular/developmental mechanisms to circuit function at a level of resolution that has not previously been possible. In the course of this work the investigators discover an axon-axon competition that reflects the order of innervation of the target. In addition, a host of reagents are developed that will be of wide use in dissecting this system.

Strengths:

(1) The developmental, functional and connectomic characterization of the wiring pattern to be dissected is impressively thorough and quantitative.<br /> (2) The reagents that the authors establish will be foundational to subsequent effort.<br /> (3) The discovery that axon-axon competition is involved in patterning this system, and might combined with innervation order to give a deterministic outcome is an interesting one (and might be useful to address variation in cell number (see below)!

Weaknesses:

(1) In my opinion, the authors miss an opportunity to leverage their connectomics characterization somewhat more. That is, from characterization of the connectomes of two flies, the authors describe substantial variation in the number of pre-synaptic cells providing inputs (for example, in FAFB, there are 55 LC4 cells, while in the hemibrain, there are 71 - almost 30 percent more), yet the number of total synapses provided by each class of cell types is remarkably stereotyped 2442 synapses versus 2290 synapses). And the ratio of LC4 to LPLC2 synapses is even more stereotyped... As this kind of stereotypy would be consistent with the authors competition model, but inconsistent with a model in which each cell makes a similar number of synapses (which would be the model from the periphery of the visual system), the authors should comment a bit more on what they see. Perhaps the wiring model the authors advocate for compensates for what appears to be quite significant variation in the numbers of LC neurons?

(2) I appreciate how the authors pivoted to interpreting their results using Kir2.1 to reflect the effects of cell ablation. However, I worry that since the mechanism behind Kir2.1 mediated ablation is unknown, there could be other effects associated with this perturbation, creating indirect effects that alter LPLC2 cells somehow. I would therefore ask that the authors repeat these experiments with a more standard cell ablation strategy (such as a light gated caspase, or ricin). More crucially, the author's model that arrival order is functionally important would be greatly strengthened if they did the reciprocal ablation of LPLC2 and asked what happens to LC4. One could easily imagine a model in which these two cell types mutually compete for real estate, after an initial bias is set by arrival order.

Reviewer #2 (Public Review):

Summary:

The authors investigate axonal and synapse development in two distinct visual feature-encoding neurons (VPN), LC4 and LPLC2. They first show that they occupy distinct regions on the GF dendrites, and likely arrive sequentially. Analysis of the VPNs' morphology throughout development, and synaptic gene and protein expression data reveals the temporal order of maturation. Functional analysis then shows that LPLC2 occupancy of the GF dendrites is constrained by LC4 presence.

Strengths:

The authors investigate an interesting and very timely topic, which will help to understand how neurons coordinate their development. The manuscript is very well written, and data are of high quality, that generally support the conclusions drawn (but see some comments for Fig. 2 below). A thorough descriptive analysis of the LC4/LPLC2 to GF connectivity is followed by some functional assessment showing that one neuron's occupancy of the GF dendrite depend on another.<br /> The manuscripts uses versatile methods to look at membrane contact, gene and protein expression (using scRNAseq data and state-of-the art genetic tools) and functional neuronal properties. I find it especially interesting and elegant how the authors combine their findings to highlight the temporal trajectory of development in this system.

Weaknesses:

After reading the summary, I was expecting a more comprehensive analysis of many VPNs, and their developmental relationships. For a better reflection of the data, the summary could state that the authors investigate *two* visual projection neurons (VPNs) and that ablation *of one cell type of VPNs* results in the expansion of the remaining VPN territory.

The manuscript is falling a bit short of putting the results into the context of what is known about synaptic partner choice/competition between different neurons during neuronal or even visual system development. Lots of work has been done in the peripheral the visual system, from the Hiesinger lab and others. Both the introduction and the discussion section should elaborate on this.

The one thing that the manuscript does not unambiguously show is when the connections between LC4 and LPLC2 become functional.

Figure 2:<br /> Figure 2A-C: I found the text related to that figure hard to follow, especially when talking about filopodia. Overall, life imaging would probably clarify at which time point there really are dynamic filopodia. For this study, high magnification images of what the authors define as filopodia would certainly help.<br /> L137ff: This section talks about filopodia between 24-48 hAPF, but only 36h APF is shown in A, where one could see filopodia. The other time points are shown in B and C, but number of filopodia is not quantified.<br /> L143: "filopodia were still present, but visibly shorter": This is hard to see, and again, not quantified.<br /> L144f: "from 72h APF to eclosion, the volume of GF dendrites significantly decreased": this is not actually quantified, comparisons are only done to 24, 36 and 48 h APF.<br /> Furthermore, 72h APF is not shown here, but in Figure 2D, so either show here, or call this figure panel already?

Figure 2D/E: to strengthen the point that LC4 and LPLC2 arrive sequentially, it would help to show all time points analyzed in Figure D/E.

L208: "significant increase ... from 60h APF to 72h APF": according to the figure caption, this comparison is marked by "+" but there is no + in the figure itself.

Figure 3:<br /> A key point of the manuscript is the sequential arrival of different VPN classes. So then why is the scRNAseq analysis in Figure 3 shown pooled across VPNs? Certainly, the reader at this point is interested in temporal differences in gene expression. The class-specific data are somewhat hidden in Supp. Fig. 9, and actually do not show temporal differences. This finding should be presented in the main data.

L438: "silencing LC4 by expressing Kir2.1... reduced the GF response": Is this claim backed by some quantification?

Figure 4K: Do the control data have error bars, which are just too small to see? And what is tested against what? Is blue vs. black quantified as well? What do red, blue, and black asterisks indicate? Please clarify in figure caption.

Optogenetics is mentioned in methods (in "fly rearing", in the genotypes, and there is an extra "Optogenetics" section in methods), but no such data are shown in the manuscripts. (If the authors have those data, it would be great to know when the VPN>GF connections become functional!)

Methods:

Antibody concentrations are not given anywhere and will be useful information for the reader

Could the authors please give more details on the re-analysis of the scRNAseq dataset? How did you identify cell type clusters in there, for example?

L785 and L794: I am curious. Why is it informative to mention what was *not* done?

Custom-written analysis code is mentioned in a few places. Is this code publicly available?

Reviewer #3 (Public Review):

Summary:

In this work, MacFarland et.al. show that difference in the time of contact between axons of LC4 and LPLC2 visual projection neurons (VPNs) in the optic glomeruli and dendrites of large descending neuron, the giant fiber (GF) shapes the differential connectivity between these neurons.

Strengths:

The authors analyzed the development of a well-known circuit between GF dendrites and LC4 andLPLC2 axons using different approaches. Additionally, they developed an ex-vivo patch clamping technique to show, together with correlative RNA-sequencing data, that contact site restriction is not dependent on neuronal activity. Based on this study, the connectivity pattern between GF and the adjacent different sets of VPNs now provides a very interesting model to investigate developmental programs that lead to synaptic specificity.

Weaknesses:

Following are the concerns that significantly impact the veracity of conclusions drawn based on the data provided.

(1) All the data related to the activity of VPNs and GF and how this activity is related to the connectivity and/or maintaining and stabilizing this connectivity is correlative. The expression profiles of synaptic molecules (only at RNA level) over time or the appearance of pre and post synaptic proteins or the spontaneous spike patterns in GF do not show the role of activity in synapse specificity program. Synaptic molecules have been previously shown to be present at presynaptic sites without being involved in activity (Chen et al., 2014, Jin et al., 2018). To show whether activity is indeed not required for connectivity for either of the cell types (LC4 and LPLC2), they should silence each and also both cell types as early as possible (with the LC4 driver that does not ablate them) and then quantify the contacts with GF. In the same vein, the authors should knock down components of the synaptic machinery as early as possible to show directly the effect on 1) contact formation and 2) contact stabilization. For example, authors state in the lines 267-269 "VPN cholinergic machinery arrives too late to contribute to the initial targeting and localization of VPN axons on GF dendrites. Cholinergic activity instead is likely to participate in VPN and GF synapse refinement and stabilization." This statement would only be valid if the authors knock down the cholinergic machinery and find the contact numbers unchanged in the early stages but significantly different in later stages in comparison to the controls. Furthermore, authors only show increase in the VAChT and ChAT in the presynaptic cells but do not show if the cholinergic receptor AChRs are even expressed in GF cells or at what point they are expressed. Without these receptor expression, cholinergic system might not even be involved in the process. Also, there might be other neurotransmitter systems involved. Authors should at least check if other neurotransmitter systems are expressed in these cells, both pre-and post-synaptic.<br /> Line 371-374: "In the later stages of development, the frequency of synaptic events increase as gap junction proteins are downregulated and cholinergic presynaptic machinery is upregulated to enhance and stabilize synapses with intended synaptic partners while refining unintended contacts". The authors did not show the activity they observed in GF is due to the contacts they make with LC4s and LPLC2s. The functionality of these contacts can be shown by silencing the LC4s and LPLC2s and then doing the patch clamping in GF to see a decrease in the activity. Further, the authors did not show that the reduction in contacts are only by refining "unintended" contacts. There is no evidence that can support this statement.

(2) In the LC4 ablation experiments, authors claim that LC4_4 split Gal4 line is expressed around 18APF, prior to GF LC4 initial contact (Line 387). However, authors do not show the time point of first contact between GF dendrites and LC4 cells. In Fig. 2 the first time point shown is at P36, where there is already significant overlap between GF dendrites and LC4 axons. Authors should show the very first time point where they see any, even if minimal, overlap and/or contact between GFs and LC4s. Once the LC4s are ablated, is the increase in the colocalization between GF and LPLC2 due to LPLC2s increasing their contact numbers or due to them not decreasing the maximum contact numbers that the authors observed at P72 (Fig 2G)? In other words, once the LC4s are ablated, what would the new graph for temporal contact numbers for LPLC2 look like and how it would compare to Fig2G?

(3) If the developmental stages for different lines match, that would be more helpful for comparison. Also, as the authors analyzed expression every 12 hours from 0APF, the panel should also contain earlier time points (e.g. P0, P12) for all lines. This is critical to understand at what point the axons of LC4, LPLC2 and LPLC1 reach their position. From the scale bar in Supp Fig.4, it seems LC4 axons have already reached final position at P24 and there is no extension between P24 and P60. Do the authors know at what point LC4 axons start extending and reach the final position? If the LC4 and LPLC2 arbors are already separated medio-laterally even before GF dendrites extend towards them, it would explain why GF dendrites extending from medial region of the brain would encounter LC4 axons first and LPLC2 axons later, just based on their localization in space.<br /> Further to this point, the authors show in the section two of the paper that it is the GF dendrites that extend, elaborate and refine during the phase the authors analyzed and the authors do not show any morphological change in the axons of the VPNs. Therefore, the title of the paper is 'axon arrival times and physical occupancy establish visual projection neuron integration on developing dendrites in the Drosophila optic glomeruli' is slightly misguided.

(4) In the absence of LC4s, does the LPLC1 and GF colocalization increase or do they still stay disconnected?

(5) Does the absence of LC4s have any effect on GF arbor complexity? Does the graph in Fig 2B and C change? Can the increase in colocalization between LPLC2 and GF be at least partially due to the expansion of GF dendritic volume?

(6) Why is there a segregation in the medial-lateral axis but not in the dorso-ventral axis? Wouldn't the same segregation mechanism be in play in both axes? Also, the authors should clarify if this reduction in dorsal-ventral distribution is because dorso-ventral expansion of GF dendrites beyond the LC4 and LPLC2 axons? Theoretically that would seem to make the LC4s move more ventrally and LPLC2 move more dorsally in comparison to the total arbor.

(7) Why the LPLC2 medial connections are regarded as "mistargeting" in the heading of Supplemental Figure 1? Both in EM data and in some of the confocal datasets, these connections are observed. What is the criteria to label a connection "mistargeting" if it is observed, albeit occasionally, both in EM and confocal datasets?

(8) In Line 126-127, authors state that "we sought to determine how the precise VPN localization along GF dendrites arises across development". However, based in EM and microscopic data, there is considerable variability in the contact numbers and distribution. With such variability present, how can the localization be termed "precise"? Authors should clarify.

eLife assessment

This study provides valuable insights into our understanding of the development of the enteric nervous system. The authors use genetically engineered mice to study the behavior of stem cells in organizing the enteric nervous system and the secreted signals that regulate these cells. The study rests on a degree of incomplete evidence since the characterization of some of the mouse resources is not complete in the current version.

Reviewer #1 (Public Review):

The manuscript by Poltavski and colleagues describes the discovery of previously unreported enteric neural crest-derived cells (ENCDC) which are marked by Pax2 and originating from the Placodes. By creating multiple conditional mouse mutants, the authors demonstrate these cells are a distinct population from the previously reported ENCDCs which originate from the Vagal neural crest cells and express Wnt1.

These Pax2-positive ENCDCs are affected due to the loss of both Ret and Ednrb highlighting that these cells are also ultimately part of the canonical processes governing ENCDC and enteric nervous system (ENS) development. The authors also make explant cultures from the mouse GI tract to detect how Ednrb signaling is important for Ret signaling pathways in these cells and rediscovers the interactions between these 2 pathways. One important observation the authors make is that CGRP-positive neurons in the adult distal colon seem to be primarily derived from these Pax2-positive ENCDCs, which are significantly reduced in the Ednrb mutants, thus highlighting the role of Ednrb in maintaining this neuronal type.

I appreciate the amount of work the authors have put into generating the mouse models to detect these cells, but there isn't any new insight on either the nature of ENCDC development or the role of Ret and Ednrb. Also, there are sophisticated single-cell genomics methods to detect rare cell type/states these days and the authors should either employ some of those themselves in these mouse models or look at extensively publicly available single-cell datasets of the developing wildtype and mutant mouse and human ENS to map out the global transcriptional profile of these cells. A more detailed analysis of these Pax2-positive cells would be really helpful to both the ENS community as well as researchers studying gut motility disorders.

Reviewer #2 (Public Review):

Summary:

This manuscript by Poltavski and colleagues explores the relative contributions of Pax2- and Wnt1- lineage-derived cells in the enteric nervous system (ENS) and how they are each affected by disruptions in Ret and Endrb signaling. The current understanding of ENS development in mice is that vagal neural crest progenitors derived from a Wnt1+ lineage migrate into and colonize the developing gut. The sacral neural crest was thought to make a small contribution to the hindgut in addition but recent work has questioned that contribution and shown that the ENS is entirely populated by the vagal crest (PMID: 38452824). GDNF-Ret and Endothelin3-Ednrb signaling are both known to be essential for normal ENS development and loss of function mutations are associated with a congenital disorder called Hirschsprung's disease. The transcription factor Pax2 has been studied in CNS and cranial placode development but has not been previously implicated in ENS development. In this work, the authors begin with the unexpected observation that conditional knockout of Ednrb in Pax2-expressing cells causes a similar aganglionosis, growth retardation, and obstructed defecation as conditional knockout of Ednrb in Wnt1-expressing cells. The investigators then use the Pax2 and Wnt1 Cre transgenic lines to lineage-trace ENS derivatives and assess the effects of loss of Ret or Ednrb during embryonic development in these lineages. Finally, they use explants from the corresponding embryos to examine the effects of GDNF on progenitor outgrowth and differentiation.

Strengths:

- The manuscript is overall very well illustrated with high-resolution images and figures. Extensive data are presented.

- The identification of Pax2 expression as a lineage marker that distinguishes a subset of cells in the ENS that may be distinct from cells derived from Wnt1+ progenitors is an interesting new observation that challenges the current understanding of ENS development.

- Pax2 has not been previously implicated in ENS development - this manuscript does not directly test that role but hints at the possibility.

- Interrogation of two distinct signaling pathways involved in ENS development and their relative effects on the two purported lineages.

Weaknesses:

- The major challenge with interpreting this work is the use of two transgenic lines, rather than knock-ins, Wnt1-Cre and Pax2-Cre, which are not well characterized in terms of fidelity to native gene expression and recombination efficiency in the ENS. If 100% of cells that express Wnt1 do not express this transgene or if the Pax2 transgene is expressed in cells that do not normally express Pax2, then these observations would have very different interpretations and not support the conclusions made. The two lineages are never compared in the same embryo, which also makes it difficult to assess relative contributions and renders the evidence more circumstantial than definitive.

- Visualization of the Pax2-Cre and Wnt-1Cre induced recombination in cross-sections at postnatal ages would help with data interpretation. If there is recombination induced in the mesenchyme, this would particularly alter the interpretation of Ednrb mutant experiments, since that pathway has been shown to alter gut mesenchyme and ECM, which could indirectly alter ENS colonization.

- No consideration of glia - are these derived from both lineages?

- No discussion of how these observations may fit in with recent work that suggests a mesenchymal contribution of enteric neurons (PMID: 38108810).

eLife assessment

This study presents valuable findings as it shows that sleep rhythm formation and memory capabilities depend on a balanced and rich diet in fly larvae. The evidence supporting the claims of the authors is convincing with rigorous behavioral assays and state-of-the-art genetic manipulations. The work will be of interest to researchers working on sleep and memory.

Joint Public Review:

Summary:

This manuscript investigates how energetic demands affect the sleep-wake cycle in Drosophila larvae. L2 stage larvae do not show sleep rhythm and long-term memory (LTM), however, L3 larvae do. The authors manipulate food content to provide insufficient nutrition, which leads to more feeding, no LTM, and no sleep even in older larvae. Similarly, activation of NPF neurons suppresses sleep rhythm. Furthermore, they try to induce a sleep-like state using pharmacology or genetic manipulations in L2 larvae, which can mimic some of the L3 behaviours. A key experimental finding is that activation of DN1a neurons activate the downstream DH44 neurons, as assayed by GCaMP calcium imaging. This occurs only in third instar and not in second instar, in keeping with the development of sleep-wake and feeding separation. The authors also show that glucose metabolic genes are required in Dh44 neurons to develop sleep rhythm and that DH44 neurons respond differently in malnutrition or younger larvae.

Strengths:

Previous studies from the same lab have shown the sleep is required for LTM formation in the larvae, and that this requires DN1a and DH44 neurons. The current work builds upon this observation and addresses in more detail when and how this might develop. The authors can show that low quality food exposure and enhanced feeding during larval stage of Drosophila affects the formation of sleep rhythm and long-term memory. This suggests that the development of sleep and LTM are only possible under well fed and balanced nutrition in fly larvae. Non-sleep larvae were fed in low sugar conditions and indeed, the authors also find glucose metabolic genes to be required for a proper sleep rhythm. The paper presents precise genetic manipulations of individual classes of neurons in fly larvae followed by careful behavioural analysis. The authors also combine thermogenetic or peptide bath application experiments with direct calcium imaging of specific neurons.

Weaknesses:

The authors tried to induce sleep in younger L2 larvae, however the behavioral results suggest that they were not able to induce proper sleep behaviour as in normal L3 larvae. Thus, they cannot show that sleep during L2 stage would be sufficient to form LTM.<br /> The authors suggest that larval Dh44 neurons may integrate "information about the nutritional environment through the direct sensing of glucose levels to modulate sleep-wake rhythm development". They identify glucose metabolism genes (e.g., Glut1) in the downstream DH44 neurons as being required for the organization of the sleep-wake-feeding rhythm, and that CCHa signaling in DN1a signaling to the DH44 cells via the receptor. However, how this is connected is not well explained. Do the authors think that the nutrient sensing is only occurring in the DH44 neurons and not in DN1a or other neurons? Would not knocking down glucose metabolism in any neuron lead to a functional defect? What is the evidence that Dh44 neurons are specific sensors of nutritional state? For example, do the authors think that e.g. the overexpression of Glut1 in Dh44 neurons, a manipulation that can increase transport of glucose into cells, would rescue the effects of low-sugar food?<br /> Some of the genetic controls seem to be inconsistent suggesting some genetic background effects. In Figure 2B, npf-gal4 flies without the UAS show no significant circadian change in sleep duration, whereas UAS-TrpA flies do. The genetic control data in Figure 2D are also inconsistent. Npf-Gal4 seems to have some effect by itself without the UAS. The same is not seen with R76G11-Gal4. Suppl Fig 2: Naïve OCT and AM preference in L3 expressing various combinations of the transgenes show significant differences. npf-Gal4 alone seems to influence preference.<br /> The sleep duration and bout number/length data are highly variable.

Reviewer #1 (Public Review):

Summary:

The manuscript gives a broad overview of how to write NeuroML, and a brief description of how to use it with different simulators and for different purposes - cells to networks, simulation, optimization, and analysis. From this perspective, it can be an extremely useful document to introduce new users to NeuroML.

However, the manuscript itself seems to lose sight of this goal in many places, and instead, the description at times seems to target software developers. For example, there is a long paragraph on the board and user community. The discussion on simulator tools seems more for developers, not users. All the information presented at the level of a developer is likely to be distracting to readers..

Strengths:

The modularity of NeuroML is indeed a great advantage. For example, the ability to specify the channel file allows different channels to be used with different morphologies without redundancy. The hierarchical nature of NeuroML also is commendable, and well illustrated in Figures 2a through c.

The number of tools available to work with NeuroML is impressive.

The abstract, beginning, and end of the manuscript present and discuss incorporating NeuroML into research workflows to support FAIR principles.

Having a Python API and providing examples using this API is fantastic. Exporting to NeuroML from Python is also a great feature.

Weaknesses:

Though modularity is a strength, it is unclear to me why the cell morphology isn't also treated similarly, i.e., specify the morphology of a multi-compartmental model in a separate file, and then allow the cell file to specify not only the files containing channels, but also the file containing the multi-compartmental morphology, and then specify the conductance for different segment groups. Also, after pynml_write_neuroml2_file, you would not have a super long neuroML file for each variation of conductances, since there would be no need to rewrite the multi-compartmental morphology for each conductance variation.

This would be especially important for optimizations, if each trial optimization wrote out the neuroML file, then including the full morphology of a realistic cell would take up excessive disk space, as opposed to just writing out the conductance densities. As long as cell morphology must be included in every cell file, then NeuroML is not sufficiently modular, and the authors should moderate their claim of modularity (line 419) and building blocks (551). In addition, this is very important for downloading NeuroML-compliant reconstructions from NeuroMorpho.org. If the cell morphology cannot be imported, then the user has to edit the file downloaded from NeuroMorpho.org, and provenance can be lost. Also, Figure 2d loses the hierarchical nature by showing ion channels, synapses, and networks as separate main branches of NeuroML.

In Figure 5, the difference between the core and native simulator is unclear. What is involved in helper scripts? I thought neurons could read NeuroML? If so, why do you need the export simulator-specific scripts? In addition, it seems strange to call something the "core" simulation engine, when it cannot support multi-compartmental models. It is unclear why "other simulators" that natively support NeuroML cannot be called the core. It might be more helpful to replace this sort of classification with a user-targeted description. The authors already state which simulators support NeuroML and which ones need code to be exported. In contrast, lines 369-370 mention that not all NeuroML models are supported by each simulator. I recommend expanding this to explain which features are supported in each simulator. Then, the unhelpful separation between core and native could be eliminated.

The body of the manuscript has so much other detail that I lose sight of how NeuroML supports FAIR. It is also unclear who is the intended audience. When I get to lines 336-344, it seems that this description is too much detail for the audience. The paragraph beginning on line 691 is a great example of being unclear about who is the audience. Does someone wanting to develop NeuroML models need to understand XSD schema? If so, the explanation is not clear. XSD schema is not defined and instead explains NeuroML-specific aspects of XSD. Lines 734-735 are another example of explaining to code developers (not model developers).

Reviewer #2 (Public Review):

Summary:

Developing neuronal models that are shareable, reproducible, and interoperable allows the neuroscience community to make better use of published models and to collaborate more effectively. In this manuscript, the authors present a consolidated overview of the NeuroML model description system along with its associated tools and workflows. They describe where different components of this ecosystem lay along the model development pathway and highlight resources, including documentation and tutorials, to help users employ this system.

Strengths:

The manuscript is well-organized and clearly written. It effectively uses the delineated model development life cycle steps, presented in Figure 1, to organize its descriptions of the different components and tools relating to NeuroML. It uses this framework to cover the breadth of the software ecosystem and categorize its various elements. The NeuroML format is clearly described, and the authors outline the different benefits of its particular construction. As primarily a means of describing models, NeuroML also depends on many other software components to be of high utility to computational neuroscientists; these include simulators (ones that both pre-date NeuroML and those developed afterwards), visualization tools, and model databases.

Overall, the rationale for the approach NeuroML has taken is convincing and well-described. The pointers to existing documentation, guides, and the example usages presented within the manuscript are useful starting points for potential new users. This manuscript can also serve to inform potential users of features or aspects of the ecosystem that they may have been unaware of, which could lower obstacles to adoption. While much of what is presented is not new to this manuscript, it still serves as a useful resource for the community looking for information about an established, but perhaps daunting, set of computational tools.

Weaknesses:

The manuscript in large part catalogs the different tools and functionalities that have been produced through the long development cycle of NeuroML. As discussed above, this is quite useful, but it can still be somewhat overwhelming for a potential new user of these tools. There are new user guides (e.g., Table 1) and example code (e.g. Box 1), but it is not clear if those resources employ elements of the ecosystem chosen primarily for their didactic advantages, rather than general-purpose utility. I feel like the manuscript would be strengthened by the addition of clearer recommendations for users (or a range of recommendations for users in different scenarios).

For example, is the intention that most users should primarily use the core NeuroML tools and expand into the wider ecosystem only under particular circumstances? What are the criteria to keep in mind when making that decision to use alternative tools (scale/complexity of model, prior familiarity with other tools, etc.)? The place where it seems most ambiguous is in the choice of simulator (in part because there seem to be the most options there) - are there particular scenarios where the authors may recommend using simulators other than the core jNeuroML software?

The interoperability of NeuroML is a major strength, but it does increase the complexity of choices facing users entering into the ecosystem. Some clearer guidance in this manuscript could enable computational neuroscientists with particular goals in mind to make better strategic decisions about which tools to employ at the outset of their work.

eLife assessment

The findings are fundamental for understanding IgM signaling in myeloid cells. The work is compelling in its ability to manipulate and harness myeloid cells to further anti-tumor immunity.

Reviewer #2 (Public Review):

Summary:

While a significant portion of immunotherapy research has focused on the pivotal role of T cells in tumor immunity, their effectiveness may be limited by the suppressive nature of the tumor environment. On the other hand, myeloid cells are commonly found within tumors and can withstand these adverse conditions. However, these cells often adopt an immunosuppressive phenotype when infiltrating tumors. Therefore, manipulating myeloid cells could potentially enhance the anti-tumor potential of immunotherapy.<br /> In this manuscript, Farhat-Younes and colleagues have demonstrated that activating the IgM receptor signaling in myeloid cells induces an oxygen burst, the secretion of Granzyme B, and the lysis of adjacent tumor cells. Furthermore, they have outlined a strategy to utilize these features to generate CAR macrophages. However, they have identified a limitation: the expression of scFv in myeloid cells induces ER stress and the degradation of misfolded proteins. To address this issue, chimeric receptors were designed based on the high-affinity FcγRI for IgG. When macrophages transfected with these receptors were exposed to tumor-binding IgG, extensive tumor cell killing, and the release of reactive oxygen species and Granzyme B were observed.

Strengths:

In general, I consider this work to be significant, and the results are compelling. It emphasizes the specific considerations and requirements for successful manipulation in myeloid cells, which could further advance the field of cellular engineering for the benefit of immunotherapy

Following the revision of the original manuscript, I can clearly state that my concerns have been addressed and the article has been improved.

Author response:

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

Public Review:

Summary:

In this manuscript, the authors set out to understand how different TLR4 agonists trigger Myddosome assembly and seek to examine how the potent LPS agonist induces a heightened TLR4 response. A strength of the study is that the authors employ a novel light sheet imaging modality coupled to nanopipette delivery of TLR4 ligands. The authors use this technological innovation to resolve the dynamics of Myddosome formation within the whole cell volume of macrophage cell lines expressing MyD88-YFP. The main finding is that the kinetics of Myddosome formation is slower for the weaker agonist Abeta than LPS. However, Abeta amyloids resulted in the formation of larger MyD88-YFP puncta that persisted for longer. The authors suggest the slower kinetics of formation and larger puncta size reflect how Abeta amyloids are a less efficient TLR4 agonist. Many Toll-like receptors are now known to recognize endogenous produced danger signals and microbially derived molecules. This work is the first to compare the signaling kinetics of endogenous versus microbially derived TLR agonists.

Strengths:

A key strength of this work is the technological achievement of imaging Myddosomes within the entire cell volume and using a nanopipette to administer ligands directly to single cells. The authors also combine this light sheet microscopy with STORM imaging to gain a super-resolved view of the assembly of Myddosomes. These findings suggest that Myddosomes formed in response to Abeta have a more irregular morphology. We conclude that these technological achievements are significant in improving our understanding of the dynamics of TLR4 signaling in response to diverse agonists. Given the limited literature on the molecular dynamics of innate immune signal transduction, this study is an important addition to the field.

Weaknesses:

One limitation of the paper is that a suitable explanation for how larger Myddosomes would contribute to an attenuated downstream signaling response. Do the larger clusters of nucleated MyD88 polymers reflect inefficiency in assembling fully formed Myddosomes that contain IRAK4/2? Could the MyD88-GFP puncta be stained with antibodies against IRAK4 (or IRAK2) to determine the frequency and probably of the two ligands to stimulate signal transduction beyond MyD88 assembly?

A second weakness is the discussion. The authors should explore other explanations for the observed differences in Myddosome formation between TLR4 agonists. For example, could the observed delay in Myddosome assembly in response to Abeta be due to different binding affinity or kinetics to TLR4? Can this be ruled out?

We thank the reviewer for these comments.

To address the first comment we have added a section on the limitations of the current study and suggested that future work could use IRAK4 or 2 staining to identify Myddosomes that are functional as well as working with cells where the Myddosome expression levels is at physiological levels, which may reduce the formation of larger Myddosomes.

The reviewer is correct that the difference in delay time for Myddosome formation could be due slow formation of a TLR4 dimer or binding to the TLR4 dimer, rather than the time take to assemble the Myddosome after TLR4 dimerisation and binding since we have only measured the delay time for Myddosome formation when triggered by LPS or Aβ aggregates. This delay times involves dimerization of TLR4, binding of LPS or Aβ aggregates to the TLR4 dimer followed by Myddosome formation. These other processes might contribute to the difference in delay time that we observed between LPS or Aβ aggregates. It is worth noting that in our experiments we deliver the LPS or Aβ aggregates directly onto the surface for 5 seconds and that we previously showed the presence of the preformed TLR4 dimers on the cell surface (Latty et al., 2018). The affinity of Aβ aggregates for TLR4 is not known but LPS has a high affinity for TLR4, estimated to ∼3 nM for lipid A–TLR4-MD-2 (Akashi et al., 2003). However, even with this high affinity which implies fast binding, direct delivery directly onto the surface and the presence of preformed TLR4 dimers on the cell surface we observed that it took 80 s to observe Myddosome formation. This indicates that Myddosome formation is the slow step for LPS triggering. This is likely to be the case Aβ aggregates, since pM concentrations of aggregates can trigger TLR4 signalling (Hughes et al., 2020) indicating high affinity. However, it is not possible to rule out a contribution of a difference in affinity to observed difference in delay time without measuring the affinity directly.

We have added both these points to a new paragraph on the limitations of the study in the Discussion.

eLife assessment

This important study uses a novel light sheet imaging technique to investigate how different TLR4 agonists regulate Myddosome formation. The data showing that LPS and A-beta can control the kinetics and size of Myddosome assembly are compelling. This paper should be of substantial interest to the innate immunity field.

Reviewer #1 (Public Review):

Recognition of bacterial lipopolysaccharide by Toll-like Receptor 4 is an essential molecular event triggering inflammation and overcoming Recognition of bacterial lipopolysaccharide by Toll-like Receptor 4 is an essential molecular event in triggering inflammation and overcoming infection by gram-negative bacteria. However, TLR4 has recently been found to respond to other endogenously derived ligands. This has implicated TLR4 signaling in the development of disease pathology, for example, Alzheimer's disease, through the recognition of amyloid-beta. Intriguingly, the signaling response to these non-bacterial-derived ligands differs from that of bacterial-derived LPS, suggesting mechanistic differences between endogenous and bacterial-derived agonists. In this work, the authors set out to characterize these mechanistic differences. TLR4 signals through two large macromolecular complexes that assemble at activated receptors: the Myddosome and Triffosome. One hypothesis the authors aimed to test was that different ligands alter these signaling complexes' kinetics and nano-scale features. The authors focused on testing this hypothesis by examining the formation of the Myddosome in live cells. A significant strength of the paper is that the authors developed technological innovations to address this problem. Using a nanopipette delivery mechanism combined with light sheet microscopy, the authors could observe Myddosome signaling in the whole cell volume of live macrophages. This allowed them to accurately quantify the Myddosome number, size, and kinetics of complex formation and compare cells stimulated with amyloid-beta and LPS. The authors discovered differences in Myddosomes formed under LPS versus amyloid-beta stimulation. In general, amyloid-beta TLR4 stimulation resulted in slower Myddosome formation with altered morphology. One limitation of the work, which the authors point out in the discussion, is that they could not distinguish signaling-competent Myddosomes. Future work will be needed to understand whether these amyloid beta induced Myddosomes assembly have a similar or altered complement of downstream signaling proteins (such as the IRAK4/1 and TRAF6). Secondly, the structural basis for how TLR4 would distinguish between different radically agonists remains speculative, and will need further investigation. Nonetheless, this paper is important for the technological innovation to look at the molecular dynamics of signal transduction, a technology that could be adapted to study other receptor signaling pathways.

It is already known that the subcellular location of intracellular TLRs is important for limiting the recognition of self-derived ligands and maintaining tolerance. This work hints at another possible layer of regulation: that a cell surface TLR (TLR4) generates diverse signaling outcomes to extrinsic or intrinsically derived agonists by changing the dynamic behavior of signaling proteins. If correct (and much further work is required to understand endogenous TLR ligands better), it might suggest that the innate immune system employs the same molecular hardware but with altered kinetics to distinguish between exogenous and endogenous inflammatory signals. Thus, pathological aggregates or markers of sterile inflammation might be recognized and responded to by a specific signaling program that is defined kinetically. It will be an interesting direction for future studies to investigate whether and how diverse pathogen and endogenous inflammatory signals modulate the dynamics of signaling complexes.

Author response:

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

We are grateful for these balanced, nuanced evaluations of our work concerning the observed epistatic trends and our interpretations of their mechanistic origins. Overall, we think the reviewers have done an excellent job at recognizing the novel aspects of our findings while also discussing the caveats associated with our interpretations of the biophysical effects of these mutations. We believe it is important to consider both of these aspects of our work in order to appreciate these advances and what sorts of pertinent questions remain.

Notably, both reviewers are concerned that our lack of experimental approaches to compare the conformational properties of GnRHR variants weakens our claims. We would first humbly suggest that this constitutes a more general caveat that applies to nearly all investigations of the cellular misfolding of α-helical membrane proteins. Whether or not any current in vitro folding measurements report on conformational transitions that are relevant to cellular protein misfolding reactions remains an active area of debate (discussed further below). Nevertheless, while we concede that our structural and/ or computational evaluations of various mutagenic effects remain speculative, prevailing knowledge on the mechanisms of membrane protein folding suggest our mutations of interest (V276T and W107A) are highly unlikely to promote misfolding in precisely the same way. Thus, regardless of whether or not we were able experimentally compare the relevant folding energetics of GnRHR variants, we are confident that the distinct epistatic interactions formed by these mutations reflect variations in the misfolding mechanism and that they are distinct from the interactions that are observed in the context of stable proteins. In the following, we provide detailed considerations concerning these caveats in relation to the reviewers’ specific comments.

Reviewer #1 (Public Review):

The paper carries out an impressive and exhaustive non-sense mutagenesis using deep mutational scanning (DMS) of the gonadotropin-releasing hormone receptor for the WT protein and two single point mutations that I) influence TM insertion (V267T) and ii) influence protein stability (W107A), and then measures the effect of these mutants on correct plasma membrane expression (PME).

Overall, most mutations decreased mGnRHR PME levels in all three backgrounds, indicating poor mutational tolerance under these conditions. The W107A variant wasn't really recoverable with low levels of plasma membrane localisation. For the V267T variant, most additional mutations were more deleterious than WT based on correct trafficking, indicating a synergistic effect. As one might expect, there was a higher degree of positive correlation between V267T/W107A mutants and other mutants located in TM regions, confirming that improper trafficking was a likely consequence of membrane protein co-translational folding. Nevertheless, context is important, as positive synergistic mutants in the V27T could be negative in the W107A background and vice versa. Taken together, this important study highlights the complexity of membrane protein folding in dissecting the mechanism-dependent impact of disease-causing mutations related to improper trafficking.

Strengths

This is a novel and exhaustive approach to dissecting how receptor mutations under different mutational backgrounds related to co-translational folding, could influence membrane protein trafficking.

Weaknesses

The premise for the study requires an in-depth understanding of how the single-point mutations analysed affect membrane protein folding, but the single-point mutants used seem to lack proper validation.

Given our limited understanding of the structural properties of misfolded membrane proteins, it is unclear whether the relevant conformational effects of these mutations can be unambiguously validated using current biochemical and/ or biophysical folding assays. X-ray crystallography, cryo-EM, and NMR spectroscopy measurements have demonstrated that many purified GPCRs retain native-like structural ensembles within certain detergent micelles, bicelles, and/ or nanodiscs. However, helical membrane protein folding measurements typically require titration with denaturing detergents to promote the formation of a denatured state ensemble (DSE), which will invariably retain considerable secondary structure. Given that the solvation provided by mixed micelles is clearly distinct from that of native membranes, it remains unclear whether these DSEs represent a reasonable proxy for the misfolded conformations recognized by cellular quality control (QC, see https://doi.org/10.1021/acs.chemrev.8b00532). Thus, the use and interpretation of these systems for such purposes remains contentious in the membrane protein folding community. In addition to this theoretical issue, we are unaware of any instances in which GPCRs have been found to undergo reversible denaturation in vitro- a practical requirement for equilibrium folding measurements (https://doi.org/10.1146/annurev-biophys-051013-022926). We note that, while the resistance of GPCRs to aggregation, proteolysis, and/ or mechanical unfolding have also been probed in micelles, it is again unclear whether the associated thermal, kinetic, and/ or mechanical stability should necessarily correspond to their resistance to cotranslational and/ or posttranslational misfolding. Thus, even if we had attempted to validate the computational folding predictions employed herein, we suspect that any resulting correlations with cellular expression may have justifiably been viewed by many as circumstantial. Simply put, we know very little about the non-native conformations are generally involved in the cellular misfolding of α-helical membrane proteins, much less how to measure their relative abundance. From a philosophical standpoint, we prefer to let cells tell us what sorts of broken protein variants are degraded by their QC systems, then do our best to surmise what this tells us about the relevant properties of cellular DSEs.

Despite this fundamental caveat, we believe that the chosen mutations and our interpretation of their relevant conformational effects are reasonably well-informed by current modeling tools and by prevailing knowledge on the physicochemical drivers of membrane protein folding and misfolding. Specifically, the mechanistic constraints of translocon-mediated membrane integration provide an understanding of the types of mutations that are likely to disrupt cotranslational folding. Though we are still learning about the protein complexes that mediate membrane translocation (https://doi.org/10.1038/s41586-022-05336-2), it is known that this underlying process is fundamentally driven by the membrane depth-dependent amino acid transfer free energies (https://doi.org/10.1146/annurev.biophys.37.032807.125904). This energetic consideration suggests introducing polar side chains near the center of a nascent TMDs should almost invariably reduce the efficiency of topogenesis. To confirm this in the context of TMD6 specifically, we utilized a well-established biochemical reporter system to confirm that V276T attenuates its translocon-mediated membrane integration (Fig. S1)- at least in the context of a chimeric protein. We also constructed a glycosylation-based topology reporter for full-length GnRHR, but ultimately found its’ in vitro expression to be insufficient to detect changes in the nascent topological ensemble.

In contrast to V276T, the W107A mutation is predicted to preserve the native topological energetics of GnRHR due to its position within a soluble loop region. W107A is also unlike V276T in that it clearly disrupts tertiary interactions that stabilize the native structure. This mutation should preclude the formation of a structurally conserved hydrogen bonding network that has been observed in the context of at least 25 native GPCR structures (https://doi.org/10.7554/eLife.5489). However, without a relevant folding assay, the extent to which this network stabilizes the native GnRHR fold in cellular membranes remains unclear. Overall, we admit that these limitations have prevented us from measuring how much V276T alters the efficiency of GnRHR topogenesis, how much the W107A destabilizes the native fold, or vice versa. Nevertheless, given these design principles and the fact that both reduce the plasma membrane expression of GnRHR, as expected, we are highly confident that the structural defects generated by these mutations do, in fact, promote misfolding in their own ways. We also concede that the degree to which these mutagenic perturbations are indeed selective for specific folding processes is somewhat uncertain. However, it seems exceedingly unlikely that these mutations should disrupt topogenesis and/ or the folding of the native topomer to the exact same extent. From our perspective, this is the most important consideration with respect to the validity of the conclusions we have made in this manuscript.

Furthermore, plasma membrane expression has been used as a proxy for incorrect membrane protein folding, but this not necessarily be the case, as even correctly folded membrane proteins may not be trafficked correctly, at least, under heterologous expression conditions. In addition, mutations can affect trafficking and potential post-translational modifications, like glycosylation.

While the reviewer is correct that the sorting of folded proteins within the secretory pathway is generally inefficient, it is also true that the maturation of nascent proteins within the ER generally bottlenecks the plasma membrane expression of most α-helical membrane proteins. Our group and several others have demonstrated that the efficiency of ER export generally appears to scale with the propensity of membrane proteins to achieve their correct topology and/ or to achieve their native fold (see https://doi.org/10.1021/jacs.5b03743 and https://doi.org/10.1021/jacs.8b08243). Notably, these investigations all involved proteins that contain native glycosylation and various other post-translational modification sites. While we cannot rule out that certain specific combinations of mutations may alter expression through their perturbation of post-translational GnRHR modifications, we feel confident that the general trends we have observed across hundreds of variants predominantly reflect changes in folding and cellular QC. This interpretation is supported by the relationship between observed trends in variant expression and Rosetta-based stability calculations, which we identified using unbiased unsupervised machine learning approaches (compare Figs. 6B & 6D).

Reviewer #2 (Public Review):

Summary:

In this paper, Chamness and colleagues make a pioneering effort to map epistatic interactions among mutations in a membrane protein. They introduce thousands of mutations to the mouse GnRH Receptor (GnRHR), either under wild-type background or two mutant backgrounds, representing mutations that destabilize GnRHR by distinct mechanisms. The first mutant background is W107A, destabilizing the tertiary fold, and the second, V276T, perturbing the efficiency of cotranslational insertion of TM6 to the membrane, which is essential for proper folding. They then measure the surface expression of these three mutant libraries, using it as a proxy for protein stability, since misfolded proteins do not typically make it to the plasma membrane. The resulting dataset is then used to shed light on how diverse mutations interact epistatically with the two genetic background mutations. Their main conclusion is that epistatic interactions vary depending on the degree of destabilization and the mechanism through which they perturb the protein. The mutation V276T forms primarily negative (aggravating) epistatic interactions with many mutations, as is common to destabilizing mutations in soluble proteins. Surprisingly, W107A forms many positive (alleviating) epistatic interactions with other mutations. They further show that the locations of secondary mutations correlate with the types of epistatic interactions they form with the above two mutants.

Strengths:

Such a high throughput study for epistasis in membrane proteins is pioneering, and the results are indeed illuminating. Examples of interesting findings are that: (1) No single mutation can dramatically rescue the destabilization introduced by W107A. (2) Epistasis with a secondary mutation is strongly influenced by the degree of destabilization introduced by the primary mutation. (3) Misfolding caused by mis-insertion tends to be aggravated by further mutations. The discussion of how protein folding energetics affects epistasis (Fig. 7) makes a lot of sense and lays out an interesting biophysical framework for the findings.

Weaknesses:

The major weakness comes from the potential limitations in the measurements of surface expression of severely misfolded mutants. This point is discussed quite fairly in the paper, in statements like "the W107A variant already exhibits marginal surface immunostaining" and many others. It seems that only about 5% of the W107A makes it to the plasma membrane compared to wild-type (Figures 2 and 3). This might be a low starting point from which to accurately measure the effects of secondary mutations.

The reviewer raises an excellent point that we considered at length during the analysis of these data and the preparation of the manuscript. Though we remain confident in the integrity of these measurements and the corresponding analyses, we now realize this aspect of the data required further discussion and documentation which we have provided in the revised version of the manuscript as is described in the following.

Still, the authors claim that measurements of W107A double mutants "still contain cellular subpopulations with surface immunostaining intensities that are well above or below that of the W107A single mutant, which suggests that this fluorescence signal is sensitive enough to detect subtle differences in the PME of these variants". I was not entirely convinced that this was true.

We made this statement based on the simple observation that the surface immunostaining intensities across the population of recombinant cells expressing the library of W107A double mutants was consistently broader than that of recombinant cells expressing W107A GnRHR alone (see Author response image 1 for reference). Given that the recombinant cellular library represents a mix of cells expressing ~1600 individual variants that are each present at low abundance, the pronounced tails within this distribution presumably represent the composite staining of many small cellular subpopulations that express collections of variants that deviate from the expression of W107A to an extent that is significant enough to be visible on a log intensity plot.

Author response image 1.

Firstly, I think it would be important to test how much noise these measurements have and how much surface immunostaining the W107A mutant displays above the background of cells that do not express the protein at all.

For reference, the average surface immunostaining intensity of HEK293T cells transiently expressing W107A GnRHR was 2.2-fold higher than that of the IRES-eGFP negative, untransfected cells within the same sample- the WT immunostaining intensity was 9.5-fold over background by comparison. Similarly, recombinant HEK293T cells expressing the W107A double mutant library had an average surface immunostaining intensity that was 2.6-fold over background across the two DMS trials. Thus, while the surface immunostaining of this variant is certainly diminished, we were still able to reliably detect W107A at the plasma membrane even under distinct expression regimes. We have included these and other signal-to-noise metrics for each experiment in the Results section of the revised manuscript.

Beyond considerations related to intensity, we also previously noticed the relative intensity values for W107A double mutants exhibited considerable precision across our two biological replicates. If signal were too poor to detect changes in variant expression, we would have expected a plot of the intensity values across these two replicates to form a scatter. Instead, we found DMS intensity values for individual variants to be highly correlated from one replicate to the next (Pearson’s R2 = 0.95, see Author response image 2 for reference). This observation empirically demonstrates that this assay consistently differentiated between variants that exhibit slightly enhanced immunostaining from those that have even lower immunostaining than W107A GnRHR. We have included these discussion points in the Results section as well as scatter plots for replicate variant intensities within all three genetic backgrounds in Figure S3 of the revised manuscript.

Author response image 2.

But more importantly, it is not clear if under this regimen surface expression still reports on stability/protein fitness. It is unknown if the W107A retains any function or folding at all. For example, it is possible that the low amount of surface protein represents misfolded receptors that escaped the ER quality control.

While we believe that such questions are outside the scope of this work, we certainly agree that it is entirely possible that some of these variants bypass QC without achieving their native fold. This topic is quite interesting to us but is quite challenging to assess in the context of GPCRs, which have complex fitness landscapes that involve their propensity to distinguish between different ligands, engage specific components associated with divergent downstream signaling pathways, and navigate between endocytic recycling/ degradation pathways following activation. In light of the inherent complexity of GPCR function, we humbly suggest our choice of a relatively simple property of an otherwise complex protein may be viewed as a virtue rather than a shortcoming. Protein fitness is typically cast as the product of abundance and activity. Rather than measuring an oversimplified, composite fitness metric, we focused on one variable (plasma membrane expression) and its dominant effector (folding). We believe restraining the scope in this manner was key for the elucidation of clear mechanistic insights.

The differential clustering of epistatic mutations (Fig. 6) provides some interesting insights as to the rules that dictate epistasis, but these too are dominated by the magnitude of destabilization caused by one of the mutations. In this case, the secondary mutations that had the most interesting epistasis were exceedingly destabilizing. With this in mind, it is hard to interpret the results that emerge regarding the epistatic interactions of W107A. Furthermore, the most significant positive epistasis is observed when W107A is combined with additional mutations that almost completely abolish surface expression. It is likely that either mutation destabilizes the protein beyond repair. Therefore, what we can learn from the fact that such mutations have positive epistasis is not clear to me. Based on this, I am not sure that another mutation that disrupts the tertiary folding more mildly would not yield different results. With that said, I believe that the results regarding the epistasis of V276T with other mutations are strong and very interesting on their own.

We agree with the reviewer. In light of our results we believe it is virtually certain that the secondary mutations characterized herein would be likely to form distinct epistatic interactions with mutations that are only mildly destabilizing. Indeed, this insight reflects one of the key takeaway messages from this work- stability-mediated epistasis is difficult to generalize because it should depend on the extent to which each mutation changes the stability (ΔΔG) as well as initial stability of the WT/ reference sequence (ΔG, see Figure 7). Frankly, we are not so sure we would have pieced this together as clearly had we not had the fortune (or misfortune?) of including such a destructive mutation like W107A as a point of reference.

Additionally, the study draws general conclusions from the characterization of only two mutations, W107A and V276T. At this point, it is hard to know if other mutations that perturb insertion or tertiary folding would behave similarly. This should be emphasized in the text.

We agree. Our findings suggest different mutations may not behave similarly, which we believe is a key finding of this work. We have emphasized this point in the Discussion section of the revised manuscript as follows:

“These findings suggest the folding-mediated epistasis is likely to vary among different classes of destabilizing mutations in a manner that should also depend on folding efficiency and/ or the mechanism(s) of misfolding in the cell.”

Some statistical aspects of the study could be improved:

(1) It would be nice to see the level of reproducibility of the biological replicates in a plot, such as scatter or similar, with correlation values that give a sense of the noise level of the measurements. This should be done before filtering out the inconsistent data.

We thank the reviewer for this suggestion and will include scatters for each genetic background like the one shown above in Figure S3 of the revised version of the manuscript.

(2) The statements "Variants bearing mutations within the C- terminal region (ICL3-TMD6-ECL3-TMD7) fare consistently worse in the V276T background relative to WT (Fig. 4 B & E)." and "In contrast, mutations that are 210 better tolerated in the context of W107A mGnRHR are located 211 throughout the structure but are particularly abundant among residues 212 in the middle of the primary structure that form TMD4, ICL2, and ECL2 213 (Fig. 4 C & F)." are both hard to judge. Inspecting Figures 4B and C does not immediately show these trends, and importantly, a solid statistical test is missing here. In Figures 4E and F the locations of the different loops and TMs are not indicated on the structure, making these statements hard to judge.

We apologize for this oversight and thank the reviewer for pointing this out. We utilized paired Wilcoxon-Signed Rank Tests to evaluate the statistical significance of these observations and modified the description of these findings in the revised version of the results section as follows:

“Variants bearing mutations within the C-terminal regions including ICL3, TMD6, and TMD7 fare consistently worse in the V276T background relative to WT (paired Wilcoxon-Signed Rank Test p-values of 0.0001, 0.02, and 0.005, respectively) (Fig. 4 B & E). Given that V276T perturbs the cotranslational membrane integration of TMD6 (Fig. S1, Table S1), this directional bias potentially suggests that the apparent interactions between these mutations manifest during the late stages of cotranslational folding. In contrast, mutations that are better tolerated in the context of W107A mGnRHR are located throughout the structure but are particularly abundant among residues in the middle of the primary structure that form ICL2, TMD4, and ECL2 (paired Wilcoxon-Signed Rank Test p-values of 0.0005, 0.0001, and 0.004, respectively) (Fig. 4 C & F).”

(3) The following statement lacks a statistical test: "Notably, these 98 variants are enriched with TMD variants (65% TMD) relative to the overall set of 251 variants (45% TMD)." Is this enrichment significant? Further in the same paragraph, the claim that "In contrast to the sparse epistasis that is generally observed between mutations within soluble proteins, these findings suggest a relatively large proportion of random mutations form epistatic interactions in the context of unstable mGnRHR variants". Needs to be backed by relevant data and statistics, or at least a reference.

We thank the reviewer for this reasonable suggestion. In the revised manuscript, we included the results of a paired Wilcoxon-Signed Rank Test that confirms the statistical significance of this observation and modified the Results section to reflect this as follows:

“Notably, these 98 variants are enriched with TMD variants (65% TMD) relative to the overall set of 251 variants (45% TMD, Fisher’s Exact Test p = 0.0019). These findings suggest random mutations form epistatic interactions in the context of unstable mGnRHR variants in a manner that depends on the specific folding defect (V276T vs. W107A) and topological context.”

Reviewer #1 (Recommendations for the Authors):

As far as this reviewer is aware, the effect of the V267T variant on MP insertion has not been measured directly; its position corresponds to T277 in TMD6 of human GnRHR that has been measured for TM insertion, but given the clear lack of conservation (threonine vs valine) the mutation in TM6 could potentially have a different impact on the mouse homologue. Please clarify what the predicted delta TM for insertion is between human and mouse GnRHR is? Moreover, I would argue that single TM insertion by tethering to Lep is insufficient to understand MP insertion/folding, as neighbouring TM helices could help to drive TM6 insertion. Has ER microsome experiments for mouse GnRHR also been carried out in the context of neighbouring helices?

We included measurements (and predictions) of the impact of the V276T substitution on the translocon-mediated membrane integration of the mouse TMD6 in the context of a chimeric Lep protein (see Fig. S1 & Table S1). Our results reveal that this substitution decreases the efficiency of TMD6 membrane integration by ~10%. Though imperfect, this prevailing biochemical assay remains popular for a variety of theoretical and technical reasons. Importantly, extensive experimental testing of this system has shown that these measurements report apparent equilibrium constants that are well-described by two-state equilibrium partitioning models (see DOIs 10.1038/nature03216 and 10.1038/nature06387). This observation provides a reasonable rationale to interpret these measurements using energetic models as we have in this work (see Table S1). From a technical perspective, the Lep system is also advantageous due to the fact that this protein is generally well expressed in the context of in vitro translation systems containing native membranes, which generally ensures a consistent signal to noise and dynamic range for membrane integration measurements. Nevertheless, the reviewers are correct that membrane integration efficiencies are likely distinct in the context of the native mGnRHR protein. For these reasons, we attempted to develop a glycosylation-based topology reporter prior to the posting and submission of this manuscript. However, all GnRHR reporters we tested were poorly expressed in vitro and the resulting 35S-labeled proteins only generated faint smears on our phosphorimaging screens that could not be interpreted. For these reasons, we chose to rely the Lep measurements for these investigations.

The lack of a more relevant topological reporter is one of many challenges we faced in our investigations of this unstable, poorly behaved protein. We share the reviewer’s frustrations concerning the speculative aspects of this work. Nevertheless, there is increasing appreciation for the fact that our perspectives on protein biophysics have been skewed by our continuing choice to focus on the relatively small set of model proteins that are compatible with our favored methodologies (doi: 10.1016/j.tibs.2013.05.001). We humbly suggest this work represents an example of how we can gain a deeper understanding of the limits of biochemical systems when we instead choose to study the unsavory bits of cellular proteomes. But this choice requires a willingness to make some reasonable assumptions and to lean on energetic/ structural modeling from time to time. Despite this limitation, we believe there is still tremendous value in this compromise.

What is the experimental evidence the W107A variant affects the protein structure? Has its melting temperature with and without inverse agonist binding for WT vs the W107A variant been measured, for example? Even heat-FSEC of detergent-solubilised membranes would be informative to know how unstable the W107A variant is. If is very unstable in detergent, then it could be that recovery mutants are going to be unlikely as you are already starting with a poor construct showing poor folding/localisation.

We again understand the rationale for this concern, but do not believe that thermal melting measurements are likely to report the same sorts of conformational transitions involved in cellular misfolding. Heating up a protein to the point in which membranes (or micelles) are disrupted and the proteins begin to form insoluble aggregates is a distinct physical process from those that occur during co- and post-translational folding within intact ER membranes at physiological temperatures (discussed further in the Response to the Reviews). Indeed, as the reviewer points out below, there seems to be little evidence that secretion is linked to thermal stability or various other metrics that others have attempted to optimize for the sake of purification and/ or structural characterization. Thus, we believe it would be just as speculative to suggest thermal aggregation represents a relevant metric for the propensity of membrane proteins to fold in the cell. The physical interpretation of membrane protein misfolding reaction remains contentious in our field due to the key fact that the denatured states of helical membrane proteins remain highly structured in a manner that is hard to generalize beyond the fact that the denatured states retain α-helical secondary structure (doi: 10.1146/annurev-biophys-051013-022926). This is in stark contrast to soluble proteins, where random coil reference states have proven to be generally useful for energetic interpretations of protein stability. For reference, our lab is currently working to leverage epistatic measurements like this to map the prevailing physiological denatured states of an integral membrane protein. Our current findings suggest that non-native electrostatic interactions form in the context of misfolded states. We hope that more information on the structural aspects of these states will help us to develop and interpret meaningful folding measurements within the membrane.

For reference, even in cases when quantitative folding measurements can be achieved, their relevance remains actively debated. As a point of reference, the corresponding author of this work previously worked on the stability and misfolding of another human α-helical membrane protein (PMP22). Like GnRHR, PMP22 is prone to misfolding in the secretory pathway and is associated with dozens of pathogenic mutations that cause protein misfolding. To understand how the thermodynamic stability of this protein is linked to secretion, the corresponding author purified PMP22, reconstituted it into n-Dodecyl-phosphocholine (DPC) micelles, and measured its resistance to denaturation by an anionic denaturing detergent (Lauryl Sarcosine, LS). The results were initially perplexing due to the fact that equilibrium unfolding curves manifested as an exponential decay (rather than a sigmoid) and relaxation kinetics appeared to be dominated by the rate constant for unfolding (doi: 10.1021/bi301635f). Unfortunately, these data could not be fit with existing folding models due to the lack of a folded protein baseline and the absence of a folding arm in the chevron plot. We eventually found that a full sigmoidal unfolding transition and refolding kinetics could be measured upon addition of 15% (v/v) glycerol. Our measurements revealed that the free energy of unfolding in DPC micelles was 0 kcal/ mol (without glycerol). This shocking lack of WT stability made it impossible to directly measure the effects of destabilizing mutations that enhance misfolding- you can’t measure the unfolding of a protein that is already unfolded. We ultimately had to instead infer the energetic effects of such mutations from the thermodynamic coupling between cofactor binding and folding (doi: 10.1021/jacs.5b03743). Finally, after demonstrating the resulting ΔΔGs correlated with both cellular trafficking and disease phenotype, we still faced justified scrutiny about the relevance of these measurements due to the fact that they were carried out in micelles. For these reasons, we do not feel that additional biophysical measurements will add much to this work until more is understood about the nature of misfolding reactions in the membrane and how to effectively recapitulate it in vitro. We also note that PMP22 is secreted with 20% efficiency in mammalian cell lines, which is 20-fold more efficient than human GnRHR under similar conditions (doi: 10.1016/j.celrep.2021.110046). Thus, we suspect equilibrium unfolding measurements are likely out of reach using previously described measurements.

Our greatest evidence suggesting W107A destabilizes the protein has to do with the fact that it deletes a highly conserved structural contact and that this structural modification kills its secretion. The fact that this mutation clearly reduces the escape of GnRHR from ER quality control is a classic indicator of misfolding that represents the cell’s way of telling us that the mutation compromises the folding of the nascent protein in some way or another. Precisely how this mutation remodels the nascent conformational ensemble of nascent GnRHR and how this relates to the free energy difference between the native and non-native portions of its conformational ensemble under cellular conditions is a much more challenging question that lies beyond the scope of this investigation (and likely beyond the scope of what’s currently possible). Indeed, there is an entire field dedicated to understanding such. Nevertheless, the difference in the epistatic interactions formed by W107A and V276T is at the very least consistent with our speculative interpretation that these two mutations vary in their misfolding mechanism and/ or in the extent to which they destabilize the protein. For these reasons, we feel the main conclusions of this manuscript are well-justified.

Please clarify if the protein is glycosylated or not and, if it is, how would this requirement affect the conclusions of your analysis?

As we noted in the Response to the Reviewers, which also constitutes a published portion of the final manuscript, this protein is indeed glycosylated. We were well aware of this aspect of the protein since inception of this project and do not think this changes our interpretation at all. Most membrane proteins are glycosylated, and several groups have demonstrated in various ways that the secretion efficiency of glycoproteins is proportional to certain stability metrics for secreted soluble proteins and membrane proteins alike. Generally, mutations that enhance misfolding do not change the propensity of the nascent chain to undergo N-linked glycosylation, which occurs during translation before protein synthesis and/ or folding is complete. Misfolded proteins typically carry lower weight glycans, which reflects their failure to advance from the ER to the Golgi, where N-linked glycans are modified and O-linked glycans are added. From our perspective, glycosyl modifications just ensure that nascent proteins are engaged by calnexin and other lectin chaperones involved in QC. It does not decouple folding from secretion efficiency. In the case of PMP22 (described above), we found that removal of its glycosylation site allows the nascent protein to bypass the lectin chaperones in a manner that enhances its plasma membrane expression eight-fold (doi: 10.1016/j.jbc.2021.100719). Similar to WT, the expression of several misfolded PMP22 variants also significantly increases upon removal of the glycosylation site. Nevertheless, their expression is still significantly lower than the un-glycosylated WT protein, and the expression patterns of the mutants relative to WT was quite similar across this panel of un-glycosylated proteins. Thus, while glycosylation certainly impacts secretion, it does not change its dependence on folding efficiency within the ER. There are many layers of partially redundant QC within the ER, and it seems that folding imposes a key bottleneck to secretion regardless of which QC proteins are involved. For these reasons, we do not think glycosylation (or other PTMs) should factor into our interpretation of these results.

One caveat with the study is that there is a poor understanding of the factors that decide if the protein should be trafficked to the PM or not. Even secretory proteins not going through the calnexin/reticulum cycle (as they have no N-linked glycans), might still get stuck in the ER, despite the fact they are functional. Could this be a technical issue of heterologous expression overloading the Sec system?

While we agree that there is much to be learned about this topic, we disagree with the notion that our understanding of folding and secretion is insufficient to generally interpret the molecular basis of the observed trends. In collaboration with various other groups, the corresponding author of this paper has shown for several other proteins that the stability of the native topology and the native tertiary structure can constrain secretion efficiency (see dois: 10.1021/jacs.8b08243, 10.1021/jacs.5b03743, and 10.1016/j.jbc.2021.100423). Moreover, the Balch and Kelly groups demonstrated many years ago that relatively simple models for the coupling between folding and chaperone binding can recapitulate the observed effects of mutations on the secretion efficiency of various proteins (doi: 10.1016/j.cell.2007.10.025). Given a wide body of prevailing knowledge in this area, we believe it is entirely reasonable to assume that the conformational effects of these mutation have a dominant effect on plasma membrane expression.

Whether or not some of the proteins retained in the ER are folded and/ or functional is an interesting question, but is outside the scope of this work. Various lines of evidence concerning approaches to rescue misfolded membrane proteins suggest many of these variants are likely to retain residual function once they escape the ER, which may suggest there are pockets of foldable/ folded proteins within the ER. But it seems generally clear that the efficiency of folding in the ER bottlenecks secretion regardless of whether or not the ER contains some fraction of folded/ functional protein. We note that it is certainly possible, if not likely, that secretion efficiency is likely to be higher at lower expression levels (doi: 10.1074/jbc.AC120.014940). However, the mutational scanning platform used in this work was designed such that all variants are expressed from an identical promoter at the same location within the genome. Thus, for the purposes of these investigations, we believe it is entirely fair to draw “apples-to-apples” comparisons of their relative effects on plasma membrane expression.

Please see Francis Arnold's paper on this point and their mutagenesis library of the channelrhodopsin (https://www.pnas.org/doi/10.1073/pnas.1700269114), which further found that 20% of mutations improved WT trafficking. Some general comparisons to this paper might be informative.

We agree that it may be interesting to compare the results from this paper to those in our own. Indeed, we find that 20% of the point mutations characterized herein also enhance the expression of WT mGnRHR, as mentioned in the Results section. However, we think it might be a bit premature to suggest this is a more general trend in light of the fact that the channelrhodopsins engineered in those studies were not of eukaryotic origin and have likely resulted from distinct evolutionary constraints. We ultimately decided against adding more on this to our already lengthy discussion in order to maintain focus on the mechanisms of epistasis.

Chris Tate and others have shown that there is a high frequency of finding stabilising point mutations in GPCRs and this is the premise of the StAR technology used to thermostabilise GPCRs in the presence of different ligands, i.e. agonist vs inverse agonists. As far as I am aware, there is a poor correlation between expression levels and thermostability (measured by ligand binding to detergent-solubilised membranes). As such, it is possible that some of the mutants might be more stable than WT even though they have lower levels of PME.

We believe the disconnect between thermostability and expression precisely speaks to our main point about the suitability of current membrane protein folding assays for the questions we address herein. The degradative activity of ER quality control has not necessarily selected for proteins that are resistant to thermal degradation and/ or are suitable for macromolecular crystallography. For this reason, it is often not so difficult to engineer proteins with enhanced thermal stability. We do not believe this disconnect signals that quality control is insensitive to protein folding and stability, but rather that it is more likely to recognize conformational defects that are distinct from those involved in thermal degradation and/ or aggregation. Indeed, recent work from the Fluman group, which builds on a wider body of previous observations, has shown that the exposure of polar groups within the membrane is a key factor that recruits degradation machinery (doi: 0.1101/2023.12.12.571171). It is hard to imagine that these sorts of conformational defects are the same as those involved in thermal aggregation.

Reviewer #2 (Recommendations For The Authors):

(1) I believe that by focusing more on the epistasis with V276T, and less on W107A, the paper could be strengthened significantly.

We appreciate this sentiment. But we believe the comparison of these two mutants really drive home the point that destabilizing mutations are not equivalent with respect to the epistatic interactions they form.

(2) In the abstract - please define the term epistasis in a simple way, to make it accessible to a general audience. For example - negative epistasis means that... this should be explicitly explained.

We thank the reviewer for this suggestion. To meet eLife formatting, we had to cut down the abstract significantly. We simplified this as best we could in the following statement:

“Though protein stability is known to shape evolution, it is unclear how cotranslational folding constraints modulate the synergistic, epistatic interactions between mutations.”

We also define positive and negative epistasis in the results section as follows:

“Positive Ɛ values denote double mutants that have greater PME than would be expected based on the effects of single mutants. Negative Ɛ values denote double mutants that have lower PME than would be expected based on the effects of single mutants. Pairs of mutations with Ɛ values near zero have additive effects on PME.”

(3) The title is quite complex and might deter readers from outside the protein evolution field. Consider simplifying it.

We thank the reviewer for this suggestion. We have simplified the title to the following:

“Divergent Folding-Mediated Epistasis Among Unstable Membrane Protein Variants”

(4) The paper could benefit from a simple figure explaining the different stages of membrane protein folding (stages 1+2) to make it more accessible to readers from outside the membrane protein field.

This is a great suggestion. We incorporated a new schematic in the revised manuscript that outlines the nature of these processes (see Fig. 1A in the revised manuscript).

(5) For the FACS-Seq experiment - it was not clear to me if and when all cells are pulled together. For example - are the 3 libraries mixed together already at the point of transfection, or are the transfected cells pulled together at any point before sorting? This could have some implications on batch effects and should, therefore, be explicitly mentioned in the main text.

We thank the reviewer for this suggestion. We modified the description of the DNA library assembly to emphasize that the mutations were generated in the context of three mixed plasmid pools, which were then transfected into the cells and sorted independently:

“We then generated a mixed array of mutagenic oligonucleotides that collectively encode this series of substitutions (Table S3) and used nicking mutagenesis to introduce these mutations into the V276T, W107A, and WT mGnRHR cDNAs (Medina-Cucurella et al., 2019), which produced three mixed plasmid pools.”

(6) The following description in the text is quite confusing. It would be better to simplify it considerably or remove it: "scores (Ɛ) were then determined by taking the log of the double mutant fitness value divided by the difference between the single mutant fitness values (see Methods)."

We thank the reviewer for this valuable feedback and have simplified the text as follows:

“To compare epistatic trends in these libraries, we calculated epistasis scores (Ɛ) for the interactions that these 251 mutations form with V276T and W107A by comparing their relative effects on PME of the WT, V276T, and W107A variants using a previously described epistasis model (product model, see Methods) (Olson et al. 2014).”

eLife assessment

This important study describes exhaustive deep mutational scanning (DMS) of the gonadotropin-releasing hormone wild-type receptor and for two single point mutations that impact its folding and structure, monitoring how plasma membrane expression levels are influenced by the introduced mutations. With solid evidence, the authors have pioneered an exploration of the interaction between mutations (epistasis) in a membrane protein, with a potential for explaining membrane protein evolution and genetic diseases.

Reviewer #1 (Public Review):

Summary:

The paper carries out an impressive and exhaustive non-sense mutagenesis using deep mutational scanning (DMS) of the gonadotropin-releasing hormone receptor for the WT protein and two single point mutations that I) influences TM insertion (V267T) and ii) influences protein stability (W107A) and then measures the effect of these mutants on correct plasma membrane expression (PME).

Overall, most mutations decreased mGnRHR PME levels in all three backgrounds, indicating poor mutational tolerance under these conditions. The W107A variant wasn't really recoverable with low levels of plasma membrane localisation. For the V267T variant, most additional mutations were more deleterious than WT based on correct trafficking, indicating a synergistic effect. As one might expect, there was a higher degree of positive correlation between V267T/W107A mutants and other mutants located in TM regions, confirming that improper trafficking was a likely consequence of membrane protein co-translational folding. Nevertheless, context is important, as positive synergistic mutants in the V27T could be negative in the W107A background and vice versa. Taken together, this important study highlights the complexity of membrane protein folding in dissecting the mechanism-dependent impact of disease-causing mutations related to improper trafficking.

Strengths:

This is a novel and exhaustive approach to dissect how receptor mutations under different mutational backgrounds related to co-translational folding, could influence membrane protein trafficking.

Weaknesses:

The premise for the study requires an in-depth understanding of how the single point mutations analysed effect membrane protein folding in context of DMS, but the single point mutants used could do with further validation. The V267T mutant only reduced MP insertion by 10% and the effect of W107A on protein stability was not assessed. Furthermore, plasma membrane expression has been used as a proxy for incorrect membrane protein folding, but this not necessarily be the case, as even correctly folded membrane proteins may not be trafficked correctly, at least, under heterologous expression conditions. In addition, mutations can effect trafficking and potential post-translational modifications, like glycosylation.

Reviewer #2 (Public Review):

Summary:

In this paper, Chamness and colleagues make a pioneering effort to map epistatic interactions among mutations in a membrane protein. They introduce thousands of mutations to the mouse GnRH Receptor (GnRHR), either under wild-type background or two mutant backgrounds, representing mutations that destabilize GnRHR by distinct mechanisms. The first mutant background is W107A, destabilizing the tertiary fold, and the second, V276T, perturbing the efficiency of cotranslational insertion of TM6 to the membrane, which is essential for proper folding. They then measure surface expression of these three mutant libraries, using it as a proxy for protein stability, since misfolded proteins do not typically make it to the plasma membrane. The resulting dataset is then used to shed light on how diverse mutations interact epistatically with the two genetic background mutations. Their main conclusion is that epistatic interactions vary depending on the degree of destabilization and the mechanism through which they perturb the protein. The mutation V276T forms primarily negative (aggravating) epistatic interactions with many mutations, as is common to destabilizing mutations in soluble proteins. Surprisingly, W107A forms many positive (alleviating) epistatic interactions with other mutations. They further show that the locations of secondary mutations correlate with the types of epistatic interactions they form with the above two mutants.

Strengths:

Such a high throughput study for epistasis in membrane proteins is pioneering, and the results are indeed illuminating. Examples of interesting findings are that: (1) No single mutation can dramatically rescue the destabilization introduced by W107A. (2) Epistasis with a secondary mutation is strongly influenced by the degree of destabilization introduced by the primary mutation. (3) Misfolding caused by mis-insertion tends to be aggravated by further mutations. The discussion of how protein folding energetics affects epistasis (Fig. 7) makes a lot of sense and lays out an interesting biophysical framework for the findings.

Weaknesses:

The major weakness comes from the potential limitations in the measurements of surface expression of severely misfolded mutants. It seems that only about 5% of the W107A makes it to the plasma membrane compared to wild-type. This point is discussed quite fairly in the paper. (Figures 2 and 3). This might be a low starting point from which to accurately measure the effects of secondary mutations. I am concerned about the extent to which surface expression can report on protein stability, especially when it comes to double mutants where each mutation alone severely decreases surface expression. It is possible that in these cases, both the single and double mutants are completely misfolded, beyond repair. The surface-expressed proteins in such mutants may not be stable, folded or active at all, and the authors do not provide any indication that the combined effects of the mutations are derived from effects on folding stability or misfolding. Therefore, the reason for the epistatic effects of these mutations is hard to interpret, leaving a notable gap in our understanding. However, I find that this point is discussed much more fairly in the current manuscript.

With that said, I believe that the results regarding the epistasis of V276T with other mutations are strong and very interesting on their own.

Another concern relates to the measurements of the epistatic effects of mutations in the background of the V107A mutation. I am concerned about their measurement accuracy. Firstly, the authors note that the surface immunostaining measurements of these mutants are on average only 2-fold above background, which is quite a low signal-to-noise regimen. Secondly, I believe that the authors still haven't demonstrated the reproducibility of their surface expression measurements. To showcase the reproducibility, the authors show the correlation of two biological replicates in Figure S3. However, these are shown only for the 251 mutations that passed a reproducibility filter, after the authors "discarded variant scores for which the difference in percentile rank across the two replicates was greater than 25%. " . this means that all mutations that showed irreproducible results were filtered out before the analysis in Figure S3. It is, therefore, no surprise that the remaining mutations are highly reproducible, and such an analysis cannot serve as an indication of the reproducibility. It remains possible that a large fraction of the surface immunostaining scores of the V107A variants are dominated by noise and that their correlation in these two replicates might be random and may not necessarily be reproduced in a third replicate, for example.

Author response:

Reviewer #1 (Public Review):

Summary:

For many years, there has been extensive electrophysiological research investigating the relationship between local field potential patterns and individual cell spike patterns in the hippocampus. In this study, using state-of-the-art imaging techniques, they examined spike synchrony of hippocampal cells during locomotion and immobility states. In contrast to conventional understanding of the hippocampus, the authors demonstrated that hippocampal place cells exhibit prominent synchronous spikes locked to theta oscillations.

Strengths:

The voltage imaging used in this study is a highly novel method that allows recording not only suprathreshold-level spikes but also subthreshold-level activity. With its high frame rate, it offers time resolution comparable to electrophysiological recordings. Moreover, it enables the visualization of actual cell locations, allowing for the examination of spatial properties (e.g., Figure 4G).

We thank the reviewer for pointing out the technical novelty of this work.

Weaknesses:

There is a notable deviation from several observations obtained through conventional electrophysiological recordings. Particularly, as mentioned below in detail, the considerable differences in baseline firing rates and no observations of ripple-triggered firing patterns raise some concerns about potential artifacts from imaging and analysis, such as cell toxicity, abnormal excitability, and false detection of spikes. While these findings are intriguing if the validity of these methods is properly proven, accepting the current results as new insights is challenging.

We appreciate the reviewer’s insightful comments regarding the intriguing aspect of our findings. Indeed, the emergence of a novel form of CA1 population synchrony presents exciting implications for hippocampal memory research and beyond.

While we acknowledge the deviations from conventional electrophysiological recordings, we respectfully contend that these differences do not necessarily imply methodological flaws. All experiments and analyses were conducted with meticulous adherence to established standards in the field.

Regarding the observed variations in averaging firing rates, it is important to note the well-documented heterogeneity in CA1 pyramidal neuron firing rates, spanning from 0.01 to 10 Hz, with a skewed distribution toward lower frequencies (Mizuseki et al., 2013). Our exclusion criteria for neurons with low estimated firing rates may have inadvertently biased the selection towards more active neurons. Moreover, prior research has indicated that averaging firing rates tend to increase during exposure to novel environments (Karlsson et al., 2008), and among deep-layer CA1 pyramidal neurons (Mizuseki et al., 2011). Given our recording setup in a highly novel environment and the predominance of deep CA1 pyramidal neurons in our sample, the observed higher averaging firing rates could be influenced by these factors. Considering these points, our mean firing rates (3.2 Hz) are reasonable estimations compared to previously reported values obtained from electrophysiological recordings (2.1 Hz in McHugh et al., 1996 and 2.4-2.6 Hz in Buzsaki et al., 2003).

Regarding concerns about potential cell toxicity, previous studies have shown that Voltron expression and illumination do not significantly alter membrane resistance, membrane capacitance, resting membrane potentials, spike amplitudes, and spike width (see Abdelfattah 2019, Science, Supplementary Figure 11 and 12). In our recordings, imaged neurons exhibit preserved membrane and dendritic morphology during and after experiments (Author response image 1), supporting the absence of significant toxicity.

Author response image 1.

Voltron-expressing neurons exhibit preserved membrane and dendritic morphology. (A) Images of two-photon z-stack maximum intensity projection showing Voltron-expressing neurons taken after voltage image experiments in vivo. (B) Post-hoc histological images of neurons being voltage-imaged.

Regarding spike detection, we use validated algorithms (Abdelfattah et al., 2019 and 2023) to ensure robust and reliable detection of spikes. Spiking activity was first separated from slower subthreshold potentials using high-pass filtering. This way, a slow fluorescence increase will not be detected as a spike, even if its amplitude is large. We benchmarked the detection algorithm in computer simulation. The sensitivity and specificity of the algorithm exceed 98% at the level of signal-to-noise ratio of our recordings. While we acknowledge that a small number of spikes, particularly those occurring later in a burst, might be missed due to their smaller amplitudes (as illustrated in Figure 1 and 2 of the manuscript), we anticipate that any missed spikes would lead to a decrease rather than an increase in synchrony between neurons. Overall, we are confident that spike detection is performed in a rigorous and robust manner.

To further strengthen these points, we will include the following in the revision:

(1) Histological images of recorded neurons during and after experiments.

(2) Further details regarding the validation of spike detection algorithms.

(3) Analysis of publicly available electrophysiological datasets.

(4) Discussion regarding the reasons behind the novelty of some of our findings compared to previous observations.

In conclusion, we assert that our experimental and analysis approach upholds rigorous standards. We remain committed to reconciling our findings with previous observations and welcome further scrutiny and engagement from the scientific community to explore the intriguing implications of our findings.

Reviewer #2 (Public Review):

Summary:

This study employed voltage imaging in the CA1 region of the mouse hippocampus during the exploration of a novel environment. The authors report synchronous activity, involving almost half of the imaged neurons, occurred during periods of immobility. These events did not correlate with SWRs, but instead, occurred during theta oscillations and were phased-locked to the trough of theta. Moreover, pairs of neurons with high synchronization tended to display non-overlapping place fields, leading the authors to suggest these events may play a role in binding a distributed representation of the context.

We thank the reviewer for a thorough and thoughtful review of our paper.

Strengths:

Technically this is an impressive study, using an emerging approach that allows single-cell resolution voltage imaging in animals, that while head-fixed, can move through a real environment. The paper is written clearly and suggests novel observations about population-level activity in CA1.

We thank the reviewer for pointing out the technical strength and the novelty of our observations.

Weaknesses:

The evidence provided is weak, with the authors making surprising population-level claims based on a very sparse data set (5 data sets, each with less than 20 neurons simultaneously recorded) acquired with exciting, but less tested technology. Further, while the authors link these observations to the novelty of the context, both in the title and text, they do not include data from subsequent visits to support this. Detailed comments are below:

We understand the reviewer’s concerns regarding the size of the dataset. Despite this limitation, it is important to note that synchronous ensembles beyond what could be expected from chance (jittering) were detected in all examined data. In the revision, we plan to add more data, including data from subsequent visits, to further strengthen our findings.

(1) My first question for the authors, which is not addressed in the discussion, is why these events have not been observed in the countless extracellular recording experiments conducted in rodent CA1 during the exploration of novel environments. Those data sets often have 10x the neurons simultaneously recording compared to these present data, thus the highly synchronous firing should be very hard to miss. Ideally, the authors could confirm their claims via the analysis of publicly available electrophysiology data sets. Further, the claim of high extra-SWR synchrony is complicated by the observation that their recorded neurons fail to spike during the limited number of SWRs recorded during behavior- again, not agreeing with much of the previous electrophysiological recordings.

We understand the reviewer’s concern. We will examine publicly available electrophysiology datasets to gain further insights into any similarities and differences to our findings. Based on these results, we will discuss why these events have not been previously observed/reported.

(2) The authors posit that these events are linked to the novelty of the context, both in the text, as well as in the title and abstract. However, they do not include any imaging data from subsequent days to demonstrate the failure to see this synchrony in a familiar environment. If these data are available it would strengthen the proposed link to novelty if they were included.

We thank the reviewer’s constructive suggestion. We will acquire more datasets from subsequent visits to gain further insights into these synchronous events.

3) In the discussion the authors begin by speculating the theta present during these synchronous events may be slower type II or attentional theta. This can be supported by demonstrating a frequency shift in the theta recording during these events/immobility versus the theta recording during movement.

We thank the reviewer’s constructive suggestion. We did demonstrate a frequency shift to a lower frequency in the synchrony-associated theta during immobility than during locomotion (see Fig. 4B, the red vs. blue curves). We will enlarge this panel and specifically refer to it in the corresponding discussion paragraph.

(4) The authors mention in the discussion that they image deep-layer PCs in CA1, however, this is not mentioned in the text or methods. They should include data, such as imaging of a slice of a brain post-recording with immunohistochemistry for a layer-specific gene to support this.

We thank the reviewer’s constructive suggestion. We do have images of brain slices post-recordings (Author response image 2). Imaged neurons are clearly located in the deep CA1 pyramidal layer. We will add these images and quantification in the revised manuscript.

Author response image 2.

Imaged neurons are located in the deep pyramidal layer of the dorsal hippocampal CA1 region.

Reviewer #3 (Public Review):

Summary:

In the present manuscript, the authors use a few minutes of voltage imaging of CA1 pyramidal cells in head-fixed mice running on a track while local field potentials (LFPs) are recorded. The authors suggest that synchronous ensembles of neurons are differentially associated with different types of LFP patterns, theta and ripples. The experiments are flawed in that the LFP is not "local" but rather collected in the other side of the brain, and the investigation is flawed due to multiple problems with the point process analyses. The synchrony terminology refers to dozens of milliseconds as opposed to the millisecond timescale referred to in prior work, and the interpretations do not take into account theta phase locking as a simple alternative explanation.

We genuinely appreciate the reviewer’s feedback and acknowledge the concerns raised. However, we believe these concerns can be effectively addressed without undermining the validity of our conclusions. With this in mind, we respectfully disagree with the assessment that our experiments and investigation are flawed. Please allow us to address these concerns and offer additional context to support the validity of our study.

Weaknesses:

The two main messages of the manuscript indicated in the title are not supported by the data. The title gives two messages that relate to CA1 pyramidal neurons in behaving head-fixed mice: (1) synchronous ensembles are associated with theta (2) synchronous ensembles are not associated with ripples.

There are two main methodological problems with the work:

(1) Experimentally, the theta and ripple signals were recorded using electrophysiology from the opposite hemisphere to the one in which the spiking was monitored. However, both signals exhibit profound differences as a function of location: theta phase changes with the precise location along the proximo-distal and dorso-ventral axes, and importantly, even reverses with depth. And ripples are often a local phenomenon - independent ripples occur within a fraction of a millimeter within the same hemisphere, let alone different hemispheres. Ripples are very sensitive to the precise depth - 100 micrometers up or down, and only a positive deflection/sharp wave is evident.

We appreciate the reviewer’s consideration regarding the collection of LFP from the contralateral hemisphere. While we acknowledge the limitation of this design, we believe that our findings still offer valuable insights into the dynamics of synchronous ensembles. Despite potential variations in theta phases with recording locations and depth, we find that the occurrence and amplitudes of theta oscillations are generally coordinated across hemispheres (Buzsaki et al., Neurosci., 2003). Therefore, the presence of prominent contralateral LFP theta around the times of synchronous ensembles in our study (see Figure 4A of the manuscript) strongly supports our conclusion regarding their association with theta oscillations, despite the collection of LFP from the opposite hemisphere.

In addition, in our manuscript, we specifically mentioned that the “preferred phases” varied from session to session, likely due to the variability of recording locations (see Line 254-256). Therefore, we think that the reviewer’s concern regarding theta phase variability has already been addressed in the present manuscript.

Regarding ripple oscillations, while we recognize that they can sometimes occur locally, the majority of ripples occur synchronously in both hemispheres (up to 70%, see Szabo et al., Neuron, 2022; Buzsaki et al., Neurosci., 2003). Therefore, using contralateral LFP to infer ripple occurrence on the ipsilateral side has been a common practice in the field, employed by many studies published in respectable journals (Szabo et al., Neuron, 2022; Terada et al., Nature, 2021; Dudok et al., Neuron, 2021; Geiller et al., Neuron, 2020). Furthermore, our observation that 446 synchronous ensembles during immobility do not co-occur with contralateral ripples, and the remaining 313 ensembles during locomotion are not associated with ripples, as ripples rarely occur during locomotion. Therefore, our conclusion that synchronous ensembles are not associated with ripple oscillations is supported by data.

(2) The analysis of the point process data (spike trains) is entirely flawed. There are many technical issues: complex spikes ("bursts") are not accounted for; differences in spike counts between the various conditions ("locomotion" and "immobility") are not accounted for; the pooling of multiple CCGs assumes independence, whereas even conditional independence cannot be assumed; etc.

We acknowledge the reviewer’s concern regarding spike train analysis. Indeed, complex bursts or different behavioral conditions can lead to differences in spike counts that could potentially affect the detection of synchronous ensembles. However, our jittering procedure (see Line 121-132) is designed to control for the variation of spike counts. Importantly, while the jittered spike trains also contain the same spike count variations, we found 7.8-fold more synchronous events in our data compared to jitter controls (see Figure 1G of the manuscript), indicating that these factors cannot account for the observed synchrony.

To explicitly demonstrate that complex bursts cannot account for the observed synchrony, we have performed additional analysis to remove all latter spikes in bursts and only count the single and the first spikes of bursts. Importantly, we found that this procedure did not change the rate and size of synchronous ensembles, nor did it significantly alter the grand-average CCG (see Author response image 3). The results of this analysis explicitly rule out a significant effect of complex spikes on the analysis of synchronous ensembles.

Author response image 3.

Population synchrony remains after the removal of spikes in bursts. (A) The grand-average cross correlogram (CCG) was calculated using spike trains without latter spikes in bursts. The gray line represents the mean grand average CCG between reference cells and randomly selected cells from different sessions. (B) Pairwise comparison of the event rates of population synchrony between spike trains containing all spikes and spike trains without latter spikes in bursts. Bar heights indicate group means (n=10 segments, p=0.036, Wilcoxon signed-rank test). (C) Histogram of the ensemble sizes as percentages of cells participating in the synchronous ensembles.

Beyond those methodological issues, there are two main interpretational problems: (1) the "synchronous ensembles" may be completely consistent with phase locking to the intracellular theta (as even shown by the authors themselves in some of the supplementary figures).

We agree with the reviewer that the synchronous ensembles are indeed consistent with theta phase locking. However, it is important to note that theta phase locking alone does not necessarily imply population synchrony. In fact, theta phase locking has been shown to “reduce” population synchrony in a previous study (Mizuseki et al., 2014, Phil. Trans. R. Soc. B.). Thus, the presence of theta phase locking cannot be taken as a simple alternative explanation of the synchronous ensembles.

To directly assess the contribution of theta phase locking to synchronous ensembles, we have performed a new analysis to randomize the specific theta cycles in which neurons spike, while keeping the spike phases constant. This manipulation disrupts spike co-occurrence while preserving theta phase locking, allowing us to test whether theta phase locking alone can explain the population synchrony, or whether spike co-occurrence in specific cycles is required. The grand-average CCG shows a much smaller peak compared to the original peak (Author response image 4A). Moreover, synchronous event rates show a 4.5-fold decrease in the randomized data compared to the original event rates (Author response image 4B). Thus, the new analysis reveals theta phase locking alone cannot account for the population synchrony.

Author response image 4.

Drastic reduction of population synchrony by randomizing spikes to other theta cycles while preserving the phases. (A) The grand-average cross correlogram (CCG) was calculated using original spike trains (black) and randomized spike trains where theta phases of the spikes are kept the same but spike timings were randomly moved to other theta cycles (red). (B) Pairwise comparison of the event rates of population synchrony between the original spike trains and randomized spike trains (n=10 segments, p=0.002, Wilcoxon signed-rank test). Bar heights indicate group means. ** p<0.01

(2) The definition of "synchrony" in the present work is very loose and refers to timescales of 20-30 ms. In previous literature that relates to synchrony of point processes, the timescales discussed are 1-2 ms, and longer timescales are referred to as the "baseline" which is actually removed (using smoothing, jittering, etc.).

Regarding the timescale of synchronous ensembles, we acknowledge that it varies considerably across studies and cell types. However, it is important to note that a timescale of dozens, or even hundreds of milliseconds is common for synchrony terminology in CA1 pyramidal neurons (see Csicsvari et al., Neuron, 2000; Harris et al., Science, 2003; Malvache et al., Science, 2016; Yagi et al., Cell Reports, 2023). In fact, a timescale of 20-30 ms is considered particularly important for information transmission and storage in CA1, as it matches the membrane time constant of pyramidal neurons, the period of hippocampal gamma oscillations, and the time window for synaptic plasticity. Therefore, we believe that this timescale is relevant and in line with established practices in the field.

eLife assessment

The authors perform voltage imaging of CA1 pyramidal cells in head-fixed mice running on a track while local field potentials (LFPs) are recorded. They suggest that synchronous ensembles of neurons are differentially associated with different types of LFP patterns, namely theta and ripples. However, evidence for the potentially useful findings is currently incomplete due to major weaknesses in the experimental and analytical approach.

Reviewer #1 (Public Review):

Summary:

For many years, there has been extensive electrophysiological research investigating the relationship between local field potential patterns and individual cell spike patterns in the hippocampus. In this study, using state-of-the-art imaging techniques, they examined spike synchrony of hippocampal cells during locomotion and immobility states. In contrast to conventional understanding of the hippocampus, the authors demonstrated that hippocampal place cells exhibit prominent synchronous spikes locked to theta oscillations.

Strengths:

The voltage imaging used in this study is a highly novel method that allows recording not only suprathreshold-level spikes but also subthreshold-level activity. With its high frame rate, it offers time resolution comparable to electrophysiological recordings. Moreover, it enables the visualization of actual cell locations, allowing for the examination of spatial properties (e.g., Figure 4G).

Weaknesses:

There is a notable deviation from several observations obtained through conventional electrophysiological recordings. Particularly, as mentioned below in detail, the considerable differences in baseline firing rates and no observations of ripple-triggered firing patterns raise some concerns about potential artifacts from imaging and analsyis, such as cell toxicity, abnormal excitability, and false detection of spikes. While these findings are intriguing if the validity of these methods is properly proven, accepting the current results as new insights is challenging.

Reviewer #2 (Public Review):

Summary:

This study employed voltage imaging in the CA1 region of the mouse hippocampus during the exploration of a novel environment. The authors report synchronous activity, involving almost half of the imaged neurons, occurred during periods of immobility. These events did not correlate with SWRs, but instead, occurred during theta oscillations and were phased-locked to the trough of theta. Moreover, pairs of neurons with high synchronization tended to display non-overlapping place fields, leading the authors to suggest these events may play a role in binding a distributed representation of the context.

Strengths:

Technically this is an impressive study, using an emerging approach that allows single-cell resolution voltage imaging in animals, that while head-fixed, can move through a real environment. The paper is written clearly and suggests novel observations about population-level activity in CA1.

Weaknesses:

The evidence provided is weak, with the authors making surprising population-level claims based on a very sparse data set (5 data sets, each with less than 20 neurons simultaneously recorded) acquired with exciting, but less tested technology. Further, while the authors link these observations to the novelty of the context, both in the title and text, they do not include data from subsequent visits to support this. Detailed comments are below:

(1) My first question for the authors, which is not addressed in the discussion, is why these events have not been observed in the countless extracellular recording experiments conducted in rodent CA1 during the exploration of novel environments. Those data sets often have 10x the neurons simultaneously recording compared to these present data, thus the highly synchronous firing should be very hard to miss. Ideally, the authors could confirm their claims via the analysis of publicly available electrophysiology data sets. Further, the claim of high extra-SWR synchrony is complicated by the observation that their recorded neurons fail to spike during the limited number of SWRs recorded during behavior- again, not agreeing with much of the previous electrophysiological recordings.

(2) The authors posit that these events are linked to the novelty of the context, both in the text, as well as in the title and abstract. However, they do not include any imaging data from subsequent days to demonstrate the failure to see this synchrony in a familiar environment. If these data are available it would strengthen the proposed link to novelty if they were included.

(3) In the discussion the authors begin by speculating the theta present during these synchronous events may be slower type II or attentional theta. This can be supported by demonstrating a frequency shift in the theta recording during these events/immobility versus the theta recording during movement.

(4) The authors mention in the discussion that they image deep-layer PCs in CA1, however, this is not mentioned in the text or methods. They should include data, such as imaging of a slice of a brain post-recording with immunohistochemistry for a layer-specific gene to support this.

Reviewer #3 (Public Review):

Summary:

In the present manuscript, the authors use a few minutes of voltage imaging of CA1 pyramidal cells in head-fixed mice running on a track while local field potentials (LFPs) are recorded. The authors suggest that synchronous ensembles of neurons are differentially associated with different types of LFP patterns, theta and ripples. The experiments are flawed in that the LFP is not "local" but rather collected in the other side of the brain, and the investigation is flawed due to multiple problems with the point process analyses. The synchrony terminology refers to dozens of milliseconds as opposed to the millisecond timescale referred to in prior work, and the interpretations do not take into account theta phase locking as a simple alternative explanation.

Weaknesses:

The two main messages of the manuscript indicated in the title are not supported by the data. The title gives two messages that relate to CA1 pyramidal neurons in behaving head-fixed mice: (1) synchronous ensembles are associated with theta (2) synchronous ensembles are not associated with ripples.

There are two main methodological problems with the work: (1) experimentally, the theta and ripple signals were recorded using electrophysiology from the opposite hemisphere to the one in which the spiking was monitored. However, both signals exhibit profound differences as a function of location: theta phase changes with the precise location along the proximo-distal and dorso-ventral axes, and importantly, even reverses with depth. And ripples are often a local phenomenon - independent ripples occur within a fraction of a millimeter within the same hemisphere, let alone different hemispheres. Ripples are very sensitive to the precise depth - 100 micrometers up or down, and only a positive deflection/sharp wave is evident. (2) The analysis of the point process data (spike trains) is entirely flawed. There are many technical issues: complex spikes ("bursts") are not accounted for; differences in spike counts between the various conditions ("locomotion" and "immobility") are not accounted for; the pooling of multiple CCGs assumes independence, whereas even conditional independence cannot be assumed; etc.

Beyond those methodological issues, there are two main interpretational problems: (1) the "synchronous ensembles" may be completely consistent with phase locking to the intracellular theta (as even shown by the authors themselves in some of the supplementary figures). (2) The definition of "synchrony" in the present work is very loose and refers to timescales of 20-30 ms. In previous literature that relates to synchrony of point processes, the timescales discussed are 1-2 ms, and longer timescales are referred to as the "baseline" which is actually removed (using smoothing, jittering, etc.).

Author response:

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

eLife assessment

Connelly and colleagues provide convincing genetic evidence that importation from mainland Tanzania is a major source of Plasmodium falciparum lineages currently circulating in Zanzibar. This study also reveals ongoing local malaria transmission and occasional near-clonal outbreaks in Zanzibar. Overall, this research highlights the role of human movements in maintaining residual malaria transmission in an area targeted for intensive control interventions over the past decades and provides valuable information for epidemiologists and public health professionals.

Reviewer #1 (Public Review):

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

Strengths:

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

Weaknesses:

Some points need to be clarified:

(1) SNPs in linkage disequilibrium (LD) can introduce bias in PCA and IBD analysis. Were SNPs in LD filtered out prior to these analyses?

Thank you for this point. We did not filter SNPs in LD prior to this analysis. In the PCA analysis in Figure 1, we did restrict to a single isolate among those that were clonal (high IBD values) to prevent bias in the PCA. In general, disequilibrium is minimal only over small distances <5-10kb without selective forces at play. This is much less than the average spacing of the markers in the panel. If there is minimal LD, the conclusions drawn on relative levels and connections at high IBD are unlikely to be confounded by any effects of disequilibrium.

( 2) Many IBD algorithms do not handle polyclonal infections well, despite an increasing number of algorithms that are able to handle polyclonal infections and multiallelic SNPs. How polyclonal samples were handled for IBD analysis?

Thank you for this point. We added lines 157-161 to clarify. This section now reads:

“To investigate genetic relatedness of parasites across regions, identity by descent (IBD) estimates were assessed using the within sample major alleles (coercing samples to monoclonal by calling the dominant allele at each locus) and estimated utilizing a maximum likelihood approach using the inbreeding_mle function from the MIPanalyzer package (Verity et al., 2020). This approach has previously been validated as a conservative estimate of IBD (Verity et al., 2020).”

Please see the supplement in (Verity et al., 2020) for an extensive simulation study that validates this approach.

Reviewer #1 (Recommendations For The Authors):

(3) I think Supplementary Figures 8 and 9 are more visually informative than Figure 2.

Thank you for your response. We performed the analysis in Figure 2 to show how IBD varies between different regions and is higher within a region than between.

Reviewer #2 (Public Review):

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

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

Thank you for your insights. We appreciated the level of detail of your review and it strengthened our work. We have input additional sentences on lines 292-295, which now reads:

“A recent study investigating population structure in Zanzibar also found local population microstructure in Pemba (Holzschuh et al., 2023). Further, both studies found near-clonal parasites within the same district, Micheweni, and found population microstructure over Zanzibar.”

Strengths:

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

Weaknesses:

A number of points need clarification:

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

Thank you for this point. We have included 282 instead of 391 in the abstract. We added a statement in the results at lines 203-205 to clarify this point, which now reads:

“PCA analysis of 232 coastal Tanzanian and Zanzibari isolates, after pruning 51 samples with an IBD of greater than 0.9 to one representative sample, demonstrates little population differentiation (Figure 1A).”

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

Thank you for this advice. Rather than switch to another table altogether, we appended two columns to the original table to better portray the information (see Table 1).

Methods

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

Cluster 3 is a mix of rural/urban while the clusters 2, 4 and 5 are mostly rural. This analysis was performed to see how IBD changes in relation to local context within different regions in Zanzibar, showing that there is higher IBD within locale than between locale.

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

The K-means clustering experiment was used to cluster a continuous space of geographic coordinates in order to compare genetic relatedness in different regions. We selected this inflection point based on the elbow plot and based the number to obtain sufficient subsections of Zanzibar to compare genetic relatedness. This point is added to the methods at lines 174-178, which now reads:

“The K-means clustering experiment was used to cluster a continuous space of geographic coordinates in order to compare genetic relatedness in different regions. We selected K = 4 as the inflection point based on the elbow plot (Supplemental Figure 5) and based the number to obtain sufficient subsections of Zanzibar to compare genetic relatedness.”

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

Population frequency is calculated based on the average within sample allele frequency of each individual in the population, which is an unbiased estimator. Within sample allele frequency can range from 0 to 1. Thus, if only one sample has an allele and it is at 0.1 within sample frequency, the population allele frequency would be 0.1/100 = 0.001. This allele is removed even though this would have resulted in a prevalence of 0.01. This filtering is prior to any final summary frequency or prevalence calculations (see MIP variant Calling and Filtering section in the methods). This protects against errors occurring only at low frequency.

Discussion:

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

Thank you for this point. We have added additional context and clarification on lines 275-280, which now reads:

“Thus, directly targeting local malaria transmission, including the asymptomatic reservoir which contributes to sustained transmission (Barry et al., 2021; Sumner et al., 2021), may be an important focus for ultimately achieving malaria control in the archipelago (Björkman & Morris, 2020). Currently, a reactive case detection program within index case households is being implemented, but local transmission continues and further investigation into how best to control this is warranted (Mkali et al. 2023).”

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

Thank you for this point. We have edited the text at lines 287-288 to indicate that highly related parasites mainly occur at the range of 20-30km, which now reads:

“In Zanzibar, highly related parasites mainly occur at the range of 20-30km.”

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

We are referring to the list of Pfk13 polymorphisms stated in the Methods from lines 146-148. We added clarifying text on lines 326-329:

“Although polymorphisms associated with artemisinin resistance did not appear in this population, continued surveillance is warranted given emergence of these mutations in East Africa and reports of rare resistance mutations on the coast consistent with spread of emerging Pfk13 mutations (Moser et al., 2021). “

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

We added a clarification on this point on lines 335-345, which now reads:

“A recent study identified “hotspot” shehias, defined as areas with comparatively higher malaria transmission than other shehias, near the port of Zanzibar town and in northern Pemba (Bisanzio et al., 2023). These regions overlapped with shehias in this study with high levels of IBD, especially in northern Pemba (Figure 4). These areas of substructure represent parasites that differentiated in relative isolation and are thus important locales to target intervention to interrupt local transmission (Bousema et al., 2012). While a field cluster-randomized control trial in Kenya targeting these hotspots did not confer much reduction of malaria outside of the hotspot (Bousema et al. 2016), if areas are isolated pockets, which genetic differentiation can help determine, targeted interventions in these areas are likely needed, potentially through both mass drug administration and vector control (Morris et al., 2018; Okell et al., 2011). Such strategies and measures preventing imported malaria could accelerate progress towards zero malaria in Zanzibar.”

Figures and Tables:

(10) Table 2: Why not enter '0' if a mutation was not detected? 'ND' is somewhat confusing, as the prevalence is indeed 0%.

Thank you for this point. We have put zero and also given CI to provide better detail.

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

Supplementary Figure 2B suffers from the same issue.

Thank you for your comment. A revised Figure 1 and Supplemental Figure 2 are included, where there are separate plots for PC1 vs. PC2 and PC1 vs. PC3.

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

Thank you for this point. The districts with at least 5 samples present are plotted in the map in Figure 1B. In Figure 2, a totally separate analysis was performed, where all shehias were clustered into separate groups with k-means and the IBD values were compared between these clusters. These maps are not supposed to match, as they are separate analyses. Figure 1B is at the district level and Figure 2 is clustering shehias throughout Zanzibar.

The figure legend of Figure 1B on lines 410-414 now reads:

“B) A Discriminant Analysis of Principal Components (DAPC) was performed utilizing isolates with unique pseudohaplotypes, pruning highly related isolates to a single representative infection. Districts were included with at least 5 isolates remaining to have sufficient samples for the DAPC. For plotting the inset map, the district coordinates (e.g. Mainland, Kati, etc.) are calculated from the averages of the shehia centroids within each district.”

The figure legend of Figure 2 on lines 417-425 now reads:

“Figure 2. Coastal Tanzania and Zanzibari parasites have more highly related pairs within their given region than between regions. K-means clustering of shehia coordinates was performed using geographic coordinates all shehias present from the sample population to generate 5 clusters (colored boxes). All shehias were included to assay pairwise IBD between differences throughout Zanzibar. Pairwise comparisons of within cluster IBD (column 1 of IBD distribution plots) and between cluster IBD (column 2-5 of IBD distribution plots) was done for all clusters. In general, within cluster IBD had more pairwise comparisons containing high IBD identity.”

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

Thank you for this point and it greatly improved this figure. We changed the plotting mechanisms through using a beeswarm plot, which plots all pairwise IBD values within each comparison group.

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

Thank you very much for these considerations. We changed the color coding to a color blind friendly palette and renamed the clusters to more informative names; Pemba, Unguja North (Unguja_N), Unguja Central (Unguja_C), Unguja South (Unguja_S) and mainland Tanzania (Mainland).

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

Thank you for this point. We have edited the legend to reflect these changes. The legend for Figure 3 on lines 427-433 now reads:

“Figure 3. Isolation by distance is shown between all Zanzibari parasites (A), only Unguja parasites (B) and only Pemba parasites (C). Samples were analyzed based on geographic location, Zanzibar (N=136) (A), Unguja (N=105) (B) or Pemba (N=31) (C) and greater circle (GC) distances between pairs of parasite isolates were calculated based on shehia centroid coordinates. These distances were binned at 4km increments out to 12 km. IBD beyond 12km is shown in Supplemental Figure 8. The maximum GC distance for all of Zanzibar was 135km, 58km on Unguja and 12km on Pemba. The mean IBD and 95% CI is plotted for each bin.”

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

Thank you for pointing this out. Figure 3 and Supplemental Figure 10 are adjusted with matching formatting for each plot.

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

In Supplemental Figure 4, all isolates were used in this analysis and isolates with unique pseudohaplotypes were not pruned to a single representative infection. That is why there are additional isolates in Kusini. The legend for Supplemental Figure 4 now reads:

“Supplemental Figure 4. PCA with highly related samples shows population stratification radiating from coastal Mainland to Zanzibar. PCA of 282 total samples was performed using whole sample allele frequency (A) and DAPC was performed after retaining samples with unique pseudohaplotypes in districts that had 5 or more samples present (B). As opposed to Figure 1, all isolates were used in this analysis and isolates with unique pseudohaplotypes were not pruned to a single representative infection.”

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

The sentence below was added to the figure legends of Supplemental Figures 6 and 7 and the legends of each network plot were increased in size:

“The width of each line represents higher magnitudes of IBD between pairs.”

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

Thank you for this comment. For Supplemental Figure 8 and 9, we did not put these lines that represent lower pairwise IBD to draw the reader's attention to the highly related pairs between and within shehias.

Reviewer #2 (Recommendations For The Authors):

(1) There is a rather long paragraph (lines 300-323) on COI of asymptomatic infections and their genetic structure. Given that the current study did not investigate most of the hypotheses raised there (e.g. immunity, expression of variant genes), and the overall limited number of asymptomatic samples typed, this part of the discussion feels long and often speculative.

Thank you for your perspective. The key sections highlighted in this comment, regarding immunity and expression of variant genes, were shortened. This section on lines 300-303 now reads:

“Asymptomatic parasitemia has been shown to be common in falciparum malaria around the globe and has been shown to have increasing importance in Zanzibar (Lindblade et al., 2013; Morris et al., 2015). What underlies the biology and prevalence of asymptomatic parasitemia in very low transmission settings where anti-parasite immunity is not expected to be prevalent remains unclear (Björkman & Morris, 2020).”

(2) As a detail, line 304 mentions "few previous studies" but only one is cited. Are there studies that investigated this and found opposite results?

Thank you for this comment. We added additional studies that did not find an association between clinical disease and COI. These changes are on lines 303-308, which now reads:

“Similar to a few previous studies, we found that asymptomatic infections had a higher COI than symptomatic infections across both the coastal mainland and Zanzibar parasite populations (Collins et al., 2022; Kimenyi et al., 2022; Sarah-Matio et al., 2022). Other studies have found lower COI in severe vs. mild malaria cases (Robert et al., 1996) or no significant difference between COI based on clinical status (Earland et al. 2019; Lagnika et al. 2022; Conway et al. 1991; Kun et al. 1998; Tanabe et al. 2015)”

(3) Table 2: Percentages need to be checked. To take one of several examples, for Pfk13-K189N a frequency of 0.019 for the mutant allele is given among 137 samples. 2/137 equals to 0.015, and 3/137 to 0.022. 0.019 cannot be achieved. The same is true for several other markers. Possibly, it can be explained by the presence of polyclonal infections. If so, it should be clarified what the total of clones sequenced was, and whether the prevalence is calculated with the number of samples or number of clones as the denominator.

Thank you for this point. We mistakenly reported allele frequency instead of prevalence. An updated Table 2 is now in the manuscript. The method for calculating the prevalence is now at lines 148-151:

“Prevalence was calculated separately in Zanzibar or mainland Tanzania for each polymorphism by the number of samples with alternative genotype calls for this polymorphism over the total number of samples genotyped and an exact 95% confidence interval was calculated using the Pearson-Klopper method for each prevalence.”

eLife assessment

Connelly and colleagues provide convincing genetic evidence that importation from mainland Tanzania is a major source of Plasmodium falciparum lineages currently circulating in Zanzibar. This study also reveals ongoing local malaria transmission and occasional near-clonal outbreaks in Zanzibar. Overall, the manuscript effectively highlights the role of human movements in maintaining residual malaria transmission in an area targeted for intensive control interventions over the past decades and provides clear and valuable information for epidemiologists and public health professionals.

Reviewer #2 (Public Review):

Summary:

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

The two studies made overall very similar findings, including strong small-scale population structure, related infections on Zanzibar and the mainland, near-clonal expansion on Pemba, and frequency of markers of drug resistance.

Strengths:

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

Comments on revised version:

The authors have addressed my comments.

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Comments on revised version:

The authors answered all my questions.

Author response:

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

Reviewer #1 (Public Review):

Granados-Aparici et al., investigate somatic-germline interactions in female mice. Mammalian oocytes are nurtured in multi-cellular ovarian follicles and communication with surrounding somatic cells is critical for oocyte development. This study focused on transzonal projections (TZP) extending from granulosa cells to the surface of oocytes and documented the importance of SMAD4, a TGF- β mediator, in regulating the TZPs. They propose a model in which individual TZPs contact the surface of the oocyte and stably attach if there is sufficient N-cadherin. In SMAD4-depleted cells, there is insufficient N-cadherin to stabilize the attachment. The TZP continues to elongate but eventually retracts. Their model is well supported by their experimental evidence and the manuscript is both well-formulated and written.

Reviewer #2 (Public Review):

Summary:

This study proposed a new mechanism by which the TGF-beta signaling pathway promotes contacts between oocytes and the surrounding somatic cells in mice, by regulating the numbers of transzonal projections (TZPs).

Strengths:

The conditional Smad4 knockout and three-dimensional observation of transzonal projections are solid and sufficiently support the major conclusions.

Weaknesses:

The physiological significance of SMAD4-dependent formation of transzonal projection networks is not assessed in this study.

Previous studies have shown that physical contact and gap junctional communication with the granulosa cells is essential for normal oocyte development. A recent study has also shown that depleting Myo10 in granulosa cells reduces the number of TZPs and leads to abnormalities in oocyte and embryo development. Thus, the importance of TZPs is well-established. These findings, which were insufficiently brought out in the Introduction of the original manuscript, have now been made more clearly (Introduction, 2nd paragraph). We recognize that these reports do not directly test a role for SMAD4-dependent TZPs. Unfortunately, it is beyond our technical capacity to obtain embryos following meiotic maturation and fertilization of oocytes that have grown in vitro, which wold be necessary for us to fully test the physiological role of SMAD4-dependent TZPs.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) The authors switch from Amhr2-cre to ER-cre to increase the number of GFP-positive granulosa cells in 12 d/o ovaries. To avoid disruption of FSH secretion by SMAD4, they use an in vitro model that requires 6 days in GEO culture (1 d tamoxifen + 5 d). Could it be that Amhr2-cre didn't work because most follicles would not have reached the atretic preantral stage in 12 d/o ovaries? Did the authors consider 6 days in vitro GEO culture to determine if Amhr2-cre would be efficient and avoid exposure to tamoxifen?

Please see below.

When is Amhr2 expressed?

Previous studies (Jorgez et al, 2004; Pangas et al, 2006) report that Amhr2 is expressed in growing follicles that have progressed beyond a single layer of granulosa cells (often defined as secondary and primary follicles, respectively). As shown in Fig. 1C, we did not observe evidence of widespread Cre activity in multilayer follicles. At least two factors may contribute why we observed relatively weak Cre activity. One possibility is that, on the genetic background our mice, Amhr2 is expressed relatively late during follicular growth. Thus, we might have observed more GFP-positive granulosa cells in antral or pre-ovulatory follicles. Because the granulosa cells of these late-stage follicles would already have produced many TZPs, the number of new TZPs generated in wild-type but not SMAD4-depleted cells after Amhr2 activation would be a relatively small proportion of the total population. This would make it more difficult to detect a reduction in TZP number in the absence of SMAD4.

A second point is that we used pre-puberal mice whereas Jorgez et al examined Amhr2 expression in ovaries of adult mice. Pangas et al evaluated both prepuberal and adult females. It may be that Amhr2 is expressed earlier or more strongly in granulosa cells of adult mice. Regarding the suggestion to culture complexes obtained from mice on the Amhr2-Cre background, as this might allow widespread expression of Cre without the need for tamoxifen, this is an excellent idea. If there is considerable heterogeneity among cells in the timing of Amhr2-Cre activity, though, this may further cloud efforts to uncover the role of SMAD4 in the production or stability of TZPs, as noted above.

(2) Did most of the GEO cultured in vitro reach the antral follicle stage after 6 days?

Since GOCs were treated with collagenase, the thecal layer was removed. Therefore, development of an antrum does not occur. We observed that, in some cases, the oocyte was extruded from the granulosa cell mass. These abnormal complexes were discarded.

(3). Was the development/diameter of the oocyte in the GEO comparable to the oocyte growing in vivo?

We did not compare the diameter of the oocytes grown in vitro to those grown in vivo. Thus, we cannot say whether the oocytes grown in vitro reached the same size as those grown in vivo. We did, however, compare the diameter of the oocytes in the wt and ko groups and observed no difference (Figure 2). This indicates that depletion of SMAD4 in the granulosa cells does not impair oocyte growth. Importantly for our studies, it excludes the possibility that the reduction in TZP-number is simply due to a smaller surface area of the oocyte.

(4) SMAD4 depletion in granulosa cells disrupts steroidogenesis leading to increased progesterone levels and precocious luteinization of granulosa cells (Pangas et al., 2006). Did the authors determine the expression level of luteal markers of granulosa cells in the in vitro GEO culture Smad4 knockout model? Are their observations direct effects of the absence of SMAD4?

This is an excellent point. We checked our previously performed RNA-seq analysis of the wild-type and knockout granulosa cells, but found no difference in the quantities of Cyp11a1, Sfrp4, Star or Ptgfr. This is now described in the Discussion (4th paragraph). One potentially important difference between our study and that of Pangas et al (2006) is that they observed premature luteinization when prepuberal (3-week old) mice were injected with the FSH analogue, equine serum gonadotropin, whereas we studied granulosa-oocyte complexes cultured in vitro. This could underlie the apparent differences with respect to luteinization.

(5) Could the reduced number of TZPs in ER-cre+; Smad4fl/fl GOCs be explained by luteinization?

This interesting and logical possibility is related to the previous point. In other words, luteinization could be considered as a default pathway of differentiation that is suppressed by SMAD signaling. It is possible that luteinized cells are unable to generate or maintain TZPs. This model offers a potential mechanistic basis for our observation, and we now raise it in the Discussion (3rd paragraph).

Reviewer #3 (Recommendations For The Authors):

The expression and localization of N-cadherin should be observed in Smad4 and control granulosa cell-oocyte complexes.

We agree that this would be an excellent approach to confirm the decreased expression of N-cadherin in the granulosa cells that was observed by immunoblotting. We were confronted by two challenges, however. First, we were unable to consistently obtain strong staining of granulosa cell membranes in the inner layers of multilayer granulosa-oocyte complexes. Other antibodies are able to stain structures at the oocyte surface, indicating that antibodies are not physically blocked from penetrating the complex. More likely, the anti-N-cadherin does not bind its target strongly enough to generate a robust signal that can be detected through multiple overlying layers of cells. Second, whereas for immunoblotting we collect all granulosa cells from culture complexes, for immunofluorescence we are only able to examine those that remain in the complex. This means that, for immunofluorescence, we essentially but unavoidably select against cells that are only loosely attached – as would be expected for N-cadherin-deficient cells – to their neighbours. Given these challenges, we believe that the immunoblotting approach, which produced highly reproducible results over six biological replicates (Fig. 6), is the most reliable.

Reviewer #1 (Public Review):

Granados-Aparici et al., investigate somatic-germline interactions in female mice. Mammalian oocytes are nurtured in multi-cellular ovarian follicles and communication with surrounding somatic cells is critical for oocyte development. This study focused on transzonal projections (TZP) extending from granulosa cells to the surface of oocytes and document the importance of SMAD4, a TGF- β mediator, in regulating the TZPs. They propose a model in which individual TZPs contact the surface of the oocyte and stably attaches if there is sufficient N-cadherin. In SMAD4-depleted cells, there is insufficient N-cadherin to stabilize the attachment. The TZP continues to elongate but eventually retracts. Their model is well supported by their experimental evidence and the manuscript is both well-formulated and written.

Comments on revised version:

The authors have addressed the issues raised in the original review.

Reviewer #2 (Public Review):

Summary:

This study proposed a new mechanism by which TGF-beta signaling pathway promotes contacts between oocyte and the surrounding somatic cells in mouse, by regulating the numbers of transzonal projections (TZPs).

Strengths:

The conditional Smad4 knockout and three-dimensional observation of transzonal projections are solid and sufficiently support the major conclusions.

Comments on revised version:

The authors have adequately addressed the reviewers' questions and comments.

eLife assessment

This study reports an important mechanism through which the TGF-beta signaling pathway promotes contacts between oocytes and their surrounding somatic cells by regulating the number of transzonal projections (TZPs) in mice. Convincing data support the conclusions. The work will be of interest to biomedical researchers who work on ovarian biology and female fertility.

Author response:

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

eLife assessment

This study presents useful findings regarding the role of formin-like 2 in mouse oocyte meiosis. The submitted data are supported by incomplete analyses, and in some cases, the conclusions are overstated. If these concerns are addressed, this paper would be of interest to reproductive biologists.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The presented study focuses on the role of formin-like 2 (FMNL2) in oocyte meiosis. The authors assessed FMNL2 expression and localization in different meiotic stages and subsequently, by using siRNA, investigated the role of FMNL2 in spindle migration, polar body extrusion, and distribution of mitochondria and endoplasmic reticulum (ER) in mouse oocytes.

Strengths:

Novelty in assessing the role of formin-like 2 in oocyte meiosis.

Weaknesses:

Methods are not properly described.

Overstating presented data.

It is not clear what statistical tests were used.

My main concern is that there are missing important details of how particular experiments and analyses were done. The material and methods section are not written in the way that presented experiments could be repeated - it is missing basic information (e.g., used mouse strain, timepoints of oocytes harvest for particular experiments, used culture media, image acquisition parameters, etc.). Some of the presented data are overstated and incorrectly interpreted. It is not clear to me how the analysis of ER and mitochondria distribution was done, which is an important part of the presented data interpretation. I'm also missing important information about the timing of particular stages of assessed oocytes because the localization of both ER and mitochondria differs at different stages of oocyte meiosis. The data interpretation needs to be justified by proper analysis based on valid parameters, as there is considerable variability in the ER and mitochondria structure and localization across oocytes based on their overall quality and stage.

Thank you for your comment. We regret the oversight of omitting critical information in the manuscript. In the revised manuscript, we have included essential details such as mouse strains, culture media, stages of oocyte and statistical methods in the materials and methods section. Please find our details responses in the “Recommendations for the authors” part.

Reviewer #2 (Public Review):

Summary:

This research involves conducting experiments to determine the role of Fmnl2 during oocyte meiosis I.

Strengths:

Identifying the role of Fmnl2 during oocyte meiosis I is significant.

Weaknesses:

The quantitative analysis and the used approach to perturb FMNL2 function are currently incomplete and would benefit from more confirmatory approaches and rigorous analysis.

(1) Most of the results are expected. The new finding here is that FMNL2 regulates cytoplasmic F-actin in mouse oocytes, which is also expected given the role of FMNL2 in other cell types. Given that FMNL2 regulates cytoplasmic F-actin, it is very expected to see all the observed phenotypes. It is already established that F-actin is required for spindle migration to the oocyte cortex, extruding a small polar body and normal organelle distribution and functions.

Thank you for your comment. In the recent decade, Arp2/3 complex (Nat Cell Biol 2011), Formin2 (Nat Cell Biol 2002, Nat Commun 2020), and Spire (Curr Biol 2011) were reported to be 3 key factors to involve into this process. These factors regulate actin filaments in different ways. However, how they cross with each other for the subcellular events were still fully clear. Our current study identified that FMNL2 played a critical role in coordinating these molecules for actin assembly in oocytes. Our findings demonstrate that FMNL2 interacts with both the Arp2/3 complex and Formin2 to facilitate actin-based meiotic spindle migration. Additionally, we discovered a novel role for FMNL2 in determining the distribution and function of the endoplasmic reticulum and mitochondria, which may in turn influence meiotic spindle migration in oocytes. Our results not only uncover the novel functions of FMNL2-mediated actin for organelle distribution, but also extend our understanding of the molecular basis for the unique meiotic spindle migration in oocyte meiosis.

(2) The authors used Fmnl2 cRNA to rescue the effect of siRNA-mediated knockdown of Fmnl2. It is not clear how this works. It is expected that the siRNA will also target the exogenous cRNA construct (which should have the same sequence as endogenous Fmnl2) especially when both of them were injected at the same time. Is this construct mutated to be resistant to the siRNA?

Thank you for your question. We regret any misunderstanding that may have been caused by the inappropriate description in our manuscript. In the rescue experiments, we initially injected FMNL2 siRNA into oocytes, followed by the microinjection of FMNL2 mRNA 18-20 hours later. After conducting our previous experiments, we have verified through Western blotting that endogenous FMNL2 is effectively suppressed 18-20 hours following the microinjection of FMNL2 siRNA. Additionally, we observed a significant increase in exogenous FMNL2 protein expression 2 hours after the injection of FMNL2 mRNA. We believe that the exogenous FMNL2 could compensate the decrease by FMNL2 knockdown, and this approach was adopted in many oocyte studies.

(3) The authors used only one approach to knockdown FMNL2 which is by siRNA. Using an additional approach to inhibit FMNL2 would be beneficial to confirm that the effect of siRNA-mediated knockdown of FMNL2 is specific.

Thank you for your question. Yes, the specificity is always the concern for siRNA or morpholino microinjection due to the off-target issue. Due to the limitation we could not generate the knock out model, and there are no known inhibitors with specific targeting capabilities for FMNL2. To solve this, we performed the rescue study with exogenous mRNA to confirm the effective knock down of FMNL2. These measures provide reassurance regarding the credibility of the experimental outcomes, and this is also the general way to avoid the off-target of siRNA or morpholino.

Reviewer #3 (Public Review):

Summary:

The authors focus on the role of formin-like protein 2 in the mouse oocyte, which could play an important role in actin filament dynamics. The cytoskeleton is known to influence a number of cellular processes from transcription to cytokinesis. The results show that downregulation of FMNL2 affects spindle migration with resulting abnormalities in cytokinesis in oocyte meiosis I.

Weaknesses:

The overall description of methods and figures is overall dismissively poor. The description of the sample types and number of replicate experiments is impossible to interpret throughout, and the quantitative analysis methods are not adequately described. The number of data points presented is unconvincing and unlikely to support the conclusions. On the basis of the data presented, the conclusions appear to be preliminary, overstated, and therefore unconvincing.

Thank you for your comment. We regret the oversight of omitting critical information in the manuscript. In the revised manuscript, we have incorporated your suggestions for modification, particularly regarding the Materials and Methods section. Please see the detailed revision and responses in the “Recommendations for the authors” part.

Recommendations for the authors:

Reviewer #1 (Recommendations for The Authors):

My main concern is that there are missing important details of how particular experiments and analyses were done. The material and methods section is not written in the way that presented experiments could be repeated - it is missing basic information (e.g., used mouse strain, timepoints of oocytes harvest for particular experiments, used culture media, image acquisition parameters, etc.). Some of the presented data are overstated and incorrectly interpreted. It is not clear to me how the analysis of ER and mitochondria distribution was done, which is an important part of the presented data interpretation. I'm also missing important information about the timing of particular stages of assessed oocytes because the localization of both ER and mitochondria differs at different stages of oocyte meiosis. The data interpretation needs to be justified by proper analysis based on valid parameters, as there is considerable variability in the ER and mitochondria structure and localization across oocytes based on their overall quality and stage. My specific comments are listed below.

(1) Information about statistical tests that were used needs to be provided for all quantification experiments.

Thank you for your suggestion. Based on your suggestions, we revised the statistical analysis description in the Materials and Methods section. Additionally, we also included a description of the statistical methods in the legends of the relevant result figures.

(2) I recommend replacing the plunger plots, used in most quantification data, with alternatives allowing evaluation of the distribution of the data (dot plots, box plots, whisker plots).

Thank you for your suggestion. Following your suggestion, we replaced the plunger plots in Fig 2C, D, H, I and Fig3 B, C with dot plots.

(3) Can the authors provide information about particular time points when were individual oocyte stages (GVBD, meiosis I, and meiosis II) harvested/used for immunofluorescence protein detection, western blotting, microinjection, and ER and mitochondria staining? Were the time points always the same in all presented experiments and experimental vs control group? If not, this needs to be clarified.

Thank you for your suggestion. We used oocytes in the metaphase I (MI) stage for the statistical analysis of spindle migration, actin filament aggregation, endoplasmic reticulum localization, and mitochondrial localization. In the Western blot analysis, GV stage oocytes were utilized to evaluate the efficiency of knockdown and rescue experiments. The protein expression levels of Arp2, Formin2, INF2, Cofilin, Grp78, and Chop in different treatment groups were detected using MI-stage oocytes. In the revised version, we provided all the detailed information about the stages.

(4) Figure 1B: Can the authors comment on why there is a missing representative image of MII oocyte FMBL2-Ab? I recommend including this in the figure to have a complete view of comparing overexpressed and endogenous FMNL2 localization in oocyte meiosis.

Thank you for your suggestion. In the revised manuscript, we added immunostaining images of FMNL2 antibody in MII stage oocytes.

(5) Figure 1C: The figure legend says, "FMNL2 and actin overlapped in cortex and spindle surrounding". In MI oocytes, there is usually no accumulated actin signal around the spindle, which is also true in the presented images, so there cannot be overlapping with the FMNL2 signal. The interpretation should be changed.

We apologize for this inappropriate description that was used, and we deleted this sentence.

(6) Figure 2B: What were the parameters of the "large" and "normal" polar bodies for performing the analysis?

Thank you for your question. In order to assess the size of the polar body, we conducted a comparison between the diameter of the polar body and that of the oocyte. If the diameter of the polar body was found to be less than 1/3 of the oocyte's diameter, we categorized it as normal-sized polar body. Conversely, if the polar body's diameter exceeded 1/3 of the oocyte's diameter, we categorized it as a large polar body. We have included these details in the Results section of the manuscript.

(7) Figure 2F: Can the authors comment on what can be the second band in the rescue group?

Thank you for your question. In the rescue experiment, we microinjected exogenous FMNL2-EGFP mRNA into the oocytes. As a result, compared to endogenous FMNL2, the protein size increased due to the addition of the EGFP tag, approximately 27 kDa. Hence, in the Western blot bands of the rescue group, the upper band represents the expression of exogenous FMNL2-EGFP, while the lower band corresponds to the expression of endogenous FMNL2. We have provided annotations in the revised Figure 2F to clarify this.

(8) Can the authors comment on the variability of PBE between 2C and 2H in the FMNL2-KD groups? In panel C, the PBE in the KD group was 59.5 {plus minus} 2.82%; in panel H, the PBE in the KD group was 48.34 {plus minus} 4.2%, and in the rescue group, the PBE was 62.62 {plus minus} 3.6%. The rescue group has a similar PBE rate as the KD group in panel C. How consistent was the FMNL2 knockdown across individual replicates? Can the authors provide more details on how the rescue experiment was performed?

Thank you for your question. We believe that the difference in PBE observed in Figure 2C and 2H of the FMNL2-KD group was due to the microinjection times and the duration of in vitro arrest. The results shown in Figure 2C depict the outcome of a single injection of FMNL2 siRNA into GV stage oocytes, followed by 18 hours of in vitro arrest; the results shown in Figure 2H contain a subsequent additional injection of FMNL2-EGFP mRNA with another 2 hours of arrest. The two rounds of microinjection and the extended period of in vitro arrest both affect oocyte maturation rates.

(9). Figure 2J and K: What groups were compared together? The used statistic needs to be properly described.

Thank you for your question. The FMNL2-KD, FMNL3-KD, and FMNL2+3-KD groups were all compared to the Control group, therefore, t-test was used for analysis. We have provided explanations in the revised manuscript.

(10) Figure 4B and C: Can the authors provide representative images without oversaturated actine signal?

Thank you for your question. For the analysis of oocyte F-actin, the F-actin are divided into cortex actin and cytoplasmic actin. Due to the contrast during imaging, the strong cortex actin signals affected the detection of cytoplasmic actin, therefore, it is necessary to increase the scanning index, which will cause the overexpose the cortex actin signal. This is for the better observation of the cytoplasmic signals.

(11) Figure 4G + 5H: Can the authors comment on why they used as a housekeeping gene actin instead of tubulin, which was used in the rest of the WB experiments?

Thank you for your question. In most of the western blot experiments conducted in this study, we used tubulin as a housekeeping gene. However, due to the supply of antibodies by delivery period, we had GAPDH and actin as well for some experiments. These housekeeping genes were all valid for the study.

(12) Based on what parameters was ER considered normally or abnormally distributed, and what stages of oocytes were assessed?

Thank you for your question. In this study, we employed oocytes at the MI stage for the analysis of ER localization. In the MI stage, the ER localized around the spindle, which is regarded as the typical localization pattern. The ER displayed a dispersed distribution throughout the cytoplasm or clustered were categorized as aberrant positioning. We included relevant descriptions in the revised version of the manuscript.

(13) Figure 5H: As a housekeeping gene was used actin - the quantification is labeled as a Grp78 to tubulin ratio.

Thank you for pointing out the error. This is a label mistake and we corrected it.

(14) Information about how JC-1 staining was done needs to be provided.

Thank you for your carefully reading. We included a description of JC1 staining in the Materials and Methods section.

(15). Line 231-232: "As shown in Figure 4A" - the text doesn't correspond to the figure.

Thank you for pointing out the error. We revised this mistake in the revised manuscript by correcting "Fig3A" to "Fig4A."

(16) Line 265: there is probably a missing word "Formin2".

Thank you and we corrected the error and made the necessary changes in the revised manuscript.

Reviewer #2 (Recommendations for The Authors):

(1) Quantification and analysis:

• Fig. 3B: The rate of spindle migration should be quantified based on the distance from the spindle to the cortex. Also, the orientation of the spindle (Z-position) needs to be taken into consideration.

• Fig. 5C, D: It is unclear how the rate of ER distribution was calculated.

• Western blot: In many experiments (such as Fig. 5H), the bands are saturated which will prevent accurate intensity measurements and quantifications.

For spindle migration, we specifically focused on spindles exhibiting a distinctive spindle-like shape with clear bipolarity to eliminate any statistical discrepancies potentially caused by variations in Z-axis alignment. Our criterion for determining successful migration was based on the contact between the spindle pole and the cortical region of the oocyte. Therefore, we think that the rate is better to reflect the phenotype than the distance.

For the examination of ER localization, Reviewer 1 also raised this issue. We utilized oocytes at the MI stage in this study. The ER localized around the spindle in MI stage. The ER displayed a dispersed distribution throughout the cytoplasm or clustered were categorized as aberrant positioning. We included relevant descriptions in the revised version of the manuscript.

For the bands of the western blot results, during the experimental procedure we typically capture multiple images at different exposure levels (3-5 images). In the revised manuscript, we have replaced the inappropriate images with more suitable ones.

(2) Given that all Immunoprecipitation experiments in this manuscript were performed on the whole ovary which contains more somatic cells than oocytes, the results do not necessarily reflect meiotic oocytes. Please consider this possibility during the interpretation.

Thank you for your suggestion. Yes, we agree with you. In the revised manuscript, we made appropriate modifications to the relevant descriptions.

(3) 351-365: The conclusion that Arp2/3 compensates for the decreased formin 2 in FMNL2 knockdown oocytes is a bit unconvincing. 1- In mouse oocytes, it is already known that Arp2/3 and formin 2 regulate different pools of F-actin nucleation. 2- The authors found an increase in Arp2/3 in FMNL2 knockdown oocytes compared to control oocytes without any change in cortical F-actin. Given that Arp2/3 is primarily promoting cortical F-actin, it is expected to see an increase in cortical F-actin in FMNL2 knockdown oocytes, which was not the case.

Thank you for your question. Yes, previous studies showed that formin2 localizes to the cytoplasm of oocytes and accumulates around the spindle, which facilitate cytoplasmic actin assembly. While Arp2/3 is primarily responsible for actin assembly at the cortex region of oocytes. In invasive cells, FMNL2 is mainly localized in the leading edge of the cell, lamellipodia and filopodia tips, to improve cell migration ability by actin-based manner (Curr Biol 2012). We showed that FMNL2 localized both at spindle periphery and cortex, but depletion of FMNL2 did not affect cortex actin intensity. We think that FMNL2 and Arp2/3 both contribute to the cortex actin dynamics, when FMNL2 decreased, ARP2 increased to compensate for this, which maintained the cortex actin level. In the revised manuscript, we have made modifications to avoid excessive extrapolation from our results, ensuring that our conclusions are presented in a more objective manner.

(4) Lines 195-197: The spindle is initially formed soon after the GVBD, so there is no spindle during GVBD. Also, I can't see oocytes at anaphase I or telophase I in this figure. Please revise.

Thank you for your suggestion. We apologize for the inappropriate descriptions that were used. In the revised manuscript, we have made modifications to the respective descriptions in the Results part.

(5) Fig. 2E: It seems that the control oocyte is abnormal with mild cytokinesis defects. Please replace or delete it since this information is already included in Fig. 3A.

Thank you for your suggestion. Based on our observations, during the extrusion of the first polar body in oocytes, there is a temporary occurrence of cellular morphological fragmentation due to cortical reorganization (11h in control oocyte from Fig 2E). However, after the extrusion of the first polar body, the oocyte morphology returns to normal. Figure 2E illustrates the meiotic division process of oocytes, while Figure 3A primarily focuses on the process of oocyte spindle migration. We think that it is better to retain both to present our results.

Reviewer #3 (Recommendations for The Authors):

In the case of the observed phenotype, the stage of GV is important. The phenotypes presented also occur in meiotic or developmentally incompetent oocytes. In addition, the images of GV oocytes appear as NSN, which also show the KD phenotype in Figs. 2 and 3.

Thank you for your concern. As the oocyte grows, the proportion of SN-type oocytes gradually increases. When the oocyte diameter reaches 70-80 μm, the proportion of SN oocytes is approximately 52.7% (Mol Reprod Dev. 1995). In our study, both the control and knockdown groups collected oocytes with a diameter of around 80 μm, which is considered as fully-grown oocytes, predominantly in the SN phase. Since the collection period and size of the oocytes were consistent, we can sure that the observed differences between the control and knockdown groups in phenotype analysis could be solid and reliable.

MII is absent in Fig. 1B.

In the revised manuscript, we added immunostaining images of FMNL2 in MII stage oocytes.

The result of KD is not convincing. Also, discuss whether the heterozygous effect of Fmnl2 deletion affects reproductive fitness.

Thank you for your concern. In our investigation, limited to the setup of knock out model, we employed siRNA to knockdown FMNL2 expression, to avoid the risk of off-target, we performed rescue experiment with exogenous mRNA, which we believe that it could solve this issue. When designing siRNA sequences, we ensured their specificity for binding to FMNL2 mRNA only, and we assessed the levels of FMNL2 and FMNL3 mRNA in oocytes after injection of FMNL2 siRNA. The results showed that, compared to the control group, the expression of FMNL2 mRNA decreased by approximately 70% after 18 hours of FMNL2 siRNA injection, while the level of FMNL3 mRNA was not decreased.

Fig. 2F rescue experiment with double bands. What bands are seen here? Did the authors inject tagged or untagged FMNL2? Or does endogenous FMNL2 appear higher in the sample after KD?

Thank you for your question. In the rescue experiment, we microinjected exogenous FMNL2-EGFP mRNA into the oocytes. As a result, compared to endogenous FMNL2, the protein size increased due to the addition of the EGFP tag, approximately 27 kDa. Hence, in the Western blot bands of the rescue group, the upper band represents the expression of exogenous FMNL2-EGFP, while the lower band corresponds to the expression of endogenous FMNL2. We provided annotations in the revised Figure 2F to clarify this.

Variability in mitochondria and ER distribution patterns is also known in healthy and developing oocytes, although the authors described only a single phenotype.

Thank you for your concern. Yes, mitochondria and ER show dynamic localization in different stage of oocyte maturation. However, in this study we employed oocyte MI stage for the analysis of ER and mitochondria localization, and in MI stage, both the ER and mitochondria localize around the spindle. This pattern is considered as the normal localization. Several studies showed that dispersed or clustered localization contributed to maturation defects. We included relevant descriptions in the revised manuscript.

What exactly is meant by input in the IP experiments? Why is the target missing in the input sample?

Thank you for your question. We subjected the input samples to electrophoresis on a single channel, all the analyzed proteins demonstrated normal expression, thereby confirming the viability of the input sample. However, upon simultaneous exposure with the IP samples, we observed a lack of clear signal for certain proteins in the input group. This phenomenon is due to the excessive signal intensity resulting from protein enrichment in the IP group, which caused the low exposure of proteins in input group.

Explain the rationale for using, actin or tubulin as loading or normalization controls in the study focusing on the cytoskeleton.

Thank you for your question. Actin and tubulin are both widely used as the control due to their stable expression. For actin, there are α-actin and β-actin isoforms. Formins and Arp2/3 complex regulate the polymerization of α-actin and β-actin to form F-actin, not isoform expression. In our study F-actin (the functional type) was examined. While α-tubulin and β-tubulin are two subtypes of tubulin, and they interact with each other to form stable α/β-tubulin heterodimers. The changes of cytoskeleton dynamics could not change the expression of α/β-tubulin. Therefore, β-actin and α-tubulin could be used as normalization controls.

Fig. 6E shows only , but the legend says *.

Thank you for pointing out the error. We correct the mistake in the revised manuscript.

Spindle positioning appears to differ between control and KD. Does this affect the quantification of Fig. 6F? Adequate nomenclature should be used here.

Thank you for your question. Yes, spindle positioning was affected by FMNL2 depletion. However, central spindle or cortex spindle all belong to MI stage, and JC1 is not related with the stage difference. To avoid misunderstanding we replaced the representative images and corresponding description in Figure 6F.

The description of the methods and legends should be significantly improved.

Thank you for your suggestion. Reviewer 1 and 2 also raised the similar concern. We enriched the description of methods and legends in the revised manuscript.

eLife assessment

This study presents useful findings regarding the role of formin-like 2 in mouse oocyte meiosis. Some of the data are supported by incomplete methodological details and analyses, and several conclusions are overstated. This paper would be of interest to reproductive biologists.

Reviewer #1 (Public Review):

Summary:

The presented study focuses on the role of formin-like 2 (FMNL2) in oocyte meiosis. The authors assessed FMNL2 expression and localization in different meiotic stages and subsequently, by using siRNA, investigated the role of FMNL2 in spindle migration, polar body extrusion, and distribution of mitochondria and endoplasmic reticulum (ER) in mouse oocytes.

Strengths:

Novelty in assessing the role of formin-like 2 in oocyte meiosis

Weaknesses:

Overstating some of the presented data

Unconvincing analysis of the endoplasmic reticulum and mitochondria distribution

The authors addressed all my comments. The section materials and methods was improved. However, some statements still need to be clarified, as they seem to be overstated. I'm still not convinced about the main findings. For example, the analysis of ER and mitochondria distribution was based on a subjective assessment of clustering in meiosis I oocytes, and it's missing objective parameters and timing of the analysis.

Comments on revised version:

The authors addressed all my comments. The section materials and methods was improved. However, some statements still need to be clarified, as they seem to be overstated.

Reviewer #2 (Public Review):

Summary:

This research involves conducting experiments to determine the role of Fmnl2 during oocyte meiosis I.

Strengths:

Identifying the role of Fmnl2 during oocyte meiosis I is significant.

Weaknesses:

The quantitative analysis and the used approach to perturb FMNL2 function would benefit from more confirmatory approaches and rigorous analysis.

Comments on revised version:

The authors addressed most of my comments. However, some comments were not addressed convincingly.

My concern is still valid. The authors used only one approach to knockdown FMNL2 which is "siRNA-mediated knockdown". Using an additional approach to inhibit FMNL2 (Trim-Away or morpholino,..) would be beneficial to confirm that the effect of siRNA-mediated knockdown of FMNL2 is specific.

Response 1: In the author's response, they mentioned that successful migration was quantified based on the contact between the spindle pole and the oocyte cortex.<br /> After spindle migration, it is very common for the spindle to be close to (but not in contact with) the cortex for a considerable time. The spindle pole comes in contact with the cortex later (just before anaphase onset and polar body extrusion). Fig. 3A shows an example where at 9 h, the spindle is already migrated but did not come in contact with the cortex until 9:30 h. Based on Fig. 3B,C, the authors assessed spindle migration in fixed oocytes, making it impossible to fix all oocytes at the time of spindle contact with the cortex. Also,<br /> the representative images in Fig. 3C do not show spindle staining to assess the contact between the spindle and the cortex.<br /> Overall, I still believe that the distance between the spindle and the cortex is more accurate for quantifying spindle migration.

Response 2: The authors mentioned, "we made appropriate modifications to the relevant descriptions of immunoprecipitation experiments". I can't find these modifications in the manuscript. The authors need to state clearly that the immunoprecipitation results do not necessarily reflect meiotic oocytes specifically because these experiments were done using the whole ovary which contains both somatic cells and oocytes.

Response 5: The authors mentioned that "Based on our observations, during the extrusion of the first polar body in oocytes, there is a temporary occurrence of cellular morphological fragmentation due to cortical reorganization". Unfortunately, this means that the live imaging system in the authors' laboratory is not ideal for oocyte maturation. Several publications show normal oocyte morphology during cytokinesis. Please delete or replace Fig. 2E.

Author response:

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

eLife assessment

This study presents valuable new insights into HIV-associated nephropathy (HIVAN) kidney phenotype in the Tg26 transgenic mouse model and delineates the kidney cell types that express HIV genes and are injured in these HIV-transgenic mice. A series of compelling experiments demonstrated that PKR inhibition can ameliorate HIVAN with reversal of mitochondrial dysfunction (mainly confined to endothelial cells), a prominent feature shared in other kidney diseases. Although there are concerns regarding the specificity of C16 to PKR inhibition, as well as with the in situ hybridization studies, the data suggests that inhibition of PKR and mitochondrial dysfunction has potential clinical significance for HIVAN.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

HIV-associated nephropathy (HIVAN) is a rapidly progressing form of kidney disease that manifests secondary to untreated HIV infection, and is predominantly seen in individuals of African descent. Tg26 mice carrying an HIV transgene lacking gag and pol exhibit high levels of albuminuria and rapid decline in renal function that recapitulates many features of HIVAN in humans. HIVAN is seen predominantly in individuals carrying two copies of missense variants in the APOL1 gene, and the authors have previously shown that APOL1 risk variant mRNA induces activity of the double-strand RNA sensor kinase PKR. Because of the tight association between the APOL1 risk genotype and HIVAN, the authors hypothesized that PKR activation may mediate renal injury in Tg26 mice and tested this hypothesis by treating mice with a commonly used PKR inhibitory compound called C16. Treatment with C16 substantially attenuated renal damage in the Tg26 model as measured by urinary albumin/creatinine ratio, urinary NGAL/creatinine ratio, and improvement in histology. The authors then performed bulk and single-nucleus RNAseq on kidneys from mice from different treatment groups to identify pathways and patterns of cell injury associated with HIV transgene expression as well as to determine the mechanistic basis for the effect of C16 treatment. They show that proximal tubule nuclei from Tg26 mice appear to have more mitochondrial transcripts which was reversed by C16 treatment and suggest that this may provide evidence of mitochondrial dysfunction in this model. They explore this hypothesis by showing there is a decrease in the expression of nuclear-encoded genes and proteins involved in oxidative phosphorylation as well as a decrease in respiratory capacity via functional assessment of respiration in tubule and glomerular preparations from these mouse kidneys. All of these changes were reversed by C16 treatment. The authors propose the existence of a novel injured proximal tubule cell-type characterized by the leak of mitochondrial transcripts into the nucleus (PT-Mito). Analysis of HIV transgene expression showed high level expression in podocytes, consistent with the pronounced albuminuria that characterizes this model and HIVAN, but transcripts were also detected in tubular and endothelial cells. Because of the absence of mitochondrial transcripts in the podocytes, the authors speculate that glomerular mitochondrial dysfunction in this model is driven by damage to glomerular endothelial cells.

Strengths:

The strengths of this study include the comprehensive transcriptional analysis of the Tg26 model, including an evaluation of HIV transgene expression, which has not been previously reported. This data highlights that HIV transcripts are expressed in a subset of podocytes, consistent with the highly proteinuric disease seen in mice and humans. However, transcripts were also seen in other tubular cells, notably intercalated cells, principal cells and injured proximal tubule cells. Though the podocyte expression makes sense, the relevance of the tubular expression to human disease is still an open question.

The data in support of mitochondrial dysfunction are also robust and rely on combined evidence from downregulation of transcripts involved in oxidative phosphorylation, decreases in complex I and II as determined by immunoblot, and assessments of respiratory capacity in tubular and glomerular preparations. These data are largely consistent with other preclinical renal injury models reported in the literature as well as previous, less thorough assessments in the Tg26 model.

Weaknesses:

The key weakness of the study lies in the use of a PKR inhibitor with questionable specificity. C16 has been reported to inhibit numerous other kinases including cyclin CDKs and GSK3α and -β, and this means that the conclusions of this study with respect to the role of PKR are highly questionable. The rationale for the dose used was not provided (and is lower than used in other publications with C16), and in the absence of drug exposure data and assessment of target engagement, it is difficult to ascertain whether substantial inhibition of PKR was achieved.

A second key weakness lies in the identification of the PT-Mito cell cluster. Though the authors provide some rationale for the identification of this specific cell type, it seems equally plausible the cells merely reflect a high background capture of mitochondria in a subset of droplets. The IHC analysis that was provided is not convincing enough to support the claim and more careful high resolution imaging and in situ hybridization (with appropriate quantitation) will be needed to provide substantive support for the presence of a proximal tubule cell type with mitochondrial transcript that are trafficked to the nucleus.

We appreciate the reviewer’s thoughtful summary.

With regard to non-specificity of C16, we added to the Discussion a description and references that describe non-specificity of C16. as suggested by the reviewer. Of note, the C16 doses that we used were also used previously (Okamoto, CommBiol, 2018). Importantly, newly-added immunofluorescence images using a phospho-PKR specific antibody showed PKR inhibition (Supplemental Figure 1).

Identification of the PT-Mito cluster in tissues was challenging, mainly due to the absence of existence of know marker genes for newly-identified cluster. Finally, We added in situ hybridization images, with a negative control probe, to show specificity of target probes.

Reviewer #2 (Public Review):

Summary:

Numerous studies by the authors and other groups have demonstrated an important role for HIV gene expression kidney cells in promoting progressive chronic kidney disease, especially HIV-associated nephropathy. The authors had previously demonstrated a role for protein kinase R (PKR) in a non-HIV transgenic model of kidney disease (Okamoto, Commun Bio, 2021). In this study, the authors used innovative techniques including bulk and single nuclear RNAseq to demonstrate that mice expressing a replication-incompetent HIV transgene have prominent dysregulation of mitochondrial gene expression and activation of PKR and that treatment of these mice with a small molecule PKR inhibitor ameliorated the kidney disease phenotype in HIV-transgenic mice. They also identified STAT3 as a key upstream regulator of kidney injury in this model, which is consistent with previously published studies. Other important advances include identifying the kidney cell types that express the HIV transgene and have dysregulation of cellular pathways.

Strengths:

Major strengths of the study include the use of a wide variety of state-of-the-art molecular techniques to generate important new data on the pathogenesis of kidney injury in this commonly used model of kidney disease and the identification of PKR as a potential druggable target for the treatment of HIV-induced kidney disease. The authors also identify a potential novel cell type within the kidney characterized by high expression of mitochondrial genes.

Weaknesses:

Though the HIV-transgenic model used in these studies results in a phenotype that is very similar to HIV-associated nephropathy in humans, the model has several limitations that may prevent direct translation to human disease, including the fact that mice lack several genetic factors that are important contributors to HIV and kidney pathogenesis in humans. Additional studies are therefore needed to confirm these findings in human kidney disease.

We appreciate the succinct summary of the present work. We agree that the findings from the HIV Tg26 mouse model warrant additional investigation in human kidney disease samples. Further studies will be needed to confirm whether the mechanisms presented here are operative in human HIVAN or other RNA virus-associated kidney diseases.

Reviewer #1 (Recommendations For The Authors)

The specificity of the C16 tool has been called into question in 3 publications - Chen et al, 2008, PMID: 19046382; Lopez-Grancha et al, 2021, PMID: 34531308; and Cusak et al, 2023, PMID: 36400288. Lopez-Grancha et al have reported a novel, more selective PKR inhibitor with good pharmacological properties that might enable a more robust test of the PKR hypothesis. Regardless, compound exposures and target engagement (i.e. by monitoring phosphorylation of PKR targets such eIF2α) should accompany these studies. Alternatively, it may be easier to probe the role of PKR in Tg26 pathogenicity by crossing the Tg26 line to a PKR knockout mouse.

In response, we have added a description and references about the the possibility of non-specificity of C16 in the Discussion as a limitation as suggested. (Page 21).

“Third, we acknowledge possibility of a non-specific effect of C16 as an inhibitor of PKR.66-68”

Further, we added immunohistochemistry images of pPKR on kidney tissue as shown in Supplemental Figure 1A-D. Images showed PKR activation in Tg26 tubular cells, which was inhibited by C16 treatment.

Author response image 1.

Immunofluorescent images showing pPKR. (A-D) Immunofluorescent images showed PKR activation by detecting pPKR in Tg26 mouse kidney. pPKR was inhibited by C16 treatments.

The suggested PKR knockout mice experiment is an excellent idea for future work but we believe Is outside the scope of the current manuscript.

To enhance the evidentiary base for the PT-Mito cell type, it would be interesting to know whether these cells can also be found in human datasets like KPMP, though this might require reprocessing the original snRNAseq data. Further in situ hybridization in both mouse and human samples using fluorescent rather than colorimetric approaches should yield a more compelling dataset to provide evidence for this cell type. These approaches would also allow for more precise quantification of the PT-Mito cells compared to the population of proximal tubule cells. Again, the default assumption here should be that the mitochondrial transcripts represent a contamination, and the purpose of these additional experiments is to definitively rule out that explanation.

Authors: First, as suggested, we carried out additional analyses. We examined a publiclyavailable human kidney snRNA-seq dataset (GSE131882) and found in it the same PT-Mito cluster as shown in Supplemental Figure 6. The PT-Mito cluster was located in close proximity to the PT cluster in a UMAP plot. We added this finding in the Results as follows (Page 12):

“We also confirmed the existence of similar PT-Mito cluster in published human kidney single-nuclear RNA-seq data47 by the re-analysis of the original data. (Supplemental Figure 6A-C).”

Author response image 2.

PT-Mito cluster detection of publicly available human kidney single-nuclear RNA-seq data (GSE131882) (A) UMAP plot of human kidney single-nuclear RNA-seq data shows 16 clusters. Cluster 1, 4 are proximal tubule (PT) clusters, and cluster 7 is PT-Mito cluster. (B) Dot plot shows expression of PT marker genes and PT-Mito marker genes obtained from current manuscript data. PTMito markers including MT-CO1 and MT-CO2 had high expression in cluster 7. (C) UMAP plot shows all six samples are contributing to all cell clusters.

Second, as suggested, we also included negative control data from in situ hybridization studies (Supplementary Figure 5A, 5B), which shows that the signals in Figure 4B, 4C are true signals.

Author response image 3.

Additional in situ hybridization images. (A) In situ hybridization images probing dapB (negative control probe) showed no signals. (B) In situ hybridization images probing Ppib (positive control probe) showed strong signals.

Reviewer #2 (Recommendations For The Authors)

(1) The supplementary data file seems to have been uploaded twice but the supplementary methods were not available which would have been helpful when assessing some methods such as using PodoCount to count podocytes.

We acknowledge that we inadvertently failed to upload the Supplementary Methods section-thank you for pointing this out. The supplementary methods are now provided in the revised submission, including detailed methods about PodoCount. Corresponding descriptions are as follows:

“Estimation of glomerular podocyte count

PodoCount5, a computational tool for whole slide podocyte estimation from digitized histologic sections, was used to detect, enumerate, and characterize podocyte nuclear profiles in the glomeruli of immunohistochemically labeled (IHC-labeled) murine kidney sections. Formalin-fixed, paraffin embedded tissues (2 µm thickness) were IHC-labeled for p57kip2, a marker of podocyte terminal differentiation (ab75974, Abcam, Cambridge, UK), and detected with horse radish peroxidase (RU-HRP1000, Diagnostic BioSystems, Pleasanton, CA) and diaminobenzidine chromogen substrate (BSB0018A, Bio SB, Santa Barbara, CA). A periodic acid-Schiff post-stain was applied without hematoxylin counterstain. The tool uses a combination of stain deconvolution, digital image processing, and feature engineering to compute histologic podometrics6 with correction for section thickness7. In this study, PodoCount was used to assess mean glomerular podocyte count per mouse.“

(2) In the abstract, the authors give the impression that they know definitively the sequence of HIV gene expression, cytoskeletal dysregulation, dedifferentiation, then loss from glomeruli. Since they could only examine cells that were present in glomeruli, they can't definitively say much about the cells that were lost from glomeruli.

As suggested, deleted the following text: “and were lost from glomeruli tuft”

(3) The authors state that 56,976 cells were used for snRNAseq studies. Was the number of cells similar for each of the 8 mice (from 4 different groups)?

In response, we have created a new table summarizing numbers of nuclei from each sample (i.e. each mouse) added to the Supplemental Figure 2D as follows:

Author response table 1.

Pre-processing of single-nuclear RNA-seq data, Breakdown of nuclei numbers from each sample showed comparable numbers of nuclei analyzed.

(4) Please provide information on the assay that was used to measure creatinine since some methods can be unreliable in mice

This is now provided in the revised submission, including creatinine measurement methods (LC-MS/MS) on page 3 of Supplementary Material:

“Mouse chemistry measurements

Plasma creatinine was measured by isotope dilution LC-MS/MS at The University of Alabama at Birmingham O’Brien Center Core C (Birmingham, AL).”

(5) The authors state that expression of PKR (Eif2ak2) was expressed in all nephron segments. However, it appears on visual inspection of the UMAP in Fig S2B that the percentage of cells expressing Eif2ak2 was low. What percent of cells expressed Eif2ak2 and if it was a low percentage, what is the authors hypothesis for how expression in a small percentage of cells led to the kidney phenotype?

Supplemental Figure 2B (now 3B) does show modest expression of Eif2ak2, approximately 10%. The technique may lack sensitivity to detect low gene expression and even low gene expression may be sufficient to cause phenotypic change.

(6a) In figure 4B and C, it is not clear what genotype/treatment group is shown.

The legend for figure 4B, 4C has been modified to state that the group was wildtype mice

(B, C) In situ hybridization of mt-Co1 and mt-Atp6 genes showed signals inside nuclei of WT mice

(6b) Also, if these ISH images are from Tg26 mice, it would be helpful to do ISH in mice with/without C16 treatment.

These images of ISH for these two genes are from wild-type mice, as now stated in the revised legend. Our purpose was to show that these mitochondrial-encoded gene transcripts (mt-Co1 and mt-Atp6) are transported to nuclei from the cytoplasm. We believe it is not necessary to do ISH in Tg26 mice because these genes are not disease-specific.

(6c) Also, only 3-6% of cells express these "PT-mito" markers by snRNAseq, but it appears that far more are expressed by ISH, raising concerns for nonspecific binding of the ISH probe.

(6d) Also, nonsense controls should be included to demonstrate the specificity of the ISH data.

First (comment 6c), the PT-mito cluster does not have specific markers, to our knowledge. Second (comment 6d) , to address the concern for non-specific binding of the ISH probes, we have now added additional ISH images, together with a negative control probe (C. elegans gene dapB) and a positive control probe (mouse Ppib), as shown in Supplementary Figure 5A and 5B, respectively.

Author response image 4.

Additional in situ hybridization images. (A) In situ hybridization images probing dapB (negative control probe) showed no signals. (B) In situ hybridization images probing Ppib (positive control probe) showed strong signals.

(7) The authors state that "mitochondrial dysfunction was most pronounced in the PT-Mito cluster" but in Figure 4D, the oxidative phosphorylation activation Z score was most down in the PT-inj (injured PT cells) and the PT-Mito cells were the 4-most downregulated cell type.

We appreciate the careful reading and agree with reviewer’s comment. In the revision, we have deleted “most” from this description.

(8) In Fig 4F, please state what "Cp expression" means.

We have spelled out ceruloplasmin (Cp).

(9) It is not clear in immunohistochemistry images in Fig 5F where the p-stat3 was detected due to the hematoxylin counterstain which may have obscured subtle nuclear staining. Also, some of the strongest staining appears to be in peritubular capillaries, instead of tubular and glomerular epithelial cells.

We have added arrows to help readers see where we show that p-Stat3 was detected as faintly-brown and distinct cytoplasmic granules in injured tubular cells in Tg26 mice (panel F), as opposed to diffuse in tubular cytoplasmic color in wild-type mice (panel E).

Author response image 5.

(10) For the studies of mitochondrial oxygen consumption (Fig 6), it would be helpful to also provide data on the effect of C16 in wild-type kidneys, in case C16 somehow causes a primary increase in mitochondrial oxygen consumption rather than preventing HIV-induced loss in kidney cells from HIV-transgenic mice.

We did not include Seahorse data regarding oxygen consumption from WT mice treated with C16, as C16 did not affect either renal function or transcriptomes in WT mice, in contrast to the Tg26 mice (Figure 1A-G).

(11) The authors emphasize that podocytes had the highest expression of HIV genes (Fig 7). However, it appears that <2% of podocytes expressed HIV genes. How do the authors explain the severe renal phenotype given the relatively small number of cells expressing the HIV transgene? Also, did the same cells express all/most of the HIV transcripts, or did some cells express some HIV transcripts? For instance, since the authors state that vpr and nef have the most important role in kidney injury, were the same cells that expressed nef also expressing Vpr?

We know that snRNA-seq cannot detect the whole transcriptome in each cell, due to the well-known drop-out effect characteristic of the method. Several factors may contribute to this drop-out effect, including stochastic patterns of gene expression, low RNA amounts and inefficient mRNA capture (Qiu, Nature Comm, 2020; Ran, Bioinformatics, 2020).

Our interpretation is that HIV gene expressing-podocytes had higher expression of HIV genes, but it does not mean that other kidney cells entirely lack HIV gene expression. With regard to co-expression of other HIV transcripts, nef and vpr were more often coexpressed as shown in Figure 7J. Vpr was expressed in nef-positive podocytes and not detected in nef-negative podocytes.

(12) In figure 8, the authors emphasize the dysregulation of genes involved in cell-cell interaction, particularly PDGF-D. They show some data for the effect of C16 in this system in Fig 8 but it would be helpful if they can state the effect in the text of the Results section.

We have added text in the Results describing activating interactions in Tg26 mice, that were reduced by C16 exposure, as follows: (page 18)

“For example, platelet derived growth factor D (PDGF-D) was upregulated in PT-Inj in Tg26 mice and was downregulated by C16 treatment (Figure 8D). Further, PDGF-D may interact with PDGFR-B in fibroblasts.”

eLife assessment

This study presents valuable new insights into a HIV-associated nephropathy (HIVAN) kidney phenotype in the Tg26 transgenic mouse model, and delineates the kidney cell types that express HIV genes and are injured in these HIV-transgenic mice. A series of compelling experiments demonstrated that PKR inhibition can ameliorate HIVAN with reversal of mitochondrial dysfunction (mainly confined to endothelial cells), a prominent feature shared in other kidney diseases. The data support that inhibition of PKR and mitochondrial dysfunction has potential clinical significance for HIVAN.

Reviewer #1 (Public Review):

Summary:

HIV associated nephropathy (HIVAN) is a rapidly progressing form of kidney disease that manifests secondary to untreated HIV infection, and is predominantly seen in individuals of African descent. Tg26 mice carrying an HIV transgene lacking gag and pol exhibit high levels of albuminuria and rapid decline in renal function that recapitulates many features of HIVAN in humans. HIVAN is seen predominantly in individuals carrying two copies of missense variants in the APOL1 gene, and the authors have previously shown that APOL1 risk variant mRNA induces activity of the double strand RNA sensor kinase PKR. Because of the tight association between the APOL1 risk genotype and HIVAN, the authors hypothesized that PKR activation may mediate the renal injury in Tg26 mice, and tested this hypothesis by treating mice with a commonly used PKR inhibitory compound called C16. Treatment with C16 substantially attenuated renal damage in the Tg26 model as measured by urinary albumin/creatinine ratio, urinary NGAL/creatinine ratio and improvement in histology. The authors then performed bulk and single-nucleus RNAseq on kidneys from mice from different treatment groups to identify pathways and patterns of cell injury associated with HIV transgene expression as well as to determine the mechanistic basis for the effect of C16 treatment. They show that proximal tubule nuclei from Tg26 mice appear to have more mitochondrial transcripts which was reversed by C16 treatment and suggest that this may provide evidence of mitochondrial dysfunction in this model. They explore this hypothesis by showing there is a decrease in the expression of nuclear encoded genes and proteins involved in oxidative phosphorylation as well as a decrease in respiratory capacity via functional assessment of respiration in tubule and glomerular preparations from these mouse kidneys. All of these changes were reversed by C16 treatment. The authors propose the existence of a novel injured proximal tubule cell-type characterized by the leak of mitochondrial transcripts into the nucleus (PT-Mito). Analysis of HIV transgene expression showed high level expression in podocytes, consistent with the pronounced albuminuria that characterizes this model and HIVAN, but transcripts were also detected in tubular and endothelial cells. Because of the absence of mitochondrial transcripts in the podocytes, the authors speculate that glomerular mitochondrial dysfunction in this model is driven by damage to glomerular endothelial cells.

Strengths:

The strengths of this study include the comprehensive transcriptional analysis of the Tg26 model, including an evaluation of HIV transgene expression, which has not been previously reported. This data highlights that HIV transcripts are expressed in a subset of podocytes, consistent with the highly proteinuric disease seen in mouse and humans. However, transcripts were also seen in other tubular cells, notably intercalated cells, principal cells and injured proximal tubule cells. Though the podocyte expression makes sense, the relevance of the tubular expression to human disease is still an open question.

The data in support of mitochondrial dysfunction are also robust and rely on combined evidence from downregulation of transcripts involved in oxidative phosphorylation, decreases in complex I and II as determined by immunoblot, and assessments of respiratory capacity in tubular and glomerular preparations. These data are largely consistent with other preclinical renal injury model reported in the literature as well as previous, less thorough assessments in the Tg26 model.

Weaknesses:

The key weakness of the study lies in the use of a PKR inhibitor with questionable specificity. C16 has been reported to inhibit numerous other kinases including cyclin CDKs and GSK3α and -β, and this means that the conclusions of this study with respect to the role of PKR are highly questionable. The rationale for the dose used was not provided (and is lower than used in other publications with C16), and in the absence of drug exposure data and assessment of target engagement, it is difficult to ascertain whether substantial inhibition of PKR was achieved.

A second key weakness lies in the identification of the PT-Mito cell cluster. Though the authors provide some rationale for the identification of this specific cell type, it seems equally plausible the cells merely reflect a high background capture of mitochondria in a subset of droplets. The IHC analysis that was provided is not convincing enough to support the claim and more careful high resolution imaging and in situ hybridization (with appropriate quantitation) will be needed to provide substantive support for the presence of a proximal tubule cell type with mitochondrial transcript that are trafficked to the nucleus.

Revision summary:

The authors have revised the manuscript to acknowledge the potential limitations of the C16 tool compound used and have performed some additional analyses that suggest the PT-Mito population can be identified in samples from KPMP. The authors added some control images for the in situ hybridizations, which are helpful, though they don't get to the core issue of limited resolution to determine whether mitochondrial RNA is present in the nuclei of injured PT cells. Some additional work has been done to show that C16 treatment results in a decrease in phospho-PKR, a readout of PKR inhibition. These changes strengthen the manuscript by providing some evidence for the translatability of the PT-mito cluster to humans and some evidence for on-target activity for C16. It would be helpful if the authors could quantify the numbers of cells in IHC with nuclear transcripts as well as pointing out some specific examples in the images provided, as comparator data for the snRNAseq studies in which 3-6% of cortex cells had evidence of nuclear mitochondrial transcripts.

Reviewer #2 (Public Review):

Summary:

Numerous studies by the authors and other groups have demonstrated an important role for HIV gene expression kidney cells in promoting progressive chronic kidney disease, especially HIV associated nephropathy. The authors had previously demonstrated a role for protein kinase R (PKR) in a non-HIV transgenic model of kidney disease (Okamoto, Commun Bio, 2021). In this study, the authors used innovative techniques including bulk and single nuclear RNAseq to demonstrate that mice expressing a replication-incompetent HIV transgene have prominent dysregulation of mitochondrial gene expression and activation of PKR and that treatment of these mice with a small molecule PKR inhibitor ameliorated the kidney disease phenotype in HIV-transgenic mice. They also identified STAT3 as a key upstream regulator of kidney injury in this model, which is consistent with previously published studies. Other important advances include identifying the kidney cell types that express the HIV transgene and have dysregulation of cellular pathways.

Strengths:

Major strengths of the study include the use of a wide variety of state-of-the-art molecular techniques to generate important new data on the pathogenesis of kidney injury in this commonly used model of kidney disease and the identification of PKR as a potential druggable target for the treatment of HIV-induced kidney disease. The authors also identify a potential novel cell type within the kidney characterized by high expression of mitochondrial genes.

Weaknesses:

Though the HIV-transgenic model used in these studies results in a phenotype that is very similar to HIV-associated nephropathy in humans, the model has several limitations that may prevent direct translation to human disease, including the fact that mice lack several genetic factors that are important contributors to HIV and kidney pathogenesis in humans. Additional studies are therefore needed to confirm these findings in human kidney disease.

Author response:

We extend our sincere gratitude to the editor and three reviewers for their invaluable feedback, which not only included positive comments but also provided constructive suggestions for enhancing the quality of our manuscript.

Of potential interest to you is our forthcoming investigation into vaccine efficacy, where we will compare the effectiveness of our live-attenuated vaccine with an mRNA-based alternative.

Moreover, we acknowledge and fully endorse the recommendation to elucidate why immunization with our live-attenuated vaccine confers protection against viral challenge, even in the absence of sufficient neutralizing antibodies. As pointed out by the reviewers, this phenomenon may be attributed to mucosal immunity. Consequently, we have outlined plans to investigate whether the attenuated live vaccine elicits mucosal immunity as part of our ongoing research.

We are currently working to gather the necessary data to address these inquiries comprehensively, and are aiming to resubmit our manuscript at the earliest opportunity.

Reviewer #1: We sincerely appreciate the insightful comments provided by Reviewer #1. In response to this feedback, we will conduct a comparative analysis of efficacy between our live-attenuated vaccine and an mRNA-based alternative. Furthermore, we will thoroughly examine and delineate the advantages and limitations of this/our live-attenuated vaccine in our discussion.

Reviewer #2: We express our sincere appreciation to Reviewer #2 for invaluable suggestions. In light of the insightful observation concerning the weakness of our study, related to the poor assessment/evaluation of the induction of mucosal immunity by our vaccine candidate, we have resolved to undertake a comprehensive analysis in this regard.

Furthermore, we will take into account this reviewer's recommendation to compare BK2102 results with those of an mRNA vaccine. We are currently in the process of planning additional experiments to thoroughly address this aspect.

Reviewer #3: We are very grateful to Reviewer #3 for the positive feedback and invaluable suggestions. In order to further explore the immune mechanisms underlying the protection against the Omicron variant in the absence of detectable neutralizing antibodies, we are currently devising plans for experiments focused on evaluating mucosal immunity.

Moreover, in accordance with Reviewer #3's suggestion, we are considering the incorporation of an ELISPOT assay experiment. However, we acknowledge uncertainties regarding the feasibility of establishing an experimental system for this purpose.

eLife assessment

This is a valuable study on the efficacy of a live attenuated vaccine that was tested in different animal models. The evidence is convincing, but it could be further strengthened by comparing the efficacy of their platform with an mRNA vaccine and further investigating mucosal protection.

Reviewer #1 (Public Review):

Summary:

The authors constructed a live-attenuated vaccine candidate, BK2102, combining naturally occurring virulence-attenuating mutations in the key coding regions. They showed that intranasal inoculation with the candidate vaccine-induced humoral and cellular immune responses in Syrian hamsters without apparent tissue damage in the lungs and protected against a wild-type SARS-CoV-2 strain with D614G mutation and the latest Omicron subvariant (BA.5) strain. The neutralizing antibodies induced by BK2102 persisted for the long term (up to 364 days). Furthermore, they confirmed the safety of the proposed vaccine using transgenic (Tg) mice expressing human ACE2 (hACE2).

Strengths:

The authors followed a robust methodology to establish the proposed vaccine's protective effect and safety profile in the hamsters and transgenic mice expressing human ACE2.

Weaknesses:

(1) A comparative safety assessment of the available m-RNA and live attenuated vaccines will be necessary. The comparison should include details of the doses, neutralizing antibody titers with duration of protection, tissue damage in the various organs, and other risks, including virulence reversal.

(2) The vaccine's effect on primates is doubtful. The study fails to explain why only two of four monkeys developed neutralizing antibodies. Information about the vaccine's testing in monkeys is also missing: What was the level of protection and duration of the persistence of neutralizing antibodies in monkeys? Were the tissue damages and other risks assessed?

(3) The vaccine's safety in immunosuppressed individuals or individuals with chronic diseases should be assessed. Authors should make specific comments on this aspect.

(4) The candidate vaccine has been tested with a limited number of SARS-CoV-2 strains. Of note, the latest Omicron variants have lesser virulence than many early variants, such as the alfa, beta, and delta strains.

(5) Limitations of the study have not been discussed.

Reviewer #2 (Public Review):

Summary:

In this manuscript "Immunogenicity and safety of a live-attenuated SARS-CoV-2 vaccine candidate based on multiple attenuation mechanisms" by Suzuki-Okutani et al., the authors evaluate the attenuation, immunogenicity, and protection efficacy of a live-attenuated SARS-CoV-2 vaccine candidate (BK2102) against SARS-CoV-2.

Strengths:

The authors demonstrate that intranasal inoculation of BK2102 is safe and able to induce humoral and cellular immune responses in hamsters, without apparent signs of damage in the lungs, that protects against homologous SARS-CoV-2 and Omicron BA.5 challenge. Safety of BK2102 was further confirmed in a new hACE2 transgenic mouse model generated by the authors.

Weaknesses:

No major weaknesses were identified, however, this reviewer notes the following:

The authors missed the opportunity to include a mRNA vaccine to demonstrate that the immunity and protection efficacy of their live attenuated vaccine BK2102 is better than a mRNA vaccine.

One of the potential advantages of live-attenuated vaccines is their ability to induce mucosal immunity. It would be great if the authors included experiments to assess the mucosal immunity of their live-attenuated vaccine BK2102.

Reviewer #3 (Public Review):

Summary:

Suzuki-Okutani and collogues reported a new live-attenuated SARS-CoV-2 vaccine (BK2102) containing multiple deletion/substitution mutations. They show that the vaccine candidate is highly attenuated and demonstrates a great safety profile in multiple animal models (hamsters and Tg-Mice). Importantly, their data show that single intranasal immunization with BK2102 leads to strong protection of hamsters against D614G and BA.5 challenge in both lungs and URT (nasal wash). Both humoral and cellular responses were induced, and neutralization activity remained for >360 after a single inoculation.

Strengths:

The manuscript describes a comprehensive study that evaluates the safety, immunogenicity, and efficacy of a new live-attenuated vaccine. Strengths of the study include (1) strong protection against immune evasive variant BA.5 in both lungs and NW; (2) durability of immunity for >360 days; (3) confirmation of URT protection through a transmission experiment.

While first-generation COVID-19 vaccines have achieved much success, new vaccines that provide mucosal and durable protection remain needed. Thus, the study is significant.

Weaknesses:

Lack of a more detailed discussion of this new vaccine approach in the context of reported live-attenuated SARS-CoV-2 vaccines in terms of its advantages and/or weaknesses.

Antibody endpoint titers could be presented.

Lack of elaboration on immune mechanisms of protection at the upper respiratory tract (URT) against an immune evasive variant in the absence of detectable neutralizing antibodies.

eLife assessment

This important study indicates a significant role for individual let-7 miRNA clusters in regulating generation of Tc17 CD8 cells and emphysema severity in a mouse model. The authors provide convincing evidence for let-7-mediated repression of the transcription factor RORgt and consequent modulation of IL-17-producing CD8 T cells, with correlated data from human emphysema material, though some of the effective let-7 clusters remain to be tested for the ability to modulate disease. The findings, which substantially advance the understanding of roles that let-7 miRNA clusters play in modulating both T cell responses and emphysematous lung disease, will be of interest to T cell and lung disease researchers.

Author response:

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

We would like to thank the editors and reviewers for providing feedback and suggestions for our manuscript.

In response to reviewers comments we changed several main Figures and added new tables and supplementary figures. We also made edits to the Discussion.

Reviewer #1 (Public Review):

Weaknesses:

Limited data is shown on the let-7afdLOF mice. Does this mouse respond similarly to nCB as the let-7bc2LOF.

In the revised manuscript, we have added a baseline lung phenotypic assessment for the let-7afdLOF mice up to 6-months of age within Figure 4-figure supplement 1. The data supports our original statement and observation that let-7afdLOF mice do not exhibit lung pathology, inflammation, or changes in T cell subsets at baseline. Our view is that current manuscript addresses the importance of let-7bc2-cluster in experimental emphysema and the let-7afd-cluster mice is used to validate Rorc as a direct target of let-7. In the future, new grant funding will make it possible to ascertain whether absence of the let-7afd-cluster also sensitizes mice to experimentally induced emphysema.

Because the authors validate their findings from a previously published RNA-seq dataset in subjects with and without emphysema, the authors should include patient demographics from the data presented in Figure 1C-D.

We thank the reviewers for their recommendation. In address of this, the revised manuscript contains a new Supplementary Table 1 with the human subject demographic information that corresponds with Figure 1D.

To validate their mouse models, the absence of Let-7 or enhanced Let-7 expression needs to be shown in isolated T cells from exposed mice.

In the case of let-7bc2-cluster, we have included Figure 2-figure supplement 2 which shows pri-let7bc2 expression assessed by qPCR from selected CD8+ lung T cells of control and let-7bc2LOF mice exposed to PBS vehicle or nCB. The let-7g GOF model used in our studies has been validated for the induction of let-7g in thymic and peripheral T cells and elicitation of gain-of-function phenotypes (Pobezinskaya et al. 2019; Angelou et al. 2020; Wells et al. 2023).

In Figure 3, the authors are missing the unexposed let-7bc2LOF group from all panels.

We emphasize that our exhaustive characterization of control and let-7bc2LOF mice in absence of challenge showed no phenotype. The baseline data was collectively shown in Figure 2-figure supplement 1.

Why did the authors choose to overexpress Let-7g, the rational is not clear?

We concur that ideal GOF experiments can be carried out with let-7b or let-7c. Unfortunately, let-7b/c2 transgenic mice are not currently available, so we elected to use the well characterized let-7g T cell GOF mouse model (Pobezinskaya et al. 2019; Angelou et al. 2020; Wells et al. 2023). Furthermore, it is worth noting that the binding/seed sequence of let-7g is identical to let-7a/b/c and other members. Nonetheless, we have edited our Discussion section to reflect this as a potential caveat that can confound the utilization of this let-7GOF mouse model.

The purity of the CD4+ and CD8+ T cells is not shown and the full gating strategy should be included.

In the revision, we included the flow gating strategy and display the representative population with purities in Supplementary Figure 1 of the revised manuscript.

Reviewer #2 (Public Review):

Weaknesses:

The functional analyses are unusually focused on IL-17 producing CD8 T cells, but it is not made clear whether these cells are an important player in emphysema pathogenesis in the nCB and CS models. The data shown reveal that they are far less numerous than IL-17-producing CD4 T cells. It is also notable that the Figure 1 expression data from human subjects used sorted CD4+ T cells. And as the author mentioned, prior work on let-7 showed that it regulated Th17 (CD4) responses.

As we showed that the let-7bc2LOF had enhanced the Tc17 cell population without any significant impact on Th17 cells, we elected to focus our analysis on this population. Furthermore, the connection of let-7 with the generation of a Tc17 inflammatory response is a novel finding, which so far remained unappreciated in the field and instigates new lines of inquiry.

Compared with Let7bc2 deletion, Let7afd deletion had a much larger effect on IL17 production by CD8 T cells in vitro, and it also had a larger effect on RORgt expression in untreated mice in vivo, especially in the lung. It would be valuable to more thoroughly characterize the let7afd mice. RORgt expression should be shown in the in vitro assays. In the results, the authors state that let7afdLOF mice "did not exhibit lung histopathology nor inflammatory changes" up to 6 months of age. Similarly, it is stated in the conclusion that "the let-7afdLOF mice ... did not exhibit changes in Tc17/Th17 subpopulations" in vivo. All these data should be shown, and if no baseline changes are apparent, then I also recommend challenging these mice with nCB and/or cigarette smoke.

We concur that additional phenotypic characterization on the let-7afdLOF mice will contribute valuable information in the future. Reviewer 1 had a similar comment. As described above in response to Reviewer 1, we added comprehensive phenotypic analysis of let-7afdLOF mice within Figure 4-figure supplement 1 in the revised manuscript. The new data indicates that there is no overt lung pathology in the let-7afdLOF mice despite the subtle induction of RORγt expression in T cells. Furthermore, we have now included flow cytometric analysis of RORγt expression from in vitro polarized Tc0 and Tc17 cells from let-7afdLOF mice within revised Figure 5H.

This brings up the larger issue of redundancy among the let-7 family members and genomic clusters. This should be discussed, including some explanation of the relative expression of each mature family member in T cells, and how that maps to the clusters studied here (and those that were not investigated). It would also be helpful to explain the relationship between mouse Let7bc2 and human Let7a3b, since Let7bc2 is the primary focus of emphysema experiments in this manuscript. This is especially important because the study of individual let-7 clusters is the core novelty of this body of work, as described in the first paragraph of the discussion. The regulation of let-7 expression has been reported before and its functional role has been investigated with a variety of tools.

We appreciate the interest and suggestion to expand the discussion on the let-7 family and their expression regulation. To address these points, we included additional references and expanded the Discussion section of the revised manuscript.

Let7g overexpression caused a marked reduction in Rorgt expression in T cells at baseline and in the setting of nCB challenge, and it reduced the frequency of IL17+ producing CD8 T cells in the lung to baseline levels. Yet there was no change in the MLI measurement of histopathology. Is this a robust result? The responses in the experiment shown in Fig. 6C-D are quite muted compared to those shown in Figure 2. The latter also shows a larger number of replicates, and it is unclear whether the data in 6D include measurement from all of the mice tested (e.g. pooled from 2 small experiments) or only mice from one experiment.

We appreciate the reviewer inquiry into the data presented in Figure 6C-D. The data is representative of a single experiment and the number of experiments has been added to the revised Figure 6 legend. We note that all let-7GOF and associated control mice in Figure 6 are exposed to doxycycline as part of the let7g induction model, whereas mice in Figure 2 are not. It has been previously reported that doxycycline, a member of the tetracycline family of molecules, has anti-inflammatory properties (Di Caprio et al. 2015), which we speculate could account for the differences in the magnitude of emphysemic response.

Reviewer #3 (Public Review):

Weaknesses:

The authors show no change in frequencies of Treg cells in let-7bc2LOF mice exposed to nCB. Do these Treg cells also express higher levels of RORgt and IL-17? The major question that was not addressed in this study is how let-7 expression is regulated in emphysema. The other recommendation is that the authors include the sequences of the let-7 mimic oligos used in the luciferase assay.

We did not have the opportunity to address whether RORγt is in fact also upregulated in Treg cells. It remains unclear what upstream mechanisms drive the downregulation of the let-7 clusters in T cells with exposure to smoke/nCB. However, we agree that this an important question and we therefore updated the Discussion section of manuscript by including several citations that could explain how let-7 clusters become repressed in a coordinated fashion. Regarding the last point, the sequence of the duplex used in luciferase assay corresponds to the canonical mature let-7b in NCBI and has been added to Supplementary Table 3.

Reviewer #2 (Recommendations For The Authors):

The authors state that "Recent evidence suggests the let-7 family is downregulated in patients with COPD, however, how they cause emphysema remains unclear." This should be reworded. Its downregulation in disease does not necessarily indicate that let-7 causes emphysema. Also, recommend rewording "Overall, our findings shed light on the let-7/RORγt axis as a braking and driving regulatory circuit in the generation of Tc17 cells..." What does it mean to be a "braking and driving" circuit? These terms seem contradictory.

We recognize that the sentences were not phrased clearly. We have rephrased these statements as “Recent evidence suggests the let-7 miRNA family is downregulated in patients with COPD, however, whether this repression conveys a functional consequence in emphysema pathology has not been elucidated.” and “Overall, our findings shed light on the let-7/RORγt axis with let-7 acting as a molecular brake in the generation of Tc17 cells…”

Experimental details are needed for the human miRNA expression studies. Too little information is provided in the methods section, and the article cited there (Yuan et al 2020) is not listed in the bibliography.

We expanded the Materials and Methods section for the collection, isolation, and qPCR analysis of human subject lung T cells. We have corrected the bibliography and added the missing citation.

The claim of novelty for miRNA-mediated silencing of Rorc in the discussion section is unnecessary and incorrect (https://pubmed.ncbi.nlm.nih.gov/23359619).

Thank you for bringing the publication to our attention. Close inspection of this publication indicates that the authors did not experimentally validate Rorc as a direct target of let-7 itself. Plus the work was limited to immortalized in vitro cell cultures. We amended the sentence in the Discussion section highlighting the novelty of our findings which is the demonstration of Rorc as an in vivo target of let-7 in T cells.

Citations

Angelou, Constance C., Alexandria C. Wells, Jyothi Vijayaraghavan, Carey E. Dougan, Rebecca Lawlor, Elizabeth Iverson, Vanja Lazarevic, et al. 2020. “Differentiation of Pathogenic Th17 Cells Is Negatively Regulated by Let-7 MicroRNAs in a Mouse Model of Multiple Sclerosis.” Frontiers in Immunology 10: 3125. https://doi.org/10.3389/fimmu.2019.03125.

Di Caprio, Roberta, Serena Lembo, Luisa Di Costanzo, Anna Balato, and Giuseppe Monfrecola. 2015. “Anti-Inflammatory Properties of Low and High Doxycycline Doses: An in Vitro Study.” Mediators of Inflammation 2015: 329418. https://doi.org/10.1155/2015/329418.

Pobezinskaya, Elena L., Alexandria C. Wells, Constance C. Angelou, Eric Fagerberg, Esengul Aral, Elizabeth Iverson, Motoko Y. Kimura, and Leonid A. Pobezinsky. 2019. “Survival of Naïve T Cells Requires the Expression of Let-7 miRNAs.” Frontiers in Immunology 10 (May). https://doi.org/10.3389/fimmu.2019.00955.

Wells, Alexandria C., Kaito A. Hioki, Constance C. Angelou, Adam C. Lynch, Xueting Liang, Daniel J. Ryan, Iris Thesmar, et al. 2023. “Let-7 Enhances Murine Anti-Tumor CD8 T Cell Responses by Promoting Memory and Antagonizing Terminal Differentiation.” Nature Communications 14 (1): 5585. https://doi.org/10.1038/s41467-023-40959-7.

Reviewer #1 (Public Review):

Summary:

Inflammatory T cells have been recognized to play an important role in human COPD lung tissue and animal models of emphysema. The authors have previously identified that Th17 cells regulate chronic inflammatory diseases, including in mice exposed to smoke or nanoparticulate carbon black (nCB). Here, the authors interrogate the role of Tc17 cells using similar mouse models. Investigating let-7 miRNA, which induces antigen-presenting cell activation and T cell-mediated Th17a inflammation, they show that the master regulator of Tc17/Th17 differentiation, RAR-related orphan receptor gamma t (RORγt), is a direct target of let-7 miRNA in T cells. Because RORγt expression is elevated in COPD patients and in mouse models of COPD, the authors generate a Let-7 overexpressing mouse in T cells and reduce RORγt expression and Th17 and Tc17 cell recruitment in nCB-exposed mice.

Strengths:

The authors use a previously published RNA-seq dataset (GSE57148) from lungs of control and COPD subjects to explore the involvement of Let-7 in emphysema. They further evaluate Let-7a expression by qPCR in lung tissue samples of smokers with emphysema and non-emphysema controls. Moreover, expression of Let-7a, Let-7b, Let-7d, and Let-7f in purified CD4+ T cells were inversely correlated with emphysema severity lungs. Similar findings were found in their mouse models (CS or nCB) in both lung tissue and isolated lung CD4+ and CD8+ T cells, with reduced let-7afd and let-7bc2 expression.

Using mice harboring a conditional deletion of the let-7bc2 cluster in all T cells (let-7bc2LOF) derived from the CD4+CD8+ double-positive stage, the authors show enhanced emphysema in nCB- or CS-exposed mice with enhanced recruitment of macrophages and neutrophils to the lung. While CD8+IL17a+ Tc17 cells and CD4+ IL17a+ Th17 cells were increased in nCB-exposed control animals, only let-7bc2LOF mice showed an increase in CD8+IL17a+ Tc17 cells. Further, unexposed let-7bc2LOF and let-7afdLOF mice expressed greater RORγt expression in both CD8+ and CD4+ T cells.

Generating a let-7 gain of function mouse with overexpression of let-7g in thymic double-positive-derived T cells, protein levels of RORγt were suppressed in CD8+ and CD4+ T cells of let-7GOF mice relative to controls. Let-7GOF mice treated with nCB showed similar lung alveolar distension as controls suggesting that increased let-7 expression does not protect the lung from emphysema. However, let-7GOF mice showed reduced lung Tc17 and Th17 cell populations and were resistant to the induction of RORγt after nCB exposure.

Weaknesses:

Limited data is shown on the let-7afdLOF mice. Does this mouse respond similarly to nCB as the let-7bc2LOF.<br /> Because the authors validate their findings from a previously published RNA-seq dataset in subjects with and without emphysema, the authors should include patient demographics from the data presented in Figure 1C-D.<br /> To validate their mouse models, the absence of Let-7 or enhanced Let-7 expression needs to be shown in isolated T cells from exposed mice.<br /> In Figure 3, the authors are missing the unexposed let-7bc2LOF group from all panels. This is again an issue in Figure 6 with the let-7GOF.<br /> Because the GOF mouse enhances Let-7g within T cells, the importance of Let-7g should be determined in human subjects. Why did the authors choose to overexpress Let-7g, the rationale is not clear.<br /> The purity of the CD4+ and CD8+ T cells is not shown and the full gating strategy should be included.<br /> The authors indicate that Tc17 and Th17 T cells were reduced in the GOF mouse, it remains unclear if macrophage or neutrophil recruitment is altered in GOF mice.

Reviewer #2 (Public Review):

Summary:

This valuable study characterizes the requirement for individual let-7 clusters to limit the generation of IL-17 producing CD8 T cells and the severity of emphysema in mouse models. Mature let-7 family miRNAs originate from multiple loci, several of which have been reported and/or are reported here to be downregulated in emphysematous lung tissue and/or lung T cells. The results provided are convincing but incomplete, as the let-7 cluster with the most convincing effects on T cell cytokine production is not tested for effects on disease pathogenesis.

Let-7 family miRNAs are largely redundant in function and originate from multiple genomic loci ("clusters"). Erice et al demonstrate that two individual clusters (let7afd and let7bc2) in mice regulate the generation of IL-17 producing CD8 T cells in vitro and in vivo in a model of emphysema. These cells also express higher levels of the IL-17-inducing transcription factor RORgt, encoded by Rorc, which the authors demonstrate to be a direct target of let-7. Since multiple let-7 family miRNAs are downregulated in T cells and lung tissue in emphysema, these data support a model in which reduced let-7 allows increased IL-17 production by T cells, contributing to disease pathogenesis.

Strengths:

The inclusion of miRNA and pri-miRNA expression data from sorted human lung T cells as well as mouse T cells from an emphysema model is a strength.

The study includes complementary loss of function and gain of function experimental systems to test the effect of altered let-7 function, though it should be noted that these involved different let-7 family members and did not yield simple, complementary results for all experimental outcomes.

The most important finding is that deletion of just one let-7 cluster ("Let7bc2") is sufficient to exacerbate emphysema in the nCB and CS models.

Weaknesses:

The human miRNA expression data that motivate functional analyses used sorted CD4+ T cells. The authors note that prior work on let-7 showed that it regulates Th17 (CD4) responses, yet this study's functional analyses are all focused on Tc17 (CD8) T cells. Data in this paper show that Tc17 cells are far less numerous than Th17 cells in the nCB and CS models of emphysema.

Compared with Let7bc2 deletion, Let7afd deletion had a much larger effect on IL17 production by CD8 T cells in vitro, and it also had a larger effect on RORgt expression in untreated mice in vivo, especially in the lung. In the revised manuscript, the authors show that let7afdLOF mice have normal numbers of CD4 and CD8 T cells in the thymus and peripheral lymphoid organs and do not exhibit lung histopathology or inflammatory changes at baseline at least up to 6 months of age. As such, they are set up perfectly to test the requirement for Let7afd in the nCB and/or CS models. These experiments would add strength to the core novelty of this work - demonstration of the functional importance of individual let-7 clusters.

The authors could do more to explain the complexity of the let7 miRNA family and the genomic clusters examined in this study. In particular, it would help to know the relationship between mouse Let7bc2 and corresponding human Let7 clusters. It would also be very helpful to know the relative expression of each mature let-7 family member in Tc17 cells. Are mature miRNAs derived from the Let7afd cluster more or less abundant?

The provided evidence for the effect of Let7GOF has an important caveat that came to light during review. Let7g overexpression caused a marked reduction in Rorgt expression in T cells at baseline and in the setting of nCB challenge, and it reduced the frequency of IL17+ producing CD8 T cells in the lung to baseline levels. Yet there was no change in the MLI measurement of histopathology. However, the responses in the experiment shown in Fig. 6C-D are quite muted compared to those shown in Figure 2. In the response to reviewers, the authors speculate that an anti-inflammatory of doxycycline, required for induction of Let7g in this model, "could account for the differences in the magnitude of emphysemic response".

Although RORgt is a great candidate to have direct effects on IL-17 expression, the mechanistic understanding of let-7 action on T cell differentiation and cytokine production is limited to this single target. As noted in the discussion, others have identified cytokine receptor targets that may play a role, but it is also likely others among the many targets of let-7 also contribute.

eLife assessment

This important study reports on the genome evolution of a poorly studied fungal group. By combining long-read sequencing and different bioinformatic analyses, the authors show that the giant genome of Entomophthora muscae expanded due to extensive transposable element activity. The strength of evidence is compelling and the authors are to be commended for their multiple comparative analyses of gene content along with transparently written and visualized techniques, data curation, and methods. This paper will be of relevance to fungal biologists as well as to evolutionary biologists interested in the study of genome size dynamics.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The authors present a detailed study of a nearly complete Entomophthora muscae genome assembly and annotation, along with comparative analyses among related and non-related entomopathogenic fungi. The genome is one of the largest fungal genomes sequenced, and the authors document the proliferation and evolution of transposons and the presence/absence of related genetic machinery to explore how this may have occurred. There has also been an expansion in gene number, which appears to contain many "novel" genes unique to E. muscae. Functionally, the authors were interested in CAZymes, proteases, circadian clock related genes (due to entomopathogenicity/ host manipulation), other insect pathogenspecific genes, and secondary metabolites. There are many interesting findings including expansions in trahalases, unique insulinase, and another peptidase, and some evidence for RIP in Entomophthoralean fungi. The authors performed a separate study examining E. muscae species complex and related strains. Specifically, morphological traits were measured for strains and then compared to the 28S+ITSbased phylogeny, showing little informativeness of these morpho characters with high levels of overlap.

This work represents a big leap forward in the genomics of non-Dikarya fungi and large fungal genomes. Most of the gene homologs have been studied in species that diverged hundreds of millions of years ago, and therefore using standard comparative genomic approaches is not trivial and still relatively little is known. This paper provides many new hypotheses and potential avenues of research about fungal genome size expansion, entomopathogenesis in zygomycetes, and cellular functions like RIP and circadian mechanisms.

Strengths:

There are many strengths to this study. It represents a massive amount of work and a very thorough functional analysis of the gene content in these fungi (which are largely unsequenced and definitely understudied). Too often comparative genomic work will focus on one aspect and leave the reader wondering about all the other ways genome(s) are unique or different from others. This study really dove in and explored the relevant aspects of the E. muscae genome.

The authors used both a priori and emergent properties to shape their analyses (by searching for specific genes of interest and by analyzing genes underrepresented, expanded, or unique to their chosen taxa), enabling a detailed review of the genomic architecture and content. Specifically, I'm impressed by the analysis of missing genes (pFAMs) in E. muscae, none of which are enriched in relatives, suggesting this fungus is really different not by gene loss, but by its gene expansions.

Analyzing species-level boundaries and the data underlying those (genetic or morphological) is not something frequently presented in comparative genomic studies, however, here it is a welcome addition as the target species of the study is part of a species complex where morphology can be misleading and genetic data is infrequently collected in conjunction with the morphological data.

Thank you for your careful reading of our work. We’re glad that you identified these areas as strengths.

Weaknesses:

The conclusions of this paper are mostly well supported by data, but a few points should be clarified.

In the analysis of Orthogroups (OGs), the claim in the text is that E. muscae "has genes in multi-species OGs no more frequently than Enotomophaga maimaiga. (Fig. 3F)" I don't see that in 3F. But maybe I'm really missing something.

Thank you for catching this. You were, in fact, not missing anything at all. There was a mismatch between the data plotted in F and G and how the caption described these data. We very much apologize for the confusion that this must have caused. We have corrected these plots and also made changes to improve interpretability (see below).

Also related, based on what is written in the text of the OG section, I think portions of Figure 3G are incorrect/ duplicated. First, a general question, related to the first two portions of the graph. How do "Genes assigned to an OG" and "Genes not assigned to an OG" not equal 100% for each species? The graph as currently visualized does not show that. Then I think the bars in portion 3 "Genes in speciesspecific OG" are wrong (because in the text it says "N. thromboides had just 16.3%" species-specific OGs, but the graph clearly shows that bar at around 50%. I think portion 3 is just a duplicate of the bars in portion 4 - they look exactly the same - and in addition, as stated in the text portion 4 "Potentially speciesspecific genes" should be the simple addition of the bars in portion 2 and portion 3 for each species.

As mentioned above, we sincerely regret the error made in the plot and for the confusion that this caused. F now reflects the percentage of orthogroups (OGs) that possess at least one representative from the indicated species (left) and the percentage of OGs that are species-specific (only possess genes from one species; right). The latter is a subset of the former. G now reflects the percentage of annotated genes that were assigned an OG, per species, as well as the inverse of this - genes that were not assigned to any OG. These should, and now do, sum to 100%. The “Within species-specific OG” data summed with the “Not assigned OG” data yields the “Potentially species-specific data” in the rightmost column.

In the introduction, there is a name for the phenomenon of "clinging to or biting the tops of plants," it's called summit disease. And just for some context for the readers, summit disease is well-documented in many of these taxa in the older literature, but it is often ignored in modern studies - even though it is a fascinating effect seen in many insect hosts, caused by many, many fungi, nematodes (!), etc. This phenomenon has evolved many times. Nice discussions of this in Evans 1989 and Roy et al. 2006 (both of whom cite much of the older literature).

You’re right. We have now clarified that this behavior is called “summit disease” and referenced the suggested articles, along with a more recent review.

Reviewer #2 (Public Review):

In their study, Stajich and co-authors present a new 1.03 Gb genome assembly for an isolate of the fungal insect parasite Entomophthora muscae (Entomophthoromycota phylum, isolated from Drosophila hydei). Many species of the Entomophthoromycota phylum are specialised insect pathogens with relatively large genomes for fungi, with interesting yet largely unexplored biology. The authors compare their new E. muscae assembly to those of other species in the Entomophthorales order and also more generally to other fungi. For that, they first focus on repetitive DNA (transposons) and show that Ty3 LTRs are highly abundant in the E. muscae genome and contribute to ~40% of the species' genome, a feature that is shared by closely related species in the Entomophthorales. Next, the authors describe the major differences in protein content between species in the genus, focusing on functional domains, namely protein families (pfam), carbohydrate-active enzymes, and peptidases. They highlight several protein families that are overrepresented/underrepresented in the E. muscae genome and other

Entomophthorales genomes. The authors also highlight differences in components of the circadian rhythm, which might be relevant to the biology of these insect-infecting fungi. To gain further insights into E. muscae specificities, the authors identify orthologous proteins among four Entomophthorales species. Consistently with a larger genome and protein set in E. muscae, they find that 21% of the 17,111 orthogroups are specific to the species. To finish, the authors examine the consistency between methods for species delineation in the genus using molecular (ITS + 28S) or morphological data (# of nuclei per conidia + conidia size) and highlight major incongruences between the two.

Although most of the methods applied in the frame of this study are appropriate with the scripts made available, I believe there are some major discrepancies in the datasets that are compared which could undermine most of the results/conclusions. More precisely, most of the results are based on the comparison of protein family content between four Entomophthorales species. As the authors mention on page 5, genome (transcriptome) assembly and further annotation procedures can strongly influence gene discovery. Here, the authors re-annotated two assemblies using their own methods and recovered between 30 and 60% more genes than in the original dataset, but if I understand it correctly, they perform all downstream comparative analyses using the original annotations. Given the focus on E. muscae and the small sample size (four genomes compared), I believe performing the comparisons on the newly annotated assemblies would be more rigorous for making any claim on gene family variation.

Thank you for this comment. While we did compare gene model predictions for two of these assemblies to assess if this difference could account for discrepancies in gene counts, completely reannotating all non-E. muscae datasets was outside of the scope of this study. In our opinion, the total number of predicted genes in a genome is not a best representation of differences since splitting or fusing gene models can inflate seeming differences; the orthology and domain counts are a more accurate assessment of the content. It’s possible that annotation differences may have inflated some gene family counts, however we will note that similar domain trends were observed between the closest species to E. muscae, Entomophaga maimaiga, suggesting that these differences were not sufficient to prevent us from detecting real biological signals. We look forward to continued improvement of our genome through additional sequencing and more clarity on total gene content of E. muscae.

The authors also investigate the putative impact of repeat-induced point mutation on the architecture of the large Entomophthorales genomes (for three of the eight species in Figure 1) and report low RIP-like dinucleotide signatures despite the presence of RID1 (a gene involved in the RIP process in Neurospora crassa) and RNAi machinery. They base their analysis on the presence of specific PFAM domains across the proteome of the three Entomophthorales species. In the case of RID1, the authors searched for a DNA methyltransferase domain (PF00145), however other proteins than RID1 bear such functional domain (DNMT family) so that in the current analysis it is impossible to say if the authors are actually looking at RID1 homologs (probably not, RID1 is monophyletic to the Ascomycota I believe). Similar comments apply to the analysis of components of the RNAi machinery. A more reliable alternative to the PFAM analysis would be to work with full protein sequences in addition to the functional domains.

While we understand this concern regarding domain vs. full length protein, the advantage of the domain search is that HMM-based searches are sensitive to detecting more distantly related homologs. Entomophthoralean fungi are distantly related from the ascomycetes in which these mechanisms have been characterized, so we chose a broader search approach that may identify proteins with similar domain structure, but are not necessarily homologs. These searches are presented in the manuscript as preliminary, but worth further investigation. However, our RID-based analysis did not identify convincing homologs for RID1 in entomophthoralean fungi included in our investigation, and we reported low homology (i.e., 12-14%) among our orthogroup of interest and RID1. We have further edited this section to clarify our understanding that these candidates are not RID1 homologs. We had hoped to avoid this implication, but we felt this investigation and null result were worth reporting.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Specific points:

Results:

"1.03 Gb genome consisting of 7,810 contigs (N50 = 301.1 kb). Additional... resulted in a final contig count of 7,810 (N50 = 329.6 kb)" So you started and ended with the same contig count but a different N50? Is this a typo?

Yes, this was a typo. Thank you for bringing this to our attention.

Figure 1D.

The colors of Complete1x and Complete2x are too similar to tell them apart.

The colors have been made more distinct.

Figure 4B.

I know C. rosea has been found from insects before, but it's mostly a mycoparasite and occasionally an endophyte, and has bioactivity against a lot of things. I just saw that it's listed as an entomopathogen, and I was surprised. Anyway, leave it as is if you want to, but it's definitely better studied and better known (Google Scholar) as a mycoparasite.

Thanks for this comment. For the sake of including a more diverse representation of entomopathogenic fungi, we have opted to leave this as is.

Full references (from the public comment)

Evans, H.C., 1989. Mycopathogens of insects of epigeal and aerial habitats. Insect-fungus interactions, pp.205-238.

Roy, H.E., Steinkraus, D.C., Eilenberg, J., Hajek, A.E. and Pell, J.K., 2006. Bizarre interactions and endgames: entomopathogenic fungi and their arthropod hosts. Annu. Rev. Entomol., 51, pp.331-357.

Reviewer #2 (Recommendations For The Authors):

I believe the manuscript could largely benefit from restructuring the results section to enhance clarity. The results section reads like a lot of descriptive back and forth, so that the reader lacks a clear rationale. The absence of a consistent dataset used for the different comparisons made all along the manuscript makes it hard to follow.

Minor comments:

(No line numbers were available so I refer to page numbers).

p1

• not sure about the use of "allied" to describe other fungal species in the title and after (sister species?).

We didn’t want to use the word sister because not all of these species could be considered sister.

• Genomic defence against transposable elements rather than "anti"?

We have rephrased to genomic defense.

p3

• Extra parenthesis at Bronski et al.

This is now corrected.

• What does newly-available mean here?

We mean recent. A lot of the datasets we used were very new, and we wanted to emphasize that point.

• The back and forth between genomes and transcriptomes makes it hard to follow, would clarify from the beginning (in addition to the sequencing method - short vs long-read assemblies as in Figure 1B) or perhaps use a consistent dataset for all subsequent comparative analysis in the Entomophthorales.

We have denoted our transcriptomic datasets in Fig 1C using parentheses.

p5

• Perhaps clarify that class II DNA transposons can also "copy" (single-strand excisions can be repaired by the host machinery).

We have now included mention of “copy” as well as “jump” mechanisms of Class II transposons per your suggestion.

p6

• "beginning roughly concurrently", not clear what "began".

This is now corrected.

• "control" rather than "protect against"?

We’ve changed “protect against” to “counter”.

• I believe RIP has only been observed (experimentally) in a handful of fungal species, all from the Ascomycota phylum.

Hood et al, 2005 found signatures of RIP in anther-smut fungus and Horns et al, 2012, found evidence of hypermutability across repeat elements within several Pucciniales species.

• "RID1 contains two DNA_methylase domains", RID1 has one methyltransferase domain according to the reference Freitag et al, 2002.

Thank you for drawing this to our attention. It is true RID1 has one methyltransferase region; however, the sequence deposited by Freitag et al, 2002 (AAM27408) is predicted by HMMer to have two adjacent Pfam DNA_methylase domains (i.e., PF00145). In this exploratory analysis, we tried to leverage this characteristic to identify candidate proteins of interest. We have reworded this section to clarify this.

p8

• Here and after I would use more informative titles for each paragraph.

With the exception of the headings for Pfam, CAZy and MEROPs analyses, we believe the other headings are informative. We appreciate this comment, but opt to leave the heading titles as is.

• I believe presenting the orthology analysis before the more in-depth protein family domain search.

We leveraged the OG analysis mostly as a way to identify potentially unique genes in E. muscae, so we think the current order makes the most sense.

p10

• Figures 3F and G are confusing. The legend for Figure 3F mentions "OGs with >= 2 species" while the figure shows "multi-species OGs", and reads as redundant with the "species-specific" OGs. For the "OGs within species" do I understand it correctly that it represents the number of genes assigned to OGs for each species? If yes, the numbers are in contradiction with Figure 3G. And in Figure 3G shouldn't the sum of "genes assigned in OGs" and "genes nor assigned in OGs" add up to 100? I'm probably missing something here, but I would clarify what the different sets of orthogroups are in the figure and in the text (perhaps adopting a pangenome-like nomenclature).

Thanks for this comment. This legend, unfortunately, reflected an earlier version of the figure and was overlooked prior to submission. We have since amended this and sincerely apologize for the error on our part.

p12

• The whole first paragraph reads more like it should be part of an introduction/discussion.

We’ve moved some of this paragraph to the discussion but left the background information necessary for the reader to understand why we were looking for homologs of wc and frq.

p13

• The last paragraph reads like discussion.

We have revised this paragraph so it now reads: “Because E. muscae is an obligate insect-pathogen only living inside live flies, we investigate the presence of canonical entomopathogenic enzymes in the genome. We find that E. muscae appear to have an expanded group of acid-trehalases compared to other entomopathogenic and non-entomopathogenic Entomophthorales (Fig. 4A), which correlates with the primary sugar in insect blood (hemolymph) being trehalose (Thompson, 2003). The obligate insectpathogenic lifestyle is also evident when comparing the repertoire of lipases, subtilisin-like serine proteases, trypsins, and chitinases in our focal species versus Zoopagomycota and Ascomycota fungi that are not obligate insect pathogens (Fig. 4B). Sordariomycetes within Ascomycota contains the other major transition to insect-pathogenicity within the kingdom Fungi (Araújo and Hughes, 2016). Based on our comparison of gene numbers, Entomophthorales possess more enzymes suitable for cuticle penetration than Sordariomycetes (Fig. 4B). In contrast, insect-pathogenic fungi within Hypocreales possess a more diverse secondary metabolite biosynthesis machinery as evidenced by the absence of polyketide synthase (PKS) and indole pathways in Entomophthorales (Fig. 4C).”

p15 and 16

• This all reads as redundant with the previous protein family domain analysis. I would try to merge them.

Thank you for this comment, however we have opted to maintain the current structure.

p18

• In the first sentence, I'm not sure about what was performed here.

This has been reworded to clarify.

p20

• Regarding the assembly, do I understand it correctly that a nuclear genome can be partially haploid / diploid?

Thanks for your comment. The genome itself is, of course, some integer multiple of n, but based on BUSCO scores our assembly doesn’t appear to have completely collapsed into a haploid genome. We think it makes more sense here to say “partially haploid” than “partially diploid” so have altered this.

p21

• RIP has only been observed in a couple of Ascomycetes. RIP-like genomic signatures (GC bias) have been observed elsewhere.

Hood et al, 2005 found signatures of RIP in anther-smut fungus and Horns et al, 2012, found evidence of hypermutability across repeat elements within several Pucciniales species.

p23

• Interesting that the peptidase A2B domain is found uniquely in E. muscae genome and is associated with Ty3 activity. Does the domain often overlap with annotated Ty3 in E. muscae genome? Or how come the domain is not present in other sister species with large genomes full of Ty3 transposons? Could it relate to a new active transposon in E. muscae specifically?

Thanks for this comment. The domain-based analysis was only performed on the predicted transcriptome of the genome assembly, which does not include the repeat elements (e.g., Ty3). It could be that this peptidase reflects a new active transposon that’s specific to E. muscae, which would certainly be very interesting. We’ve now included this idea in the discussion.

p26

• In the case of fungal genomes, I would not advise masking the assembly for repeated sequences prior to gene annotation (in particular given the current focus on protein family variation).

Thank you for this comment, however we disagree with this assertion as a typical approach for genome annotation in fungi and eukaryotic genomes is to use soft masking of transposable elements before performing gene prediction to avoid over-prediction. While there could be alternative approaches that compare masked or unmasked. This is a recommended protocol for underlying tools like Augustus (10.1002/cpbi.57) and in general descriptions of genome annotation (10.1002/0471250953.bi0401s52). The false positive rate of genes predicted through TE regions is likely to be more a problem than false negatives of missed genes in our experience. Further it seems appropriate to use consistent approach to annotation throughout when including genomes from other sources (e.g., Joint Genome Institute annotated genomes) which also use a repeat masking approach first before annotation. It seems most appropriate to use consistent methods when generating datasets to be used for comparative analyses. It is outside the scope of this project to reannotate all genomes with and without repeat masking.

p27

• Interrupted sentence at "Classification of DNA and LTR .. by similarity The".

This was an unnecessary partial phrase as the information on classification of elements via RepBase was made a few sentences above this.

p28

• Enriched/depleted rather than "significantly different"?

Thank you for this comment, however we have opted to maintain the current phrasing.

Reviewer #1 (Public Review):

Summary:

The authors present a detailed study of a nearly complete Entomophthora muscae genome assembly and annotation, along with comparative analyses among related and non-related entomopathogenic fungi. The genome is one of the largest fungal genomes sequenced, and the authors document the proliferation and evolution of transposons and presence/absence of related genetic machinery to explore how this may have occurred. There has also been an expansion in gene number, which appears to contain many "novel" genes unique to E. muscae. Functionally, the authors were interested in CAZymes, proteases, circadian clock related genes (due to entomopathogenicity/ host manipulation), other insect pathogen specific genes, and secondary metabolites. There are many interesting findings including expansions in trahalases, unique insulinase and another peptidase, and some evidence for RIP in Entomophthoralean fungi. The authors performed a separate study examining E. muscae species complex and related strains. Specifically, morphological traits were measured for strains and then compared to the 28S+ITS-based phylogeny, showing little informativeness of these morpho characters with high levels of overlap.

This work represents a big leap forward in genomics of non-Dikarya fungi and large fungal genomes. Most of the gene homologs have been studied in species that diverged hundreds of millions of years ago, and therefore using standard comparative genomic approaches are not trivial and still relatively little is known. This paper provides many new hypotheses and potential avenues of research about fungal genome size expansion, entomopathogenesis in zygomycetes, and cellular functions like RIP and circadian mechanisms.

Strengths:

There are many strengths to this study. It represents a massive amount of work and a very thorough functional analysis of the gene content in these fungi (which are largely unsequenced and definitely understudied). Too often comparative genomic work will focus on one aspect and leave the reader wondering about all the other ways genome(s) are unique or different from others. This study really dove in and explored the relevant aspects of the E. muscae genome.

The authors used both a priori and emergent properties to shape their analyses (by searching for specific genes of interest and by analyzing genes underrepresented, expanded, or unique to their chosen taxa), enabling a detailed review of the genomic architecture and content. Specifically, I'm impressed by the analysis of missing genes (pFAMs) in E. muscae, none of which are enriched in relatives, suggesting this fungus is really different not by gene loss, but by its gene expansions.

Analyzing species-level boundaries and the data underlying those (genetic or morphological) is not something frequently presented in comparative genomic studies, however, here it is a welcome addition as the target species of the study is part of a species complex where morphology can be misleading and genetic data is infrequently collected in conjunction with the morphological data.

Weaknesses:

The conclusions of this paper are well supported, and I think the clarifications and improvements made to the manuscript in the revision process have greatly improved the paper.

eLife assessment

This important study provides solid evidence, both from biochemical analyses and in vivo mouse models, that soluble uric acid serves as an enzymatic inhibitor of the NADase CD38, thereby impacting inflammatory responses. By shedding light onto the intricate interplay between uric acid and CD38, the authors highlight potential therapeutic avenues for inflammatory and age-related conditions, which may be of interest to medical biologists, biochemists, and cell biologists. Further in vivo and in vitro validation suggested would be helpful to cement the significance and implications of these findings.

Reviewer #1 (Public Review):

This manuscript describes soluble Uric Acid (sUA) as an endogenous inhibitor of CD38, affecting CD38 activity and NAD+ levels both in vitro and in vivo. Importantly, the inhibition constants calculated support the claim that sUA inhibits CD38 under physiological conditions. These findings are of extreme importance to understanding the regulation of an enzyme that has been shown to be the main NAD+/NMN-degrading enzyme in mammals, which impacts several metabolic processes and has major implications for understanding aging diseases. The manuscript is well written, the figures are self-explanatory, and in the experiments presented, the data is very solid. The authors discuss the main limitations of the study, especially in regard to the in vivo results. As a whole, I believe that this is a very interesting manuscript that will be appreciated by the scientific community and that opens a lot of new questions in the field of metabolism and aging. I found some issues that I believe constitute a weakness in the manuscript, and although they do not require new experiments, they may be considered by the authors for discussion in the final version of the manuscript.

The authors acknowledge the existence of several previous papers involving pharmacological inhibition of CD38 and their impact on several models of metabolism and aging. However, they only cite reviews. Given the focus of the manuscript, I believe that the seminal original papers should be cited.

Related to the previous comment, the authors show that they have identified the functional group on sUA that inhibits CD38, 1,3-dihydroimidazol-2-one. How does this group relate with previous structures that were shown to inhibit CD38 and do not have this chemical structure? Is sUA inhibiting CD38 in a different site? A crystallographic structure of CD38-78c is available in PDB that could be used to study or model these interactions.

Although the mouse model used to manipulate sUA levels is not ideal, the authors discuss its limitations, and importantly, they have CD38 KO mice as control. However, all the experiments were performed in very young mice, where CD38 expression is low in most tissues (10.1016/j.cmet.2016.05.006). This point should be mentioned in the discussion and maybe put in the context of variations of sUA levels during aging.

Reviewer #2 (Public Review):

Summary:

This is an interesting work where Wen et al. aimed to shed light on the mechanisms driving the protective role of soluble uric acid (sUA) toward avoiding excessive inflammation. They present biochemical data to support that sUA inhibits the enzymatic activity of CD38 (Figures 1 and 2). In a mouse model of acute response to sUA and using mice deficient in CD38, they find evidence that sUA increases the plasma levels of nicotinamide nucleotides (NAD+ and NMN) (Figure 3) and that sUA reduces the plasma levels of inflammasome-driven cytokines IL-1b and IL-18 in response to endotoxin, both dependent on CD38 (Figure 4). Their work is an important advance in the understanding of the physiological role of sUA, with mechanistic insight that can have important clinical implications.

Strengths:

The authors present evidence from different approaches to support that sUA inhibits CD38, impacts NAD+ levels, and regulates inflammatory responses through CD38.

Weaknesses:

The authors investigate macrophages as the cells impacted by sUA to promote immunoregulation, proposing that inflammasome inhibition occurs through NAD+ accumulation and sirtuin activity due to sUA inhibition of CD38. Unfortunately, the study still lacks data to support this model, as they could not replicate their in vivo findings using murine bone marrow-derived macrophages, a standard model to assess inflammasome activation. Without an alternative approach, the study lacks data to establish in vitro that sUA inhibition of CD38 reduces inflammasome activation in macrophages - consequently, they cannot determine yet if both NAD+ accumulation and sirtuin activity in macrophages is a mechanism leading to sUA role in vivo.

Reviewer #3 (Public Review):

Summary:

In the present manuscript, the authors propose that soluble Uric acid (sUA) is an enzymatic inhibitor of the NADase CD38 and that it controls levels of NAD modulating inflammatory response. Although interesting the studies are at this stage preliminary and validation is needed.

Strengths:

The study characterizes the potential relevance of sUA in NAD metabolism.

Weaknesses:

(1) A full characterization of the effect of sUA in other NAD-consuming and synthesizing enzymes is needed to validate the statement that the mechanism of regulation of NAD by sUA is mediated by CD38, The CD38 KO may not serve as the ideal control since it may saturate NAD levels already. Analysis of multiple tissues is needed.

(2) The physiological role of sUA as an endogenous inhibitor of CD38 needs stronger validation (sUA deficient model?).

(3) Flux studies would also be necessary to make the conclusion stronger.

eLife assessment

The authors analyze the relationship between human mobility and genomic data of SARS-CoV-2 using mobile phone mobility data and sequence data and present a solid proof of concept. This useful work was conducted on a fine spatial scale and provides suggestions on how mobility-derived surveillance could be conducted, although these results are mixed. The primary significance of this work is the strong use of large datasets that were highly granular. The authors provide a rigorous study, but with less clear predictive power of mobility to inform transmission patterns.

Reviewer #1 (Public Review):

Summary:

In "1 Exploring the Spatial Distribution of Persistent SARS-CoV-2 Mutations -Leveraging mobility data for targeted sampling" Spott et al. combine SARS-CoV-2 genomic data alongside granular mobility data to retrospectively evaluate the spread of SARS-CoV-2 alpha lineages throughout Germany and specifically Thuringia. They further prospectively identified districts with strong mobility links to the first district in which BQ.1.1 was observed to direct additional surveillance efforts to these districts. The additional surveillance effort resulted in the earlier identification of BQ.1.1 in districts with strong links to the district in which BQ.1.1 was first observed.

Strengths:

There are two important strengths of this work. The first is the scale and detail in the data that has been generated and analyzed as part of this study. Specifically, the authors use 6,500 SARS-CoV-2 sequences and district-level mobility data within Thuringia. I applaud the authors for making a subset of their analyses public e.g. on the associated micro react page.

Further, the main focus of the article is on the potential utility of mobility-directed surveillance sequences. While I may certainly be mistaken, I have not seen this proposed elsewhere, at least in the context of SARS-CoV-2. The authors were further able to test this concept in a real-world setting during the emergence of BQ.1.1. This is a unique real-world evaluation of a novel surveillance sequencing strategy and there is considerable value in publishing this analysis.

Weaknesses:

The article is quite strong and I find the analyses to generally be rigorous. However, there are places where I believe the text should be modified to slightly weaken the conclusions drawn from the presented analyses. Specific examples include:

- It seems the mobility-guided increased surveillance included only districts with significant mobility links to the origin district and did not include any "control" districts (those without strong mobility links). As such, you can only conclude that increasing sampling depth increased the rate of detection for BQ.1.1., not necessarily that doing so in a mobility-guided fashion provided an additional benefit. I absolutely understand the challenges of doing this in a real-world setting and think that the work remains valuable even with this limitation, but I would like the lack of control districts to be more explicitly discussed.

- Line 313: While this work has reliably shown that the spread of Alpha was slower in Thuringia, I don't think there have been sufficient analyses to conclude that this is due to the lack of transportation hubs. My understanding is that only mobility within Thuringia has been evaluated here and not between Thuringia and other parts of Germany.

- Line 333 (and elsewhere): I'm not convinced, based on the results presented in Figure 2, that the authors have reliably identified a sampling bias here. This is only true if you assume (as in line 235) that the variant was in these districts, but that hasn't actually been demonstrated here. While I recognize that for high-prevalence variants there is a strong correlation between inflow and variant prevalence, low-prevalence variants by definition spread less and may genuinely be missing from some districts. To support this conclusion that they identified a bias, I'd like to see some type of statistical model that is based e.g. on the number of sequences, prevalence of a given variant in other districts, etc. Alternatively, the language can be softened ("putative sampling bias").

Reviewer #2 (Public Review):

In the manuscript, the authors combine SARS-CoV-2 sequence data from a state in Germany and mobility data to help in understanding the movement of the virus and the potential to help decide where to focus sequencing. The global expansion in sequencing capability is a key outcome of the public health response. However, there remains uncertainty about how to maximise the insights the sequence data can give. Improved ability to predict the movement of emergent variants would be a useful public health outcome. Also knowing where to focus sequencing to maximising insights is also key. The presented case study from one State in Germany is therefore a useful addition to the literature. Nevertheless, I have a few comments.

One of the key goals of the paper is to explore whether mobile phone data can help predict the spread of lineages. However, it appears unclear whether this was actually addressed in the analyses. To do this, the authors could hold out data from a period of time, and see whether they can predict where the variants end up being found.

The abstract presents the mobility-guided sampling as a success, however, the results provide a much more mixed result. Ultimately, it's unclear what having this strategy really achieved. In a quickly moving pandemic, it is unclear what hunting for extra sequences of a specific, already identified, variant really does. I'm not sure what public health action would result, especially given the variant has already been identified.

Relatedly, it is unclear to me whether simply relying on spatial distance would not be an alternative simpler approach than mobile phone data. From Figure 2, it seems clear that a simple proximity matrix would work well at reconstructing viral flow. The authors could compare the correlation of spatial, spatial proximity, and CDR data.

eLife assessment

This fundamental study uses a creative experimental system to directly test Ohno's hypothesis, which describes how and why new genes might evolve by duplication of existing ones. In agreement with existing criticism of Ohno's original idea, the authors present compelling evidence that having two gene copies does not speed up the evolution of a new function as posited by Ohno, but instead leads to the rapid inactivation of one of the copies through the accumulation of mostly deleterious mutations. These findings will be of broad interest to evolutionary biologists and geneticists.

Reviewer #1 (Public Review):

Overview:

The authors construct a pair of E. coli populations that differ by a single gene duplication in a selectable fluorescent protein. They then evolve the two populations under differing selective regimes to assess whether the end result of the selective process is a "better" phenotype when starting with duplicated copies. Importantly, their starting duplicated population is structured to avoid the duplication-amplification process often seen in bacterial artificial evolution experiments. They find that while duplication increases robustness and speed of adaptation, it does not result in more highly adapted final states, in contrast to Ohno's hypothesis.

Major comments:

This is an excellent study with a very elegant experimental setup that allows a precise examination of the role of duplication in functional evolution, exclusive of other potential mechanisms. My main concern is to clarify some of the arguments relating to Ohno's hypothesis.

I think my main confusion on first reading the manuscript was in the precise definition of Ohno's hypothesis. I think this confusion was mine and not the authors, but it is likely common and could be addressed.

Most evolutionary biologists think of gene duplication as making neofunctionalization "easier" by providing functional redundancy and a larger mutational target, such that the evolutionary process of neofunctionalization is faster (as the authors observed). In this framework, the final evolved state might not differ when selection is applied to duplicated copies or a single-copy gene. Ohno's hypothesis, by contrast, argues that there generally exist adaptive conflicts between the ancestral function and the "desired" novel function, such that strong selection on a single-copy gene cannot produce the evolutionary optima that selection on two copies would. This idea is hinted at in the quotation from Ohno in paragraph 2 of the introduction. However, the sentences that follow I don't think reinforce this concept well enough and lead to some confusion.

With that definition in mind, I agree with the authors' conclusion that these data do not support Ohno's hypothesis. My quibble would be that what is actually shown here is that adaptive conflict in function is not universal: there are cases where a single gene can be optimized for multiple functions just as well as duplicated copies. I do not think the authors have, however, refuted the possibility that such adaptive conflicts are nonetheless a significant barrier to evolutionary innovation in the absence of gene duplication generally. Perhaps just a sentence or two to this effect might be appropriate.

I also think the authors need to clarify their approach to normalizing fluorescence between the two populations to control for the higher relative protein expression of the population with a duplicated gene. Since each population was independently selected with the highest fluorescing 60% (or less) of the cells selected, I think this normalization is appropriate. Of course, if the two populations were to compete against each other, this dosage advantage of the duplicates would itself be a selective benefit. Even as it is, the dosage advantage should be a source of purifying selection on the duplication, and perhaps this should be noted.

Finally, I am slightly curious about the nature of the adaptations that are evolving. The authors primarily discuss a few amino-acid changing mutations that seem to fix early in the experiment. Looking at Figure 3, it however, appears that the populations are still evolving late in the experiment, and so presumably other changes are occurring later on. Do the authors believe that perhaps expression changes to increase protein levels are driving these later changes?

Reviewer #2 (Public Review):

Summary:

Drawing from tools of synthetic biology, Mihajlovic et al. use a cleverly designed experimental system to dissect Ohno's hypothesis, which describes the evolution of functional novelty on the gene-level through the process of duplication & divergence.

Ohno's original idea posits that the redundancy gained from having two copies of the same gene allows one of them to freely evolve a new function. To directly test this, the authors make use of a fluorescent protein with two emission maxima, which allows them to apply different selection regimes (e.g. selection for green AND blue, or, for green NOT blue). To achieve this feat without being distracted by more complex evolutionary dynamics caused by the frequent recombination between duplicates, the authors employ a well-controlled synthetic system to prevent recombination: Duplicates are placed on a plasmid as indirect repeats in a recombination-deficient strain of E.coli. The authors implement their directed evolution approach through in vitro mutagenesis and selection using fluorescent-activated cell sorting. Their in-depth analysis of evolved mutants in single-copy versus double-copy genotypes provides clear evidence for Ohno's postulate that redundant copies experience relaxed purifying selection. In contrast to Ohno's original postulate, however, the authors go on to show that this does not in fact lead to more rapid phenotypic evolution, but rather, the rapid inactivation of one of the copies.

Strengths:

This paper contributes with great experimental detail to an area where the literature predominantly leans on genomics data. Through the use of a carefully designed, well-controlled synthetic system the authors are able to directly determine the phenotype & genotype of all individuals in their evolving populations and compare differences between genotypes with a single or double copy of coGFP. With it they find clear evidence for what critics of Ohno's original model have termed "Ohno's dilemma", the rapid non-functionalization by predominantly deleterious mutations.

Including an expressed but non-functional coGFP in (phenotypically) single copy genotypes provides an especially thoughtful control that allows determining a baseline dN/dS ratio in the absence of selection. All in all the study is an exciting example of how the clever use of synthetic biology can lead to new insights.

Weaknesses:

The major weakness of the study is tied to its biggest strength (as often in experimental biology there is a trade-off between 'resolution' and 'realism').

The paper ignores an important component of the evolutionary process in favour of an in-depth characterization of how two vs one copy evolve. Specifically, by employing a recombination-deficient strain and constructing their duplicates as inverted repeats their experimental design completely abolishes recombination between the two copies.

This is problematic for two reasons:

i) In nature, new duplicates do not arise as inverted, but rather as direct (tandem) repeats and - as the authors correctly point out - these are very unstable, due to the fact that repeated DNA is prone to recA-dependent homologous recombination (which arise orders of magnitude more frequently than point mutations).

ii) This instability often leads to further amplification of the duplicates under dosage selection both in the lab and in the wild (e.g. Andersson & Hughes, Annu. Rev. Genet. 2009), and would presumably also be an outcome under the current experimental set-up if it was not prevented from happening?

So in sum, recombination between duplicate genes is not merely a nuisance in experiments, but occurring at extremely high frequencies in nature (such that the authors needed to devise a clever engineering solution to abolish it), and is often observed in evolving populations, be it in the laboratory or the wild.

The manuscript sells controlling of copy number as a strength. And clearly, without it, the same insights could not be gained. However, if the basis for the very process of what Ohno's model describes is prevented from happening for the process to be studied, then, for reasons of clarity and context this needs pointing out, especially, to readers less familiar with the principles of molecular evolution.

Connected to this, there are several places in the introduction and the discussion where I feel that the existing literature, in particular models put forward since Ohno that invoke dosage selection (such as IAD) end up being slightly misrepresented.

My point is best exemplified in line 1 of Discussion: "To test Ohno's hypothesis and to distinguish its predictions from those of competing hypotheses, it is necessary to maintain a constant and stable copy number of duplicated genes during experimental evolution."

I think this statement is simply not true and might be misleading. To take the exaggerated position of a devil's advocate, the goal of evolutionary biology should be to find out how evolution actually proceeds in nature most of the time, rather than creating laboratory systems that manage to recapitulate influential ideas.

While fixing copy number may be a necessary step to understand how one copy evolves if a second one is present, it seems that if Ohno's hypothesis only works out in recA-deficient bacterial strains and on engineered inverted repeats, that Ohno might have missed one crucial aspect of how paralogs evolve. The mentioned competing hypotheses have been put forward to (a) address Ohno's dilemma (which the present study beautifully demonstrates exists under their experimental conditions) and (b) to reflect a commonly observed evolutionary process in bacteria (dosage gain in response to selection, e.g. a classic way of gaining antibiotic resistance). Fixing the copy number allowed the authors to show which predictions of Ohno's model hold up and which don't (under these specific conditions). But they do so without even preventing the processes described by alternative models from happening, so the experimental system is hardly appropriate to distinguish between Ohno & alternatives. Therefore, I think it could be made clearer that the experimental system is great to look at certain aspects Ohno's hypothesis in detail, but it can only inform us about a universe without recombination.

(1) Citing the works by ref 8, 26, 27 to merely state that "in some copies were gained and some were lost (ref 6, ref 25)" makes it seem as if fixing at 2 copies is some sort of sensible average. Yet ref 6 (Dhar et al.) specifically states that dosage is the most important response. Moreover, in this study gene copies are lost, but plasmid copies are gained instead. In Holloway et al. 2007 (ref 25), the 2 copies resided on different plasmids, so entirely different underlying molecular genetics might be at work (high cost of plasmid maintenance, and competitive binding on both proteins onto the respective (off)-target, where either way selection favored a single copy, so a different situation altogether). In both cited studies, fixing the copy would have prohibited learning something about the process of duplication & divergence.

Hence this statement seems to distract the readers from the main message, which seems that preventing recombination experimentally allows to follow the divergence of each copy and studying a response that does not involve dosage-increase.

(2) "These studies highlighted the importance of gene duplication in providing fast adaptation under changing environmental conditions but they focused on the importance of gene dosage." I think this constructs a false dichotomy. Instead, these studies pointed out that dosage (and with it, selection for dosage) is an important part of the equation that might have been missed by Ohno.

(3) "Such models are also easier to test experimentally, because they do not require precise control of gene copy number. The necessary tests can even benefit from massive gene amplifications8. Although Ohno's hypothesis is more difficult to test experimentally (...)" - again, I feel the wording is slightly misleading. The point is not that IAD is easier to test and Ohno's model is harder to test in laboratory experiments, rather, experiments (and some more limited observations of naturally evolving populations) seem to suggest that in reality evolution proceeds (more often?) according to IAD rather than Ohno's neofunctionalization hypothesis. However, as the authors point out, it will be exciting to see their clever experimental system used to test other genes and conditions to get a more comprehensive understanding of what gene- and selection- parameter values would overcome Ohno's dilemma.

Author response:

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, Day et al. present a high-throughput version of expansion microscopy to increase the throughput of this well-established super-resolution imaging technique. Through technical innovations in liquid handling with custom-fabricated tools and modifications to how the expandable hydrogels are polymerized, the authors show robust ~4-fold expansion of cultured cells in 96-well plates. They go on to show that HiExM can be used for applications such as drug screens by testing the effect of doxorubicin on human cardiomyocytes. Interestingly, the effects of this drug on changing DNA organization were only detectable by ExM, demonstrating the utility of HiExM for such studies.

Overall, this is a very well-written manuscript presenting an important technical advance that overcomes a major limitation of ExM - throughput. As a method, HiExM appears extremely useful, and the data generally support the conclusions.

Strengths:

Hi-ExM overcomes a major limitation of ExM by increasing the throughput and reducing the need for manual handling of gels. The authors do an excellent job of explaining each variation introduced to HiExM to make this work and thoroughly characterize the impressive expansion isotropy. The dox experiments are generally well-controlled and the comparison to an alternative stressor (H2O2) significantly strengthens the conclusions.

Weaknesses:

(1) Based on the exceedingly small volume of solution used to form the hydrogel in the well, there may be many unexpanded cells in the well and possibly underneath the expanded hydrogel at the end of this. How would this affect the image acquisition, analysis, and interpretation of HiExM data?

The hydrogel footprint covers approximately 5% of the surface within an individual well and only cells within this area are embedded in the polymerized hydrogel for subsequent processing steps. Cells that are outside of this footprint are not incorporated into the gel, meaning that these cells are digested by Proteinase K and subsequently washed away by the excess water exchange in the gel swelling step. Note that different cell types may require higher or lower concentrations of Proteinase K to adequately digest cells for expansion while maintaining fluorescence signal. Given the compatibility of HiExM with 96-well plates, this titration can be performed rapidly in a single experiment. Although cells outside of the hydrogel footprint are removed prior to imaging, we do occasionally observe Hoechst signal that appears to be underneath the gels. We believe this signal is likely from excess DNA from digested cells that was not fully washed out in the gel swelling step. This signal is both spatially and morphologically distinct from the nuclear signal of intact cells and it does not affect image acquisition, analysis, or data interpretation.

(2) It is unclear why the expansion factor is so variable between plates (e.g., Figure 2H). This should be discussed in more detail.

The variability in expansion factor across plates can likely be attributed to the small volume (~250 nL) deposited by the device posts. Small variations in gel volume could impact gel polymerization compared to standard ExM gels. For example, gels in HiExM are more sensitive to evaporation because they are ~1000x smaller than standard expansion gel preparations due to an increased air-liquid-interface. Evaporation in HiExM gels increases monomer and cross linker concentrations, leading to variation in expansion factor across plates. We note that expansion factor is robust within well plates and that variance is slightly increased between plates. These differences will be discussed in the revised manuscript.

(3) The authors claim that CF dyes are more resistant to bleaching than other dyes. However, in Figure. S3, it appears that half of the CF dyes tested still show bleaching, and no data is shown supporting the claim that Alexa dyes bleach. It would be helpful to include data supporting the claim that Alexa dyes bleach more than CF dyes and the claim that CF dyes in general are resistant to bleaching should be modified to more accurately reflect the data shown.

We did not show data using Alexa dyes because these fluorophores are highly sensitive to photobleaching using Irgacure and thus we could not obtain images. In contrast, some CF dyes are more robust to bleaching in HiExM including CF488A, CF568, and CF633 dyes. We have recently adapted our protocol to PhotoExM chemistry which is compatible with a wider range of fluorophores as described by Günay et al. (2023) and as shown in current Fig. S11.

(4) Related to the above point, it appears that Figure S11 may be missing the figure legend. This makes it hard to understand how HiExM can use other photo-inducible polymerization methods and dyes other than CF dyes.

The following figure legend will be included in the revised manuscript. Fig. S11: Example of a cell expanded in HiExM using Photo-ExM gel chemistry. Photo-ExM does not require an anoxic environment for gel deposition and polymerization, improving ease of use of HiExM. Mitochondria were stained with an Alexa 647 conjugated secondary antibody, indicating that HiExM is compatible with additional fluorophores when combined with Photo-ExM.

(5) The use of automated high-content imaging is impressive. However, it is unclear to me how the increased search space across the extended planar area and focal depths in expanded samples is overcome. It would be helpful to explain this automated imaging strategy in more detail.

We imaged plates on the Opera Phenix using the PreciScan Acquisition Software in Harmony. In brief, each well is imaged at 5x magnification in the Hoechst channel to capture the full well at low resolution. Hoechst is used for this step given its signal brightness, ubiquity across established staining protocols, and spectral independence from most fluorophores commonly conjugated to secondary antibodies. Using this information, the microscope detects regions of interest (nuclei) based on criteria including size, brightness, circularity, etc. Finally, the positional information for each region is stored, and the microscope automatically images those regions at 63x magnification. The working distance for the objective used in this study is 600 µm which is sufficient to capture the entirety of expanded cells in the Z direction. This strategy allows minimizes off-target imaging and allows robust image acquisition even in cultures with lower seeding density. A detailed description of the automated imaging strategy will be included in the revised manuscript.

(6) The general method of imaging pre- and post-expansion is not entirely clear to me. For example, on page 5 the authors state that pre-expansion imaging was done at the center of each gel. Is pre-expansion imaging done after the initial gel polymerization? If so, this would assume that the gelation itself has no effect on cell size and shape if these gelled but not yet expanded cells are used as the reference for calculating expansion factor and isotropy.

Pre-expansion imaging is performed after staining is complete, but prior to the application of AcX, which is the first step of the HiExM protocol. Following staining and imaging, plates can be sealed with paraffin and stored at 4˚C for up to a week prior to starting the expansion protocol. We typically image 61 fields of view at the center of the well plate (where the gel will be deposited) to obtain sufficient pre-expansion images as shown in Figure 2b (left). After pre-expansion imaging, we perform the HiExM protocol followed by image acquisition. We then tile all the images, as shown in Figure 2b, and compare tiled images from the same well pre- and post-expansion to manually identify the same cells. Comparisons of the pre- and post-expansion images of the same cell are then used to calculate expansion factor and isotropy measurements as described. This detailed description will be included in the revised manuscript.

(7) In the dox experiments, are only 4 expanded nuclei analyzed? It is unclear in the Figure 3 legend what the replicates are because for the unexpanded cells, it says the number of nuclei but for expanded it only says n=4. If only 4 nuclei are analyzed, this does not play to the strengths of HiExM by having high throughput.

We performed the DOX titration assay across four different well plates (i.e. n=4). For each condition, the total number of nuclei measured was 56, 71, 64, 92, and 62 for DMSO, 1nM, 10nM, 100nM, and 1µM, respectively. For SEM calculations, we included the number of technical replicates to avoid underestimating error. We have revised the Figure 3 legend to better reflect the experimental details.

(8) I am not sure if the analysis of dox-treated cells is accurate for the overall phenotype because only a single slice at the midplane is analyzed. It would be helpful to show, at least in one or two example cases, that this trend of changing edge intensity occurs across the whole 3D nucleus.

We will repeat our analysis on a subset of images using multiple optical sections for each nucleus reported. These new data will be included in the revised manuscript.

(9) It would be helpful to provide an actual benchmark of imaging speed or throughput to support the claims on page 8 that HiExM can be combined with autonomous imaging to capture thousands of cells a day. What is the highest throughput you have achieved so far?

The parameters that dictate imaging speed in HiExM include exposure time, z-stack height, and number of channels. Depending on the signal intensity for a given channel, exposure times vary from 200ms to 1000ms. For z-stack height, we found that imaging 65 sections with 1µm spacing allowed for robust identification of each region of interest in the 5x pre-scan. As an example, collecting images for a full well plate (e.g., 20 images per well with 4 channels) requires approximately 24 hours of autonomous image acquisition using the Opera Phenix. Depending on cell size, this yields imaging data for between 1200 cells (1 cell per field of view) to 6000 cells (5 cells per field of view). Different autonomous imagers as well as improving staining techniques that increase signal:noise can be expected to significantly decrease the exposure time as it will reduce the number of z-stacks needed for each region.

Reviewer #2 (Public Review):

Summary:

In the present work, the authors present an engineering solution to sample preparation in 96-well plates for high-throughput super-resolution microscopy via Expansion Microscopy. This is not a trivial problem, as the well cannot be filled with the gel, which would prohibit the expansion of the gel. A device was engineered that can spot a small droplet of hydrogel solution and keep it in place as it polymerizes. It occupies only a small portion of space at the center of each well, the gel can expand into all directions, and imaging and staining can proceed by liquid handling robots and an automated microscope.

Strengths:

In contrast to Reference 8, the authors' system is compatible with standard 96 well imaging plates for high-throughput automated microscopy and automated liquid handling for most parts of the protocol. They thus provide a clear path towards high-throughput ExM and high-throughput super-resolution microscopy, which is a timely and important goal.

Weaknesses:

The assay they chose to demonstrate what high-throughput ExM could be useful for, is not very convincing. But for this reviewer that is not important.

We appreciate this reviewer’s point. We believe the data provide an example of the power of HiExM for collecting thousands of nanoscale images that would benefit experiments that require many samples (e.g., conditions, replicates, timepoints, etc.). The ability to generate large data sets also enables quantitative analysis of images with appropriate statistical power. The intention of this experiment was to provide a proof-of-concept example of the robustness, accessibility, and experimental design flexibility of HiExM.

Reviewer #3 (Public Review):

Summary:

Day et al. introduced high-throughput expansion microscopy (HiExM), a method facilitating the simultaneous adaptation of expansion microscopy for cells cultured in a 96-well plate format. The distinctive features of this method include 1) the use of a specialized device for delivering a minimal amount (~230 nL) of gel solution to each well of a conventional 96-well plate, and 2) the application of the photochemical initiator, Irgacure 2959, to successfully form and expand the toroidal gel within each well.

Strengths:

This configuration eliminates the need for transferring gels to other dishes or wells, thereby enhancing the throughput and reproducibility of parallel expansion microscopy. This methodological uniqueness indicates the applicability of HiExM in detecting subtle cellular changes on a large scale.

Weaknesses:

To demonstrate the potential utility of HiExM in cell phenotyping, drug studies, and toxicology investigations, the authors treated hiPS-derived cardiomyocytes with a low dose of doxycycline (dox) and quantitatively assessed changes in nuclear morphology. However, this reviewer is not fully convinced of the validity of this specific application. Furthermore, some data about the effect of expansion require reconsideration.

The application we chose was intended as a proof of concept. We believe the data provide an example of the power of HiExM for collecting thousands of nanoscale images that would benefit experiments that require many samples (e.g., conditions, replicates, timepoints, etc.). The ability to generate large data sets also enables quantitative analysis of images with appropriate statistical power. The intention of this experiment was to provide a proof-of-concept example of the robustness, accessibility, and experimental design flexibility of HiExM.

The variability in expansion factor across plates can likely be attributed to the small volume (~250 nL) deposited by the device posts. Small variations in gel volume could impact gel polymerization compared to standard ExM gels. For example, gels in HiExM are more sensitive to evaporation because they are ~1000x smaller than standard expansion gel preparations due to an increased air-liquid-interface. Evaporation in HiExM gels increases monomer and cross linker concentrations, leading to variation in expansion factor across plates. We note that expansion factor is robust within well plates and that variance is slightly increased between plates. These differences will be discussed in the revised manuscript.

Reviewer #3 (Public Review):

Summary:

Day et al. introduced high-throughput expansion microscopy (HiExM), a method facilitating the simultaneous adaptation of expansion microscopy for cells cultured in a 96-well plate format. The distinctive features of this method include 1) the use of a specialized device for delivering a minimal amount (~230 nL) of gel solution to each well of a conventional 96-well plate, and 2) the application of the photochemical initiator, Irgacure 2959, to successfully form and expand the toroidal gel within each well.

Strengths:

This configuration eliminates the need for transferring gels to other dishes or wells, thereby enhancing the throughput and reproducibility of parallel expansion microscopy. This methodological uniqueness indicates the applicability of HiExM in detecting subtle cellular changes on a large scale.

Weaknesses:

To demonstrate the potential utility of HiExM in cell phenotyping, drug studies, and toxicology investigations, the authors treated hiPS-derived cardiomyocytes with a low dose of doxycycline (dox) and quantitatively assessed changes in nuclear morphology. However, this reviewer is not fully convinced of the validity of this specific application. Furthermore, some data about the effect of expansion require reconsideration.

eLife assessment

This important study develops a high throughput version of expansion microscopy that can be performed in 96-well plates. The engineered technology is convincing and compatible with standard microplates and automated microscopes and thus will be of broad interest. However, the application is incomplete and would benefit from additional experiments.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Day et al. present a high-throughput version of expansion microscopy to increase the throughput of this well-established super-resolution imaging technique. Through technical innovations in liquid handling with custom-fabricated tools and modifications to how the expandable hydrogels are polymerized, the authors show robust ~4-fold expansion of cultured cells in 96-well plates. They go on to show that HiExM can be used for applications such as drug screens by testing the effect of doxorubicin on human cardiomyocytes. Interestingly, the effects of this drug on changing DNA organization were only detectable by ExM, demonstrating the utility of HiExM for such studies.

Overall, this is a very well-written manuscript presenting an important technical advance that overcomes a major limitation of ExM - throughput. As a method, HiExM appears extremely useful, and the data generally support the conclusions.

Strengths:

Hi-ExM overcomes a major limitation of ExM by increasing the throughput and reducing the need for manual handling of gels. The authors do an excellent job of explaining each variation introduced to HiExM to make this work and thoroughly characterize the impressive expansion isotropy. The dox experiments are generally well-controlled and the comparison to an alternative stressor (H2O2) significantly strengthens the conclusions.

Weaknesses:

(1) Based on the exceedingly small volume of solution used to form the hydrogel in the well, there may be many unexpanded cells in the well and possibly underneath the expanded hydrogel at the end of this. How would this affect the image acquisition, analysis, and interpretation of HiExM data?

(2) It is unclear why the expansion factor is so variable between plates (e.g., Figure 2H). This should be discussed in more detail.

(3) The authors claim that CF dyes are more resistant to bleaching than other dyes. However, in Figure. S3, it appears that half of the CF dyes tested still show bleaching, and no data is shown supporting the claim that Alexa dyes bleach. It would be helpful to include data supporting the claim that Alexa dyes bleach more than CF dyes and the claim that CF dyes in general are resistant to bleaching should be modified to more accurately reflect the data shown.

(4) Related to the above point, it appears that Figure S11 may be missing the figure legend. This makes it hard to understand how HiExM can use other photo-inducible polymerization methods and dyes other than CF dyes.

(5) The use of automated high-content imaging is impressive. However, it is unclear to me how the increased search space across the extended planar area and focal depths in expanded samples is overcome. It would be helpful to explain this automated imaging strategy in more detail.

(6) The general method of imaging pre- and post-expansion is not entirely clear to me. For example, on page 5 the authors state that pre-expansion imaging was done at the center of each gel. Is pre-expansion imaging done after the initial gel polymerization? If so, this would assume that the gelation itself has no effect on cell size and shape if these gelled but not yet expanded cells are used as the reference for calculating expansion factor and isotropy.

(7) In the dox experiments, are only 4 expanded nuclei analyzed? It is unclear in the Figure 3 legend what the replicates are because for the unexpanded cells, it says the number of nuclei but for expanded it only says n=4. If only 4 nuclei are analyzed, this does not play to the strengths of HiExM by having high throughput.

(8) I am not sure if the analysis of dox-treated cells is accurate for the overall phenotype because only a single slice at the midplane is analyzed. It would be helpful to show, at least in one or two example cases, that this trend of changing edge intensity occurs across the whole 3D nucleus.

(9) It would be helpful to provide an actual benchmark of imaging speed or throughput to support the claims on page 8 that HiExM can be combined with autonomous imaging to capture thousands of cells a day. What is the highest throughput you have achieved so far?

Reviewer #2 (Public Review):

Summary:

In the present work, the authors present an engineering solution to sample preparation in 96-well plates for high-throughput super-resolution microscopy via Expansion Microscopy. This is not a trivial problem, as the well cannot be filled with the gel, which would prohibit the expansion of the gel. A device was engineered that can spot a small droplet of hydrogel solution and keep it in place as it polymerizes. It occupies only a small portion of space at the center of each well, the gel can expand into all directions, and imaging and staining can proceed by liquid handling robots and an automated microscope.

Strengths:

In contrast to Reference 8, the authors' system is compatible with standard 96 well imaging plates for high-throughput automated microscopy and automated liquid handling for most parts of the protocol. They thus provide a clear path towards high-throughput exM and high-throughout super-resolution microscopy, which is a timely and important goal.

Weaknesses:

The assay they chose to demonstrate what high-throughput ExM could be useful for, is not very convincing. But for this reviewer that is not important.

Author response:

eLife assessment

This study presents valuable information on the mechanism of how birnavirus VP3 protein interacts with PI3P in early endosomes. Evidence supporting the proposed two-stage mechanism is incomplete and would benefit from additional supporting experiments, and additional experimentation would also address concerns about data consistency.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

Zanetti et al. use biophysical and cellular assays to investigate the interaction of the birnavirus VP3 protein with the early endosome lipid PI3P. The major novel finding is that the association of the VP3 protein with an anionic lipid (PI3P) appears to be important for viral replication, as evidenced through a cellular assay on FFUs.

Strengths:

Supports previously published claims that VP3 may associate with early endosomes and bind to PI3P-containing membranes. The claim that mutating a single residue (R200) critically affects early endosome binding and that the same mutation also inhibits viral replication suggests a very important role for this binding in the viral life cycle.

Weaknesses:

The manuscript is relatively narrowly focused: one bimolecular interaction between a host cell lipid and one protein of an unusual avian virus (VP3-PI3P). Aspects of this interaction have been described previously. Additional data would strengthen claims about the specificity and some technical issues should be addressed. Many of the core claims would benefit from additional experimental support to improve consistency.

We focused our efforts on the characterization of the molecular interaction between the birnaviral protein VP3 and the anionic lipid PI3P, which is found in the host cell. This decision was motivated by our previous research, which made use of cell biology and virology techniques to demonstrate that VP3 facilitates the formation of the viral replication machinery on the cytosolic leaflet of early endosomes due to its inherent endosome-targeting capability (J Virol. 2018 May 14;92(11):e01964-17). Additionally, our previous findings indicated that PI3P, present in early endosomal membranes, is a critical host factor enabling VP3's association with these membranes, thereby promoting viral replication (J Virol. 2021 Feb 24;95(6):e02313-20). Consequently, an in-depth characterization of the VP3/PI3P interaction was necessary and motivated the present work. We plan to incorporate specific recommendations to further substantiate our assertions in the revised version of our manuscript.

Reviewer #2 (Public Review):

Summary:

Birnavirus replication factories form alongside early endosomes (EEs) in the host cell cytoplasm. Previous work from the Delgui lab has shown that the VP3 protein of the birnavirus strain infectious bursal disease virus (IBDV) interacts with phosphatidylinositol-3-phosphate (PI3P) within the EE membrane (Gimenez et al., 2018, 2020). Here, Zanetti et al. extend this previous work by biochemically mapping the specific determinants within IBDV VP3 that are required for PI3P binding in vitro, and they employ in silico simulations to propose a biophysical model for VP3-PI3P interactions.

Strengths:

The manuscript is generally well-written, and much of the data is rigorous and solid. The results provide deep knowledge into how birnaviruses might nucleate factories in association with EEs. The combination of approaches (biochemical, imaging, and computational) employed to investigate VP3-PI3P interactions is deemed a strength.

Weaknesses:

(1) Concerns about the sources, sizes, and amounts of recombinant proteins used for co-flotation: Figures 1A, 1B, 1G, and 4A show the results of co-flotation experiments in which recombinant proteins (control His-FYVE v. either full length or mutant His VP3) were either found to be associated with membranes (top) or non-associated (bottom). However, in some experiments, the total amounts of protein in the top + bottom fractions do not appear to be consistent in control v. experimental conditions. For instance, the Figure 4A western blot of His-2xFYVE following co-flotation with PI3P+ membranes shows almost no detectable protein in either top or bottom fractions.

Liposome-based methods, such as the co-flotation assay, are well-known and preferred to study protein-phosphoinositide interaction because the phosphoinositides are incorporated in a membrane, the composition of which can mimic cellular membranes. Additionally, by modifying the phosphoinositide incorporated in the liposomes, this technique allows for determining the specificity of the protein binding. However, this approach is rather qualitative, meaning that, after density gradient separation, the protein is found in the top fractions (bound to liposomes) or in the bottom fractions (not bound to liposomes), and our quantifications have the aim of showing the difference in the bound fraction between liposome populations with or without PI3P. Given the setting of the co-flotation assays, each protein-liposome system [2xFYVE-PI3P(-), 2xFYVE-PI3P(+), VP3-PI3P(-), or VP3-PI3P(+)] is assessed separately, and even if the conditions are homogeneous, it’s not surprising to observe differences in the protein level between each one. Indeed, our revised version of the manuscript will include membranes with more similar band intensities.

Reading the paper, it was difficult to understand which source of protein was used for each experiment (i.e., E. coli or baculovirus-expressed), and this information is contradicted in several places (see lines 358-359 v. 383-384). Also, both the control protein and the His-VP3-FL proteins show up as several bands in the western blots, but they don't appear to be consistent with the sizes of the proteins stated on lines 383-384. For example, line 383 states that His-VP3-FL is ~43 kDa, but the blots show triplet bands that are all below the 35 kDa marker (Figures 1B and 1G). Mass spectrometry information is shown in the supplemental data (describing the different bands for His-VP3-FL) but this is not mentioned in the actual manuscript, causing confusion. Finally, the results appear to differ throughout the paper (see Figures 1B v. 1G and 1A v. 4A).

We used two sources of recombinant VP3: baculovirus and Escherichia coli. Initially, we opted for the baculovirus system based on evidence from previous studies that it was suitable for ectopic expression of VP3. Subsequently, we successfully produced VP3 using Escherichia coli and chose to transition to this system due to several technical advantages. Moreover, mass spectrometry analysis did not reveal any post-translational modifications that may have favored retaining the baculoviral system. We confirmed that VP3, produced in either system, exhibited similar behavior in our co-flotation assays. We will clarify all this in the revised version of our manuscript.

(2) Possible "other" effects of the R200D mutation on the VP3 protein. The authors performed mutagenesis to identify which residues within patch 2 on VP3 are important for association with PI3P. They found that a VP3 mutant with an engineered R200D change (i) did not associate with PI3P membranes in co-floatation assays, and (ii) did not co-localize with EE markers in transfected cells. Moreover, this mutation resulted in the loss of IBDV viability in reverse genetics studies. The authors interpret these results to indicate that this residue is important for "mediating VP3-PI3P interaction" (line 211) and that this interaction is essential for viral replication. However, it seems possible that this mutation abrogated other aspects of VP3 function (e.g., dimerization or other protein/RNA interactions) aside from or in addition to PI3P binding. Such possibilities are not mentioned by the authors.

The arginine amino acid at position 200 of VP3 is not located in any of the protein regions associated with its other known functions. VP3 has a dimerization domain located in the second helical domain, where different amino acids across the three helices form a total of 81 interprotomeric close contacts; however, R200 is not involved in these contacts (Structure. 2008 Jan;16(1):29-37). VP3 also has an oligomerization domain mapped within the 42 C-terminal residues of the polypeptide, i.e., the segment of the protein composed by the residues at positions 216-257 (J Virol. 2003 Jun;77(11):6438–6449). Regarding VP3’s ability to bind RNA, it is facilitated by a region of positively charged amino acids, identified as P1, which includes K99, R102, K105, and K106 (PLoS One. 2012;7(9):e45957). Furthermore, our findings indicate that the R200D mutant retains a folding pattern similar to the wild-type protein, as shown in Figure 4B. All these lead us to conclude that the loss of replication capacity of R200D viruses results from impaired, or even lost, VP3-PI3P interaction.

(3) Interpretations from computational simulations. The authors performed computational simulations on the VP3 structure to infer how the protein might interact with membranes. Such computational approaches are powerful hypothesis-generating tools. However, additional biochemical evidence beyond what is presented would be required to support the authors' claims that they "unveiled a two-stage modular mechanism" for VP3-PI3P interactions (see lines 55-59). Moreover, given the biochemical data presented for R200D VP3, it was surprising that the authors did not perform computational simulations on this mutant. The inclusion of such an experiment would help tie together the in vitro and in silico data and strengthen the manuscript.

We acknowledge that the language used may have overstated the "unveiling" of the two-stage binding mechanism for VP3 on membranes containing PI3P. We intended to propose, rather than confirm, this mechanism, largely based on our coarse-grained simulations. Accordingly, we will revise the manuscript to temper our claims and frame them more appropriately. Regarding the absence of computer simulations for the R200D VP3 mutant, these were indeed conducted, and the results are detailed in Figure 14 of the supplementary material. We realize this was not adequately emphasized in the main manuscript, an oversight we will correct in the revised version.

Reviewer #3 (Public Review):

Summary:

Infectious bursal disease virus (IBDV) is a birnavirus and an important avian pathogen. Interestingly, IBDV appears to be a unique dsRNA virus that uses early endosomes for RNA replication that is more common for +ssRNA viruses such as for example SARS-CoV-2.

This work builds on previous studies showing that IBDV VP3 interacts with PIP3 during virus replication. The authors provide further biophysical evidence for the interaction and map the interacting domain on VP3.

Strengths: Detailed characterization of the interaction between VP3 and PIP3 identified R200D mutation as critical for the interaction. Cryo-EM data show that VP3 leads to membrane deformation.

Weaknesses:

The work does not directly show that the identified R200 residues are directly involved in VP3-early endosome recruitment during infection. The majority of work is done with transfected VP3 protein (or in vitro) and not in virus-infected cells. Additional controls such as the use of PIP3 antagonizing drugs in infected cells together with a colocalization study of VP3 with early endosomes would strengthen the study. In addition, it would be advisable to include a control for cryo-EM using liposomes that do not contain PIP3 but are incubated with HIS-VP3-FL. This would allow ruling out any unspecific binding that might not be detected on WB.

The authors also do not propose how their findings could be translated into drug development that could be applied to protect poultry during an outbreak. The title of the manuscript is broad and would improve with rewording so that it captures what the authors achieved.

In previous works from our group, we demonstrated the crucial role of the VP3 P2 region in targeting the early endosomal membranes and for viral replication, including the use of PI3K inhibitors to deplete PI3P, showing that both the control RFP-2xFYVE and VP3 lost their ability to associate with the early endosomal membranes (J Virol. 2018 May 14;92(11):e01964-17; J Virol. 2021 Feb 24;95(6):e02313-20). In the present work, to further characterize the role of R200 in binding to early endosomes and for viral replication, we show that: i) the transfected VP3 R200D protein loses the ability to bind to early endosomes in immunofluorescence assays (Figure 2E and Figure 3); ii) the recombinant VP3 R200D protein loses the ability to bind to liposomes PI3P(+) in co-flotation assays (Figure 4A); and, iii) the mutant virus R200D loses replication capacity (Figure 4C).

Regarding the cryo-EM comment: we will include images where we used liposomes PIP3(-) in the revised version of our manuscript.

We will also modify the title of the manuscript.

Regarding the question of how our findings could be translated into drug development, indeed, VP3-PI3P binding constitutes a good target for drugs that counteract infectious bursal disease. However, we did not mention this idea in the manuscript, first because it is somewhat speculative and second because infected farms do not implement any specific treatment. The control is based on vaccination. We will mention these aspects of the infection in the revised version of our manuscript.

Reviewer #1 (Public Review):

Summary:

Zanetti et al. use biophysical and cellular assays to investigate the interaction of the birnavirus VP3 protein with the early endosome lipid PI3P. The major novel finding is that the association of the VP3 protein with an anionic lipid (PI3P) appears to be important for viral replication, as evidenced through a cellular assay on FFUs.

Strengths:

Supports previously published claims that VP3 may associate with early endosomes and bind to PI3P-containing membranes. The claim that mutating a single residue (R200) critically affects early endosome binding and that the same mutation also inhibits viral replication suggests a very important role for this binding in the viral life cycle.

Weaknesses:

The manuscript is relatively narrowly focused: one bimolecular interaction between a host cell lipid and one protein of an unusual avian virus (VP3-PI3P). Aspects of this interaction have been described previously. Additional data would strengthen claims about the specificity and some technical issues should be addressed. Many of the core claims would benefit from additional experimental support to improve consistency.

eLife assessment

This study presents valuable information on the mechanism of how birnavirus VP3 protein interacts with PI3P in early endosomes. Evidence supporting the proposed two-stage mechanism is incomplete and would benefit from additional supporting experiments, and additional experimentation would also address concerns about data consistency.

Reviewer #2 (Public Review):

Summary:

Birnavirus replication factories form alongside early endosomes (EEs) in the host cell cytoplasm. Previous work from the Delgui lab has shown that the VP3 protein of the birnavirus strain infectious bursal disease virus (IBDV) interacts with phosphatidylinositol-3-phosphate (PI3P) within the EE membrane (Gimenez et al., 2018, 2020). Here, Zanetti et al. extend this previous work by biochemically mapping the specific determinants within IBDV VP3 that are required for PI3P binding in vitro, and they employ in silico simulations to propose a biophysical model for VP3-PI3P interactions.

Strengths:

The manuscript is generally well-written, and much of the data is rigorous and solid. The results provide deep knowledge into how birnaviruses might nucleate factories in association with EEs. The combination of approaches (biochemical, imaging, and computational) employed to investigate VP3-PI3P interactions is deemed a strength.

Weaknesses:

(1) Concerns about the sources, sizes, and amounts of recombinant proteins used for co-flotation: Figures 1A, 1B, 1G, and 4A show the results of co-flotation experiments in which recombinant proteins (control His-FYVE v. either full length or mutant His VP3) were either found to be associated with membranes (top) or non-associated (bottom). However, in some experiments, the total amounts of protein in the top + bottom fractions do not appear to be consistent in control v. experimental conditions. For instance, the Figure 4A western blot of His-2xFYVE following co-flotation with PI3P+ membranes shows almost no detectable protein in either top or bottom fractions. Reading the paper, it was difficult to understand which source of protein was used for each experiment (i.e., E. coli or baculovirus-expressed), and this information is contradicted in several places (see lines 358-359 v. 383-384). Also, both the control protein and the His-VP3-FL proteins show up as several bands in the western blots, but they don't appear to be consistent with the sizes of the proteins stated on lines 383-384. For example, line 383 states that His-VP3-FL is ~43 kDa, but the blots show triplet bands that are all below the 35 kDa marker (Figures 1B and 1G). Mass spectrometry information is shown in the supplemental data (describing the different bands for His-VP3-FL) but this is not mentioned in the actual manuscript, causing confusion. Finally, the results appear to differ throughout the paper (see Figures 1B v. 1G and 1A v. 4A).

(2) Possible "other" effects of the R200D mutation on the VP3 protein. The authors performed mutagenesis to identify which residues within patch 2 on VP3 are important for association with PI3P. They found that a VP3 mutant with an engineered R200D change (i) did not associate with PI3P membranes in co-floatation assays, and (ii) did not co-localize with EE markers in transfected cells. Moreover, this mutation resulted in the loss of IBDV viability in reverse genetics studies. The authors interpret these results to indicate that this residue is important for "mediating VP3-PI3P interaction" (line 211) and that this interaction is essential for viral replication. However, it seems possible that this mutation abrogated other aspects of VP3 function (e.g., dimerization or other protein/RNA interactions) aside from or in addition to PI3P binding. Such possibilities are not mentioned by the authors.

(3) Interpretations from computational simulations. The authors performed computational simulations on the VP3 structure to infer how the protein might interact with membranes. Such computational approaches are powerful hypothesis-generating tools. However, additional biochemical evidence beyond what is presented would be required to support the authors' claims that they "unveiled a two-stage modular mechanism" for VP3-PI3P interactions (see lines 55-59). Moreover, given the biochemical data presented for R200D VP3, it was surprising that the authors did not perform computational simulations on this mutant. The inclusion of such an experiment would help tie together the in vitro and in silico data and strengthen the manuscript.

Reviewer #3 (Public Review):

Summary:

infectious bursal disease virus (IBDV) is a birnavirus and an important avian pathogen. Interestingly, IBDV appears to be a unique dsRNA virus that uses early endosomes for RNA replication that is more common for +ssRNA viruses such as for example SARS-CoV-2.

This work builds on previous studies showing that IBDV VP3 interacts with PIP3 during virus replication. The authors provide further biophysical evidence for the interaction and map the interacting domain on VP3.

Strengths:

Detailed characterization of the interaction between VP3 and PIP3 identified R200D mutation as critical for the interaction. Cryo-EM data show that VP3 leads to membrane deformation.

Weaknesses:

The work does not directly show that the identified R200 residues are directly involved in VP3-early endosome recruitment during infection. The majority of work is done with transfected VP3 protein (or in vitro) and not in virus-infected cells.

Additional controls such as the use of PIP3 antagonizing drugs in infected cells together with a colocalization study of VP3 with early endosomes would strengthen the study.

In addition, it would be advisable to include a control for cryo-EM using liposomes that do not contain PIP3 but are incubated with HIS-VP3-FL. This would allow ruling out any unspecific binding that might not be detected on WB.

The authors also do not propose how their findings could be translated into drug development that could be applied to protect poultry during an outbreak. The title of the manuscript is broad and would improve with rewording so that it captures what the authors achieved.

Author Response

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

Thank you once again for your patience and guidance through this revision process. I would like to add an important aspect to our previous discussion regarding the identification and impact of potential contaminants in our study.

In recent years, advanced tools such as SCRuB (recently published in Nature Biotechnology, DOI:10.1038/s41587-023-01696-w) and the widely-used tool decontam have been developed to address the issue of contaminants in metagenomic studies. These tools primarily operate based on sequence similarity, identifying potential contaminants by marking and removing those found in only a minority of samples or those that display patterns indicative of laboratory contamination.

As the reviewer rightly pointed out, contaminants are often rare species that appear in very few samples. Our study, focusing on high-abundance species in the vaginal microbiome, is less susceptible to the influences of such rare contaminants. This approach aligns with the methodology employed by leading research groups in the field, such as Professor Jacques Ravel's lab. Their decision not to use blank controls in several of their studies on the female reproductive tract microbiome likely stems from a similar understanding — that the impact of rare contaminants is minimal on the study's conclusions, especially when high-abundance species are the main focus.

We believe that the methodologies and tools currently available for contaminant identification and removal, while highly effective for their intended purpose, reinforce our decision to focus on high-abundance species. This focus minimizes the potential impact of rare contaminants on our study's conclusions. In light of this, our study's methodology remains robust and well-suited for achieving our research objectives.

In our revised manuscript, we will include a discussion of these points, further clarifying our approach and the rationale behind our methodological choices. We hope that this additional information will address the concerns raised and provide a clearer understanding of the context and reliability of our findings.

Thank you for considering these additional points. We look forward to your feedback on our revised manuscript.

Author response:

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

We thank the reviewers for their thoughtful comments. We were pleased that they thought our study was "well crafted and written", "important", and that it provides a "valuable resource for researchers studying color vision". They also expressed several constructive criticisms, concerning – among other things – the lack of details regarding experimental procedures and analysis, the challenge in relating retinal data to cortical recordings, and consistency of results across animals. In response to the reviewers’ comments and following their suggestions, we performed additional analyses, and substantially revised the paper:

We added a section in the Discussion about "Limitations of the stimulus paradigm". In addition, we added a new Suppl. Figure that illustrates the effect of deconvolution of calcium traces on our results and clarified in the text why we use deconvolved signals for all analyses. The new Suppl. Figure also shows an additional analysis with a more conservative threshold of neuron exclusion.

We now clarify how retinal signaling relates to our cortical results and rewrote the text to be more conservative regarding our conclusions.

In addition, we added a new Suppl. Figure showing the key analyses from Figures 2 and 4 separately for each animal. We now mention consistency across animals in the Results section and clearly state which analyses were performed an data pooled across animals.

We are positive that these additions address the issues raised by the reviewers. Please find our point-by-point replies to all comments below.

eLife assessment

Franke et al. explore and characterize the color response properties in the mouse primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The data is solid; however, the evidence supporting some conclusions and details about some procedures are incomplete. In its current form, the paper makes a useful contribution to how color is coded in mouse V1. Significance would be enhanced with some additional analyses and resolution of some technical issues.

We thank the reviewers for appreciating our manuscript and their thoughtful comments.

Referee 1 (Remarks to the Author):

Summary:

In this study, Franke et al. explore and characterize the color response properties across the primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The authors use awake-behaving 2P imaging to define the spectral response properties of visual interneurons in Layer 2/3. They find that opponent responses are more prominent at photopic light levels, and diversity in color opponent responses exists across the visual science, with green ON/ UV OFF responses being stronger represented in the upper visual field. This is argued to be relevant for detecting certain features that are more salient when the chromatic space is used, possibly due to noise reductions.

Strengths:

The work is well crafted and written and provides a thorough characterization that reveals an uncharacterized diversity of visual properties in V1. I find this characterization important because it reveals how strongly chromatic information can modulate the response properties in V1. In the upper visual field, 25% of the cells differentially relay chromatic information, and one may wonder how this information will be integrated and subsequently used to aid vision beyond the detection of color per see. I personally like the last paragraph of the discussion that highlights this fact.

We thank the reviewer for appreciating our manuscript.

Weaknesses: One major point highlighted in this paper is the fact that Green ON/UV OFF responses are not generated in the retina. But glancing through the literature, I saw this is not necessarily true. Fig 1. of Joesch and Meister, a paper cited, shows this can be the case. Thus, I would not emphasize that this wasn’t present in the retina. This is a minor point, but even if the retina could not generate these signals, I would be surprised if the diversity of responses would only arise through feed-forward excitation, given the intricacies of cortical connectivity. Thus, I would argue that the argument holds for most of the responses seen in V1; they need to be further processed by cortical circuitries.

We thank the reviewer for this comment. When analyzing available data from the retina using a similar center-surround color flicker stimulus (Szatko et al. 2020), we found that Green On/UV Off color opponency is very rare in the RF center of retinal ganglion cells (Suppl. Fig. 5). This suggests that center Green On/UV Off color opponency in V1 neurons is not inherited by the RF center of retinal neurons. However, we agree with the reviewer that retinal neurons might still contribute to V1 color opponency, for example by being center-surround color opponent (e.g. Joesch et al. 2016 and Szatko et al. 2020). We rephrased the text to acknowledge this fact.

This takes me to my second point, defining center and surround. The center spot is 37.5 deg of visual angle, more than 1 mm of the retinal surface. That means that all retinal cells, at least half and most likely all of their surrounds will also be activated. Although 37.5 deg is roughly the receptive field size previously determined for V1 neurons, the one-to-one comparison with retinal recording, particularly with their center/surround properties, is difficult. This should be discussed. I assume that the authors tried a similar approach with sparse or dense checker white noise stimuli. If so, it would be interesting if there were better ways of defining the properties of V1 neurons on their complex/simple receptive field properties to define how much of their responses are due to an activation of the true "center" or a coactivation of the surround. Interestingly, at least some of the cells (Fig. 1d, cells 2 and 5) don’t have a surround. Could it be that in these cases, the "center" and "surround" are being excited together? How different would the overall statistics change if one used a full-filed flicker stimulus instead of a center/surround stimulus? How stable are the results if the center/surround flicker stimulus is shifted? These results won’t change the fact that chromatic coding is present in the VC and that there are clear differences depending on their position, but it might change the interpretation. Thus, I would encourage you to test these differences and discuss them.

Thanks for this comment. We agree with the reviewer that a one-to-one comparison of retina and V1 data is challenging, due to differences in both RF and stimulus size. We rephrased the Results text to clarify this point and now also mention it in the Discussion.

To be able to record from many V1 neurons simultaneously, we used a stimulus size of 37.5 degree visual angle in diameter, which is slightly larger than center RFs of single V1 neurons. As the reviewer mentions, the disadvantage of this approach is that the stimulus is only roughly centered on the neurons’ center RFs. To reduce the impact of potential stimulus misalignment on our results, we used the following steps:

For each recording, we positioned the monitor such that the mean RF across all neurons lies within the center of the stimulus field of view.

We confirmed that this procedure results in good stimulus alignment for the large majority of recorded neurons within individual recording fields by using a sparse noise stimulus (Suppl. Fig. 1a-c). Specifically, we found that for 83% of tested neurons, more than two thirds of their center RF, determined by the sparse noise stimulus, overlapped with the center spot of the color noise stimulus.

For analysis, we excluded neurons without a significant center STA, which may be caused by misalignment of the stimulus.

Together, we believe these points strongly suggest that the center spot and the surround annulus of the noise stimulus predominantly drive center (i.e. classical RF) and surround (i.e. extraclassical RF), respectively, of the recorded V1 neurons. This is further supported by the fact that color response types identified using an automated clustering method were robust across mice (Suppl. Fig. 6c), indicating consistent stimulus centering.

Nevertheless, we cannot exclude that the stimulus was misaligned for a subset of the recorded neurons used for analysis. We agree with the reviewer that such misalignment might have contributed to cells not having surround STAs, due to simultaneous activation of antagonistic center and surround RF components by the surround stimulus. While a full-field stimulus would get rid of the misalignment problem, it would not allow to study color tuning in center and surround RF components separately. Instead, one could compare the results of our approach with an approach that centers the stimulus on individual neurons. However, we believe that performing these additional experiments is out of the scope of the current study.

To acknowledge the experimental limitations of our study and the concerns brought up by the reviewer, we now explicitly mention the steps we perform to reduce the effects of stimulus misalignment in the Results section and discuss the problem of stimulus alignment in the Discussion. We believe these changes will help the reader to interpret our results.

Referee 2 (Remarks to the Author):

Summary:

Franke et al. characterize the representation of color in the primary visual cortex of mice and how it changes across the visual field, with a particular focus on how this may influence the ability to detect aerial predators. Using calcium imaging in awake, head-fixed mice, they characterize the properties of V1 neurons (layer 2/3) using a large center-surround stimulation where green and ultra-violet were presented in random combinations. Using a clustering approach, a set of functional cell-types were identified based on their preference to different combinations of green and UV in their center and surround. These functional types were demonstrated to have varying spatial distributions in V1, including one neuronal type (Green-ON/UV-OFF) that was much more prominent in the posterior V1 (i.e. upper visual field). Modelling work suggests that these neurons likely support the detection of predator-like objects in the sky.

Strengths:

The large-scale single-cell resolution imaging used in this work allows the authors to map the responses of individual neurons across large regions of the visual cortex. Combining this large dataset with clustering analysis enabled the authors to group V1 neurons into distinct functional cell types and demonstrate their relative distribution in the upper and lower visual fields. Modelling work demonstrated the different capacity of each functional type to detect objects in the sky, providing insight into the ethological relevance of color opponent neurons in V1.

We thank the reviewer for appreciating our manuscript.

Weaknesses:

While the study presents solid evidence a few weaknesses exist, including the size of the dataset, clarity regarding details of data included in each step of the analysis and discussion of caveats of the work. The results presented here are based on recordings of 3 mice. While the number of neurons recorded is reasonably large (n > 3000) an analysis that tests for consistency across animals is missing. Related to this, it is unclear how many neurons at each stage of the analysis come from the 3 different mice (except for Suppl. Fig 4).

Thank you for this comment. We apologize that the original manuscript did not clearly indicate the consistency of our results across animals. We have revised the manuscript in the following ways:

We have added an additional Suppl. Figure, which shows the variability of the data within and across animals (Suppl. Fig. 4). Specifically, we show the distribution of color and luminance selectivity for (i) center and surround components of V1 RFs and (ii) for upper and lower visual field. This data is used for all analyses shown in Figures 2-4. The figure legend of this figure also states the number of neurons per animal.

We now clearly state in the Results section that all analyses in the main figures were performed by pooling data across animals, and refer to the Suppl. Figures for consistency across animals.

We believe these changes help the reader to interpret our results.

Finally, the paper would greatly benefit from a more in depth discussion of the caveats related to the conclusion drawn at each stage of the analysis. This is particularly relevant regarding the caveats related to using spike triggered averages to assess the response preferences of ON-OFF neurons, and the conclusions drawn about the contribution of retinal color opponency.

Thanks. We substantially revised the text to discuss caveats and limitations of the approach. For example, we added a section into the Discussion called "Limitations of the stimulus paradigm". In addition, we clarified how retinal signals relate to cortical ones and phrased our conclusions more conservatively.

The authors provide solid evidence to support an asymmetric distribution of color opponent cells in V1 and a reduced color contrast representation in lower light levels. Some statements would benefit from more direct evidence such as the integration of upstream visual signals for color opponency in V1.

Based on the comments from Reviewer 1, we have rephrased the statements regarding the integration of upstream visual signals for color opponency in V1. We think these revisions increase the clarity of the results and help the reader with interpretation.

Overall, this study will be a valuable resource for researchers studying color vision, cortical processing, and the processing of ethologically relevant information. It provides a useful basis for future work on the origin of color opponency in V1 and its ethological relevance.

Thanks! We thank the reviewer again for the helpful comments.

Referee 3 (Remarks to the Author):

This paper studies chromatic coding in mouse primary visual cortex. Calcium responses of a large collection of cells are measured in response to a simple spot stimulus. These responses are used to estimate chromatic tuning properties - specifically sensitivity to UV and green stimuli presented in a large central spot or a larger still surrounding region. Cells are divided based on their responses to these stimuli into luminance or chromatic sensitive groups. Several technical concerns limit how clearly the data support the conclusions. If these issues can be fixed, the paper would make a valuable contribution to how color is coded in mouse V1.

We thank the reviewer for the helpful comments.

Analysis: The central tool used to analyze the data is a "spike triggered average" of the responses to randomly varying stimuli. There are several steps in this analysis that are not documented, and hence evaluating how well it works is difficult. Central to this is that the paper does not measure spikes. Instead, measured calcium traces are converted to estimated spike rates, which are then used to estimate STAs. There are no raw calcium traces shown, and the approach to estimate spike rates is not described in any detail. Confirming the accuracy of these steps is essential for a reader to be able to evaluate the paper. Further, it is not clear why the linear filters connecting the recorded calcium traces and the stimulus cannot be estimated directly, without the intermediate step of estimating spike rates.

Thank you for this comment. We have used the genetically encoded calcium sensor GCaMP6s in our recordings. This sensor is a very sensitive GCaMP6 variant, but also one with slow kinetics. To remove the effect of the slow sensor kinetics from recorded calcium responses, the recorded traces are commonly deconvolved with the impulse function of the sensor to obtain the deconvolved calcium traces. We now include this reasoning in the Results section. To illustrate the effect of the deconvolution, we added a new Suppl. Figure (Suppl. Fig. 2) showing raw calcium and deconvolved traces, and the STAs estimated from both types of traces. This illustrates that the results regarding neuronal color preferences are consistent across raw and deconvolved calcium traces.

We agree with the reviewer that the term STA might be confusing. We have replaced it with the term "even-triggered-average" (ETA). In addition, we have replaced the phrase "estimated spike rate" with "deconvolved calcium trace" throughout the manuscript because the unit of the deconvolved traces is not interpretable, like spike rate would be (spikes per second). In the revised version, we now clarify in the Methods section that we estimate the ETAs based on deconvolved calcium traces, which is correlated with and an approximation for spike rate.

A further issue about the STAs is that the inclusion criterion (correlation of predicted vs measured responses of 0.25) is pretty forgiving. It would be helpful to see a distribution of those correlation values, and some control analyses to check whether the STA is providing a sufficiently accurate measure to support the results (e.g. do the central results hold for the cells with the highest correlations).

We thank the reviewer for this comment. To exclude noisy neurons from analysis, we used the following procedure:

For each of the four stimulus conditions (center and surround for green and UV stimuli), kernel quality was measured by comparing the variance of the STA with the variance of the baseline, defined as the first 500 ms of the STA. Only cells with at least 10-times more variance of the kernel compared to baseline for UV or green center STA were considered for further analysis.

We have added the distribution of quality values to a new Suppl. Figure (Suppl. Fig. 2d,e). We now also show the percentage of neurons above threshold, given different quality thresholds. Finally, we have repeated the analysis shown in Figure 2 for a much more conservative threshold, including only the top 25% of neurons (Suppl. Fig. 2e,f). We now mention this new analysis in the Methods and Results section.

Limitations of stimulus choice: The paper relies on responses to a large (37.5 degree diameter) modulated spot and surrounding region. This spot is considerably larger than the receptive fields of both V1 cells and retinal ganglion cells. As a result, the spot itself is very likely to strongly activate both center and surround mechanisms, and responses of cells are likely to depend on where the receptive fields are located within the spot (and, e.g., how much of the true neural surround samples the center spot vs the surround region). The impact of these issues on the conclusions is considered briefly at the start of the results but needs to be evaluated in considerably more detail. This is particularly true for retinal ganglion cells given the size of their receptive fields (see also next point).

We agree with the reviewer that the centering of the stimulus is critical and apologize if this point was not discussed sufficiently. To be able to record from many V1 neurons simultaneously, we used a stimulus size of 37.5 degree visual angle in diameter, which is slightly larger than center RFs of single V1 neurons. As the reviewer mentions, the disadvantage of this approach is that the stimulus is only roughly centered on the neurons’ center RFs. To reduce the impact of potential stimulus misalignment on our results, we have used different experimental and analysis steps and controls (see also second comment of Reviewer 1):

For each recording, we positioned the monitor such that the mean RF across all neurons lies within the center of the stimulus field of view.

We confirmed that this procedure results in good stimulus alignment for the large majority of recorded neurons within individual recording fields by using a sparse noise stimulus (Suppl. Fig. 1a-c). Specifically, we found that for 83% of tested neurons, more than two thirds of their center RF, determined by the sparse noise stimulus, overlapped with the center spot of the color noise stimulus.

For analysis, we excluded neurons without a significant center STA, which may be caused by misalignment of the stimulus.

We now mention those clearly in the Results section and added the limitations of our approach to the Discussion section.

Comparison with retina: A key conclusion of the paper is that the chromatic tuning in V1 is not inherited from retinal ganglion cells. This conclusion comes from comparing chromatic tuning in a previously-collected data set from retina with the present results. But the retina recordings were made using a considerably smaller spot, and hence it is not clear that the comparison made in the paper is accurate. This issue may be handled by the analysis presented in the paper, but if so it needs to be described more clearly. The paper from which the retina data is taken argues that rod-cone chromatic opponency originates largely in the outer retina. This mechanism would be expected to be shared across retinal outputs. Thus it is not clear how the Green-On/UV-Off vs Green-Off/UV-On asymmetry could originate. This should be discussed.

We agree with the reviewer that a one-to-one comparison of retina and V1 data is challenging, due to differences in both RF and stimulus size. We rephrased the Results text to clarify this point and now also mention it in the Discussion.

When analyzing available data from the retina using a similar center-surround color flicker stimulus (Szatko et al. 2020), we found that Green On/UV Off color opponency is very rare in the RF center of retinal ganglion cells (Suppl. Fig. 5). This suggests that center Green On/UV Off color opponency in V1 neurons is not inherited by the RF center of retinal neurons. However, we agree with the reviewer that retinal neurons might still contribute to V1 color opponency, for example by being center-surround color opponent (e.g. Joesch et al. 2016 and Szatko et al. 2020). We rephrased the text to acknowledge this fact.

Residual chromatic cells at low mesopic light levels The presence of chromatically tuned cells at the lowest light level probed is surprising. The authors describe these conditions as rod-dominated, in which case chromatic tuning should not be possible. This again is discussed only briefly. It either reflects the presence of an unexpected pathway that amplifies weak cone signals under low mesopic conditions such that they can create spectral opponency or something amiss in the calibrations or analysis. Data collected at still lower light levels would help resolve this.

Thank you for this comment. We call the lowest light level "low mesopic" and "rod-dominated" because the spectral contrast of V1 center responses in posterior recording fields is green-shifted for this light level (Fig. 3a). This is only expected if responses in the UV-cone dominant ventral retina are predominantly driven by rod photoreceptors. We now explain this rationale in the Results section. In addition, we mention in the Discussion that future studies are required to test whether cone signals need to be amplified for low light levels. While we agree with the reviewer that it would be exciting to use even lower light levels during recordings, we believe this is out of the scope of the current study due to the technical challenges involved in achieving scotopic stimulation.

eLife assessment

Franke et al. explore and characterize the color response properties in the mouse primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The data is solid; however, the evidence supporting some conclusions is incomplete. In its current form, the paper makes a useful contribution to how color is coded in mouse V1. Significance would be enhanced with some additional analyses and a clearer discussion of the limitations of the data presented.

Reviewer #1 (Public Review):

Summary:

In this study, Franke et al. explore and characterize color response properties across primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The authors use awake 2P imaging to define the spectral response properties of visual interneurons in layer 2/3. They find that opponent responses are more pronounced at photopic light levels, and that diversity in color opponent responses exists across the visual field, with green ON/ UV OFF responses more strongly represented in the upper visual field. This is argued to be relevant for the detection of certain features that are more salient when using chromatic space, possibly due to noise reduction. In the revised version, Franke et al. have addressed the potential pitfalls in the discussion, which is an important point for the non-expert reader. Thus, this study provides a solid characterization of the color properties of V1 and is a valuable addition to visual neuroscience research.

My remaining concerns are based more on the interpretation. I'm still not convinced by the statement "This type of color-opponency in the receptive field center of V1 neurons was not present in the receptive field center of retinal ganglion cells and, therefore, is likely computed by integrating center and surround information downstream of the retina." and I would suggest rewording it in the abstract.

As discussed previously and now nicely added to the discussion, it is difficult to make a direct comparison given the different stimulus types used to characterize the retina and V1 recordings and the different levels of adaptation in both tissues. I will leave this point to the discussion, which allows for a more nuanced description of the phenomenon. Why do I think this is important? In the introduction, the authors argue that "the discrepancy [of previous studies] may be due to differences in stimulus design or light levels." However, while different light levels can be tested in V1, this cannot be done properly in the retina with 2P experiments. To address this, one would have to examine color-opponency in RGC terminals in vivo, which is beyond the scope of this study. Addressing these latter points directly in the discussion would, in my opinion, only strengthen the study.

Reviewer #2 (Public Review):

Summary:

Franke et al. characterize the representation of color in the primary visual cortex of mice, highlighting how this changes across the visual field. Using calcium imaging in awake, head-fixed mice, they characterize the properties of V1 neurons (layer 2/3) using a large center-surround stimulation where green and ultra-violet colors were presented in random combinations. Clustering of responses revealed a set of functional cell-types based on their preference to different combinations of green and UV in their center and surround. These functional types were demonstrated to have different spatial distributions across V1, including one neuronal type (Green-ON/UV-OFF) that was much more prominent in the posterior V1 (i.e. upper visual field). Modelling work suggests that these neurons likely support the detection of predator-like objects in the sky.

Strengths:

The large-scale single-cell resolution imaging used in this work allows the authors to map the responses of individual neurons across large regions of the visual cortex. Combining this large dataset with clustering analysis enabled the authors to group V1 neurons into distinct functional cell types and demonstrate their relative distribution in the upper and lower visual fields. Modelling work demonstrated the different capacity of each functional type to detect objects in the sky, providing insight into the ethological relevance of color opponent neurons in V1.

Weaknesses:

While the study presents convincing evidence about the asymmetric distribution of color-opponent neurons in V1, the paper would greatly benefit from a more in-depth discussion of the caveats related to the conclusions drawn about their origin. This is particularly relevant regarding the conclusion drawn about the contribution of color opponent neurons in the retina. The mismatch between retinal color opponency and V1 color opponency could imply that this feature is not solely inherited from the retina, however, there are other plausible explanations that are not discussed here. Direct evidence for this statement remains weak.

In addition, the paper would benefit from adding explicit neuron counts or percentages to the quadrants of each of the density plots in Figures 2-5. The variance explained by the principal components does not capture the percentage of color opponent cells. Additionally, there appear to be some remaining errors in the figure legend and labels that have not been addressed (e.g. '??' in Fig 2 legend).

Overall, this study will be a valuable resource for researchers studying color vision, cortical processing, and the processing of ethologically relevant information. It provides a useful basis for future work on the origin of color opponency in V1 and its ethological relevance.

Reviewer #3 (Public Review):

This paper studies chromatic coding in mouse primary visual cortex. Calcium responses of a large collection of cells are measured in response to a simple spot stimulus. These responses are used to estimate chromatic tuning properties - specifically sensitivity to UV and green stimuli presented in a large central spot or a larger still surrounding region. Cells are divided based on their responses to these stimuli into luminance or chromatic sensitive groups. The results are interesting and many aspects of the experiments and conclusions are well done; several technical concerns, however, limit the support for several main conclusions,

Limitations of stimulus choice<br /> The paper relies on responses to a large (37.5 degree diameter) modulated spot and surround region. This spot is considerably larger than the receptive fields of both V1 cells and retinal ganglion cells (it is twice the area of the average V1 receptive field). As a result, the spot itself is very likely to strongly activate both center and surround mechanisms, and responses of cells are likely to depend on where the receptive fields are located within the spot (and, e.g., how much of the true neural surround samples the center spot vs the surround region). Most importantly, the surrounds of most of the recorded cells will be strongly activated by the central spot. This brings into question statements in the paper about selective activation of center and surround (e.g. page 2, right column). This in turn raises questions about several subsequent analyses that rely on selective center and surround activation.

Comparison with retina<br /> A key conclusion of the paper is that the chromatic tuning in V1 is not inherited from retinal ganglion cells. This conclusion comes from comparing chromatic tuning in a previously-collected data set from retina with the present results. But the retina recordings were made using a considerably smaller spot, and hence it is not clear that the comparison made in the paper is accurate. For example, the stimulus used for the V1 experiments almost certainly strongly stimulates both center and surround of retinal ganglion cells. The text focuses on color opponency in the receptive field centers of retinal ganglion cells, but center-surround opponency seems at least as relevant for such large spots. This issue needs to be described more clearly and earlier in the paper.

Limitations associated with ETA analysis<br /> One of the reviewers in the previous round of reviews raised the concern that the ETA analysis may not accurately capture responses of cells with nonlinear receptive field properties such as On/Off cells. This possibility and whether it is a concern should be discussed.

Discrimination performance poor<br /> Discriminability of color or luminance is used as a measure of population coding. The discrimination performance appears to be quite poor - with 500-1000 neurons needed to reliably distinguish light from dark or green from UV. Intuitively I would expect that a single cell would provide such discrimination. Is this intuition wrong? If not, how do we interpret the discrimination analyses?

Author response:

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

As you will see, the main changes in the revised manuscript pertain to the structure and content of the introduction. Specifically, we have tried to more clearly introduce our paradigm, the rationale behind the paradigm, why it is different from learning paradigms, and why we study “relief”.

In this rebuttal letter, we will go over the reviewers’ comments one-by-one and highlight how we have adapted our manuscript accordingly. However, because one concern was raised by all reviewers, we will start with an in-depth discussion of this concern.

The shared concern pertained to the validity of the EVA task as a model to study threat omission responses. Specifically, all reviewers questioned the effectivity of our so-called “inaccurate”, “false” or “ruse” instructions in triggering an equivalent level of shock expectancy, and relatedly, how this effectivity was affected by dynamic learning over the course of the task.

We want to thank the reviewers for raising this important issue. Indeed, it is a vital part of our design and it therefore deserves considerable attention. It is now clear to us that in the previous version of the manuscript we may have focused too little on why we moved away from a learning paradigm, and how we made sure that the instructions were successful at raising the necessary expectations; and how the instructions were affected by learning. We believe this has resulted in some misunderstandings, which consequently may have cast doubts on our results. In the following sections, we will go into these issues.

The rationale behind our instructed design

The main aim of our study was to investigate brain responses to unexpected omissions of threat in greater detail by examining their similarity to the reward prediction error axioms (Caplin & Dean, 2008), and exploring the link with subjective relief. Specifically, we hypothesized that omission-related responses should be dependent on the probability and the intensity of the expected-but-omitted aversive event (i.e., electrical stimulation), meaning that the response should be larger when the expected stimulation was stronger and more expected, and that fully predicted outcomes should not trigger a difference in responding.

To this end, we required that participants had varying levels of threat probability and intensity predictions, and that these predictions would most of the time be violated. Although we fully agree with the reviewers that fear conditioning and extinction paradigms can provide an excellent way to track the teaching properties of prediction error responses (i.e., how they are used to update expectancies on future trials), we argued that they are less suited to create the varying probability and intensity-related conditions we required (see Willems & Vervliet, 2021). Specifically, in a standard conditioning task participants generally learn fast, rendering relatively few trials on which the prediction is violated. As a result, there is generally little intraindividual variability in the prediction error responses. This precludes an in-depth analysis of the probability-related effects. Furthermore, conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted. As a result, intensity-related effects cannot be tested. Finally, because CS-US contingencies change over the course of a fear conditioning and extinction study (e.g. from acquisition to extinction), there is never complete certainty about when the US will (not) follow. This precludes a direct comparison of fully predicted outcomes.

Another added value of studying responses to the prediction error at threat omission outside a learning context is that it can offer a way to disentangle responses to the violation of threat expectancy, with those of subsequent expectancy updating.

Also note that Rutledge and colleagues (2010), who were the first to show that human fMRI responses in the Nucleus Accumbens comply to the reward prediction error axioms also did not use learning experiences to induce expectancy. In that sense, we argued it was not necessary to adopt a learning paradigm to study threat omission responses.

Adaptations in the revised manuscript: We included two new paragraphs in the introduction of the revised manuscript to elaborate on why we opted not to use a learning paradigm in the present study (lines 90-112).

“However, is a correlation with the theoretical PE over time sufficient for neural activations/relief to be classified as a PE-signal? In the context of reward, Caplin and colleagues proposed three necessary and sufficient criteria all PE-signals should comply to, independent of the exact operationalizations of expectancy and reward (the socalled axiomatic approach24,25; which has also been applied to aversive PE26–28). Specifically, the magnitude of a PE signal should: (1) be positively related to the magnitude of the reward (larger rewards trigger larger PEs); (2) be negatively related to likelihood of the reward (more probable rewards trigger smaller PEs); and (3) not differentiate between fully predicted outcomes of different magnitudes (if there is no error in prediction, there should be no difference in the PE signal).”

“It is evident that fear conditioning and extinction paradigms have been invaluable for studying the role of the threat omission PE within a learning context. However, these paradigms are not tailored to create the varying intensity and probability-related conditions that are required to evaluate the threat omission PE in the light of the PE axioms. First, conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted. As a result, the magnitude-related axiom cannot be tested. Second, in conditioning tasks people generally learn fast, rendering relatively few trials on which the prediction is violated. As a result, there is generally little intra-individual variability in the PE responses. Moreover, because of the relatively low signal to noise ratio in fMRI measures, fear extinction studies often pool across trials to compare omission-related activity between early and late extinction16, which further reduces the necessary variability to properly evaluate the probability axiom. Third, because CS-US contingencies change over the course of the task (e.g. from acquisition to extinction), there is never complete certainty about whether the US will (not) follow. This precludes a direct comparison of fully predicted outcomes. Finally, within a learning context, it remains unclear whether PErelated responses are in fact responses to the violation of expectancy itself, or whether they are the result of subsequent expectancy updating.”

Can verbal instructions be used to raise the expectancy of shock?

The most straightforward way to obtain sufficient variability in both probability and intensityrelated predictions is by directly providing participants with instructions on the probability and intensity of the electrical stimulation. In a previous behavioral study, we have shown that omission responses (self-reported relief and omission SCR) indeed varied with these instructions (Willems & Vervliet, 2021). In addition, the manipulation checks that are reported in the supplemental material provided further support that the verbal instructions were effective at raising the associated expectancy of stimulation. Specifically, participants recollected having received more stimulations after higher probability instructions (see Supplemental Figure 2). Furthermore, we found that anticipatory SCR, which we used as a proxy of fearful expectation, increased with increasing probability and intensity (see Supplemental Figure 3). This suggests that it is not necessary to have expectation based on previous experience if we want to evaluate threat omission responses in the light of the prediction error axioms.

Adaptations in the revised manuscript: We more clearly referred to the manipulation checks that are presented in the supplementary material in the results section of the main paper (lines 135-141).

“The verbal instructions were effective at raising the expectation of receiving the electrical stimulation in line with the provided probability and intensity levels. Anticipatory SCR, which we used as a proxy of fearful expectation, increased as a function of the probability and intensity instructions (see Supplementary Figure 3). Accordingly, post-experimental questions revealed that by the end of the experiment participants recollected having received more stimulations after higher probability instructions, and were willing to exert more effort to prevent stronger hypothetical stimulations (see Supplementary Figure 2).”

How did the inconsistency between the instructed and experienced probability impact our results?

All reviewers questioned how the inconsistency between the instructed and experienced probability might have impacted the probability-related results. However, judging from the way the comments were framed, it seems that part of the concern was based on a misunderstanding of the design we employed. Specifically, reviewer 1 mentions that “To ensure that the number of omissions is similar across conditions, the task employs inaccurate verbal instructions; I.e., 25% of shocks are omitted regardless of whether subjects are told that the probability is 100%, 75%, 50%, 25%, 0%.”, and reviewer 3 states that “... the fact remains that they do not get shocks outside of the 100% probability shock. So learning is occurring, at least for subjects who realize the probability cue is actually a ruse.” We want to emphasize that this was not what we did, and if it were true, we fully agree with the reviewers that it would have caused serious trust- and learning related issues, given that it would be immediately evident to participants that probability instructions were false. It is clear that under such circumstances, dynamic learning would be a big issue.

However, in our task 0% and 100% instructions were always accurate. This means that participants never received a stimulus following 0% instructions and always received the stimulation of the given intensity on the 100% instructions (see Supplemental Figure 1 for an overview of the trial types). Only for the 25%, 50% and 75% trials an equal reinforcement rate (25%) was maintained, meaning that the stimulation followed in 25% of the trials, irrespective of whether a 25%, 50% or 75% instruction was given. The reason for this was that we wanted to maximize and balance the number of omission trials across the different probability levels, while also keeping the total number of presentations per probability instruction constant. We reasoned that equating the reinforcement rate across the 25%, 50% and 75% instructions should not be detrimental, because (1) in these trials there was always the possibility that a stimulation would follow; and (2) we instructed the participants that each trial is independent of the previous ones, which should have discouraged them to actively count the number of shocks in order to predict future shocks.

Adaptations in the revised manuscript: We have tried to further clarify the design in several sections of the manuscript, including the introduction (lines 121-125), results (line 220) and methods (lines 478-484) sections:

Adaptation in the Introduction section: “Specifically, participants received trial-by-trial instructions about the probability (0%, 25%, 50%, 75% and 100%) and intensity (weak, moderate, strong) of a potentially painful upcoming electrical stimulation, time-locked by a countdown clock (see Fig.1A). While stimulations were always delivered on 100% trials and never on 0% trials, most of the other trials (25%-75%) did not contain the expected stimulation and hence provoked an omission PE.”

Adaptation in the Results section: “Indeed, the provided instructions did not map exactly onto the actually experienced probabilities, but were all followed by stimulation in 25% on the trials (except for the 0% trials and the 100% trials).”

Adaptation in the Methods section: “Since we were mainly interested in how omissions of threat are processed, we wanted to maximize and balance the number of omission trials across the different probability and intensity levels, while also keeping the total number of presentations per probability and intensity instruction constant. Therefore, we crossed all non-0% probability levels (25, 50, 75, 100) with all intensity levels (weak, moderate, strong) (12 trials). The three 100% trials were always followed by the stimulation of the instructed intensity, while stimulations were omitted in the remaining nine trials. Six additional trials were intermixed in each run: Three 0% omission trials with the information that no electrical stimulation would follow (akin to 0% Probability information, but without any Intensity information as it does not apply); and three trials from the Probability x Intensity matrix that were followed by electrical stimulation (across the four runs, each Probability x Intensity combination was paired at least once, and at most twice with the electrical stimulation).”

Could the incongruence between the instructed and experienced reinforcement rate have detrimental effects on the probability effect? We agree with reviewer 2 that it is possible that the inconsistency between instructed and experienced reinforcement rates could have rendered the exact probability information less informative to participants, which might have resulted in them paying less attention to the probability information whenever the probability was not 0% or 100%. This might to some extent explain the relatively larger difference in responding between 0% and 25% to 75% trials, but the relatively smaller differences between the 25% to 75% trials.

However, there are good reasons to believe that the relatively smaller difference between 25% to 75% trials was not caused by the “inaccurate” nature of our instructions, but is inherent to “uncertain” probabilities.

We added a description of these reasons to the supplementary materials in a supplementary note (supplementary note 4; lines 97-129 in supplementary materials), and added a reference to this note in the methods section (lines 488-490).

“Supplementary Note 4: “Accurate” probability instructions do not alter the Probability-effect

A question that was raised by the reviewers was whether the inconsistency between the probability instruction and the experienced reinforcement rate could have detrimental effects on the Probability-related results; especially because the effect of Probability was smaller when only including non-0% trials.

However, there are good reasons to believe that the relatively smaller difference between 25% to 75% trials was not caused by the “inaccurate” nature of our instructions, but that they are inherent to “uncertain” probabilities.

First, in a previously unpublished pilot study, we provided participants with “accurate” probability instructions, meaning that the instruction corresponded to the actual reinforcement rate (e.g., 75% instructions were followed by a stimulation in 75% of the trials etc.). In line with the present results and our previous behavioral study (Willems & Vervliet, 2021), the results of this pilot (N = 20) showed that the difference in the reported relief between the different probability levels was largest when comparing 0% and the rest (25%, 50% and 75%). Furthermore the overall effect size of Probability (excluding 0%) matched the one of our previous behavioral study (Willems & Vervliet, 2021): ηp2 = +/- 0.50.”

Author response image 1.

Main effect of Probability including 0% : F(1.74,31.23) = 53.94, p < .001, ηp2 = 0.75

Main effect of Probability excluding 0%: F(1.50, 28.43) = 21.03, p < .001, ηp2 = 0.53

Second, also in other published studies that used CSs with varying reinforcement rates (which either included explicit written instructions of the reinforcement rates or not) showed that the difference in expectations, anticipatory SCR or omission SCR was largest when comparing the CS0% to the other CSs of varying reinforcement rates (Grings & Sukoneck, 1971; Öhman et al., 1973; Ojala et al., 2022).

Together, this suggests that when there is a possibility of stimulation, any additional difference in probability will have a smaller effect on the omission responses, irrespective of whether the underlying reinforcement rate is accurate or not.

Adaptation to methods section: “Note that, based on previous research, we did not expect the inconsistency between the instructed and perceived reinforcement rate to have a negative effect on the Probability manipulation (see Supplementary Note 4).”

Did dynamic learning impact the believability of the instructions?

Although we tried to minimize learning in our paradigm by providing instructions that trials are independent from one another, we agree with the reviewers that this cannot preclude all learning. Any remaining learning effects should present themselves by downweighing the effect of the probability instructions over time. We controlled for this time-effect by including a “run” regressor in our analyses. Results of the Run regressor for subjective relief and omission-related SCR are presented in Supplemental Figure 5. These figures show that although there was a general drop in reported relief pleasantness and omission SCR over time, the effects of probability and intensity remained present until the last run. This indicates that even though some learning might have taken place, the main manipulations of probability and intensity were still present until the end of the task.

Adaptations in the revised manuscript: We more clearly referred to the results of the Blockregressor which were presented in the supplementary material in the results section of the main paper (lines 159-162).

Note that while there was a general drop in reported relief pleasantness and omission SCR over time, the effects of Probability and Intensity remained present until the last run (see Supplementary Figure 5). This further confirms that probability and intensity manipulations were effective until the end of the task.

In the following sections of the rebuttal letter, we will go over the rest of the comments and our responses one by one.

Reviewer #1 (Public Review):

Summary:

Willems and colleagues test whether unexpected shock omissions are associated with reward-related prediction errors by using an axiomatic approach to investigate brain activation in response to unexpected shock omission. Using an elegant design that parametrically varies shock expectancy through verbal instructions, they see a variety of responses in reward-related networks, only some of which adhere to the axioms necessary for prediction error. In addition, there were associations between omission-related responses and subjective relief. They also use machine learning to predict relief-related pleasantness, and find that none of the a priori "reward" regions were predictive of relief, which is an interesting finding that can be validated and pursued in future work.

Strengths:

The authors pre-registered their approach and the analyses are sound. In particular, the axiomatic approach tests whether a given region can truly be called a reward prediction error. Although several a priori regions of interest satisfied a subset of axioms, no ROI satisfied all three axioms, and the authors were candid about this. A second strength was their use of machine learning to identify a relief-related classifier. Interestingly, none of the ROIs that have been traditionally implicated in reward prediction error reliably predicted relief, which opens important questions for future research.

Weaknesses:

To ensure that the number of omissions is similar across conditions, the task employs inaccurate verbal instructions; i.e. 25% of shocks are omitted, regardless of whether subjects are told that the probability is 100%, 75%, 50%, 25%, or 0%. Given previous findings on interactions between verbal instruction and experiential learning (Doll et al., 2009; Li et al., 2011; Atlas et al., 2016), it seems problematic a) to treat the instructions as veridical and b) average responses over time. Based on this prior work, it seems reasonable to assume that participants would learn to downweight the instructions over time through learning (particularly in the 100% and 0% cases); this would be the purpose of prediction errors as a teaching signal. The authors do recognize this and perform a subset analysis in the 21 participants who showed parametric increases in anticipatory SCR as a function of instructed shock probability, which strengthened findings in the VTA/SN; however given that one-third of participants (n=10) did not show parametric SCR in response to instructions, it seems like some learning did occur. As prediction error is so important to such learning, a weakness of the paper is that conclusions about prediction error might differ if dynamic learning were taken into account.

We thank the reviewer for raising this important concern. We believe we replied to all the issues raised in the general reply above.

Lastly, I think that findings in threat-sensitive regions such as the anterior insula and amygdala may not be adequately captured in the title or abstract which strictly refers to the "human reward system"; more nuance would also be warranted.

We fully agree with this comment and have changed the title and abstract accordingly.

Adaptations in the revised manuscript: We adapted the title of the manuscript.

“Omissions of Threat Trigger Subjective Relief and Prediction Error-Like Signaling in the Human Reward and Salience Systems”

Adaptations in the revised manuscript: We adapted the abstract (lines 27-29).

“In line with recent animal data, we showed that the unexpected omission of (painful) electrical stimulation triggers activations within key regions of the reward and salience pathways and that these activations correlate with the pleasantness of the reported relief.”

Reviewer #2 (Public Review):

The question of whether the neural mechanisms for reward and punishment learning are similar has been a constant debate over the last two decades. Numerous studies have shown that the midbrain dopamine neurons respond to both negative and salient stimuli, some of which can't be well accounted for by the classic RL theory (Delgado et al., 2007). Other research even proposed that aversive learning can be viewed as reward learning, by treating the omission of aversive stimuli as a negative PE (Seymour et al., 2004).

Although the current study took an axiomatic approach to search for the PE encoding brain regions, which I like, I have major concerns regarding their experimental design and hence the results they obtained. My biggest concern comes from the false description of their task to the participants. To increase the number of "valid" trials for data analysis, the instructed and actual probabilities were different. Under such a circumstance, testing axiom 2 seems completely artificial. How does the experimenter know that the participants truly believe that the 75% is more probable than, say, the 25% stimulation? The potential confusion of the subjects may explain why the SCR and relief report were rather flat across the instructed probability range, and some of the canonical PE encoding regions showed a rather mixed activity pattern across different probabilities. Also for the post-hoc selection criteria, why pick the larger SCR in the 75% compared to the 25% instructions? How would the results change if other criteria were used?

We thank the reviewer for raising this important concern. We believe the general reply above covers most of the issues raised in this comment. Concerning the post-hoc selection criteria, we took 25% < 75% as criterium because this was a quite “lenient” criterium in the sense that it looked only at the effects of interest (i.e., did anticipatory SCR increase with increasing instructed probability?). However, also when the criterium was more strict (e.g., selecting participants only if their anticipatory SCR monotonically increased with each increase in instructed probability 0% < 25% < 50% < 75% < 100%, N = 11 participants), the probability effect (ωp2 = 0.08), but not the intensity effect, for the VTA/SN remained.

To test axiom 3, which was to compare the 100% stimulation to the 0% stimulation conditions, how did the actual shock delivery affect the fMRI contrast result? It would be more reasonable if this analysis could control for the shock delivery, which itself could contaminate the fMRI signal, with extra confound that subjects may engage certain behavioral strategies to "prepare for" the aversive outcome in the 100% stimulation condition. Therefore, I agree with the authors that this contrast may not be a good way to test axiom 3, not only because of the arguments made in the discussion but also the technical complexities involved in the contrast.

We thank the reviewer for addressing this additional confound. It was indeed impossible to control for the delivery of shock since the delivery of the shock was always present on the 100% trials (and thus completely overlapped with the contrast of interest). We added this limitation to our discussion in the manuscript. In addition, we have also added a suggestion for a contrast that can test the “no surprise equivalence” criterium.

Adaptations in the revised manuscript: We adapted lines 358-364.

“Thus, given that we could not control for the delivery of the stimulation in the 100% > 0% contrast (the delivery of the stimulation completely overlapped with the contrast of interest), it is impossible to disentangle responses to the salience of the stimulation from those to the predictability of the outcome. A fairer evaluation of the third axiom would require outcomes that are roughly similar in terms of salience. When evaluating threat omission PE, this implies comparing fully expected threat omissions following 0% instructions to fully expected absence of stimulation at another point in the task (e.g. during a safe intertrial interval).”

Reviewer #3 (Public Review):

We thank the reviewer for their comments. Overall, based on the reviewer’s comments, we noticed that there was an imbalance between a focus on “relief” in the introduction and the rest of the manuscript and preregistration. We believe this focus raised the expectation that all outcome measures were interpreted in terms of the relief emotion. However, this was not what we did nor what we preregistered. We therefore restructured the introduction to reduce the focus on relief.

Adaptations in the revised manuscript: We restructured the introduction of the manuscript. Specifically, after our opening sentence: “We experience a pleasurable relief when an expected threat stays away1” we only introduce the role of relief for our research in lines 79-89.

“Interestingly, unexpected omissions of threat not only trigger neural activations that resemble a reward PE, they are also accompanied by a pleasurable emotional experience: relief. Because these feelings of relief coincide with the PE at threat omission, relief has been proposed to be an emotional correlate of the threat omission PE. Indeed, emerging evidence has shown that subjective experiences of relief follow the same time-course as theoretical PE during fear extinction. Participants in fear extinction experiments report high levels of relief pleasantness during early US omissions (when the omission was unexpected and the theoretical PE was high) and decreasing relief pleasantness over later omissions (when the omission was expected and the theoretical PE was low)22,23. Accordingly, preliminary fMRI evidence has shown that the pleasantness of this relief is correlated to activations in the NAC at the time of threat omission. In that sense, studying relief may offer important insights in the mechanism driving safety learning.”

Summary:

The authors conducted a human fMRI study investigating the omission of expected electrical shocks with varying probabilities. Participants were informed of the probability of shock and shock intensity trial-by-trial. The time point corresponding to the absence of the expected shock (with varying probability) was framed as a prediction error producing the cognitive state of relief/pleasure for the participant. fMRI activity in the VTA/SN and ventral putamen corresponded to the surprising omission of a high probability shock. Participants' subjective relief at having not been shocked correlated with activity in brain regions typically associated with reward-prediction errors. The overall conclusion of the manuscript was that the absence of an expected aversive outcome in human fMRI looks like a reward-prediction error seen in other studies that use positive outcomes.

Strengths:

Overall, I found this to be a well-written human neuroimaging study investigating an often overlooked question on the role of aversive prediction errors, and how they may differ from reward-related prediction errors. The paper is well-written and the fMRI methods seem mostly rigorous and solid.

Weaknesses:

I did have some confusion over the use of the term "prediction-error" however as it is being used in this task. There is certainly an expectancy violation when participants are told there is a high probability of shock, and it doesn't occur. Yet, there is no relevant learning or updating, and participants are explicitly told that each trial is independent and the outcome (or lack thereof) does not affect the chances of getting the shock on another trial with the same instructed outcome probability. Prediction errors are primarily used in the context of a learning model (reinforcement learning, etc.), but without a need to learn, the utility of that signal is unclear.

We operationalized “prediction error” as the response to the error in prediction or the violation of expectancy at the time of threat omission. In that sense, prediction error and expectancy violation (which is more commonly used in clinical research and psychotherapy; Craske et al., 2014) are synonymous. While prediction errors (or expectancy violations) are predominantly studied in learning situations, the definition in itself does not specify how the “expectancy” or “prediction” arises: whether it was through learning based on previous experience or through mere instruction. The rationale why we moved away from a conditioning study in the present manuscript is discussed in our general reply above.

We agree with the reviewer that studying prediction errors outside a learning context limits the ecological validity of the task. However, we do believe there is also a strength to this approach. Specifically, the omission-related responses we measure are less confounded by subsequent learning (or updating of the wrongful expectation). Any difference between our results and prediction error responses in learning situation can therefore point to this exact difference in paradigm, and can thus identify responses that are specific to learning situations.

An overarching question posed by the researchers is whether relief from not receiving a shock is a reward. They take as neural evidence activity in regions usually associated with reward prediction errors, like the VTA/SN . This seems to be a strong case of reverse inference. The evidence may have been stronger had the authors compared activity to a reward prediction error, for example using a similar task but with reward outcomes. As it stands, the neural evidence that the absence of shock is actually "pleasurable" is limited-albeit there is a subjective report asking subjects if they felt relief.

We thank the reviewer for cautioning us and letting us critically reflect on our interpretation. We agree that it is important not to be overly enthusiastic when interpreting fMRI results and to attribute carelessly psychological functions to mere activations. Therefore, we will elaborate on the precautions we took not to minimize detrimental reverse inference.

First, prior to analyzing our results, we preregistered clear hypotheses that were based on previous research, in addition to clear predictions, regions of interest and a testing approach on OSF. With our study, we wanted to investigate whether unexpected omissions of threat: (1) triggered activations in the VTA/SN, putamen, NAc and vmPFC (as has previously been shown in animal and human studies); (2) represent PE signals; and (3) were related to self-reported relief, which has also been shown to follow a PE time-curve in fear extinction (Vervliet et al., 2017). Based on previous research, we selected three criteria all PE signals should comply to. This means that if omission-related activations were to represent true PE signals, they should comply to these criteria. However, we agree that it would go too far to conclude based on our research that relief is a reward, or even that the omission-related activations represent only PE signals. While we found support for most of our hypotheses, this does not preclude alternative explanations. In fact, in the discussion, we acknowledge this and also discuss alternative explanations, such as responding to the salience (lines 395-397; “One potential explanation is therefore that the deactivation resulted from a switch from default mode to salience network, triggered by the salience of the unexpected threat omission or by the salience of the experienced stimulation.”), or anticipation (line 425-426; “... we cannot conclusively dismiss the alternative interpretation that we assessed (part of) expectancy instead”).

Second, we have deliberately opted to only use descriptive labels such as omission-related activations when we are discussing fMRI results. Only when we are talking about how the activations were related to self-reported relief, we talk about relief-related activations.

I have some other comments, and I elaborate on those above comments, below:

(1) A major assumption in the paper is that the unexpected absence of danger constitutes a pleasurable event, as stated in the opening sentence of the abstract. This may sometimes be the case, but it is not universal across contexts or people. For instance, for pathological fears, any relief derived from exposure may be short-lived (the dog didn't bite me this time, but that doesn't mean it won't next time or that all dogs are safe). And even if the subjective feeling one gets is temporary relief at that moment when the expected aversive event is not delivered, I believe there is an overall conflation between the concepts of relief and pleasure throughout the manuscript. Overall, the manuscript seems to be framed on the assumption that "aversive expectations can transform neutral outcomes into pleasurable events," but this is situationally dependent and is not a common psychological construct as far as I am aware.

We thank the reviewer for their comment. We have restructured the introduction because we agree with the reviewer that the introduction might have set false expectations concerning our interpretation of the results. The statements related to relief have been toned down in the revised manuscript.

Still, we want to note that the initial opening statement “unexpected absence of danger constitutes the pleasurable emotion relief” was based on a commonly used definition of relief that states that relief refers to “the emotion that is triggered by the absence of expected or previously experienced negative stimulation ” (Deutsch, 2015). Both aspects that it is elicited by the absence of an otherwise expected aversive event and that it is pleasurable in nature has received considerable empirical support in emotion and fear conditioning research (Deutsch et al., 2015; Leknes et al., 2011; Papalini et al., 2021; Vervliet et al., 2017; Willems & Vervliet, 2021).

That said, the notion that the feeling of relief is linked to the (reward) prediction error underlying the learning of safety is included in several theoretical papers in order to explain the commonly observed dopaminergic response at the time of threat omission (both in animals and humans; Bouton et al., 2020; Kalisch et al., 2019; Pittig et al., 2020).

Together, these studies indicate that the definition of relief, and its potential role in threat omission-driven learning is – at least in our research field – established. Still, we felt that more direct research linking feelings of relief to omission-related brain responses was warranted.

One of the main reasons why we specifically focus on the “pleasantness” of the relief is to assess the hedonic impact of the threat omission, as has been done in previous studies by our lab and others (Leknes et al., 2011; Leng et al., 2022; Papalini et al., 2021; Vervliet et al., 2017; Willems & Vervliet, 2021). Nevertheless, we agree with the reviewer that the relief we measure is a short-lived emotional state that is subjected to individual differences (as are all emotions).

(2) The authors allude to this limitation, but I think it is critical. Specifically, the study takes a rather simplistic approach to prediction errors. It treats the instructed probability as the subjects' expectancy level and treats the prediction error as omission related activity to this instructed probability. There is no modeling, and any dynamic parameters affected by learning are unaccounted for in this design . That is subjects are informed that each trial is independently determined and so there is no learning "the presence/absence of stimulations on previous trials could not predict the presence/absence of stimulation on future trials." Prediction errors are central to learning. It is unclear if the "relief" subjects feel on not getting a shock on a high-probability trial is in any way analogous to a prediction error, because there is no reason to update your representation on future trials if they are all truly independent. The construct validity of the design is in question.

(3) Related to the above point, even if subjects veered away from learning by the instruction that each trial is independent, the fact remains that they do not get shocks outside of the 100% probability shock. So learning is occurring, at least for subjects who realize the probability cue is actually a ruse.

We thank the reviewer for raising these concerns. We believe that the general reply above covers the issues raised in points 2 and 3.

(4) Bouton has described very well how the absence of expected threat during extinction can create a feeling of ambiguity and uncertainty regarding the signal value of the CS. This in large part explains the contextual dependence of extinction and the "return of fear" that is so prominent even in psychologically healthy participants. The relief people feel when not receiving an expected shock would seem to have little bearing on changing the long-term value of the CS. In any event, the authors do talk about conditioning (CS-US) in the paper, but this is not a typical conditioning study, as there is no learning.

We fully agree with the reviewer that our study is no typical conditioning study. Nevertheless, because our research mostly builds on recent advances in the fear extinction domain, we felt it was necessary to introduce the fear extinction procedure and related findings. In the context of fear extinction learning, we have previously shown that relief is an emotional correlate of the prediction error driving acquisition of the novel safety memory (CSnoUS; Papalini et al., 2021; Vervliet et al., 2017). The ambiguity Bouton describes is the result of extinguished CS holding multiple meanings once the safety memory is acquired. Does it signal danger or safety? We agree with Bouton that the meaning of the CS for any new encounter will depend on the context, and the passage of time, but also on the initial strength of the safety acquisition (which is dependent on the size of the prediction error, and hence the amount of relief; Craske et al., 2014). However, it was not our objective to directly study the relation of relief to subsequent CS value, and our design is not tailored to do so post hoc.

(5) In Figure 2 A-D, the omission responses are plotted on trials with varying levels of probability. However, it seems to be missing omission responses in 0% trials in these brain regions. As depicted, it is an incomplete view of activity across the different trial types of increasing threat probability.

We thank the reviewer for pointing out this unclarity. The betas that are presented in the figures represent the ROI averages from each non-0% vs 0% contrasts (i.e., 25%>0%; 50%>0%; and 75%>0% for the weak, moderate and strong intensity levels). Any positive beta therefore indicates a stronger activation in the given region compared to a fully predicted omission. Any negative beta indicates a weaker activation.

Adaptations in the revised manuscript: We have adapted the figure captions of figures 2 and 3.

“The extracted beta-estimates in figures A-D represent the ROI averages from each non0% > 0% contrast (i.e., 25%>0%; 50%>0%; and 75%>0% for the weak, moderate and strong intensity levels). Any positive beta therefore indicates a stronger activation in the given region compared to a fully predicted omission. Any negative beta indicates a weaker activation.”

(6) If I understand Figure 2 panels E-H, these are plotting responses to the shock versus no-shock (when no-shock was expected). It is unclear why this would be especially informative, as it would just be showing activity associated with shocks versus no-shocks. If the goal was to use this as a way to compare positive and negative prediction errors, the shock would induce widespread activity that is not necessarily reflective of a prediction error. It is simply a response to a shock. Comparing activity to shocks delivered after varying levels of probability (e.g., a shock delivered at 25% expectancy, versus 75%, versus 100%) would seem to be a much better test of a prediction error signal than shock versus no-shock.

We thank the reviewer for this comment. The purpose of this preregistered contrast was to test whether fully predicted outcomes elicited equivalent activations in our ROIs (corresponding to the third prediction error axiom). Specifically, if a region represents a pure prediction error signal, the 100% (fully predicted shocks) > 0% (fully predicted shock omissions) contrast should be nonsignificant, and follow-up Bayes Factors would further provide evidence in favor of this null-hypothesis.

We agree with the reviewer that the delivery of the stimulation triggers widespread activations in our regions of interest that confounded this contrast. However, given that it was a preregistered test for the prediction error axioms, we cannot remove it from the manuscript. Instead, we have argued in the discussion that future studies who want to take an axiomatic stance should consider alternative tests to examine this axiom.

Adaptations in the revised manuscript: We adapted lines 358-364.

“Thus, given that we could not control for the delivery of the stimulation in the 100% > 0% contrast (the delivery of the stimulation completely overlapped with the contrast of interest), it is impossible to disentangle responses to the salience of the stimulation from those to the predictability of the outcome. A fairer evaluation of the third axiom would require outcomes that are roughly similar in terms of salience. When evaluating threat omission PE, this implies comparing fully expected threat omissions following 0% instructions to fully expected absence of stimulation at another point in the task (e.g. during a safe intertrial interval).”

Also note that our task did not lend itself for an in-depth analysis of aversive (worse-thanexpected) prediction error signals, given that there was only one stimulation trial for each probability x intensity level (see Supplemental Figure 1). The most informative contrast that can inform us about aversive prediction error signals contrasts all non-100% stimulation trials with all 100% stimulation trials. The results of this contrast are presented in Supplemental Figure 16 and Supplemental Table 11 for completeness.

(7) I was unclear what the results in Figure 3 E-H were showing that was unique from panels A-D, or where it was described. The images looked redundant from the images in A-D. I see that they come from different contrasts (non0% > 0%; 100% > 0%), but I was unclear why that was included.

We thank the reviewer for this comment. Our answer is related to that of the previous comment. Figure 3 presents the results of the axiomatic tests within the secondary ROIs we extracted from a wider secondary mask based on the non0%>0% contrast.

(8) As mentioned earlier, there is a tendency to imply that subjects felt relief because there was activity in "the reward pathway ."

We thank the reviewer for their comment, but we respectfully disagree. Subjective relief was explicitly probed when the instructed stimulations stayed away. In the manuscript we only talk about “relief” when discussing these subjective reports. We found that participants reported higher levels of relief-pleasantness following omissions of stronger and more probable threat. This was an observation that matches our predictions and replicates our previous behavioral study (Willems & Vervliet, 2021).

The fMRI evidence is treated separately from the “pleasantness” of the relief. Specifically, we refrain from calling the threat omission-related neural responses “relief-activity” as this would indeed imply that the activation would only be attributed to this psychological function. Instead, we talked about omission-related activity, and we assessed whether it complied to the prediction error criteria as specified by the axiomatic approach.

Only afterwards, because we hypothesized that omission-related fMRI activation and selfreported relief-pleasantness were related, and because we found a similar response pattern for both measures, we examined how relief and omission-related fMRI activations within our ROIs were related on a trial-by-trial basis. To this end, we entered relief-pleasantness ratings as a parametric modulator to the omission regressor.

By no means do we want to reduce an emotional experience (relief) to fMRI activations in isolated regions in the brain. We agree with the reviewer that this would be far too reductionist. We therefore also ran a pre-registered LASSO-PCR analysis in order to identify whether a whole-brain pattern of activations can predict subjective relief (independent from the exact instructions we gave, and independent of our a priori ROIs). This analysis used trialby-trial patterns of activation across all voxels in the brain as the predictor and self-reported relief as the outcome variable. It is therefore completely data-driven and can be seen as a preregistered exploratory analysis that is intended to inform future studies.

(9) From the methods, it wasn't entirely clear where there is jitter in the course of a trial. This centers on the question of possible collinearity in the task design between the cue and the outcome. The authors note there is "no multicollinearity between anticipation and omission regressors in the firstlevel GLMs," but how was this quantified? b The issue is of course that the activity coded as omission may be from the anticipation of the expected outcome.

We thank the reviewer for pointing out this unclarity. Jitter was introduced in all parts of the trial: i.e., the duration of the inter-trial interval (4-7s), countdown clock (3-7s), and omission window (4-8s) were all jittered (see fig. 1A and methods section, lines 499-507). We added an additional line to the method section.

Adaptations in the revised manuscript: We added an additional line of to the methods section to further clarify the jittering (lines 498-500).

“The scale remained on the screen for 8 seconds or until the participant responded, followed by an intertrial interval between 4 and 7 seconds during which only a fixation cross was shown. Note that all phases in the trial were jittered (i.e., duration countdown clock, duration outcome window, duration intertrial interval).”

Multicollinearity between the omission and anticipation regressors was assessed by calculating the variance inflation factor (VIF) of omission and anticipation regressors in the first level GLM models that were used for the parametric modulation analyses.

Adaptations in the revised manuscript: We replaced the VIF abbreviation with “variance inflation factor” (line 423-424).

“Nevertheless, there was no multicollinearity between anticipation and omission regressors in the first-level GLMs (VIFs Variance Inflation Factor, VIF < 4), making it unlikely that the omission responses purely represented anticipation.”

(10) I did not fully understand what the LASSO-PCR model using relief ratings added. This result was not discussed in much depth, and seems to show a host of clusters throughout the brain contributing positively or negatively to the model. Altogether, I would recommend highlighting what this analysis is uniquely contributing to the interpretation of the findings.

The main added value of this analyses is that it uses a different approach altogether. Where the (mass univariate) parametric modulation analysis estimated in each voxel (and each ROI) whether the activity in this voxel/ROI covaried with the reported relief, a significant activation only indicated that this voxel was related to relief. However, given that each voxel/ROI is treated independently in this analysis, it remains unclear how the activations were embedded in a wider network across the brain, and which regions contributed most to the prediction of relief. The multivariate LASSO-PCR analysis approach we took attempts to overcome this limitation by examining if a more whole-brain pattern can predict relief. Because we use the whole-brain pattern (and not only our a priori ROIs), this analysis is completely data-driven and is intended to inform future studies. In addition, the LASSO-PCR model was cross-validated using five-fold cross-validation, which is also a difference (and a strength) compared to the mass univariate GLM approach.

One interesting finding that only became evident when we combined univariate and multivariate approaches is that despite that the parametric modulation analysis showed that omission-related fMRI responses in the ROIs were modulated by the reported relief, none of these ROIs contributed significantly to the prediction of relief based on the identified signature. Instead, some of the contributing clusters fell within other valuation and errorprocessing regions (e.g. lateral OFC, mid cingulate, caudate nucleus). This suggests that other regions than our a priori ROIs may have been especially important for the subjective experience of relief, at least in this task. However, all these clusters were small and require further validation in out of sample participants. More research is necessary to test the generalizability and validity of the relief signature to new individuals and tasks, and to compare the signature with other existing signature models (e.g., signature of pain, fear, reward, pleasure). However, this was beyond the scope of the present study.

Adaptations in the revised manuscript: We altered the explanation of the LASSO-PCR approach in the results section (lines 286-295) and the discussion (lines 399-402)

Adaptations in the Results section: “The (mass univariate) parametric modulation analysis showed that omission-related fMRI activity in our primary and secondary ROIs correlated with the pleasantness of the relief. However, given that each voxel/ROI is treated independently in this analysis, it remains unclear how the activations were embedded in a wider network of activation across the brain, and which regions contributed most to the prediction of relief. To overcome these limitations, we trained a (multivariate) LASSO-PCR model (Least Absolute Shrinkage and Selection Operator-Regularized Principle Component Regression) in order to identify whether a spatially distributed pattern of brain responses can predict the perceived pleasantness of the relief (or “neural signature” of relief)31. Because we used the whole-brain pattern (and not only our a priori ROIs), this analysis is completely data driven and can thus identify which clusters contribute most to the relief prediction.”

Adaptations in the Discussion section: “In addition to examining the PE-properties of neural omission responses in our a priori ROIs, we trained a LASSO-PCR model to establish a signature pattern of relief. One interesting finding that only became evident when we compared the univariate and multivariate approach was that none of our a priori ROIs appeared to be an important contributor to the multivariate neural signature, even though all of them (except NAc) were significantly modulated by relief in the univariate analysis.”

In addition to the public peer review, the reviewers provided some recommendation on how to further improve our manuscript. We will reply to the recommendations below.

Reviewer #1 (Recommendations For The Authors):

Given that you do have trial-level estimates from the classifier analysis, it would be very informative to use learning models and examine responses trial-by-trial to test whether there are prediction errors that vary over time as a function of learning.

We thank the reviewer for the suggestion. However, based on the results of the run-regressor, we do not anticipate large learning effects in our paradigm. As we mentioned in our responses above, we controlled for time-related drops in omission-responding by including a “run” regressor in our analyses. Results of this regressor for subjective relief and omission-related SCR showed that although there was a general drop in reported relief pleasantness and omission SCR over time, the effects of probability and intensity remained present until the last run. This suggests that even though some learning might have taken place, its effect was likely small and did not abolish our manipulations of probability and intensity. In any case, we cannot use the LASSO-PCR signature model to investigate learning, as this model uses the trial-level brain pattern at the time of US omission to estimate the associated level of relief. These estimates can therefore not be used to examine learning effects.

Reviewer #2 (Recommendations For The Authors):

The LASSO-PCR model feels rather disconnected from the rest of the paper and does not add much to the main theme. I would suggest to remove this part from the paper.

We thank the reviewer for this suggestion. However, the LASSO-PCR analysis was a preregistered. We therefore cannot remove it from the manuscript. We hope to have clarified its added value in the revised version of the manuscript.

eLife assessment

This study presents valuable findings on the relationship between prediction errors and brain activation in response to unexpected omissions of painful electric shock. The strengths are the research question posed, as it has remained unresolved if prediction errors in the context of biologically aversive outcomes resemble reward-based prediction errors. The evidence is solid but there are weaknesses in the experimental design, where verbal instructions do not align with experienced outcome probabilities. There is also disconnect between the introduction which focuses on the role of prediction error signaling for learning and the lack of analyses accounting for learning and updating of expectations. The work will be of interest to cognitive neuroscientists and psychologists studying appetitive and aversive learning.

Reviewer #1 (Public Review):

Summary:

Willems and colleagues test whether unexpected shock omissions are associated with reward-related prediction errors by using an axiomatic approach to investigate brain activation in response to unexpected shock omission. Using an elegant design that parametrically varies shock expectancy through verbal instructions, they see a variety of responses in reward-related networks, only some of which adhere to the axioms necessary for prediction error. In addition, there were associations between omission-related responses and subjective relief. They also use machine learning to predict relief-related pleasantness, and find that none of the a priori "reward" regions were predictive of relief, which is an interesting finding that can be validated and pursued in future work.

Strengths:

The authors pre-registered their approach and the analyses are sound. In particular, the axiomatic approach tests whether a given region can truly be called a reward prediction error. Although several a priori regions of interest satisfied a subset of axioms, no ROI satisfied all three axioms, and the authors were candid about this. A second strength was their use of machine learning to identify a relief-related classifier. Interestingly, none of the ROIs that have been traditionally implicated in reward prediction error reliably predicted relief, which opens important questions for future research.

Weaknesses:

To ensure that the number of omissions is similar across conditions, the task employs inaccurate verbal instructions; i.e. 25% of shocks are omitted, regardless of whether subjects are told that the probability is 100%, 75%, 50%, 25%, or 0%. Given previous findings on interactions between verbal instruction and experiential learning (Doll et al., 2009; Li et al., 2011; Atlas et al., 2016), it seems problematic a) to treat the instructions as veridical and b) average responses over time. Based on these prior work, it seems reasonable to assume that participants would learn to downweight the instructions over time through learning (particularly in the 100% and 0% cases); this would be the purpose of prediction errors as a teaching signal. The authors do recognize this and perform a subset analysis in the 21 participants who showed parametric increases in anticipatory SCR as a function of instructed shock probability, which strengthened findings in the VTA/SN; however given that one third of participants (n=10) did not show parametric SCR in response to instructions, it seems like some learning did occur. As prediction error is so important to such learning, a weakness of the paper is that conclusions about prediction error might differ if dynamic learning were taken into account.

Reviewer #2 (Public Review):

The question of whether the neural mechanisms for reward and punishment learning are similar has been a constant debate over the last two decades. Numerous studies have shown that the midbrain dopamine neurons respond to both negative and salient stimuli, some of which can't be well accounted for by the classic RL theory (Delgado et al., 2007). Other research even proposed that aversive learning can be viewed as reward learning, by treating the omission of aversive stimuli as a negative PE (Seymour et al., 2004).

Although the current study took an axiomatic approach to search for the PE encoding brain regions, which I like, I have major concerns regarding their experimental design and hence the results they obtained. My biggest concern comes from the false description of their task to the participants. To increase the number of "valid" trials for data analysis, the instructed and actual probabilities were different. Under such a circumstance, testing axiom 2 seems completely artificial. How does the experimenter know that the participants truly believe that the 75% is more probable than, say, the 25% stimulation? The potential confusion of the subjects may explain why the SCR and relief report were rather flat across the instructed probability range, and some of the canonical PE encoding regions showed a rather mixed activity pattern across different probabilities. Also for the post-hoc selection criteria, why pick the larger SCR in the 75% compared to the 25% instructions? How would the results change if other criteria were used?

To test axiom 3, which was to compare the 100% stimulation to the 0% stimulation conditions, how did the actual shock delivery affect the fMRI contrast result? It would be more reasonable if this analysis could control for the shock delivery, which itself could contaminate the fMRI signal, with extra confound that subjects may engage certain behavioral strategies to "prepare for" the aversive outcome in the 100% stimulation condition. Therefore, I agree with the authors that this contrast may not be a good way to test axiom 3, not only because of the arguments made in the discussion but also the technical complexities involved in the contrast.

Comments on revised version:

I want to thank the authors for their thorough and comprehensive work in revising this manuscript. I agree with the authors that learning paradigms might not be a necessity when it comes to study the PE signals, but I don't particularly agree with some of the responses in the rebuttal letter ("Furthermore, conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted."). This is of course correct description for the conditioning paradigm, but the same can be said for an instructed design: the aversive outcome was either delivered or not. That being said, adopting the instructed design itself is legitimate in my opinion.

My main concern, which the authors spent quite some length in the rebuttal letter to address, still remains about the validity for different instructed probabilities. Although subjects were told that the trials were independent, the big difference between 75% and 25% would more than likely confuse the subjects, especially given that most of us would fall prey to the Gambler's fallacy (or the law of small numbers) to some degree. When the instruction and subjective experience collides, some form of inference or learning must have occurred, making the otherwise straightforward analysis more complex. Therefore, I believe that a more rigorous/quantitative learning modeling work can dramatically improve the validity of the results. Of course, I also realize how much extra work is needed to append the computational part but without it there is always a theoretical loophole in the current experimental design.

As the authors mentioned in the rebuttal letter, "selecting participants only if their anticipatory SCR monotonically increased with each increase in instructed probability 0% < 25% < 50% < 75% < 100%, N = 11 participants", only ~1/3 of the subjects actually showed strong evidence for the validity of the instructions. This further raises the question of whether the instructed design, due to the interference of false instruction and the dynamic learning among trials, is solid enough to test the hypothesis.

Reviewer #3 (Public Review):

Summary:

The authors conducted a human fMRI study investigating the omission of expected electrical shocks with varying probabilities. Participants were informed of the probability of shock and shock intensity trial-by-trial. The time point corresponding to the absence of the expected shock (with varying probability) was framed as a prediction error producing the cognitive state of relief/pleasure for the participant. fMRI activity in the VTA/SN and ventral putamen corresponded to the surprising omission of a high probability shock. Participants' subjective relief at having not been shocked correlated with activity in brain regions typically associated with reward-prediction errors. The overall conclusion of the manuscript was that the absence of an expected aversive outcome in human fMRI looks like a reward-prediction error seen in other studies that use positive outcomes.

Strengths:

Overall, I found this to be a well-written human neuroimaging study investigating an often overlooked question on the role of aversive prediction errors, and how they may differ from reward-related prediction errors. The paper is well-written and the fMRI methods seem mostly rigorous and solid.

Comments on revised version:

The authors were extremely responsive to the comments and provided a comprehensive rebuttal letter with a lot of detail to address the comments. The authors clarified their methodology, and rationale for their task design, which required some more explanation (at least for me) to understand. Some of the design elements were not clear to me in the original paper.

The initial framing for their study is still in the domain of learning. The paper starts off with a description of extinction as the prime example of when threat is omitted. This could lead a reader to think the paper would speak to the role of prediction errors in extinction learning processes. But this is not their goal, as they emphasize repeatedly in their rebuttal letter. The revision also now details how using a conditioning/extinction framework doesn't suit their experimental needs.

It is reasonable to develop a new task to answer their experimental questions. By no means is there a requirement to use a conditioning/extinction paradigm to address their questions. As they say, "it is not necessary to adopt a learning paradigm to study omission responses", which I agree with.

But the authors seem to want to have it both ways: they frame their paper around how important prediction errors are to extinction processes, but then go out of their way to say how they can't test their hypotheses with a learning paradigm.

Part of their argument that they needed to develop their own task "outside of a learning context" goes as follows:<br /> (1) "...conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted. As a result, the magnitude-related axiom cannot be tested."<br /> (2) "....in conditioning tasks people generally learn fast, rendering relatively few trials on which the prediction is violated. As a result, there is generally little intra-individual variability in the PE responses"<br /> (3) "...because of the relatively low signal to noise ratio in fMRI measures, fear extinction studies often pool across trials to compare omission-related activity between early and late extinction, which further reduces the necessary variability to properly evaluate the probability axiom"

These points seem to hinge on how tasks are "generally" constructed. However, there are many adaptations to learning tasks:<br /> (1) There is no rule that conditioning can't include different levels of aversive outcomes following different cues. In fact, their own design uses multiple cues that signal different intensities and probabilities. Saying that conditioning "generally only include one level of aversive outcome" is not an explanation for why "these paradigms are not tailored" for their research purposes. There are also several conditioning studies that have used different cues to signal different outcome probabilities. This is not uncommon, and in fact is what they use in their study, only with an instruction rather than through learning through experience, per se.<br /> (2) Conditioning/extinction doesn't have to occur fast. Just because people "generally learn fast" doesn't mean this has to be the case. Experiments can be designed to make learning more challenging or take longer (e.g., partial reinforcement). And there can be intra-individual differences in conditioning and extinction, especially if some cues have a lower probability of predicting the US than others. Again, because most conditioning tasks are usually constructed in a fairly simplistic manner doesn't negate the utility of learning paradigms to address PE-axioms.<br /> (3) Many studies have tracked trial-by-trial BOLD signal in learning studies (e.g., using parametric modulation). Again, just because other studies "often pool across trials" is not an explanation for these paradigms being ill-suited to study prediction errors. Indeed, most computational models used in fMRI are predicated on analyzing data at the trial level.

Again, the authors are free to develop their own task design that they think is best suited to address their experimental questions. For instance, if they truly believe that omission-related responses should be studied independent of updating. The question I'm still left puzzling is why the paper is so strongly framed around extinction (the word appears several times in the main body of the paper), which is a learning process, and yet the authors go out of their way to say that they can only test their hypotheses outside of a learning paradigm.

The authors did address other areas of concern, to varying extents. Some of these issues were somewhat glossed over in the rebuttal letter by noting them as limitations. For example, the issue with comparing 100% stimulation to 0% stimulation, when the shock contaminates the fMRI signal. This was noted as a limitation that should be addressed in future studies, bypassing the critical point.

Author response:

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

We have revised the manuscript mainly in the following aspects: (1) the data of electrophysiological and behavioral responses of larvae and adults to trehalose have been added, and the related figures and texts have been modified accordingly; (2) the photos of taste organs of larvae and adults indicating the position of recorded sensilla have been added; (3) the potential off-target effects of GR knock-out on other GR expressions has been carefully explained and revised in the relevant text; (4) the abstract has been revised to present the findings more technically in a limited number of words; (5) some details of experiments in Materials and Methods and some new literatures have been added; (6) a new figure (Figure 8) summarizing the main findings of the study has been added.

In the following, we respond to the reviewers’ comments and suggestions one by one. We hope that our answers will satisfy you and the three reviewers. We are also very happy to get further valuable advices from you.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The process of taste perception is significantly more intricate and complex in Lepidopteran insects. This investigation provides valuable insights into the role of Gustatory receptors and their dynamics in the sensation of sucrose, which serves as a crucial feeding cue for insects. The article highlights the differential sensitivity of Grs to sucrose and their involvement in feeding and insect behavior.

Strengths:

To support the notion of the differential specificity of Gr to sucrose, this study employed electrophysiology, ectopic expression of Grs in Xenopus, genome editing, and behavioral studies on insects. This investigation offers a fundamental understanding of the gustation process in lepidopteran insects and its regulation of feeding and other gustation-related physiological responses. This study holds significant importance in advancing our comprehension of lepidopteran insect biology, gustation, and feeding behavior.

Thank you for your recognition of our research.

Weaknesses:

While this manuscript demonstrates technical proficiency, there exists an opportunity for additional refinement to optimize comprehensibility for the intended audience. Several crucial sugars have been overlooked in the context of electrophysiology studies and should be incorporated. Furthermore, it is imperative to consider the potential off-target effects of Gr knock-out on other Gr expressions. This investigation focuses exclusively on Gr6 and Gr10, while neglecting a comprehensive narrative regarding other Grs involved in sucrose sensation.

We accept the reviewer's suggestion. Because trehalose is a main sugar in insect blood, and it is converted by insects after feeding on plant sugars, we have added the new data on electrophysiological and behavioral responses of larvae and adults of Helicoverpa armigera to trehalose (see Figure 1-2, Figure 1-figure supplement 1, Figure 2-figure supplement 1). Now, the total eight sugars include 2 pentoses (arabinose and xylose), 4 hexoses (fructose, fucose, galactose and glucose), and 2 disaccharides (sucrose and trehalose), which were chosen because they are mainly present in host-plants of H. armigera and/or representative in the structure and source of sugars.

We fully agree to the reviewer’s opinion and have already taken the potential off-target effects of CRISPR/Cas9 knockout of Gr on other GR expressions into consideration. To predict the potential off-target sites of sgRNA of Gr6 and Gr10 establishing homozygous mutants using CRISPR/Cas9 technology, we first use online software CasOFFinder (http://www.rgenome.net/cas-offinder/) to blast the genome of the wild type cotton bollworm and set the mismatch number less than or equal to 3. We found that Gr10 sgRNA had no potential potential off-target site, and the sgRNA of Gr6 had only one potential off-target site. Therefore, we designed primers according to the sequence of potential off-target sites of Gr6 sgRNA, and conducted PCR using genomic DNA of homozygous mutant as a template， performed Sanger sequencing on the PCR products obtained, and found that the potential off-target sites of Gr6 sgRNA were no different from those of the wild type. Particularly, concerning the sgRNA of Gr6 and Gr10 may produce off-target effects on other sugar receptor genes of H. armigera, we conducted the same off-target site analysis with the designed sgRNA on each of the other eight sugar receptor genes, and found that there were no off-target sites on these receptor genes (see Line254-256).

Reviewer #2 (Public Review):

Summary:

To identify sugar receptors and assess the capacity of these genes the authors first set out to identify behavioral responses in larvae and adults as well as physiological response. They used phylogenetics and gene expression (RNAseq) to identify candidates for sugar reception. Using first an in vitro oocyte system they assess the responses to distinct sugars. A subsequent genetic analysis shows that the Gr10 and Gr6 genes provide stage specific functions in sugar perception.

Strengths:

A clear strength of the manuscript is the breadth of techniques employed allowing a comprehensive study in a non-canonical model species.

Thank you for your recognition of our research.

Weaknesses:

There are no major weaknesses in the study for the current state of knowledge in this species. Since it is much basic work to establish a broader knowledge, context with other modalities remains unknown. It might have been possible to probe certain contexts known from the fruit fly, which would have strengthened the manuscript.

Thank you so much for your suggestion. According to this suggestion, we further added some sentences probing sugar sensing and behaviors of fruit fly larvae in the Introduction and discussion sections (Line 68-71 in Introduction section, Line 395-399 in Discussion section).

Reviewer #3 (Public Review):

In this study, the authors combine electrophysiology, behavioural analyses, and genetic editing techniques on the cotton bollworm to identify the molecular basis of sugar sensing in this species.

The larval and adult forms of this species feed on different plant parts. Larvae primarily consume leaves, which have relatively lower sugar concentrations, while adults feed on nectar, rich in sugar. Through a series of experiments-spanning electrophysiological recordings from both larval and adult sensillae, qPCR expression analysis of identified GRs from these sensillae, response profiles of these GRs to various sugars via heterologous expression in Xenopus oocytes, and evaluations of CRISPR mutants based on these parameters-the authors discovered that larvae and adults employ distinct GRs for sugar sensing. While the larva uses the highly sensitive GR10, the adult uses the less sensitive and broadly tuned GR6. This differential use of GRs are in keeping with their behavioral ecology.

The data are cohesive and consistently align across the methodologies employed. They are also well presented and the manuscript is clearly written.

Recommendations for the authors:

While appreciating the quality of the work and its presentation, we have a few comments for the authors, should they wish to consider them, that would significantly improve the presentation of the work.

Title: Could the authors please revisit their title to better reflect the main finding of their work?

The title has been changed into “The larva and adult of Helicoverpa armigera use differential gustatory receptors to sense sugars”.

Text: There are a few comments related to the text, and these are listed below:

(1) Could the authors place their work in the context of what's known about sugar sensing in Drosophila larva and adult?

In the Introduction section, we added the status of research on sugar perception in Drosophila larvae, pointing out "No external sugar-sensing mechanism in Drosophila larvae has yet been characterized." (Line 70-71); in the Discussion section, the research progress of sugar sensing in Drosophila adults and larvae was also summarized (Line 397-399).

(2) For each results section, could the authors please include a sentence or two that interprets the data in the context of previously presented data?

We accept the reviewer's suggestion. In order to make it easy for readers to follow up, we included a sentence interprets the above data at the beginning of each part of the Results on the premise of avoiding duplication.

(3) Could the authors please provide details of the generation and screening of the CRISPR mutants?

We have added more details on mutant establishment and screening in the Materials and Methods section (Line 722-726, 729-732).

Figures: Could the authors please include images and schematics wherever possible? For example, a schematic depicting the position of the sense organs and one summarising the main findings of the studies.

In Figure 1 we added the photo of each taste organ, on which the recorded sensilla were indicated. We also added a new figure, Figure 8, summarizing the main findings of the study.

Choice of Sugars: Could the authors please justify their choice of sugars they have used in the analyses?

In the first paragraph of the Results section of the article, we further explain the reasons for using the sugars in the study. “We first investigated the electrophysiological responses of the lateral and medial sensilla styloconica in the larval maxillary galea to eight sugars. These sugars were chosen because they are mostly found in host-plants of H. armigera or are representative in the structure and source of sugars.”

In addition to this, there are several specific comments in the detailed reviewers comments below, which the authors could consider responding to.

Reviewer #1 (Recommendations For The Authors):

The article titled "Sucrose taste receptors exhibit dissimilarities between larval and adult stages of a moth" by Shuai-Shuai Zhang and colleagues provides an intriguing analysis. The authors have conducted a meticulously planned and executed study. However, I do have some inquiries.

(1) What precisely does the term "differ" signify in the title? It can be expounded upon in terms of differing in expression or sensitivity. The title could benefit from being more informative. The authors should appropriately specify the insect species in the title of the paper. This would make it more comprehensible to readers. Merely mentioning the term "moth" does not provide any information about the model organism. Hence, it would be preferable to mention Helicoverpa armigera instead of using the generic term "moth" in the title.

Thank you for your suggestions. We considered it better to emphasize that the receptors for sucrose are different, and we have accepted the suggestion of adding the name of the animal. The title has been changed into “The larva and adult of Helicoverpa armigera use differential gustatory receptors to sense sugars”.

(2) The abstract is written in a simple and easily understandable manner, but it overlooks important findings from a technical standpoint.

We add some key experimental techniques to illustrate some important findings in the Abstract.

(3). Almost all herbivorous insects are said to consume plants and utilize sucrose as a stimulus for feeding, as stated by the authors. Sucrose, glucose, and fructose sugar are among the commonly observed stimulants for feeding in numerous insects. It would be appropriate to incorporate not only sucrose but also glucose and fructose as feeding stimulants for almost all herbivorous insects.

Thank you for your suggestion. Sucrose is the major sugar in plants, and its concentration varies greatly from tissue to tissue, while the concentration of the hexose sugars is much lower and the concentration does not change much. In Line 48, we state that sucrose, glucose, and fructose are feeding stimuli for herbivorous insects. From the previous studies, it seems that sucrose is the strongest, followed by fructose, and finally glucose. The cotton bollworm larvae showed no electrophysiological and behavioral response to glucose.

(4) The reason why trehalose is not considered in the electrophysiology analysis is unclear. Given that trehalose is a major sugar in insects and plants, it would be intriguing to include it in the analysis.

We have accepted the reviewer's suggestion, and supplemented the electrophysiological responses of taste organs in larvae and adults of Helicoverpa armigera to trehalose (Figure 1, Figure 1-Figure Supplement 1), and also tested the behavioral responses of the larvae and adults to trehalose (Figure 2, Figure 2-Figure Supplement 1). Therefore, all the related figures have been changed.

(5) The author's intention regarding the co-receptor relationship between Gr5 and Gr6 (line 211) is unclear. If this is indeed the case, then the reason for considering Gr5 in further studies remains uncertain.

We have changed the sentence as follows: “Since Gr5 was highly expressed with Gr6 in the proboscis and tarsi (Figure 3D-3E, Figure 3—figure supplement 1), we suspected that Gr5 and Gr6 might be expressed in the same cells, and then tested the response profile of their co-expression in oocytes.”

(6) The homologous nature of Grs is emphasized by the authors. It is not specified how the author ensured that the guide RNA targeting Gr6 or Gr10 did not result in off-target effects on other Grs.

Thank you so much for your suggestion. We have rewritten the relevant paragraph (Line 238-251), detailing our tests and the results on the potential off-target effects of knocking out GRs by CRISPR/Cas9: “In order to predict the potential off-target sites of sgRNA of Gr6 and Gr10, we used online software Cas-OFFinder (http://www.rgenome.net/cas-offinder/) to blast the genome of H. armigera, and the mismatch number was set to less than or equal to 3. According to the predicted results, the Gr10 sgRNA had no potential off-target region but Gr6 sgRNA had one. Therefore, we amplified and sequenced the potential off-target region of Gr6-/- and found there was no frameshift or premature stop codon in the region compared to WT (Figure 5—figure supplement 2). It is worth mentioning that there was no potential off-target region of Gr6 and Gr10 sgRNA in other sugar receptor genes of H. armigera, Gr4, Gr5, Gr7, Gr8, Gr9, Gr11 and Gr12. We further found there was no difference in the response to xylose of the medial sensilla styloconica among WT, Gr10-/- and Gr6-/- (Figure 5—figure supplement 2). Furthermore, WT, Gr10-/- and Gr6-/- did not show differences in the larval body weight, adult lifespan, and number of eggs laid per female (Figure 5—figure supplement 2). All these results suggest that no off-target effects occurred in the study.”

(7) Is it possible that knocking out Gr10 is not compensated for by the overexpression of Gr6 or other sucrose sensing Grs? Similarly, would the vice versa scenario hold true?

In the Discussion section, we have added some sentences to discuss this issue: “From our results, knocking out Gr10 or Gr6 is unlikely to be compensated by overexpression of other sugar GRs. One of our recent studies showed that Orco knockout had no significant effect on the expression of most OR, IR and GR genes in adult antennae of H. armigera, but some genes were up- or down-regulated (Fan et al., 2022).”

(8) What was the rationale for selecting nine candidate GR genes for expression analysis?

Based on the reviewer's suggestion, we expanded the relevant paragraphs to illustrate the rationale for selecting nine candidate GR genes for expression analysis: “To reveal the molecular basis of sugar reception in the taste sensilla of H. armigera, we first analyzed the putative sugar gustatory receptor genes based on the reported gene sequences of GRs in H. armigera and their phylogenetic relationship of D. melanogaster sugar gustatory receptors (Jiang et al., 2015; Pearce et al., 2017; Xu et al., 2017). Nine putative sugar GR genes, Gr4–12 were identified, and their full-length cDNA sequences were cloned (The GenBank accession number is provided in Appendix—Table S1).” (Line 155-161)

(9) What is the potential reason for the difference between the major larval sugar receptors of Drosophila and Lepidopterans?

The difference between the major larval sugar receptors of Drosophila and Lepidopterans is probably due to differences in the food their larvae feed on. Fruit fly larvae feed on rotten fruit, the main sugar of which is fructose. The larvae of Lepidoptera mainly feed on plants, and the main sugar is sucrose. In the Discussion section, we have added a sentence “This is most likely due to fruit fly larvae feeding on rotten fruits, which contain fructose as the main sugar.” (Line 399-401)

(10) There is a disparity in GRs, specifically GR5 and GR6, between the female antenna, proboscis, and tarsi. What could be the possible justification and significance of this?

Thank you so much for this question. We have added a sentence in the Discussion section, “In this study, the expression patterns of 9 sugar GRs in three taste organs of adult H. armigera show that there is a disparity in GRs, specifically GR5 and GR6, between the female antenna, tarsi and proboscis, which may be an evolutionary adaptation reflecting subtle differentiation in the function of these taste organs in adult foraging. Antennae and tarsi play a role in the exploration of potential sugar sources, while the proboscis plays a more precise role in the final decision to feed.” (Line 433-438)

(11) I suggest that a visual representation illustrating the positioning of GSNs, particularly the lateral and medial sensilla, in both larva and adult stages would enhance the correlation with the results.

In Figure 1 we added the photo of each taste organ and the position of the recorded sensilla, and also added a new figure, Figure 8 summarizing the main findings of the studies.

(12) Further experiments can be conducted to elucidate the precise molecular mechanisms, particularly the downstream effects of GRs, in order to establish the specificity of GRs more convincingly.

Thank you so much for your suggestion. We have discussed the further experiments in the Discussion section, “To elucidate the precise molecular mechanisms of sugar reception in H. armigera is necessary to compare a series of single, double and even multiple Gr knock-out lines and investigate the downstream effects of the GRs.” (Line 363-369)

(13) Figure 6 caption: In Figure 6 (D to I), the percentage of PER is depicted. There is redundancy in the Y-axis title (Percentage of PER) and the legend. This appears to be repetitive. I suggest that it would be better to include the Y-axis title only in Figure D or in Figures D and G.

We accept the suggestion. Figure 7 (not Figure 6) has been revised accordingly.

(14) In Figures 6A and 6C, there is inconsistency in the colors used for WT, Gr6, and Gr10. This could potentially confuse the reader. I recommend using the same colors in both figures instead of using a blue color. Please specify how the authors calculated the feeding area in Figure 6.

We accept the reviewer's suggestion and have changed the color of Figure 7A, B. We have also added the detail method for calculating feeding area (Line 541-545).

(15) In Two-choice tests, why did the authors use 0.01% Tween 80? Please provide comments on this.

Use of 0.01% Tween 80 is to reduce the surface tension and increase the malleability of the solution. We have given detailed explanation in the Method section and cite the reference. (Line538-540)

(16) It would be valuable if the authors could comment on the prospects of this study, considering that GRs play a vital role in controlling behavior and developmental pathways. What are the potential consequences of blocking or disrupting these receptors in terms of behavioral and developmental phenotypic deformities? Could this potentially lead to increased insect mortality?

Thank you so much for your suggestions. In the last paragraph of the Discussion section, we have added the following perspectives, “Knockout of Gr10 or Gr6 led to a significant decrease in sugar sensitivity and food preference of the larvae and adults of H. armigera, respectively, which is bound to bring adverse consequences to survival and reproduction of the insects. Therefore, studying the molecular mechanisms underlying sugar perception in phytophagous insects may provide new insights into the behavioral ecology of this important and highly diverse group of insects, and measures blocking or disrupting sugar receptors could also have applications to control agricultural pests and improve crop yields worldwide” (Line 449-456).

Reviewer #2 (Recommendations for The Authors):

There are a few comments, that I feel would be beneficial to be addressed.

• The authors used 7 different sugars for their experimental approach. While I agree that this is a sufficiently large collection for a study, I was wondering why they specifically chose these sugars; an explanatory section might be helpful for a reader to follow the reasoning.

According to reviewer 1's suggestion, we increased trehalose to 8 sugars in experiments. Trehalose is a main sugar in insect blood. It is converted by insects after feeding on plant sugars. The 8 sugars were chosen because they are present in host-plants of H. armigera or are representative in the structure and source of sugars. They contain 2 pentoses (arabinose and xylose), 4 hexoses (fructose, fucose, galactose and glucose), and 2 disaccharides (sucrose and trehalose).

• It might be beneficial to provide some broader overview on the gustatory system in the cotton bollworm, particularly at the larval stage since this may not be common knowledge. Along these lines eg. the complexity of sensilla types, organs and overall number (or estimation) of neurons might be good to know, a graphical representation of the sense organs might be informative.

In the Introduction section, we give a more specific description on sugar sensitive GSNs in the taste system of the larva and adult of H. armigera, and cite the corresponding references.

• Concerning phylogeny of GRs, it might be relevant to know how complete the genome information is and some more general background on GR diversity in the cotton bollworm.

We agree to your opinion. According to this idea, we got the putative sugar GRs from the previously published genome (Pearce et al. 2017) and the related annotation of GRs (Jiang et al. 2015, Xu et al. 2012). We have made a more detailed explanation about this in the new version of the manuscript, “We first analyzed the putative sugar gustatory receptor genes based on the genome data of H. armigera (Pearce et al. 2017), the reported gene sequences of sugar GRs in H. armigera and their phylogenetic relationship of D. melanogaster sugar gustatory receptors (Jiang et al. 2015, Xu et al. 2012). All nine putative sugar GR genes in H. armigera, Gr4–12 were validated, and their full-length cDNA sequences were cloned (The GenBank accession number is provided in Appendix—Table S1).” (Line 155-161).

• Generation of mutants based on CRISPR is intriguing and a powerful step. While the techniques are well described in the method section, there is no information concerning efficiency or broader feasibility of the approach. I feel it would be quite interesting to learn about how feasible or laborious the approach is to generate mutants (e.g. number of initial injected eggs, the resulting F0 offspring, number of back-crosses, number of screened F1s ....).

In the Materials and Methods section, we have added specific success rates for each step in the process of building the two mutants (Line 722-726, 729-732).

Reviewer #3 (Recommendations For The Authors):

I want to congratulate the authors on this very nice study and have only minor comments for them.

(1) It would be very nice to include pictures of the larva and adult of H. armigera. It would also help to have schematics of where the sensilla they are recording from are.

We have added photos of four taste organs on which the recoded sensilla were indicated (Figure 1), and picture of the larva and adult on which the stimulating site was indicated (Figure 2).

(2) A schematic summarising their findings, including the relevance to the animal's behavioural ecology, will greatly improve interpretations for the broader audience.

A schematic summarizing the findings has been added.

(3) The manner in which PIs are represented in figure 2A, B (among others) is confusing. Can the authors please plot the PI and not the feeding area? From the PI values listed beside the plot, it actually suggests that the larvae don't really show a preference. Could the authors please comment on this?

Yes, sucrose has a significant stimulating effect on larva feeding, but the effect is not as large as the predicted based on the sensitivity of the sensillum, the main reasons are as follows: (1) there are many factors affecting larva feeding, sucrose is only one of them; (2) due to the substrate leaf discs also contain sugar, the effect of newly added sucrose may be reduced. After careful consideration, we think it is better to display the feeding area and PI together so that readers have a complete understanding of the data.

(4) The heterologous expression experiments suggest that co-expression of GR6 with either GR10 or GR5 somehow suppress the response of the GR6 alone to fucose. Am I reading the data correctly? Why would this be? Perhaps the authors could discuss this. In this context, it would help to reproduce all the GR6 data together.

Your interpretation is reasonable to a certain extent. The result of co-injection might be that Gr10 or Gr5 inhibited the response of Gr6. However, there is another possibility that the amount of Gr6 sRNA was diluted by co-injection of two GRs, resulting in a reduced response of Gr6 to fucose.

(5) In general, for each results section, it would help to have a sentence or two that interprets the data in the context of previously presented data. This would help the reader digest the data and interpret it as they read along. Currently, the authors summarise the observations and leave all the interpretation to the discussion section.

We accept the suggestion. In each part of the results, we have added a sentence to explain the above data, which will help readers to clarify the context of the research more easily.

(6) Is the GR6 data in 4C not lined up correctly?

Yes, it is right.

(7) Line 228 suggests that the mutants were validating with qPCRs - I don't see that data.

The mutants were not validating with qPCR. We used the ordinary PCR technology at the mRNA level to verify whether the related sequences were really deleted in the mutants.

eLife assessment

This important study identifies the gustatory receptors for sugar sensing in the larval and adult forms of the cotton bollworm, which is responsible for the destruction of many food crops world-wide. The authors find that the larval and adult forms utilise different receptors to sense sugars. The data are convincing and will be of interest neuroscientists working in sensory coding of sugars and to the pest management field.

Reviewer #1 (Public Review):

Summary:

The process of taste perception is significantly more intricate and complex in Lepidopteran insects. This investigation provides valuable insights into the role of Gustatory receptors and their dynamics in the sensation of sucrose, which serves as a crucial feeding cue for insects. The article highlights the differential sensitivity of Grs to sucrose and their involvement in feeding and insect behavior.

Strengths:

To support the notion of the differential specificity of Gr to sucrose, this study employed electrophysiology, ectopic expression of Grs in Xenopus, genome editing, and behavioral studies on insects. This investigation offers a fundamental understanding of the gustation process in lepidopteran insects and its regulation of feeding and other gustation-related physiological responses. This study holds significant importance in advancing our comprehension of lepidopteran insect biology, gustation, and feeding behavior.

Weaknesses:

While this manuscript demonstrates technical proficiency, there exists an opportunity for additional refinement to optimize comprehensibility for the intended audience. Several crucial sugars have been overlooked in the context of electrophysiology studies and should be incorporated. Furthermore, it is imperative to consider the potential off-target effects of Gr knock-out on other Gr expressions. This investigation focuses exclusively on Gr6 and Gr10, while neglecting a comprehensive narrative regarding other Grs involved in sucrose sensation.

Reviewer #2 (Public Review):

Summary:

To identify sugar receptors and assess the capacity of these genes the authors first set out to identify behavioral responses in larva and adult as well as physiological response. They used phylogenetics and gene expression (RNAseq) to identify candidates for sugar reception. Using first an in vitro oocyte system they assess the responses to distinct sugars. A subsequent genetic analysis shows that the Gr10 and Gr6 genes provide stage specific functions in sugar perception.

Strengths:

A clear strength of the manuscript is the breadth of techniques employed allowing a comprehensive study in a non-canonical model species.

Weaknesses:

There are no major weaknesses in the study for the current state of knowledge in this species. Since it is much basic work to establish a broader knowledge, context with other modalities remain unknown. It might have been possible to probe certain context known from the fruit fly, which would have strengthened the manuscript.

Author response:

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

Public Reviews:

Reviewer #3 (Public Review):

Kang, Huang, and colleagues have provided new data to address concerns regarding confirmation of LRRK1 and LRRK2 deletion in their mouse model and the functional impact of the modest loss of TH+ neurons observed in the substantia nigra of their double KO mice. In the revised manuscript, the new data around the characterization of the germline-deleted LRRK1 and LRRK2 mice add confidence that LRRK1 and LRRK2 can be deleted using the genetic approach. They have also added new text to the discussion to try and address some of the comments and questions raised regarding how LRRK1/2 loss may impact cell survival and the implications of this work for PD-linked variants in LRRK2 and therapeutic approaches targeting LRRK2.

The new data provides additional support for the author's claims. I have provided below some suggestions for clarification/additions to the text that can be addressed without additional experiments.

(1) The authors added additional text highlighting that more studies are warranted in mice where LRRK1/2 are deleted in other CNS cell types (microglia/astrocytes) to understand cell extrinsic drivers of the autophagy deficits observed in their previous work. It still remains unclear how loss of LRRK1/2 leads to increased apoptosis and gliosis in dopaminergic neurons in a cell-intrinsic manner, and, as suggested in the original review, it would be helpful to add some text to the discussion speculating on potential mechanisms by which this might occur.

(2) Revisions have been made to the discussion to clarify their rationale around how variants in LRRK2 associated with PD may be loss-of-function to support the relevance of this mouse model to phenotypes observed in PD. However, as written, the argument that PD-linked variants are loss-offunction is based on the fact that the double KO mice have a mild loss of TH+ neurons while the transgenic mice overexpressing PD-linked LRRK2 variants often do not and that early characterization of kinase activity was done in vitro are relatively weak. Given that the majority of evidence generated by many labs in the field supports a gain-of-function mechanism, the discussion should be further tempered to better highlight the uncertainty around this (rather than strongly arguing for a loss-offunction effect). This could include the mention of increased Rab phosphorylation observed in cellular and animal models and opposing consequences on lysosomal function observed in cellular studies in KO and pathogenic variant expressing cells. Further, a reference to the Whiffen et al. 2020 paper mentioned by another reviewer should be included in the discussion for completeness.

We thank the reviewer for the comments. The discussion has been further revised and expanded to explain the cell extrinsic microglial response to pathophysiological changes in DA neurons of cDKO mice and propose future studies of single-cell RNA-sequencing to identify molecular changes within DA neurons of cDKO mice that may drive their apoptotic death during aging.

We also added paragraphs summarizing existing experimental evidence for the toxic gain-of-function mechanism (biochemical data of increased kinase activity but the lack of evidence for the elevated pRabs and the altered pLRRK2 driving dopaminergic neurodegeneration) and for the loss-of-function mechanism (genetic data of relevant physiological roles) as well as the relationships between LRRK1 and LRRK2 (functional homologues sharing functional domains and overlapping roles in dopaminergic neuron survival) and how dominantly inherited missense mutations can confer a loss of function mechanism (impairing its function in cis and inhibiting wild-type protein function in trans). We also provided a brief summary and discussion of the Whiffen et al. 2020 paper.

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weakness:

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

Revision:

I appreciate the authors revising the manuscript with additional data that have clarified my prior comments. They now show that TH levels in the striatum decrease with SNpc neurons. Further, while there is some disagreement regarding the expression LRRK1 in SNpc, the authors provide a convincing case that LRRK1 function is important in SNpc DA neurons.

eLife assessment

This current revision builds on observations in validated conditional double KO (cDKO) mice for LRRK1 and LRRK2 that will be useful for the field, given that LRRK2 is widely expressed in the brain and periphery, and many divergent phenotypes have been attributed previously to LRRK2 expression. The manuscript presents solid data demonstrating that it is the loss of LRRK1 and LRRK2 expression within the SNpc DA cells that is not well tolerated, as it was previously unclear from past work whether neurodegeneration in the LRRK double Knock Out (DKO) was cell autonomous or the result of loss of LRRK1/LRRK2 expression in other types of cells. Future studies may pursue the biochemical mechanisms underlying the reason for the apoptotic cells noted in this study, as here, the LRRK1/LRRK2 KO mice did not replicate the dramatic increase in autophagic vacuole numbers previously noted in the germline global LRRK1/LRRK2 KO mice.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

For the first time, the study described a model in which both the Parkinson's disease-associated gene LRRK2 and its homolog LRRK1 are deleted selectively in dopaminergic neurons. This offers a new tool to understand the physiopathological role of LRRK2 and the compensating role of LRRK1 in modulating dopaminergic cell function.

Weaknesses:

The model has no construct validity since loss of function mutations of LRRK2 are well tolerated in humans and do not lead to Parkinson's disease. The evidence of a Parkinsonian phenotype in these conditional knockout mice is limited and should be considered preliminary.

Reviewer #3 (Public Review):

Kang, Huang, and colleagues have provided new data to address concerns regarding confirmation of LRRK1 and LRRK2 deletion in their mouse model and the functional impact of the modest loss of TH+ neurons observed in the substantia nigra of their double KO mice. In the revised manuscript, the new data around the characterization of the germline-deleted LRRK1 and LRRK2 mice add confidence that LRRK1 and LRRK2 can be deleted using the genetic approach. They have also added new text to the discussion to try and address some of the comments and questions raised regarding how LRRK1/2 loss may impact cell survival and the implications of this work for PD-linked variants in LRRK2 and therapeutic approaches targeting LRRK2. The new data provides additional support for the author's claims.

Author response:

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

Reviewer #1 (Public Review):

Summary:

This study identifies a family of solute transports in the enteric protist, Blastocystis, that may mediate the transport of glycolytic intermediates across the mitochondrial membrane. The study builds on previous observations suggesting that Blastocystis (and other Stramenopiles) are unusual in having a compartmentalized glycolytic pathway with enzymes involved in upper and lower glycolysis being located in the cytosol and mitochondria, respectively. In this study, the authors identified two putative Stamenopile metabolite transporters that are related to plant di/tricarboxylic acid transporters that might mediate the transport of glycolytic intermediates across the mitochondrial membrane. These GIC-transporters were localized to the Blastocystis mitochondrion using specific rabbit antibodies and shown to bind several glycolytic intermediates (including GAP, DHAP, and PEP) based on thermostability shift assays. Direct evidence for transport activity was obtained by reconstituting native proteins in proteoliposomes and measuring the uptake of 14C-malate or 35S-sulphate against unlabelled substrates. This assay showed that GIC-2 transported DHAP, GAP, and PEP. However, significant transport activity was not observed for bGIC-2. Overall, the study provides strong, but not conclusive evidence that bGIC-1 is involved in transporting glycolytic intermediates across the inner membrane of the mitochondria, while the function of GIC-2 remains unclear, despite exhibiting the same metabolite binding properties as bGIC-2 in thermostability assays.

Strengths:

Overall, the findings are of interest in the context of understanding the diversity of core metabolic pathways in evolutionarily diverse eukaryotes, as well as the process by which cytosolic glycolysis evolved in most eukaryotes. The experiments are carefully performed and clearly described.

We thank the reviewer for their constructive comments. We note that bGIC-2 is the identified glycolytic intermediate transporter, not bGIC-1.

Weaknesses:

The main weakness of the study is the lack of direct evidence that either bGIC-1 and/or bGIC2 are active in vivo. While it is appreciated that the genetic tools for disrupting GIC genes in Blastocystis are limited/lacking, are there opportunities to ectopically express or delete these genes in other Stamenopiles, such as Phaeodactylum triconuteum, to demonstrate function in vivo?

Here, we have identified a transport protein, unique to stramenopiles, which is present in mitochondria of Blastocystis and can bind and transport glycolytic intermediates. We agree that it would have been desirable to confirm that they function as glycolytic intermediate transporters in vivo. However, the reviewer is correct in saying that the genetic tools for disrupting GIC genes in Blastocystis in vivo are not available. While the reviewer mentions the possibility of performing these analyses in Phaeodactylum tricornutum, it is important to note that this species possesses aerobic mitochondria and that the pay-off phase of glycolysis is present in both the mitochondrial matrix and the cytosol. Consequently, any data obtained from this species might not be conclusive and would also not be relevant to the glycolytic metabolism in Blastocystis, the subject of this study.

The authors demonstrate that both bGIC-1 and bGIC-2 are targeted to the mitochondrion, based on immunofluorescence studies. However, the precise localization and topology of these carriers in the inner or outer membrane are not defined. The conclusions of the study would be strengthened if the authors could show that one/both transporters are present in the inner membrane using protease protection experiments following differential solubilization of the outer and inner mitochondrial membranes.

The protein is a member of the mitochondrial carrier family, which are extremely hydrophobic membrane proteins. Those with an established transport function are known to localise consistently to the mitochondrial inner membrane, which is impermeable to charged molecules, whereas the outer membrane is porous through VDAC. Furthermore, when the carriers are overproduced in Saccharomyces cerevisiae, the protein is found in the enriched mitochondrial fraction, adding further support to the idea that they are localised to the inner membrane, as the outer membrane has a limited surface area.

It is not clear why hetero-exchange reactions were not performed for bGIC-1 (only for bGIC-2).

Unfortunately, bGIC-1 did not display transport activity when tested in [14C]-malate/malate, [35S]-sulphate/sulphate or [33P]-phosphate/phosphate homo-exchange reactions, as shown in Figure 6 (Figure 5 in the revised manuscript). Phosphoenolpyruvate and dihydroxyacetone phosphate are not available in a radiolabelled form and glyceraldehyde-3-phosphate is prohibitively expensive, so we were unable to test glycolytic intermediates directly in homo-exchange reactions. Hetero-exchange reactions, as performed in Figure 5 (Figure 6 in the revised manuscript) for bGIC-2, are conclusive, as accumulation of the radio-labelled substrate inside the proteoliposomes can only occur, when the internal substrate is exported. It seems that Blastocystis has multiple copies, some of which are coding for dysfunctional carriers, being possible pseudo-genes.

The summary slide depicted in Fig 7 is somewhat simplified and inaccurate. First, the authors show that TPI is located in the mitochondria in this study, while in the summary figure, TPI is shown to be present in both the cytosol and mitochondrial matrix. A cytosolic localization for TPI provides a functional rationale for having a triose-P carrier in the inner membrane - however, this is not supported by the data shown here. Second, if bGIC1/2 uses PEP as a counter ion to import GA3P and DHAP into the mitochondrion, as proposed in Fig 7, the lower glycolytic pathway would be effectively truncated at PEP, removing substrate for pyruvate kinase and formation of pyruvate/ATP. Third, the authors suggest that DHAP may have other functions in the mitochondria although these are not shown in the figure.

Figure 7 presents a schematic comparison of the localisation of glycolysis in humans and Blastocystis, specifically focused on the transport steps of either pyruvate (humans) or glycolytic intermediates (Blastocystis) into the mitochondrial matrix. Most of the metabolism of Blastocystis has been inferred from the presence or absence of genes, encoding for particular enzymes, with the exception of the unusual glycolytic pathway. We feel that overcomplicating this schematic figure would detract from the main message of this analysis. Although the transport data show that PEP, another glycolytic intermediate, is transported, we agree with the reviewer that PEP export cannot be rationalised in the context of our current understanding of the metabolism, and we have changed the figure accordingly.

We have not suggested that DHAP has other functions in mitochondria; on line 230, we state that ‘we have not found any evidence for the presence of dihydroxyacetone phosphate inside mitochondria in the literature. It is possible that it is not transported under physiological conditions in competition with dicarboxylates or other substrates.’

Reviewer #2 (Public Review):

In this manuscript, the authors set out to identify transporters that must exist in Stramenophiles due to the fact that the second half of glycolysis appears to be conducted in the mitochondria. They hypothesize that a Stramenophile-specific clade of transporters related to the dicarboxylate carriers is likely the relevant family and then go on to test two proteins from Blastocystis due to the infectious disease relevance of this organism. They show rather convincingly that these two proteins are expressed and are localized to the mitochondria in the native organism. The purified proteins bind to glycolytic intermediates and one of them, GIC-2, transports several glycolytic intermediates in vitro. This is a very solid and well-executed study that clearly demonstrates that bCIC-2 can transport glycolytic intermediates.

We thank the reviewer for their positive comments on the manuscript, and their careful analyses of the presented data.

(1) The major weakness is that the authors aren't able to show that this protein actually has this function in the native organism. This could be impossible due to the lack of genetic tools in Blastocystis, but it leaves us without absolute confidence that bGIC-2 is the important glycolytic intermediate mitochondrial transporter (or even that it has this function in vivo).

Unfortunately, genetic manipulation in Blastocystis is currently not feasible and thus we cannot conduct a comparative metabolic study with the appropriate controls. The gold standard for identification is to prove the function with purified protein directly, which we have done here by using binding studies and transport assays.

(2) It's atypical that the figures and figure panels don't really follow the order of their citation in the text. It's not a big deal, but mildly annoying to have to skip around in the figures (e.g. Figure 3D-E are described in the same paragraph as Figure 5). In addition, to facilitate the flow and a proper understanding I would encourage a reordering between figures 5D and 6 since Figure 6 is needed to understand the results shown in panel 5D, which may lead to confusion.

We agree with the reviewer and have reordered the figures, switching Figure 5 and 6, which makes the manuscript easier to follow.

(3) My impression is that the authors under-emphasize the fact that the hDIC also binds (and is stabilized by) glycolytic intermediates (G3P and 3PG). In the opinion of this reviewer, this might change the interpretation about the uniqueness of the bGIC proteins. They act on additional glycolytic intermediates, but it's not unique.

The reviewer is correct that hDIC is stabilized by both G3P and 3PG, but neither are transported, as shown in Figure 5B (Figure 6B in the revised manuscript). It is not uncommon for compounds to bind to some extend without being transported, as they share certain structural and chemical features with the substrates, which result in stabilisation in thermostability analyses. For example, GTP stabilises the ADP/ATP carrier in thermostability analyses to some extent (Majd et al, 2018), although it is not a transported substrate of the carrier (King et al, 2020). Although thermostability assays are very useful for screening of potential substrates, it is always necessary to carry out transport assays, which are the gold standard for transporter identification.

Reviewer #3 (Public Review):

Summary:

Unlike most eukaryotes, Blastocystis has a branched glycolysis pathway, which is split between the cytoplasm and the mitochondrial matrix. An outstanding question was how the glycolytic intermediates generated in the 'preparatory' phase' are transported into the mitochondrial matrix for the 'pay off' phase. Here, the authors use bioinformatic analysis to identify two candidate solute carrier genes, bGIC-1, and bGIC-2, and use biochemical and biophysical methods to characterise their substrate specificity and transport properties. The authors demonstrate that bGIC-2 can transport dihydroxyacetone phosphate, glyceraldehyde-3-phosphate, 3-phosphoglycerate, and phosphoenolpyruvate, establishing this protein as the 'missing link' connecting the two split branches of glycolysis in this branch of single-celled eukaryotes. The authors also present their data on bGIC-1, which suggests a role in anion transport and bOGC, which is a close functional homologue of the human oxoglutarate carrier (hOGC, SLC25A11) and human dicarboxylate carrier (hDIC, SLC25A10).

Strengths:

The results are presented in a clear and logical arrangement, which nicely leads the reader through the process of gene identification and subsequent ligand screening and functional reconstitution. The results are compelling and well supported - the thermal stabilisation data is supported by the exchange studies. Caveats, where apparent, are discussed and rational explanations are given.

We thank the reviewer for their positive and constructive comments on the manuscript.

Weaknesses:

The study does not contain any significant weaknesses in my view. I would like to see the authors include the initial rate plots used in the main figures (possibly as insets), so we can observe the data points used for these calculations. It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

We have shown uptake curves in both Figure 3 and Figure 6 (Figure 5 in the revised manuscript) to provide the typical uptake curves that we record by our robot, and we also show how we calculate the initial rates. We feel that the inclusion of uptake curves for each compound for each carrier (96 uptake curves in total) would make figure 5 (Figure 6 in the revised manuscript) extremely complicated.

It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

Whilst AlphaFold is an important step forward in the prediction of protein structures, it is not accurate enough at this time to be used for the rationalisation of the substrate specificity. For instance, there are the significant structural differences between the predicted AlphaFold structure of the human uncoupling protein (https://alphafold.ebi.ac.uk/entry/P25874), by and large based on the mitochondrial ADP/ATP carrier, and the experimentally determined structure, especially for the central cavity where the substrate recognition takes place (Jones et al, 2023; Kang & Chen, 2023). More importantly, it is believed that the optimal binding of the substrate takes place in the occluded state (Klingenberg, 2007; Springett et al, 2017), for which we have no structure.

References

Jones SA, Gogoi P, Ruprecht JJ, King MS, Lee Y, Zögg T, Pardon E, Chand D, Steimle S, Copeman DM et al (2023) Structural basis of purine nucleotide inhibition of human uncoupling protein 1. Sci Adv 9: eadh4251

Kang Y, Chen L (2023) Structural basis for the binding of DNP and purine nucleotides onto UCP1. Nature 620: 226-231

King MS, Tavoulari S, Mavridou V, King AC, Mifsud J, Kunji ERS (2020) A single cysteine residue in the translocation pathway of the mitosomal ADP/ATP carrier from Cryptosporidium parvum confers a broad nucleotide specificity. Int J Mol Sci 21: 8971

Klingenberg M (2007) Transport viewed as a catalytic process. Biochimie 89: 1042-1048

Majd H, King MS, Palmer SM, Smith AC, Elbourne LD, Paulsen IT, Sharples D, Henderson PJ, Kunji ER (2018) Screening of candidate substrates and coupling ions of transporters by thermostability shift assays. Elife 7: e38821

Springett R, King MS, Crichton PG, Kunji ERS (2017) Modelling the free energy profile of the mitochondrial ADP/ATP carrier. Biochim Biophys Acta 1858: 906-914

eLife assessment

This important study identifies candidate mitochondrial metabolite carriers in stramenopile protists that may allow these divergent eukaryotes to maintain a compartmentalized glycolytic pathway. This study fills a gap in our understanding of glycolysis evolution and opens avenues for drug design to combat stramenopile parasites. The evidence, based on phylogenetic analysis, thermostability shift assays, and in vitro reconstitution of transport reactions, is convincing, albeit lacking direct in vivo confirmation of the physiological function of these candidates.

Reviewer #1 (Public Review):

Summary

This study identifies a family of solute transports in the enteric protist, Blastocystis, that may mediate the transport of glycolytic intermediates across the mitochondrial membrane. The study builds on previous observations suggesting that Blastocystis (and other Stramenopiles) are unusual in having a compartmentalized glycolytic pathway with enzymes involved in upper and lower glycolysis being located in the cytosol and mitochondria, respectively. In this study, the authors identified two putative Stamenopile metabolite transporters that are related to plant di/tricarboxylic acid transporters that might mediate the transport of glycolytic intermediates across the mitochondrial membrane. These GIC-transporters were localized to the Blastocystis mitochondrion using specific rabbit antibodies and shown to bind several glycolytic intermediates (including GAP, DHAP and PEP) based on thermostability shift assays. Direct evidence for transport activity was obtained by reconstituting native proteins in proteoliposomes and measuring uptake of 14C-malate or 35S-sulphate against unlabelled substrates. This assay showed that GIC-2 transported DHAP, GAP and PEP. However, significant transport activity was not observed for bGIC-2. Overall, the study provides strong, but not conclusive evidence that bGIC-2 is involved in transporting glycolytic intermediates across the inner membrane of the mitochondria, while the function of GIC-1 remains unclear, despite exhibiting the same metabolite binding properties as bGIC-2 n thermostability assays.

Strengths:

Overall, the findings are of interest in the context of understanding the diversity of core metabolic pathways in evolutionarily diverse eukaryotes, as well as the process by which cytosolic glycolysis evolved in most eukaryotes. The experiments are carefully performed and clearly described.

Weaknesses:

The main weakness of the study is the lack of direct evidence that either bGIC-1 and/or bGIC2 are active in vivo. While it is appreciated that the genetic tools for disrupting GIC genes in Blastocystis are limited/lacking, are there opportunities to ectopically express or delete these genes in other genetically tractable Stamenopiles, such as Phaeodactylum triconuteum?

The authors demonstrate that both bGIC-1 and bGIC-2 are targeted to the mitochondrion, based on immunofluorescence studies. However, the precise localization and topology of these carriers in the inner or outer membrane is not defined. The conclusions of the study would be strengthened if the authors could show that one/both transporters are present in the inner membrane using protease protection experiments following differential solubilization of the outer and inner mitochondrial membranes.

It is not clear why hetero-exchange reactions were not performed for bGIC-1 (only for bGIC-2).

In both their previous study (Bartulos et al (2018) and the current study, the authors have shown that Blastocystis express a TPI-GAPDH fusion protein which is located to the mitochondrion. The presence of the TPI domain in the mitochondrial matrix would obviate the need for bGIC-1/2 triose transporters and decrease their value as drug targets. It is noted that Blastocystis still retains some TPI activity in the cytosol, presumably due to expression of a second cytoplasmic isoform, which could account for the presence of the bGIC transporters. However, some discussion on the role of this mitochondrial TPI-GAPDG fusion protein in Blastocystis and other Stramenopiles would be useful.

The summary slide (Fig 7) in the revised manuscript no longer shows PEP being used as a countersolute for the import of G3P and DHAP. Although it complicates the story, the role of PEP as a counter solute should be shown for completeness and also to make sense of some of the statements in the discussion. In particular, as noted by the authors, mitochondrial PEP could be exported back to the cytsol and converted to pyruvate and/or lactate to generate ATP and NAD, although at the expense of ATP synthesis in the mitochondria.

Reviewer #2 (Public Review):

In this manuscript, the authors set out to identify transporters that must exist in Stramenophiles due to the fact that the second half of glycolysis appears to be conducted in the mitochondria. They hypothesize that a Stramenophile-specific clade of transporters related to the dicarboxylate carriers are likely the relevant family and then go on to test two proteins from Blastocystis due to the infectious disease relevance of this organism. They show rather convincingly that these two proteins are expressed and are localized to the mitochondria in the native organism. The purified proteins bind to glycolytic intermediates and one of them, GIC-2, transports several glycolytic intermediates in vitro. This is a very solid and well-executed study that clearly demonstrates that bCIC-2 can transport glycolytic intermediates.

(1) The major weakness is that the authors aren't able to show that this protein actually has this function in the native organism. This could be impossible due to the lack of genetic tools in Blastocystis, but it leaves us without absolute confidence that bGIC-2 is the important glycolytic intermediate mitochondrial transporter (or even that it has this function in vivo).

(2) My impression is that the authors under-emphasize the fact that the hDIC also binds (and is stabilized by) glycolytic intermediates (G3P and 3PG). In the opinion of this reviewer, this might change my interpretation about the uniqueness of the bGIC proteins. They act on additional glycolytic intermediates, but it's not unique.

Reviewer #3 (Public Review):

Summary:

Unlike most eukaryotes Blastocystis has a branched glycolysis pathway, which is split between the cytoplasm and the mitochondrial matrix. An outstanding question was how the glycolytic intermediates generated in the 'preparatory' phase' are transported into the mitochondrial matrix for the 'pay off' phase. Here, the authors use bioinformatic analysis to identify two candidate solute carrier genes, bGIC-1 and bGIC-2, and use biochemical and biophysical methods to characterise their substrate specificity and transport properties. The authors demonstrate that bGIC-2 can transport dihydroxyacetone phosphate, glyceraldehyde-3-phosphate, 3-phosphoglycerate and phosphoenolpyruvate, establishing this protein as the 'missing link' connecting the two split branches of glycolysis in this branch of single celled eukaryotes. The authors also present their data on bGIC-1, which suggests a role in anion transport and bOGC, which is a close functional homologue of the human oxoglutarate carrier (hOGC, SLC25A11) and human dicarboxylate carrier (hDIC, SLC25A10).

Strengths:

The results are presented in a clear and logical arrangement, which nicely leads the reader through the process of gene identification and subsequent ligand screening and functional reconstitution. The results are compelling and well supported - the thermal stabilisation data is supported by the exchange studies. Caveats, where apparent, are discussed and rational explanations given.

Weaknesses:

The study does not contain any significant weaknesses in my view. I would like to see the authors include the initial rate plots used in the main figures (possibly as insets), so we can observe the data points used for these calculations. It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

Author response:

Reviewer #2 (Public Review):

In this study, the authors report that both mice and human patients carrying function-disrupting mutations in the OFD1 gene exhibited ectopic brown adipose tissue formation in the malformed tongue. The OFD1 gene is located on the X-chromosome and encodes a protein product required for the formation and function of the primary cilium, which is required for cells to properly receive and activate several signaling pathways, particularly the hedgehog signaling pathway. Loss of OFD1 function causes prenatal lethality of male fetuses and mosaic disruption of tissues in females due to random inactivation of the X-chromosome carrying either the mutant or wildtype allele. Using cell type-specific gene inactivation and genetic lineage labeling, the manuscript shows that the ectopic brown adipose tissue in the mutant tongue was not derived from cranial neural crest cells (CNCCs). Additional genetic and embryological studies led to the conclusion that loss of Ofd1 function in the CNCC cells in the embryonic hypoglossal cord, via which the tongue myoblast precursor cells migrate from anterior somites to the tongue primordia, caused disruption of cell-cell interactions between the CNCCs and migrating muscle precursor cells, resulting in altered differentiation of those myoblast precursor cells into brown adipocytes. The authors provided data that disruption of Smo in a subset of CNCCs also resulted in ectopic adipose tissue formation in the tongue, indicating that this phenotype in the Ofd1 mutant mice was likely caused by disruption of hedgehog signaling in CNCCs. However, no experimental evidence is provided to support a major conclusion of the manuscript regarding altered differentiation of the tongue myoblast precursor cells into brown adipocytes in the Ofd1 mutant mice. Since it is well established that hedgehog signaling in the CNCCs is required for them to direct tongue myoblast cell migration as well as for tongue muscle differentiation/organization after the myoblasts arrived in the tongue primordia, the finding of tongue muscle defects in the Ofd1 mutant mice is not surprising. However, if proven true that disruption of Ofd1 function in CNCCs caused tongue myoblast precursor cells to alter their fate and differentiate into brown adipocytes, it would be an interesting new finding. Further identification of the signals produced by the Ofd1 mutant CNCCs for directing the cell fate switch will be a highly significant new advance in understanding the cellular and molecular mechanisms regulating tongue morphogenesis.

Many in vitro and in vivo data have been added as new data. We hope that these are enough for our conclusion. It is extremely difficult to identify the signals produced by the Ofd1 mutant CNCCs for directing the cell fate switch of mesodermal cells after activation of Hh signaling in CNCC. Instead, our new findings raise the possibility that Hh signaling in mesodermal cells is also important for their differentiation as well as Hh signaling in CNCC, which has been added in revised paper. However, we think that it is beyond the scope of this study to deepen these.

Reviewer #3 (Public Review):

The authors observed phenotypes of ciliopathy model mice and they seem to coincide with those in human patients. They used mutants in which cilial function genes are deleted in cranial neural crest cells, and found the mutants exhibit abnormal cell differentiation in both neural crest- and mesoderm-lineage cells. The finding clearly shows the importance of tissue/cell interaction. The authors mainly observed the mouse in which Ofd1 gene that is coded on the X chromosome is deleted, therefore, Ofd1fl/WT;Wnt1Cre(HET) mice show that about one-fourth of neural crest cells can exhibit Ofd1 function whereas Ofd1fl;Wnt1Cre (HM) shows null Ofd1 function and show severer phenotypes than HET.

For ectopic brown adipose tissue in the tongue is derived from mesoderm and the authors tried to show that the hypoglossal cord failed to obtain myogenic lineage after entering branchial arches in HET and HM due to lack of communication with neural crest cells. For ectopic bone formation, they found that it is due to the lack of Hedgehog signaling in neural crest cells, which was consistent with the reports in the Smofl/fl;Wnt1-Cre (Xu et al., 2019) and Ift88fl/fl;Wnt1Cre (Kitamura et al. 2020). The ectopic bone is connected to the original mandibular bone. The authors attribute the ectopic bone formation to the migration of mandibular bone neural crest cells into the tongue-forming area.

For the poor tongue frenum formation, the authors found the importance of cell migration from the lateral sides of the branchial arch to the midline and its formation relies on non-canonical Wnt signaling. The authors observed similar phenotypes in the human patients as those in the mutants. The adipose tissue in the tongue area is normally found in the salivary gland region and intermuscular space, and it is intriguing to find the brown adipose tissue anterior to the cervical area in which the most anterior brown adipose tissue develops. qRT-PCR indicates that some of the marker genes are expressed in the laser micro-dissected sections of the ectopic brown adipose tissue. However, histology does not show the typical brown adipose tissue feature. In addition, brown adipose tissue is normally recognized in the sixth pharyngeal region as the cervical brown tissue from around E14.5 (Schulz and Tseng 2013), not E12 as the authors observe. Although the mutants develop under abnormal conditions, is it possible to say they are brown adipose tissue? The point has to be further investigated with more marker expression by immunohistochemical detection and other methods. Since the mutants seem to show impaired midline formation (which is consistent with the condition of human ciliopathy), is it possible to hypothesize that the adipose-like tissue is derived from the mesoderm of posterior branchial arch levels if the tissue is brown adipose tissue?

Immunohistochemistry data has been added as new Figure S4 and S5.

We agree reviewer’s comment. Histology of ectopic adipose in Ofd1 cKO is slightly different from typical images of brown adipose. Molecular characters of ectopic adipose in Ofd1 mutant tongue are similar to these of low thermogenic adipocyte. Histological features of low thermogenic is known to be different from that of typical brown adipose tissue. Histological features of low thermogenic adipocyte is similar to that of ectopic adipose in Ofd1 mutant mice. This has been mentioned in Results section.

The cervical brown adipose tissue in Ofd1 mutant should be shrinked or be connected to ectopic adipose in mutant tongue, if ectopic adipose in mutant tongue was derived from the cervical brown adipose tissue due to mis-migration. However, any significant changes of the cervical brown adipose tissue or conection between cervical brown adipose and tongue adipose could not be detected in Ofd1 mutant mice. We think that ectopic adipose in mutant tongue is unlikely derived from cervical brown adipose tissue. These have been added in Result section.

Cranial neural crest cells start migrating around E8.0 and reach their destination by E9.5. The authors show the lack of neural crest cells in the midline, the fluorescence is absent from the midline in HM, however, they studied it in the E11 mandible (Fig. 4E), almost more than two days after neural crest migration completes. Since the mandibular arch seems to form at the beginning in the mutants, is there a failure in allocating the neural crest and mesoderm at the beginning of the mandibular arch formation?

It is difficult to prove how much migration is affected in mutant mice. Therefore, sentence describing migration has been deleted in revised paper

The authors tried to disturb the interaction between the hypoglossal cord and neural crest cells by making incisions in the dorsal area of the branchial arches. That area contains both neural crest and mesoderm but not the hypoglossal cord-derived mesoderm. The hypoglossal cord passed through the posterior edge of the caudal (6th) pharyngeal arch, along the lateral side of the pericardium towards the anterior, ventral to branchial arches, and then inside the 2nd and 1st branchial arches (Adachi et al., 2018). It expresses Pax3 before entering the branchial arches, then Myf5 in the branchial arches. It seems that the migration of the hypoglossal cord does not require interaction with neural crest cells but it has to be confirmed as well as neural crest migration into the branchial arches from the beginning. Although the hypoglossal cord migrates mostly in mesoderm-derived mesenchyme, we cannot exclude the possibility that hypoglossal cord migration is affected.

Cutting region in original Figure 2Q was not accurate. It has been changed in new Figure 3Q. We agree reviewer’s comment “we cannot exclude the possibility that hypoglossal cord migration is affected”. However, It is difficult to prove how much migration is affected in mutant mice. Therefore, sentence describing migration has been deleted in revised paper

The lack of Myf5 expression in Ofd1fl;Wnt1Cre (HM) was explained as a failure in the differentiation of the hypoglossal cord into myoblasts on entrance into the branchial arches. Most of the cervical brown adipose tissue is derived from either Myf5- or Pax3- expressing lineage (Sanchez-Gurmaches and Guertin, 2014). Although the authors suggest that brown adipose cells are fate-changed mesoderm in the branchial arches, how do they explain the association with Myf5- or Pax3- expression?

As reviewer mentioned, the cervical brown adipose tissue is derived from either Myf5- or Pax3- expressing lineage. However, these cells lost Myf5- or Pax3 expression when they differentiate into brawn adipocytes. Although ectopic adipose in Ofd1 mutant tongue showed Pax3 expression at early stage, they likely loose Pax3 expression soon after. There is another possibility that ectopic adipocytes retain Pax3 expression, if they would be abnormal adipocytes. If so, it's not surprised when expression pattern of ectopic adipocytes in Ofd1 mutant is different from these of normal brown adipose tissue. Anything can be possible in these situation. Therefore, we don’t mention anything about these in the text

In addition, the cervical brown tissue is supposed to be derived from the branchial arch mesoderm (Mo et al., 2017). Is the formation of the cervical brown tissue affected in the Ofd1fl/WT;Wnt1Cre(HET) or Ofd1fl;Wnt1Cre (HM) if dysfunction of neural crest cells results in the cell fate change of mesoderm?

Any significant morphological changes of the cervical brown adipose tissue could not be detected in Ofd1 mutant mice. Ectopic adipose tissue in Ofd1 cKO was found from E115, while cervical adipose tissue form from E14.5. We think that dysfunction of CNCC at E14.5 does not affect mesodermal cells for the cervical adipose tissue.

For the tongue frenum development, it is hard to understand to hypothesize that its formation is unlikely to associate with midline formation. Although Lgr5 and Tbx22 are not expressed in the midline, the defect in midline formation could cause unnecessary interaction between the right and left tissues.

We agree reviewer’s comment. The sentences have been changed in new manuscript.

Tissue morphogenesis takes place in three dimensions, which were not considered in the data, especially in the labeling experiments. When the authors labelled the cells, which cells in which area were labelled? In the textbook, tongue formation is a result of the fusion of the midline processes derived from the branchial arches, therefore, it is important to identify which cells in which area are labelled.

Data of Lgr5 and Tbx22 in situ hybridization has been added as new Figure 10-S1D and -S1E, since we labelled cells within Lgr5 and Tbx22 expression domain. Data showing section of explant with DiD injection before and after culture has been added as new Figure 10-S1F and -S1G, which showed DiD labelled cells were located within Lgr5 and Tbx22 expression domain before culture and at tongue frenum region after culture.

The weakest point is that the authors demonstrate many interesting phenotypes but fail to show the mechanism of altered cell differentiation and direct evidence of the tissue origin of ectopic brown tissue. Without the data, suggestion from the authors' argument is weak, which is reflected in the conclusion of the abstract.

Many in vitro and in vivo data have been added as new data. We hope that these are enough for our conclusion.

Author response:

Reviewer #2 (Public Review):

(1) Some changes to statistical analyses are needed in this study.

Fig. 1B, 1D, 2A, 3E, and 3F report the QL.d phenotype as a percentage of animals scored that were defective in migration. The methods make it clear this data is categorical rather than quantitative. Therefore, a t-test or any test designed for quantitative data is not appropriate. I suggest that the authors should investigate using a chi-squared or Fisher's exact test.

For the reasons mentioned above, the calculation of standard deviation (as shown in error bars) is also not appropriate for Fig. 1B, 1D, 2A, 3E, and 3F. Of course, it is excellent that the authors scored multiple trials. For experiments with mutants, I suggest the authors might combine these trials or show separate results of each trial. For experiments using RNAi (Fig. 1B), each trial should be plotted separately because RNAi effectiveness can vary. If there is not enough space to show multiple trials, then I would ask that a representative trial be shown in the main figure and additional trials in a supplement.

We thank the reviewer for pointing out the statistical mistake. For all figures assessing the QL.d migration phenotype (Fig.1B, 1D, 2A, 4A (former 3E), 4D (former 3F) and Fig.1 – figure supplement 1, Fig.2 – figure supplement 1, Fig.4 – figure supplement 2) the statistical significance was evaluated using Fisher’s exact test. For RNAi experiments (Fig. 1B) results from a representative experiment is shown and two additional trials are shown in Figure 1 – figure supplement 1. For experiments with mutants, results from separate trials were pooled and are presented in the main figures.

In Fig. 1, 2, 3, and 5, it is not specified whether/how p-values were adjusted for multiple tests.

We have applied Bonferroni correction for multiple testing in all Figures where it was relevant (Fig. 1, 2, 4, 5 and 6 and in their supplements) and this is now stated in all corresponding Figure legends.

(2) I felt the author's interpretation of the sel-5 mutant phenotypes in EXC, and the genetic interactions with Wnt signaling mutants, might be improved. The authors show convincing data that the sel-5 mutants display a shortened EXC outgrowth phenotype. Conversely, mutants with reduced Wnt signaling, such as the lin-17 or lin-44 mutants, displayed lengthened EXC outgrowth. The authors show that in double mutants, loss of sel-5 partially suppressed the EXC overgrowth defects of lin-17 or lin-44 mutants (Fig. 5). In my opinion, this data is consistent with a model where SEL-5 acts to inhibit Wnt signaling in EXC. An inhibitory role in a Wnt-receiving cell would be consistent with the known activity for human AAK1 in promoting negative feedback and endocytosis of LPR6. Interestingly, the authors mention in their discussion that a mutant of plr-1, which acts in the internalization of Frizzled receptors, has a shortened EXC phenotype similar to that of sel-5 mutants. These observations all seem consistent with an inhibitory role, yet the authors do not state this as their conclusion. A clarification of their interpretation is needed.

We thank the reviewer for this feedback. Indeed, the above interpretation of the excretory cell migration data is plausible, however, we think that several lines of evidence argue against this possibility. First, measurements of the posterior canal length during L1/L2 larval stages show that LIN-44/LIN-17 signalling is not required for the early stages of excretory canal outgrowth, unlike SEL-5/VPS-29 (Fig. 5E, 6D). This suggests that SEL-5 and VPS-29 are required earlier than LIN-44 and LIN-17 and therefore should not act at the level of Wnt receptor internalization. Our new data with more mutant combinations revealed canal shortening in cwn-1; cfz-2 and cwn-2; cfz-2 mutants. This would rather suggest a positive role for SEL-5 and VPS-29 in Wnt pathway regulation. Either SEL-5/VPS-29 employ two different mechanisms of Wnt pathway regulation or alternatively, act prior to any Wnt-dependent step in the excretory canal outgrowth. The observed partial rescue of the lin-17 or lin-44 overgrowth defect by sel-5 could then be explained for example by a reduced speed of canal outgrowth in sel-5 mutants. Based on new findings about CWN-1, CWN-2 and CFZ-2 involvement we have also modified our model now presented in Fig.7.

For changes to the Results section, see Response to Reviewer 1, point 4b. The Discussion part has been substantially rewritten and is presented below:

LINE 428 “Our analysis of single Wnt and Frizzled mutants revealed that while loss of cwn-2 or cfz-2 expression resulted in a very mild shortening of the excretory canal, loss of lin-44 or lin-17 led to profound canal overgrowth (summarized in Fig. 7A). These findings suggested that two independent Wnt pathways could be employed to establish proper excretory canal length – one promoting canal extension and one generating the stop signal for growth termination. Further analyses of double mutants and other Wnt signalling components revealed that the extension-promoting pathway includes cwn-1 in addition to cwn-2 and cfz-2, while the stop-signal pathway encompasses lin-44, lin-17, dsh-1, mig-5 and mig-14. A similar repulsive role of LIN-44/LIN-17 complex has been described in the case of a posterior axon of C. elegans GABAergic DD6 motor neuron (Maro et al., 2009) or PLM, ALN and PLN neurons (Zheng et al., 2015). Loss of lin-44 or lin-17 expression promoted outgrowth of the posterior neurites of these neurons implicating that in wild type animals, LIN-44 serves as a repulsive cue. On the other hand, cwn-2 and cfz-2 were shown to positively regulate the posterior neurite outgrowth of RMED/V neurons with cwn-2 acting as an attractive cue (Song et al., 2010). The role of two other Wnt signalling components, egl-20 and mig-1, is less clear. No effect (mig-1) or only very mild overgrowth defect (egl-20) is observed in single mutants. However, both egl-20 and mig-1 significantly rescue the overgrowth phenotype of lin-17 mutants, while at the same time, mig-1 can suppress the shortening of canals in cfz-2 mutants. EGL-20-producing cells are localized around the rectum (Whangbo et al., 1999; Harterink et al., 2011), exactly where the excretory canals stop, while LIN-44 is expressed more posteriorly (Herman et al., 1995; Harterink et al., 2011). A possible explanation could thus be that while LIN-44 provides a general posterior repulsive signal, EGL-20 fine-tunes the exact stopping position of the growing canal. The role of different Wnts and Frizzleds in excretory canal outgrowth is summarized in Fig. 7B. Further investigation will be required to decipher the exact way how SEL-5 and the retromer crosstalk with Wnt signalling during excretory cell outgrowth. It is clear though that more than one mechanism is likely involved. First, sel-5 vps-29 mutants display canal shortening similarly to cwn-1; cfz-2 or cwn-2; cfz-2 suggesting a positive regulatory role. Mutants in lin-17 and lin-44 display canal overgrowth, yet sel-5 is partially able to suppress this phenotype. This would imply a negative regulatory role of sel-5 and be in agreement with the role of AAK1 in Wnt pathway regulation (Agajanian et al., 2019). However, sel-5 and vps-29 are required already during the initial larval outgrowth while the LIN-44/LIN-17 signal is required later. The observed rescue might thus also be explained by a delayed growth of the canal and not by a direct impact of sel-5 and vps-29 on LIN-44 or LIN-17 levels or localization.”

Author response:

Reviewer #2 (Public Review):

The manuscript entitled " Multimodal HLA-I genotypes regulation by human cytomegalovirus US10 and resulting surface patterning" by Gerke et al describes the biochemical analysis of US10-mediated down regulation of HLA-I molecules. The authors systemically examine the surface expression of different HLA-I alleles in cells expressing US10 and interactions of US10 with HLA-I and antigen presentation machinery. Further, studies examined genotypic and allotypic differences during expression of US10/US11 transcripts suggest a different allelic class I downregulation. In general, the authors have included data supporting the major claims. Yet, the conclusions and findings of the study only marginally advance the overall understanding of HCMV viral evasion and the mechanism of US10 function.

Strengths:

The studies are well characterized and the studies utilize diverse HLA-I and HCMV viral molecules. The biochemistry is excellent and is of high quality. Importantly, the study describes HLA-I allelic specific HCMV down regulation at the cell surface and molecular levels.

Weaknesses:

(1) The authors use over expressive language such as "strong binding" that does not have a quantitative value and it is relative to the specific assay with only small differences among the factors.

We have changed the language to avoid non-quantitative expressions.

(2) The US10 binding to the HLA-I did not correlate with class I surface levels suggesting that binding to the APC machinery (Figure 1); hence, why does the binding of US10 to the APC define its mechanism of action.

We hypothesized that since binding to HLA-I allomorphs did not correlate with surface expression, further factors could be involved in regulation. Since the PLC (APC machinery) plays a major role for HLA-I expression, it was relevant to investigate this. The new data underlines the importance of the PLC for US10-mediated HLA-I regulation.

(3) The innovative and significant aspects of the study are limited. The study does not delineate the US10 mechanism of action or show data in which US10-mediated MHC class I down regulation impacts adaptive or innate immune function.

These remarks are important. We want to emphasize the variable impact of US10 on HLA-I. To our knowledge previous studies have not uncovered genotype-dependent effects on HLA-I as distinct as those observed with US10, indicating that US10 may exploit aspects of HLA-I that are yet to be fully elucidated. Therefore, confirming these findings is crucial for our study. The quantitative analysis of the HeLa HLA-I ligandome in US10-expressing cells strongly supports this conclusion. The precise quantification of HLA-I peptide ligands was made possible through collaboration with Dr. Andreas Schlosser from Würzburg, Germany, who possesses profound expertise in this specific method. Thus, in our opinion, this revision has enabled us to advance innovation and, importantly, enhance the significance of our study.

Author response:

Reviewer #3 (Public Review):

Software UX design is not a trivial task and a point-and-click interface may become difficult to use or misleading when such design is not very well crafted. While Phantasus is a laudable effort to bring some of the out-of-the box transcriptomics workflows closer to the broader community of point-and-click users, there are a number of shortcomings that the authors may want to consider improving.

Thank you for such an in-depth review. We really appreciate this feedback and have tried to address all of the concerns in the new version of Phantasus.

Here I list the ones I found running Phantasus locally through the available Bioconductor package:

(1) The feature of loading in one click one of the thousands of available GEO datasets is great. However, one important use of any such interfaces is the possibility for the users to analyze his/her own data. One of the standard formats for storing tables of RNA-seq counts are CSV files. However, if we try to upload from the computer a CSV file with expression data, such as the counts stored in the file GSE120660_PCamerge_hg38.csv.gz from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120660, a first problem is that the system does not recognize that the CSV file is compressed. A second problem is that it does not recognize that values are separated by commas, the very original CSV format, giving a cryptic error "columnVector is undefined". If we transform the CSV format into tab-separated values (TSV) format, then it works, but this constitutes already a first barrier for the target user of Phantasus.

Thank you for highlighting this issue of file formats support. We acknowledge the commonality of CSV and CSV.gz files in gene expression analysis. As a response, we have updated our data loading procedure to support these file formats. Moreover, the most recent version of our web application is able to recognize gzip-archived file in any of supported table formats: GCT, TSV, CSV and XLSX.

(2) Many RNA-seq processing pipelines use Ensembl annotations, which for the purpose of downstream interpretation of the analysis, need to be translated into HUGO gene symbols. When I try to annotate the rows to translate the Ensembl gene identifiers, I get the error

"There is no AnnotationDB on server. Ask administrator to put AnnotationDB sqlite databases in cacheDir/annotationdb folder"

Thank you for revealing this issue. Indeed, locally installed instances of the Phantatus might lose some functionality in absence of some auxiliary files. For example, gene annotation mapping is unavailable without annotation databases. Previously, the user had to perform additional setup steps to unlock a few features, which might be confusing and unclear. In order to overcome this we have revised significantly the installation procedure. Newly added ‘setupPhantasus’ function is able to create all necessary configuration files and provides an interactive dialog with the user that helps to load all necessary data files from our official cache mirror (https://alserglab.wsutl.edu/files/phantasus/minimal-cache/). Docker-based installation follows the same approach, however it is configured to install everything by default. Thus, with help of the new installation procedure locally installed Phantasus now has the whole functionality available at the official mirrors. The comprehensive installation description is now available at https://ctlab.github.io/phantasus-doc/installation.

(3) When trying to normalize the RNA-seq counts, there are no standard options such as within-library (RPKM, FPKM) or between-library (TMM) normalization procedures.

Appreciating your feedback, we've expanded the available normalization options in the updated version of Phantasus. We added support for TMM normalization as suggested by the edgeR package and voom normalization from the limma package. However, certain strategies like RPKM/FPKM or TPM rely on gene-specific effective lengths, which are challenging to infer without protocol and alignment details. As Phantasus operates on gene expression matrices and doesn't execute alignment steps, the implementation of these normalization seems infeasible. On the other hand, if the user has the matrix with FPKM or TPM gene values (for example from a core facility), such a matrix can be loaded into Phantasus and used for the analysis.

If I take log2(1+x) a new tab is created with the normalized data, but it's not easy to realize what happened because the tab has the same name as the previous one and while the colors of the heatmap changed to reflect the new scale of the data, this is quite subtle. This may cause that an unexperienced user to apply the same normalization step again on the normalized data. Ideally, the interface should lead the user through a pipeline, reducing unnecessary degrees of freedom associated with each step.

Thank you for your comment. Indeed our approach to create a new tab for each alteration to the expression values preserving the name might be the source of confusion for a user. On the other hand, generating informative tab names without overwhelming users with too much detail is also challenging. As a compromise we have an option for the user to manually rename the tab. Still, we agree that this remains an area for improvement. We also consider it to be a part of a larger issue: for example, the loaded data can already be log-scaled, so that even one round of log-scale transformation in Phantasus would be incorrect. Accordingly, we are exploring ways to address this issue in the future by adding automated checks for the tools or, as you suggested, implementing stricter pipelines.

(4.4) Phantasus allows one to filter out lowly-expressed genes by averaging expression of genes across samples and discarding/selecting genes using some cutoff value on that average. This strategy is fine, but to make an informed decision on that cutoff it would be useful to see a density plot of those averages that would allow one to identify the modes of low and high expression and decide the cutoff value that separates them.

Thank you for the suggestion. Indeed a density plot might help users to make informed decisions during gene filtration. We have added such a plot into the ‘Plot/Chart’ tool as a ‘histogram’ chart type.

It would be also nice to have an interface to the filterByExpr() function from the edgeR package, which provides more control on how to filter out lowly-expressed genes.

Thank you for proposing the inclusion of an interface for the filterByExpr() function from the edgeR package. In the recent update we have incorporated filterByExpr() as part of the voom normalization tool. For now, for simplicity, we have decided to keep only the default parameter values. However, we will explore the addition of the dedicated filtering tool in the future.

(5) When attempting a differential expression (DE) analysis, a popup window appears saying:

"Your dataset is filtered. Limma will apply to unfiltered dataset. Consider using New Heat Map tool."

One of the main purposes of filtering lowly-expressed genes is mainly to conduct a DE analysis afterwards, so it does not make sense that the tool says that such an analysis will be done on the unfiltered dataset. The reference to the "New Heat Map tool" is vague and unclear where should the user look for that other tool, without any further information or link.

Thank you for highlighting this issue. We agree that the message in the popup window and the default action were confusing. In response to your feedback, we've updated the default behavior of our DE tools to automatically use the filtered data in a new tab. Additionally, we've clarified the warning message to ensure a better understanding of this process.

(6) The DE analysis only allows for a two-sample group comparison, which is an important limitation in the question we may want to address. The construction of more complex designs could be graphically aided by using the ExploreModelMatrix Bioconductor package (Soneson et al, F1000Research, 2020).

Indeed, the ability to create complex designs and various comparisons is important for many applications for gene expression analysis. Accordingly, in the latest Phantasus version, we've introduced an advanced design feature for the DE analysis, enabling the utilization of multiple column annotations for the design matrix. Combined with the existing ability to create new annotations, this update facilitates the setup of diverse design matrices. While at the moment we do not allow setting a complex contrast, we hope that the current interface will cover most of the differential expression use cases.

(7) When trying to perform a pathway analysis with FGSEA, I get the following error:

"Couldn't load FGSEA meta information. Please try again in a moment. Error: cannot open the connection In call: file(file, "rt")

We hope that this issue should be resolved after we have implemented a more streamlined setup process. Among others, the new approach aims to eliminate the unexpected absence of metafiles in local installations. The latest Phantasus package version explicitly prompts the user to load necessary additional files automatically during the initial run, reducing options for an invalid setup.

Finally, there have been already some efforts to approach R and Bioconductor transcriptomics pipelines to point-and-click users, such as iSEE (Rue-Albrecht et al, 2018) and GeneTonic (Marini et al, 2021) but they are not compared or at least cited in the present work.

Indeed, our comparison was focused toward tools that offer non-programmatic functionalities for gene expression data analysis. While tools like iSEE and GeneTonic are adept at visualizing data and hold their own in providing extensive abilities, they do necessitate additional data preparation using R, distinguishing them from the specific scope of tools we assessed.

One nice features of these two tools that I missed in Phantasus is the possibility of generating the R code that produces the analysis performed through the interface. This is important to provide a way to ensure the reproducibility of the analyses performed.

The ability to generate R code within tools like these indeed aids in ensuring analysis reproducibility. Moreover, we have previously attempted implementing this functionality in Phantasus, however it proved to be hard to do in a useful fashion due to potential complex interactions between user and the client-side part of Phantasus. Nevertheless, we acknowledge the significance of such a feature and aim to introduce it in the future.

eLife assessment

This work explores how centrosomes, which function as the primary microtubule organizing center in animal cells, regulate cell division by examining the process in cells in which centrosome formation has been inhibited. The carefully conducted experiments provide convincing support for the important observation that elongated, but successful, mitosis observed in cells lacking centrosomes is due to delays in cell cycle progression.

Reviewer #1 (Public Review):

In their manuscript "Spindle assembly checkpoint-dependent mitotic delay is required for cell division in absence of centrosomes," Farrell and colleagues employ carefully chosen approaches to assay mitotic timeliness in the absence of centrosomes in mammalian culture cells, namely the mechanism behind it and its function. The authors acknowledge prior work well and present their data succinctly, clearly, and with a clear logical flow of experiments. The experiments are thoughtfully designed and presented, with appropriate controls in place.

The authors' model whereby centrosome separation and its early definition of poles mediates timely mitosis without relying on a SAC-dependent delay is compelling, and the authors' data are consistent with it. They show using two different MPS1 inhibitors that acentrosomal cell division fails, supporting their claims that a SAC-dependent delay is required in these instances. Furthermore, they show that reintroducing a time delay is sufficient to restore cell division, but inhibiting a different aspect of SAC function does not restore cell division. Next, the authors rule out polyploidy as a potential confounding factor for requiring a SAC-dependent delay, and instead demonstrate that inhibiting centrosome separation by Eg5 inhibition is sufficient to require this delay for mitotic progression. The authors' findings overall support their proposed model.

Probing what aspects of centrosomes protect against a requirement for SAC-dependent delays would strengthen the work and specifically the conclusion that centrosomes provide "two-ness". For example, the authors could examine division in a population of cells with only one centrosome. Seeing some restoration of mitotic progression in the absence of SAC-dependent delays would suggest that even one centrosome with uninhibited Eg5 is sufficient to negate SAC-dependent delays, and would limit models for what exactly centrosomes contribute. This would help disentangle the roles of actual centrosomes and their biochemical cues, Eg5-driven centrosome separation, and early definition of poles on mitotic progression in the absence of SAC-dependent delays. Making a high fraction of cells with one centrosome could be achieved by using centrinone for a shorter time.

Comments on revised version:

The main point from the initial review does not appear to be addressed in the revised version. As such, the comments on the revised version remain the same.

Reviewer #2 (Public Review):

Centrosomes are an integral part of cell division in most animal cells. There are notable exceptions, however, such as oocytes and plants. In addition, some animal cells can be engineered to lack centrosomes yet they can still manage to complete mitosis. This paper uses a couple of methods (PLK4 inhibition and deletion of SASS6) to remove centrosomes from an immortalized cell line. Indeed, a strength of the paper is that similar results are obtained using both protocols to generate acentrosomal cells. The authors find acentrosomal cells take longer to divide, mostly due to a longer metaphase. The paper is based on the finding that inhibition of MPS1 results in a failure to divide, and the hypothesis that a SAC - dependent delay is required for these acentrosomal cells to divide.

The finding that MPS1 inhibition results in a failure to division is interesting. This is investigated by analyzing cells where AurB, APC or Eg5 (to generate monastral spindles) have been inhibited. My concerns are that the results are not conclusive that the effect of MPS1 is on cell cycle regulation. There is not enough data to make a conclusion as to why inhibition of MPS1 results in cell division failure.

1) An example is how to interpret the effect of Aurora B inhibition, which does not block acentrosomal cell division. If Aurora B is required for SAC activity, it suggests this effect of MPS1 may be a function other than SAC. Given the complexity of the SAC, it would be informative to test other SAC components. Instead, the authors conclude that the mitotic delay caused by MPS is required for acentrosomal cell division. I don't think they have ruled out, or even addressed other functions of MPS1.

2) The authors find that when both the APC and MPS1 are inhibited, the cells eventually divide. These results are intriguing, but hard to interpret. The authors suggest that the failure to divide in MPS1-inhibited cells is because they enter anaphase, and then must back out. This is hard to understand and there is not data supporting some kind of aborted anaphase. Is the division observed with double inhibition some sort of bypass of the block caused by MPS1 inhibition alone? It is not clear why inhibition of APC causes increased cell division when MPS1 is inhibited.

3) The authors characterize MTOC formation in these cells, which is also interesting. MTOCs are established after NEB in acentrosomal cells. Indeed, forming these MTOCs is probably a key mechanism for how these cells complete a division, like mouse oocytes.

Following this, the results with inhibiting Eg5 are interesting. The double inhibition of MPS1 and Eg5 results in division failure, like MPS1 inhibition in acentrosomal cells. Thus, there is a cell division block when the centrioles fail to divide. This result raises the possibility that failure to make a bipolar spindle, or the presence of a monopolar spindle, is the problem. In the absence of a bipolar spindle, a SAC induced delay is required for spindle assembly. This is a possibility but there are multiple interpretations of these results. Primarily, these results do not show the MPS1 effect on acentrosomal cells is SAC related. That a SAC mediated delay is required for acentrosmomal spindle assembly is not the only conclusion.

Comments on revised version:

It appears that very few changes have been made. These are all suggestions in the writing and interpretation.

It's disappointing the most of the readouts are cell division success. There is a lack of data about what happens in the MPS1 knockdowns, such as microtubule attachment to KTs and localization/ activity of checkpoint proteins or downstream factors. More mechanistic insights may be found by testing other checkpoint proteins or assaying more metrics for spindle assembly and cell cycle progression. Or if inducing cell cycle delay suppresses the MPS1 effect. These experiments would implicate cell cycle factors as being required for acentrosomal spindle assembly while ruling out a requirement for MPS1 in spindle assembly.

The paper is well written. But some of the terminology could be improved and some descriptions of the cytology are confusing. Some clear definitions of terms may help. The authors refer to an "extended mitosis" (line 73) and then "exit in the absence of cell division" (line 96) when MPS1 is inhibited. Both are misleading and don't tell the full story. These cells attempt to divide and then fail, resulting in one cell. Use of terms like "spread back out", "rounding up", and "sitting down" seems like jargon and should at least be defined. The term "timely two-ness" (line 23-24) is also not helpful. A brief discussion of data on MPS1 function in mouse and fly acentrosomal meiosis might be appropriate. A comparison would be interesting since loss of MPS1 in acentrosomal oocytes does not have such a drastic block in cell division.

Author response:

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

We thank the reviewers for a careful review of the manuscript and for their comments, which we address below.

Reviewer #1:

(1) …the authors could examine division in a population of cells with only one centrosome. Seeing some restoration of mitotic progression in the absence of SAC-dependent delays would suggest that even one centrosome with uninhibited Eg5 is sufficient to negate SAC-dependent delays, and would limit models for what exactly centrosomes contribute.

We agree that the one-centrosome question (i.e. whether cells with a single centriole, and therefore a single centrosome, have the same SAC dependence) would be interesting to address. It is known that cells with a single centriole generated through centrinone treatment also have elongated mitoses, like cells lacking centrioles (see Chinen, et. al. 2021, compare Fig 2C to Fig 2D), We have tried this experiment in RPE-1 cells with preliminary results confirming that there is a mitotic delay. It is not known whether this delay requires SAC activity, and we hope to address that in future work. In addition, we note that we show in Fig. 4b-c that cells with the normal centrosome number but with a single focus of microtubules due to Eg5 inhibition, were also sensitive to MPS1 inhibition. This suggests that centrosome presence alone cannot overcome the requirement for SAC activity, rather, the centrosomes need to be able to separate in a timely fashion.

Reviewer #2:

(1) An example is how to interpret the effect of Aurora B inhibition, which does not block acentrosomal cell division. If Aurora B is required for SAC activity, it suggests this effect of MPS1 may be a function other than SAC. Given the complexity of the SAC, it would be informative to test other SAC components. Instead, the authors conclude that the mitotic delay caused by MPS is required for acentrosomal cell division. I don't think they have ruled out, or even addressed other functions of MPS1.

We agree that it is possible that functions of the MPS1 kinase other than those involved in the SAC could be important. Although we have not directly tested other SAC components, we did “mimic” SAC activity by delaying anaphase onset using APC/C inhibition while also inhibiting MPS1 (Fig. 2b-b’’). The fact that this restored division suggests that it is the SAC function of MPS1 kinase activity that is relevant to this delay. 

(2) The authors find that when both the APC and MPS1 are inhibited, the cells eventually divide. These results are intriguing, but hard to interpret. The authors suggest that the failure to divide in MPS1-inhibited cells is because they enter anaphase, and then must back out. This is hard to understand and there is not data supporting some kind of aborted anaphase. Is the division observed with double inhibition some sort of bypass of the block caused by MPS1 inhibition alone? It is not clear why inhibition of APC causes increased cell division when MPS1 is inhibited.

As described in the response to 1), we believe that reinstating the delay to anaphase onset by APC/C inhibition provided the time needed to establish a functional bipolar spindle even in the absence of the SAC, and that cells eventually overcome the proTAME block and proceed through mitosis, as observed in control cells in our experiments. We note that we chose concentrations of proTAME specifically for each cell line (RPE-1 and U2OS) that would result only in a temporary block, following on the work of Lara-Gonzalez and Taylor (2012), who reported similar findings for HeLa cells.

(3) The authors characterize MTOC formation in these cells, which is also interesting. MTOCs are established after NEB in acentrosomal cells. Indeed, forming these MTOCs is probably a key mechanism for how these cells complete a division, like mouse oocytes.

We agree that the observed intermediates of MTOCs are interesting and likely crucial to the mechanism of cell division in acentrosomal somatic cells. We are investigating further the differences and similarities between somatic cell MTOC formation in the absence of centrosomes and the naturally-occurring form of that process in oocytes.

Reviewer #2 (Public Review):

Summary:

This study reveals that short-term social isolation increases social behavior at a reunion, and a population of hypothalamic preoptic area neurons become active after social interaction following short-term isolation (POAiso neurons). Effectively utilizing a TRAP activity-dependent labeling method, the authors inhibit or activate the POAiso neurons and find that these neurons are involved in controlling various social behaviors, including ultrasonic vocalization, investigation, and mounting in both male and female mice. This work suggests a complex role for the POA in regulating multiple aspects of social behavior, beyond solely controlling male sexual behaviors.

Strengths:

A few studies have shown that optogenetic activation of the POA in females promotes vocalization and mounting behavior, similar to the effects observed in males. However, those were the results of artificially stimulating POA neurons, and it was unknown whether POA neurons play a role in naturally occurring female social behaviors. This paper clearly demonstrates that there exists a population of POA neurons that are necessary for naturally evoked female social vocalizations and mounting behaviors.

Weaknesses:

The authors conclude that "In the current study, we identify and characterize a population of preoptic hypothalamic neurons that contribute to the effects of short-term social isolation on the social behaviors of mice." This is an interesting hypothesis, but in my opinion, critical control experiments are missing to support this claim.

All the activity-dependent labeling experiments with TRAP mice, including the subsequent neural activity manipulation experiments (Figures 2, 3, 4, 5E-F), were conducted by labeling neurons only in socially isolated animals, not group-housed animals. The authors labeled neurons after 30-minute social interactions, raising the possibility that the labeled neurons simply represent a "social interaction/behavior population" (mediating mounting and USVs in females and males) rather than a set of neurons specific to social isolation.

I strongly recommend including experimental groups that involve labeling neurons after 30-minute social interactions in group-housed female or male mice and inhibit TRAPed neurons after social isolation or activate TRAPed neurons after group housing. If manipulating the group-housed TRAP neurons has similar effects to manipulating the isolated TRAP neurons, it would suggest the current labeling paradigm is not isolating neurons specific to the effect of social isolation per se. Rather, the neurons may mediate more general social interaction or motivation-related activities. Given the known role of POA in male mating behavior, a group-housed TRAP experiment in males with a female visitor is especially important for understanding the selectivity of the labeled cells.

Without proper controls, referring to the labeled neurons as "POAiso" neurons is potentially misleading. The data thus far suggests these neurons may predominantly reflect a "POA social behavior" population rather than a set of cells distinctly responsive to isolated housing.

Overall, this paper is well-written and provides valuable new data on the neural circuit for female social behaviors and the potentially complex role of POA in social behavior control.

eLife assessment

This useful study has identified a subset of neurons in the preoptic hypothalamus that promote social behavior in single-housed female mice. The approach is solid; however, due to a lack of significance in the key findings and competing outcomes between different manipulation methods, the evidence is incomplete. The authors have the potential to demonstrate evidence by either increasing the number of experimental animals represented in the study or by adjusting the language in the conclusions to reflect the findings.

Reviewer #1 (Public Review):

Summary:

Zhao et al. perform a series of experiments aimed at identifying the role of the preoptic area (POA) in controlling the impact of social isolation on same-sex female social behavior. They focus their manuscript on the effects of short-term (3d) isolation and females, both of which have been relatively understudied, making the overall topic of the manuscript exciting and important.

Strengths:

The work highlighted is well designed, the experiments original, and the manuscript is elegant and clearly written. The strengths of the manuscript lie in the attention to multiple facets of social behavior (investigation, mounting, USVs), sex differences, and the use of multiple loss- and gain-of-function approaches.

Weaknesses:

The main weaknesses of the paper are a lack of significance in key findings, and relatedly, concluding effects from insignificant findings. Additional elements could be improved to help strengthen this overall well-rounded and intriguing set of results.

Reviewer #3 (Public Review):

Summary:

How short-term isolation acts on the brain to promote social behavior remains incompletely understood. The authors found that social interactions after a period of acute isolation increased investigation promoted mounting, and increased the production of ultrasonic vocalizations (USVs). This was true for females during same-sex interactions as well as for males interacting with females. Concomitant with these increased behavioral readouts, cFos expression in the preoptic area of the hypothalamus (POA) was found to increase selectively in single-housed females. Chemogenetic silencing of these POA neurons attenuated all three behavioral measures in socially isolated females. Surprisingly, ablation of the same POA neurons decreased mounting duration without impacting social investigation or USV production. While optogenetic activation was sufficient to evoke USV production, it did not affect either mounting or social investigation. In males, chemogenetic silencing of POA neurons decreased mounting but not other behaviors. Together, these data point towards a role of POA neurons in mediating social behaviors after acute isolation but the exact nature of that control appears to depend on the choice of perturbation method, sex, and social context in complex ways that are hard to parse. This study is an essential first step; additional experiments will be needed to explain the apparent discrepancy between the various circuit perturbation results and to gain a more comprehensive understanding of the role of POA in social isolation.

Strengths:

The goal of understanding the neural circuit mechanisms underlying acute social isolation is clearly important and topical. Using a state-of-the-art technique to tag specific neurons that were active during certain behavioral epochs, the authors managed to identify the POA as a critical circuit locus for the effects of social isolation. The experimental design is perfectly reasonable and the quality of the data is good. The control experiments (Figures 2B-D) showing that chemogenetic inactivation of other hypothalamic regions (AH and VMH) do not affect social behavior is indeed quite satisfying and points towards a specific role of POA within the hypothalamus. Using a combination of behavioral assays, activity-dependent neural tagging, and circuit manipulation techniques, the authors present convincing evidence for the role of the preoptic area of the hypothalamus in mediating certain behaviors following social isolation. These data are likely to be a valuable resource for understanding how hypothalamic circuits adjust to the challenges of social isolation.

Weaknesses:

While the authors should be commended for performing and reporting multiple circuit perturbation experiments (e.g., chemogenetics, ablation), the conflicting effects on behavior are hard to interpret without additional experiments. For example, chemogenetic silencing of the POA neurons (using DREADDs) attenuated all three behavioral measures but the ablation of the same POA neurons (using CASPACE) decreased mounting duration without impacting social investigation or USV production. Similarly, optogenetic activation of POA neurons was sufficient to generate USV production as reported in earlier studies but mounting or social investigation remained unaffected. Do these discrepancies arise due to the efficiency differences between DREADD-mediated silencing vs. Casp3 ablation? Or does the chemogenetic result reflect off-manifold effects on downstream circuitry whereas a more permanent ablation strategy allows other brain regions to compensate due to redundancy? It is important to resolve whether these arise due to technical reasons or whether these reflect the underlying (perhaps messy) logic of neural circuitry. Therefore, while it is clear that POA neurons likely contribute to multiple behavioral readouts of social isolation, understanding their exact roles in any greater detail will require further experiments.

Reviewer #2 (Public Review):

The paper has two main merits. Firstly, it documents a new and important characteristic of the re-organization of the brains of the deaf, namely its variability. The search for a well-defined set of functions for the deprived auditory cortex of the deaf has been largely unsuccessful, with several task-based approaches failing to deliver unanimous results. Now, one can understand why this was the case: most likely there isn't a fixed one well-defined set of functions supported by an identical set of areas in every subject, but rather a variety of functions supported by various regions. In addition, the paper extends the authors' previous findings from blind subjects to the deaf population. It demonstrates that the heightened variability of connectivity in the deprived brain is not exclusive to blindness, but rather a general principle that applies to other forms of deprivation. On a more general level, this paper shows how sensory input is a driver of the brain's reproducible organization.

The method and the statistics are sound, the figures are clear, and the paper is well-written. The sample size is impressively large for this kind of study.

The main weakness of the paper is not a weakness, but rather a suggestion on how to provide a stronger basis for the authors' claims and conclusions. I believe this paper could be strengthened by including in the analysis at least one of the already published deaf/hearing resting-state fMRI datasets (e.g. Andin and Holmer, Bonna et al., Ding et al.) to see if the effects hold across different deaf populations. The addition of a second dataset could strengthen the evidence and convincingly resolve the issue of whether delayed sign language acquisition causes an increase in individual differences in functional connectivity to/from Broca's area. Currently, the authors may not have enough statistical power to support their findings.

Secondly, the authors could more explicitly discuss the broad implications of what their results mean for our understanding of how the architecture of the brain is determined by the genetic blueprint vs. how it is determined by learning (page 9). There is currently a wave of strong evidence favoring a more "nativist" view of brain architecture, for example, face- and object- sensitive regions seem to be in place practically from birth (see e.g. Kosakowski et al., Current Biology, 2022). The current results show what is the role played by experience.

eLife assessment

This study presents valuable data on the increase in individual differences in functional connectivity with the auditory cortex in individuals with congenital/early-onset hearing loss compared to individuals with normal hearing. The evidence supporting the study's claims is convincing, although additional analyses and a deeper conceptual framing would have strengthened the study. The work will be of interest to neuroscientists working on brain plasticity and may have implications for the design of interventions and compensatory strategies.

Reviewer #1 (Public Review):

This experiment sought to determine what effect congenital/early-onset hearing loss (and associated delay in language onset) has on the degree of inter-individual variability in functional connectivity to the auditory cortex. Looking at differences in variability rather than group differences in mean connectivity itself represents an interesting addition to the existing literature. The sample of deaf individuals was large, and quite homogeneous in terms of age of hearing loss onset, which are considerable strengths of the work. The experiment appears well conducted and the results are certainly of interest. I do have some concerns with the way that the project has been conceptualized, which I share below.

The authors should provide careful working definitions of what exactly they think is occurring in the brain following sensory deprivation. Characterizing these changes as 'large-scale neural reorganization' and 'compensatory adaptation' gives the impression that the authors believe that there is good evidence in support of significant structural changes in the pathways between brain areas - a viewpoint that is not broadly supported (see Makin and Krakauer, 2023). The authors report changes in connectivity that amount to differences in coordinated patterns of BOLD signal across voxels in the brain; accordingly, their data could just as easily (and more parsimoniously) be explained by the unmasking of connections to the auditory cortex that are present in typically hearing individuals, but which are more obvious via MR in the absence of auditory inputs.

I found the argument that the deaf use a single modality to compensate for hearing loss, and that this might predict a more confined pattern of differential connectivity than had been previously observed in the blind to be poorly grounded. The authors themselves suggest throughout that hearing loss, per se, is likely to be driving the differences observed between deaf and typically-hearing individuals; accordingly, the suggestion that the modality in which intentional behavioral compensation takes place would have such a large-scale effect on observed patterns of connectivity seems out of line.

The analyses highlighting the areas observed to be differentially connected to the auditory cortex and areas observed to be more variable in their connectivity to the auditory cortex seem somewhat circular. If the authors propose hearing loss as a mechanism that drives this variability in connectivity, then it is reasonable to propose hypotheses about the directionality of these changes. One would anticipate this directionality to be common across participants and thus, these areas would emerge as the ones that are differently connected when compared to typically hearing folks.

While the authors describe collecting data on the etiology of hearing loss, hearing thresholds, device use, and rehabilitative strategies, these data do not appear in the manuscript, nor do they appear to have been included in models during data analysis. Since many of these factors might reasonably explain differences in connectivity to the auditory cortex, this seems like an omission.

Reviewer #3 (Public Review):

Summary:

This study focuses on changes in brain organization associated with congenital deafness. The authors investigate differences in functional connectivity (FC) and differences in the variability of FC. By comparing congenitally deaf individuals to individuals with normal hearing, and by further separating congenitally deaf individuals into groups of early and late signers, the authors can distinguish between changes in FC due to auditory deprivation and changes in FC due to late language acquisition. They find larger FC variability in deaf than normal-hearing individuals in temporal, frontal, parietal, and midline brain structures, and that FC variability is largely driven by auditory deprivation. They suggest that the regions that show a greater FC difference between groups also show greater FC variability.

Strengths:

- The manuscript is well written.

- The methods are clearly described and appropriate.

- Including the three different groups enables the critical contrasts distinguishing between different causes of FC variability changes.

- The results are interesting and novel.

Weaknesses:

- Analyses were conducted for task-based data rather than resting-state data. It was unclear whether groups differed in task performance. If congenitally deaf individuals found the task more difficult this could lead to changes in FC.

- No differences in overall activation between groups were reported. Activation differences between groups could lead to differences in FC. For example, lower activation may be associated with more noise in the data, which could translate to reduced FC.

- Figure 2B shows higher FC for congenitally deaf individuals than normal-hearing individuals in the insula, supplementary motor area, and cingulate. These regions are all associated with task effort. If congenitally deaf individuals found the task harder (lower performance), then activation in these regions could be higher, in turn, leading to FC. A study using resting-state data could possibly have provided a clearer picture.

- The correlation between the FC map and the FC variability map is 0.3. While significant using permutation testing, the correlation is low, and it is not clear how great the overlap is.

eLife assessment

This valuable work by Zheng and colleagues uses a large cohort database from Shanghai to identify that post-infection vaccination among previously vaccinated individuals provides significant low to moderate protection against re-infection. The evidence supporting the conclusion is solid with some limitations, e.g., lack of symptom severity as an outcome, no inclusion of time since infection as an independent variable, improper definitions of some key variables, difficult-to-interpret figures, and exclusion of key groups (infected and then vaccinated). This study will be of interest to vaccinologists, public health officials and clinicians.

Reviewer #1 (Public Review):

Summary:

Zheng and colleagues assessed the real-world efficacy of SARS-CoV-2 vaccination against re-infection following the large omicron wave in Shanghai in April 2022. The study was performed among previously vaccinated individuals. The study successfully documents a small but real added protective benefit of re-vaccination, though this diminishes in previously boosted individuals. Unsurprisingly, vaccine preventative efficacy was higher if the vaccine was given in the month before the 2nd large wave in Shanghai. The re-infection rate of 24% suggests that long-term anti-COVID immunity is very difficult to achieve. The conclusions are largely supported by the analyses. These results may be useful for planning the timing of subsequent vaccine rollouts.

Strengths:

The strengths of the study are a very large and unique cohort based on synchronously timed single infection among individuals with well-documented vaccine histories. Statistical analyses seem appropriate. As with any cohort study, there are potential confounders and the possibility of misclassification and the authors outline limitations nicely in the discussion.

Weaknesses:

(1) Partially and fully vaccinated are never defined and it is difficult to understand how this differs from single, and double, booster vaccines. The figures including all of these groups are a bit confusing for this reason.

(2) Figure 3 is a bit challenging to interpret because it is a bit atypical to compare each group to a different baseline (ie 2V-I-V vs 2V-I). I would label the y-axis 2V-I-V vs 2V-I (change all of the labels) to make this easier to understand.

(3) A 15% reduction in infection is quite low. It would be helpful to discuss if any quantitative or qualitative signals suggest at least a reduction in severe outcomes such as death, hospitalization, ER visits, or long COVID. I am not sure that a 15% reduction in cases supports extra vaccination without some other evidence of added benefit.

(4) Why exclude the 74962 unvaccinated from the analysis. it would be interesting to see if getting vaccinated post-infection provides benefits to this group

(5) Pudong should be defined for those who do not live in China.

(6) The discussion about healthcare utilization bias is welcomed and well done. It would be great to speculate on whether this bias might favor the null or alternative hypothesis.

Reviewer #2 (Public Review):

Summary:

This paper evaluates the effect of COVID-19 booster vaccination on reinfection in Shanghai, China among individuals who received primary COVID-19 vaccination followed by initial infection, during an Omicron wave.

Strengths:

A large database is collated from electronic vaccination and infection records. Nearly 200,000 individuals are included in the analysis and 24% became reinfected.

Weaknesses:

The article is difficult to follow in terms of the objectives and individuals included in various analyses. There appear to be important gaps in the analysis. The electronic data are limited in their ability to draw causal conclusions.

More detailed comments:

In multiple places (abstract, introduction), the authors frame the work in terms of understanding the benefit of booster vaccination among individuals with hybrid immunity (vaccination + infection). However, their analysis population does not completely align with this framing. As best as I can tell, only individuals who first received COVID-19 vaccination, and subsequently experienced infection, were included. Why the analysis does not also consider individuals who were infected and then vaccinated is not clear.

In vaccine effectiveness analyses, why was time since initial infection not examined as a modifier of the booster effect? Time since the onset of the Omicron wave is only loosely tied to the immune status of the individual.

The effect of booster vaccination on preventing symptomatic vs. asymptomatic reinfection does not appear to have been evaluated; this is a key gap in the analysis and it would seem the data would support it.

In lines 105-108, the demographic description of the analysis population is incomplete. Is sex or gender identity being described? Are any individuals non-binary? What is the age distribution? (Only the proportions 20-39 and under 6 are stated.)

Figure 1 consort diagram is confusing. In the last row, are the two boxes independent or overlapping sets of individuals? Are all included in secondary analyses?

eLife assessment

This study provides an important tool for predicting binding between immune cells receptors and antigens based on protein sequence data. The analysis convincingly showed the tool's effectiveness in both supervised TCR binding prediction and unsupervised clustering, surpassing existing methods in accuracy and reducing annotation costs. This study will be of interest to immunologists and computational biologists.

Reviewer #2 (Public Review):

In the manuscript, the authors highlighted the importance of T-cell receptor (TCR) analysis and the lack of amino acid embedding methods specific to this domain. The authors proposed a novel bi-directional context-aware amino acid embedding method, catELMo, adapted from ELMo (Embeddings from Language Models), specifically designed for TCR analysis. The model is trained on TCR sequences from seven projects in the ImmunoSEQ database, instead of the generic protein sequences. They assessed the effectiveness of the proposed method in both TCR-epitope binding affinity prediction, a supervised task, and the unsupervised TCR clustering task. The results demonstrate significant performance improvements compared to existing embedding models. The authors also aimed to provide and discuss their observations on embedding model design for TCR analysis: 1) Models specifically trained on TCR sequences have better performance than models trained on general protein sequences for the TCR-related tasks; and 2) The proposed ELMo-based method outperforms TCR embedding models with BERT-based architecture. The authors also provided a comprehensive introduction and investigation of existing amino acid embedding methods. Overall, the paper is well-written and well-organized.

The work has originality and has potential prospects for immune response analysis and immunotherapy exploration. TCR-epitope pair binding plays a significant role in T cell regulation. Accurate prediction and analysis of TCR sequences are crucial for comprehending the biological foundations of binding mechanisms and advancing immunotherapy approaches. The proposed embedding method presents an efficient context-aware mathematical representation for TCR sequences, enabling the capture and analysis of their structural and functional characteristics. This method serves as a valuable tool for various downstream analyses and is essential for a wide range of applications.

Reviewer #3 (Public Review):

In this study, Zhang and colleagues proposed an ELMo-based embedding model (catELMo) for TCRβ CDR3 amino acid sequences. They showed the effectiveness of catELMo in both supervised TCR binding prediction and unsupervised clustering, surpassing existing methods in accuracy and reducing annotation costs. The study provides insights on the effect of model architectures to TCR specificity prediction and clustering tasks.

The authors have addressed our prior critiques of the manuscript.

eLife assessment

This valuable study explores the neural basis for a well-known auditory illusion, often utilized in movie soundtracks, in which a sequence of two complex tones can be perceived as either rising or falling in pitch depending on the context in which they are presented. Solid single-neuron data and analyses are presented to show that correlates of these pitch-direction changes are found in the ferret primary auditory cortex. The manuscript is, however, difficult to assess in places and would benefit from greater consideration of how the results fit more broadly into models of auditory coding.

Reviewer #1 (Public Review):

Summary:

Previous work demonstrated a strong bias in the percept of an ambiguous Shepard tone as either ascending or descending in pitch, depending on the preceding contextual stimulus. The authors recorded human MEG and ferret A1 single-unit activity during presentation of stimuli identical to those used in the behavioral studies. They used multiple neural decoding methods to test if context-dependent neural responses to ambiguous stimulus replicated the behavioral results. Strikingly, a decoder trained to report stimulus pitch produced biases opposite to the perceptual reports. These biases could be explained robustly by a feed-forward adaptation model. Instead, a decoder that took into account direction selectivity of neurons in the population was able to replicate the change in perceptual bias.

Strengths:

This study explores an interesting and important link between neural activity and sensory percepts, and it demonstrates convincingly that traditional neural decoding models cannot explain percepts. Experimental design and data collection appear to have been executed carefully. Subsequent analysis and modeling appear rigorous. The conclusion that traditional decoding models cannot explain the contextual effects on percepts is quite strong.

Weaknesses:

Beyond the very convincing negative results, it is less clear exactly what the conclusion is or what readers should take away from this study. The presentation of the alternative, "direction aware" models is unclear, making it difficult to determine if they are presented as realistic possibilities or simply novel concepts. Does this study make predictions about how information from auditory cortex must be read out by downstream areas? There are several places where the thinking of the authors should be clarified, in particular, around how this idea of specialized readout of direction-selective neurons should be integrated with a broader understanding of auditory cortex.

Reviewer #2 (Public Review):

The authors aim to better understand the neural responses to Shepard tones in auditory cortex. This is an interesting question as Shepard tones can evoke an ambiguous pitch that is manipulated by a proceeding adapting stimulus, therefore it nicely disentangles pitch perception from simple stimulus acoustics.

The authors use a combination of computational modelling, ferret A1 recordings of single neurons, and human EEG measurements.

Their results provide new insights into neural correlates of these stimuli. However, the manuscript submitted is poorly organized, to the point where it is near impossible to review. We have provided Major Concerns below. We will only be able to understand and critique the manuscript fully after these issues have been addressed to improve the readability of the manuscript. Therefore, we have not yet reviewed the Discussion section.

Major concerns

Organization/presentation<br /> The manuscript is disorganized and therefore difficult to follow. The biggest issue is that in many figures, the figure subpanels often do not correspond to the legend, the main body, or both. Subpanels described in the text are missing in several cases. Many figure axes are unlabelled. There is an inconsistent style of in-text citation between figures and the main text. The manuscript contains typos and grammatical errors. My suggestions for edits below therefore should not be taken as an exhaustive list. I ask the authors to consider the following only a "first pass" review, and I will hopefully be able to think more deeply about the science in the second round of revisions after the manuscript is better organized.

Frequency and pitch<br /> The terms "frequency" and "pitch" seem to be used interchangeably at times, which can lead to major misconceptions in a manuscript on Shepard tones. It is possible that the authors confuse these concepts themselves at times (e.g. Fig 5), although this would be surprising given their expertise in this field. Please check through every use of "frequency" and "pitch" in this manuscript and make sure you are using the right term in the right place. In many places, "frequency" should actually be "fundamental frequency" to avoid misunderstanding.

Insufficient detail or lack of clarity in descriptions<br /> There seems to be insufficient information provided to evaluate parts of these analysis, most critically the final pitch-direction decoder (Fig 6), which is a major finding. Please clarify.

Reviewer #3 (Public Review):

Summary:

This is an elegant study investigating possible mechanisms underlying the hysteresis effect in the perception of perceptually ambiguous Shepard tones. The authors make a fairly convincing case that the adaptation of pitch direction sensitive cells in auditory cortex is likely responsible for this phenomenon.

Strengths:

The manuscript is overall well written. My only slight criticism is that, in places, particularly for non-expert readers, it might be helpful to work a little bit more methods detail into the results section, so readers don't have to work quite so hard jumping from results to methods and back.

The methods seem sound and the conclusions warranted and carefully stated. Overall I would rate the quality of this study as very high, and I do not have any major issues to raise.

Weaknesses:

I think this study is about as good as it can be with the current state of the art. Generally speaking, one has to bear in mind that this is an observational, rather than an interventional study, and therefore only able to identify plausible candidate mechanisms rather than making definitive identifications. However, the study nevertheless represents a significant advance over the current state of knowledge, and about as good as it can be with the techniques that are currently widely available.