Reviewer #3 (Public Review):

In this paper, Toschi et al. performed dMRI to in vivo estimate axon diameter in the brain and demonstrated that multi-compartmental modeling (AxCaliber) is sensitive to microstructural axonal damage in rats and axon caliber increase in demyelinating lesions in MS patients, suggesting that axon diameter mapping provides a potential biomarker to bridge the gap between medical imaging contrasts and biological microstructure. In particular, authors injected ibotenic acid (IBO) and saline in the left and right rat hippocampus, respectively, and compared in vivo estimated axon diameter and ex vivo neurofilament staining in left and right fimbria. The axon size estimation was larger in the fimbria of IBO injection side, where the neurofilament intensity is higher. Correlation of axon size estimation and neurofilament intensity was observed in both injection sides. Further, higher axon diameter estimation was observed in normal appearing white matter (NAWM) of MS patients, compared with the healthy subjects. The axon size estimation increased in hypointense lesions of T1 weighted contrast, but not in isointense lesions. Through the comparison of dMRI-estimated axon size and histology-based fluorescence intensity, authors indirectly validated the sensitivity of axon diameter mapping to the tissue microstructure in the rat brain, and further explored the axon size change in the brain of MS patients. However, the dMRI protocol and biophysical modeling in this study were not fully optimized to maximize the sensitivity to axon size estimation, and the dMRI-estimated axon size (4.4-5.4 micron) was much larger than values reported in previous histological studies (0.5-3 micron) [Barazany et al., Brain 2009]. Finally, although the modified AxCaliber model incorporated two fiber bundles in different directions, the fiber dispersion in each bundle was not considered (c.f. fiber dispersion ~20-30 degree in corpus callosum), potentially leading to overestimated axon diameter.

The conclusions in this study are supported by experimental results. However, the dMRI protocol and biophysical model could be further optimized and validated:<br /> 1. To in vivo estimate the axon diameter ~1 micron using dMRI, strong diffusion weighting (b-value) should be applied to maximize the signal decay due to intra-axonal restricted diffusion and minimize the signal contribution of extra-cellular hindered diffusion. However, authors only applied maximal b-value = 4000 s/mm2, much smaller than values ~15,000-20,000 s/mm2 in previous studies [Assaf et al., MRM 2008; Huang et al., BSAF 2020, 225:1277]. The use of low diffusion weighting in this study leads to a lower bound ~4-6 micron for accurate diameter estimation, the so-called resolution limit in [Nilsson et al., NMR Biomed 2017, 30:e3711]. In other words, the estimated axon diameter is potentially overestimated and related with the imaging protocol and image quality, confounding the biological interpretation.<br /> 2. In this study, the positive correlation of dMRI-estimated axon size and neurofilament fluorescence intensity is indeed an encouraging result, and yet this validation is indirect since it relies on the positive correlation between neurofilament intensity and axon diameter in histology.<br /> 3. Authors did not consider the fiber dispersion in the proposed dMRI model. This can lead to overestimated axon diameter, even in the highly aligned WM, such as corpus callosum with ~20-30 degree dispersion in histology [Ronen et al., BSAF 2014, 219:1773; Leergaard et all, PLoS One 2010, 5(1), e8595] and MRI [Dhital et al., NeuroImage 2019, 189, 543; Novikov et al., NeuroImage 2018, 174:518].

Reviewer #1 (Public Review):

1. My primary concern relates to how meaningful the human-rodent comparisons are, and whether these comparisons really advance our understanding of AxCaliber estimates in MS.

I applaud the aim to conduct "matched" experiments in both rodent models and human disease. It is a strength that the experiments are aligned with respect to the MRI measurements (although there are some caveats to this mentioned below). But beyond that, the overlap is not what one might hope for: the pathology would seem to be very distinct in humans and rodents, and the histological validation is not specific to what the MRI measurements claim to estimate.

To summarize the main findings: (i) in a rat model of general axonal degeneration, axon calibre estimates correlate with neurofilaments; (ii) in MS in humans, axon calibre estimates correlate with demyelinating lesions. This gives a picture of AxCalibre estimates correlating with neuropathology, but is this something that has not already been established in the literature?

If the aim is to validate AxCaliber, then there is a logic in using a rodent model that isolates alterations to axonal radius, but what then does this add to the existing literature in that space? If the aim is to study MS (for which AxCaliber results have been previously reported in Huang et al), then why not use a rodent model of MS?

2. I appreciate that both rodent and patient studies are time intensive, major endeavors. Neverthless, the number of subjects is very low in both rodent (n=9) and human (MS=10, control=6) studies. At the very least, this should be more openly acknowledged. But I'm concerned that this is a major weakness of the paper. Related to this, I find it hard to tell how carefully multiple comparison correction was performed throughout. It seems reasonably clear for the TBSS analyses, but then other analyses were performed in ROIs. Are these multiple comparisons corrected as well? Similarly, in Methods, I am confused by the statement that: "post hoc t tests corrected for multiple comparisons whenever a significant effect was detected". What does this mean?

3. While I do not think the text is in any sense deliberately misleading, I think the authors would do well to either tone down their claims or consider more carefully the implications of the text in many places. Some that stuck out for me are:

(a) Throughout, language in the paper (e.g., "Paired t tests were used to assess differences in the axonal diameter") presumes that the AxCaliber estimates specifically reflect axon diameter. I think the jury is out over whether this is true, particularly for measurements conducted with limited hardware specs. At the very least, I would encourage the author to refer to these measurements throughout as "estimates" of axon diameter.

(b) The authors suggest that their results provide "new tools for patient stratification" based on differences in lesion type, but it isn't clear what new information these markers would confer given that the lesions are differentiated based on T1w hypo/hyperintensities. In other words, these lesions are by definition already differentiable from a much simpler MRI marker.

(c) The authors note in the Discussion that: "sensitive to early stages of axonal degeneration, even before alterations in the myelin sheet are detected". Whether intentional or not, the implication in the context of this study is that this would hold for MS (that these markers would detect axonal degeneration preceding demyelination). While there is some discussion of alterations to axonal diameter in MS, the authors do not discuss whether these are the same mechanisms thought to occur in the IBO intervention used here.

(d) In the Discussion, the authors note the lack of evidence for a relationship with disability or disease duration, but nevertheless, go on to interpret the "trends" they do observe. I would advise strongly against this: the authors acknowledge that their numbers are low, so I would avoid the temptation to speculate here.

(e) In the Discussion state that "the use of neurofilaments has also been well validated in MS". Well validated for what? MS is a complex disease with a broad range of pathology, so this statement could be read to mean "neurofilaments are known to be altered in MS". However, in the context of this paragraph, the implication would seem to be that neurofilaments are a well-established proxy for axonal diameter. Is that the implication, and if so what general evidence is there for this?

Reviewer #2 (Public Review):

Diffusion MRI is sensitive to the brain microstructure, and it has been used to assess the integrity of white matter for nearly 3 decades. Its main limitation is the limited specificity, which makes it difficult to link changes in diffusion parameters to a given pathological substrate. Recently methods based on diffusion MRI that enable the estimation of axonal diameter, non invasively, have become available. This paper aims at validating one of such methods using an experimental model of neurodegeneration. The authors found a significant correlation between axonal diameter estimated by MRI and an histological marker of neurodegeneration. Although this is of great interest, as it demonstrates that this method is sensitive to neurodegeneration, a direct validation would require a measurement of axonal diameter using electron or confocal microscopy, rather than a correlation with a measure of axonal degeneration not directly related to axonal diameter. So, although these data are compelling, they do not prove that the increase in axonal diameter suggested by diffusion MRI corresponds to actual axonal swelling. The Authors also apply the same method to compare the white matter of patients with multiple sclerosis (MS) and healthy controls, showing widespread increases in axonal diameter in the patients. These data are compelling, but again, not conclusive. Other factors such as gloss could bias the MRI measurement and lead to an apparent increase in axonal diameter.

Reviewer #3 (Public Review):

This study examined the changes in fear response, as measured by the flight initiation distances (FID), of birds living in urban areas. The authors examined the FIDs of birds during the pandemic (COVID-19 lockdown restrictions) compared to FIDs measured before the pandemic (mostly in 2018 & 2019). The main study justification was that human presence changed drastically during the pandemic lockdowns and the change in human presence might have influenced the fear response of birds as a result of changing the "landscape of fear". Human presence was quantified using a 'stringency' index (government-mandated restrictions). Urban areas were selected from within five different cities, which included four European cities (Czech Republic - Prague, Finland - Rovaniemi, Hungary - Budapest, Poland - Poznan), and one city in the global south (Australia - Melbourne). Using 6369 flight initiation distances across 147 different bird species, the authors found that FIDs were not significantly different before the pandemic versus during the pandemic, nor was the variation in FID explained by the level of 'stringency'.

Major strengths: There are several strengths to this study that allows for understanding the variety of factors that influence a bird's response to fear (measured as flight initiation distances). This study also demonstrates that FIDs are highly variable between species and regions.<br /> Specifically,<br /> 1) One of the major strengths of this paper is the focus on birds living in urban areas, a habitat type that is hypothesized to have changed drastically in the 'landscape of fear' experienced by animals during the pandemic lockdown restrictions (due to the presumed decrease in human presence and densities). Maintaining the focus on urban birds allowed for a deeper examination of the effect of human behaviour changes on bird behaviour in urban habitats, which are at the interface of human-wildlife interactions.<br /> 2) This study accounted for several variables that are predicted to influence flight initiation distances in birds including species, genus, region (country), variability between years, pandemic year (pre- versus during), the strictness of government-mandated lockdown measures, and ecological factors such as the human observer starting distance, flock size, species-specific body size, ambient air temperature (also a proxy of the timing during the breeding season), time of day, date of data collection (timing within the regional [Europe or Australia] breeding season), and categorization of urban site type (e.g. park, cemetery, city centre).<br /> 3) This study examined FIDs in two years previous to the pandemic (mostly 2018 and 2019, one site was 2014) which would account for some of the within- and between-year FID variation exhibited prior to the pandemic.<br /> 4) This study uses strong statistical approaches (mixed effect models) which allows for repeat sampling, and a post hoc analysis testing for a phylogenetic signal.

Major weaknesses: The authors used government 'stringency' as a proxy for human presence and densities, however, this may not have been an accurate measure of actual human presence at the study sites and during measurements of FIDs. Furthermore, although the authors accounted for many factors that are predicted to influence fear response and FIDs in birds, there are several other factors that may have contributed to the high level of variation and patterns in FIDS observed during this study, thus resulting in the authors' conclusion that FIDs did not vary between pre- and during pandemic years.<br /> Specifically,<br /> 1) The authors used "government stringency" as a measure of change in human activity, which makes the assumption that the higher the level of 'stringency', the fewer humans in urban areas where birds are living. However, the association between "stringency" and actual human presence at the study sites was not measured, nor was 'stringency' compared to other measures of human presence such as human mobility.<br /> 2) There was considerable variation in FID measurements, which can be seen in the figures, indicating that most of the variation in FID was not accounted for in the authors' models. Factors that may have contributed to variation in FIDs that were not accounted for in this study are as follows:<br /> a. The authors accounted for the date of data collection using the 'day' since the start of the general region's breeding season (Europe: Day 1 = 1 April; Australia: Day 1 = 15 August). Using 'day' since the breeding season started probably was an attempt to quantify the effect of the breeding stage (e.g. territory establishment, nest young, fledgling) on FIDs. However, breeding stages vary both within- and between species, as well as between sub-regions (e.g. Finland vs. Hungary). As different species respond to predation or human presence differently depending on the stage during their breeding cycle, more specificity in the breeding cycle stage may allow for explaining the observed variation and patterns in FID.<br /> b. Variation in species-specific FIDs may also vary with habitat features within urban sites, such as the proximity of trees and other protective structures (e.g. perches and cover), the openness of the area, and the level of stressors present (e.g. noise pollution, distance to roads). Perhaps accounting for this habitat heterogeneity would account for the FID variation measured in this study.<br /> c. The authors accounted for species and genus within their models, however, FIDs may vary with other species-specific (or even specific populations of a species) characteristics such as whether the species/population is neophobic versus neophilic, precocial versus altricial, and the level of behavioural plasticity exhibited. These variables were not accounted for in the analysis.<br /> d. Three different methods of measuring the distances between flight and the observer location were used, and FIDs were only measured once per bird, such that there were no measures of repeatability for a test subject. Thus, variation surrounding the measurement of FIDs would have contributed to the variation in FIDs seen during this study.<br /> 3) The sample design of this study may have influenced the FID variability associated with specific species, and specific populations of species. A different number of species were sampled across the time periods of interest; 68 species were sampled before the pandemic versus 135 species after the pandemic. However, the authors do not appear to have directly compared the FIDs for the same species before the pandemic compared to during the pandemic (e.g. the FIDs of Eurasian blackbirds before the pandemic versus during the pandemic). Furthermore, within the same country-city, it is unclear whether the species observed before the pandemic were observed at the same location (e.g. same habitat type such as the same park) during the pandemic. As a species' FID response may be influenced by population characteristics and features specific to each site (e.g. habitat openness), these factors may have influenced the variability in FID measurements in this study.<br /> 4) The models in this study accounted for many factors predicted to affect FIDs (see the section on major strengths), however, the number of fixed and random factors are large in number compared to the total sample size (N =6369), such that models may have been over-extended.

Overarching main conclusion<br /> Overall, this study examines factors influencing FIDs in a variety of bird species and concludes that FIDs did not differ during the pandemic lockdowns compared to before the pandemic (2019 and earlier). Furthermore, FIDs were not influenced by the strictness of government-mandated restrictions. Although the authors accounted for many factors influencing the measurement of FIDs in birds, the authors did not achieve their aim of disentangling the effects of pandemic-specific ecological effects from ecological effects unrelated to the pandemic (such as habitat heterogeneity). Their findings indicate that FIDs are highly variable both within- and between- species, but do not strongly support the conclusion that FIDs did not change in urban species during the pandemic lockdown. Therefore, this study is of limited impact on our understanding of how a drastic change in human behaviour may impact bird behaviour in urban habitats. Overall, the study demonstrates the challenges in using FIDs as a general fear response in birds, even during a pandemic lockdown when fewer humans are presumably present, and this study illustrates the large degree of variation in FIDs in response to a human observer.

Reviewer #1 (Public Review):

This paper uses a series of flight initiation "challenges" conducted both prior to and during COVID-19-related restrictions on human movement to estimate the degree to which avian escape responses to humans changed during the "anthropause". This technique is suitable for understanding avian behavioral responses with a high degree of repeatability. The study collects an impressive dataset over multiple years across five cities on two continents. Overall the study finds no effect of lockdown on avian escape distance (the distance at which the "target" individual flees the approaching observer). The study considers the variable of interest as both binary (during lockdown or prior to lockdown) and continuous, using the Oxford Stringency Index (with neither apparently affecting escape distance).

Overall this paper presents interesting results which may suggest that behavioral responses to humans are rather inflexible over "short" (~2 year) timespans. The anthropause represents a unique opportunity to disentangle the mechanistic drivers of myriad hypothesized impacts humans have on the behavior, distribution, and abundance of animals. Indeed, this finding would provide important context to the larger body of literature aimed at these ends. However, the paper could do more to carefully fit this finding into the broader literature and, in so doing, be a bit more careful about the conclusions they are able to draw given the study design and the measures used. Taking some of these points (in no particular order):

1) Oxford Stringency Index is a useful measure of governmental responses to the pandemic and it's true that in some scenarios (including the (Geng et al. 2021) study cited by this paper) it can correlate with human mobility. However, it is far from a direct measure of human mobility (even in the Geng study, to my reading, the index only explained a minority of the variation). Moreover, particular sub-components of the index are wholly unrelated to human mobility (e.g., would changes to a country's public information campaign lead to concomitant changes in urban human mobility?). Finally, compliance with government restrictions can vary geographically and over time (i.e., we might expect lower compliance in 2021 than in 2020) and the index is calculated at the scale of entire countries and may not be very reflective of local conditions. Overall this paper could do more to address the potential shortcomings of the Oxford Stringency Index as a measure of human mobility including attempting to validate the effect on human mobility using other datasets (e.g., the google dataset and/or those discussed in (Noi et al. 2022). This is of critical importance since the fundamental logic of the experimental design relies on the assumption that stringency ~ mobility.

2) The interpretation of the primary finding (that behavioral responses to humans are inflexible) could use a bit more contextualization within the literature. Specifically, the study offers three potential explanations for the observed invariance in escape response: 1) these behaviors are consistent within individuals and this study provides evidence that there was no population turnover as a result of lockdowns; 2) escape response is linked to other urban adaptations such that to be an urban-dwelling species dictates escape response; and/or 3) these populations already exhibit maximum habituation and the reduction in human mobility would only have increased that habituation but that trait is already at a boundary condition. Some comments on each of these respectively:

a) Even had these populations turned over as a result of a massive rural-to-urban dispersal event, it's not clear that the escape distance in those individuals would be different because this paper does not establish that these hypothetical rural birds have a different behavioral response which would be constant following dispersal. Thus the evidence gathered here is insufficient to tell us about possible relocations of the focal species. Additionally, the paper cites several papers that found no changes in abundance or movements of animals in response to lockdowns but ignore others that do. For example: (Wilmers et al. 2021), (Warrington et al. 2022) (though this may have been published after this was submitted...), and (Schrimpf et al. 2021). There is a missed opportunity to consider the drivers of some of these results - the findings in this paper are interesting in light of studies that *did* observe changes in space use or abundance - i.e., changes in space use could arise precisely *because* responses to humans are non-plastic but the distribution and activities of humans changed. To wit, the primary finding here would imply that the reaction norm to human presence is apparently fixed over such timescales - however, and critically, the putative reduction in human activity/mobility combined with fixed responses at the individual level might then imply changes in avian abundance/movement/etc.

b) If this were the case, wouldn't this be then measurable as a function of some measure of urbanity (e.g. Human Footprint Index) that varies across the cities included here? Site accounted for ~15% of the total variation in escape distance but was treated as a random effect - perhaps controlling for the nature of the urban environment using some e.g., remotely sensed variable would provide additional context here.

c) Because it's not clear the extent to which the populations tested had turned over between years, the paper could do with a bit more caution in interpreting these results as behavioral. This study spans several years so any response (or non-response) is not necessarily a measure of behavioral change because the sample at each time point could (likely does) represent different individuals. In fact, there may be an opportunity here to leverage the one site where pre-pandemic measures were taken several years prior to the pandemic. How much variance in the change in escape distance is observed when the gap between time points far exceeds the lifetime of the focal taxa versus measures taken close in time?

d) Finally, I think there are a few other potential explanations not sufficiently accounted for here:

i) These behaviors might indeed be plastic, but not over the timescales observed here.<br /> ii) Time of year - this study took place during the breeding season. The focal behavior here varies with the time of year, for example, escape distance for many of these species could be tied up in nest defense behaviors, tradeoffs between self-preservation and e.g., nest provisioning, etc.<br /> iii) Escape behaviors from humans are adaptively evolved, strongly heritable, and not context dependent - thus we would only expect these behaviors to change on evolutionary timescales.<br /> iv) See point one above - it's possible that the lockdown didn't modify human activity sufficiently to trigger a behavioral response or that the reaction norm to human behavior is non-linear (e.g. a threshold effect).

LITERATURE CITED<br /> Geng DC, Innes J, Wu W, Wang G. 2021. Impacts of COVID-19 pandemic on urban park visitation: a global analysis. J For Res 32:553-567. doi:10.1007/s11676-020-01249-w

Noi E, Rudolph A, Dodge S. 2022. Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework. Int J Geogr Inf Sci.

Schrimpf MB, Des Brisay PG, Johnston A, Smith AC, Sánchez-Jasso J, Robinson BG, Warrington MH, Mahony NA, Horn AG, Strimas-Mackey M, Fahrig L, Koper N. 2021. Reduced human activity during COVID-19 alters avian land use across North America. Sci Adv 7:eabf5073. doi:10.1126/sciadv.abf5073

Warrington MH, Schrimpf MB, Des Brisay P, Taylor ME, Koper N. 2022. Avian behaviour changes in response to human activity during the COVID-19 lockdown in the United Kingdom. Proc Biol Sci 289:20212740. doi:10.1098/rspb.2021.2740

Wilmers CC, Nisi AC, Ranc N. 2021. COVID-19 suppression of human mobility releases mountain lions from a landscape of fear. Curr Biol 31:3952-3955.e3. doi:10.1016/j.cub.2021.06.050

Reviewer #2 (Public Review):

Mikula et al. have a large experience studying the escape distances of birds as a proxy of behavioral adaptation to urban environments. They profited from the exceptional conditions of social distance and reduced mobility during the covid-19 pandemic to continue sampling urban populations of birds under exceptional circumstances of low human disturbance. Their aim was to compare these new data with data from previous "normal" years and check whether bird behavior shifted or not as a consequence of people's lockdown. Therefore, this study would add to the growing body of literature assessing the effect of the covid-19 shutdown on animals. In this sense, this is not a novel study. However, the authors provide an interesting conclusion: birds have not changed their behavior during the pandemic shutdown. This lack of effects disagrees with most of the previously published studies on the topic. I think that the authors cannot claim that urban birds were unaffected by the covid-19 shutdown. I think that the authors should claim that they did not find evidence of covid-19-shutdown effects. This point of view is based on some concerns about data collection and analyses, as well as on evolutionary and ecological rationale used by the authors both in their hypotheses and results interpretation. I will explain my criticisms point by point:

1) The authors used ambivalent, sometimes contradictory, reasoning in their predictions and results interpretation. Some examples:<br /> 1.1) The authors claimed that urban birds perceive humans as harmless (L224), but birds actually escape from us, when we approach them... Furthermore, they escape usually 5 to 20 m away. This is more distance that would be necessary just to be not trampled.<br /> 1.2) If we are harmless, why birds should spend time monitoring us as a potential threat (L102)? Indeed, I disagree with the second prediction of the authors. I could argue that reduced human activity should increase animal vigilance because real bird predators (e.g., raptors) may increase their occurrence or activity in empty cities. If birds should increase their vigilance because the invisible shield of human fear of their predators is no longer available, then I would expect longer escape distances.<br /> 1.3) To justify the same escape behavior shown by birds in pre- and pandemic conditions from an adaptive point of view, the authors argued a lack of plasticity and a strong genetic determination of such behavior. This contravenes the plasticity proposed in the previous point or the expected effect of the stringency index (L112). In my opinion, some degree of plasticity in the escape behavior would be really favorable for individuals from an adaptive perspective, as they may face quite different fear landscapes during their lives. Looking at the figures, one can see notable differences in the escape distance of the same species between sites in the same city. As I can hardly imagine great genetic differences between birds sampled in a park or a cemetery in Rovaniemi, for instance, I would expect a major role of plasticity to explain the observed variability. Furthermore, if escape behavior would not be plastic, I would not expect date or hour effects. By including them in their models, the authors are accepting implicitly some degree of plasticity.

2) Looking at the figures I do not see the immense stochasticity (L156, Fig. S3, S5) claimed by the authors. Instead, I can see that some species showed an obvious behavioral change during the shutdown. For instance, Motacilla alba, Larus ridibundus, or Passer domesticus clearly reduced their escape distances, while others like the Dendrocopos major, Passer montanus, or Turdus merula tended to increase it. On the other hand, birds in Poland tended to have larger escape distances during the shutdown for most species, while in Rovaniemi there was an apparent reduction of escape distances in most cases. The multispecies and multisite approach is a strength of this study, but it is an Achilles' heel at the same time. The huge heterogeneity in bird responses among species and sites counterbalanced and as a result, there was an apparent lack of shutdown effects overall. Furthermore, as most data comes from a few (European) species (i.e., Columba, Passer, Parus, Pica, Turdus, Motacilla) I would say that the overall results are heavily influenced (or biased) by them. The authors realize that results are often area- or species-specific (L203), therefore, does a whole approach make sense?

3) The previous point is worsened by the heterogeneity of cities and periods sampled. For instance:<br /> 3.1) I can hardly imagine any common feature between a small city in northern Finland (Rovaniemi) and a megacity in Australia (Melbourne). Thus, I would not be surprised to find different results between them.<br /> 3.2) Prague baseline data was for 2014 and 2018, while for the rest of the study sites were for 2018 and 2019. If study sites used a different starting point, you cannot compare differences at the final point.<br /> 3.3) Due to the obvious seasonal differences between the northern and southern hemispheres, data collection in Australia began five months later than in the rest of the sites (Aug vs Mar 2020). There, urban birds faced already too many months of reduced human disturbances, while European birds were sampled just at the beginning of the lockdown.<br /> 3.4) Some cities were sampled by a single observer, while others by many of them. Even if all of them are skilled birders, they represent different observers from a statistical point of view and consequently, observer identity was an extra source of noise in your data that you did not account for.

4) Although I liked the stringency index as a variable, I am not sure if it captured effectively the actual human activity every day. Even if restrictive measures were similar between countries, their actual accomplishment greatly depended on people's commitment and authorities' control and sanctions. I would suggest using a more realistic measure of human activity, such as google mobility reports.

5) The authors used escape trials from birds on the ground and perched birds. I think that they are not comparable, as birds on the ground probably perceive a greater risk than those placed some meters above the ground, i.e. I would expect shorter escape distances for perched birds. As this can be strongly dependent on the species preferences or sampling site (i.e, more or less available perches), I wonder how this mixture of observations from birds on the ground and perched birds could be affecting the results.

6) The authors did not sample the same location in the same breeding season to avoid repeated sampling of the same individuals (L331). This precaution may help, but it does not guarantee a lack of pseudoreplication. Birds are highly mobile organisms and the same individuals may be found in different places in the same city. This pseudoreplication seems particularly plausible for Rovaniemi, where sampling points must be necessarily close due to the modest size of this city.

7) An intriguing result was that the authors collected data for 135 species during the shutdown, while they collected data only for 68 species before the pandemic. Such a two-fold increase in bird richness would not be expected with a 36% increase in sampling effort during 2020-21. I wonder if this could be reflecting an actual increase in bird richness in urban areas as a positive result of the shutdown and reduced human presence.

8) The authors dismissed the multicollinearity problem of explanatory variables unjustifiably (L383). However, looking at fig. S1, I can see strong correlations between some of them. For instance, period and stringency index were virtually identical (r=0.95), while temperature and date were also strongly correlated.

9) The random structure of the models is a key element of the statistical analyses but those random factors are poorly explained and justified. I needed to look up the supplementary tables to fully understand the complex architecture of the random part of the models. To the best of my knowledge, random variables aim to account for undesirable correlations in the covariance matrix, which is expected in hierarchical designs, such as the present one. However, the theoretical violation of data independence may happen or not. As the random structure is usually of little interest, you should keep it as simple as necessary, otherwise random factors may be catching part of data variability that you would like to explain by fixed variables. I think that this is what is happening (at least, in part) here, as the authors included a too-complex random structure. For instance, if you include the year as a random factor, I think that you are leaving little room for the period effect. The authors simplified the random structure of the models (L387), but they did not explain how. Nevertheless, this model selection was not important at all, as the authors showed the results for several models. I assume, consequently, that the authors are considering all these models equally valid. This approach seems quite contradictory.

Reviewer #1 (Public Review):

The authors managed to show the broad botanical landscape and not only the main crops. This unique achievement is based on decades of establishing an excellent collection of a full comparative seed collection of the current flora. This allows the identification of species that usually are not identifiable. The authors were able to compare the crops that were grown there and identify the contribution of the Roman period with that of the Arab one. This excellent study is a landmark in how such studies should be done. The list of identified species will be used for many other studies on this subject.

Reviewer #2 (Public Review):

Fuks et al. provide extensive paleobotanical data from several sites in the Negev desert to address hypotheses regarding the relative importance of the Roman Agricultural Diffusion (RAD) and the Islamic Green Revolution (IGR) in the dispersal of crops across Eurasia.

While the overall claims from the authors are convincing, I found the presentation of the data somewhat difficult to follow.<br /> Graphical visualization of the data with respect to the proposed hypotheses would go a long way towards making the argument clearer for a non-specialist audience.

The authors apply appropriate caveats in the discussion about their ability to assess IGR given their timeline only incorporates the first few hundred years and some IGR plants may not leave macrobotanical remains. Yet I think more could be done to explain how the data they do find provides positive evidence for RAD. Many of their findings are inferred to be RAD introductions not because of the timing in their sites, but because of previous evidence of introductions at other sites. It would thus be helpful to be more explicit about what additional evidence these findings provide beyond previously published data of introductions of many of these crops into the Levant.

Reviewer #3 (Public Review):

A big open question in evolutionary biology is how single cells become multicellular organisms, capable of adaptation as a collective. Many cells form groups, but adaptation at the level of the group tends to be inefficient (especially in comparison to cells). Theoretically, it has been proposed that groups formed by clonal development (cells remain attached to each other after division) can more readily lead to group-level adaptation than groups coming together through the aggregation of different cells post-division. To evaluate empirically the plausibility of this hypothesis, the authors compared adaptation in two lines of yeast that differ only in a couple of mutations determining their mechanism of group formation. Ace2 mutants develop through staying together, and Floc mutants through aggregation. They performed a form of size selection (through settling) as a way to select for multicellularity (this selection regime has been used before to obtain multicellular phenotypes). This selective regime has two components: growing (largely due to differences between cells) and settling (largely due to differences between groups). Thus, the authors assume that increases in fitness through growth are due mostly to adaptation at the single-cell level, whereas increases in fitness through settling are mostly due to adaptation at the multicellular level. They find that adaptation in clonal groups is mostly through settling and that aggregative groups adapt more through growth (despite getting bigger).

Overall this assumption makes sense (especially in a positive way) but growth, in this case, is also selecting against groups in the snowflake case and less strongly so in the floc case in which cells aggregate and disaggregate with some probability, and therefore cells can keep growing. That is, in addition to assortment the result is somewhat expected because there is less of a trade-off between growth and settling in floc: having a higher density in floc probably leads to higher aggregation and indirectly benefits settling, whereas in the clonal case, larger groups mean that a larger proportion of cells is not growing.

The main result of the paper holds true: clonal development favors multicellular adaptation relative to aggregative multicellularity, but the reason is not exclusively a difference in the distribution of variation, but a difference in the trade-off between single cell and multicellular traits.

In the second part of the paper, the authors beautifully show that the mechanisms of group formation affect evolutionary processes. Clonal aggregation leads to a decrease in the effective population size (because the descendants of mutants are likely to be in the same group, and therefore be selected together). This result shows that the mode of development can affect evolution!

Reviewer #1 (Public Review):

Pentz et al experimentally evolve yeast populations starting from two different strains that each differ in one locus compared to the wild-type. They show that these small differences - which result in one strain forming clonal groups, while the other forms multi-strain aggregates of different genotypes - can change the evolutionary fate of the strain under their selection regime. In their evolutionary experiment, they select for growth (an individual trait) and then sedimentation (a group trait) and show that the strain that makes clonal groups evolves a greater improvement in their group trait, while the strain that forms genetically diverse groups evolves a greater improvement in their individual trait. This provides experimental evidence for the hypothesis that clonality is key to the evolution of group traits, and potentially, multicellularity. They support their findings with genomic analysis of the mutants and use a mathematical model to explain some of the interesting observations from this analysis: that selection is stronger in genotypically mixed groups, while clonal groups suffer more from drift and bottlenecking effects. The study presents solid evidence for the findings, the methods are simple and clear, the scale of the experiment is impressive, the data analyses support the conclusions and are very complete and convincing, and the paper is very clearly written and a pleasure to read.

Reviewer #2 (Public Review):

This study by Pentz et al. aims to understand how cellular attachments and/or development affect the fitness of the transition to undifferentiated multicellularity. This work has the potential to better understand why some types of multicellular development (e.g. clonal development) versus others (e.g. aggregative development) are more or less commonly observed in nature.

Presently, much of our understanding of these processes comes from observation and theoretical work. This work aims to bridge this gap by rewiring the evolutionary clock and testing if different selected undifferentiated multicellular developmental strategies are better or worse.

The authors compare the fitness of Snowflake and Floc yeast under settling-based selection. They find that Snowflake is fitter under these conditions than Floc. They augment these findings with a simplified mathematical model that supports these findings.

On their face, the findings seem interesting but have limitations in that the authors did not consider alternate selective conditions and may come to different conclusions, potentially supporting the null hypothesis. In addition, doing experiments in related multicellular model systems that the authors have previously worked in would substantially improve generalizability.

Reviewer #1 (Public Review):

The paper proposes a novel approach, named ModCRE, which utilizes structure-based learning to predict the DNA binding preferences of transcription factors (TFs). The authors integrate both experimental knowledge of the structures of TF-DNA complexes and large amounts of high-throughput TF-DNA interaction data. Additionally, the authors have developed a server that automatically produces these characteristics for other TFs and their complexes with co-factors.

Strengths: The paper's integration of experimental knowledge and high-throughput data to develop statistical knowledge-based potentials to score the binding capability of TFs in cis-regulatory elements is a powerful strategy. The proposed approach can be applied to more than 80% of TF sequences, making it a general method for characterizing binding preferences.

Weaknesses: The paper is difficult to follow, as it contains many technical details and implementation details. The method applied is not always clear, and the paper focuses on implementation rather than the message. The results indicate that the nearest neighbors approach in Figure 4 outperforms the proposed method in many cases, and the proposed method seems to perform better only when similarity with the target is low. The same applies in Fig. 5 when using normalized ranked scores.

It appears that the authors have successfully developed a structure-based learning approach for predicting DNA binding preferences of transcription factors. However, the paper's technical language and implementation focus make it challenging to follow at times.

It seems the authors have successfully achieved most of their aims in improving predictions for TF-DNA interaction, and the results support their conclusions.

This work has the potential to significantly impact the field of TF-DNA binding and gene regulation, particularly for those interested in predicting PWMs for TFs with limited or unreliable experimental data.

Reviewer #2 (Public Review):

This work describes the development of a new structure-based learning approach to predict transcription binding specificity and its application in the modeling of regulatory complexes in cis-regulatory modules. The development of accurate computer tools to model protein-DNA complexes and to predict DNA binding specificity is a very relevant research topic with significant impact in many areas.

This article highlights the importance of transcriptional regulatory elements in gene expression regulation and the challenges in understanding their mechanisms. Traditional definitions of activating regulatory elements, such as promoters and enhancers, are becoming unclear, suggesting an updated model based on DNA accessibility and enhancer/promoter potential. Experimental techniques can assess the sequence preferences of transcription factors (TFs) for binding sites. Recent models propose a cooperative model in which regulatory elements work together to increase the local concentrations of TFs, RNA polymerase II, and other co-factors. Co-operative binding can be mediated through protein-protein or DNA interactions. The authors developed a structure-based learning approach to predict TF binding features and model the regulatory complex(es) in cis-regulatory modules, integrating experimental knowledge of structures of TF-DNA complexes and high-throughput TF-DNA interactions. They developed a server to characterize and model the binding specificity of a TF sequence or its structure, which was applied to the examples of interferon-β enhanceosome and the complex of factors SOX11/SOX2 and OCT4 with the nucleosome. The models highlight the co-operativity of TFs and suggest a potential role for nucleosome opening.

The results presented by the authors have a large variability in performance upon the different TF families tested. Therefore, it would be ideal if the performance/accuracy of the method is tested in some simple predictions and validated with prospective experimental data before applying it to model difficult scenarios such as those described here: SOX11/SOX2/OCT4 and nucleosome or interferon beta and enhanceosome. This will give more support to the models generated and thus the validity of the conclusions and hypothesis derived from them.

Reviewer #1 (Public Review):

Summary:<br /> Rai1 encodes the transcription factor retinoic acid-induced 1 (RAI1), which regulates expression of factors involved in neuronal development and synaptic transmission. Rai1 haploinsufficiency leads to the monogenic disorder Smith-Magenis syndrome (SMS), which is associated with excessive feeding, obesity and intellectual disability. Consistent with findings in human subjects, Rai1+/- mice and mice with conditional deletion of Rai1 in Sim+ neurons, which are abundant in the paraventricular nucleus (PVN), exhibit hyperphagia, obesity and increased adiposity. Furthermore, RAI1-deficient mice exhibit reduced expression of brain-derived neurotrophic factor (BDNF), a satiety factor essential for the central control of energy balance. Notably, overexpression of BDNF in PVN of RAI1-deficient mice mitigated their obesity, implicating this neurotrophin in the metabolic dysfunction these animals exhibit. In this follow up study, Javed et al. interrogated the necessity of RAI1 in BDNF+ neurons promoting metabolic health.

Consistent with previous reports, the authors observed reduced BDNF expression in the hypothalamus of Rai1+/- mice. Moreover, proteomics analysis indicated impairment in neurotrophin signaling in the mutants. Selective deletion of Rai1 in BDNF+ neurons in the brain during development resulted in increased body weight, fat mass and reduced locomotor activity and energy expenditure without changes in food intake. There was also a robust effect on glycemic control, with mutants exhibiting glucose intolerance. Selective depletion of RAI1 in BDNF+ neurons in PVN in adult mice also resulted in increased body weight, reduced locomotor activity, and glucose intolerance without affecting food intake. Blunting RAI1 activity also leads to increases and decreases in the inhibitory tone and intrinsic excitability, respectively, of BDNF+ neurons in the PVN.

Strengths:<br /> Overall, the experiments are well designed and multidisciplinary approaches are employed to demonstrate that RAI1 deficits in BDNF+ neurons diminish hypothalamic BDNF signaling and produce metabolic dysfunction. The most significant advance relative to previous reports is the finding from electrophysiological studies showing that blunting RAI1 activity leads to increases and decreases the inhibitory tone and intrinsic excitability, respectively, of BDNF+ neurons in the PVN. Furthermore, that intact RAI1 function is required in BDNF+ neurons for the regulation of glucose homeostasis.

Weaknesses:<br /> Some of the data need to be reconciled with previous findings by others. For example, the authors report that more than 50% of BDNF+ neurons in PVN also express pTrkB whereas about 20% of pTrkB+ cells contain BDNF, raising the possibility that autocrine mechanisms might be at play. This is in conflict with a previous study by An et al, (2015) showing that these cell populations are largely non-overlapping in the PVN.

Another issue that deserves more in depth discussion is that diminished BDNF function appears to play a minor part driving deficits in energy balance regulation. Accordingly, both global central depletion of Rai1 in BDNF+ neurons during development and deletion of Rai1 in BDNF+ neurons in the adult PVN elicited modest effects on body weight (less than 18% increase) and did not affect food intake. This contrasts with mice with selective Bdnf deletion in the adult PVN, which are hyperphagic and dramatically obese (90% heavier than controls). Therefore, the results suggest that deficits in RAI1 in PVN or the whole brain only moderately affect BDNF actions influencing energy homeostasis and that other signaling cascades and neuronal populations play a more prominent role driving the phenotypes observed in Rai1+/- mice, which are hyperphagic and 95% heavier than controls. The results from the proteomic analysis of hypothalamic tissue of Rai1 mutant mice and controls could be useful in generating alternative hypotheses.

Depleting RAI1 in BDNF+ neurons had a robust effect compromising glycemic control. However, as the approach does not necessarily impact BDNF exclusively, there should be a larger discussion of alternative mechanisms.

Reviewer #3 (Public Review):

Summary:<br /> Smith-Magenis syndrome (SMS) is associated with obesity and is caused by deletion or mutations in one copy of the Rai1 gene which encodes a transcriptional regulator. Previous studies have shown that Bdnf gene expression is reduced in the hypothalamus of Rai1 heterozygous mice. This manuscript by Javed et al. further links SMS-associated obesity with reduced Bdnf gene expression in the PVH.

Strengths:<br /> The authors show that deletion of the Rai1 gene in all BDNF-expressing cells or just in the PVH BDNF neurons postnatally caused obesity. Interestingly, mutant mice displayed sexual dimorphism in the cause for the obesity phenotype. Overall, the data are well presented and convincing except the data from LM22A-4.

Weaknesses:<br /> 1. The most serious concern is about data from LM22A-4 administration experiments (Figure 5 and associated supplemental figures). A rigorous study has demonstrated that LM22A-4 does not activate TrkB (Boltaev et al., Science Signaling, 2017), which is consistent with unpublished results from many labs in the neurotrophin field. It is tricky to interpret body weight data from pharmacological studies because compounds always have some side effects, which can reduce body weight non-specifically.

2. The resolution of all figures are poor, and thus I could not judge the quality of the micrographs.

3. Citation of the literature is not precise. The study by An et al. (2015) shows that deletion of the Bdnf gene in the PVH leads to obesity due to increased food intake and reduced energy expenditure (not just hyperphagic obesity; Line 72). Furthermore, the study by Unger et al. (2017) carried out Bdnf deletion in the VMH and DMH using AAV-Cre and did not discuss SF1 neurons at all (Line 354). The two studies by Yang et al. (Mol Endocrinol, 2016) and Kamitakahara et al. (Mol Metab, 2015) did use SF1-Cre to delete the Bdnf gene and did not observe any obesity phenotype.

4. Animal number is not described in many figure legends.

Reviewer #2 (Public Review):

Understanding disease conditions often yields valuable insights into the physiological regulation of biological functions, as well as potential therapeutic approaches. In previous investigations, the author's research group identified abnormal expression of brain-derived neurotrophic factor (BDNF) in the hypothalamus of a mouse model exhibiting Smith-Magenis syndrome (SMS), which is caused by heterozygous mutations of the Rai1 gene. Human SMS is associated with distinct facial characteristics, sleep disturbances, behavioral issues, and intellectual disabilities, often accompanied by obesity. Conditional knockout (cKO) of the Bdnf gene from the paraventricular hypothalamus (PVH) in mice led to hyperphagic obesity, while overexpression of the Bdnf gene in the PVH of Rai1 heterozygous mice restored the SMS-like obese phenotype. Based on these preceding findings, the authors of the present study discovered that homozygous Rai1 cKO restricted to Bdnf-expressing cells, or Rai1 gene knockdown solely in Bdnf-positive neurons in the PVH, induced obesity along with intricate alterations in adipose tissue composition, energy expenditure, locomotion, feeding patterns, and glucose tolerance, some of which varied between sexes. Additionally, the authors demonstrated that a brain-penetrating drug capable of activating the TrkB pathway, a downstream signaling pathway of BDNF, partially alleviated the SMS-like obesity phenotype in female mice with Rai1 heterozygous mutations. Although the specific (neural) cell type responsible for this TrkB signaling remains an open question, the present study unequivocally highlights the importance of Rai1 gene function in PVH Bdnf neurons for the obesity phenotype, providing valuable insights into potential therapeutic strategies for managing obesity associated with SMS.

In the proteomic analysis (Fig. 1), the authors elucidated that multiple phospho-protein signaling pathways, including Akt and mTOR pathways, exhibited significant attenuation in the SMS model mice. Of significance, the manifestation of haploinsufficiency of the Rai1 gene exclusively within the BDNF+ cells demonstrated negligible impact on body weight (Fig. 2-supple 3D), despite observing a reduction in BDNF levels in the heterozygous Rai1 mutant (Fig. 1A). Conversely, the homozygous Rai1 cKO in the BDNF+ cells prominently displayed an obesity phenotype, suggesting substantial dissimilarities in the gene expression profiles between Rai1 heterozygous and homozygous conditions within the BDNF+ cell population. It would be advantageous to precisely identify the responsible differentially expressed genes, possibly including Bdnf itself, in the homozygous cKO model. The observed reduction in the excitability of PVH BDNF+ cells (Fig. 3) is presumably attributed to aberrant gene expression other than Bdnf itself, which may serve as a prospective target for gene expression analysis. Notably, the Rai1 homozygous cKO mice in BDNF+ cells exhibited some sexual dimorphisms in feeding and energy expenditures, as evidenced by Fig. 2 and related figures. Exploring the potential relevance of these sexual differences to human SMS cases and investigating the underlying cellular/molecular mechanisms in the future would provide valuable insights.

Although the CRISPR-mediated knockdown of the Rai1 gene (Fig. 4) appears to be highly effective, given the broad transduction of AAV serotype 9, it may be helpful to exclude the possibility of other brain regions adjacent to the PVH, such as the DMH or VMH, being affected by this viral procedure. If the PVH-specificity is established, the majority of Rai1 cKO effects in Bdnf+ cells are primarily attributed to PVH-Bdnf+ cells based on the similarity of phenotypes observed. With regards to the apparent rescue of the body weight phenotype in Rai1 heterozygous mutants using a selective TrkB activator, the specific biological processes, and neurons responsible for this effect remain unclear to this reviewer. Elucidating these aspects would be significant when considering potential applications to human SMS cases.

Overall, the present study represents a valuable addition to the authors' series of high-quality molecular genetic investigations into the in vivo functions of the Rai1 gene. This reviewer particularly commends their diligent efforts to enhance our comprehension of SMS and contribute to the future development of more effective therapies for this syndrome.

Reviewer #1 (Public Review):

Summary:<br /> This paper reported a protocol of using human-induced pluripotent stem cells to generate cells expressing microglia-enriched genes and responding to LPS by drastic upregulation of proinflammatory cytokines. Upon subretinal transplantation in mice, hiPSC-derived cells integrated into the host retina and maintained retinal homeostasis, while they responded to RPE injury by migration, proliferation and phagocytosis. The findings revealed the potential of using hiPSC-derived cell transplantation for microglia replacement as a therapeutic strategy for retinal diseases.

Strengths:<br /> The paper demonstrates a method of consistently generating a significant quantity of hiPSC-derived microglia-like cells for in vitro study or for in vivo transplantation. RNAseq analysis offers an opportunity for comprehensive transcriptome profiling of the derived cells. It is impressive that following transplantation, these cells integrated into the retina well, migrated to the corresponding layers, adopted microglia-like morphologies, and survived long term without generating apparent harm. The work has laid a foundation for future utilization of hiPSC-derived microglia in lab and clinical applications.

Weaknesses:<br /> 1. The primary weakness of the paper concerns its conclusion of having generated "homogenous mature microglia", partly based on the RNAseq analysis. However, the comparison of gene profiles was carried out only between "hiPSC-derived mature microglia" and the proliferating myeloid progenitors. While the transcriptome profiles revealed a trend of enrichment of microglia-like gene expression in "hiPSC-derived mature microglia" compared to proliferating myeloid progenitors, this is not sufficient to claim they are "mature microglia". It is important that one carries out a comparative analysis of the RNAseq data with those of primary human microglia, which may be done by leveraging the public database. To convincingly claim these cells are mature microglia, questions need to be addressed including how similar the molecular signatures of these cells are compared with the fully differentiated primary microglia cell or if they remain progenitor-like or take on mosaic properties, and how they distinguish from macrophages.

2. While the authors attempted to demonstrate the functional property of "hiPSC-derived mature microglia" in culture, they used LPS challenge, which is an inappropriate assay. This is because human microglia respond poorly to LPS alone but need to be activated by a combination of LPS with other factors, such as IFNγ. Their data that "hiPSC-derived mature microglia" showed robust responses to LPS indeed implicates that these cells do not behave like mature human microglia.

3. The resolution of Figs. 4 - 6 is so low that even some of the text and labels are hardly readable. Based on the morphology shown in Fig. 4 and the statement in line 147, these hiPSC-derived "cells altered their morphology to a rounded shape within an hour of incubation and rapidly internalized the fluorescent-labeled particles". This is a peculiar response. Usually, microglia do not respond to fluorescent-labeled zymosan by turning into a rounded shaped within an hour when they internalize them. Such a behavior usually implicates weak phagocytotic capacity.

4. Data presented in Fig. 5 are not very convincing to support that transplanted cells were immunopositive for "human CD11b (Fig.5C), as well as microglia signature markers P2ry12 and TMEM119 (Fig.5D)" (line 167). The resolution and magnification of Fig. 5D is too low to tell the colocalization of tdT and human microglial marker immunolabeling. In the flat-mount images (C, I), hCD11b immunolabeling is not visible in the GCL or barely visible in the IPL. This should be discussed.

5. Microglia respond to injury by becoming active and lose their expression of the resting state microglial marker, such as P2ry12, which is used in Fig. 6 for detection of migrated microglia. To confirm that these cells indeed respond to injury like native microglia, one should check for activated microglial markers and induction of pro-inflammatory cytokines in the sodium iodate-injury model.

Reviewer #2 (Public Review):

Summary:<br /> Ma et al. employed a myeloid progenitor/microglia differentiation protocol to produce human-induced pluripotent stem cell (hiPSC)-derived microglia in order to examine the potential of microglial cell replacement as a treatment for retinal disorders. They characterized the iPSC-derived microglia by gene expression and in vitro assay analysis. By evaluating xenografted microglia in the partly microglia-depleted retina, the function of the microglia was further assessed.

Strengths:

Overall, the study and the data are convincing, and xenografted microglia were also tested in a RPE injury paradigm.

Weaknesses:

Gene expression analysis of mature microglia cells should be better interpreted and it would be beneficial to compare the iPSC-derived microglia gene set to a human microglial cell line (for example, HMC3) instead of myeloid progenitor cells.<br /> The way that the manuscript has been written, unfortunately, is not optimal. I recommend that the entire manuscript be edited and proofread in English. The text contains spelling and grammar mistakes, and the manuscript is inconsistent in several parts. The manuscript should also be revised for a scientific paper format.

Reviewer #1 (Public Review):

The inferior colliculus (IC) is the central auditory system's major hub. It integrates ascending brainstem signals to provide acoustic information to the auditory thalamus. The superficial layers of the IC ("shell" IC regions as defined in the current manuscript) also receive a massive descending projection from the auditory cortex. This auditory cortico-collicular pathway has long fascinated the hearing field, as it may provide a route to funnel "high-level" cortical signals and impart behavioral salience upon an otherwise behaviorally agnostic midbrain circuit.

Accordingly, IC neurons can respond differently to the same sound depending on whether animals engage in a behavioral task (Ryan and Miller 1977; Ryan et al., 1984; Slee & David, 2015; Saderi et al., 2021; De Franceschi & Barkat, 2021). Many studies also report a rich variety of non-auditory responses in the IC, far beyond the simple acoustic responses one expects to find in a "low-level" region (Sakurai, 1990; Metzger et al., 2006; Porter et al., 2007). A tacit assumption is that the behaviorally relevant activity of IC neurons is inherited from the auditory cortico-collicular pathway. However, this assumption has never been tested, owing to two main limitations of past studies:

1) Prior studies could not confirm if data were obtained from IC neurons that receive monosynaptic input from the auditory cortex.

2) Many studies have tested how auditory cortical inactivation impacts IC neuron activity; the consequence of cortical silencing is sometimes quite modest. However, all prior inactivation studies were conducted in anesthetized or passively listening animals. These conditions may not fully engage the auditory cortico-collicular pathway. Moreover, the extent of cortical inactivation in prior studies was sometimes ambiguous, which complicates interpreting modest or negative results.

Here, the authors' goal is to directly test if auditory cortex is necessary for behaviorally relevant activity in IC neurons. They conclude that surprisingly, task relevant activity in cortico-recipient IC neuron persists in absence of auditory cortico-collicular transmission. To this end, a major strength of the paper is that the authors combine a sound-detection behavior with clever approaches that unambiguously overcome the limitations of past studies.

First, the authors inject a transsynaptic virus into the auditory cortex, thereby expressing a genetically encoded calcium indicator in the auditory cortex's postsynaptic targets in the IC. This powerful approach enables 2-photon Ca2+ imaging from IC neurons that unambiguously receive monosynaptic input from auditory cortex. Thus, any effect of cortical silencing should be maximally observable in this neuronal population. Second, they abrogate auditory cortico-collicular transmission using lesions of auditory cortex. This "sledgehammer" approach is arguably the most direct test of whether cortico-recipient IC neurons will continue to encode task-relevant information in absence of descending feedback. Indeed, their method circumvents the known limitations of more modern optogenetic or chemogenetic silencing, e.g. variable efficacy.

I also see three weaknesses which limit what we can learn from the authors' hard work, at least in the current form. I want to emphasize that these issues do not reflect any fatal flaw of the approach. Rather, I believe that their datasets likely contain the treasure-trove of knowledge required to completely support their claims.

1. The conclusion of this paper requires the following assumption to be true: That the difference in neural activity between Hit and Miss trials reflects "information beyond the physical attributes of sound." The data presentation complicates asserting this assumption. Specifically, they average fluorescence transients of all Hit and all Miss trials in their detection task. Yet, Figure 3B shows that mice's d' depends on sound level, and since this is a detection task the smaller d' at low SPLs presumably reflects lower Hit rates (and thus higher Miss rates). As currently written, it is not clear if fluorescence traces for Hits arise from trials where the sound cue was played at a higher sound level than on Miss trials. Thus, the difference in neural activity on Hit and Miss trials could indeed reflect mice's behavior (licking or not licking). But in principle could also be explained by higher sound-evoked spike rates on Hit compared to Miss trials, simply due to louder click sounds. Indeed, the amplitude and decay tau of their indicator GCaMP6f is non-linearly dependent on the number and rate of spikes (Chen et al., 2013), so this isn't an unreasonable concern.

2. The authors' central claim effectively rests upon two analyses in Figures 5 and 6. The spectral clustering algorithm of Figure 5 identifies 10 separate activity patterns in IC neurons of control and lesioned mice; most of these clusters show distinct activity on averaged Hit and Miss trials. They conclude that although the proportions of neurons from control and lesioned mice in certain clusters deviates from an expected 50/50 split, neurons from lesioned mice are still represented in all clusters. A significant issue here is that in addition to averaging all Hits and Miss trials together, the data from control and lesioned mice are lumped for the clustering. There is no direct comparison of neural activity between the two groups, so the reader must rely on interpreting a row of pie charts to assess the conclusion. It's unclear how similar task relevant activity is between control and lesioned mice; we don't even have a ballpark estimate of how auditory cortex does or does not contribute to task relevant activity. Although ideally the authors would have approached this by repeatedly imaging the same IC neurons before and after lesioning auditory cortex, this within-subjects design may be unfeasible if lesions interfere with task retention. Nevertheless, they have recordings from hundreds to thousands of neurons across two groups, so even a small effect should be observable in a between-groups comparison.

3. In Figure 6, the authors show that logistic regression models predict whether the trial is a Hit or Miss from their fluorescence data. Classification accuracy peaks rapidly following sound presentation, implying substantial information regarding mice's actions. The authors further show that classification accuracy is reduced, but still above chance in mice with auditory cortical lesions. The authors conclude from this analysis task relevant activity persists in absence of auditory cortex. In principle I do not disagree with their conclusion.

The weakness here is in the details. First, the reduction in classification accuracy of lesioned mice suggests that auditory cortex does nevertheless transmit some task relevant information, however minor it may be. I feel that as written, their narrative does not adequately highlight this finding. Rather one could argue that their results suggest redundant sources of task-relevant activity converging in the IC. Secondly, the authors conclude that decoding accuracy is impaired more in partially compared to fully lesioned mice. They admit that this conclusion is at face value counterintuitive, and provide compelling mechanistic arguments in the Discussion. However, aside from shaded 95% CIs, we have no estimate of variance in decoding accuracy across sessions or subjects for either control or lesioned mice. Thus we don't know if the small sample sizes of partial (n = 3) and full lesion (n = 4) groups adequately sample from the underlying population. Their result of Figure 6B may reflect spurious sampling from tail ends of the distributions, rather than a true non-monotonic effect of lesion size on task relevant activity in IC.

Reviewer #1 (Public Review):

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder leading to the loss of innervation of skeletal muscles, caused by the dysfunction and eventual death of lower motor neurons. A variety of approaches have been taken to treat this disease. With the exception of three drugs that modestly slow progression, most therapeutics have failed to provide benefit. Replacing lost motor neurons in the spinal cord with healthy cells is plagued by a number of challenges, including the toxic environment, inhibitory cues that prevent axon outgrowth to the periphery, and proper targeting of the axons to the correct muscle groups. These challenges seem to be well beyond our current technological approaches. Avoiding these challenges altogether, Bryson et al. seek to transplant the replacement motor neurons into the peripheral nerves, closer to their targets. The current manuscript addresses some of the challenges that will need to be overcome, such as immune rejection of the allograft and optimizing maturation of the neuromuscular junction.

Bryson et al. begin by examining the survival of mESC-derived motor neurons allografted into SOD1 mice. The motor neurons, made on a 129S1/SvImJ, were transplanted into the tibial nerve of SOD1 mice on a C57BL/6J background. Without immunosuppression, most cells were lost between 14 and 35 days, suggesting an immune response had eliminated them. Tacrolimus prevented cell loss, but it also inhibited innervation of the muscle. It also uncovered the tumorigenic potential of contaminating pluripotent cells. In contrast, immunosuppression using H57-597, an antibody targeting T-cell receptor beta, prevented graft rejection while permitting some innervation of muscle. Pretreatment of the cells with mitomycin-C eliminated pluripotent cells, preventing tumor formation. The authors noted that this combination only innervated ~10% of endplates, likely due to the fact that the implanted motor neurons are not active.

The authors then began the process of optimizing the cells themselves, using measurements taken in late-stage SOD1 mice. Fast-firing and slow-firing populations of neurons were first compared. Using optical stimulation, these two cell types appeared to be similar. The authors opted to use slow-firing neurons in the subsequent experiments. Recognizing that neuromuscular junction (NMJ) innervation and maintenance are dependent on motor neuron activity, implantable optical stimulators were also evaluated. 14 days after transplanting the cells, optical stimulation training was initiated for one hour each day. This training led to a nearly 13-fold increase in force generation, although this still remained well below the force generated by electrical stimulation. The enhanced innervation also prevented the atrophy of muscle fibers caused by denervation.

Overall, the data for the function of the implanted cells are convincing. The dCALMS technique that the authors have developed is quite interesting and will likely be applicable to analyze muscles for other therapeutics. The identification of calcineurin inhibitors as inhibitors of reinnervation will also be important for the development of other cell-based therapeutics for ALS.

However, there are some issues that should be addressed. These include some common misconceptions about ALS. While ALS is split into familial and sporadic forms based on the presence or absence of a family history of the disease, mutations in the known ALS-associated genes are found in both forms. The authors also state that exercise programs are likely to accelerate degeneration in ALS. This is incorrect. Moderate exercise is part of the current guidelines for treating ALS, and mouse studies have demonstrated a therapeutic effect of moderate exercise. Regarding the experimental design, there are some important details missing. The animals do not appear to have been operated on at the same age, and the criteria for when to perform the operation were not described. A similar problem exists for when the animals were determined to reach endpoint. The authors also do not seem to address a potential pitfall of this approach: acceleration of the disease process. Indeed, some of the data comparing the ipsilateral side to the contralateral side suggest that the implantation of the cells and/or the light source increase the denervation of the muscle. Finally, there is a fairly large difference between the motor output provided by optical stimulation relative to electrical stimulation. It is currently unclear what level needs to be reached to provide an effective response in the intact animal. Thus, it is difficult to determine if the level of reinnervation that this study has achieved will be sufficient to improve a patient's quality of life.

Reviewer #2 (Public Review):

The authors provide convincing evidence that optogenetic stimulation of ChR2-expressing motor neurons implanted in muscles effectively restores innervation of severely affected skeletal muscles in the aggressive SOD1 mouse model of ALS, and conclude that this method can be applied to selectively control the function of implicated muscles. This was supported by convincing data presented in the paper.

This is an interesting paper providing new/improved optogenetic methods to restore or improve muscle strength in ALS. In general, it is of high significance in both the techniques and concept, and the paper was well written. The evidence supporting the conclusions is convincing, with rigorous muscle tension physiological analysis, and nerve and muscle histology and image analysis. The work will be of broad interest to medical biologists on muscle disorders.

One weak point is that proper control experiments were not clearly presented - these could be shown in the paper. For example, one control experiment with only YFP but no ChR2 expression with optogenetic stimulation should be performed, following similar procedures and analysis applied to the ChR2-transduced animals.

Reviewer #1 (Public Review):

This is a key paper examining the evolution of an important structure (pillars) in the shell architecture of organo-phosphatic brachiopods. The advantages of these structures are adequately discussed and the evolution of the pillars is described and illustrated. There is much that is of fundamental significance here in understanding the ecology and evolution of these groups as a whole.

1) In several places the biological control on the development of the pillars is noted. This is explained in terms of their relationship to the growth and evolution of epithelial cells. It would be useful and make the paper more understandable if this link was mentioned early on in the paper and developed during the narrative.

2) The Cambrian Explosion is mentioned a number of times. Are these changes driven by the Cambrian Explosion, i.e. the expansion of major new body plans, or are the changes merely coincident with the long duration of the 'Explosion'?

3) I have no doubt the process is one of adaptive innovation but it would be useful to expand on this. Why is it adaptive?

4) Are pillars present in living Lingula?

Reviewer #2 (Public Review):

Summary: Two early Cambrian taxa of linguliform brachiopods are assigned to the family Eoobolidae. The taxa exhibit a columnar shell structure and the phylogenetic implications of this shell structure in relation to other early Cambrian families are discussed.

Strengths: Interesting idea regarding the evolution of shell structure.

Weaknesses: The early record of shell structures of linguliform brachiopods is incomplete and partly contradictory. The authors maintain silence regarding contradictory information throughout the article to the extent that information is cited wrongly.<br /> The structure and language of the article need reworking in my opinion, the systematic part can be in the appendix but the main results and the results relevant for the discussion should be in the main article. A critical revision of the family Eoobolidae and Lingulellotretidae including a revision of the type species of Eoobolus and Lingulellotreta is needed.

Reviewer #1 (Public Review):

The present study examines whether one can identify kinematic signatures of different motor strategies in both humans and non-human primates (NHP). The Critical Stability Task (CST) requires a participant to control a cursor with complex dynamics based on hand motion. The manuscript includes datasets on performance of NHPs collected from a previous study, as well as new data on humans performing the same task. Further human experiments and optimal control models highlight how different strategies lead to different patterns of hand motion. Finally, classifiers were developed to predict which strategy individuals were using on a given trial. There are several strengths to this manuscript. I think the CST task provides a useful behavioural task to explore the neural basis of voluntary control. While reaching is an important basic motor skill, there is much to learn by looking at other motor actions to address many fundamental issues on the neural basis of voluntary control. I also think the comparison between human and NHP performance is important as there is a common concern that NHPs can be overtrained in performing motor tasks leading to differences in their performance as compared to humans. The present study highlights that there are clear similarities in motor strategies of humans and NHPs. While the results are promising, I would suggest that the actual use of these paradigms and techniques likely need some improvement/refinement. Notably, the threshold or technique to identify which strategy an individual is using on a given trial needs to be more stringent given the substantial overlap in hand kinematics between different strategies.

The most important goal of this study is to set up future studies to examine how changes in motor strategies impact neural processing. I have a few concerns that I think need to be considered. First, a classifier was developed to identify whether a trial reflected Position Control with success deemed to be a probability of >70% by the classifier. In contrast, a probability of <30% was considered successfully predicting Velocity Control (Uncertain bandwidth middle 40%). While this may be viewed as acceptable for purposes of quantifying behaviour, I'm not sure this is strict enough for interpreting neural data. Figure 7A displays the OFC Model results for the two strategies and demonstrates substantial overlap for RMS of Cursory Position and Velocity at the lowest range of values. In this region, individual trials for humans and NHP are commonly identified as reflecting Position Control by the classifier although this region clearly also falls within the range expected for Velocity Control, just a lower density of trials. The problem is that neural data is messy enough, but having trials being incorrectly labelled will make it even messier when trying to quantify differences in neural processing between strategies. A further challenge is that trials cannot be averaged as the patterns of kinematics are so different from trial-to-trial. One option is to just move up the threshold from >70%/<30% to levels where you have a higher confidence that performance only reflects one of the two strategies (perhaps 95/5% level). Another approach would be to identify the 95% confidence boundary for a given strategy and only classify a trial as reflecting a given strategy when it is inside its 95% boundary, but outside the other strategies 95% boundary (or some other level separation). A higher threshold would hopefully also deal with the challenge of individuals switching strategies within a trial. Admittedly, this more stringent separation will likely drop the number of trials prohibitively, but there is a clear trade-off between number of trials and clean data. For the future, a tweak to the task could be to lengthen the trial as this would certainly increase separation between the two conditions.

While the paradigm creates interesting behavioural differences, it is not clear to me what one would expect to observe neurally in different brain regions beyond paralleling kinematic differences in performance. Perhaps this could be discussed. One extension of the present task would be to add some trials where visual disturbances are applied near the end of the trial. The prediction is that there would be differences in the kinematics of these motor corrections for different motor strategies. One could then explore differences in neural processing across brain regions to identify regions that simply reflect sensory feedback (no differences in the neural response after the disturbance), versus those involved in different motor strategies (differences in neural responses after the disturbance).

It seems like a mix of lambda values are presented in Figure 5 and beyond. There needs to be some sort of analysis to verify that all strategies were equally used across lambda levels. Otherwise, apparent differences between control strategies may simply reflect changes in the difficulty of the task. It would also be useful to know if there were any trends across time? Strategies used for blocks of trials or one used early when learning and then changing later.

Figure 2 highlights key features of performance as a function of task difficulty. Lines 187 to 191 highlight similarities in motor performance between humans and NHPs. However, there is a curious difference in hand/cursor Gain for Monkey J. Any insight as to the basis for this difference?

Reviewer #3 (Public Review):

This paper considers a challenging motor control task - the critical stability task (CST) - that can be performed equally well by humans and macaque monkeys. This task is of considerable interest since it is rich enough to potentially yield important novel insights into the neural basis of behavior in more complex tasks that point-to-point reaching. Yet it is also simple enough to allow parallel investigation in humans and monkeys, and is also easily amenable to computational modeling. The paper makes a compelling argument for the importance of this type of parallel investigation and the suitability of the CST for doing so.

Behavior in monkeys and in human subjects suggests that behavior seems to cluster into different regimes that seem to either oscillate about the center of the screen, or drift more slowly in one direction. The authors show that these two behavioral regimes can be reliably reproduced by instructing human participants to either maintain the cursor in the center of the screen (position control objective), or keep the cursor still anywhere in the screen (velocity control objective) - as opposed to the usual 'instruction' to just not let the cursor leave the screen. A computational model based on optimal feedback control can similarly reproduce the two control regimes when the costs are varied

Overall, this is a creative study that successfully leverages experiments in humans and computational modeling to gain insight into the nature of individual differences in behavior across monkeys (and people). The approach does work and successfully solves the core problem the authors set out to address. I do think that more comprehensive approaches might be possible that might involve, e.g. using a richer set of behavioral features to classify behavior, fitting a parametric class of control objectives rather than assuming a binary classification, and exploring the reliability of the inference process in more detail.

In addition, the authors do fully establish that varying control objectives is the only way to obtain the different behavioral phenotypes observed. It may, for instance, be possible that some other underlying differences (e.g. the sensitivity to effort costs or the extent of signal-dependent noise) might also lead to a similar range of behaviors as varying the position versus velocity costs.

Specific Comments:<br /> The simulations convincingly show that varying the control objective via the cost function can reproduce the different observed behavioral regimes. However, in principle, the differences in behavior among the monkeys and among the humans in Experiment 1 might not necessarily be due to difference in other aspects of the model. For instance, for a fixed cost function, differences in motor execution noise might perhaps lead the model to favor a position-like strategy or a velocity-like strategy. Or differences in the relative effort cost might alter the behavioral phenotype. Given that the narrative is about inferring control objectives, it seems important to rule out more systematically that some other factor might not potentially dictate each individual's style of performing the task. One approach to rule this out might be to try to formally fit the parameters of the model (or at least a subset of them) under a fixed cost function (e.g. velocity-based), and check whether the model might still recover the different regimes of behavior when parameters *other than the cost function* are varied.

The approach to the classification problem is somewhat ad hoc and based on fairly simplistic, hand-picked features (RMS position and RMS velocity). I do wonder whether a more comprehensive set of behavioral features might enable a clearer separation between strategies, or might even reveal that the uninstructed subjects were doing something qualitatively different still from the instructed groups. Different control objectives ought to predict meaningfully different control policies - that is, different ways of updating hand position based on current state of the cursor and hand - e.g. the hand/cursor gain, which does clearly differ across instructed strategies. Would it be possible to distinguish control strategies more accurately based on this level of analysis, rather than based on gross task metrics? Might this point to possible experimental interventions (e.g. target jumps) that might validate the inferred objective?

It seems that the classification problem cannot be solved perfectly, at least on a single-trial level. Although it works out that the classification can recover which participants were given which instructions, it's not clear how robust this classification is. It should be straightforward to estimate the reliability of the strategy classification by simulating participants and deriving a "confusion matrix", i.e. calculating how often e.g. data generated under a velocity-control objective gets mis-classified as following a position-control objective. It's not clear how this kind of metric relates to the decision confidence outputted by the classifier.

The problem of inferring the control objective is framed as a dichotomy between position control and velocity control. In reality, however, it may be a continuum of possible objectives, based on the relative cost for position and velocity. How would the problem differ if the cost function is framed as estimating a parameter, rather than as a classification problem?

Reviewer #1 (Public Review):

This paper falls in a long tradition of studies on the costs of reproduction in birds and its contribution to understanding individual variation in life histories. Unfortunately, the meta-analyses only confirm what we know already, and the simulations based on the outcome of the meta-analysis have shortcomings that prevent the inferences on optimal clutch size, in contrast to the claims made in the paper.

There was no information that I could find on the effect sizes used in the meta-analyses other than a figure listing the species included. In fact, there is more information on studies that were not included. This made it impossible to evaluate the data-set. This is a serious omission, because it is not uncommon for there to be serious errors in meta-analysis data sets. Moreover, in the long run the main contribution of a meta-analysis is to build a data set that can be included in further studies.

The main finding of the meta-analysis of the brood size manipulation studies is that the survival costs of enlarging brood size are modest, as previously reported by Santos & Nakagawa on what I suspect to be mostly the same data set. The paper does a very poor job of critically discussing whether we should take this at face value or whether instead there may be short-comings in the general experimental approach. A major reason why survival cost estimates are barely significantly different from zero may well be that parents do not fully adjust their parental effort to the manipulated brood size, either because of time/energy constraints, because it is too costly and therefore not optimal, or because parents do not register increased offspring needs. Whatever the reason, as a consequence, there is usually a strong effect of brood size manipulation on offspring growth and thereby presumably their fitness prospects. In the simulations (Fig.4), the consequences of the survival costs of reproduction for optimal clutch size were investigated without considering brood size manipulation effects on the offspring. Effects on offspring are briefly acknowledged in the discussion, but otherwise ignored. Assuming that the survival costs of reproduction are indeed difficult to discern because the offspring bear the brunt of the increase in brood size, a simulation that ignores the latter effect is unlikely to yield any insight in optimal clutch size. It is not clear therefore what we learn from these calculations.

There are other reasons why brood size manipulations may not reveal the costs of reproduction animals would incur when opting for a larger brood size than they produced spontaneously themselves. Firstly, the manipulations do not affect the effort incurred in laying eggs (which also biases your comparison with natural variation in clutch size). Secondly, the studies by Boonekamp et al on Jackdaws found that while there was no effect of brood size manipulation on parental survival after one year of manipulation, there was a strong effect when the same individuals were manipulated in the same direction in multiple years. This could be taken to mean that costs are not immediate but delayed, explaining why single year manipulations generally show little effect on survival. It would also mean that most estimates of the fitness costs of manipulated brood size are not fit for purpose, because typically restricted to survival over a single year.

Details of how the analyses were carried out were opaque in places, but as I understood the analysis of the brood size manipulation studies, manipulation was coded as a covariate, with negative values for brood size reductions and positive values for brood size enlargements (and then variably scaled or not to control brood or clutch size). This approach implicitly assumes that the trade-off between current brood size (manipulation) and parental survival is linear, which contrasts with the general expectation that this trade-off is not linear. This assumption reduces the value of the analysis, and contrasts with the approach of Santos & Nakagawa.

The observational study selection is not complete and apparently no attempt was made to make it complete. This is a missed opportunity - it would be interesting to learn more about interspecific variation in the association between natural variation in clutch size and parental survival.

Reviewer #2 (Public Review):

I have read with great interest the manuscript entitled "The optimal clutch size revisited: separating individual quality from the costs of reproduction" by LA Winder and colleagues. The paper consists in a meta-analysis comparing survival rates from studies providing clutch sizes of species that are unmanipulated and from studies where the clutch sizes are manipulated, in order to better understand the effects of differences in individual quality and of the costs of reproduction. I find the idea of the manuscript very interesting. However, I am not sure the methodology used allows to reach the conclusions provided by the authors (mainly that there is no cost of reproduction, and that the entire variation in clutch size among individuals of a population is driven by "individual quality").

I write that I am not sure, because in its current form, the manuscript does not contain a single equation, making it impossible to assess. It would need at least a set of mathematical descriptions for the statistical analysis and for the mechanistic model that the authors infer from it.<br /> The texts mixes concepts of individual vs population statistics, of within individual vs among-individuals measures, of allocation trade-offs and fitness trade-offs, etc ....which means it would also require a glossary of the definitions the authors use for these various terms, in order to be evaluated.

This problem is emphasised by the following sentence to be found in the discussion "The effect of birds having naturally larger clutches was significantly opposite to the result of increasing clutch size through brood manipulation". The "effect" is defined as the survival rate (see Fig 1). While it is relatively easy to intuitively understand what the "effect" is for the unmanipulated studies: the sensitivity of survival to clutch size at the population level, this should be mentioned and detailed in a formula. Moreover, the concept of effect size is not at all obvious for the manipulated ones (effect of the manipulation? or survival rate whatever the manipulation (then how could it measure a trade-off ?)? at the population level? at the individual level ?) despite a whole appendix dedicated to it. This absolutely needs to be described properly in the manuscript.

Despite the lack of information about the underlying mechanistic model tested and the statistical model used, my impression is still that the interpretation in the introduction and discussion is not granted by the outputs of the figures and tables. Let's use a model similar to that of (van Noordwijk and de Jong, 1986): imagine that the mechanism at the population level is<br /> a.c_(i,q)+b.s_(i,q)=E_q<br /> Where c_(i,q) are s_(i,q) are respectively the clutch size for individual i which is of quality q, and E_q is the level of "energy" that an individual of quality q has available during the given time-step (and a and b are constants turning the clutch size and survival rate into energy cost of reproduction and energy cost of survival, and there are both quite "high" so that an extra egg (c_(i,q) is increased by 1) at the current time-step, decreases s_(i,q) markedly (E_q is independent of the number of eggs produced), that is, we have strong individual costs of reproduction). Imagine now that the variance of c_(i,q) (when the population is not manipulated) among individuals of the same quality group, is very small (and therefore the variance of s_(i,q) is very small also) and that the expectation of both are proportional to E_q. Then, in the unmanipulated population, the variance in clutch size is mainly due to the variance in quality. And therefore, the larger the clutch size c_(i,q) the higher E_q, and the higher the survival s_(i,q).<br /> In the manipulated populations however, because of the large a and b, an artificial increase in clutch size, for a given E_q, will lead to a lower survival s_(i,q). And the "effect size" at the population level may vary according to a,b and the variances mentioned above. In other words, the costs of reproduction may be strong, but be hidden by the data, when there is variance in quality; however there are actually strong costs of reproduction (so strong actually that they are deterministic and that the probability to survive is a direct function of the number of eggs produced)

Moreover, it seems to me that the costs of reproduction are a concept closely related to generation time. Looking beyond the individual allocative (and other individual components of the trade-off) cost of reproduction and towards a populational negative relationship between survival and reproduction, we have to consider the intra-population slow fast continuum (some types of individuals survive more and reproduce less (are slower) than other (which are faster)). This continuum is associated with a metric: the generation time. Some individuals will produce more eggs and survive less in a given time-period because this time-period corresponds to a higher ratio of their generation time (Gaillard and Yoccoz, 2003; Gaillard et al., 2005). It seems therefore important to me, to control for generation time and in general to account for the time-step used for each population studied when analysing costs of reproduction. The data used in this manuscript is not just clutch size and survival rates, but clutch size per year (or another time step) and annual (or other) survival rates.

Finally, it is important to relate any study of the costs of reproduction in a context of individual heterogeneity (in quality for instance), to the general problem of the detection of effects of individual differences on survival (see, e.g., Fay et al., 2021). Without an understanding of the very particular statistical behaviour of survival, associated to an event that by definition occurs only once per life history trajectory (by contrast to many other traits, even demographic, where the corresponding event (production of eggs for reproduction, for example) can be measured several times for a given individual during its life history trajectory).

References:<br /> Fay, R. et al. (2021) 'Quantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variables', Methods in Ecology and Evolution, 2021(August), pp. 1-14. doi: 10.1111/2041-210x.13728.<br /> Gaillard, J.-M. et al. (2005) 'Generation time: a reliable metric to measure life-history variation among mammalian populations.', The American naturalist, 166(1), pp. 119-123; discussion 124-128. doi: 10.1086/430330.<br /> Gaillard, J.-M. and Yoccoz, N. G. (2003) 'Temporal Variation in Survival of Mammals: a Case of Environmental Canalization?', Ecology, 84(12), pp. 3294-3306. doi: 10.1890/02-0409.<br /> van Noordwijk, A. J. and de Jong, G. (1986) 'Acquisition and Allocation of Resources: Their Influence on Variation in Life History Tactics', American Naturalist, p. 137. doi: 10.1086/284547.

Reviewer #1 (Public Review):

The authors present a scRNAseq study describing the transcriptomes of the tendon enthesis during postnatal development. This is an important topic that has major implication for the care of common clinical problems such as rotator cuff repair. The results are a valuable addition to the literature, providing a descriptive data set reinforcing other, more comprehensive studies. There are weaknesses, however, in the scRNAseq analyses.

1.The authors should provide additional rationale for the PCA analysis shown in Fig 1d. It is uncommon to use PCA for histomorphologic parameters. These results do not convincingly demonstrate that P7 is as a critical developmental timepoint.

2. According to the methods, it appears that the entire humeral head-supraspinatus tendon was used for cell isolation for scRNAseq. This results in the inclusion of cells from a variety of tissues, including bone, growth plate, enthesis and tendon. As such, only a very small percentage of cells in the analysis came from the enthesis. Inclusion of such a wide range of cells makes interpretation of enthesis cells difficult.

3. The differentiation/pseudotime analysis described in Fig 3 is difficult to follow. This map includes cell transcriptomes from vastly different tissues. Presumably, embedded in these maps are trajectories for osteoblast differentiation, chondrocyte differentiation, tenocyte differentiation, etc. With so many layers of overlapping information, it is difficult to (algorithmically) deduce a differentiation path of a particular cell type.

4. The authors uses the term "function" throughout the paper (e.g., "functional definition of fibrocartilage subpopulations"). However, this is a descriptive scRNAseq study, and "function" can therefore only theoretically be inferred from the algorithms used to analyze the data. A functional role for any of the identified pathways or processes can only be defined with gain- and/or loss-of-function studies.

5. "C2 highly expressed biomineralization-related genes (Clec3a, Tnn, Acan)". The three example genes are not related to biomineralization.

6. The functional characterization of the three enthesis cell clusters is not convincing. For example, activation of metabolism-related processes can mean a lot of things (including changes in differentiation), yet the authors interpret it very specifically as "role in postnatal fibrochondrocyte formation and growth".

7. The pseudotime analysis of the enthesis cell clusters is not convincing. The three clusters are quite close and overlapping on the UMAP. Furthermore, the authors focus on Tnn as a novel and unique gene, yet the expression pattern shown in Fig 5g implies even expression of this gene across all three clusters.

8. The TC1 markers (Ly6a, Dlk3, Clec3b) imply a non-tendon-specific cell population. Perhaps a tendon progenitor pool or an endothelial cell phenotype is more appropriate.

9. Pseudotime analyses assume that your data set includes cells from progenitor through mature cell populations. It is unclear that the timepoints studied here included cells from early progenitor states.

10. The CellChat analysis is difficult to follow, as the authors included 18 cell types. The number of possible interactions among so many cell types is enormous, and deducing valid connections between any two cell types in this case should be justified. Is the algorithm robust to so many possible interactions?

Reviewer #2 (Public Review):

To reveals cellular and molecular heterogeneity in enthesis, the authors established a single-cell temporal atlas during development. This study provides a transcriptional resource for further investigation of fibrocartilage development.

Reviewer #2 (Recommendations for the authors):

1. As known, Fei Fang et al. have established single-cell transcriptomes of mouse supraspinatus tendon enthesis cells (Cell Stem Cell, 2022). It is suggested that the authors introduced Fei Fang et al.'s work in Introduction and emphasize the significant novelty compared with Fei Fang et al.'s work.<br /> 2. In Fig1, the authors highlighted P7 was a critical stage for enthesis differentiation. But this section was less associated with the following content. The authors should link these results with the scRNASeq data. Is there any time-dependent change/signaling in scRNASeq data at this critical time point?<br /> 3. In the H&E staining of Fig1a, the tendon structure was separated and random. It is suggested that the authors provide high-quality staining figures.<br /> 4. Fig2 showed that the Scx+ or Sox9+ cells was decreased in enthesis over time. At least it should be co-staining to show the distribution and frequency of double positive and single positive cell populations. However, a previous study has demonstrated this finding (PLOS ONE, 2020). It is suggested to verify some new findings by IF or IHC staining.<br /> 5. There are some conflicts about trajectory analysis. In Fig3c, RNA velocity showed that the arrow flowed from BTJ to MTJ and CTFb. However, in Fig3d, PAGA plot indicated that BTJ cells is independent of other cells. Furthermore, in supplementary figure S3, RNA velocity showed that the trajectory flowed from TC to BTJ. These figures were inconsistent with the described results. Please provide detailed explanation to avoid misleading readers.<br /> 6. Fig5 showed that C1 was the original cluster, and whether C1 cluster expressed canonical progenic/stem cell markers.<br /> 7. The authors performed cell-cell interaction based on cellchat analysis. But the cell-cell interaction was not actively examined.

Reviewer #3 (Public Review):

This manuscript describes the use of scRNA-seq to decipher the cellular heterogeneity, molecular dynamics and signaling interactions during fibrocartilaginous enthesis formation. They delineate the enthesis growth and the temporal atlas from embryonic stage to postnatal stage by scRNA-seq, compared the development pattern of enthesis origins with tendon and articular cartilage, then demonstrated the cellular complexity and heterogeneity of postnatal enthesis growth and revealed the molecular dynamics and signaling networks during enthesis formation.

This manuscript used appropriate and validated methodology in line with current state-of-the-art, and the conclusions of this paper are mostly well supported by data, more in vitro or in vivo experiments are encouraged to verify the key molecular dynamics and signaling networks revealed by scRNA-seq during enthesis formation.

This manuscript facilitates better understand of the enthesis development, which will benefit the important field of enthesis research.

Reviewer #1 (Public Review):

This study examines the factors underlying the assembly of MreB, an actin family member involved in mediating longitudinal cell wall synthesis in rod-shaped bacteria. Required for maintaining rod shape and essential for growth in model bacteria, single molecule work indicates that MreB forms treadmilling polymers that guide the synthesis of new peptidoglycan along the longitudinal cell wall. MreB has proven difficult to work with and the field is littered with artifacts. In vitro analysis of MreB assembly dynamics has not fared much better as helpfully detailed in the introduction to this study. In contrast to its distant relative actin, MreB is difficult to purify and requires very specific conditions to polymerize that differ between groups of bacteria. Currently, in vitro analysis of MreB and related proteins has been mostly limited to MreBs from Gram-negative bacteria which have different properties and behaviors from related proteins in Gram-positive organisms.

Here, Mao and colleagues use a range of techniques to purify MreB from the Gram-positive organism Geobacillus stearothermophilus, identify factors required for its assembly, and analyze the structure of MreB polymers. Notably, they identify two short hydrophobic sequences-located near one another on the 3-D structure-which are required to mediate membrane anchoring.

With regard to assembly dynamics, the authors find that Geobacillus MreB assembly requires both interactions with membrane lipids and nucleotide binding. Nucleotide hydrolysis is required for interaction with the membrane and interaction with lipids triggers polymerization. These experiments appear to be conducted in a rigorous manner, although the salt concentration of the buffer (500mM KCl) is quite high relative to that used for in vitro analysis of MreBs from other organisms. The authors should elaborate on their decision to use such a high salt buffer, and ideally, provide insight into how it might impact their findings relative to previous work.

Additionally, this study, like many others on MreB, makes much of MreB's relationship to actin. This leads to confusion and the use of unhelpful comparisons. For example, MreB filaments are not actin-like (line 58) any more than any polymer is "actin-like." As evidenced by the very beautiful images in this manuscript, MreB forms straight protofilaments that assemble into parallel arrays, not the paired-twisted polymers that are characteristic of F-actin. Generally, I would argue that work on MreB has been hindered by rather than benefitted from its relationship to actin (E.g early FP fusion data interpreted as evidence for an MreB endoskeleton supporting cell shape or depletion experiments implicating MreB in chromosome segregation) and thus such comparisons should be avoided unless absolutely necessary.

Reviewer #2 (Public Review):

The paper "Polymerization cycle of actin homolog MreB from a Gram-positive bacterium" by Mao et al. provides the second biochemical study of a gram-positive MreB, but importantly, the first study examines how gram-positive MreB filaments bind to membranes. They also show the first crystal structure of a MreB from a Gram-positive bacterium - in two nucleotide-bound forms, finally solving structures that have been missing for too long. They also elucidate what residues in Geobacillus MreB are required for membrane associations. Also, the QCM-D approach to monitoring MreB membrane associations is a direct and elegant assay.

While the above findings are novel and important, this paper also makes a series of conclusions that run counter to multiple in vitro studies of MreBs from different organisms and other polymers with the actin fold. Overall, they propose that Geobacillus MreB contains biochemical properties that are quite different than not only the other MreBs examined so far but also eukaryotic actin and every actin homolog that has been characterized in vitro. As the conclusions proposed here would place the biochemical properties of Geobacillus MreB as the sole exception to all other actin fold polymers, further supporting experiments are needed to bolster these contrasting conclusions and their overall model.

1. (Difference 1) - The predominant concern about the in vitro studies that makes it difficult to evaluate many of their results (much less compare them to other MreB/s and actin homologs) is the use of a highly unconventional polymerization buffer containing 500(!) mM KCL. As has been demonstrated with actin and other polymers, the high KCl concentration used here (500mM) is certain to affect the polymerization equilibria, as increasing salt increases the hydrophobic effect and inhibits salt bridges, and therefore will affect the affinity between monomers and filaments. For example, past work has shown that high salt greatly changes actin polymerization, causing: a decreased critical concentration, increased bundling, and a greatly increased filament stiffness(Kang et al., 2013, 2012). Similarly, with AlfA, increased salt concentrations have been shown to increase the critical concentration, decrease the polymerization kinetics, and inhibit the bundling of AlfA filaments (Polka et al., 2009). A more closely related example comes from the previous observation that increasing salt concentrations increasingly slow the polymerization kinetics of B. subtilis MreB (Mayer and Amann, 2009). Lastly, These high salt concentrations might also change the interactions of MreB(Gs) with the membrane by screening charges and/or increasing the hydrophobic effect.

Given that 500mM KCl was used throughout this paper, many (if not all) of the key experiments should be repeated in more standard salt concentration (~100mM), similar to those used in most previous in vitro studies of polymers. This would test if the many divergent properties of MreB(Gs) reported here arise from some difference in MreB(Gs) relative to other MreBs (and actin homologs), or if they arise from the 400mM difference in salt concentration between the studies. Critically, it would also allow direct comparisons to be made relative to previous studies of MreB (and other actin homologs) that used much lower salt, thereby allowing them to definitively demonstrate whether MreB(Gs) is indeed an outlier relative to other MreB and actin homologs. I would suggest using 100mM KCL, as historically, all polymerization assays of actin and numerous actin homologs have used 50-100mM KCL: 50mM KCl (for actin in F buffer) or 100mM KCl for multiple prokaryotic actin homologs and MreB (Deng et al., 2016; Ent et al., 2014; Esue et al., 2006, 2005; Garner et al., 2004; Polka et al., 2009; Rivera et al., 2011; Salje et al., 2011) Likewise, similar salt concentrations are standard for tubulin (80 mM K-Pipes) and FtsZ (100 mM KCl or 100mM KAc in HMK100 buffer).

2. (Difference 2) - One of the most important differences claimed in this paper is that MreB(Gs) filaments are straight, a result that runs counter to the curved T. Maritima and C. crescentus filaments detailed by the Löwe group (Ent et al., 2014; Salje et al., 2011). Importantly, this difference could also arise from the difference in salt concentrations used in each study (500mM here vs. 100mM in the Löwe studies), and thus one cannot currently draw any direct comparisons between the two studies.

One example of how high salt could be causing differences in filament geometry: high salts are known to greatly increase the bending stiffness of actin filaments, making them more rigid (Kang et al., 2013). Likewise, increasing salt is known to change the rigidity of membranes. As the ability of filaments to A) bend the membrane or B) Deform to the membrane depends on the stiffness of filaments relative to the stiffness of the membrane, the observed difference in the "straight vs. curved" conformation of MreB filaments might simply arise from different salt concentrations.

Thus, in order to draw several direct comparisons between their findings and those of other MreB orthologs (as done here), the studies of MreB(GS) confirmations on lipids should be repeated at the same buffer conditions as used in the Löwe papers, then allowing them to be directly compared.

3. (Difference 3) - The next important difference between MreB(Gs) and other MreBs is the claim that MreB polymers do not form in the absence of membranes.

A) This is surprising relative to other MreBs, as MreBs from 1) T. maritime (multiple studies), E.coli (Nurse and Marians, 2013), and C. crescentus (Ent et al., 2014) have been shown to form polymers in solution (without lipids) with electron microscopy, light scattering, and time-resolved multi-angle light scattering. Notably, the Esue work was able to observe the first phase of polymer formation and a subsequent phase of polymer bundling (Esue et al., 2006) of MreB in solution. 2) Similarly, (Mayer and Amann, 2009) demonstrated B. subtilis MreB forms polymers in the absence of membranes using light scattering.

B) The results shown in figure 5A also go against this conclusion, as there is only a 2-fold increase in the phosphate release from MreB(Gs) in the presence of membranes relative to the absence of membranes. Thus, if their model is correct, and MreB(Gs) polymers form only on membranes, this would require the unpolymerized MreB monomers to hydrolyze ATP at 1/2 the rate of MreB in filaments. This high relative rate of hydrolysis of monomers compared to filaments is unprecedented. For all polymers examined so far, the rate of monomer hydrolysis is several orders of magnitude less than that of the filament. For example, actin monomers are known to hydrolyze ATP 430,000X slower than the monomers inside filaments (Blanchoin and Pollard, 2002; Rould et al., 2006).

C) Thus, there is a strong possibility that MreB(Gs) polymers are indeed forming in solution in addition to those on the membrane, and these "solution polymers" may not be captured by their electron microscopy assay. For example, high salt could be interfering with the absorption of filaments to glow discharged lacking lipids.<br /> In order to definitively prove that MreB(Gs) does not have polymers in solution, the authors should:

i) conduct orthogonal experiments to test for polymers in solution. The simplest test of polymerization might be conducting pelleting assays of MreB(Gs) with and without lipids, sweeping through the concentration range as done in 2B and 5a.

ii) They also could examine if they see MreB filaments in the absence of lipids at 100mM salt (as was seen in both Löwe studies), as the high salt used here might block the charges on glow discharged grids, making it difficult for the polymer to adhere.

iii) Likewise, the claim that MreB lacking the amino-terminus and the α2β7 hydrophobic loop "is required for polymerization" is questionable as if deleting these resides blocks membrane binding, the lack of polymers on the membrane on the grid is not unexpected, as these filaments that cannot bind the membrane would not be observable. Given these mutants cannot bind the membrane, mutant polymers could still indeed exist in solution, and thus pelleting assays should be used to test if non-membrane associated filaments composed of these mutants do or do not exist.

A final note, the results shown in "Figure 1 - figure supplement 2, panel C" appear to directly refute the claim that MreB(Gs) requires lipids to polymerize. As currently written, it appears they can observe MreB(Gs) filaments on EM grids without lipids. If these experiments were done in the presence of lipids, the figure legend should be updated to indicate that. If these experiments were done in the absence of lipids, the claim that membrane association is required for MreB polymerizations should be revised.

4. (Difference 4) - The next difference between this study and previous studies of MreB and actin homologs is the conclusion that MreB(Gs) must hydrolyze ATP in order to polymerize. This conclusion is surprising, given the fact that both T. Maritima (Salje · 2011, Bean 2008) and B. subtilis MreB (Mayer 2009) have been shown to polymerize in the presence of ATP as well as AMP-PNP. Likewise, MreB polymerization has been shown to lag ATP hydrolysis in not only T. maritima MreB (Esue 2005), eukaryotic actin, and all other prokaryotic actin homologs whose polymerization and phosphate release have been directly compared: MamK (Deng et al., 2016), AlfA (Polka et al., 2009), and two divergent ParM homologs (Garner et al., 2004; Rivera et al., 2011).

Currently, the only piece of evidence supporting the idea that MreB(Gs) must hydrolyze ATP in order to polymerize comes from 2 observations: 1) using electron microscopy, they cannot see filaments of MreB(Gs) on membranes in the presence of AMP-PNP or ApCpp, and 2) no appreciable signal increase appears testing AMPPNP- MreB(Gs) using QCM-D. This evidence is by no means conclusive enough to support this bold claim: While their competition experiment does indicate AMPPNP binds to MreB(Gs), it is possible that MreB(Gs) cannot polymerize when bound to AMPPNP. For example, it has been shown that different actin homologs respond differently to different non-hydrolysable analogs: Some, like actin, can hydrolyze one ATP analog but not the other, while others are able to bind to many different ATP analogs but only polymerize with some of one of them. Thus, to further verify their "hydrolysis is needed for polymerization" conclusion, they should:<br /> A. Test if a hydrolysis deficient MreB(Gs) mutant (such as D158A) is also unable to polymerize by EM.<br /> B. They also should conduct an orthogonal assay of MreB polymerization aside from EM (pelleting assays might be the easiest). They should test if polymers of ATP, AMP-PNP, and MreB(Gs)(D158A) form in solution (without membranes) by conducting pelleting assays. These could also be conducted with and without lipids, thereby also addressing the points noted above in point 3.<br /> C. Polymers may indeed form with ATP-gamma-S, and this non-hydrolysable ATP analog should be tested.<br /> D. They could also test how the ADP-Phosphate bound MreB(Gs) polymerizes in bulk and on membranes, using beryllium phosphate to trap MreB in the ADP-Pi state. This might allow them to further refine their model.<br /> E. Importantly, the Mayer study of B. subtilis MreB found the same results in regard to nucleotides, "In polymerization buffer, MreB produced phosphate in the presence of ATP and GTP, but not in ADP, AMP, GDP or AMP-PNP, or without the readdition of any nucleotide". Thus this paper should be referenced and discussed

5. (Difference 5) - The introduction states (lines 128-130) "However, the need for nucleotide binding and hydrolysis in polymerization remains unclear due to conflicting results, in vivo and in vitro, including the ability of MreB to polymerize or not in the presence of ADP or the non-hydrolyzable ATP analog AMP-PNP."

A) While this is a great way to introduce the problem, the statement is a bit vague and should be clarified, detaining the conflicting results and appropriate references. For example, what conflicting in vivo results are they referring to? Regarding "MreB polymerization in AMP-PNP", multiple groups have shown the polymerization of MreB(Tm) in the presence of AMP-PNP, but it is not clear what papers found opposing results.

B) The statement "However, the need for nucleotide binding and hydrolysis in polymerization remains unclear due to conflicting results, in vivo and in vitro, including the ability of MreB to polymerize or not in the presence of ADP or the non-hydrolyzable ATP analog AMP-PNP" is technically incorrect and should be rephrased or further tested.

i. For all actin (or tubulin) family proteins, it is not that a given filament "cannot polymerize" in the presence of ADP but rather that the ADP-bound form has a higher critical concentration for polymer formation relative to the ATP-bound form. This means that the ADP polymers can indeed polymerize, but only when the total protein exceeds the ADP critical concentration. For example, many actin-family proteins do indeed polymerize in ADP: ADP actin has a 10-fold higher critical concentration than ATP actin, (Pollard, 1984) and the ADP critical concentrations of AlfA and ParM are 5X and 50X fold higher (respectively) than their ATP-bound forms(Garner et al., 2004; Polka et al., 2009)

ii. Likewise, (Mayer and Amann, 2009) have already demonstrated that B. subtilis MreB can polymerize in the presence of ADP, with a slightly higher critical concentration relative to the ATP-bound form.

Thus, to prove that MreB(Gs) polymers do not form in the presence of ADP would require one to test a large concentration range of ADP-bound MreB(Gs). They should test if ADP- MreB(Gs) polymerizes at the highest MreB(Gs) concentrations that can be assayed. Even if this fails, it may be the MreB(Gs) ADP polymerizes at higher concentrations than is possible with their protein preps (13uM). An even more simple fix would be to simply state MreB(Gs)-ADP filaments do not form beneath a given MreB(Gs) concentration.

Other Points to address:

1. There are several points in this paper where the work by Mayer and Amann is ignored, not cited, or readily dismissed as "hampered by aggregation" without any explanation or supporting evidence of that fact.

A) Lines 100-101 - While the irregular 3-D formations seen formed by MreB in the Dersch 2020 paper could be interpreted as aggregates, stating that the results from specifically the Gaballah and Meyer papers (and not others) were "hampered by aggregation" is currently an arbitrary statement, with no evidence or backing provided. Overall, these lines (and others in the paper) dismiss these two works without giving any evidence to that point. Thus, they should provide evidence for why they believe all these papers are aggregation, or remove these (and other) dismissive statements.

One important note - There are 2 points indicating that dismissing the Meyer and Amann work as aggregation is incorrect: 1) the Meyer work on B. subtilis MreB shows both an ATP and a slightly higher ADP critical concentration. As the emergence of a critical concentration is a steady-state phenomenon arising from the association/dissociation of monomers (and a kinetically limiting nucleation barrier), an emergent critical concentration cannot arise from protein aggregation, critical concentrations only arise from a dynamic equilibrium between monomer and polymer. 2) Furthermore, Meyer observed that increased salt slowed and reduced B. subtilis MreB light scattering, the opposite of what one would expect if their "polymerization signal" was only protein aggregation, as higher salts should increase the rate of aggregation by increasing the hydrophobic effect.

B) Lines 113-137 -The authors reference many different studies of MreB, including both MreB on membranes and MreB polymerized in solution (which formed bundles). However, they again neglect to mention or reference the findings of Meyer and Amann (Mayer and Amann, 2009), as it was dismissed as "aggregation". As B. subtilis is also a gram-positive organism, the Meyer results should be discussed.

2. Lines 387-391 state the rates of phosphate release relative to past MreB findings: "These rates of Pi release upon ATP hydrolysis (~ 1 Pi/MreB in 6 min at 53{degree sign}C) are comparable to those observed for MreBTm and MreB(Ec) in vitro". While the measurements of Pi release AND ATP hydrolysis have indeed been measured for actin, this statement does not apply to MreB and should be corrected: All MreB papers thus far have only measured Pi release alone, not ATP hydrolysis at the same time. Thus, it is inaccurate to state "rates of Pi release upon ATP hydrolysis" for any MreB study, as to accurately determine the rate of Pi release, one must measure: 1. The rate of polymer over time, 2) the rate of ATP hydrolysis, and 3) the rate of phosphate release. For MreB, no one has, so far, even measured the rates of ATP hydrolysis and phosphate release with the same sample.

3. The interpretation of the interactions between monomers in the MreB crystal should be more carefully stated to avoid confusion. While likely not their intention, the discussions of the crystal packing contacts of MreB can appear to assume that the monomer-monomer contacts they see in crystals represent the contacts within actual protofilaments. One cannot automatically assume the observations of monomer-monomer contacts within a crystal reflect those that arise in the actual filament (or protofilament).

A) They state, "the apo form of MreBGs forms less stable protofilaments than its G- homologs ." Given filaments of the Apo form of MreB(GS) or b. subtilis have never been observed in solution, this statement is not accurate: while the contacts in the crystal may change with and without nucleotide, if the protein does not form polymers in solution in the apo state, then there are no "real" apo protofilaments, and any statements about their stability become moot. Thus this statement should be rephrased or appropriately qualified.

B) Another example: while they may see that in the apo MreB crystal, the loop of domain IB makes a *single* salt bridge with IIA and none with IIB. This contrasts with every actin, MreB, and actin homolog studied so far, where domain IB interacts with IIB. This might reflect the real contacts of MreB(Gs) in the solution, or it may be simply a crystal-packing artifact. Thus, the authors should be careful in their claims, making it clear to the reader that the contacts in the crystal may not necessarily be present in polymerized filaments.

4. lines 201-202 - "Polymers were only observed at a concentration of MreB above 0.55 μM (0.02 mg/mL)". Given this concentration dependence of filament formation, which appears the same throughout the paper, the authors could state that 0.55 μM is the critical concentration of MreB on membranes under their buffer conditions. Given the lack of critical concentration measurement in most of the MreB literature, this could be an important point to make in the field.

5. Both mg/ml and uM are used in the text and figures to refer to protein concentration. They should stick to one convention, preferably uM, as is standard in the polymer field.

6. Lines 77-78 - (Teeffelen et al., 2011) should be referenced as well in regard to cell wall synthesis driving MreB motion.

7. Line 90 - "Do they exhibit turnover (treadmill) like actin filaments?". This phrase should be modified, as turnover and treadmilling are two very different things. Turnover is the lifetime of monomers in filaments, while treadmilling entails monomer addition at one end and loss at the other. While treadmilling filaments cause turnover, there are also numerous examples of non-treadmilling filaments undergoing turnover: microtubules, intermediate filaments, and ParM. Likewise, an antiparallel filament cannot directionally treadmill, as there is no difference between the two filament ends to confer directional polarity.

8. Throughout the paper, the term aggregation is used occasionally to describe the polymerization shown in many previous MreB studies, almost all of which very clearly showed "bundled" filaments, very distinct entities from aggregates, as a bundle of polymers cannot form without the filaments first polymerizing on their own. Evidence to this point, polymerization has been shown to precede the bundling of MreB(Tm) by (Esue et al., 2005).

9. lines 106-108 mention that "The N-terminal amphipathic helix of E. coli MreB (MreBEc) was found to be necessary for membrane binding. " This is not accurate, as Salje observed that one single helix could not cause MreB to mind to the membrane, but rather, multiple amphipathic helices were required for membrane association (Salje et al., 2011). The Salje results imply that dimers (or further assemblies) of MreB drive membrane association, a point that should be discussed in regard to the question "What prompts the assembly of MreB on the inner leaflet of the cytoplasmic membrane?" posed on lines 86-87.

10. On lines 414-415, it is stated, "The requirement of the membrane for polymerization is consistent with the observation that MreB polymeric assemblies in vivo are membrane-associated only." While I agree with this hypothesis, it must be noted that the presence or absence of MreB polymers in the cytoplasm has not been directly tested, as short filaments in the cytoplasm would diffuse very quickly, requiring very short exposures (<5ms) to resolve them relative to their rate of diffusion. Thus, cytoplasmic polymers might still exist but have not been tested.

11. lines 429-431 state, "but polymerization in the presence of ADP was in most cases concluded from light scattering experiments alone, so the possibility that aggregation rather than ordered polymerization occurred in the process cannot be excluded."

A) If an increased light scattering signal is initiated by the addition of ADP (or any nucleotide), that signal must come from polymerization or multimerization. What the authors imply is that there must be some ADP-dependent "aggregation" of MreB, which has not been seen thus far for any polymer. Furthermore, why would the addition of ADP initiate aggregation?

B) Likewise, the statement "Differences in the purity of the nucleotide stocks used in these studies could also explain some of the discrepancies" is unexplained and confusing. How could an impurity in a nucleotide stock affect the past MreB results, and what is the precedent for this claim?

12. lines 467-469 state, "Thus, for both MreB and actin, despite hydrolyzing ATP before and after polymerization, respectively, the ADP-Pi-MreB intermediate would be the long-lived intermediate state within the filaments."

A) For MreB, this statement is extremely speculative and unbiased, as no one has measured 1) polymerization, 2) ATP hydrolysis, and 3) phosphate release. For example, it could be that ATP hydrolysis is slow, while phosphate release is fast, as is seen in the actin from Saccharomyces cerevisiae.

B) For actin, the statement of hydrolysis of ATP of monomer occurring "before polymerization" is functionally irrelevant, as the rate of ATP hydrolysis of actin monomers is 430,000 times slower than that of actin monomers inside filaments(Blanchoin and Pollard, 2002; Rould et al., 2006).

13. Lines 442-444. "On the basis of our data and the existing literature, we propose that the requirement for ATP (or GTP) hydrolysis for polymerization may be conserved for most MreBs." Again, this statement both here (and in the prior text) is an extremely bold claim, one that runs contrary to a large amount of past work on not just MreB, but also eukaryotic actin and every actin homolog studied so far. They come to this model based on 1) one piece of suggestive data (the behavior of MreB(GS) bound to 2 non-hydrolysable ATP analogs in 500mM KCL), and 2) the dismissal (throughout the paper) of many peer-reviewed MreB papers that run counter to their model as "aggregation" or "contaminated ATP stocks ." If they want to make this bold claim that their finding invalidates the work of many labs, they must back it up with further validating experiments.

References cited.

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Deng A, Lin W, Shi N, Wu J, Sun Z, Sun Q, Bai H, Pan Y, Wen T. 2016. In vitro assembly of the bacterial actin protein MamK from 'Candidatus Magnetobacterium casensis' in the phylum Nitrospirae. Protein Cell 7:267-280. doi:10.1007/s13238-016-0253-x

Dersch S, Reimold C, Stoll J, Breddermann H, Heimerl T, Soufo HJD, Graumann PL. 2020. Polymerization of Bacillus subtilis MreB on a lipid membrane reveals lateral co-polymerization of MreB paralogs and strong effects of cations on filament formation. Bmc Mol Cell Biology 21:76. doi:10.1186/s12860-020-00319-5

Ent F van den, Izoré T, Bharat TA, Johnson CM, Lowe J. 2014. Bacterial actin MreB forms antiparallel double filaments. eLife 3:e02634. doi:10.7554/elife.02634

Esue O, Cordero M, Wirtz D, Tseng Y. 2005. The Assembly of MreB, a Prokaryotic Homolog of Actin. J Biol Chem 280:2628-2635. doi:10.1074/jbc.m410298200

Esue O, Wirtz D, Tseng Y. 2006. GTPase Activity, Structure, and Mechanical Properties of Filaments Assembled from Bacterial Cytoskeleton Protein MreB. J Bacteriol 188:968-976. doi:10.1128/jb.188.3.968-976.2006

Garner EC, Campbell CS, Mullins RD. 2004. Dynamic instability in a DNA-segregating prokaryotic actin homolog. Science (New York, NY) 306:1021-1025. doi:10.1126/science.1101313

Kang H, Bradley MJ, Elam WA, De La Cruz EM. 2013. Regulation of Actin by Ion-Linked Equilibria. Biophys J 105:2621-2628. doi:10.1016/j.bpj.2013.10.032

Kang H, Bradley MJ, McCullough BR, Pierre A, Grintsevich EE, Reisler E, Cruz EMDL. 2012. Identification of cation-binding sites on actin that drive polymerization and modulate bending stiffness. Proc National Acad Sci 109:16923-16927. doi:10.1073/pnas.1211078109

Mayer JA, Amann KJ. 2009. Assembly properties of the Bacillus subtilis actin, MreB. Cell Motil Cytoskel 66:109-118. doi:10.1002/cm.20332

Nurse P, Marians KJ. 2013. Purification and Characterization of Escherichia coli MreB Protein. J Biol Chem 288:3469-3475. doi:10.1074/jbc.m112.413708

Polka JK, Kollman JM, Agard DA, Mullins RD. 2009. The Structure and Assembly Dynamics of Plasmid Actin AlfA Imply a Novel Mechanism of DNA Segregation. J Bacteriol 191:6219-6230. doi:10.1128/jb.00676-09

Pollard TD. 1984. Polymerization of ADP-actin. J Cell Biology 99:769-777. doi:10.1083/jcb.99.3.769

Rivera CR, Kollman JM, Polka JK, Agard DA, Mullins RD. 2011. Architecture and assembly of a divergent member of the ParM family of bacterial actin-like proteins. The Journal of biological chemistry 286:14282-14290. doi:10.1074/jbc.m110.203828

Rould MA, Wan Q, Joel PB, Lowey S, Trybus KM. 2006. Crystal Structures of Expressed Non-polymerizable Monomeric Actin in the ADP and ATP States*. J Biol Chem 281:31909-31919. doi:10.1016/s0021-9258(19)84105-4

Salje J, van den Ent F, de Boer P, Löwe J. 2011. Direct Membrane Binding by Bacterial Actin MreB. Mol Cell 43:478-487. doi:10.1016/j.molcel.2011.07.008

Teeffelen S van, Wang S, Furchtgott L, Huang KC, Wingreen NS, Shaevitz JW, Gitai Z. 2011. The bacterial actin MreB rotates, and rotation depends on cell-wall assembly. Proceedings of the National Academy of Sciences of the United States of America 108:15822-15827. doi:10.1073/pnas.1108999108

Reviewer #3 (Public Review):

The major claim from the paper is the dependence of two factors that determine the polymerization of MreB from a Gram-positive, thermophilic bacteria 1) The role of nucleotide hydrolysis in driving the polymerization. 2) Lipid bilayer as a facilitator/scaffold that is required for hydrolysis-dependent polymerization. These two conclusions are contrasting with what has been known until now for the MreB proteins that have been characterized in vitro. The experiments performed in the paper do not completely justify these claims as elaborated below.

Major comments:

1. No observation of filaments in the absence of lipid monolayer can also be accounted due to the higher critical concentration of polymerization for MreBGS in that condition. It is seen that all the negative staining without lipid monolayer condition has been performed at a concentration of 0.05 mg/mL. It is important to check for polymerization of the MreBGS at higher concentration ranges as well, in order to conclusively state the requirement of lipids for polymerization.

2. The absence of filaments for the non-hydrolysable conditions in the lipid layer could also be because the filaments that might have formed are not binding to the planar lipid layer, and not necessarily because of their inability to polymerize.

3. Given the ATPase activity measurements, it is not very convincing that ATP rather than ADP will be present in the structure. The ATP should have been hydrolysed to ADP within the structure. The structure is now suggestive that MreB is not capable of hydrolysis, which is contradictory to the ATP hydrolysis data.

Reviewer #1 (Public Review):

In this paper, the authors tried to elucidate specific neuronal microRNAs which play an important role in the assembly of hippocampal networks. Using expression screening, they narrowed down on the microRNA miR-218, which is abundantly expressed at early postnatal stages of hippocampal development. Using different loss-of-function tools (antisense oligonucleotides, conditional microRNA knockout mice), they found that miR-218 inhibition early in life leads to a higher susceptibility of mice to develop epileptic seizures, as well as subtle behavioural alterations. These phenotypes were accompanied by disruption of early depolarizing GABAergic signaling, structural defects in dendritic spines, and altered intrinsic membrane excitability. An important role for miR-218 specifically in GABAergic interneurons is supported by the use of mice with an interneuron-specific loss of miR-218. However, the authors do not directly address which of the cellular phenotypes is causally involved in seizure susceptibility and behavioural alterations. Moreover, the authors describe molecular changes in interneurons and pyramidal neurons which are resulting from miR-218 inhibition in the mouse hippocampus. However, the identity of molecular pathways downstream of miR-218 in the context of epileptic seizures and behaviour remains unexplored.

Altogether, this study has a potentially high impact on the field of neuronal microRNA research and more specifically neuronal circuit assembly. The methods will be of high relevance for the microRNA community studying microRNA function in the context of early neural circuit development in mice in vivo. From a clinical point of view, these results could also increase our knowledge about the mechanisms of epileptic seizure development.

Reviewer #2 (Public Review):

The current study by Taylor and colleagues investigated the role of microRNA-218 in hippocampal development and discover that disturbances in miR-218 during a key developmental window can lead to persistent changes in network excitability which could have implications for neurodevelopmental and neurological diseases. They found that miR-218 is developmentally regulated in the mouse hippocampus and resides in both excitatory pyramidal neurons and interneurons. Using antagomirs (inhibitors) specifically targeted to miR-218 they find that persistent inhibition of miR-218 elevates network activity and renders mice more susceptible to seizures when challenged with a chemoconvulsant. Additionally antagomir treated mice displayed altered cognitive processing when compared to control-treated mice. Taylor and colleagues then identified potential pathways and targets through which miR-218 may exert control over network formation and stabilisation and identified cell-type-specific targets through which it may function. Overall they find that the activity of miR-218 and its effects on network development may be mediated through its activity in interneurons.

The conclusions of this paper are mostly excellently supported by extensive and advanced experimentation.

The data on miR-218 is the least convincing element of the paper but there are inherent difficulties in assessing miR-mediated targeting which the authors may have encountered. Firstly the justification for performing gene ontology on genes with an FC of greater than 0 must be included. Similarly, the use of p values of less than 0.2 lacks stringency and authors should specify why these parameters were chosen. Otherwise, the gene ontology data is difficult to interpret. Protein data may add to this section also.

The authors state they do not analyse known developmental miRs such as miR-124. But the reasoning behind this is not explained. As known developmental miRNAs, analysing their expression would add confidence to the data. Furthermore, the statistical significance of Fig 1B is unclear.

Reviewer #1 (Public Review):

The authors design a peptide, PITCR, that is similar to the transmembrane domain of the TCR zeta, but is rendered soluble by adding an additionally charged residue to the TM domain and changing basic residues in the cytoplasmic juxtamembrane sequence to acidic residues. Some other bulky hydrophobic resides were made smaller. The strategy was based on earlier work with EphA2 sequences reported in elife in 2018. The TCRzeta conditional TM peptide was then tested for effects on T cell receptor signalling, co-localisation, and effects on TCR stability in biochemical assays. Significant effects were detected and these were eliminated by a strong helix-breaking mutation. There are currently some limitations with the interpretation of the signaling and co-localization studies. The results will be of interest to those studying the TCR as well as those seeking to use the TCR or its derivatives in synthetic biology studies and immunotherapy.

Reviewer #2 (Public Review):

The authors present findings on a designed peptide, PITCR, and its role in inhibiting TCR activation through an extensive series of experiments. These include the measurement of phosphorylation in the TCR zeta chain and a number of associated signaling proteins such as Zap70, LAT, PLCg1, and SLP76. In addition, the authors measure the impact of PITCR on the TCR intracellular calcium response and examine the peptide-induced inhibition of TCR activation by antigen-presenting cells. They also present data indicating that the fluorescently labeled PITCR co-localizes with TCR in Jurkat cells and with ligand-bound TCR in primary murine cells.

Overall the experiments provide useful insights into the mechanism of T cell activation and generally support an allosteric model of activation, while not necessarily excluding alternative models.

However, some aspects of the study do need clarification.

1) The authors do not provide a clear structural basis for their peptide design, which makes it difficult to understand the rationale for choosing this particular peptide. The use of a structural model based on the TCR zeta domain, for example, and how it becomes modified to generate PITCR would provide some clarity on what types of putative interactions are being engineered.

2) The inhibitory effects of PITCR are not large. Measurement of dose dependence might improve confidence in the results.

3) Use of control peptides is not uniform. Control peptides similar to PITCR in Figure 1 and Figure 2 studies, for example, could strengthen the authors' arguments.

Reviewer #3 (Public Review):

In this study, Ye et al investigated how a peptide that binds to the transmembrane (TM) domain of the T cell receptor (TCR) subunits affects TCR activation. The objective was to test the allosteric relaxation model of TCR activation. To this end, the authors leveraged their previously established strategy of designing TM-targeting peptides and studied how such peptide alters the TCR activation and downstream signaling cascades in Jurkat T cells. The authors found that the TM-targeting peptide inhibited phosphorylation of the TCR submits, phosphorylation of downstream signaling proteins such as ZAP70, and calcium influx in T cells. Using immunoprecipitation experiments, the authors proposed that the peptide binds into the membrane gap between CD3 and CD3 subunits in the TCR complex. The authors conclude that their data support the allosteric TCR activation model, in which allosteric changes in the TM bundle in the TCR complex determine the receptor signaling.

The use of pH-responsive TM-targeting peptides, which the authors previously developed, is a novel aspect of this study. Those peptides can be quite powerful for understanding molecular mechanisms of receptor signaling, such as the allosteric activation model as tested in this study. The manuscript contains several interesting approaches and observations, but there are concerns about the experimental design and interpretation of the results. More importantly, the authors' primary conclusion that the allosteric changes in the TM bundles determine TCR activation is not fully supported by the data presented. For example:

1. The authors provided confocal fluorescence images showing the colocalization of fluorescently labeled peptides and TCR subunits. Based on the data, they concluded that "PITCR is able to bind to TCR". This is misleading, because given the spatial resolution of the imaging technique, "colocalization" does not indicate binding or interaction between molecules. Because the peptide binding to the TM region is the pillar of the primary finding of this study, direct evidence supporting the peptide-TM binding or interaction is essential.<br /> 2. In calcium response experiments, the authors compared calcium influx (indicated by Indo-1 ratio) under different cell activation conditions (Figure 2). There are some concerns about how the authors interpreted the data: (1) The calcium plots from OKT3 activation in A-C panels are inconsistent. The plot in (A) showed a calcium peak after activation, which is not present in the plots shown in (B) and (C). There is no explanation or discussion on this inconsistency. (2) What is more concerning is that this prominent calcium peak in (A) was used to draw the conclusion that the designer peptide inhibitor effectively reduces calcium response. However, inconsistent with that conclusion, the calcium plots are indistinguishable for the three conditions: with PITCR (peptide inhibitor), with PITCRG41P (negative control that should not affect TCR activation), or no peptide. All three plots have similar magnetite and fluctuations. This does not support the authors' conclusion that the PITCR (peptide inhibitor) reduces calcium response in T cells.<br /> 3. Different types of T cells were used for separate measurements: E6-1 Jurkat T cells were used for calcium influx experiments, J. OT.hCD8+ Jurkat cells were used for CD69 measurements, and primary murine CD4+ T cells were used for colocalization imaging experiments. Rationales for the choices of cells in different measurements are also unclear. This is different from the common practice where different cell types are used in repeated experiments to test the generality of a finding. Here, they were used for different experiments, and findings were lumped together as "T cells", without further evidence/discussion on how translatable the findings from different cell types are.<br /> 4. The authors set out to test the model that TCR activation by pMHC occurs through allosteric changes in the TM region, but in most experiments, they activated Jurkat T cells by anti-CD3 antibody, not by antigen peptides. The anti-CD3 antibody activates TCR signaling through clustering. It is unclear whether TCR activation by anti-CD3 leads to the same allosteric changes in the TM region as activation by pMHC.

As such, the main claim of the paper, namely that the designer peptide affects TCR signaling by disrupting the allosteric changes in the TM region, remains insufficiently supported by the data presented.

Reviewer #1 (Public Review):

This paper accomplishes the authors' goal of using two complementary CRISPR approaches to identify novel determinants of CTL killing in vitro. Through these screens, the authors identify two new genes, ILKAP and ICAM1, that both modulate CTL killing across different cancer cell types. The dissection of how different ICAM1 proteins (membrane-bound and secreted) was also performed in a rigorous fashion. The use of multiple unrelated cancer cell lines greatly increases the strength of the findings and potential future applicability. Major weaknesses of the manuscript first include how ILKAP is connected to the control of ICAM1, which is unclear from the data presented in the paper. Secondly, while the authors use many different mutational variants of ICAM1 to dissect its function, the specific role of each of these mutations is not well described. A rigorous examination of secreted ICAM1 on CTL killing is not presented, and since membrane-bound and secreted ICAM1 have opposing functions on CTL killing, the clinical relevance of modulating ICAM1 is unclear. Finally, the authors do not consider how ICAM1 may affect antigen-presenting cells and other myeloid cells in the tumor which are critical intermediaries in the antitumor immune response. Overall, once these points of weakness are addressed, this work is expected to have a high impact in the field, as it presents new targets outside the PD-L1 / PD-1 axis that may aid in CTL killing of tumors across multiple cancer types.

Reviewer #2 (Public Review):

Mattes et al. used a CRISPR screen to determine tumor-intrinsic factors modulating the efficacy of T cell-mediated cell lysis. For this purpose, colon carcinoma cell lines were modified with gain-of-function (CRISPRa) and loss-of-function (CRISPRi) sgRNA libraries. Modified colon cancer cells were subsequently exposed to antigen-specific tumor cell lysis by CD8+ cytotoxic T cells and surviving colon cancer cells were analyzed for over- and underrepresented genes. The screen replicated findings from previous studies showing the importance of IFNy, TNFa, and autophagy pathways for T cell-mediated lysis of cancer cells. In addition, the authors identified two genes involved in cell adhesion that modulate T cell-mediate cell lysis: ILKAP and ICAM1. Subsequently, the authors validate their findings in in-vitro experiments and show that a soluble form of ICAM1 is negatively affecting tumor cell lysis. Finally, they analyze publicly available gene expression data from cancer patient cohorts and show that high ICAM1 expression, in combination with high expression of genes associated with soluble ICAM1 generation, has a negative impact on patient survival. Beyond these findings, the CRISPR screening dataset from this study serves as a comprehensive resource for other researchers in the onco-immunology space.

The conclusions of this paper are well supported by data, but some aspects of the role of soluble ICAM1 in T cell-mediated tumor cell lysis and the limitations of the employed experimental system should be clarified and extended.

1. For their screening, the authors use an in-vitro model of antigen-specific tumor cell lysis based on expanded CMV-specific CD8+ T cells and CMV peptide-pulsed colon cancer cells. While this model allows for the efficient induction of cellular cytotoxicity by expanded primary T cells, it has one critical caveat: pulsing colon cancer cells with CMV peptide adds the antigen artificially to the MHC complex on the cell surface. Cell-intrinsic factors of antigen processing and presentation are not required for tumor cell recognition in this system. However, antigen processing and presentation pathways represent important targets of tumor evasion in cancer patients. Factors affecting these processes won't be detected in this study. To consider antigen processing and presentation as well, the authors could, for instance, have used an additional model with T cells containing a transgenic TCR specific for an antigen typically expressed on colon cancer cells (or another cancer cell line).

2. The authors demonstrate the negative impact of soluble ICAM1 on T cell-mediated cytotoxicity in their co-culture assay. However, they lack to provide evidence on how this is facilitated. One option, as the authors speculate in their discussion and cartoon, could be that soluble ICAM1 occupies LFA1 on T cells thereby preventing the binding of T cells to ICAM1 on the surface of tumor cells. To demonstrate that this is indeed the case, the authors could, for instance, have used microscopy and measured T cell and tumor cell interaction duration and frequency under conditions with and without soluble ICAM1 present.

3. Regarding the analysis of clinical relevance, the authors show that patients with high levels of ICAM1 expression in combination with high levels of protease expression have poor survival. The rationale behind this is that the proteases cleave ICAM1 off the membrane leading to high levels of soluble ICAM1 that then negatively affects T cell-mediate tumor cell lysis. To demonstrate that indeed the combination of both factors, ICAM1 expression, and protease expression, is responsible for poor survival, the authors should also have analyzed the impact of each of these factors alone on patient survival. If their hypothesis is true, the combination of high ICAM1 and protease expression should have a worse impact on survival than each factor alone.

Reviewer #1 (Public Review):

Blanch-Lombarte and colleagues demonstrated that the expression of certain inhibitory receptors (IRGs) on CD8 T cells is elevated in people living with HIV (PLWH) and they remain elevated despite years of viral suppression on antiretroviral therapy (ART). A comprehensive single-cell analysis by multiparametric flow cytometry demonstrated that TGIT+ CD8 T cells have a skewed phenotype following HIV infection. Blocking of TGIT partially restores the ability of CD8 T cells to produce CD107a but not the other functions.

Strengths of the current study include the comprehensive analysis of IRGs on CD8 T cells of a well-characterized group of individuals with and without HIV. Additionally, they have confirmed that blocking of TGIT should be evaluated further as a potential therapy for PLWH. The conclusions seem well justified from the presented data.

Weaknesses include the cross-sectional data and minor confusion stemming in part from the lack of clarity and rationale for some of the experiments.

Reviewer #2 (Public Review):

Antiretroviral therapy (ART) can control HIV replication and improve the quality of life for people living with HIV (PLWH); however, it does not cure infection, nor does it revert T cell exhaustion. Inhibitory receptor expression is a characteristic of CD8+ T cell exhaustion and a better understanding of the differences in receptor expression dynamics between healthy donors and PLWH on ART is of interest. In this comparative study, Blanch-Lombarte et al. use single-cell analysis of flow cytometric PBMC profiling to examine inhibitory receptor expression (IR) and functional markers in CD8+ T cells derived from PLWH on ART and healthy donors.

The authors first perform a mix of cross-sectional and longitudinal characterization of IR expression and memory differentiation markers in donors who are healthy controls, are in the early stages of HIV infection, PLWH on ART for ~ 2 years, and PLWH on ART for ~10 years. They conduct both supervised and unsupervised analyses of the phenotypic results. The authors use three experimental conditions (unstimulated, SEB stimulation, HIV Gag peptide pool stimulation) to perform cluster analyses. The longitudinal paired samples allow determination of the persistence of the alterations observed early after initiation of ART. The analyses show inverse correlations between frequencies of TIGIT+ and TIGIT+ TIM+ CD8 subsets and CD4 counts. However, findings for HIV-specific CD8 were different, with a selective reduction of TIGIT+ clusters whose functionality in terms of CD107 expression was recovered by anti-TIGIT blockade.

The authors conclude that TIGIT could be a therapeutic target to revive exhausted T cells (Tex) at all ART stages.

Strengths:<br /> - The study addressed relevant questions for the field.<br /> - The is a logical sequence of experiments and analyses.<br /> - The authors investigate interesting samples - longitudinal time points on ART several years apart are a significant asset.<br /> - Assessment of CD8 T cell populations as bulk unstimulated cells, broad stimulation with a superantigen (SEB), and HIV-specific responses (Gag peptide pool stimulation).<br /> - Complementary use of supervised and detailed unsupervised analyses of flow cytometry data.<br /> - The analyses are overall detailed and carefully presented, except for minor issues in color coding and font size.<br /> - Functional assays to assess the functional impact of TIGIT upregulation on CD8 T cell function.<br /> -<br /> Weaknesses:<br /> - While the paper reads overall well, the hypotheses and concepts should be clarified in several instances. For example, the authors speak of T cell exhaustion, which in principle is understood as antigen-specific T dysfunction associated with antigen persistence. However, a good part of the paper is focused on total CD8 T cells, and the links between findings in the different populations of CD8 examined (total, SEB-stimulated, Gag-stimulated) are hard to understand.<br /> - Upregulation of IRs can be associated with the state of T cell differentiation and also modulated by chronic inflammation independently of TCR signaling (eg, common gamma-chain cytokines upregulate PD-1), so defining these cells as univocally Tex is not correct.<br /> - The study mostly focuses on descriptive phenotypic analyses of CD8 T cells rather than dynamics studies which would imply more in-depth investigations of T cell evolution and fate.<br /> - HIV-specific CD8 T cells can be both quantitatively and quantitatively impaired, but the quantitative aspects are not considered, nor shifts in phenotype. For example, HIV-specific TIGIT+ CD8 responding to blockade proportionally over time - It is unclear if this is compensated by other subsets.<br /> - The functional assays with TIGIT blockade are limited and do not include other markers of cytotoxic cells (perforin, granzyme B expression...). It is not clear how do these subsets compare to the other clusters in terms of CD107 expression.<br /> - The statistical analyses do apparently not include correction for multiple comparisons.

Reviewer #3 (Public Review):

Here the authors use high-parameter flow cytometry to address expression patterns of inhibitory receptors and concordant functional responses in CD8+ T cells from people living with HIV (PLWH) during early vs. long-term ART treatment in order to understand the potential evolution of exhausted T cells in HIV infection. High-dimensional bioinformatic analysis is employed to uncover different subsets of CD8+ T cells expressing TIM-3, TIGIT, PD1, LAG3, and CD39. Stimulation assays were further conducted to assess polyclonal T cell responses (superantigen) or HIV-gag-specific CD8+ T cells, and whether the responding cells displayed inhibitory receptors. Finally, inhibitory receptor blockade was used (focusing on TIGIT and TIM-3 only) to examine the potential reversal of exhaustion. The authors found that CD107a+ degranulating central memory T cells apparently were sensitive to TIGIT blockade, yielding increased responses in cells from ART-treated PLWH.

Methods and Results Major Strengths: Sample size and data density. Longitudinal samples from long-term treated PLWH. Mechanistic studies to assess inhibitory receptor blockade.

Methods and Results Major Weaknesses: Lack of clarity on flow cytometric analysis and statistical methodology, including correction for multiple comparisons. Clustering density in tSNE analysis is unjustified, leading to potentially spurious outcomes. Insufficient raw flow cytometry data presented on inhibitory receptor expression in the various contexts of the study to allow determination of whether the subsequent bioinformatic analysis was merited due to the very low expression of 3/5 markers examined. Unclear whether differences observed are biologically meaningful (despite statistical differences). Finally, although the longitudinal samples are a distinct strength of the study, changes over time within individuals are unfortunately not assessed.

Aims and conclusions: The authors do find differences between the cohorts as described in the manuscript; however, the biological relevance of the findings is questionable due to an absence of direct studies on the cell populations found to be different. The use of unbiased clustering analysis is both a strength and a weakness. Specifically, the algorithm uncovers potential cell clusters that might be missed; however, the clustering program requires pre-set inputs on the expected number of clusters to be found, leading to possible irrelevant subsets being identified. The conclusions of the study are appropriately limited in scope.

Impact: There have been numerous studies of CD8+ T cell inhibitory receptor expression and T cell exhaustion in the context of HIV infection. It is well-accepted that T-cell exhaustion is a hallmark of progressive infection. This study contributes to the current knowledge in this area specifically through the examination of very long-term ART-treated PLWH. Unfortunately, it is not clear that several of the examined inhibitory receptors could be adequately detected, limiting the interpretation of the findings. Finally, it is unclear that this study justifies the potential use of TIGIT blockade to improve T cell function given the unclear biological relevance of the differential populations of CD8+ T cells observed.

Reviewer #2 (Public Review):

Summary:<br /> In the paper from Hartman, Vandenberg, and Hill entitled "assessing drug safety, by identifying the access of arrhythmia and cardio, myocytes, electro physiology", the authors, define a new metric, the axis of arrhythmia" that essentially describes the parameter space of ion channel conductance combinations, where early after depolarization can be observed.

Strengths:<br /> There is an elegance to the way the authors have communicated the scoring system. The method is potentially useful because of its simplicity, accessibility, and ease of use. I do think it adds to the field for this reason - a number of existing methods are overly complex and unwieldy and not necessarily better than the simple parameter regime scan presented here.

Weaknesses:<br /> The method described in the manuscript suffers from a number of weaknesses that plague current screening methods. Included in these are the data quality and selection used to inform the drug-blocking profile. It's well known that drug measurements vary widely, depending on the measurement conditions.

There doesn't seem to be any consideration of pacing frequency, which is an important consideration for arrhythmia triggers, resulting from repolarization abnormalities, but also depolarization abnormalities. Extremely high doses of drugs are used to assess the population risk. But does the method yield important information when realistic drug concentrations are used? In the discussion, the comparison to conventional approaches suggests that the presented method isn't necessarily better than conventional methods.

In conclusion, I have struggled to grasp the exceptional novelty of the new metric as presented, especially when considering that the badly needed future state must include a component of precision medicine.

Reviewer #1 (Public Review):

Summary:<br /> Heitmann et al introduce a novel method for predicting the potential of drug candidates to cause Torsades de Pointes using simulations. Despite the fact that a multitude of such methods have been proposed in the past decade, this approach manages to provide novelty in a way that is potentially paradigm-shifting. The figures are beautiful and manage to convey difficult concepts intuitively.

Strengths:<br /> (1) Novel combination of detailed mechanistic simulations with rigorous statistical modeling

(2) A method for predicting drug safety that can be used during drug development

(3) A clear explication of difficult concepts.

Weaknesses:<br /> (1) In this reviewer's opinion, the most important scientific issue that can be addressed is the fact that when a drug blocks multiple channels, it is not only the IC50 but also the Hill coefficient that can differ. By the same token, two drugs that block the same channel may have identical IC50s but different Hill coefficients. This is important to consider since concentration-dependence is an important part of the results presented here. If the Hill coefficients were to be significantly different, the concentration-dependent curves shown in Figure 6 could look very different.

(2) The curved lines shown in Figure 6 can initially be difficult to comprehend, especially when all the previous presentations emphasized linearity. But a further issue is obscured in these plots, which is the fact that they show a two-dimensional projection of a 4-dimensional space. Some of the drugs might hit the channels that are not shown (INaL & IKs), whereas others will not. It is unclear, and unaddressed in the manuscript, how differences in the "hidden channels" will influence the shapes of these curves. An example, or at least some verbal description, could be very helpful.

Reviewer #3 (Public Review):

Henault et al. address the important open question of whether hybridization could trigger TE mobilization. To do this they analysed MA lines derived from crosses of Saccharomyces paradoxus and Saccharomyces cerevisiae using long-read sequencing. These MA lines were already analysed in a previous publication using Illumina short-read data but the novelty of this work is the long-read sequencing data, which may reveal previously missed information. It is an interesting message of this study that hybridization between the two species did not lead to much TE activity. Due to this low activity, the authors performed an additional TE activity assay in vivo to measure transposition rates in hybrid backgrounds. The study is well written and I cannot spot any major problems. The study provides some important messages (like the influence of the genotype and mitochondrial DNA on transposition rates).

Major comments<br /> - What I miss the most in this work is the perspective of the host defence against TEs in Saccharmoces. Based on such a mechanistic perspective, why do the authors think that hybridization could lead to a TE reactivation? For example, in Drosophila small RNAs important for the defence against a TE, are solely maternally transmitted. Hybrid offspring will thus solely have small-RNAs complementary to the TEs of the mother but not to the TEs of the father, therefore a reactivation of the paternal TEs may be expected. I was thus wondering, what is the situation in yeast. Why would we expect an upregulation of TEs? Without such a mechanistic explanation the hypothesis that TEs should be upregulated in hybrids is a bit vague, based on a hunch.

Reviewer #1 (Public Review):

Henault et al build on their own previous work investigating the longstanding hypothesis that hybridization between divergent populations can activate transposable element mobilization (transposition). Previously they created crosses of increasing sequence divergence, using both intra- and inter-species hybrids, and passaged them neutrally for hundreds of generations. Their previous work showed that neither hybrids isolated from natural environments nor hybrids from their mutation accumulation lines showed consistent evidence of increased transposable element content. Here, they sequence and assemble long-read genomes of 127 of their mutation-accumulation lines and annotate all existing and de novo transposable elements. They find only a handful of de novo transposition events, and instead demonstrate that structural variation (ploidy, aneuploidy, loss of heterozygosity) plays a much larger role in the transposable element load in a given strain. They then created transposable element reporter constructs using two different Ty1 elements from S. paradoxus lineages and measured the transposition rate in a number of intraspecific crosses. They demonstrate that the transposition rate is dependent on both the Ty1 sequence and the copy number of genomic transposable elements, the latter of which is consistent with what has been observed in the literature on transposable element copy number control in Saccharomyces. To my knowledge, others have not directly tested the effect of Ty1 sequence itself (have not created diverse Ty1 reporter constructs), and so this is an interesting advance. Finally, the authors show that mitotype has a moderate effect on transposition rate, which is an intriguing finding that will be interesting to explore in future work.

This study represents a large effort to investigate how genetic background can influence transposable element load and transposition rate. The long read sequencing, assembly, and annotation, and the creation of these reporter constructs are non-trivial. Their results are straightforward, well supported, and a nice addition to the literature.

The authors state that the results from their current work support results taken from their previous study using short-read sequencing data of the same lines. The argument that follows is whether the authors gained anything novel from long-read sequencing. I would like to see the authors make a stronger argument for why this new work was necessary, and a more detailed view of similarities or differences from their previous study (when should others choose to do long read vs. short read of evolved lines?). Relatedly, the authors should report the rates of structural variants that they observe. How are these results similar/different from other mutation-accumulation work in S. cerevisiae?

Since the authors show a small, but consistent influence of mitotype on transposition rates, adding further evidence for the role of mtDNA in regulating transposition, I'm curious what the transposition rate of a p0 strain is. I think including these results could make this observation more compelling.

Reviewer #2 (Public Review):

This is an interesting follow-up study that uses long-read sequencing to examine previously constructed mutation accumulation lines between wild populations of S. cerevisiae and S. paradoxus. They also complement this work with reporter assays in hybrid backgrounds. The authors are attempting to test the hypothesis that hybridization leads to genome shock and unrestrained transposition. The paper largely confirms previous results (suggesting hybridization does not increase transposition) that are well cited and discussed in the paper, both from this group and from the Smukowski Heil/Dunham group but extends them to a new set of species/hybrids and with some additional resolution via the long read sequencing. The paper is well written and clear and I have no serious complaints.

In the abstract, the authors make three primary claims:

Structural variation plays a strong role in TE load.<br /> Transposition plays only a minor role in shaping the TE landscape in MA lines.<br /> Transposition rates are not increased by hybridization but are affected by genotype-specific factors.

I found all three claims supported, albeit with some minor questions below:

Structural variation plays a strong role in TE load.<br /> Convinced of this result. However:<br /> Line 185-187/Figure 3C: I'm curious given that the changes in Ty count are so often linked to changes in gross DNA sequence whether the count per total DNA sequence is actually changing on average in these genomes. Ie., does hybridization tend to increase TE count via CNV or does hybridization tend to increase DNA content in the MA lines and TEs come along for the ride?

One question about ploidy (lines 175-177):

Both aneuploidy and triploidy seem easy to call from this data. A 3:1 tetraploidy as well. However, in Figure 2B there are tetraploids that are around the 1:1 line. How are the authors calling ploidy for these strains? This was not clear to me from the text.

Reviewer #1 (Public Review):

Anderson, Henikoff, Ahmad et al. performed a series of genomics assays to study Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high-quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila. Some new analyses and a few new experiments are suggested here, which hopefully further take advantage of these data sets and make some results more conclusive.

Major comments:

1). The step-wise accumulation of H3K4me2 in bam, aly and wt testes are interesting. Is it possible to analyse the cis-acting sequences of different groups of genes with distinct H3K4me2 features, in order to examine whether there is any shared motif(s), suggesting common trans-factors that potentially set up the chromatin state for activating gene expression in a sequential manner?

2). Pg. 4, line 141-142: "we cannot measure H3K4me2 modification at the bam promoter in bam mutant testes or at the aly promoter in aly mutant testes", what are the allelic features of the bam mutant and aly mutant? Are the molecular features of these mutations preventing the detection of H3K4me2 at the endogenous genes' promoters? Also, the references cited (Chen et al., 2011) and (Laktionov et al., 2018) are not the original research papers where these two mutants were characterized.

3). The original paper that reported the Pc-GFP line and its localization is: Chromosoma 108, 83 (1999). The Pc-GFP is ubiquitously expressed and almost present in all cell types. In Figure 6B, there is no Pc-GFP signals in bam and aly mutant cells. According to the Method "one testis was dissected", does it mean that only one testis was prepared for immunostaining and imaging? If so, definitely more samples should be used for a more confident conclusion. Also, why use 3rd instar larval testes instead of adult testes? Finally, it is better to compare fixed tissue and live tissue, as the Pc-GFP signal could be lost during fixation and washing steps. Please refer to the above paper [Chromosoma 108, 83 (1999)] for Pc-GFP in spermatogonial cells and Development 138, 2441-2450 (2011) for Pc-GFP localization in aly mutant.

4). Ubiquitinylation of histone H2A is typically associated with gene silencing, here it has been hypothesized that ubH2A contributes to the activation of Y chromosome. This conclusion is strenuous, as it entirely depends on correlative results. For example, the lack of co-localization of ubH2A immunostaining and Pc-GFP are not convincing evidence that ubH2A is not resulting from PRC1 dRing activity. It would be a lot stronger conclusion by using genetic tools to show this. For example, if dRing is knocked down (using RNAi driven by a late-stage germline driver such as bam-Gal4) or mutated in spermatocytes (using mitotic clonal analysis), would they detect changes of ubH2A levels?

5). Regarding "X chromosome of males is thought to be upregulated in early germline cells", it has been shown that male-biased genes are deprived on the X chromosome [Science 299:697-700 (2003); Genome Biol 5:R40 (2004); Nature 450:238-241 (2007)], so are the differentiation genes of spermatogenesis [Cell Research 20:763-783 (2010)]. It would be informative to discuss the X chromatin features identified in this work with these previous findings. For example, the lack of RNAPII on X chromosome in spermatocytes could be due to a few differentiation genes expressed in spermatocytes located on the X chromosome.

Reviewer #2 (Public Review):

Anderson et al profiled chromatin features, including active chromatin marks, RNA polymerase II distribution, and histone modifications in the sex chromosomes of spermatogenic cells in Drosophila. The results are new and the experiments and analyses look well done, including with appropriate numbers of replicates. Results were parsed by comparing them among two arrest mutants and wildtype, as well as in FACS-sorted spermatocytes. The authors also profiled larval wing discs to serve as reference-somatic cells, which allowed them to focus only on features in their testis data that were associated with germ cells. Their results were further refined by categorizing the genes of interest based on available single nucleus RNA seq expression profiles. The authors document interesting phenomena, such as differences in the distribution of RNAPIIS2p on some genes in germ cells vs somatic cells, the presence of a uH2A body beginning in early spermatocytes, and high levels of uH2A on the Y chromosome and little or none on the X. The former is intriguing because this modification is usually associated with silencing, yet the Y chromosome is active in spermatogenic cells. The authors interpret some of their data as implying a lack of dosage compensation of the X chromosome in spermatocytes.

The data are believable and new, but it is not fully clear how to interpret them. The paper's interpretations rely on subtractive logic to parse results from mixtures of cells down to cell type, extracting spermatogonia, spermatocyte, etc. features by comparing bam mutants (only spermatogonia) to aly mutants (spermatogonia and early spermatocytes but no later stages) to wildtype (all spermatogenic stages), and extracting testis germline data by comparison to wing disc soma; their FACS sorted spermatocytes also have heterogeneity. I recognize that the present paper was a lot of work and am not suggesting that the authors redo their study using methods that give more purity and precision of stage (https://doi.org/10.1126/science.aal3096, https://doi.org/10.1101/gad.335331.119), but they should be aware of them and of their results.

The conclusions about dosage compensation are indirect, but are consistent with the current model documented in the studies cited by the authors, as well as earlier studies (doi: 10.1186/jbiol30).

Reviewer #1 (Public Review):

This is an intriguing and creative paper that examines whole brain cfos induction, a measure of brain activity, during mating and the formation of pair bonding. This contrasts with the classical reductionistic approach of focusing on a few individual brain regions in the monogamous and pair-bonding prairie vole. By taking this whole-brain approach following mating and then bond formation, several findings are revealed. (1) Using hierarchical cluster analysis some clusters were consistent with previously well-identified brain regions/circuits involved in bonding. The bed nucleus of the stria terminalis was identified as an important hub for bonding behavior but, importantly, the study also identified newer brain circuits likely involved in pair bond maintenance. (2) Rates of ejaculation best predicted the consistency of cfos activation that characterized a pair. (3) once the pair bond has stabilized, an amygdala cluster emerged potentially representing the coordination of a new cluster of brain regions that allow for pair bond maintenance. (4) There was a surprising lack of sexual dimorphism in active brain clusters identified during mating and pair bonding, but perhaps characteristic of a monogamous species.

While the approach used in this study cannot identify cause and effect, the whole brain approach identified clusters representing circuits of potential importance and a series of new hypotheses to explore.

The importance of the role of sexual behavior, specifically ejaculation rates, is worth emphasizing for the formation of pair bonds in prairie voles. It suggests that the role of sexual behavior in contributing to the strength of pair bonds should be explored more. It is also important to add that males and females in the study were screened for sexual receptivity. It would therefore be important to identify characteristics of animals that did not mate under the laboratory conditions used that may add depth and complexity to what was identified in the current study. The identification of brain regions for pair bond maintenance centered around the amygdala was also intriguing.

The issue of the lack of a strong presence of the reward circuitry (nucleus accumbens) in the final models is also worth more discussion. Perhaps it has been overly emphasized in the past, but there are strong results from other studies pointing to the importance of reward circuitry.

The design involved a nice time series for collecting behavioral and neural data at four time points: 0 hr (mating), 2.5 hr (mating huddling, investigation). 6 (early unstable bond) and 22 hours after mating.

Please discuss the consequences of creating the behavioral data for pair bond formation by subtracting same-sex pairs interactions from the opposite-sex interactions. What sources of information are removed by using this approach?

Time 0 is when the barrier is removed after a two-hour exposure. Please speculate on what is going on during the two-hour exposure. Time zero is potentially more than the time of mating. Is it possible that aggression is being decreased during this time point that represents mating? Could it also be a measure of the outcome of an initial compatibility assessment by the male and female?

Reviewer #2 (Public Review):

In this manuscript, the authors generate an annotated brain atlas for the prairie vole, which is a widely studied organism. This species has a suite of social behaviors that are difficult or impossible to study in conventional rodents, and has attracted a large community of researchers. The atlas is impressive and will be a fantastic resource. The authors use this atlas to examine brain-wide c-fos expression in prairie voles that were paired with same-sex or opposite-sex voles across multiple time points. In some sense, the design resembles PET studies done in primates that take whole brain scans after an important behavioral experience. The authors observed increased c-fos expression across a network of brain regions that largely corresponds with the previous literature. The study design captured several novel observations including that c-fos expression in some regions correlates strongly between males and females during pair bond formation and mating, suggesting synchrony in neural activity. An important caveat to this study not mentioned by the authors is that c-fos provides a snapshot of neural activity and that important populations of neurons could be active and not express c-fos. Thus observed correlations are likely to be robust, but the absence of differences (in say accumbens) may just reflect the limits of c-fos estimation of neural activity. Similarly, highly coordinated neural activity between males and females might still be driven by different mechanisms if different cell types were activated within a specific region. Nonetheless, the creation of this resource and its use in a well-designed study is an important accomplishment.

Reviewer #3 (Public Review):

In this manuscript, Gustison et al., describe the development of an automated whole-brain mapping pipeline, including the first 3D histological atlas of the prairie vole, and then use that pipeline to quantify Fos immunohistochemistry as a measure of neural activity during mating and pair bonding in male and female prairie voles. Prairie voles have become a useful animal model for examining the neural bases of social bonding due to their socially monogamous mating strategy. Prior studies have focused on identifying the role of a few neuromodulators (oxytocin, vasopressin, dopamine) acting in a limited number of brain regions. The authors use this unbiased approach to determine which areas become activated during mating, cohabitation, and pair bonding in both sexes to identify 68 brain regions clustered in seven brain-wide neuronal circuits that are activated over the course of pair bonding. This is an important study because i) it generates a valuable tool and analysis pipeline for other investigators in the prairie vole research community and ii) it highlights the potential involvement of many brain regions in regulating sexual behavior, social engagement, and pair bonding that have not been previously investigated.

Strengths of the study include the unbiased assessment of neural activity using the automated whole brain activity mapped onto the 3D histological atlas. The design of the behavioral aspect of the study is also a strength. Brains were collected at baseline and 2.5, 6 and 22 hrs after cohabitation with either a sibling or opposite-sex partner. These times were strategically chosen to correspond to milestones in pair bond development. Behavior was also quantified during epochs over the 22 hr period providing useful information on the progression of behaviors (e.g. mating) during pair bonding and relating Fos activation to specific behaviors (e.g. sex vs bonding). The sibling co-housed group provided an important control, enabling the identification of areas specifically activated by sex and bond formation. The analyses of the data were rigorous, resulting in convincing conclusions. While there was nothing particularly surprising in terms of the structures that were identified to be active during the mating and cohabitation, the statistical analysis revealed interesting relationships in terms of interactions of the various clusters, and also some level of synchrony in brain activation between partners. Furthermore, ejaculation was found to be the strongest predictor of Fos activation in both males and females. The sex differences identified in the study were subtle and less than the authors expected, which is interesting.

While the study provides a potentially useful tool and approach that may be of general use to the prairie vole community and identifies in an anatomically precise manner areas that may be important for mating or pair bond formation, there are some weaknesses as well. The study is largely descriptive. It is impossible to determine whether the activated areas are simply involved in sex or in the pair bond process itself. In other words, the authors did not use the Fos data to inform functional testing of circuits in pair bonding or mating behaviors. However, that is likely beyond the scope of this paper in which the goal was more to describe the automated, unbiased approach. This weakness is offset by the value of the comprehensive and detailed analysis of the Fos activation data providing temporal and precise anatomical relationships between brain clusters and in relation to behavior. The manuscript concludes with some speculative interpretations of the data, but these speculations may be valuable for guiding future investigations.

Reviewer #1 (Public Review):

The manuscript by Maio and colleagues looks at the impact of the heightened glycolytic activity induced by Mtb in monocytes, and its impact on Hif1- dependent migration of DCs.

Data concerning the biological significance of the impact of enhanced glycolysis on DC migration is strong and convincing. While Hif1-a is obviously a key factor, the evidence that it is a linear component in the cascade falls a little short as the main inhibitor used PX-478 does not have a clear, single mode of action. Additional characterization with the alternative inhibitor (Echinomycin) would make the argument more convincing.

Reviewer #2 (Public Review):

The manuscript by Maio et al attempts to examine the bioenergetic mechanisms involved in the delayed migration of DC's during Mtb infection. The authors performed a series of in vitro infection experiments including bioenergetic experiments using the Agilent Seahorse XF, and glucose uptake and lactate production experiments. This is a well-written manuscript and addresses an important question in the TB field. A major weakness is the use of dead Mtb in virtually all the experiments. Unfortunately, the authors did not attempt to address this critical confounding factor. As a result, data was interpreted, and conclusions were made as if live Mtb was used. Also, previous studies (PMID: 30444490 and PMID: 31914380) have shown that live Mtb suppresses glycolysis, which contradicts findings in this study, perhaps because dead Mtb was used here. For these reasons, obtaining any pertinent conclusions from the study is not possible, which diminishes the significance of the work.

Reviewer #1 (Public Review):

Summary:<br /> The article written by Kazdaghli et al. proposes a modification of imputation methods, to better account for and exploit the variability of the data. The aim is to reduce the variability of the imputation results. The authors propose two methods, one that still includes some imputation variability, but accounts for the distribution of the data points to improve the imputation. The other one proposes a determinantal sampling, that presents no variation in the imputation data, at least no variation in the classification task. As these methods grow easily in computation requirements and time, they also propose an algorithm to run these methods in quantum processors.

Strengths:<br /> The sampling method for imputing missing values that accounts for the variability of the data seems to be accurate.

Weaknesses:<br /> While the proposed method seems accurate and should improve the imputation task, I think that the authors must explain a little better some parts of the algorithm that they are using. Although I think the authors could have evaluated the imputations directly, as they mention in the introduction, I understand that the final goal in the task is to have a better classification. The problem is that they do not explain what the classification is, or how is it trained. In a real situation, they would have data that would be used for training the algorithm, and then new data that needs to be imputed and classified. In this article, I do not see any train, plus test or validation data. I wonder if there could be some interaction between the imputation and the classification methods, that leads to overfitting the data; in particular when the deterministic DPP is used.

In its current state, I do not think this article brings not very much value to the community that could benefit from it. I did not find an implementation of the method available to other scientists, nor the data used to evaluate it (while one data set is public, the simulated data is not available). This not only hinders the use of the method by the scientific community, but also makes it impossible to reproduce the results or test the algorithm in similar databases.

Reviewer #2 (Public Review):

In this work, the authors address the problem of missing data imputation in the life sciences domain and propose several new algorithms which improve on the current state-of-the-art. In particular (i) they modify two existing Random Forest-based imputation methods -- MissForest and miceRanger -- to use either determinantal sampling or deterministic determinantal sampling, and show slightly improved classification performance on two datasets (one synthetic, one real); in addition, (ii) the authors present a quantum circuit for performing the determinantal sampling which scales asymptotically better than the best-known classical methods, and perform small scale experiments using both a (noiseless) quantum simulator as well as a 10 qubit IBM quantum computer to validate that the approach works in principle.

The problem of data imputation is important in practice, and results that improve on existing methods should be of interest to those in the field. The use of determinantal sampling for applications beyond data imputation should also be of broader interest, and the connection to quantum computing warrants further investigation and analysis.

The use of classification accuracy (as measured by AUC) as a measure of success is well-motivated, and the authors use both real and synthetic datasets to evaluate their methods, which consistently (if only marginally) outperform the existing state-of-the-art. The results obtained here motivate the further study of this approach to a wider class of datasets, and to areas beyond life sciences.

As it stands, in my opinion, two points need addressing.

1. Additional clarity is required on what is novel:

While the application of determinantal and deterministic determinantal sampling to the specific case of data imputation appears to be novel, the authors should make it more clear that both of these methods themselves are not new, and have been directly lifted from the literature. As it stands, the current wording in the main body of the paper gives the impression that the deterministic determinantal algorithm is novel, e.g. "this motivated us to develop a deterministic version of determinantal sampling" (p.2), and it is only in the methods section that a reference is made to the paper of Schreurs et al. which proposed the algorithm.

Similarly, in the abstract and main body of the text, the wording gives the impression that the quantum circuits presented here are new (e.g., "We also develop quantum circuits for implementing determinantal point processes") whereas they have been previously proposed (although one of the authors of the current paper was also an author of the original paper proposing the quantum circuits for determinantal sampling).

2. Additional analysis is needed to support the claims of potential for quantum advantage:

The authors claim that the quantum algorithm for implementing determinantal point processes provides a computational advantage over classical ones, in that the quantum circuits scale linearly in the number of features compared with cubic scaling classically. While this may be true asymptotically, in my opinion, more discussion is required about the utility and feasibility of this method in practice, as well as the realistic prospects of this being a potential area of application for quantum computing.

For example, the authors mention that a quantum computer of 150 qubits capable of running circuits of depth 400 is needed to perform the determinantal sampling for the MIMIC-III dataset considered, and say "while [such hardware is] not available right now, it seems quite possible that they will be available in the not so far future". The authors also state "This suggests that with the advent of next-generation quantum computers... one could expect a computational speedup in performing determinantal sampling" and "it is expected that next-generation quantum computers will provide a speedup in practice". These are strong assertions (even if 'next generation' is not clearly defined), and in my opinion, are not sufficiently backed by evidence to date. Given that datasets of the size of MIMIC-III (and presumably much larger) can be handled efficiently classically, the authors should clarify whether one expects a quantum advantage by this approach in the "NISQ" (pre-error-corrected) era of quantum computing. This seems unlikely, and any argument that this is the case should include an analysis accounting for the absolute operation speeds and absolute times required to perform such computations, including any time required for inputting data, resetting quantum circuits etc. On the other hand, if by 'next generation' the authors mean quantum computers beyond the NISQ era (i.e., assuming fault-tolerant quantum computers and logical qubits), then the overhead costs of quantum error correction (both in terms of physical qubit numbers as well as computational time) should be analyzed, and the crossover regime (i.e., data size where a quantum computation takes less absolute time than classical) estimated in order to assess the prospects of a practical quantum advantage, especially in light of recent analyses e.g., [1,2] below.

[1] Hoefler, Haner, Troyer. Communicatios of the ACM, 66.5 (2023):82-87<br /> [2] Babbush et al., PRX Quantum 2.1 (2021):010103

Other comments and suggestions:<br /> The authors measure "running time [as] the depth of the necessary quantum circuits." While circuit depth may indeed correspond to wall-clock time, quantum circuit size (i.e. number of gates) is the fairer complexity metric for comparison with classical running time. If depth is used, then a fair comparison to classical methods should be to compare with classical parallel processing time using N processors. However, if circuit size is used, then the quantum complexity is Nd, which contrasts with the classical value of Nd^2 (pre-processing) + d^3 (per sample). This yields a subquadratic quantum speedup over classical, as opposed to a qubic speedup.

The results (e.g Table 1) show that the new algorithms consistently outperform the original miceRanger and MissForest methods, although the degree of improvement is small, typically of order 1% or less. Some discussion is therefore warranted on the practical benefits of this method, and any tradeoff in terms of efficiency. In particular, while Table 1 compares the classification accuracy (as measured by AUC) of the newly proposed methods vs the existing state-of-the-art, a discussion on the scalability and efficiency would be welcome. The determinantal sampling takes time Nd^2, how does this compare with the original methods? For what dataset and feature sizes are the determinantal methods feasible (which will determine the scale at which other approaches, e.g. those based on quantum computing may be required).

A discussion (or at least mention) of the algorithmic complexity of the classical deterministic determinantal sampling (which seems to also be Nd^2) in the main body of the text would be welcome.

The final paragraph of the Methods section discusses sampling many times from the quantum circuits to estimate the most probable outcome, and hence perform the deterministic determinantal sampling. A more careful analysis of the number of samples needed (for bounded variance/error) and the impact on the running time (and whether one still expects an advantage over classical (although one must define some bounded error version of the deterministic algorithm to do so) or performance of the algorithm would be welcome.

A discussion on the absolute running time required for the quantum experiments performed (and how they compare to classical) would be interesting.

A mention of which quantum simulator was used would be welcome.

In the introduction, three kinds of data missingness (MCAR, MAR, MNAR) are mentioned, although experiments are only performed for MCAR and MNAR. Can some explanation for excluding MAR be given?

Reference 24 (Shadbar et al., the study that demonstrated the effectiveness of miceRanger and MissForest) used 4 datasets: MIMIC-III, Simulated, Breast Cancer, and NHSX COVID-19. Of these, MIMIC-III is used in the current paper, and Simulated appears similar (although with 1000 instead of 2000 rows) to the synthetic dataset of the current paper. An analysis of the determinantal sampling methods applied to the Breast Cancer and NHSX COVID-19 datasets (which have naturally occurring missingness), and a comparison to the results of Shadbar et al. would be interesting.

Reviewer #1 (Public Review):

Shoemaker and Grilli analyze publicly available sequencing data to quantify how the microbial diversity of ecosystems changes with the taxonomic scale considered (e.g., diversity of genera vs diversity of families). This study builds directly on Grilli's 2020 paper which used this data to show that for many different microbial species, the distribution of abundances of the species across sampling sites belongs to a simple one-parameter family of gamma distributions. In this work, they show that the gamma distribution also describes the distribution of abundances of higher taxonomic levels. The distribution now requires two parameters, but the second parameter can be approximately derived by treating the distributions of lower-level taxonomic units as being independent. The difference between the species-level result and the result at higher taxonomic levels suggests that in some sense microbial species are ecologically meaningful units.

While the higher-level taxon abundance distributions can be well-approximated assuming independence of the constituent species, this approach substantially underestimates variation in community richness and diversity among sampling sites. Much of this extra variability appears to be driven by variability in sample size across sites. It is not clear to me how much this variation in sample size is itself due to variation in sampling effort versus variation in overall microbial densities. This variation in sample size also produces correlations between taxon richness at lower and higher taxonomic levels. For instance, sites with large samples are likely to have both many species within a genus and many genera. The authors also consider taxon diversity (Shannon index, i.e. entropy), which is constructed from frequencies and is therefore less sensitive to sample size. In this case, correlations between diversity across taxonomic scales instead appear to depend on the idiosyncratic correlations among species abundances.

This paper's results are presented in a fairly terse manner, even when they are describing summary statistics that require a lot of thought to interpret. I don't think it would make sense to try to understand it without having first worked through the 2020 paper. But everyone interested in a general understanding of microbial ecology should read the 2020 paper, and once one has done that, this paper is worth reading as well simply for seeing how the major pattern in that paper shifts as one moves up in the taxonomic scale.

Reviewer #2 (Public Review):

Summary<br /> In this research advance, the authors purport to show that the unified neutral theory of biodiversity (UNTB) is not a suitable null model for exploring the relationship between macroecological quantities, and additionally that the stochastic logistic growth model (SLM) is a viable replacement. They do this by citing other studies where UNTB was unable to capture individual macroecological quantities and then demonstrating SLM's strength at modeling macroecological diversity metrics. They extend this analysis to show SLM's modeling capability at multiple scales of coarse-graining. Finally, the authors conduct a similar analysis to Madi et al. (2020) by investigating the relationship between diversity measures within a group and across coarse-grained groups (e.g. genera diversity in one family compared to diversity of families). The authors show that choosing SLM as a null model reveals some previously reported relationships to be no longer "novel", in the sense that the patterns can be adequately captured by the null model.

Strengths<br /> 1. The authors make a strong argument that UNTB is not a good null model of macroecological observables and especially relationships between them. The authors convincingly argue that a SLM is a better null since the gamma distribution it predicts is a better description of the empirical Abundance Fluctuation Distributions (AFD).<br /> 2. The authors show that the gamma distribution predicted by SLM is a good fit for the AFD's at many different scales of coarse-graining, not just the OTU level as was previously demonstrated.<br /> 3. The authors convincingly demonstrate how SLM can be used to test the relevance of interactions to macroecological relationships.

Weaknesses<br /> 1. Use of the word "predict" with the SLM in this advance is confusing, and to this reviewer seems to make a stronger claim than shown by the authors. For example, in their abstract, the authors state "We found that measures of biodiversity at a given scale can be consistently predicted using predictions (sic) derived from a minimal model of ecology." This appears to imply that a minimal model predicted the behavior of a system when in reality it accurately described the data it was trained on. This potential for confusion extends throughout the text and obscures what was actually achieved.<br /> 2. More generally, to my mind the presentation in the manuscript could benefit from a clearer delineation between the question of "what patterns are explainable by a noninteracting model vs require interactions" (which could be assessed with no reference to SLM, but by a simple randomization test), and whether specifically, SLM is a good null model / better than UNTB.

Overall Impact<br /> The authors achieve their aims, even though the text is at times dense. The use of SLM as a non-interacting null model for macroecological quantities and relationships is well supported by the text, and SLM should be used as a null model for these types of phenomena going forward.

Joint Public Review:

Previous findings by authors show that heliomycin induces autophagy to inhibit cancer progression, while its water-soluble analogs induce apoptosis. Here, they show that one of the analogs, 4-dmH, binds to tNOX, a NADH oxidase which supports SirT1 activity, in addition to SirT1, while heliomycin only binds to SirtT1 but not tNOX, using CETSA and in silico molecular docking studies, in human oral cancer cells. The additional binding activity of 4-dmH to tNOX might explain the different biological outcome from heliomycin. 4-dmH induces ubiquitination and degradation of tNOX protein, in dependent of p53 status. The tumor suppressive effect of 4-dmH (by intra-tumoral injections) is better than heliomycin. TCGA data base analysis suggests that high tNOX mRNA expression is correlated with poor prognosis of oral cancer patients.

This group has been a leading lab of chemical and biological characterization of heliomycin and its analogs. Although their findings are interesting and advance their previous findings, they arbitrarily focus on tNOX as a potential new target of 4-dmH without clear rationale. Moreover, it remains unclear if the different biological outcomes caused by heliomycin and 4-dmH are indeed due to 4-dmH's ability to bind to tNOX in addition to SirT1. Moreover, molecular biological analyses to establish the proposed tNOX-SirT1 axis on inducing autophagy vs apoptosis are insufficiently performed.

Comments on the current version:

1. The rationale of selecting tNOX/ENOX2 as a potential target of 4-dmH, but not heliomycin, is unclear by taking a biased approach. Thus, there is high possibility that 4-dmH binds to other proteins involved in apoptosis inhibition. An unbiased screen to identify 4-dmH-binding proteins would be a better approach unless there is a clear and logical rationale.

2. The authors should show whether heliomycin indeed does not induce apoptosis, while 4-dmH cannot induce autophagy.

3. They should demonstrate whether genetic knockdown of tNOX, SirT1, or both tNOX and SirT1 induces apoptosis or autophagy and also reduces malignant properties of oral cancer cells.

4. The authors should examine whether overexpression of SirT1 or tNOX in cells treated with heliomycin or 4-dmH could nullify heliomycin-induced autophagy and 4-dmH-induced apoptosis. Also, instead of overexpressing tNOX, they can supplement NAD into cells treated with 4-dmH.

5. Related to Fig. 5C and 6a, the authors should examine the effects of heliomycin and 4-dmH on the cell cycle profiles, Annexin V positivity, and colony formation.

6. They should also examine whether either or both heliomycin and 4-dmH induce reactive oxygen species (ROS).

7. Related to Fig. 9d, they should mutate amino acid residue(s) in tNOX that are crucial for the 4-dmH-tNOX binding, including Ile 90, Lys98, Pro111, Pro113, Leu115, Pro117, and Pro118, to examine whether these mutants lose the binding to 4-dmH and fail to rescue 4-dmH-induced apoptosis, unlike wild-type tNOX.

8. Related to Fig. 10a, heliomycin appears to also reduce tNOX levels (although the extent is not as robust as 4-dmH), which is not expected since heliomycin does not bind to tNOX. They should compare the effects of heliomycin and 4-dmH on reducing the protein levels of tNOX. If heliomycin does not change the tNOX protein levels, then they need to discuss why heliomycin reduces tNOX levels in vivo.

9. Related to Fig. 10F, if tNOX is an upstream regulator of SirT1 and both heliomycin and 4-dmH ultimately target SirT1, it is unclear why heliomycin and 4-dmH cause different biological outcomes. One explanation is that tNOX has apoptosis-inhibiting function other than supporting (or independent of) SirT1 and hence 4-dmH-mediated tNOX inhibition causes apoptosis rather than autophagy. They should explain and discuss more about whether tNOX-inhibiting/binding function of 4-dmH is sufficient to explain the different biological outcomes from heliomycin.

10. They should examine the effects of heliomycin and 4-dmH on cell viability of non-tumor cells to examine their toxicities.

11. They should consistently use either tNOX or ENOX2 to avoid confusion.

Reviewer #1 (Public Review):

This manuscript conducts a classic QTL analysis to identify the molecular basis of natural variation in disease resistance. This identifies a pair of glycosyltransferases that contribute to steroidal glycoalkaloid production. Specifically altering the final hexose structure of the compound. This is somewhat similar to the work in tomatine showing that the specific hexose structure mediates the final potential bioactivity. Using the resulting transgenic complementation lines that show that the gene leads to a strong resistance phenotype to one isolate of Alternaria solani and the Colorado potato beetle. This is solid work showing the identification of a new gene and compound influencing plant biotic interactions. The authors have improved the introduction and discussion to better show the breadth of knowledge in pathogen-defense metabolite interactions involving plants.

Reviewer #2 (Public Review):

The study focuses on a mechanism of pest/pathogen resistance identified in Solanum commersonii, which appears to offer dominant resistance to Alternaria solani (potato early blight) through the activity of specific glycosyltransferases which facilitate the production of tetraose glycoalkaloids in leaf tissue. The authors demonstrated that these glycoalkaloids are suppressive to the growth of multiple pathogenic ascomycetes and furthermore, that transgenic plants expressing these glycosyltransferases in susceptible S. commersonii clones demonstrate improved resistance to specific strains of A. solani and a genotype of Colorado Potato Beetle. The study design is straightforward, yet thorough, and does a good job demonstrating the importance of these genes in resistance. This work is significant because it demonstrates the mechanism behind resistance to a necrotrophic pathogen. Resistance to this group of pathogens has historically relied on mechanisms that do not include the use of typical dominant resistance gene products (nucleotide-binding, leucine-rich repeat proteins). The identification of these glycosyltransferases and their role in resistance will give potato breeders options for the development of markers associated with resistance to this group of pathogens. However, this may demonstrate an important battle to balance between production traits (like disease resistance) and quality traits (like glycoalkaloid content), as the two may be mutually exclusive in the development of new varieties.

Reviewer #1 (Public Review):

The work in this paper is in general done carefully. Reconstructions are done appropriately and the effects of statistical uncertainty are quantified properly. My only slight complaint is that I couldn't find statistics about posterior probabilities anywhere and that the sequences and trees do not seem to be deposited. I would also have preferred to have the actual phylogeny in the main text. This is a crucial piece of data that the reader needs to see to understand what exactly is being reconstructed.<br /> The paper identifies which mutations are crucial for the functional differences between the ancestors tested. This is done quite carefully - the authors even show that the same substitutions also work in extant proteins. My only slight concern was the authors' explanation of what these substitutions do. They show that these substitutions lower the affinity of the C-terminal peptide to the alpha-crystallin domain - a key oligomeric interaction. But the difference is very small - from 4.5 to 7 uM. That seems so small that I find it a bit implausible that this effect alone explains the differences in hydrodynamic radius shown in Figure S8. From my visual inspection, it seems that there is also a noticeable change in the cooperativity of the binding interaction. The binding model the authors use is a fairly simple logarithmic curve that doesn't appear to consider the number of binding sites or potential cooperativity. I think this would have been nice to see here.

Lastly, the authors use likelihood methods to test for signatures of selection. This reviewer is not a fan of these methods, as they are easily misled by common biological processes (see PMID 37395787 for a recent critique). Perhaps these pitfalls could simply be acknowledged, as I don't think the selection analysis is very important to the impact of the work.

Reviewer #2 (Public Review):

This was an interesting study, and I enjoyed seeing different experimental approaches used to compare the properties of the different native proteins, the ancestral reconstructions, and the other mutants. I think it provides convincing mechanistic evidence as to how these small heat shock proteins have evolved. Thus, I think it represents a valuable contribution to the field. However, to a certain extent, I think the authors have at times over-interpeted their results, and over-simplified their explanations, as the differences between the ancestral proteins, and the changes induced by the two mutations, only partially explain the differences between IbpA proteins from the two different species. Furthermore, in some places, I found this difficult to follow and figures were not properly explained or labelled. If these issues were addressed, I think the paper would be considerably more accessible to readers.

Reviewer #3 (Public Review):

Summary:<br /> The study by Karaś et al. reveals how multi-protein systems can evolve into single-protein equivalents, shedding light on the molecular events enabling gene loss during evolution. This work is valuable for researchers in evolutionary fields and offers potential applications in protein and organism engineering. While the findings lack broader appeal and societal implications, the evidence presented supports the proposed molecular mechanism. Using computational methods and biochemical analysis, the authors traced the evolutionary simplification of bacterial small heat shock proteins, linking specific mutations to functional changes. The study's strength lies in its vertical approach, identifying functional residues, but it does not introduce new techniques, limiting its novelty and significance.

Strengths:<br /> 1) Experimental Approach<br /> The research question was clearly outlined and the author's approach to answering it was systematic. In particular, their model system was highly suitable to address the research question. The authors employed appropriate experimental and computational techniques, and their 'vertical approach' was beneficial in that it allowed them to discover functional residues in the sHsp system which may not have been possible otherwise. Overall, their approach to this study was solid.

2) Reproducibility<br /> The results were presented well. The number of experimental repeats was suitable, as well as their analysis of the data. The values for standard deviation were reasonable, and their results using the alternative ancestors for the substrate aggregation assays helped support the robustness of their observations.

Weaknesses:<br /> During the mutational experiments, the authors examined seven potential substitutions identified through ASR and measured their impact on protein disaggregation activity. Positions 66 and 109 exhibited a significant decrease in luciferase refolding stimulation. To explore the combined effect of these mutations, the authors created the double mutant AncA0. However, predicting the most impactful combination of mutations due to epistatic effects is challenging. A more effective strategy would be to test various combinations of mutations to identify the double mutant with the greatest decrease in luciferase refolding stimulation and/or alternatively perform a co-evolutionary study to try to understand any epistatic effects between the mutations.

Reviewer #1 (Public Review):

Summary:<br /> This study develops and applies a coarse-grained model for nucleosomes with explicit ions. The authors perform several measurements to explore the utility of a coarse-grained simulation method to model nucleosomes and nucleosome arrays with explicit ions and implicit water. 'Explicit ions' means that the charged ions are modeled as particles in simulation, allowing the distributions and dynamics of ions to be measured. Since nucleosomes are highly charged and modulated by charge modifications, this innovation is particularly relevant for chromatin simulation.

Strengths:<br /> This simulation method produces accurate predictions when compared to experiments for the binding affinity of histones to DNA, counterion interactions, nucleosome DNA unwinding, nucleosome binding free energies, and sedimentation coefficients of arrays. The variety of measured quantities makes both this work and the impact of this coarse-grained methodology compelling.

The comparison between the contributions of sodium and magnesium ions to nucleosome array compaction, presented in Figure 3, was exciting and a novel result that this simulation methodology can assess.

Weaknesses:<br /> The presentation of experimental data as representing in vivo systems is a simplification that may misrepresent the results of the simulation work. In vivo, in this context, typically means experimental data from whole cells. What one could expect for in vivo experimental data is measurements on nucleosomes from cell lysates where various and numerous chemical modifications are present. On the contrary, some of the experimental data used as a comparison are from in vitro studies. In vitro in this context means nucleosomes were formed 'in a test tube' or under controlled conditions that do not represent the complexity of an in vivo system. The simulations performed here are more directly compared to in vitro conditions. This distinction likely impacts to what extent these simulation results are biologically relevant. In vivo and in vitro differences could be clarified throughout and discussed.

Reviewer #2 (Public Review):

In this manuscript, the authors introduced an explicit ion model using the coarse-grained modelling approach to model the interactions between nucleosomes and evaluate their effects on chromatin organization. The strength of this method lies in the explicit representation of counterions, especially divalent ions, which are notoriously difficult to model. To achieve their aims and validate the accuracy of the model, the authors conducted coarse-grained molecular dynamics simulations and compared predicted values to the experimental values of the binding energies of protein-DNA complexes and the free energy profile of nucleosomal DNA unwinding and inter-nucleosome binding. Additionally, the authors employed umbrella sampling simulations to further validate their model, reproducing experimentally measured sedimentation coefficients of chromatin under varying salt concentrations of monovalent and divalent ions.

The significance of this study lies in the authors' coarse-grained model which can efficiently capture the conformational sampling of molecules while maintaining a low computational cost. The model reproduces the scale and, in some cases, the shape of the experimental free energy profile for specific molecule interactions, particularly inter-nucleosome interactions. Additionally, the authors' method resolves certain experimental discrepancies related to determining the strength of inter-nucleosomal interactions. Furthermore, the results from this study support the crucial role of intrinsic physicochemical interactions in governing chromatin organization within the nucleus.

The method is simple but can be useful, given the authors can provide more details on their ion parameterization. The paper says that parameters in their "potentials were tuned to reproduce the radial distribution functions and the potential of mean force between ion pairs determined from all-atom simulations." However, no details on their all-atom simulations were provided; at some point, the authors refer to Reference 67 which uses all-atom simulations but does not employ the divalent ions. Also, no explanation is given for their modelling of protein-DNA complexes.

Overall, the paper is well-written, concise and easy to follow but some statements are rather blunt. For example, the linker histone contribution (Figure 5D) is not clear and could be potentially removed. The result on inter-nucleosomal interactions and comparison to experimental values from Ref#44 is the most compelling. It would be nice to see if the detailed shape of the profile for restrained inter-nucleosomal interactions in Figure 4B corresponds to the experimental profile. Including the dependence of free energy on a vertex angle would also be beneficial.

Another limitation of this study is that the authors' model sacrifices certain atomic details and thermodynamic properties of the modelled systems. The potential parameters of the counter ions were derived solely by reproducing the radial distribution functions (RDFs) and potential of mean force (PMF) based on all-atom simulations (see Methods), without considering other biophysical and thermodynamic properties from experiments. Lastly, the authors did not provide any examples or tutorials for other researchers to utilize their model, thus limiting its application.

Reviewer #2 (Public Review):

Summary:<br /> The major purpose of this manuscript is to examine whether leucine treatment would be a potential strategy to treat cytokine storm syndrome (CSS). CSS is a common symptom in multiple infectious diseases in clinic, which gradually leads to multiple organ failure and high mortality. Strategies to treat CSS including pulse steroid therapy normally lead to severe side effects. Therefore, it is still required to develop a safe strategy with high efficacy to treat CSS. In clinic, sepsis is well characterized to exhibit CSS and therefore multiple studies utilized a LPS-induced sepsis model to evaluate CSS symptoms. In this study, the authors examined whether leucine, an essential amino acid that has been absorbed daily in our body, could ameliorate CSS symptoms in the LPS-induced sepsis mouse model. They found a potential protective effect of leucine in terms of the survival rate and inflammatory responses.

Strengths:<br /> The study is overall well designed and the results are well analyzed with only minor issues. The methods utilized are appropriate.

Weaknesses:<br /> The mechanistic insights are not sufficient and could not fully explain the phenotype they found. Considering the importance of this study is to identify the potential protective role of leucine in CSS, the authors could also consider investigator-initiated clinical trials to further expand the significance of this study.

Reviewer #1 (Public Review):

The authors aimed to determine the mechanisms that underpin metabolic influences, particularly via the use of leucine which has been implicated in protection in lipopolysaccharide-induced cytokine storm syndrome.

The strength of the work is in establishing the clear relationship between the macrophage subtype and the severity of cytokine storm syndrome which occurs in severe inflammation and infection. They have undertaken a solid analysis of the cellular polarization of macrophage subtypes, identifying leucine suppresses M1 polarization and promotes M2 polarization. Subsequently, the authors confirmed this polarization via examination of signal transduction was mediated through the mTORC1 pathway. Pharmacological manipulation of mTORC was shown to influence arginase 1, a hallmark of M2 polarization. In addition, the authors show that leucine promoted the expression of LXRa required for arginase induction. While these studies identify how leucine might shape M2 cellular metabolism and polarization, the studies were all performed in vitro and do not examine other cellular or molecular changes that might influence the level of cytokine storm that might occur. Thus the specific contributions in cytokine storm syndrome are correlative requiring further analysis in the disease setting. These include features such as localization influencing other immune or stromal cells that might release cytokines and contribute to the syndrome, or molecular pathways not previously described. The statistical reporting and representation of data should be provided in greater detail. The data provides an interesting direction for consideration of the manipulation of immune cells in the context of inflammation and opens further discussion on how this might be practically applied in the clinical setting.

Reviewer #1 (Public Review):

Summary:<br /> This paper by Schommartz and colleagues investigates the neural basis of memory reinstatement as a function of both how recently the memory was formed (recent, remote) and its development (children, young adults). The core question is whether memory consolidation processes as well as the specificity of memory reinstatement differ with development. A number of brain regions showed a greater activation difference for recent vs. remote memories at the long versus shorter delay specifically in adults (cerebellum, parahippocampal gyrus, LOC). A different set showed decreases in the same comparison, but only in children (precuneus, RSC). The authors also used neural pattern similarity analysis to characterize reinstatement, though I have substantive concerns about how this analysis was performed and as such will not summarize the results. Broadly, the behavioural and univariate findings are consistent with the idea that memory consolidation differs between children and adults in important ways, and takes a step towards characterizing how.

Strengths:<br /> The topic and goals of this paper are very interesting. As the authors note, there is little work on memory consolidation over development, and as such this will be an important data point in helping us begin to understand these important differences. The sample size is great, particularly given this is an onerous, multi-day experiment; the authors are to be commended for that. The task design is also generally well controlled, for example as the authors include new recently learned pairs during each session.

Weaknesses:<br /> As noted above, the pattern similarity analysis for both item and category-level reinstatement was performed in a way that is not interpretable given concerns about temporal autocorrelation within the scanning run. Below, I focus my review on this analytic issue, though I also outline additional concerns.

1. The pattern similarity analyses were not done correctly, rendering the results uninterpretable (assuming my understanding of the authors' approach is correct).

a. First, the scene-specific reinstatement index: The authors have correlated a neural pattern during a fixation cross (delay period) with a neural pattern associated with viewing a scene as their measure of reinstatement. The main issue with this is that these events always occurred back-to-back in time. As such, the two patterns will be similar due simply to the temporal autocorrelation in the BOLD signal. Because of the issues with temporal autocorrelation within the scanning run, it is always recommended to perform such correlations only across different runs. In this case, the authors always correlated patterns extracted from the same run, which moreover have temporal lags that are perfectly confounded with their comparison of interest (i.e., from Fig 4A, the "scene-specific" comparisons will always be back-to-back, having a very short temporal lag; "set-based" comparisons will be dispersed across the run, and therefore have a much higher lag). The authors' within-run correlation approach also yields correlation values that are extremely high - much higher than would be expected if this analysis was done appropriately. The way to fix this would be to restrict the analysis to only cross-run comparisons, but I don't believe this is possible unfortunately given the authors' design; I believe the target (presumably reinstated) scene only appears once during scanning, so there is no separate neural pattern during the presentation of this picture that they can use. For these reasons, any evidence for "significant scene-specific reinstatement" and the like is completely uninterpretable and would need to be removed from the paper.

b. From a theoretical standpoint, I believe the way this analysis was performed considering the fixation and the immediately following scene also means that the differences between recent and remote could have to do with either the reactivation (processes happening during the fixation, presumably) or differences in the processing of the stimulus itself (happening during the scene presentation). For example, people might be more engaged with the more novel scenes (recent) and therefore process those scenes more; such a difference would be interpreted in this analysis as having to do with reinstatement, but in fact could be just related to the differential scene processing/recognition, etc. It would be important when comparing scene-specific neural patterns as templates for reinstatement across conditions that, at the time of scene presentation itself, the two conditions are equal (e.g., no difference in familiarity and so on); otherwise, we do not know which trial period (and therefore which underlying process) is driving the differences.

c. For the category-based neural reinstatement: (1) This suffers from the same issue of correlations being performed within the run. Again, to correct this the authors would need to restrict comparisons to only across runs (i.e., patterns from run 1 correlated with patterns for run 2 and so on). With this restriction, it may or may not be possible to perform this analysis, depending upon how the same-category scenes are distributed across runs. However, there are other issues with this analysis, as well. (2) This analysis uses a different approach of comparing fixations to one another, rather than fixations to scenes. The authors do not motivate the reason for this switch. Please provide reasoning as to why fixation-fixation is more appropriate than fixation-scene similarity for category-level reinstatement, particularly given the opposite was used for item-level reinstatement. Even if the analyses were done properly, it would remain hard to compare them given this difference in approach. (3) I believe the fixation cross with itself is included in the "within category" score. Is this not a single neural pattern correlated with itself, which will yield maximal similarity (pearson r=1) or minimal dissimilarity (1-pearson r=0)? Including these comparisons in the averages for the within-category score will inflate the difference between the "within-category" and "between-category" comparisons. These (e.g., forest1-forest1) should not be included in the within-category comparisons considered; rather, they should be excluded, so the fixations are always different but sometimes the comparisons are two retrievals of the same scene type (forest1-forest2), and other times different scene types (forest1-field1). (4) It is troubling that the results from the category reinstatement metric do not seem to conceptually align with past work; for example, a lot of work has shown category-level reinstatement in adults. Here the authors do not show any category-level reinstatement in adults (yet they do in children), which generally seems extremely unexpected given past work and I would guess has to do with the operationalization of the metric.

2. I did not see any compelling statistical evidence for the claim of less robust consolidation in children. Specifically in terms of the behavioural results of retention of the remote items at 1 vs 14 days, shown in Figure 2B, the authors conclude that memory consolidation is less robust in children (line 246). Yet they do not report statistical evidence for this point, as there was no interaction of this effect with the age group. Children had worse memory than adults overall (in terms of a main effect - i.e. across recent and remote items). If it were consolidation-specific, one would expect that the age differences are bigger for the remote items, and perhaps even most exaggerated for the 14-day-old memories. Yet this does not appear to be the case based on the data the authors report. Therefore, the behavioural differences in retention do not seem to be consolidation specific, and therefore might have more to do with differences in encoding fidelity or retrieval processes more generally across the groups. This should be taken into account when interpreting the findings.

3. Please clarify which analyses were restricted to correct retrievals only. The univariate analyses states that correct and incorrect trials were modelled separately, but does not say which were considered in the main contrast (I assume correct only?). The item specific reinstatement analysis states that only correct trials were considered, but the category-level reinstatement analysis does not say. Please include this detail.

4. To what extent could performance differences be impacting the differences observed across age groups? I think (see prior comment) that the analyses were probably limited to correct trials, which is helpful, but still yields pretty big differences across groups in terms of the amount of data going into each analysis. In general, children showed more attenuated neural effects (e.g., recent/remote or session effects); could this be explained by their weaker memory? Specifically, if only correct trials are considered that means that fewer trials would be going into the analysis for kids, especially for the 14-day remote memories, and perhaps pushing the remove > recent difference for this condition towards 0. The authors might be able to address this analytically; for example, does the remote > recent difference in the univariate data at day 14 correlate with day 14 memory?

5. Some of the univariate results reporting is a bit strange, as they are relying upon differences between retrieval of 1- vs. 14-day memories in terms of the recent vs. report difference, and yet don't report whether the regions are differently active for recent and remote retrieval. For example in Figure 3A, neither anterior nor posterior hippocampus seem to be differentially active for recent vs. remote memories for either age group (i.e., all data is around 0). This difference from zero or lack thereof seems important to the message - is that correct? If so, can the authors incorporate descriptions of these findings?

6. Please provide more details about the choices available for locations in the 3AFC task. (1) Were they different each time, or always the same? If they are always the same, could this be a motor or stimulus/response learning task? (2) Do the options in the 3AFC always come from the same area - in which case the participant is given a clue as to the gist of the location/memory? Or are they sometimes randomly scattered across the image (in which case gist memory, like at a delay, would be sufficient for picking the right option)? Please clarify these points and discuss the logic/impact of these choices on the interpretation of the results.

7. Often p values are provided but test statistics, effect sizes, etc. are not - please include this information. It is at times hard to tell whether the authors are reporting main effects, interactions, pairwise comparisons, etc.

8. There are not enough methodological details in the main paper to make sense of the results. For example, it is not clear from reading the text that there are new object-location pairs learned each day.

9. The retrieval task does not seem to require retrieval of the scene itself, and as such it would be helpful for the authors to both explain their reasoning for this task to measure reinstatement. Strictly speaking, participants could just remember the location of the object on the screen. Was it verified that children and adults were recalling the actual scene rather than just the location (e.g. via self-report)? It's possible that there may be developmental differences in the tendency to reinstate the scene depending on e.g., their strategy.

10. In general I found the Introduction a bit difficult to follow. Below are a few specific questions I had.

a. At points findings are presented but the broader picture or take-home point is not expressed directly. For example, lines 112-127, these findings can all be conceptualized within many theories of consolidation, and yet those overarching frameworks are not directly discussed (e.g., that memory traces go from being more reliant on the hippocampus to more on the neocortex). Making these connections directly would likely be helpful for many readers.

b. Lines 143-153 - The comparison of the Tompary & Davachi (2017) paper with the Oedekoven et al. (2017) reads like the two analyses are directly comparable, but the authors were looking at different things. The Tompary paper is looking at organization (not reinstatement); while the Oedekoven et al. paper is measuring reinstatement (not organization). The authors should clarify how to reconcile these findings.

c. Line 195-6: I was confused by the prediction of "stable involvement of HC over time" given the work reviewed in the Introduction that HC contribution to memory tends to decrease with consolidation. Please clarify or rephrase.

d. Lines 200-202: I was a bit confused about this prediction. Firstly, please clarify whether immediate reinstatement has been characterized in this way for kids versus adults. Secondly, don't adults retain gist more over long delays (with specific information getting lost), at least behaviourally? This prediction seems to go against that; please clarify.

Reviewer #3 (Public Review):

Summary:<br /> This study aimed to understand the neural correlates of memory recall over short (1-day) and long (14-days) intervals in children (5-7 years old) relative to young adults. The results show that children recall less than young adults and that this is accompanied by less activation (relative to young adults) in brain networks associated with memory retrieval.

Strengths:<br /> This paper is one of few investigating long-term memory (multiple days) in a developmental population, an important gap in the field. Also, the authors apply a representational similarity analysis to understand how specific memories evolve over time. This analysis shows how the specificity of memories decreases over time in children relative to adults. This is an interesting finding.

Weaknesses:<br /> Overall, these results are consistent with what we already know: recall is worse in children relative to adults (e.g., Cycowicz et al., 2001) and children activate memory retrieval networks to a lesser extent than adults (Bauer et al, 2017).

It seems that the reduced activation in memory recall networks is likely associated with less depth of memory encoding in children due to inattentiveness, reduced motivation, and documented differences in memory strategies. In regards to this, there was consideration of IQ, sex, and handedness but these were not included as covariates as they were not significant although I note p<.16 suggests there was some level of association nonetheless. Also, IQ is measured differently for the children and adults so it's not clear these can be directly contrasted. The authors suggest the instructed elaborative encoding strategy is effective for children and adults but the reference in support of this (Craik & Tulving, 1975) does not seem to support this point.

Reviewer #2 (Public Review):

Schommartz et al. present a manuscript characterizing neural signatures of reinstatement during cued retrieval of middle-aged children compared to adults. The authors utilize a paradigm where participants learn the spatial location of semantically related item-scene memoranda which they retrieve after short or long delays. The paradigm is especially strong as the authors include novel memoranda at each delayed time point to make comparisons across new and old learning. In brief, the authors find that children show more forgetting than adults, and adults show greater engagement of cortical networks after longer delays as well as stronger item-specific reinstatement. Interestingly, children show more category-based reinstatement, however, evidence supports that this marker may be maladaptive for retrieving episodic details. The question is extremely timely both given the boom in neurocognitive research on the neural development of memory, and the dearth of research on consolidation in this age group. Also, the results provide novel insights into why consolidation processes may be disrupted in children. Despite these strengths, there are quite a few important design and analytical choices that derail my enthusiasm for the paper. If the authors could address these concerns, this manuscript would provide a solid foundation to better understand memory consolidation in children.

Reviewer #2 (Public Review):

In this paper, Boi et al. thoroughly classified the electrophysiological and morphological characteristics of serotonergic and dopaminergic neurons in the DRN and examined the alterations of these neurons in the 6-OHDA-induced mouse PD model. Using whole-cell patch clamp recording, they found that 5-HT and dopamine (DA) neurons in the DRN are electrophysiologically well-distinguished from each other. In addition, they characterized distinct morphological features of 5-HT and DA neurons in the DRN. Notably, these specific features of 5-HT and DA neurons in the DRN exhibited different changes in the 6-OHDA-induced PD model. Then the authors utilized desipramine (DMI) to separate the effects of nigrostriatal DA depletion and noradrenalin (NA) depletion which are induced by 6-OHDA. Interestingly, protection from NA depletion by DMI pretreatment reversed the changes in 5-HT neurons, while having a minor impact on the changes in DA neurons in the DRN. These data indicate that the role of NA lesion in the altered properties of DRN 5-HT neurons by 6-OHDA is more critical than the one of DA lesion.

Overall, this study provides foundational data on the 5-HT and DA neurons in the DRN and their potential involvement in PD symptoms. Given the defects of the DRN in PD, this paper may offer insights into the cellular mechanisms that may underlie non-motor symptoms associated with PD. Despite the importance of the primary claim proposed by the authors, however, several weaknesses undermine the significance of the data.

Reviewer #1 (Public Review):

Summary:<br /> People with Parkinson's disease often experience a variety of nonmotor symptoms, the biological bases of which remain poorly understood. Johansson et al began to study the potential roles of the dorsal raphe nucleus (DRN) degeneration in the pathophysiology of neuropsychiatric symptoms in PD.

Strengths:<br /> Johansson et al validated a transgenic reporter mouse line that can reliably label dopaminergic neurons in the DRN. This brain region shows severe neurodegeneration and has been proposed to contribute to the manifestation of neuropsychiatric symptoms in PD. Using this mouse line (and others), Johansson and colleagues characterized electrophysiological and morphological phenotypes of dopaminergic and serotoninergic neurons in the raphe nucleus. This study involved very careful topographical registration of recorded neurons to brain slices for post hoc immunohistochemical validation of cell identification, making it an elegant and thorough piece of work.

In relevance to PD pathophysiology, the authors evaluated the physiological and morphological changes of DRN serotoninergic and dopaminergic neurons after a partial loss of nigrostriatal dopamine neurons, which serves as a mouse model of early parkinsonian pathology. Importantly, the authors identified a series of physiological and morphological changes of subtypes of DRN neurons that depend on nigral dopaminergic neurodegeneration, LC adrenergic neurodegeneration, or both.

Overall, the study was well-designed, and the data were well-presented in this well-written manuscript.

Weaknesses:<br /> Caveats that should be mentioned include:

1) While desipramine experiments provide clues about the potential role of adrenaline loss in electrophysiological and morphological changes in the Figs. 3-5, a complementary set of experiments is needed to confirm these findings. For example, how might selective LC adrenergic neurodegeneration affect cellular physiology and morphology in the DRN? Can the observed phenotypes in Figs 3-4 be rescued by adrenergic receptor agonists?

2) It should be kept in mind that the key experiments of this study were conducted using mouse models of parkinsonism. Thus, these models cannot recapitulate the complexity of PD pathology and circuit dysfunction.

Reviewer #3 (Public Review):

Summary:<br /> Using ex vivo electrophysiology and morphological analysis, Boi et al. investigate the electrophysiological and morphological properties of serotonergic and dopaminergic subpopulations in the dorsal raphe nucleus (DRN). They performed labor-intensive and rigorous electrophysiology with posthoc immunohistochemistry and neuronal reconstruction to delineate the two major cell classes in the DRN: DRN-DA and DRN-5HT, named according to their primary neurotransmitter machinery. They find that the dopaminergic (DRN-DA) and serotonergic (DRN-5HT) neurons are electrophysiologically and morphologically distinct, and are altered following striatal injection of the toxin 6-OHDA. However, these alterations were largely prevented in DRN-5HT neurons by pre-treatment with desipramine. These findings suggest an important interplay between catecholaminergic systems in healthy and parkinsonian conditions, as well as a relationship between neuronal structure and function.

Strengths:<br /> A large, well-validated dataset that will be a resource for others.<br /> Complementary electrophysiological and anatomical characterizations.<br /> Conclusions are justified by the data.<br /> Relevant for basic scientists interested in DRN cell types and physiology.<br /> Relevant for those interested in serotonin and/or DRN neurons in Parkinson's Disease.

Weaknesses:<br /> Given the scope of the author's questions and hypotheses, I did not identify any major weaknesses.

Reviewer #1 (Public Review):

Koumoundourou et al., identify a pathway downstream of Bcl11b that controls synapse morphology and plasticity of hippocampal mossy fiber synapses. Using an elegant combination of in vivo, ex vivo, and in vitro approaches, the authors build on their previous work that indicated C1ql2 as a functional target of Bcl11b (De Bruyckere et al., 2018). Here, they examine the functional implications of C1ql2 at MF synapses in Bcl11b cKO mice and following C1ql2 shRNA. The authors find that Bcl11b KO and shRNA against C1ql2 significantly reduces the recruitment of synaptic vesicles and impairs LTP at MF synapses. Importantly, the authors test a role for the previously identified C1ql2 binding partner, exon 25b-containing Nrxn3 (Matsuda et al., 2016), as relevant at MF synapses to maintain synaptic vesicle recruitment. To test this, the authors developed a K262E C1ql2 mutant that disrupts binding to Nrxn3. Curiously, while Bcl11b KO and C1ql2 KD largely phenocopy (reduced vesicle recruitment and impaired LTP), only vesicle recruitment is dependent on C1ql2-Nrxn3 interactions. These findings provide new insight into the functional role of C1ql2 at MF synapses. While the authors convincingly demonstrate a role for C1ql2-Nrxn3(25b+) interaction for vesicle recruitment and a Nrxn3(25b+)-independent role for C1ql2 in LTP, the underlying mechanisms remain inconclusive. Additionally, a discussion of how these findings relate to previous work on C1ql2 at mossy fiber synapses and how the findings contribute to the biology of Nrxn3 would increase the interpretability of this work.

Reviewer #2 (Public Review):

This manuscript describes experiments that further investigate the actions of the transcription factor Bcl11b in regulating mossy fiber (MF) synapses in the hippocampus. Prior work from the same group had demonstrated that loss of Bcl11b results in loss of MF synapses as well as a decrease in LTP. Here the authors focus on a target of Bcl11b a secreted synaptic organizer C1ql2 which is almost completely lost in Bcl11b KO. Viral reintroduction of C1ql2 rescues the synaptic phenotypes, whereas direct KD of C1ql2 recapitulates the Bcl1 phenotype. C1ql2 itself interacts directly with Nrxn3 and replacement with a binding deficient mutant C1q was not able to rescue the Bcl11b KO phenotype. Overall there are some interesting observations in the study, however there are also some concerns about the measures and interpretation of data.

The authors state that they used a differential transcriptomic analysis to screen for candidate targets of Bcl11b, yet they do not present any details of this screen. This should be included and at the very least a table of all DE genes included. It is likely that many other genes are also regulated by Bcl11b so it would be important to the reader to see the rationale for focusing attention on C1ql2 in this study.

All viral-mediated expression uses AAVs which are known to ablate neurogenesis in the DG (Johnston DOI: 10.7554/eLife.59291) through the ITR regions and leads to hyperexcitability of the dentate. While it is not clear how this would impact the measurements the authors make in MF-CA3 synapses, this should be acknowledged as a potential caveat in this study.

The authors claim that the viral re-introduction "restored C1ql2 protein expression to control levels. This is misleading given that the mean of the data is 2.5x the control (Figure 1d and also see Figure 6c). The low n and large variance are a problem for these data. Moreover, they are marked ns but the authors should report p values for these. At the least, this likely large overexpression and variability should be acknowledged. In addition, the use of clipped bands on Western blots should be avoided. Please show the complete protein gel in primary figures of supplemental information.

Measurement of EM micrographs: As prior work suggested that MF synapse structure is disrupted the authors should report active zone length as this may itself affect "synapse score" defined by the number of vesicles docked. More concerning is that the example KO micrographs seem to have lost all the densely clustered synaptic vesicles that are away from the AZ in normal MF synapses e.g. compare control and KO terminals in Fig 2a or 6f or 7f. These terminals look aberrant and suggest that the important measure is not what is docked but what is present in the terminal cytoplasm that normally makes up the reserve pool. This needs to be addressed with further analysis and modifications to the manuscript.

The study also presents correlated changes in MF LTP in Bcl11b KO which are rescued by C1ql2 expression. It is not clear whether the structural and functional deficits are causally linked and this should be made clearer in the manuscript. It is also not apparent why this functional measure was chosen as it is unlikely that C1ql2 plays a direct role in presynaptic plasticity mechanisms that are through a cAMP/ PKA pathway and likely disrupted LTP is due to dysfunctional synapses rather than a specific LTP effect. The authors should consider measures that might support the role of Bcl11b targets in SV recruitment during the depletion of synapses or measurements of the readily releasable pool size that would complement their findings in structural studies.<br /> Bcl11b KO reduces the number of synapses, yet the I-O curve reported in Supp Fig 2 is not changed. How is that possible? This should be explained.

Matsuda et al DOI: 10.1016/j.neuron.2016.04.001 previously reported that C1ql2 organizes MF synapses by aligning postsynaptic kainate receptors with presynaptic elements. As this may have consequences for the functional properties of MF synapses including their plasticity, the authors should report whether they see deficient postsynaptic glutamate receptor signaling in the Bcl11b KO and rescue in the C1ql2 re-expression.

Reviewer #3 (Public Review):

Overall, this is a strong manuscript that uses multiple current techniques to provide specific mechanistic insight into prior discoveries of the contributions of the Bcl11b transcription factor to mossy fiber synapses of dentate gyrus granule cells. The authors employ an adult deletion of Bcl11b via Tamoxifen-inducible Cre and use immunohistochemical, electron microscopy, and electrophysiological studies of synaptic plasticity, together with viral rescue of C1ql2, a direct transcriptional target of Bcl11b or Nrxn3, to construct a molecular cascade downstream of Bcl11b for DG mossy fiber synapse development. They find that C1ql2 re-expression in Bcl11b cKOs can rescue the synaptic vesicle docking phenotype and the impairments in MF-LTP of these mutants. They also show that C1ql2 knockdown in DG neurons can phenocopy the vesicle docking and plasticity phenotypes of the Bcl11b cKO. They also use artificial synapse formation assays to suggest that C1ql2 functions together with a specific Nrxn3 splice isoform in mediating MF axon development, extending these data with a C1ql2-K262E mutant that purports to specifically disrupt interactions with Nrxn3. All of the molecules involved in this cascade are disease-associated and this study provides an excellent blueprint for uncovering downstream mediators of transcription factor disruption. Together this makes this work of great interest to the field. Strengths are the sophisticated use of viral replacement and multi-level phenotypic analysis while weaknesses include the linkage of C1ql2 with a specific Nrxn3 splice variant in mediating these effects.

Here is an appraisal of the main claims and conclusions:

1. C1ql2 is a downstream target of Bcl11b which mediates the synaptic vesicle recruitment and synaptic plasticity phenotypes seen in these cKOs. This is supported by the clear rescue phenotypes of synapse anatomy (Fig.2) and MF synaptic plasticity (Fig.3). One weakness here is the absence of a control assessing over-expression phenotypes of C1ql2. It's clear from Fig.1D that viral rescue is often greater than WT expression (totally expected). In the case where you are trying to suppress a LoF phenotype, it is important to make sure that enhanced expression of C1ql2 in a WT background does not cause your rescue phenotype. A strong overexpression phenotype in WT would weaken the claim that C1ql2 is the main mediator of the Bcl11b phenotype for MF synapse phenotypes.

2. Knockdown of C1ql2 via 4 shRNAs is sufficient to produce the synaptic vesicle recruitment and MF-LTP phenotypes. This is supported by clear effects in the shRNA-C1ql2 groups as compared to nonsense-EGFP controls. One concern (particularly given the use of 4 distinct shRNAs) is the potential for off-target effects, which is best controlled for by a rescue experiment with RNA-insensitive C1ql2 cDNA as opposed to nonsense sequences, which may not elicit the same off-target effects.

3. C1ql2 interacts with Nrxn3(25b+) to facilitate MF terminal SV clustering. This claim is theoretically supported by the HEK cell artificial synapse formation assay (Fig.5), the inability of the K262-C1ql2 mutation to rescue the Bcl11b phenotype (Fig.6), and the altered localization of C1ql2 in the Nrxn1-3 deletion mice (Fig.7). Each of these lines of experimental evidence has caveats that should be acknowledged and addressed. Given the hypothesis that C1ql2 and Nrxn3b(25b) are expressed in DG neurons and work together, the heterologous co-culture experiment seems strange. Up till now, the authors are looking at pre-synaptic function of C1ql2 since they are re-expressing it in DGNs. The phenotypes they are seeing are also pre-synaptic and/or consistent with pre-synaptic dysfunction. In Fig.5, they are testing whether C1ql2 can induce pre-synaptic differentiation in trans, i.e. theoretically being released from the 293 cells "post-synaptically". But the post-synaptic ligands (Nlgn1 and and GluKs) are not present in the 293 cells, so a heterologous synapse assay doesn't really make sense here. The effect that the authors are seeing likely reflects the fact that C1ql2 and Nrxn3 do bind to each other, so C1ql2 is acting as an artificial post-synaptic ligand, in that it can cluster Nrxn3 which in turn clusters synaptic vesicles. But this does not test the model that the authors propose (i.e. C1ql2 and Nrxn3 are both expressed in MF terminals). Perhaps a heterologous assay where GluK2 is put into HEK cells and the C1ql2 and Nrxn3 are simultaneously or individually manipulated in DG neurons?

4. K262-C1ql2 mutation blocks the normal rescue through a Nrxn3(25b) mechanism (Fig.6). The strength of this experiment rests upon the specificity of this mutation for disrupting Nrxn3b binding (presynaptic) as opposed to any of the known postsynaptic C1ql2 ligands such as GluK2. While this is not relevant for interpreting the heterologous assay (Fig.5), it is relevant for the in vivo phenotypes in Fig.6. Similar approaches as employed in this paper can test whether binding to other known postsynaptic targets is altered by this point mutation.

5. Altered localization of C1ql2 in Nrxn1-3 cKOs. These data are presented to suggest that Nrx3(25b) is important for localizing C1ql2 to the SL of CA3. Weaknesses of this data include both the lack of Nrxn specificity in the triple a/b KOs as well as the profound effects of Nrxn LoF on the total levels of C1ql2 protein. Some measure that isn't biased by this large difference in C1ql2 levels should be attempted (something like in Fig.1F).

Reviewer #3 (Public Review):

This study demonstrates that from fish to mammals CIB2/3 is required for hearing, revealing the high degree of conservation of CIB2/3 function in vertebrate sensory hair cells. The modeling data reveal how CIB2/3 may affect the conductance of the TMC1/2 channels that mediate mechanotransduction, which is the process of converting mechanical energy into an electrical signal in sensory receptors. This work will likely impact future studies of how mechanotransduction varies in different hair cell types.

One caveat is that the experiments with the mouse mutants are confirmatory in nature with regard to a previous study by Wang et al., and the authors use lower resolution tools in terms of function and morphological changes. Another is that the modeling data is not supported by electrophysiological experiments, however, as mentioned above, future experiments may address this weakness.

Reviewer #1 (Public Review):

This reviewed preprint is a bit of Frankenstein monster, as it crams together three quite different sets of data. It is essentially three papers combined into one-one paper focused on the role of CIB2/CIB3 in VHCs, one on the role of CIB2/CIB3 in zebrafish, and one on structural modeling of a CIB2/3 and TMC1/2 complex. The authors try to combine the three parts with the overarching theme of demonstrating that CIB2/3 play a functionally conserved role across species and hair cell types, but given the previous work on these proteins, especially Liang et al. (2021) and Wang et al. (2023), this argument doesn't work very well. My sense is that the way the manuscript is written now, the sum is less than the individual parts, and the authors should consider whether the work is better split into three separate papers.

The most important shortcoming is the novelty of the work presented here. In line 89 of the introduction the authors state "However, whether CIB2/3 can function and interact with TMC1/2 proteins across sensory organs, hair-cell types, and species is still unclear." They make a similar statement in the first sentence of the discussion and generally use this claim throughout the paper as motivation for why they performed the experiments. Given the data presented in the Liang et al. (2021) and Wang et al. (2023 papers), however, this statement is not well supported. Those papers clearly demonstrate a role for CIB2/CIB3 in auditory and vestibular cells in mice. Moreover, there is also data in Riazuddin et al. (2012) paper that demonstrates the importance of CIB2 in zebrafish and Drosophila. I think the authors are really stretching to describe the data in the manuscript as novel. Conceptually, it reads more as solidifying knowledge that was already sketched out in the field in past studies.

There is one exception, however, and that is the last part of the manuscript. Here structural studies (AlphaFold 2 modeling, NMR structure determination, and molecular dynamics simulations) bring us closer to the structure of the mammalian TMCs, alone and in complex with the CIB proteins. Moreover, the structural work supports the assignment of the TMC pore to alpha helices 4-7.

Reviewer #2 (Public Review):

The paper 'Complexes of vertebrate TMC1/2 and CIB2/3 proteins 1 form hair-cell mechanotransduction cation channels' by Giese and coworkers is quite an intense reading. The manuscript is packed with data pertaining to very different aspects of MET apparatus function, scales, and events. I have to praise the team that combined molecular genetics, biochemistry, NMR, microscopy, functional physiology, in-vivo tests for vestibulo-ocular reflexes, and other tests for vestibular dysfunction with molecular modeling and simulations. The authors nicely show the way CIBs are associated with TMCs to form functional MET channels. The authors clarify the specificity of associations and elucidate the functional effects of the absence of specific CIBs and their partial redundancy.

Joint Public Review:

The authors report the first use of the bacterial Tus-Ter replication block system in human cells. A single plasmid containing two divergently oriented five-fold TerB repeats was integrated on chromosome 12 of MCF7 cells. ChIP and PLA experiments convincingly demonstrate the occupancy of Tus at the Ter sites in cells. Using an elegant Single Molecule Analysis of Replicated DNA (SMARD) assay, compelling data demonstrate the replication block at Ter sites dependent on the presence of the protein. As an orthogonal method to demonstrate fork stalling, ChIP data show the accumulation of the replicative helicase component MCM3 and the repair protein FANCM around the Ter sites. Previous published work from the Scully and Hickson laboratories showed that Ter sites do not perturb replication fork progression and consistently the data show that the observed effects are dependent on expression of the Tus protein. The SMARD data reveal that about one third of the forks are arrested at Tus/Ter but it is unclear for how long forks remain stalled. Fork stalling led to a highly localized gammaH2AX response, as monitored by ChIP using primer pairs spread along the integrated plasmid carrying the Ter sites. This response was shown to be dependent on ATR using the ATR inhibitor VE-822. This contrasts with a single Cas9-induced DSB between the two Ter sites, which causes a more spread gammaH2AX response measured at two sites flanking the DSB. The difference between the DSB and the Tus-induced stall is very significant. Interestingly, despite evidence for ATR activation through the gammaH2AX response, no evidence for phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33 could be found under fork stalling conditions. The global replication inhibitor hydroxyurea (HU) elicited phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33. In this context, it would have been of interest to examine if a single DSB in the Ter region leads to phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33 and cell cycle arrest. The replication inhibitor HU led to an increase in gamma H2AX foci consistent with a global replication stress response. Overall, this is a well written manuscript, and the data provide convincing evidence that the Tus-Ter system poses a site-specific replication fork block in MCF7 cells leading to a localized ATR-dependent DNA damage checkpoint response that is distinct from the more global response to HU or DSBs.

Joint Public Review:

Summary:<br /> Cook, Watt, and colleagues previously reported that a mouse model of Spinocerebellar ataxia type 6 (SCA6) displayed defects in BDNF and TrkB levels at an early disease stage. Moreover, they have shown that one month of exercise elevated cerebellar BDNF expression and improved ataxia and cerebellar Purkinje cell firing rate deficits. In the current work, they attempt to define the mechanism underlying the pathophysiological changes occurring in SCA6. For this, they carried out RNA sequencing of cerebellar vermis tissue in 12-month-old SCA6 mice, a time when the disease is already at an advanced stage, and identified widespread dysregulation of many genes involved in the endo-lysosomal system. Focusing on BDNF/TrkB expression, localization, and signaling they found that, in 7-8 month-old SCA6 mice early endosomes are enlarged and accumulate BDNF and TrkB in Purkinje cells. Curiously, TrkB appears to be reduced in the recycling endosomes compartment, despite the fact that recycling endosomes are morphologically normal in SCA6. In addition, the authors describe a reduction in the Late endosomes in SCA6 Purkinje cells associated with reduced BDNF levels and a probable deficit in late endosome maturation.

Strengths:<br /> The article is well written, and the findings are relevant for the neuropathology of different neurodegenerative diseases where dysfunction of early endosomes is observed. The authors have provided a detailed analysis of the endo-lysosomal system in SCA6 mice. They have shown that TrkB recycling to the cell membrane in recycling endosomes is reduced, and the late endosome transport of BDNF for degradation is impaired. The findings will be crucial in understanding underlying pathology. Lastly, the deficits in early endosomes are rescued by chronic administration of 7,8-DHF.

Weaknesses:<br /> The specificity of BDNF and TrkB immunostaining requires additional controls, as it has been very difficult to detect immunostaining of BDNF. In addition, in many of the figures, the background or outside of Purkinje cell boundaries also exhibits a positive signal.

One important concern about the conclusions is that the RNAseq experiment was conducted in 12-month-old SCA6 mice suggesting that the defects in the endo-lysosomal system may be caused by other pathophysiological events and, likewise, the impairment in BDNF signaling may also be indirect, as also noted by the authors. Indeed, Purkinje cells in SCA6 mice have an impaired ability to degrade other endocytosed cargo beyond BDNF and TrkB, most likely because of trafficking deficits that result in a disruption in the transport of cargo to the lysosomes and lysosomal dysfunction. Moreover, the beneficial effects of 7,8-DHF treatment on motor coordination may be caused by 7,8-DHF properties other than the putative agonist role on TrkB. Indeed, many reservations have been raised about using 7,8-DHF as an agonist of TrkB activity. Several studies have now debunked (Todd et al. PlosONE 2014, PMID: 24503862; Boltaev et al. Sci Signal 2017, PMID: 28831019) or at the very least questioned (Lowe D, Science 2017: see Discussion: https://www.science.org/content/blog-post/those-compounds-aren-t-what-you-think-they-are Wang et al. Cell 2022 PMID: 34963057). Another interpretation is that 7,8-DHF possesses antioxidant activity and neuroprotection against cytotoxicity in HT-22 and PC12 cells, both of which do not express TrkB (Chen et al. Neurosci Lett 201, PMID: 21651962; Han et al. Neurochem Int. 2014, PMID: 24220540). Thus, while this flavonoid may have a beneficial effect on the pathophysiology of SCA6, it is most unlikely that mechanistically this occurs through a TrkB agonistic effect considering the potent anti-oxidant and anti-inflammatory roles of flavonoids in neurodegenerative diseases (Jones et al. Trends Pharmacol Sci 2012, PMID: 22980637).

Reviewer #1 (Public Review):

The manuscript by Zheng et al. examined the disease-causing mechanisms of two missense mutations within the homeodomain (HD) of CRX protein. Both mutations were found in humans and can produce severe dominant retinopathy. The authors investigated the two CRX HD mutants via in vitro DNA-binding assay (Spec-seq), in vivo chromatin-binding assay (ChIP-seq), in vivo expression assay of downstream target genes (RNA-seq), and retinal histological and functional assays. They concluded that p.E80A increased the transactivation activity of CRX and resulted in precocious photoreceptor differentiation, whereas p.K88N significantly changed the binding specificity of CRX and led to defects in photoreceptor differentiation and maintenance. The authors performed a significant amount of analyses. The claims are sufficiently supported by the data. The results not only uncovered the underlying disease-causing mechanisms, but also can significantly improve our understanding of the interaction between HD-TF and DNA during development.

Reviewer #2 (Public Review):

Zheng et al., investigated the molecular and functional mechanisms of two homeodomain missense mutations causing human retinal photoreceptor degeneration diseases in photoreceptor development regulated by the CRX transcription factor. They analyzed the E80A mutation associated with dominant cone-rod dystrophy (CRD) and the K88N mutation associated with dominant Leber Congenital Amaurosis (LCA). The authors found that E80A CRX binds to the same target DNA sites as WT CRX, but the binding specificity of K88N CRX is altered from that of WT in an in vitro assay. They generated Crx(E80A) and Crx(K88N) KI mice and performed ChIP assay and observed that K88N CRX binds to novel genomic regions from the WT-binding sites, while E80A binds to the WT sites. In addition, using the KI mice, they found that E80A and K88N differently affect the expression of Crx target genes. This study is well executed with proper and solid methodologies, and the manuscript is clearly written. This study gives us the insights into how single missense CRX mutations lead to different types of human retinal photoreceptor degeneration diseases.

Overall, the authors have significantly improved the manuscript, but there is still an unclarified point. In response to the inquiry in the initial review on how extent E80A KI mice function as a pathological model of dominant CoRD, the authors add data (Figures S7) and described the sixth section in the discussion. However, the authors mentioned that it is technically too challenging because of a small number of cones. The point is not clear to me, but it is possible to analyze cone differentiation and degeneration by immunostaining at multiple stages even though cone number is small. Cone arrestin and S- and M-opsins become positive at early postnatal stages in the mouse retina. Cone arrestin seems earlier than cone opsins. Cones seem born by detecting RXRg at P0, but are cone arrestin and/or cone opsins expressed in early postnatal E80A/+ retina? If positive, how about an apoptosis marker? If negative, it seems to be a cone development phenotype rather than cone degeneration phenotype. If so, authors should modify the expression to say that the E80A retina underlies CoRD-like phenotype. It seems an overstatement.

Reviewer #1 (Public Review):

The manuscript by Zheng et al. examined the disease-causing mechanisms of two missense mutations within the homeodomain (HD) of CRX protein. Both mutations were found in humans and can produce severe dominant retinopathy. The authors investigated the two CRX HD mutants via in vitro DNA-binding assay (Spec-seq), in vivo chromatin-binding assay (ChIP-seq), in vivo expression assay of downstream target genes (RNA-seq), and retinal histological and functional assays. They concluded that p.E80A increased the transactivation activity of CRX and resulted in precocious photoreceptor differentiation, whereas p.K88N significantly changed the binding specificity of CRX and led to defects in photoreceptor differentiation and maintenance. The authors performed a significant amount of analyses. The claims are sufficiently supported by the data. The results not only uncovered the underlying disease-causing mechanisms, but also can significantly improve our understanding of the interaction between HD-TF and DNA during development.

Reviewer #2 (Public Review):

Zheng et al., investigated the molecular and functional mechanisms of two homeodomain missense mutations causing human retinal photoreceptor degeneration diseases in photoreceptor development regulated by the CRX transcription factor. They analyzed the E80A mutation associated with dominant cone-rod dystrophy (CRD) and the K88N mutation associated with dominant Leber Congenital Amaurosis (LCA). The authors found that E80A CRX binds to the same target DNA sites as WT CRX, but the binding specificity of K88N CRX is altered from that of WT in an in vitro assay. They generated Crx(E80A) and Crx(K88N) KI mice and performed ChIP assay and observed that K88N CRX binds to novel genomic regions from the WT-binding sites, while E80A binds to the WT sites. In addition, using the KI mice, they found that E80A and K88N differently affect the expression of Crx target genes. The authors may want to provide explicit clarification on whether CRX E80A mice exhibit cone development and/or degeneration defects.

This study is well executed with proper and solid methodologies, and the manuscript is clearly written. This study gives us the insights into how single missense CRX mutations lead to different types of human retinal photoreceptor degeneration diseases.

Reviewer #3 (Public Review):

Ghasemahmad et al. examined behavioral and neurochemical responses of male and female mice to vocalizations associated with mating and restraint. The authors made two significant and exciting discoveries. They revealed that the affective content of vocalizations modulated both behavioral responses and the release of acetylcholine (ACh) and dopamine (DA) but not serotonin (5-HIAA) in the basolateral amygdala (BLA) of male and female mice. Moreover, the results show sex-based differences in behavioral responses to vocalizations associated with mating. The authors conclude that behavior and neurochemical responses in male and female mice are experience-dependent and are altered by vocalizations associated with restraint and mating. The findings suggest that ACh and DA release may shape behavioral responses to context-dependent vocalizations. The study has the potential to significantly advance our understanding of how neuromodulators provide internal-state signals to the BLA while an animal listens to social vocalizations; however, multiple concerns must be addressed to substantiate their conclusions.

Major concerns:

1. The authors normalized all neurochemical data to the background level obtained from a single pre-stimulus sample immediately preceding playback. The percentage change from the background level was calculated based on a formula, and the underlying concentrations were not reported. The authors should report the sample and background concentrations to make the results and analyses more transparent. The authors stated that NE and 5-HT had low recovery from the mouse brain and hence could not be tracked in the experiment. The authors could be more specific here by relating the concentrations to ACh, DA, and 5-HIAA included in the analyses.

2. For the EXP group, the authors stated that each animal underwent 90-min sessions on two consecutive days that provided mating and restraint experiences. Did the authors record mating or copulation during these experiments? If yes, what was the frequency of copulation? What other behaviors were recorded during these experiences? Did the experiment encompass other courtship behaviors along with mating experiences? Was the female mouse in estrus during the experience sessions?

3. For the mating playback, the authors stated that the mating stimulus blocks contained five exemplars of vocal sequences emitted during mating interactions. The authors should clarify whether the vocal sequences were emitted while animals were mating/copulating or when the male and female mice were inside the test box. If the latter was the case, it might be better to call the playback "courtship playback" instead of "mating playback".

4. Since most differences that the authors reported in Figure 3 were observed in Stim 1 and not in Stim 2, it might be better to perform a temporal analysis - looking at behaviors and neurochemicals over time instead of dividing them into two 10-minute bins. The temporal analysis will provide a more accurate representation of changes in behavior and neurochemicals over time.

5. In Figures 2 and 3, the authors show the correlation between Flinching behavior and ACh concentration. The authors should report correlations between concentrations of all neurochemicals (not just ACh) and all behaviors recorded (not just Flinching), even if they are insignificant. The analyses performed for the stim 1 data should also be performed on the stim 2 data. Reporting these findings would benefit the field.

6. The mice used in the study were between p90 - p180. Although CBA/CaJ mice display normal hearing, sexual behaviors, and social behaviors for at least 1 year (Ohlemiller, Dahl, and Gagnon, JARO 11: 605-623, 2010), the age of the mice covers a range of 90 days. It would strengthen the authors' argument that the affective content of vocalizations modulated both behavioral responses and the release of acetylcholine (ACh) and dopamine (DA) but not serotonin (5-HIAA) in the basolateral amygdala (BLA) of male and female mice if there were no correlations between the magnitude of the neural responses and age.

7. The authors reported neurochemical levels estimated as the animals listened to the sounds played back. What about the sustained effects of changes in neurochemicals? Are there any potential long-term effects of social vocalizations on behavior and neurochemical levels? The authors might consider discussing long-term effects.

8. Histology from a single recording was shown in supplementary figure 1. It would benefit the readers if additional histology was shown for all the animals, not just the colored schematics summarizing the recording probe locations. Further explanation of the track location is also needed to help the readers. Make it clear for the readers which dextran-fluorescein labeling image is associated with which track in the schematic.

9. The authors did not control for the sounds being played back with a speaker. This control may be necessary since the effects are more pronounced in Stim 1 than in Stim 2. Playing white noise rather than restraint or courtship vocalizations would be an excellent control. However, the authors could perform a permutation analysis and computationally break the relationship between what sound is playing and the neurochemical data. This control would allow the authors to show that the actual neurochemical levels are above or below chance.

10. The authors indicated that each animal's post-vocalization session was also recorded. No data in the manuscript related to the post-vocalization playback period was included. This omission was a missed opportunity to show that the neurochemical levels returned to baseline, and the results were not dependent on the normalization process described in major concern #1. The data should be included in the manuscript and analyzed. It would add further support for the model described in Figure 6.

11. The authors could use a predictive model, such as a binary classifier trained on the CSF sampling data, to predict the type of vocalizations played back. The predictive model could support the conclusions and provide additional support for the model in Figure 6.

Reviewer #3 (Public Review):

Using the zebrafish model, this paper by Kraus A. et al., described the anti-virus response in the Olfactory bulb (OB) neurons and microglia. This paper used the behavioral test, neuron calcium imaging, and single-cell transcriptomic analysis. Importantly, this paper discovered that following IHNV infection, the OB neuron increased Pacap expression, which likely protects the neuron cells and mediates the anti-viral defense response. Overall, the findings presented in this paper are quite interesting.

Major strength:<br /> (1) The author demonstrated for the first time that zebrafish OSN neurons sense the IHNV viruses and transmit the viral signal to OB neurons. The zebrafish can be used as a new system to investigate the viral-neuron interaction and understand the mechanisms of how the neurons in the CNS to viral infection through the peripheral chemosensory system.

(2) This paper generated the first zebrafish OB sc-RNA sequencing data. The sc-RNA sequencing data generated in this paper will also help other zebrafish researchers who study the OB neurons.

Major weakness:<br /> The experiment results presented in this paper are not well-integrated. For example, it is unclear how the behavioral phenotype is connected to the neuronal calcium phenotype. It is also unclear how the behavioral or neuronal calcium imaging results is connected to the scRNA sequencing result.

Reviewer #1 (Public Review):

Kraus et al. investigated transcriptional responses to transient exposure to infectious hematopoietic necrosis virus in the brain of adult zebrafish using single cell RNA-Seq methods. The authors discovered valuable evidence for immune responses in microglial clusters within minutes of viral exposure, and longer term changes in neuronal populations one day after viral treatment. The strength of the study is the RNA-Seq data which will act as a valuable resource for the zebrafish community. Their discoveries from the RNA-Seq studies are convincing, where they find a neuropeptide called PACAP enriched in neuronal populations a day after viral exposure, which exhibit antiviral activity. 

The authors select the 1 day time point post-infection based on initial behavioral experiments, the evidence for which is modest at best. While the experiments with larval animals are more substantiated, they use adults for their RNA-Seq experiments. The behavioral phenotype in adults is a marginal decrease in velocity 1 day after infection. The authors could have performed other tests associated with sickness behaviors, or even characterized the locomotion in the open field experiment with more in-depth analysis (for example, the larval experiments had more information regarding turning angles).

Reviewer #2 (Public Review):

Kraus, Aurora et al. investigated the potential immune response of the olfactory bulb after exposure of the infectious hematopoietic necrosis virus (IHNV), via the olfactory epithelia. Specifically, they show that a) viral-specific neuronal activation of "OSNs" (Crypt cells), b) changes in behaviour of both adult and larval zebrafish after viral exposure, c) Pituitary adenylate-cyclase-activating polypeptide (PACAP), was enriched when assayed by single cell transcriptomic profiling of cells in the OB after OSNs are exposed to IHNV

Although the paper does have strengths in principle, the weaknesses of the manuscript are that these strengths are not directly demonstrated and the referencing of the manuscript omits many references important for the understanding of the questions and the results of the study. Furthermore, the data presented are not sufficient to fully support the key claims in the manuscript. In particular:

a) Viral-specific neuronal activation of OSNs:<br /> What type of neurons? The authors are a bit elusive and do not clearly state that the neurons are crypt cells (Sepahi et al.: rainbow trout) which have a very specific axonal projection to the brain and whose response characteristics are not well characterized (see work of Korsching lab). Crypt cells are not present in the olfactory epithelia of mammals. Furthermore, in their previous work the crypt cells die; so how do they think the (inflammatory) virus response is transmitted to the olfactory bulbs in order to protect the brain?<br /> The authors state from previous work that they never detected virus in the brain, but why would they? Does INHV move trans-synaptically?<br /> The neuronal activity was monitored using a pan-neuronal marker thus these data are of limited use when trying to understand the role of neuronal activity (crypt cells) in the IHNV-triggered activity: the authors may be looking at a generalized inflammation response, and the image presented is not particularly informative it is difficult to decipher the results. The authors assume IHNV is an odorant without carefully ruling out the possibility of a generalized inflammation response.<br /> b) Changes in behaviour of both adult and larval zebrafish after viral exposure:<br /> What is the motivating question for looking at behaviour of the virus infected animals? Do we know the effects of crypt cell loss on the behaviour in any fish species? Authors need to build a better conceptual framework for the behaviour experiments.

c) Pituitary adenylate-cyclase-activating polypeptide (PACAP) was enriched when assayed by single cell transcriptomic profiling of cells in the OB after OSNs are exposed to IHNV. Authors draw many generous conclusions from limited data. Authors seem to have forgotten to cite papers previously published showing that PACAP-38 has anti-viral activities in fish (VHSV: trout) such as: Velasquez et al 2020, First in vivo evidence of pituitary adenylate cyclase-activating polypeptide antiviral activity in teleost.<br /> The histology for PACAP presented in the manuscript is not convincing. The antibody is against the human form of PACAP thus any labelling should be treated with caution (and called PACAP-38-like).

Summary: The authors need to better develop their model (perhaps a diagram would be helpful) explaining exactly which neurons are transmitting the information. Because of the elusive nature of some referencing and the skirting of important issues such as clearly stating which neurons are affected (crypt cells), what the point of the behaviour is (relate to neuronal type infected by virus), and, the lack of an antibody specific to the zebrafish protein, the model appears to be built on an unstable base.

Joint Public Review:

In this manuscript, the authors challenge the fundamental concept that all neurons are derived from ectoderm. The key points of the authors argument are as follows:

1) Roughly half of the cells in the small intestinal longitudinal muscle-myenteric plexus (LM-MP) that express a pan-neuronal marker do not, by lineage tracing, appear to be derived from the neural crest.

2) Lineage tracing and marker gene imaging suggest that these non-neural crest derived neurons originate in the mesoderm, leading to their designation as mesodermal-derived enteric neurons (MENs).

3) Single-cell sequencing of LM-MP tissues confirms the mesodermal origin of MENs.

4) MENs progressively replace neural crest derived enteric neurons as mice age, eventually representing the bulk of the EN population.

There is broad agreement among the reviewers that the identification and description of this cell population is important, and that the failure of these cells to be labeled by neural crest lineage tracers is not artifactual. The work with transgenic lines is convincing that some presumptive neurons in the enteric nervous system (ENS) likely originate from an alternative source in the postnatal intestine and that this population increases in aging mice.

There is, however, ongoing disagreement between the authors and reviewers about whether the authors' provocative and potentially paradigm-changing proposal that these are neurons of mesodermal origin has been established. While the authors believe they have addressed the reviewers' concerns in multiple rounds of review (much of this prior to submission), the reviewers remain unconvinced and continue to request additional data and analyses.

A key premise of the preprint review system is that the best interests of science are not served by endlessly litigating disagreements around papers by either compelling the authors to do extensive and expensive additional experiments that they do not believe to be necessary or by treating the authors' claim as established in the face of continued skepticism. Accordingly the editor believes it is time to present this work, which everyone agrees contains important observations and valuable data, along with the following editor's synthesis of the reviewers' concerns and author responses about the question of these cells' origins. We encourage anyone interested in the details to review the already posted reviews and authors' response.

The following key issues have been raised during review:

* Is the lineage tracing and marker gene expression data definitive as to mesodermal origin?

* Are the cells analyzed in the genomic experiments the same as those identified in the lineage tracing experiments?

* Does the genomic data establish that the sub-population of cells the authors focus on are of mesodermal origin?

* Are there alternative explanations for the lineage tracing and genomic observations than a mesodermal origin?

* Is the lineage tracing and marker gene expression data definitive as to mesodermal origin? *

The proximal evidence that the authors present for a mesodermal origin of the non-NC derived cells is presented in Figure 2, which establishes the presence, via lineage tracing of Tek+ and Mesp1+ (and therefore mesoderm derived) and Hu+ (and therefore neuronal) cells. The fraction of lineage labeled cells in each case (~50%) corresponds roughly to the fraction of cells that do not appear to be NC derived.

The reviewers raise several technical questions about the lineage tracing experiments, including issues of incomplete labeling, ectopic labeling and toxicity. The authors have addressed each of these with data and/or citations, and the editor believes they have demonstrated, subject to the broader limits of lineage tracing experiments, that there are Hu+ cells in the tissue that are derived from cells that do not express NC markers and that do express mesodermal markers.

One reviewer raised the question of whether these cells are neurons. This appears to the editor to be a valid question, in that specific neuronal activity of these cells has not been established. But the authors' argument is persuasive that their Hu+ state would have led them to be designated neurons and that changing that designation based on not being derived from NC is circular. However the possibility that, despite this accepted designation, these cells are not functionally neurons should be noted by readers.

* Are the cells analyzed in the genomic experiments the same as those identified in the lineage tracing experiments, and does this data establish mesodermal origin? *

To provide orthogonal evidence for the presence of mesodermally derived enteric neurons, the authors carried out single-cell sequencing of dissociated cells from hand-dissected longitudinal muscle - myenteric plexus (LM-MP) tissue. They use standard methods to identify clusters of cells with similar transcriptomes, and designate, based on marker gene expression, two clusters to be neural crest derived enteric neurons (NENs) and mesoderm derived enteric neurons (MENs). However the reviewers raised several issues about the designation of the cells MENs, and therefore their equation with the cells identified in lineage tracing.

While the logic behind specific choices made in the single-cell analysis is not always clear in the manuscript, such as why genes not-specific to MENs were used to identify the MEN cluster and how genes were selected for subsequent analysis (although both issues are explained better in the authors' response to reviewers), they in the end identify a single large cluster that has the characteristics of MENs (it expresses both neuronal and mesodermal markers) that is (by immunohistochemistry) broadly associated with the previously described tissue MENs.

The standard methods for the delineation of clusters in single-cell sequencing data (which the authors use) are stochastic and defy statistical interpretation, and the way these data and analyses are used is often subjective. The editor shares the reviewers' confusion about aspects of the analysis, but also finds the authors' assertions that they have described a cluster of cells that express both neuronal and mesodermal genes, and that this cluster corresponds to the tissue MENs described in lineage tracing, to be broadly sound.

The biggest weakness in the single-cell data and analysis - identified by all reviewers - is the massive overrepresentation of MENs relative to NENs. The authors' explanation - that some cells are more sensitive to manipulations required to prepare cells for sequencing - is certainly well-represented in the literature and is therefore plausible. But it isn't fully satisfactory, especially because it undermines the notion that the MENs and NENs are functionally equivalent (though one could argue in response that increased fragility of NENs is why they are progressively replaced by MENs).

There are many additional questions about the single cell analysis that are difficult to resolve with the data in hand. I think everyone would agree that an ideal analysis would have more cells, deeper sequencing, and comprehensive validation of the identity of each cluster of cells. But given the time and expense required to carry out such experiments, we cannot demand them, and must take the data for what they are rather than what they could be. And in the end, it is the editors' view that these data and analyses bolster the authors' claims, without conclusively establishing them. That is, these data should neither be dismissed nor, on their own, considered definitive.

* Are there alternative explanations for the data than that they are mesodermally derived neurons? *

As discussed above, the reviewers generally agree that the lineage tracing experiments are careful and well-executed, and the authors have provided data that demonstrates that the data are highly unlikely to be due to either incomplete or ectopic lineage marking. The reviewers raise several possible alternative hypotheses, some based on the literature and some based on the genomic data. The authors discuss each in detail in their response. The editor would note that, at this stage in the history of single-cell analysis, the criteria for using single cell sequencing data to establish cell type and cell origin is are not well established, and that neither the presence nor absence of specific sets of genes in single cells should not, for both technical and biological reasons, be considered dispositive as to identity.

* Additional aspects of paper: *

There are additional intriguing aspects of the paper, especially the increase in the number of MENs relative to NENs over time, suggesting functional replacement of one population with the other, and some evidence for and speculation about what might be regulating this evolution. However these are somewhat secondary points relative to the central question at hand of whether the authors have discovered a population of mesodermally derived neurons.

* Editor's summary and comment: *

The editor believes it is a fair summary to say that the authors believe they have gone to great lengths to provide multiple lines of evidence that support their hypothesis, but that these reviewers, while appreciating the potential importance of the authors' discovery of an unusual cell type, are not yet convinced of its origin.

In an ideal world, the authors, reviewers and editor would all ultimately agree on what claims the data presented in a paper supports, and indeed this is what the traditional journal publishing system tries to achieve. But the system fails in cases like this where no consensus between authors and reviewers can be reached, as it neither makes sense to "accept" the paper and imply that it has been endorsed by the reviewers, nor to "reject" it and keep the work in peer review limbo.

There is certainly enough here to warrant the idea and the data and arguments behind it being digested and considered by people in the field. It may very well be that the authors - who have spent years working on this problem and likely know more about this population of cells than anyone on Earth - are right that they have discovered something that changes how we think about the development of the nervous system. To the extent the reviewers are representative, people are likely to need additional data to be convinced. But it is time to put that to the test.

Reviewer #3 (Public Review):

This manuscript aims to exploit experimental measurements of the extracellular voltages produced by colliding action potentials to adjust a simplified model of action potential propagation that is then used to predict the extracellular fields at axon terminals. The overall rationale is that when solving the cable equation (which forms the substrate for models of action potential propagation in axons), the solution for a cable with a closed end can be obtained by a technique of superposition: a spatially reflected solution is added to that for an infinite cable and this ensures by symmetry that no axial current flows at the closed boundary. By this method, the authors calculate the expected extracellular fields for axon terminals in different situations. These fields are of potential interest because, according to the authors, their magnitude can be larger than that of a propagating action potential and may be involved in ephaptic signalling. The authors perform direct measurements of colliding action potentials, in the earthworm giant axon, to parameterise and test their model.

Although simplified models can be useful and the trick of exploiting the collision condition is interesting, I believe there are several significant problems with the rationale, presentation, and application, such that the validity and potential utility of the approach is not established.

Simplified model vs. Hogdkin and Huxley<br /> The authors employ a simplified model that incorporates a two-state membrane (in essence resting and excited states) and adds a recovery mechanism. This generates a propagating wave of excitation and key observables such as propagation speed and action potential width (in space) can be adjusted using a small number of parameters. However, even if a Hodgkin-Huxley model does contain a much larger number of parameters that may be less easy to adjust directly, the basic formalism is known to be accurate and typical modifications of the kinetic parameters are very well understood, even if no direct characterisations already exist or cannot be obtained. I am therefore unconvinced by the utility of abandoning the Hodgkin-Huxley version.

In several places in the manuscript, the simplified model fits the data well whereas the Hodgkin-Huxley model deviates strongly (e.g. Fig. 3CD). This is unsatisfying because it seems unlikely that the phenomenon could not be modelled accurately using the HH formulation. If the authors really wish to assert that it is "not suitable to predict the effects caused by AP [collision]" (p9) they need to provide a good deal more analysis to establish the mechanism of failure.

(In)applicability of the superposition principle<br /> The reflecting boundary at the terminal is implemented using the symmetry of the collision of action potentials. However, at a closed cable there is no reflecting boundary in the extracellular space and this implied assumption is particularly inappropriate where the extracellular field is one objective of the modelling, as here. I believe this assumption is not problematic for the calculation of the intracellular voltage, because extracellular voltage gradients can usually be neglected, but the authors need to explain how the issue was dealt with for the calculation of the extracellular fields of terminals. I assume they were calculated from the membrane currents of one-half of the collision solution, but this does not seem to be explained. It might be worth showing a spatial profile of the calculated field.

Missing demonstrations<br /> Central analytical results are stated rather brusquely, notably equations (3) and (4) and the relation between them. These merit an expanded explanation at the least. A better explanation of the need for the collision measurements in parameterising the models should also be provided.

Adjusted parameters<br /> I am uncomfortable that the parameters adjusted to fit the model are the membrane capacitance and intracellular resistance. These have a physical reality and could easily be measured or estimated quite accurately. With a variation of more than 20-fold reported between the different models in Appendix 2 we can be sure that some of the models are based upon quite unrealistic physical assumptions, which in turn undermines confidence in their generality.

p8 the values of both the extracellular (100 Ohm m) and intracellular resistivity (1 Ohm m) appear to be in error, especially the former.

(In)applicability to axon terminals<br /> The rationale of the application of the collision formalism to axon terminals is somewhat undermined by the fact that they tend not to be excitable. There is experimental evidence for this in the Calyx of Held and the cerebellar pinceau. The solution found via collision is therefore not directly applicable in these cases.

Comparison with experimental data<br /> More effort should be made to compare the modelling with the extracellular terminal fields that have been reported in the literature.

Choice of term "annihilation"<br /> The term annihilation does not seem wholly appropriate to me. The dictionary definitions are something along the lines of complete destruction by an external force or mutual destruction, for example of an electron and a positron. I don't think either applies exactly here. I suggest retaining the notion of collision which is well understood in this context.

Reviewer #1 (Public Review):

The authors explain that an action potential that reaches an axon terminal emits a small electrical field as it "annihilates". This happens even though there is no gap junction, at chemical synapses. The generated electrical field is simulated to show that it can affect a nearby, disconnected target membrane by tens of microvolts for tenths of a microsecond. Longer effects are simulated for target locations a few microns away.

To simulate action potentials (APs), the paper does not use the standard Hodgkin-Huxley formalism because it fails to explain AP collision. Instead, it uses the Tasaki and Matsumoto (TM) model which is simplified to only model APs with three parameters and as a membrane transition between two states of resting versus excited. The authors expand the strictly binary, discrete TM method to a Relaxing Tasaki Model (RTM) that models the relaxation of the membrane potential after an AP. They find that the membrane leak can be neglected in determining AP propagation and that the capacitive currents dominate the process.

The strength of the work is that the authors identified an important interaction between neurons that is neglected by the standard models. A weakness of the proposed approach is the assumptions that it makes. For instance, the external medium is modeled as a homogeneous conductive medium, which may be further explored to properly account for biological processes.

The authors provide convincing evidence by performing experiments to record action potential propagation and collision properties and then developing a theoretical framework to simulate the effect of their annihilation on nearby membranes. They provide both experimental evidence and rigorous mathematical and computer simulation findings to support their claims. The work has the potential of explaining significant electrical interaction between nerve centers that are connected via a large number of parallel fibers.

Reviewer #2 (Public Review):

In this study, the authors measured extracellular electrical features of colliding APs travelling in different directions down an isolated earthworm axon. They then used these features to build a model of the potential ephaptic effects of AP annihilation, i.e. the electrical signals produced by colliding/annihilating APs that may influence neighbouring tissue. The model was then applied to some different hypothetical scenarios involving synaptic connections. The conclusion was that an annihilating AP at a presynaptic terminal can ephaptically influence the voltage of a postsynaptic cell (this is, presumably, the 'electrical coupling between neurons' of the title), and that the nature of this influence depends on the physical configuration of the synapse.

As an experimental neuroscientist who has never used computational approaches, I am unable to comment on the rigour of the analytical approaches that form the bulk of this paper. The experimental approaches appear very well carried out, and here I just have one query - an important assumption made is that the conduction velocity of anti- and orthodromically propagating APs is identical in every preparation, but this is never empirically/statistically demonstrated.

My major concern is with the conclusions drawn from the synaptic modelling, which, disappointingly, is never benchmarked against any synaptic data. The authors state in their Introduction that a 'quantitative physical description' of ephaptic coupling is 'missing', however, they do not provide such a description in this manuscript. Instead, modelled predictions are presented of possible ephaptic interactions at different types of synapses, and these are then partially and qualitatively compared to previous published results in the Discussion. To support the authors' assertion that AP annihilation induces electrical coupling between neurons, I think they need to show that their model of ephaptic effects can quantitatively explain key features of experimental data pertaining to synaptic function. Without this, the paper contains some useful high-precision quantitative measurements of axonal AP collisions, some (I assume) high-quality modelling of these collisions, and some interesting theoretical predictions pertaining to synaptic interactions, but it does not support the highly significant implications suggested for synaptic function.

Reviewer #1 (Public Review):

Summary:<br /> The study by Fang et al. reports a 3D MERFISH method that enables spatial transcriptomics for tissues up to 200um in thickness. MERFISH, as well as other spatial transcriptomics technologies, have been mainly used for thin (e.g, 10um) tissue slices, which limits the dimension of spatial transcriptomics technique. Therefore, expanding the capacity of MERFISH to thick tissues represents a major technical advance to enable 3D spatial transcriptomics. Here the authors provide detailed technical descriptions of the new method, troubleshooting, optimization, and application examples to demonstrate its technical capacity, accuracy, sensitivity, and utility. The method will likely have a major impact on future spatial transcriptomics studies to benefit diverse biomedical fields.

Strengths:<br /> The study was well-designed, executed, and presented. Extensive protocol optimization and quality assessments were carried out and conclusions are well supported by the data. The methods were sufficiently detailed and the results are solid and compelling.

Weaknesses:<br /> The biological application examples were limited to cell type/subtype classification in two brain regions. Additional examples of how the data could be used to address important biological questions will enhance the impact of the study.

Reviewer #2 (Public Review):

Summary:<br /> In their preprint, Fang et al present data on extending a spatial transcriptomics method, MERFISH, to 3D using a spinning disc confocal. MERFISH is a well-established method, first published by Zhaung's lab in 2015 with multiple follow-up papers. In the last few years, MERFISH has been used by multiple groups working on spatial transcriptomics, including approximately 12 million cell maps measured in the mouse brain atlas project. Variants of MERFISH were used to map epigenetic information complementary to gene expression and RNA abundance. However, MERFISH was always limited to thin ~10um sections to this date. The key contribution of this work by Fang et al. was to perform the optimization required to get MERFISH working in thick (100-200um) tissue sections.

Major strengths and weaknesses:<br /> Overall the paper presents a technical milestone, the ability to perform highly multiplexed RNA measurements in 3D using MERFISH protocol. This is not the first spatial transcriptomics done in thick sections. Wang et al. 2018 - StarMAP used thick sections (150 um), and recently, Wang 2021 (EASI-FISH, not cited) performed serial HCR FISH on 300um sections. Data so far suggest that MERFISH has better sensitivity than in situ sequencing approaches (StarMAP) and has built-in multiplexing that EASI-FISH lacks. Therefore, while there is an innovation in the current work, i.e., it is a technically challenging task, the novelty, and overall contribution are modest compared to recently published work.

The authors could improve the writing and the manuscript text that places their work in the right context of other spatial transcriptomics work. Out of the 25 citations, 12 are for previous MERFISH work by Zhaung's lab, and only one manuscript used a spatial transcriptomics approach that is not MERFISH. Furthermore, even this paper (Wang et al, 2018) is only discussed in the context of neuroanatomy findings. The fact that Wang et al. were the first to measure thick sections is not mentioned in the manuscript. The work by Wang et al. 2021 (EASI-FISH) is not cited at all, as well as the many other multiplexed FISH papers published in recent years that are very relevant. For example, a key difference between seqFISH+ and MERFISH was the fact that only seqFISH+ used a confocal microscope, and MERFISH has always been relying on epi. As this is the first MERFISH publication to use confocal, I expect citations to previous work in seqFISH and better discussions about differences.

To get MERFISH working in 3D, the authors solved a few technical problems. To address reduced signal-to-noise due to thick samples, Fang et al. used non-linear filtering (i.e., deep learning) to enhance the spots before detection. To improve registrations, the authors identified an issue specific to their Z-Piezo that could be improved and replaced with a better model. Finally, the author used water immersion objectives to mitigate optical aberrations. All these optimization steps are reasonable and make sense. In some cases, I can see the general appeal (another demonstration of deep learning to reduce exposure time). Still, in other cases, the issue is not necessarily general enough (i.e., a different model of Piezo Z stage) to be of interest to a broad readership. There were a few additional optimization steps, i.e., testing four concentrations of readout and encoder probes. So while the preprint describes a technical milestone, achieving this milestone was done with overall modest innovation.

Data and code sharing - the only link in the preprint related to data sharing sends readers to a deleted Dropbox folder. Similarly, the GitHub link is a 404 error. Both are unacceptable. The author should do a better job sharing their raw and processed data. Furthermore, the software shared should not be just the MERlin package used to analyze but the specific code used in that package.

Reviewer #1 (Public Review):

This study provides valuable imaging evidence for the connectopic mapping of the locus coeruleus where a rostro-caudal gradient was linked to heterogeneous functional organisations of the structure. The functional gradient of the LC changes over ageing and reflects capacities of related brain functions. The gradient approach is well-established and solid results were obtained and validated using large 3T and 7T fMRI dataset. The work highlights the importance of using more specific spatial definition of the LC based on distinct connectivity patterns in future resting-state fMRI studies.

Reviewer #2 (Public Review):

The authors have provided evidence for a rostral-caudal organisation of locus coeruleus connectivity, which they show i) differs across the lifespan, ii) is associated with relevant cognitive and mood measures. They have taken a data-driven, gradient-based approach, which was applied in the CamCan dataset and then replicated in the HCP dataset. This is a useful contribution to the field as it comprehensively shows a rostral-caudal pattern of connectivity in vivo, which has mostly been supported by tracer studies to date.

The strengths of the study are the large sample sizes and replication across two cohorts. The connectomic mapping approach they have applied is very well suited to the question at hand, as it allows a continuous gradient of organisation to be identified.

This "IF...ELSE Mark, END" region could be reduced by replacing the three lines corresponding to those control flow keywords with a single call to Check:

Check(ORS.ident, "identifier expected");

Reviewer #1:

The authors have addressed all the comments raised in the previous reviews.

Reviewer #2:

The authors have significantly improved the manuscript, where assumptions and analytical and numerical results are now presented more clearly.

I still have some comments, more of less specific, that I list below, starting with the conceptual ones.

1. Citation of previous work on dynamical quorum sensing (lines 51 & 52) I think misses two important points: first these works (and others following them) deal with the appearance of collective oscillations at high density (therefore, the same general problem addressed here); second, Taylor et al. studied also a transition where the oscillators involved did not oscillate at low density, whereas above a density threshold, they display coherent collective oscillations whose period decreases with density - similar to what observed here. I do not think this takes anything away from the originality of this work, which refers to a different system, and models it with different equations, but the parallelism between integrate-and-fire dynamics with quenched noise and excitable dynamics in the presence of noise should in my opinion not be overlooked.<br /> 2. As the authors stress in lines 105 and 132, the analytical model shows that all that really matters in this phenomenon is the fastest frequency of the system. This could be used as an argument to say that the actual frequency distribution of individual fireflies is not all that important, as long as their fastest frequency is comparable. The assumption that they are identical would then sound less radical. Ideally, one could use the numerical simulations to check this, as well as the fact that the phenomenon does not break down when the shortest individual interburst interval Tb_min is narrowly distributed (which could also explain why having a few individuals who can flash at a higher frequency does not affect the outcome).<br /> 3. I still feel that the agreement between the model and observations is a bit overstated (line 120). At least, I think the authors may stress that whereas the model predicts that the frequency of the 7-14 minutes oscillations should increase a lot with N, this is not observed in the data. Maybe this mismatch would be reduced if inter-individual variability was added.<br /> 4. In paragraph 4.2, I found it unclear why the authors find it unsurprising that different experiments would correspond to different betas. I think that this point should be discussed, as beta and N appear in combination in determining the interaction strength. Otherwise, they could try to fit all distributions with the same beta, which would be more natural for me. I guess that the fits would be anyway good to the eye, though quantitatively suboptimal (which could be quantified with the distance introduced).

Minor stylistic comments:<br /> 1. Lines 98-100. Are all three 'Thus' needed?<br /> 2. 114: 'sufficiently identical' sounds like an oxymoron: what about just 'identical', or 'sufficiently close, so that they can be approximately considered identical'?<br /> 3. It would be more in line with the text (line 122) if panel F was the first panel of Figure 3. Also, the two orange lines are very hardly visible in print. They could be thickened. The inset, which I guess represents a zoom into the low Tbs, should be explained in the figure caption.<br /> 4. The caption of figure 5 relative to panels A-E does not say what is depicted. On line 3, row -> rows<br /> 5. Line 195 provide -> provides

Reviewer #2 (Public Review):

In this paper, Wang and colleagues build on previous technical and analytical achievements in establishing tetraploid human-chimpanzee hybrid iPSCs to investigate the cell type-specificity of allele-specific expression and allele-specific chromatin accessibility across six differentiated cell types (here, "allele-specific" indicates species differences with a cis-regulatory basis). The combined body of work is remarkable in its creativity and ambition and has real potential for overcoming major challenges in understanding the evolutionary genetics of between-species differences. The present paper contributes to these efforts by showing how differentiated cells can be used to test a long-standing hypothesis in evolutionary genetics: that cis-regulatory changes may be particularly important in divergence because of their potential for modularity.

In my view, the paper succeeds in making this case: allele (species)-specific expression (ASE) and allele-specific chromatin accessibility (ASCA) are enriched in genes asymmetrically expressed in one cell type, and many cases of ASE/ASCA are cell type-specific. The authors do an excellent job showing that these results are robust across a set of possible analysis decisions. It is somewhat less clear whether these enrichments are primarily a product of relaxed constraint on cell type-specific genes or primarily result from positive selection in the human or chimp lineage. While the authors attempt to control for constraint using several variables (variance in ASE in humans and the sequence-based probability of haploinsufficiency score, pHI), these are imperfect proxies for constraint. For the pHI scores, enrichments for ASE also appear to be strongest in the least constrained genes. Overall, the relative role of relaxation of constraint versus positive selection is unresolved, although the manuscript's language leans in favor of an important role for selection.

The remainder of the manuscript draws on the cell type-specific ASE/ASCA data to nominate candidate genes and pathways that may have been important in differentiating humans and chimpanzees. Several approaches are used here, including comparing human-chimp ASE to the distribution of ASE observed in humans and investigating biases in the direction of ASE for genes in the same pathway. The authors also identify interesting candidate genes based on their role in development or their proximity to human accelerated regions (where many changes have arisen on the human lineage in otherwise deeply conserved sequence) and use a deep neural network to identify sequence changes that might be causally responsible for ASE/ASCA. These analyses have value and highlight potential strategies for using ASE/ASCA and hybrid cell line data as a hypothesis-generating tool. Of course, the functional follow-up that experimentally tested these hypotheses or linked sequence/expression changes in the candidate pathways to organismal phenotype would have strengthened the paper further- but this is a lot to ask in an already technically and analytically challenging piece of work.

As a minor critique, the present paper is very closely integrated with other manuscripts that have used the hybrid human-chimp cell lines for biological insight or methods development. Although its contributions make it a strong stand-alone contribution, some aspects of the methods are not described in sufficient detail for readers to understand (even on a general conceptual level) without referencing that work, which may somewhat limit reader understanding.

Reviewer #1 (Public Review):

This study aims to identify gene expression differences exclusively caused by cis-regulatory genetic changes by utilizing hybrid cell lines derived from human and chimpanzee. While previous attempts have focused on specific tissues, this study expands the comparison to six different tissues to investigate tissue specificity and derive insights into the evolution of gene expression.

One notable strength of this work lies in the use of composite cell lines, enabling a comparison of gene expression between human and chimpanzee within the same nucleus and shared trans factors environment. However, a potential weakness of the methodology is the use of bulk RNA-seq in diverse tissues, which limits the ability to determine cell-type-specific gene expression and chromatin accessibility regions.

Another concern is the use of two replicates derived from the same pair of individuals. While the authors produced cell lines from two pairs of individuals in a previous study (Agloglia et al., 2021), I wonder why only one pair was used in this study. Incorporating interindividual variation would enhance the robustness of the species differences identified here.

Furthermore, the study offers the opportunity to relate inter-species differences to trends in molecular evolution. The authors discovered that expression variance and haploinsufficiency score do not fully account for the enrichment of divergence in cell-type-specific genes. The reviewer suggests exploring this further by incorporating external datasets that bin genes based on interindividual transcriptomics variation as a measure of extant transcriptomics constraint (e.g., GTEx reanalysis by Garcia-Perez et al., 2023 - PMID: 36777183). Additionally, stratifying sequence conservation on ASCA regions, which exhibit similar enrichment of cell-type-specific features, using the Zoonomia data mentioned also in the text (Andrews et al., 2023 -- PMID: 37104580) could provide valuable insights.

Another potential strength of this study is the identification of specific cases of paired allele-specific expression (ASE) and allele-specific chromatin accessibility (ASCA) with biological significance. Prioritizing specific variants remains a challenge, and the authors apply a machine-learning approach to identify potential causative variants that disrupt binding sites in two examples (FABP7 and GAD1 in motor neurons). However, additional work is needed to convincingly demonstrate the functionality of these selected variants. Strengthening this section with additional validation of ASE, ASCA, and the specific putative causal variants identified would enhance the overall robustness of the paper.

Additionally, the authors support the selected ASE-ASCA pairs by examining external datasets of adult brain comparative genomics (Ma et al., 2022) and organoids (Kanton et al., 2019). While these resources are valuable for comparing observed species biases, the analysis is not systematic, even for the two selected genes. For example, it would be beneficial to investigate if FABP7 exhibits species bias in any cell type in Kanton et al.'s organoids or if GAD1 is species-biased in adult primate brains from Ma et al. Comparing these datasets with the present study, along with the Agoglia et al. reference, would provide a more comprehensive perspective.

The use of the term "human-derived" in ASE and ASCA should be avoided since there is no outgroup in the analysis to provide a reference for the observed changes.

Finally, throughout the paper, the authors refer to "hybrid cell lines." It has been suggested to use the term "composite cell lines" instead to address potential societal concerns associated with the term "hybrid," which some may associate with reproductive relationships (Pavlovic et al., 2022 -- PMID: 35082442). It would be interesting to know the authors' perspective on these concerns and recommendations presented in Pavlovic et al., given their position as pioneers in this field.

Reviewer #3 (Public Review):

The authors utilize chimpanzee-human hybrid cell lines to assess cis-regulatory evolution. These hybrid cell lines offer a well-controlled environment, enabling clear differentiation between cis-regulatory effects and environmental or other trans effects.<br /> In their research, Wang et al. expand the range of chimpanzee-human hybrid cell lines to encompass six new developmental cell types derived from all three germ layers. This expansion allows them to discern cell type-specific cis-regulatory changes between species from more pleiotropic ones. Although the study investigates only two iPSC clones, the RNA- and ATAC-seq data produced for this paper is a valuable resource.

The authors begin their analysis by examining the relationship between allele-specific expression (ASE) as a measure of species divergence and cell type specificity. They find that cell-type-specific genes exhibit more divergent expression. By integrating this data with measures of constraint within human populations, the authors conclude that the increased divergence of tissue-specific genes is, at least in part, attributable to positive selection. A similar pattern emerges when assessing allele-specific chromatin accessibility (ASCA) as a measure of divergence of cis-regulatory elements (CREs) in the same cell lines.

By correlating these two measures, the authors identify 95 CRE-gene pairs where tissue-specific ASE aligns with tissue-specific ASCA. Among these pairs, the authors select two genes of interest for further investigation. Notably, the authors employ an intriguing machine-learning approach in which they compare the inferred chromatin state of the human sequence with that of the chimpanzee sequence to pinpoint putatively causal variants.

Overall, this study delves into the examination of gene expression and chromatin accessibility within hybrid cell lines, showcasing how this data can be leveraged to identify potential causal sequence differences underlying between-species expression changes.

I have three major concerns regarding this study:

1. The only evidence that the cells are indeed differentiated in the right direction is the expression of one prominent marker gene per cell type. Especially for the comparison of conservation between the differentiated cell types, it would be beneficial to describe the cell type diversity and the differentiation success in more detail.

2. Check for a potential confounding effect of sequence similarity on the power to detect ASE or ASCA.

3. In the last part the authors showcase 2 examples for which the log2 fold changes in chromatin state scores as inferred by the machine learning model Sei are used. This is an interesting and creative approach, however, more sanity checks on this application are necessary.

Reviewer #1 (Public Review):

Overall, I quite enjoyed reading the manuscript and found it very well-structured and organized. I congratulate the authors for building this nice research. I do have a few major points to raise, but probably they would not affect the general message of the manuscript.

I was confused about how IUCN data were used. The IUCN predictors are not mentioned in the model equations presented in the manuscript, but their effect size is reported in Figure 2. In the manuscript Methods, it is said that IUCN data was classified into 3 categories. I believe there was a mix of mechanisms in measuring it this way since at least two processes might be underlying IUCN data. First, one can inspect whether there is an effect on "scientific/societal interest" for assessed vs non-assessed species. This would not have any relationship with the assessed status itself. Assessed species are any with LC, NT, VU, EN, CR, EW, EX statuses, whereas non-assessed species might include DD and NE. Second, one may observe an effect of threat status itself, with threatened species being more researched than non-threatened species, this would only be possible for assessed species, although there are methods out there to impute missing statuses. By inspecting Figure 2, I got the feeling that only the second option was explored, but this would need to be confirmed.

In Figure 2, I was confused about the presence of three categories of domain. In the text, it states that four categories have been used. I believe these domains are non-mutually exclusive, that's why there is a fourth category. Would it not be better to assess the influence of domain through three dummy variables (terrestrial, marine, freshwater), where multiple presences (1's) would indicate the "multiple" category?

At present, I felt that the spatial components of your data were unexplored. Since you have centroids representing species distribution, it could be interesting to explore the presence of the species within protected areas or biodiversity hotspots. That might be something triggering at least scientific interest. Also, one can derive information about the major habitat of species occurrence (either using IUCN Major Habitat classification) or extracting overlap of species centroids with WWF biomes (e.g., simplified to just forested vs non-forested habitats; https://ecoregions.appspot.com/). Another point very common to research exploring biodiversity shortfalls is the proximity to research institutions (https://doi.org/10.1111/2041-210X.13152). And since societal interest is also being explored, what about the proximity to major cities (doi:10.1038/nature25181). Finally, other metrics derived from species centroids could inform "tropicality", if the species is tropical or not. Most often, the tropics species are neglected in comparison with those occurring in temperate regions.

I was also thinking about the influence of time on the models. Species described long ago are often more known to people and scientists and had more "time" to be researched. Although metrics of societal interest were restricted to the last decade here, that does not necessarily mean that peoples' interest is not affected by their accumulated experiences. Similar reasoning applies to scientific interests, which have a lengthier time frame (~80 years). That said, the year of description or time since description could be added to capture some metric of time.

Model residuals could be checked for phylogenetic or spatial autocorrelation. I am aware there is no phylogenetic tree used, but the hierarchical taxonomy could be used (Phylum / Class / Order / Family / Genus) as a proxy for phylogenetic relationship. Concerning the spatial autocorrelation, one could check whether model residuals and their respective coordinate centroids of each species range. It is stated that GLMM has been used to avoid these non-independence issues, but it would be interesting to check whether residuals remained free of them.

A last point, it would be interesting to provide some sort of inset plots, such as barplots or donut plots (within the current plots), showing the proportion of species with respect to major clades and biogeographical regions.

Reviewer #2 (Public Review):

Using standard and widely used tools, the authors revealed the factors (cultural, phenotypic, phylogenetic, etc.) shaping societal and scientific interest in natural species around the globe. The strength of this manuscript (and the authors') lies in its command of the available literature, database and variable management and analysis, and its solid discussion. The authors thus achieved a manuscript that was pleasant to read.

While I agree that doing a global study requires losing details of local patterns, maybe this is exactly the biggest shortcoming of the manuscript, oblivious to how different cultures (compare USA to PNG, for example) are reflected in these global patterns.

Related to this previous point, my only other comment is about using English as a reference of societal interest (i.e., the presence of a common name in English). While English may be widespread in Academia, it is still not that common in other societal circles, especially those not using Wikipedia for lack of internet access.

Reviewer #2 (Public Review):

In this paper, the authors presented a compelling rationale for investigating the role of UBCs in prolonging and diversifying signals. Based on the two types of UBCs known as ON and OFF UBC subtypes, they have highlighted the existing gaps in understanding UBCs connectivity and the need to investigate whether UBCs target UBCs of the same subtype, different subtypes, or both. The importance of this knowledge is for understanding how sensory signals are extended and diversified in the granule cell layer.

The authors designed very interesting approaches to study UBCs connectivity by utilizing transgenic mice expressing GFP and RFP in UBCs, Brainbow approach, immunohistochemical and electrophysiological analysis, and computational models to understand how the feed-forward circuits of interconnected UBCs transform their inputs.

This study provided evidence for the existence of distinct ON and OFF UBC subtypes based on their electrophysiological properties, anatomical characteristics, and expression patterns of mGluR1 and calretinin in the cerebellum. The findings support the classification of GRP UBCs as ON UBCs and P079 UBCs as OFF UBCs and suggest the presence of synaptic connections between the ON and OFF UBC subtypes. In addition, they found that GRP and P079 UBCs form parallel and convergent pathways and have different membrane capacitance and excitability. Furthermore, they showed that UBCs of the same subtype provide input to one another and modify the input to granule cells, which could provide a circuit mechanism to diversify and extend the pattern of spiking produced by mossy fiber input. Accordingly, they suggested that these transformations could provide a circuit mechanism for maintaining a sensory representation of movement for seconds.

Overall, the article is well written in a sound detailed format, very interesting with excellent discovery and suggested model, however, I have some comments/suggestions that may help to improve this manuscript:

• The discovery of UBCs innervating each other and their own subtypes, suggesting the presence of feed-forward networks in the cerebellum, is an incredibly fascinating and exciting finding followed by an intriguing model by authors. However, it is worth considering an alternative model as well. I acknowledge that visualizing such interactions using current tools and methods can be challenging ("The approaches used here were not able to determine the existence of networks of more than 2 UBCs connected one after the other. If present, 3 or more UBCs in series could extend and transform the input in even more dramatic ways. The temporal diversity that UBC circuits generate may underlie the flexibility of the cerebellum to coordinate movements over a broad range of behaviors."). Therefore, if this is the case in which more than 2 UBCs connected one after the other, then an alternative model PERHAPS resembles the basal nuclei, with its direct and indirect circuits, can be considered (maybe a type of circular model). The basal nuclei circuits are also regulated by modulators such as D1 dopamine receptors in the direct pathway, causing depolarization, and D2 dopamine receptors in the indirect pathway, resulting in hyperpolarization upon dopamine activation. This approach could involve using computational models to gain insight into potential alternatives within this pathway (may be a future direction).

• GRP UBCs are more densely distributed in lobes VI-IX, while P079 UBCs are more densely distributed in the dorsal leaflet of lobe X in sagittal sections. While the cerebellum is well known for its characteristic stripy pattern, are UBC distributions the same in coronal/transverse section?

• The extension of the axons from both subtypes of UBCs show they are long enough to pass several UBCs and even projections are directed toward the white matter (e.g. Fig 9A), suggesting targeting the UBCs or granule cells in other lobules. Is it suggesting UBCs connectivity between different lobules (perhaps longitudinal connectivity)? Is there any observation or information in coronal/transverse section to visualize mediolateral connectivity?

• The limitation in identifying networks involving more than two sequentially connected UBCs was briefly noted. I suggest including a paragraph describing limitations and discussing the implications of the findings would enhance the overall impact of the research and broaden our understanding of cerebellar function.

• It is a pity that there is no clear conclusion to the discussion of this very interesting study. I suggest providing the key points as a conclusion.

• Please make the correction in Figure 2A by relabeling it as IXa, IXb, and IXc to correct the typographical error.

• I recommend rotating Figure 7A to align its orientation with the other figures for consistency.

Reviewer #1 (Public Review):

The manuscript by Hariani et al. presents experiments designed to improve our understanding of the connectivity and computational role of Unipolar Brush Cells (UBCs) within the cerebellar cortex, primarily lobes IX and X. The authors develop and cross several genetic lines of mice that express distinct fluorophores in subsets of UBCs, combined with immunocytochemistry that also distinguishes subtypes of UBCs, and they use confocal microscopy and electrophysiology to characterize the electrical and synaptic properties of subsets of so-labelled cells, and their synaptic connectivity within the cerebellar cortex. The authors then generate a computer model to test the possible computational functions of such interconnected UBCs.

Using these approaches, the authors report that:

1) GRP-driven TDtomato is expressed exclusively in a subset (20%) of ON-UBCs, defined electrophysiologically (excited by mossy fiber afferent stimulation via activation of UBC AMPA and mGluR1 receptors) and immunocytochemically by their expression of mGluR1.

2) UBCs ID'd/tagged by mCitrine expression in Brainbow mouse line P079 are expressed in a similar minority subset of OFF-UBCs defined electrophysiologically (inhibited by mossy fiber afferent stimulation via activation of UBC mGluR2 receptors) and immunocytochemically by their expression of Calretinin. However, such mCitrine expression was also detected in some mGluR1 positive UBCs, which may not have shown up electrophysiologically because of the weaker fluorophore expression without antibody amplification.

3) Confocal analysis of crossed lines of mice (GRP X P079) stained with antibodies to mGluR1 and calretinin documented the existence of all possible permutations of interconnectivity between cells (ON-ON, ON-OFF, OFF-OFF, OFF-ON), but their overall abundance was low, and neither their absolute nor relative abundance was quantified.

4) A computational model (NEURON ) indicated that the presence of an intermediary UBC (in a polysynaptic circuit from MF to UBC to UBC) could prolong bursts (MF-ON-ON), prolong pauses (MF-ON-OFF), cause a delayed burst (MF-OFF-OFF), cause a delayed pause (MF-OFF-ON) relative to solely MF to UBC synapses which would simply exhibit long bursts (MF-ON) or long pauses (MF-OFF).

The authors thus conclude that the pattern of interconnected UBCs provides an extended and more nuanced pattern of firing within the cerebellar cortex that could mediate longer-lasting sensorimotor responses.

The cerebellum's long-known role in motor skills and reflexes, and associated disorders, combined with our nascent understanding of its role in cognitive, emotional, and appetitive processing, makes understanding its circuitry and processing functions of broad interest to the neuroscience and biomedical community. The focus on UBCs, which are largely restricted to vestibular lobules of the cerebellum reduces the breadth of likely interest somewhat. The overall design of specific experiments is rigorous and the use of fluorophore expressing mouse lines is creative. The data that is presented and the writing are clear. However, the overall experimental design has issues that reduce overall interpretation (please see specific issues for details), which combined with a lack of thorough analysis of the experimental outcomes severely undermines the value of the NEURON model results and the advance in our understanding of cerebellar processing in situ (again, please see specific issues for details).

Specific issues:<br /> 1) All data gathered with inhibition blocked. All of the UBC response data (Fig. 1) was gathered in the presence of GABAAR and Glycine R blockers. While such an approach is appropriate generally for isolating glutamatergic synaptic currents, and specifically for examining and characterizing monosynaptic responses to single stimuli, it becomes problematic in the context of assaying synaptic and action potential response durations for long-lasting responses, and in particular for trains of stimuli, when feed-forward and feed-back inhibition modulates responses to afferent stimulation. That is, even for single MF stimuli, given the >500ms duration of UBC synaptic currents, there is plenty of time for feedback inhibition from Golgi cells (or feedforward, from MF to Golgi cell excitation) to interrupt AP firing driven by the direct glutamatergic synaptic excitation. This issue is compounded further for all of the experiments examining trains of MF stimuli. Beyond the impact of feedback inhibition on the AP firing of any given UBC, it would also obviously reduce/alter/interrupt that UBC's synaptic drive of downstream UBCs. This issue fundamentally undermines our ability to interpret the simulation data of Vm and AP firing of both the modeled intermediate and downstream UBC, in terms of applying it to possible cerebellar cortical processing in situ.

2) No consideration for the involvement of polysynaptic UBCs driving UBC responses to MF stimulation in electrophysiology experiments. Given the established existence (in this manuscript and Dino et al. 2000 Neurosci, Dino et al. 2000 ProgBrainRes, Nunzi and Mugnaini 2000 JCompNeurol, Nunzi et al. 2001 JCompNeurol) of polysynaptic connections from MFs to UBCs to UBCs, the MF evoked UBC responses established in this manuscript, especially responses to trains of stimuli could be mediated by direct MF inputs, or to polysynaptic UBC inputs, or possibly both (to my awareness not established either way). Thus the response durations could already include extension of duration by polysynaptic inputs, and so would overestimate the duration of monosynaptic inputs, and thus polysynaptic amplification/modulation, observed in the NEURON model.

3) Lack of quantification of subtypes of UBC interconnectivity. Given that it is already established that UBCs synapse onto other UBCs (see refs above), the main potential advance of this manuscript in terms of connectivity is the establishment and quantification of ON-ON, ON-OFF, OFF-ON, and OFF-OFF subtypes of UBC interconnections. But, the authors only establish that each type exists, showing specific examples, but no quantification of the absolute or relative density was provided, and the authors' unquantified wording explicitly or implicitly states that they are not common. This lack of quantification and likely small number makes it difficult to know how important or what impact such synapses have on cerebellar processing, in the model and in situ.

4) Lack of critical parameters in NEURON model.<br /> A) The model uses # of molecules of glutamate released as the presumed quantal content, and this factor is constant. However, no consideration of changes in # of vesicles released from single versus trains of APs from MFs or UBCs is included. At most simple synapses, two sequential APs alters release probability, either up or down, and release probability changes dynamically with trains of APs. It is therefore reasonable to imagine UBC axon release probability is at least as complicated, and given the large surface area of contact between two UBCs, the number of vesicles released for any given AP is also likely more complex.<br /> B) the model does not include desensitization of AMPA receptors, which in the case of UBCs can paradoxically reduce response magnitude as vesicle release and consequent glutamate concentration in the cleft increases (Linney et al. 1997 JNeurophysiol, Lu et al. 2017 Neuron, Balmer et al. 2021 eLIFE), as would occur with trains of stimuli at MF to ON-UBCs.

5) Lack of quantification of various electrophysiological responses. UBCs are defined (ON or OFF) based on inward or outward synaptic response, but no information is provided about the range of the key parameter of duration across cells, which seems most critical to the current considerations. There is a similar lack of quantification across cells of AP duration in response to stimulation or current injections, or during baseline. The latter lack is particularly problematic because, in agreement with previous publications, the raw data in Fig. 1 shows ON UBCs as quiescent until MF stimulation and OFF UBCs firing spontaneously until MF stimulation, but, for example, at least one ON UBC in the NEURON model is firing spontaneously until synaptically activated by an OFF UBC (Fig. 11A), and an OFF UBC is silent until stimulated by a presynaptic OFF UBC (Fig. 11C). This may be expected/explainable theoretically, but then such cells should be observed in the raw data.

Reviewer #1 (Public Review):

This manuscript presents SAVEMONEY, a computational tool designed to enhance the utilization of Oxford Nanopore Technologies (ONT) long-read sequencing for the design and analysis of plasmid sequencing experiments. In the past few years, with the improvement in both sequencing length and accuracy, ONT sequencing is being rapidly extended to almost all omics analyses which are dominated by short-read sequencing (e.g., Illumina). However, relatively higher sequencing errors of long-read sequencing techniques including PacBio and ONT is still a major obstacle for plasmid/clone-based sequencing service that aims to achieve single base/nucleotide accuracy. This work provides a guideline for sequencing multiple plasmids together using the same ONT run without molecular barcoding, followed by data deconvolution. The whole algorithm framework is well-designed, and some real data and simulation data are utilized to support the conclusions. The tool SAVEMONEY is proposed to target users who have their own ONT sequencers and perform library preparation and sequencing by themselves, rather than relying on commercial services. As we know and discussed by the authors, in the real world, to ensure accuracy, the researchers will routinely pick up multiple colonies in the same plasmid construction and submit for Sanger sequencing. However, SAVEMONEY is not able to support the simultaneous analysis of multiple colonies in the same run, as compared to the barcoding-based approaches. This is a major limitation in the significance of this work. Encouraging computational efforts in ONT data debarcoding for mixed-plasmid or even single-cell sequencing would be more valuable in the field.

1. To provide more comprehensive information for users who care about the cost, the Introduction section should include a cost comparison between Sanger and ONT, with more details, such as different ONT platforms (MinION, PromethION, FlongIe), chemistries (flow cells) and kits. This additional information will be more helpful and informative for the users who have their own sequencers and are the target audience for SAVEMONEY.

2. In "Overview of the algorithm" (Pages 3-4) under the Results section, instead of stating "However, coverage varies from ~100-1000 and is difficult to predict because each nanopore flow cell has different properties.", it will be beneficial to provide more detailed information, such as sequencing length, yield/read count per flow cell of different platforms. This information will assist users in designing their own experiments effectively.

3. While this study optimized and evaluated the tool using a total of 14 plasmids, it may not provide sufficient power to represent the diversity of the plasmid world. Consideration should be given to expanding the dataset to include a broader range of plasmids in future studies to enhance the robustness and generalizability of the tool.

4. If applicable and feasible, including a comparison or benchmark of SAVEMONEY against other similar tools would further strengthen the manuscript. This comparison would allow users to evaluate the advantages and disadvantages of different tools for their specific needs.

5. The importance of pre-filtering raw sequencing reads should be emphasized as noisy reads can significantly impact the overall performance of the tool. It is essential to clarify whether any pre-filtering steps were performed in this study, such as filtering based on quality scores, read length, or other relevant factors.

6. The statement regarding the number of required reads per plasmid (20-30) and the maximum number of plasmids (up to six) that can be mixed in a single run may become outdated due to the rapid advancements in ONT technology. In the Discussion section, instead of assuming specific numbers, it would be more beneficial to provide information based on the current state of ONT sequencing, such as the number of reads per MinION flow cell that can be produced.

Reviewer #2 (Public Review):

The authors developed an algorithm that allows for deconvoluting of plasmid sequences from a mixture of plasmids that have been sequenced by nanopore long read technology. As library preparations and barcoding of individual samples increase sequencing costs, the algorithm bypasses this need and thus decreases time on sample prep and sequencing costs. In the first step, the tool assesses which of the plasmid constructions can be mixed in a single library preparation by calculating a distance matrix between the reference plasmid and the constructions producing sequence clusters. The user is given groups of plasmids, from different clusters, to be pooled together for sequencing. After sequencing, the algorithm deconvolutes the reads by classifying them based on alignments to the reference sequence. A Bayesian analysis approach is used to obtain a consensus sequence and quality scores.

Strengths<br /> The authors exploit one of the main advantages of long-read sequencing which is to accurately resolve regions of high complexity, as regularly found in plasmids, and developed a tool that can validate plasmid constructions by reducing sequencing costs. Multiple plasmids (up to six) can be analyzed simultaneously in a single library without the need for sample barcoding, also reducing sample preparation time. Although inserts must be different, just 2 bases difference would be enough for a correct assignation. It maximizes cost-efficiency for projects that require large amounts of plasmid constructions and high-throughput validation.

Weaknesses<br /> The method proposed by the authors requires prior knowledge of plasmid sequences (i.e., blueprints or plasmid reference) and is not suitable for small experiments. The plasmid inserts or backbones must be different e.g., multiple colonies from the same plasmid construction effort cannot be submitted together.

Reviewer #1 (Public Review):

This study is one of several around the world to investigate how urban wildlife responded to changes in human activity during the lockdowns associated with the COVID-19 pandemic. Unlike several other studies on the topic that used observational data from citizen science programs, this project relied on passive acoustic monitoring to record bird vocalizations during and after stringent lockdown periods in an urban environment. The authors focused on three species that differ in their level of adaptation to human presence, providing an ecologically relevant comparison that highlights the importance of micro-habitats for species living in close proximity to humans.

Strengths:

The element that most sets this study apart from previous studies examining responses to COVID-19 lockdowns is the use of passive acoustic monitoring. As the authors describe, this method offers several advantages over other methods (though, it does come with some limitations on what questions can be addressed). Perhaps the most relevant advantage is that it offers the ability to concurrently measure anthropogenic noise in the environment, which is one of the most likely mechanisms for human activity changes effects on wildlife. To my knowledge, only one other study (Derryberry et al. Science. 2020) has used recordings of vocalizations to examine the influence of COVID-19 lockdowns on birds. (Note, while these authors do reference Derryberry et al., I thought that there could have been much more direct comparison between the results of the two approaches).

It was encouraging to see a study that focused on local-scale impacts of lockdowns, with methods that could investigate effects within microhabitats. Logistics prevented many other projects from operating at such fine scales. These data also came from a country/municipality that had very defined lockdown periods known with certainty to the day (as opposed to a gradual shift in voluntary human activity, as occurred in much of North America), making the results from this study particularly useful for the examination of rapid changes in bird behavior.

Weaknesses:

One important drawback of the approach, which potentially calls into question the authors' conclusions, is that the acoustic sampling only occurred during the pandemic: for several lockdown periods and then for a period of 10 days immediately after the end of the final lockdown period in May of 2020. Several relevant things changed from March to May of 2020, most notably the shift from spring to summer, and the accompanying shift into and through the breeding season (differing for each of the three focal species). Although the statistical methods included an attempt to address this, neither the inclusion of the "count down" variable nor the temperature variable could account for any non-linear effects of breeding phenology on vocal activity. I found the reliance on temperature particularly troubling, because despite the authors' claims that it was "a good proxy of seasonality", an examination of the temperature data revealed a considerable non-linear pattern across much of the study duration. In addition, using a period immediately after the lockdowns as a "no-lockdown" control meant that any lingering or delayed effects of human activity changes in the preceding two months could still have been relevant (not to mention the fact that despite the end of an official lockdown, the pandemic still had dramatic effects on human activity during late May 2020).

Another weakness of the current version of the manuscript is the use of a supposed "contradiction" in the existing literature to create the context for the present study. Although the various studies cited do have many differences in their results, those other papers lay out many nuanced hypotheses for those differences. Almost none of the studies cited in this manuscript actually reported blanket increases or decreases in urban birds, as suggested here, and each of those papers includes examples of species that showed different responses. To suggest that they are on opposite sides of a supposed dichotomy is a misrepresentation. Many of those other studies also included a larger number of different species, whereas this study focused on three. Finally, this study was completed at a much finer spatial scale than most others and was examining micro-habitat differences rather than patterns apparent across landscapes. I believe that highlighting differences in scale to explain nuanced differences among studies is a much better approach that more accurately adds to the body of literature.

Reviewer #2 (Public Review):

In this study, the authors tried to gauge the effect of human activity on three species, (1) the Hooded grow, an urban exploiter, (2) the Rose ring parakeet, an invasive, alien species that has adapted to exploit human resources, and (3) the Graceful Prinia, an urban adapter, which is relatively shy of humans. A goal of the study was to increase awareness of the importance of urban parks.

Strengths:<br /> Strengths of the study include the fact that it was conducted at 17 different sites, including parks, roads and residential areas, and included three species with different habitat preferences. Each species produced relatively loud and repeatable vocalizations. To avoid the effect of seasonal changes, sounds were sampled within a 10 day period of the lockdown as well as post-lockdown. The analysis included a comparison of the number of sound files, binary values indicating emission of a common syllable, and also the total number of syllables emitted as a measurement of bird activity. Ambient temperatures and sound levels of human activity were also recorded. All of these factors speak to the comprehensive approach and analysis adopted in this study. The results are based on a rigorous statistical analysis, ruling out effects of various extraneous parameters.

Weaknesses:<br /> The explanation of methods can be improved. For example, it is not clear if data were low-pass filtered before resampling to avoid aliasing.<br /> It is quite possible that birds move into the trees and further from the recorders with human activity. Since sound level decreases by the square of the distance of the source from the recorders, this could significantly affect the data. As indicated in the Discussion, this is a significant parameter that could not be controlled.<br /> In interpreting the data, the authors mention the effect of human activity on bird vocalizations in the context of inter-species predator-prey interactions; however, the presence of humans could also modify intraspecies interactions by acting as triggers for communication of warning and alarm, and/or food calls (as may sometimes be the case) to conspecifics. Along the same lines, it is important to have a better understanding of the behavioral significance of the syllables used to monitor animal activity in the present study.<br /> Another potential effect that may influence the results but is difficult to study, relates to the examination of vocalizations near to the ambient noise level. This is the bandwidth of sound levels where most significant changes may occur, for example, due to the Lombard effect demonstrated in bird and bat species. However, as indicated, these are also more difficult to track and quantify. Moreover, human generated noise, other than speech, may be a more relevant factor in influencing acoustic activity of different bird species. Speech, per se, similar to the vocalizations of many other species, may simply enrich the acoustic environment so that the effects observed in the present study may be transient without significant long-term consequences.

In general, the authors achieved their aim of illustrating the complexity of the effect of human activity on animal behavior. At the same time, their study also made it clear that estimating such effects is not simple given the dynamics of animal behavior. For example, seasonality, temperature changes, animal migration and movement, as well as interspecies interactions, such as related to predator-prey behavior, and inter/intra-species competition in other respects can all play into site-specific changes in the vocal activity of a particular species.

Reviewer #1 (Public Review):

The manuscript is very-well written. Although the study is well-conducted the authors should be more convincing on how bacteria residing in tissues do not induce death. The association with IL-10 cytokine production appears weak and more experiments are needed to make it more robust.

Reviewer #2 (Public Review):

Iske et al. provide experimental data that NAD+ lessens disease severity in bacterial sepsis without impacting on the host pathogen load. They show that in macrophages, NAD+ prevents Il1b secretion potentially mediated by Caspase11.

While the in vivo and in vitro data is interesting and hints towards a crucial role of NAD+ to promote metabolic adaptation in sepsis, the manuscript has shortcomings and would profit from several changes and additional experiments that support the claims.

Conceptually, the definition of sepsis is outdated. Sepsis is not SIRS, as in sepsis-2. Sepsis-3 defines sepsis as infection-associated organ dysfunction. This concept needs to be taken into account for the introduction and when describing the potential effects of NAD+ in sepsis. Also, LPS application cannot be considered a sepsis model, since it only recapitulates the consequence of TLR-4 activation. It is a model of endotoxemia. Also, the LPS data does not allow to draw conclusions about bacterial clearance (L135).

The authors state that protective effects by NAD were independent of the host pathogen load. This clearly indicates that NAD confers protection via enhancing a disease tolerance mechanism, potentially via reducing immunopathology. This aspect is not considered by the authors. The authors should incorporate the concept of disease tolerance in their work, cite the relevant literature on the topic and discuss it their findings in light of the published evidence for metabolic alteration sand adaptations in sepsis.

For the in vitro data, the manuscript would benefit from additional experiments using in vitro infection models.

In the merge manuscript, the authors provide two different versions of the figures. In one, bar plots are shown without individual data and in the other with scatter blots. All bar plots need to be provided as scatter plots showing individual values.

The authors should show further serology data for kidney and liver failure etc. as well as further cytokine data such as IL-6 and TNF to better characterize their models.

Careful revision of the entire manuscript, the figure legends and figures is required. The figure legend should not repeat the methods and materials section. The nomenclature for mouse protein and genes needs to be thoroughly revised.

L350. The authors write that they dissect the capacity of NAD+ to dampen auto- and alloimmunity. In this work, no data that supports this statement is shown and experiments with autoantigens or alloantigens are not performed.

L163 The authors describe pyroptosis but in the figure legend call it apoptosis. Specific markers for each cell death should be measured and determined which cell death mechanisms is involved.

Animal data comes from an infection model and LPS application. The RNAseq data is obtained from cells primed with Pam3CSK4 and subsequently subjected to LPS. It is unclear how the cell culture model reflects the animal model. As such the link between IFN signaling and the bacterial infection/LPS model are not convincing and need to be further elaborated.

Figure 5: It is unclear how many independent survival experiments were done, how many mice per group were used and whether the difference between groups was statistical significant. This information should be added.

Further experiments with primary cells from Il10 k.o. and Caspase11 k.o. animals should be provided that support the findings in macrophages.

Reviewer #1 (Public Review):

The goal of this study is to understand the allosteric mechanism of overall activity regulation in an anaerobic ribonucleotide reductase (RNR) that contains an ATP-cone domain. Through cryo-EM structural analysis of various nucleotide-bound states of the RNR, the mechanism of dATP inhibition is found to involve order-disorder transitions in the active site. These effects appear to prevent substrate binding and a radical transfer needed to initiate the reaction.

Strengths of the manuscript include the comprehensive nature of the work - including numerous structures of different forms of the RNR and detailed characterization of enzyme activity to establish the parameters of dATP inhibition. The manuscript could be improved, however, by performing additional experiments to establish that the mechanism of inhibition can be observed in other contexts and it is not an artifact of the structural approach. Additionally, some of the presentations of biochemical data could be improved to comply with standard best practices.

The work is impactful because it reports initial observations about a potentially new mode of allosteric inhibition in this enzyme class. It also sets the stage for future work to understand the molecular basis for this phenomenon in more detail.

General comments:

1) It would be ideal to perform an additional experiment of some type to confirm the order-disorder phenomena observed in the cryo-EM structures to rule out the possibility that it is an artifact of the structure determination approach. Circular dichroism might be a possibility?

2) Does the disordering phenomenon of one subunit in the ATP-bound structures have any significance - could it be related to half-of-sites activity? Does this RNR exhibit half-of-sites activity?

3) Does the disordering of the GRD with dATP bound have any long-term impact on the stability of the Gly radical? I realize that the authors tested the ability to form the Gly radical in the presence of dATP in Fig. 4 of the manuscript. But it looks like they only analyzed the samples after 20 min of incubation. Were longer time points analyzed?

4) Did the authors establish whether the effect of dATP inhibition on substrate binding is reversible? If dATP is removed, can substrates rebind?

5) In some figures (Fig. 6e, for example), the cryo-EM density map for the nucleotide component of the model is not continuous over the entire molecule. Can the authors comment on the significance of this phenomenon? Were the ligands validated in any way to ensure that the assignments were made correctly?

Reviewer #2 (Public Review):

This manuscript describes the functional and structural characterization of an anaerobic (Class III) ribonucleotide reductase (RNR) with an ATP cone domain from Prevotella copri (PcNrdD). Most significantly, the cryo-EM structural characterization revealed the presence of a flap domain that connects the ATP cone domain and the active site and provides structural insights about how nucleotides and deoxynucleotides bind to this enzyme. The authors also demonstrated the catalytic functions and the oligomeric states. However, many of the biochemical characterizations are incomplete, and it is difficult to make mechanistic conclusions from the reported structures. The reported nucleotide-binding constants may not be accurate because of the design of the assays, which complicates the interpretation of the effects of ATP and dATP on PcNrdD oligomeric states. Importantly, statistical information was missing in most of the biochemical data. Also, while the authors concluded that the dATP binding makes the GRD flexible based on the absence of cryo-EM density for GRD in the dATP-bound PcNrdD, no other supports were provided. There was also a concern about the relevance of the proposed GRD flexibility and the stability of Gly radical. Overall, the manuscript provides structural insights about Class III RNR with ATP cone domain and how it binds ATP and dATP allosteric effectors. However, ambiguity remains about the molecular mechanism by which the dATP binding to the ATP cone domain inhibits the Class III RNR activity.

Strengths:<br /> 1. The manuscript reports the first near-atomic resolution of the structures of Class III RNR with ATP domain in complex with ATP and dATP. These structures revealed the NxN flap domain proposed to form an interaction network between the substrate, the linker to the ATP cone domain, the GRD, and loop 2 important for substrate specificity. The structures also provided insights into how ATP and dATP bind to the ATP cone domain of Class III RNR. Also, the structures suggested that the ATP cone domain is directly involved in the tetramer formation by forming an interaction with the core domain in the presence of dATP. These observations serve as an important basis for future study on the mechanism of Allosteric regulation of Class III RNR.

2. The authors used a wide range of methodologies including activity assays, nucleotide binding assays, oligomeric state determination, and cryo-EM structural characterization, which were impressive and necessary to understand the complex allosteric regulation of RNR.

3. The activity assays demonstrated the catalytic function of PcNrdD and its ability to be activated by ATP and low-concentration dATP and inhibited by high-concentration dATP.

4. ITC and MST were used to show the ability of PcNrdD to bind NTP and dATP.

5. GEMMA was used successfully to determine the oligomeric state of PcNrdD, which suggested that PcNrdD exists in dimeric and tetrameric forms, whose ratio is affected by ATP and/or dATP.

Weaknesses:<br /> 1. Activity assays.<br /> The activity assays were performed under conditions that may not represent the nucleotide reduction activity. The authors initiated the Gly radical formation and nucleotide reduction simultaneously. The authors also showed that the amount of Gly radical formation was different in the presence of ATP vs dATP. Therefore, it is possible that the observed Vmax is affected by the amount of Gly radical. In fact, some of the data fit poorly into the kinetic model. Also, the number of biological and technical replicates was not described, and no statistical information was provided for the curve fitting.

2. Binding assays.<br /> The interpretation of the binding assays is complicated by the fact that dATP binds both a- and s-sites and ATP binds a- and active sites. dATP may also bind the active site as the product. It is unknown if ATP binds s-site in PcNrdD. Despite this complexity, the binding assays were performed under the condition that all the binding sites were available. Therefore, it is not clear which event these assays are reporting.

3. Oligomeric states.<br /> Due to the ambiguity in the kinetic parameters and the binding constants determined above, the effects of ATP and dATP on the oligomeric states are difficult to interpret. The concentrations of ATP used in these experiments (50 and 100 uM) were significantly lower than KL determined by the activity assays (780 uM), while it is close to the Kd values determined by ITC or MST (~25 uM). Since it is unclear what binding events ITC and MST are reporting, the data in Figure 3 does not provide support for the claimed effects of ATP binding. For the effects of dATP, the authors did not observe a significant difference in oligomeric states between 50 or 100 uM dATP alone vs 50 uM dATP and 100 uM CTP. The former condition has dATP ~ 2x higher than the Kd and KL (Figure 1b) and therefore could be considered as "inhibited". On the other hand, NrdD should be fully active under the latter condition. Therefore, these observations show no correlation between the oligomeric state and the catalytic activity.

4. Effects of dATP binding on GRD structure<br /> One of the key conclusions of this manuscript is that dATP binding induces the dissociation of GRD from the active site. However, the structures did not provide an explanation for how the dATP binding affects the conformation of GRD or whether the dissociation of GRD is a direct consequence of dATP binding or it is due to the absence of nucleotide substrate. Also, Gly radical is unlikely to be stable when it is not protected from the bulk solvent. Therefore, it is unlikely that the GRD dissociates from the active site unless the inhibition by dATP is irreversible. Further evidence is needed to support the proposed mechanism of inhibition by dATP.

5. Functional support for the observed structures.<br /> Evidence for connecting structural observations and mechanistic conclusions is largely missing. For example, the authors proposed that the interactions between the ATP cone domain and the core domain are responsible for tetramer formation. However, no biochemical evidence was provided to support this proposal. Similarly, the functional significance of the interaction through the NxN flap domain was not proved by mutagenesis experiments.

Reviewer #3 (Public Review):

The manuscript by Bimai et al describes a structural and functional characterization of an anaerobic ribonucleotide reductase (RNR) enzyme from the human microbe, P. copri. More specifically, the authors aimed to characterize the mechanism by how (d)ATP modulates nucleotide reduction in this anaerobic RNR, using a combination of enzyme kinetics, binding thermodynamics, and cryo-EM structural determination. One of the principal findings of this paper is the ordering of a NxN 'flap' in the presence of ATP that promotes RNR catalysis and the disordering of both this flap and the glycyl radical domain (GRD) when the inhibitory effector, dATP, binds. The latter is correlated with a loss of substrate binding, which is the likely mechanism for dATP inhibition. It is important to note that the GRD is remote (>30 Ang) from the binding site of the dATP molecule, suggesting long-range communication of the structural (dis)ordering. The authors also present evidence for a shift in oligomerization in the presence of dATP. The work does provide evidence for new insights/views into the subtle differences of nucleotide modulation (allostery) of RNR through long-range interactions.

The strengths of the work are the impressive, in-depth structural analysis of the various regulated forms of PcRNR by (d)ATP using cryo-EM. The authors present seven different models in total, with striking differences in oligomerization and (dis)ordering of select structural features, including the GRD that is integral to catalysis. The authors present several, complementary biochemical experiments (ITC, MST, EPR, kinetics) aimed at resolving the binding and regulatory mechanism of the enzyme by various nucleotides. The authors present a good breadth of the literature in which the focus of allosteric regulation of RNRs has been on the aerobic orthologues.

Given the resolution of some of the structures in the remote regions that appear to be of importance, the rigor of the work could have been improved by complementing this experimental studies with molecular dynamics (MD) simulations to reveal the dynamics of the GRD and loops/flaps at the active site. The biochemical data supporting the loss of substrate binding with dATP association is compelling, but the binding studies of the (d)ATP regulatory molecules are not; the authors noted less-than-unity binding stoichiometries for the effectors. Also, the work would benefit from additional support for oligomerization changes using an additional biochemical/biophysical approach.

Overall, the authors have mostly achieved their overall aims of the manuscript. With focused modifications, including additional control experiments, the manuscript should be a welcomed addition to the RNR field.

Reviewer #1 (Public Review):

In this work, the authors have investigated the relationship between Carotenoid pigment depletion in the photosynthesis-related light harvesting complex, the assembly of the prokaryotic reaction center LH complex, and quinone exchange in Roseiflexus castenholzii, a chlorosome-less filamentous anoxygenic phototroph that forms the deepest branch of photosynthetic bacteria. By means of different biochemical and biophysical techniques, including cryo-electron microscopy of the purified RC-LH complexes with or depleted of carotenoids, the authors provide evidence of the structural basis by which Carotenoid assembly regulates the architecture and quinone exchange of bacterial RC-LH 40 complexes. Although most of the experiments described in this manuscript are structural, by analyzing Cryo-MS results, the authors also propose some predictions about the functional roles of proteins/pigments in LH complex, such as the role of the gap in the ring that persists without a canonical subunit X. Together, the results presented are important to understand the evolution and diversity of prokaryotic photosynthetic apparatus.

Reviewer #2 (Public Review):

In this work, Xin et al. describe cryo-EM structures of the native and carotenoid-depleted forms of RC-LH from R. castenholzii, attempting to reveal how differences in the carotenoid composition may result in the structural and functional differences in the RC-LH complex. Previously, the authors obtained the nRC-LH structure at 4.1 angstrom resolution. The current work extends the earlier moderate-resolution to a higher resolution (2.8 angstrom), which allowed them to identify 14 additional carotenoid molecules located at the external positions between adjacent LHs. These external carotenoids, together with bacteriochlorophylls, result in an impenetrable LH ring surrounding the RC, leaving only the LH opening shaped by subunit X and c-TM as the pathway for quinone exchange. They further solve the dRC-LH structure at 3.1 angstrom resolution, and find that while nRC-LH binds 15 internal and 14 external carotenoids, dRC-LH contains only five internal carotenoids, as well as a highly mobile c-TM, but no subunit X. Comparing the two types of complexes at both structural and biochemical levels, they show that these structural changes may result in the accelerated quinone exchange in dRC-LH than that in nRC-LH.<br /> The structural data in this work are solid. The cryo-EM structures are well discussed and presented by the authors to highlight the structural features that may arise from carotenoid depletion. The authors also measured the oxidation rate of the auracyanin to characterize the quinone exchange rate. The work carried out by the authors is useful in the understanding of the regulatory role of carotenoids in complex assembly and quinone exchange.

Reviewer #3 (Public Review):

Light harvesting (LH) associated with photosynthesis, photoprotection, and the formation of useful pigment-protein complexes are all major functions of carotenoid (Car) pigments. However, the connections between quinone exchange, prokaryotic reaction center (RC)-LH complex formation, and Car depletion in the LH are not entirely understood. This article examined the native RC-LH (nRC-LH) and Car-depleted RC-LH (dRC-LH) complexes in the filamentous anoxygenic phototroph Roseiflexus castenholzii. The authors show with a high degree of detail using crystallography and Cryo-EM complemented with biophysical techniques important results of a new conformation of a LH. They could assigned the amino acid sequences of subunit X and two hypothetical proteins, Y and Z, that formed the quinone channel and maintained the RC-LH connections. This study identifies a new architectural basis for the regulation of bacterial RC-LH complex and quinone exchange by Cars assembly, which is distinct from the well known purple bacteria. These findings represent a significant advancement of diversity and development of bacterial photosynthetic machinery.

Reviewer #1 (Public Review):

A modelling study was conducted to estimate how disruption of a school-based HPV vaccination program due to COVID-19 restrictive measures might affect lifetime HPV-related cancers in women and men in Australia. The authors used the Policy 1-Cervix model, which has been validated and widely used for modelling and evaluation of interventions to prevent HPV- related disease. The study shows that a large part of the negative effect of disrupting the vaccination program (in terms of HPV-related cancers) can be overcome by a catch-up campaign, if this is undertaken rapidly. Delays in the catch-up campaign or no catch-up lead, according to the model, to a significant increase in the number of cases, of which a proportion could be prevented by cervical cancer screening, provided that this is carried out for cohorts that receive HPV 9 without alterations.

1. Strengths:<br /> Well-designed modelling study, comparing several scenarios: baseline (no interruption of vaccination), catch-up with two modalities, and no catch-up vaccination, with a comparator (no vaccination at all), aiming to predict the number of HPV-related cancers for the various scenarios. Indeed, the study investigates the potential impact of disruptions, broken down into types of cancers, in both men and women. However, as always in modelling studies, the strength of the findings depends on the appropriateness and completeness of the assumptions used.

2. Weaknesses:<br /> Although the authors claim to have considered sexual behaviour they fail to show how they exactly did this. It is very likely that restrictive measures have had an impact on sexual behaviour (i.e. transmission of HPV), but the authors did not consider this in the model. Furthermore, the baseline scenario uses a higher 2-dose vaccination uptake than the figures they present for 2020, which might have overestimated the impact of HPV vaccination in that year.

Reviewer #2 (Public Review):

This is a modeled analysis of the impact of disruptions in school-based HPV vaccination due to the COVID-19 pandemic. Different catch-up scenarios were considered, ranging from a rapid catch-up period to no catch-up vaccination, and the impact of these on future HPV-related malignancies was approximated. The approach in this study could shed light on strategies for catch-up vaccination due to disruptions caused by the COVID-19 pandemic.

Strengths:<br /> - Using the context of Australia, which has led the world in vaccination, allows us to consider a best-case scenario for the impact of disruptions in a well-running HPV vaccination program with good population coverage.<br /> - The model accounts for multiple factors, including HPV transmission dynamics, mitigation of disease development by screening

Suggested clarifications:<br /> - It could benefit from fleshing out concepts instead of using parentheses, particularly in the abstract.<br /> - There is space to expand on the results presented in Table 1, including an explanation of Affected cohorts 2008 vs Affected cohorts 2008-2009. It may also be useful to explain this analysis in the methods section.<br /> - Given that Australia is a best-case scenario and other countries have not had the same success in HPV vaccination coverage, in the discussion would it be possible to give a comparison of how these three scenarios would look different in a population with school-based vaccination but lower coverage volume, such that readers could understand how much of the success / failures of each of the three catch-up scenarios? It would be particularly helpful for readers who are not familiar with the modeling tool used in this analysis.

Reviewer #1 (Public Review):

Gosh and colleagues report on their multidisciplinary effort to improve cervical cancer screening attendance in the East Boston Neighborhood Health Center (March-August 2021). Specifically, the authors 1) identified using electronic medical records overdue follow-up visits, 2) scheduled screening appointments during regular clinic hours and weekends/evenings, and 3) surveyed patients on their experience. These objectives were clearly defined (although not consistently so throughout the manuscript) and data analyses/presentation were simple and straightforward, appropriate to the study design and methodology used.

Overall, it is unclear to what extent the overdue appointments were backlogs created by the COVID-19 pandemic or due to pre-pandemic factors that could have been exacerbated by the pandemic. In order to contextualize the current study and its findings, an elaboration is needed on whether the pandemic created the delays in cervical cancer screening or simply compounded the problem. For example, the authors report on page 8, lines 196-197 that in 30% of encounters (not clear how many of the 118 reviewed charts were overdue appointments) the healthcare provider did note the overdue appointments. A breakdown of the "time delays" (i.e., beyond x number of months) would also inform the analyses and study implications. In addition, a brief description of the cervical cancer screening program in place would be informative. Table 1 provides an effort versus value summary, however, these constructs are ill-defined, with few inconsistencies with what is reported in the text.

Comments specific to Aim 1:<br /> The methodology is missing information on key elements, mainly relating to the decision-making process of establishing and defining the "validated" patient chart list (1375 overdue patients out of 6126 reviewed charts). A chart of the 1375 approached study population is also warranted (459 patients were screened, 622 could not be reached, and 203 cancelled/missed their appointments, what about the remaining 91 patients). A description of the characteristics of the study population and a comparison of the different groups (screened, not reached, cancelled/missed appointment) along these characteristics are missing.

Comments specific to Aim 2:<br /> About 63% of the 459 scheduled screenings were done during the evening/weekend clinics, which represents a substantial gain and clearly indicates a window of opportunity to increase screening rates by pinpointing the importance of offering a convenient time to women attend screening visits. In general, and as expected, offering additional screening clinics was effective in addressing the backlog of patients, although with significant investment and resources as mentioned by the authors. How significant is significant?

Comments specific to Aim 3:<br /> A more structured and detailed presentation/description of the survey instrument, its administration, response rate, and significance of results are warranted in the manuscript, albeit the joint reporting of this in the appended material.

Reviewer #2 (Public Review):

The purpose of this study is unclear from the introduction. Additionally, the methods are incomplete and did not describe how data was collected and analyzed. The results do not describe the sample. Once these are described more clearly, further comments can be made about what the authors were trying to achieve and the impact of the work on the field.

Reviewer #1 (Public Review):

Tian et al impressively record from two motor areas at once in singing birds to test if a premotor cortical area, LMAN, covaries with activity in a primary one, RA, in a way that would support learning. They find that LMAN activity covaries with RA activity at a lag consistent with driving a premotor bias and, moreover, that this covariation is significantly increased in the specific time window of the song where bias is being most strongly driven. Disruptive microstimulation of LMAN in this window reduced learning-associated bias. Though the main results in this paper are consistent with dominant models of birdsong production and learning going back decades (e.g. Kao et al, 2005; Olveczky et al, 2005; Andalman et al, 2008; Charlesworth et al, 2009; Fee and Goldberg, 2011), these results provide methodologically impressive confirmation that LMAN drives RA activity to drive adaptive bias. It's also meaningful that these covariations were strong enough to be picked up by a pair of randomly targeted LMAN and RA sites. This feature of their dataset is not emphasized by the authors but invites more attention, consideration, and discussion, as detailed below.

(1) Song is complex with many varying acoustic parameters, such as amplitude, entropy, and pitch. It is thought that pitch is controlled by only a subset of the syringeal muscles, and also that there is topography in the LMAN-RA-MN-muscle pathway. Thus, one might expect only a small fraction of neurons/sites in the LMAN-RA pathway to be associated with pitch with enough strength that one would pick it up in single unit recordings from order ~100 syllables. Indeed a past study (Sober et al, ) found that activity in a small fraction of RA neurons was weakly correlated with pitch variation. So it's really surprising that a pitch-contingent learning paradigm produced significant co-variance changes in the LMAN-RA pathway that could be picked up in the present study. Three possible explanations are with consideration. First, one wonders if they were recording specifically from pitch-associated sites. Can the authors please elaborate on what fraction of LMAN and RA recording sites in the present study exhibited significant covariance with pitch? Second, if an LMAN-RA recording site pair does not exhibit a significant correlation with pitch but nonetheless exhibits enhanced co-variation in the pre-target window in a pitch shift paradigm, this would support a different interpretation of the results. For example, it's possible that the extent by which LMAN can drive RA is gated by cholinergic inputs from VP, which might signal predicted uncertainty in the song in the precise moment preceding the target time (e.g. Chen and Goldberg, 202; Chen et al, 2019; Puzerey et al, 2018). No new experiments are required here, but these possibilities (or other considerations of the mechanisms by which LMAN-RA covariance is temporally gated) could, in the discussion or elsewhere, motivate future studies. (For example, if Ach-mediated predicted uncertainty is the key to promoting LMAN-RA covariance, then photoactivation of Ach inputs to RA at a moment in song might increase LMAN drive and, secondly, non-pitch-contingent DAF that does not drive explicitly learning associated bias would also be sufficient to promote temporally precise increases in LMAN-RA covariance. Finally, related to these questions, can the authors please check if their recording sites exhibited correlations with pitch (e.g. as in Sober et al, 2008)?

2. Multiple recording sites in both RA and LMAN provide sensible internal controls for the cross-covariance and its increase in the window before bias production in pitch-shift experiments. Can the authors analyze at LMAN-LMAN co-variance in the same way to test for LMAN-RA co-variance to examine intra-LMAN activity co-flucutations? A negative result would support the specificity of the LMAN-RA covariance but a positive result would indicate that within-LMAN dynamics also exhibit interesting learning-related changes.

Reviewer #2 (Public Review):

In studying the neural control of action generation there is a presumption that different nodes within a connected neural control circuit contribute differentially to the production of a given gesture. In many cases, these circuits also receive inputs that can bias ongoing motor commands to alter output and therefore the motor gesture itself. Showing the specific role that each of the different areas play in motor control and how inputs might bias motor output is challenging. Taking advantage of a precisely controlled error-correction learning task of adult birdsong, Tian et al. perform simultaneous neural recording in both the primary forebrain song motor output nucleus (RA) as well as in an input structure (LMAN) known to be necessary for biasing motor output during such learning tasks. By comparing the activity pattern and timing between recorded activity in both structures, they show that LMAN activity leads RA activity for each of the song syllables but that there is a preferential gain in activity level in LMAN after learning only during the precise time window (10 - 50 msec) associated with the specific syllable that is targeted during the error-correction paradigm. They then follow these recordings with short focal electrical stimulation in LMAN targeted to the precise time window that shows increased gain in the dual recording paradigm. This stimulation is intended to scramble the bias signal and they show that such manipulation, in a temporally specific manner, does indeed eliminate the acoustic bias imposed by LMAN.

The precise combination of dual recording and targeted stimulation, in my opinion, convincingly shows that LMAN provides a temporally precise command that can bias motor output in RA. It is assumed that LMAN inputs onto RA are mapped with some level of functional topography, especially given that RA is thought to have some degree of motor mapping. The more dorsal areas, for example, likely contribute more to respiratory control while the more ventral portion contributes to acoustic control with a possible acoustic motor map within that region. Unfortunately, the spatial precision of the recording electrodes in both RA as well as LMAN is rather coarse and a careful functional spatial mapping of spike timing correlation is not possible. Hopefully in future studies, more precise spatial mapping will provide correlations within these two structures that might be able to target subareas that encode the signal bias for subcomponents of the specific acoustic features that are being targeted in this error-correction learning paradigm.

Reviewer #3 (Public Review):

The present paper uncovers evidence of the coordination of two brain areas involved in a two-step learning process in birdsong plasticity. Indeed, songbirds can modify their song based on an error-correction mechanism that involves a motor bias expressed by a basal ganglia-thalamo-cortical loop. After training (hundreds or a few thousands of renditions), the motor bias necessary to correct vocal errors becomes independent of the BG-thalamo-cortical loop and is transferred into the long-term motor program stored in a primary motor network. Current understanding claims that the output nucleus of the BG-thalamo-cortical loop, LMAN, trains the primary motor networks (in area RA) to drive the learning transfer. However, no clear evidence for such entrainment was available until now. In the present study, the authors elegantly show that correlations in trial-by-trial fluctuations in the premotor activity in LMAN and RA are present spontaneously (in multi-unit electrophysiological recordings) and are increased during a lab-induced plasticity protocol. The change in correlation is specific to the syllable that undergoes plasticity. Moreover, perturbing LMAN activity through low-intensity and spatially broad electrical stimulation of LMAN during the premotor window prevents behavioral adaptation. Altogether, their results convincingly show that the entrainment of RA neural populations by LMAN neurons is present during baseline, strengthened during plasticity in a syllable-specific manner, and necessary for song plasticity.

This study thus provides important validation of the current model for the 2-step learning process underlying song learning and plasticity, where a BG-thalamo-cortical network drive motor bias to correct vocal errors based on a reinforcement learning mechanism, while the song motor engram is updated slowly through the adjustment of song-related activity in the primary motor areas. Beyond the songbird field, these results will be of importance to all studying sensorimotor learning and adaptation, and more broadly the formation of memory through a two-step learning process.

The authors present the context for their hypothesis clearly, state their hypothesis precisely, and conduct a thorough investigation of the posed question. The conclusions are well supported by data.

In particular, the statistical evaluation of the covariance of LMAN and RA activity in the premotor window is adequate and the interpretation of the results is therefore well backed by their analysis. The methods used here to assess covariation between LMAN and RA activity during singing set the ground for future studies looking at the coordination between brain areas during behavior.

Reviewer #1 (Public Review):

In this manuscript, Yang et al. investigated the mechanisms by which a high-sugar diet induces transgenerational changes in sweet sensitivity and feeding behavior. The authors identified an epigenetic mechanism that involves H3K27me3 reprogramming. Moreover, the authors found that such transgenerational behavioural change was transmitted through maternal epigenetic mechanisms. Through sequencing, the authors identified the specific genetic target of such epigenetic modification and further revealed a key neural target that is influenced by such genetic change and is critical for sweet-sensing. Together, this manuscript provided a significant advance in understanding food-induced transgenerational changes in Drosophila. The experiments were carefully designed with proper controls and well executed. The data is convincing and the findings are novel.

Reviewer #2 (Public Review):

This work attempts to connect the diet of a mother to the physiology and feeding behaviors of multiple generations of her offspring. Using genetic and molecular biology approaches in the fruit fly model, the authors argue that this Lamarckian inheritance is mediated by germline-inherited chromatin and is regulated by the general activity of a histone methylase. However, many of the measured effects are small and variable, the statistical tests to prove their significance are missing or poorly described, and some experiments are inadequately described and lack important controls.

1) The authors claim that the diet of a mother can influence the physiology of her progeny for several generations. However, the observed effects of maternal diet on later generations were small and variable for most assays (see Fig1C, S1.1A, B, D). Additionally, the effect size between F0 HSD to ND was often larger than the effect size between the progeny of F0 parents and ND. To put it another way, if the authors were to compare the F1, F2, etc. to the F0 HSD flies, they would conclude that the majority of the response to diet is not maternally transmitted, and is directly controlled by the diet of the individual being measured.<br /> 2) The authors chose to study PER, which had the largest average effect sizes between conditions. However, PER was highly variable in the averaged data, with some individuals showing large effects and others having no effects. A better characterization of transgenerational PER may increase the robustness of this assay and confidence in its results. For example, the authors could measure PER in lineages derived from individual flies to determine when transgenerational effects on PER decline or disappear. This form of data collection could help to explain the high variation in the averaged data presented in the paper.<br /> 3) What do the error bars represent on any figure? There are many examples where the data is highly variable and lies completely outside of the error bars. What is the statistical test for significance that is carried out in each figure? The brief comment about statistics in the methods section is inadequate. The authors should also supply the raw data used to generate the figures so that readers can perform their own statistical tests.<br /> 4) The model that global H3K27me3 is regulated by ancestral diet is unconvincing without further experimental validation and explanation. Points 4-10 address specific issues. The authors performed ChIP on cycle 11 embryos. This stage is extremely short (11 min) and contains roughly 10 times less chromatin than embryos only 30 minutes older. These features make it very difficult to collect large numbers of precisely staged embryos without significant contamination. It is also debatable whether early cell cycles (including and preceding cycle 11) are slow enough to deposit and propagate histone marks in the presence of new histone incorporation. See the opposing arguments in Zenk et al 2017 and Li et al 2014. The authors could perform ChIP on older embryos to avoid this controversy. Surely any maternally inherited information will also be present in cycle 14 or 15 embryos if it is to influence the development or physiology of the brain. The observed differences in global H3K27me3 levels in F1 vs ND flies could be explained by slightly different aged embryo collections or technical variations in the ChIP protocol. The authors could strengthen their conclusion by performing more ChIP replicates. Alternatively, the authors could use orthogonal approaches like antibody staining or western blots to measure global H3K27me3 levels in precisely staged embryos.<br /> 5) The authors measure PRC2 subunit mRNA levels in adult fly heads to attempt to explain the observed differences in inherited H3K27me3 levels in fly embryos. The authors should examine PRC2 components in germ cells and early embryos to understand how germ cells and early embryos generate H3K27me3 patterns.<br /> 6) The RNAi experiment targeting PRC2 components in embryos is uninterpretable without appropriate controls and an explanation of the genotypes used in the experimental paradigm. Are the authors crossing nosNGT mothers to UAS-RNAi fathers and assaying the progeny? What is the genotype of the F1 flies and how does it compare to the genotype of the ND flies? The authors should also note that the Gal4 drivers they use are not necessarily restricted to the ovary, and could directly affect other tissues controlling PER like neurons and muscle. Additionally, the authors should supply the appropriate controls to verify that their experimental paradigm has the intended effect. PRC2 proteins are presumably loaded into embryos and would be immune to zygotic-expressed RNAi. The authors could validate when PRC2 RNAi is effective by staining embryos for H3K27me3.<br /> 7) Although the authors do not note this, nosNGT>RNAi affects the PER of ND flies (compare Gal4>RNAi to just RNAi or just Gal4 in ND columns in Fig3A-D). This could be due to RNAi expression in neurons or muscles or some other indirect effect. Regardless of the mechanism, this result makes it difficult to interpret how RNAi treatments affect the transgenerational inheritance of PER if there is an equivalently strong non-transgenerational effect.<br /> 8) The matalpha gal4 experiment is inadequately explained in the text or methods. Are the authors expressing RNAi in the ovaries of the F0 flies that are fed an HSD? Does the ovary influence their PER somehow? Similar to point 8, there appears to be a non-transgenerational component to the RNAi phenotype that clouds the interpretation of the transgenerational effect (compare F0 in S3.1A-C).<br /> 9) For the EED inhibitor experiments (both PER and calcium imaging), it is unclear whether the authors fed the mothers or their adult progeny the EED inhibitor. If adult progeny were fed, what tissues were affected? The authors should stain various tissues with an H3K27me3 antibody to verify the effectiveness of their inhibitor. Finally, the effect of the EED inhibitor on calcium imaging was not convincing because the variation was so large.<br /> 10) In all of the PRC2 RNAi and inhibitor experiments, are there any other phenotypes that would suggest that the treatments are working? There are many published PRC2 loss-of-function phenotypes (molecular and developmental) in different tissues. The authors could assure the reader that their treatments are working as expected by doing these controls.<br /> 11) The authors propose that a transgenerationally inherited state of the caudal gene is responsible for the transgenerationally inherited PER. However, the experiments investigating the methylation state and expression level of caudal are unconvincing. Cad mRNA abundance varied immensely in the ND RNAseq samples. When the authors compared cad levels across generations, the effect size was small. A single outlier in the ND sample in both the RNAseq and the RTPCR experiments appears to drive up its mean and effect size. The H3K27me3 ChIP on cad is very similar in the F1 and ND samples and the acetylation peak on its promoter appears unchanged. The authors could vastly improve the caudal experiments in this paper by simply using cad antibodies to stain the relevant tissues that contribute to PER. For example, the authors could stain GR5a neurons for cad expression in different generations that inherit (or don't inherit) maternal PER to more accurately determine if cad levels are indeed transgenerationally regulated. The authors could also perform more ChIP experiments at a less variable stage to convincingly correlate epigenetic marks on cad with its expression level.

Reviewer #3 (Public Review):

Jie Yang et al. investigated the transgenerational behavioral modification of a high-sugar diet (HSD) in Drosophila and revealed the underlying molecular and neural mechanisms. It has been reported that HSD exposure decreases sweet sensitivity in gustatory sensory neurons, resulting in reduced sugar response (Proboscis extension reflex, PER) in flies. The current study reports that this effect can be transmitted across generations through the maternal germline. Furthermore, the authors show that H3K27me3 modification is enhanced in the first-generation progenies of HSD-treated flies (F1), and genetical or pharmacological disruption of PCL-PRC2 complex blocks the behavioral change and restores the sweet sensitivity in the Gr5a+ sweet sensory neurons. The authors further analyze the differentially expressed genes in the F1 flies. Among H3K27me3 hypermethylated regions, they focus on homeobox genes and find a transcription factor Caudal (Cad), which shows decreased expression in the F1 flies. Knocking down Cad in Gr5a+ neurons results in decreased PER response to sucrose.

Transgenerational changes in physiology and metabolism have been broadly studied, while inherited changes at the behavioral level are much less investigated. This work provides convincing evidence for transgenerational modification of feeding behavior and digs out the underlying molecular and neural mechanisms. However, there still are several concerns that need to be clarified.

1) The epigenetic regulator PCR2 has been found to play an essential role in the 7d-HSD-induced modification of the PER response. In this study, it's important to clarify for the transgenerational change, whether epigenetic modification is required in the flies exposed to HSD (F0), the progenies (F1), or both. It would be very helpful for better interpretation if the procedures of HSD treatment in RNAi experiments and the drug treatments were stated in more detail. In addition, the F0 flies should be examined as the control.<br /> 2) The information on the drug treatment period is also missing for imaging experiments (Fig.4C). Moreover, the response curve is very different from those recorded in the same neurons in previous studies. What's the reason? Please also provide a representative image showing which part of the Gr5a neurons is recorded.<br /> 3) It's unclear whether the decreased Cad expression upon HSD treatment specifically occurred in Gr5a+ neurons or a lot of cells. If the change in gene expression is significant in the qPCR test, it should occur in a large number of cells, most likely including different types of gustatory sensory neurons. If lower cad expression led to lower neural response and thereby lower behavioral response, how to specifically decrease the PER response to sucrose but not to other tastes? --whether HSD-induced desensitization is specific to sucrose in the offspring?<br /> 4) In Fig.2D, data are sorted for genomic regions showing an up-regulated modification of H3K27me. It's unclear whether similar sorting was performed in panel C. This needs to be clarified.

Reviewer #1 (Public Review):

This is an interesting paper that shows disruption of thalamocortical communication in anesthesia, and enhancement under 5-MeO-DMT in an animal model, combined with a model to establish that these changes can be understood as a displacement from a critical point of a neural mass model. Overall, these results are exciting as they constitute evidence that very different brain states can be understood as two different points of a continuum of states, with a critical transition point in the middle.

These are my main detailed comments about this manuscript:

1. Psychedelic drug dosage: 5 mg/kg is possibly a low dose of 5-MeO-DMT, which exhibits nonlinear pharmacokinetics presenting a transition in drug serum concentration between 2 mg/kg and 10 mg/kg. (Shen, H. W., Jiang, X. L., & Yu, A. M. (2011). Nonlinear pharmacokinetics of 5-methoxy-N, N-dimethyltryptamine in mice. Drug Metabolism and Disposition, 39(7), 1227-1234.)

2. Novelty of the neural mass approach to establish critical dynamics. The neural mass model is interesting but it is also well established that the features of LFPs during anesthesia can be captured using these kinds of models, including phenomenology such as burst suppression, emergence of high amplitude synchronized oscillations, etc.; see for instance Kuhlmann, L., Freestone, D. R., Manton, J. H., Heyse, B., Vereecke, H. E., Lipping, T., ... & Liley, D. T. (2016). Neural mass model-based tracking of anesthetic brain states. NeuroImage, 133, 438-456.). The same applies to the modeling of wakefulness LPF using neural masses to show that alpha oscillations emerge in thalamocortical systems at the edge of a dynamic phase transition, which can be reproduced by the dynamics of a Hopf bifurcation.

3. Is it possible that some of the results in the essential tremor group were influenced by the disease and its effects on the LPF dynamics, as it is known that tremors and seizures are associated by themselves with departures from critical dynamics?

4. Table 1 and other parts of the manuscript: multiple independent tests were conducted, does this require a correction for multiple comparisons to avoid the reporting of false positive results or its control by FDR or related approaches?

Reviewer #2 (Public Review):

Toker et al. use a frequency-resolved analysis of cortico-thalamic and thalamo-cortical information transfer to determine at which combinations of frequencies a frequency-specific transfer of information exists, and how this transfer is modulated by anesthesia, spike-and-wave seizures, and psychedelic states. They find that anesthesia and seizures lower the transfer of information at a specific combination of frequencies (sending: 1.5-13Hz, receiving 50-100Hz), whereas psychedelic states induced by 5-MeO-DMT increase. The reductions were observed for both directions whereas significant increases were only observed from cortex to thalamus.

Neural mean-field modeling shows that these empirical observations may be linked to a deviation of neural dynamics from the critical point between ordered and chaotic dynamics.

The manuscript tackles an important question using innovative methods. Yet, the analysis of spectrally resolved information transfer at present suffers from an unfortunate choice of analysis parameters (especially a history length of 1, and a low number of surrogate data), that need to be changed to fully install trust in the presented results. The statistical analysis seems to suffer from so-called 'double-dipping', but there are several possible ways to fix this issue.

Reviewer #1 (Public Review):

Davies et al. examined the role of the malaria parasite's FIKK4.1 protein kinase in trafficking and host membrane insertion of key proteins that are exported by the intracellular P. falciparum parasite. FIKK4.1 is one of 18 FIKK serine/threonine kinases exported into the host erythrocyte; these kinases phosphorylate both host proteins and exported parasite proteins. FIKK4.1 has previously been implicated in rigidification of the erythrocyte cytoskeleton. It is also known to affect trafficking and insertion of PfEMP1, the parasite's primary cytoadherence ligand, on the host cell surface. In the present studies, the authors perform sophisticated gene-editing experiments that combine conditional knockout of FIKK4.1 with tagging of two kinase targets with the TurboID proximity biotin-labeling enzyme to explore phosphorylation-dependent changes in target protein localization, structure, or protein-protein interactions. Using conditional knockout of each exported FIKK kinase, they determine that FIKK4.1 is the only kinase that regulates PfEMP1 surface exposure and that it does not appear to modulate surface translocation of RIFINs, a family of parasite antigens involved in immune evasion. The combination of gene-editing, proximity labeling and mass spectrometry, and biochemical studies in the paper is to be lauded. These findings identify key targets of exported kinases and will guide future studies of host cell remodeling.

Key limitations of the study:

1. TurboID tagging of FIKK4.1 followed by proximity labeling and mass spectrometry of biotinylated proteins revealed parasite-stage dependent labeling of 101 parasite proteins and 39 human proteins that come in contact with FIKK4.1. Although TurboID is a more efficient biotin ligase produced through directed evolution, nonspecific biotinylation of proteins that do not form biologically relevant interactions remains an issue. Biotin addition for 4 hours, as used here and in most studies using this ligase, allows for labeling of proteins that undergo random collisions with the TurboID-tagged protein. While there was clear enrichment of exported proteins in the FIKK4.1-tagged parasite at mature schizont stages when FIKK4.1 is in the host cytosol, only 66% of the proteins labeled were exported, consistent with labeling and recovery of irrelevant proteins. As the authors performed appropriate controls and interpreted their findings cautiously, this limitation results primarily from finite efficiency of TurboID, trace levels of endogenous biotin within cells, and other complexities associated with the technology.

2. The production of dual-edited parasites carrying conditional knockout of FIKK4.1 and TurboID tagging of either KAHRP or PTP4 permitted examination of changes in localization of exported proteins upon their phosphorylation by FIKK4.1. KAHRP and PTP4 are excellent choices for these experiments because they are established targets of the kinase and good candidates for effectors involved in PfEMP1 membrane insertion. Some 30-40 proteins exhibited significant changes in biotinylation by these TurboID-tagged proteins, suggesting altered localization or structure upon loss of FIKK4.1 kinase activity. PfEMP1 trafficking proteins (PTPs), Maurer's cleft proteins, exported heat shock proteins, and components of PSAC, a parasite-associated nutrient uptake channel, all exhibited changes. Although FIKK4.1 is not essential for in vitro parasite propagation, altered localization could result either directly from changes in phosphorylation status of the protein itself or could reflect indirect effects on the cell from loss of FIKK4.1.

3. As a consequence of these two limitations, these experiments could not conclusively implicate either KAHRP or a specific PTP in PfEMP1 surface translocation. Whether specific Maurer's cleft proteins or the nutrient channel components contribute to PfEMP1 surface translocation could also not be addressed. The authors' Discussion section is appropriately cautious in interpreting changes in biotinylation upon FIKK4.1 disruption. Although a large amount of data has been generated in this sophisticated study, the precise mechanism of PfEPM1 trafficking and membrane insertion remains elusive.

Reviewer #2 (Public Review):

Davies et al combine TurboID with conditional mutagenesis to reveal how a perturbing event alters the accessibility of a sub-cellular proteome to proximity biotinylation. The approach builds on established techniques for antibody-mediated enrichment of biotinylated peptides (rather than purification of whole biotinylated proteins by avidin) to enable mapping of the specific lysines that are biotinylated by TurboID and how access to these sites changes between conditions. The insights gained have a range of potential implications touching on protein trafficking/localization, complex dynamics and membrane topology. The authors apply this strategy to study trafficking of the key P. falciparum adhesin PfEMP1 to the infected erythrocyte surface. This group has previously shown that the exported parasite kinase FIKK4.1 is important for this process but the specific mechanism is unknown. In the first part of the present study, the authors develop PerTurboID and analyze the altered biotinylation patterns upon FIKK4.1 deletion in parasite lines bearing TurboID tags on PTP4 or KAHRP, two proteins required for this pathway and likely direct substrates of FIKK4.1. Numerous changes in site-specific biotinylation are quantitatively assessed on hundreds of proteins and possible implications for these changes are discussed, including topology of parasite integral membrane proteins exported into the RBC compartment as well as how the conformation of the RhopH complex might be altered upon RBC membrane integration. In a final set of experiments, the authors show that among 18 exported FIKK kinases, FIKK4.1 is uniquely important to PfEMP1 surface display but not to the distinct RIFIN class of parasite proteins that are also trafficked to the RBC surface. On the whole, the data are compelling and provide an important new approach that advances the proximity labeling toolkit.

While the resolution of PerTurboID captures the site-specific changes in biotinylation abundance and position that occur upon loss of FIKK4.1, a limitation of the study is that these observations do not necessarily clarify the model for how FIKK4.1 is controlling the PfEMP1 trafficking pathway. The authors convincingly show that FIKK4.1 uniquely supports PfEMP1 surface presentation and cytoadhesion. However, this is not connected to the PerTurboID data in a way that provides a mechanism for how this is achieved by FIKK4.1 activity and in my opinion doesn't deliver on the title claim to "reveal the impact of kinase deletion on cytoadhesion". Certainly the changes in biotinylation suggest a range of interesting possibilities related to the accessibility and topology of proteins within and beyond the PfEMP1 trafficking pathway; however, it is hard to interpret the relationship of these changes to the process in view. For instance, deletion of FIKK4.1 increases biotinylation of several Maurer's clefts proteins in both the PTP4- and KAHRP-TurboID experiments but why this is or whether it is significant for PfEMP1 transport is unclear.

Reviewer #3 (Public Review):

The authors aim to gain a more comprehensive understanding of the role of FIKK4.1 in parasite biology. To achieve this, they used a novel approach termed PerTurboID that allows them to map changes in the conformational and interaction environment of proteins that are in close proximity of the tagged gene of interest. Here the authors focus on two proteins KHARP and PTP4 who are known targets of FIKK4.1 and assessed the impact of the genetic disruption of the kinase on the interaction environment of these proteins. The experimental strategy identifies a range of changes that indicate that changes go beyond the direct targets of FIKK4.1 and therefore creates new insights of interaction networks that are regulated by this specific kinase.

The strength of this approach is not only that it can identify new interaction networks relating to FIKK4.1 but that serves as a proof of concept that can be used for a wide range of applications in parasite biology. At the same time as the authors have noted themselves the extent of the biotin pulse is important and most likely needs to be calibrated for every specific application. In addition, this approach is only suitable for proteins that can be tagged without impacting their function.

The authors present very convincing evidence that the PerTurboID is suitable to study FIKK kinases in parasites and have used this to shed new light on how FIKK4.1 is involved directly or indirectly in a wider range of biological activities in the parasite.

The main impact of this work is that it provides a wider understanding of the relationship between a specific kinase and structural as well as biological consequences. The methodology is also very powerful and will have a wide range of applications.

Reviewer #3 (Public Review):

Summary:<br /> The authors present a biophysically detailed model of the basolateral amygdala (BLA) that is capable of fear learning through a depression-dominated spike-timing dependent plasticity (STDP) mechanism. Furthermore, the model also replicates experimentally measured rhythmic signatures of baseline amygdala activity and changes of these signatures during and after fear learning. The authors furthermore carefully dissect the contributions of the three different types of interneurons (parvalbumin-positive (PV), somatostatin-positive (SOM), and vaso-active peptide-positive (VIP) interneurons) in regulating network activity to allow for the association between conditioned and unconditioned stimuli.

Strengths:<br /> The biophysical detail of the model allows the authors to go beyond a simple modelling of the fear learning process in terms of spiking activity of the principal cells and to link the associative learning to several oscillatory rhythms in the BLA, namely high and low theta and gamma rhythms. This provides an understanding of the generation and function of these rhythms in the baseline amygdala circuit as well as of the functional consequences of alterations of these rhythms during and after the fear learning process. This offers a new and uniquely detailed insight into the mechanistic level.

Weaknesses:<br /> The main weakness of the approach is the lack of experimental data from the BLA to constrain the biophysical models. This forces the authors to use models based on other brain regions and leaves open the question of whether the model really faithfully represents the basolateral amygdala circuitry. Furthermore, the authors chose to use model neurons without a representation of the morphology. However, given that PV and SOM cells are known to preferentially target different parts of pyramidal cells and given that the model relies on a strong inhibition form SOM to silence pyramidal cells, the question arises whether SOM inhibition at the apical dendrite in a model representing pyramidal cell morphology would still be sufficient to provide enough inhibition to silence pyramidal firing. Lastly, the fear learning relies on the presentation of the unconditioned stimulus over a long period of time (40 seconds). The authors justify this long-lasting input as reflecting not only the stimulus itself but as a memory of the US that is present over this extended time period. However, the experimental evidence for this presented in the paper is only very weak.

The authors achieved the aim of constructing a biophysically detailed model of the BLA not only capable of fear learning but also showing spectral signatures seen in vivo. The presented results support the conclusions with the exception of a potential alternative circuit mechanism demonstrating fear learning based on a classical Hebbian (i.e. non-depression-dominated) plasticity rule, which would not require the intricate interplay between the inhibitory interneurons. This alternative circuit is mentioned but a more detailed comparison between it and the proposed circuitry is warranted.

The presented model demonstrates how the complex interplay between different types of interneurons is able to precisely control neural activity to enable learning to happen. Furthermore, the presented work shows this interactive control of activity by the interneurons gives rise to specific oscillatory signatures. Since the three types of interneurons considered here are found throughout the brain, the findings will likely have a big impact on other studies of interneuron function and learning in general.

Reviewer #2 (Public Review):

This study follows up on a previous study by the group (Sibille et al Nature Communications 2022) in which high density Neuropixel probes were inserted tangentially through the superficial layers of the superior colliculus (SC) to record the activity of retinocollicular axons and postsynaptic collicular neurons in anesthetized mice. By correlating spike patterns, connected pairs could be identified which allowed the authors to demonstrate that functionally similar retinal axon-SC neuron pairs were strongly connected.

In the current study, the authors use similar techniques in vGAT-ChR2 mice and add a fiber optic to identify light-activated GABAergic and non-light-activated nonGABAergic neurons. Using their previously verified techniques to identify connected pairs, within regions of optogenetic activation they identified 214 connected pairs of retinal axons and nonGABAergic neurons and 91 pairs of connected retinal axons and GABAergic neurons. The main conclusion is that retinal activity contributed more to the activity of postsynaptic nonGABAergic SC neurons than to the activity of postsynaptic GABAergic SC neurons.

The study is very well done. The figures are well laid out and clearly establish the conclusions. My main comments are related to the comparison to other circuits and further questions that might be addressed in the SC.

It is stated several times that the superior colliculus and the visual cortex are the two major brain areas for visual processing and these areas are compared throughout the manuscript. However, since both the dorsal lateral geniculate nucleus (dLGN) and SC include similar synaptic motifs, including triadic arrangements of retinal boutons with GABAergic and nonGABAergic neurons, it might be more relevant to compare and contrast retinal convergence and other features in these structures.

The GABAergic and nonGABAergic neurons showed a wide range of firing rates. It might be interesting to sort the cells by firing rates to see if they exhibit different properties. For example, since the SC contains both GABAergic interneurons and projection neurons it would be interesting to examine whether GABAergic neurons with higher firing rates exhibit narrower spikes, similar to cortical fast spiking interneurons. Similarly, it might be of interest to sort the neurons by their receptive field sizes since this is associated with different SC neuron types.

The recording techniques allowed for the identification of the distance between connected retinocollicular fibers and postsynaptic neurons. It might also be interesting to compare the properties of connected pairs recorded at dorsal versus ventral locations since neurons with different genetic identities and response properties are located in different dorsal/ventral locations (e.g. Liu et al. Neuron 2023). Also, regarding the strength of connections, previous electron microscopy studies have shown that the retinocollicular terminals differ in density and size in the dorsal/ventral dimension (e.g Carter et al JCN 1991).

Was optogenetic activation of GABAergic neurons ever paired with visual activation? It would be interesting to examine the receptive fields of the nonGABAergic neurons before and after activation of the GABAergic neurons (as in Gale and Murphy J Neurosci 2016).

Reviewer #1 (Public Review):

Gehr and colleagues used an elegant method, using neuropixels probes, to study retinal input integration by mouse superior collicular cells in vivo. Compared to a previous report of the same group, they opto-tagged inhibitory neurons and defined the differential integration onto each group. Through these experiments, the author concluded that overall, there is no clear difference between the retina connectivity to excitatory and inhibitory superior colliculus neurons. The exception to that rule is that excitatory neurons might be driven slightly stronger than inhibitory ones. Technically, this work is performed at a high level, and the plots are beautifully conceived, but I have doubts if the interpretation given by the authors is solid. I will elaborate below.

Some thoughts about the interpretation of the results.

My main concern is the "survivor bias" of this work, which can lead to skewed conclusions. From the data set acquired, 305 connections were measured, 1/3 inhibitory and 2/3 excitatory. These connections arise from 83 RGC onto 124 RGC (I'm interpreting the axis of Fig.2 C). Here it is worth mentioning that different RGC types have different axonal diameters (Perge et al., 2009). Here the diameter is also related to the way cells relay information (max frequencies, for example). It is possible that thicker axons are easier to measure, given the larger potential changes would likely occur, and thus, selectively being picked up by the neuropixels probe. If this is the case, we would have a clear case of "survival bias", which should be tested and discussed. One way to determine if the response properties of axonal termini are from an unbiased sample is to make a rough functional characterization as generally performed (see Baden et al. 2006). This is fundamental since all other conclusions are based on unbiased sampling.

One aspect that is not clear to me is to measure of connectivity strength in Figure 2. Here it seems that connectivity strength is directly correlated with the baseline firing rate of the SC neuron (see example plots). If this is a general case, the synaptic strength can be assumed but would only differ in strength due to the excitability of the postsynaptic cell. This should be tested by plotting the correlation coefficient analysis against the baseline firing rate.

My third concern is the assessment of functional similarity in Fig. 3. It is not clear to me why the similarity value was taken by the arithmetic mean. For example, even if the responses are identical for one connected pair that exclusively responds either to the ON or OFF sparse noise, the maximal value can only be 0.67. Perhaps I misunderstood something. Secondly, correlations in natural(istic) movies can differ dramatically depending on the frame rate that the movie was acquired and the way it is displayed to the animal. What looks natural to us will elicit several artifacts at a retinal level, e.g., due to big jumps between frames (no direction-selective response) or overall little modulation (large spatial correlations). I would rather opt for uniform stimuli, as suggested previously. Of course, these are also approximations but can be easily reproduced by different labs and are not subjected to the intricacies of the detailed naturalistic stimulus used.

Fourth. It is important to control the proportion of inhibitory cells activated optogenetically across the recording probe. Currently, it is not possible to assess if there are false negatives. One way of controlling for this would be to show that the number of inhibitory interneurons doesn't vary across the probe.

Fifth. In Fig. 4, the ISI had a minimal bound of 5 ms. Why? This would cap the firing rate at 200Hz, but we know that RGC in explants can fire at higher frequencies for evoked responses. I would set a lower bound since it should come naturally from the after-depolarization block. Another aspect that remains unclear is to what extent the paired-spike ratio depends on the baseline firing rate. This would change the interpretation from the particular synaptic connection to the intrinsic properties of the cell and is plausible since the bassline firing rate varies tremendously. One related analysis would be to plot the change of PSR depending on the ISI. It would be intuitive to make a scatter plot for all paired spikes of all recorded neurons (separated into inhibitory and excitatory) of ISI vs. PSR.

Panel 4E is confusing to me. Here what is plotted is efficacy 1st against PSR (which is efficacy 2nd/efficacy 1st). Given that you have a linear relation between efficacy 1st and efficacy 2nd (panel 4C), you are essentially re-plotting the same information, which should necessarily have a hyperbolic relationship: [ f(x) = y/x ]. Thus, fitting this with a linear function makes no sense and it has to be decaying if efficacy 2nd > efficacy1st as shown in 4C.

Finally, in Figure 5, the perspective is inverted, and the spike correlations are seen from the perspective of SC neurons. Here it would also be good to plot the cumulative histograms and not look at the averages. Regarding the similarity index and use of natural stats, please see my previous comments. Also, would it be possible to plot the contribution v/s the firing rate with the baseline firing rate with no stimulation or full-field stimulation? This is important since naturalistic movies have too many correlations and dependencies that make this plot difficult to interpret.

Overall, the paper only speaks from excitatory and inhibitory differences in the introduction and results. However, it is known that there are three clear morphologically distinct classes of excitatory neurons (wide-field, narrow-field, and stellate). This topic is touched in the discussion but not directly in the context of these results. Smaller cells might likely be driven much stronger. Wide-field cells would likely not be driven by one RGC input only and will probably integrate from many more cells than 6.

Reviewer #3 (Public Review):

This study performs in vivo recordings of neurons in the mouse superior colliculus and their afferents from the retina, retinal ganglion cells (RGCs). Building on a preparation they previously published, this study adds the use of optogenetic identification of inhibitory neurons (aka optotagging) to compare RGC connectivity to excitatory and inhibitory neurons in SC. Using this approach, the authors characterize connection probability, strength, and response correlation between RGCs and their target neurons in SC, finding several differences from what is observed in the retina-thalamus-visual cortex pathway. As such, this may be a useful dataset for efforts to understand retinocollicular connectivity and computations.

Reviewer #1 (Public Review):

The authors set out to develop an organoid model of the junction between early telecephalic and ocular tissues to model RGC development and pathfinding in a human model. The authors have succeeded in developing a robust model of optic stalk(OS) and optic disc(OD) tissue with innervating retinal ganglion cells. The OS and OD have a robust pattern with distinct developmental and functional borders that allow for a distinct pathway for pathfinding RGC neurites.

Future work targeting RGC neurite outgrowth mechanisms will be exciting.

Reviewer #2 (Public Review):

The authors compare their single-cell data of the self-forming brain-eye centroids with the published single-cell data from human fetal retinas and brain/optic organoids. This analysis further supports the similarity of their centroids with the human fetal retinal cell clusters, including the detection of the VSX2+/PAX2+ cells. The new findings further support the presented centroids' applicability for future studies on human RGC development and axon guidance mechanisms.

Reviewer #1 (Public Review):

Summary<br /> In this study, Xu et al. provide insights into the substrate divergence of CASP3 and CASP7 for GSDME cleavage and activation during vertebrate evolution vertebrates. Using biochemical assays, domain swapping, site-directed mutagenesis, and bioinformatics tools, the authors demonstrate that the human GSDME C-terminal region and the S234 residue of human CASP7 are the key determinants that impede the cleavage of human GSDME by human CASP7.

Strengths<br /> The authors made an important contribution to the field by demonstrating how human CASP7 has functionally diverged to lose the ability to cleave GSDME and showing that reverse-mutations in CASP7 can restore GSDME cleavage. The use of multiple methods to support their conclusions strengthens the authors' findings. The unbiased mutagenesis screen performed to identify S234 in huCASP7 as the determinant of its GSDME cleavability is also a strength.

Weaknesses<br /> While the authors utilized an in-depth experimental setup to understand the CASP7-mediated GSDME cleavage across evolution, the physiological relevance of their findings are not assessed in detail. Additional methodology information should also be provided.

Specific recommendations for the authors<br /> 1. The authors should expand their evaluation of the physiological relevance by assessing GSDME cleavage by the human CASP7 S234N mutant in response to triggers such as etoposide or VSV, which are known to induce CASP3 to cleave GSDME (PMID: 28045099). The authors could also test whether the human CASP7 S234N mutation affects substrate preference beyond human GSDME by testing cleavage of mouse GSDME and other CASP3 and CASP7 substrates in this mutant.<br /> 2. It would also be interesting to examine the GSDME structure in different species to gain insight into the nature of mouse GSDME, which cannot be cleaved by either mouse or human CASP7.<br /> 3. The evolutionary analysis does not explain why mammalian CASP7 evolved independently to acquire an amino acid change (N234 to S234) in the substrate-binding motif. Since it is difficult to experimentally identify why a functional divergence occurs, it would be beneficial for the authors to speculate on how CASP7 may have acquired functional divergence in mammals; potentially this occurred because of functional redundancies in cell death pathways, for example.<br /> 4. For the recombinant proteins produced for these analyses, it would be helpful to know whether size-exclusion chromatography was used to purify these proteins and whether these purified proteins are soluble. Additionally, the SDS-PAGE in Figure S1B and C show multiple bands for recombinant mutants of TrCASP7 and HsCASP7. Performing protein ID to confirm that the detected bands belong to the respective proteins would be beneficial.<br /> 5. For Figures 3C and 4A, it would be helpful to mention what parameters or PDB files were used to attribute these secondary structural features to the proteins. In particular, in Figure 3C, residues 261-266 are displayed as a β-strand; however, the well-known α-model represents this region as a loop. Providing the parameters used for these callouts could explain this difference.<br /> 6. Were divergent sequences selected for the sequence alignment analyses (particularly in Figure 6A)? The selection of sequences can directly influence the outcome of the amino acid residues in each position, and using diverse sequences can reduce the impact of the number of sequences on the LOGO in each phylogenetic group.<br /> 7. For clarity, it would help if the authors provided additional rationale for the selection of residues for mutagenesis, such as selecting Q276, D278, and H283 as exosite residues, when the CASP7 PDB structures (4jr2, 3ibf, and 1k86) suggest that these residues are enriched with loop elements rather than the β sheets expected to facilitate substrate recognition in exosites for caspases (PMID: 32109412). It is possible that the inability to form β-sheets around these positions might indicate the absence of an exosite in CASP7, which further supports the functional effect of the exosite mutations performed.

Reviewer #2 (Public Review):

The authors wanted to address the differential processing of GSDME by caspase 3 and 7, finding that while in humans GSDME is only processed by CASP3, Takifugu GSDME, and other mammalian can be processed by CASP3 and 7. This is due to a change in a residue in the human CAPS7 active site that abrogates GSDME cleavage. This phenomenon is present in humans and other primates, but not in other mammals such as cats or rodents. This study sheds light on the evolutionary changes inside CASP7, using sequences from different species. Although the study is somehow interesting and elegantly provides strong evidence of this observation, it lacks the physiological relevance of this finding, i.e. on human side, mouse side, and fish what are the consequences of CASP3/7 vs CASP3 cleavage of GSDME.

Fish also present a duplication of GSDME gene and Takifugu present GSDMEa and GSDMEb. It is not clear in the whole study if when referring to TrGSDME is the a or b. This should be stated in the text and discussed in the differential function of both GSDME in fish physiology (i.e. PMIDs: 34252476, 32111733 or 36685536).

Reviewer #1 (Public Review):

In the present manuscript, Abele et al use Salmonella strains modified to robustly induce one of two different types of regulated cell death, pyroptosis or apoptosis in growth phases (when SPI2 T3SS is expressed) and cell types to assess the role of pyroptosis versus apoptosis in systemic versus intestinal epithelial pathogen clearance. They demonstrate that in systemic spread, which requires growth in macrophages, pyroptosis is required to eliminate Salmonella, while in intestinal epithelial cells (IEC), extrusion of the infected cell into the intestinal lumen induced by apoptosis or pyroptosis is sufficient for early pathogen restriction. The methods used in these studies are thorough and well-controlled and lead to robust results, that mostly support the conclusions. The impact on the field is considered minor as the observations are somewhat redundant with previous observations and not generalizable due to cited evidence of different outcomes in other models of infection and a relatively artificial study system that does not permit the assessment of later time points in infection due to rapid clearance. This excludes the study of later effects of differences between pyroptosis and apoptosis in IEC such as i.e. IL-18 and eicosanoid release, which are only observed in the former and can have effects later in infection.

Reviewer #2 (Public Review):

In this study, Abele et al. present evidence to suggest that two different forms of regulated cell death, pyroptosis and apoptosis, are not equivalent in their ability to clear infection with recombinant Salmonella strains engineered to express the pro-pyroptotic NLRC4 agonist, FliC ("FliC-ON"), or the pro-apoptotic protein, BID ("BID-ON"). In general, individual experiments are well-controlled, and most conclusions are justified. However, the cohesion between different types of experiments could be strengthened and the overall impact and significance of the study could be articulated better.

Reviewer #1 (Public Review):

Induction of beta cell regeneration is a promising approach for the treatment of diabetes. In this study, Massoz et.al., identified calcineurin (CaN) as a new potential modulator of beta cell regeneration by using zebrafish as model. They also showed that calcineurin (CaN) works together with Notch signaling calcineurin (CaN) to promote the beta cell regeneration. Overall, the paper is well organized, and technically sound. However, some evidence seems weak to get the conclusion.

Reviewer #2 (Public Review):

This work started with transcriptomic profiling of ductal cells to identify the upregulation of calcineurin in the zebrafish after beta-cell ablation. By suppressing calcineurin with its chemical inhibitor cyclosporin A and expressing a constitutively active form of calcineurin ubiquitously or specifically in ductal cells, the authors found that inhibited calcineurin activity promoted beta-cell regeneration transiently while ectopic calcineurin activity hindered beta-cell regeneration in the pancreatic tail. They also showed similar effects in the basal state but only when it was within a particular permissive window of Notch activity. To further investigate the roles of calcineurin in the ductal cells, the authors demonstrated that calcineurin inhibition additionally induced the proliferation of the ductal cells in the regenerative context or under a limited level of Notch activity. Interestingly, the enhanced proliferation was followed by a depletion of ductal cells, suggesting that calcineurin inhibition would exhaust the ductal cells. Based on the data, the authors proposed a very attractive and intriguing model of the role of calcineurin in maintaining the balance of the progenitor proliferation and the endocrine differentiation. However, the conclusions of this paper are only partially supported by the data as some evidence from the data remains suggestive.

1. In the transcriptomic profiling, genes differentially regulated in the ablated adults could be solely due to the chemical effects of metronidazole instead of the beta-cell ablation. A control group without ins:NTR-mCherry but treated with metronidazole is necessary to exclude the side effects of metronidazole.

2. Although it has been shown that the pancreatic duct is a major source of the secondary islets in the pancreatic tail in previous studies, there is no direct evidence showing the cyclosporin A-induced cells share the source in this manuscript. Without any proper lineage tracing work, the origin of those cyclosporin A-induced cells cannot be concluded.

3. It is interesting to see an increase of beta cells in the primary islet after cyclosporin A treatment (Supplemental Fig 2B). However, it remains unclear if their formation shares the same mechanism with the newly formed beta cells in the pancreatic tail.

4. The conclusion of the effect of cyclosporin A on the endocrine progenitors (Line 175) is not convincing because the data cannot distinguish the endocrine progenitors from the insulin-expressing cells. Indeed, Figure 2E shows that neurod1+ cells are fewer than ins+ cells (Figure 2D) in the pancreatic tail at 10 dpt, suggesting that all or at least the majority of neurod1+ cells are already ins+.

5. Figure 5D shows a significant loss of nkx6.1+ cells in the combined treatment group but there is no direct evidence showing this was a result of differentiation as the authors suggested. This cell loss also outnumbered the increase in ins+ cells (Figure 4D). The cell fates of these lost cells are still undetermined, and the authors did not demonstrate if apoptosis could be a reason of the cell loss.

Reviewer #1 (Public Review):

Iversen et al. performed middle cerebral artery occlusion in rats to evaluate microscopic changes in the blood flow in the ischemic region. By using measures for global (laser speckle) and local capillary blood flow (two-photon imaging), their results show that the capillary transient time/directionality is affected in this model of ischemic stroke. There are several points that need to be addressed, including what vessels authors considered as capillaries and how they controlled/compensated for the capillary blood flow heterogeneity in their analysis. The authors also proposed that the pericytes are not contributing to these functional deficits by doing morphological analysis, more functional studies are needed to confirm this conclusion.

Reviewer #2 (Public Review):

Novelty: The concept that capillary stalls occur in the ischemic penumbra is not new. However, there are several interesting findings in the current study.<br /> 1- Flow reversal, 2- the effect of flow disturbances on oxygenation, and 3- capillary pericytes do not affect the hemodynamics in the penumbra.<br /> However, more in-depth analysis is needed and the underlying mechanism of flow reversal and the link between flow reversal and pericytes is unclear.

Strengths:<br /> 1. The study employs a combination of techniques including Laser speckle imaging, two photon microscopy and biophysical modelling to specifically examine hemodynamic and metabolic changes in the penumbra following experimental stroke.<br /> 2. The importance of following microvascular flow changes during hours after stroke.<br /> 3. The authors used a rat model of stroke and confirmed previous work that has been performed in mice about capillary stalls and flow disturbance in the ischemic penumbra.

Weaknesses:<br /> 1- The reliance on laser speckle to define the ischemic core and penumbra is not convincing.<br /> 2- The mechanisms behind microvascular flow disturbance are poorly defined.<br /> 3- The inability to measure capillary flow simultaneously in the regions of interest: e.g, Bessel beam imaging or volumetric imaging.<br /> 4- Lack of baseline measurements.

Reviewer #3 (Public Review):

In the present study, Iversen et al investigate the effect of middle cerebral artery occlusion (MCAo) on penumbral capillary blood flow in rat brains. Using Laser Speckle Contrast imaging and two-photon microscopy, they found that during MCAo the red blood cell dynamics become chaotic in penumbral capillaries despite an apparent constant residual blood flow. They further conclude that these disturbances would cause decreases in steady-state cerebral metabolic rate of oxygen (CMRO2), and tissue oxygen tension (PtO2) using a post hoc biophysical model for oxygen extraction. Interestingly, the authors present data excluding a role for pericytes in altering capillary blood flow. From this observation, the study raises potentially interesting questions on the origin of the disturbance but fails to address them by not investigating the upstream arteriolar behavior. Increased vasomotion, palpability, or intermittent vasospasm may trigger capillary blood flow disturbances without necessarily impacting residual blood flow resting as measured by Laser Speckle Contrast imaging. Furthermore, the data are very poorly presented, here are some examples:<br /> Fig 1b is incorrectly labeled and, assuming this is the "first" 1f panel, the scale bar shows 500 µm while the legend says 200.<br /> Fig 1d is poorly convincing as pink or grey, as detailed in the legend, are not visible. It also looks like there is a second core and penumbra on the more rostral left part of the brain.<br /> Line 219 time is misspelled.<br /> Fig 2, what does "percent of alle capillaries" on the y axes mean? 2d is presented before 2c in the text.<br /> What is the rationale for presenting the statistics from Fig 3 in Fig 4? Panels 4e and 4f are not discussed. The reference in the Fig 4 legend is not formatted.<br /> Fig 6 is presented before Fig 5.<br /> The overall lack of a central hypothesis combined with the aforementioned weaknesses prevents the study from achieving its proposed goal "to characterize microvascular flow disturbances in penumbral tissue in a rat model of acute ischemic stroke".

Reviewer #1 (Public Review):

In this study by Yaghmaeian Salmani et al., the authors performed single-nuclei RNA sequencing of a large number of cells (>70,000) in the ventral midbrain. The authors focused on cells in the ventral tegmental area (VTA) and substantia nigra (SN), which contain heterogeneous cell populations comprising dopaminergic, GABAergic, and glutamatergic neurons. Dopamine neurons are known to consist of heterogeneous subtypes, and these cells have been implicated in various neuropsychiatric diseases. Thus, identifying specific marker genes across different dopamine subpopulations may allow researchers in future studies to develop dopamine subtype-specific targeting strategies that could have substantial translational implications for developing more specific therapies for neuropsychiatric diseases.

A strength of the authors' approach compared to previous work is that a large number of cells were sequenced, which was achieved using snRNA-seq, which the authors found to be superior compared to scRNA-seq for reducing sampling bias. A weakness of the study is that relatively little new information is provided as the results are largely consistent with previous studies (e.g., Poulin et al., 2014). Nevertheless, it should be noted that the authors found some more nuanced subdivisions in several genetically identified DA subtypes.

Lastly, the authors performed molecular analysis of ventral midbrain cells in response to 6-OHDA exposure, which leads to the degeneration of SN dopamine neurons, whereas VTA dopamine neurons are largely unaffected. Based on this analysis, the authors identified several candidate genes that may be linked to neuronal vulnerability or resilience.

Overall, the authors present a comprehensive mouse brain atlas detailing gene expression profiles of ventral midbrain cell populations, which will be important to guide future studies that focus on understanding dopamine heterogeneity in health and disease.

Reviewer #2 (Public Review):

In the manuscript by Salmani et al., the authors explore the transcriptomic characterization of dopamine neurons in order to explore which neurons are particularly vulnerable to 6-OHDA-induced toxicity. To do this they perform single nucleus RNA sequencing of a large number of cells in the mouse midbrain in control animals and those exposed to 6-OHDA. This manuscript provides a detailed atlas of the transcriptome of various types of ventral midbrain cells - though the focus here is on dopaminergic cells, the data can be mined by other groups interested in other cell types as well. The results in terms of cell type classification are largely consistent with previous studies, though a more nuanced picture of cellular subtypes is portrayed here, a unique advantage of the large dataset obtained. The major advance here is exploring the transcriptional profile in the ventral midbrain of animals treated with 6-OHDA, highlighting potential candidate genes that may influence vulnerability. This approach could be generalizable to investigate how various experiences and insults alter unique cell subtypes in the midbrain, providing valuable information about how these stimuli impact DA cell biology and which cells may be the most strongly affected.

Overall, the manuscript is relatively heavy on characterization and comparatively light on functional interpretation of findings. This limits the impact of the proposed work. It also isn't clear what the vulnerability factors may be in the neurons that die. Beyond the characterization of which neurons die - what is the reason that these neurons are susceptible to lesion? Also, the interpretation of these findings is going to be limited by the fact that 6-OHDA is an injectable, and the effects depend on the accuracy of injection targeting and the equal access of the toxin to access all cell populations. Though the site of injection (MFB) should hit most/all of the forebrain-projecting DA cells, the injection sites for each animal were not characterized (and since the cells from animals were pooled, the effects of injection targeting on the group data would be hard to determine in any case).

I am also not clear why the authors don't explore more about what the genes/pathways are that differentiate these conditions and why some cells are particularly vulnerable or resilient. For example, one could run GO analyses, weighted gene co-expression network analysis, or any one of a number of analysis packages to highlight which genes/pathways may give rise to vulnerability or resilience. Since the manuscript is focused on identifying cells and gene expression profiles that define vulnerability and resilience, there is much more that could have been done with this based on the data that the authors collected.

Another limitation of this study as presented is the missed opportunity to integrate it with the rich literature on midbrain dopamine (and non-dopamine) neuron subtypes. Many subtypes have been explored, with divergent functions, and can usually be distinguished by either their projection site, neurotransmitter identity, or both. Unfortunately, the projection site does not seem to track particularly well with transcriptomic identities, aside from a few genes such as DAT or the DRD2 receptor. However, this could have been more thoroughly explored in this manuscript, either by introducing AAVretro barcodes through injection into downstream brain sites, or through existing evidence within their sequencing dataset. There are likely clear interpretations from some of that literature, some of which may be more exciting than others. For example, the authors note that vGluT2-expressing cells were part of the resilient territory. This might be because this is expressed in medially-located DA cells and not laterally-located ones, which tends to track which cells die and which don't.

It is not immediately clear why the authors used a relaxed gate for mCherry fluorescence in Figure 1. This makes it difficult to definitively isolate dopaminergic neurons - or at least, neurons with a DAT-Cre expression history. While the expression of TH/DAT should be able to give a fairly reliable identification of these cells, the reason for this decision is not made clear in the text.

Reviewer #1 (Public Review):

This manuscript from Zaman et al., investigates the role of cKit and Kit ligand in inhibitory synapse function at molecular layer interneuron (MLI) synapses onto cerebellar Purkinje cells (PC). cKit is a receptor tyrosine kinase expressed in multiple tissues, including select populations of neurons in the CNS. cKIt is activated by Kit ligand, a transmembrane protein typically expressed at the membrane of connected cells. A strength of this paper is the use of cell-specific knockouts of cKit and Kit ligand, in MLIs and PCs, respectively. In both cases, the frequency of spontaneous or miniature (in the presence of TTX) IPSCs was reduced. This suggests either a reduction in the number of functional inhibitory release sites or reduced release probability. IPSCs evoked by electrical stimulation in the molecular layer showed no change in paired-pulse ratio, indicating release probability is not changed in the cKit KO, and favoring a reduction in the number of release sites. Changes in IPSC amplitude were more subtle, with some analyses showing a decrease and others not. These data suggest that disruption of the cKit-Kit ligand complex reduces the number of functional synapses with only minor changes in synapse strength. However, immunolabelling of inhibitory synapses in cKit KO mice using VGAT and Gephyrin antibodies revealed no change in the number of puncta, but reduced size of puncta. This result is more consistent with reduced synapse strength (size) without a change in synapse number. The apparent contradiction of these results is not resolved. It would be interesting to know if immunolabeling of inhibitory synapses in Kit ligand KO mice would produce similar results.

In separate experiments, the authors used viral expression of Cre (driven by the PC-specific L7 promotor) to sparsely KO Kit ligand in PCs. In recordings from neighboring Cre+ (Kit ligand KO) and Cre - (kit ligand intact) PCs, the spontaneous IPSC frequency and amplitude were reduced. Using a similar viral approach, they also overexpressed Kit ligand in wild-type PCs. Here the results are more difficult to interpret. The frequency and amplitude of spontaneous IPSCs were significantly greater in Cre+ PCs compared to Cre- cells. However, the effect appears to be primarily due to a drastic reduction in IPSC amplitude and frequency in the control Cre- cells rather than an increase in Cre+ cells. This puzzling result is interpreted as evidence that cKit influences the proportion of synapses that are functional for neurotransmission, but not the number of release sites. Though this interpretation is not described in detail.

Overall, this paper makes great use of genetic and viral approaches to examine the function of cKit and Kit ligand at MLI-PC synapses. Measurements are generally limited to immunolabeling and spontaneous IPSC recordings, a wider variety of approaches, such as EM imaging or recording from connected MLI-PC pairs would likely provide more detail on specific pre- or postsynaptic phenotypes and more clearly determine whether the number or strength of synapses is changing.

Reviewer #2 (Public Review):

In their study, Zaman et al. demonstrate that deletion of either the receptor tyrosine kinase Kit from cerebellar interneurons or the kit ligand (KL) from Purkinje cells reduces the inhibition of Purkinje cells. They delete Kit or KL at different developmental time points, illustrating that Kit-KL interactions are not only required for developmental synapse formation but also for synapse maintenance in adult animals. The study is interesting as it highlights a molecular mechanism for the formation of inhibitory synapses in Purkinje cells.

The tools generated, such as the floxed Kit mouse line and the virus for Kit overexpression, may have broader applications in neuroscience and beyond.

However, to enhance the publication's impact and strengthen its hypotheses, conclusions, and scientific rigor, it would be beneficial to include additional experimental details, data analyses (particularly regarding the quantification of electrophysiology data), as well as methodological and textual clarifications.

One general weakness is that Kit expression is not limited to molecular layer interneurons but also extends to the Purkinje layer and Golgi interneurons. Although this expression may not conflict with the reported results, as Purkinje layer interneurons form few or no synapses onto Purkinje cells, it should be highlighted in the text (introduction and/or discussion).

In summary, the data support the hypothesis that the interaction between Kit and KL between cerebellar Molecular Layer Interneurons and Purkinje Cells plays a crucial role in promoting the formation and maintenance of inhibitory synapses onto PCs. This study provides valuable insights that could inform future investigations on how this mechanism contributes to the dynamic regulation of Purkinje cell inhibition across development and its impact on mouse behavior.

Reviewer #3 (Public Review):

Summary:<br /> Bidirectional transsynaptic signaling via cell adhesion molecules and cell surface receptors contributes to the remarkable specificity of synaptic connectivity in the brain. Zaman et al., investigate how the receptor tyrosine kinase Kit and its trans-cellular kit ligand regulate molecular layer interneuron (MLI)- Purkinje cell (PC) connectivity in the cerebellum. Presynaptic Kit is specific for MLIs, and forms a trans-synaptic complex with Kit ligand in postsynaptic PC cells. The authors begin by generating Kit cKOs via an EUCOMM allele to enable cell-type specific Kit deletion. They cross this Kit cKO to the MLI-specific driver Pax2-Cre and conduct validation via Kit IHC and immunoblotting. Using this system to examine the functional consequences of presynaptic MLI Kit deletion onto postsynaptic PC cells, they record spontaneous and miniature synaptic currents from PC cells and find a selective reduction in IPSC frequency. Deletion of Kit ligand from postsynaptic PC cells also results in reduced IPSC frequency, together supporting that this trans-synaptic complex regulates GABAergic synaptic formation or maturation. The authors then show that sparse Kit ligand overexpression in PCs decreases neighboring uninfected control sIPSCs in a potentially competitive manner.

Strengths:<br /> Overall, the study addresses an important open question, the data largely support the authors' conclusions, the experiments appear well-performed, and the manuscript is well-written. I just have a few suggestions to help shore up the author's interpretations and improve the study.

Weaknesses:<br /> The strong decrease in sIPSC frequency and amplitude in control uninfected cells in Figure 4 is surprising and puzzling. The competition model proposed is one possibility, and I think the authors need to do additional experiments to help support or refute this model. The authors can conduct similar synaptic staining experiments as in Fig S4 but in their sparse infection paradigm, comparing synapses on infected and uninfected cells. Additional electrophysiological parameters in the sparse injection paradigm, such as mIPSCs or evoked IPSCs, would also help support their conclusions.

The authors should validate KL overexpression and increased cell surface levels using their virus to support their overexpression conclusions.

Reviewer #1 (Public Review):

The authors examine the fascinating question of how T lymphocytes regulate proteome expression during the dramatic cell state change that accompanies the transition from the resting quiescent state to the activated, dividing state. Orthogonal, complementary assays for translation (RPM/RTA, metabolic labeling) are combined with polyribosome profiling and quantitative, biochemical determinations of protein and ribosome content to explore this question, primarily in the OT-I T lymphocyte model system. The authors conclude that the ratio of protein levels to ribosomes/protein synthesis capacity is insufficient to support activation-coupled T cell division and cell size expansion. The authors hint at cellular mechanisms to explain this apparent paradox, focusing on protein acquisition strategies, including emperipolesis and entosis, though these remain topic areas for future study.

The strengths of the paper include the focus on a fundamental biological question - the transcriptional/translational control mechanisms that support the rapid, dramatic cell state change that accompanies lymphocyte activation from the quiescent to activated state, the use of orthogonal approaches to validate the primary findings, and the creative proposal for how this state change is achieved.

The weakness of the work is that several cellular regulatory processes that could explain the apparent paradox are not explored, though they are accessible for experimental analysis. In the accounting narrative that the authors highlight, a thorough accounting of the cellular process inventory that could support the cell state change should be further explored before committing to the proposal, provocative as it is, that protein acquisition provides a principal mechanism for supporting lymphocyte activation cell state change.

Appraisal and Discussion:<br /> 1) relating to the points raised above, two recent review articles explore this topic area and highlight important areas of study in RNA biology and translational control that likely contribute to the paradox noted by the authors: Choi et al. 2022,<br /> doi.org/10.4110/in.2022.22.e39 ("RNA metabolism in T lymphocytes") and Turner 2023, DOI: 10.1002/bies.202200236 ("Regulation and function of poised mRNAs in lymphocytes"). These should be cited, and the broader areas of RNA biology discussed by these authors integrated into the current manuscript.

2) The authors cite the Wolf et al. study from the Geiger lab (doi.org/10.1038/s41590-020-0714-5, ref. 41) though largely to compare determined values for ribosome number. Many other elements of the Wolf paper seem quite relevant, for example, the very high abundance of glycolytic enzymes (and whose mRNAs are quite abundant as well), where (and as others have reported) there is a dramatic activation of glycolytic flux upon T cell activation that is largely independent of transcription and translation, the evidence for "pre-existing, idle ribosomes", the changes in mRNA copy number and protein synthesis rate Spearman correlation that accompanies activation, and that the efficiencies of mRNA translation are heterogeneous. These data suggest that more accounting needs to be done to establish that there is a paradox.

As one example, what if glycolytic enzyme protein levels in the resting cell are in substantial excess of what's needed to support glycolysis (likely true) and so translational upregulation can be directed to other mRNAs whose products are necessary for function of the activated cell? In this scenario, the dilution of glycolytic enzyme concentration that would come with cell division would not necessarily have a functional consequence. And the idle ribosomes could be recruited to key subsets of mRNAs (transcriptionally or post-transcriptionally upregulated) and with that a substantial remodeling of the proteome (authors ref. 44). The study of Ricciardi et al. 2018 (The translational machinery of human CD4+ T cells is poised for activation and controls the switch from quiescence to metabolic remodeling (doi.org/10.1016/j.cmet.2018.08.009) is consistent with this possibility. That study, and the short reviews noted above, are useful in highlighting the contributions of selective translational remodeling and the signaling pathways that contribute to the cell state change of T cell activation. From this perspective, an alternative view can be posited, where the quiescent state is biologically poised to support activation, where subsets of proteins and mRNAs are present in far higher levels than that necessary to support basal function of the quiescent lymphocyte. In such a model, the early stages of lymphocyte activation and cell division are supported by this surplus inventory, with transcriptional activation, including ribosomal genes, primarily contributing at later stages of the activation process. An obvious analogy is the developing Drosophila embryo where maternal inheritance supports early-stage development and zygotic transcriptional contributions subsequently assuming primary control (e.g. DOI 10.1002/1873-3468.13183 , DOI: 10.1126/science.abq4835). To pursue that biological logic would require quantifying individual mRNAs and their ribosome loading states, mRNA-specific elongation rates, existing individual protein levels, turnover rates of both mRNAs and proteins, ribosome levels, mean ribosome occupancy state, and how each of these parameters is altered in response to activation. Such accounting could go far to unveil the paradox. This is a considerable undertaking, though, and outside the scope of the current paper.

Reviewer #2 (Public Review):

This paper takes a novel look at the protein economy of primary human and mouse T-cells - in both resting and activated state. Their findings in primary human T-cells are that:

1. A large fraction of ribosomes are stalled in resting cultured primary human lymphocytes, and these stalled ribosomes are likely to be monosomes.<br /> 2. Elongation occurs at similar rates for HeLa cells and lymphocytes, with the active ribosomes in resting lymphocytes translating at a similar rate as fully activated lymphocytes.

They then turn their attention to mouse OT-1 lymphocytes, looking at translation rates both in vitro and in vivo. Day 1 resting T-cells also show stalling - which curiously wasn't seen on freshly purified cells - I didn't understand these differences.

In vivo, they show that it is possible to monitor accurate translation and measure rates. Perhaps most interestingly they note a paradoxically high ratio of cellular protein to ribosomes insufficient to support their rapid in vivo division, suggesting that the activated lymphocyte proteome in vivo may be generated in an unusual manner.

This was an interesting and provocative paper. Lots of interesting techniques and throwing down challenges to the community - it manages to address a number of important issues without necessarily providing answers.

Reviewer #3 (Public Review):

This manuscript provides a more or less quantitative analysis of protein synthesis in lymphocytes. I have no issue with the data as presented, as I'm sure all measurements have been expertly done. I see no need for additional experimental work, although it would be helpful if the authors could comment on the possibility of measuring the rate of synthesis of a defined protein, say a histone, in cells prior to and after activation. The conclusion the authors leave us with is the idea that the rates of protein synthesis recorded here are incompatible with observed rates of T cell division in vivo. Indeed, in the final paragraph of the discussion, the authors note the mismatch between what they consider a requirement for cell division, and the observed rates of protein synthesis. They then invoke unconventional mechanisms to make up for the shortfall, without -in this reviewer's opinion- discussing in adequate detail the technical limitations of the methodology used.

A key question is the broad interest, novelty, and extension of current knowledge, in comparison with Argüello's (reference 27) 'SunRise' method. It would be helpful for the authors to stake out a clear position as to the similarities and differences with reference 27: what have we learned that is new? The authors could cite reference 27 in the introduction of their manuscript, given the similarity in approach. That said, the findings reported here will generate further discussion.

The manuscript would increase in impact if the authors were to clearly define why a particular measurement is important and then show the actual experiment/result. As an example, it would be helpful to explain to the non-expert why the distinction between monosomes, polysomes, and stalled versions of the same is important, and then explain the rationale of the actual experiment: how can these distinctions be made with confidence, and what are confounding variables? The initial use of human cells, later abandoned in favor of the OT-1 in vitro and in vivo models, requires contextualization. If the goal is to address the relationship between rates of translation and cell division of antigen-activated T cells in vivo, then a lot of the work on the human model and the in vitro experiments becomes more of a distraction, unless properly contextualized. Is there any reason to assume that antigen-specific activation in vivo will impact translation differently than the use of the PMA/ionomycin/IL2 cocktail? The way the work is presented leaves me with the impression that everything that was done is included, regardless of whether it goes to the core of the question(s) of interest.

It would be helpful if the authors made explicit some of the assumptions that underlie their quantitative comparisons. Likewise, the authors should discuss the limitations of their methods and provide alternative interpretations where possible, even if they consider them less/not plausible, with justification. As they themselves note, improvements in the RPM protocols raised the increase in translating ribosomes upon activation from 10-fold to 15-fold. Who's to say that is the best achievable result? What about the reliability/optimization of the other measurements?

The composition of the set of proteins produced upon activation will differ from cell to cell (CD4, CD8, B, resting vs. dividing). Even if analyses are performed on fixed cells, the ability of the monoclonal anti-puromycin antibody to penetrate the matrix of the various fixed cell types may not be equal for all of them, depending on protein composition, susceptibility to fixation etc. Is it possible for puromycin to occupy the ribosome's A site and terminate translation without forming a covalent bond with the nascent chain? This could affect the staining with anti-puromycin antibodies and also underestimate the number of nascent chains.

I believe that the concept of FACS-based quantitation also requires an explanation for the non-expert. For the FACS plots shown, the differences between the highest and lowest RPM scores for cells that divided and that have a similar CFSE score is at least 10-fold. Does that mean that divided cells can differ by that margin in terms of the number of nascent chains present? If I make the assumption that cells stimulated with PMA/ionomycin/IL2 respond more or less synchronously, why would there be a 10-fold difference in absolute fluorescence intensity (anti=puromycin) for randomly chosen cells with similar CFSE values? While the use of MFI values is standard practice in cytofluorimetry, the authors should devote some comments to such variation at the population level.

It is assumed that for cells to complete division, they must have produced a full and complete copy of their proteome and only then divide. What if cells can proceed to divide even when expressing a subset of the proteome of departure (=the threshold set required for initiation of division), only to complete synthesis of the 'missing ' portion once cell division is complete? Would this obviate the requirement for an unusual mechanism of protein acquisition (trogocytosis; other)?

Translation is estimated to proceed at a rate of ~6 amino acids per second, but surely there is variability in this number attributable to inaccuracies of the methods used, in addition to biological variability. Were these so-called standard values determined for a range of different tissues? It stands to reason that there might be variation depending on the availability of initiation/elongation factors, NTPs, aminoacyl tRNAs etc. What is the margin of error in calculating chain elongation rates based on the results shown here?

Reviewer #1 (Public Review):

The manuscript by Geurrero and colleagues introduces two new metrics that extend the concept of "druggability"- loosely speaking, the potential suitability of a particular drug, target, or drug-target interaction for pharmacological intervention-to collections of drugs and genetic variants. The study draws on previously measured growth rates across a combinatoriality complete mutational landscape involving 4 variants of the TEM-50 (beta lactamase) enzyme, which confers resistance to commonly used beta-lactam antibiotics. To quantify how growth rate - in this case, a proxy for evolutionary fitness - is distributed across allelic variants and drugs, they introduce two concepts: "variant vulnerability" and "drug applicability".

Variant vulnerability is the mean vulnerability (1-normalized growth rate) of a particular variant to a library of drugs, while drug applicability measures the mean across the collection of genetic variants for a given drug. The authors rank the drugs and variants according to these metrics. They show that the variant vulnerability of a particular mutant is uncorrelated with the vulnerability of its one-step neighbors, and analyze how higher-order combinations of single variants (SNPs) contribute to changes in growth rate in different drug environments.

The work addresses an interesting topic and underscores the need for evolution-based metrics to identify candidate pharmacological interventions for treating infections. The authors are clear about the limitations of their approach - they are not looking for immediate clinical applicability - and provide simple new measures of druggability that incorporate an evolutionary perspective, an important complement to the orthodoxy of aggressive, kill-now design principles. I think the ideas here will interest a wide range of readers, but I think the work could be improved with additional analysis - perhaps from evolutionary simulations on the measured landscapes - that tie the metrics to evolutionary outcomes.

Reviewer #2 (Public Review):

The authors introduce the notions of "variant vulnerability" and "drug applicability" as metrics quantifying the sensitivity of a given target variant across a panel of drugs and the effectiveness of a drug across variants, respectively. Given a data set comprising a measure of drug effect (such as growth rate suppression) for pairs of variants and drugs, the vulnerability of a variant is obtained by averaging this measure across drugs, whereas the applicability of a drug is obtained by averaging the measure across variants.

The authors apply the methodology to a data set that was published by Mira et al. in 2015. The data consist of growth rate measurements for a combinatorially complete set of 16 genetic variants of the antibiotic resistance enzyme beta-lactamase across 10 drugs and drug combinations at 3 different drug concentrations, comprising a total of 30 different environmental conditions. For reasons that did not become clear to me, the present authors select only 7 out of 30 environments for their analysis. In particular, for each chosen drug or drug combination, they choose the data set corresponding to the highest drug concentration. As a consequence, they cannot assess to what extent their metrics depend on drug concentration. This is a major concern since Mira et al. concluded in their study that the differences between growth rate landscapes measured at different concentrations were comparable to the differences between drugs. If the new metrics display a significant dependence on drug concentration, this would considerably limit their usefulness.

As a consequence of the small number of variant-drug combinations that are used, the conclusions that the authors draw from their analysis are mostly tentative with weak statistical support. For example, the authors argue that drug combinations tend to have higher drug applicability than single drugs, because a drug combination ranks highest in their panel of 7. However, the effect profile of the single drug cefprozil is almost indistinguishable from that of the top-ranking combination, and the second drug combination in the data set ranks only 5th out of 7.

To assess the environment-dependent epistasis among the genetic mutations comprising the variants under study, the authors decompose the data of Mira et al. into epistatic interactions of different orders. This part of the analysis is incomplete in two ways. First, in their study, Mira et al. pointed out that a fairly large fraction of the fitness differences between variants that they measured were not statistically significant, which means that the resulting fitness landscapes have large statistical uncertainties. These uncertainties should be reflected in the results of the interaction analysis in Figure 4 of the present manuscript. Second, the interpretation of the coefficients obtained from the epistatic decomposition depends strongly on the formalism that is being used (in the jargon of the field, either a Fourier or a Taylor analysis can be applied to fitness landscape data). The authors need to specify which formalism they have employed and phrase their interpretations accordingly.

Reviewer #3 (Public Review):

The authors introduce two new concepts for antimicrobial resistance borrowed from pharmacology, "variant vulnerability" (how susceptible a particular resistance gene variant is across a class of drugs) and "drug applicability" (how useful a particular drug is against multiple allelic variants). They group both terms under an umbrella term "drugability". They demonstrate these features for an important class of antibiotics, the beta-lactams, and allelic variants of TEM-1 beta-lactamase.

The strength of the result is in its conceptual advance and that the concepts seem to work for beta-lactam resistance. However, I do not necessarily see the advance of lumping both terms under "drugability", as this adds an extra layer of complication in my opinion.

I also think that the utility of the terms could be more comprehensively demonstrated by using examples across different antibiotic classes and/or resistance genes. For instance, another good model with published data might have been trimethoprim resistance, which arises through point mutations in the folA gene (although, clinical resistance tends to be instead conferred by a suite of horizontally acquired dihydrofolate reductase genes, which are not so closely related as the TEM variants explored here).

The impact of the work on the field depends on a more comprehensive demonstration of the applicability of these new concepts to other drugs.

Reviewer #1 (Public Review):

Papazian et al. demonstrate that human peripheral blood mononuclear cells (PBMCs) can be successfully and stably grafted into immunodeficient mice. They demonstrate that the adoptive transfer of PBMCs from multiple sclerosis (MS) patients is capable of inducing damage to the central nervous system (CNS). Furthermore, they demonstrate that the CNS inflammatory properties of these transferred cells are more dependent on HLA restriction rather than the disease status of the donor. Specifically, T cells restricted by HLA-DR15 (from both an MS patient and a healthy control) showed a greater propensity to induce neuroinflammation than T cells transferred from an MS patient that are restricted by a different MHC haplotype. This observation suggests that the differences in the peptide repertoire presented by this MHC haplotype biases adaptive immune responses toward encephalitogenic T cell generation. The conclusions of this paper are partially supported by their data, but the lack of important considerations and various controls limits the overall impact of this study. Major weaknesses of this study include:

1) The extent to which various immune cell quantification is performed. Two of the reasons the authors cite for the use of this model rather than a traditional EAE model are: i) the lack of involvement of CD8 T cells in the pathogenesis of EAE and ii) the marginal importance of B cells in EAE pathogenesis. However, throughout their paper, the authors never quantify the difference in CD4 vs CD8 T cell infiltration into the CNS. While repeatedly claiming that there are fewer CD4 T cells present than CD8 T cells within the CNS, this data is not included. Further, spinal cord numbers of CD4 and CD8 are not provided in lieu of CD3 T cell characterization. Given that there are far more hCD4 T cells in the periphery in these mice than CD8 T cells as well as the fact that the lack of B2m expression in this mouse model biases cells towards a CD4 fate, the omission of these data is concerning. Additionally, B cells don't make up any significant component of the cells transferred from HLA-DR15 donors. While the cells transferred from the HLA-DR13 donor are composed of a considerable number of B cells, the mice that received these cells didn't develop any signs of neurologic disease.

2) Incomplete exploration of potential experimental autoimmune encephalomyelitis (EAE) modeling. The authors justify the use of an extremely high amount of myelin peptide when immunizing their mice by citing that another humanized mouse model had such a requirement to induce clinical EAE. However, a demonstration of this technical requirement in their own model is not provided. Rather, they show that C57BL/6 mice get milder disease when such large doses of peptides are administered, leading to speculation that this is due to a tolerizing immune response that occurs at such high doses. Comparison of the susceptibility of B2m-NOG mice to EAE dependent on various peptide doses would be highly informative. Given that the number of hCD45+ in the periphery of NOG mice decreases following this immunization it would be prudent for the authors to determine if such a high peptide dose is truly ideal for EAE development in this mouse model.

3) The degree of myelin injury is not presented. The statement is repeatedly made that "demyelination was not observed in the brain or spinal cord" but no quantification of myelin staining is shown. A central feature of multiple sclerosis and related diseases is demyelination of the CNS. Hence, while compartmentalized inflammatory responses are detailed in this report, the utility of the humanized model for the exploration of human CNS demyelinating diseases remains unclear and in doubt.

Minor points:

- Method of quantification (e.g. cells per brain slice in figures 2E; 4E) is not very quantitative and should be justified or more appropriately updated to be more rigorous in methodology.

- Fig. 4 data should be shown from un-immunized DR15 MS and DR15 HI mice.

The premise of this work carries great potential. Namely, developing a humanized mouse system in which features of adaptive immunity that contribute to inflammatory demyelination can be interrogated will allow for traction into therapeutics currently unavailable to the field. Immediate questions stemming from the current study include the potential effect of ex vivo activation of PBMCs (or individual T and B cells) in vitro prior to transfer as well as the TCR and BCR repertoire of CNS vs peripheral lymphocytes before and after immunization. This group has been thoughtful and clever about their approach (e.g. use of subjects treated with natalizumab), which gives hope that fundamental aspects of pathogenesis will be uncovered by this form of modeling MS disease. Overall, while the current study makes several unique observations, the data collection is incomplete and the impact of this study could be greatly improved by addressing the limitations noted.

Reviewer #2 (Public Review):

Multiple sclerosis is an inflammatory and demyelinating disease of the central nervous system where immune cells play an important role in disease pathobiology. Increased incidence of disease in individuals carrying certain HLA class-II genes plus studies in animal models suggests that HLA-DRB1*15 restricted CD4 T cells might be responsible for disease initiation, and other immune cells such as B cells, CD8 T cells, monocytes/macrophages, and dendritic cells (DC) also contribute to disease pathology. However, a direct role of human immune cells in disease is lacking to a lag between immune activation and the first sign of clinical disease. Therefore, there is an emphasis on understanding whether immune cells from HLA-DR15+ MS patients differ from HLA-DR15+ healthy controls in their phenotype and pro-inflammatory capacity. To overcome this, authors have used severely immunodeficient B2m-NOG mice that lack B, T cells, and NK cells and have defective innate immune responses and engrafted PBMCs from 3 human donors (HLA-DR15+ MS and HI donors, HLA-DR13+ MS donor) in these B2m-NOG mice to determine whether they can induce CNS inflammation and demyelination like MS.<br /> The study's strength is the use of PBMCs from HLADRB1-typed MS subjects and healthy control, the use of NOG mice, the characterization of immune subsets (revealing some interesting observations), CNS pathology etc. The major weaknesses are i) lack of sufficient sample size (n=1 in each group) to make any conclusion, ii) lack of phenotype in mice, iii) no disease phenotype even in humanized mice immunized for disease using standard disease induction protocol employed in an animal model of MS, and iv) mechanistic data on why CD8 T cells are more enriched than CD4+ T cells. The last point is very important as postmortem human MS patients' brain tissue had been shown to have more CD8+ T cells than CD4+ T cells.

Thus, this work is an important step in the right direction as previous humanized studies have not used HLA-DRB1 typed PBMCs however the weaknesses as highlighted above make the findings incremental to the field.

Reviewer #1 (Public Review):

In the manuscript entitled "A theory of hippocampal theta correlations", the authors propose a new mechanism for phase precession and theta-time scale generation, as well as their interpretation in terms of navigation and neural coding. The authors propose the existence of extrinsic and intrinsic sequences during exploration, which may have complementary functions. These two types of sequences depend on external input and network interactions, but differ on the extent to which they depend on movement direction. Moreover, the authors propose a novel interpretation for intrinsic sequences, namely to signal a landmark cue that is independent of direction of traversal. Finally, a readout neuron can be trained to distinguish extrinsic from intrinsic sequences.

The study puts forward novel computational ideas related to neural coding, partly based on previous work from the authors, including published (Leibold, 2020, Yiu et al., 2022) and unpublished (Ahmedi et al., 2022. bioRxiv) work. The manuscript will contribute to the understanding of the mechanisms behind phase precession, as well as to how we interpret hippocampal temporal coding for navigation and memory.

Reviewer #2 (Public Review):

Place cells fire sequentially during hippocampal theta oscillations, forming a spatial representation of behavioral experiences in a temporally-compressed manner. The firing sequences during theta cycles are widely considered as essential assemblies for learning, memory, and planning. Many theoretical studies have investigated the mechanism of hippocampal theta firing sequences; however, they are either entirely extrinsic or intrinsic. In other words, they attribute the theta sequences to external sensorimotor drives or focus exclusively on the inherent firing patterns facilitated by the recurrent network architectures. Both types of theories are inadequate for explaining the complexity of the phenomena, particularly considering the observations in a previous paper by the authors: theta sequences independent of animal movement trajectories may occur simultaneously with sensorimotor inputs (Yiu et al., 2022).

In this manuscript, the authors concentrate on the CA3 area of the hippocampus and develop a model that accounts for both mechanisms. Specifically, the model generates extrinsic sequences through the short-term facilitation of CA3 cell activities, and intrinsic sequences via recurrent projections from the dentate gyrus. The model demonstrates how the phase precession of place cells in theta sequences is modulated by running direction and the recurrent DG-CA3 network architecture. To evaluate the extent to which firing sequences are induced by sensorimotor inputs and recurrent network architecture, the authors use the Pearson correlation coefficient to measure the "intrinsicity" and "extrinsicity" of spike pairs in their simulations.

I find this research topic to be both important and interesting, and I appreciate the clarity of the paper. The idea of combining intrinsic and extrinsic mechanisms for theta sequences is novel, and the model effectively incorporates two crucial phenomena: phase precession and directionality of theta sequences. I particularly commend the authors' efforts to integrate previous theories into their model and conduct a systematic comparison. This is exactly what our community needs: not only the development of new models, but also understanding the critical relationships between different models.

Reviewer #2 (Public Review):

The manuscript by Elfstrom et al describes the impact of implementing self-sampling as the primary screening test in Sweden to address decreases in coverage following the COVID pandemic. The authors have a very rich dataset including all records of invitations to screen and screening results in the Stockholm area. A limitation is that there is no individual record linkage to allow investigation of the profile of the individuals who chose to screen using the self-sample.

The conclusions are generally well supported by the authors with the following exceptions:

1) There was not enough evidence presented in the manuscript to conclude that "The most likely explanation for the large increase in population coverage seen is that the sending of self-sampling kits resulted in improved attendance in particular among previously non-attending women."

2) The authors state there is no evidence that delays in screening have impacted cervical cancer rates however they present no data to this effect in the manuscript.

Reviewer #2 (Public Review):

In this article, Moses and Harel present genetic knock-out and partial rescue of the phenotypes of neuropeptides gh1 and fshb, and tshb in a short-lived vertebrate African turquoise killifish Nothobranchius furzeri. Neuropeptides are among the key regulators of growth, reproduction, and metabolism. Understanding their mechanisms of action has important implications for vertebrate physiology.

The authors first characterize the loss of function phenotypes of gh1, fshb, and tshb in killifish, followed by attempts to rescue the loss of function phenotypes through ectopic expression of two of the neuropeptides. The primary strength and innovation of this work are partially rescuing the phenotypes by muscular injection of plasmids followed by electroporation, including a doxycycline-inducible system for tunable expression control. The techniques for tunable expression control and rescue of knock-out phenotypes have not been established for killifish and will be useful to expand the technical repertoire of this emerging model organism. Once established, these techniques can be extended to other categories of genes to rapidly evaluate their function and the impact of their loss or gain of function on killifish and other fish models.

However, the phenotypes discussed need further characterization, many technical details are unclear, and it seems that appropriate controls are missing for some of the experiments. The rescued phenotypes also need more validation.

Reviewer #3 (Public Review):

This manuscript describes the development of CRISPR knockouts for gh, fsh and tsh in the fast-aging Nothobranchius furzeri grz strain. CRISPR knockouts have been published before, and the strength of the paper is that here, the authors include a novel, easy and fast way of rescuing the loss of function in the entire body by electroporation in muscle. This offers flexibility in timing and dosage, and leads to intriguing results regarding the role of these hormones in growth and fertility. Finally they also add a conditional doxycycline-dependent overexpression model that would allow even more control over the modalities of the rescue. The phenotypes of the knockouts were not the key message of the paper and remained at times only superficially described. The doxycycline-dependent overexpression was only minimally validated, and here it is not yet clear how robust this system is in terms of overexpression levels, timing, and reversibility.

Overall this study brings a new set of tools in the killifish toolbox that can have much wider applications and will be appreciated also in other teleost models.

Reviewer #2 (Public Review):

This article focuses on drug resistance acquired by Plasmodium falciparum malaria parasites that have been pressured with different inhibitors of the essential enzyme DHODH (dihydroorotate dehydrogenase). The study focuses on collateral sensitivity between DSM265, which has been evaluated in a human clinical trial and found to select for resistance via the point mutation C276Y (C276F and G181S were also implicated; PMID 29909069), and the GSK compound TMCDC-125334, against which a panel of DHODH mutant parasites (including C276Y) were found to have increased sensitivity. The authors herein explore this case of "collateral sensitivity" by examining whether these two inhibitors, when used simultaneously, might preclude the selection of resistant parasites. The answer, in this case, is no; collateral sensitivity did not prevent parasites from acquiring a novel mutation (V532A) that mediated resistance to both. Culture competition assays provide evidence that this mutant retains normal fitness. The authors conclude that for this target the idea of combining these inhibitors is not a viable therapeutic strategy. The authors also illustrate how TMCDC-125334 can select for resistance via a separate mutation (I263S) or amplification of a chromosomal segment containing dhodh. They also present modeling data to examine binding poses and how mutations could impact drug binding, which is allosteric to the enzyme's substrates (orotate and FMN). The data are thorough and provide convincing evidence that in this case collateral sensitization by distinct chemotypes does not translate into a viable strategy to inhibit DHODH in a way that can preclude mutations that confer cross-resistance.

Reviewer #1 (Public Review):

This well written and designed study by Broca-Brisson et al describes the generation of a new in vitro model for creatine transporter deficiency (CTD), making use of human brain organoid cultures derived from CTD patients. This new model will certainly prove itself very useful to better understand this genetic disease essentially affecting CNS. As CTD has no satisfactory treatment so far (despite more than 20 years of research), this new model will also be very useful to design and develop new treatments.

In particular, through the use of immunohistochemistry, real time PCR, and proteomics combined with integrative bioinformatic and statistical analysis, authors provide very interesting new information on the brain pathways affected in CTD (e.g. neurogenesis with down-regulation of SOX2 and PAX6 but up-regulation of GSK3b; and proteins involved in autistic spectrum, epilepsies or intellectual disabilities).

Reviewer #2 (Public Review):

In their recent manuscript, Broca-Brisson et al. deliver a multidisciplinary approach to investigate creatine transporter deficiency (CTD) using human-derived brain organoids. The authors have provided a compelling CTD human brain organoid model using induced pluripotent stem cells (iPSCs) derived from individuals with CTD. This model shows distinct differences in creatine uptake between organoids originating from CTD patients and their healthy counterparts. Furthermore, the researchers effectively restored creatine uptake by reintroducing the wild-type CRT in the iPSCs.

The team used advanced molecular biology techniques and sophisticated mass spectrometry to identify changes in protein regulation within these CTD brain organoids. They propose an intriguing theory linking reduced creatine uptake to abnormalities in the GSK3β kinase pathway and mitochondrial function, which might underlie intellectual disability seen in CTD patients.<br /> This study is well-structured and easy to follow, with clear and concise explanations of the experiments. The authors present an important idea: a dysfunction in just one protein transporter (CRT) can cause significant biochemical changes in the brain. Their findings are well-presented and backed by high-quality figures and comprehensive data analysis.

There are only minor suggestions for improvement in this manuscript. The authors strongly link creatine uptake, the GSK3β pathway, and intellectual disability. Enhancing this claim with data on phosphorylation differences between organoids derived from healthy individuals and those from CTD patients could solidify this foundation and facilitate a more holistic understanding of the disease. In addition, the in vitro model based on organoids might be closer than other experimental setups; however, proving that those differences are also present in vivo would greatly benefit the story.

There is also some uncertainty around the rescue experiment using the exogenous SLC6A8 gene. Could the difference in creatine uptake between the rescue iPSCs and the healthy control be due to CRT overexpression? Higher levels of the transporter may explain the elevated levels of intracellular creatine. Thus, a comparison using Western blotting experiments could be a valuable addition to evaluating the expression levels of this protein.

Overall, this study provides valuable insights into CTD and potential therapeutic targets. It enriches our understanding of CTD and opens up new avenues for future research in this field.

Reviewer #1 (Public Review):

The authors were seeking to improve understanding of how wind and wave action affect the use of energetically demanding wing flapping and running by albatross engaged in takeoff flight. To accomplish this in the complex and challenging environment in which albatross live, the authors sought to use accelerometry and geographic positioning to infer patterns of locomotion, flight orientation relative to the prevailing wind, and wave height during takeoff.

The major strength of the methods and results is that the use of accelerometry and novel interpretations of data from a geographic positioning system provides new insight into the use of waves by albatross and how the effects of wave magnitude interact with the wind to modulate energy demands during takeoff. Weaknesses of the approach are due to the challenging environmental conditions in which albatross live. The interpretation of accelerometry data was not validated using a subset of the sample synchronized with video (prior validation was cited for shearwaters). The interpretation of wind direction relative to flight path is based on the behavior of the bird without concurrent measures of local wind velocity.

The authors achieved their aims, and their results support their conclusions.

Although it is generally understood that albatross and many other birds choose to takeoff into the wind to reduce energetic costs, the authors provide novel quantitative data on this behavior. Their results on the effects of wave height and the interactions between wave height and wind provide novel insight into how albatross harvest energy from their complicated and dynamic environment to reduce the energy they must output to get into the air. In particular, the new insight into the effects of wave height should revise understanding among ornithologists, ocean ecologists and those who study the mechanics of animal locomotion. The use of accelerometry and geographic positioning systems to measure flight behavior and ocean ecology should inspire other researchers to adopt similar methods.

Albatross live in a complex and poorly understood environment that is likely to be threatened by climate change. This research provides worthwhile new insight into how wind and wave action affect takeoff in albatross, and can therefore improve insight into how changes in these variables with climate change may affect the distribution of albatross populations.

Reviewer #2 (Public Review):

The authors used cutting-edge bio-telemetry technology to decipher the roles of wind speed and wave height on the take-off of albatrosses from the water surface. They revealed that each of these factors contributes to take-off in a unique way with interesting interactions of the two factors. The authors achieved their objectives and their results support their conclusions. This work will set new standards in integrating information about bird movement and environmental conditions experienced by the bird in a comprehensive, integrative and hypothesis-driven framework. The approach of the authors is highly advanced, providing heuristic insights for many additional systems where organisms are influenced by, and respond to small-scale environmental conditions.

Reviewer #3 (Public Review):

The present study used novel data logging devices to record the foraging behavior of wandering albatrosses. Specifically, the authors showed how localized winds and wave heights influence their ability to take off from the sea surface, which is the most expensive behavior they engage in while foraging. There is no better platform for this initial work because these birds are so large, the equipment they can carry without creating significant impact is tremendous.

The results were impressive, presented well, and the paper was generally written in an accessible way to readers with less knowledge. The authors provide a convincing set of results that support the aims and conclusions. The theory and application could be used to inform our understanding of flight behavior in other seabirds.

Although the idea of taking off from the sea surface may sound trivial, it is essential to understand that albatrosses and other soaring seabirds have wings that are adapted for soaring (i.e. long and narrow). The trade off, however, is that powered flight through wing flapping is energetically expensive because the wings have a shallow amplitude and generate less power compared to a shorter, wider wing. Thus, wind is everything and this study shows how wind facilitates the ability of the birds to gain flight using wind and waves. Awesome!