Author Response

Reviewer #1 (Public Review):

This paper aims to test whether a series of light activated ion channels (GtCCRT4, KnChR) and enzymes that regulate second messengers (BeGC1, bPac, OaPac) can be used to manipulate cells in the zebrafish.

Among the strengths of the paper are the use of several independent methods to test whether the tools are functional - e.g. electrophysiology of mammalian cells for GtCCR4, calcium and cAMP imaging in zebrafish cells in vivo, behaviour tests (tail movement) and monitoring of heart beat. Multiple transgenic lines were established, to select for lines with optimal expression levels. Experiments are carried out in two cell types - reticulospinal neurons in the hindbrain and cardiomyocytes.

The authors have largely achieved their aim of determining whether the rhodopsins can be used in zebrafish. They demonstrate that the cation channel KnChR is particularly sensitive in triggering depolarization of the reticulospinal neurons, as indicated by tail movement. They show that the photoactivatable adenylyl cyclase bPAC and cation channels have an effect on heartbeat. Two other photoactivatable enzymes OaPAC and BeGC1 have no effect on heartbeat, although it is not evident whether this is due to lack of effect on cAMP and cGMP levels.

The abstract sets out to investigate the role of second messengers, emphasizing the need for specificity. However, KnChR is not specific for Na+. As noted by Tashiro et al, the channel can also conduct H+, Ca2+ and Mg2+. The knowledge gap that is being addressed by the manuscript thus needs to be reframed. The concluding statement of the abstract, that the tools tested here can be used to investigate second messengers, is not accurate given the broad conductance of KnChR.

We agree with the reviewer. We changed the title to “Optogenetic manipulation of neuronal and cardiomyocyte functions in zebrafish using microbial rhodopsins and adenylyl cyclases” and revised the abstract and introduction, accordingly. The last sentence of the abstract was modified to “These data suggest that these optogenetic tools can be used to reveal the function and regulation of zebrafish neurons and cardiomyocytes.”

The tools described here have been tested previously in other species, either in cultured mammalian cells (GtCCR4, KnChR, OaPAC) or in vivo (bPAC and BeGC1). The current work thus does not introduce novel tools, but provides evidence that some of these tools can be used in zebrafish. Overall, the lines characterized here will be of use to scientists using zebrafish as the experimental system in a variety of areas.

We appreciated the positive comments from the reviewer. It was worthwhile generating and analyzing so many transgenic zebrafish.

Reviewer #2 (Public Review):

Optogenetic proteins are important tools for circuit neuroscience. The authors characterize five proteins, GtCCR4, KnCHR2, BeGC1, bPAC, and OaPAC with respect to their ability to suppress normal cell excitability and compare the results to those for the more established GtACR1 and CrChR2[T159]. The study makes use of expression in the zebrafish heart and hindbrain, as well as in a cell line. Electrophysiology in the cell line demonstrates that GtCCR photo-activation induces similar currents as CrChR2 activation and shows less signs of desensitization. Using a transgenic vsx2:Gal4 zebrafish line, immunohistochemistry shows that the tools are expressed. When activated, they triggered the expected behavioral responses (swimming) at short latency (<4s). This was true even for the three tools that are guanylyl or adenylyl cyclases (BeGC1, bPAC, OaPAC) and thus affect cell excitability only indirectly. At the tested light intensity, the Klebsormidium nitens channelrhodopsin (KnChR) had the shortest latency (<0.5 s) and highest (100%) probabilities of inducing locomotion. When expressing the tools in the zebrafish heart, brief illumination (100 ms) induces brief (100 ms - 1500 ms) suppression of the heartbeat. Notably, also tools that evoke depolarization induce heartbeat suppression. Heartbeat movies and calcium imaging demonstrate that this is caused by prolonged cardiomyocyte contraction. The optogenetic guanylyl and adenylyl cyclases were not effective in perturbing zebrafish heartbeat (except for bPAC over longer time scales).

Given the large number of optogenetic proteins available to date and the challenge of employing them in well-controlled neuroscience experiments, this study presents an important contribution for neuroscientists performing optogenetic research in animal models. Two light-gated cation channels, GtCCR4 and KnChR, are tested for the first time in vivo. The evidence supporting the claims regarding heartbeat and induced swimming behavior is solid. Since GtCCR4 is more Na+-selective than other channelrhodopsins, it should allow better control of experimental variables and is a valuable addition to the optogenetic tool box. The created transgenic zebrafish lines will be useful for the zebrafish neuroscience community.

The expression in zebrafish was compared using immunohistochemical staining (of a single Gal4 driver line). From this experiment alone, it is difficult to judge the expression level, the in vivo visibility of the fluorescence under the microscope, and the proportion of target cells that do express the optogenetic gene of interest.

The evidence for optogenetically induced alteration of swimming behavior is compelling. However, the associated neuronal responses and their dependence on different light intensity levels remain uncharacterized. Therefore, if anyone plans to use these tools to investigate a neural circuit in the future, the needed light levels and the specificity of the manipulation would still need to be determined.

We stimulated neuronal ND7/23 cells, reticulospinal V2a neurons or cardiomyocytes expressing microbial optogenetic tools at various light intensities and examined their effects on neuronal activities and behaviors (tail movements and cardiac arrest). These data are shown in revised Figure 1, Figure 1-supplement 1, Figure 3, Figure 3-supplements 2, 3, Figure 5, and Figure 5-supplements 1, 2. We described the data on page 12, line-page 13, line 1 and page 14, lines 10-13 in the revised manuscript.

For the optogenetic guanylyl and adenylyl cyclases, which clearly were able to alter behavioral responses, the signaling and circuit mechanisms that lead to neuronal depolarization remain unknown, but possible activation pathways are discussed.

Reviewer #3 (Public Review):

In this study, the authors set out to test several new optogenetic tools in zebrafish. They motivate the study by citing differences in ion selectivity of channelrhodopsins and the potential utility of photoactivatable anenylyl and guanylyl cyclases to control cell functions. Although the study provides some useful new information about the utility of these tools in zebrafish, the characterization is limited and there are serious caveats around interpretation of behavioral responses.

The latency of behavioral responses is often extremely long and there is a lack of control data from opsin negative animals, raising serious doubts as to whether these responses are optogenetically mediated.

In other words, many of these responses may not result from optogenetic activation of V2a cells, but instead arise from indirect effects such as visual stimulation of the animal. Previous zebrafish studies have shown swimming responses in opsin-negative control animals at latencies above ~100 ms and used a 50 ms cut-off for optogenetically evoked swims. One can see evidence suggestive of this issue in the authors' data: latency data for GtCCR4 appears bimodal with a cluster of short latency swims and a second spread at latencies >2s; this could be a mix of fast optogenetic and slow artifactual responses. As the authors have already tested opsin negative control animals, they should examine the latency distribution of these responses. The long latency is even more striking in the case of BeGC1, pPAC and OaPAC where in all cases mean latency exceeds 2 seconds. No short latency responses are apparent and the delay is too long to be solely a result of second messenger action (e.g. activation of cyclic nucleotide gated ion channels). In any case, no explanation is provided.

We understand the reviewer’s concern that the responses were too slow. However, the neurons responded after accumulation of cAMP or cGMP, which bind and activate CNG in the neurons. Similar delayed responses were observed when G protein-coupled bistable rhodpsins were activated in reticulospinal V2a neurons (please see the accompanying manuscript).

We compared the latency of zebrafish larvae expressing each tool with those not expressing the tool. The data are shown in Figure 3, Figure 3-supplement 1, Figure 5, Figure 6, Figure 7, and Figure 7-supplement 1. Statistically, we considered responses within 8 s after the start of light stimulation as positive, and significant differences in responses were observed depending on the presence or absence of tool expression, suggesting that tail movements were induced by tool activation. In the absence of tool expression, spontaneous movements were occasionally observed, but they did not often occur within 8 s. We have described the data on page 15, line 20-page 16, line 4 in the revised manuscript.

Although this study is motivated by the need to precisely control the flux of specific ions and modulate specific second messenger pathways, there is almost no characterisation of these processes in zebrafish cells. As such, the degree to which these tools are useful to "precisely control second messengers in vivo" is unclear and the lack of mechanistic data also leaves open questions about unexpected aspects of behavioral results (e.g. the long latency of presumed cyclic-nucleotide induced behavior, above).

We believe that the description "controlling second messengers" was misleading. Since Reviewer #3 has taken issue with this aspect, we note that this paper does not provide a detailed analysis of second(ary) messengers. We have restructured the entire manuscript to focus on optogenetic regulation of zebrafish neurons and cardiomyocytes rather than on "control messenger regulation".

Finally, there is little comparison with other commonly used optogenetic actuators. CrChR2[T159C] is used as the only control but more recent tools (e.g. CoChR, Chrmine, ChroME) are not considered. Thus, beyond showing that the new tools have behavioral effects in zebrafish, the usefulness of this report for researchers wanting to compare and select between tools is limited.

We examined the activity of CoChR and ChrimsonR in neuronal ND7/23 cells. In addition, we generated transgenic zebrafish expressing CoChR or ChrimsonR, and examined their activity in V2a neurons and cardiomyocytes. We thereby compared the activity of GtACR4, KnChR, and CrChR2[T159C] with that of CoChR and ChrimsonR. The data are shown in Figure 1, Figure 1-supplement 1, Figure 2, Figure 3, Figure 3-supplement 3, and Figure 5-supplements 1, 2. We described the data for CoChR and ChrimsonR in the relevant part of the Result section (pages 8-14) and discussed a comparison on page 18, lines 2-16 in the revised manuscript.

We found that KnChR was a more potent optogenetic tool than GtCCR4, CrChR2, and ChrimsonR in zebrafish reticulospinal V2a neurons. Optogenetic activity of KnChR was comparable to that of CoChR in both reticulospinal V2a neurons and cardiomyocytes (Figures 1, 3, 5). Truncation of KnChR prolonged the channel open lifetime by more than 10-fold (Tashiro et al. , 2021) (Figure 1). KnChR conducts various monovalent and bivalent cations, including H+, Na+, and Ca2+, while KnChR has a higher permeability to Na+ and Ca2+ and a higher permeability ratio of Ca2+ to Na+ than CrChR2 (Tashiro et al. , 2021). These properties may contribute to the high photo-inducible activity of KnChR. Activation of KnChR may induce influx of more cations with a longer channel open time than CrChR2 and ChrimsonR, leading to stronger cell depolarization. Optogenetic activity of KnChR was comparable to that of GtCCR4 in cultured cells, but higher than GtCCR4 in zebrafish reticulospinal V2a neurons and cardiomyocytes. While the exact reason is unclear, it is possible that the expression of functional KnChR protein may be high in zebrafish cells.

Author Response

Reviewer #2 (Public Review):

Dipeptide repeat (DPR) proteins produced from both sense GGGGCC (poly-GA, poly-GP and poly-GR) and antisense CCCCGG (poly-PR, poly-PG, poly-PA) repeat RNAs are found C9ORF72-linked ALS/FTD and contribute to neurodegeneration. The translation of the repeat RNA can initiate without the AUG start codon, a process known as repeat associated non-AUG (RAN) translation. In this manuscript, the authors used luciferase reporter construct to show that the translation of PR and PG from the CCCCGG repeats initiated from in-frame AUG in the C9 sequences before the repeats. After mutating candidate AUG codons, the translation can initiate from other AUG, so there is redundancy. But if mutating all the in-frame AUG codons, the luciferase was dramatically reduced, supporting the translation initiated at the AUG start codon. The translation initiation factor eIF2D has been shown to be important for CUG start codon-dependent poly-GA translation from GGGGCC repeats. Here it is shown that eIF2D is not required for poly-PG and poly-PR translation from CCCCGG repeats using both reporter and patient iPS-neurons. The data using luciferase reporter to study antisense repeat translation is solid, the translation initiates from AUG start codon as there are AUG in frame with PG and PR in the constructs containing the antisense sequences.

We thank the reviewer for the constructive feedback.

On the other hand, as the reporter construct includes the sequences containing the AUG codon, it is not surprising that AUG was used. This is canonical translation.

We completely agree. In the revised Introduction, we now point out that, before our study, it was not clear which mode of translation (RAN vs AUG canonical) is employed for DPR synthesis.

Also, in the revised Discussion (lines 251-257)), we mention the following: “Hence, our findings together with these previous studies suggest that DPR synthesis may involve at least three different modes of translation: (a) near-cognate start codon (e.g., CUG, AGG) dependent-translation for poly-GA and poly-GR from sense GGGGCC transcripts, (b) canonical AUG-dependent translation for poly-PR and poly-PG synthesis from antisense CCCCGG transcripts, and (c) DPR synthesis may also occur through RAN translation mechanisms that solely utilize the repeat. It is conceivable that all three modes of translation may occur simultaneously in disease, and that the use of non-canonical and canonical initiation codons may be the primary contributors of DPR production ”.

The 1,000bp intronic sequence included in our antisense 35xCCCCGG constructs (Figure 1A) is the authentic human intronic sequence. We agree that it does contain multiple putative initiation codons, and this was our motivation for conducting systematic mutagenesis of all these codons. To narrow down the list of putative initiation codons, we used our recently developed machine-learning algorithm for initiation codon prediction (PMID: 35648796). We found a CUG and an AUG in poly-PR frame; a CUG and three AUGs in the poly-PG frame), all of which had a good Kozak sequence (as mentioned in Results). Systematic mutagenesis of these codons (single and multiple codon mutations were generated) revealed that an AUG at -273bp is necessary for poly-PR synthesis (Figure 2). Of note, poly-PR is one of the most toxic DPRs, for which an initiation codon had not been previously identified in the literature.

Additionally, the AUG-initiated translation of antisense repeats has been reported previously. Therefore, the novelty is limited.

We agree that an AUG initiation codon was previously described for poly-PG (Boivin et al., EMBO J, 2020, PMID: 31930538). However, our findings significantly extend this observation because redundancy at the level of AUG initiation codon usage was not reported in that study.

We believe our study significantly contributes to the field of C9ORF72 ALS/FTD in the following way:

(i) We identified for the first time an AUG (at -273nt) necessary for synthesis of poly-PR, one of the most toxic DPRs.

(ii) We propose the concept of initiation codon redundancy for poly-PG, which may apply to other DPRs in C9ORF72 ALS/FTD, as well as in other neurological disorders caused by nucleotide repeat expansion mutations.

(iii) Our findings merged with those of previous studies suggest that DPR synthesis may involve at least three different modes of translation: (a) near-cognate start codon (e.g., CUG, AGG) dependent-translation for poly-GA and poly-GR from sense GGGGCC transcripts, (b) canonical AUG-dependent translation for poly-PR and poly-PG synthesis from antisense CCCCGG transcripts, and (c) DPR synthesis may also occur through RAN translation mechanisms that solely utilize the repeat. It is conceivable that all three modes of translation may occur simultaneously in disease, and the use of non-canonical and canonical initiation codons may be the primary contributor of DPR production”.

(iv) We found that the non-canonical translation initiation factor eIF2D is mainly responsible for poly-GA (sense DPR) production without affecting anti-sense DPRs. Hence, we propose a model where DPR translation occurs in a “piecemeal manner”, i.e., a distinct machinery of translation initiation factors may be needed for the synthesis of each DPR.

In the revised manuscript, we now better highlight these key contributions.

How the antisense DPRs are translated endogenously, AUG-canonical translation or RAN translation, depends on whether the AUG is included in the antisense RNA in patients and where the transcription of the antisense starts, upstream or downstream of the AUG start codons. However, this is not considered in the manuscript.

Thank you for this important point. Zu et al., (PNAS, 2013) observed antisense DPR aggregation in brain samples of C9ORF72 ALS/FTD patients. In the same study, the authors conducted 5’ Rapid Amplification of cDNA Ends (RACE). Although this analysis did not identify the exact transcription start site for the antisense CCCCGG RNA, it did show that the region that includes the AUG codons, which we found to be important for poly-PR or poly-PG, is included in the antisense RNA from human C9ORF72 ALS/FTD samples. In page E4969, Zu et al write: “RACE analysis of FCX samples showed intron 1b antisense transcripts begin at varying sites 251–455 bp upstream of the G2C4 repeat”. The same study also detected antisense RNA foci in brain samples of C9ORF72 ALS/FTD patients.

The exact transcription start site for the antisense (and sense) transcript remains unknown. In the near future, we plan RACE experiments to identify it and share these finding with the community in a separate manuscript.

We have modified the Results (lines 133-136) to: “These results strongly suggest that AUG at -273 bp is the start codon for translation of poly-PR, one of the most toxic DPRs in C9ORF72 ALS/FTD. This AUG is predicted to be included in the endogenous antisense CCCCGG transcript based on 5’ Rapid Amplification of cDNA Ends (RACE) analysis on brain samples of C9ORF72 ALS/FTD patients14.”

Author Response

Reviewer #1 (Public Review):

1) While the current dataset aims to demonstrate a "correlation" between grid cell encoding and task performance, the other variables that could confound this correlation should be carefully examined.

(1) The exact breakdown of the fraction of beaconed/non-beaconed/probe trials is never shown. if the session makeup has a significant effect on the coding scheme or other results, this variable should be accounted for.

(2) The manuscript did not provide information about whether individual mice experienced sessions with different combinations of the three trial types, and whether they show different preferences in position or distance encoding even in comparable sessions. This leads to the question of whether different behaviour and activity encoding were dominated by experimental or natural differences between individual mice. Presenting the data per mouse will be helpful.

(3) Related to the above point, in Figure 5, the mice appeared to behave worse in probe trials than non-beaconed trials. If the mouse did not know if a trial is a probe or a non-beacon trial, they should behave equivalently until the reward location and thus should stop an equal amount. If this difference is because multiple probe trials are placed consecutively, did the mouse learn that it will not get a reward and then stop trying to get rewards? Did this affect switching between position and distance coding?

(4) It is not shown how the behaviours (e.g., running speed away from the reward zone, licking for reward) in beaconed/non-beaconed/probe trials were different and whether the difference in behaviours led to the different encoding schemes.

We appreciate these suggestions and will add all of the requested analyses in a revised manuscript. We note here that while the proportion of trial types differed between sessions, in all sessions trial types were varied in a repeating sequence, so blocks of behaviour where grid firing is anchored (or not anchored) to the track coordinates can not be explained as a consequence of a particular trial type. We will make this clearer in a revised manuscript.

2) Regarding the behaviour and activity encoding on a trial-by-trial basis, did the behavioural change occur first, or did the encoding switch occur first, or did they happen within the same trial? This analysis will potentially determine whether the encoding is causal for the behaviour, or the other way around.

We agree this is an important point and the corresponding analyses will be reported in a revised manuscript.

3) The author determined that the grid cell coding schemes were limited to distance encoding and position encoding. However, there could be other schemes, such as switching between different position encodings (with clear spatial fields but at different locations), as indicated by Low et. al., 2021, and switching between different distant encodings (with different distance periods). If these other schemes indeed existed in the data, they might contribute to the variation of the behaviours.

We did not observe switching between coding schemes of the same type within our dataset and so did not document this. We agree it is important to do so and will provide additional analyses in the revised manuscript

4) The percentage of neurons categorised in each coding scheme was similar between non-grid and grid cells. This implies that non-grid cells might switch coding schemes in sync with grid cells, which would mean the whole MEC network was switching between distance and position coding. This raises the question of whether the grid cell coding scheme was important per se, or just the MEC network coding scheme.

We appreciate the suggestion and very much agree that looking at cells outside of just grid cells is important in determining which cells are functionally relevant in spatial behaviours. We will provide additional analyses in a revised manuscript.

5) In Figure 2 there are several cell examples that are categorised as distance or position coding but have a high fraction of the other coding scheme on a per-trial basis. Given this variation, the full session data in F should be interpreted carefully, since this included all cells and not just "stable" coding cells. It will be cleaner to show the activity comparison only between the stable cells.

We agree that showing stable examples before introducing examples that switch on a per-trial basis will be helpful. We will amend this in a revised manuscript.

6) The manuscript is not well written. Throughout the manuscript, there are many unexplained concepts (especially in the introduction) and methods, mis-referenced figures, and unclear labels.

We appreciate the feedback and will work to address the concerns in a revised manuscript.

Reviewer #2 (Public Review):

This study is very timely as there is a pressing need to identify/delimitate the contribution of grid cells to spatial behaviors. More studies in which grid cell activity can be associated with navigational abilities are needed. The link proposed by Clark and Nolan between "virtual position" coding by grid cells and navigational performance is a significant step toward better understanding how grid cell activity might support behavior. It should be noted that the study by Clark and Nolan is correlative. Therefore, the effect of selective manipulations of grid cell activity on the virtual task will be needed to evaluate whether the activity of grid cells is causally linked to the behavioral performance on this task. In a previous study by the same research group, it was shown that inactivating the synaptic output of stellate cells of the medial entorhinal cortex affected mice's performance of the same virtual task (Tennant et al., 2018). Although this manipulation likely affects non-grid cells, it is still one of the most selective manipulations of grid cells that are currently available.

We appreciate this additional context provided here. In our view, it is critical to narrow down the space of possible behaviours that grid cells might contribute to. As the reviewer notes, our previous work provided evidence that speaks to this question by targeting genetic manipulations (Tennat et al., 2018), but while this approach was specific to stellate cells it does not discriminate grid from non-grid cells and so does not tell us specifically about roles for grid cells. As far as we are aware there is currently no manipulation that will do this. In the experiments here, we take a complementary approach, leveraging the variability inherent in behaviour and the fact that in our location memory task animals will perform many trials in a session. By showing that spatially anchored grid firing does not predict behavioural success on cued trials, but does predict success on trials that are solved by path integration, we substantially narrow the space of behaviours that grid cells could contribute to. Importantly, stellate cells appear necessary for both cued and uncued behaviour in the task (Tennant et al., 2018), suggesting that their roles are more general than the grid cell population, which is likely to be only a subset of stellate cells. We will more carefully address this point in a revised manuscript.

When interpreting the "position" and "distance" firing mode of grid cells, it is important to appreciate that the "position" code likely involves estimating distance. The visual cues on the virtual track appear to provide mainly optic flow to the animal. Thus, the animal has to estimate its position on the virtual track by estimating the distance run from the beginning of the track (or any other point in the virtual world).

We agree this terminology has the potential for causing confusion. A simpler descriptive definition would be track-anchored and track-independent rather than position and distance coding. We will consider this and other alternatives for a revised manuscript.

Reviewer #3 (Public Review):

This study addresses the major question of 'whether and when grid cells contribute to behaviour'. There is no doubt that this is a very important question. My major concern is that I'm not convinced that this study gives a significant contribution to this question, although this study is well-performed and potentially interesting. This is mainly due to the fact that the relation between grid cell properties and behaviour is exclusively correlative and entirely based on single cell activity, although the introduction mentions quite often the grid cell network properties and dynamics. In general, this study gives the impression that grid cells exclusively support the cognitive processes involved in this task. This problem is in part related to the text. However, it would be interesting to look at the population level (even beyond grid cells) to test whether at the network level, the link between behavioural performance and neural activity is more straightforward compared to the single-cell level.

We appreciate the feedback and suggestions. As we note in our response to Reviewer #2, there is currently no method for selective manipulation of grid cells, while testing correlation is a critical step on the path to establishing causation. Our study contributes by reducing the space of possible functions of grid cells to exclude behaviours in which local cues are available, while providing evidence for a clear relationship between anchoring of grid cells and successful outcomes when path integration is used for localisation. We’re unclear here about what the reviewer means by ‘more straightforward’ as the relationships we establish do not appear overly complicated, and as strong relationships between activity of single grid cells and populations of grid cells are already well established (Gardner et al., 2021; Waaga et al., 2021; Yoon et al., 2013).

The authors used a statistical method based on the computation of the frequency spectrum of the spatial periodicity of the neural firing to classify grid cells as 'position-coding' (with fields anchored to the virtual track) and 'distance-coding' (with fields repeating at regular intervals across trials). This is an interesting approach that has nonetheless the default to be based exclusively on autocorrelograms. It would be interesting to compare with a different method based on the similarities between raw maps.

We’re not sure we understand the point here. The manuscript provides analyses comparing rate maps for activity periods in which grid cells are / are not anchored to the task environment (e.g. Figure 2A-C, Figure 3B-E); when grid cells are anchored the rate maps are clearly spatial, when they are not anchored we show that spatial information (in the track reference frame) is very substantially reduced.

Beyond this minor point, cell categorization is performed using all trial types. Each trial type (i.e. beacon or non-beacon) is supposed to force mice to use different strategies and should induce different spatial representations within the entorhinal-hippocampal circuit (and not only in the grid cell system). In that context, since all trials are mixed, it is difficult to extrapolate general information.

Again, we’re not sure we understand the point. We appreciate this likely reflects a lack of clarity on our part in the writing of the manuscript. As noted in our response to Reviewer #1, we will include additional details about the organisation of trials and relationships between trials, behavioural outcomes and neural codes observed. We should note here that mice are not ‘forced’ to adopt any particular strategy. Rather, on uncued trials a path integration strategy is the most efficient way to solve the task. Mice could instead use a less efficient strategy of stopping at short intervals and still obtain rewards, although the behavioural evidence suggests they do not choose to do this after learning the task.

On page 5 the authors state that 'Since only position representations should reliably predict the reward location, ..., we reasoned that the presence of positional coding could be used to assess whether grid firing contributes to the ongoing behaviour'. I do not agree with this statement. First of all, position coding should be more informative only in a cue-guided trial. Second, distance coding could be as informative as position coding since at the network level may provide information relevant to the task (such as distance from the reward).

Again, this point perhaps reflects a lack of clarity on our part in writing the manuscript. When grid cells are anchored to the track reference frame (position encoding in the manuscript), then the location of the rate peaks in grid firing is reliable from trial to trial. This is the case whether or not the trial is cued. When grid cells are independent of the track reference frame (distance encoding in the manuscript, but we now appreciate this is a poor choice of words), then the location of the firing rate peaks vary from trial to trial; thus position can not be read out directly from trial to trial. In principle, when grid cells are not anchored to the track the mouse could read out track position by storing the grid network configuration at the start of each trial and then subtracting this from readouts of distance as mice move along the track. If mice do use this computation we would expect them to do so equally well on cued and uncued trials, whereas our results clearly show a dissociation between trial types in the relationship between grid firing and behavioural outcome. We will highlight this possibility in a revised manuscript.

Third, position-coding is interpreted as more relevant because it predominates in correct trials. However, this does not imply that this coding scheme is indeed used to perform correct trials.

As we note above, our analyses reduce the space of behaviours to which grid cells might contribute, by providing evidence that anchoring of grid firing is associated with successful outcomes specifically when mice adopt a path integration strategy. We agree that alternative models remain plausible, for example perhaps the behaviourally relevant computations are implemented elsewhere in the brain with grid anchoring to the track as an indirect consequence. Nevertheless, the space of alternative models is substantially reduced given our experiments and analyses, while our approach complements tests of grid-behaviour functions that rely on manipulations which leave open alternative explanations based on off target effects. We expect that inclusion in a revised manuscript of the further analyses suggested above should provide further tests of the grid-behaviour relationship.

It could be more informative to push forward the correlative analysis by looking at whether behavioural performance can be predicted by the coding scheme on a trial-by-trial basis.

Figure 5E shows the recommended analysis.

Author Response

eLife assessment

This useful study emphasizes some previously ignored aspects of synaptic communication between Purkinje neurons and their targets in the cerebellar nuclei. Reviewers felt that some aspects of the evidence were solid but that others were incomplete.

We think this is an extensive and complete study. The major issue that the reviewers raised is about the usage of high chloride internals in our recordings. We feel that this single issue does not really match the statement “others were incomplete”, which suggests that this study is incomplete in some way. Please note that in our complete revision we will respond to the issue of chloride by pointing out: (1) the advantages of using high chloride internals to determine the distribution of input sizes, (2) the challenges of estimating the relationship between input sizes for different chloride internals, (3) the previous studies that have established the relationship between input sizes and chloride levels at other synapses, and (4) additional simulations will be provided indicating that subtle changes in the input sizes would have minor quantitative effects on the influences of individual inputs, but would not affect the main conclusions of the paper.

Reviewer #1 (Public Review):

This manuscript explores physiological properties of Purkinje-to-nuclear synapses. The report provides largely incremental advances over what has already been discovered about this synaptic relationship. The main findings, as articulated by the authors, are that Purkinje-to-nuclear synaptic strength is variable, with a few very strong inputs to the cerebellar nuclei. They show that single inputs effectively inhibit nuclear firing and that the diversity of synaptic strength influences nuclear neuron responsivity to inputs by enhancing synaptic variance. In addition, while not necessarily surprising, it's nice to see that stronger inputs would have a stronger influence on a postsynaptic cell, both in terms of rates and temporal coding transfer. Overall, as it stands, the manuscript is not very scholarly, overstates the novelty of findings, and frames a straw-man. That said, buried in here are some potentially interesting observations.

This review provides us with an opportunity to more clearly summarize what is new in our findings. Our study builds upon Person and Raman (2012) and other studies, and makes a number of important advances. (1) We provide a much more extensive characterization of input sizes (n=157) than previous studies, and show that the distribution of input sizes is skewed, with the largest inputs almost 100 times larger than the smallest inputs. This distribution is clearly different from that of Person and Raman (2012), where the estimation of unitary PC input sizes was based on small sample sizes from a broad range of age (n=30, P13-29 animals). The high Cl- concentration internal we used in our recordings provides us with superior stability and sensitivity in detecting such variability in input size. (2) We show for the first time that the distribution of input sizes becomes more skewed in juvenile animals than in young animals, suggesting that PC-CbN synapses are modified by plasticity mechanisms during development. (3) Our dynamic clamp approach is based on the skewed distribution of input sizes we observed, and the Purkinje cell firing patterns we recorded in vivo, whereas Person and Raman (2012) primarily focused their dynamic clamp studies on 40 uniform sized inputs (even though they recognized that there are also somewhat larger inputs), with their firing interspike intervals drawn from Gaussian distributions (which lack refractory periods and do not represent realistic PCs firing patterns). We also complement our dynamic clamp studies with simulations using an integrate-and-fire model that does a good job of replicating our dynamic clamp studies. This allowed us to more thoroughly explore the effects of different size input that would not be practical with dynamic clamp studies. (4) We show that individual PC inputs powerfully regulate the rate and timing of CbN neuron firing, without requiring a high degree of PC synchrony. (5) We further show that timing control by PCs leads to strong inhibition of CbN firing and, surprisingly, a brief elevation prior to the inhibition. This result from the refractory period of PCs, which generate a disinhibition period prior to the inhibition, and is shaped by the firing statistics of PC inputs. If such an elevation prior to inhibition was observed in vivo, it could be misinterpreted as excitation of CbN neurons by other inputs (e.g., mossy fiber collaterals) preceding the PC inputs. (6) We show that the total inhibitory conductance and the coefficient of variation (CV) of this conductance are both important factors in controlling the firing rate of CbN neurons. Having variable input sizes or synchronized inputs all lead to higher CV of the inhibitory conductance and therefore higher firing rates. (7) We show that all different-sized PC inputs transmit a robust rate code that simply depend on their sizes. (8) Our study helps to resolve a long-standing controversy in the field. Some thought that PC synchrony is an effective way of controlling CbN neuron firing, while others doubted the physiological relevance of PC synchrony. Here we show that a single large input is functionally equivalent to many small, perfectly synchronized inputs, which can influence the rate and timing of CbN firing as previously proposed (Person and Raman, 2012a), but without requiring a high degree of PC synchrony. We also suggest that a high degree of synchrony is not a prerequisite for an appreciable influence, because synchronizing a few large inputs can have large effects on CbN neuron firing. We strived to be fair and thorough, and we think that the study is scholarly. Prior to the initial submission, we sought advice from experts in the field, Indira Raman and Nicolas Brunel, and their input was very helpful in this regard. We will revise the manuscript to more clearly articulate what has been done previously, and what aspects of our study are new.

Reviewer #2 (Public Review):

In this manuscript, the authors address how cerebellar Purkinje cells (PC) control the firing of nuclear cells (CbN), the output stage of the cerebellar. They used patch-clamp recordings in acute cerebellar slices, and combined dynamic clamp with simulations of nuclear cell firing rate.

This article addresses one of the most fundamental unresolved question of the cerebellar physiology: how inhibitory PCs control the output stage of the cerebellum?

They first described a developmental evolution of the that PC-CbN synapses. Inhibitory synaptic weights become highly variable after three weeks of age, with a group of very large PC inputs. They used dynamic clamp to examine the influence of these variable inputs on CbN firing rate. They demonstrate that while all input size affect CbN discharge, larger ones can stop them for a few milliseconds. Using a distribution of variable input size, they showed that increasing the variability of PC inputs favor CbN discharge, while increasing the magnitude of a constant inhibitory conductance decrease their firing rate. By varying the frequency of PC inputs, they suggest that CbNs faithfully transmit rate code, but larger inputs are more effective to decrease their firing rate. Finally, addressing how synchrony of variable PC inputs influence CbN discharge, dynamic clamp studies and simulations showed that input synchronization enhance firing, but driven by the total charge of the inhibitory input.

The keystone observations that PC inputs are highly variable is very interesting and convincing and open new questions about PC-CbN plasticity. More importantly the combination of dynamic clamp and simulations is a real strength of the study, allowing the authors to test many combinations of inputs in real cells and extrapolating their hypotheses in silico. Weaknesses result from the assumptions made on the construction of the distribution of inputs and the many different conditions explored. The organization of the article could be difficult to read for a non-specialist of cerebellar physiology.

We thank the reviewer for their kind comments. We will revise the manuscript to clarify the assumptions made to construct the distribution of input sizes. We will do our best to revise the manuscript to make it easier for a non-specialist to read.

Author Response

We thank the editors and the reviewers for their comments. In response, we plan to revise the manuscript in order to provide the details requested and include additional bioinformatic analysis of the data, along the lines suggested by the reviewers. We will also take into account individual variations among the subjects investigated in this study, and discuss the extent to which factors other than age might contribute to the results. And we will expand the discussion to consider how our results may apply to other cells/tissues and how they relate to other findings in the field.

Author Response

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

We will make some minor changes to address the issues in the revised manuscript during preparation of the Version of Record.

1) Acknowledge the previous discovery that COUPTFII expression is confined to the ventral hippocampus in early human fetal forebrain (doi: 10.1093/cercor/bhx185).

We agree. We will incorporate the previous discovery that COUPTFII expression is confined to the ventral hippocampus in early human fetal forebrain (doi: 10.1093/cercor/bhx185) in the discussion section of "COUP-TFII governs the distinct characteristics of the ventral hippocampus".

2) Give some consideration to this observation from my original review "Abnormalities in the trisynaptic circuit. No studies of actual synapses, either physiological or morphological, were carried out. I wonder to what extent these immunohistochemical studies just further reflect the abnormalities in hippocampal morphology presented earlier in the manuscript without specifically telling us about synaptic circuits? Although the immunohistochemical preparations are beautiful, they are inadequate on their own in telling us much about what sort of synaptic circuitry exists in the transgenic animals".

Our data in Figure 4 show clearly that at the neural circuit level, compared with the corresponding control, the trisynaptic circuit is abnormal in all three models; therefore, in the discussion section of "COUP-TF genes are imperative for the formation of the trisynaptic circuit", we will add the following sentence, "We would like to investigate what sort of synaptic circuitry is compromised either physiologically or morphologically in the trisynaptic circuit of individual animal model in detail in the future studies.

In addition, we will correct a reference related to the COUP-TFII gene and congenital heart defects.

The reference of "High, F. A., Bhayani, P., Wilson, J. M., Bult, C. J., Donahoe, P. K., & Longoni, M. (2016). De novo frameshift mutation in COUP-TFII (NR2F2) in human congenital diaphragmatic hernia. Am J Med Genet A, 170(9), 2457-2461. doi:10.1002/ajmg.a.37830" was replaced with "Al Turki, S., Manickaraj, A. K., Mercer, C. L., Gerety, S. S., Hitz, M. P., Lindsay, S., . . . Hurles, M. E. (2014). Rare variants in NR2F2 cause congenital heart defects in humans. Am J Hum Genet, 94(4), 574-585. doi:10.1016/j.ajhg.2014.03.007".

—————

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

Reviewer #1(Recommendations For The Authors):

1) Better presentation of the western blot results

We agree with the reviewer. Based on the suggestion, new information about the western blot results has been added in the revised Figure 1Ap. We added a dash to each western blot image to indicate the target band of COUP-TFI (46 KDa), COUP-TFII (45 KDa), and GAPDH (37 KDa), respectively. There were two bands in the blot of COUP-TFII, with the upper band corresponding to mouse IgG at 50 KDa, and the bottom band corresponding to COUP-TFII protein at 45 KDa. Therefore, only the lower bands of COUP-TFII are used for the quantitative analysis. The expression of COUP-TFII in the ventral hippocampus is clearly higher than that in the dorsal hippocampus.

2) Full presentation of the Immunohistochemistry and qPCR results for at E11.5 and E14.5 in double knockdown mice.

Thanks for the suggestion. Based on the suggestion, we added immunofluorescent data in the double knockout mice at E11.5 in the Figure 5Ba-h. Meanwhile, given that it takes time to prepare animal samples at E14.5 for RT-qPCR assays, we performed immunofluorescent assays at both E13.5 and E14.5 to make sure that the changes of Lhx5 and Lhx2 expression in the hippocampal regions between the control and mutant mice were consistent. As shown in the new Figure 5B, consistent with the downregulated expression of Lhx5 transcripts in the double mutant, the expression of the Lhx5 protein was reduced in the CH in the double mutants at E11.5; moreover, the numbers of Lhx5-positive Cajal-Retzius cells decreased in the double mutant embryos at E11.5, E13.5 and E14.5 (Figure 5Ba-d, a’-d’, a’’-d’’, i-l, i’-l’, q-t, q’-t’). Consistent with RT-qPCR data, the expression of Lhx2 was comparable between the control and double-mutant mice at E11.5 (Figure 5Be-h, e’-h’). Interestingly, the expression of the Lhx2 protein was increased in the hippocampal primordium in the COUP-TF double-mutant mice at E13.5 and E14.5 (Figure 5Bm-p, m’-p’, u-x, u’-x’). Please find the altered descriptions in the Page 15, lines 347-351, 353-358 and Page 21, lines 500-503 in the revised manuscript.

3) Minor corrections. Lines 159-162, prospected not quite the right word. I would suggest "an ectopic CA-like region was observed medially in the temporal hippocampus in the COUP1TFII mutant, where the prospective posterior part of the medial amygdaloid nucleus was situated, (MeP), indicated by the star (Figure 1Ba-f). The presence of the ectopic CA-like region in the ventral but not dorsal hippocampus of the mutant was further confirmed by the presence of the prospective MeP and amygdalohippocampal area (AHi) in sagittal sections, as indicated by the star. See also line 251. Line437/438 I would suggest "... most important breakthroughs in understanding the role of the hippocampus in memory."

Thanks for the suggestion. We made the changes based on the suggestion. Please find the amendments in Page 8, lines 178-181; Page 12, lines 270, 276; Page 14, line 318; Page 19, lines 451; Page 20, lines 461-462 in the revised manuscript.

Reviewer #2 (Recommendations For The Authors):

1) It is also important to point out that the immunofluorescence data in Figure 5B is contrary to what is known for Lhx5 (it's not expressed in the neocortical and hippocampal vz) and Lhx2 (it's not expressed in the choroid plexus). Authors should explain how their conclusions could align more clearly, and consider the possibility that their results are due to a possible artifact of image setting issues or worse, antibody specificity issues.

Very good point. Based on the comments and suggestions, we first tested another Lhx5 antibody, R&D, Cat # AF6290, in the immunofluorescence assays. Indeed, there was something wrong with the previous Lhx5 antibody, Millipore, Cat # AB5762. With the new Lhx5 antibody, consistent with the reported in situ data, the expression of Lhx5 was detected specifically in the CH at E11.5, and in the Cajal-Retzius cells in the marginal zone of the telencephalon. The same Lhx2 antibody, Santa Cruz, Cat # sc-19344, which has been used successfully in one of our previous studies (Tang et al., Development, 2012) (PMID: 22492355), was used in the present study. We believe that the observations at the MP and DP of the samples are really associated with the expression of Lhx2 protein. We performed new immunofluorescence assays with the new Lhx5 antibody and confirmed with the Lhx2 antibody. As shown in new Figure 5B, consistent with the downregulated expression of Lhx5 transcripts in the double mutant, the expression of the Lhx5 protein was reduced in the CH in the double mutants at E11.5; moreover, the numbers of Lhx5-positive Cajal-Retzius cells decreased in the double mutant embryos at E11.5, E13.5 and E14.5 (Figure 5Ba-d, a’-d’, a’’-d’’, i-l, i’-l’, q-t, q’-t’). Consistent with RT-qPCR data, the expression of Lhx2 was comparable between the control and double-mutant mice at E11.5 (Figure 5Be-h, e’-h’). Interestingly, the expression of the Lhx2 protein was increased in the hippocampal primordium in the COUP-TF double-mutant mice at E13.5 and E14.5 (Figure 5Bm-p, m’-p’, u-x, u’-x’). Please find the changed descriptions in Page 15, lines 347-351, 353-358 and Page 21, lines 500-503 in the revised manuscript.

The reference:

Tang, K., Rubenstein, J. L., Tsai, S. Y., & Tsai, M. J. (2012). COUP-TFII controls amygdala patterning by regulating neuropilin expression. Development, 139(9), 1630-1639. doi:10.1242/dev.075564

2) The expression domain of RxCre remains poorly explained, and the early expression of COUPTFI and II (E10.5-E12.5) could be considered major weaknesses of the paper.

Thanks for the suggestion. The generation of RXCre was reported by Swindell et al., Genesis, 2006 (PMID: 16850473). Given that the activation of the LacZ expression serves as an indicator for the deletion of the COUP-TFII gene (Tang et al., Development, 2012) (PMID: 22492355), we performed the immunofluorescent data with antibodies against COUP-TFII and LacZ on the sagittal sections of RXCre/+; COUP-TFIIF/+ heterozygous mutant and RXCre/+; COUP-TFIIF/F homozygous mice at E11.5. As shown in the new Figure 1—figure supplement 1Da-f, COUP-TFII was readily detected at the hippocampal primordium of the heterozygous mutant embryo at E11.5 (Figure 1—figure supplement 1Da, c, g); in contrast, the expression of COUP-TFII significantly decreased in the homozygous mutant (Figure 1—figure supplement 1Dd, f, j). In addition, compared with the heterozygous mutant embryo, the LacZ signals increased distinctly in the hippocampal primordium of the homozygous mutant embryo at E11.5 (Figure 1—figure supplement 1Db-c, e-f, h, k), suggesting that RXCre recombinase can efficiently excise the COUP-TFII gene in the hippocampal primordium as early as E11.5. Please find the corresponding changes in Page 7, lines 149-159 and Page 8, lines 160-164 in the revised manuscript.

Meanwhile, we also added the early expression of COUP-TFI and -TFII at E10.5 and E11.5 in new Figure 1—figure supplement 1Aa-d. At embryonic days 10.5 (E10.5), COUP-TFI was detected in the dorsal pallium (DP) laterally and COUP-TFII was expressed in the MP and CH medially (Figure 1—figure supplement 1Aa, b). At E11.5, the expression of COUP-TFII remained in the hippocampal primordium, including MP and CH (Figure 1—figure supplement 1Ac, d). Please find the corresponding changes in Page 6, lines 129-132 and Page 9, lines 202-203 in the revised manuscript.

The references:

Swindell, E. C., Bailey, T. J., Loosli, F., Liu, C., Amaya-Manzanares, F., Mahon, K. A., . . . Jamrich, M. (2006). Rx-Cre, a tool for inactivation of gene expression in the developing retina. Genesis, 44(8), 361-363. doi:10.1002/dvg.20225

Tang, K., Rubenstein, J. L., Tsai, S. Y., & Tsai, M. J. (2012). COUP-TFII controls amygdala patterning by regulating neuropilin expression. Development, 139(9), 1630-1639. doi:10.1242/dev.075564

Reviewer #3 (Recommendations For The Authors):

1) Regarding the RxCre line, I was also confused about its spatiotemporal expression, as this line is not a commonly used Cre line and no detailed description is provided in the manuscript. Searching this line shows a previous paper by the authors (PMID: 22492355) in which they tested the RxCre recombinase activity. At E12.5, RxCre induced high LacZ expression in the ventral telencephalon but much less in the dorsal telencephalon. But they did not check later stage. Therefore, it's hard to explain the defective dorsal hippocampus in RxCre, CFI CKO. They should check later stage.

The generation of RXCre was reported by Swindell et al., Genesis, 2006 (PMID: 16850473), which reveals high Cre recombinase activity of RXCre in the eye and ventral telencephalon. Given that the activation of the LacZ expression serves as an indicator for the deletion of COUP-TFII gene, Tang et al., Development, 2012 (PMID: 22492355), we performed the immunofluorescent data with antibodies against COUP-TFII and LacZ on the sagittal sections of RXCre/+; COUP-TFIIF/+ heterozygous mutant and RXCre/+; COUP-TFIIF/F homozygous mice at E11.5. As shown in new Figure 1—figure supplement 1D, compared with the heterozygous mutant embryo, the expression of COUP-TFII was significantly decreased in the homozygous mutant; in addition, the LacZ signals evidently increased in the hippocampal primordium of the homozygous mutant embryo at E11.5, suggesting that RXCre recombinase can efficiently excise the target gene in the hippocampal primordium as early as E11.5. The expression of COUP-TFI is barely detectable in the early developing hippocampal primordium including MP at E10.5, E11.5 and E12.5. The expression of COUP-TFI is high in the MP of the control (Figure 1Cj, l); in contrast, the COUP-TFI expression is barely detectable in the MP of the homozygous double mutant at E14.5, indicating that RXCre can efficiently delete the COUP-TFI gene in the hippocampal primordium at E14.5. The loss of the COUP-TFI gene in the MP as early as E14.5 by RXCre initiates the defective dorsal hippocampus in RXCre/+; COUP-TFIF/F knockout mice.

2) Authors should check and review extensively for improvements to the use of English.

We carefully checked and made changes throughout the manuscript accordingly. For example, “imperative” was used 6 times in the previous manuscript, lines 20, 255, 486, 499, 522, 553; “imperative” was used only once in Page 22, line 522 in the revised manuscript.

3) Please correct the manuscript; 1-month-old mice are not adult mice.

Thanks for the suggestion. Based on the suggestion, we have corrected related words and sentences in the manuscript. Please find the amendments in the revised manuscript (Page 7, line 146; Page 9, lines 203-204; Page 10, line 213; Page 13, lines 299-300; Page 17, line 406; Page 20, line 476).

4) Additional ref should be added at line 93 on page 5.

Based on the suggestion, we added some new references (Bertacchi et al., EMBO J, 2020) (PMID: 32572460); (Del Pino et al., Cereb Cortex, 2020) (PMID: 32484994); (J. Feng et al., Sci Adv, 2021) (PMID: 34215582) at line 96 on page 5.

The references:

Bertacchi, M., Romano, A. L., Loubat, A., Tran Mau-Them, F., Willems, M., Faivre, L., . . . Studer, M. (2020). NR2F1 regulates regional progenitor dynamics in the mouse neocortex and cortical gyrification in BBSOAS patients. Embo j, 39(13), e104163. doi:10.15252/embj.2019104163

Del Pino, I., Tocco, C., Magrinelli, E., Marcantoni, A., Ferraguto, C., Tomagra, G., . . . Studer, M. (2020). COUP-TFI/Nr2f1 Orchestrates Intrinsic Neuronal Activity during Development of the Somatosensory Cortex. Cereb Cortex, 30(11), 5667-5685. doi:10.1093/cercor/bhaa137

Feng, J., Hsu, W. H., Patterson, D., Tseng, C. S., Hsing, H. W., Zhuang, Z. H., . . . Chou, S. J. (2021). COUP-TFI specifies the medial entorhinal cortex identity and induces differential cell adhesion to determine the integrity of its boundary with neocortex. Sci Adv, 7(27). doi:10.1126/sciadv.abf6808

5) I am confused why the authors analyzed 1-month-old mice in some instances but 3-month-old mice in others.

The RXCre/+; COUP-TFIF/F; COUP-TFIIF/F double mutant mice barely survived beyond postnatal 3 weeks. To make our findings consistent and comparable, we mainly prepared figures with observations on about 1-month-old mice in the RXCre related single or/and double gene mutant mouse models. In the study of the Emx1Cre related COUP-TFI mouse model, due to behavioral tests such as the Morris water maze test, experiments were performed with the adult experimental animal about postnatal 3 months. In order to be consistent with the stage of the mice for the behavioral tests, we only displayed morphological data with observations on the control and Emx1Cre/+; COUP-TFIF/F mutant mice at about postnatal 3-month.

Author Response

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

We thank the reviewers for their comments. We have now addressed all the comments in a revised version of the manuscript, which we believe has strengthened our paper.

1) Introduction LINE 60: the authors cite Funato et al 2016 as the paper first describing a role for SIk3 in sleep regulation. In fact, the role for this kinase was first identified nearly a decade earlier in C. elegans (Van der Linden et al, Genetics 2008 PMID 18832350).

Thank you for pointing us to this reference. Van der Linden et al. demonstrated that the C. elegans homolog of Sik3 (KIN-29) regulates satiety quiescence, in which worms stop moving following feeding on high quality food. However, as pointed out in Trojanowski and Raizen “Call it Worm Sleep” (2016), not all of the behavioral criteria for sleep has been applied to C. elegans satiety quiescence, and we cannot find any references that unequivocally demonstrate satiety quiescence is a sleep state. As McClanahan et al., (2020) show, quiescent states following mild sensory arousal do not fulfill the sleep criteria of changes in arousal threshold and homeostatic regulation, so not all quiescent states in C. elegans are sleep. Then again Grubbs et al, 2020 does demonstrate that KIN29 regulates both developmentally timed and stress induced sleep states in worms, suggesting that the observations in Van der Linden were ahead of its time and these behavioral states are possibly inter-related. We believe, though, that our line “the roles of… SIK3 kinase in modulating sleep homeostasis in mice (Funato et al. 2016) were identified in genetic screens” remains accurate.

2) Introduction LINE 71: remove the word "known" from "...while some known human sleep/wake regulators, such as the...")

Good idea. Done.

3) I was confused regarding Supplemental data 1 describing the genes they targeted with their forward genetic screen. Am I understanding correctly from the "Summary stats" tab that 702 fish lines with virus insertions were screened behaviorally? In Figure S1, it looks like about 60 are shown in the histograms but in the text (in the Discussion) they say 25 were screened. Were all the genes listed under the Excel tabs (GPCRs, channels, etc) tested? Or was just a subset tested? Where are the sleep data for these lines? Negative results may be relevant to their manuscript since they listed (tested??) a number of ion channel genes under tab "channels" which appear to NOT have a sleep phenotype.

We apologize for the confusion on these points. As highlighted in the legend to Supplementary Figure S1, we had planned a screening strategy with the following pipeline: Candidate mammalian gene → Zebrafish ortholog → ID viral insertion from “Zenemark” library → grow viral insertion lines from frozen sperm→ phenotype F3 heterozygous and homozygous mutant generation. Unfortunately, the company, Znomics, which held the Zenemark library, could not reliably reconstitute the correct live fish from the sperm library, and of the 702 lines we planned to screen, we could only screen 26 (25 was a typo) lines. We treated heterozygous and homozygous animals for each line independently, for a total of 52 screened lines in the histograms.

To make this clearer, we have edited the main text as follows (lines 104-105): “For screening, we identified zebrafish sperm samples from the Zenemark collection (Varshney et al., 2013) that harboured viral insertions in genes of interest and used these samples for in vitro fertilization and the establishment of F2 families, which we were able to obtain for 26 lines.” And lines 111-112: “While most screened heterozygous and homozygous lines had minimal effects on sleep-wake behavioural parameters (Figure S1B-S1C),”

We believe it is important to include the full set of Supplementary Data 1, even though the vast majority of these candidate lines were not tested.

4) Results LINE 117: remove the word "prominent", which is subjective, from the sentence "...showed a prominent decrease in sleep during the..."

Good point. Done.

5) LINES 185-186: did you see any circadian variation in your dmist:GFP protein abundance or localization? Protein trafficking has been described as a mechanism of circadian regulation of excitability.

For practical reasons, we imaged the membrane localization of Dmist:GFP in plasmidinjected embryos at 90% epiboly, which is about 9 hours after fertilization and when the cells remain large and in a relatively flat epithelium. Thus, we could not follow circadian fluctuations in abundance or localization. For circadian studies, we believe the best method will be to raise an antibody that recognizes Dmist.

6) LINE 203: does the GFP-tagged Dmist rescue the loss-of-function phenotype? This is relevant to Figure 2E. it is also relevant to the issue of structure-function. If it rescues, then the C-terminus may not be essential to protein function.

As noted, for practical reasons, we observed Dmist-GFP only transiently at early stages of development, expressed using a strong, ubiquitous promoter. A rescue experiment is a good idea for future experiments, where we carefully control the expression of Dmist in neurons.

7) LINE 220: explain what you mean by "...consistent with nonsense-mediated decay." and/or give a reference.

In zebrafish and other species including humans, mutant transcripts that have premature stop codons often undergo “nonsense mediated decay”, whereby the expression levels are largely reduced (Wittkopp et al., 2009). In the zebrafish community, this is often used as secondary evidence of a loss of function mutation, as relatively few antibodies are available to directly observe zebrafish proteins. We have added a reference that describes this phenomenon (Wittkopp et al., 2009).

8) LINE 225: define "LME model"

Now reads: “Linear mixed effects (LME).”

9) LINES 227-229: could the vir/vir phenotype be explained by specific effects on protein structure? could vir/vir be a gain-of-function allele?

We can’t rule this out formally, and vir/+ animals do show some sleep phenotypes, albeit weaker than those of vir/vir animals (Figure 1G). However, it is not uncommon for heterozygous mutants to show significant phenotypes that are weaker than those of their homozygous mutant siblings, and the strong suppression of dmist expression by the viral insertion (which is located in the dmist intron) is more consistent with a hypomorphic loss-of-function phenotype for the vir allele.

10) LINES 229-230: I don't quite follow the argument for pursuing further studies only of i8/i8. i8/i8 seems to also be a hypomorphic allele based on your qPCR data.

First, the dmist viral line was generated by an insertional mutagenesis method followed by sequencing, and each line has multiple other inserts in a background that does not match the background of the other animals reported in this paper. Second, the dmist vir allele is an insertion in the intron, leading to reduced, but not complete loss of expression. In contrast, the i8 allele was generated on the same background strain as our other existing and newly reported lines. Moreover, our i8 line is likely a loss-of-function allele and not a hypomorph. Yes, dmist expression is reduced in the i8 allele; however, this is likely due to nonsense mediated decay of dmist mRNA. The mutation introduces a frameshift in the dmist coding sequence, and as a result the amino acid sequence of the protein is altered after the N-terminal signal sequence.

11) LINES 241-243: grammar.

Fixed

12) LINE 245: define "JackHMMR iterative search"

We’ve added the phrase: “and seeding a hidden Markov model iterative search (JackHMMR)”

13) LINE 246 is missing the word "we" prior to "...found distant homology between..."

Added

14) LINE 301: show data demonstrating deviation from Mendelian ratios. Also, comment on meaning of such data (embryonic lethality??).

We have added this data in the line (301):

“atp1a3b mutant larvae were not obtained at Mendelian ratios (55 wild type [52.5 expected], 142 [105] atp1a3b+/-, 13 [52.5] atp1a3b-/-; p<0.0001, Chi-squared) suggesting some impact on early stages of development leading to lethality.”

15) Discussion LINES 362-372: This paragraph seems to be of only tangential relevance to the paper. Consider removing.

Our screening strategy was a large-scale reverse genetic screen, but the number of lines was limited by the technical issues described above. We think it is important to mention that the strategy, if employed today, could benefit from newer technologies.

16) Discussion. Another model is that Dmist and NaK pump have a developmental effect. Arguing against this developmental model is the Oubain expt.

This is an important point. We’ve added the line (454:457): “We also cannot exclude a role for Dmist and the Na+/K+ pump in developmental events that impact sleep, although our observation that ouabain treatment, which inhibits the pump acutely after early development is complete, also impacts sleep, argues against a developmental role.”

17) FIGURE 1G: Are these significance cut offs corrected for multiple comparisons?

Yes, all the data is corrected for multiple comparisons.

18) performing neuronal activity measures, either via neural activity imaging or phospho-ERK labeling in different mutants at day or night conditions, to determine whether baseline neuronal activity brain-wide or in specific brain regions are altered.

These are excellent experiments that we plan to perform in the future.

19) Please check all Figure numbers for accuracy.

We have double checked these.

20) The authors emphasize the role of increased cellular sodium, but equally plausibly, the phenotypes could be due to decreased cellular potassium. The potassium channel shaker has been previously identified as a critical sleep regulator in Drosophila.

We completely agree. We would like to highlight that we did devote an entire paragraph to the possibility of changes in extracellular potassium in the discussion: “A third possibility is that Dmist and the Na+,K+-ATPase regulate sleep not by modulation of neuronal activity per se but rather via modulation of extracellular ion concentrations. Recent work has demonstrated that interstitial ions fluctuate across the sleep/wake cycle in mice. For example, extracellular K+ is high during wakefulness, and cerebrospinal fluid containing the ion concentrations found during wakefulness directly applied to the brain can locally shift neuronal activity into wake-like states (Ding et al., 2016). Given that the Na+,K+-ATPase actively exchanges Na+ ions for K+ , the high intracellular Na+ levels we observe in atp1a3a and dmist mutants is likely accompanied by high extracellular K+. Although we can only speculate at this time, a model in which extracellular ions that accumulate during wakefulness and then directly signal onto sleep-regulatory neurons could provide a direct link between Na+,K+ ATPase activity, neuronal firing, and sleep homeostasis. Such a model could also explain why disruption of fxyd1 in non-neuronal cells also leads to a reduction in night-time sleep.”

We also agree that Shaker may be an important component of this sleep regulatory mechanism. Indeed, we previously showed that another potassium channel in zebrafish regulates sleep (Rihel et al., 2010).

We have emphasized sodium homeostasis in our title and paper only because we were able to directly observe intracellular sodium levels, so we are confident that these have been altered in our mutants. We can only presume that potassium levels have also been altered, but we could not directly observe this.

21) The similar phenotype between dmist and Fxyd1 in sleep reduction yet very different expression patterns, with dmist being mostly neuronal while fxyd1 being mostly non-neuronal, raise many possible questions: 1) are the sleep phenotypes due to neuronal Na/K imbalance? Or 2) Are the sleep phenotypes due to extracellular Na/K imbalance? Or 3) both? Some feasible experiments may help achieve a better mechanistic understanding of the observed sleep defects.

Yes, we think these are excellent studies for future work. As noted in the previous point (20), we did discuss the possibility that changes to extracellular potassium might be a parsimonious explanation for the similar phenotypes of fxyd1 and dmist mutants.

Future experiment suggestions (not required)

1) Perform a double mutant analysis of fxyd1 and atp1a3a, to determine whether an epistatic relationship similar to that of dmist and atp1a3a is observed in the case of fxyd1 and atp1a3a.

This is a great experiment that we will do in the future. Unfortunately, the fxyd1 mutant had been sperm frozen during the COVID-19 pandemic, so we cannot do this experiment at this time.

2) Given the differences in the sleep phenotypes between vir/vir and i8/i8 mutants, would be informative to see the phenotype of the vir/i8 trans-heterozygote.

This is also a good experiment to perform in the future. Since obtaining the cleaner i8 allele, the dmistvir/vir lines were sperm frozen.

Author Response:

We would like to thank the eLife reviewers for the considerable time and effort they have invested to review these manuscripts. We have also benefited from a previous round of review of the manuscript describing the proposed burial features, which underwent two rounds of revisions in a high-impact journal over a period of approximately 8 months during 2022 and early 2023. Both sets of reviews have reflected mixed responses to the evidence we have presented, with one reviewer recommending acceptance with minor editorial revisions, two recommending acceptance with minor revisions and the fourth recommending rejection based upon similar arguments to those reflected by some of the reviewers in this current round of reviews in eLife. Ultimately the managing editor of this first journal took the decision that the review process could not be completed in a timely manner and rejected the manuscript although the submission here reflected our consideration of these reviewers suggestions.

We have chosen in this initial response to the eLife reviews to include some references to the previous anonymous reviews in order to illustrate differences of opinion and differences in revision suggestions within the review process. Our goal is to offer maximal insight into our decision-making process and to acknowledge the considerable time and effort put into the assessment of these manuscripts by reviewers (for eLife and in the case of the earlier review process). We hope that this approach will assist the readers, and reviewers, of our manuscripts in understanding why we are proceeding with certain decisions during the revision process.

This is a new process for us and the reviewers, and one way in which it significantly differs from more traditional review is that both the reviews and our reply will be public well in advance of our revisions to the manuscript. Indeed, considering the scope of the reviews, some of those revisions may take considerable time, although many can be accomplished fairly easily. Thus, we are not in a position to say that we have solved every issue raised by the reviewers. Instead, we will examine what appear to be the key critical issues raised regarding the data and the analyses and how we propose to address these as we revise the papers. We will also address several philosophical and ethical issues raised by the reviews and our proposal for dealing with these. More specific editorial and citational recommendations will be dealt with on a case-by-case basis, and we do not address these point-by-point in this reply. Please note, this response to the reviewers is not the revision of the manuscript and is only the initial opinion of the corresponding authors with some guidance from the larger group of authors of all three papers. Our final submitted revision will reflect the input of all authors included on those submissions.

We took the decision to submit three separate papers consciously. The two different categories of evidence, burials and engravings, involve different kinds of analysis and different (although overlapping) teams of researchers, and we recognized that each deserved their own presentation and assessment. Meanwhile, together they inform the context of H. naledi in a way that requires some synthetic discussion, in which both kinds of evidence are relevant, leading to a third paper. But the mutual relevance of these different kinds of evidence and their review by a common set of reviewers naturally raises cross-cutting issues, and the reviewers have cross-referenced the three articles. This has sometimes led to suggestions about one manuscript based on the contents of another. Considering the situation, we accepted the recommendation that it would be clearer to consider all three articles in a single reply. Thus, while each of the three papers will proceed separately during the revision process, it will be necessary to highlight across all three papers occasionally in our responses.

Scientific Issues:

In reading the reviews, we feel there are 9 critical points/assertions raised by one or more of the reviewers that present a problem for, or challenge to, our hypothesis that the observed evidence (bone accumulations and engravings) described in the Dinaledi subsystem are of intentional naledigenic origin. These are:

1. The evidence presented does not demonstrate a clear interruption of the floor sediments, thus failing to demonstrate excavated holes.

2. The sediments infilling the holes where the skeletal remains are found have not been demonstrated to originate from the disruption of the floor sediments and thus could be part of a natural geological process (e.g. water movement, slumping) or carnivore accumulations.

3. Previous geological interpretations by our research group have given alternative geological explanations for formation of the bony accumulations that contradict the present evidence presented here and result in alternative origins hypotheses.

4. Burial cannot be effectively assessed without complete excavation of the features and site.

5. The skeletal remains as presented do not conform clearly to typical body arrangement/positions associated with human (Homo sapiens) burials.

6. There is no evidence of grave goods or lithic scatters that are typically associated with human burials.

7. Humans may have been involved with the creation of either the Homo naledi bone accumulations, the engravings, or both.

8. Without a date of the engravings, the null hypothesis should be the engravings were created by Homo sapiens.

9. The null hypothesis for explanation of the skeletal remains in this situation should be “natural accumulation”.

Our analysis of the Dinaledi Feature 1 leads us to accept that the laminated orange-red mudstone (LORM) sedimentary layer is interrupted, indicating a non-natural intervention, and that the hole created by the interruption was then filled by both a fleshed body (and perhaps parts of other bodies) which were then covered by sediment that originated from the hole that was dug. We recognize that the four eLife reviewers are not convinced that our presentation is sufficient to establish this. Interestingly, this was not the universal opinion of earlier reviewers of the initial manuscript several of whom felt we had adequately supported this hypothesis. The lack of clarity in this current version of the burial manuscript is our responsibility. In the upcoming revision of this paper to be submitted, we will take the reviewers’ critiques to heart and add additional figures that illustrate better the disruption of the LORM and clarify the sedimentological data showing the material covering the skeletal remains in the hole are the disrupted sediments excavated from the same hole. We are proposing to isolate this most critical evidence for burial into a separate section in the revised submission based on the reviewers’ comments. The fact that the LORM layer is disrupted, a fleshed body was placed in the hole created by this disruption, and the body (and perhaps parts of other bodies) was/were then covered by the same sediments from the hole is the central feature of our hypothesis that the bone accumulations observed reflect a burial and not a natural process.

The possibility of fluvial transport or involvement in the subsystem is a topic that we have addressed extensively in past work, and it is clear from these reviews that we must enhance our current manuscript to discuss this issue at greater length. Our previous work (Dirks et al. 2015; Dirks et al. 2017) emphasized that fluvial transport of whole bodies into the subsystem was precluded by several lines of sedimentological evidence. We excavated a rich accumulation of skeletal remains, including articulated limbs and other elements in subvertical orientations inconsistent with slow sedimentary infill, which were difficult to explain without positing either a large and dense pile of bodies and/or sediment movement. We encountered fractured chunks of laminated orange-red mudstone (LORM) in random orientations within our excavation area, within and among skeletal remains, which directly refuted that the remains were inundated with water at the time of burial, and this limited the possibility of fluvial transport. Water flow sufficient to displace bodies or complete skeletal evidence would also transport large and course sediment, which is absent from the subsystem, and would sort the commingled skeletal material that we found by size, which we do not observe. But our excavation only covered less than a square meter at very limited depth, and this was the limit to our knowledge of subsurface sediment. We thus were left with uncertainty that led us to suggest the possibility of sediment slumping or movement into subsurface drains, although these were not observed near our excavation. Our current work expands our knowledge of the subsurface and presents an alternative explanation for the disposition of skeletal remains from our earlier excavation. But we acknowledge that this new explanation is vulnerable to our own previous published proposals, and we must do a better job of explaining how the new information addresses our previous suggestions. By not clearly creating a section where we explained how these previous hypotheses were now nullified by new evidence, we clearly confused the reviewers with our own previous work. We will revise the manuscript by enhancing the review of the significant geological evidence demonstrating that there is no significant fluvial action in the system and making it clear how the burial hypothesis provides a clearer explanation for the situation of skeletal remains from our previous excavation work.

One of the central issues raised by reviewers has been a perceived need to excavate these features completely, totally exhuming all skeletal remains from them. Reviewers have written that it is necessary to identify every skeletal element that is present and account for any missing elements. On this point, we have both ethical and scientific differences from these reviewers. We express our ethical concerns first. Many of the best-preserved possible burials ever discovered by archaeologists were subjected to total excavation and exhumation. Cases like La Chapelle-aux-Saints, La Ferrassie, and Skhūl were fully excavated at a time when data recording and excavation methods did not include the range of spatial and geomorphological approaches that later became routine. The judgment of early investigators that these situations were intentional burials was challenged by later workers, and the kind of information that might enable better tests had been irrevocably lost (Gargett 1999; Dibble et al. 2015; Rendu et al. 2014).

Later, improved excavation standards have not sufficed to remove uncertainty or debate about possible burials. For example, it was long presumed that well-preserved remains of young children were by themselves diagnostic of intentional burial, such as those from Dederiyeh, Border Cave, or Roc de Marsal. Such cases were also fully excavated, with adequate documentation of the positioning of skeletal remains and their surrounding stratigraphic situation, but such cases were later challenged on several bases and the complete exhumation of material has confused or precluded testing of new hypotheses (e.g. Gargett 1999). The case of Roc de Marsal is one in which data from the initial excavation combined with data from the initial excavation combined with re-excavation and geoarchaeological analysis led to a naturalistic interpretation of the skeletal material (Sandgathe et al. 2011; Goldberg et al. 2017). But even in this case, the researchers erred in their interpretation of the skeleton’s situation due to a lack of identification of parts of the infant’s skeleton (Gómez-Olivencia and García-Martinez 2019). That is to say, it is not only the burial hypothesis but other hypotheses that suffer from complete excavation. Researchers concerned with preserving all possible information have sometimes taken extraordinary measures to remove and study possible burials at high-resolution in the laboratory. Such was the case of the Shanidar IV burial removed from the site and transported in plaster jacket by Solecki, which led to the disruption and loss of internal stratigraphic information (Pomeroy et al. 2020). Arguably, the current state of the art is full excavation with partial preparation, such as that undertaken at Panga ya Saidi (Martinón-Torres et al. 2021). But again, any future attempt to reinterpret or test the hypothesis of burial must rely on the adequacy of documentation as the original context has been removed.

In our decision to leave material in place as much as possible, we are expanding upon standard practice to leave witness sections and unexcavated areas for future research. The situation is novel, representing possible burials by a nonhuman species, and that makes it doubly important in our opinion to be conservative in not fully exhuming the skeletal material from its context. We anticipate that many other researchers, including future investigators, will suggest additional methods to further test the hypothesis of burial, something that would be impossible if we had excavated the features in their entirety prior to publishing a description of our work. We believe strongly that our ethical responsibility is to publish the work and the most likely interpretation while leaving as much evidence in place as possible to enable further testing and replication. We welcome the suggestions of additional methods/analyses to test the H. naledi burial hypothesis.

This being said, we also observe that total exhumation would not resolve the concerns raised by the reviewers. The recommendation of total exhumation is in pursuit of a full account of all skeletal material present and its preservation and spatial situation, in order to demonstrate that they conform to body positions comparable to human burials. As has been highlighted in forensic casework, the excavation of an inhumation feature does not necessarily provide an accurate spatial or anatomical manifest of the stratigraphical relationships between the body, encapsulating matrix, and any cut present due to preservational, taphonomic and operational factors (Dirkmaat and Cabo, 2016; Hunter, 2014). In particular, in cases where skeletal elements are highly fragmented, friable, or degraded (such as through bioerosion) then complete excavation—even under controlled laboratory conditions—may destroy bone and severely limit skeletal identification (Henderson, 1997; Hochrein, 2002; Owsley and Compton, 1997), particularly in elements where the ratio of trabecular to cortical bone is high (Darwent and Lyman, 2002; Lyman, 1994). As such, non-invasive methods of 3D and 4D modelling (preservation in situ) are often considered preferable to complete necropsy or excavation (preservation by record) where appropriate (Bolliger and Thali, 2009; Dell’Unto and Landeschi, 2022; Randolph-Quinney et al., 2018; Silver, 2016). 

The test of burial is not primarily positional, but taphonomic and geological. The position and number of bones can elaborate on process-driven questions of decay and destruction in the burial environment, or post-mortem modification, but are not singularly indicative of whether the remains were intentionally buried – the post-mortem narrative of all the processes affecting the cadaveric island is required (Knüsel and Robb, 2016). In previous cases, researchers have disputed or accepted the hypothesis of intentional hominin burial based upon assumptions about how modern humans or Neandertals would have positioned bodies, with the idea that some positions reflect ritual intent while others do not. But applying such assumptions is unjustifiable, particularly for a species like H. naledi, whose culture may have differed fundamentally from our own. Our work acknowledges that the present evidence does not enable a full reconstruction of the burial positions, but it does show that fleshed remains were encased in sediment prior to decomposition of soft tissue, and that subsequent spatial changes can be most parsimoniously explained by natural decomposition within sedimentary matrix contained within a burial feature (after Green, 2022; Mickleburgh and Wescott, 2018; Mickleburgh et al., 2022). If the argument is that extraordinary claims require extraordinary evidence, we feel that the evidence documents excavation and interment (and will do so more clearly in the revision) and the fact of the remains do not match a “typical” human burial in body positioning is not in itself evidence that these are not H. naledi burials.

We feel that the reviewers (in keeping with many palaeoanthropologists) have a clear idea of what they “think” a burial should look like in an idealised sense, but this platonic ideal of burial form is not matched by the extensive literature in archaeothanatology, funerary archaeology and forensic science which indicates enormous variability in the activity, morphology and post-mortem system experienced by the human body in cases of interment and body disposal (e.g. Aspöck, 2008; Boulestin and Duday, 2005 and 2006; Connelly et al., 2005; Channing and Randolph-Quinney, 2006; Cherryson, 2008; Donnelly et al., 1995; Finley, 2000; Hunter, 2014; Parker Pearson, 1999; Randolph-Quinney, 2013). Decades of experience in the identification, recovery and interpretation of clandestine, deviant, and non-formal burials indicates the platonic ideal is rare, and in many contexts, the exception (Cherryson, 2008; Parker Pearson, 1999). This variability is particularly relevant to morphological traits in burial context, such as the informal nature of the grave cut in plan and section, shallow burial depth, and initial disposition of body (placement) during the early post-mortem period. These might run counter to the expectations of reviewers or others referencing the fossil hominin record, but are well accepted within the communities of researchers investigating Holocene archaeological sites and forensic contexts.

It is encouraging to see reviewers beginning to incorporate the extensive (often experimentally derived) literature from archaeothanatology and forensic taphonomy in their deliberations, and we will be taking these comments on board going forward. In particular, we acknowledge reviewers’ comments and the need to construct a more detailed post-mortem narrative, accounting for joint disarticulation (labile versus persistent joints etc), displacement, and final disposition of elements within the burial space. As such we will incorporate the hierarchy of decomposition (rank order disarticulation), associations between regions of anatomical association, areas of disassociation, and the voids produced during decomposition (after Mickleburgh and Wescott, 2018; Mickleburgh et al., 2022) into our narrative. In doing so we acknowledge the tensions between the inductive archaeolothanatological narrative-driven approach (e.g. Duday, 2005 & 2009) versus robust decomposition data derived from human forensic taphonomic experimentation recently articulated by Schotsmans and colleagues (2022) - noting that we will highlight comparative data based on forensic experimental casework and actualistic modelling over inductive intuitive approaches which come with significant evidential shortcomings (Bristow et al. 2011).

Finally, from a taphonomic perspective it is worth pointing out to reviewers that we have already addressed the issue of lack of taphonomic evidence for carnivore involvement in the formation of the Dinaledi assemblage (Dirks, et al., 2016). Absence of any carnivore-induced bone surface modifications, patterns of skeletal part representation, and a total absence of any carnivore remains found within the Dinaledi chamber (following Kuhn and colleagues, 2010) lead us to reject carnivores as possible vectors of body accumulation within the Dinaledi Chamber and Hill Antechamber.

Reviewers suggest that without a date derived from geochronological methods, the engravings cannot be associated with H. naledi, and that it is possible (or probable) that the engravings were done in the recent past by H. sapiens. This suggestion neglects the context of the site. We have previously documented the structure and extremely limited accessibility of the Dinaledi subsystem. This subsystem was not recorded on maps of the documented Rising Star Cave system prior to our work and its discovery by our teams. Furthermore, there is no evidence of prehistoric human activity in the areas of the cave related to possible subterranean entrances There is no evidence that humans in the past typically ventured into such extreme spaces like those of Rising Star. It is clear from the presence of the remains of many individuals that H. naledi ventured into these spaces again and again. It is likely that H. naledi moved through these spaces more easily than humans do based on their physique. We show that the engravings overlay each other suggesting multiple engraving events.  These engravings took time and effort and the only evidence for use of the Dinaledi subsystem by any hominin is by H. naledi. The context leads to the null hypothesis that H. naledi made the marks. In our revision, we will elaborate on this argument to clarify the evidence for our stance on this hypothesis. Several reviewers took issue with the title of the engraving paper as we did not insert a qualifier in front of the suggested date range for the engravings. We deliberately left out qualifying language so that the title took the form of a testable hypothesis rather than a weak assertation. Should future work find the engravings were not produced within this time range, then we will restate this hypothesis.

Finally, with regards to the engravings we have chosen to report them because they exist. Not reporting the presence of engraved marks on the walls of a cave above hypothesized burials would be tantamount to leaving relevant evidence out of the description of an archeological context. We recognize and state in our manuscript that these markings require substantial further study, including attempts at geochronological dating. But the current evidence is clearly relevant to the archaeological context of the subsystem. We take a similar stance with reporting the presence of the tool shaped artefact near the hand of the H. naledi skeleton in the Hill Antechamber. It is evident that this object requires further study, as we stated in our manuscript, but again omitting it from our study would be leaving out relevant evidence.

Some have suggested that the null hypothesis should be that all of these observed circumstances are of natural origin. Our team took this approach in our early investigation of the Dinaledi subsystem (Dirks et al. 2015). We adopted the null hypothesis that the geological processes involved in the accumulation of H. naledi skeletal remains were “natural” (e.g., non-naledigenic involvement), and we were able to reject many alternative explanations for the assemblage, including carnivore accumulation, “death trap” accumulation, and fluvial transport of bodies or bones (Dirks et al. 2015). This led us to the hypothesis that H. naledi were involved in bringing the bodies into the spaces where they were found. But we did not hypothesize their involvement in the formation of the deposit itself beyond bringing the bodies to the location.

This approach seems conservative. It followed the traditional view that small-brained hominins do not engage in cultural practices. But we recognize in hindsight that this null hypothesis approach did harm to our analyses. It impeded us from recognizing within our initial excavations of the puzzle box area and other excavations between 2014 – 2017 that we might be encountering remains that were intrusive in the sedimentary floor of the chamber. If we had approached the accumulation of a large number of hominins from the perspective of the null hypothesis being that the situation was likely cultural, we perhaps would have collected evidence in a slightly different manner. We certainly note that if the Dinaledi system had been full of the remains of modern humans, there would have been little doubt that the null hypothesis would have been that this was a cultural space and not a “natural space”.  We therefore respectfully disagree with the reviewers who continue to support the idea that we should approach hominin excavations with the null hypothesis that they will be natural (specifically non-cultural) in origins. If excavations continue with this mindset we believe that potential cultural evidence is almost certain to be lost.

There has been a gradient across paleoanthropological excavations, archaeological work, and forensic investigation, with increasing precision of context. The reality is that the recording precision and frame of approach is typically different in most paleontological excavations than in those related to contemporary human remains. If anything comes from the present discussion of whether the Dinaledi system is a burial site for H. naledi or not, we hope that by taking seriously the possibility of deep cultural dynamics of hominins, we will encourage other teams to meet the highest standards of excavation in order to preserve potential cultural evidence. Given H. naledi’s cranial capacity we suggest that even very early hominin skeletal assemblages should be re-examined, if there is sufficient evidence or records available.  These would include examples such as the A.L. 333 Au. afarensis site (the so called First Family site in Hadar Ethiopia), the Dikika infant skeleton, WT 15000 (Turkana Boy) and even A.L. 288 (Lucy) as such unusual taphonomic situations where skeletons are preserved cannot be simply explained away as “natural” in origin, based solely on the cranial capacity and assumed lack of cognitive and cultural complexity of the hominins as emphasized by us in Fuentes et al. (2023). We are not the first to observe that some very early hominin situations may represent early mortuary activity (Pettitt 2013), but we would advocate a step further. We suggest it may be damaging to take “natural accumulation” as the standard null hypothesis for hominin paleoanthropology, and that it is more conservative in practice to engage remains with the null hypothesis of possible cultural formation.

We are deeply grateful for the time and effort all of the 8 reviewers (across three reviews) have taken with this work.  We also acknowledge the anonymous reviewers from previous submissions who’s opinions and comments will have made the final iterations of these manuscripts better for their efforts. As this process is rather public and includes commentary outside of the eLife forum, we ask that the efforts of all 37 authors and 8 reviewers involved be respected and that the discourse remain professional in all venues as we study this fascinating and quite complex occurrence. We appreciate also the efforts of members of the public who have engaged with this relatively new process where preprints are posted prior to the reviews allowing comments and interactions from colleagues and the public who are normally not part of the internal peer review process.  We believe these interactions will make for better final papers. We feel we have met the standards of demonstrating burials in H. naledi and that the engraving are most likely associated with H. naledi. However, given the reviews we see many areas where our clarity and context, and analyses, were less strong than they can be. With the clarifications and additions taken on board through these review processes the final papers will be stronger and clearer. We, recognize that this is an ongoing process of scientific investigation and further work will allow continued, and possibly better, evaluation of these hypothesis and others.

Lee R Berger, Agustín Fuentes, John Hawks, Tebogo Makhubela

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• Kuhn, B.F., Berger, L.R. & Skinner, J.D. (2010). Examining criteria for identifying and differentiating fossil faunal assemblages accumulated by hyenas and hominins using extant hyenid accumulations. International Journal of Osteoarchaeology 20, 15-35.

• Lyman, R. (1994). Vertebrate Taphonomy. Cambridge, Cambridge University Press.

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• Mickleburgh, H.L & Wescott, D.J. (2018). Controlled experimental observations on joint disarticulation and bone displacement of a human body in an open pit: implications for funerary archaeology. Journal of Archaeological Science: Reports 20: 158-167.

• Mickleburgh, H.L., Wescott, D.J., Gluschitz, S. & Klinkenberg, V.M. (2022). Exploring the use of actualistic forensic taphonomy in the study of (forensic) archaeological human burials: An actualistic experimental research programme at the Forensic Anthropology Center at Texas State University (FACTS), San Marcos, Texas. In C.J. Knüsel and E.M.J. Schotsmans (eds.) The Routledge Handbook of Archaeothanatology. London: Routledge. pp 542-562.

• Owsley, D. & B. Compton (1997). Preservation in late 19th Century iron coffin burials. In W. Haglund and M. Sorg (eds). Forensic Taphonomy: The Postmortem Fate of Human Remains. Boca Raton, FL, CRC Press: 511-526.

• Parker Pearson, M. (1999). The Archaeology of Death and Burial. College Station: Texas A&M University Press.

• Pettitt, P. (2013). The Palaeolithic Origins of Human Burial. Routledge.

• Pomeroy, E., Bennett, P., Hunt, C. O., Reynolds, T., Farr, L., Frouin, M., Holman, J., Lane, R., French, C., & Barker, G. (2020). New Neanderthal remains associated with the ‘flower burial’ at Shanidar Cave. Antiquity, 94(373), 11–26.

• Randolph-Quinney, P.S. (2013). From the cradle to the grave: the bioarchaeology of Clonfad 3 and Ballykilmore 6. In N. Brady, P. Stevens and J. Channing (eds.). Settlement and Community in the Fir Tulach Kingdom. Dublin: National Roads Authority Press. pp A2.1-48.

• Randolph-Quinney, P.S., Haines, S. and Kruger, A. (2018). The use of three-dimensional scanning and surface capture methods in recording forensic taphonomic traces: issues of technology, visualisation, and validation. In: W.J. M. Groen and P. M. Barone (eds). Multidisciplinary Approaches to Forensic Archaeology. Berlin: Springer International Publishing, pp. 115-130.

• Rendu, W., Beauval, C., Crevecoeur, I., Bayle, P., Balzeau, A., Bismuth, T., Bourguignon, L., Delfour, G., Faivre, J.-P., Lacrampe-Cuyaubère, F., Tavormina, C., Todisco, D., Turq, A., & Maureille, B. (2014). Evidence supporting an intentional Neandertal burial at La Chapelle-aux-Saints. Proceedings of the National Academy of Sciences, 111(1), 81–86.

• Sandgathe, D. M., Dibble, H. L., Goldberg, P., & McPherron, S. P. (2011). The Roc de Marsal Neandertal child: A reassessment of its status as a deliberate burial. Journal of Human Evolution, 61(3), 243–253.

• Silver, M. (2016). Conservation Techniques in Cultural Heritage. In E. Stylianidis and F. Remondino (eds) 3D Recording, Documentation and Management of Cultural Heritage. Dunbeath: Whittles Publishing. pp 15-106.

• Schotsmans, E.M.J., Georges-Zimmermann, P., Ueland, M. and Dent, B.B. (2022). From flesh to bone: Building bridges between taphonomy, archaeothanatology and forensic science for a better understanding of mortuary practices. In C.J. Knüsel and E.M.J. Schotsmans (eds.) The Routledge Handbook of Archaeothanatology. London: Routledge. pp 501-541.

Author Response:

We would like to thank the eLife reviewers for the considerable time and effort they have invested to review these manuscripts. We have also benefited from a previous round of review of the manuscript describing the proposed burial features, which underwent two rounds of revisions in a high-impact journal over a period of approximately 8 months during 2022 and early 2023. Both sets of reviews have reflected mixed responses to the evidence we have presented, with one reviewer recommending acceptance with minor editorial revisions, two recommending acceptance with minor revisions and the fourth recommending rejection based upon similar arguments to those reflected by some of the reviewers in this current round of reviews in eLife. Ultimately the managing editor of this first journal took the decision that the review process could not be completed in a timely manner and rejected the manuscript although the submission here reflected our consideration of these reviewers suggestions.

We have chosen in this initial response to the eLife reviews to include some references to the previous anonymous reviews in order to illustrate differences of opinion and differences in revision suggestions within the review process. Our goal is to offer maximal insight into our decision-making process and to acknowledge the considerable time and effort put into the assessment of these manuscripts by reviewers (for eLife and in the case of the earlier review process). We hope that this approach will assist the readers, and reviewers, of our manuscripts in understanding why we are proceeding with certain decisions during the revision process.

This is a new process for us and the reviewers, and one way in which it significantly differs from more traditional review is that both the reviews and our reply will be public well in advance of our revisions to the manuscript. Indeed, considering the scope of the reviews, some of those revisions may take considerable time, although many can be accomplished fairly easily. Thus, we are not in a position to say that we have solved every issue raised by the reviewers. Instead, we will examine what appear to be the key critical issues raised regarding the data and the analyses and how we propose to address these as we revise the papers. We will also address several philosophical and ethical issues raised by the reviews and our proposal for dealing with these. More specific editorial and citational recommendations will be dealt with on a case-by-case basis, and we do not address these point-by-point in this reply. Please note, this response to the reviewers is not the revision of the manuscript and is only the initial opinion of the corresponding authors with some guidance from the larger group of authors of all three papers. Our final submitted revision will reflect the input of all authors included on those submissions.

We took the decision to submit three separate papers consciously. The two different categories of evidence, burials and engravings, involve different kinds of analysis and different (although overlapping) teams of researchers, and we recognized that each deserved their own presentation and assessment. Meanwhile, together they inform the context of H. naledi in a way that requires some synthetic discussion, in which both kinds of evidence are relevant, leading to a third paper. But the mutual relevance of these different kinds of evidence and their review by a common set of reviewers naturally raises cross-cutting issues, and the reviewers have cross-referenced the three articles. This has sometimes led to suggestions about one manuscript based on the contents of another. Considering the situation, we accepted the recommendation that it would be clearer to consider all three articles in a single reply. Thus, while each of the three papers will proceed separately during the revision process, it will be necessary to highlight across all three papers occasionally in our responses.

Scientific Issues:

In reading the reviews, we feel there are 9 critical points/assertions raised by one or more of the reviewers that present a problem for, or challenge to, our hypothesis that the observed evidence (bone accumulations and engravings) described in the Dinaledi subsystem are of intentional naledigenic origin. These are:

1. The evidence presented does not demonstrate a clear interruption of the floor sediments, thus failing to demonstrate excavated holes.

2. The sediments infilling the holes where the skeletal remains are found have not been demonstrated to originate from the disruption of the floor sediments and thus could be part of a natural geological process (e.g. water movement, slumping) or carnivore accumulations.

3. Previous geological interpretations by our research group have given alternative geological explanations for formation of the bony accumulations that contradict the present evidence presented here and result in alternative origins hypotheses.

4. Burial cannot be effectively assessed without complete excavation of the features and site.

5. The skeletal remains as presented do not conform clearly to typical body arrangement/positions associated with human (Homo sapiens) burials.

6. There is no evidence of grave goods or lithic scatters that are typically associated with human burials.

7. Humans may have been involved with the creation of either the Homo naledi bone accumulations, the engravings, or both.

8. Without a date of the engravings, the null hypothesis should be the engravings were created by Homo sapiens.

9. The null hypothesis for explanation of the skeletal remains in this situation should be “natural accumulation”.

Our analysis of the Dinaledi Feature 1 leads us to accept that the laminated orange-red mudstone (LORM) sedimentary layer is interrupted, indicating a non-natural intervention, and that the hole created by the interruption was then filled by both a fleshed body (and perhaps parts of other bodies) which were then covered by sediment that originated from the hole that was dug. We recognize that the four eLife reviewers are not convinced that our presentation is sufficient to establish this. Interestingly, this was not the universal opinion of earlier reviewers of the initial manuscript several of whom felt we had adequately supported this hypothesis. The lack of clarity in this current version of the burial manuscript is our responsibility. In the upcoming revision of this paper to be submitted, we will take the reviewers’ critiques to heart and add additional figures that illustrate better the disruption of the LORM and clarify the sedimentological data showing the material covering the skeletal remains in the hole are the disrupted sediments excavated from the same hole. We are proposing to isolate this most critical evidence for burial into a separate section in the revised submission based on the reviewers’ comments. The fact that the LORM layer is disrupted, a fleshed body was placed in the hole created by this disruption, and the body (and perhaps parts of other bodies) was/were then covered by the same sediments from the hole is the central feature of our hypothesis that the bone accumulations observed reflect a burial and not a natural process.

The possibility of fluvial transport or involvement in the subsystem is a topic that we have addressed extensively in past work, and it is clear from these reviews that we must enhance our current manuscript to discuss this issue at greater length. Our previous work (Dirks et al. 2015; Dirks et al. 2017) emphasized that fluvial transport of whole bodies into the subsystem was precluded by several lines of sedimentological evidence. We excavated a rich accumulation of skeletal remains, including articulated limbs and other elements in subvertical orientations inconsistent with slow sedimentary infill, which were difficult to explain without positing either a large and dense pile of bodies and/or sediment movement. We encountered fractured chunks of laminated orange-red mudstone (LORM) in random orientations within our excavation area, within and among skeletal remains, which directly refuted that the remains were inundated with water at the time of burial, and this limited the possibility of fluvial transport. Water flow sufficient to displace bodies or complete skeletal evidence would also transport large and course sediment, which is absent from the subsystem, and would sort the commingled skeletal material that we found by size, which we do not observe. But our excavation only covered less than a square meter at very limited depth, and this was the limit to our knowledge of subsurface sediment. We thus were left with uncertainty that led us to suggest the possibility of sediment slumping or movement into subsurface drains, although these were not observed near our excavation. Our current work expands our knowledge of the subsurface and presents an alternative explanation for the disposition of skeletal remains from our earlier excavation. But we acknowledge that this new explanation is vulnerable to our own previous published proposals, and we must do a better job of explaining how the new information addresses our previous suggestions. By not clearly creating a section where we explained how these previous hypotheses were now nullified by new evidence, we clearly confused the reviewers with our own previous work. We will revise the manuscript by enhancing the review of the significant geological evidence demonstrating that there is no significant fluvial action in the system and making it clear how the burial hypothesis provides a clearer explanation for the situation of skeletal remains from our previous excavation work.

One of the central issues raised by reviewers has been a perceived need to excavate these features completely, totally exhuming all skeletal remains from them. Reviewers have written that it is necessary to identify every skeletal element that is present and account for any missing elements. On this point, we have both ethical and scientific differences from these reviewers. We express our ethical concerns first. Many of the best-preserved possible burials ever discovered by archaeologists were subjected to total excavation and exhumation. Cases like La Chapelle-aux-Saints, La Ferrassie, and Skhūl were fully excavated at a time when data recording and excavation methods did not include the range of spatial and geomorphological approaches that later became routine. The judgment of early investigators that these situations were intentional burials was challenged by later workers, and the kind of information that might enable better tests had been irrevocably lost (Gargett 1999; Dibble et al. 2015; Rendu et al. 2014).

Later, improved excavation standards have not sufficed to remove uncertainty or debate about possible burials. For example, it was long presumed that well-preserved remains of young children were by themselves diagnostic of intentional burial, such as those from Dederiyeh, Border Cave, or Roc de Marsal. Such cases were also fully excavated, with adequate documentation of the positioning of skeletal remains and their surrounding stratigraphic situation, but such cases were later challenged on several bases and the complete exhumation of material has confused or precluded testing of new hypotheses (e.g. Gargett 1999). The case of Roc de Marsal is one in which data from the initial excavation combined with data from the initial excavation combined with re-excavation and geoarchaeological analysis led to a naturalistic interpretation of the skeletal material (Sandgathe et al. 2011; Goldberg et al. 2017). But even in this case, the researchers erred in their interpretation of the skeleton’s situation due to a lack of identification of parts of the infant’s skeleton (Gómez-Olivencia and García-Martinez 2019). That is to say, it is not only the burial hypothesis but other hypotheses that suffer from complete excavation. Researchers concerned with preserving all possible information have sometimes taken extraordinary measures to remove and study possible burials at high-resolution in the laboratory. Such was the case of the Shanidar IV burial removed from the site and transported in plaster jacket by Solecki, which led to the disruption and loss of internal stratigraphic information (Pomeroy et al. 2020). Arguably, the current state of the art is full excavation with partial preparation, such as that undertaken at Panga ya Saidi (Martinón-Torres et al. 2021). But again, any future attempt to reinterpret or test the hypothesis of burial must rely on the adequacy of documentation as the original context has been removed.

In our decision to leave material in place as much as possible, we are expanding upon standard practice to leave witness sections and unexcavated areas for future research. The situation is novel, representing possible burials by a nonhuman species, and that makes it doubly important in our opinion to be conservative in not fully exhuming the skeletal material from its context. We anticipate that many other researchers, including future investigators, will suggest additional methods to further test the hypothesis of burial, something that would be impossible if we had excavated the features in their entirety prior to publishing a description of our work. We believe strongly that our ethical responsibility is to publish the work and the most likely interpretation while leaving as much evidence in place as possible to enable further testing and replication. We welcome the suggestions of additional methods/analyses to test the H. naledi burial hypothesis.

This being said, we also observe that total exhumation would not resolve the concerns raised by the reviewers. The recommendation of total exhumation is in pursuit of a full account of all skeletal material present and its preservation and spatial situation, in order to demonstrate that they conform to body positions comparable to human burials. As has been highlighted in forensic casework, the excavation of an inhumation feature does not necessarily provide an accurate spatial or anatomical manifest of the stratigraphical relationships between the body, encapsulating matrix, and any cut present due to preservational, taphonomic and operational factors (Dirkmaat and Cabo, 2016; Hunter, 2014). In particular, in cases where skeletal elements are highly fragmented, friable, or degraded (such as through bioerosion) then complete excavation—even under controlled laboratory conditions—may destroy bone and severely limit skeletal identification (Henderson, 1997; Hochrein, 2002; Owsley and Compton, 1997), particularly in elements where the ratio of trabecular to cortical bone is high (Darwent and Lyman, 2002; Lyman, 1994). As such, non-invasive methods of 3D and 4D modelling (preservation in situ) are often considered preferable to complete necropsy or excavation (preservation by record) where appropriate (Bolliger and Thali, 2009; Dell’Unto and Landeschi, 2022; Randolph-Quinney et al., 2018; Silver, 2016). 

The test of burial is not primarily positional, but taphonomic and geological. The position and number of bones can elaborate on process-driven questions of decay and destruction in the burial environment, or post-mortem modification, but are not singularly indicative of whether the remains were intentionally buried – the post-mortem narrative of all the processes affecting the cadaveric island is required (Knüsel and Robb, 2016). In previous cases, researchers have disputed or accepted the hypothesis of intentional hominin burial based upon assumptions about how modern humans or Neandertals would have positioned bodies, with the idea that some positions reflect ritual intent while others do not. But applying such assumptions is unjustifiable, particularly for a species like H. naledi, whose culture may have differed fundamentally from our own. Our work acknowledges that the present evidence does not enable a full reconstruction of the burial positions, but it does show that fleshed remains were encased in sediment prior to decomposition of soft tissue, and that subsequent spatial changes can be most parsimoniously explained by natural decomposition within sedimentary matrix contained within a burial feature (after Green, 2022; Mickleburgh and Wescott, 2018; Mickleburgh et al., 2022). If the argument is that extraordinary claims require extraordinary evidence, we feel that the evidence documents excavation and interment (and will do so more clearly in the revision) and the fact of the remains do not match a “typical” human burial in body positioning is not in itself evidence that these are not H. naledi burials.

We feel that the reviewers (in keeping with many palaeoanthropologists) have a clear idea of what they “think” a burial should look like in an idealised sense, but this platonic ideal of burial form is not matched by the extensive literature in archaeothanatology, funerary archaeology and forensic science which indicates enormous variability in the activity, morphology and post-mortem system experienced by the human body in cases of interment and body disposal (e.g. Aspöck, 2008; Boulestin and Duday, 2005 and 2006; Connelly et al., 2005; Channing and Randolph-Quinney, 2006; Cherryson, 2008; Donnelly et al., 1995; Finley, 2000; Hunter, 2014; Parker Pearson, 1999; Randolph-Quinney, 2013). Decades of experience in the identification, recovery and interpretation of clandestine, deviant, and non-formal burials indicates the platonic ideal is rare, and in many contexts, the exception (Cherryson, 2008; Parker Pearson, 1999). This variability is particularly relevant to morphological traits in burial context, such as the informal nature of the grave cut in plan and section, shallow burial depth, and initial disposition of body (placement) during the early post-mortem period. These might run counter to the expectations of reviewers or others referencing the fossil hominin record, but are well accepted within the communities of researchers investigating Holocene archaeological sites and forensic contexts.

It is encouraging to see reviewers beginning to incorporate the extensive (often experimentally derived) literature from archaeothanatology and forensic taphonomy in their deliberations, and we will be taking these comments on board going forward. In particular, we acknowledge reviewers’ comments and the need to construct a more detailed post-mortem narrative, accounting for joint disarticulation (labile versus persistent joints etc), displacement, and final disposition of elements within the burial space. As such we will incorporate the hierarchy of decomposition (rank order disarticulation), associations between regions of anatomical association, areas of disassociation, and the voids produced during decomposition (after Mickleburgh and Wescott, 2018; Mickleburgh et al., 2022) into our narrative. In doing so we acknowledge the tensions between the inductive archaeolothanatological narrative-driven approach (e.g. Duday, 2005 & 2009) versus robust decomposition data derived from human forensic taphonomic experimentation recently articulated by Schotsmans and colleagues (2022) - noting that we will highlight comparative data based on forensic experimental casework and actualistic modelling over inductive intuitive approaches which come with significant evidential shortcomings (Bristow et al. 2011).

Finally, from a taphonomic perspective it is worth pointing out to reviewers that we have already addressed the issue of lack of taphonomic evidence for carnivore involvement in the formation of the Dinaledi assemblage (Dirks, et al., 2016). Absence of any carnivore-induced bone surface modifications, patterns of skeletal part representation, and a total absence of any carnivore remains found within the Dinaledi chamber (following Kuhn and colleagues, 2010) lead us to reject carnivores as possible vectors of body accumulation within the Dinaledi Chamber and Hill Antechamber.

Reviewers suggest that without a date derived from geochronological methods, the engravings cannot be associated with H. naledi, and that it is possible (or probable) that the engravings were done in the recent past by H. sapiens. This suggestion neglects the context of the site. We have previously documented the structure and extremely limited accessibility of the Dinaledi subsystem. This subsystem was not recorded on maps of the documented Rising Star Cave system prior to our work and its discovery by our teams. Furthermore, there is no evidence of prehistoric human activity in the areas of the cave related to possible subterranean entrances There is no evidence that humans in the past typically ventured into such extreme spaces like those of Rising Star. It is clear from the presence of the remains of many individuals that H. naledi ventured into these spaces again and again. It is likely that H. naledi moved through these spaces more easily than humans do based on their physique. We show that the engravings overlay each other suggesting multiple engraving events.  These engravings took time and effort and the only evidence for use of the Dinaledi subsystem by any hominin is by H. naledi. The context leads to the null hypothesis that H. naledi made the marks. In our revision, we will elaborate on this argument to clarify the evidence for our stance on this hypothesis. Several reviewers took issue with the title of the engraving paper as we did not insert a qualifier in front of the suggested date range for the engravings. We deliberately left out qualifying language so that the title took the form of a testable hypothesis rather than a weak assertation. Should future work find the engravings were not produced within this time range, then we will restate this hypothesis.

Finally, with regards to the engravings we have chosen to report them because they exist. Not reporting the presence of engraved marks on the walls of a cave above hypothesized burials would be tantamount to leaving relevant evidence out of the description of an archeological context. We recognize and state in our manuscript that these markings require substantial further study, including attempts at geochronological dating. But the current evidence is clearly relevant to the archaeological context of the subsystem. We take a similar stance with reporting the presence of the tool shaped artefact near the hand of the H. naledi skeleton in the Hill Antechamber. It is evident that this object requires further study, as we stated in our manuscript, but again omitting it from our study would be leaving out relevant evidence.

Some have suggested that the null hypothesis should be that all of these observed circumstances are of natural origin. Our team took this approach in our early investigation of the Dinaledi subsystem (Dirks et al. 2015). We adopted the null hypothesis that the geological processes involved in the accumulation of H. naledi skeletal remains were “natural” (e.g., non-naledigenic involvement), and we were able to reject many alternative explanations for the assemblage, including carnivore accumulation, “death trap” accumulation, and fluvial transport of bodies or bones (Dirks et al. 2015). This led us to the hypothesis that H. naledi were involved in bringing the bodies into the spaces where they were found. But we did not hypothesize their involvement in the formation of the deposit itself beyond bringing the bodies to the location.

This approach seems conservative. It followed the traditional view that small-brained hominins do not engage in cultural practices. But we recognize in hindsight that this null hypothesis approach did harm to our analyses. It impeded us from recognizing within our initial excavations of the puzzle box area and other excavations between 2014 – 2017 that we might be encountering remains that were intrusive in the sedimentary floor of the chamber. If we had approached the accumulation of a large number of hominins from the perspective of the null hypothesis being that the situation was likely cultural, we perhaps would have collected evidence in a slightly different manner. We certainly note that if the Dinaledi system had been full of the remains of modern humans, there would have been little doubt that the null hypothesis would have been that this was a cultural space and not a “natural space”.  We therefore respectfully disagree with the reviewers who continue to support the idea that we should approach hominin excavations with the null hypothesis that they will be natural (specifically non-cultural) in origins. If excavations continue with this mindset we believe that potential cultural evidence is almost certain to be lost.

There has been a gradient across paleoanthropological excavations, archaeological work, and forensic investigation, with increasing precision of context. The reality is that the recording precision and frame of approach is typically different in most paleontological excavations than in those related to contemporary human remains. If anything comes from the present discussion of whether the Dinaledi system is a burial site for H. naledi or not, we hope that by taking seriously the possibility of deep cultural dynamics of hominins, we will encourage other teams to meet the highest standards of excavation in order to preserve potential cultural evidence. Given H. naledi’s cranial capacity we suggest that even very early hominin skeletal assemblages should be re-examined, if there is sufficient evidence or records available.  These would include examples such as the A.L. 333 Au. afarensis site (the so called First Family site in Hadar Ethiopia), the Dikika infant skeleton, WT 15000 (Turkana Boy) and even A.L. 288 (Lucy) as such unusual taphonomic situations where skeletons are preserved cannot be simply explained away as “natural” in origin, based solely on the cranial capacity and assumed lack of cognitive and cultural complexity of the hominins as emphasized by us in Fuentes et al. (2023). We are not the first to observe that some very early hominin situations may represent early mortuary activity (Pettitt 2013), but we would advocate a step further. We suggest it may be damaging to take “natural accumulation” as the standard null hypothesis for hominin paleoanthropology, and that it is more conservative in practice to engage remains with the null hypothesis of possible cultural formation.

We are deeply grateful for the time and effort all of the 8 reviewers (across three reviews) have taken with this work.  We also acknowledge the anonymous reviewers from previous submissions who’s opinions and comments will have made the final iterations of these manuscripts better for their efforts. As this process is rather public and includes commentary outside of the eLife forum, we ask that the efforts of all 37 authors and 8 reviewers involved be respected and that the discourse remain professional in all venues as we study this fascinating and quite complex occurrence. We appreciate also the efforts of members of the public who have engaged with this relatively new process where preprints are posted prior to the reviews allowing comments and interactions from colleagues and the public who are normally not part of the internal peer review process.  We believe these interactions will make for better final papers. We feel we have met the standards of demonstrating burials in H. naledi and that the engraving are most likely associated with H. naledi. However, given the reviews we see many areas where our clarity and context, and analyses, were less strong than they can be. With the clarifications and additions taken on board through these review processes the final papers will be stronger and clearer. We, recognize that this is an ongoing process of scientific investigation and further work will allow continued, and possibly better, evaluation of these hypothesis and others.

Lee R Berger, Agustín Fuentes, John Hawks, Tebogo Makhubela

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Author Response:

We would like to thank the eLife reviewers for the considerable time and effort they have invested to review these manuscripts. We have also benefited from a previous round of review of the manuscript describing the proposed burial features, which underwent two rounds of revisions in a high-impact journal over a period of approximately 8 months during 2022 and early 2023. Both sets of reviews have reflected mixed responses to the evidence we have presented, with one reviewer recommending acceptance with minor editorial revisions, two recommending acceptance with minor revisions and the fourth recommending rejection based upon similar arguments to those reflected by some of the reviewers in this current round of reviews in eLife. Ultimately the managing editor of this first journal took the decision that the review process could not be completed in a timely manner and rejected the manuscript although the submission here reflected our consideration of these reviewers suggestions.

We have chosen in this initial response to the eLife reviews to include some references to the previous anonymous reviews in order to illustrate differences of opinion and differences in revision suggestions within the review process. Our goal is to offer maximal insight into our decision-making process and to acknowledge the considerable time and effort put into the assessment of these manuscripts by reviewers (for eLife and in the case of the earlier review process). We hope that this approach will assist the readers, and reviewers, of our manuscripts in understanding why we are proceeding with certain decisions during the revision process.

This is a new process for us and the reviewers, and one way in which it significantly differs from more traditional review is that both the reviews and our reply will be public well in advance of our revisions to the manuscript. Indeed, considering the scope of the reviews, some of those revisions may take considerable time, although many can be accomplished fairly easily. Thus, we are not in a position to say that we have solved every issue raised by the reviewers. Instead, we will examine what appear to be the key critical issues raised regarding the data and the analyses and how we propose to address these as we revise the papers. We will also address several philosophical and ethical issues raised by the reviews and our proposal for dealing with these. More specific editorial and citational recommendations will be dealt with on a case-by-case basis, and we do not address these point-by-point in this reply. Please note, this response to the reviewers is not the revision of the manuscript and is only the initial opinion of the corresponding authors with some guidance from the larger group of authors of all three papers. Our final submitted revision will reflect the input of all authors included on those submissions.

We took the decision to submit three separate papers consciously. The two different categories of evidence, burials and engravings, involve different kinds of analysis and different (although overlapping) teams of researchers, and we recognized that each deserved their own presentation and assessment. Meanwhile, together they inform the context of H. naledi in a way that requires some synthetic discussion, in which both kinds of evidence are relevant, leading to a third paper. But the mutual relevance of these different kinds of evidence and their review by a common set of reviewers naturally raises cross-cutting issues, and the reviewers have cross-referenced the three articles. This has sometimes led to suggestions about one manuscript based on the contents of another. Considering the situation, we accepted the recommendation that it would be clearer to consider all three articles in a single reply. Thus, while each of the three papers will proceed separately during the revision process, it will be necessary to highlight across all three papers occasionally in our responses.

Scientific Issues:

In reading the reviews, we feel there are 9 critical points/assertions raised by one or more of the reviewers that present a problem for, or challenge to, our hypothesis that the observed evidence (bone accumulations and engravings) described in the Dinaledi subsystem are of intentional naledigenic origin. These are:

1. The evidence presented does not demonstrate a clear interruption of the floor sediments, thus failing to demonstrate excavated holes.

2. The sediments infilling the holes where the skeletal remains are found have not been demonstrated to originate from the disruption of the floor sediments and thus could be part of a natural geological process (e.g. water movement, slumping) or carnivore accumulations.

3. Previous geological interpretations by our research group have given alternative geological explanations for formation of the bony accumulations that contradict the present evidence presented here and result in alternative origins hypotheses.

4. Burial cannot be effectively assessed without complete excavation of the features and site.

5. The skeletal remains as presented do not conform clearly to typical body arrangement/positions associated with human (Homo sapiens) burials.

6. There is no evidence of grave goods or lithic scatters that are typically associated with human burials.

7. Humans may have been involved with the creation of either the Homo naledi bone accumulations, the engravings, or both.

8. Without a date of the engravings, the null hypothesis should be the engravings were created by Homo sapiens.

9. The null hypothesis for explanation of the skeletal remains in this situation should be “natural accumulation”.

Our analysis of the Dinaledi Feature 1 leads us to accept that the laminated orange-red mudstone (LORM) sedimentary layer is interrupted, indicating a non-natural intervention, and that the hole created by the interruption was then filled by both a fleshed body (and perhaps parts of other bodies) which were then covered by sediment that originated from the hole that was dug. We recognize that the four eLife reviewers are not convinced that our presentation is sufficient to establish this. Interestingly, this was not the universal opinion of earlier reviewers of the initial manuscript several of whom felt we had adequately supported this hypothesis. The lack of clarity in this current version of the burial manuscript is our responsibility. In the upcoming revision of this paper to be submitted, we will take the reviewers’ critiques to heart and add additional figures that illustrate better the disruption of the LORM and clarify the sedimentological data showing the material covering the skeletal remains in the hole are the disrupted sediments excavated from the same hole. We are proposing to isolate this most critical evidence for burial into a separate section in the revised submission based on the reviewers’ comments. The fact that the LORM layer is disrupted, a fleshed body was placed in the hole created by this disruption, and the body (and perhaps parts of other bodies) was/were then covered by the same sediments from the hole is the central feature of our hypothesis that the bone accumulations observed reflect a burial and not a natural process.

The possibility of fluvial transport or involvement in the subsystem is a topic that we have addressed extensively in past work, and it is clear from these reviews that we must enhance our current manuscript to discuss this issue at greater length. Our previous work (Dirks et al. 2015; Dirks et al. 2017) emphasized that fluvial transport of whole bodies into the subsystem was precluded by several lines of sedimentological evidence. We excavated a rich accumulation of skeletal remains, including articulated limbs and other elements in subvertical orientations inconsistent with slow sedimentary infill, which were difficult to explain without positing either a large and dense pile of bodies and/or sediment movement. We encountered fractured chunks of laminated orange-red mudstone (LORM) in random orientations within our excavation area, within and among skeletal remains, which directly refuted that the remains were inundated with water at the time of burial, and this limited the possibility of fluvial transport. Water flow sufficient to displace bodies or complete skeletal evidence would also transport large and course sediment, which is absent from the subsystem, and would sort the commingled skeletal material that we found by size, which we do not observe. But our excavation only covered less than a square meter at very limited depth, and this was the limit to our knowledge of subsurface sediment. We thus were left with uncertainty that led us to suggest the possibility of sediment slumping or movement into subsurface drains, although these were not observed near our excavation. Our current work expands our knowledge of the subsurface and presents an alternative explanation for the disposition of skeletal remains from our earlier excavation. But we acknowledge that this new explanation is vulnerable to our own previous published proposals, and we must do a better job of explaining how the new information addresses our previous suggestions. By not clearly creating a section where we explained how these previous hypotheses were now nullified by new evidence, we clearly confused the reviewers with our own previous work. We will revise the manuscript by enhancing the review of the significant geological evidence demonstrating that there is no significant fluvial action in the system and making it clear how the burial hypothesis provides a clearer explanation for the situation of skeletal remains from our previous excavation work.

One of the central issues raised by reviewers has been a perceived need to excavate these features completely, totally exhuming all skeletal remains from them. Reviewers have written that it is necessary to identify every skeletal element that is present and account for any missing elements. On this point, we have both ethical and scientific differences from these reviewers. We express our ethical concerns first. Many of the best-preserved possible burials ever discovered by archaeologists were subjected to total excavation and exhumation. Cases like La Chapelle-aux-Saints, La Ferrassie, and Skhūl were fully excavated at a time when data recording and excavation methods did not include the range of spatial and geomorphological approaches that later became routine. The judgment of early investigators that these situations were intentional burials was challenged by later workers, and the kind of information that might enable better tests had been irrevocably lost (Gargett 1999; Dibble et al. 2015; Rendu et al. 2014).

Later, improved excavation standards have not sufficed to remove uncertainty or debate about possible burials. For example, it was long presumed that well-preserved remains of young children were by themselves diagnostic of intentional burial, such as those from Dederiyeh, Border Cave, or Roc de Marsal. Such cases were also fully excavated, with adequate documentation of the positioning of skeletal remains and their surrounding stratigraphic situation, but such cases were later challenged on several bases and the complete exhumation of material has confused or precluded testing of new hypotheses (e.g. Gargett 1999). The case of Roc de Marsal is one in which data from the initial excavation combined with data from the initial excavation combined with re-excavation and geoarchaeological analysis led to a naturalistic interpretation of the skeletal material (Sandgathe et al. 2011; Goldberg et al. 2017). But even in this case, the researchers erred in their interpretation of the skeleton’s situation due to a lack of identification of parts of the infant’s skeleton (Gómez-Olivencia and García-Martinez 2019). That is to say, it is not only the burial hypothesis but other hypotheses that suffer from complete excavation. Researchers concerned with preserving all possible information have sometimes taken extraordinary measures to remove and study possible burials at high-resolution in the laboratory. Such was the case of the Shanidar IV burial removed from the site and transported in plaster jacket by Solecki, which led to the disruption and loss of internal stratigraphic information (Pomeroy et al. 2020). Arguably, the current state of the art is full excavation with partial preparation, such as that undertaken at Panga ya Saidi (Martinón-Torres et al. 2021). But again, any future attempt to reinterpret or test the hypothesis of burial must rely on the adequacy of documentation as the original context has been removed.

In our decision to leave material in place as much as possible, we are expanding upon standard practice to leave witness sections and unexcavated areas for future research. The situation is novel, representing possible burials by a nonhuman species, and that makes it doubly important in our opinion to be conservative in not fully exhuming the skeletal material from its context. We anticipate that many other researchers, including future investigators, will suggest additional methods to further test the hypothesis of burial, something that would be impossible if we had excavated the features in their entirety prior to publishing a description of our work. We believe strongly that our ethical responsibility is to publish the work and the most likely interpretation while leaving as much evidence in place as possible to enable further testing and replication. We welcome the suggestions of additional methods/analyses to test the H. naledi burial hypothesis.

This being said, we also observe that total exhumation would not resolve the concerns raised by the reviewers. The recommendation of total exhumation is in pursuit of a full account of all skeletal material present and its preservation and spatial situation, in order to demonstrate that they conform to body positions comparable to human burials. As has been highlighted in forensic casework, the excavation of an inhumation feature does not necessarily provide an accurate spatial or anatomical manifest of the stratigraphical relationships between the body, encapsulating matrix, and any cut present due to preservational, taphonomic and operational factors (Dirkmaat and Cabo, 2016; Hunter, 2014). In particular, in cases where skeletal elements are highly fragmented, friable, or degraded (such as through bioerosion) then complete excavation—even under controlled laboratory conditions—may destroy bone and severely limit skeletal identification (Henderson, 1997; Hochrein, 2002; Owsley and Compton, 1997), particularly in elements where the ratio of trabecular to cortical bone is high (Darwent and Lyman, 2002; Lyman, 1994). As such, non-invasive methods of 3D and 4D modelling (preservation in situ) are often considered preferable to complete necropsy or excavation (preservation by record) where appropriate (Bolliger and Thali, 2009; Dell’Unto and Landeschi, 2022; Randolph-Quinney et al., 2018; Silver, 2016). 

The test of burial is not primarily positional, but taphonomic and geological. The position and number of bones can elaborate on process-driven questions of decay and destruction in the burial environment, or post-mortem modification, but are not singularly indicative of whether the remains were intentionally buried – the post-mortem narrative of all the processes affecting the cadaveric island is required (Knüsel and Robb, 2016). In previous cases, researchers have disputed or accepted the hypothesis of intentional hominin burial based upon assumptions about how modern humans or Neandertals would have positioned bodies, with the idea that some positions reflect ritual intent while others do not. But applying such assumptions is unjustifiable, particularly for a species like H. naledi, whose culture may have differed fundamentally from our own. Our work acknowledges that the present evidence does not enable a full reconstruction of the burial positions, but it does show that fleshed remains were encased in sediment prior to decomposition of soft tissue, and that subsequent spatial changes can be most parsimoniously explained by natural decomposition within sedimentary matrix contained within a burial feature (after Green, 2022; Mickleburgh and Wescott, 2018; Mickleburgh et al., 2022). If the argument is that extraordinary claims require extraordinary evidence, we feel that the evidence documents excavation and interment (and will do so more clearly in the revision) and the fact of the remains do not match a “typical” human burial in body positioning is not in itself evidence that these are not H. naledi burials.

We feel that the reviewers (in keeping with many palaeoanthropologists) have a clear idea of what they “think” a burial should look like in an idealised sense, but this platonic ideal of burial form is not matched by the extensive literature in archaeothanatology, funerary archaeology and forensic science which indicates enormous variability in the activity, morphology and post-mortem system experienced by the human body in cases of interment and body disposal (e.g. Aspöck, 2008; Boulestin and Duday, 2005 and 2006; Connelly et al., 2005; Channing and Randolph-Quinney, 2006; Cherryson, 2008; Donnelly et al., 1995; Finley, 2000; Hunter, 2014; Parker Pearson, 1999; Randolph-Quinney, 2013). Decades of experience in the identification, recovery and interpretation of clandestine, deviant, and non-formal burials indicates the platonic ideal is rare, and in many contexts, the exception (Cherryson, 2008; Parker Pearson, 1999). This variability is particularly relevant to morphological traits in burial context, such as the informal nature of the grave cut in plan and section, shallow burial depth, and initial disposition of body (placement) during the early post-mortem period. These might run counter to the expectations of reviewers or others referencing the fossil hominin record, but are well accepted within the communities of researchers investigating Holocene archaeological sites and forensic contexts.

It is encouraging to see reviewers beginning to incorporate the extensive (often experimentally derived) literature from archaeothanatology and forensic taphonomy in their deliberations, and we will be taking these comments on board going forward. In particular, we acknowledge reviewers’ comments and the need to construct a more detailed post-mortem narrative, accounting for joint disarticulation (labile versus persistent joints etc), displacement, and final disposition of elements within the burial space. As such we will incorporate the hierarchy of decomposition (rank order disarticulation), associations between regions of anatomical association, areas of disassociation, and the voids produced during decomposition (after Mickleburgh and Wescott, 2018; Mickleburgh et al., 2022) into our narrative. In doing so we acknowledge the tensions between the inductive archaeolothanatological narrative-driven approach (e.g. Duday, 2005 & 2009) versus robust decomposition data derived from human forensic taphonomic experimentation recently articulated by Schotsmans and colleagues (2022) - noting that we will highlight comparative data based on forensic experimental casework and actualistic modelling over inductive intuitive approaches which come with significant evidential shortcomings (Bristow et al. 2011).

Finally, from a taphonomic perspective it is worth pointing out to reviewers that we have already addressed the issue of lack of taphonomic evidence for carnivore involvement in the formation of the Dinaledi assemblage (Dirks, et al., 2016). Absence of any carnivore-induced bone surface modifications, patterns of skeletal part representation, and a total absence of any carnivore remains found within the Dinaledi chamber (following Kuhn and colleagues, 2010) lead us to reject carnivores as possible vectors of body accumulation within the Dinaledi Chamber and Hill Antechamber.

Reviewers suggest that without a date derived from geochronological methods, the engravings cannot be associated with H. naledi, and that it is possible (or probable) that the engravings were done in the recent past by H. sapiens. This suggestion neglects the context of the site. We have previously documented the structure and extremely limited accessibility of the Dinaledi subsystem. This subsystem was not recorded on maps of the documented Rising Star Cave system prior to our work and its discovery by our teams. Furthermore, there is no evidence of prehistoric human activity in the areas of the cave related to possible subterranean entrances There is no evidence that humans in the past typically ventured into such extreme spaces like those of Rising Star. It is clear from the presence of the remains of many individuals that H. naledi ventured into these spaces again and again. It is likely that H. naledi moved through these spaces more easily than humans do based on their physique. We show that the engravings overlay each other suggesting multiple engraving events.  These engravings took time and effort and the only evidence for use of the Dinaledi subsystem by any hominin is by H. naledi. The context leads to the null hypothesis that H. naledi made the marks. In our revision, we will elaborate on this argument to clarify the evidence for our stance on this hypothesis. Several reviewers took issue with the title of the engraving paper as we did not insert a qualifier in front of the suggested date range for the engravings. We deliberately left out qualifying language so that the title took the form of a testable hypothesis rather than a weak assertation. Should future work find the engravings were not produced within this time range, then we will restate this hypothesis.

Finally, with regards to the engravings we have chosen to report them because they exist. Not reporting the presence of engraved marks on the walls of a cave above hypothesized burials would be tantamount to leaving relevant evidence out of the description of an archeological context. We recognize and state in our manuscript that these markings require substantial further study, including attempts at geochronological dating. But the current evidence is clearly relevant to the archaeological context of the subsystem. We take a similar stance with reporting the presence of the tool shaped artefact near the hand of the H. naledi skeleton in the Hill Antechamber. It is evident that this object requires further study, as we stated in our manuscript, but again omitting it from our study would be leaving out relevant evidence.

Some have suggested that the null hypothesis should be that all of these observed circumstances are of natural origin. Our team took this approach in our early investigation of the Dinaledi subsystem (Dirks et al. 2015). We adopted the null hypothesis that the geological processes involved in the accumulation of H. naledi skeletal remains were “natural” (e.g., non-naledigenic involvement), and we were able to reject many alternative explanations for the assemblage, including carnivore accumulation, “death trap” accumulation, and fluvial transport of bodies or bones (Dirks et al. 2015). This led us to the hypothesis that H. naledi were involved in bringing the bodies into the spaces where they were found. But we did not hypothesize their involvement in the formation of the deposit itself beyond bringing the bodies to the location.

This approach seems conservative. It followed the traditional view that small-brained hominins do not engage in cultural practices. But we recognize in hindsight that this null hypothesis approach did harm to our analyses. It impeded us from recognizing within our initial excavations of the puzzle box area and other excavations between 2014 – 2017 that we might be encountering remains that were intrusive in the sedimentary floor of the chamber. If we had approached the accumulation of a large number of hominins from the perspective of the null hypothesis being that the situation was likely cultural, we perhaps would have collected evidence in a slightly different manner. We certainly note that if the Dinaledi system had been full of the remains of modern humans, there would have been little doubt that the null hypothesis would have been that this was a cultural space and not a “natural space”.  We therefore respectfully disagree with the reviewers who continue to support the idea that we should approach hominin excavations with the null hypothesis that they will be natural (specifically non-cultural) in origins. If excavations continue with this mindset we believe that potential cultural evidence is almost certain to be lost.

There has been a gradient across paleoanthropological excavations, archaeological work, and forensic investigation, with increasing precision of context. The reality is that the recording precision and frame of approach is typically different in most paleontological excavations than in those related to contemporary human remains. If anything comes from the present discussion of whether the Dinaledi system is a burial site for H. naledi or not, we hope that by taking seriously the possibility of deep cultural dynamics of hominins, we will encourage other teams to meet the highest standards of excavation in order to preserve potential cultural evidence. Given H. naledi’s cranial capacity we suggest that even very early hominin skeletal assemblages should be re-examined, if there is sufficient evidence or records available.  These would include examples such as the A.L. 333 Au. afarensis site (the so called First Family site in Hadar Ethiopia), the Dikika infant skeleton, WT 15000 (Turkana Boy) and even A.L. 288 (Lucy) as such unusual taphonomic situations where skeletons are preserved cannot be simply explained away as “natural” in origin, based solely on the cranial capacity and assumed lack of cognitive and cultural complexity of the hominins as emphasized by us in Fuentes et al. (2023). We are not the first to observe that some very early hominin situations may represent early mortuary activity (Pettitt 2013), but we would advocate a step further. We suggest it may be damaging to take “natural accumulation” as the standard null hypothesis for hominin paleoanthropology, and that it is more conservative in practice to engage remains with the null hypothesis of possible cultural formation.

We are deeply grateful for the time and effort all of the 8 reviewers (across three reviews) have taken with this work.  We also acknowledge the anonymous reviewers from previous submissions who’s opinions and comments will have made the final iterations of these manuscripts better for their efforts. As this process is rather public and includes commentary outside of the eLife forum, we ask that the efforts of all 37 authors and 8 reviewers involved be respected and that the discourse remain professional in all venues as we study this fascinating and quite complex occurrence. We appreciate also the efforts of members of the public who have engaged with this relatively new process where preprints are posted prior to the reviews allowing comments and interactions from colleagues and the public who are normally not part of the internal peer review process.  We believe these interactions will make for better final papers. We feel we have met the standards of demonstrating burials in H. naledi and that the engraving are most likely associated with H. naledi. However, given the reviews we see many areas where our clarity and context, and analyses, were less strong than they can be. With the clarifications and additions taken on board through these review processes the final papers will be stronger and clearer. We, recognize that this is an ongoing process of scientific investigation and further work will allow continued, and possibly better, evaluation of these hypothesis and others.

Lee R Berger, Agustín Fuentes, John Hawks, Tebogo Makhubela

Works cited:

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Author Response:

We thank eLife and the reviewer for the nice summary of our manuscript. We largely agree with the summary and review, and just add a few small points.

First, the review asks about the reproducibility of our findings, and suggests that they are only from a single experiment. In fact, our manuscript reports data from two independent single-cell experiments: one performed at low multiplicity of infection (MOI), and another at higher MOI. The broad trends, including the lack of strong correlations between viral mRNA transcription and progeny production, are consistent across both experiments.

Second, the reviewer asks about what happens when two different virions bearing the same viral barcode infect two different cells, given that we estimate 4-8% of barcodes to be shared between multiple infecting virions. When two cells are infected by different virions with the same barcode, this breaks the one-to-one link between transcription in that cell and progeny in the supernatant, since it is not possible to determine which cell contributed the progeny with that barcode. This means that between 4-8% of the points on our correlation plots could be affected by this factor, meaning that a few outliers should be expected. Another scenario, where a single cell is infected by two barcodes, is not problematic for our method because we can simply sum the progeny output for both barcodes from that cell.

Finally, the reviewer notes that some cells appear to produce progeny virions despite failing to express one or more viral genes. Such cells can be explained in one of two ways. First, as noted immediately above, we expect a small fraction (4-8%) of the points to be erroneous due to a lack of a guaranteed one-to-one link between cell and progeny for non-unique barcodes. Second, in some cases the missing viral gene could be a technical artifact caused by a stochastic failure to capture modestly expressed transcripts from the gene; this phenomenon, known as gene dropout, occurs at a fairly high rate in single-cell experiments (see Qiu Nature Communications 2020 for a detailed discussion). Genes that are expressed at lower levels, like the Influenza virus polymerase genes, are more likely to be missed during single-cell RNA sequencing. The absent viral genes in each infected cell can be explored in detail using the interactive plots at https://jbloomlab.github.io/barcoded_flu_pdmH1N1/

Author Response:

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

Major Revisions:

1) Although we appreciate this work was carried out independently, it would improve this paper if this structure presented here was compared to the recently published structure of Cx43 (Nat Commun 14, 931 (2023)) with the conclusions including added in the discussion.

We encourage the readers to read both our study on Cx43 and the one mentioned by the reviewer. However, we believe the optimal format for such a comparison is going to be a more comprehensive review article, which is outside the scope of our study.

2) Please elaborate on the lipid-binding pockets observed for lipid 1, lipid 2, and the N-lipid/PGL. For example, what are the residues involved in these lipid-protein interactions? Are these residues conserved in other connexin isoforms? Do these lipid-binding pockets match with previous structures, including the recent Cx43 structure? Please clarify what lipid sites are ambiguous due to insufficient resolution.

Within the scope of our study, we have shown that some of the disease-linked residues are located in close proximity to the lipid sites (Fig. 4b). This suggests a possible role of the lipid sites in diseases associated with Cx43 mutations (and possibly with the mutations in other connexins, as the structures of other connexin channels also feature bound lipids inside the pore region). We feel that a more in-depth comparison will require a careful study, beyond the analysis that we have performed here, and for this reason we would like to reserve such a detailed comparison for our future work (possibly a comprehensive review article on connexin structure and function).

3) The NT domain and TM2 segments are referred to as the gate region. If there is no strong evidence to support this claim then please use "putative" gate region.

We have updated the text accordingly, referring to this region as a putative gate region where appropriate.

4) It is mentioned that there is a reorientation of extracellular loops 1 and 2 after Gap junction formation. Based on their structures, I wonder how this rearrangement alters the channel conduction pathway. For example, Do the electrostatic surface and hydrophobic properties change? Please consider adding further details as this information could be useful to understand why some properties of hemichannels differ from intercellular GJ channels.

We have updated the Fig. 5 with an illustration of the Cx43 HC surface coloured according to electrostatic potential (to match the same representation of the Cx43 GJC). It is obvious that the rearrangement of the extracellular loops 1 and 2 do not dramatically alter the electrostatic properties of the HC relative to the GJC. A more obvious difference is in the local environment of the ECLs: it is radically different in a “free” HC (exposed to the solvent or to the extracellular space of a cell), compared to the ECL environment in a connexon within a GJC (which is sealed by a docked connexon from the opposite membrane).

5) Related to the previous point, the pore profile shown in Figure 5C shows that there is a constriction site in the extracellular part with the same diameter as the observed constriction caused by the NT domain. This constriction point seems to be associated with the high energies calculated for Cl-. Please clarify if this constriction is produced by the formation of the GJC or is also present in HC?

This is the same constriction zone, and the Cl- barriers are further down the channel axis where the electrostatic potential of the protein is negative. We have included a similar calculation for the HC simulation in Fig. 5 (revised Fig. 5f).

6) Related to the MD simulations shown in Figure 5d: if the voltage is applied across the whole GJC, the free energy under voltage should not be symmetric. Please clarify.

The symmetry observed in the free energies is due to the fact that the ions enter and exit from the same hemichannel. Only at very high voltages we observe some rare full GJC permeation events, slightly unbalancing the free energy at 500 mV.

7) The scheme in Figure 6 many needs further editing. The authors propose a putative closed state in which lipids are bound next to the NT, but we suggest it should be made clearer in the figure that this is a putative model, since there is no functional evidence supporting the role of these lipids in the gating/permeation properties of Cx43. Also, please clarify what is meant by a "semi-permeable gate" - a channel that only permeates ions but not molecules?

We have updated the legend of the figure 6, to clearly reflect that this is a putative model. The “semi-permeable” state of the channel is something that was suggested previously by the authors of the Cx31.3 study, and we refer to that structure in the figure.

Minor comments:

1) In the result section there are some statements that currently lack solid experimental support. Please consider editing or moving this text to the discussion section only. A good example of this is the Diseaselinked mutation section, specifically lines 199-206. In another example: in lines, 237-238 authors state that NT can move laterally and vertically, but this idea still requires experimental validation.

We feel that the original formulations of these portions of the text are appropriate. Disrupting them would interrupt the flow of the manuscript, and we prefer to stay with the original text in this case.

2) Line 283. "With these structures in mind, we can now establish the existence of several structurally defined gating substates of the connexin channels". Please, tone down this statement. Replace "establish" with "propose" or another more appropriate word.

We have updated the text as suggested ("propose” instead of “establish”)

3) Line 313-314. " The presence of such molecules could have important implications for HC or GJC assembly, substrate permeation, and molecular gating". Currently, this entire statement does not have any support. Is there any paper that authors can discuss to suggest with some basis that lipids might have a role in assembly, permeation or gating?

We feel that this statement is sufficiently careful, conveying a thought that the presence of such molecules could have important implications for various HC- or GJC-related processes. It is not a particularly strong claim and seems to be appropriate in this context.

4) It seems that the structure shown in panels A and C in Figure 2 are shown in opposite directions, which makes the figure confusing. If needed, please rotate the structure in panel A to show the cytosolic part of the protein as panel C. Also, in the same figure, panels G and F are wrongly labeled. Please correct.

For Fig. 2a, the angle is very different from anything else we show in the figure, so we would rather keep this as it is now. We have corrected the labelling for Fig. 2g-h.

5) Check spelling mistakes in the legend of Extended data Fig.2, Extended data Fig.9, and line 243.

We are grateful to the reviewers for pointing out the typos, which have now been corrected.

6) The colors for G-L isoforms are not specified in Extended Data Fig.10. Please correct this.

We updated the figure, removing the PGL label (the correct label is “lipid-N”).

7) It is not clear what is the difference between PGL and the N-lipid density. Does PGL refers to the lipid-like density observed in nanodiscs, as indicated in Extended Fig. 4 and 10?. Please clarify this issue in the manuscript.

The labeling has been corrected in like with the revised version of the manuscript (this density element is now referred to as the “lipid-N”).

8) Page 7 line 234-235 "The pore opening has a solvent-accessible radius of ~6Å (Figure 5c) very close to the effective hydrated radius of K+ (~6.6 Å) and Cl- (~7.2 Å). This makes it the most narrow pore opening...", it should be diameter, not radius.

We have added a calculation for the HC (new Fig. 5f) and corrected the text as follows (line 234):

“The pore opening observed in our cryo-EM structures has a solvent-accessible radius of ~3 Å (Figure 2b). This makes it the most narrow pore opening observed for a connexin channel to date (a comparison of the pore openings in the cryo-EM structures of connexin channels is shown in Extended Data Fig. 12). However, the average solvent-accessible radius of the pore during molecular dynamics was ~6 Å (Figure 5c); note that the effective hydrated radius of K+ and Cl- is ~3.3 Å and ~3.6 Å, respectively.”

And line 277:

“The average pore radius during the simulations was consistent with that observed in the cryo-EM structure (Fig. 5f).”

Author Response

Reviewer #1 (Public Review):

In this study, Shin and colleagues investigate the role of the posttranslational modification of the DNA methyltransferase by covalent linkage of the N-Acetylglucosamine (O-GlcNAc).

The authors present compelling evidence showing that a prolonged high fat/sucrose diet causes global protein O-GlcNAcylation in the liver and DNMT1 is among the proteins that increase their O-GlcNAc level. This result is significant because of the paucity of in vivo data addressing the interplay between metabolism and protein O-GlcNAcylation. The paper also shows that DNMT1's O-GlcNAcylation level correlated to the extracellular glucose levels in other cell types.

Using mass spectrometry, the authors identify S878 as the main site for O-GlcNAcylation. It is noteworthy that the mapping was performed with hyper-O-GlcNAcylated cells and may be different in a physiological situation. To investigate how O-GlcNAcylation of S878 of DNMT1 impacts its activity and ultimately DNA methylation patterns, Shin and colleagues mostly use a cellular model of hyper O-GlcNAcylation induced by the combination of high glucose and a chemical inhibitor of OGA (the only enzyme responsible for O-GlcNAc removal). The data shows that increased O-GlcNAcylation resulting from the combination of high glucose and OGA inhibition causes a reduction of DNMT1 activity and local loss of DNA methylation specifically at partially methylated domains.

This study brings completely new knowledge on the regulatory function of glycosylation of DNMT1 and its impact on its methyl-transferase activity and downstream genomic methylation. Furthermore, the manuscript introduces new data on the interplay between cellular metabolism and O-GlcNAcylation on DNMT1 and other proteins. The experiments are well-controlled, and their interpretation is sound. This study should be of special interest to the fields of fundamental and environmental epigenetics, as well as metabolism.

The main limitation of the study is the convolution of the functional experiments where the perturbation is a combination of high glucose and chemical inhibition of OGA. The relative contribution of the two variables is partially addressed in Figure 3-figure supplement 1B which shows that high glucose increases DNMT1 activity (Hep3B cells) while Figure 3D shows that high glucose when combined with OGA inhibitor decreases DNMT1 activity (Hep3B cells). As discussed, the data suggest that high-glucose and OGA inhibition may have an antagonistic effect on DNMT1 activity. An experiment of treatment of the cells with the OGA inhibitor in physiological glucose conditions would address this gap of knowledge.

We thank the reviewer for the suggestion. The physiological glucose levels are between 5 to 7 mM, and 25mM is in hyperglycemic range, which corresponds to severe diabetes. The new Figure 1A shows TMG treatment with physiological glucose conditions. We have included new WB data of 5mM glucose, 5mM glucose + TMG, 25mM glucose, and 25mM glucose + TMG (Figure 1A).

To understand the impact of the environment (in this study: extracellular glucose level) on the epigenome, one should keep in mind the variation of cytosine methylation patterns between individuals and over time. A recent large-scale profiling of DNA methylation of 137 individuals shows a near absence of individual variation between replicates of the same cell type, suggesting that genomic methylation patterns are largely insensitive to the environment (https://doi.org/10.1038/s41586-022-05580-6).

Comparative methylomes of healthy and diabetic individuals are needed to examine the medical significance of the findings presented here. It is possible that the modulation of DNMT1 activity by O-GlcNAc modification is relevant for a specific cell type or developmental stage that remains to be discovered.

We thank the reviewer for the suggestion. While the present study is focused on the functional impact of glucose concentrations on O-GlcNAcylation of DNMT1, the extension of this work to diabetic individuals is a goal for a follow up project.

Reviewer #2 (Public Review):

I've read the manuscript by Shin et al with great interest. The authors describe the identification of O-GlcNAcylation of DNMT1 and the impact this modification has on the maintenance activity of DNMT1 genome-wide and that modification of S878 leads to enzyme inhibition. The manuscript is written in a clear and understandable way making it easy for the reader to understand the logic as well as the steps of the experimental approach.

The authors identify O-GlcNAcylation of DNMT1 in a number of different cell lines by combining inhibition studies and WB and further on they identify the modification sites with LC/MS, predictions, and mutational studies. I really like the experimental approach, which while being straightforward (albeit technically challenging), is powerful and well-controlled in this case to unequivocally prove the modification of DNMT1 and identify the site. However, mutation of the two identified modification sites does not remove all the O-GlcNAcylation signal associated with DNMT1, thus possibly not all the possible sites were identified. While this is not a criticism of this manuscript, it would be interesting to know what other sites are modified and the enzymatic/biological effects associated.

We completely agree with the reviewer. As the O-GlcNAc band was also detected in double mutated DNMT1 (Figure 2D), it is expected that undetected O-GlcNAcylated sites will exist. This is a limitation of current MS analysis and is known to be difficult to detect in the case of modified sites located at both 5’- and 3’- ends of the protein or around the site cut by endoprotease such as trypsin. In follow up work we plan to detect more diverse O-GlcNAc modified sites using more types of endoproteases and observe changes in the phenotype of various cells accordingly.

Also, the authors isolate the modified DNMT1 from cells using immunoprecipitation, which is indeed useful to study the changes in catalytic activity but does not provide any information if the cellular localisation of modified DNMT1 changes.

We apologize for this oversight. We have added a DNMT1 localization assay via immunofluorescence (IF) in the revised manuscript (Figure 3—figure supplement 3). We found no difference in DNMT1 localization between wild type and S878A mutants.

Subsequently, the authors checked the impact of high glucose diet on the genome-wide DNA methylation patterns. The observed effects (Fig 4A) are very strong, almost as strong as observed with Aza treatment and therefore I wonder if LINE/IAP or other elements are getting activated (as observed with genome-wide demethylation with Aza).

We thank the reviewer for the suggestion. Changes in methylation of LINE-1 by hyperglycemia condition are displayed in Figure 4—figure supplement 4. In the case of LINE-1, DNA methylation is lost globally in hyperglycemia conditions. While beyond the scope of this study, a more thorough examination of the impact of the observed loss of methylation under high glucose conditions is of interest.

Do the authors see any changes in cell phenotype, slower/faster proliferation, or increased apoptosis due to the activation of mobile elements (not only ROS)?

This is also a very interesting idea. We plan on further investigating this as part of a follow up study.

Another point is that the S878A mutant seems not to be able to fully maintain the DNA methylation (Fig 4A). Does O-GlcNAcylation recruit any additional interactors? Given that the authors immunoprecipitated DNMT1 and use it for activity assay, it is possible, that the modification attracts an additional protein factor that could in turn inhibit DNMT1 activity (as observed). Therefore, the observed kinetic effect could be indirect, while still interesting and important, the mechanism of inhibition would be different.

We thank the reviewer for the great suggestions. According to Figure 4A, in the case of mutated DNMT1, a slight methylation loss appears to occur in both conditions. There could be for a number of reasons. It may be due to interacting proteins or it may be caused by some damage of DNMT1 itself. A further investigation of this is planned as a follow up project.

DNA methylation clock can be used to estimate the biological age of a tissue/cells. While not directly in the line of the manuscript, I was wondering if the DNA methylation changes in the high glucose diet would affect the methylation sites used for the DNAme clock. Meaning, would the cells/tissue epigenetically age faster when in high glucose media, and if the Ala mutant could provide resistance to that?

We thank the reviewer for the interesting suggestion. We believe this is beyond the scope of this manuscript, but we'll consider this with interest in the future.

In discussion, the authors write that this is the first investigation of O-GlcNAcylation in relation to DNA methylation, while this is true for DNMTs, TET enzymes, that oxidise 5mC and trigger active DNA demethylation have been shown before to also be modified.

We have toned down the language throughout the revised manuscript. This is the first investigation into the maintenance of DNA methylation. Although there is a great deal of evidence regarding the important regulatory role of O-GlcNAcylation in gene regulation, a direct link with maintenance of DNA methylation has not previously been established.

A nice and rigorous study, with important observations and connections to biological effects. It would be nice to prove that the effects are direct and not associated with other factors that could be recruited by the modification and impact the activity of DNMT1. I find it a bit surprising that phosphorylation of the target serine does not impact DNMT1 activity as well.

We thank the reviewer for the positive comments and agree that there are many interesting avenues to follow up on this.

Reviewer #3 (Public Review):

The authors investigate the potential effect of OGlcNacylation on the activity of the DNA methyltransferase DNMT1.

Some results that are convincingly obtained include:

• There is more overall OGlcNacylation when Glucose concentration in the culture medium or the feed is high;

• DNMT1 is OGlcNacylated, and more so in high glucose or on rich chow;

• The position S878 can be OGlcNacylated;

• The activity of transfected DNMT1 is decreased in high glucose conditions. This effect is lessened when S878 is mutated to A or D.

Some results that are suggested but not fully backed by experimental data include:

• This process happens to the endogenous protein under physiologically relevant conditions;

We agree that we could not completely rule out endogenous DNMT1 in our experiments. We have adjusted the language in the revised manuscript to acknowledge this. However, we confirmed the change in activity of recombinant DNMT1 (Figure 3D), and also demonstrated the change in activity under physiological conditions (normal physiological glucose level vs hyperglycemic range) in Figure 3—figure supplement 1B. This is a result that directly shows that the activity of DNMT1 changes under physiological conditions. In addition, DNA hypomethylation due to high glucose has been previously reported, already (Kandilya et al., 2020; Lan et al., 2016). Our results suggest a possible mechanism for this.

Kandilya, D., Shyamasundar, S., Singh, D.K., Banik, A., Hande, M.P., Stunkel, W., Chong, Y.S., and Dheen, S.T. (2020). High glucose alters the DNA methylation pattern of neurodevelopment associated genes in human neural progenitor cells in vitro. Sci Rep 10, 15676.

Lan, C.C., Huang, S.M., Wu, C.S., Wu, C.H., and Chen, G.S. (2016). High-glucose environment increased thrombospondin-1 expression in keratinocytes via DNA hypomethylation. Transl Res 169, 91-101 e101-103.

• This process is responsible for changes in DNA methylation, leading to changes in gene expression, leading to increased ROS and increased apoptosis.

We confirmed that ROS levels increased under high glucose conditions through DCFH-DA fluorescence experiments (Figure 5A). In addition, γH2A.X fluorescence experiments showed that DNA damage was increased under high glucose conditions (Fig. 5B). On the other hand, in the case of the S878A mutant, DNA damage was reduced under hyperglycemic conditions compared to wild type DNMT1 despite an increase in ROS levels (Fig. 5B). Moreover, we verified that the DNA damage did not come from oxidative stress through 8-OHdG analysis (Figure 5—figure supplement 4). Therefore, DNA oxidative stress is suppressed by DNMT1 due to the increase of ROS under high glucose conditions. However, the reduction of DNA methylation by O-GlcNAcylation of DNMT1 induces apoptosis due to oxidative stress.

Studying the connection between cellular metabolism and epigenetic phenomena is interesting. However, I feel that the article falls short of its aims because of the limits of the experimental system, some missing controls, and some data overinterpretation.

We hope the reviewer finds our revised manuscript more suitable.

Author Response

Reviewer #1 (Public Review):

Overall, this manuscript exposes key gaps in patient care resulting from the pandemic, as well as the challenges and unmet needs felt by healthcare workers in cervical cancer screening. The authors’ findings on the struggles while regaining screening volume across the nation in a sustainable way, demonstrate that pre-existing weaknesses in the cancer control system were exacerbated by the pandemic and are integral to amend. The authors were able to identify these gaps in care and work environments through their synthesis of qualitative interviews. I applaud the use of such mixed methods, which emphasizes the complementary need for both quantitative and qualitative data. What could be better strengthened in the manuscript is the authors’ justification for statistical analyses within the context of the research question, and reporting of survey administration and management.

The authors thank the reviewer for a thorough assessment of the manuscript. We have addressed the reviewer’s concerns regarding justification of statistical analyses in the Data Analysis, Quantitative survey data section, and reporting of survey administration and management in the Results, Quantitative survey data section.

Reviewer #2 (Public Review):

Fuzzell et al. conducted a mixed-method study looking into the possible impact of COVID-19 on clinician perceptions of cervical cancer screening. The authors examined how the pandemic-related staffing changes might have affected the screening and abnormal results follow-up during the period October 2021 through July 2022.

They found that 80% of the clinicians experienced decreased screening during the start of the pandemic and that ≈67% reported a return to pre-pandemic levels. The general barriers for not returning to pre-pandemic levels were staffing shortages and problems with structural systems for tracking overdue patients and those in need of follow-up after abnormal screening tests.

Strengths:

There is a high focus on the consequences and the need for action to prevent the ongoing impact of COVID-19 on cervical cancer screening. Some of the actions mentioned by the authors could be the use of HPV self-sampling kits, and it is interesting to be provided knowledge on the clinicians' views on HPV self-sampling. Both are of high interest to the general population in the US. Throughout the discussion, the authors and their claims are supported by other studies.

Weaknesses:

The lack of a National representative sample, where 63% of the responding clinicians were practicing in the Northeast, affects the possibility of generalization of the results found in the study. The overrepresentation of white females is not addressed in the discussion. This composition could have affected the results, especially when the authors report a need to look at higher salaries and better childcare to maintain adequate staffing.

The conclusions are mostly supported by the data, however, some aspects of the data analysis need to be clarified.

We thank the reviewer for their constructive feedback. Despite our best efforts, we were unable to recruit a sample more representative of all US regions. We note this limitation in the discussion: “Notwithstanding efforts to achieve a regionally diverse sample, 63% of responding clinicians were practicing in the Northeast at the time of their participation. Given that COVID-19 policies varied widely by state, this regional imbalance may limit the generalizability of our results. Despite the oversample of clinicians in the Northeast, region was not a significant predictor of either outcome.” Also, we acknowledge the high enrollment of White women in our provider sample and now address this point in the discussion: “Similarly, our sample was 85% female and 70% White. Although ideally we would have included a sample that was more diverse with respect to race and gender, these characteristics are not disparate from the majority of clinicians who perform cervical cancer screening (e.g., race: Women’s Health NPs [77% White], active Ob/Gyns [67% White], all active physicians [64% White]; gender: all NPs [92% female], Ob/Gyns [64% female], all active physicians [37% female]).” Data describing these characteristics are reported in the Association of American Medical Colleges (AAMC) 2022 Physician Specialty Data Report and Executive Summary, the 2018 NPWH Women’s Health Nurse Practitioner Workforce Demographics and Compensation Survey: Highlights Report, and a published paper describing the characteristics of nurse practitioners in the US, which are cited in text.

Reviewer #3 (Public Review):

This US study presents findings from an online survey and in-person interviews of healthcare providers regarding themes associated with cervical screening in federally qualified health centres (FQHCs). The study provides insights during the post-acute phase of the pandemic into a range of areas, including perceived changes in the provision of cervical cancer screening services and the impact of the pandemic, staffing and systems barriers to cervical cancer screening, strategies for tracking missed screens and catch-ups, follow-up of abnormal screening results, as well as attitudes towards HPV self-sampling. Results indicate persisting pandemic-related impacts on patient engagement and staffing, as well as system barriers to effective screening, catch-up of missed screens and follow-ups. Taken together, these issues may lead to increases in cervical cancer in the long-term in populations serviced by these centres, if measures are not taken to adequately support them. Participants were recruited from various regions in the US, however, the study was not conducted using a nationally-representative sample. Although highlighted issues are informative, findings cannot be generalised and larger studies are warranted in the future to monitor cervical screening provision and outcomes in FQHCs.

We thank the reviewer for their thorough assessment of the manuscript. In the discussion, we have made sure to note the non-nationally representative sample and need for continued monitoring of cervical cancer screening and related outcomes in underserved settings and communities.

Author Response

Reviewer #2 (Public review):

1) The systematic review includes data from some studies where PCOS is self-reported. While self-reported PCOS information has been found to be largely sensitive and specific, it would be of interest to know if prevalence ratios of mental health-related were impacted by self-reporting.

Thank you for your insightful comment regarding the potential impact of self-reporting on the prevalence ratios of mental health-related outcomes in women with PCOS. We agree that this is an important factor to consider.

In response, we have revisited all the studies included in our review. We have updated Supplemental Tables 2-4 to provide greater transparency and understanding. These revised tables now include a new column specifying the mental health assessment method used in each study. This update should allow for a more nuanced interpretation of the results, taking into account the potential impact of self-reporting.

Furthermore, we conducted a sensitivity analysis by rerunning the meta-analysis to discern the potential influence of self-reported PCOS on our results, excluding the studies that relied solely on self-reported PCOS diagnosis. After we excluded studies where PCOS was self-reported, the point estimate for anxiety was similar whereas point estimates for depression and eating disorder were slightly higher but none of the estimates were different beyond chance compared to the original analysis. We believe these steps significantly strengthen the clarity and robustness of our findings (Line 314; Supplemental Tables 7 and 8).

2) Likewise, the screening vs self-reported nature of the mental health disorders is not clear from the information included in the characteristics table.

We have modified our Supplemental Tables 2-5 to include a column detailing the method of ‘Mental Health Assessment’. We should note that the majority of the studies directly assessed mental health using a variety of validated questionnaires. We have also included in the Discussion a section emphasizing that some of the studies included in the review relied on self-reported PCOS diagnosis and its potential impact. We also highlighted that while self-reported information is generally reliable, it is subject to potential bias that could impact the prevalence ratios of mental health-related conditions (Line 460).

3) Calculated prevalence ratios were compared with prevalence values for the general population to determine the excess prevalence. However, the source of these general population statistics (i.e., whether these figures come from the control data in the included studies or other sources) is not clear.

Thank you for raising this important point. We have now clarified in our Methods section that the general population statistics used for determining excess prevalence were derived from the control data in the included studies. We hope this provides the necessary transparency for our approach in calculating and interpreting the prevalence ratios (Line 210).

4) The estimated costs for anxiety-, depression- and eating disorder-related care are accessed in published papers and used to calculate the excess costs. Conclusions would be strengthened by a defence of these figures, particularly for anxiety where the source paper is from 1999.

Thank you for your insightful comment. We agree that providing a justification for our choice of cost estimates, especially for the anxiety care cost from a 1999 study, would strengthen our conclusions. The 1999 source was selected because it is a seminal study that offers a comprehensive breakdown of anxiety-related care costs. Despite its age, this paper is often cited in contemporary research due to its rigorous methodology and the granularity of its cost analysis. Adjusted for inflation, its findings still provide an insightful comparison point for current data. To ensure that these figures accurately represent present-day costs, we have adjusted them for inflation using the medical care inflation calculator. Our choice of these specific studies was based on their rigorous methodology, the detailed breakdown of costs, and their relevance to our targeted age groups. The aforementioned adjustments and justifications ensure that these figures aptly represent the present-day costs of treating these conditions.

Similarly, the 2021 papers on depression and eating disorders present comprehensive and up-to-date analyses of the economic burdens associated with these conditions. These papers were selected for their rigorous methodologies, comprehensive cost breakdowns, and alignment with our age-specific focus. The Greenberg et al. (2021) paper, for example, is an authoritative source that provides detailed analysis on the economic burden of adults with major depressive disorder. Likewise, the paper by Streatfeild et al. (2021) offers a meticulous investigation into the socio-economic cost of eating disorders in the U.S., making it an apt choice for our study. We recognize the necessity of providing a robust justification for our choice of these particular papers, and we have endeavored to do so in our Methods section, thus reinforcing the transparency of our approach. We have clarified this in our Methods section to make our approach more transparent to readers (Line 225).

5) An inflation tool is used to adjust the figure, but this does not take into account changes in treatment or practice since this estimate was made. The accuracy of these estimated figures is central to the final conclusions.

Thank you for your valuable comment. We do note that the inflation figures used are a healthcare-specific inflation factor, as healthcare inflation differs from general consumer inflation. However, we agree that the inflation-adjusted figures do not necessarily account for changes in treatment practices since the original estimate was made, assuming these changes would alter the cost of care. We have added a discussion of this limitation in our manuscript and proposed future studies to validate these estimates using more recent data (Line 473).

Author Response

Reviewer #1 (Public Review):

GSK3 is a multi-tasking kinase that recognises primed (i.e. phosphorylated) substrates. One of the mechanisms by which the activity of GSK3 can be regulated is through N-terminal (pSer9) phosphorylation. In this case, the phosphorylated N-terminus turns into a pseudo-substrate that occupies the substrate binding pocket and thus inhibits the activity of GSK3 towards its real substrates.

One outstanding question is how this autoinhibitory mechanism can affect some, but not all signaling pathways that GSK3 is involved in. One example is WNT/CTNNB1 signaling. Here, GSK3 plays a central role in the turnover of CTNNB1 in the absence of WNT, but this pool of GSK3 is not affected by pSer9 phosphorylation.

Gavagan et al. address this question using an in vitro approach with purified proteins. They identify a role for AXIN1 in protecting the "WNT signaling pool" of GSK3 from the auto- inhibition that occurs upon pSer9 phosphorylation.

Specifically, they show that i) GSK3-pSer9 is less capable of binding and phosphorylating primed CTNNB1 - thus suggesting that GSK3-pSer9 does not contribute to WNT signaling, ii) in the presence of AXIN1, GSK3-pSer9 becomes more capable of binding and phosphorylating CTNNB1 - suggesting that Axin can promote binding of GSK3 and CTNNB1 even when the primed binding pocket on GSK3 is blocked initially, iii) AXIN1 specifically prevents the PKA mediated phosphorylation of GSK3B on pSer9 - while leaving the phosphorylation of other PKA substrates unaffected.

Strengths:

• The authors use an in vitro system in which they can reconstitute different interactions and reactions using purified proteins, thus allowing them to zoom in on specific biochemical events in isolation.

• The authors measure the phosphorylation of primed substrates (pSer45-CTNNB1 or WNT- independent substrates) and quantify specific kinetic parameters (kcat, KM, and kcat/KM) - of wildtype non-phosphorylated GSK3B, pSer9GSK3B, or the non-phosphorylatable S9A-GSK3B, either in the presence or absence of AXIN1 (or an AXIN1 fragment).

• The experiments appear to be well-controlled and the results appear to be interpreted correctly.

Weaknesses:

• Key experiments (e.g. Figures 2 and 3) are described as being performed as n=3 technical replicates rather than independent/biological replicates.

We suggest that the replicates described in our work can properly be described as biological replicates, and we have updated the manuscript accordingly. We apologize for the confusion and elaborate on our reasoning below.

Each replicate reported for our in vitro kinetic assays is an independent reaction prepared in a separate reaction vessel, and replicates were analyzed on separate gels. Thus, each reaction is a distinct biological sample and should have been described as a biological replicate. A technical replicate would have been repeat measurements of the same timepoint from a single reaction.

Our original description as technical replicates was based on the notion that each replicate came from the same protein purification (biological sample). However, an analogy to cell culture experiments can illustrate why our initial reasoning was incorrect. In a cell culture experiment, cells from the same initial source are typically split into independent wells for biological replicates. Similarly, our proteins come from the same initial source but are split into independent reaction vessels for biological replicates.

The critical point is that, regardless of the precise terminology, our replicates capture the variability between independent experiments.

• The validation in a biologically relevant setting (i.e. a cellular context) is limited to Figure 4C, which shows that over-expression of AXIN1 reduces the total levels of pSer9-GSK3.

The biochemical experiments presented in our work address a critical gap in the signaling field and, together with the in vivo validation in Figure 4C, establish a model that was previously speculative. We suggest that further in vivo experiments are beyond the scope of the current manuscript.

The authors convincingly show that AXIN1 can play a role in shielding GSK3 from auto- inhibition. As it stands, the impact of this work on the field of WNT/CTNNB1 signaling is likely to remain limited. This is mainly due to the reason that the mechanism by which AXIN1 shields the WNT/CTNNB1 signaling pool of GSK3 from pSer9 inhibition remains unresolved. Based on the fact that a mini AXIN1 (i.e. an AXIN1 fragment) behaves the same as WT AXIN1, the authors conclude that AXIN1 likely causes allosteric changes on GSK3 but is less likely to block PKA from binding. They cannot conclusively show this, however, as they do not have evidence in favour of one or the other explanation.

We thank the reviewer for this important comment which details the central concern raised in the review process. To address this point, we have collected additional biochemical data that conclusively shows that the Axin shielding effect is allosteric and not a steric block. We demonstrated that a minimal, 27 amino acid Axin peptide produces the same GSK3β shielding behavior as full length Axin and miniAxin. The minimal Axin peptide does not sterically occlude the GSK3β phosphorylation site. This data is included in a revised Fig 4A and described on lines 115-120 of the revised manuscript.

However, this study does offer more insight into the compartmentalisation of GSK3 and the quantitative parameters may be used in computational models describing the different cellular activities of GSK3.

This work also has conceptual significance: Scaffold proteins are known to promote signal transduction by bringing proteins together (often: kinases and substrates). Here, Gavagan et al. show that AXIN1 also plays a second role, namely in protecting one of its binding kinases (GSK3) from inhibitory signals. This could potentially hold for other scaffolding proteins as well.

Reviewer #2 (Public Review):

Gavagan et al. investigated the role of the scaffolding protein, Axin, in the cross-pathway inhibition of GSK3b. The authors utilize reconstituted Axin, b-catenin, GSK3b, and protein kinase A to test 2 models. In the first model, the formation of the complex consisting of Axin, b-catenin, and GSK3b overcomes inhibitory phosphorylation of serine 9 of GSK3b. In the second model, the binding of Axin to GSK3b inhibits serine 9 phosphorylation through allosteric effects. Previous literature has established that the phosphorylation of serine 9 of GSK3b inhibits its kinase activity. To provide a quantitative measure of inhibition, the authors determine the binding affinity and catalytic efficiency of GSK3b in comparison to GSK3b phosphoS9 towards b-catenin. Interestingly, the data demonstrate a 200-fold decrease in Kcat/Km and 7 fold increase in Km. It is unclear why serine 9 mutation to alanine increases the rate of B-catenin phosphorylation more than the GSK unphosphorylated protein in figure S10.

We thank the reviewer for catching this inconsistency. In the Michaelis-Menten plots presented in the main text (Figure 2 & Figure 3D), rates for unphosphorylated GSK3β and GSK3β_S9A are indistinguishable. These plots were used to determine the kinetic parameters reported in Table S1 (now Supplementary file 1a). The purpose of Figure S10 (now Figure 2-figure supplement 8) was to confirm that these reactions were first order (linear) in enzyme concentration, but the reviewer is correct to flag the inconsistency in absolute rates. In Figure S10A (now Figure 2-figure supplement 8A), the rates for unphosphorylated GSK3β were ~2-3-fold lower than expected.

We have reanalyzed the original frozen reaction timepoints on new western blots. The results were identical for unphosphorylated GSK3β and GSK3β_S9A, resolving the apparent discrepancy. Upon review of the original western blot images, we noted that they were relatively noisy, potentially indicating incomplete blot transfer or an antibody going bad. Because we were able to reanalyze the original samples and obtained internally consistent results, we suggest that the updated data should replace the original data. The updated data are included in a revised Figure S10A (now Figure 2-figure supplement 8A).

Next, the authors tested if the addition of Axin could overcome this inhibition. Although the addition of Axin decreases the Km, thereby producing a 20-fold increase in catalytic efficiency, the addition of Axin does not rescue the catalytic turnover of the phosphorylated GSK3b. Hence, the authors propose that Axin does not rescue the kinase activity of GSK3b from the inhibitory effects of serine 9 phosphorylation.

Next, the authors test if Axin protects GSK3b from phosphorylation by the upstream kinase PKA. Excitingly, the data show a decrease in binding affinity and catalytic efficiency of PKA with GSK3b phosphoS9 in comparison to GSK3b. The binding of Axin inhibits GSK3b serine 9 phosphorylation by PKA but does not inhibit the phosphorylation of other PKA substrates such as Creb. The authors demonstrate that a fragment of Axin, residues 384-518, behaves similarly to the full-length Axin to shield GSK3b from phosphorylation. However, it is unclear how this fragment may bind in the destruction complex and if Axin has allosteric effects on GSK3b.

Author Response

Reviewer #1 (Public Review):

Various parts of the premotor cortex have been implicated in choices underlying decisionmaking tasks. Further, norepinephrine has been implicated in modulating behavior during various decision-making tasks. Less work has been done on how noradrenergic modulation would affect M2 activity to alter decision-making, nor is it clear whether noradrenergic modulation effects on activity would differ between the male and female sexes.

This manuscript addresses some of these questions.

• In particular, clear sex differences in task engagement are seen.

• May also show some interesting differences and distributions of β2 adrenergic receptors in M2 between males and females.

We thank the reviewer for their summary of our findings and thoughtful critique of our manuscript. In our revised manuscript we have taken measures to address the reviewer’s comments in line (blue edits in text and revised figures) with direct responses outlined below. We believe these revisions improve the scientific rigor of our findings and provide relevant context for our studies. We hope that they have sufficiently addressed the reviewer’s concerns.

Less clear is the specificity of systemic antagonism of β adrenergic receptors on the changes in M2 activity reported. As propranolol was given systemically, changes in M2 firing rates could also be due to broader circuit (indirect) activity changes. As it was not given locally, nor were local receptor populations manipulated, one is unable to make the conclusion that changes in neural activity are due to the direct effects of adrenergic receptors within M2 populations.

We agree that propranolol driven changes in anterior M2 activity may arise via multiple mechanisms, including direct action on the adrenoreceptors within M2, and indirect action via other regions that project to M2. Although locally activating inhibitory interneurons within M2 is sufficient to disrupt cueguided action plans and behavior in a 2AFC task (Inagaki et al., 2018), our noradrenergic manipulation was not restricted to M2. We have clarified our conclusions and provided additional discussion to highlight that propranolol actions were multifaceted and that direct actions in M2 are likely working in concert with propranolol mediated actions in other regions.

Also not clear, is the contribution of M2 to this task, and whether the changes in M2 activity patterns observed are directly responsible for the behavioral disruptions measured.

We have revised our introduction and discussion to more clearly outline the critical role of cue-guided action plans in M2 for successful behavior in 2AFC tasks. Suppression of cue-guided activity in M2 results in behavioral performance at near chance levels, similar to what we saw in females after propranolol (Guo et al., 2017; Inagaki et al., 2018; Li et al., 2016). Furthermore, targeted photostimulation of action plan encoding neurons in M2 is sufficient to drive behavioral responses (Daie et al., 2021). In our investigations it is plausible to expect propranolol related disruptions in other cognitive, sensory or motor regions. Based on the strong foundational evidence for M2 activity in 2AFC, the propranolol driven changes in anterior M2 in females, whether direct or indirectly mediated, are likely sufficient to drive behavioral disruptions in accuracy and/or trial completion.

Reviewer #2 (Public Review):

This paper by Rodbarg et al describes an interesting study on the role of beta noradrenergic receptors in action-related activity in the premotor cortex of behaving rats. This work is precious because even if the action of neuromodulatory systems in the cortex is thought to be critical for cognition, there is very little data to actually substantiate the theories. The study is well conducted and the paper is well written. I think, however, that the paper could benefit from several modifications since I can see 3 major issues:

We thank the reviewer for their generous comments on the potential impact of our manuscript as well as their suggestions to improve this work. Below we outline responses to specific comments raised by the reviewer in addition to adresing them in the revised manuscript. We hope these responses sufficiently address the reviewer’s concerns.

Both from a theoretical and from a practical point of view, the emphasis on 'cue-related' activity and the potential influence of NA on sensory processing is problematic. First, recent studies in rodents and primates have clearly demonstrated that LC activation is more closely related to actions than to stimulus processing (see Poe et al, 2020 for review).

Indeed during optimal performance the peaks of LC activity are larger when PETH are aligned to action initiation rather than the cue itself (Clayton et al., 2004). This alignment resolves variability in decision processing times and omitted cues. Although LC responses align with action they are evoked by, and occur after, cue presentation with LC responses to visual cues occurring ~ 60ms after presentation (Aston-Jones & Bloom, 1981). The same behavioral action without preceding task relevant cues does not evoke an LC response (Rajkowski et al., 2004)

In our current study cues initiate activity in anterior M2, this is our primary interest and where our electrodes are placed. The window between cue delivery and action completion hones in on our goal of investigating the role for β noradrenergic signaling in target cortical processing, rather than LC explicitly. In both NHP and rodents NE signaling (and evoked LC) promotes sustained cortical representations between cue onset and actions across cortical regions (dlPFC, S1) (Ramos & Arnsten, 2007; Vazey et al., 2018; Wang et al., 2007). In the current study we aligned neural data to either cue presentation (Figure 3) or action (lever press; Figure 4). Both presentations support a critical role for β adrenoreceptor signaling in suppressing irrelevant information, resolving and maintaining action plans. A unique feature of aligning the data to cue onset is that it allows us to see how the neural activity changes not only on completed trials (that end with a lever press) but also on omitted trials (which strongly increase after propranolol). We propose the reason we are seeing large increases in omitted trials is because β adrenoreceptor blockade either directly or indirectly prevents anterior M2 from resolving an action plan.

Second, the analysis of neural activity around cue onset should be examined with spikes aligned on the action, since M2 is a motor region and raster plots suggest that activity is strongly related to action (I'll be more specific below).

We agree that M2 shows important action plan activity which we highlight throughout the manuscript. In cued tasks, M2 neurons have been shown to represent action plans starting at cue onset that continues up to behavioral execution. Neural data was examined and results presented aligned to cue onset (illustrated in Figure 3) and aligned to action - lever press (illustrated in Figure 4). The impact of propranolol in diminishing action plan selection was similar in both action, and cue-aligned analyses.

The distinction between neural activity and behavior or cognition is not always clear. I understand that spike count can be related to motor preparation or decision, but it should not be taken for granted that neuronal activity is action planning. The analysis should be clarified and the relation between neural activity, behavior, and potential hidden cognitive operations should be explicated more clearly.

We have worked to clarify in our revised introduction, results and discussion the specifics of the known roles of neural activity in M2 in both action planning and decision making. We further expand that the neuronal activity in our study may reflect potential changes in cognitive processing and thus alter resultant behavioral outcomes.

The sex difference is interesting, but at the moment it seems anecdotal. From a theoretical point of view, is there any ecological/ biological reason for a sex dependency of noradrenergic modulation of the cortex? Is there any background literature on sex differences in motor functions in rats, or in terms of NA action? If not, why does it matter (how does it change the way we should interpret the data?) From a practical point of view, is there a functional sex difference in absence of treatment, or is it that the drug has a distinct effect on males vs females? This has very distinct consequences, I think.

We did not find overt differences in behavior in the absence of treatment. Only when noradrenergic function was challenged using propranolol did we identify functional sex differences. We agree that this has very distinct consequences – specifically it supports sex differences that can be revealed by perturbations of normal function. These functional sex differences may be a result of differences in the anatomy of central noradrenergic systems, a hypothesis further supported by our mRNA expression findings and existing literature on LC anatomy across species (Bangasser et al., 2011, 2016; Luque et al., 1992; Mulvey et al., 2018; Ohm et al., 1997; Pinos et al., 2001). Collectively these results have potential ramifications for understanding sex differences in disease prevalence and targeted treatments.

Background literature supports some innate sex differences in motor function and executive function in rodents and humans. Of particular relevance to our investigation is an established difference in behavioral strategy with females being more risk averse than males (Grissom & Reyes, 2019). Ethologically risk adverse strategies may support parental care roles, and increased inhibitory mechanisms may be selected for in females. Although this strategy was not directly tested in our study, the large increase in omissions after propranolol seen in females is in line with avoiding risk (incorrect choices) during uncertainty (disrupted neural signaling). As with other executive functions, the utilization of norepinephrine within the cortex along with other neuromodulators, and local microcircuit interactions would all contribute to promoting risk averse behavior.

These issues could be clarified both in the introduction and in the discussion, but the authors might have a different view on what is theoretically relevant here. In the result section, however, I think that both the lack of specificity in the description of behavior and cognitive operation and the confusion between 'sensory' and 'motor' functions make it very difficult to figure out what is going on in these experiments, both at a behavioral and at a neurophysiological level. First, the description of the behavior in the task is clearly not sufficient, which makes the interpretation of the measures very difficult.

We have made an effort to better specify the task and relevant behavioral operations in both the methods and results and have included a clearer task schematic (Figure 1A). We agree that the confusion between ‘sensory’ and ‘motor’ functions may make it more difficult to understand the findings in this study. Anterior M2 plays a unique role in representing motor/action plans that can be informed by sensory information. This integrative function creates difficulty in parsing the neural activity of anterior M2 as strictly motor, sensory or cognitive. In attempts to improve clarity we have expanded and highlighted relevant information on the known roles of M2 in the introduction and discussion.

One possible interpretation of the effects of the drug is a decrease in motivation, for instance, due to a decrease in reward sensitivity or an increase in sensitivity to effort. But there are others. More importantly, none of these measures can be used to tease apart action preparation from action execution, even though the study is supposed to be about the former.

Neural activity during action planning, prior to action execution is known to be an essential function of M2 (Barthas & Kwan, 2017; Gremel & Costa, 2013; Guo et al., 2017; Inagaki et al., 2018, 2022; Li et al., 2016; Siniscalchi et al., 2016; Sul et al., 2011; Wei et al., 2019) for optimal performance in 2AFC tasks. In all, we found that the representation/separation of opposing action plans (a well validated function of M2) prior to responses (lever press) is degraded after propranolol, especially in females. We have provided additional emphasis on these foundational studies throughout our revised manuscript.

To minimize impact of motivational factors, effort and reward size remain consistent within our task, and all trials require a random initiation hold prior to cue delivery. As described in our general response to the editor above (Figure 1, above), we investigated whether motivational changes may be reflected in our M2 recordings. PETHs from the first and last 10 trials within saline sessions did not identify potential motivation related differences in anterior M2 activity. Similarly, across propranolol sessions the neural activity was consistent between early and late trials. We used early and late trials as there was a mild decrease in trial rate during saline sessions in both males and females, potentially indicative of motivation/reward sensitivity changes during these sessions. M2 neural responses consistently separate action plans (after saline) or failed to separate action plans (propranolol sessions).

Also, but this is less critical: In Figures 2C and D, it looks like there is a bimodal distribution for the effect of propranolol in females. Is there something similar in the neuronal effects of the drug? And in the distribution of receptors? Can it be accounted for by hormonal cycles/ anything else?

Although there is some clustering in behavioral outcomes all data passed normality assumption as appropriate. Propranolol treatments were not synchronized to hormonal cycles, and the data likely include animals at various hormonal stages. Similar clustering was not apparent in neuronal effects of propranolol, although propranolol increased variability in many measures.

In a pilot experiment we did not see any difference in baseline performance on our 2AFC task across the hormonal cycle (diestrous, proestrous, estrous or metestrous) of females in any measure including accuracy (F(3,33)=0.59, p=0.63, one-way ANOVA) and omissions (F(3,33)=0.51, p=0.68).

The description of neural activity is also very superficial. In general, it is not clear how spike count measures have been extracted. For example, legend and figure C are not clear, is the (long) period of cue presentation included in the 'decision time'?? "Cues were presented at a variable interval 200-700ms after initiation and until animals left the well, 'Well Exit'. The time from cue onset to well exit was identified as the decision time (yellow)." Yet on the figure only the period after cue presentation is in yellow. This is critical because, given the duration of the cue, the animals are probably capable of deciding (to exit the well) before the cue turns off. Indeed, as shown in fig 2D, the animals can decide within about 500 ms. So to what extent is the 'cue response' actually a 'decision response'?

We have clarified the task and spike count measurements in methods and added a revised task schematic. It is correct that the cues are available throughout the decision time (for up to 5 seconds or until well exit), and an action plan is generated before well exit/cues turn off as reflected by the separation of neural action plans (Fig 3, saline). Anterior M2 neurons maintain action plan representation from cue onset until the lever press under normal conditions (Fig 4, saline). These action plans encapsulate “cue responses” and “decision responses”. We have aligned neural data to discrete timestamps at either end of the window in which M2 processing is known to be critical, specifically between cues and actions (lever press) and focus on neural activity relative to those points. We refer to this activity throughout the manuscript as an ‘action plan’ as action planning functions of M2 activity have been well established in prior studies.

When looking at figure 3A, there is clearly a pattern on the raster, a line going from top left to bottom right. If the trials are sorted chronologically, something is happening over time. If, as I suspect, trials are sorted by ascending response time, this raster is showing that what authors are calling a 'response to cues' is actually a response around action. Basically, if propranolol slows down reaction time, the spikes will be delayed from cue onset only because they remain locked to the action. Then the whole analysis and interpretation need to be reconsidered. But it might be for the best: as I mentioned earlier, recent work on LC activity has clearly emphasized its influence on motor rather than sensory processing (Poe et al, 2020).

Figure 3A is a single neuron example, and data analyses focus on population-wide activity. Neural data is presented both aligned to cues, for all trials in which a cue was received, and aligned to lever press (action), for all trials on which a lever press occurred. In both cases, aligned to cue or aligned to action, the impact of propranolol is the same. β adrenoreceptor blockade reduces the separation of action plans in M2, severely so in females. However, a major finding is that females receive a cue but omit a large number of trials after propranolol, for this outcome the action does not occur. We propose this is due to the lack of action plan separation in anterior M2 (either directly or indirectly). When no behavioral response occurs, these trials cannot be aligned to action, yet we are still interested in the neural activity during the critical window between cue delivery and actions. We are not assigning this neural activity to sensory processing but using this discrete sensory event within our trials (cue) to align the data as there is substantial evidence that action plans in M2 arise after cue presentation in tasks such as ours where performance is guided by external cues.

Fig 2D-F: it is hard to believe that the increase in firing rate induced by propranolol in females is not significant. Presumably, because the range of the median firing rate is so high in the first place, distribution (2E) really indicates an increase in firing. Maybe some other test? e.g paired t.test, or standardized values (z.score) to get rid of variability in firing across neurons?

We agree that the session wide firing rate appears rightward shifted in females after propranolol. As our recordings were taken on different days, several days apart we cannot assume they are the same neurons for paired analyses. In our revised manuscript we evaluated these distributions using a MannWhitney test to increase power and decrease the impact of variability within the population. Previously we had used a Kolmogorov-Smirnov test. Using our new analysis, we can confirm that the propranolol significantly increases session wide firing rates in anterior M2 of females (p=0.027) but not males. This finding increases evidence for direct actions of propranolol within M2 and supports our hypothesis that propranolol leads to local disinhibition by reducing β noradrenergic signaling in interneurons and that without this noradrenergic tone anterior M2 is less efficient at suppressing irrelevant action plans.

Along those lines, would it be worth looking for effects on specific populations (interneurons) which are sometimes characterized by thinner spikes and higher mean firing rates? Given the distribution of beta receptors RNA on interneurons, one would actually expect an effect of propranolol on the firing rate irrespective of task events. Or what is it that prevents the influence of propranolol on interneurons from changing the firing rate? In any case, one of the strengths of this study is the localization of beta receptors on specific neuronal populations in the cortex, so I think that the authors should really try to build on it and find something related to the neurophysiological effects. Otherwise, one cannot exclude the possibility that the behavioral effects are not related to the influence of the drug on these receptors in that region.

Data were collected using stainless steel electrode arrays and our sample population of task related neurons is likely biased to pyramidal neurons, with a small number of fast spiking interneurons. We used validated spike waveform parameters of interneurons in premotor cortex (peak-to-trough ratio and duration; Giordano et al., 2023) in an attempt to isolate putative interneurons and found only a very small number of these cells in our recordings (n=5-7 per group). This population is too small to make any inferences about specific impacts. We have focused on the collective population activity of M2 as this is most strongly related to optimal action planning.

You are correct that from the given findings we cannot conclusively show that the results found here are a result of propranolol acting solely within anterior M2. We have made sure to clarify throughout our revised manuscript that the behavioral and physiological changes we identified are a result of collective direct and indirect actions of propranolol.

The conclusion that neuronal discrimination decreases because the proportion of neurons showing no effect increases is confusing (negative results, basically). It would be clearer if they were reporting the number of neurons that do show an effect, and presumably that this number shows a significant decrease.

The reviewer is correct that the number of neurons that do show an effect (task related activity) does significantly decrease with propranolol (from n=70 to 27 in females and n=71 to 48 in males). These n are now given adjacent to the proportions rather than at the end of the paragraph. Proportions were used for statistical analysis due to an overall decrease in the total number of units after propranolol. All PETH presented are from neurons that show some task related activity, these PETH confirm that neural activity no longer effectively discriminates/separates action plans in M2.

Figs 3F-I: a good proportion of neurons (at least 20%) show a significant encoding before cue onset. How is it possible? This raises the issue of noise level/ null hypothesis for this kind of repeated analysis. How did the author correct for multiple comparison issues?

In response to reviews, we have altered the manner in which we identify the significantly modulated neurons to increase rigor and no longer include these figures or analyses. The proportion of neurons showing action plan encoding prior to cue onset was likely an artifact of how the data was analyzed and an insufficient correction for multiple comparisons, allowing inclusion of internally generated action plans in some neurons.

The description of the action-related activity is globally confusing. Again, how can the authors discriminate between activity related to planning vs action itself? What is significant and what is not, in males vs females? What is being measured here? For example, a very unclear statement on line 238: "Propranolol primarily disrupted active inhibition of irrelevant action selection in M2 activity, reducing the ability to maintain action plan representation in M2, delaying lever press responses (Figure 4L, 4M)." What is 'active inhibition? What is an irrelevant action plan? What is selection? All of that should be defined using objective behavioral criteria and tested formally.

We have changed our wording to clarify what we are describing and why we have chosen the words we have, and to ensure consistency and objectivity throughout the manuscript. Much of the wording we have used – for example action planning or action plan selection, are the words used in the literature to describe M2 neural activity. We call the activity in M2 action planning (either externally/cue guided or internally guided) because that is what has been previously demonstrated. In our task design and analysis we are tracking cue guided actions, as opposed to internally guided.

We also separate the electrophysiology data as preferred and nonpreferred because the literature has shown individual M2 neurons show specific directional tuning as noted in our results, using the term ‘preferred’ encapsulates that tuning regardless of left/right direction. An example M2 neuron that increases activity for left cues and responses (preferred direction), will show active inhibition (low/negative z scores) on trials with right cues and responses (nonpreferred), other neurons would show the inverse relationship with direction.

A primary impact of propranolol was the loss of negative z-scores for nonpreferred trials ie neurons with a left preference that are usually inhibited on right trials were still firing and vice-versa. After propranolol neurons continue to fire for an irrelevant action plan (for the opposite direction), and the resulting population activity is not significantly different for opposing cues/responses. Behavioral responses normally occur after opposing action plans have significantly separated in M2, collapsing action plans by preventing relevant signaling (Guo et al., 2017; Inagaki et al., 2018; Li et al., 2016) or facilitating irrelevant signaling as we see here with propranolol leads impairments in 2AFC performance.

Also, the description of the classifier analysis should be more thorough. Referencing the toolbox is not sufficient to understand what has been done.

We have added additional explanation in both the methods and description of the results to clarify the functions of the neural decoding box and how we are using it to evaluate information encoding within M2. We have provided detail on how the algorithm was trained, how shuffled data was generated and how we determined significance of decoding accuracy.

Measuring Beta adrenoceptors is a great idea, and the results are interesting, especially the difference between neuron types. But again, how does that fit with neurophysiological results? Note, that since this is RNA measures, it should not be phrased as 'receptors' but 'receptors RNA' throughout. One possible interpretation of these anatomical results that cannot be reconciled with physiology is that protein expression at the membrane shows a distinct pattern.

We have changed the references to β receptor expression to β receptor mRNA expression throughout the manuscript. Although mRNA provides a valuable proxy for adrenoreceptor production, as noted by the reviewer protein expression at the membrane may differ. Reliable antibodies that allow quantitative analysis of membrane bound adrenoreceoptors in situ with co-labeling of specific cell types are limited. The goal of assessing mRNA expression within M2 was to determine if the functional sex differences we identified in M2 neurophysiology when manipulating β adrenoreceptor function could be mediated by basal differences in adrenoreceptors. The causal impact of differential mRNA expression in anterior M2 was not directly tested but our findings provide preliminary evidence that adrenoreceptor regulation may differ across sexes. Our results provide a plausible avenue for differential sensitivity to β adrenoreceptor manipulation across sexes, that may also be found in other brain regions.

In conclusion, I think that this is a very interesting study and that the results are potentially relevant for a wide audience. But the paper would clearly benefit from revisions. If the authors could clearly identify a significant relationship between the action of NA on beta receptors on specific cortical neurons, at a physiological and behavioral level, that would be a seminal study. At the moment, the evidence is not convincing enough but the data suggest that it is the case.

We thank the reviewer for the kind remarks. We have undertaken a number of new analyses, refined existing analysis and clarified our claims in the manuscript to improve rigor. Collectively our data reflect that the behavioral and neural deficits after systemic propranolol are likely due to both direct and indirect actions on M2. We believe this work is compelling and that it will inform future work investigating potential sex differences in central noradrenergic anatomy and functional sex differences after perturbations of noradrenergic signaling.

Author Response

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

Reviewer #1 (Public Review):

(1) What's the rationale of trypsinizing the tissue prior to mitochondrial isolation? This is not standard for subsequent proteomics analysis. This step will inevitably cause protein loss, especially for the post mitochondrial fractions (PMF). Treating samples with 0.01ug/uL trypsin for 37oC 30 min is sufficient to partially digest a substantial portion of the proteome. If samples from different subjects were not of the same weight, then this partial digestion step may introduce artificial variability as variable proportions of proteins from different subjects would be lost during this step. In addition, the mitochondrial protein enrichment in the mito fraction, despite statistically significant, does not look striking (Figure 1E, ~30% mitochondrial proteins in the mito fraction). As a comparison, Williams et al., MCP 2018 seem to have obtained high mitochondrial protein content in the mito fraction without trpsinizing the frozen quadriceps using a similar SWATH-MS-based approach.

Trypsinisation of the tissue prior to mitochondrial isolation is based on previous work and a Nature Protocol (1, 2) which isolated mitochondria for skeletal muscle. The rationale is that it aids in mechanical homogenisation from highly fibrous tissues such as quadriceps muscle by digesting extracellular matrix proteins. The trypsin/protein ratio used to aid in this process is at least 400 times lower than the amount of trypsin used for formal proteomic tryptic digestion. Three pieces of evidence suggest this step has negligible effect on downstream proteomic analysis. First, because the trypsinisation buffer is detergent free, trypsin will only affect extracellular or exposed membrane proteins. Filtering our PMF dataset for proteins with ‘extracellular matrix’ gene ontology identifies at least 90 unique extracellular matrix proteins indicating good retention of proteins susceptible to partial digestion. Second, the trypsin dose used is 50 times lower than the concentration used for passaging cultured cells, which retain viability after trypsinisation. Third, and contrary to the point raised by the reviewer, we observe less missingness in PMF samples compared to mitochondrial samples. We thank the reviewer for bringing the Williams et al. 2018 MCP paper to our attention. We note that mitochondrial enrichment between the two papers is comparable (~2- fold). To improve clarity line 408 now reads: “Whole quadriceps muscle samples were prepared as previously described with modification (99, 100). First, tissue was snap frozen with liquid nitrogen…” and line 95 reads: “Mitochondrial proteins were defined based on their presence in MitoCarta 3.0 (24) and consistent with previous work (25) were approximately two-fold enriched in the mitochondrial fraction relative to the PMF (Fig 1E).”

(2) The authors mentioned that the proteomics data were Log2 transformed and median- normalized. Would it be possible to provide a bit more details on this? Were the subjects randomized?

Samples were randomised prior to sample processing and mass spectrometry analysis. Because of possible variation in total protein content, it is critical to normalise protein intensities between samples. Median normalisation adjusts the samples so that they have the same median, thereby accounting for technical variation. Log2 normalisation helps to achieve normal distributions, critical for many downstream statistical tests. Line 471 now reads: “…to achieve normal distributions and account for technical variation in total protein.”

(3) In Figure 1D, what were the numbers of mice the authors used for the CV comparisons in each group? Were they of similar age and sex? Were the differences in CV values statistically significant?

The mitochondrial and PMF proteomes originated from the same quadriceps sample from the same mouse, and thus the age and sex are the same across both proteomes. After quality control, we had mitochondrial proteomes for 194 mice and PMF proteomes for 215 mice. The overall CV in the mitochondrial fraction was significantly greater than in the PMF, however whether the source of this variation is biological, or the result of mitochondrial isolation is unclear and as such we have avoided making a statement within the body of the manuscript. We have now more clearly described the nature of the samples in the revised manuscript and added sample sizes to figure 1F.

(4) The authors stated in lines 155-157 that proteins negatively associated with the Matsuda index were further filtered by presence of their cis-pQTLs. Perhaps more explanations would be needed to justify this filtering criterion? Having a cis-pQTL would mean the protein abundance variation is explained by the variation in its coding gene, this however conceptually would not be relevant to its association with the Matsuda index. With the data that the authors have in hand, would it not be natural to align the Matsuda index QTL with the pQTLs (cis and trans if available), and/or to perform mediation analysis to examine causal relationships with statistical significance?

The rationale for filtering by cis-pQTL was not to study the genetics of either Matsuda or associated proteins but rather to identify proteins that were more likely to be causally associated with Matsuda Index as opposed to adaptively associated. To clarify this line 165 now reads: “Filtering based on cis-pQTL presence was based on the rationale that if genetic variation can explain protein abundance differences between mice, then we can be confident that phenotype (Matsuda Index) is not driving the observed differences and therefore the protein-phenotype associations are likely causal. Importantly, this assumption can only be made for cis-acting pQTLs.” Previous work by Matthew et al. (see https://qtlviewer.jax.org/) has demonstrated that cis-pQTL have markedly higher LOD scores than trans-pQTLs, and our own unpublished work suggests that trans-pQTLs do not reproduce well between datasets. The reviewer rightfully suggests aligning protein QTL with those for Matsuda. This is our long-term goal but to identify genome wide significant peaks associated with altered Matsuda will require many more mice than studied here.

(5) It seems a bit odd that the first half of the paper focused extensively on the authors' discoveries in the mitochondrial proteome, and how proteins involved in mitochondrial processes (such as complex I) were associated with Matsuda Index, but the final fingerprint list of insulin resistance, which contained 76 proteins, only had 7 mitochondrial proteins. Was this because many mitochondrial proteins were filtered out due to no cis-pQTL presenting?

There are three reasons our fingerprint is lacking mitochondrial proteins: 1) there are more non-mitochondrial than mitochondrial proteins in the muscle proteome; 2) we focussed on negatively associated proteins, and as demonstrated in figure 2c, the mitochondrial proteome is enriched for positively associated proteins; 3) as implied by the reviewer, we filtered for pQTL presence, further reducing the number of mitochondrial proteins in our fingerprint. To improve clarity, line 170 now reads: “Low mitochondrial representation in the fingerprint is the result of selecting negatively associating proteins, and as seen (Figure 2C) previously, the mitochondrial proteome is enriched for positive contributors to insulin resistance.”

(6) The authors found that thiostrepton-induced insulin resistance reversal effects were not through insulin signalling. It activated glycolysis but the mechanism of action was not clear. What are the proteins in the fingerprint list that led to identification of thiostrepton on CMAP?

Is thiostrepton able to bind or change the expression of these proteins? Since thiostrepton was identified by searching the insulin resistance fingerprint protein list against CMAP, it would be rational to think that it exerts the biological effects by directly or indirectly acting on these protein targets.

This is indeed the implication of our data. Because of the timescales involved it is unlikely that thiostrepton is changing fingerprint protein levels but could be binding to and inhibiting them. Searching the CMAP thiostrepton signature reveals ARHGDIB and NAGK as the fingerprint proteins with the most positive and negative fold-changes respectively perhaps suggesting they play a role in thiostrepton’s mechanism of action. Experiments are underway to test this hypothesis however these are beyond the scope of the current paper.

Reviewer #2 (Public Review):

Line 105: The observation that variance in respiratory proteins is stable while lipid pathways is variable is quite interesting. Is this due to lower overall levels of lipid metabolism enzymes (ex. do these differ substantially from similar pathways ranked from high-low abundance?).

The relationship between coefficient of variation (CV) and relative abundance of proteins is important to consider. To address this, we have now also performed GSEA on proteins ranked from high to low relative abundance. These comparisons have been added to supplementary figure 1 and line 110 now reads: “As a control experiment, we also performed enrichment analysis on proteins ranked by LFQ relative abundance. High CV pathways (enriched for high CV proteins) tended to be lower in relative abundance (enriched for low relative abundance proteins) (Supplementary Fig 1a, b). However, many high variability pathways, lipid metabolism for example, were not enriched in either direction based on relative abundance suggesting differences in relative abundance do not fully explain pathway variability differences.”

Line 154: the 664 associations are impressive and potentially informative. It would be valuable to know which of these co-map to the same locus - either to distinguish linkage in a 2mb window or identify any cis-proteins which directly exert effects in trans-

To assess this, we have analysed pQTL position relative to gene position to generate a ‘hotspot’ plot. We have also generated a histogram of this pQTL density (in a 2 Mbp window) and added these figures to figure 3. We did not detect any obvious pQTL hotspots, and the distribution of pQTLs across the genome appears fairly uniform. Line 159 now reads: “These were distributed across the genome and were predominately cis acting (Figure 3A)...”

Line 194: Cross-platform validation of the CMAP fingerprint results is an admirable set of validations. It might be good to know general parameters like how many compounds were shared/unique for each platform. Also the concordance between ranking scores for significant and shared compounds.

The Connectivity Map (CMap) query included 5163 compounds, the Prestwick library included 1120, and the overlap was 420. We have added these comparisons to supplementary figure 2. Supplementary figure 2 now also contains a comparison of CMap scores between overlapping compounds (found in CMap and the Prestwick library) against all significant compounds identified by CMap (supplementary figure 2b). Interestingly, compounds present in both platforms scored higher on average, suggesting the Prestwick library captures a significant proportion of highly scoring CMap candidates. Line 206 now reads: “In total, 420 compounds were found across both platforms, and these consensus compounds captured a significant proportion of highly scoring CMap compounds (Supplementary Figure 2A, B).”

Line 319: Another consideration in the molecular fingerprint is how unique these are for muscle. While studies evaluating gene expression have shown that many cis-eQTLs are shared across tissues, to my knowledge, this hasn't been performed systematically for pQTLs. Therefore, consider adding a point to the discussion pointing out that some of the proteins might be conserved pQTLs whereas others which would be more relevant here present unique druggable targets in muscle.

To examine tissue specificity, we determined whether our skeletal muscle fingerprint proteins were detected and contained a pQTL in two metabolically important tissues, liver and adipose. Despite detecting almost all the fingerprint proteins in both adipose and liver tissue, they were depleted for pQTL compared to skeletal muscle. These data have now been added to figure 3c. Line 172 now reads: “To assess the tissue specificity of our fingerprint we searched for the same proteins in metabolically important adipose and liver tissues. Despite detecting 94% and 82% of muscle fingerprint proteins across each tissue respectively, both adipose and liver were depleted for pQTL presence (Figure 3C) suggesting that regulation of our fingerprint protein abundance is specific to skeletal muscle.”

Line 332: These are fascinating observations. 1, that in general insulin signaling and ampk were not themselves shown as top-ranked enrichments with matsuda and that this was sufficient to alter glucose metabolism without changes in these pathways. While further characterization of this signaling mechanism is beyond the scope of this study, it would be good to speculate as to additional signaling pathways that are relevant beyond ROS (ex. CNYP2 and others)

We have now added further discussion to the manuscript to address this point., Line 347 now reads: “Aside from glycolysis, other pathways may be involved in enhancing insulin sensitivity. For example, the negatively associated protein ARHGDIA (Figure 2F) is a potent negative regulator of insulin sensitivity, and our fingerprint of insulin resistance contained its homologue ARHGDIB. Both ARHGDIA and ARHGDIB have been reported to inhibit the insulin action regulator RAC1 thus lowering GLUT4 translocation and glucose uptake. Further investigations may uncover a role for thiostrepton in modulating the RAC1 signalling pathway via ARHGDIB.”

Line: 314: Remove the statement: "While this approach is less powerful than QTL co- localisation for identifying causal drivers,", as I don't believe that this has been demonstrated. Clearly, the authors provide a sufficient framework to pinpoint causality and produce an actionable set of proteins.

We have edited line 314, which now reads: “Moreover, our approach has the major advantage that it requires far fewer mice to obtain meaningful outcomes (222 mice in this study) compared to that required for genetic mapping of complex traits like Matsuda Index.”

Line 346: I would highlight one more appeal of the approach adopted by the authors. Given that these compound libraries were prioritized from patterns of diverse genetics, these observations are inherently more-likely to operate robustly across target backgrounds.

This point is further supported by our thiostrepton results in both C57BL6/j and BXH9 mice. Line 317 now reads: “Furthermore, because we have used genetically diverse datasets (DOz mice and multiple cell lines in Connectivity Map) our findings are likely robust across diverse target backgrounds.”

Line 434: I might have missed but can't seem to find where the muscle data are available to researchers. Given the importance and novelty of these studies, it will be important to provide some way to access the proteomic data.

These data are now available via the ProteomeXchange Consortium. Line 465 now reads: “The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (104) partner repository with the dataset identifier PXD042277.”

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2. Acin-Perez R, Benador IY, Petcherski A, Veliova M, Benavides GA, Lagarrigue S, et al. A novel approach to measure mitochondrial respiration in frozen biological samples. The EMBO Journal. 2020;39(13):e104073.

3. Chick JM, Munger SC, Simecek P, Huttlin EL, Choi K, Gatti DM, et al. Defining the consequences of genetic variation on a proteome-wide scale. Nature. 2016;534(7608):500- 5.

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Author Response

Reviewer #1 (Public Review):

In this study, the authors set out to investigate spatial RNA processing events, specifically alternative splicing and 3' UTR usage, in mouse brain and kidney tissues using ReadZS and SpliZ methodologies on spatial transcriptomics data. The research contributes to understanding tissue-specific gene expression regulation from a spatial perspective. The study introduces a novel approach for analyzing spatial transcriptomics data, allowing for the identification of RNA processing and regulation patterns directly from 10X Visium data. The authors present convincing evidence supporting the identification of novel RNA processing patterns using their methodology, which holds significant implications for researchers in the field of spatial transcriptomics and the study of alternative splicing and 3' UTR usage.

Thank you for this thorough overview of our work.

The conclusions of the study are mostly well-supported by the data; however, certain aspects could be improved to strengthen the findings.

1) The conclusions of this study would be strengthened by conducting a more extensive tissue sample analysis and including biological replicates. Additionally, appropriate batch effect corrections should be applied when dealing with biological replicates.

We agree that including biological replicates would strengthen our findings. We will include biological replicates of the mouse brain tissues in the revision.

2) The 3' UTR usage and alternative splicing should be compared among clearly labeled clusters for a more comprehensive analysis.

We understand that it can be difficult to see how the SpliZ quantiles map spatially onto the tissue images. For the splicing of Gng13, Myl6, and Rps24, we will include box plots broken down by spatial quadrant in the revision. However, this does result in an oversimplification of the spatial patterns found in the tissue slices, which make the plots less informative than the quantile plots to our view.

3) The authors should clarify their rationale for choosing ReadZS and SpliZ approaches and provide comparisons with other methods to demonstrate the advantages and potential limitations of their chosen methodologies.

Thank you for pointing out the lack of sufficient discussion of ReadZS and SpliZ in the manuscript. The ReadZS and SpliZ were chosen for this analysis because both of these methods provide an individual score for each cell-gene pair, which is easily adapted to providing a score for each spot-gene pair. Due to the sparsity and 3’ bias of Visium data, approaches designed to analyze RNA processing in full-length sequencing analysis are not applicable. The SpliZ and ReadZS are two of the limited number of tools available that are designed for the analysis of RNA processing in droplet-based data. Other available tools tend to rely on aggregating data across multiple cells using a method called pseudo-bulking (Li et al., 2021; Patrick et al., 2020). It is not clear how this could be used for spatial transcriptomics data without potentially obscuring subtle spatial patterns in the data. Others are based on PSI measurements, which are vulnerable to artifacts due to sparsity (Buen Abad Najar et al., 2020; Olivieri et al., 2022; Wen et al., 2022). The tradeoff between pseudo-bulking and a single score per spot-gene pair means that the ReadZS and SpliZ do not have the power to detect changes for genes with very low read counts. We will add text in the revision to clarify this point.

Reviewer #2 (Public Review):

The authors applied existing ReadZS and the SpliZ methods, previously developed to analyze RNA process in scRNA-seq data, to Visium data to study spatial splicing and RNA processing events in tissues by Moran's I. The authors showed several example genes in mouse brain and kidney, whose processing are spatially regulated, such as Rps24, Myl6, Gng13.

Thank you for this thorough overview of our work.

The paper touches on an important question in RNA biology about how RNA processing is regulated spatially. Both experimental and computational challenges remain to address it. Despite some potentially interesting findings, most claims remain to be validated by orthogonal methods such as RNA FISH and simulations.

We appreciate that the reviewer finds the question important, and that the findings are potentially interesting. In the revision we will include biological replicates for our findings in the mouse brain. Unfortunately, experimental validation is outside of our budget for this project. It is unclear what further simulations could validate the biological discoveries in this manuscript: permutations were used to calculate the p value of each discovery, and the false positive and negative rates of the SpliZ have been assessed through simulation (Olivieri et al., 2022).

In addition, the percentage of spatial processing events (splicing in 0.8-2.2% of detected genes, i.e. 8-17 genes and RNA processing in 1.1-5.5% of detected genomic windows, i.e. 57-161 windows) discovered is low. Does it suggest that most of RNA processing events were not spatially regulated across the tissue? Or does it question the assumption of treating spatial transcriptomics data similar to scRNA-seq data?

We agree that the question of the prevalence of spatial RNA processing regulation is critical. Rather than the two options proposed here, we believe that the sparsity of the data limits our ability to call more of these events. In the revision, we will provide a supplemental figure showing the relationship between read depth and p value for each gene to quantify how the fraction of observed regulation changes with sequencing depth. It is worth noting that as these technologies improve, we expect the sequencing depth of spatial technologies to increase which would likely result in more discoveries.

The unique features for ST data, such as mixture of neighboring cells, different capture biases and much smaller number of spots (pseudo cells here), may have significant effects on the power of scRNA-seq based methods, but it is not discussed in the manuscript. The lack of careful evaluation and low discovery rates could limit application of the approach to other tissues and subcellular data.

We appreciate the concern that technical differences between scRNA-seq data and spatial transcriptomics data could affect our results. We agree that this point could be addressed more thoroughly in the text. None of the specificities of spatial transcriptomics data invalidate the assumptions of the SpliZ or ReadZS. The method we use to identify genes with significant spatial regulation of RNA processing was specifically created to be used for Visium data. It takes into account mixture of RNAs in neighboring cells by randomly sampling scores of neighboring cells, rather than randomization of the location of the spots themselves, which does indeed result in a high false positive rate (see “Permutations for Moran’s I” in the Methods). We do note that there is a limit to the power of this kind of analysis based on the number of spots and the read depth, which we will quantify in a plot in the revision.

Author Response:

We thank Reviewer #1 for their positive assessment of our work.

Reviewer #2 (Public Review):

[…] Although these results confirm what we already know about processes involved in the meninges in MS and its models and gradients of pathology in sub-pial regions, this is the first to use spatial transcriptomics to demonstrate such gradients at a molecular level in an animal model that demonstrates lymphoid like tissue development in the meninges and associated grey matter pathology. The mouse EAE model being used here does reproduce many, although not all, of the pathological features of MS and the ability to look at longer time points has been exploited well. However, this particular spatial transcriptomics technique cannot resolve at a cellular level and therefore there is a lot of overlap between gene expression signatures in the meninges and the underlying grey matter parenchyma.

We appreciate the reviewer’s concise summary and comments on our manuscript. We agree that the Visium spatial sequencing technology we applied is limited in its resolution and cannot precisely distinguish individual cells or anatomic regions. For that reason, there is undoubtedly some overlap between gene expression signatures in the meninges and underlying parenchyma, particularly in spots on the borders of the meningeal inflammation clusters. However, we believe that the majority of meningeal inflammation (“cluster 11”) spots are indeed in the meninges and represent the spatial transcriptome of that niche. To support this, in the revised manuscript we will provide H&E images with the UMAP clusters overlayed to demonstrate the anatomic borders that correlate with the clusters.

The short nature of this report means that the results are presented and discussed in a vague way, without enough molecular detail to reveal much information about molecular pathogenetic mechanisms.

We thank the reviewer for this comment. The goal of this work is to transcriptomically characterize the spatial relationship between areas of meningeal inflammation and the underlying parenchyma. While we agree that mechanistic studies are needed to further evaluate the role of presented signaling pathways, those experiments are beyond the scope of this brief report.

The trajectory analysis is a good way to explore gradients within the tissues and the authors are to be applauded for using this approach. However, the trajectory analysis does not tell us much if you only choose 2 genes that you think might be involved in the pathogenetic processes going on in the grey matter. It might be more useful to choose some genes involved in pathogenetic processes that we already know are involved in the tissue damage in the underlying grey matter in MS, for which there is already a lot of literature, or genes that respond to molecules we know are increased in MS CSF, although the animal models may be very different. Why were C3 and B2m chosen here?

We appreciate the reviewer’s points here. C3 and B2m were chosen as examples of genes that have differential fit to the gradient descending pattern to assist the reader in interpreting subsequent gene set trajectory analysis. However, we agree that there are many other genes of interest and will expand the number of genes displayed in our revised manuscript. 

Strengths: <br /> - The mouse model does exhibit many of the features of the compartmentalized immune response seen in MS, including the presence of meningeal immune cell infiltrates in the central sulcus and over the surface of the cortex, with the presence of FDC's HEVs PNAd+ vessels and CXCL13 expression, indicating the formation of lymphoid like cell aggregates. In addition, disruption of the glia limitans is seen, as in MS. Increased microglial reactivity is also present at the pial surface. <br /> - Spatial transcriptomics is the best approach to studying gradients in gene expression in both white matter and grey matter and their relationship between compartments. <br /> - It would be useful to have more discussion of how the upregulated pathways in the two .compartments fit with what we know about the cellular changes occurring in both, for which presumably there is prior information from the group's previous publications.

Limitations: <br /> - EAE in the mouse is not MS and may be far removed when one considers molecular mechanisms, especially as MS is not a simple anti-myelin protein autoimmune condition. Therefore, this study could be following gene trajectories that do not exist in MS. This needs a significant amount of discussion in the manuscript if the authors suggest that it is mimicking MS. <br /> - The model does not have the cortical subpial demyelination typical of MS and it is unknown whether neuronal loss occurs in this model, which is the main feature of cytokine-mediated neurodegeneration in MS. If it does not then a whole set of genes will be missing that are involved in the neuronal response to inflammatory stimuli that may be cytotoxic. <br /> - Visium technology does not get down to single cell level and does not appear to allow resolution of the border between the meninges and the underlying grey matter. <br /> - Neuronal loss in the MS cortex is independent of demyelination and therefore not related to remyelination failure. There does not appear to be any cortical grey matter demyelination in these animals, so it is difficult to relate any of the gene changes seen here to demyelination. <br /> - No mention of how the ascending and descending patterns of gene expression may be due to the gradient of microglial activation that underlies meningeal inflammation, which is a big omission.

We thank the reviewer for their insightful comments on the strengths and limitations of our study. Regarding the SJL EAE model we use in this paper, it certainly is not a perfect model of meningeal inflammation in MS, indeed we believe that no such animal model exists, but it does recapitulate several key features of human disease as described by the reviewer. Spatial transcriptomics of cortical grey matter lesions and overlying meninges of samples derived from patients with MS would be ideal, though access to this tissue is highly limited. In the revised manuscript we will include more detailed discussion of the limitations in applying these findings to MS. However, in addition to potential implications for MS research, our data contribute more generally to understanding of meningeal inflammation and penetrance of inflammation into brain tissue.

We acknowledge that sub-pial neuronal loss has not been assessed in SJL EAE, and if present it would increase the relevance of this model to neurodegeneration. We are currently working to assess this.

We agree with the reviewer that Visium technology is limited in its ability to discriminate individual cells, as discussed above (2.2).

We agree that gene expression by activated microglia is likely a major driver of the transcriptomic changes observed in the parenchyma, and thank the reviewer for highlighting this. We will add discussion of this to our revised manuscript, and intend to generate additional data regarding the contribution of subpial microglial activation to the measured transcriptomic changes.

Finally, we thank Reviewer #3 for their assessment of our work.

Author Response

eLife assessment:

Trypanosoma brucei evades mammalian humoral immunity through the expression of different variant surface glycoprotein genes. In this fundamental paper, the authors extend previous observations that TbRAP1 both interacts with PIP5pase and binds PI(3,4,5)P3, indicating a role for PI(3,4,5)P3 binding and suggesting that antigen switching is signal dependent. While much of the evidence is compelling, one reviewer suggested that the work would benefit from further controls.

We appreciate the evaluation of the work and agree that the findings substantially advance our understanding of antigenic variation. A detailed response to the public review is included below, which addresses and clarifies the issues raised by the reviewers, including those concerning controls. We also want to highlight the comment by Reviewer #3 “The methods used in the study are rigorous and well-controlled…. their results support the conclusions made in the manuscript.”. We hope this and our comments will help address the issue of controls in this eLife statement.

Reviewer #1 (Public Review):

Trypanosoma brucei undergoes antigenic variation to evade the mammalian host’s immune response. To achieve this, T. brucei regularly expresses different VSGs as its major surface antigen. VSG expression sites are exclusively subtelomeric, and VSG transcription by RNA polymerase I is strictly monoallelic. It has been shown that T. brucei RAP1, a telomeric protein, and the phosphoinositol pathway are essential for VSG monoallelic expression. In previous studies, Cestari et al. (ref. 24) have shown that PIP5pase interacts with RAP1 and that RAP1 binds PI(3,4,5)P3. RNAseq and ChIPseq analyses have been performed previously in PIP5pase conditional knockout cells, too (ref. 24). In the current study, Touray et al. did similar analyses except that catalytic dead PIP5pase mutant was used and the DNA and PI(3,4,5)P3 binding activities of RAP1 fragments were examined. Specifically, the authors examined the transcriptome profile and did RAP1 ChIPseq in PIP5pase catalytic dead mutant. The authors also expressed several C-terminal His6-tagged RAP1 recombinant proteins (full-length, aa1-300, aa301-560, and aa 561-855). These fragments’ DNA binding activities were examined by EMSA analysis and their phosphoinositides binding activities were examined by affinity pulldown of biotin-conjugated phosphoinositides. As a result, the authors confirmed that VSG silencing (both BES-linked and MES-linked VSGs) depends on PIP5pase catalytic activity, but the overall knowledge improvement is incremental. The most convincing data come from the phosphoinositide binding assay as it clearly shows that N-terminus of RAP1 binds PI(3,4,5)P3 but not PI(4,5)P2, although this is only assayed in vitro, while the in vivo binding of full-length RAP1 to PI(3,4,5)P3 has been previously published by Cestari et al (ref. 24) already. Considering that many phosphoinositides exert their regulatory role by modulating the subcellular localization of their bound proteins, it is reasonable to hypothesize that binding to PI(3,4,5)P3 can remove RAP1 from the chromatin. However, no convincing data have been shown to support the author’s hypothesis that this regulation is through an “allosteric switch”. Therefore, the title should be revised.

We appreciate the reviewer’s detailed evaluation of our work. There are a few general comments that we would like to clarify. We will break them into three points. All data included here are new and were not previously published.

i) “RNAseq and ChIPseq analyses have been performed previously …(ref. 24).” Reference 24 is Cestari et al. 2019, Mol Cell Biol. We, or others, have not published ChIP-seq of RAP1 in T. brucei. Previous work showed ChIP-qPCR, which analyses specific loci. The ChIP-seq shows genome-wide binding sites of RAP1, and new findings are shown here, including binding sites in the BES, MESs, and other genome loci such as centromeres. We also identified DNA sequence bias defining RAP1 binding sites (Fig 2A). We also show by ChIP-seq how RAP1-binding to these loci changes upon expression of catalytic inactive PIP5Pase. As for the RNA-seq, this is also the first time we show RNA-seq of T. brucei expressing catalytic inactive PIP5Pase, which establishes that the regulation of VSG silencing and switching is dependent on PIP5Pase enzyme catalysis, i.e., PI(3,4,5)P3 dephosphorylation. To improve clarity in the manuscript, we edited page 4, line 122, as follows: “We showed that RAP1 binds telomeric or 70 bp repeats (24), but it is unknown if it binds to other ES sequences or genomic loci.”

ii) “The in vivo binding of full-length RAP1 to PI(3,4,5)P3 has been previously published by Cestari et al. (ref. 24) already.”. We published in reference 24 that RAP1-HA can bind agarose beads-conjugated synthetic PI(3,4,5)P3. Here, we were able to measure T. brucei endogenous PI(3,4,5)P3 associated with RAP1-HA (Fig 4F). Moreover, we showed that the endogenous RAP1-HA and PI(3,4,5)P3 binding is about 100-fold higher when PIP5Pase is catalytic inactive than WT PIP5Pase. The data establish that in vivo endogenous PI(3,4,5)P3 binds to RAP1-HA and how the binding changes in cells expressing mutant PIP5Pase; this data is new and relevant to our conclusions.

iii) “no convincing data have been shown to support the author’s hypothesis that this regulation is through an “allosteric switch””. We show here in vitro and in vivo data supporting the conclusion. We show that PI(3,4,5)P3 binds to the N-terminus of rRAP1-His with a calculated Kd of about 20 µM (Fig 4B-E, Table 1). In contrast, we show by EMSA and binding kinetics by microscale thermophoresis that rRAP1-His binds to 70 bp and telomeric repeats via protein regions encompassing the Myb (central) or Myb-L domains (C-terminal) but not the N-terminus containing the VHP domain (Fig 3C-G, and Fig S5). Using microscale thermophoresis, we also show that rRAP1-His binds to 70 bp and telomeric repeats with Kd of 10 and 24 nM, respectively (Fig 3 and Table 1). Notably, we show that 30 µM of PI(3,4,5)P3, but not PI(4,5,)P2 – used as a control – disrupts rRAP1-His binding to 70 bp and telomeric repeats, changing Kds to about 188 and 155 nM, respectively (Fig 5A-C). We also show that PI(3,4,5)P3 does not disrupt the binding of rRAP1-His fragments (Myb or MybL) without the N-terminus domain (Fig S5), implying binding of PI(3,4,5)P3 to RAP1 N-terminus is required for displacement of RAP1 DNA binding domains (Myb and MybL) from telomeric and 70 bp repeats, and that PI(3,4,5)P3 is not competing for Myb or Myb-L binding to DNA. Moreover, we show that RAP1-HA binding to 70 bp and telomeric repeats in vivo is displaced in T. brucei cells expressing catalytic inactive PIP5Pase (Fig 5D-G), which we show results in RAP1-HA binding about 100-fold more endogenous PI(3,4,5)P3 than in T. brucei expressing WT PIP5Pase (Fig 4F). The in vivo data agrees with the in vitro data. The data show a typical allosteric regulator system, in which binding of a ligand to one site of the protein, here PI(3,4,5)P3 binding to RAP1 N-terminus, affects other domains (RAP1 Myb and Myb-L domains) binding to DNA. To improve the clarity of the title, we will change it in the revised version to imply a direct role of PI(3,4,5)P3 regulation of RAP1 in the process. This will provide more specific information to the readers and addresses the concern of the reviewer related to the “allosteric switch”. The new title will be: PI(3,4,5)P3 allosteric regulation of RAP1 controls antigenic switching in trypanosomes

There are serious concerns about many conclusions made by Touray et al., according to their experimental approaches:

1) The authors have been studying RAP1’s chromatin association pattern by ChIPseq in cells expressing a C-terminal HA tagged RAP1. According to data from tryptag.org, RAP1 with an N-terminal or a C-terminal tag does not seem to have identical subcellular localization patterns, suggesting that adding tags at different positions of RAP1 may affect its function. It is therefore essential to validate that the C-terminally HA-tagged RAP1 still has its essential functions. However, this data is not available in the current study. RAP1 is essential. If RAP1-HA still retains its essential functions, cells carrying one RAP1-HA allele and one deleted allele are expected to grow the same as WT cells. In addition, these cells should have the WT VSG expression pattern, and RAP1-HA should still interact with TRF. Without these validations, it is impossible to judge whether the ChIPseq data obtained on RAP1-HA reflect the true chromatin association profile of RAP1.

Tryptag data show both N- and C-terminus RAP1 with nuclear localization in procyclic forms, although there are differences in signal intensities in the images (http://tryptag.org/?id=Tb927.11.370). It is important to note that Tryptag data is from procyclic forms, and DNA constructs are not validated for their integration in the correct locus. As for the RAP1-HA localization in bloodstream forms, we demonstrated that C-terminally HA-tagged RAP1 co-localizes with telomeres by a combination of immunofluorescence and fluorescence in situ hybridization (Cestari and Stuart, 2015, PNAS), and RAP1-HA co-immunoprecipitate telomeric and 70 bp repeats (Cestari et al. 2019 Mol Cell Biol). We also showed by immunoprecipitation and mass spectrometry that HA-tagged RAP1 interacts with nuclear and telomeric proteins, including PIP5Pase (Cestari et al. 2019). Others have also tagged T. brucei RAP1 in bloodstream forms with HA without disrupting its nuclear localization (Yang et al. 2009, Cell; Afrin et al. 2020, Science Advances). As for the experiment suggested by the reviewer, there is no guarantee that cells lacking one allele of RAP1 will behave as wildtype, i.e., normal growth and repression of VSGs genes. Also, less than 90% of T. brucei TRF was reported to interact with RAP1 (Yang et al. 2009, Cell), which might be indirect via their binding to telomeric DNA repeats rather than direct protein-protein interactions.

2) Touray et al. expressed and purified His6-tagged recombinant RAP1 fragments from E. coli and used these recombinant proteins for EMSA analysis: The His6 tag has been used for purifying various recombinant proteins. It is most likely that the His6 tag itself does not convey any DNA binding activities. However, using His6-tagged RAP1 fragments for EMSA analysis has a serious concern. It has been shown that His6-tagged human RAP1 protein can bind dsDNA, but hRAP1 without the His6 tag does not. It is possible that RAP1 proteins in combination with the His6 tag can exhibit certain unnatural DNA binding activities. To be rigorous, the authors need to remove the His6 tag from their recombinant proteins before the in vitro DNA binding analyses are performed. This is a standard procedure for many in vitro assays using recombinant proteins.

We show in Fig 3C-G that His-tagged full-length rRAP1 does not bind to scrambled telomeric dsDNA sequences, which indicates that His-tagged rRAP1 does not bind unspecifically to DNA. Moreover, in Fig 3G, we show that His-tagged rRAP11-300 also does not bind to 70 bp or telomeric repeats. In contrast, full-length His-tagged rRAP1, rRAP1301-560, or rRAP1561-855 bind to 70 bp or telomeric repeats (Fig 3C-G). Since all proteins were His-tagged, the His tag cannot be responsible for the DNA binding.

As for the statement that human rRAP1-His has unspecific DNA binding properties, we could not find a reference to this statement; we cannot compare it without knowing the details of the experiment. Biochemical assays can result in unspecific binding depending on binding/buffer conditions. Also, humans and T. brucei RAP1 share only 15% of amino acid identity; unspecific binding to DNA could be specific to human RAP1.

3) It is unclear why Nanopore sequencing was used for RNAseq and ChIPseq experiments. The greatest benefit of Nanopore sequencing is that it can sequence long reads, which usually helps with mapping, particularly at genome loci with repetitive sequences. This seems beneficial for RAP1 ChIPseq analysis as RAP1 is expected to bind telomere repeats. However, for ChIPseq, the chromatin needs to be fragmented. Larger DNA fragments from ChIPseq experiments will decrease the accuracy of the final calculated binding sites. Therefore, ChIPseq experiments are not supposed to have long reads to start with, so Nanopore sequencing does not seem to bring any advantage. In addition, compared to Illumina sequencing, Nanopore sequencing usually yields smaller numbers of reads, and the sequencing accuracy rate is lower. The Nanopore sequencing accuracy may be a serious concern in the current study. All telomeres have the perfect TTAGGG repeats, all VSG genes have a very similar 3’ UTR, and all 70 bp repeats have very similar sequences. In fact, the active and silent ESs have 90% sequence identity. Are sequence reads accurately mapped to different ESs? How is the sequencing and mapping quality controlled? Furthermore, it is unclear whether the read depth for RNAseq is deep enough.

The mean sequence length for the ChIP-seq was about 500 bp (see Table S3), which helps to align reads to ESs and distinguish the different ESs, and it is a reasonable size range to define RAP1 binding sites. Although sequencing depths are usually higher in Illumina than in nanopore (all depending on the amount of sequencing), most Illumina short reads map to multiple genomic sequences, making it difficult to distinguish ESs. This is particularly important for RAP1 because it binds to repeats such as 70 bp and telomeric repeats. Mapping short reads to those regions would be virtually impossible; hence, our choice of nanopore sequencing. For RNA-seq, the ~500 bp read length help sequence alignment to the subtelomeric regions containing many VSG genes. The nanopore reads obtained here had an average sequencing score 12 (i.e., base call accuracy of 94%). Filtering reads with MAPQ ≥ 20 (99% probability of correct alignment) helped us to distinguish RAP1 binding to specific ESs, including silent vs active ES (ChIP-seq) or VSG sequences (RNA-seq). The details of the analysis and sequencing metrics (i.e., sequencing depth and read length) were described in the Methods section “Computational analysis of RNA-seq and ChIP-seq” and Table S3, respectively.

4) Many statements in the discussion section are speculations without any solid evidence. For example, lines 218 - 219 “likely due to RAP1 conformational changes”, no data have been shown to support this at all. In lines 224-226, the authors acknowledged that more experiments are necessary to validate their observations, so it is important for the authors to first validate their findings before they draw any solid conclusions. Importantly, RAP1 has been shown to help compact telomeric and subtelomeric chromatin a long time ago by Pandya et al. (2013. NAR 41:7673), who actually examined the chromatin structure by MNase digestion and FAIRE. The authors should acknowledge previous findings. In addition, the authors need to revise the discussion to clearly indicate what they “speculate” rather than make statements as if it is a solid conclusion.

The statement “likely due to RAP1 conformational changes” in lines 218-219 (page 6) is part of the Discussion. We did not make a strong statement but discussed a possibility. We believe that it is beneficial to the reader to have the data discussed, and we do not feel this point is overly speculative.

For lines 224-226 (page 6), the statement refers to the finding of RAP1 binding to centromeric regions by ChIP-seq, which is a new finding but not the focus of this work. Hence, future studies are necessary for this finding, and we believe it is appropriate in the Discussion to be upfront and highlight this point to the readers. However, for the RAP1 binding to telomeric ES sites, e.g., 70 bp repeats and telomeric repeats (the focus of this work), we validated the binding by EMSA and by performing binding kinetics using microscale thermophoresis.

We did not include Pandya et al. 2013 NAR because the authors demonstrated RAP1 compaction of chromatin to occur in procyclic forms only. Pandya et al. stated in their abstract: “no significant chromatin structure changes were detected on depletion of TbRAP1 in BF cells”. Hence, the suggested reference is not relevant to the context of our conclusions in bloodstream forms. Nevertheless, we have reviewed the Discussion to avoid broad speculations in the revised version of the manuscript.

There are also minor concerns:

1) In the PIP5Pase conditional knockout system, the WT or mutant PIP5Pase with a V5 tag is constitutively expressed from the tubulin array. What’s the relative expression level of this allele and the endogenous PIP5Pase? Without a clear knowledge of the mutant expression level, it is hard to conclude whether the mutant has any dominant negative effects or whether the mutant phenotype is simply due to a lower than WT PIP5pase expression level.

The relative mRNA levels of the exclusive expression of PIP5Pase Mut compared to the WT is available in the Data S1, RNA-seq. The Mut allele’s relative expression level is 0.85-fold to the WT allele (both from tubulin loci). We also showed by Western blot the WT and Mut PIP5Pase protein expression (Cestari et al. 2019, Mol Cell Biol). Concerning PIP5Pase endogenous alleles, we compared RNA-seq reads counts per million from the conditional null PIP5Pase cells exclusively expressing WT or the Mut PIP5Pase alleles (Data S1, this work) to our previous RNA-seq of single-marker 427 strain (Cestari et al. 2019, Mol Cell Biol). We used the single-maker 427 because the conditional null cells were generated in this strain background. The PIP5Pase WT and Mut mRNAs expressed from tubulin loci are 1.6 and 1.3-fold the endogenous PIP5Pase levels in single-marker 427, respectively. We include a statement in the Methods, page 7, lines 265-268: “The WT or Mut PIP5Pase mRNAs exclusively expressed from tubulin loci are 1.6 and 1.3-fold the WT PIP5Pase mRNA levels expressed from endogenous alleles in the single marker 427 strain. The fold-changes were calculated from RNA-seq reads counts per million from this work (WT and Mut PIP5Pase, Data S1) and our previous RNA-seq from single marker 427 strain (24).”

2) In EMSA analysis, what are the concentrations of the protein and the probe used in each reaction? The amount of protein used in the binding assay appears to be very high, and this can contribute to the observation that many complexes are stuck in the well. Better quality EMSA data need to be shown to support the authors’ claims.

All concentrations were provided in the Methods section. See page 9 Electrophoretic mobility shift assays: “100 nM of annealed DNA were mixed with 1 μg of recombinant protein…”. For microscale thermophoresis, also see page 9, Microscale thermophoresis binding kinetics: “1 μM rRAP1 was diluted in 16 two-fold serial dilutions in 250 mM HEPES pH 7.4, 25 mM MgCl2, 500 mM NaCl, and 0.25% (v/v) N P-40 and incubated with 20 nM telomeric or 70 bp repeats…”. Note that two different biochemical approaches, EMSA and microscale thermophoresis, were used to assess rRAP1-His binding to DNA. Both show similar results (Fig 3 and 5, and Fig S5; microscale thermophoresis shows the binding kinetics, data available in Table 1). The EMSA images clearly show the binding of RAP1 to 70 bp or telomeric repeats but not to scramble telomeric repeat DNA.

Reviewer #2 (Public Review):

This manuscript by Touray, et al. provides a significant new twist to our understanding of how antigenic variation may be regulated in T. brucei. Key aspects of antigenic variation are the mutually exclusive expression of a single antigen per cell and the periodic switching from expression of one antigen isoform to another. In this manuscript, the authors show, as they have previously shown, that depletion of the nuclear phosphatidylinositol 5-phosphatase (PIP5Pase) results in a loss of mutually exclusive VSG expression. Furthermore, using ChIP-seq, the authors show that the repressor/activator protein 1 (RAP1) binds to regions upstream and downstream of VSG genes located in transcriptionally repressed expression sites and that this binding is lost in the absence of a functional PIP5Pase. Importantly, the authors decided to further investigate this link between PIP5Pase and RAP1, a protein that has previously been implicated in antigenic variation in T. brucei, and found that inactivation of PIP5Pase results in the accumulation of PI(3,4,5)P3 bound to the RAP1 N-terminus and that this binding impairs the ability of RAP1 to bind DNA. Based on these observations, the authors suggest that the levels of PI(3,4,5)P3 may determine the cellular function of RAP1, either by binding upstream of VSG genes and repressing their function, or by not binding DNA and allowing the simultaneous expression of multiple VSG genes in a single parasite.

While I find most of the data presented in this manuscript compelling, there are aspects of Figure 1 that are not clear to me. Based on Figure 1F, the authors claim that transient inactivation of PIP5Pase results in a switch from the expression of one VSG isoform to another. However, I am not exactly sure what the authors are showing in this panel, nor do the data in Figure 1F seem to be consistent with those shown in Figure 1C. Based on Figure 1F, a transient inactivation of PIP5Pase appears to result in an almost exclusive switch to a VSG located in BES12. However, based on Figure 1E, the VSG transcripts most commonly found after a transient inactivation of PIP5Pase are those from the previously active VSG (BES1) and VSGs located on chr 1 and 6 (I believe). The small font and the low resolution make it impossible to infer the location of the expressed VSG genes, nor to confirm that ALL VSG genes located in expression sites are activated, as the authors claim. Also, I was not able to access the raw ChIP-seq and RNA-seq reads. Thus, could not evaluate the quality of the sequencing data.

We appreciate the reviewer’s comments and evaluation of our work. Fig 1E shows VSG-seq of a population after transient (24h) exclusive expression of the PIP5Pase mutant, followed by re-expression of the WT PIP5Pase allele for 60 hours (multiple VSGs are detected). As a control, it also shows VSG-seq in cells continuously expressing WT PIP5Pase (mostly VSG2, BES1 is detected). Fig 1F and Fig S1 show the sequencing of VSGs expressed by clones isolated (5-6 days of growth) after a temporary knockdown (24h) of PIP5Pase (tet -), followed by its re-expression. For comparison, no knockdown (tet +) was included. Fig 1F shows potential switchers in the population, the Fig 1E confirms VSG switching in clones.

To clarify the difference between Fig 1E and 1F, we edited the manuscript on page 3, lines 103-110: “To verify PIP5Pase role in VSG switching, we knocked down PIP5Pase for 24h (Tet -), then restored its expression (Tet +) and isolated clones by limiting dilution and growth for 5-6 days. Analysis of isolated clones after temporary PIP5Pase knockdown (Tet -/+) confirmed VSG switching in 93 out of 94 (99%) of the analyzed clones (Fig 1F, Fig S1). The cells switched to express VSGs from silent ESs or subtelomeric regions, indicating switching by transcription or recombination mechanisms. Moreover, no switching was detected in 118 isolated clones from cells continuously expressing WT PIP5Pase (Tet +, Fig 1F).”. We also edited Fig 1F to indicate temporary knockdown (Tet -/+) vs no knockdown (Tet -). The modifications will be available in the resubmitted version of the manuscript.

We agree that the heat map is difficult to read due to the amount of information. We will include in the revised version of the manuscript a table with the data in the supplementary information; the reader will be able to evaluate the data in detail.

A preference for switching to specific ESs has been observed in T. brucei (Morrison et al. 2005, Int J Parasitol; Cestari and Stuart, 2015, PNAS), which may explain several clones switching to BES12. Many potential switchers were detected in the VSG-seq (Fig 1F, the whole cell population is over 107 parasites), but not all potential switchers were detected in the clonal analysis because we analyzed 212 clones total, a fraction of the over 107 cells analyzed by VSG-seq (Fig 1E). Also, it is possible that not all potential switchers are viable. However, the point of the clonal analysis is to validate the VSG switching after genetic perturbation of PIP5Pase.

Fig 1C shows examples of ES derepression by RNA-seq after 24h exclusive expression of the mutant compared to WT PIP5Pase. The RNA-seq shows that all ESs are derepressed (Fig 1B). This can be visualized in the volcano plot (Fig 1B, BES and MES VSGs are labelled) and on the spreadsheet Data S1. Although all ESs are derepressed after PIP5Pase mutant expression, not all ESs are selected during switching, as observed in Fig 1E-F. This agrees with our previous observations in switching assays with proteins that control VSG switching (Cestari and Stuart, 2015, PNAS).

As for metrics of sequencing and raw sequencing data. See Methods section, page 13, lines 483-485: “Sequencing information is available in Table S3 and fastq data is available in the Sequence Read Archive (SRA) with the BioProject identification PRJNA934938.” Table S3 has a summary of sequencing data. Metrics information such as sequencing quality and analysis can be found in the Methods section “Computational analysis of RNA-seq and ChIP-seq”. The latter includes information about nanopore reads, i.e., mean Q-score of 12.

Reviewer #3 (Public Review):

In this manuscript, Touray et al investigate the mechanisms by which PIP5Pase and RAP1 control VSG expression in T. brucei and demonstrate an important role for this enzyme in a signalling pathway that likely plays a role in antigenic variation in T. brucei.

The methods used in the study are rigorous and well-controlled. The authors convincingly demonstrate that RAP1 binds to PI(3,4,5)P3 through its N-terminus and that this binding regulates RAP1 binding to VSG expression sites, which in turn regulates VSG silencing. Overall their results support the conclusions made in the manuscript.

There are a few small caveats that are worth noting. First, the analysis of VSG derepression and switching in Figure 1 relies on a genome that does not contain minichromosomal (MC) VSG sequences. This means that MC VSGs could theoretically be misassigned as coming from another genomic location in the absence of an MC reference. As the origin of the VSGs in these clones isn’t a major point in the paper, I do not think this is a major concern, but I would not over-interpret the particular details of switching outcomes in these experiments.

The authors state that “our data imply that antigenic variation is not exclusively stochastic.” I am not sure this is true. While I also favor the idea that switching is not exclusively stochastic, evidence for a signaling pathway does not necessarily imply that antigenic variation is not stochastic. This pathway could be important solely for lifecycle-related control of VSG expression, rather than antigenic variation during infection. Nevertheless, these data are critical for establishing a potential pathway that could control antigenic variation and thus represent a fundamental discovery.

Another aspect of this work that is perhaps important, but not discussed much by the authors, is the fact that signalling is extremely poorly understood in T. brucei. In Figure 1B, the RNA-seq data show many genes upregulated after expression of the Mut PIP5Pase (not just VSGs). The authors rightly avoid claiming that this pathway is exclusive to VSGs, but I wonder if these data could provide insight into the other biological processes that might be controlled by this signaling pathway in T. brucei.

Overall, this is an excellent study that represents an important step forward in understanding how antigenic variation is controlled in T. brucei. The possibility that this process could be controlled via a signalling pathway has been speculated for a long time, and this study provides the first mechanistic evidence for that possibility.

We thank the reviewer for the evaluation of our work. We agree that it is difficult to ensure the origin of all VSG genes not having minichromosome sequences; hence we did not emphasize this point in the manuscript. We used the 427-2018 reference genome assembled by PacBio and Hi-C (Muller et al. 2018, Nature), which we believe is the best assembly for the 427 strain, especially related to the VSG genes.

We also agree that having signaling controlling switching in vitro does not mean the switching necessarily occurs by signaling in vivo. Nevertheless, stochastic switching is an accepted model; but it has not been proved, whereas we provide molecular evidence that signaling can cause switching. To express this reviewer’s suggestion, we edited the Discussion, page 7, line 250: from “our data imply that antigenic variation is not exclusively stochastic” to “our data suggest that antigenic variation is not exclusively stochastic”.

Most of the RNA-seq data were VSGs genes/pseudogenes. Other genes upregulated included retrotransposons and DNA/RNA processing enzymes such as endonucleases and polymerases. We included in the Results, page 3, line 100: “Other genes upregulated include primarily retrotransposons, endonucleases, and polymerase proteins.”.

Author Response

Reviewer #2 (Public Review):

Associative learning assigns valence to sensory cues paired with reward or punishment. Brain regions such as the amygdala in mammals and the mushroom body in insects have been identified as primary sites where valence assignment takes place. However, little is known about the neural mechanisms that translate valence-specific activity in these brain regions into appropriate behavioral actions. This study identifies a small set of upwind neurons (UpWiNs) in the Drosophila brain that receive direct inputs from two mushroom body output neurons (MBONs) representing opposite valences. Through a series of behavioral, imaging, and electrophysiological experiments, the authors show that UpWiNs are differentially regulated by the two MBONs, i.e., inhibited by the glutamatergic MBON-α1(encoding negative valence) while activated by the cholinergic MBON-α3 (encoding positive valence). They also show that UpWiNs control the wind-directed behavior of flies. Activation of UpWiNs is sufficient to drive flies to orient and move upwind, and inhibition of UpWiNs reduces flies' upwind movement toward the source of reward-predicting odors (CS+). These results, together with existing knowledge about the function of the mushroom body in memory processing, suggest an appealing model in which reward learning decreases and increases the responses of MBON-α1 and MBON-α3 to the CS+ odor, respectively, and these changes cause UpWiNs to respond more strongly to the CS+ odor and drive upwind locomotion. Interestingly, in the final part of the results, the authors reveal a wind-independent function of UpWiNs: increasing the probability that flies will revisit the site where UpWiNs were activated. Thus, UpWiNs guide learned reward-seeking behavior with and without airflow. Although the mushroom body has been extensively studied for its role in learning and memory, the downstream neural circuits that read the information from the mushroom body to guide memory-driven behaviors remain poorly characterized. This study provides an important piece of the puzzle for this knowledge gap.

Strength

1) Memory studies have predominantly relied on binary choice (go or no-go) assays as measures of memory performance. While these assays are convenient and efficient, they fall short of providing a comprehensive understanding of underlying behavioral structures. In an effort to overcome this limitation, the current study used video recording and tracking software to delve deeper into memory-guided behavior. This innovative approach allowed the authors to uncover novel neurons and examine their contribution to behavior with a level of detail not possible with binary choice assays.

2) This study used electron microscopy-based Drosophila hemibrain connectome data to reveal the synaptic connection between UpWiNs and MBON-α1 and MBON-α3. Using this method, the study shows that a single UpWiN receives direct input from both MBON-α1 and MBON- α3, which is confirmed by a functional imaging experiment. The connectome dataset also reveals several neurons downstream of UpWiNs, opening avenues for further research into the neural mechanisms linking memory and behavior.

Weakness

1) The authors repeatedly state in the manuscript that MBON-α1 and MBON-α3 convey appetitive or aversive memories, respectively. This assertion may not be entirely accurate. Evidence from sugar reward conditioning experiments suggests that MBON-α3 is potentiated and required for sugar reward memory retrieval. Therefore, the compartmentalization for appetitive and aversive memories appears not as obvious at the level of MBONs.

What we intended was that activation of DANs in these compartments can induce aversive and appetitive memories, respectively, when paired with odors, and that these are the sole output pathway from these compartments to read out the memories in these compartments. As we previously proposed (Aso et al., 2014a eLife), these MBONs can integrate inputs from MBONs of other compartments and their activity can reflect appetitive memory stored as synaptic plasticity in other compartments. Since DANs in the α3 compartment respond to heat, bitter and electric shock but not sugar, the observation that MBON-α3 acquires an enhanced CS+ odor response after appetitive conditioning is presumably due to these intercompartmental connections rather than plasticity of KC-MBON synapses in the α3 compartment. In any case, the fact that excitatory activity of MBON-α1 and MBON-α3 conveys opposite valence of memory still holds true since appetitive conditioning induces depression and potentiation of odor responses, respectively.

To clarify this point, we now cited related literature in the following sentence in the final paragraph of Introduction: “UpWiNs receive inputs from several types of lateral horn neurons and integrate inhibitory and excitatory inputs from MBON-α1 and MBON-α3, which are the output neurons of MB compartments that store long-lasting appetitive or aversive memories, respectively (Aso and Rubin, 2016; Ichinose et al., 2015; Jacob and Waddell, 2022a; Pai et al., 2013; Yamagata et al., 2015).”

2) This study did not conclusively establish the importance of the MBON-α1/α3 to UpWiN pathways in memory-driven behavior. In the experiments shown in Figure 5, flies were trained to associate the activation of reward-related DANs with a specific odor (CS+). After conditioning, UpWiNs were observed to show enhanced responses to the CS+ odor. However, the results should be interpreted with caution because the driver line used to activate DANs (R58E02-LexAp65) labels not only DANs projecting to the MBON-α1 compartment, but all DANs in the protocerebral anterior medial (PAM) cluster. Thus, it remains unclear to what extent the observed enhanced responses are influenced by changes in inhibitory inputs from MBON-α1. While UpWiNs have been shown to play a critical role in the expression of sugar reward memory (Figure 7), it should be noted that UpWiNs receive inputs from multiple upstream neurons, making it difficult to accurately assess the contribution of MBON-α1/α3 to UpWiN pathways in UpWiN recruitment. Further research is needed to fully address this issue.

We totally agree with this point and added a sentence to explain an alternative mechanism. “This enhancement of CS+ response can be most easily explained as an outcome of disinhibition from MBON-α1 whose output had been decreased by memory formation; MBON-α1 is inhibitory to UpWiNs (Figure 4B) and MBON-α1 response to the CS+ is reduced following the same training protocol (Yamada et al. 2023). In addition to such a mechanism, plasticity in the β1 compartment may contribute to the enhanced CS+ response in UpWiNs because the driver R58E02 contains DANs in the β1 and glutamatergic MBON from the β1 directly synapse on the dendrites of MBON-α1 and MBON-α3. “

3) UpWind neurons (UpWiNs) were so named because their activation promotes upwind locomotion. However, when activated in the absence of airflow, flies show increased locomotor speed and an increased probability of revisiting the same location (Figure 7 and Figure 7-figure supplement 1). The revisiting behavior can be observed during the activation of UpWiNs, which is distinct from the local search behavior that typically begins after a reward stimulus is turned off (e.g., Gr64f-GAL4 results in Figure 7-figure supplement 1).

Return probability was calculated within a 15-s time window. High return probability during LED ON period (10-20s) in Figure 7-figure supplement 1 does not necessarily mean that flies returned during LED ON period. If a fly is at the position A when t=10s, to be counted as “returned”, it needs to move more than 10mm away from A and move back to the position less than 3mm distance from A by t=25s. In the case of sugar sensory neuron activation with Gr64f-GAL4, the peak of return probability is shifted toward a later time point because flies stop and extend proboscis during activation period.

Because revisiting a location can also be a consequence of repeated turns, it seems more accurate to describe UpWiNs as controlling the speed and likelihood of turns and promoting upwind movement by integrating with neurons that sense the direction of airflow.

The return probability plotted in Figure 7E is probability of return to the position at the end of LED period within 15s post LED period when angular speed of SS33917>CsChrimson and SS33918>CsChrimson flies are identical to empty-split-GAL4>CsChrimson control flies (Figure 7-figure supplement 1). Thus, revisiting behavior cannot be explained by a simple increase in turing probability.

Although functions of UpWiNs are not limited to promotion of wind-directed walking, we still think that the “UpWind Neurons” is a practical name for broad readers and oral communications at the current stage of investigations, because EM neuron IDs and names (SMP348, SMP353, SMP354, SLP399 and SLP400) are too lengthy and do not contain any functional information. We initially defined a set of 11 neurons labeled by SS33197 split-GAL4 as “UpWind Neurons (UpWiNs)” based on initial optogenetic screening (Figure 2A). We found other driver lines for mushroom body interneuron cell types that can promote release of dopamine and more robust returning phenotype (e.g. SS49755), but SS33917 remained to be the champion driver line for upwind locomotion phenotype.

Reviewer #3 (Public Review):

Aso et al. provide insight into how learned valences are transformed into concrete memory-driven actions, using a diverse set of proven techniques.

Here the authors use a four-armed arena to evaluate flies' preference for a reward-predicting odor and measure upwind locomotion. This behavioral paradigm was combined with the photoactivation of different memory-eliciting neurons, revealing that appetitive memories stored in different compartments of the mushroom bodies (center of olfactory memory) induce different levels of upwind locomotion. The authors then proceed to a non-exhaustive optogenetic screen of the neurons located downstream of the output neurons of the mushroom bodies (MBONs) and identify a group of 8-11 Cholinergic neurons promoting significant changes in upwind locomotion, the UpWins. By combining confocal immunolabelling of these neurons with electron microscope images, they manage to establish the UpWins' connectome within themselves and with the MBONs. Then, using two in vivo cell recording techniques, electrophysiology, and calcium imaging, they define that UpWins integrate both inhibitory and excitatory synaptic inputs from the MBONs encoding appetitive and aversive memory, respectively. In addition, they show that the UpWins' response to a reward-predicting odor is increased after appetitive training. On a behavioral level, the authors establish that the UpWins respond to wind direction only and are not involved in lower-level motor parameters, such as turning direction and acceleration. Finally, they demonstrate that the UpWins' activity is necessary for long-term appetitive memory retrieval, and even suggest a broader role for the UpWins in olfactory navigation, as their photoactivation increases the probability of revisiting behavior. In the end, the authors state that they provide new insights into how memory is translated into concrete behavior, which is fully supported by their data. Altogether, the authors present a pretty complete study that provides very interesting and reliable data, and that opens a new field of investigation into memory-driven behaviors.

Strengths of the study:

• To support their conclusions, the authors provide detailed data from different levels of analysis (behavioral, cellular, and molecular), using multiple sophisticated techniques.

• The measurement of multiple parameters in the behavioral analysis supports the strong changes in upwind locomotion. In addition, taken individually these parameters provide precise insights into how upwind locomotion changes, and allow the authors to more precisely define the role of the UpWins.

• The authors use split-Gal4 drivers instead of Gal4, allowing them to better refine neuron labelling.

The authors discussed and investigated all possible biases, making their data very reliable. For example, they demonstrated that the phenotypes observed in the behavioral assay were wind-directed behaviors and could not be explained by bias avoidance of the arena's center area.

Limitations of the study:

• In the absence of more precise drivers, the UpWins' labelling lacks precision. For example, there is no way to know exactly which UpWin is responding in the electrophysiological experiment presented in Figure 4.

We have ongoing efforts to generate split-GAL4 and split-LexA driver lines for specific subsets of UpWiN neurons, but the data using those lines are not ready for this manuscript. However, we would like to point out that historically, identification of a group of neurons with striking phenotype has been foundational to promote follow-up studies. A good example is P1 neurons for courtship behavior.

• The screening of neurons located downstream of the MBONs is not exhaustive, meaning that other groups of neurons might be involved in memory-driven upwind locomotion. Although, it does not diminish the authors' conclusions.

The UpWiNs is certainly not the only one cell type for mediating memory-driven upwind locomotion, since our and other groups’ studies (e.g. Matheson et al., 2022; PMCID: PMC9360402) identified a collection of cell types that can promote upwind locomotion upon optogenetic activation.

In 2021, we released images and driver lines of a larger collection of split-GAL4 driver lines at https://splitgal4.janelia.org. We are preparing a manuscript to provide anatomical descriptions of these lines. This collection of new drivers will help elucidate more comprehensive views of circuits for memory-driven actions.

• All data were obtained with walking flies. So far, there have been no experiments on flying flies.

This is an intriguing question and we mentioned in Discussion that “Our study was limited to walking behaviors, and the role of UpWiNs in flight behaviors remains to be investigated.”

Author Response

Review #1 Public Review:

This is an interesting study which attempts to assess the effect of the pandemic on diagnoses of pancreatic cancer. The authors have used a large national database to evaluate this, however, it should be noted that this database only captures 40% of the population in England. The authors have looked at specific parameters including Body Mass Index (BMI) as well as markers of diabetes and liver function. Only BMI had a difference in the frequency of measurements during the pandemic, presumably due to reduced face-to-face visits to allow weight and height to be captured.

Interestingly the authors noticed a reduction in surgery for pancreatic cancer by 25%, yet reported that there were no differences in the frequency of death within 6 months following the diagnosis of pancreatic cancer. The reduction in surgery is likely related at least in part to the loss of operating lists due to pandemic restrictions, however, this paper is not equipped to address another important possibility behind this, which is that pancreatic cancers were presenting too late for surgical intervention. It is not sufficient to comment that pancreatic cancer treatment was not affected by the pandemic based on the data presented on deaths within 6 months of the diagnosis of pancreatic cancer alone, as the median survival of patients diagnosed with pancreatic cancer within the pandemic has not been captured and compared to that of patients diagnosed in the preceding 5 years.

Therefore while the study can conclude no difference in pancreatic cancer diagnoses before and during the pandemic, more work needs to be done to truly assess if the pandemic had any effect on the outcomes from pancreatic cancer for patients diagnosed within this timeframe.

Thank you for taking time to undertake the review and for all the constructive comments. This study was designed to assess the effect of the pandemic on pancreatic cancer services in England. We focused on the quantity of healthcare.

We acknowledge and understand the comments by the reviewer with regards to the limitations of this study in relation to the effect of the COVID-19 pandemic on diagnosis and survival. We did not assess the effect of the pandemic on the staging information and survival length.

Author Response

Reviewer #1 (Public Review):

This research aimed to discern the pattern of methylation changes that occur during aging, distinguishing between a unified specific mechanism and stochastic changes. To date, no unified hypothesis exists to guide our understanding of the changes in chromatin geography observed during the aging of cells. This work analysed six different types of purified blood-borne white blood cells allowing comparison across different immune cell subsets to determine if similar patterns occurred in all cell populations. Intriguingly, each subset exhibited its own distinct differential methylation rather than a single program. However, a core set of gene changes close to age-associated CpGs was identified suggesting that a central program existed, but that individual cell type function and metabolism shaped the overall chromatin landscape for the population. These findings establish a new framework for considering the aging process and open new questions about how the individual clocks of different populations might be regulated. While circulating cells are readily accessible for evaluation in humans, the majority of immune cells that regulate immune homeostasis are found within the tissues of the body. Whether these cells exhibit a similar profile to circulating cells or are rather shaped by their tissue or organ-specific ecosystem remains to be determined. In this setting, these tissue-resident cells are exposed to very different oxygen tensions and metabolic substrates. Furthermore, genes identified have been associated with aging, they concurrently appear to be associated with inflammation, thus it is not clear whether aging and low-grade inflammation are inherently linked, or whether these two pathways can be segregated. Thus a number of questions remain warranting further investigation.

The reviewer makes a very good point regarding different tissue resident cells being exposed to different oxygen and metabolic stress. In the reviewed manuscript we have Arid3a coming up as one of the transcription factors with motifs in and around probes hypermethylated with age in monocytes. Arid3a is known to target inflammatory genes but future research is warranted to implicate the link between aging and low-grade inflammation. To address the comment about connection between aging and low-grade inflammation, in the revised manuscript, we have incorporated new analysis by looking into SomaScan array derived protein levels of seven cytokines from the same cohort of donors. We tested the hypothesis that part of the age-associated changes in DNA methylation are connected with the well-known age-related proinflammatory state. We have now added the details in the Results and Methods sections. Briefly, we run two regression models (CpGi~age+sex and CpGi~age+sex+analytej, where i is each CpG probe from EPIC array and j is each of the seven cytokines). We find that change in DNA methylation levels in nearly 70009000 CpG sites in CD4 cells and 124 CpG sites in B cells that were originally age-associated, also are associated with increasing levels of TNFRSF1A, TNFRSF1B and TNF-alpha levels thereby indicating a link between DNA methylation change and aging as well as inflammatory cytokines levels.

Author Response

Reviewer #1 (Public Review):

The work described herein would have an impact on the field in multiple ways. Firstly, it demonstrates a novel metabolic role for MSH in the regulation of hepatic cholesterol metabolism. This may prove to be a viable therapeutic strategy for the treatment of dyslipidemia. Furthermore, the authors demonstrate an alternative signaling cascade elicited by MSH independent of cAMP, but rather relying on AMPK. This novel interaction between AMPK and MC1R could have more widespread implications beyond the control of hepatic cholesterol metabolism.

For the most part, the conclusions offered by the authors are supported by the data that is presented. There are, however, a number of concerns in the current version of this manuscript detailed below.

We thank the reviewer for the encouraging and insightful comments, and we are pleased to read that the manuscript has raised considerable interest.

1) The authors demonstrate the expression of MC1R in hepatocytes through IHC staining and western blot analysis. Furthermore, the authors show an alteration in systemic bile acid homeostasis in MC1R KO mice. However, no mention of MC1R expression or function in cholangiocytes is discussed. This is important to assess both experimentally and within the discussion given the profound role of the biliary epithelium in modulating bile acid homeostasis. Furthermore, in figure 1 the authors validate the MC1R knockdown only through mRNA expression. Given panels A and C of figure 1 shows there is clearly a functional antibody for MC1R, validation of protein knockdown is needed.

The reviewer raises an important point, which we addressed by performing immunofluorescence staining using an antibody against the cholangiocyte marker cytokeratin 19 (CK-19). These colocalization studies demonstrate the presence of MC1-R in CK19-positive cholangiocytes (Figure 1-figure supplement 1). Furthermore, we have now added a discussion on the possible role of MC1-R in modulating bile acid homestasis in cholangiocytes (page 12, lines 456-462).<br /> We also quantified MC1-R protein expression by Western blotting in the liver of LMc1r-/- mice. MC1-R protein level was significantly reduced in L-Mc1r-/- mice compared to L-Mc1+/- mice (Figure 2-figure supplement 2).

2) Figure 2 demonstrates a steatotic effect of MC1R knockdown in hepatocytes. The authors attempt to provide mechanistic insight into this phenomenon through assessing the mRNA expression of genes involved in cholesterol and fatty acid synthesis. The data provided is modest at the gene level and no protein validation was provided to demonstrate functional alterations of these proteins in MC1R KO mice. Key proteins proposed such as SREBP2 and HMGCR need to be validated via a western blot of IHC analysis.

As requested by the reviewer, we quantified the expression of key proteins in the liver of L-Mc1r-/- mice by Western blotting. We observed that the protein levels of HMGCR and DHCR7 as well as the ratio between the mature and precursor forms of SREBP2 were reduced in L-Mc1r-/- mice (Figure 2F-H, page 6/lines 182-191 & page 10-11/lines 390-401). This is likely a result of the feedback regulation, whereby cholesterol accumulation suppresses the cleavage of SREBP2 and leads to a consequent downregulation of the key cholesterol synthesis enzymes such as HMGCR and DHCR7 (Brown S & Goldstein JL, Cell. 1997 May 2;89(3):331-40).

We discussed in the original submission (page 11) as follows: ‘In the presence of excess cellular cholesterol, transcriptional induction and posttranslational activation of SREBP-2 should be attenuated, which in turn downregulates Hmgcr and Dhcr7 and reduces cholesterol synthesis as a counterregulatory mechanism. Therefore, given the increase in hepatic cholesterol content, it was unexpected that Srebp2 expression was upregulated in the liver of L-Mc1r-/- mice’. The finding of reduced SREBP2/HMGCR protein expression is thus more logical, but admittedly, it is discordant with increased Srebp2/Hmgcr mRNA expression (as reported in the original submission), which might be a compensatory response to suppressed SREBP2 cleavage. Taking into account that activation of MC1-R did not affect the protein expression of HMGCR or DHCR7 in HepG2 cells, it is plausible that hepatic cholesterol accumulation in L-Mc1r-/- mice is driven by a defect in bile acid metabolism, rather than by a direct effect of MC1-R signaling on cholesterol synthesis. To avoid unnecessary confusion, we decided to omit the qPCR data and related text parts from the manuscript and report the protein expression data instead.

4) The authors suggest the involvement of AMPK in mediating the cholesterol-lowering effects of MSH. However, MSH is still able to lower free cholesterol levels even in the presence of an AMPK inhibitor. This suggests that MSH does not in fact rely on the activation of AMPK to elicit these cholesterol-lowering effects. The authors' conclusions are stronger than the actual data support. Furthermore, the authors claim LD211 phenocopies the effects of MSH in the presence of an AMPK inhibitor. However, the authors only measured the phosphorylation of Akt as their outcome. This begs the question, does LD211 still lower total cholesterol in the presence of AMPK inhibitors? This experiment is essential to conclude whether or not LD211 phenocopies the effects of MSH.

The reviewer may have missed that we postulate in the manuscript that ‘MC1-R activation engages multiple signaling mechanisms to regulate cholesterol metabolism in HepG2 cells’ (manuscript page 8, lines 310-311 & page 13, lines 498508), since low concentration of a-MSH was still able to lower free cholesterol level in the presence of the AMPK inhibitor dorsomorphin. We have been careful not to claim that the effects of a-MSH are solely dependent on AMPK phosphorylation. Likewise, we have not claimed in the original submission that LD211 phenocopies the effects of MSH in the presence of an AMPK inhibitor. However, as suggested by the reviewer, we performed new experiments to investigate the effects of LD211 on cellular cholesterol levels in the absence and presence of dorsomorphin. We found that AMPK inhibition with dorsomorphin completely abolished the cholesterollowering effect of LD211 (Figure 7-figure supplement 2), which might indicate that this synthetic agonist has a stronger signaling bias toward the AMPK pathway compared to α-MSH.

5) The authors initiate the project by showing high-fat diet disrupts the expression of MC1R. However, all of the subsequent experiments in hepatic MC1R KO mice are performed under normal chow. This begs the question of what is the phenotype of the hepatic MC1R KO mice fed a high-fat diet. Does KO of MC1R in the liver exacerbate HFD-induced obesity, glucose intolerance, and dyslipidemia? Inversely, can WT mice challenged with an HFD be rescued metabolically by treatment with either MSH or LD211? Providing data along these lines of investigation will provide physiological/clinical relevance to their findings.

As suggested by the reviewer, we phenotyped the hepatic MC1R KO (LMc1r-/-) mice after feeding them a cholesterol- and fat-rich Western diet for 12 weeks (RD Western Diet, D12079B, Research Diets Inc, NJ, USA). This was exactly the same dietary regimen (product and duration) that was used to study the changes in hepatic MC1-R expression in wild-type C57Bl mice (Figure 1B&C). We observed that 12-week Western diet feeding induced a significant gain in body weight and total fat mass as well as an increase in plasma and hepatic cholesterol and TG levels (Figure 2-figure supplement 2). L-Mc1r-/- mice did not show a difference in body weight gain, but the weight gain was attributable to enhanced gain in fat mass and a blunted increase in lean mass compared to control Mc1rfl/fl mice (Figure 2-figure supplement 2A, D & E). Furthermore, liver weight and plasma cholesterol and TG concentrations were unchanged in HFD-fed L-Mc1r-/- mice (Figure 2-figure supplement 2B, C, F & G). Importantly, recapitulating the phenotype observed in chow-fed mice, hepatic cholesterol and TG content was significantly increased in LMc1r-/- mice after a HFD challenge (Figure 2-figure supplement 2H & I). Taken together, it appears that the phenotype of HFD-fed L-Mc1r-/- mice was slightly diluted compared to the phenotype observed in chow-fed L-Mc1r-/- mice. This phenotypic difference might relate to the finding that Western diet feeding reduced the hepatic expression of MC1-R, thus limiting the incremental effect of genetically induced MC1-R deficiency on hypercholesterolemia and hepatic lipid accumulation.

We have previously studied the effects of pharmacological MC1-R activation in Western diet-fed mice and observed that chronic treatment with a selective MC1-R agonist reduced plasma cholesterol level and upregulated hepatic Ldlr expression without affecting body weight gain (Rinne P et al, Circulation. 2017 Jul 4;136(1):8397.). These findings are also discussed on manuscript page 12, lines 475-478. Although the selective MC1-R agonist was different in that particular study, it is expected that LD211 would also elicit a similar cholesterol-lowering effect in Western diet-fed mice. Chronic treatment with a-MSH, on the other hand, would likely produce wide-ranging metabolic effects. In addition to MC1-R activation in hepatocytes and its consequent effect on liver cholesterol metabolism, a-MSH would affect feeding, energy expenditure and cholesterol metabolism via MC4-R activation in the central nervous system as well as fatty acid and glucose metabolism via MC5-R activation in the skeletal muscle. Therefore, the phenotype associated with a-MSH treatment would be complex and mediated by multiple mechanisms and MC-R subtypes, thus making it difficult to interpret the exact contribution of hepatic MC1-R signaling to the observed phenotype.

Reviewer #2 (Public Review):

Keshav Thapa et al. investigated the role of melanocortin 1 receptor (MC1-R) in cholesterol and bile acid metabolism in the liver. First, they observed that MC1-R is present in the mouse liver and that its expression is reduced in response to a cholesterolrich diet. To determine the role of MC1-R in the liver, they generated hepatocyte-specific MC1-R KO mice (L-Mc1r-/-). These animals exhibited a significant increase in liver weight, lipid accumulation, triglycerides and cholesterol levels, and fibrosis in comparison with control mice. By performing liquid chromatography-mass spectrometry, the authors also found that L-Mc1r-/- mice also have fewer bile acids in the plasma and faeces, but not in the liver. In accordance with these findings, mRNA/protein expression of different genes involved in these processes were altered in L-Mc1r-/- animals.

Secondly, in an attempt to evaluate the underlying mechanisms, they measured the expression of MC1-R in HepG2 cells under different treatments (i.e., palmitic acid, LDL, and atorvastatin). Moreover, they stimulated these cells with the endogenous MC1-R agonist - MSH, where they show that this molecule decreases the free cholesterol content, whereas increasing LDL and HDL uptake, as well as recapitulates some previously observed phenotypes in the proportions of bile acids. These effects were also encountered when using a selective agonist for MC1-R (i.e., LD211), further supporting the specific role of MC1-R. Finally, some experiments indicated that -MSH evokes not one single, but multiple intracellular signalling cascades for which MC1-R activation effects might take place.

Overall, this work provides novel and interesting findings on the role of MC1-R in cholesterol and bile acid metabolism in the liver, which undoubtedly will have some crucial implications for future research. Nevertheless, some experimental details should be better explained for the correct interpretation of the data. Besides, discrepant results exist regarding the molecular mechanisms behind MC1-R action that requires additional experimentation to support the conclusions drawn.

We thank the reviewer for the encouraging and insightful comments, and we are pleased to read that the manuscript has raised considerable interest.

Author Response

Reviewer #1 (Public Review):

The authors aim to understand the role of clonal heterogeneity of tumors in immunogenicity of clonally expressed antigens. This is a significant problem with many basic as well as translational implications.

The strength of the manuscript lies in the novel demonstration that a poorly immunogenic tumor antigen, when paired with a stronger tumor antigen, begins to elicit significant immune response. The weakness lies in the fact that the actual mechanism of the key demonstration is never shown. There is a lot of speculation and tangential experimentation, but little actual evidence of a mechanism.

By making the key observation (mentioned in the strength section in the previous paragraph), the authors did achieve their objective albeit very partially. Their observation is based on excellent experimental tools and design. This study will stimulate further experiments in this important field.

Their key observation is somewhat reminiscent of the practice of conjugating small "non-immunogenic" antigens (such as some carbohydrates) to large protein carriers (such as serum albumin) in order to elicit strong antibody response to the weaker antigen. It is interesting to contemplate if the underlying mechanisms have any commonality.

We thank the reviewer for their consideration of our work and their constructive feedback. We concur that our study has limitations and further work will be necessary to fully deconstruct the mechanism leading to the observed phenotype. We have revised the text to better reflect the aim and scope of our study. However, the goal of our work was to establish a trackable model that would allow us to model different, albeit limited, degrees of antigen expression patterns reflecting what is observed in patients with different levels of ITH. Our key observation reproduces what is observed clinically, adding strength to the model. Next, we wanted to study what was different about the induced immune responses to develop strategies to better treat tumors with heterogeneous NeoAg expression patterns that currently do not respond to checkpoint blockade therapy. Studying KP-HetHigh and KP-HetLow tumors revealed that tumor debris-carrying cDC1 draining from KP-HetLow tumors phagocytosed both NeoAgs. This population of cDC1, carrying both NeoAgs, had a more stimulatory phenotype compared to cDC1 without tumor debris or cDC1 that had engulfed only one NeoAg. We were able to develop a targeted therapy including CD40 agonism based on our key observations: KP-HetLow had a more robust response towards the weaker NeoAg which was associated with more stimulatory cDC1 presenting both NeoAgs compared to KP-HetHigh tumors. The stronger immune response increased responsiveness to CBT.

The reviewer makes an interesting point about conjugate vaccines, which canonically elicit greater responses because they engage multiple immune cells, namely T cells with B cells, resulting in stronger antibody responses. The prevalence of tumor debris-carrying cDC1 with both neoantigens in KP-HetLow does make us consider that this population of cDC1 may be engaging multiple immune populations, i.e., different neoantigen-specific T cells. We suggest this as a possible mechanism for greater Aatf responses, but further work is necessary to determine if the same cDC1 can directly interact with both neoantigen-specific T cells.

Reviewer #2 (Public Review):

There are data to suggest that intratumour mutational heterogeneity (ITH; the proportion of all mutations that are found only within cancer subclones) is associated with worse therapeutic outcomes. Specifically, patients with more mutations (and thus neoantigens) mostly expressed by subclones (high ITH) have poorer responses to checkpoint immunotherapy. The authors set out to explore the mechanisms underlying this by studying 2 dimensions of neoantigen biology: firstly, distribution (clonal vs subclonal) and secondly, immunogenicity (weak vs strong binding to MHC class I). Using a panel of lung cancer cell lines modified to express individual or dual neoantigens in order to model clonal and subclonal expression, elegant studies show that clonal co-expression with a "strong" neoantigen can boost the immunogenicity of a "weak" neoantigen and result in tumour control. Mechanistically, this is related to engulfment of both neoantigens by cross presenting type 1 conventional dendritic cells and the associated enhanced activation state of this cell type. This is an interesting and potentially important finding that may be related to mechanisms of epitope spreading as immune responses diverge from targeting more to less immunogenic epitopes. Overall, the study is thought-provoking, informative in relation to how neoantigen immunogenicity is shaped and may have practical relevance.

We greatly appreciate the constructive comments from the reviewer and their insightful comments and questions on our work. We have edited the text in response to their feedback. We believe these changes have made the writing clearer and more effectively communicates the scope of our study and our results to the reader.

Author Response:

We would like to thank the Editors and Reviewers for their positive evaluations, constructive comments, and for the opportunity to revise our manuscript. We feel that the comments and suggestions will further improve our manuscript.

In the updated manuscript we aim to incorporate all suggested changes and considerations provided by the Reviewers. In particular, we will provide further information on the quality-control ratings per subfield, as suggested by Reviewer 1. Moreover, we will evaluate whether the training-related changes were specific to CA1-3, rather than just showing significant alterations in CA1-3 and not in the other subfields. Last, as suggested by Reviewer 2, we will additionally test for multivariate associations between hippocampal subfield structure and function, to further evaluate the specificity of hippocampal subfield change as a function of training and cortisol.

Author Response

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

Reviewer #1 (Recommendations For The Authors):

This study is well presented and contains all the necessary experiments to support their claims. They made the interesting finding of an additional factor Dyn2. However, it is unclear whether it is present in the human complex. Hence, it would be interesting to see whether Dyn2 co-purifies when expressed with the other complex components in insect cells. Also, purification of a tagged complex from yeast would have indicated whether Dyn2 is part of the complex and whether other factors, like RBM15 or Hakai, present in humans are also present in yeast.

We agree that Dyn2 subunit is an exciting new finding that is worth further investigation. The IP-MS experiments suggest that Dyn2 is subunit of the complex and that the Dyn2 interaction is mediated via Slz1. We also noticed a reduction in m6A levels (50%) in the dyn2 deletion mutant. What the function of Dyn2 is and whether it is conserved remains to be determined.

Our IP-MS experiments with Mum2 identified the complex as described in the manuscript, however we did not find evidence of orthologs of RBM15 and Hakai. More follow up work is needed using in vivo and in vitro assays are needed to determine how m6A by the yeast MTC is regulated.

P3 top: Although m6A is the most abundant internal methylation variant, it is far below the methylation levels of cap-adjacent nucleotides in mammalian mRNAs (PMID: 35970556 ).

We have added the word “internal” to the first sentence of the introduction.

A list of author contributions is missing.

We have added this in the revised version.

Reviewer #2 (Recommendations For The Authors):

Most of the conclusions of this paper are well supported by data, and the text is clearly written and easy to read. Here are my suggestions and comments:

1) In Fig.2, why not use LC-MS to measure m6A levels in Ygl036w, Dyn2, Pab1, Npl3 mutants, as in Fig.1?

For measuring m6A levels, we use combination of LC-MS and m6A ELISA and m6A-seq2 throughout the manuscript. We used ELISA in the Fig2 because we had established this assay in the lab (Ensinck et al, RNA Journal, 2023). M6A-ELISA technique was more accessible and easier to execute compared to LC-MS. Additionally our collaborator for the LC-MS moved his lab to another country, which made it impractical to continue the use of LC-MS.

2) The protein purification experiment described in Fig. 4D is informative. Can they include Dyn2 in the expression system as well?

Thank you for the suggestion. Dyn2 was not the focus of the manuscript as Dyn2 has, at best, only a minor role in m6A deposition in vivo. We are also currently aiming to dissect how Dyn2 regulates m6A and the yeast MTC in follow up work. Hence we decided not to add more experiments on Dyn2 to the current manuscript.

3) Among the MTC components identified in this study, Dyn2 is a new and interesting subunit. It was shown that in C. elegans Dlc1 is involved in stabilizing the m6A writer Mett10. I wonder if yeast has a homolog of C. elegans Mett10?

As far as we know, there is no ortholog identified of Mett10 (METTL16 in mammals) in budding yeast.

4) The authors have emphasized "the m6A dependent and independent functions"; however, this is only based on previous observations. Is it possible that the less severe phenotype associated with ime4 catalytic mutant is due to residual catalytic activity? I think the data presented in Fig. 5 tell us that Ime4 and other MTC subunits have no additional moonlighting function. It is not entirely clear to me what "the m6A-independent function" is.

The observation that the yeast MTC complex has m6A dependent and independent function is based on the previous observations and the current work. In Agarwala et al 2012 PLOS Genetics, it was shown that mum2 and ime4 deletion mutants have more severe phenotype than slz1 deletion mutant or the catalytically inactive mutant of Ime4. We confirmed these observations in the revised manuscript (see Figure S5A and S5B). In this work, we showed that kar4 and vir1 deletion mutants have comparable delay in the onset of meiosis as mum2 and ime4 deletion mutants. Also, the MTC remains intact with absence of Slz1, but falls apart in ime4D, mum2D, vir1D or showed strongly reduced RNA binding (kar4 deletion mutant). Based on this we conclude that an m6A independent function of the MTC exists.

We have included data demonstrating that the catalytically inactive mutant has no residual m6A and a milder meiotic phenotype compared to the ime4 deletion mutant (see Figure S5A and S5B).

5) In Mum2-TEV-ProA IP (1B) and Kar4-TEV-ProA IP (S1A), Slz1 was not significantly enriched; however, in the repeated Mum2-TEV-ProA IP with/without RNAse (S1B, 4C), Slz1 was strongly enriched. Why are the Slz1 results so variable?

This is an astute observation, for which we do not have a definitive answer. One possibility is that Slz1 is the only subunit that is induced during meiosis. It is possible that induction of Slz1 varied between the different IP-MS experiments, hence leading to variability in its association with the MTC complex.

6) The last paragraph on page 11, "Collectively...", and the first paragraph on page 12, "Collectively...", seem redundant.

We have removed the duplicated paragraph in the revised manuscript.

Author Response

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

Reviewer #1 (Public Review):

Membrane receptor guanylyl cyclases are important for many physiological processes but their structures in full-length and their mechanism are poorly understood. Caveney et al. determined the cryo-EM structure of a highly engineered GC-C in a complex with endogenous HSP90 and CDC37. The structural work is solid and the structural information will be useful for the membrane receptor guanylyl cyclases field and the HSP90 field. However, a detailed characterization of the protein sample is lacking. Moreover, the physiological significance of this structure is not fully exploited by supporting experiments and the mechanistic insight is currently limited.

We thank Reviewer #1 for constructive reviews and agree that this work forms the basis for future exploration by the guanylyl cyclase and HSP90 fields.

1) The characterization of the protein sample is lacking. SDS-PAGE would be useful to identify potential proteolysis, leading to the dissociation of GC dimer. Further size-exclusion chromatography would be helpful to estimate the molecular weight of the complex and to determine if only GC-C monomer is purified.

We have included a representative SDS-PAGE gel in our revised version of the manuscript (Figure 1—figure supplement 1). While we agree that SEC could be beneficial to further explore the stoichiometry of the imaged sample, we see no significant degradation of the guanylyl cyclase via SDS-PAGE, and therefore believe that the zippered construct would remain dimeric. Relatively poor yields of these samples precluded further exploration in this regard.

2) The orientation distribution of the particles is not homogenous in Fig. S1D. It would be helpful to present the 3DFSC curve to evaluate the effect of preferred orientation on the reconstruction.

While the orientational distribution is not perfectly uniform, the provided angles allowed for sufficient reconstruction of maps with no notable anisotropy. We have included 3DFSC curves in our revised version of Figure 1—figure supplement 1.

3) Description of protein expression details is lacking. Did the author use transient transfection, stable cell line or virus-mediated transduction?

We have clarified that these cells were expressed using transiently transfected ExpiCHO cells.

4) HSP90 binds ATP and is often co-purified with endogenous ATP/ADP. Is there ATP or ADP present in the sample/cryo-EM maps? Is the conformation of NBD similar to ATP-bound HSP90? The author needs to include the description/figures about the nucleotide state of HSP90.

There is clear density for present nucleotide in our reconstruction. Given the mechanistic role for ATP turnover in the release of HSP90 client (Young, Hartl, 2000 – PMID 11060043) and the resolved density, we believe the identity for this nucleotide is ATP. We have added comment to this regard in the revised manuscript: “…the C2 pseudosymmetric, ATP bound, closed state Hsp90 dimer.”

5) The catalytic domains of GC have to be dimerized to perform cyclase function. The presence of only one GC-PK monomer in the cryo-EM structure indicates the structure does not represent an active state of GC. These results suggest the GC expressed in this way is not functional. The authors need to explain why most of the GC protein is trapped in this inactive form.

Indeed, we do believe that this regulatory state is non-functional, as observed for active kinases. We have clarified this in the revised manuscript: “In addition, this disruption of the native state of GC-C, as observed in our structure, would likely leave GC domains out of each other’s proximity, precluding their catalytic activity while Hsp90 is bound.”

6) The GC-C construct used here is a highly engineered "artificial" construct, which has not been fully characterized in this work. Does this construct have similar activity as the activated wt GC-C? Does the protein (this engineered construct) expressed in CHO cells show activity?

While our original goal in developing this construct was to create an imageable construct that was locked in the active state, our current interpretation of the data is that the leucine-zipper induced, putative active geometry leads to the majority of this construct falling into the regulatory state with HSP90 binding. We make no claim to have resolved an active conformation in this work, yet believe that this state is of note due to the previously unresolved nature of these regulatory complexes for guanylyl cyclase receptors.

7) Are the residues on the interface between GC and HSP conserved in other members of membrane receptor guanylyl cyclases? Would mutations on this interface affect the activity of GC?

Given the role this structure plays in our understanding that HSP90 client recruitment is largely not driven by specific residue interactions and the ~30% identity of GC-C to NPR-A and NPR-B, we do not believe that mutations that do not significantly change the stability or fold of the PK domain would significantly modify recruitment to HSP.

8) The authors propose that targeting HSP90 would tune the activity of GC. Is there any experimental data supporting this idea?

Based on the work of Kumar et al., 2001 (PMID 11152473), we do believe that there is a functional link between HSP90 recruitment and GC activity. We hope that this work will spark further exploration of these concepts.

9) The model in Fig. S3 is largely speculative due to the lack of supporting functional data. In addition, it would be better to change the title to "structure of the protein kinase domain of guanylyl cyclase receptor in complex with HSP90 and cdc37" because the mechanistic insight is limited.

We agree that our supplemental figure is more speculative. We have referenced this in the discussion section of the manuscript and put this figure in the supplement to ensure that this is understood to be more speculative in nature.

Reviewer #2 (Public Review):

Caveney et al have overexpressed an engineered construct of the human membrane receptor guanyl cyclase GC-C in hamster cells and co-purified it with the endogenous HSP90 and CDC37. They have then determined the structure of the resultant complex by single particle cryoEM reconstruction at sufficient resolution to dock existing structures of HSP90 and CDC37, plus an AlphaFold model of the pseudo-kinase domain of the guanylyl cyclase. The novelty of the work stems from the observation that the pseudo-kinase domain of GC-C associates with CDC37 and HSP90 similarly to how the bona fide protein kinases CDK4, CRAF and BRAF have been previously shown to interact.

The experimentation is limited to the cryoEM analysis, and is lacking additional studies that would give deeper insight into the oligomeric nature - if any - of the GC-C when bound to HSP90-CDC37 as compared to the free protein. This is relevant, as the dimerization domain downstream of the pseudokinase, is evident in the maps - albeit not well resolved - and it is not clear whether it is still able to mediate dimerization with a second free or HSP90-CDC37bound GC-C. It would also be good to see some experimentation that asks whether association with HSP90-CDC37 inhibits the guanyl cyclase activity. It is clear from previous work that HSP90-CDC37 silence the kinase activity of their bound client kinases, but in this case the catalytic guanyl cyclase is not directly associated with the chaperone complex and may still be able to function.

Given the geometry of the interaction, the dimerization domain of the GC would likely be monomerized, albeit with global dimerization remaining – contributed by the ECD, or in our case the liganded-ECD mimicking leucine zipper. Experimentally, it has been shown in live cells (Kumar et al., 2001, PMID 11152473) that the HSP90 association is required for maximal GC-A function. This is likely due to some sort of resetting nature to the associating to allow further activity, as opposed to activity during the association – given the latter is unlikely based on our structure, where the two GC domains would not be able to form the active dimerized state. Further dissection of this, while outside the scope of the current work, is of great interest.

Although the sequence alignment presented in SuppFig 2 shows that GC-C conserves the classic DFG motif that plays a critical role in the regulation of most kinases, the numbering of the sequence is absent, making it very difficult to relate this to the structural detail shown in Fig 2B. This needs to be clarified, as the interaction of CDC37-Trp31 with the DFG motifs and downstream activation loops in CRAF and BRAF have been proposed as important features of the selectivity of these kinases for the HSP90-CDC37 system, and it would be good to be able to see clearly how much of this is also conserved in the GC-C pseudokinase domain interaction. For example, is the much shorter activation segment (DFG -> APE) ordered in the complex or disordered?

We have clarified Figure 2—figure supplement 1 with additional numbering. While we agree that the DFG motif may play a role in recognition, only the first residue of this motif is interacting with CDC37 in our structure, so it may be likely that the role of this motif is more structural in maintaining a CDC37 complementary fold, as opposed to direct residue interactions. Additionally, many kinases which are not regulated by CDC37/HSP90 contain this motif. The shorter DFGAPE of GC-C is traceable with the exception of N613, S614, I615, though the density in this region reflects this loop not being well stabilized.

It was not easy to follow what was in the sample used for cryoEM. The cloning of the guanylyl cyclase (GC) component is described in the methods and they have shown some illustrations in fig 1 but a proper numbered figure of the domain organisation clearly showing domain boundaries and linker segments is really needed for a reader not familiar with the structure of GCs, especially since they have replaced the ECD with a leucine zipper in their construct. It is important to show a domain figure of what this construct looks like as well, as from the illustrations in fig 1 for examples its hard to see what's PK, DD, GC domains. It would also be helpful to see in the supplementary a gel of complex they put on the grids, to make it clearer what exactly the sample is and to reassure that the GC-C domains that are not resolved in the cryoEM are nonetheless present in the sample.

We have added in a gel figure to the supplement and clarified the content of the imaged construct in the methods section: “This construct contains all domains of the native GC-C, with the exception of the ECD.”

Overall there is only minimal proposal of mechanism or biological function based on the structure. The speculation in the Discussion of two fates - PP5 dephosphorylation or E3 ligase recruitment, is not supported by any experimentation, which is reasonable for speculation, but is also not underpinned by reference to any previously published work suggesting that these additional processes may be important. In the absence of any work by the authors can they put these speculations more in context with previously published work that supports the importance of these processes specifically for GC regulation?

We have ensured that these potential pathways only appear in the discussion section. It has been observed, for instance by Oberoi et al., 2022 that phosphatases can act on all components of a HSP90–CDC37–client system. Given there are well characterized phosphorylation sites for membrane GC receptors, we believe this is worth discussing in this manuscript, to stimulate further exploration of these mechanisms in the field. In addition, it has been reported that many E3 ligases are recruited to HSP90 complexes and can degrade rather non-specifically. It has been shown that one can generate PROTAC-like molecules to target non-specific clients to HSP90–E3 ligase machinery for degradation (Li et al., 2023). Given this proximity induced nature to E3 degradation of HSP90 clients, it would be highly likely that, at least in some cases, mGCs would be degraded by this mechanism as well.

Reviewer #3 (Public Review):

A detailed understanding of how membrane receptor guanylyl cyclases (mGC) are regulated has been hampered by the absence of structural information on the cytoplasmic regions of these signaling proteins. The study by Caveney et al. reports the 3.9Å cryo-EM structure of the human mGC cyclase, GC-C, bound to the Hsp90-Cdc37 chaperone complex. This structure represents a first view of the intracellular functional domains of any mGC and answers without doubt that Hsp90-Cdc37 recognizes mGCs via their pseudokinase (PK) domain. This is the primary breakthrough of this study. Additionally, the new structural data reveals that the manner in which Hsp90-Cdc37 recognizes the GC-C PK domain C-lobe is akin to how kinase domains of soluble kinases docks to the chaperone complex. This is the second major finding of this study, which provides a concrete framework to understand, more broadly, how Hsp90-Cdc37 recruits a large number of other diverse client proteins containing kinase or pseudokinase domains. Finally, the Hsp90-Cdc37-GC-C structure offer clues as to how GC-C may be regulated by phosphorylation and/or ubiquitinylation by serving as a platform for recruitment of PP5 and/or E3 ligases.

Comments:

1) The authors used an interesting approach to obtain the GC-C-Hsp90-Cdc37 complex. Flagtagged human GC-C was overexpressed in CHO cells with the expectation of co-purifying endogenous hamster homologs of Hsp90 and Cdc37. There are several points worth noting:

a) It is not clear from the data presented (Figure 1C, Suppl Fig 1A) or the Methods the percentage of particles in the cryo-EM specimen that represent the GC-C-Hsp90-Cdc37 complex. Presumably, some fraction of GC-C isolated will not be associated with Hsp90Cdc37. If a very large portion of GC-C is associated with Hsp90-Cdc37, it would be good to explain why this is to be expected. Are 2D/3D classes corresponding to the activated GC-C dimer found? If not, why?

While we see some traces of GC-C not bound by Hsp90, there is, in the least, a significant alignment bias for the Hsp90 bound complex. We believe that the engineered construct, which we designed to be locked in a putative active conformation, is going through catalytic cycles to some point where the regulatory mechanism is kicking in. It may be that for proper resetting of the receptor, the receptor needs to cycle back through an unliganded, inactive conformation, which our leucine zipper construct is unable to allow, thus locking our GC in the regulatory complex, though this is speculation.

b) Figure 1A suggests that GC-C is phosphorylated before recruitment of Hsp90-Cdc37. What is the phosphorylation status of the GC-C specimen that was imaged by cryo-EM?

We had placed the P in grey in this figure to represent the potential for the active state to be phosphorylated. For GC-C in particular, the phosphorylation state does not affect activity as much as GC-A and GC-B for example. We have removed this P from the figure for clarity.

c) The resolution of the cryo-EM map (3.9 Å) is too low for unambiguous identification of proteins. Please provide more precise justification for the claim that the densities observed do in fact correspond to hamster Hsp90 and Cdc37.

While we agree that the resolution is limiting for protein identification, the fact that we are using a very stringent FLAG purification allows confidence in the ID for our target, GC-C. For Hsp90 and Cdc37, we are confident that they are endogenous hamster Hsp90 and Cdc37, given the large structural similarity observed in comparison to prior Hsp90/Cdc37/client complex structures, and the ID/register well confirmed by the placement of bulky residues.

d) The authors state that human GC-C pulls down hamster Hsp90-cdc37 but soluble kinases cannot, despite the high sequence identity between human and hamster Hsp90-cdc37. Is this because GC-C recognition is more promiscuous? Can this difference be understood in light of the new structural information presented?

“This native pulldown strategy contrasts with the structures of Hsp90–Cdc37 in complex with soluble kinases (García-Alonso et al., 2022; Oberoi et al., 2022; Verba et al., 2016), for which Hsp90 and Cdc37 had to be overexpressed to obtain complex suitable for imaging.”

It is our understanding, from reading the papers cited above, that Hsp90/Cdc37 needed to be overexpressed to obtain these samples for imaging. We use a different strategy because our sample does not require overexpression of Hsp90 and Cdc37. This may be because of something specific to hamster cells, which were (presumably) not tested in the above studies, or it could be something specific to do with GC-C.

2) A large portion of the enforced GC-C dimer was not visible in the cryo-EM maps. It is not easy to learn from Figure 1 exactly which parts of the GC-C construct was sufficiently ordered and observed structurally. Please improve Figure 1.

We have adjusted Figure 1 to better depict what is observed in the cryoEM density.

3) On page 4, the authors claim that they are able to orient the GC-C-Hsp90-Cdc37 complex "as it would sit on a membrane" and referred to Figure 1B. It is not clear what is implied here. Does Hsp90-Cdc37 binding constrain the complex to face the inner leaflet of the membrane in a specific orientation as shown in Figure 1B? If true, this could potentially have important functional implications. Please illustrate how this was deduced based on the information available.

Given the observed density for the PK domain, which is membrane proximal, we can safely assume that the TM would be located immediately above this region. Given the size of Hsp90 and assuming the soluble Hsp90 must sit below the membrane, we can determine, with some accuracy the relative orientation of this complex next to the membrane. This orientation is depicted in Figure 1B.

4) Also on page 4, it is stated that it is sterically unlikely an additional Hsp90-Cdc37 complex is associated with the other copy of GC-C in the leucine zippered dimer. It is not obvious to the reader how this may be the case. An additional figure could help make this more clear. Additional biochemical evidence will also help. The absence of GC-C-Hsp90-Cdc37 dimers in cryo-EM micrographs can also support the argument.

We have clarified this: “is sterically unlikely that an additional regulatory complex is forming on the second GC-C in a concurrent fashion, given the large size of the first Hsp90–Cdc37 and the requisite proximity of the second GC-C.”

5) Some comments on Figure 2:

a) NTD and CTD are mislabeled in Figure 2A.

Thank you for catching this, we have fixed this.

b) The authors should show cryo-EM density to support their modeling of GC-C in Figures 2B and C.

We have provided maps and models to the reviewer and will release these maps and models upon publication so that all relevant densities can be interpreted to their fullest extent by readers. In addition, we have added representative density panels to Figure 1-figure supplement 2.

6) The authors claim that Hsp90-Cdc37 clients are more similar structurally near the cdc37 interface. Please illustrate this with additional figures. Suppl. Figure 2 is inadequate for this purpose.

We have added a structural overlay to Figure 2—figure supplement 1A to illustrate this.

The authors can also consider adding a more detailed discussion comparing the interactions between the pseudokinase/kinase C-lobe and Cdc37 in known structures. Is shape/charge complementarity a universal feature of cdc37-dependent kinase/pseudokinase recruitment? It would be interesting to also consider if it would be possible to predict which of the ~60 human pseudokinases are possible Hsp90-Cdc37 clients. New structural findings from this study and publicly available AI-predicted protein structures could help.

While the use of AI to predict pseudokinase interactions would indeed be interesting, we believe this is outside the scope of this work. Given methodology is in place for determination of kinase clients for Hsp90 (Taipale et al., 2012), this could be an additional route to obtain this information in future work.

Reviewer #2 (Recommendations For The Authors):

In Figure 1B the authors show a large unaccounted-for region of density which they speculate may be due to the dimerization domain. That this is lost in the sharpened maps suggests that it is more mobile than the core which probably dominates the automatic mask generation used by cryoSPARC. It would be very interesting to try and resolve this region further by using focussed classification and refinement - probably in RELION. This would add further novelty, as so far in the three HSP90-CDC37 kinase complexes previously described, little is seen outside the C-terminal lobe of the kinase (or in this case pseudokinase) lobe.

Given the structurally uncharacterized nature of the DD and GC domains for mGCs, using computational means to further our understanding of these regions was attempted. Across several software packages, these attempts were unsuccessful. We will be uploading these micrographs to EMPIAR shortly after publication, which will allow for other groups to re-process this data as they see fit and as new software techniques emerge in this rapidly developing field. We believe that the partially unfolded nature of the PK domain is providing too much of a hinge point prior to the DD for the software to be able to resolve this currently.

Author Response

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

Reviewer # 1

Specific comments

1) Figure 1: it is unclear how many mice were used for the described phenotypic analyses (panels D and E). Please clarify.

We acknowledge that we made a mistake in failing to clearly describe the phenotypic analyses. In Figure 1D and E, we performed statistical analysis on the number of TEBs in whole mammary mounts. One mouse stained a mammary whole mount with Carmine-alum staining. Thus, “n” represents the 10 mice we analyzed. We have modified the legend of Figure 1 to " D, E. Quantification of the average number of TEBs and bifurcated TEBs in littermate Crb3fl/fl (n=10) and Crb3fl/fl;MMTV-Cre (n=10) mice at 8 weeks old" in lines 909-911.

2) Figure 2: in panels B and C it is unclear how the data was quantified; the legend states "n=10", does this mean the experiment in B was done 10 times? And that 10 acini per condition were measured in panel C? In panel D a difference in 0.3% between NC and shCRB3 seems miniscule; do the authors mean 30% instead? And how many acini were counted per condition per (how many) experiments? Same applies to panels G and H, it is unclear how many cells were analyzed per (how many) experiments.

Thanks for your suggestions. We failed to describe the details of the statistical analysis well in the experimental method. To provide a brief overview of our statistical analysis method, we took 3-4 random bright-field micrographs of each well in the chamber slide system and repeated the experiment three times. We then counted the number of acini in all micrographs (Figure 2B) and examined the diameter of all acini in each photograph, averaging the values as data (Figure 2C). We also determined the percentage of aberrant acini in each photograph, which was used as an analysis value (Figure 2D). We carefully confirmed that the vertical axis of Figure 3D was indeed mislabeled and should mean 30%, and revised the original figure. For IF analysis of the mitotic spindle orientation during lumen formation, we examined the division angle of one cell in one acinus that was mitotically dividing, 3-4 acini were randomly examined in each well in the chamber slide system, and this experiment was repeated three times (Figure 2G and H). Therefore, we have provided a detailed description of these issues in the Figure 2 legend. The revised parts are found in lines 922-924, lines 926-927, lines 929-930, and line 932.

3) Figure 2: it would be desirable if authors were able to quantify the data in panels E and I.

Thank you for your comments. According to your suggestions, we performed the quantitative analysis of Figure 2E and I, which is now presented in the new Figure 2D and H.

4) For all cell-based assays using shRNA to knock down CRB3 (Fig. 2A-H; Fig. 3A-F; Fig. 4C-E; Fig. 5G-J; Fig. 6C; Fig. 7C, D; Fig. 8E-G), it would be desirable to perform rescue experiments to ensure that the observed phenotype of CRB3 depleted cells is specific and not due to off-target effects of the shRNA.

Yes, rescue experiments involving overexpression of CRB3 in CRB3 depleted cells can accurately account for the specific phenotype as well as eliminate the off-target effects of shRNA. However, our group has long focused on the role of the cell polarity protein CRB3 in contact inhibition and tumorigenesis. Our previous studies have ruled out the off-target effects of shRNA and reported that CRB3 regulates contact inhibition and tumorigenesis through Hippo or Wnt signaling pathways (Cell Death Dis 2017;8(1):e2546, Oncogenesis 2017;6(4):e322, J Cell Mol Med 2018;22(7):3423-33). Therefore, we will pay close attention to rescue experiments to ensure experimental integrity and phenotypic specificity in our subsequent studies.

5) Figure 3: how many cells were counted/measured per condition (in how many experiments) in panels B, D, H, F, G and H? In panels C and D, what is the CRB3 protein level in these cells? This is of relevance as protein overexpression per se could impinge on ciliation frequency. This question could be addressed by performing a western blot analysis with CRB3 antibody.

We did not clearly describe the measurement and statistical analysis methods in the previous manuscript. Similarly, we took 3-4 random IF and SEM micrographs of each sample in one experiment, and this experiment was repeated three times. Subsequently, the number of ciliated cells and total cells were counted, and the proportion of ciliated cells was calculated (Figure 3B, D and F). In these figures, the cilium length of representative ciliated cells was measured in each photograph. In the knockout mouse model, we needed to find the intact mammary ductal lumen and renal tubule in IF staining of mouse mammary and renal tissue sections, with 5-6 random fields micrographs taken per slice, and the proportion of ciliated cell was measured by counting and taking the average. A total of ten mice were repeated in these experiments (Figure 3G and H). Therefore, the legend of Figure 3G and H has been partially modified and a detailed description has been added to the Figure 3 legend. The revised parts are in lines 945-946, lines 950-951, line 953.

Thank you for your suggestions that we perform a western blot analysis with CRB3 antibody in Figure 3C and D. And we have added the western blotting with CRB3 analysis in the new Supplementary Figure 3A.

6) Figure 3G: it is very difficult to see that the red stained structures are primary cilia.

Yes, the staining structure of primary cilia in mammary ductal lumen are less clear than that of individual cells and in renal tubule in Figure 3G. We used recognized acetylated tubulin and γ-tubulin to stain the primary cilia, which were clearly labeled in individual cells. However, the labeled primary cilia in renal tubule were longer length and demonstrated a more pronounced structure than those in the mammary ductal lumen. In the mammary ductal lumen of the 10 mice we analyzed, the primary cilia showed shorter length and staining structure than the others shown in Figure 3G. This difference may be due to the distinct characteristics of primary cilia in different tissues.

7) Figure 4B: how many cells were analyzed in how many experiments?

Our statistical methods for analyzing cellular experiments using IF were essentially the same. We randomly selected 3-4 IF micrographs of each sample in one experiment, and this experiment was repeated three times. Subsequently, the number of colocalization cells and total cells were counted, and the proportion of cells with pericentrin and CRB3 colocalization was calculated (Figure 4B). The detailed description has been added to the Figure 4 legend. The revised part is in lines 962-963.

8) Lines 217-219: since the cells were not stained with a cilia marker, only a centrosome marker, the claim that CRB3 localizes to the base of cilia is unsubstantiated.

Thank you for your comments. The base of cilia is the basal body, which develops from the mother centriole of the centrosome (Cancer Res. 2006;66(13): 6463-7). Firstly, we found colocalization of CRB3 and pericentrin, a centrosome marker, in MCF10A cells (Figure 4A and B). Secondly, we verified the colocalization of CRB3 with γ-tubulin, a marker of basal body in primary cilia, in confluent quiescence cells (Figure 4C and D). In addition, we found that CRB3 was localized at the base of primary cilia labeled with acetylated tubulin (Figure 4E and F). Due to the species of commercialized CRB3 antibody, we were able to indirectly claim that CRB3 localizes to the base of cilia through these experiments.

9) Figure 3 and Figure 4: is it problematic to use gamma tubulin as centrosome marker if CRB3 depletion causes reduced centrosomal recruitment of gamma tubulin ring complex components? Also, in Figure S3A no gamma tubulin staining can be seen in the lower panel, why?

Thank you for your positive comments. As is well known, γ-tubulin is a marker of the centrosome, and we found that CRB3 depletion causes reduced centrosomal recruitment of gamma tubulin ring complex components. However, Our Figure 3 was illustrated the effect of CRB3 on ciliary assembly, and Figure 4 was analyzed the localization of CRB3 in primary cilia. In some reports on ciliary assembly, the fluorescent double staining of acetylated tubulin and γ-tubulin have been used to label primary cilia, and the effect of target genes on ciliary number and assembly were analyzed by these markers (Nature. 2013;502(7470): 254-7, Cell. 2007;130(4): 678-90 and so on). Although CRB3 affects the recruitment of gamma tubulin ring complex components, it does not affect the analysis of ciliary number and localization in Figures 3 and 4.

In Figure S3A, green staining labeled with γ-tubulin could be clearly found in the lower left panel. The representative area from the left amplification may have been poorly selected, resulting in no γ-tubulin staining on the right side. We have updated the lower right panel in the new Supplementary Figure 3B.

10) Figure S4A: the grouping of indicated proteins is factually wrong. For example, FBF1, SCLT1 and ODF2 are not IFT-B components, and several of the proteins indicated as localizing to the basal body also localize to (unciliated) centrioles. In contrast, CP110 is usually only found on unciliated centrioles and not mature basal bodies. Authors should consult the relevant literature and correct the figure accordingly. Alternatively, this misleading text/grouping could be removed from the figure. Furthermore, in the legend to Figure S4 there is no information provided about this quantitative analysis (how many independent experiments, which cells were analyzed etc.).

Thank you for your helpful suggestions. We have taken your advice and removed this misleading information from the manuscript, Supplementary Figure 4A and its corresponding legend. In the legend to Supplementary Figure 4A, we have added the detailed information for this quantitative analysis in the legend. The revised legend is shown in lines 1098-1100.

11) Figure S4B: how do authors know which of the bands correspond to CRB3 fusion protein?

Based on the construction strategy of the CRB3-GFP fusion protein (Figure 6D) and its base sequence, we were able to calculate its molecular weight. Then the molecular weight of CRB3-GFP fusion protein was verified by western blotting (Figure 6F and 7A). Meanwhile, exogenous overexpression allowed for the production of the CRB3-GFP fusion protein in large quantities. Due to these features, we could know that the band indicated by the black arrow is most likely CRB3-GFP fusion proteins. In order to check the molecular weight, we have labeled the key molecular weight markers in the new Supplementary Figure 4B.

12) Lines 251-253: this seems like data overinterpretation.

Thank you for your comments. We have revised this sentence in lines 252-254.

13) Lines 260-261: the data showing perturbed gamma tubulin localization is not convincing as data was not quantified.

According to your suggestions, we performed the quantitative analysis of Figure 4C, which is now presented in the new Figure 4E.

14) Figure 5H and Figure 6C: to show that the GCP6 IP actually worked, these blots should be probed also for GCP6.

Thank you for your good suggestions. We have added these blots probed for GCP6 in new Figure 5H and 6C.

15) Figure 5I: how many cells were analyzed in how many experiments?

Our statistical methods for analyzing cellular experiments using IF were essentially the same. We took 3-4 random IF micrographs of each sample in one experiment, and this experiment was repeated three times. The detailed description has been added to the Figure 5 legend. The revised part is in lines 992-994.

16) Figure S5: it looks like GPC6 and Rab11 are localizing all over the cell, are the antibodies used for the IFMs specific for these proteins?

After checking the specificity of these antibodies used for the IFMs, we have decided to delete the corresponding results in the Supplementary Figure 5 and their description in the original manuscript.

17) Lines 43, 89, and 314-315: the claim that CRB3 directly binds Rab11 is not supported by the data. The data provided only shows that these proteins interact indirectly. To show direct interaction, yeast-2-hybrid analysis or pull-down assays with purified proteins would be required.

Thank you for your positive comments. Since we were unable to complete the relevant experiments to demonstrate direct interaction of two proteins, we have revised our conclusions. Replace " CRB3 directly binds Rab11" with " CRB3 binds Rab11" in the manuscript.

18) Figure 6G and lines 314-315: this result is surprising as it indicates GTP- and GDP-locked versions of Rab11 have the same inhibitory effect on CRB3 binding? Please comment, and also indicate how data in Figure 6G was quantified (and how many independent experiments were used for the quantification).

We were also puzzled by the results shown in Figure 6G. Based on the western blotting bands, we suspected that there may have been some issues with the experiment. Specifically, we believed that the inefficient transfection of Flag-Rab11aWT, Flag-Rab11a[Q70L], Flag-Rab11a[S20V], and Flag-Rab11a[S25N] plasmids, as well as the insufficient amount of GFP antibody used in the co-IP experiment, led to the corresponding bands being too weak and masking the true differences.

To address this, we optimized the experimental conditions, strictly increased the experimental control, and repeated the experiment in triplicate. The new results are shown in the revised Figure 6G. The statistics from the three independent experiments revealed that CRB3b had a stronger interaction with Rab11a[Q70L] and Rab11a[S20V], while showing a weaker interaction with Rab11a[S25N], compared to Rab11aWT. As this result, we revised the original manuscript in lines 308-310 and added a detailed description to the Figure 6 legend in lines 1012-1013.

19) Figure 8G: data needs to be quantified.

Thank you for your comments. We replaced the unattractive bands in the western blotting of Figure 8G with better quality ones. The statistical analysis of the Figure 8G data is shown in Supplementary Figure 6.

Further minor comments

1) Abstract should indicate that this study describes conditional knockout of Crb3 in mouse mammary gland epithelial cells.

This is good writing advice. We have added the relevant description in lines 40-42.

2) Line 87: specify which gland (mammary?).

We have modified to " mammary gland" in line 87.

3) Line 140: sentence states that knockout of Crb3 is essential for branching morphogenesis in mammary gland development, I do not think this is correct.

We have removed the inappropriate finding.

4) Line 152: "formed more number" should be "formed more" or "formed higher number of".

We modified "formed more number" to "formed more" in line 154.

5) Lines 157-163: text and logic are difficult to follow for a non-expert.

We have modified the logic of this paragraph, as detailed in lines 158-165.

6) Figure 4A, C: figure resolution could be improved. It is difficult to see what the authors claim these figures are showing.

The clarity of the original images in Figure 4A and C is acceptable, while the images on the right are electronically enlarged. Although there is a decrease in pixels, it can still display our findings.

7) Figure 7D, E: images look pixelated.

The clarity of the original images in Figure 7D and E is acceptable using a laser confocal microscope, while the images on the right are electronically enlarged.

8) Line 222: unclear what authors mean by "detected a series".

We modified "detected a series" to "some important" in line 226.

9) Lines 221-225: which cells were used for the analysis in Fig. S4?

We used MCF10A cells for the analysis in Supplementary Figure 4, and modified its legend in line 1098.

10) Line 245: what is "cytomembrane"?

We modified "cytomembrane" to "cell membrane" in lines 246-247.

11) Lines 246-250: wording is unclear/difficult to understand.

We have modified this paragraph, as detailed in lines 248-251.

12) Line 273: should "regimented" be "sedimented"?

We modified "regimented" to "sedimented" in line 274.

13) Line 287-288: sentence does not make sense.

We have removed this sentence.

14) Figure 5A: it would be desirable to show the original dataset (Excel file) used for generating this figure.

To maintain data integrity, we should provide the original dataset (Excel file). However, there are some unpublished data in this file that we must withhold for the time being. If needed, the corresponding author can be requested to provide the file.

15) Lines 298-299: wording is unclear.

We have modified this sentence, as detailed in lines 296-298.

16) Lines 285-287: replace "instead of" with "but not".

We modified "instead of" to "but not" in line 286.

17) For all IFMs showing merged images of the green and red channel, please also show the red and green channel separately.

Most of our fluorescence images are presented separately for each channel in this manuscript, with only a few merged images due to space limitations. This type of presentation is commonly used in published papers.

18) Lines 326 and 327: replace "bonded" with "bound".

We have modified in lines 322-323.

19) Lines 327-328 and 361-364: wording is unclear/grammatically incorrect.

We have modified these paragraphs, as detailed in line 323 and lines 357-360.

20) Line 342: what is meant by "the combination of"?

We modified "the combination of" to "the binding of" in line 338.

21) Line 365: localization of what?

This means "subcellular localization" in lines 360-361.  

Reviewer # 2

Major points

1) CRB3 is present in mammals as 2 isoforms, A and B, originating from alternative splicing. In this study, the authors never mention this fact and when using approaches to KO or KD CRB3A/B they are likely to deplete both isoforms which have been shown to have different C-terminal domains and functions (Fan et al., 2007). This is also important for the CRB3 antibodies used in the study since according to the material and methods section they are either against the extracellular domain common to both isoforms or the intracellular domain which is only similar in the domain close to transmembrane between the 2 isoforms. Since the antibodies used in each figure are not detailed it is impossible to know if the authors are detecting CRB3A or B or both. Please provide the information and correct for the actual isoform detected in the data and conclusions.

Thanks for your positive comments. In mammals, CRB3 has two isoforms, CRB3a and CRB3b, distinguished by alternative splicing within the fourth exon of the CRB3 gene, which in turn produces a protein with 23 amino acid differences at the C terminus. Both CRB3a and CRB3b have mostly identical amino acid sequences, and have indistinguishable molecular weight sizes. As a result, the knockout mouse construction strategy and the design principles of RNAi sequences target both CRB3a and CRB3b. This is described in lines 100-104 and lines 149-150. Additionally, commercially available antibodies detect both CRB3a and CRB3b, as mentioned in line 123 and lines 636-637 in revised manuscript.

However, it should be noted that our CRB3 overexpression, as shown in the CRB3 structural domain in Figure 6D, refers specifically to the sequence of CRB3b. As a result, we have updated the original manuscript as well as the legends of Figures 3C, 3E, 4A, 5A, 5B, 6D-G, 7A, 7B and Supplementary Figure 2F-H, 3A, 4B, 6B to reflect this change. All instances of overexpressed CRB3 have been changed to CRB3b.

2) CRB3A and B have been localized in the cilium itself (Fan et al., 2004; 2007) but in the study CRB3A/B does not enter the cilium but is localized in the basal body (figure 4). How the authors reconcile these different localizations?

Indeed, we found that CRB3 is mainly localized at the basal body of the primary cilium, which differs from previous reports in the literature (Curr Biol. 2004;14(16):1451-61 and J Cell Biol. 2007;178(3):387-98). However, upon closer examination of one of these reports (Curr Biol. 2004;14(16):1451-61), it appears that CRB3 was actually scattered on the primary cilia, with a strong focus at the basal body. Additionally, in rat kidney collecting ducts, the localization of CRB3 on primary cilia was significantly reduced, with obvious localization at the basal body. Another study (J Cell Biol. 2007;178(3):387-98) also reported the co-localization of CRB3b and γ-tubulin in MDCK cells, which is consistent with our conclusion. We further verified the co-localization of CRB3 with the centrosome by overexpressing CRB3b in mammary epithelial cells, indicating that CRB3 mainly localizes to the basal body of the primary cilium. This information is discussed in the Discussion section of the manuscript (lines 400-410).

3) The authors use GFP-CRB3A/B, it is not stated which isoform, over-expression to localize CRB3A/B in MCF10A cells (figure 4A). The levels of expression appear to be very high in the GFP panel and it is likely that the secretory pathway of the cells is clogged with GFP-CRB3A/B in transit from the ER to the plasma membrane. Thus, the colocalization with pericentrin might be due to the accumulation of ER and Golgi around the centrosome. This colocalization should be done with the endogenous CRB3A/B and with a better resolution.

Thank you for your comments. We were also interested in the co-localization of endogenous CRB3 and centrosome proteins. However, the only commercial CRB3 antibody available is the rabbit species, and the pericentrin antibody (Abcam, ab4448) that is very useful is also the rabbit species. We had difficulty finding commercial centrosome-associated antibodies for other species. Therefore, we examined the co-localization of endogenous CRB3 with γ-tubulin in Figure 4C and combined the results with those of exogenous CRB3 to illustrate the co-localization of CRB3 with centrosomes.

4) The staining for CRB3A/B in figure 4C (red) is striking with a very strong accumulation in an undefined intracellular structure and the authors do not provide any explanation for such a difference with the GFP-CRB3A/B just above.

Thank you for your good suggestions. The immunofluorescence images of GFP-CRB3 in Figure 4a were obtained using a fluorescence microscope, while the images of endogenous CRB3 were obtained using a laser confocal microscope. The fluorescence microscope excites a fluorescent dye to emit a signal, which is amplified into a visible light signal and presents a full fluorescent signal. In Figure 4a, we can clearly see the full distribution of exogenous CRB3 in MCF10A cells, including its tight junctional localization consistent with previous reports in the literature and its co-localization with centrosomal proteins. On the other hand, laser confocal microscopy uses a laser as the light source to excite the fluorescence within the sample point by point. It employs a precision pinhole filtering technique with strong laminar imaging capabilities. In the specific analysis of endogenous CRB3 co-localization studies with centrosomes and primary cilium, signals at tight junctions must be excluded. Therefore, Figure 4c represents the fluorescence signal at the level of intracellular CRB3 co-localization with γ-tubulin. The two methods use different detection means and techniques, and are not directly comparable.

5) The staining in figure 4E is also different from those shown in figure 4F in which the CRB3A/B staining is right at the base of the axoneme while it is not the case in figure 4E where we can see a red dot close to but not right at the base of the axoneme.

Thank you for your comments. The new Figure 4F displays the localization relationship between CRB3 and primary cilium, analyzed using laser confocal microscopy. With the unique single-level detection function of this microscope, the problem of level selection may cause the red dots to appear close to, rather than right at the basal body of the primary cilium. However, the new Figure 4G, based on the use of 3D reconstruction scanning technique, clearly demonstrates the localization of CRB3 at the basal body of the primary cilium under the same cells and conditions.

6) The authors claim that CRB3A/B interacts directly with Rab11 but they only show co-immunoprecipitation experiments from cell lysates which do not support direct interactions. The only way to show a direct interaction is to produce both proteins in vitro. Thus, the term direct interaction should be removed.

Thank you for your positive comments. Since we were unable to complete the relevant experiments to demonstrate direct interaction of two proteins, we have revised our conclusions. Replace " CRB3 directly binds Rab11" with " CRB3 binds Rab11" in the manuscript.

7) In addition, the authors claim (Line 251/252) that Rab11 is necessary for the transport of CRB3A/B but they should KD Rab11 to show this.

Thank you for your good suggestions. It is essential to observe CRB3 trafficking after knockdown Rab11. However, in Figure 5C, we used the endocytosis inhibitor dynasore, which also inhibits Rab11-positive endosomes. This result shows that dynasore can significantly inhibit CRB3 trafficking in MCF10A cells. We believe that this experiment partially demonstrates that inhibiting Rab11 function can affect CRB3 trafficking.

8) The domain of CRB3A/B that is necessary for the interaction with Rab11 is the N-terminal part of the extracellular domain. This domain is thus inside the transport vesicles and not accessible from the cytoplasm. Given that Rab11 is a cytoplasmic protein, how the 2 proteins could interact across the membrane? The authors do not even discuss this essential point for their hypothesis.

Thank you for your positive comments. As shown in the schematic model in Figure 9, we believe that when cells form tight junctions, CRB3 is primarily located on the cell membrane. Subsequently, endosomes are involved in the intracellular degradation process of CRB3 on the cell membrane. Intracellular CRB3 can bind to Rab11 through the extracellular domain, which in turn participates in primary cilia assembly. We have made detailed modifications to lines 418-421.

9) Figures are not numbered.

Thank you for your comments. We have updated the numbers in the original manuscript as well as the legends of Figures 1D, 1E, 2B, 2D, 2F, 2G, 3B, 3D, 3F-H, 4B, 4E, 5I, 6, 8G and Supplementary Figure 1E, 2, 3C, 4A, 5B, 6.

Minor points

1) The authors cite several studies showing that a down regulation of CRB3A/B in human cells promotes cancer but other studies show the contrary: Lin et al., 2015 for example. Please discuss these discrepancies.

Thanks for your good suggestion. We have included additional studies with contrasting results in the discussion section, specifically in lines 378-380.

2) Line 98: "exhibit smaller" smaller than what?

We modified "exhibit smaller" to "exhibit smaller size" in line 97.

3) Line 152: "form more number, ..." ???

We modified "formed more number" to "formed more" in line 154.

4) Line 180: "Compared with the control, the number of cells with primary cilium was significantly increased ». To me it is the contrary! This part is not clear at all. Please rewrite.

We have revised the sentence in lines 183-185.

5) Authors should check and review extensively for improvements to the use of English.

Thanks for your good writing advice. We have carefully reviewed and revised the entire manuscript to improve its readability.

Author Response

Reviewer #1 (Public Review):

The objective of this investigation was to determine whether experimental pain could induce alterations in cortical inhibitory/facilitatory activity observed in TMS-evoked potentials (TEPs). Previous TMS investigations of pain perception had focused on motor evoked potentials (MEPs), which reflect a combination of cortical, spinal, and peripheral activity, as well as restricting the focus to M1. The main strength of this investigation is the combined use of TMS and EEG in the context of experimental pain. More specifically, Experiment 1 investigated whether acute pain altered cortical excitability, reflected in the modulation of TEPs. The main outcome of this study is that relative to non-painful warm stimuli, painful thermal stimuli led to an increase on the amplitude of the TEP N45, with a larger increase associated with higher pain ratings. Because it has been argued that a significant portion of TEPs could reflect auditory potentials elicited by the sound (click) of the TMS, Experiment 2 constituted a control study that aimed to disentangle the cortical response related to TMS and auditory activity. Finally, Experiment 3 aimed to disentangle the cortical response to TMS and reafferent feedback from muscular activity elicited by suprathreshold TMS applied over M1. The fact that the authors accompanied their main experiment with two control experiments strengthens the conclusion that the N45 TEP peak could be implicated in the perception of painful stimuli.

Perhaps, the addition of a highly salient but non-painful stimulus (i.e. from another modality) would have further ruled out that the effects on the N45 are not predominantly related to intensity/saliency of the stimulus rather than to pain per se.

We thank the reviewer for their comment on the possibility of whether stimulus salience influences the N45 as opposed to pain per se. However, we note that in Experiment 1, despite the same level of stimulus salience/intensity for all participants (46 degrees), individual differences in pain ratings were associated with the change in the N45 amplitude, suggesting that the results cannot be explained by stimulus intensity/salience.

Reviewer #2 (Public Review):

The authors have used transcranial magnetic stimulation (TMS) and motor evoked potentials (MEPs) and TMS-electroencephalography (EEG) evoked potentials (TEPs) to determine how experimental heat pain could induce alterations in these metrics.In Experiment 1 (n = 29), multiple sustained thermal stimuli were administered over the forearm, with the first, second, and third block of stimuli consisting of warm but non-painful (pre-pain block), painful heat (pain block) and warm but non-painful (post-pain block) temperatures respectively. Painful stimuli led to an increase in the amplitude of the fronto-central N45, with a larger increase associated with higher pain ratings. Experiments 2 and 3 studied the correlation between the increase in the N45 in pain and the effects of a sham stimulation protocol/higher stimulation intensity. They found that the centro-frontal N45 TEP was decreased in acute pain.

The study comes from a very strong group in the pain fields with long experience in psychophysics, experimental pain, neuromodulation, and EEG in pain. They are among the first to report on changes in cortical excitability as measured by TMS-EEG over M1.

While their results are in line with reductions seen in motor-evoked responses during pain and effort was made to address possible confounding factors (study 2 and 3), there are some points that need attention. In my view the most important are:

1) The method used to calculate the rest motor threshold, which is likely to have overestimated its true value : calculating highly abnormal RMT may lead to suprathreshold stimulations in all instances (Experiment 3) and may lead to somatosensory "contamination" due to re-afferent loops in both "supra" and "infra" (aka. less supra) conditions.

The method used to assess motor threshold was the TMS motor threshold Assessment Tool (Awiszus et al., 2003). This was developed as a quicker alternative for calculating motor threshold compared to the traditional Rossini-Rothwell method which involves determining the lowest intensity that evokes 5/10 MEPs of at least 50 microvolts. The method has been shown to achieve the same accuracy of determining motor threshold as the traditional Rossini-Rothwell method, but with fewer pulses (Qi et al., 2011; Silbert et al., 2013). Therefore, the high RMTs in our study cannot be explained by the threshold assessment method. Instead, they are likely explained by aspects of the experimental setup that increased the distance between the TMS coil and the scalp, including the layer of foam placed over the coil, the EEG cap and the fact that the electrodes we used had a relatively thick profile.

Awiszus, F. (2003). TMS and threshold hunting. In Supplements to Clinical neurophysiology (Vol. 56, pp. 13-23). Elsevier.

Qi, F., Wu, A. D., & Schweighofer, N. (2011). Fast estimation of transcranial magnetic stimulation motor threshold. Brain stimulation, 4(1), 50-57.

Silbert, B. I., Patterson, H. I., Pevcic, D. D., Windnagel, K. A., & Thickbroom, G. W. (2013). A comparison of relative-frequency and threshold-hunting methods to determine stimulus intensity in transcranial magnetic stimulation. Clinical Neurophysiology, 124(4), 708-712.

2) The low number of pulses used for TEPs (close to ⅓ of the usual and recommended)

We agree that increasing the number of pulses can increase the signal to noise ratio. During piloting, participants were unable to tolerate the painful stimulus for long periods of time and we were required to minimize the number of pulses per condition.

We note that there is no set advised number of trials in TMS-EEG research. According to the recommendations paper, the number of trials should be based on the outcome measure e.g., TEP peaks vs. frequency domain measures vs. other measures and based on previous studies investigating test-retest reliability (Hernandez-Pavon et al., 2023). The choice of 66 pulses per condition was based on the study by Kerwin et al., (2018) showing that optimal concordance between TEP peaks can be found with 60-100 TMS pulses delivered in the same run (as in the present study). The concordance was particularly higher for the N40 peak at prefrontal electrodes, which was the key peak and electrode cluster in our study.

Further supporting the reliability of the TEP data in our experiment, we note that the scalp topographies of the TEPs for active TMS at various timepoints (Figures 5, 7 and 9) were similar across all three experiments, especially at 45 ms post-TMS (frontal negative activity, parietal-occipital positive activity).

In addition to this, the interclass correlation coefficient (Two-way fixed, single measure) for the N45 to active suprathreshold TMS across timepoints for each experiment was 0.90 for Experiment 1 (across pre-pain, pain, post-pain time points), 0.74 for Experiment 2 (across pre-pain and pain conditions), and 0.95 for Experiment 3 (across pre-pain conditions). This suggests that even with the fluctuations in the N45 induced by pain, the N45 for each participant was stable across time, further supporting the reliability of our data. These ICCs will be reported in the next revision.

Hernandez-Pavon, J. C., Veniero, D., Bergmann, T. O., Belardinelli, P., Bortoletto, M., Casarotto, S., ... & Ilmoniemi, R. J. (2023). TMS combined with EEG: Recommendations and open issues for data collection and analysis. Brain Stimulatio, 16(3), 567-593

Kerwin, L. J., Keller, C. J., Wu, W., Narayan, M., & Etkin, A. (2018). Test-retest reliability of transcranial magnetic stimulation EEG evoked potentials. Brain stimulation, 11(3), 536-544.

Lack of measures to mask auditory noise.

In TMS-EEG research, various masking methods have been proposed to suppress the somatosensory and auditory artefacts resulting from TMS pulses, such as white noise played through headphones to mask the click sound (Ilmoniemi and Kičić, 2010), and a thin layer of foam placed between the TMS coil and EEG cap to minimize the scalp sensation (Massimini et al., 2005). However, recent studies have shown that even when these methods are used, sensory contamination of TEPs is still present, as shown by studies that show commonalities in the signal between active and sensory sham conditions that mimic the auditory/somatosensory aspects of real TMS (Biabani et al., 2019; Conde et al., 2019; Rocchi et al., 2021). This has led many authors (Biabani et al., 2019; Conde et al., 2019) to recommend the use of sham conditions to control for sensory contamination. To separate the direct cortical response to TMS from sensory evoked activity, Experiment 2 (n = 10) included a sham TMS condition that mimicked the auditory/somatosensory aspects of active TMS to determine whether any alterations in the TEP peaks in response to pain were due to changes in sensory evoked activity associated with TMS, as opposed to changes in cortical excitability. Therefore, the lack of auditory masking does not impact the main conclusions of the paper.

Ilmoniemi, R. J., & Kičić, D. (2010). Methodology for combined TMS and EEG. Brain topography, 22, 233-248.

Massimini, M., Ferrarelli, F., Huber, R., Esser, S. K., Singh, H., & Tononi, G. (2005). Breakdown of cortical effective connectivity during sleep. Science, 309(5744), 2228-2232.

Biabani, M., Fornito, A., Mutanen, T. P., Morrow, J., & Rogasch, N. C. (2019). Characterizing and minimizing the contribution of sensory inputs to TMS-evoked potentials. Brain stimulation, 12(6), 1537-1552.

Conde, V., Tomasevic, L., Akopian, I., Stanek, K., Saturnino, G. B., Thielscher, A., ... & Siebner, H. R. (2019). The non-transcranial TMS-evoked potential is an inherent source of ambiguity in TMS-EEG studies. Neuroimage, 185, 300-312.

Rocchi, L., Di Santo, A., Brown, K., Ibáñez, J., Casula, E., Rawji, V., ... & Rothwell, J. (2021). Disentangling EEG responses to TMS due to cortical and peripheral activations. Brain stimulation, 14(1), 4-18.

3) A supra-stimulus heat stimulus not based on individual HPT, that oscillates during the experiment and that lead to large variations in pain intensity across participants is unfortunate.

The choice of whether to calibrate or fix stimulus intensity is a contentious question in experimental pain research. A recent discussion by Adamczyk et al., (2022) explores the pros and cons of each approach and recommends situations where one method may be preferred over the other. That paper suggests that the choice of the methodology is related to the research question – when the main outcome of the research is objective (neurophysiological measures) and researchers are interested in the variability in pain ratings, the fixed approach is preferrable. Given we explored the relationship between MEP/N45 modulation by pain and pain intensity, this question is better explored by using the same stimulus intensity for all participants, as opposed to calibrating the intensity to achieve a similar of pain across participants.

Adamczyk, W. M., Szikszay, T. M., Nahman-Averbuch, H., Skalski, J., Nastaj, J., Gouverneur, P., & Luedtke, K. (2022). To calibrate or not to calibrate? A methodological dilemma in experimental pain research. The Journal of Pain, 23(11), 1823-1832.

So is the lack of report on measures taken to correct for a fortuitous significance (multiple comparison correction) in such a huge number of serial paired tests.

Note that we used a Bayesian approach for all analyses as opposed to traditional frequentist approach. In contrast to the frequentist approach, the Bayesian approach does not require corrections for multiple comparisons (Gelman et al., 2000) given that they provide a ratio representing the strength of evidence for the null vs. alternative hypotheses as opposed to accepting or rejecting the null hypothesis based on p-values. As such, throughout the paper, we frame our interpretations and conclusions based on the strength of evidence (e.g. anecdotal/weak, moderate, strong, very strong) as opposed to referring to the significance of the effects.

Gelman A, Tuerlinckx F. (2000). Type S error rates for classical and Bayesian single and multiple comparison procedures. Computational statistics, 15(3):373-90.

Reviewer #3 (Public Review):

The present study aims to investigate whether pain influences cortical excitability. To this end, heat pain stimuli are applied to healthy human participants. Simultaneously, TMS pulses are applied to M1 and TMS-evoked potentials (TEPs) and pain ratings are assessed after each TMS pulse. TEPs are used as measures of cortical excitability. The results show that TEP amplitudes at 45 msec (N45) after TMS pulses are higher during painful stimulation than during non-painful warm stimulation. Control experiments indicate that auditory, somatosensory, or proprioceptive effects cannot explain this effect. Considering that the N45 might reflect GABAergic activity, the results suggest that pain changes GABAergic activity. The authors conclude that TEP indices of GABAergic transmission might be useful as biomarkers of pain sensitivity.

Pain-induced cortical excitability changes is an interesting, timely, and potentially clinically relevant topic. The paradigm and the analysis are sound, the results are mostly convincing, and the interpretation is adequate. The following clarifications and revisions might help to improve the manuscript further.

1) Non-painful control condition. In this condition, stimuli are applied at warmth detection threshold. At this intensity, by definition, some stimuli are not perceived as different from the baseline. Thus, this condition might not be perfectly suited to control for the effects of painful vs. non-painful stimulation. This potential confound should be critically discussed.

In Experiment 3, we also collected warmth ratings to confirm whether the pre-pain stimuli were perceived as different from baseline. We did not include this data initially in the first submission, but will do so in the supplemental material in our next revision. This data showed warmth ratings were close to 2/10 on average. This confirms that the non-painful control condition produced some level of non-painful sensation.

2) MEP differences between conditions. The results do not show differences in MEP amplitudes between conditions (BF 1.015). The analysis nevertheless relates MEP differences between conditions to pain ratings. It would be more appropriate to state that in this study, pain did not affect MEP and to remove the correlation analysis and its interpretation from the manuscript.

The interindividual relationship between changes in MEP amplitude and individual pain rating is statistically independent from the overall group level effect of pain on MEP amplitude. Therefore, conclusions for the individual and group level effects can be made independently.

It is also important to note that in the pain literature, there is now increasing emphasis placed on investigating the individual level relationship between changes in cortical excitability and pain as opposed to the group level effect (Seminowicz et al., 2019; Summers et al., 2019). As such, it is important to make these results readily available for the scientific community.

Summers, S. J., Chipchase, L. S., Hirata, R., Graven-Nielsen, T., Cavaleri, R., & Schabrun, S. M. (2019). Motor adaptation varies between individuals in the transition to sustained pain. Pain, 160(9), 2115-2125.

Seminowicz, D. A., Thapa, T., & Schabrun, S. M. (2019). Corticomotor depression is associated with higher pain severity in the transition to sustained pain: a longitudinal exploratory study of individual differences. The Journal of Pain, 20(12), 1498-1506.

3) Confounds by pain ratings. The ISI between TMS pulses is 4 sec and includes verbal pain ratings. Considering this relatively short ISI, would it be possible that verbal pain ratings confound the TEP? Moreover, could the pain ratings confound TEP differences between conditions, e.g., by providing earlier ratings when the stimulus is painful? This should be carefully considered, and the authors might perform control analyses.

It is unlikely that the verbal ratings contaminated the TEP response as the subsequent TMS pulse was not delivered until the verbal rating was complete and given that each participant was cued by the experimenter to provide the pain rating after each pulse (rather than the participant giving the rating at any time). As such, it would not be possible for participants to provide earlier ratings to more painful stimuli. We will make this part of the protocol clearer in the next revision of the manuscript.

4) Confounds by time effects. Non-painful and painful conditions were performed in a fixed order. Potential confounds by time effects should be carefully considered.

Previous research suggests that pain alters neural excitability even after pain has subsided. In a recent meta-analysis (Chowdhury et al., 2022) we found effect sizes of 0.55-0.9 for MEP reductions 0-30 minutes after pain had resolved. As such, we avoided intermixing pain and warm blocks given subsequent warm blocks would not serve as a valid baseline, as each subsequent warm block would have residual effects from the previous pain blocks.

At the same time, given there was no conclusive evidence for a difference in N45 amplitude between pre-pain and post-pain conditions of Experiment 1 (Supplementary Figure 1), it is unlikely that the effect of pain was an artefact of time i.e., the explanation that successive thermal stimuli applied to the skin results an increase in the N45, regardless of whether they are painful or not. We will make this point in our next revision.

Chowdhury, N. S., Chang, W. J., Millard, S. K., Skippen, P., Bilska, K., Seminowicz, D. A., & Schabrun, S. M. (2022). The Effect of Acute and Sustained Pain on Corticomotor Excitability: A Systematic Review and Meta-Analysis of Group and Individual Level Data. The Journal of Pain, 23(10), 1680-1696.

5) Data availability. The authors should state how they make the data openly available.

We will upload the MEP, TEP and pain data on the Open science framework at the time of the next revision.

Author Response

Reviewer #1 (Public Review):

Sun and colleagues investigated the cross-reactive antibodies between E. coli and the host in severe alcoholic hepatitis (SAH). The study found that IgA and IgG were deposited in the liver of SAH patients. Complements C3d and C4d were also deposited in the SAH patient's liver. Moreover, they found that the Ig accumulated in the SAH liver, but not in the SAH serum, induced hepatocyte killing, suggesting that liver Ig is important. Then, they found that these Ig can recognize both human and E. coli antigens. Very interestingly, SAH-derived Ig shows cross-reactivity to both human and E. coli antigens, suggesting E. coli-primed Ig in SAH may damage hepatocytes through host antigen recognition. These Ig are not observed in alcoholic cirrhosis patients. The liver RNA-seq data suggested that Ig was also produced in the liver, not only gut-derived Ig. This is a very interesting study showing the novel mechanism of SAH mediated by the Ig with the cross-reactivity with bacteria and host antigens, which is not observed in AC patients. Overall, the study design is reasonable and the data are consistent to support their central hypothesis. There are a few comments.

We thank the Reviewer for his/her positive comments on our manuscript!

Specific comments:

1) Figures 1 and 2 show Ig deposition in the liver (it seems on hepatocytes). Not only Ig reaction to the specific antigen but also non-specific Fc receptor-mediated binding to hepatocytes could have contributed.

2) Similarly, in Figure 2G Ig-mediated hepatocyte killing, Fc receptor-mediated hepatocyte killing may be involved.

Anti-IgG antibody (ab200699) recognizes a protein of 75 kDa, identified as gamma heavy chain of human immunoglobulins. It is possible that non-specific Fc receptor-mediated binding to hepatocytes in the SAH liver can also be recognized by this anti-IgG antibody staining.

However, no IgG or IgA deposition in the healthy donor livers was identified by anti-IgG or IgA staining. These results suggest that there was no antigen specific or Fc receptor-mediated binding to healthy hepatocytes.

In the ADCC assay, hepatocytes isolated from healthy donor livers were used as the target cells. Immune cell (NK) mediated ADCC is mainly triggered by IgG (binding to antigens of hepatocytes) through the interaction between IgG Fc fragment and Fc-receptors (FcγRs) of NK cells. If IgG deposition in the SAH liver were mainly due to non-specific Fc receptor-mediated binding to hepatocytes, we would expect IgG binding to FcγRs of hepatocytes and no activation of NK cells. Ig-mediated hepatocyte killing (Figure 2G) indicates the Ig (from SAH liver) reaction to the specific antigens.

3) The study examined the possibility of liver resident B cell and plasma cell-mediated Ig. As the authors mentioned in the discussion, B cells may be translocated from the intestine to the liver. Or the resident B cells (not from the gut) are also involved.

We agree with the Reviewer at this point. The resident B cells may be also involved in the Ig production.

Reviewer #2 (Public Review):

In this paper, Ahmadi et al demonstrated that antibodies produced locally in the liver by infiltrating B cells can enhance liver damage caused by fat accumulation. The main finding is that human samples extracted from severe alcoholic hepatitis showed antibody accumulation that may be related to an enhanced immune response to self-antigens, which could ultimately fuel liver damage - which was already present due to alcohol consumption. Their data are corroborated by arrays and gene ontology assays, and I strongly believe that these data could add to the future options we have to treat patients.

We thank the Reviewer for his/her positive comments on our manuscript!

Author Response:

We thank the reviewers and eLife editorial team for their valuable assessment. While additional experiments could further strengthen the theoretical framework proposed in this study, we believe that we have successfully established the delayed nuclear export of hemagglutinin and neuraminidase mRNAs by quantifying the FISH observation with the mathematical model. We agree that this finding raises a further important question to be addressed regarding the molecular mechanism underlying the prolonged nuclear retention of these segments. Our ongoing investigation is focusing on identifying potential cis-elements that contribute to the delay of these segments.

Author Response:

We are grateful to the three referees for their overall positive evaluation of our work and valuable constructive suggestions. We will address their public reviews with utmost care, as well as their private recommendations.

To Reviewer #1: thanks for the positive comments and for the appreciation of our « impressive approaches »

• We will add a more comprehensive section of neuronal migration analysis in the Material and Methods section. Sorry for that regrettable lack of precision.

• We will address the comments about the sinuosity index definition and interpretations.

• We will enhance the clarity of our writing and delve deeper into the discussion. As mentioned to Reviewer #3, the brevity of the text was influenced by the Short report format.

To Reviewer #2 : thanks for the overall positive appreciation.

We will also consider the recommendations for authors with care.

To Reviewer #3 : thanks a lot for the feedback.

• We will further develop the introduction and discussion sections as suggested. Regrettably and as mentioned to Reviewer #1, we had to significantly condense them due to the space constraints imposed by the Short Report format.

• We will attempt to overexpress Map1B in order to assess the potential phenotypic similarity to the Fmr1 null condition, as suggested. However, it is important to acknowledge that this experiment may not yield a definitive answer due to potential differences in the level of Map1B expression driven by a CMV promoter compared to its endogenous expression in Fmr1 null neurons, as well as variations in the subcellular distribution of the overexpressed Map1B.

• Regarding the anatomical consequences of aberrant migration, we acknowledge that neither our present work nor our previous study by Scotto-Lomassesse et al. provide evidence in this regard, as pointed out by the reviewer. Indeed, the delayed neurons do reach the olfactory bulb based on our findings. However, other studies have demonstrated that a delay in migration can have important functional consequences (eg Bocchi et al, 2017 doi: 10.1038/s41467-017-01046-w). Accordingly, we will revise and moderate our conclusions on this specific point.

Author Response

Reviewer #1 (Public Review):

Cedillo et al. address the critically important question of how biguanides exert their positive effects on longevity using the powerful C. elegans model. Biguanides metformin and phenformin have been widely prescribed in the clinic to address metabolic challenges of diabetes; more recently the value of metformin in addressing specific cancers has emerged, and testing for impact on healthy human aging is getting underway. The need to understand the mechanism of biguanide action and the metabolic consequences of biguanide administration is clear.

The authors report that three genes that suppress longevity associated with metformin or phenformin treatment affect a common pathway for ether lipid biosynthesis; this ether lipid biosynthesis pathway is required for mitochondrial lifespan extension, eat-2 mediated dietary restriction longevity, and TOR inhibition-associated longevity, but not insulin pathway mediated longevity. Authors document with lipid profiling how ether lipids and some other lipids are impacted by phenformin vs. genetic disruption of ether lipid biosynthesis, define the tissue primarily responsible for the ether lipid biosynthesis, show that over-expression of enzyme fard-1 is sufficient to confer most of the phenformin effect, and implicate conserved stress transcription factor SKN-1 as a downstream outcome of the ether lipid change.

Strengths include the exploitation of the nematode model to address requirements not readily discerned in other models, the rigor of genetic documentation, the inclusion of metabolic profiling, the testing of multiple potential pathways that have been in the general discourse regarding metformin action, and the elaboration of a reasonably supported model that ether lipid biosynthesis is required for phenformin to activate longevity-promoting metabolic defenses downstream of conserved stress-responsive transcription factor SKN-1/NRF2. The novelty includes that ether lipids are directly linked to lifespan, ether lipid biosynthesis is needed for specific longevity pathways, and that ether lipids might play a role in a shift to pro-longevity metabolism.

There are some points that require clarification and could benefit from additional study, some wording and presentation issues, and a few missing points of potential discussion.

Overall, the data reported in this paper contribute a highly valuable advance in the biguanide field and adds stimulating hypotheses to the scientific community for moving forward in this biomedically important area.

We thank Reviewer #1 for their positive feedback regarding our work, and for their insightful suggestions to improve the rigor and impact of this manuscript.

Reviewer #2 (Public Review):

This manuscript pulls together a series of integrated genetic and metabolomic data sets to examine the molecular basis for biguanide action in C. elegans. Biguanides such as Metformin are important anti-diabetic drugs as well as being explored as a therapeutic mechanism for increasing human longevity. Understanding the molecular basis of biguanide action is of general interest to those in the ageing and age-related health fields as well as to those studying metabolism and obesity. The work here has been carried out in C. elegans but the work can be picked up by those working in mammalian systems. More could be done to highlight the conserved aspects of the mechanisms involved to assist with this translatability.

The methodology used is in general standard in the field and experiments are reported in detail. The successful use of metabolomics in C. elegans and its associated protocols is helpful as more labs expand to do this type of work.

Strengths: In general all the experiments presented are logical and well executed with the conclusions supported by the data. I am convinced that: 1) Metformin and Phenformin extend C. elegans lifespan (although that has previously been shown), 2) biguanides induce changes in ether lipids, 3) genes required for ether lipid biogenesis are required for the lifespan incurred with biguanide treatment and, in the case of fard-1 oe, can also promote longevity when levels are increased, 4) ether lipid biogenesis is also needed for other specific key longevity processes to extend lifespan, and 5) that some key ageing regulators (skn-1, aak-2 and daf-16) are required for fard-1 oe to extend lifespan.

Weaknesses: I was less convinced by the fat accumulation data and felt that the link between skn-1 gain of function and ether lipid genes was not clear and that the results were more correlative than mechanistic. If age-associated somatic depletion of fat is important for the lifespans seen here then this is interesting and important and identifying an epistatic, genetic link between the implicated genes and fat levels is desirable. Additionally, biguanides are reported to have major effects on the metabolism and growth of bacteria. As C. elegans grows on and eats E. coli, it is important that the biguanides in question do not alter the worm's food source. If bacterial growth is restricted or metabolically altered this would have a major impact on fat metabolism and the other outputs examined here (see Cabreiro et al 2013). Therefore the impact of these biguanide treatments on the C. elegans foods used here should be clearly addressed. Additionally, biguanide treatment is subject to dose dependence. Different concentrations of biguanide are used for different types of experiments to make correlative points e.g. growth inhibition at 160mM metformin, and metformin uptake measured in C. elegans treated with 50mM. It is not clear why, or whether this could impact the results. Can the authors be sure that these different doses do not alter metformin action and/or uptake either by the worms or the way the bacteria metabolise it? I appreciate that it is interesting and important to understand what biguanides are doing in the organism irrespective of whether this is a direct or indirect effect but knowing how the effects are achieved could be important for treatment strategies moving forwards.

We thank Reviewer #2 for their favorable comments on our manuscript and for their helpful feedback regarding the weaknesses in our initial manuscript submission. We address the major comments below:

1. Regarding the genetic link between SKN-1 and ether lipid biosynthetic machinery in regulation of fat accumulation, we have performed Asdf analysis in skn-1(zu135) total loss-of-function animals, rigorously indicating that biguanides require SKN-1 to drive somatic lipid depletion (Figure 6D-E). We additionally show that biguanides activate the innate immune response sensor dod-24, previously shown by us to be activated by a transcriptionally redirected SKN-1 metabolic stress response program2, in a manner that requires both SKN-1 and all ether lipid biosynthetic machinery (Figure 6F and Figure 6 – figure supplement 1C). Combined with our previous result showing that fard-1 (oe3) requires SKN-1 to extend lifespan (Figure 5D), and our observation that SKN-1 gain-of-function animals do not mimic the ether lipid pattern seen in FARD-1 overexpressing animals (Reviewer Response 1), our results rigorously corroborate that biguanides activate SKN-1 downstream of ether lipid machinery to exert a metabolic stress defense response. This activation results in alterations of somatic lipid homeostasis, innate immune response, and pro-longevity outcomes.

2. Regarding possible indirect effects of biguanides on bacterial growth and metabolism to modulate ether lipid biosynthetic activity, we performed FAME GC/MS of Adult Day 1 nematodes treated with or without phenformin and grown on live or dead, metabolically inactive OP50-1 E. coli food sources using a rigorously established 1% PFA treatment protocol (Figure 6 – figure supplement 2)3. We additionally performed lifespan analyses in the same experimental design, with the inclusion of lifespan extending doses of metformin (Figure 6 – figure supplement 3). Both experiments show, with biological replication, that biguanide-mediated induction of ether lipid synthesis, biguanide-mediated lifespan extension, and the dependency of ether lipid machinery on biguanide-mediated lifespan extension all operate through direct interactions in the worm, as opposed to indirect effects on bacterial growth and metabolism.

3. Regarding the use of different doses of biguanides: this point was also raised by Reviewer 1 and is responded to above in Author Response 4. Briefly, the goal of the 160 mM dosage of metformin used in our prior genetic screens10 and subsequently highlighted in Figure 1 – figure supplement 1A is to enhance the sensitivity and specificity of our discovery approach to identify effectors of the biological action of biguanides. The 160 mM dose causes potent growth inhibition in C. elegans. Our prior published work indicates that use of this dose to identify growth inhibitory effectors of biguanides can also identify longevity effectors of metformin 10. Thus, we used a similar strategy here to identify fard-1 and acl-7, which were initially identified as gene knockdowns that block the growth inhibitory effects of 160 mM metformin. The justification for the different biguanide concentrations used in this work is now included in the text for clarity (lines 135 to 153).

Author Response

Reviewer #2 (Public Review):

"... the fact that MGN-BLA circuit disruptions were done during the conditioning phase of associative threat learning, and not during the recall phase only, complicates the side-by-side comparison: it could be argued that in this case what is disturbed is the processing of the unconditioned innately aversive stimulus in the task, the foot shock, instead of the learnt threat of the sound".

In our previous email to the editors, we mentioned work by Barsy et al., showing that indeed the inhibition of this input during the recall phase reduces freezing response (Please see Fig. 8 in Barsy et al). In the new revision, we refer to this experiment.

Specific comments (weaknesses):

e) There are not enough analysis and method descriptions to demonstrate the specificity of the targeting approach

We have included these data as supplementary figures (S2A and B, S5B, S7, S9A and S10K) and added a more detailed methodology in the method section.

f) …the authors administer blockers of beta-adrenergic receptors systemically. This reveals differences between MGN-BLA projecting neurons, BLA neurons, and innate and learnt threat, but the mechanistic implications are not clear and should be discussed.

In the revised manuscript, we extensively discuss these points: (This indicates that the looming stimulus conveyed through the thalamic input…may contribute to the variability in the effect of the drug in freezing response); (...in mice injected with propranolol, the defensive responses…The differences in species or strains used, or experimental parameters may contribute to the variability in the effect of the drug in freezing response.)

Author Response

Reviewer #2 (Public Review):

Mahbub et al further elucidate the structural and functional consequences of the ARL15-CNNM2 interaction for divalent cation transport. They show that ARL15 has low GTP binding affinity and could not detect GTPase activity, questioning whether ARL15 functions as a GTPase. Although the interaction of ARL15 and CNNMs has been demonstrated by multiple groups before, this study addresses some of the key questions that are central within the TRPM-CNNM-PRL-ARL15 field. Particularly, the authors have identified residues in both ARL15 and CNNM proteins which are required for their binding to one another. In addition, they have also illustrated how PRL proteins compete with ARL15 for their binding to CNNMs. Lastly, the functional consequences of ARL15 binding to CNNMs are shown by TRPM7-mediated Zn2+ transport assays.

We thank the reviewer for the many positive comments.

However, the current dataset also comes with limitations. Previous studies demonstrated that PRLs interact with the CBS domains of CNNMs and lock them in their so-called "flat" confirmation. It remains unclear how ARL15 affects the structure of the CBS domains, especially in the presence of ATP. The subcellular localisation of these interactions has not been examined. Moreover, the consequences of ARL15 on TRPM7 activity are not completely elucidated. It remains unclear whether this functional effect is CNNM-dependent. Moreover, how the zinc uptakes translate to other divalent ion transport, such as magnesium, has not been examined. These questions should be answered to confirm the model as presented in Figure 7.

We agree that CBS-pair domain dimerization is important. Structural studies of a prokaryotic CNNM homolog from our group showed large conformational changes in an ATP-binding mutant (Chen et al., Nat Comm, 2021).

While most crystal structure of PRL-CNNM complexes do indeed show the flat conformation, it is unclear if that is a consequence of crystal packing or PRL binding. We do not see an effect of ATP on PRL binding affinity. The CBS-pair domain dimerization interface appears to be very adaptable; our recent structure of PRL-CNNM proteins from flies shows a completely different dimerization interface (Fakih et al, JBC, 2023).

In contrast, the ARL15-CNNM interaction is affected by ATP. As suggested by the reviewer, we have examined ARL15 binding to a CNNM2 mutant (T568I) that is unable to bind ATP. These results confirm the roughly two-fold improvement in affinity is due to ATP binding to the CNNM2 CBS-pair domain and resulting conformational changes.

As requested by all the reviewers, we have added experiments to Figure 7 that investigate the effect of ARL15 on Mg2+ transport.

Author Response

Reviewer #1 (Public Review):

It has recently been shown that the HIV-1 protease can cleave and activate the inflammasome-forming sensor CARD8 upon treatment of infected cells with non-nucleoside reverse-transcriptase inhibitors (Wang et al., Science 2021). Here, Kulsuptrakul and colleagues show that the high susceptibility to proteolytic activation by the HIV-1 protease is a specific feature of human CARD8. They show that changes in human-specific F-F motif render the CARD8 protein of non-human primates largely resistant to cleavage. Interestingly, the protease of SIVcpz the direct precursor of pandemic HIV-1 strains are also capable of cleaving human but not chimpanzee CARD8. Thus, the authors propose that a human-specific CARD8 motif may contribute to the increased levels of inflammation and disease progression in HIV-infected humans compared to non-human primates that are naturally infected with SIV.

Strengths of the study are that the authors convincingly show that a single human-specific amino acid change in CARD8 determines its susceptibility to cleavage by the HIV-1 protease and that the results shown are well controlled and presented. It is also interesting that SIVcpz can cleave human CARD8 and activate an inflammatory response. The major weakness is that it remains unclear whether HIV-1 of SIVcpz may induce CARD8-dependent inflammatory responses in primary CD4+ T cells or macrophages. The most relevant setting in the study was the infection of THP-1 cells with the T cell line-adapted X4-tropic HIV-1 LAI molecular clone. However, the effects on cell death were modest (Figure 3A) and on IL-1ß secretion was not dose-dependent (Figure 3B). Altogether, stronger effects were observed with VSV-G-pseudotyped HIV-1 and only those were used in subsequent experiments involving human CARD8 cleavage mutants (Figure 4). Additional evidence that primary HIV-1 molecular clones and/or SIVcpz may indeed induce CARD8-dependent inflammatory responses in primary viral target cells would greatly increase the significance of the study. In the absence of such data, conclusions about the potential role of CARD8 sensing of the viral protease for the pathogenesis of AIDS should be cautioned throughout.

We have now added an experiment using the HIV-1 strain BG505, which uses a distinct co-receptor and is from a different clade than LAI. The results show that BG505 infection also induces CARD8-depdenent inflammasome activation (Figure 3E).

We have also more specifically measured caspase-1 activation using a FLICA assay (which specifically measures active CASP1) in WT, CARD8 KO and CASP1 KO THP-1 cells (Figure 3D, right panel). In experiments with both VSV-g pseudotyped and infectious virus, we observed increased FLICA signal in WT but not CASP1 KO THP-1 cells. Moreover, the FLICA signal and other readouts of inflammasome activation in CARD8 KO THP-1 cells was indistinguishable from the CASP1 KO THP-1 cells (Figure 3D). Thus, our results are consistent with HIV-1 infection inducing CASP1-dependent pyroptosis downstream of CARD8.

While we agree with the reviewers that primary cell data would be informative, we believe that this is not the main point of our paper. Moreover, others have already shown CARD8-dependent cell death after infection of primary T cells with HIV-1 (Wang et al., 2021, Science; Clark et al. 2022, Nature Chem Biol; Balibar et al. 2023, Science Trans Med; Wang & Shan, 2023, BioRxiv). We therefore have not extensively pursued primary cell experiments in this manuscript and instead have elected to use a more easily manipulatable cell line to focus on the evolutionary and mechanistic basis of CARD8 activation by simian lentiviruses.

Author Response:

Reviewer #1 (Public Review):

[…] Collective variable choice:

The explanation for the choice of CVs on page 5 is not sufficient to understand the process and its likely success. How were the most important and unimportant CVs identified exactly? Table 2 on page 19 shows only gate distances, cavity-filter distances and a single variable related to filter structure itself (77 CA - 77 CA) representing a pinch. Is that pinching really the only slow variable associated with inactivation changes in the filter? Why are there no variables, say for carbonyl flipping, E71 or D80 movements or even for ion and water occupancy (although water may be sampled with control of other interactions, such as involving L81)?

CVs for steering simulations were selected based on structural comparisons between the X-ray structures as well as the information about the inactivation available in the literature. These steering CVs were later used as CVs for the string method with the exception of those found to be irrelevant in preliminary string simulations (see methods for details). For example we discarded CVs that would just oscillate freely and thus represent fast equilibrating CVs. We will add additional explanations to the methods section of the manuscript in revisions.

Carbonyl flipping, E71 and D80 movement and SF occupancy were observed in the initial steering simulation to correlate with the 77 CA - 77 CA opening and the opening of the L81-W67 contact. They were not biased but followed the expected path as a consequence of the motion of the imposed selectivity filter constriction. Therefore, they did need not be explicitly biased. The same can be said with respect to water occupancy behind the selectivity filter, which correlates with the opening of the L81-W67 contact.

I understand that the X-ray structure is the one source of information used to define an inactivated structure and is one with just a pinch and no complete carbonyl flipping away from the pore, as has been identified in past studies and discussed as being involved by the authors on page 14. Key changes like carbonyl flipping surely are part of the story and may be slow variables. At the very least, if not part of the CV space, could be analysed.

Indeed, the reviewer is correct in stating that there are molecular motions of interest aside from the ones included in the CV space. Figure 3 and associated supplementary figures indeed extensively investigate the probability distributions of many of those as the system progresses along the inactivation pathway. These results are presented in the section titled “Free energy landscapes offer insights into atomistic-resolution mechanistic details”. Carbonyl flipping seemed to be highly correlated with the 77CA- 77CA distance and this analysis was therefore not presented.

On page 10 the authors discuss possible differences in Amber and Charmm involving the extent to which the 4 subunits change in respect to the L81-W67 water pathway and W67-D80 hydrogen bond, arguing the different results for force field could be to do with different numbers of subunits doing different things. If I understand, the chosen CVs are all tetramer-based distances (including across subunits) and not subunit-based CVs, so that random and incomplete changes may occur to subunits for a given point in CV space.

In fact, some of the CVs represent intrasubunit distances, for example L81-W67 while others represent distance across subunits. This distinction never represented a criterion to select CVs.

There is thus potential for the string to converge on a local minimum pathway with partial changes to its interactions within and between subunits, and may not be a unique global solution. Can the authors please explain whether or not this is possible and what analysis has been done to check it?

This indeed represent a well-recognized shortcoming of all string-based enhanced sampling methods. The string-of-swarms method used herein indeed assumes that there is a dominant minimum free energy path and requires a reasonable starting path. One major advantage of this methodological choice, however, is that the path can be described in high dimension, thus avoiding stark dimensionality reduction as is the case in many collective-variable based methods such as metadynamics.

We do note that though the initial path was the same for the two force fields, the final pathway is different, which tends to indicate that the results do not only depend on the initial path but also on the force field guiding the dynamics of the process.

X-ray endpoints and initial pathway:

The string was created from a pulling/steered MD between existing X-ray structures for the closed (5VKH), partially open (3FB5), fully open (5VK6) and finally inactivated (5VKE) states. The authors write on page 12 that "The block of conduction during inactivation appears to result from pinching at the selectivity filter...", but given the end point was forced to be the X-ray structure with pinching, wasn't this outcome predetermined? This raises a significant point of how much has choice of endpoints predetermined the final states of the string? i.e. How much is an end state actually allowed to draft away from the initial Xray structure. Was a bead placed at the very endpoint and allowed to update via swarms, or was it fixed and all beads just interpolate between those fixed end states? The reason this is important is that it is plausible the inactivated crystal structure with pinching but not other changes (such as complete V76 carbonyl flipping or outer filter splaying), may not be the actual free energy minimum structure for that state and that force field.

The reviewer is right to point out that this observation is most likely a consequence of the choice of the end points of the initial string. The string method assumes that the end points of the string are fairly representative of the initial and final states of the processed studied. In this case, for ease of use, the endpoints of the simulation were fixed. When endpoints are left free to relax, they drift towards the closest minima and make comparisons between force fields, between simulation conditions, etc more difficult.

We do agree that the selection of initial and final states as well as the starting string are important modeling choices. For this reason, we were very mindful and made these choices based on the existing published evidence (available at the time).

We will make these details explicit in a revised version of the manuscript.

Another obvious concern is the possible reliance on the initial pulling procedure used before string optimisation began. Fig.2 Supp 1 shows generally that the Amber path stayed pretty close to the initial steered MD path, whereas Charmm drifted downward away from that path. One could justifiably ask, if a very different initial path was chosen, might different local minimum pathways result, including Amber sampling a path like Charmm? How does one test whether or not the final path has not been trapped in some local trough of free energy? e.g. Imagine starting the Amber string using an initial path like the more diagonal Charmm-like path, or even a more extreme unphysiological one, such as a steered trajectory that initially inactivates before opening the gate. Would the final results be the same? I appreciate the simulations are very expensive and such trials may not be possible, but what evidence is there that the final path has not been trapped away from the global minimum?

As stated above, the reviewer is right to point out the weakness of the method of converging to the closest local minimum free energy path. It is unfortunately computationally infeasible to test many possible paths. For this reason, we chose to initiate our calculations with a pathways based on experimental data; in this case based on available X-ray structures. In addition, it is necessary to contrast the results of the simulation with available experimental evidence: the string method with swarms of trajectories, when aptly used, has a history of bringing useful insights to several biological systems (Lev et al. 2017b; Suh et al. 2019, Fleetwood et al 2021, 2019; McComas et al. 2022).

As already noted, the fact that the two force field yield very different energy landscapes is evident since they would otherwise converge to the same final pathway given the same initial pathway guess.

One test offered by the authors is a set of unbiased MD simulations launched from points on the string. The authors ran 200ns simulations and write on page 5 that "These simulations have the expected stability based on their starting values. This is a good quality test to check the correct estimation of the general features of the free energy surface". While this sounds reasonable, 200ns MD may only be sufficient to begin to explore locally within the solved free energy trough, much like the swarms in the iterations were able to do. My own examination of Fig2 Supp 5 is that some of these simulations linger around the expected states and some drift away within the general trough of sampling, which is a good sign. What those 200ns simulations may not be able to do is escape that trough and see evidence of other possible solutions, beyond what was sampled with the string that was tied to Xray endpoints and trapped in the solution pathway that was already formed after 100-300 iterations. Overall, the string involved 800 iterations of 10ps swarms (80ns around each bead; albeit 32 trajectories in parallel), allowing good local sampling around the beads in the free energy trough, but in terms of ability to diffuse away from that point, only being comparable in contiguous trajectory time to the unbiased MD tests. It therefore would have been interesting to see if longer simulations remain in this trough; though I understand the challenges in running so much MD. Such simulations may, however, lead to exploration beyond what was seen in the string solutions.

We agree with the authors that longer simulations would be very interesting to understand the behavior of the string-of-swarms method and how it behaves for this intricate FES. Note however, that 80 ns divided over 32 trajectories yields an overall trajectory length that is ~two orders of magnitude below a single 200 ns-long simulation. We thus still stand by our statement that the fact that these simulations behave as expected from the free energy landscapes is a good quality check of the CVs and of the resulting free energy landscapes.

Force field effects and origin:

Regarding the effect of the chosen force field, the authors state that "Given that our simulations were conducted under activating conditions, we had expected the open states to be more populated than the closed ones. Simulations carried out at higher pH may be able to resolve this inconsistency". Also running at high pH would be a nice thing to do to prove the method is in fact sensitive to conditions to see a shift in the distribution of states.

Indeed this is the logical next step for future work.

But the question is why were open states not more occupied under low pH and 50mM K+? From my analysis of the figures, the results show that the Charmm force field tends to allow for opening of the channel somewhat (at least with similar free energy for partially and fully open to closed) whereas Amber tends to close the channel more (with more uphill energy as the channel opens than Charmm; Fig 2). i.e. at low pH and 50 K+, isn't the Amber model incorrectly reporting fairly strong bias against opening? Moreover, regarding the free energy of the inactivated state itself, why should we not expect equilibrated channels under activating conditions to eventually fall into an inactivated state, in which case we should expect low free energy of that state (as found with Charmm and not Amber in Fig2), but with a slow rate. While much discussion in the manuscript appears to discuss limitations in Charmm (although on page 12 discussion leans either way), these factors may seem to favour Charmm over Amber.

We would like to thank the reviewer for raising these points. We can only speculate about what might be the reasons for these discrepancies, and we have tried to be as honest as possible in our manuscript and avoid overinterpretation of our results. It is interesting that Reviewer 2 gathered from our data that the AMBER results were more consistent with expectations while this reviewer thought the opposite. This does reinforce our decision to avoid taking sides and present both options. Our personal opinion is currently that both force fields are imperfect at describing all the aspects of the activation-inactivation gates coupling. We will include more discussion in the revisions of the manuscript.

On page 12 the authors explain the possible causes for force field dependence, although this seems limited to ion interactions, glutamate charges and dihedrals. But it would be nice to get a bit more insight into what terms may have influenced the pathway, in particular involving interactions between TM2 and the base of the selectivity filter and hydration behind the filter. Regarding ion interactions, is there a good reason to believe ions are key to the difference seen? i.e. How were ions involved differently in the state transitions involving Amber and Charmm? The authors have noted a role for ion-carbonyl interactions.

We agree that this would be interesting, but judged that this would be better done in a separate study. We do note that the K-carbonyl interactions have been reported as candidates for these discrepancies, as mentioned and cited in the manuscript. Very recent simulations using ab initio MD support that the overstimation of the K-carbonyl interaction is the reason for the low conductance of potassium channels in classical MD, refer to Hui et al. Biophysical Journal, vol. 122, issue 3, p. 520a. We will add this reference in revisions.

It is important that the authors explain which is the two competing models has been used and why. i.e. Off-the-shelf Charmm36 force field includes strong K+-backbone carbonyl interaction, previously seen to promote high ion occupancy, similar to Amber, whereas Lennard-Jones parameters modified to match N-methyl-acetamide and water partitioning (such as early Berneche, Noskov and Roux work) reduce ion occupancy and increase water content inside the filter.

We have used “off-the-shelf” or conventional CHARMM36 as described in the literature cited.

Reviewer #2 (Public Review):

[…] The study is impressive and interesting. However, I have a number of concerns that the authors may wish to address in a revised version of the manuscript.

First, concerning a set of unbiased simulations spawned at different regions of the investigated free energy landscapes, the authors write: "These simulations have the expected stability based on their starting values".

Fig 2.c shows a rather smooth downhill slope in the free energy curve towards the closed state for AMBER , so wouldn't the expected behavior in that case be that all unbiased trajectories end up in the closed state, or at least travel a substantial amount in that direction? However, that is not observed. This should be further investigated.

It is true that this would be the effect we should observe after a significant simulation time. Resorting to 200ns-long simulations, our goal was to test whether the local free energy basins identified by the string-of-swarms method were indeed metastable. If that were the case, we would expect the trajectories to remain within the basins on medium timescales due to the kinetic barriers that would need to be overcome to transfer to other basins. Of course, if simulations were long enough, all basins would eventually be explored by the trajectory with a probability related to the relative free energy of the basins.

Second, "This suggests that stabilization of the partially open state by the removal of bound lipids can explain the increase in open probability" is an odd statement, as "stabilization of the partially open state" means almost the same as "increase in open probability".

It is true that one appears to necessarily imply the other. An increase in open probability could potentially come from two effects: a stabilization of the open state or a destabilization of the closed one. In a two-state system, the two cases are indistinguishable since only relative difference in free energies matter. However, this is a three state system, if one takes as a reference the energy of the inactivated state, there is an effective difference in the physics of the system if a stabilization of the open state or a destabilization of the closed state occurs.

The statement "both force fields yield inactivation barriers that are orders of magnitude lower than what is expected from electrophysiology experiments" seems inaccurate. Perhaps the authors mean "inactivation rates that are orders of magnitude lower" rather than barriers?

Yes, this was a mistake on our part. We will amend the manuscript.

In addition, the assertion "The CHARMM force field, on the other hand, results in landscapes in agreement with the fact that one of the dominant states in activating conditions is the partially open state, as revealed by a combination of ssNMR+MD." seems to hold for the AMBER force field without PG lipids rather than for CHARMM?

AMBER simulations with or without bound PG lipids have a fully open state basin within the minimum free energy path (Fig 4a, 4b) which is not the case for CHARMM (Fig 2b). In that sense, the CHRAMM force field seems to be in better agreement with the ssNMR data. The ssNMR+MD study however suggests that the PO open state basin should be the lowest in free energy. In both cases, however, the C basin is lower in free energy than the PO. We can only speculate about why that may be.

Together with the higher barrier towards the inactivated state as well as covering most known x-ray structures along the inactivation pathway, this would seem to point all in the direction that the studied AMBER force field provides a more faithful picture of the inactivation pathway than CHARMM. I, therefore, find the somewhat inconclusive summary as presented in Fig. 5 a bit uninformative, as it suggests that both mechanisms might be equally likely.

Although the X-ray structures do suggest an AMBER-like path, structural information in isolation is not sufficient to fully understand a phenomenon of dynamical nature. The X-ray structures of metastable structures particularly of open states require the use of engineered mutations and other techniques to trap these states. We of course do not question that a lot of very valuable information can be derived from them, but they should be considered in the context of other computational and experimental techniques. We believe we are very explicit in the text in discussing the weakness and strengths of either possibilities. In fact, we find it interesting that Reviewer 1 gathered from our data that the CHARMM results were more consistent with expectations. This does reinforce our decision to avoid taking sides and present both options. Our personal opinion is currently that both force fields are imperfect at describing all the aspects of the activation-inactivation gates coupling.

Overall, the study would benefit from a follow-up step to become more conclusive. This could be either in the form of the suggested L81 mutation or changing the simulation conditions to inactivating conditions such as low salt, in which case the inactivated state would be expected to become a minimum, which would provide an additional reference point for validation. Either of these would narrow down the spectrum of possible mechanisms.

We absolutely agree with this reviewer. These are great suggestions for further investigations that will definitely be considered in future studies.

Reviewer #3 (Public Review):

[…] The analysis is careful and is state-of-the-art. The results reveal remarkable differences between the CHARMM and AMBER force fields.

Unfortunately, the "elephant in the room" with regards to K+ channel inactivation is the significance of the dilated structures more recently obtained by Xray and EM. While it is worthwhile doing our best to really understand the constriction mechanism of KcsA, and the present manuscript does an excellent job at that, the ground has shifted and understanding finer points about KcsA constriction has become, unfortunately, not the most prominent issue in the field at the present time.

Let's discuss the current situation about the inactivation of K+ channels. The situation is fairly unsettled. The KcsA channel was the first for which some atomic structure and mechanism, centered on a constriction of the selectivity filter, were proposed. The constricted conformation really does not conduct because the filter is too narrow. More recently a few structures (Xray and EM) for channel mutants known to have more propensity to inactivate have revealed a different conformation of the filter which appears to be dilated toward the extracellular side. This is a conformation that had never been seen previously. Different "camps" co-exist in the K+ channel community about inactivation. Those who were very skeptical about the constricted conformation claim that the new dilated structures is the final truth. While the dilated structures are certainly part of the body of information that we have now, but their significance remains somewhat unclear if anything because of the fact that they are not perfectly occluded and they allow ion conduction! While it is worthwhile doing our best to really understand the constriction mechanism of KcsA, and the present manuscript does an excellent job at that, the ground has shifted and understanding finer points about KcsA constriction has become, unfortunately, not the most prominent issue in the field at the present time.

We appreciate the reviewer’s comments and we are also grateful for the contextualization of the current state of the literature with respect to KcsA inactivation.

Although we acknowledge the importance of these new findings and look forward to a lively debate in the literature regarding the importance of this alternative mechanism, this information was not available at the time when this study was started. In any case, for an initial study with a novel technology and with methodological choices such as the force field choice, studying the more established path seems still a valid choice. Of course, the techniques used to study this method can be used to study new hypotheses and contrast them with our current work. This will be an important line of work going forward. We will add further literature discussion to the manuscript and better outline how we decided on the scope of this study.

Author Response:

Weaknesses:

1) In vivo studies are limited to select outcomes of recovery and do not validate or address mechanism of action in vivo.

2) Known activities of DMAPT beyond microtubule detyrosination, such as oxidative stress, mitochondrial function and NFkB inhibition, are not considered in experimental examinations or in the interpretation of findings.

Response: Our research indicates that parthenolide exhibits a regenerative effect within a nanomolar range and with a bell-shaped concentration-response curve in culture. Moreover, we demonstrate a close correlation between the inhibition of detyrosinated microtubules and regeneration and consider the effects of hIL-6 or PTEN-KO on detyrosination in mouse and human RGCs. Therefore, we offer a coherent and satisfactory mechanistic explanation for the effects of parthenolide. We, therefore, feel the request to experimentally explore additional, somewhat speculative possibilities is not reasonable or helpful, and this issue should not be considered as a weakness.

Moreover, to the best of our knowledge, no evidence suggests profound antioxidative effects of DMAPT or parthenolide within these low-concentration ranges and that these would affect axon regeneration. Antioxidative effects may also not explain the observed bell-shaped curve. Furthermore, we have already considered the effect of NFkappaB in our previous work (Gobrecht et al., 2016) and shown that NFkappaB remains unaffected by low concentrations of parthenolide. Hence, conducting additional experiments addressing oxidative stress or other speculative causes will not strengthen our findings and do not justify the additional sacrifice of animal lives. Nevertheless, we will consider discussing these points in a revised version.

Author Response

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

Reviewer #1 (Public Review):

Jamge et al. sought to identify the relationships between histone variants and histone modifications in Arabidopsis by systematic genomic profiling of 13 histone variants and 12 histone modifications to define a set of "chromatin states". They find that H2A variants are key factors defining the major chromatin types (euchromatin, facultative heterochromatin, and constitutive heterochromatin) and that loss of the DDM1 chromatin remodeler leads to loss of typical constitutive heterochromatin and replacement of this state with features common to genes in euchromatin and facultative heterochromatin. This study deepens our understanding of how histone variants shape the Arabidopsis epigenome and provides a wealth of data for other researchers to explore.

Strengths:

1) The manuscript provides convincing evidence supporting the claims that: A) Arabidopsis nucleosomes are homotypic for H2A variants and heterotypic for H3 variants, B) that H3 variants are not associated with specific H2A variants, and C) H2A variants are strongly associated with specific histone post-translational modifications (PTMs) while H3 variants show no such strong associations with specific PTMs. These are important findings that contrast with previous observations in animal systems and suggest differences in plant and animal chromatin dynamics.

2) The authors also performed comprehensive epigenomic profiling of all H2A, H2B, and H3 variants and 12 histone PTMs to produce a Hidden Markov Model-based chromatin state map. These studies revealed that histone H2A variants are as important as histone PTMs in defining the various chromatin states, which is unexpected and of high significance.

3) The authors show that in ddm1 mutants, normally heterochromatic transposable element (TE) genes lose H2A.W and gain H2A.Z, along with the facultative heterochromatin and euchromatin signatures associated with H2A.Z at silent and expressed genes, respectively.

Weaknesses:

1) Following up on the finding that H2A.Z replaces H2A.W at TE genes in ddm1 mutants, the authors provide in vitro evidence that DDM1 binds to H2A.Z-H2B dimers. These results are taken together to conclude that DDM1 normally removes H2A.Z-H2B dimers from nucleosomes at TE genes and replaces them with H2A.W-H2B dimers. However, the evidence for this model is circumstantial and such a model raises a variety of other questions that are not addressed by the authors.

The Reviewer raises a series of interesting questions. We proposed that DDM1 exchanges H2A.Z to H2A.W because it is the simplest model and also because LSH - the mammalian ortholog of DDM1 exchanges H2A to macroH2A. However we do stress in the revised manuscript that this is a model and other possible models that could involve chaperones and additional remodelers are possible. Addressing why the loss of DDM1 results in a net exchange of H2A.W to H2A.Z is not the purpose of this study. Here we use the perturbation caused by ddm1 as a means to address the importance of the dynamics exchange of H2A variants in setting up the chromatin states. We do observe that perturbing this dynamic exchange causes an important perturbation of chromatin states. This further supports our main conclusion: H2A variants dynamics are one important factor that organizes chromatin states.

For example: if DDM1 does remove H2A.Z from TE genes, how does H2A.Z normally come to occupy these sites, given that they are highly DNA methylated and that H2A.Z is known to anticorrelate with DNA methylation in plants and animals?

The anticorrelation between H2A.Z and DNA methylation is observed at steady state. The exchange of H2A.Z to H2A.W that results from the action of DDM1 would indeed remove unwanted H2A.Z from regions occupied by DNA methylation as suggested by the Reviewer.

Given that H2A.Z does not accumulate in TEs in h2a.w mutants, how would H2A.X and H2A instead become enriched at these sites if DDM1 cannot bind these forms of H2A?

This is a valid question: We envisage that H2A.X and H2A are deposited by remodelers and chaperones other than DDM1 in the h2a.w mutant.

Given that there are no apparent regions with common sequence between H2A.Z and H2A.W variants that are not also shared with other H2A classes, how would DDM1 selectively bind to H2A.W-H2B and H2A.Z-H2B dimers to the exclusion of H2A(.X)-H2B dimers?

It was shown by the Muegge Lab both in vitro and in vivo that LSH - the mammalian ortholog of DDM1 binds to macroH2A and H2A, and these two H2A variants do not share similar specific region. Yet it remains to determine which region of H2A.Z and H2A.W binds to DDM1, which does not fit in the scope of this study.

Reviewer #2 (Public Review):

Jamge et al. set out to delineate the relationship between histone variants, histone modifications and chromatin states in Arabidopsis seedlings and leaves. A strength of the study is its use of multiple types of data: the authors present mass-spec, immunoblotting and ChIPseq from histone variants and histone modifications. They confirm the association between certain marks and variants, in particular for H2A, and nicely describe the loss of constitutive heterochromatin in the ddm1 mutant.

The support for some of the conclusions is weak. The title of the discussion, "histone variants drive the overall organization of chromatin states" implies a causation which wasn't investigated, and overstates the finding that some broad chromatin states can be further subdivided when one considers histone variants (adding variables to the model).

We have removed subtitles in the discussion and have taken care to avoid over simplified statements.

Adding variables to a ChromHMM model naturally increases the complexity of the models that can be built, however it is difficult to objectively define which level of complexity is optimal. The differences between states may be subtle to the point that they may be considered redundant. The authors claim that the sub-states they define are biologically important, but provide little evidence to support this claim. It is not obvious whether the 26 states model is much more useful than a 9-states model. Removing variables naturally affects the definition of states that depend on these variables, but it is also hard to define the biological significance of that change. This sensitivity analysis is thus not very developed.

We agree that adding more input tracks/ data will increase the complexity.

But we would like to mention the differences of this study and the 9-state model,

1) We have included the histone variants which have been previously missed in chromatin state definition.

2) The previous 9-state model used data from different tissue types. In this study all the data generated and analyzed is from seedlings.

3) Increasing the number of states allowed us to resolve heterochromatin states compared to 9-state model which was previously missed. (BioRXiv)

4) The biological relevance of the 26 states model is analyzed and described in depth (States BioRxiv paper).

In addition we have now updated the Figure 2F to include a more direct comparison of marks used in both models. And we have expanded the description in the methods section and our reasoning behind using 26 state model to be analyzed in depth.

There are issues with the logical sequence of arguments in Fig1 and Fig3. Fig1A shows that nucleosomes often contain both H3.1 and H3.3. Therefore pulling-down H3.1-containing nucleosomes also pulls down H3.3 and whether specific H2A variants associated with H3.1 cannot be answered in this way (Fig1B).

We thank the Reviewer for point this out. If 60% of nucleosomes are homotypic and if they would associate with a specific H2A variant this would be clearly visible on WB as a much stronger band. Also, the MS data presented in Figure1 figure supplement 1D clearly show that all H2A variants associate with both H3.1 and H3.3. We have included in the revised version more detailed explanation to clarify this point.

The same issue likely carries to the investigation of the association with H3 modifications if Fig1C and 1D, since the H3.1-HA pull-down also pulls down endogenous H3.1 (so presumably the rest of the nucleosome, with H3.3, as well).

We disagree on this point. The H3 band corresponding to the transgene copy is either H3.1 or H3.3, so all signals on upper band (T) in Figure 1C are associated with either H3.1 (H3.1 IP) or H3.3 (H3.3 IP), thus unambiguously showing that all modifications we analyzed are present on both H3.1 and H3.3. Furthermore, data shown in Figure 1D and E, where we analyzed modifications on K27 and K36 which are in the H3 region that can be distinguished between H3.1 and H3.3 by MS clearly demonstrate that these modifications are present on both H3.1 and H3.3. In order to make this clearer, we also extended the description of this part in the Results section to emphasize this.

In Fig3, the conclusion that it is the loss of H2A.Z -> H2A.W exchange in the ddm1 mutant that causes loss of constitutive heterochromatin is rushed. The fact that the h2a.w mutant does not recapitulate the loss of constitutive heterochromatin seen in ddm1 argues against this interpretation.

We agree that at first the minimal impact of the loss of H2A.W alone is surprising. However, we point to the preprint https://www.biorxiv.org/content/10.1101/2022.05.31.493688v1. There it is shown that the joint loss of H2A.W and H3K9 methylation (also observed in ddm1) affects silencing of a large range of transposons that also lose silencing in ddm1.

It's also difficult to conclude about the importance of dynamic exchanges when the ddm1 mutation has been present for generations and the chromatin landscape has fully readapted. Further work is needed to support the authors' hypothesis.

We apologize that the Reviewer could not find the information regarding the origin of ddm1 mutant material. We did not use a mutant where ddm1 mutations was kept for generations. We were in fact very careful on this point and used leaves from ddm1 first homozygous plants segregated from heterozygous ddm1 kept heterozygous.

The study also relies on a large number of custom (polyclonal) antibodies with no public validation data. Lack of specificity, a common issue with antibodies, would muddle the interpretation of the data.

We added information about validation of custom made antibodies into Methods: ”Specificities of custom made polyclonal antibodies against Arabidopsis H2A.Z.9, H2A.X, H2A.W.6, H2A.13, H2A.W.7, H2Bs, and linker histone H1 were validated in previous publications (Yelagandula et al., 2014; Lorkovic et al., 2017; Jiang et al., 2020; Osakabe et al., 2021).“ For H2A.2 and H2A.Z.11 antibodies we provide validation data as Figure 2 figure supplement 1.

Overall, this study nicely illustrates that, in Arabidopsis, histone variants (and H2A variants in particular) display specificity in modifications and genomic locations, and correlate with some chromatin sub-states. This encourages future work in epigenomics to consider histone variants with as much attention as histone modifications.

Reviewer #3 (Public Review):

How chromatin state is defined is an important question in the epigenetics field. Here, Jamge et al. proposed that the dynamics of histone variant exchange control the organization of histone modifications into chromatin states. They found 1) there is a tight association between H2A variants and histone modifications; 2) H2A variants are major factors that differentiate euchromatin, facultative heterochromatin, and constitutive heterochromatin; 3) the mutation in DDM1, a remodeler of H2A variants, causes the mis-assembly of chromatin states in TE region. The topic of this paper is of general interest and results are novel.

Overall, the paper is well-written and results are clearly presented. The biochemical analysis part is solid.

Reviewer #4 (Public Review):

This work aims at analyzing the impact of histone variants and histone modifications on chromatin states of the Arabidopsis genome. Authors claim that histone variants are as significant as histone modifications in determining chromatin states. They also study the effect of mutations in the DDM1 gene on the exchange of H2A.Z to H2A.W, which convert the silent state of transposons into a chromatin state normally found on protein coding genes.

This is an interesting and well done study on the organization of the Arabidopsis genome in different chromatin states, adding to the previous reports on this issue.

Reviewer #1 (Recommendations For The Authors):

1) The rationale for switching from using 10-day old seedlings for chromatin profiling to using mature leaves in Figure 3 and beyond is not explained and introduces additional complexity into the analyses. The reasoning should be clearly explained in the text, and there are several additional suggestions or questions related to this that should be addressed:

This was done for practical reasons. We had already obtained some profiles of marks in ddm1 mutants and extended the dataset using the same stage of development because this tied this study with our previous study. Using different stages of development provides an additional benefit. The same chromatin states are observed in 10 day old seedlings and leaves of older plants. Constitutive heterochromatin is occupied by the same chromatin states and logically euchromatin is positioned on different genes as expected by the distinct pattern of gene expression at the two stages of development.

A) In the 16-state model (Figure 3A), euchromatin states were not well defined compared to the 26-state model. Why did the authors not profile these marks also, and could this explain why ddm1 mutants did not show a significant effect on euchromatin states in this model?

We apologize for the lack of detailed explanation: In our previous study we used leaves of five weeks ld plants to show the impact of ddm1 on the profiles of H2A.W.6, H2A.X, H1, H3K9me2, H3K36me3 and H3K27me3 in leaves (Jamge, Osakabe et al., 2021). This study showed that DDM1 causes the deposition of H2A.W.6 to heterochromatin and we thus used leaves to extend this investigation to the two other marks of heterochromatin (constitutive or facultative) H3K9me1, H2A.W.7 and H2A.Z.9 and H2A.Z.11.

B) The authors state that the tissue types do not impact the definition of chromatin states. However, there is a clear difference in the portion of the genome occupied by each chromatin state between leaf and seedling (states 1, 5, 8, 13, and 14; Figure S3A).

We had missed a comment on supFig3B and have now provided more explanation: “Although the composition of the chromatin states did not vary significantly between seedlings and leaves, each state occupied a similar proportion of the genome in seedling or leaves to the exception of state 5 present primarily in leaves and state 13 only present in seedlings (Figure 3 figure supplement 3A, right column with green bars) and the euchromatin states occupied different genes (Figure 3 figure supplement 3B) as expected by the dissimilar transcriptomes of these two developmental stages.”

2) The naming of supplemental figures throughout the text is confusing as the legends refer to them as "Figure SX" but they are called out in the text as "Figure X figure supplement XA-B". The eLifeconvention is "Figure X figure supplement XA-B".

This was changed.

3) In Figure 4, Panel D is mislabeled as C in the figure, and C is lacking a label.

4) Please remove the word "the" from the title.

This was done

Reviewer #2 (Recommendations For The Authors):

Fig1D legend should also mention K37.

This was corrected.

Fig2F legend should say "no H3 modifications" rather than "no histone modifications" This was corrected.

Fig4 labels C/D do not correspond to the legend. D is missing and C should go to the ddm1 stacked barplot.

This was corrected.

H3 variants analysis: Taking the relative abundance of H3.1 and H3.3 (and transgenes) into account would be useful to interpret the results of the nucleosome composition results. If they are at equivalent amounts, the null hypothesis of independent association would give 50% heterotypic nucleosomes and 50% homotypic.

This is a valid comment. In an ideal system the last statement would be correct, but this does not take into account chromatin dynamics associated with replication, transcription, etc. Also, total amounts of H3.1 and H3.3 in tissue we used for the experiment is not known. It could possibly be inferred from RNAseq data, but if this would reflect real amounts of the protein is highly questionable. In Arabidopsis there are 5 H3.1 genes and 3 H3.3 genes. Nevertheless, we recalculated data for H3.1 and H3.3 and this has been updated in the main text (~60% of H3.1 and ~42% of H3.3 immunoprecipitated nucleosomes contained both H3 variants). Thus, from the available data these numbers are the best we can get.

p. 5 bottom paragraph. Repetition.

This was corrected

p12. The reference to LSH is dropped in without making clear how it is relevant. Expand on mechanism to suggest similar DDM1 mechanism?

This section was expanded to provide more background in the interpretation of the results.

p13. inversion between H2A.W and H2A.Z in "the loss of DDM1 prevents the replacement of H2A.W by H2A.Z".

This was corrected

p13. make it clear that the last sentence of the results is a working model, not a fully backed up conclusion.

Alternative models are mentioned in this section and in the discussion in the revised version.

p14 middle paragraph. Not clear what "in silico simulation" refers to. Simply chromatin-state classification with ChromHMM?

This refers to the Jacard index calculation in Fig. 2F that models the impact of the loss of H2A variants (or other elements of chromatin) on the definition of chromatin states by ChromHMM. This is now clarified.

p14 bottom paragraph: the H2A.Z tail repression of ubiquitin ligase but its being the favoured substrate for H2AK121Ub is apparently contradictory. Can this be explained?

This refers to H2B Ubiquitination and is now clarified

p15. Correlation between variants and modifications/chromatin states does not necessarily mean causation.

We agree and have improved the revised version in this respect.

p15 "forward feedback loop" is ambiguous (is it a feed-forward loop? A feedback loop?), just use "positive feedback loop".

This was corrected.

p23 top "$(Ingouff et al)" doesn't seem properly formatted.

This reference did not belong there and has been removed.

Data availability: GSE226469 is not public. The manuscript also mentions availability of source data for all the main figures, but I could not find it. It would be great to make the code publicly available too.

All the data and code will be public upon posting the revised version of the manuscript.

Reviewer #3 (Recommendations For The Authors):

My major concern is authors only used DDM1 as an example to show that the exchange of the histone variant contributes to definition and distribution of chromatin state on transposons (i.e., constitutive heterochromatin regions associated with H2A.W). Readers may wonder whether similar mechanisms also work at the euchromatin region. This point should be clearly discussed and mentioned in the Results (for example, cite recent work on INO80).

We discuss the impact of other remodelers in the Discussion in the revised version. We hope that the reviewer will understand that doing a study on the impact of other remodelers on chromatin states which would require dozens of new ChIP profiles and is clearly beyond the scope of revising a manuscript.

Minor:

1) Fig. 2A and 2B, what does color mean? I guess the color code is referred to chromatin states (Fig. 2F).

We have clarified on Figure 2A the attribution of a specific color to each chromatin state. This same color is used also in other panels of Figures 2 and S2.

2) Supplemental Figures: All the figure panels should be on the same page.

We rearranged supplemental figures so that each figure fits on one page. In places where this was not possible, we created additional supplemental figures.

3) "We observed that increasing state numbers from 26 to 27 gave rise to biologically redundant states.": Where are the data? Fig S2A? This figure is hard to understand.

In the updated manuscript, we have described the legend and the methods for FigS2A in more detail.

Reviewer #4 (Recommendations For The Authors):

A general concern refers to the text that frequently falls into excessive oversimplifications and/or overstatements, with the danger of being misleading for the reader. This needs to be thoroughly revised.

We added more careful statements and proposed alternative models when it was possible.

Specific comments.

1) Fig 1A. Authors found the ~40% of nucleosomes contained both H3.1 and H3.3. This is a significant finding that deserves a more detailed comment.

We now provide a more detailed description of IP and MS data presented in Figure 1. This should also help to avoid oversimplifications and/or overstatements as criticized in a general comment.

2) Fig 1C. "H3. And H3.3 bore the same sets and comparable levels of methylation and acetylation...". Too general statement, please specify. Is this also the case for H3K9me2? Others?

We did describe this part into more detail to emphasize more precisely what Figure 1 shows. We also included data on K9me into Figure 1 figure supplement 1H.

3) Fig 1D. Could you confirm the high level of H3K27me1 on H3.3?

H3K27me1 data are shown both by WB (Figure 1C) and Mass spectrometry (Figure 1D and E). We also provide a possible explanation for high levels of this mark on H3.3 by taking into account the fact that H3K27me1 is also produced by demethylation of H3K27me3 by JMJ demethylases.

4) All WB in Fig 1. They need to be quantified and normalized (plus statistical analysis) in order to provide strong support to the conclusions.

The conclusion of all WB are supported by quantified Mass spectrometry data and many WB were even repeatedly shown in Figure 1F (for example IPs for H2A variants and a large set of H3 marks used for WBs) with the same results. Also, association of H3K4me3 and H3K36me3 with H2A variants was analyzed in both ways (Figure 1F); IPs of variants and WBs of variants and marks and IPs of marks and WBs of marks and variants. For most of the data we do not have more than two repeats, so statistical analysis may not be possible.

Nevertheless, we are convinced that our major conclusions from data presented in Figure 1 and Supporting figure 1 (these are: that H3 variants form both homotypic and heterotypic nucleosomes, that H3 marks do not preferentially associate with H3 variants but some of them do so with H2A variants and that H3 modifications show very complex pattern of associations with each other) are fully valid as they were drawn from two orthogonal approaches and further supported by the chromatin states identified.

5) Fig. 2A. Authors focus on "the most parsimonious model" based on 26 chromatin states. This needs to be justified in a more explicit manner. It is surprising that this number emerges for an analysis of 27 independent variants and marks. What are the differences in the conclusions when other number of states are used? See also below (reduced number of number derived from the "concatenated model").

Why 26 states were chosen is now explained in great details in the method section. Since to the exception of H2A variants that are invariably homotypic, nucleosomes can be heterotypic for all other histone variants and histone modifications, the random combination of the 27 marks in one nucleosome representing one states is 4 H2A (without the subtypes) x 4H3 x 2H1 x 2(power16) (for each mark) which is well above the circa 26 states observed. This shows that our probabilistic model reduces the potential complexity of a theorical random association in a remarkable manner.

6) As a summary, it would be very helpful to generated a table (or similar) where is proposed chromatin state is ascribed to functional genomic elements.

This aspect of the work is presented in a preprint where the biological association with the chromatin is described in details. See Jamge et al 2002, https://www.biorxiv.org/content/10.1101/2022.06.02.494419v1

7) Fig 2F (and S2B). A comprehensive comparison a various approaches should include others and estimate the Jaccard similarity index: (1) the same of marks and variants used in the Sequeira-Mendes et al paper, and (2) the subset of marks and variants added in this study. In this way, a direct evaluation of the contributions could be more properly made.

We thank the reviewer for this suggestion and have now included a new column with the combination of marks and variants as used in Sequeira-Mendes et al., 2014 (see Figure 2F). These data clearly demonstrate that adding histone variants significantly contribute to the definition of chromatin states.

8) Fig. 3. Explain in more detail the concatenated model used here. Does the reduction in the number of chromatin states mean that the other do not add new information?

ChromHMM concatenated model allows to identify common definition of chromatin state in multiple tissue types. Here multiple cell types are concatenated leading to a shared definition of chromatin states, but specific to each cell type.

In our paper we used the concatenated model to identify common chromatin states in two different genotypes (WT and ddm1). The data for WT and ddm1 was obtained from leaves. As we had a limited number of ChIP-seq profiles in the leaves dataset The complexity of the concatenated model was also reduced compared to the extensive 26 chromatin state model. We chose to analyze 16-states in the concatenated model because this was the minimal number of states that gave rise to a similar complexity of heterochromatic states.

9) The ddm1 mutant. The text in page 14 is a bit confusing. It seems that H2A.Z is deposited on TEs and the exchanged by the H2A.W.

We have provided additional alternative models that could explain our observations.

10) Page 15: link between H2A.Z and H3K27me3. Gomez-Zambrano et al (2018, cited in the text, found that only a relatively small subset of (putative) targets are common to H2A.Z and H3K27me3. How do authors reconcile this with their statement supporting a link between both of them?

We refer to Gomez-Zambranao et al to illustrate the link between H2A.Z and H2AK121ub so we do not understand this comment. The strong link between H2A.Z and H3K27me3 is shown without ambiguity by our work and also Carter et al., 2018.

Author Response:

Reviewer #1 (Public Review):

The study investigates the nature of "trailblazer" cells in distinct tumor models, including luminal B (MMTV/PyMT) and triple negative (TNBC) tumors (C3-TAg). The authors note that the trail-blazer phenotypes in the TNBC model are more complex relative to the Luminal B model and represent distinct EMT programs associated with the expression of distinct EMT-TFs (Zeb1, Zeb2 and Fra-1). They demonstrated that of numerous EMT-TFs, Zeb1 and Fra-1 were required for increased cancer cell migration and invasion. They reveal that TGF-beta and EGF-mediated signaling are required for the diverse EMT states that are required for trailblazer cell activity and increased cell migration/invasion. TGF-beta signaling engaged Zeb 1 and Zeb2 while EGF sig-naling activated Fra-1. Indeed, inhibitors of either TGF-beta or EGF signaling could impair cell migration/invasion. While both pathways contributed to trailblazer phenotypes, EGF signaling was shown to interfere with certain TGF-beta induced transcriptional response, including the ex-pression of genes encoding extracellular matrix proteins.

One concern was the heavy reliance of the C3-TAg as the sole TNBC model in which the dis-tinct trailblazer phenotypes were described. The data in Fig. 3 of the submission reveals that the phenotypes observed in the C3-TAg model could be recapitulated in a TNBC patient-derived xenograft model (PDX). Using this PDX, the authors were able to show vimentin expression in lung metastatic TNBC cells that were intravascular, those that had extravasated and clusters of cancer cells fully within the lung parenchyma. This was an important addition to the manuscript. The additional experiments to investigate the role of Zeb1 and Zeb1 more fully, beyond the focus on Fra-1 in the initial submission was an additional strength of the new submission. Additional clarifications to the discussion also clarified the concepts articulated in the study. The study em-ploys multiple breast cancer models, utilizes numerous in vitro and in vivo assessments of the trailblazer phenotypes, and the experimental design is rigorous and the interpretation of the data is sound. The manuscript will be of general interest to the research community.

Thank you for the supportive comments. We are glad that the revisions addressed your prior concerns.

Reviewer #2 (Public Review):

This represents an important study that demonstrates a high degree of heterogeneity within trailblazer cells in clusters that participate in collective migration. Solid methods highlight this het-erogeneity and show that in TNBC cancers, trailblazer cells are defined by vimentin (and not Keratin 14) and are dependent on both TGFbeta and EGFR signaling. Additional, single cell stud-ies would further support this work.

Thank you for the suggestion. Our current data establishes that trailblazer cells are heterogene-ous using FACS, immunostaining and functional studies of fresh tumor organoids and estab-lished tumor organoid lines. In addition, our RNA-seq experiments provided deep insight into the nature of gene expression changes that corresponded with the evolution of new trailblazer states. This discovery of trailblazer cell heterogeneity was one of multiple key new discoveries in this manuscript, along with revealing a Krt14-independent invasion mechanism, the regulation of trailblazer cells by Tgfβ and Egfr signaling and a new compromise mode of signal integration. We agree that our results support further investigation of the nature and function of basal-like breast cancer heterogeneity during the progression to metastasis. However, a comprehensive implementation of scRNA-seq is mostly likely required to further unravel new aspects of hetero-geneity that substantially advance upon the conclusions supported by our current data. Such an undertaking is beyond the scope of this investigation.

We agree that scRNA-seq would be confirmatory of trailblazer cell heterogeneity that has been demonstrated with multiple approaches rather than a new discovery of heterogeneity.

Strengths:

The paper highlights that collective migration, and the nature of trailblazer cells can be highly heterogeneous. This is important as it suggests that the ability to move between states may su-persede a singular phenotype.

The paper uses animal models and organoids and in several areas attempts to correlate find-ings to human tissues.

The experiments are logically described.

Reviewer #3 (Public Review):

Cancer is a disease of many faces and in particular, the ability of cancers cells to change their phenotypes and cell behaviors - cancer cell plasticity - is a major contributor to cancer lethality and therapeutic challenge of treating this disease. In this study, Nasir, Pearson et al., investigate tumor cell plasticity through the lens of invasive heterogeneity, and in particular in models of tri-ple-negative breast cancer (TNBC), a subtype of breast cancer with particularly poor clinical prognosis and more limited treatment modalities. Using organoid models in a variety of matrix systems, microscopy, and signaling pathway inhibitors, they find that invading TNBC breast tu-mors, primarily in the C31-Tag genetically engineered mouse model of TNBC, are composed of heterogeneous invasive/"trailblazer" type tumor cells that in many cases express vimentin, a classical intermediate filament marker of epithelial-mesenchymal transition, and reduced keratin-14, another filament marker of basal epithelial cells associated with collective invasion in differ-ent breast cancer models. Supportive genetic and pharmacologic evidence is provided that gen-eration of these cells is TGF-beta signaling pathway driven, likely in vivo from the surrounding tumor microenvironment, in accord with published studies in this space. Another important as-pect of this study is the good transcriptional evidence for multiple migratory states showing dif-fering degrees of partial overlap with canonical EMT programs, dependent on TGF-beta, and suggestive but at present incomplete understanding of a parallel program involving Egfr/Fra-1 mediated effects on invasion. When taken in context with other recent studies (Grasset et al. Science Translational Medicine 2022), these data are broadly supportive of concept of targeting vimentin-dependent invasion programs in TNBC tumors.

The core conclusions of this paper are generally supported by the data, but there are some conceptual and technical considerations that should be taken into account when interpreting this study. Specific comments:

1) The contribution of the different vimentin-positive trailblazer cells to distant metastasis was not directly confirmed in vivo in this study. Given the limited proliferative potential of many fully EMT'd cells and in light of recent studies indicating that invasion can be uncoupled from meta-static potential, it seems important to directly test whether the different C31-tag isolates, varying in invasive potential in this study, produce metastases and if so do metastases abundance corre-late with the invasive potential in 3D culture. The collection of lungs at 34 days post injection de-scribed in methods is too short to evaluate metastatic frequency.

We agree that it is important to determine the contribution of trailblazer cells towards metastatic dissemination. In this manuscript, we show that Vimentin expressing cells in a triple negative breast cancer (TNBC) PDX model disseminate to the lungs (Figure 3F). We have also shown that Vimentin expressing SUM159 breast cancer (BC) trailblazer cells spontaneously metasta-size to the lungs in previous publications (Fig. 2–figure supplement 1C) and (Westcott et al, J Clin Invest, 2015, 10.1172/JCI77767 and Maine et al, Oncotarget, 2016, 10.18632/oncotarget.7408). Notably, the depletion of genes specifically expressed in trailblazer cells reduced spontaneous metastasis without significantly impinging on primary tumor growth (Westcott et al, J Clin Invest, 2015, 10.1172/JCI77767 and Maine et al, Oncotarget, 2016, 10.18632/oncotarget.7408). Our new results in Figure 5D show that Tgfβ activates genes that define the trailblazer state in the metastatic SUM159 trailblazer cell model. Thus, features of the Tgfβ regulated trailblazer program in the C3-TAg cells is active in the SUM159 trailblazer model of spontaneous metastasis. In addition, commonly employed BC cell line metastasis models, such as MDAMB231 derivatives are highly mesenchymal (Fig. 2–figure supplement 1C) and (Kang et al, Cell, 2003, 10.1016/S1535-6108(03)00132-6 and Minn et al, Nature, 2005, 10.1038/nature03799, as examples).

It is not technically feasible to establish a correlation between the relative invasion of The C3-TAg GEMM primary tumors and spontaneous metastasis. C3-TAg GEMM primary tumors de-velop rapidly and the mice must be euthanized prior to the detection of metastasis. This limitation of the model is mentioned in the Results section “Trailblazer cells are specified by Vimentin ex-pression in basal-like breast cancer patient tumors”. The aggressive primary tumor growth and limited spontaneous metastasis of the the C3-TAg model has also been previously reported by others (Green et al, Oncogene, 2000, 10.1038/sj.onc.1203280). Surgical resection of the original primary tumor is not feasible option to allow metastases to form since additional tumors develop in multiple mammary glands.

In response to reviewer requests, we initiated the growth of orthotopic primary tumors from con-trol or Tgfβ treated 1339-org cells to address the relationship between induction of the trailblazer state and primary tumor cell dissemination. We had to euthanize the mice at day 34 (d34) be-cause tumors within both cohorts had reached the maximum permitted diameter of 2 cm. This will be indicated in the Methods section with revised text. We detected CTCs from the mice bearing control and Tgfβ treated 1339-org cell tumors. However, no micrometastases were de-tected, which is indicated in the text describing Figure 4–figure supplement 3A-B. Thus, per-forming surgical resection in new experiments would not be expected to allow the later detection of metastasis, as there did not appear to be DTCs in the lungs that could initiate colonization. In addition, we would have to resect the tumors prior to d34 to successfully and humanely remove the primary tumors, further reducing the odds of metastases developing. We will continue our work to identify an experimental balance that permits sufficient primary tumor growth to initiate spontaneous metastasis. However, the time scale of resolving this technical challenge is uncer-tain and we believe that our published analysis of trailblazer cell metastasis and new findings here showing the dissemination of Vimentin expressing cells in a PDX model addresses the question of whether Vimentin expressing trailblazer cells metastasize.

We agree that certain cell states induced by EMT programs can limit the proliferative potential of tumor cells. As described in the Introduction, we previously found that the induction of a trailblaz-er state in a subset of breast cancer cell line models triggers a collateral cost in fitness that limits the ability of trailblazer cells to initiate tumor growth (Westcott et al, Cancer Res, 2020, 10.1158/0008-5472.CAN-20-0014). The traits that distinguish trailblazer cells which are capable of tumor initiation and metastasis versus trailblazer cells with reduced fitness have begun to be delineated. Our prior report suggested that cells that were dependent on p63 for growth lost their proliferative capacity when converting to a trailblazer state (Westcott et al, Cancer Res, 2020, 10.1158/0008-5472.CAN-20-0014). C3-TAg cells are not dependent on p63 for growth, which is indicated by the vast majority of the tumor cells lacking p63 expression in primary tumors and primary tumor organoids (Westcott et al, Cancer Res, 2020, 10.1158/0008-5472.CAN-20-0014), similar to the metastatic SUM159 breast cancer cell line model. We were also able to derive clonal trailblazer cell lines that lacked detectable p63 expression from a C3-TAg tumor (Figure 2—figure supplement 1B) and grow organoids even when the limited extent of p63 expression was further reduced by Tgfβ (Figure 5C). Additionally, the persistent Tgfβ treated 1339-org cells, which were enriched for trailblazer cells and had reduced p63 expression, were capable of initiating primary tumor growth (Figure 4F). Together, these results indicate that C3-TAg trail-blazer cells are capable of initiating metastatic colonization. However, given the heterogeneity in trailblazer states that we discovered, it is possible that a subset of trailblazer cell states have re-duced proliferative capacity. Our analysis approach in this manuscript would not necessarily de-tect these low fitness trailblazer cells if they were a relatively small fraction of the total trailblazer population. We will clarify this point in the Discussion section in the revised manuscript. Our re-sults have begun to reveal mechanisms for the transcriptional regulation of trailblazer cell heter-ogeneity. We plan to continue delineating the regulatory programs conferring specific transcrip-tion state, defining approaches for the prospective isolation of distinct trailblazer subpopulations and determining trailblazer subpopulation specific biomarkers to understand the specific contri-bution of distinct trailblazer subpopulations towards metastasis. Given the scope of this analysis, it is not feasible to incorporate these future studies into this manuscript.

2) The invasion of cancer cells is dependent on 3D matrix composition. In other studies, collec-tive cancer invasion is performed in exclusively collagen type 1 gels or in other instances entirely in 3D reconstituted basement membrane gel, e.g. lung cancer invasion studies. In this study, the authors use a mixture composed of both matrices. Given the invasion suppressive effects of matrigel, particularly for epithelial type cells, further studies would be important to determine whether the invasion phenotypes seen in this study are generalizable across matrix environ-ments.

The invasion of C3-TAg and PyMT organoids embedded in a 100% pure reconstituted base-ment is shown in Fig. 1–figure supplement 1G. We will emphasize that trailblazer invasion was evaluated in multiple ECM compositions with revised text and figure graphic. We also provide images for the reviewer showing that C3-TAg organoids collectively invade in a pure Collagen I ECM. Importantly, these findings are consistent with our results showing that Vimentin express-ing cells are associated with basal-like mammary tumor cell invasion in the complex ECM of C3-TAg GEMM primary tumors (Figure 2G) and patient primary tumors (Figure 3D). Moreover, Vimentin expressing cells disseminated to the lungs in the TNBC PDX that we evaluated (Figure 3F).

The ECM composition selected for experiments is dictated by the experimental question(s) being addressed. It is unlikely that mammary tumor cells would only ever collectively invade through an ECM that is either pure Collagen I or pure reconstituted basement membrane (BM). Indeed, it has been proposed that mixtures of Collagen I and BM proteins best reconstitute the complexity of primary tumor ECM (Hooper et al, Methods Enzymol, 2006, 10.1016/S0076-6879(06)06049-6). In line this observation, mixtures of Collagen I and BM proteins have been routinely used for the past 20 years to define mechanisms of 3D invasion; Xiang and Muthuswamy, Methods En-zymol, 2006, 10.1016/S0076-6879(06)06054-X; Calvo et al, Nat Cell Biol, 2013 10.1038/ncb2756; and Kato et al, eLife, 2023, 10.7554/eLife.76520, as examples).

Consistent with the known complexity of the ECM in the tumor microenvironment (TME), we detect Collagen I and Collagen IV (a key component of experimental BM) in the TME of primary breast cancer tumor models (Westcott et al, J Clin Invest, 2015, 10.1172/JCI77767). Important-ly, we have found that a mixture of collagen I and experimentally derived BM proteins reliably reveals breast cancer trailblazer cell invasion mechanisms that promote the malignant progres-sion and metastasis of primary tumors and whose expression correlates with poor patient out-come (Westcott et al, J Clin Invest, 2015, 10.1172/JCI77767 and Westcott et al, Cancer Res, 2020, 10.1158/0008-5472.CAN-20-0014, as examples). Notably, the relative differences in trail-blazer and opportunist cell invasive phenotypes are not dictated by the ECM composition used in our 3D assays. We have previously tested the invasion of trailblazer and opportunist subpopula-tions in different ECM compositions using both spheroid vertical invasion assays (Westcott et al, J Clin Invest, 2015, 10.1172/JCI77767). Increasing collagen I concentration enhanced the rela-tive rate of trailblazer cell invasion, with trailblazer cells always showing a significantly enhanced invasion relative to opportunist cells.

The relationship between trailblazer and opportunist cells that we have detected in primary tu-mors is recapitulated when using mixtures of Collagen I and BM proteins in our past publications and in this manuscript. The clonal opportunist cell lines derived from a C3-TAg tumor expressed high levels of the transcription factor p63 (Figure 2–figure supplement 1A-B). We previously showed that p63 restricts induction of a trailblazer state in human breast cancer trailblazer cell lines (Westcott et al, Cancer Res, 2020, 10.1158/0008-5472.CAN-20-0014). Notably, we showed that p63 expressing C3-TAg cells were not able to initiate collective invasion in the same ECM composition used in our current manuscript. Moreover, p63 cells in primary C3-TAg tumors were noninvasive opportunist cells that were limited to trailing p63-low trailblazer cells when collective-ly invading in primary tumors and in organoids (Westcott et al, Cancer Res, 2020). We now show that p63 expressing opportunist cell lines are limited to invading behind primary C3-TAg trailblazer cells and trailblazer cell lines in our 3D invasion assays (Figure 1B and Figure 1–figure supplement 1D-E). Together, these results indicate that the ECM employed in our 3D assays reveals the mechanistic underpinnings of both trailblazer and opportunist cell invasion in primary tumors.

With respect to lung cancer invasion, leader cells that we would classify as trailblazer cells have been isolated from 2 non-small cell lung cancer cell line spheroid models grown in pure reconsti-tuted BM extract (Konen et al, Nat Comm, 2017, 10.1038/ncomms15078). However, it unclear whether these cell line derived NSCLC trailblazer cells are more intrinsically invasive than non-trailblazer siblings in primary NCSCLC tumors or if the traits associated cell line NSCLC trail-blazer cells are required for metastasis. These tests have never been reported to the best of our knowledge. Similarly, it is not clear whether these NSCLC cell line derived trailblazer cells reflect features of primary NSLC primary tumor cells, as we are unaware of any such comparisons be-ing reported. Thus, there is no reason to consider pure reconstituted BM to be an equivalent or preferred experimental option to define trailblazer cell features. Nevertheless, as we mentioned before, our discovery approach identifies trailblazer cells that are intrinsically more invasive than opportunist siblings across multiple ECM conditions, including pure reconstituted BM and, im-portantly, in primary tumors.

3) TGF-beta is well known to induce EMT. Although this study identifies potential transcriptional mediators of the invasion/trailblazer program, is this program reversible?

We have previously shown the breast cancer trailblazer cells can convert to an opportunist state, demonstrating that trailblazer states are reversible (Westcott et al, J Clin Invest, 2015, 10.1172/JCI77767). In this manuscript. we show that C3-TAg organoid lines derived in the Tgfbr1 inhibitor A83-01 have few if any cells with a trailblazer phenotype relative to C3-TAg pri-mary tumors, suggesting a reversion of the trailblazer state (Fig. 4C and Figure 4–figure sup-plement 2A-C). However, our results do not entirely rule out the possibility that only non-trailblazer cells grew to establish the organoid lines. Indeed, the problem of tracing phenotypic conversions when evaluating heterogeneous populations is a systemic challenge that extends beyond our analysis of trailblazer cells. Clearly defining the conversion rates for trailblazer cells will require multiple genetic markers to distinguish the different trailblazer states we have now identified, in addition to phenotypic and molecular analysis over multiple days, or possibly weeks. Thus, further definition of the rate of reversion of different trailblazer cells is worthy line of future investigation rather than a feasible objective of this study.

Author Response:

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

Reviewer #1 (Public Review):

This paper describes the discovery, functional analysis and structure of TcaP, a protein encoded by the Vibrio phage satellite PLE that forms a size-determining scaffold around PLE procapsids made from helper phage ICP1 structural proteins. The system displays a fascinating similarity to the P2/P4 system, which had previously been unique in its use of a size-determining external scaffolding protein, Sid. The work is interesting, comprehensive and of high quality. The presentation could be improved as listed in the suggestions below.

An interesting observation is that PLE appears to be dependent on small capsids for efficient transduction. This is not completely surprising if the element uses a cos site type mechanism for packaging, since this requires an integer number of genomes to be packaged when the capsid is full, and this might be more difficult to accomplish when the helper capsid is much larger than the satellite, as is the case with ICP1. The authors mention in a few places that this is the first known satellite to have this requirement. However, this is not quite correct: a similar defect was seen in phi12/SaPIbov5, where the large phi12 capsid was not quite the right size for either two or three copies of the wildtype ("unevolved") SaPIbov5 (Carpena et al. 2016).

We thank the reviewer for bringing up this point. First, we agree that for cos type packaging systems, this would not be surprising. However, ICP1 is a pac type phage and we have evidence that PLE is also a pac rather than a cos type packaging satellite; therefore, PLE is the first headful satellite to show such a defect. For cos packaging elements, both SaPIbov5 and P4, non-integer genome lengths have been shown to pack less efficiently into capsids as pointed out above and shown in Carpena et al 2016 and Shore 1978. However, in both of these cases, the genomes were manipulated to change their size, suggesting that naturally occurring cos satellites maintain their genome sizes to be proportional to their capsid sizes or in integer proportion to their helper capsids. We will include a short summary of these previous findings in the main text to provide context for the rare decreases in transduction efficiency reported in the cos satellites.

The authors present several micrographs showing capsids formed in the presence or absence of wildtype or mutant TcaP and CP (Fig. 1, Fig 2., Fig 3). However, each micrograph shows only a handful of particles of the "correct" size, in addition to a few shells that are aberrant or of a different size. I miss a more statistically rigorous enumeration of shells of different size (PLE or ICP1 sized, or different), empty vs. full, aberrant shells etc. This could be presented as a size distribution graph, a histogram or in table form.

We thank the reviewer for this recommendation and agree that it would add to the manuscript. We will quantify these particles and present the data in the main text.

In the abstract, the term "divergent satellite P4" is vague and unclear. Divergent from what? Probably they mean distinct from or unrelated to PLE. Please clarify.

Yes, we did mean unrelated to PLE, and we will clarify in the text.

How do they know that gp123 is a decoration protein? Was this previously determined, does it have (sequence) similarity to other known decoration proteins, or is it simply the most likely designation based on its position in the genome?

Gp123 was annotated based on its position. While there is sequence similarity to other annotated Vibrio phages’ decoration proteins, we will clarify in the text that Gp123 is a putative decoration protein.

Although the reconstruction and modeling statistics are good, it is difficult to assess the quality of the map and the model from the presented figures. Details of the density and FSC curves (half-map and model-to-map) should be shown. It is also difficult to see the TcaP structure and how it compares to Sid from the figures presented.

We will address this concern in the revised manuscript.

Introduction, Paragraph 3: "...which is the number of coat proteins divided by 60" is not strictly speaking the definition of T number. The T number corresponds to the number of subtriangles that one triangular face of the icosahedron is divided into. It corresponds to the number of coat proteins divided by 60 in the canonical case, but in tailed phages, 5 copies are removed to make way for the portal protein. (Other viruses could be described as having architecture corresponding to a specific T number, but with divergent numbers of subunits, e.g. adenoviruses or polyomaviruses.)

We agree that our simplified explanation of the T number is not entirely accurate and will modify the sentence appropriately.

Reviewer #2 (Public Review):

Phage satellites are fascinating elements that have evolved to hijack phages for induction, packaging, and transfer, promoting their widespread dissemination in nature. It is remarkable how different satellites use conserved strategies of parasitism, utilising unrelated proteins that perform similar roles in their cognate elements. In the current manuscript, Dr. Seed and coworkers elucidated the mechanism used by one family of satellites, the PLEs, to produce small capsids, a process that inhibits phage reproduction while increasing PLE transmission. The work is presented beautifully, and the results are astonishing. The authors identified the gene responsible for generating the small capsids, characterised its role in the PLE transfer and phage inhibition, and determined the structure of the PLE-sized small capsids. It is a truly impressive piece of work.

We thank the reviewer for their positive evaluation of our work.

Reviewer #3 (Public Review):

The manuscript by Boyd and co-authors "A Vibrio cholerae viral satellite maximizes its spread and inhibits phage by remodelling hijacked phage coat proteins into small capsids" reports important results related to self-defending mechanisms that bacteria are used against phages that infect them. It has been shown previously that bacteria produce phage-inducible chromosomal island-like elements (PLE) that encode proteins that are integrated into bacterial genome. These proteins are used by bacteria to amend the phage capsids and to create phage-like particles (satellites) that move between cells and transfer the genetic material of PLE to another bacteria. That study highlights the interactions between a PLE-encoded protein, TcaP, and capsid proteins of the phage ICP1.

The manuscript is well written, provides a lot of new information and the results are supported by biochemical analysis.

We thank the reviewer for their supportive evaluation of our work.

Author Response:

We would like to thank the reviewers for their time in evaluating our manuscript. The reviewers provided constructive comments and suggested changes to improve our manuscript. The main comment was about the framing. We agree with the reviewers and will rewrite the manuscript to focus more on migration patterns than conservation. We will add and expand the paper's theoretical framework and include the studies and descriptions of migration patterns of individual species suggested by the reviewers. At the same time, some of the reviewers' comments (especially on the terms and suggestions for changing the title of the paper) are mutually exclusive. We will pay particular attention to this issue and improve the paper's theoretical basis.

Author Response

We are grateful for the constructive feedback and the possibility of further improving our manuscript in terms of quality and clarity. Below, we have prepared a brief answer to the points raised in the reviewers’ feedback. We plan to address all these issues fully in the revised version of the manuscript.

We agree that some of our claims were overly enthusiastic. We will rewrite parts of the manuscript to tame our statements. Additionally, we are thankful for the comments on the use of language, which we will certainly apply while editing the manuscript. Below, we focus on the main comments.

Both reviewers: We appreciate advice on possible confounding factors. We should note here that there is substantial evidence on the effects of alpha rhythm amplitude on the excitability of a neuronal network and, as a consequence, on the amplitude of evoked responses (Baumgarten et al., 2016 Cerebral Cortex; Iemi et al., 2017 eLife; Stephani et al., 2021 eLife). This effect is due to changing the gain for evoked responses, and it is quite different compared to the baseline-shift mechanism (BSM). In BSM, the changes in the amplitude of evoked responses occur due to the generation of an additional evoked response component, which we tried to reveal in our current work. Still, we agree with suggestions to test additional factors, such as earlier evoked responses, baseline window, and head size, and we will test those.

Reviewer #2 Comment 2: Certainly, for low-density recordings, some method of data transformation is required. Here we would like to show our reasoning for why we did not use current-source density (CSD) but rather utilised other approaches. First, the CSD transform performs well for spatially localised activities since it is a spatial high-pass filter. In our case, P300 and alpha amplitude dynamics are fairly widespread with low spatial frequency, and we believe we would not benefit from applying CSD. Second, CSD has been shown to be more sensitive to surface sources in the crowns of gyri. For activity in the P300 window, we have no reason to believe that this is the case. Third, as we completely agree that low density montage is a limitation, we used source reconstruction with eLoreta (Fig. 5) to refine the spatial localisation of potential sources of P300 and alpha amplitude change.

Reviewer #1 Comment 4: Our study is indeed based on a sample of older participants. However, in our previous work (Studenova et al., 2022), we compared young and elderly participants using resting-state data. There, we measured the baseline-shift index (BSI). We found that BSIs for elderly participants were lower in comparison to those for young participants. Therefore, despite these limitations, in the current study, we were still able to detect a correspondence between BSIs and evoked responses in elderly participants. Therefore, we believe that for a sample of young participants, the results should not be different.

Reviewer #2 Comment 4: We agree that mediation analysis will provide additional insights, and we will add it to the revised version of the manuscript.

Overall, we found the reviewer's comments very helpful. We will update the manuscript accordingly.

Author Response:

We would like to thank the reviewers for their comments on the manuscript. The primary concern that they raised is that the imaging data are largely qualitative. This is a fair assessment, and we agree that a careful quantitative characterization of TF clustering with and without IDRs using high resolution imaging would provide valuable insight that would extend our findings. Our goal for this study was to conduct a high level survey of IDR localization, for which we believe a qualitative overview was sufficient. We hope that this work can serve as a useful foundation for future studies of the complex roles that IDRs play in TF function.

Author Response

Reviewer #1 (Public Review):

1) Only one PITAR siRNA was tested in majority of the experiments, which compromises the validity of the results. Some results are inconsistent. For example, Fig 2G indicates that PITAR siRNA caused G1 arrest. However, PITAR overexpression in the same cell line did not show any effect on cell cycle progression in Fig 5I.

We thank the reviewer for this comment. Indeed, we have used two siRNAs in experiments related to Fig. 2C, 2D, and 2E. Keeping the reviewer’s comment, we plan to reproduce the results of Fig. 2F, 2G, 2H, 2I, 5A, 5B, 5E, and supplementary Fig. 5A using additional siRNA targeting PITAR.

The reason for the fact that “PITAR silencing showed a robust G1 arrest, but PITAR overexpression failed to show any effect on the cell cycle profile” is as follows: since glioma cells overexpress PITAR (which keeps the p53 suppressed), silencing PITAR (which will elevate p53 levels) in glioma cells will show a robust phenotype in cell cycle profile (in the form of increase G1 arrest). In contrast, the overexpression of PITAR in glioma cells (which already has high levels of PITAR and hence drastically reduced p53 levels) is unlikely to show any significant change in the cell cycle profile. But, a phenotype for PITAR overexpression on cell cycle profile can be shown in DNA-damaged (which induces p53 levels) glioma cells. Indeed, we have done this experiment in Fig. 5L, which shows G2/M arrest (42.34%) induced by DNA damage is reduced significantly (19%) in PITAR overexpressed condition (34.42%). However, keeping reviewers' comments in the right spirit, we plan to repeat this experiment with appropriate modifications to arrive at a more robust phenotype for PITAR overexpression.

2) The conclusion that PITAR inactivates p53 through regulating TRIM28, which is highlighted in the title of the manuscript, is not supported by convincing results. Although the authors showed that a PITAR siRNA increased while PITAR overexpression decreased p53 level, the siRNA only marginally increased the stability of p53 (Fig 5E). The p53 ubiquitination level was barely affected by PITAR overexpression in Fig 5F. To convincingly demonstrate that PITAR regulates p53 through TRIM28, the authors need to show that this regulation is impaired/compromised in TRIM28-knockout conditions. The authors only showed that TRIM28 overexpression suppressed PITAR siRNAinduced increase of p53, which is not sufficient. Note that only one cell line was investigated in Fig 5.

To address this issue, we will overexpress PITAR in TRIM28 silenced cells to show the requirement of TRIM28 for PITAR to inhibit p53. In addition, we also plan to carry out PITAR silencing and overexpression experiments in another glioma cell line as recommended by the reviewer.

3) Another major weakness of this manuscript is that the authors did not provide any evidence indicating that the glioblastoma-promoting activities of PITAR were mediated by its regulation of p53 or TRIM28 (Fig 6 and Fig 7). Thus, the regulation of glioblastoma growth and the regulation of TRIM28/p53 appear to be disconnected.

We would like to respectfully disagree with the reviewer on this particular point. We have indeed provided the following evidence in the current version of the manuscript glioblastomapromoting activities of PITAR were mediated by its regulation of p53 or TRIM28.

A) In Fig. 6, we demonstrate that PITAR silencing-induced reduction in the neurosphere growth is accompanied by a reduction in TRIM28 RNA and an increase in the CDKN1A RNA without a change in p53 RNA levels. We also demonstrate that PITAR overexpression-induced neurosphere growth is accompanied by an increase in the TRIM28 RNA, and a decrease in CDKN1A RNA without a change in p53 RNA levels.

B) To add strength to the above results, we plan to do western blot experiments under similar conditions to demonstrate the appropriate changes in TRIM28, p53, and CDKN1A levels. Also, we will do a TRIM28 rescue experiment in RG5 neurosphere cells.

C) In supplementary Fig. 6 (related to Fig. 6), we show that PITAR silencing failed to decrease neurosphere growth in mutant p53 containing GSC line (MGG8).

D) In supplementary Fig. 7 (related to Fig. 6), we show that PITAR silencing failed to inhibit colony growth of p53-silenced U87 glioma cells (U87/shp53#1). We also show that while PITAR silencing decreased TRIM28 RNA levels in U87/shNT and U87/shp53#1 glioma cells, it failed to increase CDKN1A and MDM2 (p53 targets) at the RNA level.

E) In Fig. 7, we show that the TRIM28 protein level is drastically reduced in small tumors formed by U87/siPITAR cells.

F) In supplementary Fig. 8 (related to Fig. 7), we show that glioma tumor formed by U87/PITAR OE express high levels of TRIM28 protein but reduced levels of p21 protein.

G) We also plan to do additional experiments, as described below, to demonstrate that glioblastoma-promoting activities of PITAR are indeed mediated by its regulation of p53 or TRIM28. We will demonstrate the inability of PITAR overexpression to induce the growth of glioma-tumor initiated by TRIM28 silenced U87 cells.

4) It is not clear what kind of message the authors tried to deliver in Fig 7F/G. Based on the authors' hypothesis, DNA-damaging agents like TMZ would induce PITAR to inactivate p53, which would compromise TMZ's anti-cancer activity. However, the data show that TMZ was very effective in the inhibition of U87 growth. The authors may need to test whether PITAR downregulation, which would increase p53 activity, have any effects on TMZ-insensitive tumors. Such results are more therapeutically relevant.

Reviewer #1 rightly pointed out that TMZ induces PITAR expression, which should compromise TMZ's anti-cancer activity. In addition, overexpression of PITAR also promotes glioma-tumor growth. Figure 7F&G demonstrates the following two facts:1. PITAR overexpression increases the glioma-tumor growth (Figure 7G, compare red line with the blue line), 2. PITAR overexpressing glioma-tumor are resistant to TMZ chemotherapy (Figure 7G, compare the pink line with the green line).

In addition, in Figure 2I, we indeed show that PITAR-silenced cells are more sensitive to TMZ and Adriamycin chemotherapy.

However, considering reviewers’ comments, we plan to repeat Figure 7A, combining TMZ chemotherapy and PITAR silencing to demonstrate that TMZ chemotherapy-induced PITAR indeed promotes chemo-resistance.

5) Lastly, the model presented in Fig 7H is confusing. It is not clear what the exact role of PITAR in the DNA damage response based on this model. If DNA damage would induce PITAR expression, this would lead to inactivation of p53 as revealed by this manuscript. However, DNA damage is known to activate p53. Do the authors want to imply that PITAR induction by DNA damage would help to bring down the p53 level at the end of DNA damage response? The presented data do not support this role unfortunately.

We appreciate reviewer #1 comments. Based on our model in 7H, we believe DNA damageinduced PITAR attenuates DNA damage response by increasing TRIM28 protein levels. TRIM28 ubiquitinates p53 in an MDM2-dependent manner ( Wang et al., 2005). Based on this, we hypothesised that PITAR-induced TRIM28 also contributes to MDM2 mediated ending of DNA damage response.

Considering the reviewers' comments, we plan to do the following experiment.

The kinetics of p53, TRIM28, p21, MDM2 protein levels, and PITAR RNA levels after DNA damage will be monitored in PITAR-silenced conditions. It is known that reduction in the DNA damage-induced p53 levels coincides with high levels of MDM2 accumulation. We believe that in PITAR-silenced cells, p53 levels will remain high for a longer time compared to control cells because of the lack of PITAR-induced TRIM28-mediated degradation of p53.

Author Response:

Reviewer #1 (Public Review):

[…] The major strength of the study is the elegant and well-powered data set. Longitudinal data on this scale is very difficult to collect, especially with patient cohorts, so this approach represents an exciting breakthrough. Analysis is straightforward and clearly presented. However, no multiple comparison correction is applied despite many different tests. While in general I am not convinced of the argument in the citation provided to justify this, I think in this case the key results are not borderline (p<0.001) and many of the key effects are replications, so there are not so many novel/exploratory hypothesis and in my opinion the results are convincing and robust as they are. The supplemental material is a comprehensive description of the data set, which is a useful resource.

The authors achieved their aims, and the results clearly support the conclusion that the AD and mean confidence in a perceptual task covary longitudinally. I think this study provides an important impact to the project of computational psychiatry.Sspecifically, it shows that the relationship between transdiagnostic symptom dimensions and behaviour is meaningful within as well as across individuals.

Response: We thank the reviewer for their appraisal of our paper and positive feedback on the main manuscript and supplementary information. We agree with the reviewer that the lack of multiple comparison corrections can also justified by key findings being replications and not borderline significance. We have added this additional justification to the manuscript (Methods, Statistical Analyses, page 15, line 568: “Adjustments for multiple comparisons were not conducted for analyses of replicated effects”)

Reviewer #2 (Public Review):

[…] The major strength and contribution of this study is the use of a longitudinal intervention design, allowing the investigation of how the well-established link between underconfidence and anxious-depressive symptoms changes after treatment. Furthermore, the large sample size of the iCBT group is commendable. The authors employed well-established measures of metacognition and clinical symptoms, used appropriate analyses, and thoroughly examined the specificity of the observed effects.

However, due to the small effect sizes, the antidepressant and control groups were underpowered, reducing comparability between interventions and the generalizability of the results. The lack of interaction effect with treatment makes it harder to interpret the observed differences in confidence, and practice effects could conceivably account for part of the difference. Finally, it was not completely clear to me why, in the exploratory analyses, the authors looked at the interaction of time and symptom change (and group), since time is already included in the symptom change index.

Response: We thank the reviewer for their succinct summary of the main results and strengths of our study. We apologise for the confusion in how we described that analysis. We examine state-dependence., i.e. the relationship between symptom change and metacognition change, in two ways in the paper – perhaps somewhat redundantly. (1) By correlating change indices for both measures (e.g. as plotted in Figure 3D) and (2) by doing a very similar regression-based repeated-measures analysis, i.e. mean confidence ~ time*anxious-depression score change. Where mean confidence is entered with two datapoints – one for pre- and one for post-treatment (i.e. within-person) and anxious-depression change is a single value per person (between-person change score). This allowed us to test if those with the biggest change in depression had a larger effect of time on confidence. This has been added to the paper for clarification (Methods, Statistical Analysis, page 14, line 553-559: “To determine the association between change in confidence and change in anxious-depression, we used (1) Pearson correlation analysis to correlate change indices for both measures and, (2) regression-based repeated-measures analysis: mean confidence ~ time*anxious-depression score change, where mean confidence is entered with two datapoints (one for pre- and one for post-treatment i.e., within-person) and anxious-depression change is a single value per person (between-person change score)”).

The analyses have also been reported as regression in the Results for consistency (Treatment Findings: iCBT, page 5, line 197-204: ‘To test if changes in confidence from baseline to follow-up scaled with changes in anxious-depression, we ran a repeated measure regression analyses with per-person changes in anxious-depression as an additional independent variable. We found this was the case, evidenced by a significant interaction effect of time and change in anxious-depression on confidence (b=-0.12, SE=0.04, p=0.002)… This was similarly evident in a simple correlation between change in confidence and change in anxious-depression (r(647)=-0.12, p=0.002)”).

This longitudinal study informs the field of metacognition in mental health about the changeability of biases in confidence. It advances our understanding of the link between anxiety-depression and underconfidence consistently found in cross-sectional studies. The small effects, however, call the clinical relevance of the findings into question. I would have found it useful to read more in the discussion about the implications of the findings (e.g., why is it important to know that the confidence bias is state-dependent; given the effect size of the association between changes in confidence and symptoms, is the state-trait dichotomy the right framework for interpreting these results; suggestions for follow-up studies to better understand the association).

Response: Thank you for this comment. We have elaborated on the implications of our findings in the Discussion, including the relevance of the state-trait dichotomy to future research and how more intensive, repeated testing may inform our understanding of the state-like nature of metacognition (Discussion, Limitations and Future Directions, page 10, line 378-380: “More intensive, repeating testing in future studies may also reveal the temporal window at which metacognition has the propensity to change, which could be more momentary in nature.”).

Reviewer #3 (Public Review):

[…] I think these findings are exciting because they directly relate to one of the big assumptions when relating cognition to mental health - are we measuring something that changes with treatment (is malleable), so might be mechanistically relevant, or even useful as a biomarker?

This work is also useful in that it replicates a finding of heightened confidence in those with compulsivity, and lowered confidence in those with elevated anxious-depression.

One caveat to the interest of this work is that it doesn't allow any causal conclusions to be drawn, and only measures two timepoints, so it's hard to tell if changes in confidence might drive treatment effects (but this would be another study). The authors do mention this in the limitations section of the paper.

Another caveat is the small sample in the antidepressant group.

Some thoughts I had whilst reading this paper: to what extent should we be confident that the changes are not purely due to practice? I appreciate there is a relationship between improvement in symptoms and confidence in the iCBT group, but this doesn't completely rule out a practice effect (for instance, you can imagine a scenario in which those whose symptoms have improved are more likely to benefit from previously having practiced the task).

Response: We thank the reviewer for commenting on the implications of our findings and we agree with the caveats listed. We thank the reviewer for raising this point about practice effects. A key thing to note is that this task does not have a learning element with respect to the core perceptual judgement (i.e., accuracy), which is the target of the confidence judgment itself. While there is a possibility of increased familiarity with the task instructions and procedures with repeated testing, the task is designed to adjust the difficulty to account of any improvements, so accuracy is stable. We see that we may not have made this clear in some of our language around accuracy vs. perceptual difficulty and have edited the Results to make this distinction clearer (Treatment Findings: iCBT, pages 4-5, lines 184-189: “Although overall accuracy remained stable due to the staircasing procedure, participants’ ability to detect differences between the visual stimuli improved. This was reflected as the overall increase in task difficulty to maintain the accuracy rates from baseline (dot difference: M=41.82, SD=11.61) to follow-up (dot difference: M=39.80, SD=12.62), (b=-2.02, SE=0.44, p<0.001, r2\=0.01)”.)

However, it is true that there can be a ‘practice’ effect in the sense that one may feel more confident (despite the same accuracy level) due to familiarity with a task. One reason we do not subscribe to the proposed explanation for the link between anxious-depression change and confidence change is that the other major aspect of behaviour that improved with practice did so in a manner unrelated to clinical change. As noted above in the quoted text, participants’ discrimination improved from baseline to follow-up, reflected in the need for higher difficulty level to maintain accuracy around 70%. Crucially, this was not associated with symptom change. This speaks against a general mechanism where symptom improvement leads to increased practice effects in general. Only changes in confidence specifically are associated with improved symptoms. We have provided more detail on this in the Discussion (page 9, lines 324-326: “This association with clinical improvements was specific to metacognitive changes, and not changes in task performance, suggesting that changes in confidence do not merely reflect greater task familiarity at follow-up.”).

Relatedly, to what extent is there a role for general task engagement in these findings? The paper might be strengthened by some kind of control analysis, perhaps using (as a proxy for engagement) the data collected about those who missed catch questions in the questionnaires.

Response: Thank you for your comment. We included the details of data quality checks in the Supplement. Given the small number of participants that failed more than one attention checks (1% of the iCBT arm) and that all those participants passed the task exclusion criteria, we made the decision to retain these individuals for analyses. We have since examined if excluding these small number of individuals impacts our findings. Excluding those that failed more than one catch item did not affect the significance of results, which has now been added to the Supplementary Information (Data Quality Checks: Task and Clinical Scales, page 5, lines 181-185: “Additionally, excluding those that failed more than one catch item in the iCBT arm did not affect the significance of results, including the change in confidence (b=0.16, SE=0.02, p<0.001), change in anxious-depression (b=-0.32, SE=0.03, p<0.001), and the association between change in confidence and change in anxious-depression (r(638)=-0.10, p=0.011)”).

I was also unclear what the findings about task difficulty might mean. Are confidence changes purely secondary to improvements in task performance generally - so confidence might not actually be 'interesting' as a construct in itself? The authors could have commented more on this issue in the discussion.

Response: Thank you for this comment and sorry it was not clear in the original paper. As we discussed in a prior reply, accuracy – i.e. proportion of correct selections (the target of confidence judgements) are different from the difficulty of the dot discrimination task that each person receives on a given trial. We had provided more details on task difficulty in the Supplement. Accuracy was tightly controlled in this task using a ‘two-down one-up’ staircase procedure, in which equally sized changes in dot difference occurred after each incorrect response and after two consecutive correct responses. The task is more difficult when the dot difference between stimuli is lower, and less difficult when the dot difference between stimuli is greater. Therefore, task difficulty refers to the average dot difference between stimuli across trials. Crucially, task accuracy did not change from baseline to follow-up, only task difficulty. Moreover, changes in task difficulty were not associated with changes in anxious-depression, while changes in confidence were, indicating confidence is the clinically relevance construct for change in symptoms.

We appreciate that this may not have been clear from the description in the main manuscript, and have added more detail on task difficulty to the Methods (Metacognition Task, page 14, lines 540-542: “Task difficulty was measured as the mean dot difference across trials, where more difficult trials had a lower dot difference between stimuli.”) and Results (Treatment Findings: iCBT, pages 4-5, lines 184-186: “Although overall accuracy remained stable due to the staircasing procedure, participants’ ability to detect differences between the visual stimuli improved.”). We have also elaborated more on how improvements in symptoms are associated with change in confidence, not task performance in the Discussion (page 9, lines 324-326: “This association with clinical improvements was specific to metacognitive changes, and not changes in task performance, suggesting that changes in confidence do not merely reflect greater task familiarity at follow-up”).

To make code more reproducible, the authors could have produced an R notebook that could be opened in the browser without someone downloading the data, so they could get a sense of the analyses without fully reproducing them.

Response: Thank you for your comment. We appreciate that an R notebook would be even better than how we currently share the data and code. While we will consider using Notebooks in future, we checked and converting our existing R script library into R Notebooks would require a considerable amount of reconfiguration that we cannot devote the time to right now. We hope that nonetheless the commitment to open science is clear in the extensive code base, commenting and data access we are making available to readers.

Rather than reporting full study details in another publication I would have found it useful if all relevant information was included in a supplement (though it seems much of it is). This avoids situations where the other publication is inaccessible (due to different access regimes) and minimises barriers for people to fully understand the reported data.

Response: We agree this is good practice – the Precision in Psychiatry study is very large, with many irrelevant components with respect to the present study (Lee et al., BMC Psychiatry, 2023). For this reason, we tried to provide all that was necessary and only refer to the Precision in Psychiatry study methods for fine-grained detail. Upon review, the only thing we think we omitted that is relevant is information on ethical approval in the manuscript, which we have now added (Methods, Participants, page 11, lines 412-417: “Further details of the PIP study procedures that are not specific to this study can be found in a prior publication (21). Ethical approval for the PIP study was obtained from the Research Ethics Committee of School of Psychology, Trinity College Dublin and the Northwest-Greater Manchester West Research Ethics Committee of the National Health Service, Health Research Authority and Health and Care Research Wales”). If any further information is lacking, we are happy to include it here also.

Author Response

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

Reviewer #1 (Public Review):

She et al studied the evolution of gene expression reaction norms when individuals colonise a new environment that exposes them to physiologically challenging conditions. Their objective was to test the "plasticity first" hypothesis, which suggest that traits that are already plastic (their value changes when facing a new environment compared to the original environment) facilitates the colonisation of novel environments, which, if true, would be predicted to result in the evolution of gene expression values that are similar in the population that colonised the new environment and evolved under these particular selection pressures. To test this prediction, they studied gene expression in cardiac and muscle tissues in individuals originating from three conditions: lowland individuals in their natural environment (ancestral state), lowland individuals exposed to hypoxia (the plastic response state), and a highland population facing hypoxia for several generations (the coloniser state). They classified gene expression patterns as maladaptive or adaptive in lowland individuals responding to short term hypoxia by classifying gene expression patterns using genes that differed between the ancestral state (lowland) and colonised state (highland). Genes expressed in the same direction in lowland individuals facing hypoxia (the plastic state) as what is found in the colonised state are defined as adaptative, while genes with the opposite expression pattern were labelled as maladaptive, using the assumption that the colonised state must represent the result of natural selection. Furthermore, genes could be classified as representing reversion plasticity when the expression pattern differed between the plasticity and colonised states and as reinforcement when they were in the same direction (for example more expressed in the plastic state and the colonised state than in the ancestral state). They found that more genes had a plastic expression pattern that was labelled as maladaptive than adaptive. Therefore, some of the genes have an expression pattern in accordance with what would be predicted based on the plasticity-first hypothesis, while others do not.

Thank you for a precise summary of our work. We appreciate the very encouraging comments recognizing the value of our work. We have addressed concerns from the reviewer in greater detail below.

Q1. As pointed out by the authors themselves, the fact that temperature was not included as a variable, which would make the experimental design much more complex, misses the opportunity to more accurately reflect the environmental conditions that the colonizer individuals face at high altitude. Also pointed out by the authors, the acclimation experiment in hypoxia lasted 4 weeks. It is possible that longer term effects would be identifiable in gene expression in the lowland individuals facing hypoxia on a longer time scale. Furthermore, a sample size of 3 or 4 individuals per group depending on the tissue for wild individuals may miss some of the natural variation present in these populations. Stating that they have a n=7 for the plastic stage and n= 14 for the ancestral and colonized stages refers to the total number of tissue samples and not the number of individuals, according to supplementary table 1.

We shared the same concerns as the reviewer. This is partly because it is quite challenging to bring wild birds into captivity to conduct the hypoxia acclimation experiments. We had to work hard to perform acclimation experiments by taking lowland sparrows in a hypoxic condition for a month. We indeed have recognized the similar set of limitations as the review pointed out and have discussed the limitations in the study, i.e., considering hypoxic condition alone, short time acclimation period, etc. Regarding sample sizes, we have collected cardiac muscle from nine individuals (three individuals for each stage) and flight muscle from 12 individuals (four individuals for each stage). We have clarified this in Supplementary Table 1.

Q2. Finally, I could not find a statement indicating that the lowland individuals placed in hypoxia (plastic stage) were from the same population as the lowland individuals for which transcriptomic data was already available, used as the "ancestral state" group (which themselves seem to come from 3 populations Qinghuangdao, Beijing, and Tianjin, according to supplementary table 2) nor if they were sampled in the same time of year (pre reproduction, during breeding, after, or if they were juveniles, proportion of males or females, etc). These two aspects could affect both gene expression (through neutral or adaptive genetic variation among lowland populations that can affect gene expression, or environmental effects other than hypoxia that differ in these populations' environments or because of their sexes or age). This could potentially also affect the FST analysis done by the authors, which they use to claim that strong selective pressure acted on the expression level of some of the genes in the colonised group.

The reviewer asked how individual tree sparrows used in the transcriptomic analyses were collected. The individuals used for the hypoxia acclimation experiment and represented the ancestral lowland population were collected from the same locality (Beijing) and at the same season (i.e., pre-breeding) of the year. They are all adults and weight approximately 18g. We have clarified this in the Supplementary Table S1 and Methods. We did not distinguish males from females (both sexes look similar) under the assumption that both sexes respond similarly to hypoxia acclimation in their cardiac and flight muscle gene expression.

The Supplementary Table 2 lists the individuals that were used for sequence analyses. These individuals were only used for sequence comparisons but not for the transcriptomic analyses. The population genetic structure analyzed in a previously published study showed that there is no clear genetic divergence within the lowland population (i.e., individuals collected from Beijing, Tianjing and Qinhuangdao) or the highland population (i.e., Gangcha and Qinghai Lake). In addition, there was no clear genetic divergence between the highland and lowland populations (Qu et al. 2020).

Q4. Impact of the work

There has been work showing that populations adapted to high altitude environments show changes in their hypoxia response that differs from the short-term acclimation response of lowland population of the same species. For example, in humans, see Erzurum et al. 2007 and Peng et al. 2017, where they show that the hypoxia response cascade, which starts with the gene HIF (Hypoxia-Inducible Factor) and includes the EPO gene, which codes for erythropoietin, which in turns activates the production of red blood cell, is LESS activated in high altitude individuals compared to the activation level in lowland individuals (which gives it its name). The present work adds to this body of knowledge showing that the short-term response to hypoxia and the long term one can affect different pathways and that acclimation/plasticity does not always predict what physiological traits will evolve in populations that colonize these environments over many generations and additional selection pressure (UV exposure, temperature, nutrient availability). Altogether, this work provides new information on the evolution of reaction norms of genes associated with the physiological response to one of the main environmental variables that affects almost all animals, oxygen availability. It also provides an interesting model system to study this type of question further in a natural population of homeotherms.

Erzurum, S. C., S. Ghosh, A. J. Janocha, W. Xu, S. Bauer, N. S. Bryan, J. Tejero et al. "Higher blood flow and circulating NO products offset high-altitude hypoxia among Tibetans." Proceedings of the National Academy of Sciences 104, no. 45 (2007): 17593-17598.

Peng, Y., C. Cui, Y. He, Ouzhuluobu, H. Zhang, D. Yang, Q. Zhang, Bianbazhuoma, L. Yang, Y. He, et al. 2017. Down-regulation of EPAS1 transcription and genetic adaptation of Tibetans to high-altitude hypoxia. Molecular biology and evolution 34:818-830.

Thank you for highlighting the potential novelty of our work in light of the big field. We found it very interesting to discuss our results (from a bird species) together with similar findings from humans. In the revised version of manuscript, we have discussed short-term acclimation response and long-term adaptive evolution to a high-elevation environment, as well as how our work provides understanding of the relative roles of short-term plasticity and long-term adaptation. We appreciate the two important work pointed out by the reviewer and we have also cited them in the revised version of manuscript.

Reviewer #2 (Public Review):

This is a well-written paper using gene expression in tree sparrow as model traits to distinguish between genetic effects that either reinforce or reverse initial plastic response to environmental changes. Tree sparrow tissues (cardiac and flight muscle) collected in lowland populations subject to hypoxia treatment were profiled for gene expression and compared with previously collected data in 1) highland birds; 2) lowland birds under normal condition to test for differences in directions of changes between initial plastic response and subsequent colonized response. The question is an important and interesting one but I have several major concerns on experimental design and interpretations.

Thank you for a precise summary of our work and constructive comments to improve this study. We have addressed your concerns in greater detail below.

Q1. The datasets consist of two sources of data. The hypoxia treated birds collected from the current study and highland and lowland birds in their respective native environment from a previous study. This creates a complete confounding between the hypoxia treatment and experimental batches that it is impossible to draw any conclusions. The sample size is relatively small. Basically correlation among tens of thousands of genes was computed based on merely 12 or 9 samples.

We appreciate the critical comments from the reviewer. The reviewer raised the concerns about the batch effect from birds collected from the previous study and this study. There is an important detail we didn’t describe in the previous version. All tissues from hypoxia acclimated birds and highland and lowland birds have been collected at the same time (i.e., Qu et al. 2020). RNA library construction and sequencing of these samples were also conducted at the same time, although only the transcriptomic data of lowland and highland tree sparrows were included in Qu et al. (2020). The data from acclimated birds have not been published before.

In the revised version of manuscript, we also compared log-transformed transcript per million (TPM) across all genes and determined the most conserved genes (i.e., coefficient of variance ≤  0.3 and average TPM ≥ 1 for each sample) for the flight and cardiac muscles, respectively (Hao et al. 2023). We compared the median expression levels of these conserved genes and found no difference among the lowland, hypoxia-exposed lowland, and highland tree sparrows (Wilcoxon signed-rank test, P<0.05). As these results suggested little batch effect on the transcriptomic data, we used TPM values to calculate gene expression level and intensity. This methodological detail has been further clarified in the Methods and we also provided a new supplementary Figure (Figure S5) to show the comparative results.

The reviewer also raised the issue of sample size. We certainly would have liked to have more individuals in the study, but this was not possible due to the logistical problem of keeping wild bird in a common garden experiment for a long time. We have acknowledged this in the manuscript. In order to mitigate this we have tested the hypothesis of plasticity following by genetic change using two different tissues (cardiac and flight muscles) and two different datasets (co-expressed gene-set and muscle-associated gene-set). As all these analyses show similar results, they indicate that the main conclusion drawn from this study is robust.

Q2. Genes are classified into two classes (reversion and reinforcement) based on arbitrarily chosen thresholds. More "reversion" genes are found and this was taken as evidence reversal is more prominent. However, a trivial explanation is that genes must be expressed within a certain range and those plastic changes simply have more space to reverse direction rather than having any biological reason to do so.

Thank you for the critical comments. There are two questions raised we should like to address them separately. The first concern centered on the issue of arbitrarily chosen thresholds. In our manuscript, we used a range of thresholds, i.e., 50%, 100%, 150% and 200% of change in the gene expression levels of the ancestral lowland tree sparrow to detect genes with reinforcement and reversion plasticity. By this design we wanted to explore the magnitudes of gene expression plasticity (i.e., Ho & Zhang 2018), and whether strength of selection (i.e., genetic variation) changes with the magnitude of gene expression plasticity (i.e., Campbell-Staton et al. 2021).

As the reviewer pointed out, we have now realized that this threshold selection is arbitrarily. We have thus implemented two other categorization schemes to test the robustness of the observation of unequal proportions of genes with reinforcement and reversion plasticity. Specifically, we used a parametric bootstrap procedure as described in Ho & Zhang (2019), which aimed to identify genes resulting from genuine differences rather than random sampling errors. Bootstrap results suggested that genes exhibiting reversing plasticity significantly outnumber those exhibiting reversing plasticity, suggesting that our inference of an excess of genes with reversion plasticity is robust to random sampling errors. We have added these analyses to the revised version of manuscript, and provided results in the Figure 2d and Figure 3d.

In addition, we adapted a bin scheme (i.e., 20%, 40% and 60% bin settings along the spectrum of the reinforcement/reversion plasticity). These analyses based on different categorization schemes revealed similar results, and suggested that our inference of an excess of genes with reversion plasticity is robust. We have provided these results in the Supplementary Figure S2 and S4.

The second issue that the reviewer raised is that the plastic changes simply have more space to reverse direction rather than having any biological reason to do so. While a causal reason why there are more genes with expression levels being reversed than those with expression levels being reinforced at the late stages is still contentious, increasingly many studies show that genes expression plasticity at the early stage may be functionally maladapted to novel environment that the species have recently colonized (i.e., lizard, Campbell-Staton et al. 2021; Escherichia coli, yeast, guppies, chickens and babblers, Ho and Zhang 2018; Ho et al. 2020; Kuo et al. 2023). Our comparisons based on the two genesets that are associated with muscle phenotypes corroborated with these previous studies and showed that initial gene expression plasticity may be nonadaptive to the novel environments (i.e., Ghalambor et al. 2015; Ho & Zhang 2018; Ho et al. 2020; Kuo et al. 2023; Campbell-Staton et al. 2021).

Q3. The correlation between plastic change and evolved divergence is an artifact due to the definitions of adaptive versus maladaptive changes. For example, the definition of adaptive changes requires that plastic change and evolved divergence are in the same direction (Figure 3a), so the positive correlation was a result of this selection (Figure 3d).

The reviewer raised an issue that the correlation between plastic change and evolved divergence is an artifact because of the definition of adaptive versus maladaptive changes, for example, Figure 3d. We agree with the reviewer that the correlation analysis is circular because the definition of adaptive and maladaptive plasticity depends on the direction of plastic change matched or opposed that of the colonized tree sparrows. We have thus removed previous Figure 3d-e and related texts from the revised version of manuscript. Meanwhile, we have changed Figure 3a to further clarify the schematic framework.

Reviewer #1 (Recommendations For The Authors):

Q1. Here are private recommendations that I think could help improve the manuscript. West-Eberhard was a pioneer back in 2003 in explicating the hypothesis of "plasticity first". I think it is important to cite their main work in the first paragraph of introduction and to use the term "plasticity-first", which is widely known among evolutionary biologists studying phenotypic plasticity, instead of "plasticity followed by genetic change", since the three papers cited in paragraph 1 call it « plasticity first ».

West-Eberhard, M.J. (2003) Developmental Plasticity and Evolution, Oxford University Press.

Thank you for suggesting West-Eberhard (2003) and we have cited this important work. We have also changed “plasticity followed by genetic change” to “plasticity first”.

Q2. Introduction. Line 5, Change for « On the one hand, if plasticity changes ... »

We have modified as suggested.

Q3. Line 52, Change for « ...same direction as adaptive evolution does ...»

We have modified as suggested.

Q4. Line 66,When presenting papers that address the plasticity and evolution of gene expression in response to environmental variables, paper by Morris et al is another example that could be useful to include (but this is only a suggestion in case the authors missed it).

Thank you for suggesting this nice work. We have cited Morris et al. (2014).

Q5. Line 94, Change for "We acclimated"

We have modified as suggested.

Q6. In Figure 3, the figure in panel A and B is labelled "normaxia", but I think that "normoxia" is usually the term used.

Thank you for spot the typo. We have modified Figure 3a and we no longer used the term “normaxia”.

Material and methods

It would be important to merge supplementary table 1 and 2 and only present the individuals that were used with their respective cardiac and muscle libraries (if they come from the same individual?). Also, the origin of the individuals used in the hypoxia experiment should be explained at the beginning of the methods section and explicated in the supplementary table. Information on sex or stage of development (juvenile? Adult? Male? female?) and time of year (in breeding stage? Pre-migration (if any), etc) would allow the reader to see that individuals from lowland differed only in their exposure to hypoxia or not, or if other variables may affect gene expression patterns. Similarly, if all individuals form the highland are males and the lowland hypoxia exposed individuals are females (or juveniles versus breeders, or different time of year, etc) this should be stated in the methods. Gene expression is labile so the reader should know if other variables influence the results presented or not.

Thank you for suggestion. We have added detailed information (i.e., age, collecting time and season) to the supplementary Table 1. We have also added this information to the Methods. Because the birds used in transcriptomic analysis (Supplementary Table 1) were different individuals from those used in the sequence analyses (Supplementary Table 2), these two tables cannot be merged.

References:

Campbell-Staton SC, Velotta JP, Winchell KM. 2021. Selection on adaptive and maladaptive genes expression plasticity during thermal adaptation to urban heat islands. Nat. Commun. 12: 6195.

Ghalambor CK, Hoke KL, Ruell EW, Fischer EK, Reznick DN, Hughes KA. 2015. Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature. Nature 525:372–375.

Hao et al. 2023. Divergent contributions of coding and noncoding sequences to initial high-altitude adaptation in passerine birds endemic to the Qinghai–Tibet Plateau. Mol. Ecol. Doi: 10.1111/mec.16942.

Ho WC, Zhang J. 2018. Evolutionary adaptations to new environments generally reverse plastic phenotypic changes. Nat. Commun. 9: 350.

Ho WC, Zhang J. 2019. Genetic gene expression changes during environmental adaptations tend to reverse plastic changes even after correction for statistical nonindependence. Mol. Biol. Evol. 36: 604–612.

Ho WC, Li D, Zhu Q, Zhang J. 2020. Phenotypic plasticity as a long-term memory easing readaptations to ancestral environments. Sci. Adv. 6: eaba3388.

Kuo KC, Yao CT, Liao BY, Weng MP, Dong F, Hsu YC, Hung CM. 2023. Weak gene-gene interaction facilitates the evolution of gene expression plasticity. BMC Biol. 21: 57.

Author Response

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

Reviewer #1 (Recommendations For The Authors):

I would recommend the authors check the results section, it seems to me that the first two paragraphs are not results, but methods.

We would like to express our appreciation to both reviewers for bringing this to our attention. Indeed, we discussed this in detail, but decided that because the methods come after the results section. We believe that providing the basic methodological approach to readers before the results is essential for better comprehension. Once again, we sincerely thank the reviewers for their valuable feedback, however, we would prefer to leave this part as it is.

In Figure 3B, why there is not male and female shown in different lines, as in the rest of figures? I recommend following the same pattern everywhere.

Has been changed accordingly, and the respective sex-specific lines were also added to Figure 4.

I recommend checking carefully all the articles included in Table 2. Maybe some of the included information here is not precise.

We thank the reviewer for highlighting this. We carefully checked the articles again, and made some small adjustments.

In Material and methods: just note that when ages are estimated, usually there is a variable accounting for the amount of estimated years, that should be included in the model, and see that it has no effect on the dependent variable. I recommend including this variable.

We sincerely appreciate the helpful comment from the reviewer, which we have carefully considered and implemented in our manuscript. However, we would like to highlight that addressing age estimation error is complex, as it involves measurement error. Thus, simply adding it as an independent variable may not fully capture its potential impact, as the effect may be positive or negative depending on the individual. Hence, the potential effect would be better accounted for by the implementation of individual random intercepts and smooths to adjust the confidence intervals, which is part of our model structures. Furthermore, we would like to emphasize that we have also conducted analyses on a reduced dataset that only included zoo-born individuals with precisely known birthdates, and the results remained consistent. So instead of changing our analyses, we now emphasize how our approach also addresses this aspect.

Creatinine: Is there any other reference, more recent and in English, to complement the original one cited?

We have now supplemented the original citation with an additional English citation: Anestis et al. 2009.

Reviewer #2 (Recommendations For The Authors):

Minor corrections

Please, in Study population, the citation of table 2 is in fact Table 3. For table 3 (in Methodology), please provide the units Body weight having a mean of 32.4, has it a median of 9 ?

Please, provide results separately for males and females

We changed the table as requested, though the table only reports sample sizes and thus only numbers without units. The values for body weight are accurate.

In Results

The two first paragraphs have to be included in methods and structured with those already present.

We would like to express our appreciation to both reviewers for bringing this to our attention. Indeed, we discussed this in detail, but decided that because the methods come after the results section, we believe that providing the basic methodological approach to readers before the results is essential for better comprehension. Once again, we sincerely thank the reviewers for their valuable feedback, however, we would prefer to leave this part as it is.

In Table 1, indicate what 'Est' means.

Has been changed accordingly

Author Response

Reviewer #1 (Public Review):

The cerebral cortex, or surface of the brain, is where humans do most of their conscious thinking. In humans, the grooves (sulci) and bumps (convolutions) have a particular pattern in a region of the frontal lobe called Broca's area, which is important for language. Specialists study features imprinted on the internal surfaces of braincases in early hominins by casting their interiors, which produces so-called endocasts. A major question about hominin brain evolution concerns when, where, and in which fossils a humanlike Broca's area first emerged, the answer to which may have implications for the emergence of language. The researchers used advanced imaging technology to study the endocast of a hominin (KNM-ER 3732) that lived about 1.9 million years ago (Ma) in Kenya to test a recently published hypothesis that Broca's remained primitive (apelike) prior to around 1.5 Ma. The results are consistent with the hypothesis and raise new questions about whether endocasts can be used to identify the genus and/or species of fossils.

We would like to thank Rev. 1 for their comments on our paper.

Reviewer #2 (Public Review):

The authors tried to support the hypothesis that early Homo still had a primitive condition of Broca's cap (the region in fossil endocasts corresponding to Broca's area in the brain), being more similar to the condition in chimpanzees than in humans. The evidence from the described individual points to this direction but there are some flaws in the argumentation.

We are grateful to Rev. 2 for their comments, although we partially agree with some of them.

First, we would like to rectify the statement of Rev. 2 that we “tried to support the hypothesis that early Homo still had a primitive condition of Broca's cap”, indeed, our aim was to test this hypothesis and not to try to validate it.

First, only one human and one chimpanzee were used for comparison, although we know that patterns of brain convolutions (and in addition how they leave imprints in the endocranial bones) are very variable.

We understand the point raised by Rev. 2 about the variation of brain convolutions in humans and chimpanzees. We used atlases published by Connolly (1950), Falk et al. (2018) and de Jager et al. (2019, 2022) to analyse the endocast of KNM-ER 3732 and compare it to the extant human and chimpanzee cerebral conditions. However, in Figure 2, for the sake of clarity only two Homo and Pan specimens were used to illustrate the comparison (as it has been done in other published papers, e.g., Carlson et al., 2011; Science, Gunz et al., 2020 Sci Adv). In the revised version, we modified the manuscript to explain further our approach (line 156) “We used brain and endocast atlases published in Connolly (1950), Falk et al. (2018) and de Jager et al. (2019, 2022; see also www.endomap.org) for comparing the pattern identified in KNM-ER 3732 to those described in extant humans and chimpanzees. To the best of our knowledge, these atlases are the most extensive atlases of extant human and chimpanzee brains/endocasts available to date and are widely used in the literature to explore variability in sulcal patterns. In Figure 2, the extant human and chimpanzee conditions are illustrated by one extant human (adult female) and one extant chimpanzee (adult female) specimens from the Pretoria Bone Collection at the University of Pretoria (South Africa) and in the Royal Museum for Central Africa in Tervuren (Belgium), respectively (Beaudet et al., 2018).”.

Second, the evidence from this fossil specimen adds to the evidence of previously describe individuals but still not yet fully prove the hypothesis.

We tempered our discussion by concluding that (line 116) “Overall, the present study not only demonstrates that Ponce de León et al.’s (2021) hypothesis of a primitive brain of early Homo cannot be rejected, but also adds information […]”.

Third, there is a vicious circle in using primitive and derived features to define a fossil species and then using (the same or different) features to argue that one feature is primitive or derived in a given species. In this case, we expect members of early Homo to be derived compared to their predecessors of the genus Australopithecus and that's why it seems intriguing and/or surprising to argue that early Homo has primitive features. However, we should expect that there is some kind of continuum or mosaic in a time in which a genus "evolves into" another genus. This discussion requires far more discussions about the concepts we use, maybe less discussion about what is different between the two groups but more discussion about the evolutionary processes behind them.

We fully agree with Rev. 2 on this aspect. We believe that identifying these differences/similarities between fossil and extant hominids constitute the first step of a better understanding of the evolutionary mechanisms. Our work suggests indeed a certain continuity between genera and raises questions on the genus concept and how to interpret the specimens currently attributed to early Homo. In the revised version of the manuscript we included a reference to this possible scenario (line 134): “[…] or to the absence of a definite threshold between the two genera based on the morphoarchitecture of their endocasts (Wood and Collard, 1999).”.

Fourth, the data of convolutional imprints presented are rather subjective when identifying which impressions represent which brain convolutions. Not seeing an impression does not necessarily mean that the corresponding brain feature did not exist. Interestingly, the manuscript does not mention and discuss at all the frontoorbital sulcus. This is a sulcus that usually runs from the orbital surface of the frontal lobe up to divide the inferior frontal gyrus in chimpanzees, a condition totally different than in humans who do not have a frontoorbital sulcus. Could such a sulcus be identified, this would provide a far more convincing argument for a primitive condition in this specimen. In Australopithecus sediba, e.g., the condition in this region seems to be a mosaic in which some aspects of the morphology seem to be more modern while one of the sulcual impressions can well be interpreted as a short frontoorbital sulcus. For this specimen, by the way, I would come back to my third point above: some experts in the field might argue that this specimen could belong to Homo rather than Australopithecus...

We agree that the presence of a fronto-orbital sulcus would be more conclusive. However, this sulcus has not been identified in KNM-ER3732 and the region in which we would expect to find it is not preserved. As demonstrated by Ponce de León et al. (2021), because of the topographic relationships between sulci (and cranial structures), it is possible to interpret imprints on endocasts and the evolutionary polarity of some traits even in the absence of landmarks such as the fronto-orbital sulcus. In Australopithecus sediba the main derived feature of the endocast corresponds to the ventrolateral bulge in the left inferior frontal gyrus, and not to the sulcal pattern itself (Carlson et al., 2011 Science). However, the discussion around the taxonomic status of this taxon confirms the urgent need for reconsidering specimens from that time period and clarifying the mosaic-like or concerted evolution of the derived Homo-like traits within our lineage. Regarding the subjective nature of this approach, we invite readers to examine the specimen on MorphoSource (https://www.morphosource.org/concern/media/000497752?locale=en) and to request access to the National Museums of Kenya to the physical or virtual specimen to falsify our hypothesis.

According to my arguments above, I think that this manuscript might revive interesting discussions about this topic but it is not likely to settle them because the data presented are not strong enough to fully support the hypothesis.

We would be more than happy to consider new/other specimens with similar chronological and geographical contexts and investigate further this hypothesis in the future.

Reviewer #3 (Public Review):

The authors provide a detailed analysis of the sulcal and sutural imprints preserved on the natural endocast and associated cranial vault fragments of the KNM-ER3732 early Homo specimen. The analyses indicate a primitive ape-like organization of this specimen's frontal cortex. Given the geological age of around 1.9 million years, this is the earliest well-documented evidence of a primitive brain organization in African Homo.

In the discussion, the authors re-assess one of the central questions regarding the evolution of early Homo: was there species diversity, and if yes, how can we ascertain it? The specimen KNM-ER1470 has assumed a central role in this debate because it purportedly shows a more advanced organization of the frontal cortex compared to other largely coeval specimens (Falk, 1983). However, as outlined in Ponce de León et al. 2021 (Supplementary Materials), the imprints on the ER1470 endocranium are unlikely to represent sulcal structures and are more likely to reflect taphonomic fracturing and distortion. Dean Falk, the author of the 1983 study, basically shares this view (personal communication). Overall, I agree with the authors that the hypothesis to be tested is the following: did early Homo populations with primitive versus derived frontal lobe organizations coexist in Africa, and did they represent distinct species?

I greatly appreciate that the authors make available the 3D surface data of this interesting endocast.

We are grateful to Rev. 3 for their comments and for contextualizing our finding. We would also like to point out that, although the 3D surface can be viewed on MorphoSource, permission from the National Museums of Kenya has to be requested for studying the specimen and getting access to the physical specimen and/or the 3D model.

Author Response:

We are grateful to the reviewers for their insightful comments, suggestions, and criticism. In the updated version of the manuscript, all these will be properly reflected. Here we briefly address the main points raised:

Reviewer #1:

1.1. Patient selection and tumor area selection are crucial for this study but not very carefully defined. Why are some core and others not? Figure referral is an issue here (sup figure 6 where all core and non-core samples are supposed to be according to the legend of Fig 4 is likely sup fig 7 but this is then a complete copy paste of Figure 4). In the methods it is stated that the core samples are based on limited contamination of additional morphotypes (<20%) but Fig 4 suggests that all tumours listed have multiple morphotypes.

The tissue samples were obtained from a hospital cohort of patients with stage II-IV colorectal cancer (at diagnostic time), with no particular selection criteria imposed, as this was an exploratory study.

Tumor regions were marked for macro-dissection by an experienced pathologist following the standard practice for whole-tumor transcriptomics studies. The subregions (morphological regions) were marked by the same experienced pathologist for macro-dissection (in an adjacent section) and reassessed later with respect to their “morphological purity”. It is impossible to macro-dissect regions containing a single morphological pattern. Hence, those regions which contained significant amount (>=20%) of other morphologies were considered “non-core”, while the rest were called “core” regions. This distinction applies to morphological regions solely and not to whole-tumor samples.

Indeed, the reference in caption to Figure 4, should refer to Supp. Fig. 7 (which needs to be updated).

1.2. CMS subtype should be performed with single sample predictor rather than CMScaller.

We agree that a single-sample predictor for CMS is needed, however CMScaller is the de facto classifier for CMS (>130 citations) so we used it to illustrate the practical implications.

1.3. A couple of surprising observations need specification. MUC2 is a strong CMS3 reporter gene yet Mucinous tumours appear to end up in CMS4 rather than 3. Can the authors show that indeed stroma cells are very evident in these samples?

We do not have a direct estimation of the amount of stromal cells, but the high scores of the various fibroblast-related signatures in mucinous regions (Fig2 B, D) indicate that, indeed, there is an enrichment in stroma. In the follow-up study we plan to perform specific staining as well as spatial transcriptomics of these regions to further investigate our findings.

1.4. The SE PP and CT are assigned to CMS2, but in Figure 4 this appears a lot more variable than the authors would make the reader believe. The full data are not completely clear (see point 1).

In the paper, we transparently state that PP, SE, and CT were assigned to CMS2 in 62.5%, 41.7% and 41.9% of cases, respectively. These proportions referred to all samples for which CMSCaller made a prediction. In Fig.4, we also show the proportion of cases in which CMSCaller did not predict any subtype.

1.5. The tumor response rates are rather weird as this is likely dependent on the complete tumour and not so much the subareas. It is not very well described what we see in this analysis.

We did not compute any response rates but simple prognostic scores as (weighted, if weights were provided) means of genes in the specific signatures (see Methods). The question addressed was whether these scores were comparable between whole tumor and corresponding tumor regions (within same tumor). Given the observed (relative) variability, the more important follow-up question - which we cannot answer with our limited survival data – is whether a higher score in a region in comparison with whole-tumor is indeed indicative of a higher risk of relapse.

1.6. Serrated adenomas have previously been aligned with CMS4. Is this different from serrated areas in cancers?

We do not have data from adenomas to compare with the serrated carcinoma regions. But a comparison of (regions of) both traditional serrated and sessile serrated adenomas to serrated carcinoma would be interesting.

1.7. The fact that iCMS2 and iCMS3 align rather well with the current analysis of the distinct regions suggests that the analysis that was reported last year is the proper way to view tumor intrinsic signatures. The authors now propose a rather similar outcome to this issue which does take away a lot of the novelty of the findings of this study.

Our goal was not to propose another stratification paradigm for colorectal cancer, but rather to study the associations between morphology and transcriptome and its implications in practice. As such, our analyses are not limited to molecular subtypes and the respective observations are but a small part of our findings. Indeed, the intrinsic subtypes (iCMS 2/3) are stable and robust, as they are based on the genes expressed in epithelial cells, and they may well prove to be of clinical importance too. However, they do not cover all aspects (e.g. fibroblasts subtypes) and, as stated in Joanito et al. Nat Gen 54, pages 963–975 (2022), “iCMS, MSI status and CMS jointly inform the molecular classification of CRC”. Last, in our opinion, the molecular classification of CRC, while a useful point of view in tumour classification, is not covering all the necessary perspectives on tumour heterogeneity.

Reviewer #2:

2.1. Overall, the manuscript provides an interesting histological/morphological framework through which we can consider heterogeneity in colorectal carcinoma and an approach by which we might improve the performance of gene expression-based classifiers in predicting clinical behaviour and/or responses to therapy. Exploration of CRC morphotypes and their differences was quite interesting. However, more work is needed to support the claims made by the authors. While I appreciate that the authors themselves identify limitations of their study within the manuscript, I believe awareness of these limitations is not reflected in some of the claims made in the abstract and at points in the main text when discussing the use of expression-based classifiers.

We will improve the manuscript to stress the exploratory nature of our analyses and their limitations.

Author Response

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

This important work reports the identification of a list of proteins that may participate in the clearance of paternal mitochondria during fertilization, which is known as essential for normal fertilization and embryonic and fetal development. While the main method used is state of the art and the supporting data are solid, the vigor of the biochemical assays and function validation is inadequate. This work will be of interest to developmental and reproductive biologists working on fertilization. Key revisions (for the authors) include 1) Use a mitochondria-enriched fraction instead of whole sperm for the assays, and add more control samples to monitor what got lost during sperm and oocyte treatments before the coincubation step. 2) Functional validation of the key proteins identified.

We thank Editors of eLife, as well as Special Issue Guest-Editors and Reviewers for a favorable assessment and helpful recommendations for key revisions. Provisional revisions included in our revised article are detailed below. We agree with Editors’ comment about the use of mitochondrion enriched fractions and additional functional validation of key proteins. In fact, we are developing experimental protocols for oocyte extract coincubation with isolated sperm heads and tails, and eventually with purified mitochondrial sheaths, to separate the ooplasmic sperm nucleus remodeling factors from the mitophagic ones. Such experiments, as well as functional validations using porcine zygotes are contingent upon anticipated post-pandemic rebound in the availability of porcine oocytes, obtained from ovaries harvested on slaughterhouse floors, requiring currently unavailable workforce which has hampered our access to this necessary resource.

Reviewer #1 (Peer Review):

Could the authors make clear how much the presented pictures reflect the described localisation? There is no information on the number of spermatozoa and embryos observed nor the fraction of these embryos showing the presented pattern of localisation. This must be included.

Two hundred spermatozoa were counted per replicate of the cell-free system co-incubation and 20 zygotes per replicate, with 3 replicates of immunolabelling for each phase/picture which were examined to establish the typical localization patterns that were observed. The displayed patterns were observed in 65 to 88% of examined spermatozoa/zygotes; varying dependent on protein, replicate, and phase of immunolabelling. In all cases, the signal displayed is the typical pattern that was displayed in most cells. This information has been added to the Materials and Methods section for clarification.

It is not clear if the authors also examined the localization of other proteins and obtained a different pattern than anticipated from the proteomic approach or if they only tested these 6 proteins and got a 100% of correlation.

These are the 6 proteins which were selected based on extensive literature review into known functions of all identified proteins, as well as extensive research into available and reliable antibodies to detect such proteins within our porcine systems. Even so, no particular localization patterns were anticipated; instead, we presented the patterns actually observed and even some patterns which defied our expectations (i.e., the localization of BAG5 in the sperm acrosome).

The authors use "MS" in the text to indicate "mitochondrial Sheath" and "Mass spectrometry". this is confusing.

The authors agree and the usage of MS as an acronym for either has been removed entirely to avoid confusion.

In the introduction the author refers to Ankel-Simons and Cummins, 1996 as a reference for the number of sperm mitochondria in mammalian species, this is incorrect since the quoted paper is about the number of mtDNA molecules and mentioned an earlier publication.

This has been revised and the appropriate citation has been used.

Reviewer #2 (Peer Review):

Major:

1) It has been proved from the earlier studies from this group that the porcine cell-free system is useful to observe spermatozoa interacting with ooplasmic proteins in a single trial and could recapitulate fertilization sperm mitophagy events that take place in a zygote without affecting later cell-division process. However, the post-fertilization sperm mitophagy process is a complex time-associated event that many processes that occur sequentially and interactively, which means ooplasmic proteins might be involved in this process but may not directly interact with sperm or may associate with sperm-ooplasmic protein complex at different time points. It is certainly a great advance already in knowledge to identify "the candidate players" from the list of 185 proteins; however, with the time-resolution (4 and 24hr) in the current study and without functional validation experiments at this stage, it is still difficult to postulate the importance of these identified proteins. The functional validation experimental designs, in my opinion, is critically important for better interpretation of the data.

The authors agree with this reviewer’s sentiments and do plan to conduct further functional analysis. This project was able to generate a list of candidate, sperm-mitophagy promoting proteins and we were further able to show that many of these proteins were detectable both via mass spectrometry and via immunocytochemistry in spermatozoa exposed to our cell-free system. Furthermore, similar localization patterns were found in spermatozoa that were detected within newly fertilized zygotes. These results boost our confidence in our cell-free system and show that our list of candidate proteins is truly a useful list for future localization and functional analyses. We are certainly aware that we have not captured every protein that may play a role in post-fertilization sperm mitophagy and that the proteins captured are just candidates until proven otherwise. Likewise, we have almost certainly captured multiple proteins that are currently candidates that will likely not be shown to play a role in postfertilization sperm mitophagy, while it is plausible that at least some of these candidate proteins do play a role in mitophagy and some of them likely participate (perhaps have yet to be described roles) in other fertilization events, in which we would be extremely interested in as well.

2) As shown in Figure 1, whole sperm was used in the co-incubation and the later MS analysis; thus, proteins identified in the current study might be relevant in fertilization processes other than postfertilization sperm mitophagy, as proteins identified in the current study may be associated with other parts of the sperm (e.g. sticky sperm head, e.g. PSMG2 associated with sperm midpieces, tail at 4hr coincubation, but then only associate with sperm head at 24hr co-incubation) rather than sperm midpiece, despite the fact that authors applied immunohistochemistry to show the localization of this protein, but the evidence is indirect, so how authors functionally differentiate these 6 identified proteins from sperm mitophagy process with other processes and to confirm (or to associate) the relevance of these proteins with sperm mitophagy process?

The authors agree that the 6 proteins which were further studied by using immunocytochemistry may be playing roles in other processes such as pronuclear formation. We discussed some potential roles including and beyond post-fertilization mitophagy, in the Supplemental Discussion. After reviewer comments, we moved the Supplemental Discussion back in the main Discussion section. Thus, this section now considers additional putative pathways in which the said 6 proteins cold participate, though we concede that thorough functional studies must still be performed.

3) Class 3 proteins were present in both the gametes or only the primed control spermatozoa, but are decreased in the spermatozoa after co-incubation, which authors interpreted as sperm-borne mitophagy determinants and/or sperm-borne proteolytic substrates of the oocyte autophagic system, this data categorization may need to be revised as sperm-borne proteolytic substrates of the oocyte autophagic system only, not for sperm borne mitophagy determinants. The argument for this disagreement is due to the fact that if the protein is a sperm-borne mitophagy determinant, after coincubation, to execute the mitophagy process, this protein should still be associated with the sperm at least at the early stage (of 4hr) (constant under MS detection when comparing control with 4hr treated) rather than being released from the sperm. Or alternatively, they could result in class 3 proteins (but not all those 6 were in class 3). Nevertheless, if these proteins serve as substrates, they can be used (consumed) and show decreased under MS detection.

This argument for redefining the Class 3 proteins more accurately is understood and we agree. The definition is revised in the paper.

4) Of particular interest among the 6 proteins that were further investigated. Unlike other proteins, MVP was highly significant (p<0.001) after 4hr incubation, but the significance became less after 24hr (p=0.19). Interpretation of this dynamic change in the relevance of the mitophagy process would facilitate the readers to understand the relevance and the role of MVP.

The differences in significance are likely influenced by the abundance of MVP detectable by mass spectrometry. As the time of cell-free system incubation increases, the variability between replicates also seemed to increase, likely due to the sustained proteolytic activity taking place in our system. This work was based on three replicates of mass spectrometry for each time point; additional replicates likely would have reduced the p-value for the 24hr cell-free data set, for MVP and potentially other proteins also. At both time points, MVP was only detectable in spermatozoa after they had been exposed to the cell-free system treatment which is the criteria that truly interested us more than the actual differences in content between the timepoints and is why it was added to our list of candidate proteins.

5) In figure 3, the association of ooplasmic MVP to sperm midpiece is not convincing enough as sperm midpiece and tail often show some levels of non-specific signals under fluorescent microscopy. And the dynamic association of ooplasmic MVP to sperm midpiece in Fig. 3F-G is difficult to reach a conclusion solely based on data presented in the manuscript. Additional negative control of sperm MVP staining from the primed and treated sperm would be helpful. Additionally, a quantitative comparison (15 vs 25hr) of sperm-associated MVP signals from the fertilized embryo or a stack image from different angles would clarify the doubts raised here.

For all images and all replicates, serum controls were also generated. These controls were then viewed under fluorescent microscope, and light intensities and exposures thresholds for each fluorescent light channel were set based on the background intensity that came from these nonimmune serum-treated control samples. We set our light intensity/acquisition time below a threshold where the non-specific signal began to appear. All the presented patterns are based on setting this peak intensity threshold and as such the signal we see should be the true signal. Furthermore, 200 spermatozoa were counted per treatment per replicate of the cell-free system co-incubation and 20 zygotes per replicate, with 3 replicates of immunolabelling for each protein and data point, which was used to represent the typical localization patterns that were observed. The displayed patterns were observed between in 65- 88% of examined spermatozoa/zygotes. Invariably, the signal displayed in the manuscript is the typical pattern that was seen in a majority of cells. This information has now been added to the Materials & Methods section for clarification.

6) Same concerns for the other 5 proteins (PSMG2, PSMA3, FUNDC2, SAMM50, BAG5) as indicated above.

See response to Question 5.

7) The patterns of these 6 proteins under the immunofluorescent study are confusing as the pattern varies after co-incubation (treated), and mostly, the signal of these proteins observed from the fertilized embryos is not really associated with sperm midpieces. Therefore, the evidence of these proteins involving in post-fertilization sperm mitophagy is, at this moment, weak based on the data presented. But the relevance of these proteins in events post-fertilization or early embryo development is certainly (evidence did not strong enough to support "sperm mitophagy," in my opinion).

The authors agree that some of these proteins seem to be playing roles beyond postfertilization sperm mitophagy and that there is a need for true functional studies before the authors can state with certainty that these proteins play a role in any of the discussed fertilization events. We state this in the discussion: “Considering the dynamic proteomic remodeling of both the oocyte and spermatozoa which takes place during early fertilization, these 185 proteins which have been identified likely play roles in processes beyond sperm mitophagy.” It should be noted that the authors went into greater detail about potential alternative protein functions based on the present data and literature review in the Supplemental Discussion. Based on this comment and other reviewer comments we have now included the Supplemental Discussion as part of the main Discussion section, and this will hopefully help clarify some of the authors’ thoughts about the 6 candidate proteins which were further analyzed during this study.

Minor:

1) To my understanding, statistical significance (relevance) is normally set at a p-value of either <0.1 or 0.05. The reason for loosening the p-value of 0.2 in the current study needs to be justified as this was not a common statistical criterium, and the interpretation of those candidates from this loosened criterium should also be careful.

The loosening of statistical relevance in this study to 0.2, only applied to our Class 1 proteins. This is because for a protein to fall into the Class 1 proteins it was a protein that was only present in samples after they were exposed to the cell-free system. In the case of these Class 1 proteins, this happened for all 3 replicates at each stated timepoint. We found this pattern of detection to be important whether the p-value fell under 0.1 or 0.2. As such, we loosened our statistical threshold for our Class 1 proteins. Any proteins added to our candidate list will be subject to further investigation before definitive conclusions can be drawn, and as such we think that capturing more proteins was more important for the goals of this study than limiting the number of proteins captured, especially for those Class 1 proteins. An explanation of this has been added to the Materials & Methods section Mass Spectrometry Data Statistical Analysis.

2) First cell cleavage of porcine embryo normally occurs within 48hr post-insemination or activation; therefore, the 4 and the 24hr time points used in the current study require justification included in the discussion or methods and material section.

First cleavage of porcine embryos normally occurs around 24 - 28 hours post-insemination. Thus, for both the cell-free system and the embryo studies we were capturing an advanced 1 cell stage zygote/zygote like system with our 24 hour and 25-hour time points.

3) In figure 2, colors used in different time points and in two different classes represent (sometimes) different protein categories, would be easier for the readers for quick comparisons if the same color could be used to represent the same protein category throughout the graph. (E.g, proteins for early zygote development are shown in red in "A", but blue in "B")

This has been corrected and the color scheme for Figure 2 has been revised for easier comparisons.

Reviewer #3 (Peer Review):

I am not used to seeing a supplementary discussion in a manuscript. I also believe it should be incorporated into normal discussion.

The Supplemental Discussion has been incorporated into the main Discussion now.

It would be very helpful to make an additional figure in which the proposed interactome of identified factors with the sperm mitochondria before and after incubation are drawn schematically and also which factors are not IDed in both cases (when comparing to somatic mito- or autophagy). This eases to get through the discussion and will beautifully summarize and illustrate the importance and progress that the authors have made with this assay.

We made a diagram that depicts the changes in protein localization patterns overtime within our cell-free system. This diagram has been added to the manuscript as Figure 9.

Reviewer #1 (Public Review):

In this manuscript, the authors used an unbiased method to identify proteins from porcine oocyte extracts associated with permeabilised boar spermatozoa in vitro. The identification of the proteins is done by mass spectrometry. A previous publication of this lab validated the cell-free extract purification methods as recapitulating early events after sperm entry in the oocyte. This novel method with mammalian gametes has the advantage that it can be done with many spermatozoa at the time and allows the identification of proteins associated with many permeabilised boar spermatozoa at the time. This allowed the authors to establish a list of proteins either enriched or depleted after incubation with the oocytes extract or even only associated with spermatozoa after incubation for 4h or 24h. The total number of proteins identified in their test is around 2 hundred and with very few present in the sample only when spermatozoa were incubated with the extracts. The list of proteins identified using this approach and these criteria provide a list of proteins likely associated with spermatozoa remnants after their entry and either removed or recruited for the transformation of spermatozoa-derived structures. Using WB and histochemistry labelling of spermatozoa and early embryos using specific antibodies the authors confirmed the association/dissociation of 6 proteins suspected to be involved in autophagy.

While this unique approach provides a list of potential proteins involved in sperm mitochondria clearance it's (only) a starting point for many future studies and does not provide the demonstration that any of these proteins has indeed a role in the processes leading to sperm mitochondria clearance since the protein identified may also be involved in other processes going-on in the oocyte at this time of early development.

We thank reviewer 1 for positive comments. We added a sentence in Discussion addressing the obvious shortcoming of present study, as further functional validations of candidate mitophagy factors are planned.

Concerning the localisation of the 6 proteins further analysed, the authors must add how much the presented picture represents the observed patterns. They must include the details on the fraction of spermatozoa and embryos displaying the presented pattern.

We now specify that the patterns depicted in manuscript are typical and representative of data from at least three replicates of immunolabeling in spermatozoa and zygotes. For each of these replicates, 200 spermatozoa were examined per replicate of the cell-free system co-incubation or 20 zygotes per replicate. The displayed patterns were observed between 65-88% in examined spermatozoa/zygotes. Invariably, the signal displayed in manuscript is the typical pattern that was seen in a majority of cells. This information has now been added to the Materials & Methods section for clarification.

Reviewer #2 (Public Review):

Mitochondria are essential cellular organelles that generate ATPs as the energy source for maintaining regular cellular functions. However, the degradation of sperm-borne mitochondria after fertilization is a conserved event known as mitophagy to ensure the exclusively maternal inheritance of the mitochondrial DNA genome. Defects on post-fertilization sperm mitophagy will lead to fatal consequences in patients. Therefore, understanding the cellular and molecular regulation of the postfertilization sperm mitophagy process is critically important. In this study, Zuidema et. al applied mass spectrometry in conjunction with a porcine cell-free system to identify potential autophagic cofactors involved in post-fertilization sperm mitophagy. They identified a list of 185 proteins that might be candidates for mitophagy determinants (or their co-factors). Despite the fact that 6 (out of 185) proteins were further studied, based on their known functions, using a porcine cell-free system in conjunction with immunocytochemistry and Western blotting, to characterize the localization and modification changes these proteins, no further functional validation experiments were performed. Nevertheless, the data presented in the current study is of great interest and could be important for future studies in this field.

We thank reviewer 2 for positive comments. As we explain in our response to Editors and Reviewer 1, further validation studies will be resumed once the availability of slaughterhouse ovaries for such studies improves. Examples of such functional validation of pro-mitophagic proteins SQSTM1 and VCP are included in our previous studies (DOI: 10.1073/pnas.1605844113 and DOI: 10.3390/cells10092450) that led to the development of cell-free system reported here, and are cited in present study.

Reviewer #3 (Public Review):

In this manuscript, a cytosolic extract of porcine oocytes is prepared. To this end, the authors have aspirated follicles from ovaries obtained from by first maturing oocytes to meiose 2 metaphase stage (one polar body) from the slaughterhouse. Cumulus cells (hyaluronidase treatment) and the zona pellucida (pronase treatment) were removed and the resulting naked mature oocytes (1000 per portion) were extracted in a buffer containing divalent cation chelator, beta-mercaptoethanol, protease inhibitors, and a creatine kinase phosphocreatine cocktail for energy regeneration which was subsequently triple frozen/thawed in liquid nitrogen and crushed by 16 kG centrifugation. The supernatant (1.5 mL) was harvested and 10 microliters of it (used for interaction with 10,000 permeabilized boar sperm per 10 microliter extract (which thus represents the cytosol fraction of 6.67 oocytes). The sperm were in this assay treated with DTT and lysoPC to prime the sperm's mitochondrial sheath. After incubation and washing these preps were used for Western blot (see point 2) for Fluorescence microscopy and for proteomic identification of proteins.

Points for consideration:

1) The treatment of sperm cells with DTT and lysoPC will permeabilize sperm cells but will also cause the liberation of soluble proteins as well as proteins that may interact with sperm structures via oxidized cysteine groups (disulfide bridges between proteins that will be reduced by DTT).

This is certainly a possibility, the lysoPC and DTT permeabilization steps were designed to mimic natural processing (plasma membrane removal and sperm protein disulfide bond reduction), which the spermatozoa would undergo during fertilization. However, we do realize that this is a chemically induced processing and thus is not a perfect recapitulation of fertilization processes. However, in this study and in previous studies with this system, we were able to show alignment between proteomic interactions taking place in the cell-free system and within the zygotes.

2) Figure 3: Did the authors really make Western blots with the amount of sperm cells and oocyte extracts as the description in the figures is not clear? This point relates to point 1. The proteins should also be detected in the following preparations (1) for the oocyte extract only (done) (2) for unextracted nude oocytes to see what is lost by the extraction procedure in proteins that may be relevant (not done) (3) for the permeabilized (LPC and DTT treated and washed) sperm only (not done) (4) For sperm that were intact (done) (5) After the assay was 10,000 permeabilized sperm and the equivalent of 6.67 oocyte extracts were incubated and were washed 3 times (or higher amounts after this incubation; not done). Note that the amount of sperm from one assay (10,000) likely will give insufficient protein for proper Western blotting and or Coomassie staining. In the materials and methods, I cannot find how after incubation material was subjected to western blotting the permeabilized sperm. I only see how 50 oocyte extracts and 100 million sperm were processed separately for Western blot.

The authors did make Western blots with the number of spermatozoa and oocytes stated in the materials and methods, a total protein equivalent of 10 to 20 million spermatozoa (equivalent to ~20-40 µg of total protein load) and 100 MII oocytes (equivalent to ~20 µg of total protein load). These numbers have been corrected in the Materials & Methods. Also, we did find in the Materials & Methods section that the Co-Incubation of Permeabilized Mammalian Spermatozoa with Porcine Oocyte Extracts section refers to using cell-free exposed spermatozoa for electrophoresis; however, for none of the presented Western blot work was this true. Rather, all of the presented Western blots as per their descriptions are utilizing ejaculated or capacitated sperm or oocytes. This line has been removed from the Materials & Methods to reduce confusion.

Regarding preparation (2), we have previously assessed the difference between oocyte extract and intact oocytes in this manner internally and we are certainly losing proteins due to the oocyte extraction process. We make caveats in this vein throughout the article such as: “Furthermore, this cell-free system while useful does not perfectly capture all the events which take place during in vivo fertilization. The cell-free system is intended to mimic early fertilization events but is presumably not the exact same as in vitro fertilization.”

3) Figures 4, 5, 6, 7, and 8 see point 2. I do miss beyond these conditions also condition 1 despite the fact that the imaged ooplasm does show positive staining.

For all the presented Western blots, the tissue type is stated in the image description and the protocol which was used to prepare these samples is stated in the Materials & Methods.

4) These points 1-3 are all required for understanding what is lost in the sperm and oocyte treatments prior to the incubation step as well as the putative origin of proteins that were shown to interact with the mitochondrial sheath of the oocyte extract incubated permeabilized sperm cells after triple washing. Is the origin from sperm only (Figs 5-8) or also from the oocyte? Is the sperm treatment prior to incubation losing factors of interest (denaturation by DTT or dissolving of interacting proteins preincubation Figs 3-8)?

The authors understand that there are proteins and interactions lost on both sides of the cellfree system equation and we have added a sentence to the Discussion to caveat this limitation in the system.

5) Mass spectrometry of the permeabilized sperm incubated with oocyte extracts and subsequent washing has been chosen to identify proteins involved in the autophagy (or cofactors thereof). The interaction of a number of such factors with the mitochondrial sheath of sperm has been shown in some cases from sperm and others for an oocyte origin. Therefore, it is surprising that the authors have not sub-fractionated the sperm after this incubation to work with a mitochondrial-enriched subfraction. I am very positive about the porcine cell-free assay approach and the results presented here. However, I feel that the shortcomings of the assay are not well discussed (see points 1-5) and some of these points could easily be experimentally implemented in a revised version of this manuscript while others should at least be discussed.

We agree that the use of a mitochondrial-enriched subfraction for further analysis would be interesting and useful. We are actively developing experimental protocols for oocyte extract coincubation with isolated sperm heads and tails, and eventually with purified mitochondrial sheaths. However, such experiments are contingent upon our access to porcine oocytes, which has continued to be a struggle since the COVID-19 pandemic compromised our ability to attain oocytes in large, cheap, and reliable quantities. This was a continuous problem with preparing materials for this very paper and has continued to be an issue for our laboratory as well as many others at our university and across the country. We continue to maximize oocytes every time we can get access to them, but the unfortunate reality is that this access has become sparce and unreliable over the past three years.

Author Response

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

Reviewer 1 (Recommendations For The Authors):

1) The strikingly different conclusion from the previous Bourane study seems to stem from the experimental approaches. Rather than using genetic crosses that target all neurons from the hindbrain and spinal cord that express Npy at any point in development, Boyle et al target their manipulations specifically to the lumbar region of the superficial dorsal horn in adult mice using direct viral injections. Thus, Boyle is almost certainly manipulating much fewer neurons that the original study. How then is their behavioral effects so much greater? At the minimum, the authors need to discuss this discrepancy head on. Better would be a direct molecular/anatomical comparison of the neurons targeted by each approach. This could be done using Nyp-Cre mice crossed to a Rosa-LSL-reporter strain and quantifying the overlap with the same markers used here. Perhaps, the intersectional approach with Lbx1 resulted in labeling of a different population of neurons than the adult AAV injections? Although likely outside the scope, given this work directly questions the main conclusion of the Bourane paper, it will be important to see a replication of the original finding of selectivity to mechanical itch.

We agree that our approach should be manipulating a smaller population of neurons, and that it is therefore suprising that we see greater behavioural effects. Please see our response to "Weakness 1" of Reviewer 2 for consideration of this point. We have already provided a direct molecular comparison as requested by the reviewer, and this appears in Figure 1 supplement 1. Here we used tissue from NPY::Cre that had been crossed with Ai9 mice (i.e. a Rosa-LSL-reporter) and had received intraspinal injections of AAV.flex.GFP. We then characterised the neurochemistry of tdTomato+ cells that were GFP+ or GFP-negative.

2) The authors state that, "91.6% ± 0.3% of cells classed as Cre-positive cells were also Npy-positive, and these accounted for 62.1% ± 0.6% of Npy-positive cells" If I am reading this correctly, does that mean that 40% of the Npy+ cells are Cre negative? If so, how is this possible?

This interpretation is correct. For quantification of RNAscope data we used a cut-off level of 4 transcripts, and cells with fewer than 4 transcripts were classed as negative. It is likely that some of the NPY cells classified as negative for Cre would have had some Cre mRNA (sufficient to cause recombination), but at a level below this threshold. It is also possible that some NPY+ cells would fail to express Cre, since this is a BAC transgenic mouse, rather than a knock-in.

3) Similarly, the authors state that "great majority of FP-expressing neurons in laminae I-III were immunoreactive (IR) for NPY (78.5% ± 3.6%), and these accounted for 74.6% ± 109 1.9% of the NPY-IR neurons in this area". So does this mean 20% of the recombination is non-specific/in other cell types that could be involved in pain/itch sensation?

Our finding that 91.6% of cells with Cre mRNA were also positive for Npy mRNA (see above) indicates that Cre expression was largely restricted to NPY cells. The failure to detect NPY peptide in some of these cells probably results from the relatively low level of peptide seen in the cell bodies of peptidergic neurons, which results from the rapid transport of peptides into their axons.

4) Comparing Fig 3B and Fig4B it seems the control baseline von Frey responses are different. In fact, baseline response in Fig4b is quite like the CNO effect in Fig 3B. Unless I'm misunderstanding something, this seems quite odd?

We agree that there is a difference between the baseline responses. We are not aware of any particular reason for this, and we think that it reflects a degree of variability that is seen with the von Frey test. Interestingly, the baseline values for the SNI cohort (Fig 4E) lies between the values in Fig 3B and Fig 4B.

5) In Fig 4E, the behavior of the CNO treated mice is quite variable. Can the authors comment as to how this might be happening? Does the effect correlate with viral transduction?

We did not see any obvious correlation between the extent of viral transduction and the behaviour of individual mice.

6) Fig6, the PDyn-Cre experiment, is a bit of a non sequitur?

Please see our response to "Weakness 2" of Reviewer 2 for consideration of this point.

7) The conclusion is unusually long. I recommend trimming it to make it more concise.

We presume that this refers to the Discussion. However, this was ~1550 words, and we do not feel that that is unusually long.

Reviewer 2 (Public Review):

Weaknesses

1) There is inadequate discussion about previous studies of NPY interneurons. Specifically, the authors should address why a more restricted subset of these neurons (this study) have broader effects than seen previously.

We have expanded the discussion on the discrepancies between our findings and those reported previously. We state at the outset that we are targeting a more restricted population (lines 509-10), and we now go into more detail concerning both similarities and differences between our findings and the reasons that we think may underlie any discrepancies (various changes between lines 522-575).

2) I cannot see the reason for including results from manipulation of Dyn+ interneurons in this paper. First, the title does not reflect roles of spinal Dyn+ population. In addition, without further experiments characterizing relationships between NPY and Dyn interneurons in modulating itch and/or nociception, Dyn datasets seem to deviate from the main theme.

We had previously shown that activating Dyn-INs suppressed pruritogen-evoked itch (Huang et al 2018), but it was important to test whether silencing these cells would have the opposite effect. Our finding of overlap in function (i.e. both NPY-INs and Dyn-INs suppress itch, and that both innervate GRPR cells) provides strong evidence against the idea that neurochemically-defined interneuron populations have highly specific functions, and we now state this in the Discussion. The anatomical experiments (which follow on from the functional studies) provide important new information concerning synaptic circuitry of the dorsal horn, by showing that NPY-INs preferentially innervate GRPR cells, and provide around twice as many synapses on these cells, compared to the Dyn-INs. Interestingly, this correlates with the relatively large optogenetically-evoked IPSCs that we saw when NPY-INs were activated, compared to those reported by Liu et al (2019) when galanin-expressing (which largely correspond to Dyn-INs) were activated. By including these findings in the paper, we are able to make comparisons between these two populations.

3) While the authors provided convincing evidence that GRPR+ neurons serve as a downstream effector of NPY+ neuron evoked itch, the relationship between GRPR and NPY neurons in modulating pain is not examined. Therefore, Fig. 7B is pure speculation and should be removed.

We feel that our recent findings that GRPR neurons correspond to vertical cells, that they respond to noxious stimuli, and that activating them results in pain-related behaviours, makes it reasonable to speculate that the NPY/GRPR circuit may also be involved in the anti-nociceptive action of NPY cells. The legend for Fig 7B already refers to this as a "potential circuit", and we have toned down the corresponding part of the discussion to say that our findings "raise the possibility" that this is the case (lines 605-7). We feel that this part of the figure is important, as otherwise our summary diagram ignores some of the main findings of the paper, and we hope that this is now acceptable.

Recommendations For The Authors

1) Fig. 1G: the "misexpression" of tdTomato neurons was much more prominent in deep dorsal horn laminae but not in the superficial ones. Was this representative? Can the authors perform a laminae specific characterization?

We did test for this possibility in 2 NPY::Cre;Ai9 mice that had received intraspinal injections of AAV.flex.GFP, and found that there was a modest difference - 62% of tdTomato+ cells in laminae I-II, but only 39% of those in lamina III, were GFP+. This suggests that "misexpression" may have differed slightly between these regions. However, since the difference was quite modest, and we were only able to analyse tissue from two mice in this way, we did not include these findings in the paper.

2) I have a lot of problems interpreting the c-Fos data in Fig. 2 E and F. For the mCherry- population, how was the quantification performed? From the image, it does not look like 2030% of cells express c-Fos; at a minimum a clear stain of neurons would be needed. Similarly, the identification of NPY cells is not particularly convincing (e.g., middle arrowhead lower 2 panels in C).

We have provided further details on how the analysis was performed (changes made to lines 1016-29). NeuN staining was used to reveal all neurons, and a modified optical disector method was performed from somatotopically appropriate regions of the dorsal horn. As noted by the Reviewer, NeuN staining was required to allow identification of mCherrynegative cells. However, we have not included the NeuN immunoreactivity in the image, as this would add considerably to the complexity. These images are from single optical sections, and therefore the overall numbers of cells are low (in comparison to what would be seen in a projected image). The intensity of mCherry staining varied between cells. However, for all mCherry-positive cells (including the example referred to by the Reviewer), there was clear staining in the membrane, which could be followed in serial sections.

3) Please add individual data points for all quantifications.

These have been added.

Reviewer 3 Recommendations For The Authors:

1) It is somewhat surprising that there is no effect on CPP after activating spinal NPY neurons in neuropathic mice, given the almost complete rescue of hypersensitivity to baseline values in the nociceptive tests. Based on the methods, it appears that conditioning was carried out already 5 min after CNO injection. Yet, suppression of c-fos activity in excitatory spinal dh neurons was observed 30min after CNO injection. Also, it is not clear to me when CNO was injected prior to the nociceptive or CQ testing?

Have the authors considered that conditioning from 5-35 min after CNO injection might be too short after CNO injection to achieve a profound analgetic effect?

In a previous study (Polgár et al 2023), we had observed the timecourse of CNO-evoked itch and pain behaviours in mice in which GRPR cells expressed hM3Dq. We found that these started within 5 minutes of i.p. CNO injection (e.g. Fig S2 in that paper). In addition, the timecourse of action of gabapentin and CNO (both given i.p.) are likely to be similar, and there was a preference for the chamber paired with gabapentin. We are therefore confident that the conditioning period with CNO was adequate. We now explain this in the Methods section (lines 846-52). The timing of CNO injections for the nociceptive and CQ tests is now described (lines 749-55).

2) The authors claim that tonic pain was not affected based on the conditioned place preference test. Efficacy in withdrawal response tests and in the CPP differ by more than duration of the stimulus. I'd suggest using more cautious wording here.

We agree that caution is needed in interpreting the results of the CPP experiments. We have therefore replaced "does" with "may" in the Results section (line 336) and "did" with "may" in the Discussion (line 620).

3) On page 9 the authors state "...suggesting that they suppress the transmission of pain- and itch-related information in the dorsal horn." However, pain is not affected in the loss of function experiments suggesting some qualitative differences in the role of the NPY neurons in itch and pain. This should also be reflected more clearly in this statement and in the discussion e.g. "suppress itch" and "can suppress pain".

We accept the point made by the Reviewer. We have slightly altered the wording in lines 249-51 and 610 to reflect this.

Author Response

Reviewer #1 (Public Review):

In this study, the authors study the effect of dynactin disruption on kinetochore fiber (k-fiber) length in spindles of dividing cultured mammalian cells. Dynactin disruption is known to interfere with dynein function and hence spindle pole formation. The main findings are that poles are not required for correct average k-fiber length and that severed k-fibers can regrow to their correct length both in the presence and absence of poles by modulating their dynamic properties at both k-fiber ends. In the presence of poles, regrowth is faster and the variation between k-fiber lengths is smaller. This is a very interesting study with high-quality quantitative imaging data that provides important new insight into potential mechanisms of spindle scaling, extending in an original manner previous work on this topic in cultured cells and in Xenopus egg extract. The Discussion is interesting to read as several possible mechanisms for k-fiber length control are discussed. The technical quality of the study is very high, the experiments are very original, and most conclusions are well supported by the data. Especially, the experiments observing the regrowth of k-fibers after severing and the study of the dynamic properties of these k-fibers provide very novel insight. Addressing the following concerns could potentially improve the manuscript:

We thank the reviewer for their fair, rigorous, and conceptually engaging remarks.

(1) The phenotype generated here by disrupting dynactin via overexpressing p50 appears to be different from that caused by knocking down NuMA or dynein - as previously reported by the Dumont lab (Hueschen et al., 2019). In this study here, unfocused spindles are observed whereas earlier turbulent spindles were observed. This raises the question of whether dynein activity that contributes to pole focusing is really completely inhibited here. These discrepancies in phenotypes seem to deserve an explanation. Is k-fiber length in cultured mammalian cells only maintained in the case of this specific type of inhibition?

We thank the reviewer for the important point about the different phenotypes observed in different dynein inhibition conditions and we refer them to our response to Essential Revision #1. In summary, we believe that different dynein inhibition phenotypes are similar. Unfocused spindles appear turbulent on longer timescales and appear to reach a steady-state on shorter timescales. The amount of pole-unfocusing also seems to correspond to the severity of dynein inhibition (Figure 1—figure supplement 1). We have chosen to study inhibited spindles that were steady-state and unfocused. We have added this discussion in line 129 as well as better characterized our system of dynein inhibition by adding two new figures (Figure 1—figure supplement 1, Figure 1—figure supplement 3).

Furthermore, we address the question of whether dynein might still be responsible for length regulation despite poles being unfocused in line 433 of the Discussion: “recent work has revealed that mammalian spindles can achieve similar architecture whether or not dynein (or its recruiter NuMA) is knocked out (Neahring et al., 2021). This suggests that the severe defects in spindle coordination (Figure 1, Figure 5) and maintenance (Figure 2) observed in p50-unfocused spindles are more likely due to the loss of spindle poles than due to the loss of dynein activity per se.”

We have additionally overexpressed p50 in human RPE1 cells and observed qualitatively similarly unfocused yet generally bi-oriented spindles as in rat kangaroo PtK2 cells, showing that the formation of unfocused spindles in PtK2 is not an artifact unique to that cell line (see newly added Figure 1—figure supplement 3). However, these unfocused RPE1 spindles did not have clear, resolvable k-fibers as in PtK2, so length was not quantified. The only method we are aware of that robustly unfocuses poles in PtK2 spindles is p50 overexpression.

(2) p50 addition and also p150-cc1 addition was often used in Xenopus egg extract in order to inhibit dynein function. Considerably larger concentrations of p50 than p150-cc1 needed to be used. Can the authors estimate the level of overexpression of p50 in the cells they study? It seems that could be possible given that a mCherry fusion protein can be overexpressed. Was it necessary to select cells with a particular level of mCherry-p50 overexpression to observe the reported phenotypes?

We thank the reviewers for the suggestion to quantify p50 expression and have added Figure 1—figure supplement 1. Due to gradual red laser power loss over months, data from a single day were plotted for proper comparison, but trends were always consistent within any given day. As discussed above, we observed that higher levels of mean p50 intensity corresponded to unfocused spindles. We have clarified that we chose to study these highly overexpressing unfocused spindles in the text and methods, and we speculate that level of p50 overexpression correlates with amount of dynein inhibition and subsequent pole-unfocusing. This is also consistent with the higher concentrations of p50 needed to inhibit dynein in Xenopus.

(3) Some comparison to previous experiments using p50 and p150-cc1 addition to Xenopus egg extract spindles could put this study better into the context of the available literature. It seems from previous publications that the p50 addition produced short, unfocused, barrel-shaped spindles, indicating that spindle length is maintained without poles, whereas the p150-cc1 addition produced elongating spindles (e.g. Gaetz & Kapoor, 2004).

We appreciate the reviewer’s discussion of dynein inhibition in the Xenopus context.

While Xenopus has been used to study spindle size regulation, it has not been as useful to study k-fiber length regulation, which we focus on. Xenopus spindles have a different architecture, with k-fibers that are not discrete and continuous like in mammalian spindles. Indeed, while p50 and p150-CC1 overexpression alter spindle length in Xenopus, they do not have the same effect in mammalian spindles. Additionally, p150-CC1 does not robustly unfocus poles in mammalian spindles as it does in Xenopus; instead, it leads to an inconsistent variety of spindle disorganization phenotypes with frequently focused poles in PtK2 (data not shown). We speculate this variety of spindle phenotypes arise from a different mechanism of dynein inhibition that does not fully target pole-focusing.

However, we agree that referencing prior Xenopus work establishes important context and precedent. In line 95 of the Introduction, we state “…inhibiting dynein unfocuses poles but spindles still form albeit with altered lengths in Drosophila (Goshima et al., 2005) and Xenopus (Gaetz and Kapoor, 2004; Heald et al., 1996; Merdes et al., 1996), and without a clear effect on mammalian spindle length (Guild et al., 2017; Howell et al., 2001),” addressing the different effects of dynein inhibition in Xenopus compared to mammalian spindles. We have also added direct mentions of p50 in Xenopus in line 129 (see Essential Revision #1 response).

Finally, we have added a figure showing overexpression of p50 in a human RPE1 cells to show reproducibility of pole unfocusing across other mammalian cell types (see newly added Figure 1—figure supplement 3).

(4) In this context, it seems that some more explanation is required for the observations presented in Fig. 1D and 1E. It appears that spindle length and k-fiber length have been measured quite differently. Not much information is provided for how spindle length was defined and measured (please expand this part of the Methods). Could the two different methods of measurement be the reason for the mean k-fiber length remaining unaltered in dynactin-disrupted spindles, whereas the spindle length increases in these cells? If not, do non-k-fiber microtubules contribute to unfocused spindles being longer or are chromosomes not aligned in the metaphase plate causing the increase in spindle length by misalignment of k-fiber sister pairs?

We thank the reviewers for pointing out the lack of clarity in Figures 1D and 1E. We have expanded and clarified the Methods section describing how spindle axes were measured and how k-fiber lengths were measured, as well as included examples and cartoons to illustrate them (see newly added Figure1—figure supplement 4).

To clarify, we did not intend to directly measure spindle length, but we did approximate the size of each spindle’s “footprint” in Figure 1D as well as measure individual k-fiber length in Figure 1E. It is now clarified in the Methods line 898 as “Spindle minor and major axes lengths were determined by cropping, rotating, then thresholding spindle images with the Otsu filter using SciKit. Ellipses were fitted to thresholded spindles to approximate the length of their major and minor axes using SciKit’s region properties measurement (Figure1—figure supplement 4A). In control spindles, the major axis corresponded to spindle length along the pole-to-pole axis, and the minor axis corresponded to spindle width along the metaphase plate axis. However, unfocused spindles were disorganized along both axes to the extent where the minor axis did not always correspond to the metaphase plate axis. Thus, Figure 1D reports ”spindle minor axis length” and “spindle major axis length” rather than “spindle width” and “spindle length”. Furthermore, it is worth noting that in unfocused spindles, spindle length is decoupled from k-fiber length because of k-fiber disorganization along both axes. Thus, spindle length was not measured in unfocused spindles...”

We additionally removed the potentially confusing terminology of “wider” and “longer” in the Results section to make clear that we are approximating spindle size, not spindle length and width, and we now state in line 168,“ k-fibers were more spread out in the cell, with spindles covering a larger area compared to control along both its major and minor axes (Figure 1D).”

We believe our clarification and expansion of the Methods section, as well as inclusion of a new supplementary figure and cartoon address the reviewer’s points, and we thank them for pointing out the lack of clarity.

(5) It seems that in the Discussion it is implied that k-fibers can respond to severing in both focused and unfocused spindles by modulating their dynamics at both ends of the k-fibers, but in the Results section the wording is more cautious because of the difference in 'flux' in severed and unsevered unfocused spindles is not significant (Fig. 4D, blue data). It appears indeed that there is also a difference in flux between severed and unsevered unfocused spindles, but the number of data points is too small. Depending on how difficult these experiments are, it could be worth increasing the size of the data set to come to a clear conclusion, given that the data shown in Figs. 3 and 4 are quite remarkable and form the core of the study.

We appreciate the reviewer’s close reading and pertinent suggestions.

As detailed in our response to Essential Revision #3, we did not increase the sample size for unfocused spindles since it would not be reasonably feasible to show significant differences in flux. However, we performed more ablations and photomarking in control spindles as detailed in our response to this reviewer’s point 6 below, a different but related point.

(6) Can the authors exclude that the stopping of 'flux' at minus ends after severing is due to some sort of permanent damage induced by ablation? In other words, do severed spindles begin to flux again once they have regrown to their original length?

We thank the reviewer for their important points.

We have addressed this question in the newly added Figure 4—figure supplement 1 as described in our response to Essential Revision #3 to show that flux resumes after length recovery. In summary, we observed no adverse effects of ablation on k-fiber minus-ends. Severed k-fibers have restored lengths, and minus-end dynamics several minutes after ablation.

(7) To this reader, the conceptualization of distinguishing between 'global' and 'local' effects/behavior was a little confusing, both in the title and also later in the text. The concept of 'local' regulation of k-fiber length appears to contradict the observation that k-fiber length can be regained after severing by changes in the dynamics at both ends (so at two very different locations) which is a rather remarkable finding. Maybe distinguishing between 'individual' and 'collective' k-fiber behavior could be clearer.

We appreciate the reviewer’s consideration of terminology. We have addressed this by clearly defining our use of ‘local’ to refer to individual k-fibers as a unit where appropriate in the text (lines 271, 449). We chose these terms since they can help describe individual versus collective properties, while simultaneously emphasizing the aspects of global architecture and spatial organization in the spindle.

(8) Can the authors exclude that some of the differences between unfocused and focused spindles could be due to altered dynein activity at kinetochores? Or due to the dynein-dependent accumulation of certain spindle proteins along microtubules towards the minus ends of k-fibers or other spindle microtubules, instead of being due to only the presence versus absence of poles? Could this be tested by ablating both poles? If this is too challenging, a discussion of these possibilities could be justified.

We appreciate the reviewer’s consideration of kinetochore activity as well as other methods of removing poles. However, p50 overexpression is currently the only method to robustly unfocus spindles in PtK2 cells – ablating poles or removing pole-associated structures such as centrosomes does not abolish pole-focusing in this system (Khodjakov et al., 2000). Furthermore, we now discuss the possibility that altered dynein activity (such as activity at kinetochores) may give rise to the phenotypes we describe in our work in line 433: “…recent work has revealed that mammalian spindles can achieve similar architecture whether or not dynein (or its recruiter NuMA) is knocked out (Neahring et al., 2021). This suggests that the severe defects in spindle coordination (Figure 1, Figure 5) and maintenance (Figure 2) observed in p50-unfocused spindles are more likely due to the loss of spindle poles than due to the loss of dynein activity per se. Though we cannot exclude it, this also suggests that the findings we make in unfocused spindles are not due changes in activity of the dynein population at kinetochores.”

Reviewer #2 (Public Review):

The mitotic spindle of eukaryotic cells is a microtubule-based assembly responsible for chromosome segregation during cell division. For a given cell type, the steady-state size and shape of this structure are remarkably consistent. How this morphologic consistency is achieved, particularly when one considers the complex interplay between dynamic microtubules, spatial and temporal regulation of microtubule nucleation, and the activities of several microtubule-based motor proteins, remains a fundamental unanswered question in cell biology. In this work by Richter et al., the authors use biochemical and biophysical perturbations to explore the feedback between mitotic spindle shape and the dynamics of one of its main structural elements, kinetochore fibers (k-fibers) - bundles of microtubules that extend from kinetochores to spindle poles. Overexpression of the p50 dynactin subunit in mammalian tissue culture cells (Ptk2) was used to inhibit the microtubule motor cytoplasmic dynein resulting in misshapen spindles with unfocused poles. Measurements of k-fiber lengths in control and unfocused conditions showed that although mean k-fiber length was not statistically different, the variation of length was significantly higher in unfocused spindles, suggesting that k-fiber length is set locally, occurring in the absence of focused poles. With a clever combination of live-cell imaging with photoablation and/or photobleaching of fluorescently-labeled k-fibers, the authors went on to explore the mechanistic bases of this length regulation. K-fiber regrowth following ablation occurred in both conditions, albeit more slowly in unfocused spindles. Paired ablation and localized photobleaching on the same k-fiber revealed that microtubule dynamics, specifically those at the plus-end, can be tuned at the level of individual k-fiber. Lastly, the authors show that chromosome segregation is severely impaired when cells with unfocused spindles are forced to enter mitosis. The work's biggest strength is the application of an innovative experimental approach to address thoughtful and well-articulated hypotheses and predictions. Conclusions stemming from the experiments are generally well-supported, though the experiments addressing the "tuning" of k-fiber dynamics could be bolstered by additional data points and perhaps better presented. The manuscript would also benefit from the inclusion of some investigation of spatial differences in the observed effects as well as the molecular and biophysical basis of the observed feedback between k-fiber length and focused poles.

We appreciate the reviewer providing pertinent, rigorous, and intellectually astute suggestions.

Comments/Concerns/Questions:

1) In the discussion, the authors acknowledge that the changes in spindle morphology resulting from p50 overexpression are likely also causing changes in the well-characterized RanGTP/SAF gradients that radiate from chromosome surfaces. Why did the authors did not include an analysis of k-fiber length as a function of positioning within the spindle? The inclusion of this data would not require more experimentation and could be added as a plot showing K-fiber length versus distance from the geometric center of the spindle (defined by the intersection of the major and minor axes perhaps?).

We thank the reviewer for this pertinent suggestion and refer them to our response to Essential Revision #2. Briefly, we have added the recommended analyses to Figure 1—figure supplement 6 by correlating k-fiber length to position along the spindle’s longitudinal and latitudinal axes.

2) The authors also acknowledge the established relationship between MT length and MT end dynamics, yet in their ablation studies, the average initial k-fiber length at ablation in control spindles was higher than that for k-fibers in unfocused spindles. It seems that this difference makes the interpretation of the data, particularly the conclusion that fiber growth rates differ due to the absence of focused poles, a bit tenuous. To address this, the authors should consider including plots of grow-back rates versus k-fiber length (again, this should not require additional experiments, just more analysis).

We thank the reviewer for their critical thinking about experiments. We would like to clarify to the reviewer that initial k-fiber lengths within unfocused spindles preceding ablation were not actually longer on average compared to the average length of control k-fibers from Figure 1E (Figure 2—figure supplement 1). We apologize that this unexpected artifact was not clear in the text and have now reworded line 232 to be more straightforward: “Mean k-fiber lengths in unfocused spindles before ablation appeared to be shorter (Figure 2D); however, this was due to not capturing the full length of k-fibers in a single z-plane while imaging ablated k-fibers. Indeed, length analysis of full z-stacks from unfocused spindles before ablation yielded an indistinguishable mean k-fiber length compared to control k-fibers in Figure 1E (Figure 2—figure supplement 1). Thus, ablated k-fibers were compared to their unablated neighbors as internal controls.”

We believe that this language clearly calls out the perceived inconsistency, and that our use of internal controls overcomes this confounding factor to make meaningful conclusions. We address the relationship of k-fiber length and growth rate in our response to Essential Revision #2. We are not including it in the manuscript based on our inability to make any meaningful conclusion to either support or exclude the possibility of length-dependent growth rates.

3) As presented, the data shown in Figure 4 is confusing and does not seem very compelling. The relationship between the kymographs and time series is unclear as is the relationship between the dashed lines in the kymographs and the triangles and the plots in the 4B time series and 4C, respectively. Furthermore, it's not always clear what the triangles are pointing to (e.g. in the unfocused condition time series). The authors might want to consider reworking this figure and providing more measurements of flux following ablation in both the control and unfocused conditions. Lastly, the authors should clarify what negative displacement means.

We apologize for the unclear figure annotations and thank reviewers for their suggestions. As discussed in our response to Essential Revision #3, we believe we have improved the clarity and presentation of figures and kymographs. More measurements of flux after ablation in unfocused spindles was not feasible as discussed; however, we have performed these measurements in control spindles and added Figure 4—figure supplement 1 to strengthen conclusions about turning flux off/on after ablation.

We have additionally clarified axis titles by replacing “negative displacement” with the more intuitive descriptor “photomark position relative to minus-end” and clearly defining it in the figure legends in line 565 as follows: “Figure 3 […] (D) Minus-end dynamics, where photomark position over time describes how the mark approaches the k-fiber’s minus-end over time in control and unfocused k-fibers.”

We thank reviewers for their suggestions to improve clarity and bolster our conclusions.

Author Response

We thank the Editor for his assessment. We agree that the data we present in this manuscript can be a starting point for more in-depth analysis. We are currently developing a mathematical model of HIV transmission dynamics; we plan to use the data that we present in this paper as parameter values.

Reviewer #1 (Public Review):

One aim of this paper was to study historical migration from Botswana during the time of the development of the HIV epidemic. The second aim was to test whether the migration networks impacted the development of the epidemic. The first aim was achieved: this paper used historical census data in a clear way, to describe the qualities of characteristics of migration in the country at four points in time, from 1981 to 2011. Very detailed data are presented in clear ways, using network chord diagrams, sharing age- and sex-specific migration rates, and urban-rural classifications. However, data was not presented to achieve the second aim. The authors reviewed some important literature about migration and HIV. They suggested that the migration patterns, such as from specific mining towns and mostly between districts, could have been important in supporting the generalized spread of HIV. But without evidence linking HIV prevalence over time in the linked districts in Botswana, this aim was not supported.

We have now made it clear that we are not testing whether the migration networks impacted the development of Botswana’s HIV epidemic: this is what the Reviewer describes as the second aim of our paper. We have only one aim: to test the hypothesis that, during the development of Botswana’s HIV epidemic, the population was extremely mobile and highly connected through migratory flows and counter-flows. This is based on the fact that these conditions are necessary for the development of a generalized HIV epidemic. However – previous to our analysis – these conditions have not been shown to occur during the development of a generalized HIV epidemic. Given that our results support our mobility hypothesis (i.e., that the population was very mobile and essentially all the districts were connected throughout the country), in the discussion (lines 338-362) we describe how the migration networks that we have identified may have impacted the development of the generalized hyperendemic HIV epidemic in Botswana. We have also clarified that our study has only one hypothesis that we are testing by referring to this single hypothesis as the mobility hypothesis (Abstract: lines 25-29).

One other limitation of the paper was that very little context, outside of migration rates, was provided. Is there any additional information about economic growth, or political event for example, that could clarify or add context to these migration flows? As it stands now, these analyses are quite basic and don't take into account underlying demographic, economic, or political trends.

In response to this concern we have expanded the text in the introduction to provide more context regarding political, demographic and economic factors (Introduction: lines 66-75). We have also expanded our discussion of the implications of our results (and of additional results that we have included: lines 263-283) for understanding the role of internal migration on urbanization in Botswana (Discussion: lines 379-420); urbanization occurred simultaneously to the development of Botswana’s generalized hyperendemic HIV epidemic.

The data presented in this paper has potential impact. As the paper stands now, it could be quite useful for future work when linked to additional data sources on HIV prevalence over time (or other questions that could have been influenced by migration patterns).

We thank this Reviewer for their helpful comments.

Reviewer #2 (Public Review):

To provide context into the HIV epidemic in Botswana over the latter half of the 20th century and the beginning of the 21st, the authors have analyzed micro census data to examine patterns of migration. They use this dataset to show how patterns between urban and rural areas have changed over several decades, and the demographic characteristics of migrants. The dataset used for this study is a very reliable source, and the insights in terms of migration patterns are interesting. The primary weakness of the analyses regards the link to HIV transmission: micro-census data only examine mobility that leads to individuals changing residence for longer periods of time, without accounting for shorter-term trips that may also lead to HIV transmission, such as seasonal migration or short trips. This is likely less of an issue with HIV than other diseases, however, due to its transmission often involving new sexual partners, which will generally be less likely to occur during short trips. Broadly, however, this is an interesting report on the migration patterns during a critical period for HIV transmission nationwide.

We thank the Reviewer for their comments.

In our current manuscript, we have discussed the potential impact of mobility on Botswana’s HIV epidemic, and focused on migration, i.e., one directional movement in terms of a permanent re-location of residency. This type of migration, by changing an individual’s sexual network and social environment, has been shown to increase the risk of acquiring HIV for both women and men. Short-term mobility (e.g., short-term circular migration, where the trip can range in duration from overnight to an entire season) can also affect HIV transmission dynamics. Circular migrants have been shown to both have an increased risk of acquiring HIV, and of transmitting HIV. The greater the number of trips and/or the duration of the trip, the greater the risk. We note that both migration and short-term mobility are important, and their relative importance to each other is likely to evolve over time as a generalized HIV epidemic diffuses through the population. Their relative importance is also likely to vary amongst countries in sub-Saharan Africa.

We have added all of the previous paragraph, with citations, to the text (Discussion: lines 364-377).

Author Response

Reviewer #2 (Public Review):

Root growth is driven by cell elongation, and its local control allows roots to navigate the complex soil environment. Cell growth is driven by the relaxation of the cell wall, a process requiring a drop in pH. Auxin is a key regulator of root development that inhibits root growth. Auxin effects on proton dynamics are complex, it can promote both acidification and alkalinization of the extracellular space through different signaling modules, some only recently uncovered. Serre et al. report on using a new dye to monitor extracellular pH in the region surrounding the Arabidopsis thaliana root. Their manuscript aims to clarify the relationships between pH around the root, proton flux, auxin, cell elongation, and root growth with this tool. They show a typical zonation of pH values along the root: a more acidic domain corresponding to the transit-amplifying compartment, followed by a more alkaline one at the transition and early elongation zones and a more acidic one in the late elongation/root hair zone. This zonation is in agreement with previous reports obtained by other methods. A particularly puzzling aspect is the origin of the more alkaline domain. Serre et al. present evidence supporting the involvement of the AUX1-AFB1-CNGC14 module for the emergence of this more alkaline domain and how it can contribute to the ability of the root to navigate its environment.

Serre et al. show that the more alkaline domain in the transition zone is not directly determined by the activity or localization of the AHA proton pumps but rather by the auxin influx carrier AUX1. They show that the components of the rapid auxin response pathway, in particular, the auxin co-receptor AFB1 and the calcium channel CNGC14, contribute to the emergence of this more alkaline domain. Finally, they show that mutants in these two genes, impaired in the rapid auxin response pathway, show less efficient navigation of the root tip.

The manuscript is clear and well-written. The logic is sound, and the conclusions are supported by the data.

The new dye appears as a promising tool for monitoring the pH in the rhizosphere with advantages over the previous ones. Yet, as pointed out by the authors in the discussion, it reports on pH at the organ scale in the region around the root, not in the apoplast or the cell wall, which can eventually complexify the elaboration of a mechanistic model joining auxin, proton efflux, cell wall properties, cell elongation, and root growth. Although several of the findings confirm previous reports, the manuscript brings novelty by demonstrating the involvement of the rapid auxin response. I am overall supportive of the manuscript. Yet, several points should be addressed:

• The presentation of the more acidic and alkaline domains could be easier to visualize.

• The authors refer to acidic and alkaline domains but do not report on absolute pH values; they monitor the emission ratio of the dye. They justify why to use relative pH value in the discussion and refer there to internal controls that are not clearly defined. In my opinion, the wording should be more consistent across the text and figures and refer to more acidic and more alkaline domains rather than acidic (pH<7) and alkaline (pH>7) domains.

• The data related to the unaltered distribution of AHA using antibody staining should be backed up.

• The way the pH profile and the statistical analyses should be improved.

• The authors should test the effect of extracellular auxin perception (tmk, abp) mutants on pH zonation.

• Conclusion could be strengthened by moving several pieces of data currently in supplemental material to the main text.

We agree with the comment to the definition of ‘acidic’ and ‘alkaline’ domains; we altered the text and explained that we observe ‘relatively alkaline’ and ‘relatively acidic’ domains in comparison to the medium pH in the first part of results.

We defined the ‘internal controls’ in the text – by this we mean mock treated or wild type plants imaged together with the treated or mutant plants.

To address the role of the apoplastic auxin pathway in the root surface pH, we analyzed the tmk1, tmk4 and abp1 mutants. Surprisingly, all three mutants appear undistinguishable from the controls, showing the crucial importance of the cytoplasmic AFB1 auxin perception pathway. We have included the data as Fig.S4-1.

Author Response

Reviewer #1 (Public Review):

This paper studies color vision in anemonefish. The central conclusion of the paper is that anemonefish use signals from their UV cones to discriminate colors that would not otherwise be distinguishable; this differs from other fish in which UV cones extend the range of wavelengths of sensitivity but do not add a dimension to color vision. The work fits into a rich history of studies investigating how color vision fits into an animal's ecological niche. My primary concerns regard the microspectrophotometry data from single cones and some aspects of the presentation of the behavioral data.

Microspectrophotometry

The spectral properties of the cone types are a key issue for interpreting the results. These were measured using MSP, and fits are shown in Figure 2. The raw data shown in Fig. S1 appears more complicated than indicated in the main text. The templates miss the measurements across broad wavelength bands in each cone type. Particularly concerning is the high UV absorbance across cone types and the long-wavelength absorbance in the UV cone. It is not clear how this picture supports the relatively simple description of cone types and spectral sensitivities given in the main text and which forms the basis of the modeling.

Microspectrophotometry is an inherently noise-prone measurement technique, particularly for very small photoreceptor outer segments such as that of single cones, which are also difficult to detect as intact, isolated (nonoverlapping) cells. As such, the absorbance curve fitting and derived lambda max (λmax) values should be treated as estimates. The accuracy of these estimates is adequate for this type of study, and visual modelling results have been shown to be robust against small errors (±10 nm λmax) in photoreceptor sensitivity for multiple species [see Lind, O. & Kelber, A. (2009). Vis Res. 49(15), 1939-1947; and Bitton, PP. et al. (2017). PLOS ONE, 12: e0169810]. We consider it highly unlikely that small shifts in cone λmax from measurement error would make a meaningful difference to the colour discrimination thresholds.

It should be noted that the raw data shown in the original Supplementary Figure 1, included all scans overlain with an average absorbance curve for presentation purposes; however, the actual lambda max values for different cone types were measured and then averaged among individual scans fitted with photopigment absorbance curve templates. For clarity and transparency, we have now provided three multipaned plots (see Figure 1 – figure supplements 1-3) showing the individual pre- and post-bleach scans of absorbance spectra, fitted absorbance curve templates, and R2 values from the best visual pigment template fit.

It is worth noting that most of the cone absorbance spectra found in our study closely resemble those in λmax and quality to those measured in another anemonefish species (Amphiprion akindynos) [see Supplementary Figure 1 in Stieb S. et al. (2019). Sci Rep. 9, 16459]. These cone λmax values can also be reconciled with previous estimates on opsin λmax based on amino acid sequences and cone opsin expression in the A. ocellaris retina characterised in Mitchell LJ et al. (2021). GBE, 13: evab184.

Evidence that the unusual long-wavelength absorbance detected in a couple of the single cone (pre-bleach) measurements were not of visual pigment in origin comes from post-bleach scans, which showed their persistence (i.e., did not show a photobleaching response) and were likely instead contaminants (e.g., blood, RPE pigment). UV absorbance in some of the double cone measurements (above that expected of the prebleached beta peak from chromophore spectral absorption) can be attributed to either noise from scans as is quite typical of MSP and/or partial (accidental) bleaching from stray light sources. Although utmost care was taken to minimise contamination and unintended bleaching sometimes it is unavoidable.

We refer the Reviewer to multiple published studies for further examples of typical MSP measurements that share similar levels of noise to ours e.g., see Figure 1 in Knott B. et al. (2013). JEB, 216:4454-4461; Figure 3 in Schott, RK et al. (2015). PNAS, 113(2): 356-361; Figure 2 in Dalton BE et al. (2014). Proc R Soc B. 281; Figure 5 in Tosetto, JE et al. (2021). Brain Behav Evol. 96: 103-123.

Presentation

The results are not presented in a straightforward way - at least for this reviewer. What is missing for me is a clear link between the psychometric curves in Figure 3A and the discrimination thresholds indicated in Figure 3B and Figure 4. Figure 3A is only discussed in the text on line 289 - after Figure 4 has been introduced and discussed. It would have been very helpful for me if the psychometric curves were first introduced and described, then the relation to Figure 3B was clearly indicated (perhaps with a single psychometric curve as an example). Similarly for Figure 4 the relationship between specific psychometric curves and the threshold plotted would be quite helpful. Currently it takes a careful reading to understand why being below the dashed line in Figure 4 is important.

We have made the following changes, including the introduction of the psychometric curves earlier in the results (lines 236-249) and moved the psychometric function comparison before the mention of Figure 4. Additionally, to make the association between the plotted colour loci and psychometric curves clearer, we have added a smaller psychometric curve plot adjacent to the colour space (in Figure 3B) using red as an example which has an averaged psychometric curve overlying the individual fish curves. The figure caption (lines 250-274) explains that the plotted colour loci and given thresholds are mean values calculated from the individual fish behavioural data.

We have also added a brief reminder that the theoretical limit of colour discrimination is predicted by the RNL model as 1∆S, where in our task fish should be just able to distinguish targets from grey distractors (see lines 222-224). To clarify, the plotted values in Figure 4B are both the individual fish thresholds (points) and average threshold (black bar) per colour set. The individual threshold values are taken at a correct choice probability of 50% from fitted psychometric curves of fish behavioural performance (shown in Figure 3A).

RNL model

The data is fit and interpreted in the context of the receptor noise limited model. The paragraph in the discussion about complementary color pairs suggests that this model is incorrect (text around line 332). Consideration of how the results depend on the RNL model is important, especially given the interpretation here.

The inability of the RNL model to account for the observed asymmetry between color discrimination thresholds implies that they cannot be solely attributed to photoreceptor noise. We can therefore infer from the asymmetry that thresholds are set by a higher-level process, whether that involves post-receptor processes within the inner retina or in the brain remains to be investigated. As explained in lines 396-397 one possibility is that activation of the UV receptor suppresses noise in the visual pathway or enhances the saliency of colors for anemonefish. The high sensitivity to violet-green, which was found in all six of the fish tested, is consistent with the heightened saliency of this color (lines 397-399).

Figure 3B

This is the key figure in the paper. But several issues make seeing the data in this figure difficult. First, the important part of the figure is buried near the origin and hard to see. Can you show a surface that connects the thresholds in the different chromatic directions, or otherwise highlight the regions of discriminable and not discriminable colors?

See previous comment. In short, we have taken the advice of the Reviewer and added highlighted areas around the regions of discriminable colors in Figure 3B to help visually separate them from the non-discriminable regions of colors (from grey). Additionally, we have added an inset showing an enlarged image of the area surrounding the centre of colour space.

Reviewer #2 (Public Review):

Mitchell and colleagues examined the contribution of a UV-sensitive cone photoreceptor to chromatic detection in Amphiprion ocellaris, a type of anemonefish. First, they used biophysical measurements to characterize the response properties of the retinal receptors, which come in four spectrally-distinct subtypes: UV, M1, M2, and L. They then used these spectral sensitivities to construct a 4-dimensional (tetrahedral) color space in which stimuli with known spectral power distributions can be represented according to the responses they elicit in the four cone types. A novel five-LED display was used to test the fish's ability to detect "chromatic" modulations in this color space against a background of random-intensity, "achromatic" distractors that produce roughly equal relative responses in the four cone types. A subset of stimuli, defined by their high positive UV contrast, were more readily detected than other colors that contained less UV information. A well-established model was used to link calculated receptor responses to behavioral thresholds. This framework also enabled statistical comparisons between models with varying number of cone types contributing to discrimination performance, allowing inferences to be drawn about the dimensionality of color vision in anemonefish.

The authors make a compelling case for how UV light in the anemonefish habitat is likely an important ecological source of information for guiding their behavior. The authors are to be commended for developing an elegant behavioral paradigm to assess visual performance and for incorporating a novel display device especially suited to addressing hypotheses about the role of UV light in color perception. While the data are suggestive of behavioral tetrachromacy in anemonefish, there are some aspects of the study that warrant additional consideration:

1) One challenge faced by many biological imaging systems is longitudinal chromatic aberration (LCA) - that is, the focal power of the system depends on wavelength. In general, focal power increases with decreasing wavelength, such that shorter wavelengths tend to focus in front of longer wavelengths. In the human eye, at least, this focal power changes nonlinearly with wavelength, with the steepest changes occurring in the shorter part of the visible spectrum (Atchison & Smith, 2005). In the fish eye, where the visible spectrum extends to even shorter wavelengths, it seems plausible that a considerable amount of LCA may exist, which could in turn cause UV-enriched stimuli to be more salient (relative to the distractor pixels) due to differences in perceived focus rather than due solely to differences in their respective spectral compositions. Such a mechanism has been proposed by Stubbs & Stubbs (2016) as a means for supporting "color vision" in monochromatic cephalopods (but see Gagnon et al. 2016). It would be worth discussing what is known about the dispersive properties of the crystalline lens in A. ocellaris (or similar species), and whether optical factors could produce sufficient cues in the retinal image that might explain aspects of the behavioral data presented in the current study.

This is an interesting point, and we appreciate the reviewer’s thoughtful comment regarding this topic especially as LCA increases exponentially in the UV. Although we certainly cannot disprove such a mechanism in the present study, we are highly sceptical that LCA could be used by reef fish and is involved in the heightened saliency of UV stimuli. Previous work has found that LCA is mostly corrected for in the teleost retina of both marine and freshwater species by graded, multifocal lenses that focus different wavelengths at the same depth as their maximally sensitive cone photoreceptors [e.g., for evidence in African cichlids see Kröger, R. H. H. et al. (1999). J Comp Physiol. A, 184, 361-369; Malkki, P. E. & Kröger, R. H. H. (2005). J Opt. A, 7, 691-700; and for various reef fishes see Karpestam, B. et al. (2007). J Exp Biol., 210, 16: 2923-2931]. In essence, LCA is corrected in the eyes of many teleosts by accurately tuning longitudinal spherical aberration through having a graded density lens. We draw particular attention to the latter reference which comparatively examined the optical properties of reef fish lenses, including diurnal, planktivorous damselfishes (from the same family as anemonefishes, Pomacentridae). They found that not only were the lenses of these species highly UV-transmissive (as we show in anemonefish), but all were multifocal and capable of focusing both visible (non-UV) and UV wavelengths. Considering the coastal cephalopod species examined thus far, all of them contain only one type of visual pigment which is packed in their long photoreceptor (150-450µm long outer segment) across an entire retina (Chung and Marshall 2016, Proceeding B). Theoretically, given these long photoreceptors, the LCA and the resulting differentials of focal length onto different patches of photoreceptors or different depth of the outer segment might provide cues for colour discrimination even though no behavioural evidence exists to prove this hypothesis yet. Unlike the cephalopod case, the four specific spectral cones arranged in a mosaic pattern along with their very short outer segments (5-10µm) in the anemonefish retina likely makes the LCA less effective in this retinal design.

We have added a short paragraph (Lines 400-412) discussing the possibility of an optical mechanism contributing to heightened UV saliency with a particular focus on LCA and our thoughts on why we consider it an unlikely mechanism in anemonefish.

2) The authors provide a quantitative description of anemonefish visual performance within the context of a well-developed receptor-based framework. However, it was less clear to me what inferences (if any) can be drawn from these data about the post-receptoral mechanisms that support tetrachromatic color vision in these organisms. Would specific cone-opponent processes account for instances where behavioral data diverged from predictions generated with the "receptor noise limited" model described in the text? The general reader may benefit from more discussion centered on what is known (or unknown) about the organization of cone-opponent processing in anemonefish and related species.

In short, we do not know the specific opponent interactions of anemonefish cones. The RNL model assumes all possible opponent interactions in its calculations. From our results, very little can be said about the post-receptor mechanisms involved in their putative tetrachromatic vision. We would like to avoid overreaching beyond what our data can show. A future directions section has now been added to the discussion (lines 467-497), which briefly mentions the known UV opponency in larval zebrafish and that future investigation in anemonefish should attempt to disentangle the specific opponent (chromatic) and non-opponent (achromatic) circuits in the anemonefish retina.

Reviewer #3 (Public Review):

The comments below focus mainly on ways that the data and analysis as currently present do not to this reviewer compel the conclusions the authors wish to draw. It is possible that further analysis and/or clarification in the presentation would more persuasively bolster the authors' position. It also seems possible that a presentation with more limited conclusions but clarity on exactly what has been demonstrated and where additional future work is needed would make a strong contribution to the literature.

• Fig 3A. It might be worth emphasizing a bit more explicitly that the x-axis (delta S) is the result of a model fit to the data being shown, since this then means that if RNL model fit the data perfectly, all of the thresholds would fall at deltaS = 1. They don't, so I would like to see some evaluation from the authors' experience with this model as to whether they think the deviations (looks like the delta S range is ~0.4 to ~1.6 in Figure 4B) represent important deviations of the data from the model, the non-significant ANOVA notwithstanding. For example, Figure 4B suggests that the sign of the fit deviations is driven by the sign of the UV contrast and that this is systematic, something that would not be picked up by the ANOVA. Quite a bit is made of the deviations below, but that the model doesn't fully account for the data should be brought out here I think. As the authors note elsewhere, deviations of the data from the RNL model indicate that factors other than receptor noise are at play, and reminding the reader of this here at the first point it becomes clear would be helpful.

We have now stated more explicitly in the figure caption for Figure 3A, that the delta S values presented were calculated by fitting fish behavioral data to the RNL model. To test the overall effect that the sign of the UV contrast had on the discrimination threshold, we have now included ‘contrast’ (positive or negative) as another fixed effect in the linear mixed effects model. We have now included details of this test in the results which shows the systematic effect (lines 338-340). Additionally, as suggested we now briefly introduce in the results the idea that factors other than receptor noise are causing the observed deviations in data from the RNL model.

• Line 217 ff, Figure 4, Supplemental Figure 4). If I'm understanding what the ANOVA is telling us, it is that the deviations of the data across color directions and fish (I think these are the two factors based on line 649) is that the predictions deviate significantly from the data, relative to the inter-fish variability), for the trichromatic models but not the tetrachromatic model. If that's not correct, please interpret this comment to mean that more explanation of the logic of the test would be helpful.

The interpretation of the ANOVA by the Reviewer is mostly correct. We had the variables color set and Fish ID, with threshold delta S as the dependent variable. This showed that deviations from the predicted threshold were significant relative to the inter-fish variability for the trichromatic models. Missing details describing the ANOVA have now been added to the methods (lines 789-798).

Assuming that the above is right about the nature of the test, then I don't think the fact that the tetrachromatic model has an additional parameter (noise level for the added receptor type) is being taken into account in the model comparison. That is, the trichromatic models are all subsets of the tetrachromatic model, and must necessarily fit the data worse. What we want to know is whether the tetrachromatic model is fitting better because its extra parameter is allowing it to account for measurement noise (overfitting), or whether it is really doing a better job accounting for systematic features of the data. This comparison requires some method of taking the different number of parameters into account, and I don't think the ANOVA is doing that work. If the models being compared were nested linear models, than an F-ratio test could be deployed, but even this doesn't seem like what is being done. And the RNL model is not linear in its parameters, so I don't think that would be the right model comparison test in any case.

Typical model comparison approaches would include a likelihood ratio test, AIC/BIC sorts of comparisons, or a cross-validation approach.

If the authors feel their current method does persuasively handle the model comparison, how it does so needs to be brought out more carefully in the manuscript, since one of the central conclusions of the work hinges at least in part on the appropriateness of such a statistical comparison.

Our visual model comparisons were aimed at assessing whether a trichromatic or tetrachromatic model best fit the colour discrimination data. The trichromatic and tetrachromatic models assume two and three opponency pathways, respectively. If the fish were not tetrachromatic, and instead trichromatic, then we would expect that the RNL model should better fit the data with two opponency mechanisms (rather than three). Our reason for making this assessment, is because of the possibility that not all the cones could be contributing to colour vision and could be used exclusively for achromatic tasks (e.g., luminance vision or motion detection). However, according to our finding that the data best fit the tetrachromatic model (i.e., how the behavioural discrimination thresholds more closely fitted the theoretical prediction of 1∆S), it is likely that anemonefish used all four cones for colour vision.

We have also now repeated our analysis using unweighed delta S values which are calculated using general n-dimensional models of colour vision (using the PAVO2 package). These models essentially follow the same initial steps followed by the RNL model (and many others) but omit the receptor noise correction stage. After comparing (using ANOVA, see lines 303-311) the predicted thresholds with the data in this non-RNL space, it was found that again the tetrachromatic model predictions did not deviate significantly from the data relative to individual fish performance; however, we also found that the trichromatic model without M2 cone input no longer differed from the predicted values. In this case, it seems that the extra noise parameter did contribute to the difference in fit. Whether this is a biologically meaningful comparison (as all photoreceptors contain noise) is an open question. We have added a short statement explicitly framing our interpretation of anemonefish having a 3-D colour space to being in accordance with the closeness of RNL model predictions (lines 370-371, 506-508).

• Also on the general point on conclusions drawn from the model fits, it seems important to note that rejecting a trichromatic version of the RNL model is not the same as rejecting all trichromatic models. For example, a trichromatic model that postulates limiting noise added after a set of opponent transformations will make predictions that are not nested within those of RNL trichromatic models. This point seems particularly important given the systematic failures of even the tetrachromatic version of the RNL model.

This is a good point. We have limited our conclusions to specifically address trichromatic models generated within the framework of the RNL model by adding in the conclusion section that fish psychophysical thresholds were best explained by the RNL model when all four cone types contributed to colour vision (see lines 370-371, 506-508). In this same sentence, we have also added in parentheses that “suggesting (but not proving) tetrachromacy” (line 508). We have also edited the abstract to state that our results were “…best described by a tetrachromatic model using all four cone types…”, rather than stating we have shown tetrachromacy (lines 36-37).

• More generally, attempts to decide whether some human observers exhibit tetrachromacy have taught us how hard this is to do. Two issues, beyond the above, are the following. 1) If the properties of a trichromatic visual system vary across the retina, then by imaging stimuli on different parts of the visual field an observer can in principle make tetrachromatic discriminations even though visual system is locally trichromatic at each retinal location. 2) When trying to show that there is no direction in a tetrachromatic receptor space to which the observer is blind, a lot of color directions need to be sampled. Here, 9 directions are studied. Is that enough? How would we know? The following paper may be of interest in this regard: Horiguchi, Hiroshi, Jonathan Winawer, Robert F. Dougherty, and Brian A. Wandell. "Human trichromacy revisited." Proceedings of the National Academy of Sciences 110, no. 3 (2013): E260-E269. Although I'm not suggesting that the authors conduct additional experiments to try to address these points, I do think they need to be discussed. We agree with the reviewer, that colour discriminability achieved by tetrachromatic vision could in theory be achieved by the combined effect of localised, distinct forms of trichromacy. Evidence in other fishes suggests that such multiple forms of trichromacy across the retina likely exist in many species. However, the behavioural effects of this retinal setup remain to be studied likely due to its extremely difficult nature. We have added a new section titled “future directions” (Lines 474-489), in which we discuss the possibility that distinct forms of trichromacy in the anemonefish retina could in theory achieve colour discrimination on par with tetrachromatic vision. We also give suggestions on how this could be investigated.

Although we tried to include as many colour directions as practically possible in our experiment, we have certainly not provided an exhaustive range that completely encompasses anemonefish colour space. Whether 9 colour directions are adequate to assess the dimensionality of their color vision is difficult to say. As addressed in the previous comment, we now acknowledge this limitation by refining our conclusion, saying that our results do not prove tetrachromacy.

• Line 277 ff. After reading through the paper several times, I remain unsure about what the authors regard as their compelling evidence that the UV cone has a higher sensitivity or makes an omnibus higher contribution to sensitivity than other cones (as stated in various forms in the title, Lines 37-41, 56-57, 125, 313, 352 and perhaps elsewhere).

At first, I thought they key point was that the receptor noise inferred via the RNL model as slightly lower (0.11) for the UV cone than for the double cones (0.14). And this is the argument made explicitly at line 326 of the discussion. But if this is the argument, what needs to be shown is that the data reject a tetrachromatic version of the RNL model where the noise value of all the cones is locked to be the same (or something similar), with the analysis taking into account the fewer parametric degrees of freedom where the noise parameters are so constrained. That is, a careful model comparison analysis would be needed. Such an analysis is not presented that I see, and I need more convincing that the difference between 0.11 and 0.14 is a real effect driven by the data. Also, I am not sanguine that the parameters of a model that in some systematic ways fails to fit the data should be taken as characterizing properties of the receptors themselves (as sometimes seems to be stated as the conclusion we should draw).

We have performed various modelling scenarios where receptor noise was adjusted for each channel; however, the UV channel was consistently found to be more sensitive than the other channels. In (the original) Supplementary Figure 6 (now Figure 4 – figure supplements 1 and 2), we show predicted dS values calculated using receptor noise levels in the exact manner that the Reviewer suggests by ranging from 0.05 to 0.15, and most importantly, included scenarios where receptor noise was held equal across cone types and others where it was varied between single cones and double cones. None of the models adjusted the data so that sensitivity was equal across all four channels, which means that by an unknown mechanism, the UV channel is more sensitive, but this is unrelated to noise levels. Our best-fit receptor noise values of 0.11 (for single cones) and 0.14 (for double cones) are estimate values and should be treated as such till actual receptor noise measurements are made.

Then, I thought maybe the argument is not that the noise levels differ, but rather that the failures of the model are in the direction of thresholds being under predicted for discriminations that involve UV cone signals. That's what seems to be being argued here at lines 277 ff, and then again at lines 328 ff of the discussion. But then the argument as I read it more detail in both places switches from being about the UV cones per se to being about postive versus negative UV contrast. That's fine, but it's distinct from an argument that favors omnibus enhanced UV sensitivity, since both the UV increments and decrements are conveyed by the UV cone; it's an argument for differential sensitivity for increments versus decrements in UV mediated discriminations. The authors get to this on lines 334 of the discussion, but if the point is an increment/decrement asymmetry the title and many of the terser earlier assertions should be reworked to be consistent with what is shown.

To clarify our argument, we found that the colour discrimination thresholds were systematically lower than predicted by the RNL model for colours which elicited higher UV cone stimulation relative to other cone types. These colours we refer to as UV positive based on the sign direction of their contrast against grey distractors produced by higher UV/V LED channel (i.e., in a positive direction). Whereas colours with UV negative chromatic contrast had lower UV cone stimulation relative to the other cone types. Therefore, our interpretation of the importance of UV cone signals for colour discrimination are congruent with the results. In the discussion, we suggest a possibility that activation of the UV receptor suppresses noise downstream in the visual pathway or enhances the saliency of colours (see lines 397-398). This activation of the UV receptor would, of course, be at its highest for colours with positive UV chromatic contrast.

Note that we have added to the discussion the possibility that colour preferences or a difference in attentiveness might have contributed to differences in discrimination thresholds (see discussion lines 412-413, 427-428, 433-435, 456-466, and 469-473). However, we consider it a less likely explanation due to a couple of reasons, including 1) a lack of difference in responsiveness across colour sets in their timing to peck the target, and 2) any non-learnt bias would have likely been overridden or at least weakened by training prior to the experiment where colours were rewarded equally (see lines 462-466).

We have edited the results (lines 334-352) to make our point clearer and by changing the subtitle to be more explicit: “Lower discrimination thresholds induced by positive UV contrast”. The subsection begins by explaining the different types of UV chromatic contrast by elevation angle and, finally, how this division among colour sets was a major determinant of colour discrimination thresholds.

Perhaps the argument with respect to model deviations and UV contrast independent of sign could be elaborated to show more systematically that the way the covariation with the contrasts of the other cone stimulations in the stimulus set goes, the data do favor deviations from the RNL in the direction of enhanced sensitivity to UV cone signals, but if this is the intent I think the authors need to think more about how to present the data in a manner that makes it more compelling than currently, and walk the reader carefully through the argument.

We have added to the results the linear mixed-effects model output with ‘contrast’ (positive/negative) added as a fixed effect. This analysis shows that the sign direction of UV contrast was a strong predictor of threshold (see address to previous comments and lines 399-401, 790-799).

• On this point, if the authors decide to stick with the enhanced UV sensitivity argument in the revision, a bit more care about what is meant by "the UV cone has a comparatively high sensitivity (line 313 and throughout)" needs more unpacking. If it is that these cones have lower inferred noise (in the context of a model that doesn't account for at least some aspects of the data), is this because of properties of the UV cones, or the way that post-receptoral processing handles the signals from these cones mimicking a cone effect in the model. And if it is thought that it is because of properties of the cones, some discussion of what those properties might be would be helpful. As I understand the RNL model, relative numbers of cones of each type are taken into account, so it isn't that. But could it be something as simple as higher photopigment density or larger entrance aperture (thus more quantum catches and higher SNR)?

It is unknown what aspect of the cone morphology or physiology sets the activation or inactivation threshold. Electrophysiological data collected from the UV cones of other fish species e.g., in goldfish and zebrafish [see Hawryshyn & Beauchamp (1985). 25, Vis Res.; and Yoshimatsu et al. (2020). 107, Neuron.] show that they have exceptionally high sensitivity. What has not been shown is that having a UV cone can improve colour discrimination.

Previous quantitative cone opsin gene expression analysis showed that the single cone opsins (SWS1 and SWS2B) are expressed at lower levels than all double cone opsin genes. This difference in expression combined with the smaller size of single cone outer segments than the double cones make it unlikely that a larger photoreceptor size, higher volume or packing density of visual pigment is responsible. Contrary to our findings, these aspects of the different cone types (if they had an effect) would instead predict that double cones have a higher SNR, and non-UV colours would be more discriminable. We have now added these details to the discussion (see lines 391-397).

• Line 288 ff. The fact that the slopes of the psychometric functions differed across color directions is, I think, a failure of the RNL model to describe this aspect of the data, and tells us that a simple summary of what happens for thresholds at delta S = 1 does not generalize across color directions for other performance levels. Since one of the directions where the slope is shallower is the UV direction, this fact would seem to place serious limits on the claim that discrimination in the UV direction is enhanced relative to other directions, but it goes by here without comment along those lines. Some comment here, both about implications for fit of RNL model and about implications for generalizations about efficacy of UV receptor mediated discrimination and UV increment/decrement asymmetries, seems important.

The variation in the psychometric functions is difficult to interpret and cannot be explained by the RNL model. What the RNL model predicts is delta S based on low level factors (namely receptor noise). In the discussion, we completely agree with the notion that the asymmetry in thresholds from predicted values, and the variation in psychometric slopes cannot be explained by the RNL model, e.g., this is heavily implied by “colour discrimination thresholds cannot be directly attributed to noise in the early stages of the visual pathway…” (lines 388-390). To clarify the inability of the RNL model to account for this aspect of the data, we have included a statement (see line 390).

It is a good point that this could be an indication of heterogeneity in colour space. Heterogeneity in discrimination thresholds across animal colour space (both surrounding the threshold area and for more saturated regions) has been explored in detail using trichromatic triggerfish by Green N. F. et al. (2022). JEB, 7(225):jeb243533. We have added this idea to the discussion (see lines 490-498). For UV, it seems that two of the five fish (#34 and 20) had noticeably shallower curves than the others tested for UV (fish #19, 33, 36). Both also varied more in their ability to distinguish targets, as shown by their wider confidence intervals. One of these two fish (#34) was retested for UV at the end of the experiment, and in the secondary assessment had a steeper psychometric curve more in line with the other fish in the experiment (see Figure 3 – figure supplement 1 and added lines 247-250). Based on this discrepancy in performance between assessments, it is also possible that individual learning effects had a role in impacting the shape of the psychometric curve. Note, this had minimal effect on colour discrimination thresholds and any differences were in the direction of change observed across colour sets in the experiment (i.e., lower dS for UV positive directions).

• Line 357 ff. Up until this point, all of the discussion of differences in threshold across stimulus sets has been in terms of sensitivity. Here the authors (correctly) raise the possibility that a difference in "preference" across stimulus sets could drive the difference in thresholds as measured. Although the discussion is interesting and germaine, it does to some extent further undercut the security of conclusions about differential sensitivity across color directions relative to the RNL model predictions, and that should be brought out for the reader here. The authors might also discuss about how a future experiment might differentiate between a preference explanation and a sensitivity explanation of threshold differences.

We have now added a paragraph (see lines 469-473) discussing that future work should test for color preferences and suggest how this could be done using a similar foraging task. We also include our thoughts immediately prior on why it is unlikely that a colour preference was a major contribution towards the results. In short, we consider it unlikely as fish showed no evidence of reduced latency for pecking at targets across the colour sets and because the training regime prior to the experiment equally rewarded fish for all colours and would likely have overridden a strong preference (at least in this specific foraging context).

• RNL model. The paper cites a lot of earlier work that used the RNL model, but I think many readers will not be familiar with it. A bit more descriptive prose would be helpful, and particularly noting that in the full dimensional receptor space, if the limiting noise at the photoreceptors is Gaussian, then the isothreshold contour will be a hyper-ellipsoid with its axes aligned with the receptor directions.

There is now added explanation of the RNL model (see lines 141-151), particularly on its assumptions that it only receives chromatic input and that discrimination is limited by noise arising in the photoreceptors and not by any specific opponent mechanisms. We also added the mention of the expected hyper-ellipsoid shape of isothreshold contours if receptor noise is Gaussian. Note, while we appreciate the importance of the reader to understand the basic functionality of the model, we wanted to avoid overloading the introduction with details on the RNL model which is not the focus of the paper. The RNL model is well-established in the field of visual ecology and animal vision research for well over a decade and has been thoroughly dissected by previous methodological reviews. We refer to one of these more recent reviews by Olsson et al. (2018) Behav Ecol. 29(2):273-282, and direct the reader to the methods section for further details on the RNL model.

• Use of cone isolating stimuli? For showing that all four cone classes contribute to what the authors call color discrimination, a more direct approach would seem to be to use stimuli that target stimulation of only one class of cone at a time. This might require a modified design in which the distractors and target were shown against a uniform background and approximately matched in their estimated effect on a putative achromatic mechanism. Did the authors consider this approach, and more generally could they discuss what they see as its advantages and disadvantages for future work.

The Reviewer is correct in that a targeted approach of isolated cone stimulation would be the optimal approach to demonstrating tetrachromatic colour vision. However, the extreme spectral overlap in the absorption curves of anemonefish cones, particularly in the mid-wavelength region makes this problematic in using the current LED display. We added to the discussion ways that this could be studied in the future (see lines 474-489). This might be possible (but still challenging) using a monochromator, but such technology severely limits the diversity of stimuli which can be created and usually restricts experiments to a simple paired choice design (or grey card experiment). The traditional paired choice experiment requires animals to be trained to distinguish a specific colour, while the Ishihara-like task trains animals to distinguish targets using an odd-one-out approach. This latter approach is highly efficient, as it does not require retraining when testing a new colour (i.e., fish learnt the task not a specific colour). Here, we wanted to assess colour discrimination in multiple directions to compare performance, and the flexible LED display combined with a generalisable task was important.

The above assumes that anemonefish do not use multiple trichromatic systems. In which case, the use of standard experimental stimuli (e.g., a monochromator, an LED display) would be unsuitable as they illuminate the whole retina. To definitively test the range of opponent interactions, it would be necessary to make electrophysiological measurements targeting the transmitting neurons using a retinal multielectrode array (MEA) approach or by in-vivo calcium imaging (lines 484-486).

We understand that our results are not a direct test of the dimensionality of anemonefish colour vision and should not be interpreted as such, as we do not have direct evidence of tetrachromacy. To recognize this limitation of our data, we have drawn back some of our conclusive statements that claimed to have demonstrated tetrachromacy.

Author Response

Reviewer #1 (Public Review):

Precise regulation of gamete fusion ensures that offspring will have the same ploidy as the parents. However, breaking this regulation can be useful for plant breeding. Haploid induction followed by chemical-induced genome doubling can be used to fix desirable genotypes, while triparental hybrids where two sperm cells with two different genotypes fertilize an egg cell can be advantageous for bypassing hybridization barriers to create interspecies hybrids with increased fitness. This manuscript follows up on a previous study from the same research group that used a clever high throughput polyspermy detection assay (HIPOD) to show that wild-type Arabidopsis naturally forms triparental hybrids at very low frequencies (less than 0.05% of progeny) and that these triparental hybrids can bypass dosage barriers in the endosperm (Nakel, et al., 2017). Mao and co-authors hypothesized that mutants that conferred polytubey, the attraction of multiple pollen tubes by mutant female gametophytes, would also increase the rate of triparental hybrids. They used a double mutant in the endopeptidase genes ECS1 and ECS2 which had previously been reported to induce supernumerary pollen tube attraction to test this hypothesis with their two-component HIPOD system in which one pollen donor constitutively expresses the mGAL4-VP16 transcription factor while the second pollen donor carries an herbicide resistance gene regulated by the GAL4-responsive UAS promoter. Triparental hybrids are detected as herbicide-resistant progeny from wild-type Arabidopsis flowers that have been pollinated by the two paternal genotypes. The authors convincingly show that the ecs1 ecs2-1 double mutant more than doubled the frequency of triparental, triploid hybrids in HIPOD crosses. They next tested the hypothesis that this increase in triparental hybrids was due to a gametophytic effect by using an ecs1-/- ecs2-1/ECS2 maternal parent in the HIPOD assay and testing whether the ecs2-1 mutant allele was preferentially inherited in triparental hybrids. The mutant allele was inherited at a much higher rate than expected, confirming their hypothesis.

The triparental hybrid results with the ecs1 ecs2 mutant were not that surprising since the presence of extra sperm cells gives more opportunities for triparental hybrids to form, especially if gamete fusion is misregulated. However, an unexpected result came when the authors used aniline blue staining to analyze the ecs1 ecs2 polytubey phenotype. They confirmed that the double mutant had increased levels of polytubey compared to wild-type ovules, but they also noticed that 13% of seeds were not developing normally. This phenotype was confirmed with a second ecs2 allele and was complemented with both ECS1 and ECS2 transgenes under their native promoters. Microscopic analysis revealed normal gametophyte morphology before fertilization, but 8% of pollinated ovules failed to develop an embryo and 7% failed to develop endosperm, suggesting single fertilization events. In a logical set of experiments, they followed up on this result by crossing ecs1 ecs2 with pollen carrying a fluorescent reporter that would be expressed in developing embryos and endosperm. In this experiment, they were again surprised. Some of the wild-type-looking seeds lacked a paternal contribution (i.e. no fluorescent signal from the paternal reporter construct) in the embryo. This prompted them to look more closely at the progeny, upon which they detected small plants that were haploid. They confirmed the haploid nature by chromosome spreads. Finally, they used interaccession crosses between ecs1 ecs2 (Col-0) and Landsberg to verify that haploid progeny only carried maternal alleles of markers on all five chromosomes, indicating that the ecs1 ecs2 genotype can induce maternal haploids.

This interesting study highlights the importance of following up on unexpected results. The conclusions are well-supported by the data and quite exciting. Paternal haploid inducers have been discovered in several species, but this is one of only two examples of maternal haploid induction. While the percentage of maternal haploids is very low, this phenomenon could be useful for plant breeding.

Weaknesses

The data in the manuscript is intriguing, but the question of how the same mutant combination promotes the formation of both triploid and haploid progeny remains unanswered and is not thoroughly discussed, nor is any model suggested for how the ECS1/2 peptidases could play a role in regulating gamete fusion and/or repressing parthenogenesis. A second unanswered question is whether the maternal haploids are a result of failed plasmogamy or karyogamy between the egg and sperm leading to parthenogenesis or a result of paternal genome elimination after plasmogamy. In figure 3B, the authors attempted to test whether plasmogamy occurs between the male and female gametes in ecs1 ecs2 ovules by crosses with pollen that expresses a mitochondrial marker under control of the pRPS5a promoter which is active in sperm cells as well as embryos and endosperm of fertilized ovules. This experiment allowed them to detect sperm cells that had not fused with the egg and central cell at 2 days after pollination. They also counted the percentage of seeds that expressed the mitochondrial marker in both embryo and endosperm at 2 DAP and found that ecs1 ecs2 mutants had a 20% reduction of visible mitochondria in embryo sacs compared to wildtype. They conclude that the result indicates a potential plasmogamy defect. However, the dependability of this marker is questionable since only ~55% of wild-type seeds had detectable signal in the embryo and endosperm. The authors imply that this experiment could be used to test plasmogamy, but it is not clear how any conclusions related to the abnormal seed phenotype could be drawn from examining the rate of signal in both the embryo and endosperm. Since the mitochondrial marker was not expressed from a sperm-specific promoter, the fluorescent signal at 2DAP is likely due to new gene expression from pRPS5a in the fertilized embryo and endosperm, not an indication of the presence of sperm-derived mitochondria. Perhaps an earlier timepoint could be used as well as a spermspecific promoter instead of pRPS5a to answer the question of whether plasmogamy is happening in the ecs1 ecs2 ovules.

Thanks for the suggestion. We here provide two additional new data sets to provide evidence that ecs1 ecs2 mutant plants indeed exhibit single fertilization that lead to fertilization recovery.

We determined the fertilization failure by checking the decondensation HTR10-RFP labelled sperm nuclei 8-10 HAP (Figure 3B) and the frequency of heterofertilization through dual pollination experiment (Figure 3C-E) (see above).

Reviewer #2 (Public Review):

The manuscript reports the triploid and haploid productions using an ecs1ecs2 mutant as the maternal donor, in addition to the evaluation of the sexual process observed in the mutant. The indicated data show exquisite quality. To improve the content, I recommend carefully reconsidering the descriptions because some of the insights would cause a stir in the controversy regarding ECS1&2 functions in plant reproduction.

Strengths

Triploid production by a combination of ecs1ecs2 mutant and HIPOD system has potential as a future plant breeding tool. Moreover, it's intriguing that both triploid and haploid productions were achieved using the same mutant as a maternal donor. I think authors can claim the value of their results more by adding descriptions about the usefulness of the aneuploid plants in plant breeding history.

The evidence of the persistent synergid nucleus (Figure 3A) is critical insight reported by this study. As Maruyama et al. (2013) reported by live cell imaging, synergid-endosperm fusion had occurred at the two endosperm nuclei stage. It would be valuable to claim the observed fact by citing Maruyama's previous observation.

Weakness

As the authors suggested, the higher triploid frequency observed in ecs1ecs2 than WT was likely caused by the increased polyspermy. However, it also could be that reduction of normal seed number in ecs1ecs2 (whichever is due to failure of fertilization or embryo development arrest) accounts for the increased frequency of the triploid compared to WT.

The results in Figure 3C-E suggested the single fertilization for both egg and central cells at similar frequencies. This is an exciting result, but it is still possible that the fertilized egg or central cell degenerated after fertilization resulting in the disappearance of paternally inherited fluorescence. Evaluation of fertilization patterns at 7-10HAP in ecs1ecs2 mutant may provide more confident insight, although unfused sperm cell was evaluated at 1DAP (Figure 3-figure supplement 1B). The fertilization states can be distinguished depending on the HTR10RFP sperm nuclei morphology and their positions, as reported by Takahashi et al (2018).

Thank you for your suggestion. We added the requested experiment see Figure 3B in the revised manuscript. In addition, we conducted a dual pollination experiment, that provides evidence for the activation of the fertilization recovery machinery (Figure 3C-E) (see above).

Several recent studies have reported exciting insights on ECS1&2 functions; however, various results from different laboratories have raised controversy. Though, the commonly found feature is the repression of polytubey. For readers, it would be helpful to organize the explanation about which insights are concordant or different.

Thank you for your suggestion. We now indicate using terms like in line with or in contrast to, where our data confirms /or contradicts with previous data.

In addition, a drawing that explains the time course in the process from pollination to seed development (up to 6DAP) based on WT would help to understand which point is evaluated in each data.

Thank you for your suggestion. We added a model figure (Figure 4E) at the end of the manuscript that brings the concepts together and facilitates the understandings.

Reviewer #3 (Public Review):

In this manuscript, Mao et al. reported that the two proteases ECS1 and ECS2 participate in both polyspermy block and gamete fusion in Arabidopsis thaliana. The authors could observe polytubey phenotype which has been reported previously and obtain both triparental plants and haploids in ecs1 ecs2 mutants. Therefore, they proposed that the triparental plants resulted from the polytubey block defect, whereas the haploids were caused by the gamete fusion defect. Together with two other previous reports, I think it is very interesting to see these two proteases participating in so many different but connected processes. Although they did not provide the molecular mechanism of how ECS participated in polyspermy block and gamete fusion, their findings provide more options for and thus promote plant breeding. The work may have a wide application in the future and will be of broad interest to cell biologists working on gamete fusion and plant breeders.

We thank the reviewer for their positive comments.

Although most of the conclusions in this paper are well supported by the data, it could be improved with a minor revision including providing clearer data analysis and descriptions, images with higher resolution, and more discussions.

Author Response

Reviewer #2 (Public Review):

In the discussion, the authors suggest that the binding of CHAPS could be an inspiration to develop compounds, targeting, for instance, mammalian receptors, that would bind to both the orthosteric site and a potential groove underneath loop C (where the sterol moiety of CHAPS binds in Alpo4). A figure (SI4) shows a few homologues in surface representation, giving an idea of whether this groove is generally present in the family.

Seeing this figure, I wondered if it would be relevant to compare several conformations of one or a few chosen homologues. Given that gating always impacts the quaternary assembly, is this groove more pronounced in say the inhibited state of a given homologue than in its agonist-bound state?

The width of the groove in 7 does change as the channel transition from apo to open state. This is now demonstrated with an additional Figure 3 – figure supplement 1b and the discussion was adjusted accordingly p 18, line 379:

“The sterol group connected by a linker binds in between subunits and induces conformational changes which also change the width of the groove in Alpo4 (Figure 3f, g), therefore it likely plays an active role in the observed quaternary twist. The changes in the groove shape are not specific to Alpo4 but are also observed for example in nicotinic 7 receptor (Figure 3 – supplement 1b) suggesting that the groove can be targeted for allosteric modulation of the channel. ”

A related thought was that some of the protein binders affecting pLGIC function (toxins, VHH) contact two subunits and wrap around/below loop C. Do these have binding sites that overlap with the groove?

We inspected the structures of pLGICs homologs with bound -bungarotoxin (6UWZ, 4HQP, 7Z14, and 7KOO) and 2 with bound VHHs (6SSI and 6HJY). The toxins were bound in similar conformations but not the VHHs. The examples of the complexes are now shown as Supplementary Figure 13a (see above). In the case of ELIC, the nanobody Nb72 was bound on top of the sterol-binding cavity, but it did not interact with the interior of the cavity. This is now explained on p 17 from line 374:

“When binding sites of larger know binders, including VHH47,48 and -bungarotoxin10,49 were examined (Figure 3 – supplement 1a) a nanobody bound to ELIC in the site covering the sterol-binding groove was identified, however, its interactions with ELIC did not overlap significantly with the interior of the sterol-binding groove. This suggests that the latter is a novel target location for binders.”

Very interestingly, the binding of CHAPS stabilizes a conformation that differs from the apo one. It includes a twist of the ECDs but does not lead to a significant opening of the M2 bundle. The authors note that the direction of the twist is reversed to that often associated with the binding of ligands in homologues. This reversion is quite a feature, which deserves to be shown in a supplementary movie (e.g overlay of the Alpo apo>CHAPs transition with the nico>apo transition of a7).

We have re-examined the rotation and compared it to the conformational changes in nACh 7 and 5-HT3 receptors. Upon closer examination, it became clear that relative rotation of the ECD and the TMD provides a very simplistic view of the quaternary conformational changes which are more complex 3D quaternary changes than a simple relative domain rotation. Careful alignment of the structures to the extracellular side of the trans-membrane pore showed that in both channels resting-> open state transition is associated with clockwise rotation, but resting-> desensitized state transition in 5-HT3 involves a counterclockwise rotation. Thus, 1) the direction of rotation is not a ‘universal’ feature of pLGICs and 2) the clockwise rotation is the direction of channel activation for α7 nACh receptor and 5-HT3 and shares similarities with rearrangements observed in Alpo4. However, the relative movement of the ECDs is different between Alpo upon CHAPS binding and α7 nACh and 5-HT3 receptor upon activation. To demonstrate this, we added Video 2 which shows quaternary changes for all 3 channels and the text has been modified as follows on page 11 line 208:

“Quaternary changes in Alpo4 induced upon CHAPS binding and those associated with the activation of related α7 nACh and 5-HT3 receptors induced rotation of ECD relative to TMD in the same direction, however, the shifts of principal relative to complementary subunits were different (Video 2). In Alpo4, the complementary subunit slides upward whereas in the two other channels it consistently shifts towards the principal subunit and tilts relative to the TMD. The tilt is less pronounced in Alpo4 which is probably why it does not lead to the pore dilation.”

We are grateful to the reviewer for drawing our attention to this point, which permitted us to correct initially inaccurate statements.

Author Response

Reviewer #2 (Public Review):

Here, a simple model of cerebellar computation is used to study the dependence of task performance on input type: it is demonstrated that task performance and optimal representations are highly dependent on task and stimulus type. This challenges many standard models which use simple random stimuli and concludes that the granular layer is required to provide a sparse representation. This is a useful contribution to our understanding of cerebellar circuits, though, in common with many models of this type, the neural dynamics and circuit architecture are not very specific to the cerebellum, the model includes the feedforward structure and the high dimension of the granule layer, but little else. This paper has the virtue of including tasks that are more realistic, but by the paper’s own admission, the same model can be applied to the electrosensory lateral line lobe and it could, though it is not mentioned in the paper, be applied to the dentate gyrus and large pyramidal cells of CA3. The discussion does not include specific elements related to, for example, the dynamics of the Purkinje cells or the role of Golgi cells, and, in a way, the demonstration that the model can encompass different tasks and stimuli types is an indication of how abstract the model is. Nonetheless, it is useful and interesting to see a generalization of what has become a standard paradigm for discussing cerebellar function.

We appreciate the Reviewer’s positive comments. Regarding the simplifications of our model, we agree that we have taken a modeling approach that abstracts away certain details to permit comparisons across systems. We now include an in-depth discussion of our simplifying assumptions (Assumptions & Extensions section in the Discussion) and have further noted the possibility that other biophysical mechanisms we have not accounted for may also underlie differences across systems.

Our results predict that qualitative differences in the coding levels of cerebellum-like systems, across brain regions or across species, reflect an optimization to distinct tasks (Figure 7). However, it is also possible that differences in coding level arise from other physiological differences between systems.

Reviewer #3 (Public Review):

1) The paper by Xie et al is a modelling study of the mossy fiber-to-granule cell-to-Purkinje cell network, reporting that the optimal type of representations in the cerebellar granule cell layer depends on the type task. The paper stresses that the findings indicate a higher overall bias towards dense representations than stated in the literature, but it appears the authors have missed parts of the literature that already reported on this. While the modelling and analysis appear mathematically solid, the model is lacking many known constraints of the cerebellar circuitry, which makes the applicability of the findings to the biological counterpart somewhat limited.

We thank the Reviewer for suggesting additional references to include in our manuscript, and for encouraging us to extend our model toward greater biological plausibility and more critically discuss simplifying assumptions we have made. We respond to both the comment about previous literature and about applicability to cerebellar circuitry in detail below.

2) I have some concerns with the novelty of the main conclusion, here from the abstract: ’Here, we generalize theories of cerebellar learning to determine the optimal granule cell representation for tasks beyond random stimulus discrimination, including continuous input-output transformations as required for smooth motor control. We show that for such tasks, the optimal granule cell representation is substantially denser than predicted by classic theories.’ Stated like this, this has in principle already been shown, i.e. for example: Spanne and Jo¨rntell (2013) Processing of multi-dimensional sensorimotor information in the spinal and cerebellar neuronal circuitry: a new hypothesis. PLoS Comput Biol. 9(3):e1002979. Indeed, even the 2 DoF arm movement control that is used in the present paper as an application, was used in this previous paper, with similar conclusions with respect to the advantage of continuous input-output transformations and dense coding. Thus, already from the beginning of this paper, the novelty aspect of this paper is questionable. Even the conclusion in the last paragraph of the Introduction: ‘We show that, when learning input-output mappings for motor control tasks, the optimal granule cell representation is much denser than predicted by previous analyses.’ was in principle already shown by this previous paper.

We thank the Reviewer for drawing our attention to Spanne and Jo¨rntell (2013). Our study shares certain similarities with this work, including the consideration of tasks with smooth input-output mappings, such as learning the dynamics of a two-joint arm. However, our study differs substantially, most notably the fact that we focus our study on parametrically varying the degree of sparsity in the granule cell layer to determine the circumstances under which dense versus sparse coding is optimal. To the best of our ability, we can find no result in Spanne and J¨orntell (2013) that indicates the performance of a network as a function of average coding level. Instead, Spanne and Jo¨rntell (2013) propose that inhibition from Golgi cells produces heterogeneity in coding level which can improve performance, which is an interesting but complementary finding to ours. We therefore do not believe that the quantitative computations of optimal coding level that we present are redundant with the results of this previous study. We also note that a key contribution of our study is mathemetical analysis of the inductive bias of networks with different coding levels which supports our conclusions.

We have included a discussion of Spanne and Jo¨rntell (2013) and (2015) in the revised version of our manuscript:

"Other studies have considered tasks with smooth input-output mappings and low-dimensional inputs, finding that heterogeneous Golgi cell inhibition can improve performance by diversifying individual granule cell thresholds (Spanne and J¨orntell, 2013). Extending our model to include heterogeneous thresholds is an interesting direction for future work. Another proposal states that dense coding may improve generalization (Spanne and Jo¨rntell, 2015). Our theory reveals that whether or not dense coding is beneficial depends on the task."

3) However, the present paper does add several more specific investigations/characterizations that were not previously explored. Many of the main figures report interesting new model results. However, the model is implemented in a highly generic fashion. Consequently, the model relates better to general neural network theory than to specific interpretations of the function of the cerebellar neuronal circuitry. One good example is the findings reported in Figure 2. These represent an interesting extension to the main conclusion, but they are also partly based on arbitrariness as the type of mossy fiber input described in the random categorization task has not been observed in the mammalian cerebellum under behavior in vivo, whereas in contrast, the type of input for the motor control task does resemble mossy fiber input recorded under behavior (van Kan et al 1993).

We agree that the tasks we consider in Figure 2 are simplified compared to those that we consider elsewhere in the paper. The choice of random mossy fiber input was made to provide a comparison to previous modeling studies that also use random input as a benchmark (Marr 1969, Albus 1971, Brunel 2004, Babadi and Sompolinsky 2014, Billings 2014, LitwinKumar et al., 2017). This baseline permits us to specifically evaluate the effects of lowdimensional inputs (Figure 2) and richer input-output mappings (Figure 2, Figure 7). We agree with the Reviewer that the random and uncorrelated mossy fiber activity that has been extensively used in previous studies is almost certainly an unrealistic idealization of in vivo neural activity—this is a motivating factor for our study, which relaxes this assumption and examines the consequences. To provide additional context, we have updated the following paragraph in the main text Results section:

"A typical assumption in computational theories of the cerebellar cortex is that inputs are randomly distributed in a high-dimensional space (Marr, 1969; Albus, 1971; Brunel et al., 2004; Babadi and Sompolinsky, 2014; Billings et al., 2014; Litwin-Kumar et al., 2017). While this may be a reasonable simplification in some cases, many tasks, including cerebellumdependent tasks, are likely best-described as being encoded by a low-dimensional set of variables. For example, the cerebellum is often hypothesized to learn a forward model for motor control (Wolpert et al., 1998), which uses sensory input and motor efference to predict an effector’s future state. Mossy fiber activity recorded in monkeys correlates with position and velocity during natural movement (van Kan et al., 1993). Sources of motor efference copies include motor cortex, whose population activity lies on a lowdimensional manifold (Wagner et al., 2019; Huang et al., 2013; Churchland et al., 2010; Yu et al., 2009). We begin by modeling the low dimensionality of inputs and later consider more specific tasks."

4) The overall conclusion states: ‘Our results....suggest that optimal cerebellar representations are task-dependent.’ This is not a particularly strong or specific conclusion. One could interpret this statement as simply saying: ‘if I construct an arbitrary neural network, with arbitrary intrinsic properties in neurons and synapses, I can get outputs that depend on the intensity of the input that I provide to that network.’ Further, the last sentence of the Introduction states: ‘More broadly, we show that the sparsity of a neural code has a task-dependent influence on learning...’ This is very general and unspecific, and would likely not come as a surprise to anyone interested in the analysis of neural networks. It doesn’t pinpoint any specific biological problem but just says that if I change the density of the input to a [generic] network, then the learning will be impacted in one way or another.

We agree with the Reviewer that our conclusions are quite general, and we have removed the final sentence as we agree it was unspecific. However, we disagree with the Reviewer’s paraphrasing of our results.

First, we do not select arbitrary intrinsic properties of neurons and synapses. Rather, we construct a simplified model with a key quantity, the neuronal threshold, that we vary parametrically in order to assess the effect of the resulting changes in the representation on performance. Second, we do not vary the intensity/density of inputs provided to the network – this is fixed throughout our study for all key comparisons we perform. Instead, we vary the density (coding level) of the expansion layer representation and quantify its effect on inductive bias and generalization. Finally, our study’s key contribution is an explanation of the heterogeneity in average coding level observed across behaviors and cerebellum-like systems. We go beyond the empirical statement that there is a dependence of performance on the parameter that we vary by developing an analytical theory. Our theory describes the performance of the class of networks that we study and the properties of learning tasks that determine the optimal expansion layer representation.

To clarify our main contributions, we have updated the final paragraph of the Introduction. We have also removed the sentence that the Reviewer objects to, as it was less specific than the other points we make here.

"We propose that these differences can be explained by the capacity of representations with different levels of sparsity to support learning of different tasks. We show that the optimal level of sparsity depends on the structure of the input-output relationship of a task. When learning input-output mappings for motor control tasks, the optimal granule cell representation is much denser than predicted by previous analyses. To explain this result, we develop an analytic theory that predicts the performance of cerebellum-like circuits for arbitrary learning tasks. The theory describes how properties of cerebellar architecture and activity control these networks’ inductive bias: the tendency of a network toward learning particular types of input-output mappings (Sollich, 1998; Jacot et al., 2018; Bordelon et al., 2020; Canatar et al., 2021; Simon et al., 2021). The theory shows that inductive bias, rather than the dimension of the representation alone, is necessary to explain learning performance across tasks. It also suggests that cerebellar regions specialized for different functions may adjust the sparsity of their granule cell representations depending on the task."

5) The interpretation of the distribution of the mossy fiber inputs to the granule cells, which would have a crucial impact on the results of a study like this, is likely incorrect. First, unlike the papers that the authors cite, there are many studies indicating that there is a topographic organization in the mossy fiber termination, such that mossy fibers from the same inputs, representing similar types of information, are regionally co-localized in the granule cell layer. Hence, there is no support for the model assumption that there is a predominantly random termination of mossy fibers of different origins. This risks invalidating the comparisons that the authors are making, i.e. such as in Figure 3. This is a list of example papers, there are more: van Kan, Gibson and Houk (1993) Movement-related inputs to intermediate cerebellum of the monkey. Journal of Neurophysiology. Garwicz et al (1998) Cutaneous receptive fields and topography of mossy fibres and climbing fibres projecting to cat cerebellar C3 zone. The Journal of Physiology. Brown and Bower (2001) Congruence of mossy fiber and climbing fiber tactile projections in the lateral hemispheres of the rat cerebellum. The Journal of Comparative Neurology. Na, Sugihara, Shinoda (2019) The entire trajectories of single pontocerebellar axons and their lobular and longitudinal terminal distribution patterns in multiple aldolase C-positive compartments of the rat cerebellar cortex. The Journal of Comparative Neurology.

6) The nature of the mossy fiber-granule cell recording is also reviewed here: Gilbert and Miall (2022) How and Why the Cerebellum Recodes Input Signals: An Alternative to Machine Learning. The Neuroscientist. Further, considering the re-coding idea, the following paper shows that detailed information, as it is provided by mossy fibers, is transmitted through the granule cells without any evidence of re-coding: Jo¨rntell and Ekerot (2006) Journal of Neuroscience; and this paper shows that these granule inputs are powerfully transmitted to the molecular layer even in a decerebrated animal (i.e. where only the ascending sensory pathways remains) Jo¨rntell and Ekerot 2002, Neuron.

We agree that there is strong evidence for a topographic organization in mossy fiber to granule cell connectivity at the microzonal level. We thank the Reviewer for pointing us to specific examples. We acknowledge that our simplified model does not capture the structure of connectivity observed in these studies.

However, the focus of our model is on cerebellar neurons presynaptic to a single Purkinje cell. Random or disordered distribution of inputs at this local scale is compatible with topographic organization at the microzonal scale. Furthermore, while there is evidence of structured connections at the local scale, models with random connectivity are able to reproduce the dimensionality of granule cell activity within a small margin of error (Nguyen et al., 2022). Finally, our finding that dense codes are optimal for learning slowly varying tasks is consistent with evidence for the lack of re-coding – for such tasks, re-coding may absent because it is not required.

We have dedicated a section on this issue in the Assumptions and Extensions portion of our Discussion:

"Another key assumption concerning the granule cells is that they sample mossy fiber inputs randomly, as is typically assumed in Marr-Albus models (Marr, 1969; Albus, 1971; LitwinKumar et al., 2017; Cayco-Gajic et al., 2017). Other studies instead argue that granule cells sample from mossy fibers with highly similar receptive fields (Garwicz et al., 1998; Brown and Bower, 2001; J¨orntell and Ekerot, 2006) defined by the tuning of mossy fiber and climbing fiber inputs to cerebellar microzones (Apps et al., 2018). This has led to an alternative hypothesis that granule cells serve to relay similarly tuned mossy fiber inputs and enhance their signal-to-noise ratio (Jo¨rntell and Ekerot, 2006; Gilbert and Chris Miall, 2022) rather than to re-encode inputs. Another hypothesis is that granule cells enable Purkinje cells to learn piece-wise linear approximations of nonlinear functions (Spanne and J¨orntell, 2013). However, several recent studies support the existence of heterogeneous connectivity and selectivity of granule cells to multiple distinct inputs at the local scale (Huang et al., 2013; Ishikawa et al., 2015). Furthermore, the deviation of the predicted dimension in models constrained by electron-microscopy data as compared to randomly wired models is modest (Nguyen et al., 2022). Thus, topographically organized connectivity at the macroscopic scale may coexist with disordered connectivity at the local scale, allowing granule cells presynaptic to an individual Purkinje cell to sample heterogeneous combinations of the subset of sensorimotor signals relevant to the tasks that Purkinje cell participates in. Finally, we note that the optimality of dense codes for learning slowly varying tasks in our theory suggests that observations of a lack of mixing (J¨orntell and Ekerot, 2002) for such tasks are compatible with Marr-Albus models, as in this case nonlinear mixing is not required."

7) I could not find any description of the neuron model used in this paper, so I assume that the neurons are just modelled as linear summators with a threshold (in fact, Figure 5 mentions inhibition, but this appears to be just one big lump inhibition, which basically is an incorrect implementation). In reality, granule cells of course do have specific properties that can impact the input-output transformation, PARTICULARLY with respect to the comparison of sparse versus dense coding, because the low-pass filtering of input that occurs in granule cells (and other neurons) as well as their spike firing stochasticity (Saarinen et al (2008). Stochastic differential equation model for cerebellar granule cell excitability. PLoS Comput. Biol. 4:e1000004) will profoundly complicate these comparisons and make them less straight forward than what is portrayed in this paper. There are also several other factors that would be present in the biological setting but are lacking here, which makes it doubtful how much information in relation to the biological performance that this modelling study provides: What are the types of activity patterns of the inputs? What are the learning rules? What is the topography? What is the impact of Purkinje cell outputs downstream, as the Purkinje cell output does not have any direct action, it acts on the deep cerebellar nuclear neurons, which in turn act on a complex sensorimotor circuitry to exert their effect, hence predictive coding could only become interpretable after the PC output has been added to the activity in those circuits. Where is the differentiated Golgi cell inhibition?

Thank you for these critiques. We have made numerous edits to improve the presentation of the details of our model in the main text of the manuscript. Indeed, granule cells in the main text are modeled as linear sums of mossy fiber inputs with a threshold-linear activation function. A more detailed description of the model for granule cells can now be found in Equation 1 in the Results section:

"The activity of neurons in the expansion layer is given by: h = φ(Jeffx − θ), (1) where φ is a rectified linear activation function φ(u) = max(u,0) applied element-wise. Our results also hold for other threshold-polynomial activation functions. The scalar threshold θ is shared across neurons and controls the coding level, which we denote by f, defined as the average fraction of neurons in the expansion layer that are active."

Most of our analyses use the firing rate model we describe above, but several Supplemental Figures show extensions to this model. As we mention in the Discussion, our results do not depend on the specific choice of nonlinearity (Figure 2-figure supplement 2). We have also considered the possibility that the stochastic nature of granule cell spikes could impact our measures of coding level. In Figure 7-figure supplement 1 we test the robustness of our main conclusion using a spiking model where we model granule cell spikes with Poisson statistics. When measuring coding level in a population of spiking neurons, a key question is at what time window the Purkinje cell integrates spikes. For several choices of integration time windows, we show that dense coding remains optimal for learning smooth tasks. However, we agree with the Reviewer that there are other biological details our model does not address. For example, our spiking model does not capture some of the properties the Saarinen et al. (2008) model captures, including random sub-threshold oscillations and clusters of spikes. Modeling biophysical phenomena at this scale is beyond the scope of our study. We have added this reference to the relevant section of the Discussion:

"We also note that coding level is most easily defined when neurons are modeled as rate, rather than spiking units. To investigate the consistency of our results under a spiking code, we implemented a model in which granule cell spiking exhibits Poisson variability and quantify coding level as the fraction of neurons that have nonzero spike counts (Figure 7-figure supplement 1; Figure 7C). In general, increased spike count leads to improved performance as noise associated with spiking variability is reduced. Granule cells have been shown to exhibit reliable burst responses to mossy fiber stimulation (Chadderton et al., 2004), motivating models using deterministic responses or sub-Poisson spiking variability. However, further work is needed to quantitatively compare variability in model and experiment and to account for more complex biophysical properties of granule cells (Saarinen et al., 2008)."

A second concern the Reviewer raises is our implementation of Golgi cell inhibition as a homogeneous rather than heterogeneous input onto granule cells. In simplified models, adding heterogeneous inhibition does not dramatically change the qualitative properties of the expansion layer representation, in particular the dimensionality of the representation (Billings et al., 2014, Cayco-Gajic et al., 2017, Litwin-Kumar et al., 2017). We have added a section about inhibition to our Discussion:

"We also have not explicitly modeled inhibitory input provided by Golgi cells, instead assuming such input can be modeled as a change in effective threshold, as in previous studies (Billings et al., 2014; Cayco-Gajic et al., 2017; Litwin-Kumar et al., 2017). This is appropriate when considering the dimension of the granule cell representation (Litwin-Kumar et al., 2017), but more work is needed to extend our model to the case of heterogeneous inhibition."

Regarding the mossy fiber inputs, as we state in response to paragraph 3, we agree with the Reviewer that the random and uncorrelated mossy fiber activity that has been used in previous studies is an unrealistic idealization of in vivo neural activity. One of the motivations for our model was to relax this assumption and examine the consequences: we introduce correlations in the mossy fiber activity by projecting low-dimensional patterns into the mossy fiber layer (Figure 1B):

"A typical assumption in computational theories of the cerebellar cortex is that inputs are randomly distributed in a high-dimensional space (Marr, 1969; Albus, 1971; Brunel et al., 2004; Babadi and Sompolinsky, 2014; Billings et al., 2014; Litwin-Kumar et al., 2017). While this may be a reasonable simplification in some cases, many tasks, including cerebellumdependent tasks, are likely best-described as being encoded by a low-dimensional set of variables. For example, the cerebellum is often hypothesized to learn a forward model for motor control (Wolpert et al., 1998), which uses sensory input and motor efference to predict an effector’s future state. Mossy fiber activity recorded in monkeys correlates with position and velocity during natural movement (van Kan et al., 1993). Sources of motor efference copies include motor cortex, whose population activity lies on a low-dimensional manifold (Wagner et al., 2019; Huang et al., 2013; Churchland et al., 2010; Yu et al., 2009). We begin by modeling the low dimensionality of inputs and later consider more specific tasks.

We therefore assume that the inputs to our model lie on a D-dimensional subspace embedded in the N-dimensional input space, where D is typically much smaller than N (Figure 1B). We refer to this subspace as the “task subspace” (Figure 1C)."

The Reviewer also mentions the learning rule at granule cell to Purkinje cell synapses. We agree that considering online, climbing-fiber-dependent learning is an important generalization. We therefore added a new supplemental figure investigating whether we would still see a difference in optimal coding levels across tasks if online learning were used instead of the least squares solution (Figure 7-figure supplement 2). Indeed, we observed a similar task dependence as we saw in Figure 2F. We have added a new paragraph in the Discussion under Assumptions and Extensions describing our rationale and approach in detail:

"For the Purkinje cells, our model assumes that their responses to granule cell input can be modeled as an optimal linear readout. Our model therefore provides an upper bound to linear readout performance, a standard benchmark for the quality of a neural representation that does not require assumptions on the nature of climbing fiber-mediated plasticity, which is still debated. Electrophysiological studies have argued in favor of a linear approximation (Brunel et al., 2004). To improve the biological applicability of our model, we implemented an online climbing fiber-mediated learning rule and found that optimal coding levels are still task-dependent (Figure 7-figure supplement 2). We also note that although we model several timing-dependent tasks (Figure 7), our learning rule does not exploit temporal information, and we assume that temporal dynamics of granule cell responses are largely inherited from mossy fibers. Integrating temporal information into our model is an interesting direction for future investigation."

Finally, regarding the function of the Purkinje cell, our model defines a learning task as a mapping from inputs to target activity in the Purkinje cell and is thus agnostic to the cell’s downstream effects. We clarify this point when introducing the definition of a learning task:

"In our model, a learning task is defined by a mapping from task variables x to an output f(x), representing a target change in activity of a readout neuron, for example a Purkinje cell. The limited scope of this definition implies our results should not strongly depend on the influence of the readout neuron on downstream circuits."

8) The problem of these, in my impression, generic, arbitrary settings of the neurons and the network in the model becomes obvious here: ‘In contrast to the dense activity in cerebellar granule cells, odor responses in Kenyon cells, the analogs of granule cells in the Drosophila mushroom body, are sparse...’ How can this system be interpreted as an analogy to granule cells in the mammalian cerebellum when the model does not address the specifics lined up above? I.e. the ‘inductive bias’ that the authors speak of, defined as ‘the tendency of a network toward learning particular types of input-output mappings’, would be highly dependent on the specifics of the network model.

We agree with the Reviewer that our model makes several simplifying assumptions for mathematical tractability. However, we note that our study is not the first to draw analogies between cerebellum-like systems, including the mushroom body (Bell et al., 2008; Farris, 2011). All the systems we study feature a sparsely connected, expanded granule-like layer that sends parallel fiber axons onto densely connected downstream neurons known to exhibit powerful synaptic plasticity, thus motivating the key architectural assumptions of our model. We have constrained anatomical parameters of the model using data as available (Table 1). However, we agree with the Reviewer that when making comparisons across species there is always a possibility that differences are due to physiological mechanisms we have not fully understood or captured with a model. As such, we can only present a hypothesis for these differences. We have modified our Discussion section on this topic to clearly state this.

"Our results predict that qualitative differences in the coding levels of cerebellum-like systems, across brain regions or across species, reflect an optimization to distinct tasks (Figure 7). However, it is also possible that differences in coding level arise from other physiological differences between systems."

9) More detailed comments: Abstract: ‘In these models [Marr-Albus], granule cells form a sparse, combinatorial encoding of diverse sensorimotor inputs. Such sparse representations are optimal for learning to discriminate random stimuli.’ Yes, I would agree with the first part, but I contest the second part of this statement. I think what is true for sparse coding is that the learning of random stimuli will be faster, as in a perceptron, but not necessarily better. As the sparsification essentially removes information, it could be argued that the quality of the learning is poorer. So from that perspective, it is not optimal. The authors need to specify from what perspective they consider sparse representations optimal for learning.

This is an important point that we would like to clarify. It is not the case that sparse coding simply speeds up learning. In our study and many related works (Barak et al. 2013; Babadi and Sompolinsky 2014; Litwin-Kumar et al. 2017), learning performance is measured based on the generalization ability of the network – the ability to predict correct labels for previously unseen inputs. As our study and previous studies show, sparse codes are optimal in the sense that they minimize generalization error, independent of any effect on learning speed. To communicate this more effectively, we have added the following sentence to the first paragraph of the Introduction:

"Sparsity affects both learning speed (Cayco-Gajic et al., 2017), and generalization, the ability to predict correct labels for previously unseen inputs (Barak et al., 2013; Babadi and Sompolinsky, 2014; Litwin-Kumar et al., 2017)."

10) Introduction: ‘Indeed, several recent studies have reported dense activity in cerebellar granule cells in response to sensory stimulation or during motor control tasks (Knogler et al., 2017; Wagner et al., 2017; Giovannucci et al., 2017; Badura and De Zeeuw, 2017; Wagner et al., 2019), at odds with classic theories (Marr, 1969; Albus, 1971).’ In fact, this was precisely the issue that was addressed already by Jo¨rntell and Ekerot (2006) Journal of Neuroscience. The conclusion was that these actual recordings of granule cells in vivo provided essentially no support for the assumptions in the Marr-Albus theories.

In our reading, the main finding of J¨orntell and Ekerot (2006) is that individual granule cells are activated by mossy fibers with overlapping receptive fields driven by a single type of somatosensory input. However, there is also evidence of nonlinear mixed selectivity in granule cells in support of the re-coding hypothesis (Huang et al., 2013; Ishikawa et al., 2015). Jo¨rntell and Ekerot (2006) also suggest that the granule cell layer shares similar topographic organization as mossy fibers, organized into microzones. The existence of topographic organization does not invalidate Marr-Albus theories. As we have suggested earlier, a local combinatorial expansion can coexist with a global topographic organization.

We have described these considerations in the Assumptions and Extensions portion of the Discussion:

"Another key assumption concerning the granule cells is that they sample mossy fiber inputs randomly, as is typically assumed in Marr-Albus models (Marr, 1969; Albus, 1971; LitwinKumar et al., 2017; Cayco-Gajic et al., 2017). Other studies instead argue that granule cells sample from mossy fibers with highly similar receptive fields (Garwicz et al., 1998; Brown and Bower, 2001; J¨orntell and Ekerot, 2006) defined by the tuning of mossy fiber and climbing fiber inputs to cerebellar microzones (Apps et al., 2018). This has led to an alternative hypothesis that granule cells serve to relay similarly tuned mossy fiber inputs and enhance their signal-to-noise ratio (Jo¨rntell and Ekerot, 2006; Gilbert and Chris Miall, 2022) rather than to re-encode inputs. Another hypothesis is that granule cells enable Purkinje cells to learn piece-wise linear approximations of nonlinear functions (Spanne and J¨orntell, 2013). However, several recent studies support the existence of heterogeneous connectivity and selectivity of granule cells to multiple distinct inputs at the local scale (Huang et al., 2013; Ishikawa et al., 2015). Furthermore, the deviation of the predicted dimension in models constrained by electron-microscopy data as compared to randomly wired models is modest (Nguyen et al., 2022). Thus, topographically organized connectivity at the macroscopic scale may coexist with disordered connectivity at the local scale, allowing granule cells presynaptic to an individual Purkinje cell to sample heterogeneous combinations of the subset of sensorimotor signals relevant to the tasks that Purkinje cell participates in. Finally, we note that the optimality of dense codes for learning slowly varying tasks in our theory suggests that observations of a lack of mixing (J¨orntell and Ekerot, 2002) for such tasks are compatible with Marr-Albus models, as in this case nonlinear mixing is not required."

We have also included the Jo¨rntell and Ekerot (2006) study as a citation in the Introduction:

"Indeed, several recent studies have reported dense activity in cerebellar granule cells in response to sensory stimulation or during motor control tasks (Jo¨rntell and Ekerot, 2006; Knogler et al., 2017; Wagner et al., 2017; Giovannucci et al., 2017; Badura and De Zeeuw, 2017; Wagner et al., 2019), at odds with classic theories (Marr, 1969; Albus, 1971)."

11) Results: 1st para: There is no information about how the granule cells are modelled.

We agree that this should information should have been more readily available. We now more completely describe the model in the main text. Our model for granule cells can be found in Equation 1 in the Results section and also the Methods (Network Model):

"The activity of neurons in the expansion layer is given by: h = φ(Jeffx − θ), (2)

where φ is a rectified linear activation function φ(u) = max(u,0) applied element-wise. Our results also hold for other threshold-polynomial activation functions. The scalar threshold θ is shared across neurons and controls the coding level, which we denote by f, defined as the average fraction of neurons in the expansion layer that are active."

12) 2nd para: ‘A typical assumption in computational theories of the cerebellar cortex is that inputs are randomly distributed in a high-dimensional space.’ Yes, I agree, and this is in fact in conflict with the known topographical organization in the cerebellar cortex (see broader comment above). Mossy fiber inputs coding for closely related inputs are co-localized in the cerebellar cortex. I think for this model to be of interest from the point of view of the mammalian cerebellar cortex, it would need to pay more attention to this organizational feature.

As we discuss in our response to paragraphs 5 and 6, we see the random distribution assumption at the local scale (inputs presynaptic to a single Purkinje cell) as being compatible with topographic organization occurring at the microzone scale. Furthermore, as discussed earlier, we specifically model low-dimensional input as opposed to the random and high-dimensional inputs typically studied in prior models.

"A typical assumption in computational theories of the cerebellar cortex is that inputs are randomly distributed in a high-dimensional space (Marr, 1969; Albus, 1971; Brunel et al., 2004; Babadi and Sompolinsky, 2014; Billings et al., 2014; Litwin-Kumar et al., 2017). While this may be a reasonable simplification in some cases, many tasks, including cerebellumdependent tasks, are likely best-described as being encoded by a low-dimensional set of variables. For example, the cerebellum is often hypothesized to learn a forward model for motor control (Wolpert et al., 1998), which uses sensory input and motor efference to predict an effector’s future state. Mossy fiber activity recorded in monkeys correlates with position and velocity during natural movement (van Kan et al., 1993). Sources of motor efference copies include motor cortex, whose population activity lies on a low-dimensional manifold (Wagner et al., 2019; Huang et al., 2013; Churchland et al., 2010; Yu et al., 2009). We begin by modeling the low dimensionality of inputs and later consider more specific tasks. We therefore assume that the inputs to our model lie on a D-dimensional subspace embedded in the N-dimensional input space, where D is typically much smaller than N (Figure 1B). We refer to this subspace as the “task subspace” (Figure 1C)."

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Author Response

Reviewer #1 (Public Review):

This study combines in vitro somatic and dendritic recordings and computational modeling to study how cholinergic agonists modulate the response of CA1 pyramidal neurons to triangular current injections. The authors have previously used a similar approach (Upchurch, 2022, JNeuroscience) to show that CA1 neurons exhibit asymmetric AP firing (more firing on the upward ramp) in response to such current injections and that this effect is due to Na channel inactivation. The present work builds on these results by showing that cholinergic modulation changes this response, i.e., there is more firing on the downward part of the ramp. This change appears to require an intracellular Ca2+ concentration increase (mediated via IP3 and voltage-gated Ca2+ channels), which activates TRPM4 channels. In this scheme, cholinergic activity increases IP3, and the depolarizing current injection opens voltage-gated Ca2+ channels. This study will be of some interest to cellular neurophysiology experts working on the hippocampus.

1) This study claims that the triangular current injections recapitulate hippocampal place cell activity. However, it has been shown recently that the asymmetric firing of CA1 place cells is due to synaptic weight changes resulting from synaptic plasticity (e.g., Bittner et al., 2017). This suggests that the asymmetric firing of place cells is primarily the result of asymmetric synaptic input. Therefore, the authors should test whether carbachol similarly affects a synaptically driven membrane potential ramp. If this is not the case, the strong claim that this work has implications for place cell firing is not justified, in my opinion.

We have added the results showing the effects of cholinergic modulation on a synaptically-driven membrane potential ramp, obtained by electrically stimulating the Schaffer collaterals with a stimulation frequency that was adjusted according to a linear, symmetric ramp (see also Hsu et al, Neuron 99,147-162, 2018). These results have been added to the manuscript in the Results section for new Figure 2 (lines 169-197) and in the Methods section (lines 716-726).

2) Along the same lines, it has been shown before that the precision of spike timing depends on the stimulation pattern in vitro (Mainen and Sejnowski, 1995). Constant stimuli led to imprecise AP firing trains, whereas current injections that included fluctuations resembling synaptic input generated spike trains that were more reliable and reproducible in terms of timing. This study concluded that a low intrinsic noise level in spike generation was essential in generating informative spike sequences. Following this pivotal work, the authors could add noise to their current stimulus and observe the effect on the AP firing patterns. If this is not possible, the authors should at least report the sweep-to-sweep variability for the data shown, e.g., in panels 1A2, 1B2, 1D2, and 1E2.

We thank the reviewer for this suggestion to acknowledge the variability in the data across trials and we have added the Mainen and Sejnowski, 1995 citation to the manuscript (see Results lines 128-134). We addressed sweep-to-sweep variability among the various trials.

3) In most of the data presented in this manuscript, Carbachol appears to induce a 3 mV hyperpolarization and increase input resistance. As a result, the amount of current injected during Carbachol is drastically lower than during the controls. This should be emphasized more, and the input resistance should be quantified for each experimental condition. It should also be discussed whether this change in input resistance can account for the changes in the firing pattern observed. Finally, it should be clearly stated how the amount of the current injected was chosen for each cell, and data from a range of injected current ramps should be shown for each cell.

We thank the reviewers for this comment, which made us realize that our initial presentation was not clear, in particular with regard to the traces that were chosen as examples in the initial submission of the paper. We now clarify on page 5 (lines 113-125) of the manuscript as follows:

“In some trials, under control conditions, we applied a baseline depolarization prior to the ramp, in order to capture the variability observed in vivo (Harvey et al Nature 461:941–946, 2009; Epsztein et al. Neuron 70:109–120, 2011). Application of the cholinergic agonist carbachol (CCh, 2 µM) caused a depolarization of 2-6 mV. We compensated for this depolarization by injecting tonic hyperpolarizing current to reestablish the original membrane potential (see also Losonczy, et al., Nature 452, 436-442, 2008), as indicated by an offset from the 0 pA current level in the traces of the injected current ramps. The amplitude of background fluctuations in the resting membrane potential increased from a few tenths of a mV in control to 2-4 mV in CCh. Moreover, the threshold for action potential generation became more hyperpolarized. For all these reasons, we were not able to consistently vary the membrane potential using baseline depolarizations in the presence of CCh, because baseline depolarization alone frequently evoked spiking.”

For this reason, many of the carbachol example traces in the initial submission had more hyperpolarized Vm than their control counterparts. Acetylcholine also caused a depolarization in a dose-dependent manner, that was compensated for in the same way. In this new version of the manuscript, we systematically report the effects of cholinergic agonists on membrane potential and neuronal excitability. Further, we show example traces with resting membrane potentials within 1 mV for each pharmacological comparison, therefore removing this variable and hopefully making results clearer. We also now state how the amount of injected current was chosen for each condition, and that the amount of injected current was generally lower in the presence of cholinergic agonists. Both the tonic hyperpolarizing current and the amplitude of the injected ramp for each example can now be appreciated in each figure.

Finally, the reviewers’ comment also made us realize that, in principle, the center of mass of firing could be systematically skewed by the initial membrane potential, the amplitude of the current ramp injection and/or the input resistance. For this reason, we added a supplementary figure (1-2) where the adaptation index was plotted as a function of each these variables. In all cases, it is apparent that the main factor determining whether the center of mass of firing is shifted earlier or later in the ramp is the presence or absence of carbachol rather than initial membrane potential, current injection amplitude, or input resistance.

4) It remains unclear how the current result that TRPM4 channels can mediate the firing pattern change relates to the previous finding that the current injection evoked CA1 neuronal firing pattern is due to long-term Na channel inactivation.

We thank the reviewers for this suggestion, which helps to clarify our initial results. New Figure 8 addresses the connection between long-term inactivation of Na+ channels and the activation of TRPM4 channels, as characterized by the model (see Results lines 375-391). Furthermore, the model was instrumental in assessing how the Ca2+ and voltage-dependence of TRPM4 channels synergize to contribute to the shift in the center of mass of firing (Figure 9). Figure 9 illustrates the positive feedback loop between Ca2+ entry and the additional depolarization produced by Ca2+ activation of TRPM4 channels that can potentially accelerate firing (see Results lines 392-427).

5) Figure 8: Panel C is supposed to confirm the prediction from the model that the carbachol-mediated change of firing activity is related to intracellular Ca2+ domains. However, the example cell shown is depolarized to -52 mV, and there is no hyperpolarization following Carbachol. Is this an effect of the high concentration of BAPTA? Again, what was the current injected under this experimental condition?

Again, we thank the reviewer for pointing out the lack of clarity in the presentation of our results. We have now rewritten the results section for former Figure 8 (now Figure 10) to more clearly present these findings. The reviewer is correct that with the combination of 30 mM BAPTA + 10 nM free Ca2+ added to the intracellular solution (panel C of current Figure 10) the addition of carbachol did not change the membrane potential, as there were no changes in the holding current. Also, the amplitude of the ramp is comparable in control conditions and in the presence of carbachol under these conditions.

We have now added all these details in the Results section for figure 10C.

Reviewer #2 (Public Review):

The manuscript focuses on the cholinergic modulation of TRPM4 channels in the CA1 pyramidal neurons. The authors presented solid convincing evidence that TRPM4 but not TRPC channels are the Ca2+-activated nonselective cation channel in CA1 pyramidal neurons being modulated by activation of muscarinic receptors. Using bi-directional ramp protocol, the authors revealed that ACh modulation could lead to forward shifts in place field center of mass, whereas decreased ACh modulation could contribute to backward shifts. This represents a significant molecular/cellular finding that links neuromodulation of intrinsic properties to place field shifts, a phenomenon seen in vivo. The authors used a computational approach to model this CA1 neuron spiking to further reveal the mechanism.

To further improve the manuscript, I have the following suggestions/questions:

1) The triangular ramp stimulation (introduced by the same group; Upchurch et al., 2022) makes it possible to emulate the hill-shaped depolarization during place field firing. However, one concern is the time scale/duration of the ramp (2 sec) compared to the physiological pattern (100ms~200ms in the in vivo recording in freely moving rat, Epsztein et al., 2011). Using a longer ramp to generate more spikes for calculating the adaptation index is understandable. However, considering the Ca entry/accumulation during prolonged depolarization, repeating one set of experiments with a shorter ramp is crucial to verify the major findings.

When determining the duration of the current injections for our ramps, we relied on the data recorded in vivo in freely moving rats (Epsztein et al. Neuron 70:109–120, 2011) or in head-fixed mice running on spherical a treadmill immersed in virtual reality (Harvey et al Nature 461:941–946, 2009). In those papers, the voltage deflections are shown as a function of time, and gray bars or boxes represent the time the animals spend traversing the place field. We interpret those figures as showing that the hill-shaped depolarizations have variable durations, on the order of 1-20 s; we therefore think that our experiments with 2 and 10 second-long ramps cover a fair range of these durations. The place fields in Epsztein et al., 2011 were 4 cm long, and the authors give an example in Figure 3, in which the 2 meter track is traversed 1.5 times in 3 minutes. At that rate, the rat spent on average 2.4 seconds in each place field. We interpret the numerous shorter epochs of firing on the order of 100-200 ms shown Figure 2 in Epsztein et al. as the result of ongoing theta modulation within one overall depolarization during a single place field traversal. The following quote from that paper supports our interpretation “Some (Figure 2E, trace 1), but not all (trace 2), passes revealed spiking associated with a series of large (to ~-25 mV), long-lasting (~100 ms) depolarizations (Kandel and Spencer, 1961; Wong and Prince, 1978; Traub and Llinás, 1979; Takahashi and Magee, 2009) occurring rhythmically at ~4–5 Hz (theta frequency).” We thank the reviewer for pointing out these traces; our results are more directly applicable to the traces without theta modulation. Adding theta modulation is beyond the scope of this study but will be considered in future studies. Our average results in Figure 1 show that carbachol similarly affects 2 s and 10 s ramps, therefore we decided to present only the data on 2 second ramps for all the subsequent figures (see Results lines 156-157).

2) Strictly speaking, the term "Ca2+-induced Ca2+ release (CICR)" is only used in ER Ca2+ release via ryanodine receptors (RyR) rather than IP3Rs. The author should be careful since it is used in the abstract (Line 36). In addition, pharmacology inhibition experiments should be incorporated to further dissect the role of RyR-induced CICR.

We thank the reviewer for pointing out the possible confusion regarding the use of the term Ca2+-induced Ca2+ release (CICR) and we removed it from the text. Further, for this resubmission, we have pharmacologically dissected the role of IP3 vs ryanodine receptors in the cholinergic shift in the center of mass of firing due to the activation of TRPM4 channels, as suggested by the reviewer (see new Figure 6). To our surprise, neither the IP3R antagonist, Xestospongin C (1-2 µM), nor the RyR antagonist ryanodine (40 µM) were effective in preventing the cholinergic shift of the center of mass of firing when added to the intracellular solution (see Results lines 310-340).

3) Applying strong buffering BAPTA not only removed the IP3R-TRPM nanodomain but also hindered Ca entry via VGCC. To validate the role of ER Ca2+ release in regulating TRPM, depletion of ER Ca2+ pool with SERCA inhibitor (e.g. thapsigargin) would be a more direct way to test the model (also make sure to add TRPC inhibitor to avoid the store-operated Ca2+ entry).

We agree with the reviewer that 30 mM BAPTA also disrupts intracellular Ca2+ elevation via voltage-dependent Ca2+ channels on the neuronal membrane. Given that our experiments excluded a role of Ca2+ release from the intracellular stores (see below), our new model includes a nanodomain where, during cholinergic activation, the Ca2+ entry through VGCC is amplified to reach micromolar concentrations, through a currently unknown mechanism. As pointed out by the reviewer, the experimental results with 30 mM BAPTA support the existence of a nanodomain for the activation of TRPM4 channels, regardless of the nature of the calcium source.

We have also addressed the role of ER Ca2+ release in our experiments.

4) How does the TRPM current overcome the long-term inactivation of Nav? A channel state model should be added to the manuscript to make it easier to understand.

Figure 11C now shows the Markov model of the NaV channel and new Figure 8 is devoted to explaining the mechanism by which current through the TRPM4 channels overcomes the long-term inactivation of the NaV channel.

Reviewer #3 (Public Review):

Combining slice physiology and simulation, Combe and colleagues discovered that TRPM4 channels activated by Ca2+ in nanodomains mediate ICAN currents in CA1 pyramidal neurons that drive the cholinergic modulation of firing rate. The finding is novel and interesting.

Strengths:

1) Identification of TRPM4 channels as the carrier of ICAN currents with independent pharmacological inhibitors and other supporting evidence.

2) Physiological and simulational verification of physically closely located Ca2+ source and TRPM4 channels required for ICAN activation.

Weaknesses:

1) The conclusion of the cholinergic role in down-ramp or backward firing shifts is not convincing.

We agree with the reviewer that our interpretation is somewhat speculative, and we have now included disclaimers throughout the manuscript as well as placed most of these interpretations in a portion of the discussion titled “Ideas and speculations: Implications of our results for place fields in intact rodents”. In addition, we added the word “potential” in the title.

Author Response

Reviewer #1 (Public Review):

The manuscript by Masschelin et al. describes how Vitamin B2 deficiency affects body composition, energy expenditure, and glucose metabolism. B2 deficient mice have lower O2 consumption, and locomotor activity, with no difference in food intake. These mice also have lower liver FAD levels, which is expected given that B2 is a necessary cofactor for this coenzyme. Additionally, these mice have lower blood glucose levels following pyruvate injection, implying a lower capacity for gluconeogenesis. Using PPAR KO mice, they show that this effect on pyruvate tolerance is due to PPARα activation, though there is still a minor difference between wildtype and KO mice. Importantly, they show that fenofibrate PPAR agonism can improve glucose output following pyruvate injection in the absence of B2. The authors also perform robust metabolomics in each experimental condition and phenotype of the mouse well.

Thank you for the positive input.

1) The authors have yet to explore other explanations of differences in glucose metabolism under B2D +/Fenofibrate. The canonical targets of PPARα are involved in fatty acid oxidation, ketogenesis, and VLDL/HDL metabolism, in addition to gluconeogenesis (Bougarne et al. 2018). Gluconeogenesis is more of a fasting response due to CREB, FOXO1/PGC1a activation rather than PPAR. In response to B2D, the PPARα KO mice have increased plasma TGs, which may suggest a difference in VLDL TG secretion (Suppl. S3). Perhaps lipid metabolism is more directly affected, and changes in glucose metabolism are secondary to that of triglyceride metabolism. Regarding ketogenesis, the fenofibrate+ B2D fed mice have decreased plasma betahydroxybutyrate, suggesting decreased ketogenesis, which is a more canonical PPARα pathway (Suppl. S3). Testing each of these processes would help control that this mechanism is specific to gluconeogenesis and not secondary to something else.

We value this reviewer’s comment. To address this point, we considered other mechanisms in our revised Discussion. In future studies, we plan to further explore these metabolic effects and to use ATAC-Seq to understand the transcription factors responsive to B2D. We anticipate these studies will take additional years to complete. Nonetheless, the present studies set the foundation for future work to investigate how FAD influences transcriptional regulation of metabolism.

2) Is the effect on ISR dependent on PPARα? Is the mechanism of Fenofibrate on the liver, or on another cell type? In Figure 1, the authors state that Riboflavin deficiency alters body composition and energy expenditure, and then focuses on the liver. However, FAD levels are also increased in the heart and kidneys in addition to the liver. These tissues also respond to PPARα agonism, in addition to the muscle which plays a role in regulating glucose metabolism (B2D mice also have a higher lean mass (Fig 1e)). Additionally, the authors haven't shown specifically if the effects of Fenofibrate on electron transport and the ISR are dependent on the presence of PPARα (Figure 5, 6).

We agree that knowing whether the effects of Fenofibrate on the ISR require liver PPARA is a critical issue, which will require dedicated studies for a thorough and meaningful conclusion. In new experiments, we knocked down Ppara in the liver using AAV8-Cre administration to Pparaflox/flox mice. Our data show liver-specific Ppara knockdown recapitulates whole-body B2D effects on pyruvate tolerance and hepatic steatosis (Figure 3I). These results agree with findings in whole-body Ppara knockout mice (Supplemental Figure 4), reinforcing the idea that the direct impact of B2D mainly occurs via PPARA activity in the liver. We acknowledge in the discussion ATF4 and ISR activation may contribute to PPARA-independent responses to B2D (Biochem J 443:165–71, 2012; Gut 65:1202-1214, 2016).

An assessment of genetic requirements will require a large, rigorous set of experiments to identify the ratelimiting responses for fenofibrate activities during B2D, which we plan to do in the future. For this report, we decided to focus exclusively on tissue-specific knockout of Ppara. We will establish evidence for ISR responses to B2D in a separate study based on the feedback received here.

Reviewer #2 (Public Review):

The objective of this work by Masschelin et al. is to investigate the physiological relevance of flavin adenine dinucleotide (FAD). In particular, FAD supports the activity of flavoproteins involved in the production of cellular energy. Mutations in genes encoding flavoproteins often are associated with inborn errors of metabolism (IEMs), thus the clinical interest in investigating in more depth the physiological role of FAD. In this study, the authors first subjected male mice to a vitamin B12 deficient diet (B2D), demonstrating that loss of B12 replicates the phenotypes often observed with IEMs, including loss of body weight, hypoglycemia, and fatty liver. Using a combination of metabolomic phenotyping, transcriptomic analyses, and pharmacology (treatment with Fenofibrate, a PPARa agonist), the authors then reach the general conclusion that activation of the nuclear receptor PPARa can rescue the B2D phenotypes, thus revealing that PPARa directly controls the metabolic responses to FAD availability. Although the phenotypic analysis of the mice subjected to B2D increases our knowledge of the physiological impact of depleting the FAD pools on global energy metabolism, not all conclusions and statements made by the authors are totally supported by the data. In particular, the study is overall too descriptive and lacks mechanistic insights. While PPARa is likely an important player in the metabolic response to FAD availability, the molecular details on how FAD controls the activity of PPARa either directly or indirectly are entirely missing. Therefore, the authors are encouraged to directly assess whether B2D directly influences PPARa activity on the genes identified in the study, perform rescue experiments in the liver of PPARa KO mice and explore the possibility that other factors (including nuclear receptors) also participate in the response to B2 deficiency and diminished FAD pools.

We appreciate the input from Reviewer 2. The direct and indirect effects of B2D on PPARA activity are likely not trivial. However, we performed experiments to determine how FAD depletion affects PPARA transcriptional activity using the riboflavin analog and competitive inhibitor lumiflavin (Figure 3L). We found lumiflavin reduced PPRE-luciferase activity in the presence of PPARA agonist. Although the assay is a synthetic reporter expressed in vitro, the experiment provides evidence of how B2D influences PPARA transcriptional activity. And, yes, we agree that our manuscript does not completely reconcile the factor(s) explaining the effects of B2D on gene expression, and expanded the discussion to comment on this point. In future studies, we intend to identify which transcription factor(s) regulate the liver responses to B2D, and further elucidation of the molecular mechanisms will be a central objective of future work.

Author Response

Reviewer #1 (Public Review):

In this manuscript, Scagliotti and colleagues investigate the role of Dlk1 in regulating pituitary size in multiple mouse models with different Dlk1 gene dosages in order to understand the mechanisms of organ size control. They find that overexpression of Dlk1 leads to pituitary overgrowth and loss of Dlk1 causes undergrowth. Authors find two compartments of Dlk1 expression in the pituitary, in the marginal zone stem cell compartment and the parenchymal differentiated cell compartment, and by combing genetic mouse models show that a specific interaction of Dlk1 expression in both regions is necessary to affect pituitary organ size. They present to suggest that Dlk1 may repress Wnt signaling during development to control a shift from progenitor proliferation to differentiation. The data are meticulous, high quality, and clear.

I have some questions about the interpretation of their data regarding the mechanism of Dlk1 regulation of pituitary organ size, as I believe there could be potential alternative explanations for their observations:

I was wondering about the cause of the enlargement of the pituitary gland in Fig 1E, and whether it is caused by an increased number of cells (hyperplasia), an increased cell size (hypertrophy), or both. Line 104 states it is hyperplasia, and that cell size was not affected in WT-TG ('not shown', line 121). However, line 444 says the TG is hypertrophic. It would be good if the authors could elaborate on this and show or state how cell size was determined. Figs 5/6 show that WT-Tg proliferation is generally similar to WT, which suggests the increased size is not hyperplasia. It would be good to know whether this is correct. Some previous studies have shown that in pregnancy, lactotroph hypertrophy can be responsible for pituitary enlargement without hyperplasia (Castrique 2010, Hodson 2012).

We have now clarified this point throughout the manuscript. We had previously counted cells per field in the analysis shown in Figure 1D as a proxy for cell number (these did not significantly differ by genotype). We have now performed a more robust examination. Cell number was determined using a well-established stereological technique: For each animal the maximal cross-sectional area (CSA) was determined from the volumetric analysis. At this level 3 independent sections were used to measure anterior pituitary CSA and count haematoxilin-stained nuclei, giving a mean cells/CSA measurement per individual. This number was multiplied by the AP volume to give an estimate of cell number.

This analysis was performed on mice from the new cohort of animals containing litter matched adults of all 4 genotypes, and shown in Figure 4E. WT-TG animals had a significant increase in cell number compared to WT littermates (p = 0.0443), therefore pituitary expansion occurs by hyperplasia.

Related to the organ size question above, I had a question about the cell number and proportions in Fig 1D/E/F, which shows the maintenance of endocrine cell proportions and an increase in the volume of ~30% in WT-Tg. For the cell proportions to be maintained, I thought the increase in volume per cell type (Fig 1G) would therefore have to also increase proportionally in every cell type, while 1G appears to show an increase in GH (sig) and PRL/TSH cells (ns). It would be good if the authors could discuss this briefly.

We agree and indeed we see this trend across all cell types. When the data in Figure 1G is compared by 2-Way ANOVA we see a significant effect by cell type (p< 0.0001) and by genotype (p = 0.0009). However, for other hormone producing cells the effect size is does not overcome the variation in a smaller cell population so the difference between genotypes does not pass multiple significance testing with the relatively small sample size used. We have modified the legend to Figure 1G to make the ANOVA result clearer.

This study is impactful and will be of interest to several research communities, including those interested in pituitary development and function, organ size control, and gene imprinting mechanisms.

Reviewer #2 (Public Review):

Scagliotti et al address how organ size is regulated by imprinted genes. Using a series of mouse models to modulate the dosage of the paternally expressed gene, Dlk1, the authors demonstrate that DLK1 is important for the maintenance of the stem cell compartment leading to the growth of the pituitary gland and the expansion of growth hormone-producing cells. The authors show that overexpression of Dlk1 leads to pituitary hyperplasia while deletion of the paternal allele leads to reduced pituitary size. Reduced pituitary size is accompanied by reduced cell proliferation in the cleft at e13.5 and an increase in the number of POU1F1+ cells, suggesting that loss of Dlk1 alters the balance between the number of cells remaining in the replicating stem cell pool and those differentiating into the POU1F1 lineage. An elegant caveat of this paper is the rescue of Dlk1 expression in the population of cells expressing Pou1f1 but not in SOX2+ stem cells. Expression of Dlk1 only in POU1F1+ cells is not sufficient to rescue pituitary size. The authors suggest that this is because DLK1 must be present in stem cells which then activate paracrine WNT signaling to promote cell proliferation in POU1F1+ cells.

Strengths:

This is an important study that provides a mechanistic understanding of how the imprinted gene, Dlk1, regulates organ size. The study employs an elegant experimental design to address the dosage requirement for Dlk1 in regulating pituitary gland size. Rescuing Dlk1 in the POU1F1+ cells, but not the marginal zone SOX2+ cells provides intriguing results about a possible role for DLK1 in paracrine signaling between these different pituitary cell types. The study uses publicly available scRNAseq and ChIPseq data to further support their findings and identify Dlk1 as a likely target of POU1F1.

Weaknesses:

The study only analyzes females for the adult time point. For embryonic and postnatal time points sexes are pooled. Gender differences in pituitary gene expression embryonically or postnatally could potentially affect experimental outcomes.

We have now added adult data for both sexes.

The authors employ a mouse model that rescues Dlk1 expression starting at e15.5 in POU1F1+ parenchymal cells but not in marginal zone stem cells. Rescuing Dlk1 expression in a specific population of cells is one of the strengths of this study. Based on this information and the fact that overexpression of Dlk1 leads to increased pituitary size, the authors suggest that DLK1+ marginal zone stem cells and DLK+ parenchymal cells may interact to promote postnatal proliferation. However, the ability to more carefully parse out the complex spatial and temporal contributions of DLK1 to pituitary size would be enhanced by the addition of a mouse model that rescues Dlk1 expression only in SOX2+ cells and a model that rescues expression in both stem cells and POU1F1+ cells.

We agree that the addition of a model where Dlk1 is only expressed in SOX2+ cells would add significant mechanistic insight. To our knowledge an inducible gain-of-function Dlk1 model does not yet exist. Moreover, use of a SOX2-Cre driver would also increase Dlk1 expression in the hypothalamus as well as Rathke’s pouch, further complicating the analysis.

Author Response

Reviewer #1 (Public Review):

In this manuscript, Huang et al., assess cognitive flexibility in rats trained on an animal model of anorexia nervosa known as activity-based anorexia (ABA). For the first time, they do this in a way that is fully automated and free from experimenter interference, as apparently experimenter interference can affect both the development of ABA as well as the effect on behaviour. They show that animals that are more cognitively flexible (i.e. animals that had received reversal training) were better able to resist weight loss upon exposure to ABA, whereas animals exposed to ABA first show poorer cognitive flexibility (reversal performance).

Strengths:

• The development of a fully-automated, experimenter-free behavioural assessment paradigm that is capable of identifying individual rats and therefore tracking their performance.

• The bidirectional nature of the study - i.e. the fact that animals were tested for cognitive flexibility both before and after exposure to ABA, so that direction of causality could be established.

• The analyses are rigorous and the sample sizes sufficient.

• The use of touchscreens increases the translational potential of the findings.

Weaknesses

• Some descriptions of methods and results are confusing or insufficiently detailed.

We have been through all methods and results to include additional details as requested by this reviewer below.

It seems to me that performance on the pairwise discrimination task cannot be directly (statistically) compared to performance on reversal (as in Figure 4E), as these are tapping into fundamentally different cognitive processes (discrimination versus reversal learning). I think comparing groups on each assessment is valid, however.

We agree that discrimination and reversal are different cognitive processes, and statistical comparisons between these two components of the task were only made when examining the speed of learning in the validation of the novel testing system. Moreover, our inclusion of the pink and purple bars on graphs such as Figure 4C & 4E represent “main effects of ABA exposure”, regardless of learning phase (PD or reversal) rather than, as you describe, comparing PD to R1. Perhaps this comparison wasn’t clear, so we have amended the text to say ‘main effect of ABA exposure p=.0017’ rather than just “exposure”.

Not necessarily a 'weakness' but I would have loved to see some assessment of the alterations in neural mechanisms underlying these effects, and/or some different behavioural assessments in addition to those used here. In particular, the authors mention in the discussion that this manipulation can affect cholinergic functioning in the dorsal striatum We (Bradfield et al., Neuron, 2013) and a number of others have now demonstrated that cholinergic dysfunction in the dorsomedial striatum impairs a different kind of reversal learning that based on alterations in outcome identity and thus relies on a different cognitive process (i.e. 'state' rather than 'reward' prediction error). It would be interesting perhaps in the future to see if the ABA manipulation also alters performance on this alternative 'cognitive flexibility' task.

This is an excellent suggestion and we have already begun exploring this in other ongoing work in the laboratory. Due to ‘compulsive’ wheel running being a hallmark of ABA, we are interested in determining if this also translates to a goal-directed action impairment using the well-established outcome-specific devaluation task. Perhaps with ABA it may be more relevant to investigate outcome-reversals rather than stimulus-reversals, and if this is the case, it would further support the use of the ABA model for investigating cognitive dysfunction relevant to AN. We have included an additional section in the discussion text relating to our hypotheses regarding outcome-specific reversal learning in the ABA model.

Nevertheless, I certainly think the manuscript provides a solid appraisal of cognitive flexibility using more traditional tasks, and that the authors have achieved their aims. I think the work here will be of importance, certainly to other researchers using the ABA model, but perhaps also of translational importance in the future, as the causal relationship between ABA and cognitive inflexibility is near impossible to establish using human studies, but here evidence points strongly towards this being the case.

Reviewer #2 (Public Review):

Huang and colleagues present data from experiments assessing the role of cognitive inflexibility in the vulnerability to weight loss in the activity-based anorexia paradigm in rats. The experiments employ a novel in-home cage touchscreen system. The home cage touch screen system allows reduced testing time and increased throughput compared with the more widely used systems resulting in the ability to assess ABA following testing cognitive flexibility in relatively young female rats. The data demonstrate that, contrary to expectations, cognitive inflexibility does not predispose to greater ABA weight loss, but instead, rats that performed better in the reversal learning task lost more weight in the ABA paradigm. Prior ABA exposure resulted in poorer learning of the task and reversal. An additional experiment demonstrated that rats that had been trained in reversal learning resisted weight loss in the ABA paradigm. The findings are important and are clearly presented. They have implications for anorexia nervosa both in terms of potentially identifying those at risk also in understanding the high rates of relapse.

Thanks for a great summary of the manuscript.

Reviewer #3 (Public Review):

Activity-based anorexia (ABA), which combines access to a running wheel and restricted access to food, is a most common paradigm used to study anorexic behavior in rodents. And yet, the field has been plagued by persistent questions about its validity as a model of anorexia nervosa (AN) in humans. This group's previous studies supported the idea that the ABA paradigm captures cognitive inflexibility seen in AN. Here they describe a fully automated touchscreen cognitive testing system for rats that makes it possible to ask whether cognitive inflexibility predisposes individuals to severe weight loss in the ABA paradigm. They observed that cognitive inflexibility was predictive of resistance to weight loss in the ABA, the opposite of what was predicted. They also reported reciprocal effects of ABA and cognitive testing on subsequent performance in the other paradigm. Prior exposure to the ABA decreased subsequent cognitive performance, while prior exposure to the cognitive task promoted resistance to the ABA. Based on these findings, the authors argue that the ABA model can be used to identify novel therapeutic targets for AN.

The strength of this manuscript is primarily as a methods paper describing a novel automated cognitive behavioral testing system that obviates the need for experimentalist handling and single housing, which can interfere with behavioral testing, and accelerate learning on the task. Together, these features make it feasible to perform longitudinal studies to ask whether cognitive performance is predictive of behavior in a second paradigm during adolescence, a peak period of vulnerability for many psychiatric disorders. The authors also used machine learning tools to identify specific behaviors during the cognitive task that predicted later susceptibility to the ABA paradigm. While the benefits of this system are clear, the rigor and reproducibility of experiments using this paradigm would be enhanced if the authors provided clear guidelines about which parameters and analyses are most useful. In their absence, the large amount of data generated can promote p-hacking.

The authors use their automated behavioral testing paradigm to ask whether cognitive inflexibility is a cause or consequence of susceptibility to ABA, an issue that cannot be addressed in AN. They provide compelling evidence that there are reciprocal effects of the two behavioral paradigms, but do not perform the controls needed to evaluate the significance of these observations. For example, the learning task involves sucrose consumption and food restriction, conditions that can independently affect susceptibility to the ABA. Similarly, the ABA paradigm involves exercise and restricted access to food, which can both affect learning.

In the Discussion, the authors hypothesize that the ABA paradigm produces cognitive inflexibility and argue that uncovering the underlying mechanism can be used to identify new therapeutic targets for AN. The rationale for their claim of translational relevance is undermined by the fact that the biggest effect of the ABA paradigm is seen in the pair discrimination task, and not reversal learning. This pattern does not fit clinical observations in AN.

In summary, the significance of this manuscript lies in the development of a new system to test cognitive function in rats that can be combined with other paradigms to explore questions of causality. While the authors clearly demonstrate that cognitive flexibility does not promote susceptibility to ABA, the experiments presented do not provide a compelling case that their model captures important features of the pathophysiology of AN.

We thank the reviewer for this detailed review and note that we have now both explicitly defined the most useful parameters for analyses from the novel touchscreen system as well as removed some comparisons that could be considered superfluous. We argue that the additional information provided by the machine learning analyses are, at this stage, exploratory, and rather than reveal independent descriptions of behavioural change in ABA exposed versus naïve rats this information will aid in the generation of hypotheses to be tested in future studies. Therefore, the figures pertaining to these analyses have now been provided as supplements to Figures 3 & 4 (Figure 3-figure supplement 3; Figure 4-figure supplements 3&4). We have also clarified our intention to explore possible behavioural differences using this technique in the methods and discussion.

We have also completed the essential control experiment, defined in the “essential revisions” section of this review, whereby we show only moderate impairments in reversal learning following a matched period of food restriction without rapid weight loss, suggesting that the substantial impairment seen following ABA exposure was not due to food restriction alone (see updated Figure 4 and supplements).

However, we do not agree with this reviewer “that the biggest effect of the ABA paradigm is seen in the pair discrimination task” and point to the outcomes of both reciprocal experiments.

In the first experiment, rats that went onto be susceptible or resistant to ABA did not differ on pairwise discrimination learning but specifically on performance at the reversal of reward contingencies (Figure 3B & E). Although this result was not in the hypothesised direction, this suggests that reversal learning specifically and not pairwise discrimination can differentiate those rats that go on to be susceptible to weight loss. We have included additional discussion in the text related to this finding (see line 490-497).

In the second experiment, it is clear by the number of ABA exposed rats that were unable to learn the reversal component even after being able to learn pairwise discrimination, that flexible learning is more impaired by ABA. While it is true that ABA exposed rats that were successful in learning the reversal task were slower to learn the pairwise discrimination component than naïve rats (Figure 4E), this was not related to their ability to learn the reversal task overall – with equivalent learning rates in pairwise discrimination to ABA exposed rats that failed to learn the reversal component (Figure 4G-I). The absence of significant differences between ABA exposed and naïve animals in Figure 4F relates to the fact that the large proportion of ABA exposed animals never reached performance criterion in the reversal phase of the task and therefore data from these animals could not be included in the figure. This is where the trials completed within each session becomes important for interpretation (i.e. Figure 4-figure supplement 1M-O), whereby ABA exposure caused impaired responding specifically within the reversal phase of the task. The results text has been updated to better reflect this critical point.

Overall, this suggests that the impairment in cognitive flexibility caused by ABA exposure was related both to an associative learning impairment (slower to learn PD than naïve animals) and an impairment in the integration of new and existing learning (failure to learn R1 in a large proportion of animals).

Author Response

Reviewer #1 (Public Review):

Weaknesses

1) I was curious as to how novel this setup is. Although I do not do head-fixed research myself, I thought there were already some open-source, relatively cheap systems available. I'm not sure how the current setup differs from those already available. Personally, even if this system involves only the wheel turning, as this is a truly operant response, that is novel enough for my liking.

The novelty of the system stems from the synergistic combination of functionality, the low-cost open source nature of the design, and the breadth of behavioral procedures the system is able to support. The use of a wheel as an operant response was adapted from the International Brain Laboratory rig which has been used extensively for visual discrimination tasks. We adapted this wheel design to make the response closer to lever pressing through the use of the wheel brake, which ensures that subjects have to rotate the wheel in discrete rotational bouts rather than continuously spinning the wheel and potentially disengaging and allowing the wheel to rotate independently. There are no examples of systems capable of delivering 5+ solutions within a behavioral session or conducting valence testing with a modification of real-time place preference without the cost and complexity associated with virtual reality. We believe that the combination of factors, the flexibility and scalability of the system makes OHRBETS a novel and useful system for diverse motivation and consumption behaviors in head-fixed mice.

2) It would be useful to have a bit more detail in the manuscript (not just on the GitHub link - in supplemental material perhaps?) on how to build such a system, just to get a sense of how difficult building such a system might be and how many components it has.

With this submission we have included detailed assembly instructions as a supplement to the main manuscript and added reference to the file within the methods section. We have also added details, including time estimates, to the methods section.

3) I wasn't sure how to feel about the comparisons across experimental set-ups in Figures 2 and 3. Usually, these sorts of comparisons are not considered statistically valid due to the many variables that differ between set-ups. However, I do see that the intent here is a bit different - i.e. is to show that despite all these alterations in variables the behavioural outputs are still highly correlated. However, without commenting on this intent, I did find these comparisons a little jarring to read.

Thank you for highlighting this. We have added in a justification for why we measured the consistency in behavior measured with each head-fixed system.

4) The only dataset I was not wholly convinced by was that in Figure 3 (real-time place preference and aversion). I think the authors have done the best job that they can of replicating such a procedure in a head-fixed mouse, but the head-fixed version is going to necessarily differ from the freely moving version in a fundamental way when the contextual cues and spatial navigation form part of the RTPT task. Giving a discrete cue, such as a tone, just is not a sufficient substitute for contextual cues, and I think the two types of task would engage fundamentally different brain cells and circuits (e.g. only the free-moving version is likely to engage place cells in the hippocampus).

To avoid confusion regarding the place component of the real-time place preference assay name, we have renamed the head-fixed assay for assessing valence to Wheel-Time Preference (WTP). We have also added a full paragraph to the discussion where we outline the differences in the task requirements and relevant neuronal circuits between the freely-moving RTPP and head-fixed WTP. We understand that the head-fixed task is not a perfect analog of the RTPP task, however based on the similarity in the resulting time spent in the stimulation chamber/zone we believe that the WTP is able to replicate the valence assessment that many in the field uses RTPP to measure. We believe that the WTP with OHRBETS opens up new possibilities for assessing preference in head-fixed mice and this justifies keeping the figure within the main manuscript.

To thoroughly address the potential confound of spatial information during the multi-spout experiment, we have added an additional supplemental figure (Figure 4- figure supplement 5) that depicts the proportion of trials with licking and added a paragraph to the discussion centered on the potential confound associated with learning the solution identity.

5) Personally, I found having the statistics in a separate file confusing.

Thank you for raising this concern. With our initial submission, we were concerned that including all of the statistics within the main text would make the paper difficult to read due to the extensive amount of statistics. With this submission, in addition to the statistics table, we have included statistics within the figure legends and main text where applicable.

6) Line 589-594. Suggesting the medial/lateral shell recording results mean that the medial shell 'tracks value, and the range of values during the multi-spout consumption of gradients of NaCl is greater than the range of values during multi-spout consumption of gradients of sucrose" seems to engage in circular logic to me. That is, the authors should use behavioural data to infer what the animal is experiencing and whether it is a change in value, and/or a greater change in value during NaCl vs. sucrose consumption, and only then should they make an inference about what the larger medial shell response means.

Thank you for identifying this potential site of confusion. To address this concern we have modified the language to better communicate our interpretation of the data.

“If we assume that the range of values is greater during multi-spout consumption of gradients of NaCl compared to gradients of sucrose, as indicated by a greater range in licking behavior (Figure 8- Figure Supplement 4), then the greater range of dopamine release in the NacShM could imply that dopamine release in this structure tracks value.”

Author Response

Reviewer #1 (Public Review):

Wang, Y. et al. investigated the role of TPL2 signaling in acute and chronic neuroinflammatory conditions using small molecule inhibitors and a TPL2 kinase-dead mutant mouse line. They find that TPL2 is upregulated by various brain-resident cells, including microglia, astrocytes, and endothelial cells, during neurodegenerative disease progression and following peripheral LPS injection. They show that upon pharmacological and genetic inhibition during acute LPS stimulation, pro-inflammatory cytokine concentration, microgliosis, and neuronal loss can be reversed. In chronic neuroinflammation, as seen in a tauopathy mouse model, the loss of TPL2 rescues reactive gliosis, immune cell infiltration, neurodegeneration, and cognitive health. Interestingly, TPL2 loss of function was not significantly beneficial in models of nerve injury and stroke. By analyzing their multiple sequencing datasets and those of other research teams, the authors find that TPL2 aids to upregulate transcripts for the DAM signature, immediate early genes, and astrocyte reactivity. These data build together to further emphasize the intricacy and importance of the immune component in neurodegeneration and other neuroinflammatory conditions.

The conclusions of this paper are mostly well supported by their data, but further confirmation of sequencing results and microglia intrinsic mechanisms need to be expanded.

1) In the discussion section, it will be important to highlight that TPL2 could also be directly contributing to tauopathy disease progression through its actions in brain-resident endothelial cells. They spend a lot of time characterizing the effects of TPL2 on in vitro microglial responses and do not adequately discuss the potential that their disease phenotypes in the tauopathy model have more to do with TPL2's ability to regulate BBB permeability or facets of endothelial biology. It will be important to highlight that there are various discrete cellular mechanisms (e.g. functions for TPL2 in microglia, endothelial cells, astrocytes, peripheral immune cells, etc.) that could be underlying the disease readouts seen in their global TPL2 kinase-dead mice. They should discuss this in the context of previous literature demonstrating roles for TPL2 in other non-microglial cell types (e.g. Nanou et al PMID: 34038728).

Thank you for this comment. We agree that while TPL2 is most highly expressed in microglia in the brain, TPL2 expression in endothelial cells and other cell types could potentially contribute to the disease. We have added discussion of this to the manuscript including discussion of the Nanou et al paper which raises the possibility that the TPL2-dependent infiltration of peripheral immune cells in TauP301S mice could be due to regulation of the BBB by TPL2 activity in endothelial cells. We also discuss potential roles for TPL2 in the various other cell types. In addition, we have now added characterization of cell-autonomous TPL2-dependent phenotypes in cultured astrocytes and have provided additional analysis of TPL2-dependent changes in endothelial cells in the scRNAseq experiment in TauP301S mice.

2) Hippocampal single-cell RNA sequencing led the authors to report that TLP2KD in the PS19 model of tauopathy reduced the number of T-cell and dendritic cell (DC) infiltrates into the brain. The authors should corroborate this finding with immunohistochemistry or flow cytometry to confirm the presence of changing CD4+, CD8+, and DC populations. Most notably, it is critical for them to enumerate the cell numbers in an effort to validate that there are indeed empirical, and not just proportional, reductions in these cell populations.

Thank you for the suggestion. We have performed immunohistochemistry to examine T cells in fixed brain tissue sections. We have included the data for T cell staining in Figure 5-figure supplement 2. We focused the IHC analysis on staining for CD8+ T cells based on the substantially greater abundance of CD8+ T cells compared to CD4+ T cells or DC in the single cell data (Figure 5C, Figure 5-figure supplement 5) and the availability of an antibody that worked well in our hands. These results corroborate the single cell data by empirically showing significantly increased numbers of T cells in TauP301S mice and significantly reduced numbers in the TauP301S x TPL2KD mice (Figure 5-figure supplement 2).

3) The authors concluded from Figure 3 that TPL2 plays a key role in in vivo microglia and astrocyte activation. Adding in an in vitro study, like those done in Figures 1, 2, and S4, that looks at a cell-autonomous role for TPL2 in astrocyte reactivity would strengthen this claim and rule out a microglial-independent pathway of TPL2 inflammation.

Thank you for the suggestion. To investigate the potential cell-autonomous role of TPL2 in astrocytes, we cultured primary mouse astrocyte and stimulated astrocytes with either LPS or cytokines, in the absence or presence of TPL2 inhibitor and measured stimulation induced changes in cytokine release and gene expression. Data are included in Figure 3-figure supplement 1 and the results are discussed in the manuscript. In contrast to the broader TPL2-dependence of cytokine release by cultured microglia only a much more restricted set of cytokines exhibited TPL2-dependence in cultured astrocytes. Furthermore, RT-qPCR analysis of TPL2-dependent activated astrocyte genes identified in the LPS in vivo study found much less TPL2-dependent activation in cultured astrocytes. We discuss that these results suggest that the TPL2-dependent astrocyte activation observed in vivo was probably largely contributed to indirectly by the function of TPL2 in microglia, but there was also potentially some contribution of cell-autonomous function of TPL2 in astrocytes.

4) Although the TPL2KD mouse line is a valuable tool to impair TPL2's function while retaining its expression, the researchers failed to comment on the potential effects a global mutation in TPL2 could have in their model systems. Peripheral immunological challenges, like their IP injections of LPS, could behave differently and affect the nervous system in a microglia-independent pathway if monocyte/macrophage signaling is also impaired.

We agree that during peripheral immunological challenges TPL2 could affect the nervous system in a microglia-independent manner. We have added this point to the discussion.

5) Oligodendrocytes and OPCs have comparable numbers of DEGs to astrocytes (Figure S11a). What is changing within their transcriptional profile?

In this manuscript we focused on TPL2-dependent DEGs in the Tauopathy model, which were all in microglia. We agree the TPL2-independent changes in the TauP301S mice in other cell types are also interesting. This data set has been uploaded to public data repository (GSE180041) and analysis of the changes in oligodendrocytes has been performed from this data set, as well as other disease models, in a recent publication: “Disease-associated oligodendrocyte responses across neurodegenerative diseases” (PMID: 36001972).

Author Response

Reviewer #1 (Public Review):

Strengths

This paper is well situated theoretically within the habit learning/OCD literature. Daily training in a motor-learning task, delivered via smartphone, was innovative, ecologically valid and more likely to assay habitual behaviors specifically. Daily training is also more similar to studies with non-humans, making a better link with that literature. The use of a sequential-learning task (cf. tasks that require a single response) is also more ecologically valid. The in-laboratory tests (after the 1 month of training) allowed the researchers to test if the OCD group preferred familiar, but more difficult, sequences over newer, simpler sequences.

The authors achieved their aims in that two groups of participants (patients with OCD and controls) engaged with the task over the course of 30 days. The repeated nature of the task meant that 'overtraining' was almost certainly established, and automaticity was demonstrated. This allowed the authors to test their hypotheses about habit learning. The results are supportive of the authors' conclusions.

We truly appreciate the positive assessment of referee 1, particularly the consideration that our study is theoretically strong and that ‘the results are supportive of the authors' conclusions’. This is an important external endorsement of our conclusions, contrasting somewhat with the views of referee 2.

Weaknesses

The sample size was relatively small. Some potentially interesting individual differences within the OCD group could have been examined more thoroughly with a bigger sample (e.g., preference for familiar sequences). A larger sample may have allowed the statistical testing of any effects due to medication status.

The authors were not able to test one criterion of habits, namely resistance to devaluation, due to the nature of the task

We agree with the reviewer that the proof of principle established in our study opens new avenues for research into the psychological and behavioral determinants of the heterogeneity of this clinical population. However, considering the study timeline and the pandemic constraints, a bigger sample was not possible. Our sample can indeed be considered small if one compares it with current online studies, which do not require in-person/laboratory testing, thus being much easier to recruit and conduct. However, given the nature of our protocol (with 2 demanding test phases, 1-month engagement per participant and the inclusion of OCD patients without comorbidities only) and the fact that this study also involved laboratory testing, we consider our sample size reasonable and comparable to other laboratory studies (typically comprising on average between 30-50 participants in each group).

This article is likely to be impactful -- the delivery of a task across 30 days to a patient group is innovative and represents a new approach for the study of habit learning that is superior to an inlaboratory approach.

An interesting aspect of this manuscript is that it prompts a comparison with previous studies of goal-directed/habitual responding in OCD that used devaluation protocols, and which may have had their effects due to deficits in goal-directed behavior and not enhanced habit learning per se.

Thank you for acknowledging the impact of our study, in particular the unique ability of our task to interrogate the habit system.

Reviewer #2 (Public Review):

In this study, the researchers employed a recently developed smartphone application to provide 30 days of training on action sequences to both OCD patients and healthy volunteers. The study tested learning and automaticity-related measures and investigated the effects of several factors on these measures. Upon training completion, the researchers conducted two preference tests comparing a learned and unlearned action sequences under different conditions. While the study provides some interesting findings, I have a few substantial concerns:

1) Throughout the entire paper, the authors' interpretations and claims revolve around the domain of habits and goal-directed behavior, despite the methods and evidence clearly focusing on motor sequence learning/procedural learning/skill learning. There is no evidence to support this framing and interpretation and thus I find them overreaching and hyperbolic, and I think they should be avoided. Although skills and habits share many characteristics, they are meaningfully distinguishable and should not be conflated or mixed up. Furthermore, if anything, the evidence in this study suggests that participants attained procedural learning, but these actions did not become habitual, as they remained deliberate actions that were not chosen to be performed when they were not in line with participants' current goals.

We acknowledge that the research on habit learning is a topic of current controversy, especially when it comes to how to induce and measure habits in humans. Therefore, within this context referee’s 2 criticism could be expected. Across disQnct fields of research, different methodologies have been used to measure habits, which represent relaQvely stereotyped and autonomous behavioral sequences enacted in response to a specific sQmulus without consideraQon, at the Qme of iniQaQon of the sequence, of the value of the outcome or any representaQon of the relaQonship that exists between the response and the outcome. Hence these are sQmulus-bound responses which may or may not require the implementaQon of a skill during subsequent performance. Behavioral neuroscienQsts define habits similarly, as sQmulus-response associaQons which are independent of reward or outcome, and use devaluaQon or conQngency degradaQon strategies to probe habits (Dickinson and Weiskrantz, 1985; Tricomi et al., 2009). Others conceptualize habits as a form of procedural memory, along with skills, and use motor sequence learning paradigms to invesQgate and dissect different components of habit learning such as acQon selecQon, execuQon and consolidaQon (Abrahamse et al., 2013; Doyon et al., 2003; Squire et al., 1993). It is also generally agreed that the autonomous nature of habits and the fluid proficiency of skills are both usually achieved with many hours of training or pracQce, respecQvely (Haith and Krakauer, 2018).

We consider that Balleine and Dezfouli (2019) made an excellent attempt to bring all these different criteria within a single framework, which we have followed. We also consider that our discussion in fact followed a rather cautious approach to interpretation solely in terms of goaldirected versus habitual control.

Referee 2 does not actually specify criteria by which they define habits and skills, except for asserting that skilled behavior is goal-directed, without mentioning what the actual goal of the implantation of such skill is in the present study: the fulfillment of a habit? We assume that their definition of habit hinges on the effects of devaluation, as a single criterion of habit, but which according to Balleine and Dezfouli (2019) is only 1 of their 4 listed criteria. We carefully addressed this specific criterion in our manuscript: “We were not, however, able to test the fourth criterion, of resistance to devaluation. Therefore, we are unable to firmly conclude that the action sequences are habits rather than, for example, goal-directed skills. Regardless of whether the trained action sequences can be defined as habits or goal-directed motor skills, it has to be considered…”. Therefore, we took due care in our conclusions concerning habits and thus found the referee’s comment misleading and unfair.

We note that our trained motor sequences did in fact fulfil the other 3 criteria listed by Balleine and Dezfouli (2019), unlike many studies employing only devaluation (e.g. Tricomi et al 2009; Gillan et al 2011). Moreover, we cited a recent study using very similar methodology where the devaluation test was applied and shown to support the habit hypothesis (Gera et al., 2022).

Whether the initiation of the trained motor sequences in experiment 3 (arbitration) are underpinned by an action-outcome association (or not) has no bearing on whether those sequences were under stimulus-response control after training (experiment 1). Transitions between habitual and goal-directed control over behavior are quite well established in the experimental literature, especially when choice opportunities become available (Bouton et al (2021), Frölich et al (2023), or a new goal-directed schemata is recruited to fulfill a habit (Fouyssac et al, 2022). This switching between habits and goal-directed responding may reflect the coordination of these systems in producing effective behavior in the real world.

• Fouyssac M, Peña-Oliver Y, Puaud M, Lim NTY, Giuliano C, Everitt BJ, Belin D. (2021).Negative Urgency Exacerbates Relapse to Cocaine Seeking After Abstinence. Biological Psychiatry. doi: 10.1016/j.biopsych.2021.10.009

• Frölich S, Esmeyer M, Endrass T, Smolka MN and Kiebel SJ (2023) Interaction between habits as action sequences and goal-directed behavior under time pressure. Front. Neurosci. 16:996957. doi: 10.3389/fnins.2022.996957

• Bouton ME. 2021. Context, attention, and the switch between habit and goal-direction in behavior. Learn Behav 49:349– 362. doi:10.3758/s13420-021-00488-z

2) Some methodological aspects need more detail and clarification.

3) There are concerns regarding some of the analyses, which require addressing.

We thank referee 2 for their detailed review of the methods and analyses of our study and for the helpful feedback, which clearly helps improve our manuscript. We will clarify the methodological aspects in detail and conduct the suggested analysis. Please see below our answers to the specific points raised.

Introduction:

4) It is stated that "extensive training of sequential actions would more rapidly engage the 'habit system' as compared to single-action instrumental learning". In an attempt to describe the rationale for this statement the authors describe the concept of action chunking, its benefits and relevance to habits but there is no explanation for why sequential actions would engage the habit system more rapidly than a single-action. Clarifying this would be helpful.

We agree that there is no evidence that action sequences become habitual more readily than single actions, although action sequences clearly allow ‘chunking’ and thus likely engage neural networks including the putamen which are implicated in habit learning as well as skill. In our revised manuscript we will instead state: “we have recently postulated that extensive training of sequential actions could be a means for rapidly engaging the ‘habit system’ (Robbins et al., 2019)]”

5) In the Hypothesis section the authors state: “we expected that OCD patients... show enhanced habit attainment through a greater preference for performing familiar app sequences when given the choice to select any other, easier sequence”. I find it particularly difficult to interpret preference for familiar sequences as enhanced habit attainment.

We agree that choice of the familiar response sequence should not be a necessary criterion for habitual control although choice for a familiar sequence is, in fact, not inconsistent with this hypothesis. In a recent study, Zmigrod et al (2022) found that 'aversion to novelty' was a relevant factor in the subjective measurement of habitual tendencies. It should also be noted that this preference was present in patients with OCD. If one assumes instead, like the referee, that the familiar sequence is goal-directed, then it contravenes the well-known 'egodystonia' of OCD which suggests that such tendencies are not goal-directed.

To clarify our hypothesis, we will amend the sentence to the following: “Finally, we expected that OCD patients would generally report greater habits, as well as attribute higher intrinsic value to the familiar app sequences manifested by a greater preference for performing them when given the choice to select any other, easier sequence”.

A few notes on the task description and other task components:

6) It would be useful to give more details on the task. This includes more details on the time/condition of the gradual removal of visual and auditory stimuli and also on the within practice dynamic structure (i.e., different levels appear in the video).

These details will be included in the revised manuscript. Thank you for pointing out the need for further clarification of the task design.

7) Some more information on engagement-related exclusion criteria would be useful (what happened if participants did not use the app for more than one day, how many times were allowed to skip a day etc.).

This additional information will be added to the revised manuscript. If participants omitted to train for more than 2 days, the researcher would send a reminder to the participant to request to catch up. If the participant would not react accordingly and a third day would be skipped, then the researcher would call to understand the reasons for the lack of engagement and gauge motivation. The participant would be excluded if more than 5 sequential days of training were missed. Only 2 participants were excluded given their lack of engagement.

8) According to the (very useful) video demonstrating the task and the paper describing the task in detail (Banca et al., 2020), the task seems to include other relevant components that were not mentioned in this paper. I refer to the daily speed test, the daily random switch test, and daily ratings of each sequence's enjoyment and confidence of knowledge.

If these components were not included in this procedure, then the deviations from the procedure described in the video and Banca al. (2020) should be explicitly mentioned. If these components were included, at least some of them may be relevant, at least in part, to automaticity, habitual action control, formulation of participants' enjoyment from the app etc. I think these components should be mentioned and analyzed (or at least provide an explanation for why it has been decided not to analyze them).

This is also true for the reward removal (extinction) from the 21st day onwards which is potentially of particular relevance for the research questions.

The task procedure was indeed the same as detailed in Banca et al., 2020. We did not include these extra components in this current manuscript for reasons of succinctness and because the manuscript was already rather longer than a common research article, given that we present three different, though highly inter-dependent, experiments in order to answer key interrelated questions in an optimal manner. However, since referee 2 considers this additional analysis to be important, we will be happy to include it in the supplementary material of the revised manuscript.

Training engagement analysis:

9)I find referring to the number of trials including successful and unsuccessful trials as representing participants "commitment to training" (e.g. in Figure legend 2b) potentially inadequate. Given that participants need at least 20 successful trials to complete each practice, more errors would lead to more trials. Therefore, I think this measure may mostly represent weaker performance (of the OCD patients as shown in Figure 2b). Therefore, I find the number of performed practice runs, as used in Figure 2a (which should be perfectly aligned with the number of successful trials), a "clean" and proper measure of engagement/commitment to training.

We acknowledge referee’s concern on this matter and agree to replace the y-axis variable of Figure 2b to the number of performed practices (thus aligning with Figure 2a). This amendment will remove any potential effect of weaker performance on the engagement measurement and will provide clearer results.

10) Also, to provide stronger support for the claim about different diurnal training patterns (as presented in Figure 2c and the text) between patients and healthy individuals, it would be beneficial to conduct a statistical test comparing the two distributions. If the results of this test are not significant, I suggest emphasizing that this is a descriptive finding.

We will conduct the statistical test and report accordingly.

Learning results:

11) When describing the Learning results (p10) I think it would be useful to provide the descriptive stats for the MT0 parameter (as done above for the other two parameters).

Thank you for pointing this out. The descriptive stats for MT0 will be added to the revised version of the manuscript.

12) Sensitivity of sequence duration and IKI consistency (C) to reward:

I think it is important to add details on how incorrect trials were handled when calculating ∆MT (or C) and ∆R, specifically in cases where the trial preceding a successful trial was unsuccessful. If incorrect trials were simply ignored, this may not adequately represent trial-by-trial changes, particularly when testing the effect of a trial's outcome on performance change in the next trial.

This is an important question. Our analysis protocol was designed to ensure that incorrect trials do not contaminate or confound the results. To estimate the trial-to-trial difference in ∆MT (or C) and ∆R, we exclusively included pairs of contiguous trials where participants achieved correct performance and received feedback scores for both trials. For example, if a participant made a performance error on trial 23, we did not include ∆R or ∆MT estimates for the pairs of trials 23-22 and 24-23. Instead of excluding incorrect trials from our analyses, we retained them in our time series but assigned them a NaN (not a number) value in Matlab. As a result, ∆R and ∆MT was not defined for those two pairs of trials. Similarly for C. This approach ensured that our analyses are not confounded by incremental or decremental feedback scores between noncontiguous trials. In the past, when assessing the timing of correct actions during skilled sequence performance, we also considered events that were preceded and followed by correct actions. This excluded effects such as post-error slowing from contaminating our results (Herrojo Ruiz et al., 2009, 2019). Therefore, we do not believe that any further reanalysis is required.

• Ruiz MH, Jabusch HC, Altenmüller E. Detecting wrong notes in advance: neuronal correlates of error monitoring in pianists. Cerebral cortex. 2009 Nov 1;19(11):2625-39.

• Bury G, García-Huéscar M, Bhattacharya J, Ruiz MH. Cardiac afferent activity modulates early neural signature of error detection during skilled performance. NeuroImage. 2019 Oct 1;199:704-17.

13) I have a serious concern with respect to how the sensitivity of sequence duration to reward is framed and analyzed. Since reward is proportional to performance, a reduction in reward essentially indicates a trial with poor performance, and thus even regression to the mean (along with a floor effect in performance [asymptote]) could explain the observed effects. It is possible that even occasional poor performance could lead to a participant demonstrating this effect, potentially regardless of the reward. Accordingly, the reduced improvement in performance following a reward decrease as a function of training length described in Figure 5b legend may reflect training-induced increased performance that leaves less room for improvement after poor trials, which are no longer as poor as before. To address this concern, controlling for performance (e.g., by taking into consideration the baseline MT for the previous trial) may be helpful. If the authors can conduct such an analysis and still show the observed effect, it would establish the validity of their findings."

Thank you for raising this point. Figure 5b illustrates two distinct effects of reward changes on behavioral adaptation, which are expected based on previous research.

I. Practice effects: Firstly, we observe that as participants progress across bins of practice, the degree of improvement in behavior (reflected by faster movement time, MT) following a decrease in reward (∆R−) diminishes, consistent with our expectations based on previous work. Conversely, we found that ∆MT does not change across bins of practices following an increase in reward (∆R+). We appreciate the reviewer's suggestion regarding controlling for the reference movement time (MT) in the previous trial when examining the practice effect in the p(∆T|∆R−) and p(∆T|∆R+) distributions. In the revised manuscript, we will conduct the proposed control analysis to better understand whether the sensitivity of MT to score decrements changes across practice when normalising MT to the reference level on each trial. But see below for a preliminary control analysis.

II. Asymmetry of the effect of ∆R− and ∆R+ on performance: Figure 5b also depicts the distinct impact of score increments and decrements on behavioural changes. When aggregating data across practice bins, we consistently observed that the centre of the p(∆T|∆R−) distribution was smaller (more negative) than that of p(∆T|∆R+). This suggests that participants exhibited a greater acceleration following a drop in scores compared to a relative score increase, and this effect persisted throughout the practice sessions. Importantly, this enhanced sensitivity to losses or negative feedback (or relative drops in scores) aligns with previous research findings (Galea et al., 2015; Pekny et al., 2014; van Mastrigt et al., 2020).

We have conducted a preliminary control analysis to exclude the potential impact that reference movement time (MT) values could have on our analysis. We have assessed the asymmetry between behavioural responses to ∆R− and ∆R+ using the following analysis: We estimated the proportion of trials in which participants exhibited speed-up (∆T < 0) or slow-down (∆T > 0) behaviour following ∆R− and ∆R+ across different practice bins (bins 1 to 4). By discretising the series of behavioural changes (∆T) into binary values (+1 for slowing down, -1 for speeding up), we can assess the type of changes (speed-up, slow-down) without the absolute ∆T or T values contributing to our results. We obtained several key findings:

• Consistent with expectations (sanity check), participants exhibited more instances of speeding up than slowing down across all reward conditions.

• Participants demonstrated a higher frequency of speeding up following ∆R− compared to ∆R+, and this asymmetry persisted throughout the practice sessions (greater proportion of -1 events than +1 events). 53% events were speed-up events in the in the p(∆T|∆R+) distribution for the first bin of practices, and 55% for the last bin. Regarding p(∆T|∆R-), there were 63% speed-up events throughout each bin of practices, with this proportion exhibiting no change over time.

• Accordingly, the asymmetry of reward changes on behavioural adaptations, as revealed by this analysis, remained consistent across the practice bins.

Thus, these preliminary findings provide an initial response to referee 2 and offer valuable insights into the asymmetrical effects of positive/negative reward changes on behavioural adaptations. We plan to include these results in the revised manuscript, as well as the full control analysis suggested by the referee. We will further expand upon their interpretation and implications.

14) Another way to support the claim of reward change directionality effects on performance (rather than performance on performance), at least to some extent, would be to analyze the data from the last 10 days of the training, during which no rewards were given (pretending for analysis purposes that the reward was calculated and presented to participants). If the effect persists, it is less unlikely that the effect in question can be attributed to the reward dynamics.

The reviewer’s concern is addressed in the previous quesQon. Also, this analysis would not be possible because our Gaussian fit analyses use the Qme series of conQnuous reward scores, in which ∆R− or ∆R+ are embedded. These events cannot be analyzed once reward feedback is removed because we do not have behavioral events following ∆R− or ∆R+ anymore.

15) This concern is also relevant and should be considered with respect to the sensitivity of IKI consistency (C) to reward. While the relationship between previous reward/performance and future performance in terms of C is of a different structure, the similar potential confounding effects could still be present.

We will conduct this analysis for the revised manuscript, similarly to the control analysis suggested by referee 2 on MT. Our preliminary control analysis, as explained above, suggests that the fundamental asymmetry in the effect of ∆R+ and ∆R+ on behavioral changes persists when excluding the impact of reference performance values in our Gaussian fit analysis.

16) Another related question (which is also of general interest) is whether the preferred app sequence (as indicated by the participants for Phase B) was consistently the one that yielded more reward? Was the continuous sequence the preferred one? This might tell something about the effectiveness of the reward in the task.

We have now conducted this analysis. There is in fact no evidence to conclude that the continuously rewarded sequence was the preferred one. The result shows that 54.5% of HV and 29% of the OCD sample considered the continuous sequence to be their preferred one. Of note, this preference may not necessarily be linked to the trial-by-trial reward sensitive analysis. The latter assesses how learning may be affected by reward. The overall preference may be influenced by many other factors, such as, for example, the aesthetic appeal of particular combinations of finger movements.

Regarding both experiments 2 and 3:

17) The change in context in experiment 2 and 3 is substantial and include many different components. These changes should be mentioned in more detail in the Results section before describing the results of experiments 2 and 3.

Following referee’s advice, we will move these details (currently written in the Methods section) to the Results section, when we introduce Phase B and before describing the results of experiments 2 and 3.

Experiment 2:

18) In Experiment 2, the authors sometimes refer to the "explicit preference task" as testing for habitual and goal-seeking sequences. However, I do not think there is any justification for interpreting it as such. The other framings used by the authors - testing whether trained action sequences gain intrinsic/rewarding properties or value, and preference for familiar versus novel action sequences - are more suitable and justified. In support of the point I raised here, assigning intrinsic rewarding properties to the learned sequences and thereby preferring these sequences can be conceptually aligned with goal-directed behavior just as much as it could be with habit.

We clearly defined the theoretical framing of experiment 2 as a test of whether trained action sequences gain intrinsic value and we are pleased to hear that the referee agrees with this framing. If the referee is referring to the paragraph below (in the Discussion), we actually do acknowledge within this paragraph that a preference for the trained sequences can either be conceptually aligned with a habit OR a goal-directed behavior.

“On the other hand, we are describing here two potential sources of evidence in favor of enhanced habit formation in OCD. First, OCD patients show a bias towards the previously trained, apparently disadvantageous, action sequences. In terms of the discussion above, this could possibly be reinterpreted as a narrowing of goals in OCD (Robbins et al., 2019) underlying compulsive behavior, in favor of its intrinsic outcomes”

This narrowing of goals model of OCD refers to a hypothetically transiQonal stage of compulsion development driven by behavior having an abnormally strong, goal-directed nature, typically linked to specific values and concerns.

If the referee is referring to the penulQmate sentence of hypothesis secQon, this has been amended in response to Q5. We cannot find any other possible instances in this manuscript stating that experiment 2 is a test of habitual or goal-directed behavior.

Experiment 3:

19) Similar to Experiment 2, I find the framing of arbitration between goal-directed/habitual behavior in Experiment 3 inadequate and unjustified. The results of the experiment suggest that participants were primarily goal-directed and there is no evidence to support the idea that this reevaluation led participants to switch from habitual to goal-directed behavior.

Also, given the explicit choice of the sequence to perform participants had to make prior to performing it, it is reasonable to assume that this experiment mainly tested bias towards familiar sequence/stimulus and/or towards intrinsic reward associated with the sequence in value-based decision making.

This comment is aligned with (and follows) the referee’s criticism of experiment 1 not achieving automatic and habitual actions. We have addressed this matter above, in response 1 to Referee 2.

Mobile-app performance effect on symptomatology: exploratory analyses:

20) Maybe it would be worth testing if the patients with improved symptomatology (that contribute some of their symptom improvement to the app) also chose to play more during the training stage.

We have conducted analysis to address this relevant question. There is no correlation between the YBOCS score change and the number of total practices, meaning that the patients who improved symptomatology post training did not necessarily chose to play the app more during the training stage (rs = 0.25, p = 0.15). Additionally, we have statistically compared the improvers (patients with reduced YBOCS scores post-training) and the non-improvers (patients with unchanged or increased YBOCS scores post-training) in their number of app completed practices during the training phase and no differences were observed (U = 169, p = 0.19).

Discussion:

21) Based on my earlier comments highlighting the inadequacy and mis-framing of the work in terms of habit and goal-directed behavior, I suggest that the discussion section be substantially revised to reflect these concerns.

We do not agree that the work is either "inadequate or mis-framed" and will not therefore be substantially revising the Discussion. We will however clarify further the interpretation we have made and make explicit the alternative viewpoint of the referee. For example, we will retitle experiment 3 as “Re-evaluation of the learned action sequence: possible test of goal/habit arbitration” to acknowledge the referee’s viewpoint as well as our own interpretation.

22) In the sentence "Nevertheless, OCD patients disadvantageously preferred the previously trained/familiar action sequence under certain conditions" the term "disadvantageously" is not necessarily accurate. While there was potentially more effort required, considering the possible presence of intrinsic reward and chunking, this preference may not necessarily be disadvantageous. Therefore, a more cautious and accurate phrasing that better reflects the associated results would be useful.

We recognize that the term "disadvantageously" may be semantically ambiguous for some readers and therefore we will remove it.

Materials and Methods:

23) The authors mention: "The novel sequence (in condition 3) was a 6-move sequence of similar complexity and difficulty as the app sequences, but only learned on the day, before starting this task (therefore, not overtrained)." - for the sake of completeness, more details on the pre-training done on that day would be useful.

Details of the learning procedure of the novel sequence (in condition 3, experiment 3) will be provided in the methods of the revised version of the manuscript.

Minor comments:

24) In the section discussing the sensitivity of sequence duration to reward, the authors state that they only analyzed continuous reward trials because "a larger number of trials in each subsample were available to fit the Gaussian distributions, due to feedback being provided on all trials." However, feedback was also provided on all trials in the variable reward condition, even though the reward was not necessarily aligned with participants' performance. Therefore, it may be beneficial to rephrase this statement for clarity.

We will follow this referee’s advice and will rephrase the sentence for clarity.

25) With regard to experiment 2 (Preference for familiar versus novel action sequences) in the following statement "A positive correlation between COHS and the app sequence choice (Pearson r = 0.36, p = 0.005) further showed that those participants with greater habitual tendencies had a greater propensity to prefer the trained app sequence under this condition." I find the use of the word "further" here potentially misleading.

The word "further" will be removed.

Author Response

eLife assessment

This study assesses homeostatic plasticity mechanisms driven by inhibitory GABAergic synapses in cultured cortical neurons. The authors report that up- or down-regulation of GABAergic synaptic strength, rather than excitatory glutamatergic synaptic strength, is critical for homeostatic regulation of neuronal firing rates. The reviewers noted that the findings are potentially important, but they also raised questions. In particular, the evidence supporting the findings is currently incomplete and demonstration of independent regulation of mEPSCs and mIPSCs is a necessary experiment to support the major claims of the study.

We appreciate the detailed, thoughtful assessment of our paper by the reviewers and editors and will submit a revised version in the future that addresses the reviewers’ comments as detailed below in response to each concern. We will include a more open discussion of alternative possibilities. Further, we will repeat the optogenetic experiments assessing AMPAergic scaling in our mouse cortical cultures in order to demonstrate independent regulation of mEPSCs and mIPSCs as suggested.

Reviewer #1 (Public Review):

In the manuscript titled "GABAergic synaptic scaling is triggered by changes in spiking activity rather than transmitter receptor activation," the authors present an investigation of the role of GABAergic synaptic scaling in the maintenance of spike rates in networks of cultured neurons. Their main findings suggest that GABAergic scaling exhibits features consistent with a key homeostatic mechanism that contributes to the stability of neuronal firing rates. Their data demonstrate that GABAergic scaling is multiplicative and emerges when postsynaptic spike rates are altered. Finally, their data suggest that, in contrast to their prior data on glutamatergic scaling, GABAergic scaling is driven by spike rates. The authors set the paper up as an argument that GABAergic scaling, rather than glutamatergic scaling, serves as the critical homeostatic mechanism for spike rate regulation.

While the paper is ambitious in its rhetorical scope and certainly presents intriguing findings, there are several serious concerns that need to be addressed to substantiate the interpretations of the data. For example, the CTZ data do not support the interpretations and conclusions drawn by the authors. Summarily, the authors argue that GABAergic scaling is measuring spiking (at the time scale of the homeostatic response, which they suggest is a key feature of a homeostat) yet their data in figure 5B show more convincingly that CTZ does not influence spiking levels - only one out of four time points is marginally significant (also, I suspect that the bootstrapping method mentioned in line 454-459 was conducted as a pairwise comparison of distributions. There is no mention of multiple comparisons corrections, and I have to assume that the significance at 3h would disappear with correction).