Reviewer #3 (Public Review):

Kang, Huang, and colleagues have provided new data to address concerns regarding confirmation of LRRK1 and LRRK2 deletion in their mouse model and the functional impact of the modest loss of TH+ neurons observed in the substantia nigra of their double KO mice. In the revised manuscript, the new data around the characterization of the germline-deleted LRRK1 and LRRK2 mice add confidence that LRRK1 and LRRK2 can be deleted using the genetic approach. They have also added new text to the discussion to try and address some of the comments and questions raised regarding how LRRK1/2 loss may impact cell survival and the implications of this work for PD-linked variants in LRRK2 and therapeutic approaches targeting LRRK2. The new data provides additional support for the author's claims.

eLife assessment

This important study identifies candidate mitochondrial metabolite carriers in stramenopile protists that may allow these divergent eukaryotes to maintain a compartmentalized glycolytic pathway. This study fills a gap in our understanding of glycolysis evolution and opens avenues for drug design to combat stramenopile parasites. The evidence, based on phylogenetic analysis, thermostability shift assays, and in vitro reconstitution of transport reactions, is convincing, albeit lacking direct in vivo confirmation of the physiological function of these candidates.

Reviewer #1 (Public Review):

Summary

This study identifies a family of solute transports in the enteric protist, Blastocystis, that may mediate the transport of glycolytic intermediates across the mitochondrial membrane. The study builds on previous observations suggesting that Blastocystis (and other Stramenopiles) are unusual in having a compartmentalized glycolytic pathway with enzymes involved in upper and lower glycolysis being located in the cytosol and mitochondria, respectively. In this study, the authors identified two putative Stamenopile metabolite transporters that are related to plant di/tricarboxylic acid transporters that might mediate the transport of glycolytic intermediates across the mitochondrial membrane. These GIC-transporters were localized to the Blastocystis mitochondrion using specific rabbit antibodies and shown to bind several glycolytic intermediates (including GAP, DHAP and PEP) based on thermostability shift assays. Direct evidence for transport activity was obtained by reconstituting native proteins in proteoliposomes and measuring uptake of 14C-malate or 35S-sulphate against unlabelled substrates. This assay showed that GIC-2 transported DHAP, GAP and PEP. However, significant transport activity was not observed for bGIC-2. Overall, the study provides strong, but not conclusive evidence that bGIC-2 is involved in transporting glycolytic intermediates across the inner membrane of the mitochondria, while the function of GIC-1 remains unclear, despite exhibiting the same metabolite binding properties as bGIC-2 n thermostability assays.

Strengths:

Overall, the findings are of interest in the context of understanding the diversity of core metabolic pathways in evolutionarily diverse eukaryotes, as well as the process by which cytosolic glycolysis evolved in most eukaryotes. The experiments are carefully performed and clearly described.

Weaknesses:

The main weakness of the study is the lack of direct evidence that either bGIC-1 and/or bGIC2 are active in vivo. While it is appreciated that the genetic tools for disrupting GIC genes in Blastocystis are limited/lacking, are there opportunities to ectopically express or delete these genes in other genetically tractable Stamenopiles, such as Phaeodactylum triconuteum?

The authors demonstrate that both bGIC-1 and bGIC-2 are targeted to the mitochondrion, based on immunofluorescence studies. However, the precise localization and topology of these carriers in the inner or outer membrane is not defined. The conclusions of the study would be strengthened if the authors could show that one/both transporters are present in the inner membrane using protease protection experiments following differential solubilization of the outer and inner mitochondrial membranes.

It is not clear why hetero-exchange reactions were not performed for bGIC-1 (only for bGIC-2).

In both their previous study (Bartulos et al (2018) and the current study, the authors have shown that Blastocystis express a TPI-GAPDH fusion protein which is located to the mitochondrion. The presence of the TPI domain in the mitochondrial matrix would obviate the need for bGIC-1/2 triose transporters and decrease their value as drug targets. It is noted that Blastocystis still retains some TPI activity in the cytosol, presumably due to expression of a second cytoplasmic isoform, which could account for the presence of the bGIC transporters. However, some discussion on the role of this mitochondrial TPI-GAPDG fusion protein in Blastocystis and other Stramenopiles would be useful.

The summary slide (Fig 7) in the revised manuscript no longer shows PEP being used as a countersolute for the import of G3P and DHAP. Although it complicates the story, the role of PEP as a counter solute should be shown for completeness and also to make sense of some of the statements in the discussion. In particular, as noted by the authors, mitochondrial PEP could be exported back to the cytsol and converted to pyruvate and/or lactate to generate ATP and NAD, although at the expense of ATP synthesis in the mitochondria.

Reviewer #2 (Public Review):

In this manuscript, the authors set out to identify transporters that must exist in Stramenophiles due to the fact that the second half of glycolysis appears to be conducted in the mitochondria. They hypothesize that a Stramenophile-specific clade of transporters related to the dicarboxylate carriers are likely the relevant family and then go on to test two proteins from Blastocystis due to the infectious disease relevance of this organism. They show rather convincingly that these two proteins are expressed and are localized to the mitochondria in the native organism. The purified proteins bind to glycolytic intermediates and one of them, GIC-2, transports several glycolytic intermediates in vitro. This is a very solid and well-executed study that clearly demonstrates that bCIC-2 can transport glycolytic intermediates.

(1) The major weakness is that the authors aren't able to show that this protein actually has this function in the native organism. This could be impossible due to the lack of genetic tools in Blastocystis, but it leaves us without absolute confidence that bGIC-2 is the important glycolytic intermediate mitochondrial transporter (or even that it has this function in vivo).

(2) My impression is that the authors under-emphasize the fact that the hDIC also binds (and is stabilized by) glycolytic intermediates (G3P and 3PG). In the opinion of this reviewer, this might change my interpretation about the uniqueness of the bGIC proteins. They act on additional glycolytic intermediates, but it's not unique.

Reviewer #3 (Public Review):

Summary:

Unlike most eukaryotes Blastocystis has a branched glycolysis pathway, which is split between the cytoplasm and the mitochondrial matrix. An outstanding question was how the glycolytic intermediates generated in the 'preparatory' phase' are transported into the mitochondrial matrix for the 'pay off' phase. Here, the authors use bioinformatic analysis to identify two candidate solute carrier genes, bGIC-1 and bGIC-2, and use biochemical and biophysical methods to characterise their substrate specificity and transport properties. The authors demonstrate that bGIC-2 can transport dihydroxyacetone phosphate, glyceraldehyde-3-phosphate, 3-phosphoglycerate and phosphoenolpyruvate, establishing this protein as the 'missing link' connecting the two split branches of glycolysis in this branch of single celled eukaryotes. The authors also present their data on bGIC-1, which suggests a role in anion transport and bOGC, which is a close functional homologue of the human oxoglutarate carrier (hOGC, SLC25A11) and human dicarboxylate carrier (hDIC, SLC25A10).

Strengths:

The results are presented in a clear and logical arrangement, which nicely leads the reader through the process of gene identification and subsequent ligand screening and functional reconstitution. The results are compelling and well supported - the thermal stabilisation data is supported by the exchange studies. Caveats, where apparent, are discussed and rational explanations given.

Weaknesses:

The study does not contain any significant weaknesses in my view. I would like to see the authors include the initial rate plots used in the main figures (possibly as insets), so we can observe the data points used for these calculations. It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

eLife assessment

This valuable study explores the neural basis for a well-known auditory illusion, often utilized in movie soundtracks, in which a sequence of two complex tones can be perceived as either rising or falling in pitch depending on the context in which they are presented. Solid single-neuron data and analyses are presented to show that correlates of these pitch-direction changes are found in the ferret primary auditory cortex. The manuscript is, however, difficult to assess in places and would benefit from greater consideration of how the results fit more broadly into models of auditory coding.

Reviewer #1 (Public Review):

Summary:

Previous work demonstrated a strong bias in the percept of an ambiguous Shepard tone as either ascending or descending in pitch, depending on the preceding contextual stimulus. The authors recorded human MEG and ferret A1 single-unit activity during presentation of stimuli identical to those used in the behavioral studies. They used multiple neural decoding methods to test if context-dependent neural responses to ambiguous stimulus replicated the behavioral results. Strikingly, a decoder trained to report stimulus pitch produced biases opposite to the perceptual reports. These biases could be explained robustly by a feed-forward adaptation model. Instead, a decoder that took into account direction selectivity of neurons in the population was able to replicate the change in perceptual bias.

Strengths:

This study explores an interesting and important link between neural activity and sensory percepts, and it demonstrates convincingly that traditional neural decoding models cannot explain percepts. Experimental design and data collection appear to have been executed carefully. Subsequent analysis and modeling appear rigorous. The conclusion that traditional decoding models cannot explain the contextual effects on percepts is quite strong.

Weaknesses:

Beyond the very convincing negative results, it is less clear exactly what the conclusion is or what readers should take away from this study. The presentation of the alternative, "direction aware" models is unclear, making it difficult to determine if they are presented as realistic possibilities or simply novel concepts. Does this study make predictions about how information from auditory cortex must be read out by downstream areas? There are several places where the thinking of the authors should be clarified, in particular, around how this idea of specialized readout of direction-selective neurons should be integrated with a broader understanding of auditory cortex.

Reviewer #2 (Public Review):

The authors aim to better understand the neural responses to Shepard tones in auditory cortex. This is an interesting question as Shepard tones can evoke an ambiguous pitch that is manipulated by a proceeding adapting stimulus, therefore it nicely disentangles pitch perception from simple stimulus acoustics.

The authors use a combination of computational modelling, ferret A1 recordings of single neurons, and human EEG measurements.

Their results provide new insights into neural correlates of these stimuli. However, the manuscript submitted is poorly organized, to the point where it is near impossible to review. We have provided Major Concerns below. We will only be able to understand and critique the manuscript fully after these issues have been addressed to improve the readability of the manuscript. Therefore, we have not yet reviewed the Discussion section.

Major concerns

Organization/presentation<br /> The manuscript is disorganized and therefore difficult to follow. The biggest issue is that in many figures, the figure subpanels often do not correspond to the legend, the main body, or both. Subpanels described in the text are missing in several cases. Many figure axes are unlabelled. There is an inconsistent style of in-text citation between figures and the main text. The manuscript contains typos and grammatical errors. My suggestions for edits below therefore should not be taken as an exhaustive list. I ask the authors to consider the following only a "first pass" review, and I will hopefully be able to think more deeply about the science in the second round of revisions after the manuscript is better organized.

Frequency and pitch<br /> The terms "frequency" and "pitch" seem to be used interchangeably at times, which can lead to major misconceptions in a manuscript on Shepard tones. It is possible that the authors confuse these concepts themselves at times (e.g. Fig 5), although this would be surprising given their expertise in this field. Please check through every use of "frequency" and "pitch" in this manuscript and make sure you are using the right term in the right place. In many places, "frequency" should actually be "fundamental frequency" to avoid misunderstanding.

Insufficient detail or lack of clarity in descriptions<br /> There seems to be insufficient information provided to evaluate parts of these analysis, most critically the final pitch-direction decoder (Fig 6), which is a major finding. Please clarify.

Reviewer #3 (Public Review):

Summary:

This is an elegant study investigating possible mechanisms underlying the hysteresis effect in the perception of perceptually ambiguous Shepard tones. The authors make a fairly convincing case that the adaptation of pitch direction sensitive cells in auditory cortex is likely responsible for this phenomenon.

Strengths:

The manuscript is overall well written. My only slight criticism is that, in places, particularly for non-expert readers, it might be helpful to work a little bit more methods detail into the results section, so readers don't have to work quite so hard jumping from results to methods and back.

The methods seem sound and the conclusions warranted and carefully stated. Overall I would rate the quality of this study as very high, and I do not have any major issues to raise.

Weaknesses:

I think this study is about as good as it can be with the current state of the art. Generally speaking, one has to bear in mind that this is an observational, rather than an interventional study, and therefore only able to identify plausible candidate mechanisms rather than making definitive identifications. However, the study nevertheless represents a significant advance over the current state of knowledge, and about as good as it can be with the techniques that are currently widely available.

eLife assessment

This useful study has identified a subset of neurons in the preoptic hypothalamus that promote social behavior in single-housed female mice. The approach is solid; however, due to a lack of significance in the key findings and competing outcomes between different manipulation methods, the evidence is incomplete. The authors have the potential to demonstrate evidence by either increasing the number of experimental animals represented in the study or by adjusting the language in the conclusions to reflect the findings.

Reviewer #1 (Public Review):

Summary:

Zhao et al. perform a series of experiments aimed at identifying the role of the preoptic area (POA) in controlling the impact of social isolation on same-sex female social behavior. They focus their manuscript on the effects of short-term (3d) isolation and females, both of which have been relatively understudied, making the overall topic of the manuscript exciting and important.

Strengths:

The work highlighted is well designed, the experiments original, and the manuscript is elegant and clearly written. The strengths of the manuscript lie in the attention to multiple facets of social behavior (investigation, mounting, USVs), sex differences, and the use of multiple loss- and gain-of-function approaches.

Weaknesses:

The main weaknesses of the paper are a lack of significance in key findings, and relatedly, concluding effects from insignificant findings. Additional elements could be improved to help strengthen this overall well-rounded and intriguing set of results.

Reviewer #3 (Public Review):

Summary:

How short-term isolation acts on the brain to promote social behavior remains incompletely understood. The authors found that social interactions after a period of acute isolation increased investigation promoted mounting, and increased the production of ultrasonic vocalizations (USVs). This was true for females during same-sex interactions as well as for males interacting with females. Concomitant with these increased behavioral readouts, cFos expression in the preoptic area of the hypothalamus (POA) was found to increase selectively in single-housed females. Chemogenetic silencing of these POA neurons attenuated all three behavioral measures in socially isolated females. Surprisingly, ablation of the same POA neurons decreased mounting duration without impacting social investigation or USV production. While optogenetic activation was sufficient to evoke USV production, it did not affect either mounting or social investigation. In males, chemogenetic silencing of POA neurons decreased mounting but not other behaviors. Together, these data point towards a role of POA neurons in mediating social behaviors after acute isolation but the exact nature of that control appears to depend on the choice of perturbation method, sex, and social context in complex ways that are hard to parse. This study is an essential first step; additional experiments will be needed to explain the apparent discrepancy between the various circuit perturbation results and to gain a more comprehensive understanding of the role of POA in social isolation.

Strengths:

The goal of understanding the neural circuit mechanisms underlying acute social isolation is clearly important and topical. Using a state-of-the-art technique to tag specific neurons that were active during certain behavioral epochs, the authors managed to identify the POA as a critical circuit locus for the effects of social isolation. The experimental design is perfectly reasonable and the quality of the data is good. The control experiments (Figures 2B-D) showing that chemogenetic inactivation of other hypothalamic regions (AH and VMH) do not affect social behavior is indeed quite satisfying and points towards a specific role of POA within the hypothalamus. Using a combination of behavioral assays, activity-dependent neural tagging, and circuit manipulation techniques, the authors present convincing evidence for the role of the preoptic area of the hypothalamus in mediating certain behaviors following social isolation. These data are likely to be a valuable resource for understanding how hypothalamic circuits adjust to the challenges of social isolation.

Weaknesses:

While the authors should be commended for performing and reporting multiple circuit perturbation experiments (e.g., chemogenetics, ablation), the conflicting effects on behavior are hard to interpret without additional experiments. For example, chemogenetic silencing of the POA neurons (using DREADDs) attenuated all three behavioral measures but the ablation of the same POA neurons (using CASPACE) decreased mounting duration without impacting social investigation or USV production. Similarly, optogenetic activation of POA neurons was sufficient to generate USV production as reported in earlier studies but mounting or social investigation remained unaffected. Do these discrepancies arise due to the efficiency differences between DREADD-mediated silencing vs. Casp3 ablation? Or does the chemogenetic result reflect off-manifold effects on downstream circuitry whereas a more permanent ablation strategy allows other brain regions to compensate due to redundancy? It is important to resolve whether these arise due to technical reasons or whether these reflect the underlying (perhaps messy) logic of neural circuitry. Therefore, while it is clear that POA neurons likely contribute to multiple behavioral readouts of social isolation, understanding their exact roles in any greater detail will require further experiments.

eLife assessment

This study presents valuable data on the increase in individual differences in functional connectivity with the auditory cortex in individuals with congenital/early-onset hearing loss compared to individuals with normal hearing. The evidence supporting the study's claims is convincing, although additional analyses and a deeper conceptual framing would have strengthened the study. The work will be of interest to neuroscientists working on brain plasticity and may have implications for the design of interventions and compensatory strategies.

Reviewer #1 (Public Review):

This experiment sought to determine what effect congenital/early-onset hearing loss (and associated delay in language onset) has on the degree of inter-individual variability in functional connectivity to the auditory cortex. Looking at differences in variability rather than group differences in mean connectivity itself represents an interesting addition to the existing literature. The sample of deaf individuals was large, and quite homogeneous in terms of age of hearing loss onset, which are considerable strengths of the work. The experiment appears well conducted and the results are certainly of interest. I do have some concerns with the way that the project has been conceptualized, which I share below.

The authors should provide careful working definitions of what exactly they think is occurring in the brain following sensory deprivation. Characterizing these changes as 'large-scale neural reorganization' and 'compensatory adaptation' gives the impression that the authors believe that there is good evidence in support of significant structural changes in the pathways between brain areas - a viewpoint that is not broadly supported (see Makin and Krakauer, 2023). The authors report changes in connectivity that amount to differences in coordinated patterns of BOLD signal across voxels in the brain; accordingly, their data could just as easily (and more parsimoniously) be explained by the unmasking of connections to the auditory cortex that are present in typically hearing individuals, but which are more obvious via MR in the absence of auditory inputs.

I found the argument that the deaf use a single modality to compensate for hearing loss, and that this might predict a more confined pattern of differential connectivity than had been previously observed in the blind to be poorly grounded. The authors themselves suggest throughout that hearing loss, per se, is likely to be driving the differences observed between deaf and typically-hearing individuals; accordingly, the suggestion that the modality in which intentional behavioral compensation takes place would have such a large-scale effect on observed patterns of connectivity seems out of line.

The analyses highlighting the areas observed to be differentially connected to the auditory cortex and areas observed to be more variable in their connectivity to the auditory cortex seem somewhat circular. If the authors propose hearing loss as a mechanism that drives this variability in connectivity, then it is reasonable to propose hypotheses about the directionality of these changes. One would anticipate this directionality to be common across participants and thus, these areas would emerge as the ones that are differently connected when compared to typically hearing folks.

While the authors describe collecting data on the etiology of hearing loss, hearing thresholds, device use, and rehabilitative strategies, these data do not appear in the manuscript, nor do they appear to have been included in models during data analysis. Since many of these factors might reasonably explain differences in connectivity to the auditory cortex, this seems like an omission.

Reviewer #3 (Public Review):

Summary:

This study focuses on changes in brain organization associated with congenital deafness. The authors investigate differences in functional connectivity (FC) and differences in the variability of FC. By comparing congenitally deaf individuals to individuals with normal hearing, and by further separating congenitally deaf individuals into groups of early and late signers, the authors can distinguish between changes in FC due to auditory deprivation and changes in FC due to late language acquisition. They find larger FC variability in deaf than normal-hearing individuals in temporal, frontal, parietal, and midline brain structures, and that FC variability is largely driven by auditory deprivation. They suggest that the regions that show a greater FC difference between groups also show greater FC variability.

Strengths:

- The manuscript is well written.

- The methods are clearly described and appropriate.

- Including the three different groups enables the critical contrasts distinguishing between different causes of FC variability changes.

- The results are interesting and novel.

Weaknesses:

- Analyses were conducted for task-based data rather than resting-state data. It was unclear whether groups differed in task performance. If congenitally deaf individuals found the task more difficult this could lead to changes in FC.

- No differences in overall activation between groups were reported. Activation differences between groups could lead to differences in FC. For example, lower activation may be associated with more noise in the data, which could translate to reduced FC.

- Figure 2B shows higher FC for congenitally deaf individuals than normal-hearing individuals in the insula, supplementary motor area, and cingulate. These regions are all associated with task effort. If congenitally deaf individuals found the task harder (lower performance), then activation in these regions could be higher, in turn, leading to FC. A study using resting-state data could possibly have provided a clearer picture.

- The correlation between the FC map and the FC variability map is 0.3. While significant using permutation testing, the correlation is low, and it is not clear how great the overlap is.

eLife assessment

Peng et al. reported important findings that 36THz high-frequency terahertz stimulation (HFTS) could suppress the activity of pyramidal neurons by enhancing the conductance of voltage-gated potassium channels. The significance of the findings in this paper is that chronic pain remains a significant medical problem, and there is a need to find non-pharmacological interventions for treatment. The authors present convincing evidence that high-frequency stimulation of the anterior cingulate cortex can alter neuronal activity and improve sensory pain behaviors in mice.

Reviewer #1 (Public Review):

In this manuscript, by using simulation, in vitro and in vivo electrophysiology, and behavioral tests, Peng et al. nicely showed a new approach for the treatment of neuropathic pain in mice. They found that terahertz (THz) waves increased Kv conductance and decreased the frequency of action potentials in pyramidal neurons in the ACC region. Behaviorally, terahertz (THz) waves alleviated neuropathic pain in the mouse model. Overall, this is an interesting study. The experimental design is clear, the data is presented well, and the paper is well-written. I have a few suggestions.

(1) The authors provide strong theoretical and experimental evidence for the impact of voltage-gated potassium channels by terahertz wave frequency. However, the modulation of action potential also relies on non-voltage-dependent ion channels. For example, I noticed that the RMP was affected by THz application (Figure 3F) as well. As the RMP is largely regulated by the leak potassium channels (Tandem-pore potassium channels), I would suggest testing whether terahertz wave photons have also any impact on the Kleak channels as well.

(2) The activation curves of the Kv currents in Figure 2h seem to be not well-fitted. I would suggest testing a higher voltage (>100 mV) to collect more data to achieve a better fitting.

(3) In the part of behavior tests, the pain threshold increased after THz application and lasted within 60 mins. I suggest conducting prolonged tests to determine the end of the analgesic effect of terahertz waves.

(4) Regarding in vivo electrophysiological recordings, the post-HFTS recordings were acquired from a time window of up to 20 min. It seems that the HFTS effect lasted for minutes, but this was not tested in vitro where they looked at potassium currents. This long-lasting effect of HFTS is interesting. Can the authors discuss it and its possible mechanisms, or test it in slice electrophysiological experiments?

(5) How did the authors arrange the fiber for HFTS delivery and the electrode for in vivo multi-channel recordings? Providing a schematic illustration in Figure 4 would be useful.

(6) Some grammatical errors should be corrected.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Peng et al., reported that 36THz high-frequency terahertz stimulation (HFTS) can suppress the activity of pyramidal neurons by enhancing the conductance of voltage-gated potassium channel. The authors also demonstrated the effectiveness of using 36THz HFTS for treating neuropathic pain.

Strengths:

The manuscript is well written and the conclusions are supported by robust results. This study highlighted the potential of using 36THz HFTS for neuromodulation.

Weaknesses:

More characterization of HFTS is needed, so the readers can have a better assessment of the potential usage of HFTS in their own applications.

(1) It would be very helpful to estimate the volume of tissue that can be influenced by HFTS. It is not clear how 15 mins HFTS was chosen for this functional study. Does a longer time have a stronger effect? A better characterization of the relationship between the stimulus duration of HFTS and its beneficial effects would be very useful.

(2) How long does the behavioral effect last after 15 minutes of HFTS? Figure 5b only presents the behavioral effect for one hour, but the pain level is still effectively reduced at this time point. The behavioral measurement should last until pain sensitization drops back to pre-stim level.

(3) Although the manuscript only tested in ACC, it will also be useful to demonstrate the neural modulation effect on other brain regions. Would 36THz HFTS also robustly modulate activities in other brain regions? Or are different frequencies needed for different brain regions?

Reviewer #3 (Public Review):

Summary:

This manuscript by Peng et al. presents intriguing data indicating that high-frequency terahertz stimulation (HFTS) of the anterior cingulate cortex (ACC) can alleviate neuropathic pain behaviors in mice. Specifically, the investigators report that terahertz (THz) frequency stimulation widens the selectivity filter of potassium channels thereby increasing potassium conductance and leading to a reduction in the excitability of cortical neurons. In voltage clamp recordings from layer 5 ACC pyramidal neurons in acute brain slice, Peng et al. show that HFTS enhances K current while showing minimal effects on Na current. Current clamp recording analyses show that the spared nerve injury model of neuropathic pain decreases the current threshold for action potential (AP) generation and increases evoked AP frequency in layer 5 ACC pyramidal neurons, which is consistent with previous studies. Data are presented showing that ex-vivo treatment with HFTS in slice reduces these SNI-induced changes to excitability in layer 5 ACC pyramidal neurons. The authors also confirm that HFTS reduces the excitability of layer 5 ACC pyramidal neurons via in vivo multi-channel recordings from SNI mice. Lastly, the authors show that HFTS is effective at reducing mechanical allodynia in SNI using both the von Frey and Catwalk analyses. Overall, there is considerable enthusiasm for the findings presented in this manuscript given the need for non-pharmacological treatments for pain in the clinical setting.

Strengths:

The authors use a multifaceted approach that includes modeling, ex-vivo and in-vivo electrophysiological recordings, and behavioral analyses. Interpretation of the findings is consistent with the data presented. This preclinical work in mice provides new insight into the potential use of directed high-frequency stimulation to the cortex as a primary or adjunctive treatment for chronic pain.

Weaknesses:

There are a few concerns noted that if addressed, would significantly increase enthusiasm for the study.

(1) The left Na current trace for SNI + HFTS in Figure 2B looks to have a significant series resistance error. Time constants (tau) for the rate of activation and inactivation for Na currents would be informative.

(2) It is unclear why an unpaired t-test was performed for paired data in Figure 2. Also, statistical methods and values for non-significant data should be presented.

(3) It would seem logical to perform HFTS on ACC-Pyr neurons in acute slices from sham mice (i.e. Figure 3 scenario). These experiments would be informative given the data presented in Figure 4.

(4) As the data are presented in Figure 4g, it does not seem as if SNI significantly increased the mean firing rate for ACC-Pyr neurons, which is observed in the slice. The data were analyzed using a paired t-test within each group (sham and SNI), but there is no indication that statistical comparisons across groups were performed. If the argument is that HFTS can restore normal activity of ACC-Pyr neurons following SNI, this is a bit concerning if no significant increase in ACC-Pyr activity is observed in in-vivo recordings from SNI mice.

(5) The authors indicate that the effects of HFTS are due to changes in Kv1.2. However, they do not directly test this. A blocking peptide or dendrotoxin could be used in voltage clamp recordings to eliminate Kv1.2 current and then test if this eliminates the effects of HFTS. If K current is completely blocked in VC recordings then the authors can claim that currents they are recording are Kv1.1 or 1.2.

(6) The ACC is implicated in modulating the aversive aspect of pain. It would be interesting to know whether HFTS could induce conditioned place preference in SNI mice via negative reinforcement (i.e. alleviation of spontaneous pain due to the injury). This would strengthen the clinical relevance of using HFTS in treating pain.

eLife assessment

Hou and colleagues describe the the use of a previously characterized FRET sensor for use in determining gamma secretase activity in the brain of living mice. In an approach that targeted the sensor to neurons, they observe patterns of fluorescent sensor readout suggesting clustered regions of secretase activity. These results once validated would be valuable in the field of Alzheimer's Disease research, yet further validation of the approach is required, as the current evidence provided is inadequate to support the conclusions.

Reviewer #1 (Public Review):

Summary:

In their paper, Hou and co-workers explored the use of a FRET sensor for endogenous g-sec activity in vivo in the mouse brain. They used AAV to deliver the sensor to the brain for neuron specific expression and applied NIR in cranial windows to assess FRET activity; optimizing as well an imaging and segmentation protocol. In brief they observe clustered g-sec activity in neighboring cells arguing for a cell non-autonomous regulation of endogenous g-sec activity in vivo.

Weaknesses:

Overall the authors provide a very limited data set and in fact only a proof of concept that their sensor can be applied in vivo. This is not really a research paper, but a technical note. With respect to their observation of clustered activity, the images do not convince me as they show only limited areas of interest: from these examples (for instance fig 5) one sees that merely all neurons in the field show variable activity and a clustering is not really evident from these examples. Even within a cluster, there is variability. With r values between 0.23 to .36, the correlation is not that striking. The authors herein do not control for expression levels of the sensor: for instance, can they show that in all neurons in the field, the sensor is equally expressed, but FRET activity is correlated in sets of neurons? Or are the FRET activities that are measured only in positively transduced neurons, while neighboring neurons are not expressing the sensor? Without such validation, it is difficult to make this conclusion.

Secondly, I am lacking some more physiological relevance for this observation. The experiments are performed in wild-type mice, but it would be more relevant to compare this with a fadPSEN1 KI or a PSEN1cKO model to investigate the contribution of a gain of toxic function or LOF to the claimed cell non-autonomous activations. Or what would be the outcome if the sensor was targeted to glial cells?

For this reviewer it is not clear what resolution they are measuring activity, at cellular or subcellular level? In other words are the intensity spots neuronal cell bodies? Given g-sec activity are in all endosomal compartments and at the cell surface, including in the synapse, does NIR imaging have the resolution to distinguish subcellular or surface localized activities? If cells 'communicate' g-sec activities, I would expect to see hot spots of activity at synapses between neurons: is this possible to assess with the current setup?

Without some more validation and physiological relevant studies, it remains a single observation and rather a technical note paper, instead of a true research paper.

Reviewer #2 (Public Review):

Summary:

The manuscript by Hou et al is a short technical report which details the potential use of a recently developed FRET based biosensor for gamma-secretase activity (Houser et al 2020) for in vivo imaging in the mouse brain. Gamma-secretase plays a crucial role in Alzheimer disease pathology and therefore developing methodologies for precise in vivo measurements would be highly valuable to better understand AD pathophysiology in animal models.

The current version of the sensor utilizes a pair of far-red fluorescent proteins fused to a substrate of the enzyme. Using live imaging, it was previously demonstrated it is possible to monitor gamma-secretase activity in cultured cells. Notably, this is a variant of a biosensor that was previously described using CFP-YFP variants FRET pair (Maesako et al, iScience. 2020). The main claim and hypothesis for the MS is that IR excitation and emission has considerable advantages in terms of depth of penetration, as well as reduction in autofluorescence. These properties would make this approach potentially suitable to monitor cellular level dynamics of Gama-secretase in vivo.

The authors use confocal microscopy and show it is possible to detect fluorescence from single cortical cells. The paper described in detail technical information regarding imaging and analysis. The data presented in figures 5-8 details analysis of FRET ratio (FR) measurements within populations of cells. The authors claim it is possible to obtain reliable measurements at the level of individual cells. They compare the FR values across cells and mice and find a spatial correlation among neighboring cells. This is compared with data obtained after inhibition of endogenous gamma-secretase activity, which abolishes this correlation.

Strengths:

The authors describe in detail their experimental design and analysis for in vivo imaging of the reporter. The idea of using a far-red FRET sensor for in vivo imaging is novel and potentially useful to circumvent many of the pitfalls associated with intensity-based FRET imaging in complex biological environments (such as autofluorescence and scattering).

Weaknesses:

There are several critical points regarding validation of this approach and concerns with the data presented that must be addressed:

(1) Regarding the variability and spatial correlation- the dynamic range of the sensor previously reported in vitro is in the range of 20-30% change (Houser et al 2020) whereas the range of FR detected in vivo is between cells is significantly larger (Fig. 3). This raises considerable doubts for specific detection of cellular activity (see point 3).<br /> (2) One direct way to test the dynamic range of the sensor in vivo, is to increase or decrease endogenous gamma-secretase activity and to ensure this experimental design allows to accurately monitor gamma-secretase activity. In the previous characterization of the reporter (Hauser et al 2020), DAPT application and inhibition of gamma-secretase activity results in increased FR (Figures 2 and 3 of Houser et al). This is in agreement with the design of the biosensor, since FR should be inversely correlated with enzymatic activity. Here, while the authors repeat the same manipulation and apply DAPT to block gamma-secretase activity, it seems to induce the opposite effect and reduces FR (comparing figures 8 with figures 5,6,7). First, there is no quantification comparing FR with and without DAPT. Moreover, it is possible to conduct this experiment in the same animals, meaning comparing FR before and after DAPT in the same mouse and cell populations. This point is absolutely critical- if indeed FR is reduced following DAPT application, this needs to be explained since this contradicts the basic design and interpretation of the biosensor.<br /> (3) For further validation, I would suggest including in vivo measurements with a sensor version with no biological activity as a negative control, for example, a mutation that prevents enzymatic cleavage and FRET changes. This should be used to showcase instrumental variability and would help to validate the variability of FR is indeed biological in origin. This would significantly strengthen the claims regarding spatial correlation within population of cells.<br /> (4) In general, confocal microcopy is not ideal for in vivo imaging. Although the authors demonstrate data collected using IR imaging increases penetration depth, out of focus fluorescence is still evident (Figure 4). Many previous papers have primarily used FLIM based analysis in combination with 2p microscopy for in vivo FRET imaging (Some examples: Ma et al, Neuron, 2018; Massengil et al, Nature methods, 2022; DIaz-Garcia et al, Cell Metabolism, 2017; Laviv et al, Neuron, 2020). This technique does not rely on absolute photon number and therefore has several advantage sin terms of quantification of FRET signals in vivo.<br /> It is therefore likely that use of previously developed sensors of gamma-secretase with conventional FRET pairs, might be better suited for in vivo imaging. This point should be at least discussed as an alternative.

Reviewer #3 (Public Review):

This paper builds on the authors' original development of a near infrared (NIR) FRET sensor by reporting in vivo real-time measurements for gamma-secretase activity in the mouse cortex. The in vivo application of the sensor using state of the art techniques is supported by a clear description and straightforward data, and the project represents significant progress because so few biosensors work in vivo. Notably, the NIR biosensor is detectable to ~ 100 µm depth in the cortex. A minor limitation is that this sensor has a relatively modest ΔF as reported in Houser et al, which is an additional challenge for its use in vivo. Thus, the data is fully dependent on post-capture processing and computational analyses. This can unintentionally introduce biases but is not an insurmountable issue with the proper controls that the authors have performed here.

The observation of gamma-secretase signaling that spreads across cells is potentially quite interesting, but it can be better supported. An alternative interpretation is that there exist pre-formed and clustered hubs of high gamma-secretase activity, and that DAPT has stochastic or differential accessibility to cells within the cluster. This could be resolved by an experiment of induction, for example, if gamma-secretase activity is induced or activated at a specific locale and there was observed coordinated spreading to neighboring neurons with their sensor.

Furthermore, to rule out the possibility that uneven viral transduction was not simply responsible for the observed clustering, it would be helpful to see an analysis of 670nm fluorescence alone.

Author response:

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

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

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

Reviewer #1 (Public Review):

Weaknesses:

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

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

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

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

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

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

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

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

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

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

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

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

Reviewer #2 (Public Review):

Weaknesses:

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

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

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

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

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

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

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

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

Reviewer #3 (Public Review):

Weaknesses:

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

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

Reviewer #2 (Recommendations For The Authors):

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

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

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

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

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

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

Citations

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

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

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

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

Reviewer #2 (Public Review):

Summary:

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

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

Strengths:

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

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

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

Weaknesses:

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

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

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

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

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

Author response:

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

Reviewer #1 (Recommendations For The Authors):

(1) The description of the wing phenotype that results from combinations of wingless and delex alleles at the bottom of page 4 (figure 1) is quite confusing. Are the trans-hets suppressed to wt or enhanced? The images in the Fig look enhanced.

We thank the reviewer for this thoughtful observation regarding the wing phenotype description in combination with wg and dx alleles. We understand the confusion and appreciate the opportunity to clarify.

In response to the concern raised, the trans-heterozygous indeed enhanced rather than suppressed to wild type. We acknowledge that the description would have been clearer. We have revised the relevant section to explicitly state that trans-heterozygous exhibit an enhanced wing phenotype in the updated version of the manuscript.

(2) Use of Cut as a Wg readout in Fig1 is problematic since it is also a Notch target. Perhaps a more direct measure of Arm activity would be a better choice here, e.g., naked-lacZ.

We appreciate the reviewer’s insightful comment regarding the use of Cut as a Wg readout. The point about being Cut as a Notch target raises a valid concern. To address this issue and provide a more direct measurement of Arm activity, we agree that incorporating a specific Arm readout, such as naked lacZ, would be a more suitable choice.

We will incorporate this valuable feedback into our future research endeavors to augment the comprehensiveness of our study.

(3) The dx allele effects on Sens and Vg in Fig 2C appear greater at two points along the DV margin (arrows). Do these match the expression pattern of dx mRNA?

We thank the reviewer for this thoughtful observation. We understand that the effect of the dx LOF allele on Sens and Vg seems more pronounced at two specific points along the D/V margin. As far as our understanding Dx shows a homogeneous expression pattern throughout the Wg disc which has been reported earlier (Busseau et al., 1994., Mukherjee et al., 2005).

(4) It really looks to my eye that dx loss lowers Wg expression in source cells in Fig 2. To confirm the model that Dx controls the spread of Wg protein, it would be ideal to rule out txnal effects with a wg-lacZ reporter.

We appreciate the reviewer for raising this important point. In the revised version of the manuscript, we have introduced Wg-lacZ staining for both Wg-lacZ/+ and dx152/Y; Wg-lacZ/+ combination in Figure 2. This additional information eliminates the possibility of Deltex influencing Wg transcriptional regulation in source cells, thus reinforcing our hypothesis that the reduction of Deltex leads to a decline in Wg protein levels in the source cells, given Dx essential role in wingless gradient formation.

(5) The drop in DV Wg and expansion of Vg domain in dx mutants seem paradoxical but could be explained by accelerated Wg spread and uptake. This could be tested by depleting the dally-like glypican that promotes long-range Wg diffusion in dx mutants, and seeing if this restores Wg levels at the DV margin.

This is indeed a very thoughtful comment and we thank the reviewer for this insightful suggestion for further exploration. We believe that depleting dally-like glypican in dx mutants could possibly restore Wg levels at the DV margin.

We recognize the importance of this experiment in providing a more comprehensive understanding of the underlying mechanisms, and we will give major emphasis on incorporating this suggestion in our future research.

(6) The authors describe the effect of Dx over-expression as "reducing" the Wg gradient when they actually mean "flattening". Please be careful with this word choice as they mean different things.

We thank the reviewer for the insightful feedback. The suggested modifications have been incorporated into the revised version of the manuscript.

(7) The combined effects of Rab5dn and Dx o/e on Wg protein loc/levels are interesting but need to be followed up by testing whether the endogenous Dx/Rab5 show genetic interactions in control of Wg protein levels/localization.

We acknowledge the reviewer's comment and in addressing it, we wish to highlight that the over-expression of Dx with endogenous Rab5 or Rab7 does not affect Wg protein levels or localization. We have mentioned the supporting data for this control in Figure 5(G, H).

(8) The ability of MG132 to restore Arm levels in en-Dx discs is very promising. However, MG132 will also block Arm degradation by the Slmb-APC destruction complex, so this result could be non-specific. Tests of whether Dx drives poly-ub of Arm, and how much Dx is redundant to Slmb in this role, would be needed to solidify the authors' conclusion.

We thank the reviewer for this insightful comment. We understand that the concern about MG132 blocking Arm degradation by Slmb-APC destruction complex adds an important layer of complexity to the interpretation of the results. We agree with the reviewer's comment that conducting these experiments will indeed offer valuable insight into the specificity of MG132 effects and further strengthen our conclusion.

We are interested to see how future experiments addressing the points raised by the reviewer will shape our understanding of the intricate mechanisms involved in Wg signaling and Arm/-catenin degradation. Once again, we thank the reviewer for the thoughtful engagement with the research, and the comments will undoubtedly stimulate further investigation and discussion in this area.

Reviewer #2 (Recommendations For The Authors):

The work really needs more experiments to further provide a mechanistic understanding and distinguish between direct and indirect action (via Notch signaling) on Wingless, but instead switches in the second half to a second interaction with β-catenin, leaving the conclusions of the first part hanging. More mechanistic information on the cell biology of how Deltex might affect wingless endocytic trafficking directly would be beneficial, for example involving some cell culture experiments where the action of deltex on Notch and wingless could be more clearly separated and a more detailed study of the consequences on wingless trafficking could be explored.

Wingless is secreted into an extracellular compartment and so won't be accessible for a direct interaction with cytoplasmic deltex. Therefore are the authors proposing Deltex interacts with a membrane-bound wingless receptor such as frizzled in order to mediate its effects? These avenues could be explored further experimentally to derive a more mechanistic conclusion.

The colocalisation images are not high resolution and colocalisation is not quantified, and no differences ( +/- Deltex) in wingless subcellular localisation, which would aid mechanistic interpretation, are shown.

We thank the reviewer for the insightful feedback on our work. We appreciate the suggestion for more experiments to provide a mechanistic understanding and to distinguish between direct and indirect actions of Notch on Wingless signaling. We acknowledge the importance of clarifying these aspects and agree that further experiments could help separate the effects of Deltex on Notch and Wingless signaling, allowing for a more detailed examination of their respective trafficking and ubiquitination mechanisms.

We will consider your valuable input in our future research efforts to enhance the comprehensiveness of our study.

Other specific points

Figure 2: Narrowing and broadening of different marker gene expression patterns in dx mutants needs to be quantified so that variation is taken into account and the numbers of wings imaged should be clearly stated.

We greatly appreciate this valuable suggestion from the reviewer. As a response, we have incorporated quantification data to address the observed variations. We have also provided information regarding the number of wing discs that were imaged for the purpose of quantification.

Figure 3: The number of discs imaged in total should be mentioned

We express our appreciation to the reviewer for the input. We have taken their comment into account and have subsequently included details regarding the number of discs imaged in the figure legend section of the manuscript.

Figure 6: There is no description of (E5-E6) in the figure legend. F1 to F5 eye size phenotypes require quantification.

We are grateful to the reviewers for bringing this to our attention. In response, we have included a description of E5-E6 in the figure legend. Also, as per the reviewer’s suggestions, we have incorporated the quantification data of the eye size phenotype.

Discussion

Links between Notch and wingless pathway should be more comprehensively discussed, including previous work that has previously linked Notch/Deltex to β-catenin degradation e.g.

Acar et al. .Sci Rep 2021 Apr 27;11(1):9096. doi: 10.1038/s41598-021-88618-5

Hayward et al. Development 2005 Apr;132(8):1819-30. doi: 10.1242/dev.01724;

Kwon et al Nat Cell Biol 2011 Aug 14;13(10):1244-51. doi: 10.1038/ncb2313.

Sanders et al. PLoS Biol 2009 Aug;7(8):e1000169. doi:10.1371/journal.pbio.1000169. Epub 2009 Aug 11.

The links between endocytic trafficking and wingless gradient formation could also be further discussed eg.

Marois et al. Development 2006 Jan;133(2):307-17.doi: 10.1242/dev.02197. Epub 2005 Dec 14

Yamazaki et al Nat Cell Biol 2016 Apr;18(4):451-7. doi: 10.1038/ncb3325. Epub 2016 Mar 14.

We appreciate the reviewer's valuable suggestions and we have now included these references in the discussion section of the revised manuscript.

eLife assessment

This is a useful study of the connection between the ubiquitin ligase protein deltex and the wingless signaling pathway. Two different links are inferred from genetic interactions in vivo between loss-of-function mutations and overexpression. While the genetic data are solid, the precise mechanism underlying either effect remains to be established.

Reviewer #1 (Public Review):

This study presents a genetic and molecular analysis of the role of the cytoplasmic ub ligase Deltex (Dx) in regulating the Drosophila Wingless (Wg) pathway in the larval wing disc. The study exploits the strength of the fly system to uncover a series of genetic interactions between dx and wg and fz allele that support a role for Dx upstream of the Wg pathway. These are paired with molecular evidence that dx lof alleles lower Wg protein in 'source' cells at the DV margin, and that Dx associates with Arm and lowers its levels in a manner that can be rescued by pharmacological inhibition of the proteasome. The genetic data are solid but subject to alternative explanations based on the authors' model that Dx both inhibits and activates the pathway. The molecular data are suggestive, but need follow up tests of how Dx affects Wg spread, and how Dx mediates poly-ub of Arm, and the degree to which Dx shares this role with the validated Arm E3 ligase Slmb. Overall, the story is very interesting but has mechanistic gaps that lead to speculative models that require more rigorous study to clarify mechanism. Dx sharing a role in Arm degradation with the Slmb/APC destruction would have important implications for the many Wg/Wnt regulated processes in development and disease.

Reviewer #2 (Public Review):

The manuscript investigates the connections between the ubiquitin ligase protein deltex and the wingless pathway. Two different connections are proposed, one is function of deltex to modulate the gradient of wingless diffusion and hence modulate the spatial patter of wingless pathway targets, which regulate at different thresholds of wingless concentration. The second is a direct interaction between deltex and armadillo, a downstream component of the wingless pathway. Deltex is proposed to cause the degradation of armadillo resulting in suppression of wingless pathway activity. The results and conclusions of the manuscript are interesting and for the most part novel, although previously published work linking Notch and deltex to wingless signal regulation, and endocytosis to wingless gradient formation could be more extensively discussed. However neither of the two parts to the manuscript seem, in themselves sufficiently complete, and combining both parts together therefore seems to lack focus.

The main issue with the manuscript is that much of the conclusions are inferred from genetic interactions in vivo between loss of function mutants and overexpression. While providing useful in vivo physiological context, this type of approach struggles to be able to make definitive conclusions on whether an interaction is due to direct or indirect mechanism, as the authors themselves conclude at the end of section 2.3. The problem is confounded by the fact that there is already documented much cross talk between the Notch signaling pathway and wingless at the transcriptional level, and deltex is already a Notch modulator that can alter wingless mRNA expression (See Hori et al 2004). Deltex in addition to promoting a ligand-independent Notch signal can also induce expression of Notch ligand, allowing further non-autonomous Notch activation and subsequent cell autonomous cis-inhibition of the initial deltex-induced signal. The dynamics and outcomes of the Notch signal response to deltex in vivo is therefore already very complicated to interpret before even considering to unravel indirect (via Notch) and direct interactions with wingless, although the two possibilities are not mutually exclusive. Whilst the revised manuscript does not completely overcome these limitations, further data and quantification have improved the support for the conclusions and there is a wider discussion of the relevant literature. The conclusions are interesting and add significantly to our understanding of the intersections between Wingless, Notch and trafficking regulators in an in vivo context.

Author response:

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

Reviewer #1 (Public Review):

(1) The data strongly suggest that iron depletion in urine leads to conditional essentiality of some genes. It would be informative to test the single gene deletions (Figure 3G) for growth in urine supplemented with iron, to determine how many of those genes support growth in urine due to iron limitation.

We appreciate this suggestion. We have now included this suggested experiment as a new panel (Figure 5G).

(2) Line 641. The authors raise the intriguing possibility that some mutants can "cheat" by benefitting from the surrounding cells that are phenotypically wild-type. Growing a fepA deletion strain in urine, either alone or mixed with wild-type cells, would address this question. Given that other mutants may be similarly "masked", it is important to know whether this phenomenon occurs.

We thank the reviewer for this suggestion but believe that this would be very difficult to ascertain in K. pneumoniae as several redundant iron uptake systems exist. This would require significantly more time to construct sequential/combinatorial iron-uptake mutants to exactly determine this “cheating” and “masking” phenomenon and such work is beyond the scope of the current study.

(3) In cases where there are disparities between studies, e.g., for genes inferred to be essential for serum resistance, it would be informative to test individual deletions for genes described as essential in only one study.

We thank the reviewer for this suggestion, and we agree that deleting conditionally essential genes (i.e. serum resistance) could help identify discrepancies in methodology with other studies but this is beyond the scope of this study. Furthermore, we do not have these other strains readily available to us and importing these strains into Australia is challenging due to the strict import/quarantine laws.

Reviewer #1 (Recommendations For The Authors)

(4) Line 529. Why was 50 chosen as the read count threshold?

This was chosen as the minimum threshold needed to exclude essential genes from the comparative analysis, as these can contribute false positive results where a change from, for example, 2 to 5 reads between conditions is considered a >2-fold change. We have updated the manuscript text to highlight this: “were removed from downstream analysis to exclude confounding essential genes and minimize the effect of stochastic mutant loss” (line 539

(5) The titles for Figure 5 and Figure 6 appear to be switched.

Thank you, we have now corrected this error.

(6) Line 381. "Forty-six of these regions contain potential open reading frames that could encode proteins". How is a potential ORF defined?

This was based on submitting the selected 145bp regions to BLASTx using default parameters and listing the top hit (if one was found). We have now edited the manuscript text to make this clearer. (Line 394)

(7) Two previous TnSeq studies looking at Escherichia coli and Vibrio cholerae suggest that H-NS can prevent transposon insertion, leading to false positive essentiality calls. Is there any evidence of this phenomenon here? A/T content could be used as a proxy for H-NS occupancy.

We thank the reviewer for this point and also agree that H-NS or other DNA-binding proteins could indeed lead to false-positive essentiality calls using TraDIS. Based on this, we have now included a sentence in the conclusion section mentioning this methodological caveat (Line 631). We believe that A/T content could potentially be used as a proxy for H-NS occupancy,

Reviewer #2 (Recommendations For The Authors):

(1) The authors may wish to reformat the manuscript by decanting a number of panels and figures as supplementary material. These include the panels related to the description of TraDIS (for example Fig 1D, 1E, 1F. 1G, Fig 2A, Fig 3C, 3D, 3E, 3F, Fig 5C, Fig 6D). This is a well-established method.

We thank the reviewer for this suggestion but believe that these panels allow the methodology and resulting insertion plots to be more followable and allow other researchers, of varying expertise, to better understand this functional genetic screen technique.

(2) The authors need to indicate how relevant the strain they have probed is. Is it a good reference strain of the KpI group?

This is a great suggestion and we have now included a new figure illustrating the genetic context and relatedness of K. pneumoniae ECL8 within the KpI phylogroup (New Figure 3).

(3) The authors need to provide an extensive comparison between the data obtained and those reported testing other Klebsiella strains. A Table identifying the common and different genes, as well as a figure, may suffice. I would encourage authors to compare also their data against E. coli and Salmonella. For example, igaA seems to be not essential in Kebsiella although data indicates it is in Salmonella.

We thank the reviewer for their comment and appreciate that our data could be extended and compared to other relevant Enterobacteriaceae members. However, we believe this is beyond the scope of this study as the focus is more on K. pneumoniae.

(4) None of the mutants tested further are complemented. Without these experiments, it cannot be rigorously claimed that these loci play any role in the phenotypes investigated.

We agree that complementation is an important tenet for validation of mutant gene phenotypes to specific gene loci, in this case wbbY has already been complemented and believe complementation for an already known molecular mechanism would be redundant. Please refer to our response in point 6.

We complemented isolated transposon mutants hns7::Tn5 and hns18::Tn5 with a mid-copy IPTG inducible . We observed a slight increase in serum susceptibility but not full rescue of the WT phenotype (i.e. serum susceptibility). We suspect that the imperfect rescue of the serum-resistance phenotype observed could be due to the expression levels and copy number of the complement hns plasmid used. As hns is a known global regulator its possible pleiotropic role is complex as many aspects of stress response, metabolism or capsule could be affected in Klebsiella (doi.org/10.1186/1471-2180-6-72, doi.org/10.3389/fcimb.2016.00013). We have now included in the text our efforts in complementation and have included a new supplementary figure (Figure S11).

(5) The contribution of siderophores to survival in urine is not conclusively established. Authors may wish to test the transcription of relevant genes, and to assess whether the expression is fur dependent in urine. Also, authors may wish to identify the main siderophore needed for survival in urine by probing a number of mutants; this will allow us to assess whether there is a degree of selection and redundancy.

We thank the reviewer for their comment and agree siderophore uptake is important. We have now included an additional panel (Figure 5G) interrogating the importance of iron-uptake genes grown in urine which is iron limited. We do appreciate that further experiments looking into the Fur regulon and siderophore biosynthesis would be interesting but believe this is outside the scope of this study.

(6) The role of wbbY is intriguing, pointing towards the importance of high molecular weight O-polysaccharide. In this mutant background, the authors need to assess whether the expression of the capsule, and ECA is affected. Authors need also to complement the mutant. Which is the mechanism conferring resistance?

We thank the reviewer for their comment and would like to mention that wbbY has already been shown to play a role in LPS profile/biosynthesis and serum-resistance (10.3389/fmicb.2014.00608 ). Furthermore, blast analysis shows that the wbbY gene between the NTUH-K2044 (strain used in aforementioned study) and ECL8 shares 100% sequence identity and also shares lps operon structure. Hence, we do not find it pertinent to complement this mutant as we believe its molecular mechanism has already been established. We have now in the text more prominently highlighted the results of this study and how our screen was robust enough to also identify this gene for serum resistance.

(7) hns and gnd mutants most likely will have their capsule affected. The authors need to assess whether this is the case. Which is the mechanism conferring resistance?

As mentioned in point 6, we believe that the serum resistance phenotype is attributable to the LPS phenotype. Previous studies have listed hns and gnd mutants would likely have differences in capsule but due to hns being pleiotropic and gnd being intercalated/adjacent to the LPS/O-antigen biosynthesis it would be difficult to exactly delineate which cellular surface structure is involved.

(8) The conclusion section can be shortened significantly as much of the text is a repetition of the results/discussion section.

We thank the reviewer for their suggestion and have made edits to limit repetition in the conclusion section.

Reviewer #3 (Public Review):

Below I include several comments regarding potential weaknesses in the methodology used:

• The study was done with biological duplicates. In vitro studies usually require 3 samples for performing statistical robust analysis. Thus, are two duplicates enough to reach reproducible results? This is important because many genes are analyzed which could lead to false positives. That said, I acknowledge that genes that were confirmed through targeted mutagenesis led to similar phenotypic results. However, what about all those genes with higher p and q values that were not confirmed? Will those differences be real or represent false positives? Could this explain the differences obtained between this and other studies?

We thank the reviewer for their comment and apologize for the confusion, data were only pooled for the statistical analysis of gene essentiality. Here, two technical replicates of the input library were sequenced and the number of insertions per gene quantified (insertion index scores). These replicates had a correlation coefficient of r2 = 0.955, and the insertions per gene data were pooled to give total insertions index scores to predict gene essentiality. For conditional analyses (growth in urine or serum), replicate data were not combined. As mentioned previously, differences between this and other studies could also be attributed to inherent genomic differences or due to differences in experimental methodology, computational approaches, or the stringency of analysis used to categorize these genes.

• Two approaches are performed to investigate genes required for K. pneumoniae resistance to serum. In the first approach, the resistance to complement in serum is investigated. And here a total of 356 genes were identified to be relevant. In contrast, when genes required for overall resistance to serum are studied, only 52 genes seem to be involved. In principle, one would expect to see more genes required for overall resistance to serum and within them identify the genes required for resistance to complement. So this result is unexpected. In addition, it seems unlikely that 356 genes are involved in resistance to complement. Thus, is it possible false positives account for some of the results obtained?

We thank the reviewer for their comment and do believe false positives may account for some of the identified genes. Specifically, to the large contrast in genes, we believe this is due to the methodology as alluded to in our conclusion section. For overall resistance to serum, we used a longer time point (180 min exposure) where fewer surviving mutants are recovered hence fewer overall genes will be identified, whereas strains with short killing windows will have more (i.e. complement-mediated killing, 90 minute exposure).

Reviewer #3 (Recommendations For The Authors):

• In Figure 4 it is shown that genes important for growth in urine include several that are required for enterobactin uptake. Moreover, an in vitro experiment shows that the complementation of urine with iron increases K. pneumoniae growth. It would have been informative to do a competition experiment between the WT and Fep mutants in urine supplemented with iron. This could demonstrate that the genes identified are only necessary for conditions in which iron is in limiting concentrations and confirm that the defect of the mutants is not due to other characteristics of urine.

We appreciate this suggestion. We have now included a new panel (Figure 5G) addressing the supplementation of iron in urine for these select mutants.

• Considering the results section, the title for Figure 6 seems to be more appropriate for Figure 5.

Thank you, this has now been corrected.

Other points:

• Line 44: treat instead of treating

Thank you, this has now been corrected.

• Line 63: found that only 3 genes played a role instead of "found only 3 genes played a role"

Thank you, this has now been corrected.

• Line 105: is there any reason for only using males? Since UTIs are frequent in women? Why not use urine from women volunteers?

Due to accessibility of willing volunteers and human ethic application processes, only male samples were available. We are currently undertaking further studies to understand how male and female urine influences growth of uropathogens.

• Line 105: since the urine was filter-sterilized, maybe the authors can comment that another point that is missing in urine - and that it may be important to study - will be the presence of the urine microbiome and how this affects growth of K. pneumoniae.

We again thank the reviewer for this comment and have now edited the manuscript discussing how the absence of urine microbiome could affect growth (Line 659). As an aside, future studies in our lab are interested in looking at the role of commensal/microbiome co-interactions for essentiality/pathogenesis using TraDIS.

• Line 116: I understand that the 8 healthy volunteers combined males and females

Thank you, we have now edited this methods line to make this clearer.

• Line 120: incubate in serum 90 min and 180 RPM shaking: any reasons for using these conditions, any reference supporting these conditions?

Thank you for pointing this out, we were mirroring a previous K. pneumoniae serum-resistance study (doi.org/10.1128/iai.00043-).

• Line 156: space after the dot.

Thank you, we have now corrected this in the manuscript.

• Line 164: resulting reads were mapped to the K. pneumoniae: what are the parameters used for mapping (e.g. % of identity...)?

Thank you for bringing this to our attention, we have now included in our manuscript that we used the default parameters of BWA-MEM for mapping for minimum seed length (default -k =20bp exact match)

• Line 180: it will be good to upload to a repository the In-house scripts used or indicate the link beside the reference for those scripts.

Our scripts are derived from the pioneering TraDIS study (doi: 10.1101/gr.097097.109). We are currently still optimizing our scripts and intend to upload these to be publicly available. However, in the meantime we are more than happy to share them with other parties upon request.

• Line 191: why were genes classified as 12 times more likely to be situated in the left mode? Any particular reason for using this threshold?

We opted for a more-stringent threshold for classifying essential genes, in keeping with previous and comparable studies (doi.org/10.1371/journal.pgen.1003834).

• Line 209: do you mean Q-value of <0.05 instead of >0.05 ? How is this Q value is calculated, and which specific tests are applied?

Thank you for pointing out this Q value error, we have now corrected this in the manuscript. These values were generated using the biotradis tradis_comparison.R script which uses the EdgeR package. For further reading please see DOI: 10.1093/bioinformatics/btp616. The Q-values are from P values corrected for multiple testing by the Benjamini-Hochberg method.

• Line 212: again, which type of test is used? What about the urine growth analysis? The same type of tests were applied?

Thank you for bringing this to our attention, we have now indicated in the referenced method section the use of which package for which datasets (i.e. or serum). Line 212 refers to our use of the AlbaTraDIS package, which builds on the biotradis toolkit, to identify gene commonalities/differences in the selected growth conditions again using multiple testing by the Benjamini-Hochberg methods. For further reading, please refer to DOI: 10.1371/journal.pcbi.1007980

• Line 226: do the authors mean Sanger sequencing instead of SangerSanger sequencing?

Thank you, we have now corrected this in the manuscript.

• Line 239: does the WT strain contain another marker for differentiating this strain from the mutant? Or is the calculation of the number of WT CFUs done by subtracting the number of CFUs in media with antibiotics from the total number of CFUs in media without antibiotics? The former will be a more accurate method.

The calculation was based on the latter assumption, “number of WT CFUs done by subtracting the number of CFUs in media with antibiotics from the total number of CFUs in media without antibiotics”. We have now updated the methods section to make this clearer.

• Line 266: can you indicate approximately how many CFUs you have in this OD?

Thank you, we have now also indicated an approximate CFU for this mentioned OD600 (OD600 1 = 7 × 108 cells).

• Line 309: besides indicating Figure 1D please indicate here Dataset S1 (the table where one can see the list of essential and non-essential genes). This table is shown afterwards but I think it will be more appropriate to show it at the begging of the section.

Thank you, we have now taken on this recommendation and have now edited the manuscript to also indicate Dataset S1 earlier.

• Table 3. regarding the comparison of essential genes between different strains. I think it will be more clear if a Venn diagram was drawn including only genes that have homologs in all the studied strains (i.e. defining the core genome essentially).

We would like to thank the reviewer for suggesting a venn diagram and have now removed Table 3 which has been replaced with a new Figure 3.

• Line 461: replicates were combined for downstream analyses? But are replicates combined for doing the statistical analysis? If so, how is the statistical analysis performed? How is it taken into account the potential variability in the abundance in each library? An r of 0.9 is high but not perfect.

Technical replicates of the sequenced input library were combined following identification of a correlation coefficient of r2 = 0.955, for the calculation of insertion index scores used in gene essentiality analysis. While r2 = 0.955 is not perfect, discrepancies here can be attributed to higher variance in insertion index scores when sampling small genes, as these are represented by fewer insertions and the stochastic absence of a single insertion event has a greater effect on the overall IIS. Replicate data were not pooled for statistical analysis of mutant fitness (growth in urine and serum).

• Line 487: is there any control strain containing the kanamycin gene in a part of the genome that does not affect the growth of K. pneumoniae? This could be used to show that having the kanamycin gene does not provide any defect in urine growth.

We thank the reviewer for this suggestion but argue that introduction of the kanamycin gene into each unique loci may result in various levels of gene fitness that would be incomparable to a single control strain. Instead, we culture the ECL8 mutant library in urine and ensure that its kinetics are comparable to the wildtype. As the library contains thousands of kanamycin cassettes uniquely positioned across most of the genome with no observable growth defect, we do not anticipate the presence or expression of the cassette to have an appreciable impact.

• Line 569: in the methodology it was indicated that control cells were incubated in PBS for the same amount of time. I think this is an important control that is not cited in the results section. Please can you indicate?

We apologise for this misunderstanding due to how the methodology was written. The experiment did not sequence the PBS incubated samples as this was solely used a check for viability of the used K. pneumoniae ECL8 stock solution.

• Line 597: "Mutants in igaA are enriched in our experiments". Can you show this data?

We have now included this as a supplementary (Figure S11A)

• Line 615: when doing this calculation, I guess the authors take into account only genes that are also present in the other strains.

That is correct, we were aiming to highlight the high conservation of “essential genes” among all the selected strains.

• Line 627: why surprisingly? Because is too low. Then indicate.

Thank you, we have now edited this sentence to indicate that.

• Figure 4: please, for clarity, can you indicate the meaning of the colors in the figure itself besides indicating it in the figure legend?

Thank you, we have now included a color legend in these figure panels for clarity.

Reviewer #1 (Public Review):

The study provides strong evidence that some genes are conditionally essential in urine because of iron limitation.

The authors raise the intriguing possibility that some mutants can "cheat" by benefitting from the surrounding cells that are phenotypically wild-type. The authors make it clear that the proposed cheating mechanism is speculation, but there is a missed opportunity to test this hypothesis. I did not understand the authors' rationale for not doing this experiment.

In cases where there are disparities between studies, e.g., for genes inferred to be essential for serum resistance, it would be informative to test individual deletions for genes described as essential in only one study. The authors argue this is beyond the scope of the study. Their conclusions of the study are not impacted by the absence of these experiments, but readers will be left wondering which lists of conditionally essential genes are correct, or whether there are strain-dependent or condition-dependent contexts that influence conditional essentiality.

Reviewer #3 (Public Review):

In this study Gray and coworkers use a transposon mutant library in order to define: (i) essential genes for K. pneumoniae growth in LB medium, (ii) genes required for growth in urine, (iii) genes required for resistance to serum and complement mediated killing. Although there are previous studies, using a similar strategy, to describe essential genes for K. pneumoniae growth and genes required for serum resistance, this is the first work to perform such a study in urine. This is important because these types of pathogens can cause urinary tract infections. Moreover, the authors performed the work using a highly saturated library of mutants, which makes the results more robust, and used a clinically relevant strain from a pathotype for which similar studies have not been performed yet. Besides applying the transposon mutant library coupled with high-throughput sequencing, the authors validate some of the most relevant genes required for each condition using targeted mutagenesis. This is an important step to confirm that the results obtained from the library are reliable. Although this was done for only a small subset of the most significant genes. In addition, in vitro experiments involving complementation of urine with iron provide additional support to the results obtained with the mutants suggesting the importance of genes required for iron acquisition in a limiting-iron environment such as urine. Overall, the study is well-designed and written, and the methodology and analysis performed are adequate. The study would have benefited from in vivo experiments, including a mouse model of bacterial sepsis or urinary tract infections which could have demonstrated the role of some of the identified genes in the infection process. Nevertheless, the results obtained are informative for the scientific community since they pinpoint genes potentially more relevant in infections caused by K. pneumoniae. The identified genes could represent future targets for developing new therapies against a type of pathogen that is acquiring resistance to all available antibiotics. Although, as mentioned above, these potential targets should be confirmed using in vivo models.

One potential weakness of the work is that the TnSeq analysis only included two replicates per condition, thus it is possible that some of the differences detected may not be reproducible in future studies, first of all those that are less significant. In this sense, hundreds of genes were detected to be theoretically relevant for bacterial resistance to complement in serum. It is possible that some of these genes represent false positives. Thus, confirmation of the relevance of these genes in resistance to complement should be performed in future studies.

Author response:

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

Reviewer #3:

Summary:

The receptor tyrosine kinase Anaplastic Lymphoma Kinase (ALK) in humans is nervous system expressed and plays an important role as an oncogene. A number of groups have been studying ALK signalling in flies to gain mechanistic insight into its various roles. In flies, ALK plays a critical role in development, particularly embryonic development and axon targeting. In addition, ALK also was also shown to regulate adult functions including sleep and memory. In this manuscript, Sukumar et al., used a suite of molecular techniques to identify downstream targets of ALK signalling. They first used targeted DamID, a technique that involves a DNA methylase to RNA polymerase II, so that GATC sites in close proximity to PolII binding sites are marked. They performed these experiments in wild type and ALK loss of function mutants (using an Alk dominant negative ALkDN), to identify Alk responsive loci. Comparing these loci with a larval single cell RNAseq dataset identified neuroendocrine cells as an important site of Alk action. They further combined these TaDa hits with data from RNA seq in Alk Loss and Gain of Function manipulations to identify a single novel target of Alk signalling - a neuropeptide precursor they named Sparkly (Spar) for its expression pattern. They generated a mutant allele of Spar, raised an antibody against Spar, and characterised its expression pattern and mutant behavioural phenotypes including defects in sleep and circadian function.

Strengths:

The molecular biology experiments using TaDa and RNAseq were elegant and very convincing. The authors identified a novel gene they named Spar. They also generated a mutant allele of Spar (using CrisprCas technology) and raised an antibody against Spar. These experiments are lovely, and the reagents will be useful to the community. The paper is also well written, and the figures are very nicely laid out making the manuscript a pleasure to read.

We thank the reviewer for this analysis.

Weaknesses:

The manuscript has improved substantially in the revision. Yet, some concerns remain around the genetics and behavioural analysis which is incomplete and confusing. The authors generated a novel allele of Spar - Spar ΔExon1 and examined sleep and circadian phenotypes of this allele and of RNAi knockdown of Spar. The RNAi knockdown is a welcome addition. However, the authors only show one parental control the GAL4 / +, but leave out the other parental control i.e. the UAS RNAi / + e.g. in Fig. 9. It is important to show both parental controls.

We would like to express our gratitude for your insightful comments and feedback on our manuscript. We acknowledge the concerns raised regarding the genetics and behavioural analysis, and we appreciate the opportunity to address these issues. We have added the reciprocal UAS Spar-RNAi control in addition to the GAL4/+ control and we have incorporated both controls in the revised Figure 9, Figure 9 Supplementary Figure 1 and Figure 9 Supplementary Figure 2. Figure legends have been modified accordingly.

Further, the sleep and circadian characterisation could be substantially improved. It is unclear how sleep was calculated - what program was used or what the criteria to define a sleep bout was.

The data underwent analysis utilizing an Excel macro, as outlined in the study by Berlandi et al. (2017) (PMID: 28912696). As previously indicated in the methodology, sleep is characterized as 5 minutes of inactivity. The raw data acquired from the Trikenetics DAM system was input into an Excel spreadsheet, and the parameters, encompassing sleep and activity, were computed for each day of the trial as an average derived from the data of all living animals at that time. Subsequently, these parameters were exhibited over the course of the experiment. We have further detailed this part in the methods section to avoid confusion (Page 32 of revised MS).

In the legend for Fig 8c, it says sleep was shown as "percentage of time flies spend sleeping measured every 5min across a 24h time span". Sleep in flies is (usually) defined as at least 5 min of inactivity. With this definition, I'm not sure how one can calculate the % time asleep in a 5 min bin! Typically people use 30min or 60min bins.

We thank the reviewer for bringing this to our attention. As previously stated, in our experiments, sleep is defined as 5 minutes of inactivity. We have now modified the wording in the figure legend (Figure 8, Page 41), which was previously misleading.

The sleep numbers for controls also seem off to me e.g. in Fig. 8H and H' average sleep / day is ~100. Is this minutes of sleep? 100 min / day is far too low, is it a typo? The same applies to Figure 8, figure supplement 2. Other places e.g. Fig 8 figure supplement 1, avg sleep is around 1000 min / day.

The numbers for sleep bouts are also too low to me e.g. in Fig 9 number of sleep bouts avg around 4, and in Fig. 8 figure supplement 2 they average 1 sleep bout. There are several free software packages to analyse sleep data (e.g. Sleep Mat, PMID 35998317, or SCAMP). I would recommend that the authors reanalyse their data using one of these standard packages that are used routinely in the field. That should help resolve many issues.

We thank the reviewer for pointing this out. There was indeed a typo “missing 0”, resulting in 0 values as only 3 days of raw data were chosen for the analysis of the average sleep in the mentioned figures. We have corrected this mistake in all figures.

The circadian anticipatory activity analyses could also be improved. The standard in the field is to perform eduction analyses and quantify anticipatory activity e.g. using the method of Harrisingh et al. (PMID: 18003827). This typically computed as the ratio of activity in the 3hrs preceding light transition to activity in the 6hrs preceding light transition. The programs referenced above should help with this.

For consistency purposes we used the same macro excel (Berlandi et al, 2017) (PMID: 28912696) and followed the methodology of Harrisingh et al. (PMID: 18003827) to assess the anticipatory activity. We selected the activity in the 6 h period before lights on and defined it as a.m. anticipation, and the activity in the 6h period preceding the lights off and defined as p.m. anticipation (Figure 8 f-g).

Finally, in many cases I'm not sure that the appropriate statistical tests have been used e.g. in Fig 8c, 8e, 8h t-tests have been used when are three groups in the figure. The appropriate test here would an ANOVA, followed by post-hoc comparisons.

We agree with the reviewer’s comments. We have re-evaluated the data in Figure 8 b, c, e, h and h’ and Figure 8 Supplement 2 and 4 using a One-Way ANOVA followed by Tukey post-hoc test and we have indicated this in all legends.

Reviewer #2 (Public Review):

This manuscript illustrates the power of "combined" research, incorporating a range of tools, both old and new to answer a question. This thorough approach identifies a novel target in a well-established signalling pathway and characterises a new player in Drosophila CNS development.

Largely, the experiments are carried out with precision, meeting the aims of the project, and setting new targets for future research in the field. It was particularly refreshing to see the use of multi-omics data integration and Targeted DamID (TaDa) findings to triage scRNA-seq data. Some of the TaDa methodology was unorthodox, however, this does not affect the main finding of the study. The authors (in the revised manuscript) have appropriately justified their TaDa approaches and mentioned the caveats in the main text.

Their discovery of Spar as a neuropeptide precursor downstream of Alk is novel, as well as its ability to regulate activity and circadian clock function in the fly. Spar was just one of the downstream factors identified from this study, therefore, the potential impact goes beyond this one Alk downstream effector.

Reviewer #3 (Public Review):

Summary:

The receptor tyrosine kinase Anaplastic Lymphoma Kinase (ALK) in humans is nervous system expressed and plays an important role as an oncogene. A number of groups have been studying ALK signalling in flies to gain mechanistic insight into its various roles. In flies, ALK plays a critical role in development, particularly embryonic development and axon targeting. In addition, ALK was also shown to regulate adult functions including sleep and memory. In this manuscript, Sukumar et al., used a suite of molecular techniques to identify downstream targets of ALK signalling. They first used targeted DamID, a technique that involves a DNA methylase to RNA polymerase II, so that GATC sites in close proximity to PolII binding sites are marked. They performed these experiments in wild type and ALK loss of function mutants (using an Alk dominant negative ALkDN), to identify Alk responsive loci. Comparing these loci with a larval single cell RNAseq dataset identified neuroendocrine cells as an important site of Alk action. They further combined these TaDa hits with data from RNA seq in Alk Loss and Gain of Function manipulations to identify a single novel target of Alk signalling - a neuropeptide precursor they named Sparkly (Spar) for its expression pattern. They generated a mutant allele of Spar, raised an antibody against Spar, and characterised its expression pattern and mutant behavioural phenotypes including defects in sleep and circadian function.

Strengths:

The molecular biology experiments using TaDa and RNAseq were elegant and very convincing. The authors identified a novel gene they named Spar. They also generated a mutant allele of Spar (using CrisprCas technology) and raised an antibody against Spar. These experiments are lovely, and the reagents will be useful to the community. The paper is also well written, and the figures are very nicely laid out making the manuscript a pleasure to read.

Weaknesses:

The manuscript has improved very substantially in revision. The authors have clearly taken the comments on board in good faith. Yet, some small concerns remain around the behavioural analysis.

In Fig. 8H and H' average sleep/day is ~100. Is this minutes of sleep? 100 min/day is far too low, is it a typo?

The numbers for sleep bouts are also too low to me e.g. in Fig 9 number of sleep bouts avg around 4.

In their response to reviewers the authors say these errors were fixed, yet the figures appear not to have been changed. Perhaps the old figures were left in inadvertently?

The circadian anticipatory activity analyses could also be improved. The standard in the field is to perform eduction analyses and quantify anticipatory activity e.g. using the method of Harrisingh et al. (PMID: 18003827). This typically computed as the ratio of activity in the 3hrs preceding light transition to activity in the 6hrs preceding light transition.

In their response to reviewers, the authors have revised their anticipation analyses by quantifying the mean activity in the 6 hrs preceding light transition. However, in the method of Harrisingh et al., anticipation is the ratio of activity in the 3hrs preceding light transition to activity in the 6hrs preceding light transition. Simply computing the activity in the 6hrs preceding light transition does not give a measure of anticipation, determining the ratio is key.

Author response:

We kindly thank the senior editor, the reviewing editor, and the esteemed reviewers for their invaluable insights in enhancing our manuscript. The assessment and feedback, particularly on the role of directly released bacterial ATP versus OMV-delivered bacterial ATP and its role on neutrophils, addressing study limitations, and discussing our models is highly appreciated.

The points you raised let us critically rethink our approach, our results, and our conclusions. Furthermore, it gave us the chance to elaborate on some critical aspects that you mentioned. With your help, we will make clarifications throughout the manuscript, and we will add the data about neutrophil numbers in the different organs (reviewer #1, weaknesses #3).

Reviewer #1 (Public Review):

Summary:

• Extracellular ATP represents a danger-associated molecular pattern associated to tissue damage and can act also in an autocrine fashion in macrophages to promote proinflammatory responses, as observed in a previous paper by the authors in abdominal sepsis. The present study addresses an important aspect possibly conditioning the outcome of sepsis that is the release of ATP by bacteria. The authors show that sepsis-associated bacteria do in fact release ATP in a growth dependent and strain-specific manner. However, whether this bacterial derived ATP play a role in the pathogenesis of abdominal sepsis has not been determined. To address this question, a number of mutant strains of E. coli has been used first to correlate bacterial ATP release with growth and then, with outer membrane integrity and bacterial death. By using E. coli transformants expressing the ATP-degrading enzyme apyrase in the periplasmic space, the paper nicely shows that abdominal sepsis by these transformants results in significantly improved survival. This effect was associated with a reduction of peritoneal macrophages and CX3CR1+ monocytes, and an increase in neutrophils. To extrapolate the function of bacterial ATP from the systemic response to microorganisms, the authors exploited bacterial OMVs either loaded or not with ATP to investigate the systemic effects devoid of living microorganisms. This approach showed that ATP-loaded OMVs induced degranulation of neutrophils after lysosomal uptake, suggesting that this mechanism could contribute to sepsis severity.

Strengths:

• A strong part of the study is the analysis of E. coli mutants to address different aspects of bacterial release of ATP that could be relevant during systemic dissemination of bacteria in the host.

We want to thank the reviewer for recognizing this important aspect of our experimental approach.

Weaknesses:

• As pointed out in the limitations of the study whether ATP-loaded OMVs provide a mechanistic proof of the pathogenetic role of bacteria-derived ATP independently of live microorganisms in sepsis is interesting but not definitively convincing. It could be useful to see whether degranulation of neutrophils is differentially induced by apyrase-expressing vs control E. coli transformants.

We thank the reviewer for raising several important points. In our study, we assessed local and systemic effects of released bacterial ATP. The consequences of local bacterial ATP release were assessed using an apyrase-expressing E. coli transformant. Locally, bacterial ATP resulted in a decrease in neutrophil numbers and we hypothesize that directly released bacterial ATP either leads to neutrophil death (e.g. via P2X7 receptor (Proietti et al., 2019)) or interferes with the recruitment of neutrophils (e.g. via P2Y receptors (Junger, 2011)).

The systemic consequences were assessed using ATP-loaded and empty OMV. We have shown that degranulation is induced by OMV-derived bacterial ATP. ATP-containing OMV are engulfed by neutrophils, reach its endolysosomal compartment and might activate purinergic receptors, which then lead to aberrant degranulation. This concept, that needs to be explored in future studies, is fundamentally different from classical purinergic signaling via directly released bacterial ATP into the extracellular space.

It is possible that neutrophil degranulation is also modulated by directly released bacterial ATP. We agree that this should be assessed in future studies. Also, the role of OMV-derived bacterial ATP should be assessed locally as well as the importance of directly released vs. OMV-mediated bacterial ATP dissected locally. Based on our measurements (Figure 4-figure supplement 1A and Figure 5C), we estimate that the effect of OMV-derived bacterial ATP might be much smaller than the effects of directly released bacterial ATP. Thus, direct ATP release might predominate locally. However, we fully agree that this has to be investigated in a future study to reconcile the different aspects of bacterial ATP signaling. A paragraph will be added to the manuscript, in which we discuss this particular issue.

• Also, the increase of neutrophils in bacterial ATP-depleted abdominal sepsis, which has better outcomes than "ATP-proficient" sepsis, seems difficult to correlate to the hypothesized tissue damage induced by ATP delivered via non-infectious OMVs.

We fully acknowledge the mentioned discrepancy. What we propose is that bacterial ATP exhibits different functions that are dependent on the release mechanism (see above). Locally, in the peritoneal cavity, neutrophil numbers are decreased by directly released bacterial ATP. Remotely, ATP is delivered via OMV and impacts on neutrophil function. We agree that, in particular, in the peritoneal cavity, both effects may play a role. However, the impact of directly released bacterial ATP seems to be dominant (see above).

We propose that neutrophils are decreased locally because of directly released bacterial ATP, which prevents efficient infection control and, therefore, impairs sepsis survival. In addition, these fewer neutrophils might even be dysregulated by the engulfment of bacterial ATP delivered via OMV, which leads to an upregulated and possibly aberrant degranulation process worsening local and remote tissue damage. We agree that in addition to neutrophil numbers, the function of local neutrophils should be assessed with and without the influence of OMV-delivered bacterial ATP. This could be done by RNA sequencing of primary neutrophils from the peritoneal cavity or neutrophil cell lines as well as degranulation assays.

• Are the neutrophils counts affected by ATP delivered via OMVs?

This is difficult to show in the peritoneal cavity where we have both, directly released bacterial ATP and OMV-derived bacterial ATP. We assessed such putative difference, however, for the systemic organs and the blood, where we did not find any differences in neutrophil numbers. We will include the figure in the revised manuscript as Figure 6-figure supplement 3C.

Author response image 1.

• A comparison of cytokine profiles in the abdominal fluids of E. coli and OMV treated animals could be helpful in defining the different responses induced by OMV-delivered vs bacterial-released ATP. The analyses performed on OMV treated versus E. coli infected mice are not closely related and difficult to combine when trying to draw a hypothesis for bacterial ATP in sepsis.

We fully agree that there are several open questions that remain to be elucidated, in particular, to differentiate the local role of directly released versus OMV-delivered bacterial ATP. In this study, we laid the foundation for future in vivo research to examine the specific role of bacterial ATP in sepsis. Such future research avenues might be to investigate the local effects of OMV-delivered bacterial ATP, and how neutrophil migration, apoptosis and degranulation are altered. We agree that exploration of the local secretory immune response and cytokine profiles are relevant to understand the different mechanisms of how bacterial ATP alters sepsis. However, such experiments should be ideally performed in systems where the source and the delivery of ATP can be modulated locally.

• Also it was not clear why lung neutrophils were used for the RNAseq data generation and analysis.

Thank you for this remark. We have chosen primary lung neutrophils for four reasons:

(1) Isolation of primary lung neutrophils allowed us to assess an in vivo response that would not have been possible with cell lines.

(2) The lung and the respiratory system are among the clinically most important organs affected during sepsis resulting in a significant cause of mortality.

(3) We show in Figure 6C that specifically in the lung, OMV are engulfed by neutrophils, which shows the relevance of the lung also in our study context.

(4) And finally, lung neutrophils were chosen to examine specifically distant and not local effects.

Reviewer #2 (Public Review):

Summary:

• In their manuscript "Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis", Daniel Spari et al. explored the dual role of ATP in exacerbating sepsis, revealing that ATP from both host and bacteria significantly impacts immune responses and disease progression.

Strengths:

• The study meticulously examines the complex relationship between ATP release and bacterial growth, membrane integrity, and how bacterial ATP potentially dampens inflammatory responses, thereby impairing survival in sepsis models. Additionally, this compelling paper implies a concept that bacterial OMVs act as vehicles for the systemic distribution of ATP, influencing neutrophil activity and exacerbating sepsis severity.

We thank the reviewer for mentioning these key points and supporting the relevance of our study.

Weaknesses:

(1) The researchers extracted and cultivated abdominal fluid on LB agar plates, then randomly picked 25 colonies for analysis. However, they did not conduct 16S rRNA gene amplicon sequencing on the fluid itself. It is worth noting that the bacterial species present may vary depending on the individual patients. It would be beneficial if the authors could specify whether they've verified the existence of unculturable species capable of secreting high levels of Extracellular ATP.

Most septic complications are caused by a limited spectrum of bacteria, belonging mainly either to the Firmicutes or the Proteobacteria phyla, including E. coli, K. pneumoniae, S. aureus or E. faecalis (Diekema et al., 2019; Mureșan et al., 2018). We validated this well documented existing evidence by randomly assessing 25 colonies. For the planned experiments, it was crucial to work with culturable bacteria; otherwise, ATP measurements, the modulation of ATP generation or loading of OMV would not have been possible. Using such culturable bacteria allowed us to describe mechanisms of ATP release.

We fully agree that hard-to-culture or unculturable bacteria might contribute significantly to septic complications. This, however, would need to be explored in future studies using extensive culturing methods (Cheng et al., 2022).

(2) Do mice lacking commensal bacteria show a lack of extracellular ATP following cecal ligation puncture?

ATP is typically secreted by many cells of the host in active and passive manners in the case of any injury, including cecal ligation and puncture (Burnstock, 2016; Dosch et al., 2018; Eltzschig et al., 2012; Idzko et al., 2014). We hypothesize that bacterial ATP is a potential priming agent at early stages of sepsis, and indeed, at such early time points, a comparison of peritoneal ATP levels between germfree and colonized mice could support our hypothesis. Future studies addressing this question must, however, correct for the different immune responses between germ-free and colonized mice. This is of utmost importance, especially for the cecal ligation and puncture model, since the cecum of germ-free mice is extremely large, making such experiments hard to control.

(3) The authors isolated various bacteria from abdominal fluid, encompassing both Gram-negative and Gram-positive types. Nevertheless, their emphasis appeared to be primarily on the Gram-negative E. coli. It would be beneficial to ascertain whether the mechanisms of Extracellular ATP release differ between Gram-positive and Gram-negative bacteria. This is particularly relevant given that the Gram-positive bacterium E. faecalis, also isolated from the abdominal fluid, is recognized for its propensity to release substantial amounts of Extracellular ATP.

We fully agree with this comment. In this paper, we used E. coli as our model organism to determine the principles of sepsis-associated bacterial ATP release and therefore focused on gram-negative bacteria. In addition to the direct, growth-dependent release, we found a relevant impact of OMV-delivered bacterial ATP. For this latter purpose, a gram-negative strain, in which OMV generation has been well described (Schwechheimer & Kuehn, 2015), was chosen. Recently, gram-positive bacteria have been shown to secrete ATP and OMV as well (Briaud & Carroll, 2020; Hironaka et al., 2013; Iwase et al., 2010). Given the fundamental differences in the structure of the cell wall of gram-positive bacteria and the mechanisms of OMV generation and release, future studies are required to assess the relevance of directly released and OMV-delivered ATP in gram-positive bacteria.

(4) The authors observed changes in the levels of LPM, SPM, and neutrophils in vivo. However, it remains uncertain whether the proliferation or migration of these cells is modulated or inhibited by ATP receptors like P2Y receptors. This aspect requires further investigation to establish a convincing connection.

We fully agree with this comment. The decrease in LPM and the consequential predomination of SPM have been well described after inflammatory stimuli in the context of the macrophage disappearance reaction (Ghosn et al., 2010). Also, it has been shown that purinergic signaling modulates infiltration of neutrophils and can lead to cell death as a consequence of P2Y and P2X receptor activation (Junger, 2011; Proietti et al., 2019). In our study, we propose that intracellular purinergic receptors contribute to neutrophil function during sepsis. After introducing the general principles and fundaments of bacterial ATP with our studies, we fully agree that additional experiments need to address downstream purinergic receptor activation. That, however, would go beyond the scope of our study.

(5) Additionally, is it possible that the observed in vivo changes could be triggered by bacterial components other than Extracellular ATP? In this research field, a comprehensive collection of inhibitors is available, so it is desirable to utilize them to demonstrate clearer results.

This question is of utmost importance and defined the choice of our model and experimental approach. When we started the project, we used two different E. coli mutants that release low (ompC) and high (eaeH) amounts of ATP. However, the limitation of this approach is that these are different bacteria, which may also differ in the components they secrete or the surface proteins they express. We, therefore, decided against that approach. With the approach we finally used (same bacterium, just with and without ATP), we aimed to minimize the influence of non-ATP bacterial components.

(6) Have the authors considered the role of host-derived Extracellular ATP in the context of inflammation?

Yes, the role of host-derived extracellular ATP in inflammation and sepsis is well-established with contradictory results (Csóka et al., 2015; Ledderose et al., 2016). This conflicting data was the rationale to test the relevance of bacterial ATP. We suggest that bacterial ATP is essential in the early phase of sepsis when bacteria invade the sterile compartment and before efficient host response, including the eukaryotic release of ATP, is established.

(7) The authors mention that Extracellular ATP is rapidly hydrolyzed by ectonucleotases in vivo. Are the changes of immune cells within the peritoneal cavity caused by Extracellular ATP released from bacterial death or by OMVs?

This is a relevant question that was also asked by reviewer #1, and we answered it in detail above (weaknesses comment #1 and #2). From our ATP measurements (Figure 4-figure supplement 1A and Figure 5C), we conclude that locally, the role of directly released bacterial ATP (extracellular) predominates over OMV-derived bacterial ATP. Furthermore, the mechanisms between directly released and OMV-derived bacterial ATP (within OMV, engulfed and transported to the endolysosomal compartment) are different, and especially extracellular ATP has been described to lead to apoptosis via P2X7 signaling.

(8) In the manuscript, the sample size (n) for the data consistently remains at 2. I would suggest expanding the sample size to enhance the robustness and rigor of the results.

Two biological replicates (independent cultures) were only used for the bacteria cultures in Figure 1, Figure 2, and Figure 3, which achieved similar results and the standard deviation remained very small, indicating its robustness. In the in vitro experiments in Figure 5 we used a sample size of 6 (three biological replicates measured in technical duplicates), since we saw bigger deviations in our measurements. For the in vivo experiments, we always used 5 or more animals in at least two independent experiments.

References

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Burnstock, G. (2016). P2X ion channel receptors and inflammation. Purinergic Signalling, 12(1), 59–67. https://doi.org/10.1007/s11302-015-9493-0

Cheng, A. G., Ho, P.-Y., Aranda-Díaz, A., Jain, S., Yu, F. B., Meng, X., Wang, M., Iakiviak, M., Nagashima, K., Zhao, A., Murugkar, P., Patil, A., Atabakhsh, K., Weakley, A., Yan, J., Brumbaugh, A. R., Higginbottom, S., Dimas, A., Shiver, A. L., … Fischbach, M. A. (2022). Design, construction, and in vivo augmentation of a complex gut microbiome. Cell, 185(19), 3617-3636.e19. https://doi.org/10.1016/j.cell.2022.08.003

Csóka, B., Németh, Z. H., Törő, G., Idzko, M., Zech, A., Koscsó, B., Spolarics, Z., Antonioli, L., Cseri, K., Erdélyi, K., Pacher, P., & Haskó, G. (2015). Extracellular ATP protects against sepsis through macrophage P2X7 purinergic receptors by enhancing intracellular bacterial killing. The FASEB Journal, 29(9), 3626–3637. https://doi.org/10.1096/fj.15-272450

Diekema, D. J., Hsueh, P.-R., Mendes, R. E., Pfaller, M. A., Rolston, K. V., Sader, H. S., & Jones, R. N. (2019). The Microbiology of Bloodstream Infection: 20-Year Trends from the SENTRY Antimicrobial Surveillance Program. Antimicrobial Agents and Chemotherapy, 63(7), e00355-19. https://doi.org/10.1128/AAC.00355-19

Dosch, M., Gerber, J., Jebbawi, F., & Beldi, G. (2018). Mechanisms of ATP Release by Inflammatory Cells. International Journal of Molecular Sciences, 19(4), 1222. https://doi.org/10.3390/ijms19041222

Eltzschig, H. K., Sitkovsky, M. V., & Robson, S. C. (2012). Purinergic Signaling during Inflammation. New England Journal of Medicine, 367(24), 2322–2333. https://doi.org/10.1056/NEJMra1205750

Ghosn, E. E. B., Cassado, A. A., Govoni, G. R., Fukuhara, T., Yang, Y., Monack, D. M., Bortoluci, K. R., Almeida, S. R., Herzenberg, L. A., & Herzenberg, L. A. (2010). Two physically, functionally, and developmentally distinct peritoneal macrophage subsets. Proceedings of the National Academy of Sciences, 107(6), 2568–2573. https://doi.org/10.1073/pnas.0915000107

Hironaka, I., Iwase, T., Sugimoto, S., Okuda, K., Tajima, A., Yanaga, K., & Mizunoe, Y. (2013). Glucose Triggers ATP Secretion from Bacteria in a Growth-Phase-Dependent Manner. Applied and Environmental Microbiology, 79(7), 2328–2335. https://doi.org/10.1128/AEM.03871-12

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eLife assessment

This fundamental study advances our understanding of the role of bacterial derived extracellular ATP in the pathogenesis of sepsis. The evidence supporting the conclusions is solid, particularly with the analysis of E. coli mutants to address different aspects of bacterial release of ATP. The work will be of broad interest to researchers on microbiology and infectious diseases.

Reviewer #1 (Public Review):

Summary:

Extracellular ATP represents a danger-associated molecular pattern associated to tissue damage and can act also in an autocrine fashion in macrophages to promote proinflammatory responses, as observed in a previous paper by the authors in abdominal sepsis. The present study addresses an important aspect possibly conditioning the outcome of sepsis that is the release of ATP by bacteria. The authors show that sepsis-associated bacteria do in fact release ATP in a growth dependent and strain-specific manner. However, whether this bacterial derived ATP play a role in the pathogenesis of abdominal sepsis has not been determined. To address this question, a number of mutant strains of E. coli has been used first to correlate bacterial ATP release with growth and then, with outer membrane integrity and bacterial death. By using E. coli transformants expressing the ATP-degrading enzyme apyrase in the periplasmic space, the paper nicely shows that abdominal sepsis by these transformants results in significantly improved survival. This effect was associated with a reduction of peritoneal macrophages and CX3CR1+ monocytes, and an increase in neutrophils. To extrapolate the function of bacterial ATP from the systemic response to microorganisms, the authors exploited bacterial OMVs either loaded or not with ATP to investigate the systemic effects devoid of living microorganisms. This approach showed that ATP-loaded OMVs induced degranulation of neutrophils after lysosomal uptake, suggesting that this mechanism could contribute to sepsis severity.

Strengths:

A strong part of the study is the analysis of E. coli mutants to address different aspects of bacterial release of ATP that could be relevant during systemic dissemination of bacteria in the host.

Weaknesses:

As pointed out in the limitations of the study whether ATP-loaded OMVs provide a mechanistic proof of the pathogenetic role of bacteria-derived ATP independently of live microorganisms in sepsis is interesting but not definitively convincing. It could be useful to see whether degranulation of neutrophils is differentially induced by apyrase-expressing vs control E. coli transformants. Also, the increase of neutrophils in bacterial ATP-depleted abdominal sepsis, which has better outcomes than "ATP-proficient" sepsis, seems difficult to correlate to the hypothesized tissue damage induced by ATP delivered via non-infectious OMVs. Are the neutrophils counts affected by ATP delivered via OMVs? A comparison of cytokine profiles in the abdominal fluids of E. coli and OMV treated animals could be helpful in defining the different responses induced by OMV-delivered vs bacterial-released ATP. The analyses performed on OMV treated versus E. coli infected mice are not closely related and difficult to combine when trying to draw a hypothesis for bacterial ATP in sepsis. Also it was not clear why lung neutrophils were used for the RNAseq data generation and analysis.

Reviewer #2 (Public Review):

Summary:

In their manuscript "Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis", Daniel Spari et al. explored the dual role of ATP in exacerbating sepsis, revealing that ATP from both host and bacteria significantly impacts immune responses and disease progression.

Strengths:<br /> The study meticulously examines the complex relationship between ATP release and bacterial growth, membrane integrity, and how bacterial ATP potentially dampens inflammatory responses, thereby impairing survival in sepsis models. Additionally, this compelling paper implies a concept that bacterial OMVs act as vehicles for the systemic distribution of ATP, influencing neutrophil activity and exacerbating sepsis severity.

Weaknesses:

(1) The researchers extracted and cultivated abdominal fluid on LB agar plates, then randomly picked 25 colonies for analysis. However, they did not conduct 16S rRNA gene amplicon sequencing on the fluid itself. It is worth noting that the bacterial species present may vary depending on the individual patients. It would be beneficial if the authors could specify whether they've verified the existence of unculturable species capable of secreting high levels of Extracellular ATP.

(2) Do mice lacking commensal bacteria show a lack of extracellular ATP following cecal ligation puncture?

(3) The authors isolated various bacteria from abdominal fluid, encompassing both Gram-negative and Gram-positive types. Nevertheless, their emphasis appeared to be primarily on the Gram-negative E. coli. It would be beneficial to ascertain whether the mechanisms of Extracellular ATP release differ between Gram-positive and Gram-negative bacteria. This is particularly relevant given that the Gram-positive bacterium E. faecalis, also isolated from the abdominal fluid, is recognized for its propensity to release substantial amounts of Extracellular ATP.

(4) The authors observed changes in the levels of LPM, SPM, and neutrophils in vivo. However, it remains uncertain whether the proliferation or migration of these cells is modulated or inhibited by ATP receptors like P2Y receptors. This aspect requires further investigation to establish a convincing connection.

(5) Additionally, is it possible that the observed in vivo changes could be triggered by bacterial components other than Extracellular ATP? In this research field, a comprehensive collection of inhibitors is available, so it is desirable to utilize them to demonstrate clearer results.

(6) Have the authors considered the role of host-derived Extracellular ATP in the context of inflammation?

(7) The authors mention that Extracellular ATP is rapidly hydrolyzed by ectonucleotases in vivo. Are the changes of immune cells within the peritoneal cavity caused by Extracellular ATP released from bacterial death or by OMVs?

(8) In the manuscript, the sample size (n) for the data consistently remains at 2. I would suggest expanding the sample size to enhance the robustness and rigor of the results.

Author response:

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

Reviewing Editor's comments:

There appears to be several mistakes/missing details in the additional statistical analyses reported in their response to Reviewer #'1 comments:

(1) Detecting differentially expressed genes (DEGs):

Reviewer #1 suggested adding an interaction term between sex and environment (ethnicity) in identifying DEGs. The authors performed ANCOVA analysis with sex and ethnicity as covariates (but not the interaction) and found sex explained more variance. This is not what the reviewer asked for, and the results do not help identify DEGs.

We understand the reviewer’s suggestion about identification of DEGs using sex × ethnicity interaction. However, we could not find an appropriate tool to make such analysis, though we have carefully searched it in the literature. It should be noted that the interaction analysis between sex and environment was only designed to study genotype data rather than gene expression data. Besides, considering that we have added multiple covariates in our DEG detection, adding an interaction term between sex and environment (ethnicity) in identifying DEGs make the formulation too complex to resolve using current tools. Alternatively, we have made a linear regression model to test the explanation of sex for DEG detection in the revision (see details below). We would appreciate if the reviewer could provide any available tools, or previous studies conducting interaction analysis for DEG identification.

(2) Overlap between DEGs and genes under positive selection in Tibetans (TSNGs)

The authors claimed that the overlaps are significantly enriched in "sex-combined" set (p=0.048) and "male-only" set (p=9e-4), but it seems that the authors calculated the p-values incorrectly. Based on the histogram shown in Fig 3R (left penal), at least 750 out of 10,000 permutations led to 4 genes in overlap and there are additional permutations with 5 or more genes in overlap, so the p-value for the sex-combined set cannot be 0.048. In addition, the permutation procedure is somewhat questionable: it is unclear whether randomly sampling 192 genes from the human genome is reasonable choice, without matching for relevant gene features.

As we explained in the response to Reviewer-1, we agree with the reviewer’s point that random sampling of genes in permutation should be extracted from genes expressed in each tissue rather than the entire genome. Based on this updated random sampling procedure, we redid the analysis, and our previous conclusions remain unchanged.

(3) Polygenic adaptation signal based on eQTL information:

The PolyGraph method is designed for highly polygenic traits with causal variants spread across the genome. However, the genetic architecture of the expression of a gene is much less polygenic with at most few cis- eQTLs per gene, so the PolyGraph model does not apply for expression of individual genes. On the other hand, eQTLs for different genes are associated with different "traits", so they cannot be simply aggregated together for PolyGraph analysis. Based on the Methods description, it is unclear how the authors ran the PolyGraph analysis on eQTLs practically and whether this practice is appropriate for detecting polygenic adaptation signal on gene expression.

We understand the reviewer’s concern on polygenic adaptation analysis. In this study, we tested whether the estimated polygenic scores from eQTLs (estimated using sums of allele frequencies at independent eQTLs weighted by their effect sizes) were significantly enriched in Tibetans compared to other populations. The detailed descriptions of polygenic test are provided in the response to Reviewer-1.

Reviewer #1 (Public Review):

The revised manuscript new presented 1) a permutation-based test for the significance of the overlap between DEGs and genes with positive selection signals in Tibetans, and 2) polygenic adaptation test for the eQTLs. I make my suggestions in detail as below:

Major Comments

(1) My previous concern regarding the DEG analysis remains unresolved. Although the authors agreed in their response that the difference between the male- and female-specific DEGs are insufficient to the difference between sex-combined and sex-specific DEGs (Figure S6). However, the results section still states the opposite pattern between males and females as a decisive reason for the difference (p. 9, lines 236-239). Again, I would like to recommend the authors to test alternative ways of analysis to boost statistical power for DEG detection other than simply splitting data into males and females and performing analysis in each subset. For example, the authors may consider utilizing gene by environment interaction analysis schemes here biological sex as an environmental factor.

To evaluate the effect of gene expression of each layer by sex, we adopted two strategies: 1) to calculate the variance explained by sex from the expression data; 2) to evaluate the statistical significance of association between sex from the expression data.

Firstly, we observed a significantly higher variance explained by sex than by ethnicity in six layers of the placenta (see details in our previous response to reviewers).

Then, we performed a linear regression model to test whether gender affects the gene expression. For each gene, a linear regression model was made by using R glm function with sex as covariates: glm (gene expression ~ sex). We discovered 5,865 genes significantly associated with sex, and most of them were located on the sex chromosomes. We observed 62.63% genes overlapped with those genes with opposite differential directions between the sex-combined and the sex-specific analyses.

Considering the opposite direction of DEGs is likely only one of the explanations for the discrepancy between the sex-combined and the sex-specific DEGs, and there might be alternative mechanism for this phenomenon, we have tune down the description of this point in the revised manuscript:

“Considering 62.63% of DEGs (248/396) with an opposite direction of between-population expression divergence in males and females, respectively (Figure S6), we reckon that there might be other factors such as sample size or cell composition affecting the identification of DEGs, which could cancel out the differences in the sex-combined analysis.” (Page 9)

(2) Multiple testing schemes are still sub-optimal in some cases. Most of all, the p-values in the WGCNA analysis (p. 11), the authors corrected for the number of traits (n=12) after adjusting for the correlation between them. However, they did not mention whether they counted for the number of modules they tested at all (n=136 and 161 for males and females, respectively). Whether they account for the number of modules will make a substantial difference in the significance threshold, please incorporate and describe a proper multiple testing scheme for this analysis.

We understand the reviewer’s point. Indeed, for multiple testing schemes, we considered both the number of traits and the number of modules. For the number of modules, multiple testing correction is already imbedded in WGCNA, as described in the published studies (Li et al. 2018; Zeng et al. 2023).

(3) Evidence for natural selection on the observed DEG pattern is still weak and not properly described.

(1) For the overlap between DEGs and TSNGs, the authors introduced a permutation-based test, but used a total set of genes in the human genome as a comparison set (p. 25, lines 699-700). I believe that the authors should sample random sets of genes from those already expressed in each tissue to make a fair comparison.

We agree with the reviewer’s point that random sampling of genes in permutation should be extracted from genes expressed in each tissue, which is a fair comparison between the observed and the simulated counts of the overlapped genes.

Therefore, for each permutation, we randomly extracted 192 genes from all the placenta expressed genes identified from the seven layers (17,284 genes in total), and we overlapped them with DEGs of the three sets (female + male, female only, and male only) and counted the gene numbers. After 10,000 permutations, we constructed a null distribution for each set, and found that the overlaps between DEGs and TSNGs were significantly enriched in the “sex-combined” set (p-value = 0.0123) and the “male-only” set (p-value < 1e-4), but not in the “female-only” set (p-value = 0.0572) (Figure R1). This result suggests that the observed DEGs are significantly enriched in TSNGs when compared to the set of random sampling, especially for the DEGs from the “male-only” set.

Author response image 1.

The distribution of 10,000 permutation tests of counts of the overlapped genes between 192 TSNGs and the DEGs randomly selected from the expressed genes in the placenta. The red-dashed lines indicate the observed values based on the randomly selected DEGs.

(2) The entire polygraph analysis for polygenic adaptation is poorly described. The current version of the Methods does not clarify i) for which genes the eQTLs are discovered, 2) how the authors performed the eQTL analysis, iii) how the authors polarized the effect, and iv) how they set up a comparison between the eQTLs and the others.

Considering the RNA-seq data of placenta mostly represent the transcriptomes of the newborns according to our analysis on maternal-fetal compositions of each dissected layer, we conducted eQTL analysis using the fetal genotypes and the placental tissue gene expression data (TPM) using R package MatrixEQTL (https://github.com/andreyshabalin/MatrixEQTL), and the altitude and maternal age were taken as covariates. We take a window 1 Mb upstream and 1 Mb downstream around each SNP to select genes or expression probes to test. Associations between these SNP–gene combinations are calculated using linear model. This tool can distinguish local (cis-) and distant (trans) eQTLs. We performed separate corrections for multiple testing.

Finally, we detected 5,251 eQTLs (involving 319 eGenes), covering the SNPs significantly associated with gene expression (p-value < 5e-8). To identify the signatures of polygenic selection in Tibetans using eQTL information, we removed those SNPs in linkage disequilibrium (r2 > 0.2 in 1000 Genome Project) and obtained 176 independent eQTLs as input into PolyGraph (Racimo et al. 2018). QB (Racimo et al. 2018) and QX (Berg and Coop 2014) framework are used in Polygraph to determine whether the estimated polygenic scores exhibit more variance among populations than null expectation under genetic drift, by retrieving the summary statistics from the eQTL set.

In this study, we focused on testing whether the estimated polygenic scores from eQTLs (estimated using sums of allele frequencies at independent eQTLs weighted by their effect sizes) were significantly enriched in Tibetans compared to other populations. The significance was evaluated by comparing to 10,000 sets of the control SNPs. Each set of control SNPs was randomly drawn from the genomic SNPs, and contained an equal number of SNPs as the eQTLs matched one-to-one by minor allele frequency.

The PolyGraph result showed that Tibetans have a clear signature of polygenic selection on gene expression (Bonferroni-corrected p-value = 0.003, Figure S12). In other words, the frequency of alleles associated with gene expression (up-regulation or down-regulation) were specifically enriched in Tibetans, a signal of positive selection.

Minor comments (1) In Figure S1, the amount of variance explained by PC1 and PC2 need to be corrected. PC1 explains less variance than PC2 (0.11 vs 0.68%).

It was a typing error that mixed up the variances between PC1 and PC2. We have corrected it in the revised version.

(2) In the section "Sex-biased expression divergence ..." (p. 8), the authors are using the term "gender" instead of sex. Considering that they are talking about the biological sex of each infant, I believe that sex is a more appropriate term to be used than gender.

Following the reviewer’s suggestion, we rephrased “gender” as “sex” in the revised manuscript to describe the biological differences between females and males.

Reviewer #3 (Public Review):

More than 80 million people live at high altitude. This impacts health outcomes, including those related to pregnancy. Longer-lived populations at high altitudes, such as the Tibetan and Andean populations show partial protection against the negative health effects of high altitude. The paper by Yue sought to determine the mechanisms by which the placenta of Tibetans may have adapted to minimise the negative effect of high altitude on fetal growth outcomes. It compared placentas from pregnancies from Tibetans to those from the Han Chinese. It employed RNAseq profiling of different regions of the placenta and fetal membranes, with some follow-up of histological changes in umbilical cord structure and placental structure. The study also explored the contribution of fetal sex in these phenotypic outcomes.

A key strength of the study is the large sample sizes for the RNAseq analysis, the analysis of different parts of the placenta and fetal membranes, and the assessment of fetal sex differences.

A main weakness is that this study, and its conclusions, largely rely on transcriptomic changes informed by RNAseq. Changes in genes and pathways identified through bioinformatic analysis were not verified by alternate methods, such as by western blotting, which would add weight to the strength of the data and its interpretations. There is also a lack of description of patient characteristics, so the reader is unable to make their own judgments on how placental changes may link to pregnancy outcomes. Another weakness is that the histological analyses were performed on n=5 per group and were rudimentary in nature.

For the three weaknesses raised by the reviewer, here are our responses:

(1) Considering that our conclusions largely rely on the transcriptomic data, we agree with reviewer that more experiments are needed to validate the results from our transcriptomic data. However, this study was mainly aimed to provide a transcriptomic landscape of high-altitude placenta, and to characterize the gene-expression difference between native Tibetans and Han migrants. The molecular mechanism exploration is not the main task of this study, and more validation experiments are warranted in the future.

(2) For the lack of description of patient characteristics, actually, we provided three-level results on the placental changes of Tibetans: macroscopic phenotypes (higher placental weight and volume), histological phenotypes (larger umbilical vein walls and umbilical artery intima and media; lower syncytial knots/villi ratios) and transcriptomic phenotypes (DEG and differential modules). Combined with the previous studies, these placenta changes suggest a better reproductive outcome. For example, the placenta volume shows a significantly positive correlation with birth weight (R = 0.31, p-value = 2.5e-16), therefore, the larger placenta volume of Tibetans is beneficial to fetal development at high altitude. In addition, the larger umbilical vein wall and umbilical artery intima and media of Tibetans can explain their adaptation in preventing preeclampsia.

(3) For the sample size of histological analyses, we understand the reviewer’s concern that 5 vs. 5 samples are not very large in histological analyses. This is because it was difficult to collect high-altitude Han placenta samples, and we only got 13 Han samples, from which we selected 5 infant sex matched samples.

Minor point:

I feel the authors have responded well to the other reviewer comments. However, I am disappointed that the authors did not address my comment related to the validation of their RNAseq data. In particular, they failed to add new data that verifies and supports their RNAseq findings on pathways affected. This is imperative as their conclusions are based solely on the RNAseq analysis. The only other comment I have is that they should add a description of all abbreviations, including those in the supplementary information (like Table S12).

For experimental validation of transcriptome, we understand the concern of reviewer. However, as we mentioned before, this study was mainly aimed to provide a transcriptomic landscape of high-altitude placenta, the molecular mechanism exploration is not the main task of this study, and more validation experiments are warranted in the future. Actually, we have tune down the description of power from transcriptomic data for explanation of biological difference, and called for the further functional validations in the future:

“the transcriptome data is insufficient to explain the underlying molecular mechanisms of genetic adaptation in Tibetans. Future single-cell transcriptome analysis and functional validations of the candidate genes are warranted to reveal the responsible cell types and the molecular pathways.” (highlighted in Page 20)

For abbreviations of the manuscript, according to the reviewer’s suggestion, we added descriptions of all abbreviations of this study in corresponding position (Table S1 and S12).

References

Berg JJ, and Coop G (2014). A population genetic signal of polygenic adaptation. PLoS Genet 10(8): e1004412.

Li J, et al. (2018). Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design. Sci Rep 8(1): 622.

Racimo F, Berg JJ, and Pickrell JK (2018). Detecting Polygenic Adaptation in Admixture Graphs. Genetics 208(4): 1565-1584.

Zeng JF, et al. (2023). Functional investigation and two-sample Mendelian randomization study of neuropathic pain hub genes obtained by WGCNA analysis. Frontiers in Neuroscience 17.

eLife assessment

This fundamental study reports differential expression of key genes in full-term placenta between Tibetans and Han Chinese at high elevations, which are more pronounced in the placentae of male than in female fetuses. If validated as functionally relevant, these results will help us understand how human populations adapt to high elevation by mitigating the negative effects of low oxygen on fetal growth. While the differential gene expression analyses are solid, the downstream analyses offer incomplete support for the connection to hypoxia-specific responses and adaptive genetic variation.

Joint Public Review:

This manuscript by Yue et al. aims to understand the molecular mechanisms underlying the better reproductive outcomes of Tibetans at high altitude by characterizing the transcriptome and histology of full-term placenta of Tibetans and compare them to those Han Chinese at high elevations.

The approach is innovative, and the data collected are valuable for testing hypotheses regarding the contribution of the placenta to better reproductive success of populations that adapted to hypoxia. The authors identified hundreds of differentially expressed genes (DEGs) between Tibetans and Han, including the EPAS1 gene that harbors the strongest signals of genetic adaptation. The authors also found that such differential expression is more prevalent and pronounced in the placentas of male fetuses than those of female fetuses, which is particularly interesting, as it echoes with the more severe reduction in birth weight of male neonates at high elevation observed by the same group of researchers (He et al., 2022).

This revised manuscript addressed several concerns raised by reviewers in last round. However, we still find the evidence for natural selection on the identified DEGs--as a group--to be very weak, despite more convincing evidence on a few individual genes, such as EPAS1 and EGLN1.

The authors first examined the overlap between DEGs and genes showing signals of positive selection in Tibetans and evaluated the significance of a larger overlap than expected with a permutation analysis. A minor issue related to this analysis is that the p-value is inflated, as the authors are counting permutation replicates with MORE genes in overlap than observed, yet the more appropriate way is counting replicates with EQUAL or MORE overlapping genes. Using the latter method of p-value calculation, the "sex-combined" and "female-only" DEGs will become non-significantly enriched in genes with evidence of selection, and the signal appears to solely come from male-specific DEGs. A thornier issue with this type of enrichment analysis is whether the condition on placental expression is sufficient, as other genomic or transcriptomic features (e.g., expression level, local sequence divergence level) may also confound the analysis.

The authors next aimed to detect polygenic signals of adaptation of gene expression by applying the PolyGraph method to eQTLs of genes expressed in the placenta (Racimo et al 2018). This approach is ambitious but problematic, as the method is designed for testing evidence of selection on single polygenic traits. The expression levels of different genes should be considered as "different traits" with differential impacts on downstream phenotypic traits (such as birth weight). As a result, the eQTLs of different genes cannot be naively aggregated in the calculation of the polygenic score, unless the authors have a specific, oversimplified hypothesis that the expression increase of all genes with identified eQTL will improve pregnancy outcome and that they are equally important to downstream phenotypes. In general, PolyGraph method is inapplicable to eQTL data, especially those of different genes (but see Colbran et al 2023 Genetics for an example where the polygenic score is used for testing selection on the expression of individual genes).

We would recommend removal of these analyses and focus on the discussion of individual genes with more compelling evidence of selection (e.g., EPAS1, EGLN1)

Author response:

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

Reviewer #1 (Recommendations for The Authors):

(1) Since the data suggests that the degradation of Mecp2 is a crucial event in the exit from quiescence, gaining a better understanding of the underlying mechanism would improve the significance of the study. In this regard, the authors should take advantage of the serum stimulated degradation of Mecp2 (Fig. 3D) to identify the signaling pathway(s) required for the degradation.

Thank you for this suggestion. To decipher the molecular mechanisms underlying Mecp2-regulated quiescence exit, we performed RNA-seq combined with ChIP-seq to identify the Mecp2-dependent transcriptome genome-wide during the early stage of liver regeneration (Figure S6C). There were 2658 Mecp2 direct target genes, in which 537 were PHx-activated and 2121 were PHx-repressed genes (Figure 6A). GO analysis showed that PHx-activated Mecp2 targets were highly enriched in proliferation-associated biological processes such as ribosome biogenesis, rRNA metabolic process, ncRNA metabolic process, and regulation of transcription by RNA polymerase I, whereas PHx-repressed Mecp2 targets were associated with several metabolic processes including carboxylic acid catabolic process, cellular amino acid metabolic process, fatty acid metabolic process and steroid metabolic process (Figure 6B). These results suggest that Mecp2 plays a negative regulatory role during quiescence exit by activating metabolism-associated genes while repressing proliferation-associated genes in quiescent cells.

Given the more rapid decay of Mecp2 at the protein compared to the mRNA level during the quiescence-proliferation transition, we speculated that Mecp2 is targeted by posttranslational regulation. This hypothesis was supported by proteasome inhibition with the proteasome inhibitor MG132, which attenuated the reduction of Mecp2 in quiescent cells after S.R. (Figure S5A). To identify the signaling pathway that regulate Mecp2 degradation during the G0/G1 transition, we performed immunoprecipitation followed by mass spectrometry (IP-MS) using Mecp2 antibody in quiescent 3T3 cells treated with or without S.R. (Figure S5B). A total of 647 proteins were identified as putative Mecp2 interactors. We were particularly interested in the proteins involved in proteasome-mediated ubiquitin-dependent protein catabolic process which was one of the enriched Gene Ontology (GO) items in the Mecp2 interactome (Table S1).

(2) The authors suggest that Mecp2 downregulation accelerates the induction of pRb, which serves as a key marker for G0/G1 transition. However, their data only show increased magnitudes of the expression in Mecp2 downregulated cells at the timepoints when samples were collected (Figs. 2B and 4B). In the in vitro experiments, the authors should investigate earlier timepoints to demonstrate that induction of pRB during the quiescence exit occurs earlier in Mecp2 deficient cells compared to control cells. Likewise, a later induction of pRB in Mecp2 overexpression cells, in comparison to normal cells, should be demonstrated.

Thank you for these valuable suggestions. We have, accordingly, collected cell samples re-entered the cell cycle at 30-, 60-, 90- and 120-minutes post-S.R. We examined the pRb expression and found that phosphorylation of retinoblastoma protein (pRb) at Ser807/811 occurs earlier (about 90 minutes) in Mecp2 deficient cells compared to control cells (Figure S4C). Compared to the EV, Mecp2 OE resulted in the delayed induction of pRB (about 60 minutes) upon S.R. (Figure S4D). These data indicate that enhanced reduction of Mecp2 stimulates exit from quiescence.

(3) There are three well-known phosphorylation sites in Mecp2, including S80, S229, and S423. As protein ubiquitination and degradation are often triggered by phosphorylation, it would be interesting to examine whether phosphorylation at these sites of Mecp2 is required for its downregulation during quiescence exit. This can be achieved using non-phosphorylate mutants of Mecp2.

This is a very good question. Indeed, the 26S ubiquitin-proteasome system (26S UPS) is responsible for the breakdown of MeCP2 (PMID: 28394263, 28973632). In 2009, the bona fide PEST (enriched in proline, glutamic acid, serine, and threonine) domains have been identified, which are highly conserved across vertebrate evolution (PMID: 19319913). Consensus sequences enriched in PEST residues have been found to predispose proteins containing them for rapid proteolytic degradation (PMID: 8755249, 2876518). In addition, phosphorylation within PEST motifs precedes ubiquitination of proteins (PMID: 15229225). One of the best characterized sites of MeCP2 phosphorylation (S80) (PMID: 19225110), as well as one of the identified ubiquitination sites (K82/K99) (PMID: 22615490), both fall within one of these regions. It is still noteworthy that most of the MeCP2 phosphorylation sites were found in close proximity to potential ubiquitylation sites. For example, Rett syndrome missense mutations in Rett syndrome affecting three (K82R, K135A, K256S) of the ubiquitination sites (PMID: 25165434) and S80 (within one of the PEST sequences) and K82 have been shown to be phosphorylated and ubiquitinated.

Based on the above discussion, we providing a potential hypothesis that the MeCP2 turnover during cell cycle re-entry is achieved by an initial phosphorylation signal (phosphorylated at S80, S229, or S421) that triggers the ubiquitination of a close lysine residue. We hope to solve these issues and be able to present the findings in future work. Thanks again for your professional suggestions.

(4) It would be interesting if the authors could also examine the effect of altered expression of Mecp2 on the maintenance of quiescence. For example, whether the downregulation of Mecp2 sensitizes quiescent cells for entry of the cell cycle in response to serum stimulation or delays withdrawal from the cell cycle upon serum starvation or contact inhibition.

Thank you for your suggestions. Cell cycle synchronization was induced with serum deprivation. When nutrients are exhausted, altered expression of Mecp2 have no statistical influence on the maintenance of quiescence as analyzed by Flow cytometric (Figure 4D and H). This suggests that the altered expression of Mecp2 alone may not be sufficient for cell cycle exit. In the presence of growth factors or nutrients, loss of MeCP2 only accelerates the rate of cell cycle re-entry.

Minor points:

For Figs. 2D, 2H, and 2L, it would be more intuitive if the percentage of changes in liver index rather than the relative index values were used. Also, the values listed in the figures should start from time zero after partial hepatectomy rather than pre-surgery.

Liver weight have the corresponding change with body weight. The liver index (ratio of regenerate liver weight/body weight) is tightly regulated and depends on metabolic demands of the organism. During the course of liver regeneration, reestablishment of liver volume after resection is regulated by the functional needs of the organism. Using the percentage of regenerate liver weight/body weight as a liver growth index could reflect the regenerative function. Next, we agree with the data presentation form and the values listed in the figures have been modified in the revised version.

Reviewer #2 (Recommendations for The Authors):

My concerns are as follows:

(1) The authors note that the decrease in Mecp2 protein levels was more pronounced than the decrease in mRNA levels, suggesting the presence of post-translational regulation of Mecp2 during the early stages of G0 exit. Could the decrease in MeCP2 levels be related to autophagy flux?

Thank you for your valuable comments. Also, we have compared the cells extracts from untreated and chloroquine-treated cells (to block lysosomal degradation). Chloroquine did not cause any accumulation of MeCP2 (Figure S5B). The results suggest that autophagy activity do not involve in the decrease the MeCP2 protein.

(2) In addition to Cyclin D1, how about other cell cycle-related proteins (cyclin A, cyclin B, and cyclin E) were changed when MeCP2 was lost during cell cycle re-entry? Protein expression should be examined by western blot.

We appreciate your valuable suggestions. The expression of cell cycle related protein cyclin A2, cyclin B1 and cyclin E1 were evaluated by Western blotting. The expression of cyclin A2, cyclin B1 and cyclin E1 was enhanced by the knockdown of MeCP2 (Figure 4B). Conversely, the repressed expression of cyclin A2, cyclin B1 and cyclin E1 was observed by the over-expression of MeCP2 (Figure 4F).

(3) By combining MeCP2 ChIP-seq and RNA-seq of genes regulated by MeCP2, the authors uncovered the dual role of Mecp2 in preventing quiescence exit by targeting Rara and Nr1h3. All they show are the Q-PCR results. The authors should show the protein level of Rara and Nr1h3 when MeCP2 was lost during cell cycle re-entry.

Thank you for your advice. In Figure 7C, the knockdown efficiency of Rara and Nr1h3 were checked by Western blot analysis.

(4) The authors performed lentiviral and AAV-mediated gene knockdown to target Rara and Nr1h3 in Cells and Mecp2-cKO livers, respectively. The Knockdown efficacy should be verified by western blots (Fig 7 C and F).

In Figure 7F, the consequences of the Rara and Nr1h3 knockdown efficiency was verified by Western blot analysis.

(5) The other major concern is regarding the lack of quantitative assessments of MeCP2 WB results (Fig 2, Fig 4, and Fig 7).

Thank you for this suggestion. We added supplementary figures to Figure 2B, 2F and 2J to show the quantification membrane signal of MeCP2 protein in liver regeneration. And Fig S4A and 4B showing the quantification signal of MeCP2 protein in NIH3t3 cell cycle re-entry model.

(6) In the Figure legends of Fig 4 B and Fig 4F, the authors should delete the statistical descriptions, as there are no statistical results. In Fig 5F, Fig 5J, Fig 6D, Fig 7D and Fig7H, there are no statistical results of p < 0.01, p < 0.05 or *p < 0.0001, respectively. The authors should check the description in the figure legends. In Fig S2C, the level of significance should be annotated.

We would like to express our heartfelt thanks for your thorough reading of our manuscript. We have made corrections to make manuscript clearer and more accurate. The level of significance have been annotated in Fig S2C.

(7) In Fig S4A, there are no WB results of Cyclin D1 and pRb, the authors should check the description.

Thank you for pointing this out. We have deleted the confusing statements in the revised manuscript.

eLife assessment

This fundamental study provides insights into the mechanism controlling cell cycle reentry, establishing a regulatory role for Mecp2 degradation in shifting transcription from metabolic to proliferation genes during quiescence exit. The evidence, which includes experimental data from in vitro cell culture and an in vivo injury-induced liver regeneration model, is convincing but the trigger for MeCP2 degradation and how MeCP2 differentially regulates proliferation and metabolic genes remain unclear.

Reviewer #1 (Public Review):

In the study described in the manuscript, the authors identified Mecp2, a methyl-CpG binding protein, as a key regulator involved in the transcriptional shift during the exit of quiescent cells into the cell cycle. Their data show that Mecp2 levels were remarkably reduced during the priming/initiation stage of partial hepatectomy-induced liver regeneration and that altered Mecp2 expression affected the quiescence exit. Additionally, the authors identified Nedd4 E3 ligase that is required for downregulation of Mecp2 during quiescence exit. This is an interesting study with well-presented data that supports the authors' conclusions regarding the role of Mecp2 in transcription regulation during the G0/G1 transition. However, the significance of the study is limited by a lack of mechanistic insights into the function of Mecp2 in the process. This weakness can be addressed by identifying the signaling pathway(s) that trigger Mecp2 degradation during the quiescence exit.

Author response:

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

We thank the constructive criticism provided by the reviewers and editor. Based on these suggestions, we have thoroughly reworked the manuscript. More specifically but not limit:

(1) We have corrected the mistakes mentioned by the reviewers on a point-by-point basis.

(2) We have provided additional experimental evidences to explain the rationale behind selecting five miRNAs for q-PCR validation. Furthermore, we have elaborated on the reasons for focusing primarily on research related to cartilage.

(3) In response to concerns regarding overinterpretation in the manuscript, we have made more precise descriptions and revisions. Furthermore, we have added some details in our methods, including the addition of results showing the conservation of miR-199b-5p sequences between human and mouse species.

(4) We have provided additional details on the experiments, including the process for predicting target genes, timing of chondrocyte culture and other experimental operations.

(5) Finally, we have made additional revisions to the details of the figures to avoid any distortions and enhance the precision of the language.

Below please find our responses to the reviewers’ comments on a point-by-point basis. You also can track the changes in the modified manuscript. We believe that this revision has been substantially improved.

eLife assessment

The manuscript provides interesting evidence that miR-199b-5p regulates osteoarthritis and as such it may be considered as a potential therapeutic target. This finding may be useful to further advance the field.

Thank you for your positive comments.

Although the study is considered potentially clinically relevant, the evidence provided was deemed insufficient and incomplete to support the conclusions drawn by the authors.

Thank you for your critical comments and constructive advices. We have response point to point according to the reviewers’ questions and thoroughly re-working our manuscript. We hope the revised manuscript can be qualified to the criteria and be published on the journal of eLife.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors observed that miR-199b-5p is elevated in osteoarthritis (OA) patients. They also found that overexpression of miR-199b-5p induced OA-like pathological changes in normal mice and inhibiting miR-199b-5p alleviated symptoms in knee OA mice. They concluded that miR-199b-5p is not only a potential micro-target for knee OA but also provides a potential strategy for the future identification of new molecular drugs.

Thanks for your comment.

Strengths:

The data are generated from both human patients and animal models.

Thanks for the positive comment.

Weaknesses:

The data presented in this manuscript is not solid enough to support their conclusions. There are several questions that need to be addressed to improve the quality of this study.

The following questions that need to be addressed to improve the quality of the study.

(1) Exosomes were characterized by electron microscopy and western blot analysis (for CD9, 264 CD63, and CD81). However, figure S1 only showed two sample WB results and there is no positive and negative control as well as the confused not clear WB figure.

Thank you for your suggestion. We acknowledge that a comprehensive identification of extracellular vesicles should include both positive and negative samples. However, in some of the initial studies we referenced, the positive and negative control were not mentioned1;2. In our study, we identified extracellular vesicles using a combination of electron microscopy, nanoparticle tracking analysis, and marker detection of exosomes. We agree that having negative samples would make our results more convincing, and we will include a negative control group in our future experiments. Additionally, we have provided clearer images in the revised version. (supplemental fig1 A)

Reference

(1) Ying W, Riopel M, Bandyopadhyay G, et al. Adipose Tissue Macrophage-Derived Exosomal miRNAs Can Modulate In Vivo and In Vitro Insulin Sensitivity. Cell. 2017;171(2).

(2) Fang T, Lv H, Lv G, et al. Tumor-derived exosomal miR-1247-3p induces cancer-associated fibroblast activation to foster lung metastasis of liver cancer. Nature Communications. 2018;9(1):191.

(2) The sequencing of miRNAs in serum exosomes showed that 88 miRNAs were upregulated and 89 miRNAs were downregulated in KOA patients compared with the control group based on fold change > 1.5 and p < 0.05. Figure 2 legend did not clearly elucidate what those represent and why the authors chose those five miRNAs to further validate although they did mention it with several words in line 108 'based on the p-value and exosomal'.

In fact, our study included two additional groups: the acupuncture treatment group (4 weeks of continuous acupuncture treatment) and the waiting treatment group (no intervention, followed by acupuncture treatment after 4 weeks), in addition to the healthy control and knee osteoarthritis (OA) patient groups. After comparing these four groups, we found that 11 genes (hsa-miR-504-3p, hsa-miR-1915-3p, hsa-miR-103a-2-5p, hsa-miR-887-3p, hsa-miR-1228-5p, hsa-miR-34c-3p, hsa-miR-3168, hsa-miR-518e-3p, hsa-miR-1296-5p, hsa-miR-338-3p, and hsa-miR-199b-5p) were upregulated in KOA patients but downregulated after acupuncture treatment, with no change in the waiting treatment group. Additionally, 7 genes (hsa-miR-448, hsa-miR-514a-3p, hsa-miR-4440, hsa-let-7f-5p, hsa-let-7a-5p, hsa-let-7d-5p, and hsa-miR-15b-3p) were downregulated in KOA patients but upregulated after acupuncture treatment, with no change in the waiting treatment group. Considering the improvement in clinical symptoms of KOA patients after acupuncture treatment, we believe that these 18 genes are of significant value. Based on overall expression abundance and species specificity, we finally selected 5 genes, namely the 5 genes mentioned in this article. Regarding this result, we have already included it in the supplementary fig5(fig. S5).

Author response image 1.

Venn diagram showing differentially expressed miRNAs in the OA group compared with healthy patients and patients who recovered after acupuncture treatment.

(3) In Figure 3 legend and methods, the authors did not mention how they performed the cell viability assay. What cell had been used? How long were they treated and all the details? Other figure legends have the same problem without detailed information.

Thank you for your suggestions. In Figure 3, cell viability was determined using the CCK-8 assay. We used second-generation chondrocytes for this analysis. The chondrocytes were obtained from young mice aged 3-5 days after birth. The cartilage tissues were extracted, and the cells were cultured in complete medium after digestion with collagenase. The detailed description of the cell viability assay, cell culture procedures, specific timing, and treatment methods of the cells used can be found in our revised manuscript. (page14-15，line304-313)

Besides, we have made thorough revisions to all figure legends to provide a clearer explanation of the relevant content.

(4) The authors claimed that Gcnt2 and Fzd6 are two target genes of miR-199b-5p. However, there is no convincing evidence such as western blot to support their bioinformatics prediction.

In the current study, we first identified six potential target genes by intersecting the predicted targets obtained from six bioinformatics websites. Subsequently, q-PCR was employed to test all six genes, revealing two genes with significant changes, namely Fzd6 and Gcnt2. We then predicted the binding sites of these genes and validated their existence through luciferase assays. Moreover, we examined the expression of these two potential targets in human KOA samples using a human database and found them to be expressed specifically in the samples. These results suggest that Fzd6 and Gcnt2 are potential target genes for KOA. However, we didn’t do western blot assay to verify the results. Based on your suggestions, we have further discussed the limitations of our study in this regard and proposed future research strategies.

(5) To verify the binding site on 3'UTR of two potential targets, the authors designed a mouse sequence for luciferase assay, but not sure if it is the same when using a human sequence.

Thank for your great advice. We carried out the comparative analysis of sequence conservatism between human and mouse, and find the binding site on 3'UTR matches to human sequence very well. The sequence conservation between hsa_miR-199b-5p and mmu_miR-199b-5p was as high as 95.65%. We added the methods and results in the revised manuscript. (page9, line181-184; page17, line361-365) (supplemental fig6).

In detail: Firstly, the sequence information of mmu_miRNA-199b-5p was used to locate the human homologous sequence in the UCSC database. The homologous sequence was found to be located in the human genome at chr9:128244721-128244830 (supplemental fig6 A). Based on this positional information and the source gene, a further comparison was conducted in miRbase to identify the nearest miRNA at the position of the human genome. It was discovered that hsa_miR-199b-5p is positionally conserved and located at chr9:128244721-128244830 (supplemental fig6 B). The sequence of hsa_miR-199b-5p was obtained from the miRbase database (supplemental fig6 C), and a comparative analysis was performed between the sequences of humans and mouse (supplemental fig6 D). Besides being positionally conserved, the sequence conservation between hsa_miR-199b-5p and mmu_miR-199b-5p was as high as 95.65%, indicating a good sequence conservation.

Author response image 2.

(A) By using the sequence information of mmu_miRNA-199b-5p, we located the position of its human homologous sequence in the UCSC database. (B) Based on the positional information and the source gene, we further aligned this position with the closest miRNA in miRbase. (C) We compared the sequences of hsa_miR-199b-5p and mmu_miR-199b-5p. (D) Conservation analysis was performed to compare the sequence conservation of miR-199b-5p.

Reviewer #2 (Public Review):

Summary:

The authors identified miR-199b-5p as a potential OA target gene using serum exosomal small RNA-seq from human healthy and OA patients. Their RNA-seq results were further compared with publicly available datasets to validate their finding of miR-199b-5p. In vitro chondrocyte culture with miR-199b-5p mimic/inhibitor and in vivo animal models were used to evaluate the function of miR-199b-5p in OA. The possible genes that were potentially regulated by miR-199b-5p were also predicted (i.e., Fzd6 and Gcnt2) and then validated by using Luciferase assays.

We greatly appreciate Reviewer #2 constructive comments.

Strengths:

(1) Strong in vivo animal models including pain tests.

(2) Validates the binding of miR-199b-5p with Fzd6 and binding of miR-199b-5p with Gcnt2.

Thanks for positive comment.

Weaknesses:

(1) The authors may overinterpret their results. The current work shows the possible bindings between miR-199b-5p and Fzd6 as well as bindings between miR-199b-5p and Gcnt2. However, whether miR-199b-5p truly functions through Fzd6 and/or Gcnt2 requires genetic knockdown of Fzd6 and Gcnt2 in the presence of miR-199b-5p.

In this study, we employed a comprehensive approach by integrating data from six bioinformatics databases to identify potential target genes for miR-199b-5p. Subsequent qPCR analysis revealed significant changes in two genes, Fzd6 and Gcnt2. We then utilized luciferase assays to validate the predicted binding sites and confirmed the interaction between miR-199b-5p and these genes. Additionally, we examined the expression profiles of these potential target genes in human KOA samples using a human database, which unveiled distinct expression patterns.

While our findings suggest that Fzd6 and Gcnt2 may serve as potential target genes for miR-199b-5p, we acknowledge the necessity for further experimental validation and in-depth functional characterization. Building upon your insightful recommendations, we have thoroughly addressed the research limitations and proposed potential research strategies for future investigations in our discussion. (page11，line227-231)

(2) In vitro chondrocyte experiments were conducted in a 2D manner, which led to chondrocyte de-differentiation and thus may not represent the chondrocyte response to the treatments.

We admit that 3D culture system will be more accurate and reliable. However, according to Liu Qianqian et al researches3, the 2D culture systems were also used and work well. Besides, the second-generation primary mice chondrocytes we used in the current study did not exhibit a significant dedifferentiated morphology. So, considering the experiment condition in our lab, we chose the second-generation cultured primary mouse chondrocytes in the whole process of cell experiment. To show the reliability of the cells, we provided more pictures in the supplement fig 7(fig. S7) In the future study, we will adopt 3D culture system for experiments. Thank you for your advices and we have added this limitation in the revised manuscript. (page11，line237-240)

Author response image 3.

Primary mice chondrocytes we cultured （P1）and the secondary generation cells(P2) we used in the following experiment.

References which used 2D ：

(3) Liu Q, Zhai L, Han M, et al. SH2 Domain-Containing Phosphatase 2 Inhibition Attenuates Osteoarthritis by Maintaining Homeostasis of Cartilage Metabolism via the Docking Protein 1/Uridine Phosphorylase 1/Uridine Cascade. Arthritis & Rheumatology (Hoboken, NJ). 2022;74(3):462-474.

(3) There is a lack of description for bioinformatic analysis.

Sorry for our neglection. We have added relevant descriptions and details. (Pages 14, line299-303)

(4) There are several errors in figure labeling.

We have revised. (Fig. 3, Fig. 4, Fig. 5 and Fig. 7)

Recommendations for the authors:

We appreciate the reviewers' feedback as we believe it has significantly contributed to the refinement of our manuscript. We are confident that our revisions have strengthened the quality and impact of our study, and we agree that the suggestions presented by the reviewers are valuable and appropriate for publication.

Reviewer #2 (Recommendations For The Authors):

I would like to thank the authors for investigating the functional role of miR-199b-5p in knee OA. While this study has the potential to provide valuable knowledge to the fields of miRNAs and joint diseases, significant improvements in several areas are required.

We appreciate your constructive comments, and we have made a substantial improvement to the manuscript. We thank all the reviewers for their advice as well as their criticisms.

Major concerns:

(1) According to the Authors, miR-199b-5p is identified by the results from their own miRNA-sequencing as well as comparison with other publicly available datasets (both synovium and cartilage datasets). It is unclear to me why the synovium dataset was used here as it appears that the entire manuscript was mainly focused on chondrocytes.

Thank you for your question. As we are aware, cartilage degradation is the initial pathological change in knee osteoarthritis (KOA), which subsequently leads to other pathological changes such as synovial inflammation4. These factors are interrelated, and current research on KOA encompasses cartilage, synovium, and system inflammation et al. Therefore, when we identified a large number of dysregulated miRNAs in extracellular vesicles isolated from serum, it was crucial to determine whether these dysregulated miRNAs were also altered in cartilage or synovium. To address this, we compared our findings with publicly available databases and found a higher overlap with the cartilage cell dataset, including miRNA-199b. Consequently, we decided to focus our subsequent investigations on cartilage-related research.

Reference

(4) Hunter D, Bierma-Zeinstra S. Osteoarthritis. Lancet (London, England). 2019;393(10182):1745-1759.

(2) Also, 169 of 177 differentially expressed exosome miRNAs were intersected with differentially expressed miRNAs from OA cartilage datasets. It is surprising that in the 5 selected miRNAs for further qRT-PCR validation, 3 out of 5 were not in the exosome miRNA dataset (i.e., hsa-mir-1296-5p, hsa-mir-15b-3p, and hsa-mir-338-3p; page 5, line 109 and Fig. 1B). Isn't that selecting the miRNAs that both differently expressed in exosome and cartilage datasets for validation more essential? Furthermore, from the Authors' exosome miRNA dataset, only 5 out of 15 KOA patients actually exhibited up-regulated miR-199b-5p vs. health controls. Please elaborate on how the target was determined.

In fact, our study included two additional groups: the acupuncture treatment group (4 weeks of continuous acupuncture treatment) and the waiting treatment group (no intervention, followed by acupuncture treatment after 4 weeks), in addition to the healthy control and knee osteoarthritis (OA) patient groups. After comparing these four groups, we found that 11 genes (hsa-miR-504-3p, hsa-miR-1915-3p, hsa-miR-103a-2-5p, hsa-miR-887-3p, hsa-miR-1228-5p, hsa-miR-34c-3p, hsa-miR-3168, hsa-miR-518e-3p, hsa-miR-1296-5p, hsa-miR-338-3p, and hsa-miR-199b-5p) were upregulated in KOA patients but downregulated after acupuncture treatment, with no change in the waiting treatment group. Additionally, 7 genes (hsa-miR-448, hsa-miR-514a-3p, hsa-miR-4440, hsa-let-7f-5p, hsa-let-7a-5p, hsa-let-7d-5p, and hsa-miR-15b-3p) were downregulated in KOA patients but upregulated after acupuncture treatment, with no change in the waiting treatment group. Considering the improvement in clinical symptoms of KOA patients after acupuncture treatment, we believe that these 18 genes are of significant value. Based on overall expression abundance and species specificity, we finally selected 5 genes, namely the 5 genes mentioned in this article. Regarding this result, we have already included it in the supplementary fig5(fig. S5).

Author response image 4.

Venn diagram showing differentially expressed miRNAs in the OA group compared with healthy patients and patients who recovered after acupuncture treatment.

(3) There is also a lack of description for bioinformatic analysis regarding how miRNA sequencing datasets were analyzed. What R/python packages or algorithms were used? What were the QC criteria?

We apologize for any confusion caused. We have now included a clear description of the method employed, and R was utilized for this data analysis (revised in Page14, Line301-305). To ensure consistency, we compared our findings with publicly available human serum data from the database (GSE105027) using a fold change threshold of > 1.5 and a significance level of p < 0.05. In the cartilage data (GSE175961), we observed a list of miRNAs with shared expression patterns, yet the precise differential values could not be determined.

(4) Another major concern is the chondrocyte culture method. Chondrocytes should be cultured in a 3D manner (i.e., a 3D pellet culture system or a micro mass culture method). 2D cultured chondrocytes tend to de-differentiate into MSC-like cells and thus lose their chondrocyte phenotype. This is evident from Fig. 3B and C. Cells started to spread out and only a few cells were positive for COL2A1 with a deep brown staining color. Thus, the results from the in vitro studies may not be representative of chondrocyte response to the treatments.

We admit that 3D culture system will be more accurate and reliable. However, according to Liu Qianqian et al researches3, the 2D culture systems were also used and work well. Besides, the second-generation primary mice chondrocytes we used in the current study did not exhibit a significant dedifferentiated morphology. So, considering the experiment condition in our lab, we chose the second-generation cultured primary mouse chondrocytes in the whole process of cell experiment. To show the reliability of the cells, we provided more pictures in the supplement fig 7(fig. S7) In the future study, we will adopt 3D culture system for experiments. Thank you for your advices and we have added this limitation in the revised manuscript. (page11, line237-240)

Author response image 5.

Primary mice chondrocytes we cultured （P1）and the secondary generation cells(P2) we used in the following experiment.

References which used 2D ：

(3) Liu Q, Zhai L, Han M, et al. SH2 Domain-Containing Phosphatase 2 Inhibition Attenuates Osteoarthritis by Maintaining Homeostasis of Cartilage Metabolism via the Docking Protein 1/Uridine Phosphorylase 1/Uridine Cascade. Arthritis & Rheumatology (Hoboken, NJ). 2022;74(3):462-474.

(5) Page 7, lines 148-149: "The cartilage of mice injected with the miR-199b-5p mimic was slightly degraded (p=0.02) (Fig. 4E, F)". However, there was no significance between the groups found in Fig. 4F. Also, from the histological images of Fig. 4E, it looks like mice with inhibitor injection had more cartilage damage than miR-199b-5p mimic.

We apologize for any confusion caused. Figures 4E and 4F represent the Safranin Fast Green Staining staining of the joint after the administration of miR-199b-5p inhibitor and mimic under physiological conditions. As you can see, there is minimal difference between these four images. There is no statistically significant difference. However, in Figures 5E and 5F, the MIA-induced KOA model was utilized, and noticeable differences can be observed after the administration of the inhibitor and mimic. In the revised version, we have emphasized that Figures 4E and 4F represent the results under physiological conditions, not under the MIA-induced model. (page 7, line 146-151)

(6) Page 7, lines 149-150: "Additionally, the articular surface showed insect erosion (Fig. 4G)." It is also unclear how micro-CT analysis will be able to demonstrate the erosion of cartilage. Or the authors actually indicate the trochlear groove. However, this could also be observed in the control group and the results were not quantified. It is also unclear if the cross-section images of micro-CT shown here are helpful at all without any further explanation in the manuscript.

Figure 4 G represents control, vehicle control, inhibitor, and mimic groups, while Figure 5 G represents model, model+vehicle control, model+inhibitor, and model+mimic groups. From Figure 4G, it can be observed that the simulator group showed the most obvious erosion appearance, while the inhibitor group did not exhibit this phenomenon5. From Figure 5G, it can be seen that the model group and model+mimic group exhibited the most pronounced erosion appearance, while the model+inhibitor group showed the best recovery. To highlight the pathological changes in the erosion appearance, we marked the typical locations with red arrows in the images for easy comparison and reading by the readers (Fig. 4G; Fig. 5G). We also made corresponding textual modifications in the original manuscript to address these findings (page 7, line 150-151; page 8, line 160-161). In addition, the 3D reconstruction of micro-CT is based on the synthesis of these cross-sectional images.

References

(5) Tao Y, Wang Z, Wang L, et al. Downregulation of miR-106b attenuates inflammatory responses and joint damage in collagen-induced arthritis. Rheumatology (Oxford, England). 2017;56(10):1804-1813.

(7) Page 17, line 309-310: "Before model establishment and at 3, 7, 10, 14, 21, and 28 days after model establishment." Please re-write this as this is not clear regarding the experimental procedure.

Thank you. We had to re-write the sentences as following：Baseline testing of behavioral pain thresholds was conducted prior to model establishment, followed by behavioral pain threshold testing on days 3, 7, 10, 14, 21, and 28 after model establishment. (pages15, line322-324)

(8) Fig. 5A. The M + inhibitor and Model images are not at the same plane as M + mimic and M + RNAnc images.

Thank you. We have modified.

(9) Fig. 5B. There are two lines both with circle markers (Control and M+inhibitor). Please correct.

We have corrected.

(10) Fig. 5F. Missing * sign.

We added *sign.

(11) Please elaborate how the potential binding sites between miR-199b-5p and Gcnt2 and between miR-199b-5p and Fzd6.

We apologize for any lack of clarity in the original text. In fact, we utilized targets to predict potential binding sites. Specifically, for the mouse species, we predicted that the 3'UTR of Fzd6 binds with miR-199b-5p at positions 2483-2490, 3244-3251, 3303-3309, and 3854-3860, while the 3'UTR of Gcnt2 binds with miR-199b-5p at positions 2755-2762 and 4144-4151. In the revised version, we provide a detailed description of the methodology used for predicting these sites and offer an elaborate explanation of the results. (pages16, line352)

Additionally, to demonstrate consistency with human binding sites, we not only predicted the binding sites of human miR with these two target genes but also found a high conservation of up to 95.65% between the human and mouse sequences of miR-199b-5p. We have included this information in the supplementary materials (Fig. S6). In Fig. 6E-F, we presented the potential binding sites between miR-199b-5p and Gcnt2, as well as between miR-199b-5p and Fzd6. In addition, we provide the predicted binding of human sequence to illustrate the binding sites. Furthermore, the predicted binding of human miR-199b-5p with fzd6 and gcnt2 showed a high degree of consistency. (The fluorescent labeling in the following text indicates the potential predicted binding sites.) (Supplement file 8)

hsa-miR-199b-5p MIMAT0000263

CCCAGUGUUUAGACUAUCUGUUC

NCBI Gene ID 8323 GenBank Accession NM_001164615

Gene Symbol FZD6 3' UTR Length 1368

Gene Description frizzled class receptor 6

3' UTR Sequence: agaacattttctctcgttactcagaagcaaatttgtgttacactggaagtgacctatgcactgttttgtaagaatcactgttacattcttcttttgcacttaaagttgcattgcctactgttatactggaaaaaatagagttcaagaataatatgactcatttcacacaaaggttaatgacaacaatatacctgaaaacagaaatgtgcaggttaataatatttttttaatagtgtgggaggacagagttagaggaatcttccttttctatttatgaagattctactcttggtaagagtattttaagatgtactatgctattttacttttttgatataaaatcaagatatttctttgctgaagtatttaaatcttatccttgtatctttttatacatatttgaaaataagcttatatgtatttgaacttttttgaaatcctattcaagtatttttatcatgctattgtgatattttagcactttggtagcttttacactgaatttctaagaaaattgtaaaatagtcttcttttatactgtaaaaaaagatataccaaaaagtcttataataggaatttaactttaaaaacccacttattgataccttaccatctaaaatgtgtgatttttatagtctcgttttaggaatttcacagatctaaattatgtaactgaaataaggtgcttactcaaagagtgtccactattgattgtattatgctgctcactgatccttctgcatatttaaaataaaatgtcctaaagggttagtagacaaaatgttagtcttttgtatattaggccaagtgcaattgacttcccttttttaatgtttcatgaccacccattgattgtattataaccacttacagttgcttatattttttgttttaacttttgttttttaacatttagaatattacattttgtattatacagtacctttctcagacattttgtagaattcatttcggcagctcactaggattttgctgaacattaaaaagtgtgatagcgatattagtgccaatcaaatggaaaaaaggtagttttaataaacaagacacaacgtttttatacaacatactttaaaatattaaggagttttcttaattttgtttcctattaagtattattctttgggcaagattttctgatgcttttgattttctctcaatttagcatttgcttttggtttttttctctatttagcattctgttaaggcacaaaaactatgtactgtatgggaaatgttgtaaatattaccttttccacattttaaacagacaactttgaatacaaaaactttgttttgtgtgatcttttcattaataaaattatctttgtataagaaaaaaaaaaaaaa

hsa-miR-199b-5p MIMAT0000263

CCCAGUGUUUAGACUAUCUGUUC

NCBI Gene ID 2651 GenBank Accession NM_001491

Gene Symbol GCNT2 3' UTR Length 2780

Gene Description glucosaminyl (N-acetyl) transferase 2 (I blood group)

3' UTR Sequence: gctattcatgagctactcatgactgaagggaaactgcagctgggaagaggagcctgtttttgtgagagacttttgccttcgtaatgttaaccgtttcaggaccacgtttatagcttcaggacctggctacgtaattatacttaaaatatccactggacactgtgaaatacactaacaggatggctgggtagagcaatctgggcactttggccaattttagtcttgctgtttcttgatgctcacctctatattagtttattgttaggatcaatgataaatttaaatgacctcagatctttgcaccagatactcatcatatacaaatgttttagtaaaaaagagaattgtagataatactgtctaggaaaataagaattaggtttctttgaagaaggaatcttttataacaccttaacagtcaccactgtgctcaaccagacagatagtgaaacagctttctgggtaattcaccaatttcctttaaaacataagctacctgaatggagaatacatcttgtttctgagtttcaacactagcatttttggcttactcatggacaaagttctgtatatagtataaagtcattaacaagaaacaggatatgctttaagacagaattcactgtctgttgcttcagtaaaaggacctcggggaataaaacatttctctcttatatgccagaatgtaggctggtccctatgtcatgtcttccattaagaacactaaaaagtccttgcaagaatggagatatgcattcaagagaggtgctatcacatagatctagtctgaagtctggaacactttcctcttctatgacccctctctccccagtattatcttacttgcaaaatggagaccaaattctatcctgtgaggcttttaattgcaccatagtatgctctgagtagctttacactgcctggtactgatagtagtggctcgatttttaagagccttcaattgtagatgaacatctctgttatttatccctcattcatccatccgttcattcattcagccttcaatcaacatctcttgagtgtctattatgtacaggacatgtactgagacaaaaaggaaacataagagctttttcactctaaaaatcttggcaataatgtcaacaccagaaagcctcctctggagaatcttacagagtgattgtagtttaatacaggaacacacagggctgtgtagcatgataccaggcccaggagatcagtaattacaaattaagggttaaatcagagattattcaacagagagggagaaaggaggagacagagggaggacctgttgtgttccagccattctggtattcctttatgtatctaatttcattcaaacctcacaacagtcttgtgaggcccttatataattactcccattttgcagatgaagtaactgaggcttagaaaggttaatagcaccggggaacaatttctctgggtgagaattgggactctgttgctggtcttctcagttcatttcctgaggtggatttactgagagaaggtgaaataaagccatatttagtataccagagaaggtagattttaagaatggtctcagtgttaatactgagaaaaagtcctgtcagttcagaaaaaatgtgaagtctactttagtattcctgtaatactaaaccgttgagtttctaaatatttatttattctaacaaaaagcaattactacaaatggatgacacatttaatgaacacaattttattttttttctgtaactgtgcttgttgaatgtcaatcatatttaaagggaatgactttgaagtaaaaccttttttcttgctactgaaaaaaatggagttgttttgggtggtaaagtgttaaggaatagggacagctggtcacacaaggaactcttgaaggccacatgtgaaaacctgtcacttgcacagaggccagtcccactaaggtgaccagagtgggctccaagcacaaactgccattggctatagatgggactgtgtccccccaaaattcatgtgttggagccttaaccctcaatgtgatggtatttgagatggggcctttggtaagggaagtttagatgaggtcacgagggtaggaccctcatgatgggatgagtccccttacaagacctctggcttgggccgggcgtggtggctcacacctgtaatcccaacactttgggaggccaaggcaggtagatcacttgatgccaggagttccagaccaggctggccgacatggtgaaaccccatctctactaaaaaatataaaaattagccgggctttgtggcatgtgcctgtaatcccagctatttggcaggctgaggcatgagaatcgcttgaacccaggaggtggaggttacagtgagctgagagtgccccactgcactccagcctgggtgacagagcgagactttgtcccaaaacaaaataggtgaggggatagcgaatgcactcagggtcagcagtggagtttaaaaattgtctcttttcaacttatttaaatgacagcacctgagaagaggaaccgttttacactggatgtttctcatgtagaacaagaaatctttctggaattgatgtttacatgtctgttgttggtcatctctcctgtgtcttaaatactttaatgttggaagagcatagtgtttgggctagtgggtttctgacagcccatgggaatgccctgaaactactgtatctgatgtttgttttcgatgaggttccatgttttgttttcttgggaataaattaatatattgttttccaaaaaaaaaaaaaaaaaaaa

(12) Page 10-11, Line 222-223: "Our findings indicate that miR-199b-5p plays a crucial role in KOA by targeting Fzd6 and Gcnt2". This is an overstatement. The current work shows the possible bindings of miR-199b-5p and Fzd6 as well as bindings of miR-199b-5p and Gcnnt2. Whether miR-199b-5p truly functions through Fzd6 and/or Gcnt2 requires genetic knockdown of Fzd6 and Gcnt2 in the presence of miR-199b-5p. Thus, please tune down this statement and the title of the manuscript.

We agree your opinion of our conclusion. Therefore, we delete the overstatement sentences and tune down the conclusion of the manuscript. (the title; page 8,179; page11, line227-228)

(13) The Schematic figure (the last figure). Please remove osteophyte as this was not quantified in the study.

We modified the schematic figure accordingly.

Minor concerns:

(1) Most figures were distorted.

We provide a new version of the figure to avoid distortions.

(2) Providing GO term numbers in Fig. 1C is not very helpful. Maybe show the GO term and corresponding numbers in the manuscript (Page 4, lines 79 - 82).

Thank you for your advice. We added the corresponding notes of the GO term numbers in the manuscript to explain each biological concept of it. (Page 4, line 77-89；Page 22，line 515-532)

(3) What were M-0.5 and M-1 in Fig. 2D? Different MIA concentrations?

Yes, these are different MIA concentrations, which we illustrate in the legend. (Page 23, line 535-536)

(4) Please follow the nomenclature of the gene symbol. For example, Fig. 3E-P should be mouse genes (?).

We modified the relevant gene symbol.

(5) Page 3, line 59. Not all chondrocytes are pathogenic cells in OA.

We are sorry for the mistake, now it has been modified. (Page 3, line 59)

(6) Typo. Page 3, line 55.

We changed the Typo.

(7) Page 4, line 78. These are differentially expressed miRNAs, not genes.

We have revised the unsuitable expression. (Page4, line75-76)

I wish the authors all the best with their continued work in this area.

Thank you for your wishes.

eLife assessment

This valuable study reports that miR-199b-5p is elevated in human osteoarthritis patients. There is solid evidence for the finding that inhibiting miR-199b-5p alleviates symptoms in mice with knee osteoarthritis. Additionally, potential targets of miR-199b-5p are identified but whether miR-199b-5p truly functions through Fzd6 and/or Gcnt2 requires further investigation.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors reported that miR-199b-5p is elevated in osteoarthritis (OA) patients. They also found that overexpression of miR-199b-5p induced OA-like pathological changes in normal mice and inhibiting miR-199b-5p alleviated symptoms in knee OA mice. They concluded that miR-199b-5p is not only a potential micro target for knee OA, but also provides a potential strategy for future identification of new molecular drugs.

Strengths:

The data are generated from both human patients and animal models. The data presented in this revised manuscript is solid and support their conclusions. The questions from reviewers are also properly addressed and the quality of this manuscript has been significantly improved.

There are no significant weaknesses identified in this revised manuscript.

Reviewer #2 (Public Review):

Summary:

The Authors identified miR-199b-5p is a potential OA target gene using serum exosomal small RNA-seq from human healthy and OA patients. Their RNA-seq results were further compared with publicly available datasets to validate their finding of miR-199b-5p. In vitro chondrocyte culture with miR-199b-5p mimic/inhibitor and in vivo animal models were used to evaluate the function of miR-199b-5p in OA. The possible genes that were potentially regulated by miR-199b-5p were also predicted (i.e., Fzd6 and Gcnt2) and then validated by using Luciferase assays.

Strengths:

(1) Strong in vivo animal models including pain tests.<br /> (2) Validate the binding of miR-199b-5p with Fzd6 and binding of miR-199b-5p with Gcnt2

The authors have addressed my concerns.

Author response:

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

eLife assessment

The authors build upon prior data implicating the secreted peptidoglycan hydrolase SagA produced by Enterococcus faecium in immunotherapy. Leveraging new strains with sagA deletion/complementation constructs, the investigators reveal that sagA is non-essential, with sagA deletion leading to a marked growth defect due to impaired cell division, and sagA being necessary for the immunogenic and anti-tumor effects of E. faecium. In aggregate, the study utilizes compelling methods to provide both fundamental new insights into E. faecium biology and host interactions and a proof-of-concept for identifying the bacterial effectors of immunotherapy response.

We thank the Reviewers for their positive feedback on our manuscript. We also appreciate their helpful comments/critiques and have revised the manuscript as indicated below.

Public Reviews:

Reviewer #1 (Public Review):

Klupt, Fam, Zhang, Hang, and colleagues present a novel study examining the function of sagA in E. faecium, including impacts on growth, peptidoglycan cleavage, cell separation, antibiotic sensitivity, NOD2 activation, and modulation of cancer immunotherapy. This manuscript represents a substantial advance over their prior work, where they found that sagA-expressing strains (including naturally-expressing strains and versions of non-expressing strains forced to overexpress sagA) were superior in activating NOD2 and improving cancer immunotherapy. Prior to the current study, an examination of sagA mutant E. faecium was not possible and sagA was thought to be an essential gene.

The study is overall very carefully performed with appropriate controls and experimental checks, including confirmation of similar densities of ΔsagA throughout. Results are overall interpreted cautiously and appropriately.

I have only two comments that I think addressing would strengthen what is already an excellent manuscript.

In the experiments depicted in Figure 3, the authors should clarify the quantification of peptidoglycans from cellular material vs supernatants. It should also be clarified whether the sagA need to be expressed endogenously within E. faecium, and whether ambient endopeptidases (perhaps expressed by other nearby bacteria or recombinant enzymes added) can enzymatically work on ΔsagA cell wall products to produce NOD2 ligands?

We mentioned in the main text that peptidoglycan was isolated from bacterial sacculi and digested with mutanolysin for LC-MS analysis. We have now also included “mutanolysin-digested” sacculi in the Figure 3 legend as well.

We have added the following text “We next evaluated live bacterial cultures with mammalian cells to determine their ability to activate the peptidoglycan pattern recognition receptor NOD2” and “our analysis of these bacterial strains” to indicate live cultures were evaluated for NOD2 activation.

We have also added the following text “Our results also demonstrated that while many enzymes are required for the biosynthesis and remodeling of peptidoglycan in E. faecium, SagA is essential for generating NOD2 activating muropeptides ex vivo.”

In the murine experiments depicted in Figure 4, because the bacterial intervention is being performed continuously in the drinking water, the investigators have not distinguished between colonization vs continuous oral dosing of the mice peptidoglycans. While I do not think additional experimentation is required to distinguish the individual contributions of these 2 components in their therapeutic intervention, I do think the interpretation of their results should include this perspective.

We have added the following text “We note that by continuous oral administration in the drinking water, live E. faecium and soluble muropeptides that are released into the media during bacterial growth may both contribute to NOD2 activation in vivo.” and revised the following text “Nonetheless, these results demonstrate SagA is not essential for E. faecium colonization, but required for promoting the ICI antitumor activity through NOD2 in vivo.

Reviewer #2 (Public Review):

Summary:

The gut microbiome contributes to variation in the efficacy of immune checkpoint blockade in cancer therapy; however, the mechanisms responsible remain unclear. Klupt et al. build upon prior data implicating the secreted peptidoglycan hydrolase SagA produced by Enterococcus faecium in immunotherapy, leveraging novel strains with sagA deleted and complemented. They find that sagA is non-essential, but sagA deletion leads to a marked growth defect due to impaired cell division. Furthermore, sagA is necessary for the immunogenic and anti-tumor effects of E. faecium. Together, this study utilizes compelling methods to provide fundamental new insights into E. faecium biology and host interactions, and a proof-of-concept for identifying the bacterial effectors of immunotherapy response.

Strengths:

Klupt et al. provide a well-written manuscript with clear and compelling main and supplemental figures. The methods used are state-of-the-art, including various imaging modalities, bacterial genetics, mass spectrometry, sequencing, flow cytometry, and mouse models of immunotherapy response. Overall, the data supports the conclusions, which are a valuable addition to the literature.

Weaknesses:

Only minor revision recommendations were noted.

Recommendations for the authors:

Reviewer #2 (Recommendations For The Authors):

General comments - the number/type of replicates and statistics are missing from some of the figure panels. Please be sure to add these throughout - all main figure panels should have replicates. I've also noted some specific cases below.

Abstract - sagA is non-essential, need to edit text at "essential functions".

This change has been made.

"small number of mutations" - specify how many in the text.

We revised the text. “Small number” is changed to “11”.

"under control of its native promoter" - what was the plasmid copy number? It looks clearly overexpressed in Figure 1d despite using a native promoter, although it's a bit hard to know for sure without a loading control.

pAM401 has p15A origin of replication, therefore the plasmid copy number ~20-30 copies (Lutz R. et al Nucleic Acids Res. 1997). Total protein was visualized by Stain-Free™ imaging technology (BioRad) and serves as protein loading control and has been relabeled accordingly.

"decrease levels of small muropeptides" - the asterisks are missing from Figure 3a.

Green asterisks for peaks 2, 3, 7 and purple asterisks for peaks 13, 14 were added.

The use of "Com 15 WT" in the figures is confusing - just replace it with "wt" and specify the strain in the text. Presumably, all of the strains are on the Com 15 background.

“Com15 WT” was replaced to “WT” in figures and main text.

Change 1d to 1b so that the panels are in order (reading left to right and then top to bottom).

Figure 1 legend is missing a number of replicates and statistics for 1a.

Number of replicates were added.

Figure 1b - it's unclear to me what to look at here, could add arrows indicating the feature or interest and expand the relevant text.

Arrows pointing to cell clusters were added.

Figure 1d - what is "stain free"? It would be preferable to show a loading control using an antibody against a constitutive protein to allow for normalization of the loading control.

Stain-Free Imaging technology (BioRad) utilizes gel-containing trihalo compound to make proteins fluorescent directly in the gel with a short photoactivation, allowing the immediate visualization of proteins at any point during electrophoresis and western blotting. Stain-Free total protein measurement serves as a reliable loading control comparable to Coomassie Blue Staining. This has been relabeled a “Total protein” in the Figure and Stain-free imaging technology is noted in the legend.

ED Figure 1 - representative of how many biological replicates?

Legends are updated.

ED Figure 2a - I would replace this with a table, it's not necessary to show the strip images. Also, please specify the number of replicates per group.

Additional Extended Data Table 2 was added.

ED Figure 2b - This data was not that convincing since the sagA KO has a marked growth defect and the time points are cut off too soon to know if growth would occur later. The MIC definition is potentially misleading. Should specific a % growth cutoff (i.e. <10% of vehicle control) and the metric used (carrying capacity or AUC). Then assign MIC to the tested concentration, not a range. The empty vector also seems to impact MIC, which is concerning and complicates the interpretation. Specify the number of replicates and add statistics. Given these various concerns, I might suggest removing this figure, as it doesn't really add much to the story.

We appreciate this comment from the Reviewer, but believe this data is helpful for paper and have included longer time points for the growth data. The definition of MIC for ED Fig. 2b has been included in the legend.

Figure 2 - specify the type of replicate. Number of cells? Number of slices? Number of independent cultures?

For Cryo-ET experiments single bacterial cultures were prepared. Number of cells and slices for analysis are indicated in the legend. Legends are updated.

Figure 4e - missing the water group, was it measured?

Water (αPD-L1) group was not included in immune profiling of tumor infiltrating lymphocytes (TILs) experiment, as we have previously demonstrated limited impact on ICI anti-tumor activity and T cell activation in this setting (Griffin M et al Science 2021).

Figure 4d - is this media specific to your strains? If not, qPCR may be a better method using strain-specific primers.

Yes, HiCrome™ Enterococcus faecium agar plates (HIMEDIA 1580) are selective for Enterococcus species, moreover the agar is chromogenic allowing to identify E. faecium as yellow colonies among other Enterococcus species.

Reviewer #1 (Public Review):

Klupt, Fam, Zhang, Hang and colleagues present a novel study examining the function of sagA in E. faecium, including impacts on growth, peptidoglycan cleavage, cell separation, antibiotic sensitivity, NOD2 activation and modulation of cancer immunotherapy. This manuscript represents a substantial advance over their prior work, where they found that sagA-expressing strains (including naturally-expressing strains and versions of non-expressing strains forced to overexpress sagA) were superior in activating NOD2 and improving cancer immunotherapy. Prior to the current study, an examination of sagA mutant E. faecium was not possible and sagA was thought to be an essential gene.

The study is overall very carefully performed with appropriate controls and experimental checks, including confirmation of similar densities of ΔsagA throughout. Results are overall interpreted cautiously and appropriately.

eLife assessment

The authors build upon prior data implicating the secreted peptidoglycan hydrolase SagA produced by Enterococcus faecium in immunotherapy. Leveraging new strains with sagA deletion/complementation constructs, the investigators reveal that sagA is non-essential, with sagA deletion leading to a marked growth defect due to impaired cell division, and sagA being necessary for the immunogenic and anti-tumor effects of E. faecium. In aggregate, the study utilizes compelling methods to provide both fundamental new insights into E. faecium biology and host interactions and a proof-of-concept for identifying the bacterial effectors of immunotherapy response.

Author response:

We are planning to extend our results of the Jurkat model system to primary T cells, as requested by the referees and eLife’s Senior Editor. This will involve the inclusion of new figures, including super-resolution/STED images to reinforce our results and to satisfy the referees’ points. In addition, we will improve and/or replace all the mentioned images to solve the raised caveats, including further quantification and analyses.

eLife assessment

This important study uses the Jurkat T cell model to study the role of Formin-like 1 β phosphorylation at S1086 on actin dynamics and exosome release at the immunological synapse. While the evidence is compelling within the framework of the Jurkat model, it is limited in a broader immunological and cell-biological context due to the limitations of the model system. Jurkat is known to have a bias toward formin-mediated actin filament formation at the expense of Arp2/3-mediated branched F-actin foci observed in primary T cells. In this light, confirming major findings in primary T cells will be of importance.

Reviewer #1 (Public Review):

Summary:

In their article entitled "Formin-like 1 beta phosphorylation at S1086 is necessary for secretory polarized traffic of exosomes at the immune synapse", Javier Ruiz-Navarro and co-workers address the question of the mechanisms regulating the polarization of the microtubule organizing center (MTOC) and of the multivesicular bodies (MVB) at the immunological synapse (IS) in T lymphocytes.

This work is a follow-up of previous studies published by the same team showing that TCR-stimulated protein kinase C delta(PKCdelta) phosphorylates FMNL1beta, which plays a crucial role in cortical actin reorganization at the IS, and controls MTOC/MVB polarization and thus exosome secretion by T lymphocytes at the IS.

The authors first compare the amino acid sequences of FMNL2 and of FMNL1beta, to seek similarities in the DID-DAD auto-inhibition sequences and find that the sequence surrounding S1086 in the arginine-rich DAD of FMNL1beta displays high similarity to that around S1072 in FMNL2 which is phosphorylated by PKCdelta. They then interrogate the role of the phosphorylation of S1086 in the arginine-rich DAD of FMNL1betaby introducing S1086A and S1086D mutations that, respectively, cannot be phosphorylated or mimic the phosphorylated form of FMNL1beta, in cells expressing an FMNL1 shRNA.

Using these tools, they show that:

- FMNL1beta is phosphorylated by PMA an activator of PKCs.

- The S1086A mutant of FMNL1beta does not restore the defect in MTOC and MVB polarization at the IS present in FMNL1 deficient T cells, whereas the phosphomimetic mutant does.

- Although FMNL1betaphosphorylation at S1086 is necessary, it is not sufficient for MTOC polarization, since it does not restore the defect of polarization observed in PKCdelta deficient T cells.

- FMNL1b translocates to the IS. This neither requires PKC expression nor phosphorylation of S1086.

- Phosphorylation of FMNL1betaon S1086 regulates actin remodeling at the immune synapse.

- Phosphorylation of FMNL1betaon S1086 regulates secretion of extracellular vesicles containing CD63 by T lymphocytes.

Strengths:

This work shows for the first time the role of the phosphorylation of FMNL1beta on S1086 on the regulation of the IS formation and secretion of extracellular vesicles by T lymphocytes.

Weaknesses:

Although of interest, this work has several weaknesses. First, all the experiments are performed in Jurkat T cells that may not recapitulate the regulation of polarization in primary T cells. Moreover, all the experiments analyzing the role of PKCdelta are performed in one clone of wt or PKCdelta KO Jurkat cells. This is problematic since clonal variation has been reported in Jurkat T cells. Moreover, the remodeling of F-actin at the IS lacks careful quantification as well as detailed analysis of the actin structure in mutant cells. Finally, although convincing, the defect in the secretion of vesicles by T cells lacking phosphorylation of FMNL1beta on S1086 is preliminary. It would be interesting to analyze more precisely this defect. The expression of the CD63-GFP in mutants by WB is not completely convincing. Are other markers of extracellular vesicles affected, e.g. CD3 positive?

Reviewer #2 (Public Review):

Summary:

The authors have addressed the role of S1086 in the FMNL1beta DAD domain in F-actin dynamics, MVB polarization, and exosome secretion, and investigated the potential implication of PKCdelta, which they had previously shown to regulate these processes, in FMNL1beta S1086 phosphorylation. This is based on:<br /> (1) the documented role of FMNL1 proteins in IS formation;<br /> (2) their ability to regulate F-actin dynamics;<br /> (3) the implication of PKCdelta in MVB polarization to the IS and FMNL1beta phosphorylation;<br /> (4) the homology of the C-terminal DAD domain of FMNL1beta with FMNL2, where a phosphorylatable serine residue regulating its auto-inhibitory function had been previously identified.

They demonstrate that FMNL1beta is indeed phosphorylated on S1086 in a PKCdelta-dependent manner and that S1086-phosphorylated FMNL1beta acts downstream of PKCdelta to regulate centrosome and MVB polarization to the IS and exosome release. They provide evidence that FMNL1beta accumulates at the IS where it promotes F-actin clearance from the IS center, thus allowing for MVB secretion.

Strengths

The work is based on a solid rationale, which includes previous findings by the authors establishing a link between PKCdelta, FMNL1beta phosphorylation, synaptic F-actin clearance, and MVB polarization to the IS. The authors have thoroughly addressed the working hypotheses using robust tools. Among these, of particular value is an expression vector that allows for simultaneous RNAi-based knockdown of the endogenous protein of interest (here all FMNL1 isoforms) and expression of wild-type or mutated versions of the protein as YFP-tagged proteins to facilitate imaging studies. The imaging analyses, which are the core of the manuscript, have been complemented by immunoblot and immunoprecipitation studies, as well as by the measurement of exosome release (using a transfected MVB/exosome reporter to discriminate exosomes secreted by T cells).

Weaknesses

The data on F-actin clearance in Jurkat T cells knocked down for FMNL1 and expressing wild-type FMNL1 or the non-phosphorylatable or phosphomimetic mutants thereof would need to be further strengthened, as this is a key message of the manuscript. Also, the entire work has been carried out on Jurkat cells. Although this is an excellent model easily amenable to genetic manipulation and biochemical studies, the key finding should be validated on primary T cells.

eLife assessment

This study presents a useful reassessment of the potential role of dendritic cell-derived IL-27 p28 cytokine in the functional maturation of CD4+CD8- thymocytes, and CD4+ recent thymic emigrants. The evidence supporting the claims of the authors is solid and serves to reaffirm what has been previously described, with the overall advance in understanding the mechanism(s) responsible for the intrathymic functional programming of CD4+ T cells being limited.

Reviewer #1 (Public Review):

Summary:

Zhang et al. demonstrate that CD4+ single positive (SP) thymocytes, CD4+ recent thymic emigrants (RTE), and CD4+ T naive (Tn) cells from Cd11c-p28-flox mice, which lack IL-27p28 selectively in Cd11c+ cells, exhibit a hyper-Th1 phenotype instead of the expected hyper Th2 phenotype. Using IL-27R-deficient mice, the authors confirm that this hyper-Th1 phenotype is due to IL-27 signaling via IL-27R, rather than the effects of monomeric IL-27p28. They also crossed Cd11c-p28-flox mice with autoimmune-prone Aire-deficient mice and showed that both T cell responses and tissue pathology are enhanced, suggesting that SP, RTE, and Tn cells from Cd11c-p28-flox mice are poised to become Th1 cells in response to self-antigens. Regarding mechanism, the authors demonstrate that SP, RTE, and Tn cells from Cd11c-p28-flox mice have reduced DNA methylation at the IFN-g and Tbx21 loci, indicating 'de-repression', along with enhanced histone tri-methylation at H3K4, indicating a 'permissive' transcriptional state. They also find evidence for enhanced STAT1 activity, which is relevant given the well-established role of STAT1 in promoting Th1 responses, and surprising given IL-27 is a potent STAT1 activator. This latter finding suggests that the Th1-inhibiting property of thymic IL-27 may not be due to direct effects on the T cells themselves.

Strengths:

Overall the data presented are high quality and the manuscript is well-reasoned and composed. The basic finding - that thymic IL-27 production limits the Th1 potential of SP, RTE, and Tn cells - is both unexpected and well described.

Weaknesses:

A credible mechanistic explanation, cellular or molecular, is lacking. The authors convincingly affirm the hyper-Th1 phenotype at epigenetic level but it remains unclear whether the observed changes reflect the capacity of IL-27 to directly elicit epigenetic remodeling in developing thymocytes or knock-on effects from other cell types which, in turn, elicit the epigenetic changes (presumably via cytokines). The authors propose that increased STAT1 activity is a driving force for the epigenetic changes and resultant hyper-Th1 phenotype. That conclusion is logical given the data at hand but the alternative hypothesis - that the hyper-STAT1 response is just a downstream consequence of the hyper-Th1 phenotype - remains equally likely. Thus, while the discovery of a new anti-inflammatory function for IL-27 within the thymus is compelling, further mechanistic studies are needed to advance the finding beyond phenomenology.

Reviewer #2 (Public Review):

Summary:

Naïve CD4 T cells in CD11c-Cre p28-floxed mice express highly elevated levels of proinflammatory IFNg and the transcription factor T-bet. This phenotype turned out to be imposed by thymic dendritic cells (DCs) during CD4SP T cell development in the thymus [PMID: 23175475]. The current study affirms these observations, first, by developmentally mapping the IFNg dysregulation to newly generated thymic CD4SP cells [PMID: 23175475], second, by demonstrating increased STAT1 activation being associated with increased T-bet expression in CD11c-Cre p28-floxed CD4 T cells [PMID: 36109504], and lastly, by confirming IL-27 as the key cytokine in this process [PMID: 27469302]. The authors further demonstrate that such dysregulated cytokine expression is specific to the Th1 cytokine IFNg, without affecting the expression of the Th2 cytokine IL-4, thus proposing a role for thymic DC-derived p28 in shaping the cytokine response of newly generated CD4 helper T cells. Mechanistically, CD4SP cells of CD11c-Cre p28-floxed mice were found to display epigenetic changes in the Ifng and Tbx21 gene loci that were consistent with increased transcriptional activities of IFNg and T-bet mRNA expression. Moreover, in autoimmune Aire-deficiency settings, CD11c-Cre p28-floxed CD4 T cells still expressed significantly increased amounts of IFNg, exacerbating the autoimmune response and disease severity. Based on these results, the investigators propose a model where thymic DC-derived IL-27 is necessary to suppress IFNg expression by CD4SP cells and thus would impose a Th2-skewed predisposition of newly generated CD4 T cells in the thymus, potentially relevant in autoimmunity.

Strengths:

Experiments are well-designed and executed. The conclusions are convincing and supported by the experimental results.

Weaknesses:

The premise of the current study is confusing as it tries to use the CD11c-p28 floxed mouse model to explain the Th2-prone immune profile of newly generated CD4SP thymocytes. Instead, it would be more helpful to (1) give full credit to the original study which already described the proinflammatory IFNg+ phenotype of CD4 T cells in CD11c-p28 floxed mice to be mediated by thymic dendritic cells [PMID: 23175475], and then, (2) build on that to explain that this study is aimed to understand the molecular basis of the original finding.

In its essence, this study mostly rediscovers and reaffirms previously reported findings, but with different tools. While the mapping of epigenetic changes in the IFNg and T-bet gene loci and the STAT1 gene signature in CD4SP cells are interesting, these are expected results, and they only reaffirm what would be assumed from the literature. Thus, there is only incremental gain in new insights and information on the role of DC-derived IL-27 in driving the Th1 phenotype of CD4SP cells in CD11c-p28 floxed mice.

Altogether, the major issues of this study remain unresolved:

(1) It is still unclear why the p28-deficiency in thymic dendritic cells would result in increased STAT1 activation in CD4SP cells. Based on their in vitro experiments with blocking anti-IFNg antibodies, the authors conclude that it is unlikely that the constitutive activation of STAT1 would be a secondary effect due to autocrine IFNg production by CD4SP cells. However, this possibility should be further tested with in vivo models, such as Ifng-deficient CD11c-p28 floxed mice. Alternatively, is this an indirect effect by other IFNg producers in the thymus, such as iNKT cells? It is necessary to explain what drives the STAT1 activation in CD11c-p28 floxed CD4SP cells in the first place.

(2) It is also unclear whether CD4SP cells are the direct targets of IL-27 p28. The cell-intrinsic effects of IL-27 p28 signaling in CD4SP cells should be assessed and demonstrated, ideally by CD4SP-specific deletion of IL-27Ra, or by establishing bone marrow chimeras of IL-27Ra germline KO mice.

eLife assessment

This useful study investigated the appearance of a "new-type" ultrasonic vocalization around 44 kHz that occurs in response to prolonged fear conditioning in rats. While the descriptive approach applied may be of interest to some researchers, evidence in support of the conclusions is incomplete.

Author response:

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In their manuscript entitled 'The domesticated transposon protein L1TD1 associates with its ancestor L1 ORF1p to promote LINE-1 retrotransposition', Kavaklıoğlu and colleagues delve into the role of L1TD1, an RNA binding protein (RBP) derived from a LINE1 transposon. L1TD1 proves crucial for maintaining pluripotency in embryonic stem cells and is linked to cancer progression in germ cell tumors, yet its precise molecular function remains elusive. Here, the authors uncover an intriguing interaction between L1TD1 and its ancestral LINE-1 retrotransposon.

The authors delete the DNA methyltransferase DNMT1 in a haploid human cell line (HAP1), inducing widespread DNA hypo-methylation. This hypomethylation prompts abnormal expression of L1TD1. To scrutinize L1TD1's function in a DNMT1 knock-out setting, the authors create DNMT1/L1TD1 double knock-out cell lines (DKO). Curiously, while the loss of global DNA methylation doesn't impede proliferation, additional depletion of L1TD1 leads to DNA damage and apoptosis.

To unravel the molecular mechanism underpinning L1TD1's protective role in the absence of DNA methylation, the authors dissect L1TD1 complexes in terms of protein and RNA composition. They unveil an association with the LINE-1 transposon protein L1-ORF1 and LINE-1 transcripts, among others.

Surprisingly, the authors note fewer LINE-1 retro-transposition events in DKO cells than in DNMT1 KO alone.

Strengths:

The authors present compelling data suggesting the interplay of a transposon-derived human RNA binding protein with its ancestral transposable element. Their findings spur interesting questions for cancer types, where LINE1 and L1TD1 are aberrantly expressed.

Weaknesses:

Suggestions for refinement:

The initial experiment, inducing global hypo-methylation by eliminating DNMT1 in HAP1 cells, is intriguing and warrants a more detailed description. How many genes experience misregulation or aberrant expression? What phenotypic changes occur in these cells?

The transcriptome analysis of DNMT1 KO cells showed hundreds of deregulated genes upon DNMT1 ablation. As expected, the majority were up-regulated and gene ontology analysis revealed that among the strongest up-regulated genes were gene clusters with functions in “regulation of transcription from RNA polymerase II promoter” and “cell differentiation” and genes encoding proteins with KRAB domains. In addition, the de novo methyltransferases DNMT3A and DNMT3B were up-regulated in DNMT1 KO cells suggesting the set-up of compensatory mechanisms in these cells. We will include this data set in the revised version of the manuscript.

Why did the authors focus on L1TD1? Providing some of this data would be helpful to understand the rationale behind the thorough analysis of L1TD1.

We have previously discovered that conditional deletion of the maintenance DNA methyltransferase DNMT1 in the murine epidermis results not only in the up-regulation of mobile elements, such as IAPs but also the induced expression of L1TD1 ((Beck et al, 2021), Suppl. Table 1 and Author response image 1). Similary, L1TD1 expression was induced by treatment of primary human keratinocytes or squamous cell carcinoma cells with the DNMT inhibitor aza-deoxycytidine (Author response image 2 and 3). These finding are in accordance with the observation that inhibition of DNA methyltransferase activity by azadeoxycytidine in human non-small cell lung cancer cells (NSCLCs) results in upregulation of L1TD1 (Altenberger et al, 2017). Our interest in L1TD1 was further fueled by reports on a potential function of L1TD1 as prognostic tumor marker. We will include this information in the revised manuscript.

Author response image 1.

RT-qPCR of L1TD1 expression in cultured murine control and Dnmt1 Δ/Δker keratinocytes. mRNA levels of L1td1 were analyzed in keratinocytes isolated at P5 from conditional Dnmt1 knockout mice (Beck et al., 2021). Hprt expression was used for normalization of mRNA levels and wildtype control was set to 1. Data represent means ±s.d. with n=4. **P < 0.01 (paired t-test).

Author response image 2.

RT-qPCR analysis of L1TD1 expression in primary human keratinocytes. Cells were treated with 5-aza-2-deoxycidine for 24 hours or 48 hours, with PBS for 48 hours or were left untreated. 18S rRNA expression was used for normalization of mRNA levels and PBS control was set to 1. Data represent means ±s.d. with n=3. **P < 0.01 (paired t-test).

Author response image 3.

Induced L1TD1 expression upon DNMT inhibition in squamous cell carcinoma cell lines SCC9 and SCCO12. Cells were treated with 5-aza-2-deoxycidine for 24 hours, 48 hours or 6 days. (A) Western blot analysis of L1TD1 protein levels using beta-actin as loading control. (B) Indirect immunofluorescence microscopy analysis of L1TD1 expression in SCC9 cells. Nuclear DNA was stained with DAPI. Scale bar: 10 µm. (C) RT-qPCR analysis of L1TD1 expression in primary human keratinocytes. Cells were treated with 5-aza-2deoxycidine for 24 hours or 48 hours, with PBS for 48 hours or were left untreated. 18S rRNA expression was used for normalization of mRNA levels and PBS control was set to 1. Data represent means ±s.d. with n=3. P < 0.05, *P < 0.01 (paired t-test).

The finding that L1TD1/DNMT1 DKO cells exhibit increased apoptosis and DNA damage but decreased L1 retro-transposition is unexpected. Considering the DNA damage associated with retro-transposition and the DNA damage and apoptosis observed in L1TD1/DNMT1 DKO cells, one would anticipate the opposite outcome. Could it be that the observation of fewer transposition-positive colonies stems from the demise of the most transposition-positive colonies? Further exploration of this phenomenon would be intriguing.

This is an important point and we were aware of this potential problem. Therefore, we calibrated the retrotransposition assay by transfection with a blasticidin resistance gene vector to take into account potential differences in cell viability and blasticidin sensitivity. Thus, the observed reduction in L1 retrotransposition efficiency is not an indirect effect of reduced cell viability.

Based on previous studies with hESCs, it is likely that, in addition to its role in retrotransposition, L1TD1 has additional functions in the regulation of cell proliferation and differentiation. L1TD1 might therefore attenuate the effect of DNMT1 loss in KO cells generating an intermediate phenotype (as pointed out by Reviewer 2) and simultaneous loss of both L1TD1 and DNMT1 results in more pronounced effects on cell viability.

Reviewer #2 (Public Review):

In this study, Kavaklıoğlu et al. investigated and presented evidence for the role of domesticated transposon protein L1TD1 in enabling its ancestral relative, L1 ORF1p, to retrotranspose in HAP1 human tumor cells. The authors provided insight into the molecular function of L1TD1 and shed some clarifying light on previous studies that showed somewhat contradictory outcomes surrounding L1TD1 expression. Here, L1TD1 expression was correlated with L1 activation in a hypomethylation-dependent manner, due to DNMT1 deletion in the HAP1 cell line. The authors then identified L1TD1-associated RNAs using RIP-Seq, which displays a disconnect between transcript and protein abundance (via Tandem Mass Tag multiplex mass spectrometry analysis). The one exception was for L1TD1 itself, which is consistent with a model in which the RNA transcripts associated with L1TD1 are not directly regulated at the translation level. Instead, the authors found the L1TD1 protein associated with L1-RNPs, and this interaction is associated with increased L1 retrotransposition, at least in the contexts of HAP1 cells. Overall, these results support a model in which L1TD1 is restrained by DNA methylation, but in the absence of this repressive mark, L1TD1 is expressed and collaborates with L1 ORF1p (either directly or through interaction with L1 RNA, which remains unclear based on current results), leads to enhances L1 retrotransposition. These results establish the feasibility of this relationship existing in vivo in either development, disease, or both.

eLife assessment

This potentially important paper reports on interactions between L1TD1, an RNA binding protein (RBP), and the ancestral LINE-1 retrotransposon from which it originates. Overall, the results support a model in which L1TD1 and LINE-1 ORF1p have synergistic effects on LINE-1 retrotransposition, but the evidence for whether this is through direct protein-protein interaction or through simultaneous interaction with LINE-1 RNA is currently incomplete.

Reviewer #1 (Public Review):

Summary:

In their manuscript entitled 'The domesticated transposon protein L1TD1 associates with its ancestor L1 ORF1p to promote LINE-1 retrotransposition', Kavaklıoğlu and colleagues delve into the role of L1TD1, an RNA binding protein (RBP) derived from a LINE1 transposon. L1TD1 proves crucial for maintaining pluripotency in embryonic stem cells and is linked to cancer progression in germ cell tumors, yet its precise molecular function remains elusive. Here, the authors uncover an intriguing interaction between L1TD1 and its ancestral LINE-1 retrotransposon.

The authors delete the DNA methyltransferase DNMT1 in a haploid human cell line (HAP1), inducing widespread DNA hypo-methylation. This hypomethylation prompts abnormal expression of L1TD1. To scrutinize L1TD1's function in a DNMT1 knock-out setting, the authors create DNMT1/L1TD1 double knock-out cell lines (DKO). Curiously, while the loss of global DNA methylation doesn't impede proliferation, additional depletion of L1TD1 leads to DNA damage and apoptosis.

To unravel the molecular mechanism underpinning L1TD1's protective role in the absence of DNA methylation, the authors dissect L1TD1 complexes in terms of protein and RNA composition. They unveil an association with the LINE-1 transposon protein L1-ORF1 and LINE-1 transcripts, among others.

Surprisingly, the authors note fewer LINE-1 retro-transposition events in DKO cells than in DNMT1 KO alone.

Strengths:

The authors present compelling data suggesting the interplay of a transposon-derived human RNA binding protein with its ancestral transposable element. Their findings spur interesting questions for cancer types, where LINE1 and L1TD1 are aberrantly expressed.

Weaknesses:

Suggestions for refinement:

The initial experiment, inducing global hypo-methylation by eliminating DNMT1 in HAP1 cells, is intriguing and warrants a more detailed description. How many genes experience misregulation or aberrant expression? What phenotypic changes occur in these cells? Why did the authors focus on L1TD1? Providing some of this data would be helpful to understand the rationale behind the thorough analysis of L1TD1.

The finding that L1TD1/DNMT1 DKO cells exhibit increased apoptosis and DNA damage but decreased L1 retro-transposition is unexpected. Considering the DNA damage associated with retro-transposition and the DNA damage and apoptosis observed in L1TD1/DNMT1 DKO cells, one would anticipate the opposite outcome. Could it be that the observation of fewer transposition-positive colonies stems from the demise of the most transposition-positive colonies? Further exploration of this phenomenon would be intriguing.

Reviewer #2 (Public Review):

In this study, Kavaklıoğlu et al. investigated and presented evidence for the role of domesticated transposon protein L1TD1 in enabling its ancestral relative, L1 ORF1p, to retrotranspose in HAP1 human tumor cells. The authors provided insight into the molecular function of L1TD1 and shed some clarifying light on previous studies that showed somewhat contradictory outcomes surrounding L1TD1 expression. Here, L1TD1 expression was correlated with L1 activation in a hypomethylation-dependent manner, due to DNMT1 deletion in the HAP1 cell line. The authors then identified L1TD1-associated RNAs using RIP-Seq, which displays a disconnect between transcript and protein abundance (via Tandem Mass Tag multiplex mass spectrometry analysis). The one exception was for L1TD1 itself, which is consistent with a model in which the RNA transcripts associated with L1TD1 are not directly regulated at the translation level. Instead, the authors found the L1TD1 protein associated with L1-RNPs, and this interaction is associated with increased L1 retrotransposition, at least in the contexts of HAP1 cells. Overall, these results support a model in which L1TD1 is restrained by DNA methylation, but in the absence of this repressive mark, L1TD1 is expressed and collaborates with L1 ORF1p (either directly or through interaction with L1 RNA, which remains unclear based on current results), leads to enhances L1 retrotransposition. These results establish the feasibility of this relationship existing in vivo in either development, disease, or both.

eLife assessment

This is valuable work showing that a combination of drugs can reduce growth of Diffuse midline gliomas (clinically classified as DMG, H3 K27M-mutant) when applied in vitro and in tumor xenografts in mice. It is a significant first step towards understanding how these drugs work, and provides convincing results to encourage future pre-clinical studies. Further rationale on how doses for specific drugs were chosen, directly demonstrating a survival benefit, or implicating the Pin1 pathway components mechanistically, would make the manuscript stronger.

Reviewer #1 (Public Review):

Summary:

This is an interesting study that utilizes a novel epigenome profiling technology (single molecule imaging) in order to demonstrate its utility as a readout of therapeutic response in multiple DIPG cell lines. Two different drugs were evaluated, singly and in combination. Sulfopin, an inhibitor of a component upstream of the MYC pathway, and Vorinostat, an HDAC inhibitor. Both drugs sensitised DIPG cells, but high (>10 micromolar) concentrations were needed to achieve half-maximal effects. The combination seemed to have some efficacy in vivo, but also produced debilitating side-effects that precluded the measurement of any survival benefit.

Strengths:

Interesting use of a novel epigenome profiling technology (single molecule imaging).

Weaknesses:

The use of this novel imaging technology ultimately makes up only a minor part of the study. The rest of the results, i.e. DIPG sensitivity to HDAC and MYC pathway inhibition, have already been demonstrated by others (Grasso Monje 2015; Pajovic Hawkins 2020, among others). The drugs have some interesting opposing effects at the level of the epigenome, demonstrated through CUT&RUN, but this is not unexpected in any way. The drugs evaluated here also didn't have higher efficacy, or efficacy at especially low concentrations, than inhibitors used in previous reports. The combination therapy attempted here also caused severe side effects in mice (dehydration/deterioration), such that an effect on survival could not be determined. I'm not sure this study advances knowledge of targeted therapy approaches in DIPGs, or if it iterates on previous findings to deliver new, or more efficient, mechanistic or therapeutic/pharmaclogic insights. It is a translational report evaluating two drugs singly and in combination, finding that although they sensitise cells in vitro, efficacy in vivo is limited at best, as this particular combination cannot progress to human translation.

Reviewer #2 (Public Review):

Summary:

The study by Algranati et al. introduces an exciting and promising therapeutic approach for the treatment of H3-K27M pediatric gliomas, a particularly aggressive brain cancer predominantly affecting children. By exploring the dual targeting of histone deacetylases (HDACs) and MYC activation, the research presents a novel strategy that significantly reduces cell viability and tumor growth in patient-derived glioma cells and xenograft mouse models. This approach, supported by transcriptomic and epigenomic profiling, unveils the potential of combining Sulfopin and Vorinostat to downregulate oncogenic pathways, including the mTOR signaling pathway. While the study offers valuable insights, it would benefit from additional clarification on several points, such as the rationale behind the dosing decisions for the compounds tested, the specific contributions of MYC amplification and H3K27me3 alterations to the observed therapeutic effects, and the details of the treatment protocols employed in both in-vitro and in-vivo experiments.

Clarification is needed on how doses were selected for the compounds in Figure S2A and throughout the study. Understanding the basis for these choices is crucial for interpreting the results and their potential clinical relevance. IC50s are calculated for specific patient derived lines, but it is not clear how these are used for selecting the dose.

The introduction mentions MYC amplification in high-grade gliomas. It would be beneficial if the authors could delineate whether the models used exhibit varying degrees of MYC amplification and how this factor, alongside differences in H3K27me3, contributes to the observed effects of the treatment.

In Figure 2A, the authors outline an optimal treatment timing for their in vitro models, which appears to be used throughout the figure. It would be helpful to know how this treatment timing was selected and also why Sulfopin is dosed first (and twice) before the vorinostat. Was this optimized?

It should be clarified whether the dosing timeline for the combination drug experiments in Figure 3 aligns with that of Figure 2. This information is also important for interpreting the epigenetic and transcriptional profiling and the timing should be discussed if they are administered sequentially (also shown in Figure 2A).I have the same question for the mouse experiments in Figure 4.

The authors mention that the mice all had severe dehydration and deterioration after 18 days. It would be helpful to know if there were differences in the side effects for different treatment groups? I would expect the combination to be the most severe. This is important in considering the combination treatment.

Minor Points:

(1) For Figure 1F, reorganizing the bars to directly compare the K27M and KO cell lines at each dose would improve readability of this figure.

(2) In Figure 4D, it would be helpful to know how many cells were included (or a minimum included) to calculate the percentages.

Reviewer #3 (Public Review):

Summary:

The authors use in vitro grown cells and mouse xenografts to show that a combination of drugs, Sulfopin and Vorinostat, can impact the growth of cells derived from Diffuse midline gliomas, in particular the ones carrying the H3 K27M-mutations (clinically classified as DMG, H3 K27M-mutant). The authors use gene expression studies, and chromatin profiling to attempt to better understand how these drugs exert an effect on genome regulation. Their main findings are that the drugs reduce cell growth in vitro and in mouse xenografts of patient tumours, that DMG, H3 K27M-mutant tumours are particularly sensitive, identify potential markers of gene expression underlying this sensitivity, and broadly characterize the correlations between chromatin modification changes and gene expression upon treatment, identifying putative pathways that may be affected and underlie the sensitive (and thus how the drugs may affect the tumour cell biology).

Strengths:

It is a neat, mostly to-the-point work without exploring too many options and possibilities. The authors do a good job not overinterpreting data and speculating too much about the mechanisms, which is a very good thing since the causes and consequences of perturbing such broad epigenetic landscapes of chromatin may be very hard to disentangle. Instead, the authors go straight after testing the performance of the drugs, identifying potential markers and characterizing consequences.

Weaknesses:

If anything, the experiments done on Figure 3 could benefit from an additional replicate.

eLife assessment

This important article presents the results of a large screen for non-genetic transgenerational effects that may influence gene expression and other phenotypes in mice. An extraordinary amount of mouse breeding, phenotyping, and RNA sequencing data provide compelling evidence that, for the phenotypes and genomic regions interrogated in these mouse strains, non-genetic transgenerational effects of appreciable magnitude are likely to be extremely rare. This paper will be of broad interest to geneticists and of particular interest to those studying epigenetic inheritance.

Reviewer #1 (Public Review):

Summary:

This paper explores the contribution of transgenerational effects to phenotypic variation in twenty-five phenotypes and transcript variation in the heart, liver, pituitary, whole embryo, and placenta. The authors use a powerful design, exploiting the use of consomics, and argue that there are no observable changes attributable to the differences in the parental origin of the four chromosomes they examine.

Strengths:<br /> It's good to see a use for consomics. This is a powerful and useful design to address the problem they are tackling.

Weaknesses:<br /> The difficulty faced by the authors is that they have interrogated only a small portion of the genome, using bulk RNA sequencing and a set of correlated phenotypes, thus restricting the conclusions they can draw from the absence of significant findings.

Reviewer #2 (Public Review):

Summary:

In this study, Gularte-Merida et al investigate the occurrence of transgenerational effects of non-transmitted parental alleles outside of the well-described effect of "genetic nurture." To achieve this they employed consomic male mice to generate an N2 and N3 population, allowing for the observation of effects due to non-transmitted paternal alleles while controlling for maternal care by using isogenic B6 dams. The authors conduct RNAseq, qPCR validation, and anatomical phenotyping measures to investigate the presence of non-genetic nurture TGE. The author's findings challenge the frequency of non-genetic nurture TGE, a meaningful contribution to the field. Overall, this is an ambitious study with important negative data. The authors are to be commended on this. This greatly strengthens the negative findings within the paper.

The paper, however, is written extremely technically, with little detail, and is not currently suitable for the lay audience. The authors need to greatly increase the clarity of the writing and data presentation.

Strengths:

Elegant experimental design using consomic mouse populations.

The use of a second replication cohort using the same genetic founders as the first study.

Weaknesses:

While much of the explanation of the methods is understandable by geneticists, the paper has implications outside of the genetics field. Overall, I suggest expanding the explanation and language for non-geneticists. This will allow the paper to reach a wider audience.

Reviewer #3 (Public Review):

Summary:

Gularte-Mérida and colleagues took advantage of the existence of so-called consomic strains in the mouse, which result from the substitution of one of their chromosomes by that of another strain, to ask through appropriate crosses whether information carried by this substitution chromosome impacts progeny that do not inherit it. With one exception, the authors did not detect any significant effect for any of the four non-transmitted chromosomes tested. Given these results, the authors conclude that such effects, if they exist, must be extremely rare in the mouse.

Strengths:

This is a very convincing and impressive study, with effects assessed in almost 2500 mice. The negative results obtained should put to rest once and for all the notion that intergenerational, let alone transgenerational, non-DNA sequence-based inheritance via the male germline could be substantial in the mouse.

Weaknesses:

The terminology used (epigenetics, nurture-independent TGE, etc. ) is somewhat confusing and unnecessary.

eLife assessment

This important mouse study shows that wild-type female progeny of Khdc3 mutants have abnormal gene expression relating to hepatic metabolism, which persists over multiple generations and passes through both female and male lineages. Information about litter size and a full phenotypic description of the phenotype of each progeny should be included to evaluate the impact of KHDC3 mutation on the progeny; in its current state, the evidence for the authors' claims is incomplete. A role for small RNAs on this phenomenon is proposed but has not been functionally validated. The work will be of interest to researchers in the field of DNA-independent mechanism of inheritance. Mentioning the experimental organism in title and abstract would ensure that it targets the appropriate audience.

Reviewer #1 (Public review):

The key discovery of the manuscript is that the authors found that genetically wild type females descended from Khdc3 mutants shows abnormal gene expression relating to hepatic metabolism, which persist over multiple generations and pass through both female and male lineages. They also find dysregulation of hepatically-metabolized molecules in the blood of these wild type mice with Khdc3 mutant ancestry. These data provide solid evidence further support that phenotype can be transmitted to multiple generations without altering DNA sequence, supporting the involvement of epigenetic mechanisms. The authors further performed exploratory studies on the small RNA profiles in the oocytes of Khdc3-null females, and their wild type descendants, suggesting that altered small RNA expression could be a contributor of the observed phenotype transmission, although this has not been functionally validated.

Reviewer #2 (Public review):

Summary:

This manuscript aimed to investigate the non-genetic impact of KHDC3 mutation on the liver metabolism. To do that they analyzed the female liver transcriptome of genetically wild type mice descended from female ancestors with a mutation in the Khdc3 gene. They found that genetically wild type females descended from Khdc3 mutants have hepatic transcriptional dysregulation which persist over multiple generations in the progenies descended from female ancestors with a mutation in the Khdc3 gene. This transcriptomic deregulation was associated with dysregulation of hepatically-metabolized molecules in the blood of these wild type mice with female mutational ancestry. Furthermore, to determine whether small non-coding RNA could be involved in the maternal non-genetic transmission of the hepatic transcriptomic deregulation, they performed small RNA-seq of oocytes from Khdc3-/- mice and genetically wild type female mice descended from female ancestors with a Khdc3 mutation and claimed that oocytes of wild type female offspring from Khdc3-null females has dysregulation of multiple small RNAs.

Finally, they claimed that their data demonstrates that ancestral mutation in Khdc3 can produce transgenerational inherited phenotypes.

However, at this stage and considering the information provided in the paper, I think that these conclusions are too preliminary. Indeed, several controls/experiments need to be added to reach those conclusions.

Additional context you think would help readers interpret or understand the significance of the work<br /> • Line 25: this first sentence is very strong and needs to be documented in the introduction.<br /> • Line 48: Reference 5 is not appropriate since the paper shows the remodeling of small RNA during post-testicular maturation of mammalian sperm and their sensibility to environment. Please, change it<br /> • Line 51: "implies" is too strong and should be replaced by « suggests »<br /> • Line 67: reference is missing<br /> Database, the accession numbers are lacking.<br /> • References showing the maternal transmission of non-genetically inherited phenotypes in mice via small RNA need to be added<br /> • Line 378: All RNA-Seq and small RNA-Seq data are available in the NCBI GEO

Reviewer #3 (Public Review):

In this important work, the authors show compelling evidence that the Rapid Alkalinisation Factor1 (RALF1) peptide acts as an interlink between pectin methyl esterification status and FERONIA receptor-like kinase in mediating extracellular sensing. Moreover, the RALF1-mediated pectin perception is surprisingly independent of LRX-mediated extracellular sensing in roots. The authors also show that the peptide directly binds demethylated pectin and the positively charged amino acids are required for pectin binding as well as for its physiological activity.

Some present findings are surprising; previously, the FERONIA extracellular domain was shown to bind pectin directly, and the mode of operation in the pollen tube involves the LRX8-RALF4 complex, which seems not the case for RALF1 in the present study. Although some aspects remain controversial, this work is a very valuable addition to the ongoing debate about this elusive complex regulation and signaling.

The authors drafted the manuscript well, so I do not have a lot of criticism or suggestions. The experiments are well-designed, executed, and presented, and they solidly support the authors' claims.

eLife assessment

This fundamental study provides mostly convincing evidence for pectin modification as a requirement for RALF peptide signalling altering the apoplastic pH, adding further support for a key role of RALF peptides in linking the assembly and dynamics of the extracellular matrix with cellular activity and function. A small number of additional controls would further enhance the study.

Reviewer #1 (Public Review):

Summary:

Rößling et al., report in this study that the perception of RALF1 by the FER receptor is mediated by the association of RALF1 with deesterified pectin, contributing to the regulation of the cell wall matrix and plasma membrane dynamics. In addition, they report that this mode of action is independent from the previously reported cell wall sensing mechanism mediated by the FER-LRX complex.

This manuscript reproduces and aligns with the results from a recently published study (Liu et al., Cell) where they also report that RALF1 can interact with deesterified pectin, forming coacervates and promoting the recruitment of LLG-FER at the membrane.

Reviewer #2 (Public Review):

Summary:

The study by Rößling et al. addresses the link between the biochemical constitution of the cell wall, in particular the methylesterification state of pectin with signalling induced by the extracellular RALF peptide. The work suggests that only in the presence of demethylesterifies pectin, RALF is able to trigger activation of its receptor FERONIA (FER).

Remarkably, the application of RALF peptides leads to rather dramatic FER-dependent changes in wall integrity and plasma membrane invaginations not observed before. Interestingly, RALF can be out-titrated from the wall by short pectin fragments. In addition, the study provides further evidence for multiple FER-dependent pathways by showing the presence of LRX proteins is not required for the pectin/RALF mediated signalling.

Strengths:

This work provides fundamental insight into a complex emerging pathway, or perhaps several pathways, linking pectin sensing, pectin structure and RALF/FER signalling. The study provides convincing evidence that pectin methylesterase activity is required for RALF sensing, indicating that the physical interaction of RALFs with the cell wall is important for signalling. Beyond that, the study documents very clearly how profoundly RALF signalling can affect cell wall integrity and membrane topology.

Weaknesses:

The genetic material used by the authors to strengthen the connection of RALF signalling and PME activity might not be as suitable as an acute inhibition of PME activity.

The PMEI3ox line generated by Peaucelle et al., 2008 is alcohol-inducible. Was expression of the PMEI induced during the experiments? As ethanol inducible systems can be rather leaky, it would not be surprising if PME activity would be reduced even without induction, but maybe this would warrant testing whether PMEI3 is actually overexpressed and/or whether PME activity is decreased. On a similar note, the PMEI5ox plants do not appear to show the typical phenotype described for this line. I personally don't think these lines are necessary to support the study. Short-term interference with PME activity (such as with EGCG) might be more meaningful than life-long PMEI overexpression, in light of the numerous feedback pathways and their associated potential secondary effects. This might also explain why EGCG leads to an increase in pH, as one would expect from decreased PME activity, while PMEI expression (caveats from above apply) apparently does not (Fig 3A-D).

At least at first sight, the observation that OGs are able to titrate RALF from pectin binding seems at odds with the idea of cooperative binding with low affinity, leading to high avidity oligomers. Perhaps the can provide a speculative conceptual model of these interactions?

I could not find a description of the OG treatment/titration experiments, but I think it would be important to understand how these were performed with respect to OG concentration, timing of the application, etc.

Reviewer #1 (Public Review):

Summary:

The authors report evidence for a microprotein of AtHB2-miP. The authors came across HB2 in a screen for alternative transcription start sites in Arabidopsis in response to white light or a white light followed by a far red light representative of shade. Out of 337 potential microproteins, authors selected AtHB2. At the beginning of the manuscript, it is investigated that an alternative transcription start site of HB2 gene can be used in response to far red light. The resulting shorter protein form seems to interact with HB2 protein forms, altering the localization of HB2 in transient expression assays. The functionality of HB2-miP overexpression has been addressed in transgenic Arabidopsis lines using a 35S promoter. The responses and phenotypes were compared with either WT or various types of athb2 mutant lines with disrupted HB2 gene. Such mutants and the 35S promoter-driven AtHB2-miP line showed various types of phenotypes versus each other that can be classified as mild or none, e.g. small effects on root growth, iron homeostasis gene expression, and iron contents.

Strengths:

The authors performed an interesting screen for alternative transcription start sites which resulted in 337 candidates (Figure 1A). Principally, it can be interesting to find that plants may use alternative start sites for HB2 in response to shading light. The authors provide evidence that alternative transcription start sites of HB2 can be present and used in response to FR. The possibility that potentially resulting small protein may have effects under FR light, causing alteration of root growth and physiology, is an interesting idea.

Weaknesses:

In the present manuscript, there are several signs of incomplete analysis.

(1) The transient expression experiments are not conducted with much detail to demonstrate that indeed HB2 miP is produced and can interact with regular protein. The localization of HB2 was found to be linked with condensates, but perhaps not in the presence of HB2 miP. Clearly, the lack of quantitative and qualitative analysis hampers a clear assessment of this point.

(2) The authors, unfortunately, did not provide the data of the screen to demonstrate which concrete candidates may have miPs and whether there is enrichment of certain functions. There is no supplemental table accompanying Figure 1A.

(3) One of the major unclear points that is also not addressed in the discussion is that the function of miR is studied in overexpression plants (35S promoter::miP). The effects are only compared to wild type and various lines of HB2 knockouts or knockdowns, partly with fairly uncharacterized phenotypes. It can now not be clearly determined whether the miP effects are due to a regular function of miP or due to overexpression of it. A needed control would be a 35S::AtHB2 line, or better at least two different lines (only a single miP overexpression line investigated). Since it has not been assessed by deletion mutant analysis to determine which protein parts of miP are involved in the protein regulation, it cannot be ruled out that the observed miP effects are not naturally occurring but the result of ectopic expression of a protein. Clearly, the effect of miP would be ideally studied in an environment where the levels can be controlled and the resulting phenotypes and protein levels quantified.

(4) It is not shown that the microprotein is generated in Arabidopsis in response to shade, e.g. through Western or fluorescence protein detection. The main idea that authors want to claim, namely that miP binds with regular protein and thereby controls its localization or activity has not been addressed in Arabidopsis. There are no localization experiments of HB2 protein data in the presence of miP in Arabidopsis.

(5) The plants with altered HB2 forms seem to grow well and the recorded phenotypes are rather minor. Photos are not shown. At some point, the authors discuss that there could be redundancy or that HB miP might interact with other HB proteins. However, such protein interactions have not been experimentally investigated.

Reviewer #2 (Public Review):

The first portion of the manuscript centered on identifying and confirming the ATHB2 microprotein (ATHB2miP), which constitutes the core message of this study. Overall, I find no issue with the selection criteria employed for identifying alternative microprotein mRNA transcripts. However, I do have some queries that I hope the authors can address for clarity.

(1) Upon reviewing the supplemental dataset where the authors listed the 377 unique novel miPs, along with those specifically in WL or shade treatments, I sought to comprehend the rationale behind focusing on ATHB2. Have the authors examined the shade response of all 377 potential microprotein candidates? Readers may be intrigued to learn how many of these candidates exhibit induction or repression under shade conditions, and whether such changes correlate positively or negatively with alterations in the full-length TSSs in response to shade. Essentially, I aim to discern the prevalence of microprotein production during shade responses and any shared characteristics among these microprotein transcripts. This inquiry also aims to uncover the existence of a common mechanism regulating microprotein transcription.

(2) To confirm that ATHB2miP stems from an independent transcription event, the authors sequenced full-length cDNAs using PacBio isoseq. However, I find the information regarding isoseq missing from the manuscript. My assumption is that the full-length cDNAs were reverse transcribed from mRNAs isolated from whole seedlings, where mature mRNAs in the cytoplasm predominate, making it challenging to evaluate whether a specific mRNA undergoes post-transcriptional processing. One approach to confirming ATHB2miP as a product of independent transcription involves examining nascent mRNA produced in the nucleus. The authors may need to isolate nascent mRNAs associated with RNA Polymerase II in the nucleus from seedlings treated with shade for 45 min, and then perform reverse transcription and PacBio isoseq.

(3) The authors noted the identification of two potential start codons, TTG and CTG, in the alternative TSS of ATHB2 using TISpredictor. Yet, it's imperative to identify the actual translation initiation site and the full-length sequence of ATHB2miP. I suggest the authors fuse an epitope tag (e.g., 3xFLAG) to the C-terminus of ATHB2 (utilizing the genomic sequence of ATHB2) and generate transgenic lines to be treated with shade to induce ATHB2miP-3xFLAG production. Affinity purification (anti-FLAG beads) and mass spectrometry can then identify the actual start site of ATHB2miP. This step is crucial, as the current ATHB2miP used may not be the exact sequence, and any observed phenotype could be artifacts arising from these lines.

(4) My confusion arose when analyzing the results in Figures 1E - G. The authors didn't specify whether these plants were subjected to shade treatment. What are the sequences within the second intron and third exon excluded from pATHB2control::GUS that promote transcription and translation? Have the authors examined the sequence features? This information is pivotal and related to the above question #1 because it may tell us whether the sequence feature is shared by other miP candidates.

The latter part of the manuscript focused on the functional characterization of ATHB2miP. The approaches adopted by the authors resemble those used in studying antimorphic (dominant negative) alleles. However, I have several concerns regarding the approaches and conclusions.

(5) Firstly, as mentioned in question #3, the authors did not map the actual translation initiation site of ATHB2miP. Therefore, all constructs involving ATHB2miP, such as eGFP-ATHB2miP, BD-ATHB2miP, and mCherry-ATHB2miP in Figure 2, and 35S::miP in Figures 3-5, may contain extra amino acids in the N-terminus, given that epitope tags were all added to the N terminus. These additional amino acids could potentially impact the behavior of ATHB2miP and lead to artifacts. Identifying the translation initiation site in ATHB2miP would facilitate the development of tools to disrupt ATHB2miP expression without affecting full-length ATHB2 expression. For instance, if the "CTG" before the leucine zipper domain is confirmed as the translation initiation site, mutating it to another Leu codon (e.g., TTA) could generate transgenic lines using the genomic sequence of ATHB2, including this mutation, to evaluate the impact of losing ATHB2miP on shade responses.

(6) Another concern pertains to the 35S::miP line utilized in Figures 3-5. The authors only presented results from one 35S::miP line, raising the possibility of T-DNA insertion disrupting an endogenous gene in the transgenic plant genome. It is essential to clarify how many individual T1 plants were generated and how many of them showed the same phenotype as the line used in the manuscript. Additionally, the use of the constitutive CaMV35S promoter could generate artifacts akin to neomorphic mutations. For example, the authors identified Cluster 1 genes that were only induced in 35S::miP, but not in t-athb2 or WT plants (Figure 3B); moreover, they found an overrepresentation of genes involved in root development in this cluster. This observation correlated well with the root phenotype of 35S::miP under the proximity shade (Figure 4D), in which the short-root phenotype was only observed in lines expressing 35S::miP. These data could be artifacts due to the constitutive expression of ATHB2miP in roots but didn't necessarily reflect the natural function of ATHB2miP.

(7) Furthermore, I seek clarification regarding the rationale behind employing different shade conditions, including deep shade, canopy shade, and proximity shade, and the significance of treating plants with these conditions. The results were challenging to interpret, and I have reservations about some statements made. The authors claimed that ATHB2 acts as a growth repressor in deep shade but a growth promoter in the canopy and proximity shade (Lines 366-368). However, it appears that regardless of the shade conditions, most mutant and transgenic lines were not significantly different from WT (Figure 4C). Additionally, the definition of proximity shade in this manuscript (R:FR = 0.06) differs from that in Roig-Villanova & Martinez-Garcia (Front. Plant Sci., 2016; R:FR, 0.5-0.3). Clarity on this disparity would be appreciated.

(8) In Figure 5, no statistical analyses were presented in Figure 5C. It remains unclear whether the differences observed are statistically significant. Moreover, the values appear quite similar among all three genotypes. Even if statistically significant, do these minor differences in Fe concentrations significantly impact plant physiology? Additionally, some statements related to Figure 5 do not align with the data presented. For instance, claims about longer hypocotyls in t-athb2, athb2∆, and atbh2∆LZ mutants compared to wild type under shade conditions on high iron media (lines 453-455) were not supported by the data in Figure 5D. Similarly, statements about the differences between mutants (lines 458-460) were not substantiated by the data.

Reviewer #3 (Public Review):

Summary and Strengths:

In this interesting manuscript, the authors identify a large number of alternative transcription start sites (TSS) and focus their functional analysis on an alternative TSS that is expected to produce a micro-protein (miP) encoding the C-terminus of ATHB2 (ATHB2miP). ATHB2miP is expected to comprise the leucine zipper part of ATHB2 and hence interact with the full-length protein through this dimerization motif. Such interactions are shown using yeast two-hybrid and FRET-FLIM assays. ATHB2 is a well-known shade-induced gene that has been implicated in shade-regulated growth responses. The authors then test the potential role for ATHB2miP genetically by comparing several athb2 loss-of-function (LOF) alleles: one does not express either full-length ATHB2 or the short ATHB2miP (t-ATHB2), two CRISPR alleles give rise to frameshift mutations in the full-length transcript but still express a potentially functional short ATHB2miP (athb2deltaLZ and athb2delta). The authors also use plants that over and ectopically express ATHB2miP (35S:miP). Overall, the results are consistent with the hypothesis that ATHB2miP inhibits the function of ATHB2, which constitutes a novel negative feedback loop. Potentially ATHB2miP may also inhibit the activity of other related HD ZIP proteins (based on 35S:miP). The effects of these genetic alterations on shade-regulated hypocotyl growth are relatively modest. Effects on root growth are also investigated and in one intriguing case, the negative feedback model does not appear to explain the data (Figure 4D, effect on lateral roots, because for this phenotype 35S:miP is very different from the lof alleles). The authors also identify a potentially interesting link between shade-regulated hypocotyl growth and iron uptake. A number of text changes and corrections to the figures would be important for clarity. They primarily concern three issues: names of the alleles, names of the studied shade conditions, and statements about significant differences between genotypes. Also, it would be interesting to know whether the effects of ATHB2 on iron uptake are due to local effects of ATHB2. Is ATHB2 expressed in roots?

Weaknesses:

(1) The naming of the different shade conditions is difficult to follow and not consistent with the way most authors in the field call such conditions. Deep shade is ok (low PAR and low R/FR, WL, PAR 13microE, R/FR 0.13). This condition is clearly defined for experiments in Figure 4. However, data in Figure 1 also use Deep shade (line 174) but PAR is not defined there. I suggest that all light conditions are clearly defined in the figure legends and in the M&M (not the case in this ms). Regarding Canopy shade (WL, PAR 45microE, R/FR 0.15) and proximity shade (WL, PAR 45microE, R/FR 0.06), see lines 355-357, this nomenclature is unclear. First proximity shade has a higher R/FR ratio than canopy shade. Second for canopy shade (compared to the WL control) PAR should decrease which is not what is done here. What is called proximity shade and canopy shade are 2 WL conditions with different R/FR ratios, which are compared to WL controls with the same PAR. It would make more sense to call them proximity shade and indicate the different R/FR ratios. Finally, extensive literature from many plant species and numerous labs has shown that hypocotyl elongation increases with R/FR decreasing. In the data shown in Figure 4, it is the opposite. Hypocotyls in Canopy shade (WL, PAR 45microE, R/FR 0.15) are longer than those in proximity shade (WL, PAR 45microE, R/FR 0.06), while with these R/FR ratios the opposite is expected. Could this be a mistake in the text? Please check.

(2) In several instances (in particular regarding data from Figures 4 and 5), the authors write that 2 genotypes are significantly different while the statistical analysis of the data does not support such statements. For example lines 392-395, the authors write that in WL the t-DNA mutant, both CRISPR mutants and 35S:miP lines all had significantly lower number of lateral roots than the WT. This is true for the t-DNA mutant (group bc, while the WT is in group a), however, all other genotypes are in group ab, hence not significantly different from the WT. Please carefully check all such statements about significant differences.

(3) The naming of the CRISPR mutants is problematic. In particular athb2delta, such a name suggests that the gene is deleted (also suggested by Figure 4A), which is not the case in this CRISPR allele leading to a frameshift early in the coding sequence. This is particularly problematic because in this allele ATHB2miP is still expressed, while based on such a name one would expect that in this mutant both the full length and the miP are lost. Both CRISPR alleles lead to a frameshift and this should be clarified in Figure 4A and in the text.

(4) Overall hypocotyl growth phenotypes of athb2 lof mutants and 35S:miP are similar and consistent with a model according to which ATHB2miP inhibits the full-length protein. However, this is not the case for the root phenotype described in 4D. It would be interesting to discuss this.

(5) The authors propose a role for ATHB2 in the root, in particular linked to iron uptake. Is this due to a local effect of ATHB2 in the roots? Is ATHB2 expressed in roots? It would be very informative if the authors would show such data, e.g. using the reporter lines used in Figure 1. Are both the FL and the miP expressed in roots?

(6) From the description regarding 5'PEAT.seq data presented in Figure 1 (see lines 174-177) it is not clear in which light conditions the seedlings were grown. It appears that samples were collected in 3 conditions. WL and after 45 and 90 minutes of low R/FR treatment. However, then the data is discussed collectively. Does the 12398 TSS correspond to what was found in all three conditions together? Are the authors showing shade-regulation of TSS? This is clearly the case for ATHB2miP. This needs to be clarified.

(7) The way gene expression of low F/FR effects is done might conflate circadian effects and low R/FR effects because the samples from different light conditions are not collected at the same ZT. This is how I understood the text. If I'm wrong please clarify the text. If I am right, this potential problem should be mentioned in the text.

(8) Could the authors envisage a way to genetically test the role of ATHB2miP by using an allele that makes the full length but not the miP? Currently, the authors use lof alleles that either make none of the transcripts (t-DNA) or potentially only the miP (CRISPR alleles). Overall, these alleles do not appear to differ in their phenotypes, suggesting that most of the effect of ATHB2miP is through ATHB2 FL. Having an allele only producing the FL would be nice (but technically I'm not sure how one could do that).

eLife assessment

This valuable study showcases a novel and exciting vaccine platform but the evidence supporting the claims is incomplete. The work would benefit from robust statistical analysis of experimental groups with a larger number of individuals. There is also comparison to other existing vaccine platforms (such as the mosaic nanoparticle where hemagglutinin trimers are used).

Reviewer #1 (Public Review):

Summary:

In this manuscript by Thronlow Lamson et al., the authors develop a "beads-on-a-string" or BOAS strategy to link diverse hemagglutinin head domains, to elicit broadly protective antibody responses. The authors are able to generate varying formulations and lengths of the BOAS and immunization of mice shows induction of antibodies against a broad range of influenza subtypes. However, several major concerns are raised, including the stability of the BOAS, that only 3 mice were used for most immunization experiments, and that important controls and analyses related to how the BOAS alone, and not the inclusion of diverse heads, impacts humoral immunity.

Strengths:

Vaccine strategy is new and exciting.

Analyses were performed to support conclusions and improve paper quality.

Weaknesses:

Controls for how different hemagglutinin heads impact immunity versus the multivalency of the BOAS.

Only 3 mice were used for most experiments.

There were limited details on size exclusion data.

Reviewer #2 (Public Review):

Summary:

The authors describe a "beads-on-a-string" (BOAS) immunogen, where they link, using a non-flexible glycine linker, up to eight distinct hemagglutinin (HA) head domains from circulating and non-circulating influenzas and assess their immunogenicity. They also display some of their immunogens on ferritin NP and compare the immunogenicity. They conclude that this new platform can be useful to elicit robust immune responses to multiple influenza subtypes using one immunogen and that it can also be used for other viral proteins.

Strengths:

The paper is clearly written. While the use of flexible linkers has been used many times, this particular approach (linking different HA subtypes in the same construct resembling adding beads on a string, as the authors describe their display platform) is novel and could be of interest.

Weaknesses:

The authors did not compare to individuals HA ionized as cocktails and did not compare to other mosaic NP published earlier. It is thus difficult to assess how their BOAS compare.

Other weaknesses include the rationale as to why these subtypes were chosen and also an explanation of why there are different sizes of the HA1 construct (apart from expression). Have the authors tried other lengths? Have they expressed all of them as FL HA1?

Reviewer #3 (Public Review):

This work describes the tandem linkage of influenza hemagglutinin (HA) receptor binding domains of diverse subtypes to create 'beads on a string' (BOAS) immunogens. They show that these immunogens elicit ELISA binding titers against full-length HA trimers in mice, as well as varying degrees of vaccine mismatched responses and neutralization titers. They also compare these to BOAS conjugated on ferritin nanoparticles and find that this did not largely improve immune responses. This work offers a new type of vaccine platform for influenza vaccines, and this could be useful for further studies on the effects of conformation and immunodominance on the resulting immune response. 

Overall, the central claims of immunogenicity in a murine model of the BOAS immunogens described here are supported by the data. 

Strengths included the adaptability of the approach to include several, diverse subtypes of HAs. The determination of the optimal composition of strains in the 5-BOAS that overall yielded the best immune responses was an interesting finding and one that could also be adapted to other vaccine platforms. Lastly, as the authors discuss, the ease of translation to an mRNA vaccine is indeed a strength of this platform. 

One interesting and counter-intuitive result is the high levels of neutralization titers seen in vaccine-mismatched, group 2 H7 in the 5-BOAS group that differs from the 4-BOAS with the addition of a group 1 H5 RBD. At the same time, no H5 neutralization titers were observed for any of the BOAS immunogens, yet they were seen for the BOAS-NP. Uncovering where these immune responses are being directed and why these discrepancies are being observed would constitute informative future work. 

There are a few caveats in the data that should be noted: 

(1) 20 ug is a pretty high dose for a mouse and the majority of the serology presented is after 3 doses at 20 ug. By comparison, 0.5-5 ug is a more typical range (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6380945/, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980174/). Also, the authors state that 20 ug per immunogen was used, including for the BOAS-NP group, which would mean that the BOAS-NP group was given a lower gram dose of HA RBD relative to the BOAS groups. 

(2) Serum was pooled from all animals per group for neutralization assays, instead of testing individual animals. This could mean that a single animal with higher immune responses than the rest in the group could dominate the signal and potentially skew the interpretation of this data. 

(3) In Figure S2, it looks like an apparent increase in MW by changing the order of strains here, which may be due to differences in glycosylation. Further analysis would be needed to determine if there are discrepancies in glycosylation amongst the BOAS immunogens and how those differ from native HAs.

eLife assessment

The study reports on a previously unrecognized function of ATG6 in plant immunity. The work is valuable because it proposes a direct interaction between ATG6 and a well-studied salicylic acid receptor protein, NPR1, which may interest researchers investigating plant immunity regulation. While the data presented are compelling, more information regarding the specificity of ATG6's role would improve the overall impact of the study, especially with an eye towards consistency with prior work.

Reviewer #1 (Public Review):

Summary:

The authors showed that autophagy-related genes are involved in plant immunity by regulating the protein level of the salicylic acid receptor, NPR1.

Strengths:

The experiments are carefully designed and the data is convincing. The authors did a good job of understanding the relationship between ATG6 and NRP1.

Weaknesses:<br /> - The authors can do a few additional experiments to test the role of ATG6 in plant immunity.<br /> I recommend the authors to test the interaction between ATGs and other NPR1 homologs (such as NPR2).

-The concentration of SA used in the experiment (0.5-1 mM) seems pretty high. Does a lower concentration of SA induce ATG6 accumulation in the nucleus?

-Does the silencing of ATG6 affect the cell death (or HR) triggered by AvrRPS4?

-SA and NPR1 are also required for immunity and are activated by other NLRs (such as RPS2 and RPM1). Is ATG6 also involved in immunity activated by these NLRs?

Reviewer #2 (Public Review):

Summary:

The manuscript by Zhang et al. explores the effect of autophagy regulator ATG6 on NPR1-mediated immunity. The authors propose that ATG6 directly interacts with NPR1 in the nucleus to increase its stability and promote NPR1-dependent immune gene expression and pathogen resistance. This novel role of ATG6 is proposed to be independent of its role in autophagy in the cytoplasm. The authors demonstrate through biochemical analysis that ATG6 interacts with NPR1 in yeast and very weakly in vitro. They further demonstrate using overexpression transgenic plants that in the presence of ATG6-mcherry the stability of NPR1-GFP and its nuclear pool is increased.

However, the overall conclusions of the study are not well supported experimentally. The significance of the findings is low because of their mostly correlational nature, and lack of consistency with earlier reports on the same protein.

Based on the integrity and quality of the data as well as the depth of analysis, it is not yet clear if ATG6 is a specific regulator of NPR1 or if it is affecting NPR1's stability indirectly, through inducing an elevation of SA levels in plants. As such, the current study demonstrates a correlation between overexpression of ATG6, SA accumulation, and NPR1 stability, however, whether and how these components work together is not yet demonstrated.

Based on the provided biochemical data, it is not yet clear if the ATG6 functions specifically through NPR1 or through its paralogs NPR3 and NPR4, which are negative regulators of immunity. It is quite possible that interaction with NPR1 (or any NPR) is not the major regulatory step in the activity of ATG6 in plant immunity. The effect of ATG6 on NPR1 could well be indirect, through a change in the SA level and redox environment of the cell during the immune response. Both SA level and redox state of the cell were reported to induce accumulation of NPR1 in the nucleus and increase in stability.

Another major issue is the poor quality of the subcellular analyses. In contradiction to previous studies, ATG6 in this study is not localized to autophagosome puncta, which suggests that the soluble localization pattern presented here does not reflect the true localization of ATG6. Even if the authors propose a novel, non-canonical nuclear localization for ATG6, they still should have detected the canonical autophagy-like localization of this protein.

eLife assessment

The investigation of the functional significance of the X-linked ciliary protein OFD1 gene in regulating the fate of cranial neural crest-derived cells (CNCCs) and its potential effect on myogenic progenitors during tongue development is interesting because the Ofd1 conditional knockout mouse model has a very striking phenotype and nicely mimics the phenotype in humans. It is a valuable model to understand human disease. This study will require additional experiments to support their conclusions.

Reviewer #1 (Public Review):

In this study, the authors reported that disruption of the X-linked ciliary protein OFD in the cranial neural crest-derived cells (CNCCs) leads to a migration defect in the CNCCs and that aberrant CNCCs abnormally differentiate into osteoblasts due to a lack of Hh signal. Furthermore, CNCC defects lead to the failure of mesoderm-derived cells to differentiate into myoblasts and instead result in abnormal differentiation of mesoderm-derived cells into adipocytes. The Ofd cko mouse model has a very striking phenotype and nicely mimics the phenotype of human patients, making it a very valuable model to understand human disease.

Reviewer #2 (Public Review):

In this study, the authors report that both mice and human patients carrying function-disrupting mutations in the OFD1 gene exhibited ectopic brown adipose tissue formation in the malformed tongue. The OFD1 gene is located on the X-chromosome and encodes a protein product required for the formation and function of the primary cilium, which is required for cells to properly receive and activate several signaling pathways, particularly the hedgehog signaling pathway. Loss of OFD1 function causes prenatal lethality of male fetuses and mosaic disruption of tissues in females due to random inactivation of the X-chromosome carrying either the mutant or wildtype allele. Using cell type-specific gene inactivation and genetic lineage labeling, the manuscript shows that the ectopic brown adipose tissue in the mutant tongue was not derived from cranial neural crest cells (CNCCs). Additional genetic and embryological studies led to the conclusion that loss of Ofd1 function in the CNCC cells in the embryonic hypoglossal cord, via which the tongue myoblast precursor cells migrate from anterior somites to the tongue primordia, caused disruption of cell-cell interactions between the CNCCs and migrating muscle precursor cells, resulting in altered differentiation of those myoblast precursor cells into brown adipocytes. The authors provided data that disruption of Smo in a subset of CNCCs also resulted in ectopic adipose tissue formation in the tongue, indicating that this phenotype in the Ofd1 mutant mice was likely caused by disruption of hedgehog signaling in CNCCs. However, no experimental evidence is provided to support a major conclusion of the manuscript regarding altered differentiation of the tongue myoblast precursor cells into brown adipocytes in the Ofd1 mutant mice. Since it is well established that hedgehog signaling in the CNCCs is required for them to direct tongue myoblast cell migration as well as for tongue muscle differentiation/organization after the myoblasts arrived in the tongue primordia, the finding of tongue muscle defects in the Ofd1 mutant mice is not surprising. However, if proven true that disruption of Ofd1 function in CNCCs caused tongue myoblast precursor cells to alter their fate and differentiate into brown adipocytes, it would be an interesting new finding. Further identification of the signals produced by the Ofd1 mutant CNCCs for directing the cell fate switch will be a highly significant new advance in understanding the cellular and molecular mechanisms regulating tongue morphogenesis.

Reviewer #3 (Public Review):

The authors observed phenotypes of ciliopathy model mice and they seem to coincide with those in human patients. They used mutants in which cilial function genes are deleted in cranial neural crest cells, and found the mutants exhibit abnormal cell differentiation in both neural crest- and mesoderm-lineage cells. The finding clearly shows the importance of tissue/cell interaction. The authors mainly observed the mouse in which Ofd1 gene that is coded on the X chromosome is deleted, therefore, Ofd1fl/WT;Wnt1Cre(HET) mice show that about one-fourth of neural crest cells can exhibit Ofd1 function whereas Ofd1fl;Wnt1Cre (HM) shows null Ofd1 function and show severer phenotypes than HET.

For ectopic brown adipose tissue in the tongue is derived from mesoderm and the authors tried to show that the hypoglossal cord failed to obtain myogenic lineage after entering branchial arches in HET and HM due to lack of communication with neural crest cells. For ectopic bone formation, they found that it is due to the lack of Hedgehog signaling in neural crest cells, which was consistent with the reports in the Smofl/fl;Wnt1-Cre (Xu et al., 2019) and Ift88fl/fl;Wnt1Cre (Kitamura et al. 2020). The ectopic bone is connected to the original mandibular bone. The authors attribute the ectopic bone formation to the migration of mandibular bone neural crest cells into the tongue-forming area.

For the poor tongue frenum formation, the authors found the importance of cell migration from the lateral sides of the branchial arch to the midline and its formation relies on non-canonical Wnt signaling. The authors observed similar phenotypes in the human patients as those in the mutants. The adipose tissue in the tongue area is normally found in the salivary gland region and intermuscular space, and it is intriguing to find the brown adipose tissue anterior to the cervical area in which the most anterior brown adipose tissue develops. qRT-PCR indicates that some of the marker genes are expressed in the laser micro-dissected sections of the ectopic brown adipose tissue. However, histology does not show the typical brown adipose tissue feature. In addition, brown adipose tissue is normally recognized in the sixth pharyngeal region as the cervical brown tissue from around E14.5 (Schulz and Tseng 2013), not E12 as the authors observe. Although the mutants develop under abnormal conditions, is it possible to say they are brown adipose tissue? The point has to be further investigated with more marker expression by immunohistochemical detection and other methods. Since the mutants seem to show impaired midline formation (which is consistent with the condition of human ciliopathy), is it possible to hypothesize that the adipose-like tissue is derived from the mesoderm of posterior branchial arch levels if the tissue is brown adipose tissue?

Cranial neural crest cells start migrating around E8.0 and reach their destination by E9.5. The authors show the lack of neural crest cells in the midline, the fluorescence is absent from the midline in HM, however, they studied it in the E11 mandible (Fig. 4E), almost more than two days after neural crest migration completes. Since the mandibular arch seems to form at the beginning in the mutants, is there a failure in allocating the neural crest and mesoderm at the beginning of the mandibular arch formation?<br /> The authors tried to disturb the interaction between the hypoglossal cord and neural crest cells by making incisions in the dorsal area of the branchial arches. That area contains both neural crest and mesoderm but not the hypoglossal cord-derived mesoderm. The hypoglossal cord passed through the posterior edge of the caudal (6th) pharyngeal arch, along the lateral side of the pericardium towards the anterior, ventral to branchial arches, and then inside the 2nd and 1st branchial arches (Adachi et al., 2018). It expresses Pax3 before entering the branchial arches, then Myf5 in the branchial arches. It seems that the migration of the hypoglossal cord does not require interaction with neural crest cells but it has to be confirmed as well as neural crest migration into the branchial arches from the beginning. Although the hypoglossal cord migrates mostly in mesoderm-derived mesenchyme, we cannot exclude the possibility that hypoglossal cord migration is affected.

The lack of Myf5 expression in Ofd1fl;Wnt1Cre (HM) was explained as a failure in the differentiation of the hypoglossal cord into myoblasts on entrance into the branchial arches. Most of the cervical brown adipose tissue is derived from either Myf5- or Pax3- expressing lineage (Sanchez-Gurmaches and Guertin, 2014). Although the authors suggest that brown adipose cells are fate-changed mesoderm in the branchial arches, how do they explain the association with Myf5- or Pax3- expression?

In addition, the cervical brown tissue is supposed to be derived from the branchial arch mesoderm (Mo et al., 2017). Is the formation of the cervical brown tissue affected in the Ofd1fl/WT;Wnt1Cre(HET) or Ofd1fl;Wnt1Cre (HM) if dysfunction of neural crest cells results in the cell fate change of mesoderm?

For the tongue frenum development, it is hard to understand to hypothesize that its formation is unlikely to associate with midline formation. Although Lgr5 and Tbx22 are not expressed in the midline, the defect in midline formation could cause unnecessary interaction between the right and left tissues.

Tissue morphogenesis takes place in three dimensions, which were not considered in the data, especially in the labeling experiments. When the authors labelled the cells, which cells in which area were labelled? In the textbook, tongue formation is a result of the fusion of the midline processes derived from the branchial arches, therefore, it is important to identify which cells in which area are labelled.

The weakest point is that the authors demonstrate many interesting phenotypes but fail to show the mechanism of altered cell differentiation and direct evidence of the tissue origin of ectopic brown tissue. Without the data, suggestion from the authors' argument is weak, which is reflected in the conclusion of the abstract.

eLife assessment

This useful study defines developmental roles for a protein kinase involved in endocytosis and reports a surprising finding that the kinase catalytic activity is unnecessary. However, several claims of the authors are only partially supported by the data. Although in its current form, this work is incomplete, it will be of broad interest to cell biologists and biochemists because this kinase was previously suggested to be a target of drug design efforts.

Reviewer #1 (Public Review):

Recent work reported that the AP2-associated kinase 1 (AAK1) downregulates Wnt signaling by phosphorylating, thus activating, the µ-subunit of the AP2 complex (AP2M1), which recognizes an endocytic signal on the intracellular domain of the Wnt co-receptor LRP6 leading to its internalization (Agajanian, et al., 2018). It has also long been known that DPY-23/AP2M1 and the retromer complex, which controls trafficking between endosomes and the trans-golgi network and recycling from endosomes to the plasma membrane, regulate Wnt signaling in C. elegans, at least in part by modulating trafficking of the Wnt-secretion factor MIG-14/WLS (Pan, et al., 2008; Yan et al., 2008).

Here the authors first set out to ask whether SEL-5/AAK1 plays a conserved role in Wnt signaling via phosphorylation of DPY-23/AP2M1 by assessing the function of SEL-5 in Wnt-regulated morphogenetic events; specifically, the well-characterized migration and polarization of several neurons and the less-understood process of excretory canal cell outgrowth.

The authors found that the simultaneous removal of sel-5 and the retromer complex gene vps-29 resulted in synthetic neuronal and excretory canal outgrowth phenotypes, indicating that sel-5 and the retromer complex function in parallel in these processes. Genetic interactions between sel-5 and Wnt pathway components were also examined, and for QL neuroblast migration, loss of sel-5 exacerbated phenotypes caused by loss of the Wnt receptor LIN-17/FZD, but not those caused by loss of a different receptor, MIG-1/FZD. The authors assessed the site of sel-5 function in neuronal migration defects via tissue-specific rescue and identified the hypodermis, a known source of Wnt ligands, and muscles as sites where sel-5/AAK1 activity is required.

The novelty in this work comes from the discovery of a function for sel-5/AAK1 and the retromer complex in excretory canal outgrowth, identified by phenotypes caused by simultaneous loss of sel-5 and retromer components. This synthetic phenotype is rescued by restoring sel-5 to either the excretory canal cell or the hypodermis, suggesting autonomous and non-autonomous functions for sel-5 in canal outgrowth. The authors also confirmed previous results showing that loss of LIN-17/FZD results in excretory canal overgrowth, and by carrying out an extensive survey of Wnt-pathway mutants they discovered that LIN-44/Wnt is likely the ligand that functions via LIN-17 as a "stop" signal in canal outgrowth. They also implicate a CWN-1/Wnt-CFZ-2/FZD pathway as required for canal outgrowth and find genetic interactions between sel-5/AAK1 and the lamellipodin ortholog mig-10, suggesting that these genes function in parallel to promote excretory canal outgrowth.

The most intriguing claim in this work is the suggestion that neither DPY-23 phosphorylation nor SEL-5 kinase activity is required for their function in Wnt signaling. However, the tools used to support these conclusions are not well-characterized. First, a new dpy-23 phosphorylation site-mutant is not genetically characterized, thus it is difficult to interpret the negative results obtained with this allele. Second, although the mutations introduced into SEL-5 are expected to abolish kinase activity, this is not demonstrated biochemically, nor are the effects, if any, of mutations on protein stability/localization assessed. Finally, experiments testing the function of SEL-5 kinase mutants are reported using only one multi-copy extrachromosomal array per construct. Because these types of transgenes vastly overexpress proteins, it is likely that even proteins with reduced function will rescue, raising concerns regarding the conclusion that kinase activity is not necessary for SEL-5 function.

In conclusion, it is not clear that the findings presented here will be of great general interest, as they mostly support previously-known functions for SEL-5/AAK1, DPY-23/AP2M1, and the retromer complex in Wnt-mediated signaling. Thus, this work will mainly be of interest to researchers studying Wnt-mediated cell outgrowth, and more specifically to those studying the C. elegans excretory canal. Moreover, the study lacks coherence: initially, there is a clear hypothesis testing a role for SEL-5/AAK1 in DPY-23/AP2M1 phosphorylation and how this impinges on Wnt signaling. This model appears to be refuted (although, as noted above the tools used to do this need to be better validated), but the authors do not explore alternative targets or functions for SEL-5/AAK1, nor do they directly assess how SEL-5 or the retromer complex impinge on Wnt signaling in excretory canal outgrowth. Thus, there is little mechanistic insight provided by this work.

Reviewer #2 (Public Review):

Summary<br /> This study by Knop, et al. defines two different developmental roles for the conserved SEL-5/AAK1 protein kinase in Caenorhabditis elegans. In other organisms, AAK1 was known to promote the recycling of the Wntless sorting receptor and endocytosis of Wnt receptors. This study establishes that SEL-5 acts in two roles in C. elegans: in Wnt-producing cells, a role that promotes migration of a neuroblast termed QL.d, and in Wnt-receiving cells, a role that promotes outgrowth of the excretory cell (EXC). Before this study, SEL-5/AAK1 was thought to regulate endocytosis through phosphorylation of AP2M1 and other endocytic adaptor proteins. This study shows convincing data that the SEL-5 makes a partial contribution to AP2M1 phosphorylation, and more surprisingly, that its roles in Wnt-producing and Wnt-receiving cells of C. elegans do not require SEL-5 catalytic activity. Human AAK1 was previously suggested to be a target of drug design efforts due to its roles in neuropathic pain, viral infection, and Alzheimer's disease. The discovery that some roles for SEL-5/AAK1 are independent of catalytic activity will be of broad interest to cell biologists and biochemists.

Strengths<br /> (1) The data establishing the requirement for SEL-5 in QL.d migration and EXC outgrowth (Fig. 1 and Fig. 4) is rigorous and convincing. My assessment of the rigor is based on the following: First, the authors show that two independently derived sel-5 deletion mutations result in defects in QL.d and EXC. Second, the authors show that providing wild-type, GFP-tagged SEL-5 results in significant rescue of both phenotypes. Importantly, they use tissue-specific transgenes to show that the requirement for SEL-5 in QL.d migration is non-cell-autonomous, and the requirement for SEL-5 in EXC outgrowth is cell-autonomous (Fig. 2). For rescue experiments, they show that each tissue-specific transgene is indeed expressed strongly in the tissue of interest. This establishes the roles for SEL-5 in two different roles, in Wnt-producing and Wnt-receiving cells.

(2) The authors present three lines of convincing biochemical and genetic evidence that SEL-5 kinase catalytic activity is not important for its roles in Wnt-producing and Wnt-receiving cells.

Taking a biochemical approach, they use quantitative Westerns to assess the degree of AP2M1 phosphorylation in sel-5 mutants (Fig. 3). Their results show that AP2M1 phosphorylation is diminished, but not absent in mutants. Their results are convincing because they make use of GFP-tagged AP2M1 to probe for total and phospho-AP2M1. I note that they included uncropped Western blots in supplemental data. Furthermore, they make use of a GFP-tagged AP2M1 mutant (T160A) to confirm which residue is phosphorylated. Their results suggest that some mechanism other than AP2M1 phosphorylation may account for the sel-5 mutant phenotypes.

Taking a genetic approach, they make use of a unique allele, dpy-23(mew25), that alters the known AP2M1 phosphorylation site. They show that animals carrying this allele do not display the QL.d and EXC phenotypes (Fig. 3 and Fig. 5). Finally, in a more direct test of whether SEL-5 requires catalytic activity, they make use of GFP-tagged SEL-5 forms mutated at either the active site or the ATP-binding site of the SEL-5 kinase domain. They show that either SEL-5 mutant form successfully rescues the QL.d and EXC defects seen in sel-5 mutants (Fig. 3), suggesting that SEL-5 catalytic activity is unnecessary.

(3) The authors have produced an elegant GFP knock-in allele of the sel-5 gene, allowing analysis of expression and localization in living animals (Fig. 2).

(4) The authors make use of genetic interactions with Wnt signaling mutants to show that SEL-5 acts in a role that promotes Wnt signaling for the QL.d cell (Fig. 1) and counteracts Wnt signaling for the EXC (Fig. 5).

Weaknesses<br /> (1) Some changes to statistical analyses are needed in this study.

Fig. 1B, 1D, 2A, 3E, and 3F report the QL.d phenotype as a percentage of animals scored that were defective in migration. The methods make it clear this data is categorical rather than quantitative. Therefore, a t-test or any test designed for quantitative data is not appropriate. I suggest that the authors should investigate using a chi-squared or Fisher's exact test.

For the reasons mentioned above, the calculation of standard deviation (as shown in error bars) is also not appropriate for Fig. 1B, 1D, 2A, 3E, and 3F. Of course, it is excellent that the authors scored multiple trials. For experiments with mutants, I suggest the authors might combine these trials or show separate results of each trial. For experiments using RNAi (Fig. 1B), each trial should be plotted separately because RNAi effectiveness can vary. If there is not enough space to show multiple trials, then I would ask that a representative trial be shown in the main figure and additional trials in a supplement.

In Fig. 1, 2, 3, and 5, it is not specified whether/how p-values were adjusted for multiple tests.

(2) I felt the author's interpretation of the sel-5 mutant phenotypes in EXC, and the genetic interactions with Wnt signaling mutants, might be improved. The authors show convincing data that the sel-5 mutants display a shortened EXC outgrowth phenotype. Conversely, mutants with reduced Wnt signaling, such as the lin-17 or lin-44 mutants, displayed lengthened EXC outgrowth. The authors show that in double mutants, loss of sel-5 partially suppressed the EXC overgrowth defects of lin-17 or lin-44 mutants (Fig. 5). In my opinion, this data is consistent with a model where SEL-5 acts to inhibit Wnt signaling in EXC. An inhibitory role in a Wnt-receiving cell would be consistent with the known activity for human AAK1 in promoting negative feedback and endocytosis of LPR6. Interestingly, the authors mention in their discussion that a mutant of plr-1, which acts in the internalization of Frizzled receptors, has a shortened EXC phenotype similar to that of sel-5 mutants. These observations all seem consistent with an inhibitory role, yet the authors do not state this as their conclusion. A clarification of their interpretation is needed.

Impact/significance<br /> (1) Among researchers using C. elegans, this study provides a foundation for further investigation of the role of endocytosis, SEL-5, and the retromer, in Wnt trafficking. It is particularly useful that the authors define two different phenotypes that arise from Wnt-producing and Wnt-receiving cells.

(2) Among a broader community of cell biologists and biochemists, this study will be of interest in its finding that SEL-5/AAK1 kinase catalytic activity is unnecessary for the regulation of Wnt signaling.

eLife assessment

This important study advances our understanding of the molecular mechanism underlying salt stress-induced inhibition of seed germination and seedling growth. The evidence supporting the conclusions is convincing, with rigorous genetic, physiological, and metabolic analyses. This paper will be of interest to plant stress biologists and crop breeders.

Reviewer #1 (Public Review):

Salt-inhibited germination and growth in Arabidopsis and other plant species. Here the authors demonstrated that part of that inhibitory effect is caused by the arginine-derived urea hydrolysis, a novel mechanism. They also postulated that urea transport is involved in germination inhibition, but they do not link urea transport from cotyledons to pH changes in roots. At last, they generalized the mechanisms to other glycophytic crops and halophytic plants, but the salt concentration used is the same for the four groups, which are supposed to have very different salt tolerance ranges, questioning the validity of this generalization.<br /> Overall, the authors have provided well-organized genetic and pharmacological evidence to support most of their conclusions.

Reviewer #2 (Public Review):

Urea is widely utilized in agriculture. In this study, the authors the mechanism underlying the adverse impact of urea on seed germination and seedling growth under salt stress conditions. The results show that salt stress induces a pronounced hydrolysis of urea, resulting in an elevation of cytoplasmic pH and subsequent inhibition of seed germination. These findings challenge the previous notion that ammonium accumulation is the primary cause of salt-induced inhibition of germination, thereby offering novel insights into this process.

The authors have provided well-organized genetic or biochemical evidence to support most of their conclusions.

Reviewer #3 (Public Review):

This work submitted by Bu et al. investigated mechanisms of how salt stress-induced arginine catabolism, which is catalyzed by arginase and urease, inhibits seed germination and seedling growth in Arabidopsis using a combination of genetic, biochemical, and live-cell imaging approaches. Their results showed that the two steps for the turnover of arginine into ammonia and the transport of urea from the cotyledon to the root are required for the salt-induced inhibition of seed germination (SISG). Further analysis showed that the cellular accumulation of the end product ammonia is not associated with SISG, but it is the cytoplasmic alkaline stress that primarily causes SISG. Interestingly, they found that the mechanism underlying SISG is conserved in other plant species. In general, this work will be valuable for plant biologists to deeply dissect the complex mechanism that controls salt stress-induced inhibition of plant growth and development in the future.

The conclusions derived from this work are well supported by the data, but some aspects of data analysis need to be clarified and extended.

(1) Inhibition of arginine hydrolysis by enzyme inhibitors (NOHA for arginase and PPD for urease) significantly improved seed germination and seedling growth (Figure 2). It seems that the suppressive effect of NOHA against the salt-induced inhibition of seedling growth is dose-dependent (Figure 2b). Whether NOHA effect on SISG is also dose-dependent and application of a certain level of NOHA can fully rescue the phenotype of SISG remains to be answered. The answers may help to explain the genetic data shown in Figure 3c, where either single (argah1 and argah2) or double (argah1/argah2) mutants partially rescued the phenotype of SISG. However, arginase activity, particularly in argah1 and argah2, is not closely correlated to the phenotype shown in Figure 3c and 3d.

(2) The data shown in Figure 4b and 4e were not fully consistent. The percentage of seed germination rate was about 70% when treated with the highest concentration (7.5 μM) of PPD, but was less than 40% for the aturease mutant.

(3) Cellular pH values detected at the seed germination stage were not convincing. In the text, they did not describe the results showing that the cytoplasmic pH values in hypocotyl and cotyledon cells were alkaline and not affected by NaCl treatment, and PPD treatment only restored the alkaline cytoplasmic pH to that of the control (Figure 7b). This raises two questions: is it true that cytoplasmic pH values are different between root and cotyledon/hypocotyl cells under normal growth conditions? and does PPD treatment alter the cytoplasmic pH only in roots?

eLife assessment

This study presents a useful finding on a virally encoded immune-evasin which differentially inhibits antigen presentation by cellular protein complexes called Major histocompatibility complex (MHC) class I, thereby diminishing the activation of cytotoxic T cells. The evidence supporting the claims of the authors is solid, although the addition of more mechanistic insights would strengthen the study. The work will be of interest to virologists and immunologists working on the adaptive immune response to herpesviral infection. Some conclusions would require additional experimental support.

Reviewer #1 (Public Review):

HMCV encodes various immunoevasins to inhibit being presented by MHC class I molecules to the cytotoxic cells of the immune system. Here, the authors studied the role and specificity of US10, a relatively uncharacterized immunoevasin from HCMV. They found that US10 differentially affects antigen presentation by different MHC class I allotypes. HLA-A and certain HLA-B and C alleles (so-called "tapasin-independent") were unaffected, while other HLA-B and C alleles (so-called "tapasin-dependent") as well as HLA-G were negatively affected. US10 can bind to different MHC class I allotypes, which inhibits their incorporation into peptide loading complex and slowers maturation. By comparing US10 to the other well-studied immunoevasins from HCMV, US2, US3, and US11, the authors demonstrated only partial overlap between them suggesting the cumulative action of immunoevasins in inhibiting MHC class I antigen presentation of HMCV epitopes. This work contributes to our understanding of the complex immune evasion mechanism by HCMV.

The strengths include using a broad use of available techniques, including overexpression of US10 and US10 siRNA in the infection context that allowed comparison of its net and cumulative effects. Bioinformatic analysis of US10 and US11 to describe how transcription and expression of these two gene products contribute to the control of immunoevasion by HCMV. The conclusions are mostly supported by the experiments.

Reviewer #2 (Public Review):

The manuscript entitled " Multimodal HLA-I genotypes regulation by human cytomegalovirus US10 and resulting surface patterning" by Gerke et al describes the biochemical analysis of US10-mediated down regulation of HLA-I molecules. The authors systemically examine the surface expression of different HLA-I alleles in cells expressing US10 and interactions of US10 with HLA-I and antigen presentation machinery. Further, studies examined genotypic and allotypic differences during expression of US10/US11 transcripts suggest a different allelic class I downregulation. In general, the authors have included data supporting the major claims. Yet, the conclusions and findings of the study only marginally advance the overall understanding of HCMV viral evasion and the mechanism of US10 function.

Strengths:<br /> The studies are well characterized and the studies utilize diverse HLA-I and HCMV viral molecules. The biochemistry is excellent and is of high quality. Importantly, the study describes HLA-I allelic specific HCMV down regulation at the cell surface and molecular levels.

Weaknesses:<br /> (1) The authors use over expressive language such as "strong binding" that does not have a quantitative value and it is relative to the specific assay with only small differences among the factors.<br /> (2) The US10 binding to the HLA-I did not correlate with class I surface levels suggesting that binding to the APC machinery (Figure 1); hence, why does the binding of US10 to the APC define its mechanism of action.<br /> (3) The innovative and significant aspects of the study are limited. The study does not delineate the US10 mechanism of action or show data in which US10-mediated MHC class I down regulation impacts adaptive or innate immune function.

Reviewer #3 (Public Review):

Correlation of the HLA-B effects with previously demonstrated allelic differences in dependence on the peptide loading complex (PLC) component chaperone/editor tapasin and demonstration that US10 does not bind the PLC reflect on possible mechanisms of US10 function. Thus, this paper adds new information that may be integrated into evolving models of the steps of MHC-I dependent antigen presentation and how viruses counter immune recognition for their own benefit. Clearer focus on the proposed models for the function of US10 and its mechanism--i.e. what experiments address the mechanism and what additional finding might clarify the mechanism would be helpful.

Author response:

Reviewer #1 (Public Review):

Summary:

[...] This study is a fundamental step towards our better understanding of the mechanisms underlying light effects on cognition and consequently optimising lighting standards.

Strengths:

While it is still impossible to distinguish individual hypothalamic nuclei, even with the high-resolution fMRI, the authors split the hypothalamus into five areas encompassing five groups of hypothalamic nuclei. This allowed them to reveal that different parts of the hypothalamus respond differently to an increase in illuminance. They found that higher illuminance increased the activity of the posterior part of the hypothalamus encompassing the MB and parts of the LH and TMN, while decreasing the activity of the anterior parts encompassing the SCN and another part of TMN. These findings are somewhat in line with studies in animals. It was shown that parts of the hypothalamus such as SCN, LH, and PVN receive direct retinal input in particular from ipRGCs. Also, acute chemogenetic activation of ipRGCs was shown to induce activation of LH and also increased arousal in mice.

Weaknesses:

While the light characteristics are well documented and EDI calculated for all of the photoreceptors, it is not very clear why these irradiances and spectra were chosen. It would be helpful if the authors explained the logic behind the four chosen light conditions tested. Also, the lights chosen have cone-opic EDI values in a high correlation with the melanopic EDI, therefore we can't distinguish if the effects seen here are driven by melanopsin and/or other photoreceptors. In order to provide a more mechanistic insight into the light-driven effects on cognition ideally one would use a silent substitution approach to distinguish between different photoreceptors. This may be something to consider when designing the follow-up studies.

We thank the reviewer for acknowledging the quality and interest of our work and agree with the weaknesses they pointed out.

Blue-enriched light illuminances were set according to the technical characteristics of the light source and to keep the overall photon flux similar to prior 3T MRI studies of our team (between ~1012 and 1014 ph/cm²/s) (Vandewalle et al. 2010 PNAS, Vandewalle et al. 2011 Biol. Psy.). The orange light was introduced as a control visual stimulation for potential secondary whole-brain analyses. It’s photopic illuminance should ideally have been set similar to the low illuminance blue-enriched light condition, but it was not the case. For the present region of interest analyses, we discarded colour differences between the light conditions and only considered illuminance as indexed by mel EDI lux. This constitutes indeed a limitation of our study as it does not allow attributing the findings to a particular photoreceptor class.

The revised version of the manuscript will include a better explanation as to the choice of illuminances and spectra. The discussion will make clear that these choices limit the interpretation about the photoreceptors involved. The discussion will also point out that silent substitution could be used in the future to resolve such question.

Reviewer #2 (Public Review):

[...] By shedding light on these complex interactions, this research endeavors to contribute to the foundational knowledge necessary for developing innovative therapeutic strategies aimed at enhancing cognitive function through environmental modulation.

Strengths:

(1) Considerable Sample Size and Detailed Analysis: The study leverages a robust sample size and conducts a thorough analysis of hypothalamic dynamics, which enhances the reliability and depth of the findings.

(2) Use of High-Resolution Imaging: Utilizing 7 Tesla fMRI to analyze brain activity during cognitive tasks offers high-resolution insights into the differential effects of illuminance on hypothalamic activity, showcasing the methodological rigor of the study.

(3) Novel Insights into Illuminance Effects: The manuscript reveals new understandings of how different regions of the hypothalamus respond to varying illuminance levels, contributing valuable knowledge to the field.

(4) Exploration of Potential Therapeutic Applications: Discussing the potential therapeutic applications of light modulation based on the findings suggests practical implications and future research directions.

Weaknesses:

(1) Foundation for Claims about Orexin and Histamine Systems: The manuscript needs to provide a clearer theoretical or empirical foundation for claims regarding the impact of light on the orexin and histamine systems in the abstract.

(2) Inclusion of Cortical Correlates: While focused on the hypothalamus, the manuscript may benefit from discussing the role of cortical activation in cognitive performance, suggesting an opportunity to expand the scope of the manuscript.

(3) Details of Light Exposure Control: More detailed information about how light exposure was controlled and standardized is needed to ensure the replicability and validity of the experimental conditions.

(4) Rationale Behind Different Exposure Protocols: To clarify methodological choices, the manuscript should include more in-depth reasoning behind using different protocols of light exposure for executive and emotional tasks.

We thank the reviewer for recognising the interest and strength of our study. We agree that corrections and clarifications to the text were needed. We will address the weaknesses they pointed out as follows:

(1) As detailed in the discussion, we do believe orexin and histamine are excellent candidates for mediating the results we report. As also pointing out, however, we are in no position to know which neurons, nuclei, neurotransmitter and neuromodulator underlie the results. We will therefore remove the last sentence of the abstract as we agree our final statement in the abstract was too strong. We will carefully reconsider the discussion to avoid such overstatements.

(2) We are unsure at this stage how to address the comment of the reviewer without considerably lengthening the manuscript with statements which can only be putative. Hypothalamus nuclei are connected to multiple cortical (and subcortical) structures. The relevance of these projections will vary with the cognitive task considered. In addition, we have not yet considered the cortex in our analyses such that truly integrating cortical structures appears premature. We will nevertheless refer to the general statement that subcortical structures (and particularly those receiving direct retinal projections) are likely to receive light illuminance signal first before passing on the light modulation to the cortical regions involved in the ongoing cognitive process.

(3) Illuminance and spectra could not be directly measured within the MRI scanner due to the ferromagnetic nature of measurement systems. The MR coil and the associated optic fibre stand, together with the entire lighting system were therefore placed outside of the MR room to reproduce the experimental conditions of the in a completely dark room. A sensor was placed 2 cm away from the mirror of the coil (mounted at eye level), i.e. where the eye of the first author of the paper would be positioned, to measure illuminance and spectra. The procedure was repeated 4 times for illuminance and twice for spectra and measurements were averaged. This procedure does not take into account inter-individual variation in head size and orbit shape such that the reported illuminance levels may have varied slightly across subjects. The relative differences between illuminance are very unlikely to vary substantially across participants such that statistics consisting of tests for the impact of relative differences in illuminance were not affected. We will report these methodological details in the supplementary material file associated to the paper.

(4) The comment is similar to the issue raised by reviewer 1 (and reviewer 3) so we refer to the response provided to reviewer 1 to address the final comment of reviewer 2.

Reviewer #3 (Public Review):

[...] The authors find evidence in support of a posterior-to-anterior gradient of increased blood flow in the hypothalamus during task performance that they later relate to performance on two different tasks. The results provide an enticing link between light levels, hypothalamic activity, and cognitive/affective function, however, clarification of some methodological choices will help to improve confidence in the findings.

Strengths:

The authors' focus on the hypothalamus and its relationship to light intensity is an important and understudied question in neuroscience.

Weaknesses:

I found it challenging to relate the authors' hypotheses, which I found to be quite compelling, to the apparatus used to test the hypotheses - namely, the use of orange light vs. different light intensities; and the specific choice of the executive and emotional tasks, which differed in key features (e.g., block-related vs. event-related designs) that were orthogonal to the psychological constructs being challenged in each task.

Given the small size of the hypothalamus and the irregular size of the hypothalamic parcels, I wondered whether a more data-driven examination of the hypothalamic time series would have provided a more parsimonious test of their hypothesis.

We thank the reviewer for acknowledging the originality and interest of our study. We agree that some methodological choices needed more explanations. We will address the weaknesses they pointed out as follows:

The first comment questions the choices of the light conditions and of the tasks. Regarding light conditions, since reviewer 1 (and reviewer 2) raised a similar issue, we refer to the response provided to reviewer 1. We agree that many different tasks could have been used to test our hypotheses. Prior work of our team showed that the n-back task and emotional task we used were successful probes to demonstrate that light illuminance modulates cognitive activity, including within subcortical structures (though resolution did not allow precise isolation of nuclei or subparts). When taking the step of ultra-high field imaging we therefore opted for these tasks as our goal was to show that illuminance affects subcortical brain activity across cognitive domains in general and we were not interested in tasks that would test specific aspects of these domains. The fact that one task is event-related while the other consists of a block design adds, in our view, to the robustness of our finding that a similar anterior-posterior gradient of activity modulation by illuminance is present in hypothalamus. We will update the discussion to highlight this aspect.

As mentioned in the text, the protocol also included an auditory attentional task that could have further broadened the potential generalisability of our findings, but it was not part of the analyses as it could only include 2 illuminance levels due to time constrains.

We agree that a data driven approach could have constituted an alternative means to tests our hypothesis. We opted for an approach that we mastered best while still allowing to conclusively test for regional differences in activity across the hypothalamus. Examination of time series of the very same data we used will mainly confirm the results of our analyses – an anterior-posterior gradient in the impact of illuminance - and may yield slight differences in the limits of the subparts of the hypothalamus undergoing decreased or increased activity with increasing illuminance. While the suggested approach may have been envisaged if we had been facing negative results (i.e. no differences between subparts, potentially because subparts would not correspond functional differences in response to illuminance change), it would now constitute a circular confirmation of our main findings (i.e. using the same data). While we truly appreciate the suggestion, we do not consider that it would constitute a more parsimonious test of our hypothesis now that we successfully applied GLM/parcellation and GLMM approaches.

Reviewer #2 (Public Review):

Summary:

The interplay between environmental factors and cognitive performance has been a focal point of neuroscientific research, with illuminance emerging as a significant variable of interest. The hypothalamus, a brain region integral to regulating circadian rhythms, sleep, and alertness, has been posited to mediate the effects of light exposure on cognitive functions. Previous studies have illuminated the role of the hypothalamus in orchestrating bodily responses to light, implicating specific neural pathways such as the orexin and histamine systems, which are crucial for maintaining wakefulness and processing environmental cues. Despite advancements in our understanding, the specific mechanisms through which varying levels of light exposure influence hypothalamic activity and, in turn, cognitive performance, remain inadequately explored. This gap in knowledge underscores the need for high-resolution investigations that can dissect the nuanced impacts of illuminance on different hypothalamic regions. Utilizing state-of-the-art 7 Tesla functional magnetic resonance imaging (fMRI), the present study aims to elucidate the differential effects of light on the hypothalamic dynamics and establish a link between regional hypothalamic activity and cognitive outcomes in healthy young adults. By shedding light on these complex interactions, this research endeavors to contribute to the foundational knowledge necessary for developing innovative therapeutic strategies aimed at enhancing cognitive function through environmental modulation.

Strengths:

(1) Considerable Sample Size and Detailed Analysis:<br /> The study leverages a robust sample size and conducts a thorough analysis of hypothalamic dynamics, which enhances the reliability and depth of the findings.

(2) Use of High-Resolution Imaging:<br /> Utilizing 7 Tesla fMRI to analyze brain activity during cognitive tasks offers high-resolution insights into the differential effects of illuminance on hypothalamic activity, showcasing the methodological rigor of the study.

(3) Novel Insights into Illuminance Effects:<br /> The manuscript reveals new understandings of how different regions of the hypothalamus respond to varying illuminance levels, contributing valuable knowledge to the field.

(4) Exploration of Potential Therapeutic Applications:<br /> Discussing the potential therapeutic applications of light modulation based on the findings suggests practical implications and future research directions.

Weaknesses:

(1) Foundation for Claims about Orexin and Histamine Systems:<br /> The manuscript needs to provide a clearer theoretical or empirical foundation for claims regarding the impact of light on the orexin and histamine systems in the abstract.

(2) Inclusion of Cortical Correlates:<br /> While focused on the hypothalamus, the manuscript may benefit from discussing the role of cortical activation in cognitive performance, suggesting an opportunity to expand the scope of the manuscript.

(3) Details of Light Exposure Control:<br /> More detailed information about how light exposure was controlled and standardized is needed to ensure the replicability and validity of the experimental conditions.

(4) Rationale Behind Different Exposure Protocols:<br /> To clarify methodological choices, the manuscript should include more in-depth reasoning behind using different protocols of light exposure for executive and emotional tasks.

eLife assessment

This fundamental work describes the complex interplay between light exposure, hypothalamic activity, and cognitive function. The evidence supporting the conclusion is compelling with potential therapeutic applications of light modulation. The work will be of broad interest to basic and clinical neuroscientists.

Reviewer #1 (Public Review):

Summary:

Campbell et al investigated the effects of light on the human brain, in particular the subcortical part of the hypothalamus during auditory cognitive tasks. The mechanisms and neuronal circuits underlying light effects in non-image forming responses are so far mostly studied in rodents but are not easily translated in humans. Therefore, this is a fundamental study aiming to establish the impact light illuminance has on the subcortical structures using the high-resolution 7T fMRI. The authors found that parts of the hypothalamus are differently responding to illuminance. In particular, they found that the activity of the posterior hypothalamus increases while the activity of the anterior and ventral parts of the hypothalamus decreases under high illuminance. The authors also report that the performance of the 2-back executive task was significantly better in higher illuminance conditions. However, it seems that the activity of the posterior hypothalamus subpart is negatively related to the performance of the executive task, implying that it is unlikely that this part of the hypothalamus is directly involved in the positive impact of light on performance observed. Interestingly, the activity of the posterior hypothalamus was, however, associated with an increased behavioural response to emotional stimuli. This suggests that the role of this posterior part of the hypothalamus is not as simple regarding light effects on cognitive and emotional responses. This study is a fundamental step towards our better understanding of the mechanisms underlying light effects on cognition and consequently optimising lighting standards.

Strengths:

While it is still impossible to distinguish individual hypothalamic nuclei, even with the high-resolution fMRI, the authors split the hypothalamus into five areas encompassing five groups of hypothalamic nuclei. This allowed them to reveal that different parts of the hypothalamus respond differently to an increase in illuminance. They found that higher illuminance increased the activity of the posterior part of the hypothalamus encompassing the MB and parts of the LH and TMN, while decreasing the activity of the anterior parts encompassing the SCN and another part of TMN. These findings are somewhat in line with studies in animals. It was shown that parts of the hypothalamus such as SCN, LH, and PVN receive direct retinal input in particular from ipRGCs. Also, acute chemogenetic activation of ipRGCs was shown to induce activation of LH and also increased arousal in mice.

Weaknesses:

While the light characteristics are well documented and EDI calculated for all of the photoreceptors, it is not very clear why these irradiances and spectra were chosen. It would be helpful if the authors explained the logic behind the four chosen light conditions tested. Also, the lights chosen have cone-opic EDI values in a high correlation with the melanopic EDI, therefore we can't distinguish if the effects seen here are driven by melanopsin and/or other photoreceptors. In order to provide a more mechanistic insight into the light-driven effects on cognition ideally one would use a silent substitution approach to distinguish between different photoreceptors. This may be something to consider when designing the follow-up studies.

Reviewer #3 (Public Review):

Summary:

Campbell and colleagues use a combination of high-resolution fMRI, cognitive tasks, and different intensities of light illumination to test the hypothesis that the intensity of illumination differentially impacts hypothalamic substructures that, in turn, promote alterations in arousal that affect cognitive and affective performance. The authors find evidence in support of a posterior-to-anterior gradient of increased blood flow in the hypothalamus during task performance that they later relate to performance on two different tasks. The results provide an enticing link between light levels, hypothalamic activity, and cognitive/affective function, however, clarification of some methodological choices will help to improve confidence in the findings.

Strengths:

* The authors' focus on the hypothalamus and its relationship to light intensity is an important and understudied question in neuroscience.

Weaknesses:

* I found it challenging to relate the authors' hypotheses, which I found to be quite compelling, to the apparatus used to test the hypotheses - namely, the use of orange light vs. different light intensities; and the specific choice of the executive and emotional tasks, which differed in key features (e.g., block-related vs. event-related designs) that were orthogonal to the psychological constructs being challenged in each task.

* Given the small size of the hypothalamus and the irregular size of the hypothalamic parcels, I wondered whether a more data-driven examination of the hypothalamic time series would have provided a more parsimonious test of their hypothesis.

Reviewer #3 (Public Review):

Summary:

In this study, Han and co-authors showed that implantation of Pik3ca deficient KPC cells (aKO) induced clonal expansion of CD8 T cells in the tumor microenvironment. Using aKO cells, they conducted an in vivo genome-wide gene-deletion screen, which showed that deletion of propionyl-CoA carboxylase subunit B gene (Pccb) in αKO cells (p-aKO) leads to immune evasion and tumor progression. Eventually, mice injected with p-aKO but not aKO succumbed to their tumors. Similar to the parental aKO cell line, p-aKO tumors were still infiltrated with clonally expanded CD8+ and CD4+ T cells, as shown by the IHC. Further analyses showed that T cells infiltrating p-aKO tumors expressed high levels of exhaustion markers (PD-1, CTLA-4, TIM3, and TIGIT). Furthermore, PD-1 signaling blockade using PD-1 mAb or genetic depletion of PD-1 reactivated the infiltrated T cells, controlling tumor progression and improving the overall mice survival. Thus, the authors concluded in the abstract that "Pccb can modulate the activity of cytotoxic T cells infiltrating some pancreatic cancers." Although the data clearly showed that the loss of Pccb facilitated the immune evasion of pancreatic cancer cells, there is no clear evidence provided that Pccb deletion can actually modulate the activity of CD8 T cells. One may argue that the deletion of Pccb reduces the immunogenicity of the p-aKO cancer cells, making them less susceptible to killing by normally functional CD8+ T cells.

Strengths:

In vivo, Crisper-Cas-9 screen using tumor cell lines.

Identify a gene that could reduce the immunogenicity of cancer cells.

Weaknesses:

The IHC technique that was used to stain and characterize the exhaustion status of the tumor-infiltrating T cells.

eLife assessment

The significance of the findings is valuable, with implications for immunotherapy design in pancreatic ductal adenocarcinoma. The evidence was considered incomplete and partially supportive of the major claims.

Reviewer #1 (Public Review):

Summary:

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease that does not respond to immunotherapy. This work represents an extension of the authors' prior observation that PI3Ka deletion in an orthotopic KPC pancreatic tumor model confers susceptibility to immune-mediated elimination. The authors' major claims in the present manuscript are as follows:

(1) PI3Ka (Pik3ca) knockout in KPC pancreatic tumor cells induces clonal T cell expansion.

(2) Genome-wide LOF screen in aKPC cells to identify tumor-intrinsic determinants of PI3Ka-KO-enhanced T cell response identified Pccb.

(3) When Pccb is knocked out in the context of Pi3ka knockout KPC, anti-tumor T cell response is reduced as measured by<br /> a. Increased tumor progression<br /> b. Decreased survival<br /> c. T cells are still clonally expanded but less functional

(4) ICB is able to "reactivate" clonally expanded T cells.

(5) Conclusion: Pccb modulates the activity of T cells in PDAC.

Overall, the experiments were appropriately executed and technically sound, albeit underpowered for single-cell analyses. Upon careful consideration of the data, the biggest weakness of the paper is the authors' interpretations of results, particularly for claims 1 and 4 (see below for details). Much of the data is correlative and does not delve into causation, leaving this reviewer wishing for experiments that would clearly demonstrate that Pccb in tumor cells directly impacts T cell anti-tumor activity.

Strengths:

(1) Tumor intrinsic determinants of intratumoral T cell infiltration in PDAC are less commonly evaluated as combination therapies for ICB. This is a point of conceptual innovation and importance.

(2) A sensitized CRISPR screen to identify mutations that rescue KPC/PI3Ka-KO tumors from immune-mediated killing is an elegant method to better understand the molecular mechanisms contributing to KPC immunosurveillance. Further, one screen candidate (Pccb) was experimentally validated.

(3) Single-cell clonotype analyses hold promise for identifying tumor-reactive T cells (though authors never demonstrated that specific clones were tumor antigen specific).

Weaknesses:

(1) "Clonal expansion of cytotoxic T cells infiltrating the pancreatic αKO tumors"<br /> a. Only two tumor-bearing hosts were evaluated by single-cell TCR sequencing, thus limiting conclusions that may be drawn regarding repertoire diversity and expansion.<br /> b. High abundance clones in the TME do not necessarily have tumor specificity, nor are they necessarily clonally expanded. They may be clones which are tissue-resident or highly chemokine-responsive and accumulate in larger numbers independent of clonal expansion. Please consider softening language to clonal enrichment or refer to clone size as clonal abundance throughout the paper.<br /> c. The whole story would be greatly strengthened by cytotoxicity assays of abundant TCR clones to show tumor antigen specificity.

(2) "A genome-wide CRISPR gene-deletion screen to identify molecules contributing to Pik3ca-mediated pancreatic tumor immune evasion"<br /> a. CRISPR mutagenesis yielded outgrowth of only 2/8 tumors. A more complete screen with an increased total number of tumors would yield much stronger gene candidates with better statistical power. It is unsurprising that candidates were observed in only one of the two tumors. Nevertheless, the authors moved forward successfully with Pccb.

(3) T cells infiltrate p-αKO tumors with increased expression of immune checkpoints<br /> a. In Figure 4D, cell counts are not normalized to totalCD8+ T cell counts making it difficult to directly compare aKO to p-aKO tumors. Based on quantifications from Figure 4D, I suspect normalization will strengthen the conclusion that CD8+ infiltrate is more exhausted in p-aKO tumors.<br /> b. Flow cytometric analysis to further characterize the myeloid compartment is incomplete (single replicate) and does not strengthen the argument that p-aKO TME is more immunosuppressive.<br /> c. It could, however, strengthen the argument that TIL has less anti-tumor potential if effector molecule expression in CD8+ infiltrating cells were quantified.

(4) Inhibition of PD1/PD-L1 checkpoint leads to elimination of most p-αKO tumors<br /> a. It is reasonable to conclude that p-aKO tumors are responsive to immune checkpoint blockade. However, there is no data presented to support the statement that checkpoint blockade reactivates an existing anti-tumor CD8+ T cell response and does not instead induce a de novo response.<br /> b. The discussion of these data implies that anti-PD-1 would not improve aKO tumor control, but these data are not included. As such, it is difficult to compare the therapeutic response in aKO versus p-aKO. Further, these data are at best an indirect comparison of the T cell responsiveness against tumor, as the only direct comparison is infiltrating cell count in Figure 4 and there are no public TCR clones with confirmed anti-tumor specificity to follow in the aKO versus p-aKO response.

Reviewer #2 (Public Review):

Summary:

Pancreatic ductal adenocarcinoma is generally considered a "cold" tumor type with little T cell infiltration. This group demonstrated previously that deletion of the PIK3CA isoform of PI3K in the orthotopic pancreatic ductal adenocarcinoma KPC mouse tumor model led to the elimination of tumors by T cells. Here they performed a genome-wide gene-deletion screen in this tumor using CRISPR to determine what was required for this T cell-mediated infiltration and tumor rejection. Deletion of Pccb in the tumors, which encodes propionyl-CoA carboxylase subunit B, allowed for the outgrowth of the PIK3CA-deleted KPC tumors. This was confirmed with the specific deletion of Pccb in the tumor cells. Demonstrating a likely role in tumor progression in human patients as well, high expression of PCCB in pancreatic ductal adenocarcinoma correlated with lower patient survival. T cells still infiltrated these tumors, but had much higher expression of exhaustion markers. Blockade of PD-1 signaling allowed for the rejection of these tumors. While these are intriguing data demonstrating that loss of PCCB by pancreatic ductal adenocarcinoma is a mechanism to escape T cell immunity, the mechanism by which this occurs is not determined. In addition, there are a few issues that suggest the conclusions of the manuscript should be tempered.

Strengths:

In vivo analysis of tumor CRISPR deletion screen.

The study describes a possible novel mechanism by which a tumor maintains a "cold" microenvironment.

Weaknesses:

(1) A major issue is that it seems these data are based on the use of a single tumor cell clone with PIK3CA deleted. Therefore, there could be other changes in this clone in addition to the deletion of PIK3CA that could contribute to the phenotype.

(2) The conclusion that the change in the PCCB-deficient tumor cell line is unrelated to mitochondrial metabolic changes may be incorrect based on the data provided. While it is true that in the experiments performed, there was no statistically significant change in the oxygen consumption rate or metabolite levels, this could be due to experimental error. There is a trend in the OCR being higher in the PCCB-deficient cells, although due to a high standard deviation, the change is not statistically significant. There is also a trend for there being more aKG in this cell line, but because there were only 3 samples per cell line, there is no statistically significant difference.

(3) More data are required to make the authors' conclusion that there are myeloid changes in the PCCB-deficient tumor cells. There is only flow data from shown from one tumor of each type.

(4) The previous published study demonstrated increased MHC and CD80 expression in the PIK3CA-deficient tumors and these differences were suggested to be the reason the tumors were rejected. However, no data concerning the levels of these proteins were provided in the current manuscript.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors delineate the crucial role of the SIRT2-ACSS2 axis in ACSS2 degradation. They demonstrate that SIRT2 acts as an ACSS2 deacetylase specifically under nutrient stress conditions, notably during amino acid deficiency. The SIRT2-mediated deacetylation of ACSS2 at K271 consequently triggers its proteasomal degradation. Additionally, they illustrate that acetylation of ACSS2 at K271 enhances ACSS2 protein levels, thereby promoting De Novo lipogenesis.

Strengths:

The findings presented in this manuscript are clearly interesting.

Weaknesses:

Further support is required for the model put forward by the authors.

eLife assessment

This useful study describes a role for acetylation in controlling the stability of acetyl-CoA synthetase 2, which converts acetate to acetyl-CoA for de novo lipid synthesis. While some aspects of the study are solid, the overall evidence supporting these findings is incomplete. Including additional critical controls for protein levels and stability and extending the findings to additional cell lines will strengthen the study. This work will be of interest to researchers studying lipid metabolism and related diseases.

Reviewer #2 (Public Review):

Summary:

Karim et al investigated the regulation of ACSS2 by SIRT2. The authors identified a previously undescribed acetylation that they then show is important for the regulation and stability of ACSS2 in cells. The authors show that ACSS2 ubiquitination and degradation by the proteasome is regulated by SIRT2-mediated deacetylation of ACSS2 and that stabilizing ACSS2 by blocking SIRT2 can alter lipid accumulation in adipocytes.

Strengths:

Identification of a novel acetylation site on ACSS2 that regulates its protein stability and that has consequences on its activity in adipocytes. Multiple standard approaches were used to manipulate the expression and function of SIRT2 and ACSS2 (i.e., overexpression, knockdown, inhibitors).

Weaknesses:

The authors do not show direct deacetylation of ACSS2 by SIRT2 in an in vitro biochemical assay.

It would have been nice to have included a bona-fide SIRT2 target as a control throughout the study.

Throughout the manuscript, normalizing the data to 1 and then comparing the fold-change using a t-test is not the best statistical approach in that situation since every normalized value for control is 1 with zero standard deviation. The authors should consider an alternative statistical approach.

Though not necessary, using 13C-acetate or D3-acetate tracing would be better for understanding the impact of acetylation on the activity of ACSS2 and its impact on lipogenesis.

Did the authors also consider investigating SIRT1 in their assays? SIRT1 activates ACSS2 while SIRT2 leads to degradation of ACSS2. They should at least discuss these seemingly opposing roles of SIRT1 and SIRT2 in the regulation of ACSS2 and acetate metabolism in more depth, particularly as it concerns situations (i.e., diseases, pathologies) where either SIRT1, SIRT2, or both sirtuins, are active. This would enhance the significance of the findings to the broader research community.

In Figure 3, the authors should consider immunoblotting for endogenous ACSS2 throughout the differentiation and lipogenesis study since the total ACSS2 levels is the crucial aspect to affecting acetate-dependent promotion of lipogenesis in adipocytes, and to confirm TM-dependent stabilization of ACSS2 in that assay.

Do the authors have any data proving the K271 mutants of ACSS2 are still functional? Or that K271 ACSS2 protein is folded correctly?

Reviewer #3 (Public Review):

Summary:

The manuscript shows SIRT2 can regulate acetylation of ACSS2 at residue 271, acetylation of 271 protects ACSS2 from proteasomal degradation in a SIRT2-dependent manner. Lastly, authors show that ACSS2 acetylation at K271 promotes lipid accumulation.

Strengths:

The author provides solid data showing ACSS2 acetylation can be regulated by targeting SIRT2 and that SIRT2 regulates ACSS2 ubiquitination. They identify K271 as a site of acetylation and show this is a site when mutated alters SIRT2-mediated ubiquitination.

Weaknesses:

However, data for this manuscript seems preliminary as nearly all data is performed in one cell line, some of the conclusions are not well supported by data and the overall role of ACSS2 K271 acetylation is not well characterized.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, Bell et al. provide an exhaustive and clear description of the diversity of a new class of predicted type IV restriction systems that the authors denote as CoCoNuTs, for their characteristic presence of coiled-coil segments and nuclease tandems. Along with a comprehensive analysis that includes phylogenetics, protein structure prediction, extensive protein domain annotations, and an in-depth investigation of encoding genomic contexts, they also provide detailed hypotheses about the biological activity and molecular functions of the members of this class of predicted systems. This work is highly relevant, it underscores the wide diversity of defence systems that are used by prokaryotes and demonstrates that there are still many systems to be discovered. The work is sound and backed-up by a clear and reasonable bioinformatics approach. I do not have any major issues with the manuscript, but only some minor comments.

Strengths:

The analysis provided by the authors is extensive and covers the three most important aspects that can be covered computationally when analysing a new family/superfamily: phylogenetics, genomic context analysis, and protein-structure-based domain content annotation. With this, one can directly have an idea about the superfamily of the predicted system and infer their biological role. The bioinformatics approach is sound and makes use of the most current advances in the fields of protein evolution and structural bioinformatics.

Weaknesses:

It is not clear how coiled-coil segments were assigned if only based on AF2-predicted models or also backed by sequence analysis, as no description is provided in the methods. The structure prediction quality assessment is based solely on the average pLDDT of the obtained models (with a threshold of 80 or better). However, this is not enough, particularly when multimeric models are used. The PAE matrix should be used to evaluate relative orientations, particularly in the case where there is a prediction that parts from 2 proteins are interacting. In the case of multimers, interface quality scores, such as the ipTM or pDockQ, should also be considered and, at minimum, reported.

A description of the coiled-coil predictions has been added to the Methods. For multimeric models, PAE matrices and ipTM+pTM scores have been included in Supplementary Data File S1.

Reviewer #2 (Public Review):

Summary:

In this work, using in-depth computational analysis, Bell et al. explore the diverse repertoire of type IV McrBC modification-dependent restriction systems. The prototypical two-component McrBC system has been structurally and functionally characterised and is known to act as a defence by restricting phage and foreign DNA containing methylated cytosines. Here, the authors find previously unanticipated complexity and versatility of these systems and focus on detailed analysis and classification of a distinct branch, the so-called CoCoNut, named after its composition of coiled-coil structures and tandem nucleases. These CoCoNut systems are predicted to target RNA as well as DNA and to utilise defence mechanisms with some similarity to type III CRISPR-Cas systems.

Strengths:

This work is enriched with a plethora of ideas and a myriad of compelling hypotheses that now await experimental verification. The study comes from the group that was amongst the first to describe, characterize, and classify CRISPR-Cas systems. By analogy, the findings described here can similarly promote ingenious experimental and conceptual research that could further drive technological advances. It could also instigate vigorous scientific debates that will ultimately benefit the community.

Weaknesses:

The multi-component systems described here function in the context of large oligomeric complexes. Some of the single chain AF2 predictions shown in this work are not compatible, for example, with homohexameric complex formation due to incompatible orientation of domains. The recent advances in protein structure prediction, in particular AlphaFold2 (AF2) multimer, now allow us to confidently probe potential protein-protein interactions and protein complex formation. This predictive power could be exploited here to produce a better glimpse of these multimeric protein systems. It can also provide a more sound explanation for some of the observed differences amongst different McrBC types.

Hexameric CnuB complexes with CnuC stimulatory monomers for Type I-A, I-B, I-C, II, and III-A CoCoNuT systems have been modeled with AF2 and included in Supplementary Data File S1, albeit without the domains fused to the GTPase N-terminus (with the exception of Type I-B, which lacks the long coiled-coil domain fused to the GTPase and was modeled with its entire sequence). Attempts to model the other full-length CnuB hexamers did not lead to convincing results.

Recommendations for the authors:

Reviewing Editor:

The detailed recommendations by the two reviewers will help the authors to further strengthen the manuscript, but two points seem particularly worth considering: 1. The methods are barely sketched in the manuscript, but it could be useful to detail them more closely. Particularly regarding the coiled-coil segments, which are currently just statists, useful mainly for the name of the family, more detail on their prediction, structural properties, and purpose would be very helpful. 2. Due to its encyclopedic nature, the wealth of material presented in the paper makes it hard to penetrate in one go. Any effort to make it more accessible would be very welcome. Reviewer 1 in particular has made a number of suggestions regarding the figures, which would make them provide more support for the findings described in the text.

A description of the techniques used to identify coiled-coil segments has been added to the Methods. Our predictions ranged from near certainty in the coiled-coils detected in CnuB homologs, to shorter helices at the limit of detection in other factors. We chose to report all probable coiled-coils, as the extensive coiled-coils fused to CnuB, which are often the only domain present other than the GTPase, imply involvement in mediating complex formation by interacting with coiled-coils in other factors, particularly the other CoCoNuT factors. The suggestions made by Reviewer 1 were thoughtful and we made an effort to incorporate them.

Reviewer #1 (Recommendations For The Authors):

I do not have any major issues with the manuscript. I have however some minor comments, as described below.

• The last sentence of the abstract at first reads as a fact and not a hypothesis resulting from the work described in the manuscript. After the second read, I noticed the nuances in the sentence. I would suggest a rephrasing to emphasize that the activity described is a theoretical hypothesis not backed-up by experiments.

This sentence has been rephrased to make explicit the hypothetical nature of the statement.

• In line 64, the authors rename DUF3578 as ADAM because indeed its function is not unknown. Did the authors consider reaching out to InterPro to add this designation to this DUF? A search in interpro with DUF3578 results in "MrcB-like, N-terminal domain" and if a name is suggested, it may be worthwhile to take it to the IntrePro team.

We will suggest this nomenclature to InterPro.

• I find Figure 1E hard to analyse and think it occupies too much space for the information it provides. The color scheme, the large amount of small slices, and the lack of numbers make its information content very small. I would suggest moving this to the supplementary and making it instead a bar plot. If removed from Figure 1, more space is made available for the other panels, particularly the structural superpositions, which in my opinion are much more important.

We have removed Figure 1E from the paper as it adds little information beyond the abundance and phyletic distribution of sequenced prokaryotes, in which McrBC systems are plentiful.

• In Figure 2, it is not clear due to the presence of many colorful "operon schemes" that the tree is for a single gene and not for the full operon segment. Highlighting the target gene in the operons or signalling it somehow would make the figure easy to understand even in the absence of the text and legend. The same applies to Supplementary Figure 1.

The legend has been modified to show more clearly that this is a tree of McrB-like GTPases.

• In line 146, the authors write "AlphaFold-predicted endonucelase fold" to say that a protein contains a region that AF2 predicts to fold like an endonuclease. This is a weird way of writing it and can be confusing to non-expert readers. I would suggest rephrasing for increased clarity.

This sentence has been rephrased for greater clarity.

• In line 167, there is a [47]. I believe this is probably due to a previous reference formatting.

Indeed, this was a reference formatting error and has been fixed.

• In most figures, the color palette and the use of very similar color palettes for taxonomy pie charts, genomic context composition schemes, and domain composition diagrams make it really hard to have a good understanding of the image at first. Legends are often close to each other, and it is not obvious at first which belong to what. I would suggest changing the layouts and maybe some color schemes to make it easier to extract the information that these figures want to convey.

It seemed that Figure 4 was the most glaring example of these issues, and it has been rearranged for easier comprehension.

• In the paragraph that starts at line 199, the authors mention an Ig-like domain that is often found at the N-terminus of Type I CoCoNuTs. Are they all related to each other? How conserved are these domains?

These domains are all predicted to adopt a similar beta-sandwich fold and are found at the N-terminus of most CoCoNuT CnuC homologs, suggesting they are part of the same family, but we did not undertake a more detailed sequenced-based analysis of these regions.

We also find comparable domains in the CnuC/McrC-like partners of the abundant McrB-like NxD motif GTPases that are not part of CoCoNuT systems, and given the similarity of some of their predicted structures to Rho GDP-dissociation inhibitor 1, we suspect that they have coevolved as regulators of the non-canonical NxD motif GTPase type. Our CnuBC multimer models showing consistent proximity between these domains in CnuC and CnuB GTPase domains suggest this could indeed be the case. We plan to explore these findings further in a forthcoming publication.

• In line 210, the authors write "suggesting a role in overcrowding-induced stress response". Why so? In >all other cases, the authors justify their hypothesis, which I really appreciated, but not here.

A supplementary note justifying this hypothesis has been added to Supplementary Data File S1.

• At the end of the paragraph that starts in line 264, the authors mention that they constructed AF2 multimeric models to predict if 2 proteins would interact. However, no quality scores were provided, particularly the PAE matrix. This would allow for a better judgement of this prediction, and I would suggest adding the PAE matrix as another panel in the figure where the 3D model of the complex is displayed.

The PAE matrix and ipTM+pTM scores for this and other multimer models have been added to Supplementary Data File S1. For this model in particular, the surface charge distribution of the model has been presented to support the role of the domains that have a higher PAE in RNA binding.

• In line 306, "(supplementary data)" refers to what part of the file?

This file has been renamed Supplementary Table S3 and referenced as such.

• In line 464, the authors suggest that ShdA could interact with CoCoNuTs. Why not model the complex as done for other cases? what would co-folding suggest?

As we were not able to convincingly model full-length CnuB hexamers with N-terminal coiled-coils, we did not attempt modeling of this hypothetical complex with another protein with a long coiled-coil, but it remains an interesting possibility.

• In line 528, why and how were some genes additionally analyzed with HHPred?

Justification for this analysis has been added to the Methods, but briefly, these genes were additionally analyzed if there were no BLAST hits or to confirm the hits that were obtained.

• In the first section of the methods, the first and second (particularly the second) paragraphs are extremely long. I would suggest breaking them to facilitate reading.

This change has been made.

• In line 545, what do the authors mean by "the alignment (...) were analyzed with HHPred"?

A more detailed description of this step has been added to the Methods.

• The authors provide the models they produced as well as extensive supplementary tables that make their data reusable, but they do not provide the code for the automated steps, as to excise target sequence sections out of multiple sequence alignments, for example.

The code used for these steps has been in use in our group at the NCBI for many years. It will be difficult to utilize outside of the NCBI software environment, but for full disclosure, we have included a zipped repository with the scripts and custom-code dependencies, although there are external dependencies as well such as FastTree and BLAST. In brief, it involves PSI-BLAST detection of regions with the most significant homology to one of a set of provided alignments (seals-2-master/bin/wrappers/cog_psicognitor). In this case, the reference alignments of McrB-like GTPases and DUF2357 were generated manually using HHpred to analyze alignments of clustered PSI-BLAST results. This step provided an output of coordinates defining domain footprints in each query sequence, which were then combined and/or extended using scripts based on manual analysis of many examples with HHpred (footprint_finders/get_GTPase_frags.py and footprint_finders/get_DUF2357_frags.py), then these coordinates were used to excise such regions from the query amino acid sequence with a final script (seals-2-master/bin/misc/fa2frag).

Reviewer #2 (Recommendations For The Authors):

(1) Page 4, line 77 - 'PUA superfamily domains' could be more appropriate to use instead of "EVE superfamily".

While this statement could perhaps be applied to PUA superfamily domains, our previous work we refer to, which strongly supports the assertion, was restricted to the EVE-like domains and we prefer to retain the original language.

(2) Page 5. lines 128-130 - AF2 multimer prediction model could provide a more sound explanation for these differences.

Our AF2 multimer predictions added in this revision indeed show that the NxD motif McrB-like CoCoNuT GTPases interact with their respective McrC-like partners such that an immunoglobulin-like beta-sandwich domain, fused to the N-termini of the McrC homologs and similar to Rho GDP-dissociation inhibitor 1, has the potential to physically interact with the GTPase variants. However, we did not probe this in greater detail, as it is beyond the scope of this already highly complex article, but we plan to study it in the future.

(3) Page 8, line 252 - The surface charge distribution of CnuH OB fold domain looks very different from SmpB (pdb3iyr). In fact, the regions that are in contact with RNA in SmpB are highly acidic in CoCoNut CnuH. Although it looks likely that this domain is involved in RNA binding, the mode of interaction should be very different.

We did not detect a strong similarity between the CnuH SmpB-like SPB domain and PDB 3IYR, but when we compare the surface charge distribution of PDB 1WJX and the SPB domain, while there is a significant area that is positively charged in 1WJX that is negatively charged in SPB, there is much that overlaps with the same charge in both domains.

The similarity between SmpB and the SPB domain is significant, but definitely not exact. An important question for future studies is: If the domains are indeed related due to an ancient fusion of SmpB to an ancestor of CnuH, would this degree of divergence be expected?

In other words, can we say anything about how the function of a stand-alone tmRNA-binding protein could evolve after being fused to a complex predicted RNA helicase with other predicted RNA binding domains already present? Experimental validation will ultimately be necessary to resolve these kinds of questions, but for now, it may be safe to say that the presence of this domain, especially in conjunction with the neighboring RelE-like RTL domain and UPF1-like helicase domain, signals a likely interaction with the A-site of the ribosome, and perhaps restriction of aberrant/viral mRNA.

eLife assessment

This paper marks a fundamental advance in our understanding of prokaryotic Type IV restriction systems. The authors provide an encyclopedic overview of a hitherto uncharacterized branch of these systems, which they name CoCoNuTs, for coiled-coil nuclease tandems. They provide compelling evidence that these nucleases target RNA and are part of an echeloned defense response following viral infection. This article will be of great interest to scientists studying prokaryotic immunity mechanisms, as well as broadly to protein scientists engaged in the analysis, classification, and functional annotation of the proteome of life.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Bell et al. provide an exhaustive and clear description of the diversity of a new class of predicted type IV restriction systems that the authors denote as CoCoNuTs, for their characteristic presence of coiled-coil segments and nuclease tandems. Along with a comprehensive analysis that includes phylogenetics, protein structure prediction, extensive protein domain annotations, and in-depth investigation of encoding genomic contexts, they also provide detailed hypothesis about the biological activity and molecular functions of the members of this class of predicted systems. This work is highly relevant, it underscores the wide diversity of defence systems that are used by prokaryotes and demonstrates that there are still many systems to be discovered. The work is sound and backed up by a clear and reasonable bioinformatics approach.

Strengths:

The analysis provided by the authors is extensive and covers the three most important aspects that can be covered computationally when analysing a new family/superfamily: phylogenetics, genomic context analysis, and protein-structure-based domain content annotation. With this, one can directly have an idea about the superfamily of the predicted system and infer about their biological role. The bioinformatics approach is sound and makes use of the most current advances in the fields of protein evolution and structural bioinformatics.

Weaknesses:

It is not clear how coiled-coil segments were assigned if only based on AF2-predicted models or also backed by sequence analysis, as no description is provided in the methods. The structure prediction quality assessment is based solely on the average pLDDT of the obtained models (with a threshold of 80 or better). However, this is not enough, particularly when multimeric models were used. The PAE matrix should be used to evaluate relative orientations, particularly in the case where there is a prediction that parts from 2 proteins are interacting. In the case of multimers, interface quality scores, as the ipTM or pDockQ, should also be considered and, at minimum, reported.

These weaknesses were addressed during revision, and the results provided by the authors support their conclusions. The data resulting from this work will be useful for the general life sciences community, particularly the prokaryotic defense and microbiology communities. It also underscores the high range of functionally unknowns in sequenced genomes that are now much easier to find and interpret due to the success of deep-learning based methods and automated robust bioinformatics pipelines.

Reviewer #2 (Public Review):

Summary:

In this work, using in-depth computational analysis, Bell et al. explore the diverse repertoire of type IV McrBC modification dependent restriction systems. The prototypical two-component McrBC system has been structurally and functionally characterised and is known to act as a defence by restricting phage and foreign DNA containing methylated cytosines. Here, the authors find previously unanticipated complexity and versatility of these systems and focus on detailed analysis and classification of a distinct branch, the so-called CoCoNut, named after its composition of coiled-coil structures and tandem nucleases. These CoCoNut systems are predicted to target RNA as well as DNA and to utilise defence mechanisms with some similarity to type III CRISPR-Cas systems.

Strengths:

This work is enriched with a plethora of ideas and a myriad of compelling hypotheses that now will await experimental verification. The study comes from the group that was amongst the first to describe, characterise, and classify CRISPR-Cas systems. By analogy, the findings described here can similarly promote ingenious experimental and conceptual research that could further drive technological advances. It could also instigate vigorous scientific debates that will ultimately benefit the community.

Weaknesses:

The multi-component systems described here function in the context of large oligomeric complexes similarly to the prototypical McrBC system. While the AlphaFold2 (AF2) multimer predictions are provided in this work, these are not compared with the known McrBC structures. These comparisons could have been helpful not only for providing insights into these multimeric protein systems but also for giving more sound explanations of the differences observed amongst different McrBC types.

eLife assessment

The paper presents valuable insights into the success of the parasitoid Trichopria drosophilae on Drosophila suzukii, elucidating the importance of both molecular adaptations, such as specialized venom proteins and unique cell types, and ecological strategies, including tolerance of intraspecific competition and avoidance of interspecific competition. Through convincing methodological approaches, the authors demonstrate how these adaptations optimize nutrient uptake and enhance parasitic success, highlighting the intricate coordination between molecular and ecological factors in driving parasitization success.

Reviewer #1 (Public Review):

Summary:

Major findings or outcomes include a genome for the wasp, characterization of the venom constituents and teratocyte and ovipositor expression profiles, as well as information about Trichopria ecology and parasitism strategies. It was found that Trichopria cannot discriminate among hosts by age, but can identify previously parasitized hosts. The authors also investigated whether superparasitism by Trichopria wasps improved parasitism outcomes (it did), presumably by increasing venom and teratocyte concentrations/densities. Elegant use of Drosophila ectopic expression tools allowed for functional characterization of venom components (Timps), and showed that these proteins are responsible for parasitoid-induced delays in host development. After finding that teratocytes produce a large number of proteases, experiments showed that these contribute to digestion of host tissues for parasite consumption.<br /> The discussion ties these elements together by suggesting that genes used for aiding in parasitism via different parts of the parasitism arsenal arise from gene duplication and shifts in tissue of expression (to venom glands or teratocytes).

Strengths:

The strength of this manuscript is that it describes the parasitism strategies used by Trichopria wasps at a molecular and behavioral level with broad strokes. It represents a large amount of work that in previous decades might have been published in several different papers. Including all of these data in a manuscript together makes for a comprehensive and interesting study.

Weaknesses:

The weakness is that the breadth of the study results in fairly shallow mechanistic or functional results for any given facet of Trichopria's biology. Although none of the findings are especially novel given results from other parasitoid species in previous publications, integrating results together provides significant information about Trichopria biology.

Reviewer #2 (Public Review):

Summary:

Key findings of this research include the sequencing of the wasp's genome, identification of venom constituents and teratocytes, and examination of Trichopria drosophilae (Td)'s ecology and parasitic strategies. It was observed that Td doesn't distinguish between hosts based on age but can recognize previously parasitized hosts. The study also explored whether multiple parasitisms by Td improved outcomes, which indeed it did, possibly by increasing venom and teratocyte levels. Utilizing Drosophila ectopic expression tools, the authors functionally characterized venom components, specifically tissue inhibitors of metalloproteinases (Timps), which were found to cause delays in host development. Additionally, experiments revealed that teratocytes produce numerous proteases, aiding in the digestion of host tissues for parasite consumption. The discussion suggests that genes involved in different aspects of parasitism may arise from gene duplication and shifts in tissue expression to venom glands or teratocytes.

Strengths:

This manuscript provides an in-depth and detailed depiction of the parasitic strategies employed by Td wasps, spanning both molecular and behavioral aspects. It consolidates a significant amount of research that, in the past, might have been distributed across multiple papers. By presenting all this data in a single manuscript, it delivers a comprehensive and engaging study that could help future developments in the field of biological control against a major insect pest.

Weaknesses:

While none of the findings are particularly groundbreaking, as similar results have been reported for other parasitoid species in prior research, the integration of these results into one comprehensive overview offers valuable biological insights into an interesting new potential biocontrol species.

eLife assessment

This important study asks whether motor neurons within the vestibulo-ocular circuit of zebrafish are required to determine the identity, connectivity, and function of upstream premotor neurons. They provide convincing genetic, anatomical and behavioral evidence that the answer is no. This work is of general interest to developmental neurobiologists and motivates future studies of whether motor neurons are dispensable for assembly of other sensorimotor neural circuits.

Reviewer #1 (Public Review):

Summary:

This study has as its goal to determine how the structure and function of the circuit that stabilizes gaze in the larval zebrafish depends on the presence of the output cells, the motor neurons. A major model of neural circuit development posits that the wiring of neurons is instructed by their postsynaptic cells, transmitting signals retrogradely on which cells to contact and, by extension, where to project their axons. Goldblatt et al. remove the motor neurons from the circuit by generating null mutants for the phox2a gene. The study then shows that, in this mutant that lacks the isl1-labelled extraocular motor neurons, the central projection neurons have 1) largely normal responses to vestibular input; 2) normal gross morphology; 3) minimally changed transcriptional profiles. From this, the authors conclude that the wiring of the circuit is not instructed by the output neurons, refuting the major model.

Strengths:

I found the manuscript to be exceptionally well-written and presented, with clear and concise writing and effective figures that highlight key concepts. The topic of neural circuit wiring is central to neuroscience, and the paper's findings will interest researchers across the field, and especially those focused on motor systems.

The experiments conducted are clever and of a very high standard, and I liked the systematic progression of methods to assess the different potential effects of removing phox2a on circuit structure and function. Analyses (including statistics) are comprehensive and appropriate and show the authors are meticulous and balanced in most of the conclusions that they draw. Overall, the findings are interesting, and with a few tweaks, should leave little doubt about the paper's main conclusions.

Weaknesses:

The main point is the incomplete characterisation of the effects of removing phox2a on the extra-ocular motor neurons. Are these cells no longer there, or are they there but no longer labelled by isl1:GFP? If they are indeed removed, might they have developed early on, and subsequently lost? These questions matter as the central focus of the manuscript is whether the presence of these cells influences the connectivity and function of their presynaptic projection neurons. Therefore, for the main conclusions to be fully supported by the data, the authors would need to test whether 1) the motor neurons that otherwise would have been labelled by the isl1:GFP line are physically no longer there; 2) that this removal (if, indeed, it is that) is developmental. If these experiments are not feasible, then the text should be adjusted to take this into account. A further point to address is the context of the manipulation. If the phox2a removal does indeed take out the extra-ocular motor neurons, what percentage of postsynaptic neurons to the projection neurons are still present? In other words, how does the postsynaptic nMLF output relate to the motor neurons? If, for instance, the nMLF (which, as the authors state, are likely still innervated by the projection neurons) are the main output of the projections neurons, then this would affect the interpretation of the results.

Reviewer #2 (Public Review):

Summary:

This study was designed to test the hypothesis that motor neurons play a causal role in circuit assembly of the vestibulo-ocular reflex circuit, which is based on the retrograde model proposed by Hans Straka. This circuit consists of peripheral sensory neurons, central projection neurons, and motor neurons. The authors hypothesize that loss of extraocular motor neurons, through CRISPR/Cas9 mutagenesis of the phox2a gene, will disrupt sensory selectivity in presynaptic projection neurons if the retrograde model is correct.

Account of the major strengths and weaknesses of the methods and results:

The work presented is impressive in both breadth and depth, including the experimental paradigms. Overall, the main results were that the loss of function paradigm to eliminate extraocular motor neurons did not 1) alter the normal functional connections between peripheral sensory neurons and central projection neurons, 2) affect the position of central projection neurons in the sensorimotor circuit, or 3) significantly alter the transcriptional profiles of central projection neurons. Together, these results strongly indicate that retrograde signals from motor neurons are not required for the development of the sensorimotor architecture of the vestibulo-ocular circuit.

Appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

The results of this study showed that extraocular motor neurons were not required for central projection neuron specification in the vestibulo-ocular circuit, which countered the prevailing retrograde hypothesis proposed for circuit assembly. A concern is that the results presented may be limited to this specific circuit and may not be generalizable to other circuit assemblies, even to other sensorimotor circuits.

Discussion of the likely impact of the work on the field, and the utility of the methods and data to the community:

As mentioned above, this study sheds valuable new insights into the developmental organization of the vestibulo-ocular circuit. However, different circuits likely utilize various mechanisms, extrinsic or intrinsic (or both), to establish proper functional connectivity. So, the results shown here, although begin to explain the developmental organization of the vestibulo-ocular circuit, are not likely to be generalizable to other circuits; though this remains to be seen. At a minimum, this study provides a starting point for the examination of patterning of connections in this and other sensorimotor circuits.

Reviewer #3 (Public Review):

In this manuscript by Goldblatt et al. the authors study the development of a well-known sensorimotor system, the vestibulo-ocular reflex circuit, using Danio rerio as a model. The authors address whether motor neurons within this circuit are required to determine the identity, upstream connectivity and function of their presynaptic partners, central projection neurons. They approach this by generating a CRISPR-mediated knockout line for the transcription factor phox2a, which specifies the fate of extraocular muscle motor neurons. After showing that phox2a knockout ablates these motor neurons, the authors show that functionally, morphologically, and transcriptionally, projection neurons develop relatively normally.

Overall, the authors present a convincing argument for the dispensability of motor neurons in the wiring of this circuit, although their claims about the generalizability of their findings to other sensorimotor circuits should be tempered. The study is comprehensive and employs multiple methods to examine the function, connectivity and identity of projection neurons.

Specific comments:

(1) In the introduction the authors set up the controversy on whether or not motor neurons play an instructive role in determining "pre-motor fate". This statement is somewhat generic and a bit misleading as it is generally accepted that many aspects of interneuron identity are motor neuron-independent. The authors might want to expand on these studies and better define what they mean by "fate", as it is not clear whether the studies they are citing in support of this hypothesis actually make that claim.

(2) Although it appears unchanged from their images, the authors do not explicitly quantitate the number of total projection neurons in phox2a knockouts.

(3) For figures 2C and 3C, please report the proportion of neurons in each animal, either showing individual data points here or in a separate supplementary figure; and please perform and report the results of an appropriate statistical test.

(4) In the topographical mapping of calcium responses (figures 2D, E and 3D), the authors say they see no differences but this is hard to appreciate based on the 3D plotting of the data. Quantitating the strength of the responses across the 3-axes shown individually and including statistical analyses would help make this point, especially since the plots look somewhat qualitatively different.

(5) The transcriptional analysis is very interesting, however, it is not clear why it was performed at 72 hpf, while functional experiments were performed at 5 days. Is it possible that early aspects of projection neuron identity are preserved, while motor neuron-dependent changes occur later? The authors should better justify and discuss their choice of timepoint. The inclusion of heterozygotes as controls is problematic, given that the authors show there are notable differences between phox2a+/+ and phox2a+/- animals; pooling these two genotypes could potentially flatten differences between controls and phox2a-/-.

(6) Projection neurons appear to be topographically organized and this organization is maintained in the absence of motor neurons. Are there specific genes that delineate ventral and dorsal projection neurons? If so, the authors should look at those as candidate genes as they might be selectively involved in connectivity. Showing that generic synaptic markers (Figure 4E) are maintained in the entire population is not convincing evidence that these neurons would choose the correct synaptic partners.

eLife assessment

This is a fundamental study that addresses the key question of how the tetraspanin Tspan12 functions biochemically as a co-receptor for Norrin to initiate β-catenin signaling. The strength of the work lies in the rigorous and compelling binding analyses involving various purified receptors, co-receptors, and ligands, as well as molecular modeling by AlphaFold that was subsequently validated by an extensive series of mutagenesis experiments. The study advances the field by providing a novel mechanism of co-receptor function and shedding new light on how signaling specificity is achieved in the complex Wnt/Norrin signaling system.

Reviewer #1 (Public Review):

Though the Norrin protein is structurally unrelated to the Wnt ligands, it can activate the Wnt/β-catenin pathway by binding to the canonical Wnt receptors Fzd4 and Lrp5/6, as well as the tetraspanin Tspan12 co-receptor. Understanding the biochemical mechanisms by which Norrin engages Tspan12 to initiate signaling is important, as this pathway plays an important role in regulating retinal angiogenesis and maintaining the blood-retina-barrier. Numerous mutations in this signaling pathway have also been found in human patients with ocular diseases. The overarching goal of the study is to define the biochemical mechanisms by which Tspan12 mediates Norrin signaling. Using purified Tspan12 reconstituted in lipid nanodiscs, the authors conducted detailed binding experiments to document the direct, high-affinity interactions between purified Tspan12 and Norrin. To further model this binding event, they used AlphaFold to dock Norrin and Tspan12 and identified four putative binding sites. They went on to validate these sites through mutagenesis experiments. Using the information obtained from the AlphaFold modeling and through additional binding competition experiments, it was further demonstrated that Tspan12 and Fzd4 can bind Norrin simultaneously, but Tspan12 binding to Norrin is competitive with other known co-receptors, such as HSPGs and Lrp5/6. Collectively, the authors proposed that the main function of Tspan12 is to capture low concentrations of Norrin at the early stage of signaling, and then "hand over" Norrin to Fzd4 and Lrp5/6 for further signal propagation. Overall, the study is comprehensive and compelling, and the conclusions are well supported by the experimental and modeling data.

Strengths:

• Biochemical reconstitution of Tspan12 and Fzd4 in lipid nanodiscs is an elegant approach for testing the direct binding interaction between Norrin and its co-receptors. The proteins used for the study seem to be of high purity and quality.

• The various binding experiments presented throughout the study were carried out rigorously. In particular, BLI allows accurate measurement of equilibrium binding constants as well as on and off rates.

• It is nice to see that the authors followed up on their AlphaFold modeling with an extensive series of mutagenesis studies to experimentally validate the potential binding sites. This adds credence to the AlphaFold models.

• Table S1 is a further testament to the rigor of the study.

• Overall, the study is comprehensive and compelling, and the conclusions are well supported by the experimental and modeling data.

Suggestions for improvement:

• It would be helpful to show Coomassie-stained gels of the key mutant Norrin and Tspan12 proteins presented in Figures 2E and 2F.

• Many Norrin and Tspan12 mutations have been identified in human patients with FEVR. It would be interesting to comment on whether any of the mutations might affect the Norrin-Tspan12 binding sites described in this study.

• Some of the negative conclusions (e.g. the lack of involvement of Tspan12 in the formation of the Norrin-Lrp5/6-Fzd4-Dvl signaling complex) can be difficult to interpret. There are many possible reasons as to why certain biological effects are not recapitulated in a reconstitution experiment. For instance, the recombinant proteins used in the experiment may not be presented in the correct configurations, and certain biochemical modifications, such as phosphorylation, may also be missing.

Reviewer #2 (Public Review):

This is an interesting study of high quality with important and novel findings. Bruguera et al. report a biochemical and structural analysis of the Tspan12 co-receptor for norrin. Major findings are that Norrin directly binds Tspan12 with high affinity (this is consistent with a report on BioRxiv: Antibody Display of cell surface receptor Tetraspanin12 and SARS-CoV-2 spike protein) and a predicted structure of Tspan12 alone or in complex with Norrin. The Norrin/Tspan12 binding interface is largely verified by mutational analysis. An interaction of the Tspan12 large extracellular loop (LEL) with Fzd4 cannot be detected and interactions of full-length Tspan12 and Fzd4 cannot be tested using nano-disc based BLI, however, Fzd4/Tspan12 heterodimers can be purified and inserted into nanodiscs when aided by split GFP tags. An analysis of a potential composite binding site of a Fzd4/Tspan12 complex is somewhat inconclusive, as no major increase in affinity is detected for the complex compared to the individual components. A caveat to this data is that affinity measurements were performed for complexes with approximately 1 molecule Tspan12 and FZD4 per nanodisc, while the composite binding site could potentially be formed only in higher order complexes, e.g., 2:2 Fzd4/Tspan12 complexes. Interestingly, the authors find that the Norrin/Tspan12 binding site and the Norrin/Lrp6 binding site partially overlap and that the Lrp6 ectodomain competes with Tspan12 for Norrin binding. This result leads the authors to propose a model according to which Tspan12 captures Norrin and then has to "hand it off" to allow for Fzd4/Lrp6 formation. By increasing the local concentration of Norrin, Tspan12 would enhance the formation of the Fzd4/Lrp5 or Fzd4/Lrp6 complex.

The experiments based on membrane proteins inserted into nano-discs and the structure prediction using AlphaFold yield important new insights into a protein complex that has critical roles in normal CNS vascular biology, retinal vascular disease, and is a target for therapeutic intervention. However, it remains unclear how Norrin would be "handed off" from Tspan12 or Tspan12/Fzd4 complexes to Fzd4/Lrp6 complexes, as the relatively high affinity of Norrin to Fzd4/Tspan12 dimers likely does not favor the "handing off" to Fzd4/Lrp6 complexes.

Areas that would benefit from further experiments, or a discussion, include:

- The authors test a potential composite binding site of Fzd4/Tspan12 heterodimers for norrin using nanodiscs that contain on average about 1 molecule Fzd4 and 1 molecule Tspan12. The Fzd4/Tspan12 heterodimer is co-inserted into the nanodiscs supported by split-GFP tags on Fzd4 and Tspan12. The authors find no major increase in affinity, although they find changes to the Hill slope, reflecting better binding of norrin at low norrin concentrations. In 293F cells overexpressing Fzd4 and Tspan12 (which may result in a different stoichiometry) they find more pronounced effects of norrin binding to Fzd4/Tspan12. This raises the possibility that the formation of a composite binding requires Fzd4/Tspan12 complexes of higher order, for example, 2:2 Fzd4/Tspan12 complexes, where the composite binding site may involve residues of each Fzd4 and Tspan12 molecule in the complex. This could be tested in nanodiscs in which Fzd4 and Tspan12 are inserted at higher concentrations or using Fzd4 and Tspan12 that contain additional tags for oligomerization.

- While Tspan12 LEL does not bind to Fzd4, the successful reconstitution of GFP from Tspan12 and Fzd4 tagged with split GFP components provides evidence for Fzd4/Tspan12 complex formation. As a negative control, e.g., Fzd5, or Tspan11 with split GFP tags (Fzd5/Tspan12 or Fzd4/Tspan11) would clarify if FZD4/Tspan12 heterodimers are an artefact of the split GFP system.

- Fzd4/Tspan12 heterodimers stabilized by split GFP may be locked into an unfavorable orientation that does not allow for the formation of a composite binding site of FZD4 and Tspan12, this is another caveat for the interpretation that Fzd4/Tspan12 do not form a composite binding site. This is not discussed.

- Mutations that affect the affinity of norrin/fzd4 are not used to further test if Fzd4 and Tspan12 form a composite binding site. Norrin R41E or Fzd4 M105V were previously reported to reduce norrin/frizzled4 interactions and signaling, and both interaction and signaling were restored by Tspan12 (Lai et al. 2017). Whether a Fzd4/Tspan12 heterodimer has increased affinity for Norrin R41E was not tested. Similarly, affinity of FZD4 M105V vs a Fzd4 M105V/Tspan12 heterodimer were not tested.

- An important conclusion of the study is that Tspan12 or Lrp6 binding to Norrin is mutually exclusive. This could be corroborated by an experiment in which LRP5/6 is inserted into nanodiscs for BLI binding tests with Norrin, or Tspan12 LEL, or a combination of both. Soluble LRP6 may remove norrin from equilibrium binding/unbinding to Tspan12, therefore presenting LRP6 in a non-soluble form may yield different results.

- The authors use LRP6 instead of LRP5 for their experiments. Tspan12 is less effective in increasing the Norrin/Fzd4/Lrp6 signaling amplitude compared to Norrin/Fzd4/Lrp5 signaling, and human genetic evidence (FEVR) implicates LRP5, not LRP6, in Norrin/Frizzled4 signaling. The authors find that Norrin binding to LRP6 and Tspan12 is mutually exclusive, however this may not be the case for Lrp5.

- The biochemical data are largely not correlated with functional data. The authors suggest that the Norrin R115L FEVR mutation could be due to reduced norrin binding to tspan12, but do not test if Tspan12-mediated enhancement of the norrin signaling amplitude is reduced by the R115L mutation. Similarly, the impressive restoration of binding by charge reversal mutations in site 3 is not corroborated in signaling assays.

Reviewer #3 (Public Review):

Brugeuera et al present an impressive series of biochemical experiments that address the question of how Tspan12 acts to promote signaling by Norrin, a highly divergent TGF-beta family member that serves as a ligand for Fzd4 and Lrp5/6 to promote canonical Wnt signaling during CNS (and especially retinal) vascular development. The present study is distinguished from those of the past 15 years by its quantitative precision and its high-quality analyses of concentration dependencies, its use of well-characterized nano-disc-incorporated membrane proteins and various soluble binding partners, and its use of structure prediction (by AlphaFold) to guide experiments. The authors start by measuring the binding affinity of Norrin to Tspan12 in nanodiscs (~10 nM), and they then model this interaction with AlphaFold and test the predicted interface with various charge and size swap mutations. The test suggests that the prediction is approximately correct, but in one region (site 1) the experimental data do not support the model. [As noted by the authors, a failure of swap mutations to support a docking model is open to various interpretations. As AlphFold docking predictions come increasingly into common use, the compendium of mutational tests and their interpretations will become an important object of study.] Next, the authors show that Tspan12 and Fzd4 can simultaneously bind Norrin, with modest negative cooperativity, and that together they enhance Norrin capture by cells expressing both Tspan12 and Fzd4 compared to Fzd4 alone, an effect that is most pronounced at low Norrin concentration. Similarly, at low Norrin concentration (~1 nM), signaling is substantially enhanced by Tspan12. By contrast, the authors show that LRP6 competes with Tspan12 for Norrin binding, implying a hand-off of Norrin from a Tspan12+Fzd4+Norrin complex to a LRP5/6+Fzd4+Norrin complex. Thanks to the authors' careful dose-response analyses, they observed that Norrin-induced signaling and Tspan12 enhancement of signaling both have bell-shaped dose-response curves, with strong inhibition at higher levels of Norrin or Tspan12. The implication is that the signaling system has been built for optimal detection of low concentrations of Norrin (most likely the situation in vivo), and that excess Tspan12 can titrate Norrin at the expense of LRP5/6 binding (i.e., reduction in the formation of the LRP5/6+Fzd4+Norrin signaling complex). In the view of this reviewer, the present work represents a foundational advance in understanding Norrin signaling and the role of Tspan12. It will also serve as an important point of comparison for thinking about signaling complexes in other ligand-receptor systems.

Author Response

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

eLife assessment

This work provides a valuable contribution and assessment of what it means to replicate a null study finding, and what are the appropriate methods for doing so (apart from a rote p-value assessment). Through a convincing re-analysis of results from the Reproducibility Project: Cancer Biology using frequentist equivalence testing and Bayes factors, the authors demonstrate that even when reducing 'replicability success' to a single criterion, how precisely replication is measured may yield differing results. Less focus is directed to appropriate replication of non-null findings.

Reviewer #1 (Public Review):

Summary:

The goal of Pawel et al. is to provide a more rigorous and quantitative approach for judging whether or not an initial null finding (conventionally with p ≥ 0.05) has been replicated by a second similarly null finding. They discuss important objections to relying on the qualitative significant/non-significant dichotomy to make this judgment. They present two complementary methods (one frequentist and the other Bayesian) which provide a superior quantitative framework for assessing the replicability of null findings.

Strengths:

Clear presentation; illuminating examples drawn from the well-known Reproducibility Project: Cancer Biology data set; R-code that implements suggested analyses. Using both methods as suggested provides a superior procedure for judging the replicability of null findings.

Weaknesses:

The proposed frequentist and the Bayesian methods both rely on binary assessments of an original finding and its replication. I'm not sure if this is a weakness or is inherent to making binary decisions based on continuous data.

For the frequentist method, a null finding is considered replicated if the original and replication 90% confidence intervals for the effects both fall within the equivalence range. According to this approach, a null finding would be considered replicated if p-values of both equivalences tests (original and replication) were, say, 0.049, whereas would not be considered replicated if, for example, the equivalence test of the original study had a p-value of 0.051 and the replication had a p-value of 0.001. Intuitively, the evidence for replication would seem to be stronger in the second instance. The recommended Bayesian approach similarly relies on a dichotomy (e.g., Bayes factor > 1).

Thanks for the suggestions, we now emphasize more strongly in the “Methods for assessing replicability of null results” and “Conclusions” sections that both TOST p-values and Bayes factors are quantitative measures of evidence that do not require dichotomization into “success” or “failure”.

Reviewer #2 (Public Review):

Summary:

The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

Strengths:

The study uses reliable and shareable/open data to demonstrate its findings, sharing as well the code for statistical analysis. The study provides sensitivity analysis for different scenarios of equivalence margin and alfa level, as well as for different scenarios of standard deviations for the prior of Bayes factors and different thresholds to consider. All analysis and code of the work is open and can be replicated. As well, the study demonstrates on a case-by-case basis how the different criteria can diverge, regarding one sample of a field of science: preclinical cancer biology. It also explains clearly what Bayes factors and equivalence tests are.

Weaknesses:

It would be interesting to investigate whether using Bayes factors and equivalence tests in addition to p-values results in a clearer scenario when applied to replication data from other fields. As mentioned by the authors, the Reproducibility Project: Experimental Philosophy (RPEP) and the Reproducibility Project: Psychology (RPP) have data attempting to replicate some original studies with null results. While the RPCB analysis yielded a similar picture when using both criteria, it is worth exploring whether this holds true for RPP and RPEP. Considerations for further research in this direction are suggested. Even if the original null results were excluded in the calculation of an overall replicability rate based on significance, sensitivity analyses considering them could have been conducted. The present authors can demonstrate replication success using the significance criteria in these two projects with initially p < 0.05 studies, both positive and non-positive.

Other comments:

• Introduction: The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

• Overall picture vs. case-by-case scenario: An interesting finding is that the authors observe that in most cases, there is no substantial evidence for either the absence or the presence of an effect, as evidenced by the equivalence tests. Thus, using both suggested criteria results in a picture similar to the one initially raised by the paper itself. The work done by the authors highlights additional criteria that can be used to further analyze replication success on a case-by-case basis, and I believe that this is where the paper's main contributions lie. Despite not changing the overall picture much, I agree that the p-value criterion by itself does not distinguish between (1) a situation where the original study had low statistical power, resulting in a highly inconclusive non-significant result that does not provide evidence for the absence of an effect and (2) a scenario where the original study was adequately powered, and a non-significant result may indeed provide some evidence for the absence of an effect when analyzed with appropriate methods. Equivalence testing and Bayesian factor approaches are valuable tools in both cases.

Regarding the 0.05 threshold, the choice of the prior distribution for the SMD under the alternative H1 is debatable, and this also applies to the equivalence margin. Sensitivity analyses, as highlighted by the authors, are helpful in these scenarios.

Thank you for the thorough review and constructive feedback. We have added an additional “Appendix C: Null results from the RPP and EPRP” that shows equivalence testing and Bayes factor analyses for the RPP and EPRP null results.

Reviewer #3 (Public Review):

Summary:

The paper points out that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. Also, it can not be considered a "replication success". The main point of the paper is rather obvious. It may be that both studies are underpowered, in which case their non-significance does not prove anything. The absence of evidence is not evidence of absence! On the other hand, statistical significance is a confusing concept for many, so some extra clarification is always welcome.

One might wonder if the problem that the paper addresses is really a big issue. The authors point to the "Reproducibility Project: Cancer Biology" (RPCB, Errington et al., 2021). They criticize Errington et al. because they "explicitly defined null results in both the original and the replication study as a criterion for replication success." This is true in a literal sense, but it is also a little bit uncharitable. Errington et al. assessed replication success of "null results" with respect to 5 criteria, just one of which was statistical (non-)significance.

It is very hard to decide if a replication was "successful" or not. After all, the original significant result could have been a false positive, and the original null-result a false negative. In light of these difficulties, I found the paper of Errington et al. quite balanced and thoughtful. Replication has been called "the cornerstone of science" but it turns out that it's actually very difficult to define "replication success". I find the paper of Pawel, Heyard, Micheloud, and Held to be a useful addition to the discussion.

Strengths:

This is a clearly written paper that is a useful addition to the important discussion of what constitutes a successful replication.

Weaknesses:

To me, it seems rather obvious that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. I'm not sure how often this mistake is made.

Thanks for the feedback. We do not have systematic data on how often the mistake of confusing absence of evidence with evidence of absence has been made in the replication context, but we do know that it has been made in at least three prominent large-scale replication projects (the RPP, RPEP, RPCB). We therefore believe that there is a need for our article.

Moreover, we agree that the RPCB provided a nuanced assessment of replication success using five different criteria for the original null results. We emphasize this now more in the “Introduction” section. However, we do not consider our article as “a little bit uncharitable” to the RPCB, as we discuss all other criteria used in the RPCB and note that our intent is not to diminish the important contributions of the RPCB, but rather to build on their work and provide constructive recommendations for future researchers. Furthermore, in response to comments made by Reviewer #2, we have added an additional “Appendix B: Null results from the RPP and EPRP” that shows equivalence testing and Bayes factor analyses for null results from two other replication projects, where the same issue arises.

Reviewer #1 (Recommendations For The Authors):

The authors may wish to address the dichotomy issue I raise above, either in the analysis or in the discussion.

Thank you, we now emphasize that Bayes factors and TOST p-values do not need to be dichotomized but can be interpreted as quantitative measures of evidence, both in the “Methods for assessing replicability of null results” and the “Conclusions” sections.

Reviewer #2 (Recommendations For The Authors):

Given that, here follow additional suggestions that the authors should consider in light of the manuscript's word count limit, to avoid confusing the paper's main idea:

2) Referencing: Could you reference the three interesting cases among the 15 RPCB null results (specifically, the three effects from the original paper #48) where the Bayes factor differs qualitatively from the equivalence test?

We now explicitly cite the original and replication study from paper #48.

3) Equivalence testing: As the authors state, only 4 out of the 15 study pairs are able to establish replication success at the 5% level, in the sense that both the original and the replication 90% confidence intervals fall within the equivalence range. Among these 4, two (Paper #48, Exp #2, Effect #5 and Paper #48, Exp #2, Effect #6) were initially positive with very low p-values, one (Paper #48, Exp #2, Effect #4) had an initial p of 0.06 and was very precisely estimated, and the only one in which equivalence testing provides a clearer picture of replication success is Paper #41, Exp #2, Effect #1, which had an initial p-value of 0.54 and a replication p-value of 0.05. In this latter case (or in all these ones), one might question whether the "liberal" equivalence range of Δ = 0.74 is the most appropriate. As the authors state, "The post-hoc specification of equivalence margins is controversial."

We agree that the post hoc choice of equivalence ranges is a controversial issue. The margins define an equivalence region where effect sizes are considered practically negligible, and we agree that in many contexts SMD = 0.74 is a large effect size that is not practically negligible. We therefore present sensitivity analyses for a wide range of margins. However, we do not think that the choice of this margin is more controversial for the mentioned studies with low p-values than for other studies with greater p-values, since the question of whether a margin plausibly encodes practically negligible effect sizes is not related to the observed p-value of a study. Nevertheless, for the new analyses of the RPP and EPRP data in Appendix B, we have added additional sensitivity analyses showing how the individual TOST p-values and Bayes factors vary as a function of the margin and the prior standard deviation. We think that these analyses provide readers with an even more transparent picture regarding the implications of the choice of these parameters than the “project-wise” sensitivity analyses in Appendix A.

4) Bayes factor suggestions: For the Bayes factor approach, it would be interesting to discuss examples where the BF differs slightly. This is likely to occur in scenarios where sample sizes differ significantly between the original study and replication. For example, in Paper #48, Exp #2 and Effect #4, the initial p is 0.06, but the BF is 8.1. In the replication, the BF dramatically drops to < 1/1000, as does the p-value. The initial evidence of 8.1 indicates some evidence for the absence of an effect, but not strong evidence ("strong evidence for H0"), whereas a p-value of 0.06 does not lead to such a conclusion; instead, it favors H1. It would be interesting if the authors discussed other similar cases in the paper. It's worth noting that in Paper #5, Exp #1, Effect #3, the replication p-value is 0.99, while the BF01 is 2.4, almost indicating "moderate" evidence for H0, even though the p-value is inconclusive.

We agree that some of the examples nicely illustrate conceptual differences between p-values and Bayes factors, e.g., how they take into account sample size and effect size. As methodologists, we find these aspects interesting ourselves, but we think that emphasizing them is beyond the scope of the paper and would distract eLife readers from the main messages.

Concerning the conceptual differences between Bayes factors and TOST p-values, we already discuss a case where there are qualitative differences in more detail (original paper #48). We added another discussion of this phenomenon in the Appendix C as it also occurs for the replication of Ranganath and Nosek (2008) that was part of the RPP.

5) p-values, magnitude and precision: It's noteworthy to emphasize, if the authors decide to discuss this, that the p-value is influenced by both the effect's magnitude and its precision, so in Paper #9, Exp #2, Effect #6, BF01 = 4.1 has a higher p-value than a BF01 = 2.3 in its replication. However, there are cases where both p-values and BF agree. For example, in Paper #15, Exp #2, Effect #2, both the original and replication studies have similar sample sizes, and as the p-value decreases from p = 0.95 to p = 0.23, BF01 decreases from 5.1 ("moderate evidence for H0") to 1.3 (region of "Absence of evidence"), moving away from H0 in both cases. This also occurs in Paper #24, Exp #3, Effect #6.

We appreciate the suggestions but, as explained before, think that the message of our paper is better understood without additional discussion of more general differences between p-values and Bayes factors.

6) The grey zone: Given the above topic, it is important to highlight that in the "Absence of evidence grey zone" for the null hypothesis, for example, in Paper #5, Exp #1, Effect #3 with a p = 0.99 and a BF01 = 2.4 in the replication, BF and p-values reach similar conclusions. It's interesting to note, as the authors emphasize, that Dawson et al. (2011), Exp #2, Effect #2 is an interesting example, as the p-value decreases, favoring H1, likely due to the effect's magnitude, even with a small sample size (n = 3 in both original and replications). Bayes factors are very close to one due to the small sample sizes, as discussed by the authors.

We appreciate the constructive comments. We think that the two examples from Dawson et al. (2011) and Goetz et al. (2011) already nicely illustrate absence of evidence and evidence of absence, respectively, and therefore decided not to discuss additional examples in detail, to avoid redundancy.

7) Using meta-analytical results (?): For papers from RPCB, comparing the initial study with the meta-analytical results using Bayes factor and equivalence testing approaches (thus, increasing the sample size of the analysis, but creating dependency of results since the initial study would affect the meta-analytical one) could change the conclusions. This would be interesting to explore in initial studies that are replicated by much larger ones, such as: Paper #9, Exp #2, Effect #6; Goetz et al. (2011), Exp #1, Effect #1; Paper #28, Exp #3, Effect #3; Paper #41, Exp #2, Effect #1; and Paper #47, Exp #1, Effect #5).

Thank you for the suggestion. We considered adding meta-analytic TOST p-values and Bayes factors before, but decided that Figure 3 and the results section are already quite technical, so adding more analyses may confuse more than help. Nevertheless, these meta-analytic approaches are discussed in the “Conclusions” section.

8) Other samples of fields of science: It would be interesting to investigate whether using Bayes factors and equivalence tests in addition to p-values results in a clearer scenario when applied to replication data from other fields. As mentioned by the authors, the Reproducibility Project: Experimental Philosophy (RPEP) and the Reproducibility Project: Psychology (RPP) have data attempting to replicate some original studies with null results. While the RPCB analysis yielded a similar picture when using both criteria, it is worth exploring whether this holds true for RPP and RPEP. Considerations for further research in this direction are suggested. Even if the original null results were excluded in the calculation of an overall replicability rate based on significance, sensitivity analyses considering them could have been conducted. The present authors can demonstrate replication success using the significance criteria in these two projects with initially p < 0.05 studies, both positive and non-positive.

Thank you for the excellent suggestion. We added an Appendix B where the null results from the RPP and EPRP are analyzed with our proposed approaches. The results are also discussed in the “Results” and “Conclusions” sections.

9) Other approaches: I am curious about the potential impact of using an approach based on equivalence testing (as described in https://arxiv.org/abs/2308.09112). It would be valuable if the authors could run such analyses or reference the mentioned work.

Thank you. We were unaware of this preprint. It seems related to the framework proposed by Stahel W. A. (2021) New relevance and significance measures to replace p-values. PLoS ONE 16(6): e0252991. https://doi.org/10.1371/journal.pone.0252991

We now cite both papers in the discussion.

10) Additional evidence: There is another study in which replications of initially p > 0.05 studies with p > 0.05 replications were also considered as replication successes. You can find it here: https://www.medrxiv.org/content/10.1101/2022.05.31.22275810v2. Although it involves a small sample of initially p > 0.05 studies with already large sample sizes, the work is currently under consideration for publication in PLOS ONE, and all data and materials can be accessed through OSF (links provided in the work).

Thank you for sharing this interesting study with us. We feel that it is beyond the scope of the paper to include further analyses as there are already analyses of the RPCB, RPP, and EPRP null results. However, we will keep this study in mind for future analysis, especially since all data are openly available.

11) Additional evidence 02: Ongoing replication projects, such as the Brazilian Reproducibility Initiative (BRI) and The Sports Replication Centre (https://ssreplicationcentre.com/), continue to generate valuable data. BRI is nearing completion of its results, and it promises interesting data for analyzing replication success using p-values, equivalence regions, and Bayes factor approaches.

We now cite these two initiatives as examples of ongoing replication projects in the introduction. Similarly as for your last point, we think that it is beyond the scope of the paper to include further analyses as there are already analyses of the RPCB, RPP, and EPRP null results.

Reviewer #3 (Recommendations For The Authors):

I have no specific recommendations for the authors.

Thank you for the constructive review.

Reviewing Editor (Recommendations For the Authors):

I recognize that it was suggested to the authors by the previous Reviewing Editor to reduce the amount of statistical material to be made more suitable for a non-statistical audience, and so what I am about to say contradicts advice you were given before. But, with this revised version, I actually found it difficult to understand the particulars of the construction of the Bayes Factors and would have appreciated a few more sentences on the underlying models that fed into the calculations. In my opinion, the provided citations (e.g., Dienes Z. 2014. Using Bayes to get the most out of non-significant results) did not provide sufficient background to warrant a lack of more technical presentation here.

Thank you for the feedback. We added a new “Appendix C: Technical details on Bayes factors” that provides technical details on the models, priors, and calculations underlying the Bayes factors.

Author response:

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

Reviewer #1 (Public Review):

Summary:

Bendzunas, Byrne et al. explore two highly topical areas of protein kinase regulation in this manuscript. Firstly, the idea that Cys modification could regulate kinase activity. The senior authors have published some standout papers exploring this idea of late, and the current work adds to the picture of how active site Cys might have been favoured in evolution to serve critical regulatory functions. Second, BRSK1/2 are understudied kinases listed as part of the "dark kinome" so any knowledge of their underlying regulation is of critical importance to advancing the field.

Strengths:

In this study, the author pinpoints highly-conserved, but BRSK-specific, Cys residues as key players in kinase regulation. There is a delicate balance between equating what happens in vitro with recombinant proteins relative to what the functional consequence of Cys mutation might be in cells or organisms, but the authors are very clear with the caveats relating to these connections in their descriptions and discussion. Accordingly, by extension, they present a very sound biochemical case for how Cys modification might influence kinase activity in cellular environs.

Weaknesses:

I have very few critiques for this study, and my major points are barely major.

Major points

(1) My sense is that the influence of Cys mutation on dimerization is going to be one of the first queries readers consider as they read the work. It would be, in my opinion, useful to bring forward the dimer section in the manuscript.

We agree that the influence of Cys on BRSK dimerization is a topic of significant interest. Our primary focus was to explore oxidative regulation of the understudied BRSK kinases as they contain a conserved T-loop Cys, and we have previously demonstrated that equivalent residues at this position in related kinases were critical drivers of oxidative modulation of catalytic activity. We have demonstrated here that BRSK1 & 2 are similarly regulated by redox and this is due to oxidative modification of the T+2 Cys, in addition to Cys residues that are conserved amongst related ARKs as well as BRSK-specific Cys. Although we also provide evidence for limited redox-sensitive higher order BRSK species (dimers) in our in vitro analysis, these represent a small population of the total BRSK protein pool (this was validated by SEC-MALs analysis). As such, we do not have strong evidence to suggest that these limited dimers significantly contribute to the pronounced inhibition of BRSK1 & 2 in the presence of oxidizing agents, and instead believe that other biochemical mechanisms likely drive this response. This may result from oxidized Cys altering the conformation of the activation loop. Indeed, the formation of an intramolecular disulfide within the T-loop of BRSK1 & 2, which we detected by MS, is one such regulatory modification. It is noteworthy, that intramolecular disulfide bonds within the T-loop of AKT and MELK have already been shown to induce an inactive state in the kinase, and we posit a similar mechanism for BRSKs.

While we recognize the potential importance of dimerization in this context, our current data from in vitro and cell-based assays do not provide substantial evidence to assert dimerization as a primary regulatory mechanism. Hence, we maintained a more conservative stance in our manuscript, discussing dimerization in later sections where it naturally followed from the initial findings. That being said, we acknowledge the potential significance of dimerization in the regulation of the BRSK T-loop cysteine. We believe this aspect merits further investigation and could indeed be the focus of a follow-up study.

(2) Relatedly, the effect of Cys mutation on the dimerization properties of preparations of recombinant protein is not very clear as it stands. Some SEC traces would be helpful; these could be included in the supplement.

In order to determine whether our recombinant BRSK proteins (and T-loop mutants) existed as monomers or dimers, we performed SDS-PAGE under reducing and non-reducing conditions (Fig 7). This unambiguously revealed that a monomer was the prominent species, with little evidence of dimers under these experimental conditions (even in the presence of oxidizing agents). Although we cannot discount a regulatory role for BRSK dimers in other physiological contexts, we could not produce sufficient evidence to suggest that multimerization played a substantial role in modifying BRSK kinase activity in our assays. We note that our in vitro analysis was performed using truncated forms of the protein, and as such it is entirely possible that regions of the protein that flank the kinase domain may serve additional regulatory functions that may include higher order BRSK conformations. In this regard, although we have not included SEC traces of our recombinant proteins, we have included analytical SEC-MALS of the truncated proteins (Supplementary Figure 6) which we believe to be more informative. We have also now included additional SEC-MALS data for BRSK2 C176A and C183A (Supplementary Figure 6d and e), which supports our findings in Fig 7, demonstrating the presence of limited dimer species under non-reducing conditions.

(3) Is there any knowledge of Cys mutants in disease for BRSK1/2?

We have conducted an extensive search across several databases: COSMIC (Catalogue of Somatic Mutations in Cancer), ProKinO (Protein Kinase Ontology), and TCGA (The Cancer Genome Atlas). These databases are well-regarded for their comprehensive and detailed records of mutations related to cancer and protein kinases. Our analysis using the COSMIC and TCGA databases focused on identifying any reported instances of Cys mutations in BRSK1/2 that are implicated in cancer. Additionally, we utilized the ProKinO database to explore the broader landscape of protein kinase mutations, including any potential disease associations of Cys mutations in BRSK1/2. However, we found no evidence to indicate the presence of Cys mutations in BRSK1/2 that are associated with cancer or disease. This lack of association in the current literature and database records suggests that, as of our latest search, Cys mutations in BRSK1/2 have not been reported as significant contributors to pathogenesis.

(4) In bar charts, I'd recommend plotting data points. Plus, it is crucial to report in the legend what error measure is shown, the number of replicates, and the statistical method used in any tests.

We have added the data points to the bar charts and included statistical methods in figure legends.

(5) In Figure 5b, the GAPDH loading control doesn't look quite right.

The blot has been repeated and updated.

(6) In Figure 7 there is no indication of what mode of detection was used for these gels.

We have updated the figure legend to confirm that the detection method was western blot.

(7) Recombinant proteins - more detail should be included on how they were prepared. Was there a reducing agent present during purification? Where did they elute off SEC... consistent with a monomer of higher order species?

We have added ‘produced in the absence of reducing agents unless stated otherwise’ in the methods section to improve clarity. Although we have not added additional sentences to describe the elution profile of the BRSK proteins by SEC during purification, we believe that the inclusion of analytical SEC-MALS data is sufficient evidence that the proteins are largely monomeric under non-reducing conditions.

Reviewer #2 (Public Review):

Summary:

In this study by Bendzunas et al, the authors show that the formation of intra-molecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys at an unusual CPE motif at the end of the activation segment function as repressive regulatory mechanisms in BSK1 and 2. They observed that mutation of the CPE-Cys only, contrary to the double mutation of the pair, increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide-mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family. Understanding the molecular mechanisms underlying kinase regulation by redox-active Cys residues is fundamental as it appears to be widespread in signaling proteins and provides new opportunities to develop specific covalent compounds for the targeted modulation of protein kinases.

The authors demonstrate that intramolecular cysteine disulfide bonding between conserved cysteines can function as a repressing mechanism as indicated by the effect of DTT and the consequent increase in activity by BSK-1 and -2 (WT). The cause-effect relationship of why mutation of the CPE-Cys only increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells is not clear to me. The explanation given by the authors based on molecular modeling and molecular dynamics simulations is that oxidation of the CPE-Cys (that will favor disulfide bonding) destabilizes a conserved salt bridge network critical for allosteric activation. However, no functional evidence of the impact of the salt-bridge network is provided. If you mutated the two main Cys-pairs (aE-CHRD and A-loop T+2-CPE) you lose the effect of DTT, as the disulfide pairs cannot be formed, hence no repression mechanisms take place, however when looking at individual residues I do not understand why mutating the CPE only results in the opposite effect unless it is independent of its connection with the T+2residue on the A-loop.

Strengths:

This is an important and interesting study providing new knowledge in the protein kinase field with important therapeutic implications for the rationale design and development of next-generation inhibitors.

Weaknesses:

There are several issues with the figures that this reviewer considers should be addressed.

Reviewer #1 (Recommendations for The Authors):

Major points

Page 26 - the discussion could be more concise. There's an element of recapping the results, which should be avoided.

Regarding the conciseness of the discussion section, we have thoroughly revised it to ensure a more succinct presentation, deliberately avoiding the recapitulation of results. The revised discussion now focuses on interpreting the findings and their implications, steering clear of redundancy with the results section.

Figure 1b seems to be mislabeled/annotated. I recommend checking whether the figure legends match more broadly. Figure 1 appears to be incorrectly cited throughout the results.

Thank you for pointing out the discrepancies in the labeling and citation of Figure 1b. We have carefully reviewed and corrected these issues to ensure that all figure labels, legends, and citations accurately reflect the corresponding data and illustrations. We appreciate your attention to detail and the opportunity to improve the clarity and accuracy of our presentation.

Figure 6 - please include a color-coding key in the figure. Further support for these simulations could be provided by supplementary movies or plots of the interaction. Figure 4 colour palette should be adjusted for the spheres in the Richardson diagrams to have greater distinction.

As suggested, we have amended the colour palette in Figure 4 to improve conformity throughout the figure.

Minor points

Figure 2 - it'd be helpful to know what the percentage coverage of peptides is.

We have updated the figure legend to include peptide coverage for both proteins

Some typos - Supp 2 legend "Domians".

Fixed

Figure 6 legend - analyzed by needs a space;

Fixed

Fig 8 legend schematic misspelled.

Fixed

Broadly, if you Google T-loop you get a pot pourri of enzyme answers. Why not just use Activation loop?

The choice of "T-loop" over "Activation loop" in our manuscript was made to maintain consistency with other literature in the field, and in particular our previous paper “Aurora A regulation by reversible cysteine oxidation reveals evolutionarily conserved redox control of Ser/Thr protein kinase activity” where we refer to the activation loop cysteine as T-loop + 2. We acknowledge the varied enzyme contexts in which "T-loop" is used and agree on the importance of clarity. To address this, we made an explicit note in the manuscript that the "T-loop" is also referred to as the "Activation loop", ensuring readers are aware of the interchangeable use of these terms. Additionally, this nomenclature facilitates a more straightforward designation of cysteine residues within the loop (T+2 Cysteine). We believe this approach balances adherence to established conventions with the need for clarity and precision in our descriptions.

Methods - what is LR cloning. Requires some definition. Some manufacturer detail is missing in methods, and referring to prior work is not sufficient to empower readers to replicate.

We agree, and have added the following to the methods section:

“BRSK1 and 2 were sub-cloned into pDest vectors (to encode the expression of N-terminal Flag or HA tagged proteins) using the Gateway LR Clonase II system (Invitrogen) according to the manufacturer’s instructions. pENtR BRSK1/2 clones were obtained in the form of Gateway-compatible donor vectors from Dr Ben Major (Washington University in St. Louis). The Gateway LR Clonase II enzyme mix mediates recombination between the attL sites on the Entry clone and the attR sites on the destination vector. All cloned BRSK1/2 genes were fully sequenced prior to use.”

Page 7 - optimal settings should be reported. How were pTau signals quantified and normalised?

We have added the following to the methods section:

“Two-color Western blot detection method employing infrared fluorescence was used to measure the ratio of Tau phospho serine 262 to total Tau. Total GFP Tau was detected using a mouse anti GFP antibody and visualized at 680 nm using goat anti mouse IRdye 680 while phospho-tau was detected using a Tau phospho serine 262 specific antibody and visualized at 800 nm using goat anti rabbit IRdye 800. Imaging was performed using a Licor Odessey Clx with scan control settings set to 169 μm, medium quality, and 0.0 mm distance. Quantification was performed using Licor image studio on the raw image files. Total Tau to phospho Tau ratio was determined by measuring the ratio of the fluorescence intensities measured at 800 nm (pTau) to those at 680 nm (total tau).”

In the Figure 6g-j legend, the salt bridge is incorrectly annotated as E185-R248 rather than 258.

Fixed

Lines 393-395 provides a repeat statement on BRSKs phosphorylating Tau (from 388-389).

We have removed the repetition and reworded the opening lines of the results section to improve the overall flow of the manuscript.

Supp. Figure 1 is difficult to view - would it be possible to increase the size of the phylogenetic analysis?

We thank the reviewer for this observation. We have rotated (90°) and expanded the figure so that it can be more clearly viewed

Supp. Figure 2 - BRSK1/2 incorrectly spelled.

Fixed

Please check the alignment of labels in Supp. Figure 3e.

Fixed

Reviewer #2 (Recommendations For The Authors):

(1) In Figure 1, current panel b is not mentioned/described in the figure legend and as a consequence, the rest of the panels in the legends do not fit the content of the figure.

Reviewer 1 also noted this error, and we have amended the manuscript accordingly.

What is the rationale for using the HEK293T cells as the main experimental/cellular system? Are there cell lines that express both proteins endogenously so that the authors can recapitulate the results obtained from ectopic overexpression?

The selection of HEK-293T cells was driven by their well-established utility in overexpression studies, which make them ideal for the investigation of protein interactions and redox regulation. This cell line's robust transfection efficiency and well-characterized biology provide a reliable platform for dissecting the molecular mechanisms underlying the redox regulation of proteins. Furthermore, the use of HEK-293T cells aligns with the broader scientific practice, serving as a common ground for comparability with existing literature in the field of BRSK1/2 signaling, protein regulation and interaction studies.

The application of HEK-293T cells as a model system in our study serves as a foundational step towards eventually elucidating the functions of BRSK1/2 in neuronal cells, where these kinases are predominantly expressed and play critical roles. Given the fact that BRSKs are classed as ‘understudied’ kinases, the choice of a HEK-293T co-overexpression system allowed us to analyze the direct effects of BRSK kinase activity (using phosphorylation of Tau as a readout) in a cellular context and in more controlled manner. This approach not only aids in the establishment of a baseline understanding of the redox regulation of BRSK1/2, but also sets the stage for subsequent investigations in more physiologically relevant neuronal models

In current panel d, could the authors recapitulate the same experimental conditions as in current panel c?

Figure 1 panel c shows that both BRSK1 and 2 are reversibly inhibited by oxidizing agents such as H2O2, whilst panels d and e show the concentration dependent activation and inhibition of the BRSKs with increasing concentrations of DTT and H2O2 respectively. The experimental conditions were identical, other than changing amounts of reducing and oxidizing agents, and used the same peptide coupled assays. Data for all experiments were originally collected in ‘real time’ as depicted in Fig 1c (increase in substrate phosphorylation over time). However, to aid interpretation of the data, we elected to present the latter two panels as dose response curves by calculating the change in the rate of enzyme activity (shown as pmol phosphate incorporated into the peptide substrate per min) for each condition. To aid the reader, we now include an additional supplementary figure (new supplementary figure 2) depicting BRSK1 and 2 dependent phosphorylation of the peptide substrate in the presence of different concentrations of DTT and H2O2 in a real time (kinetic) assay. The new data shown is a subset of the unprocessed data that was used to calculate the rates of BRSK activity in Fig 1d & e.

Why did the authors use full-length constructs in these experiments and did not in e.g. Figure 2 where they used KD constructs instead?

In the initial experiments, illustrated in Figure 1, we employed full-length protein constructs to establish a proof of concept, demonstrating the overall behavior and interactions of the proteins in their full-length form. This confirmed that BRSK1 & 2, which both contain a conserved T + 2 Cys residue that is frequently prognostic for redox sensitivity in related kinases, displayed a near-obligate requirement for reducing agents to promote kinase activity.  

Subsequently, in Figure 2, our focus shifted towards delineating the specific regions within the proteins that are critical for redox regulation. By using constructs that encompass only the kinase domain, we aimed to demonstrate that the redox-sensitive regulation of these proteins is predominantly mediated by specific cysteine residues located within the kinase domain itself. This strategic use of the kinase domain of the protein allowed for a more targeted investigation. Furthermore, in our hands these truncated forms of the protein were more stable at higher concentrations, enabling more detailed characterization of the proteins by DSF and SEC-MALS. We predict that the flanking disordered regions of the full-length protein (as predicted by AlphaFold) contribute to this effect.

(2) In Figure 2, Did the authors try to do LC/MS-MS in the same experimental conditions as in Figure 1 (e.g. buffer minus/plus DTT, H2O2, H2O2 + DTT)?

We would like to clarify that the mass spectrometry experiments were conducted exclusively on proteins purified under native (non-reducing) conditions. We did not extend the LC/MS-MS analyses to include proteins treated with various buffer conditions such as minus/plus DTT, H2O2, or H2O2 + DTT as used in the experiments depicted in Figure 1. Given that we could readily detect disulfides in the absence of oxidizing agents, we did not see the benefit of additional treatment conditions as peroxide treatment of protein samples can frequently complicate interpretation of MS data. However, it should be noted that prior to MS analysis, tryptic peptides were subjected to a 50:50 split, with one half alkylated in the presence of DTT (as described in the methods section) to eliminate disulfides and other transiently oxidized Cys forms. Comparative analysis between reduced and non-reduced tryptic peptides improved our confidence when assigning disulfide bonds (which were eliminated in identical peptides in the presence of DTT).

On panel b, why did the authors show alphafold predictions and not empiric structural information (e.g. X-ray, EM,..)?

The AlphaFold models were primarily utilized to map the general locations of redox-sensitive cysteine pairs within the proteins of interest. Although we have access to the crystal structure of mouse BRSK2, they do not fully capture the active conformation seen in the Alphafold model of the human version. The use of AlphaFold models for human proteins in this study aids in consistently tracking residue numbering across the manuscript, offering a useful framework for understanding the spatial arrangement of these critical cysteine pairs in their potentially active-like states. This approach facilitates our analysis and discussion by providing a reference for the structural context of these residues in the human proteins.

What was the rationale for using the KD construct and not the FL as in Figure 1?

The rationale to use the kinase domain was primarily based on the significantly lower confidence in the structural predictions for regions outside the kinase domain (KD). Our experimental focus was to investigate the role of conserved cysteine residues within the kinase domain, which are critical for the protein's function and regulation. This targeted approach allowed us to concentrate our analyses on the most functionally relevant and structurally defined portion of the protein, thereby enhancing the precision and relevance of our findings. As is frequently the case, truncated forms of the protein, consisting only of the kinase domain, are much more stable than their full length counterparts and are therefore more amenable to in vitro biochemical analysis. In our hands this was true for both BRSK1 and 2, and as such much of the data collected here was generated using kinase-domain (KD) constructs. Simulations using the KD structures are therefore much more representative of our original experimental setup.

The BSK1 KD construct appears to be rather inactive and not responsive to DTT treatment. Could the authors comment on the differences observed with the FL construct of Figure 1

It is important to note that BRSK1, in general, exhibits lower intrinsic activity compared to BRSK2. This reduced activity could be attributed to a range of factors, including the need for activation by upstream kinases such as LKB1, as well as potential post-translational modifications (PTMs) that may be absent in the bacterially expressed KD construct. The full-length forms of the protein were purified from Sf21 cells, and as such may have additional modifications that are lacking in the bacterially derived KD counterparts. We also cannot discount additional regulatory roles of the regions that flank the KD, and these may contribute in part to the modest discrepancy observed between constructs.  Despite these differences, it is crucial to emphasize that both the KD and FL constructs of BRSK1 are regulated by DTT, indicating a conserved redox-dependent activation for both of the related BRSK proteins.  

(3) In Figure 4, on panel A wouldn´t the authors expect that mutating on the pairs e.g. C198A in BSK1 would have the same effect as mutating the C191 from the T+2 site? Did they try mutating individual sites of the aE/CHRD pair? The same will apply to BSK2

We appreciate the insightful comment. It's important to clarify that the redox regulation of these proteins is influenced not solely by the formation of disulfide bonds but also by the oxidation state of individual cysteine residues, particularly the T+2 Cys. This nuanced mechanism of regulation allows for a diverse range of functional outcomes based on the specific cysteine involved and its state of oxidation. This aspect forms a key finding of our paper, highlighting the complexity of redox regulation beyond mere disulfide bond formation. For example, AURA kinase activity is regulated by oxidation of a single T+2 Cys (Cys290, equivalent to Cys191 and Cys176 of BRSK1 and 2 respectively), but this regulation can be supplemented through artificial incorporation of a secondary Cys at the DFG+2 position (Byrne et al., 2020). This targeted genetic modification or AURA mirrors equivalent regulatory disulfide-forming Cys pairs that naturally occur in kinases such as AKT and MELK, and which provide an extra layer of regulatory fine tuning (and a possible protective role to prevent deleterious over oxidation) to the T+2 Cys. We surmise that the CPE Cys is also an accessory regulatory element to the T+2 Cys in BRSK1 +2, which is the dominant driver of BRSK redox sensitivity (as judged by the fact that CPE Cys mutants are still potently regulated by redox [Fig 4]), by locking it in an inactive disulfide configuration.

In our preliminary analysis of BRSK1, we observed that mutations of individual sites within the aE/CHRD pair was similarly detrimental to kinase activity as a tandem mutation (see reviewer figure 1). As discussed in the manuscript, we think that these Cys may serve important structural regulatory functions and opted to focus on co-mutations of the aE/CHRD pair for the remainder of our investigation.

Author response image 1.

In vitro kinase assays showing rates of in vitro peptide phosphorylation by WT and Cys-to-Ala (aE/CHRD residues) variants of BRSK1 after activation by LKB1.

In panels C and D, the same experimental conditions should have been measured as in A and B.

Panels A and B were designed to demonstrate the enzymatic activity and the response to DTT treatment to establish the baseline redox regulation of the kinase and a panel of Cys-to-Ala mutant variants. In contrast, panels C and D were specifically focused on rescue experiments with mutants that showed a significant effect under the conditions tested in A and B. These panels were intended to further explore the role of redox regulation in modulating the activity of these mutants, particularly those that retained some level of activity or exhibited a notable response to redox changes.

The rationale for this experimental design was to prioritize the investigation of mutants, such as those at the T+2 and CPE cysteine sites, which provided the most insight into the redox-dependent modulation of kinase activity. Other mutants, which resulted in inactivation, were deprioritized in this context as they offered limited additional information regarding the redox regulation mechanism. This focused approach allowed us to delve deeper into understanding how specific cysteine residues contribute to the redox-sensitive control of kinase function, aligning with the overall objective of elucidating the nuanced roles of redox regulation in kinase activity.

(4) In figure 5: Why did the authors use reduced Glutathione instead of DTT? The authors should have recapitulated the same experimental conditions as in Figure 4 and not focused only on the T+2 or the CPE single mutants but using the double and the aE/CHRD mutants as well, as internal controls and validation of the enzymatic assays using the modified peptide

Regarding the use of reduced glutathione (GSH) instead of DTT in Figure 5, we chose GSH for its well characterized biological relevance as an antioxidant in cellular responses to oxidative stress. Furthermore, while DTT has been widely used in experimental setups, it is also potentially cytotoxic at high concentrations.

Addressing the point on experimental consistency with Figure 4, we appreciate the suggestion and indeed had already conducted such experiments (Previously Supp Fig 3, now changed to current Supp Fig 4). These experiments include analyses of BRSK mutant activity in a HEK-293T model. However, we chose not to focus on inactivating mutants (such as the aE/CHRD mutants which had depleted expression levels possibly as a consequence of compromised structural integrity) or pursue the generation of double mutant CMV plasmids, as these were deemed unlikely to add significant insights into the core narrative of our study. Our focus remained on the mutants that yielded the most informative results regarding the redox regulation mechanisms in the in vitro setting, ensuring a clear and impactful presentation of our findings.

A time course evaluation of the reducing or oxidizing reagents should have been performed. Would we expect that in WT samples, and in the presence of GSH, and also in the case of the CPE mutant, an increment in the levels of Tau phosphorylation as a readout of BSK1-2 activity?

We acknowledge the importance of such analyses in understanding the dynamic nature of redox regulation on kinase activity and have included a time course (Supp Fig 2 e-g). These results confirm a depletion of Tau phosphorylation over time in response to peroxide generated by the enzyme glucose oxidase.

(5) In Figure 6, did the authors look at the functional impact of the residues with which interact the T+2 and the CPE motifs e.g. T174 and the E185-R258 tether?

Our primary focus was on the salt bridges, as this is a key regulatory structural feature that is conserved across many kinases. Regarding the additional interactions mentioned, we have thoroughly evaluated their roles and dynamics through molecular dynamics (MD) simulations but did not find any results of significant relevance to warrant inclusion.

(6) In Figure 7: Did the author look at the oligomerization state of the BSK1-2 multimers under non-reducing conditions? Were they also observed in the case of the FL constructs? What was the stoichiometry?

Our current work indicates that the kinase domain of BRSK1-2 primarily exists in a monomeric state, with some evidence of dimerization or multimer formation under specific conditions. Our SEC-MALS (Supp Fig 6) and SDS-PAGE analysis (Figure 7) clearly demonstrates that monomers are overwhelmingly the dominant species under non-reducing conditions (>90 %). We also conclude that these limited oligomeric species can be removed by inclusion of reducing agents such as DTT (Figure 7), which may suggest a role for a Cys residue(s). Notably, removal of the T+2 Cys was insufficient to prevent multimerization.

We were unable to obtain reliable SEC-MALS data for the full-length forms of the protein, likely due to the presence of disordered regions that flank the kinase domain which results in a highly heterodispersed and unstable preparation (at the concentrations required for SEC-MALS). Although we are therefore unable to comment on the stoichiometry of FL BRSK dimers, we can detect BRSK1 and 2 hetero- and homo-complexes in HEK-293T cells by IP, which supports the existence of limited BRSK1 & 2 dimers (Supp Fig 6a). However, we were unable to detect intermolecular disulfide bonds by MS, although this does not necessarily preclude their existence. The physiological role of BRSK multimerization (if any) and establishing specifically which Cys residues drive this phenomenon is of significant interest to our future investigations.

eLife assessment

This study provides fundamental new knowledge into the role of reversible cysteine oxidation and reduction in protein kinase regulation. The data provide convincing evidence that intra-molecular disulfide bonds serve a repressive regulatory role in the Brain Selective Kinases (BRSK) 1 & 2; part of the as yet understudied 'dark kinome'. The findings will be of broad interest to biochemists, structural biologists, and those interested in the rational design and development of next-generation kinase inhibitors.

Reviewer #1 (Public Review):

Summary:<br /> Bendzunas, Byrne et al. explore two highly topical areas of protein kinase regulation in this manuscript. Firstly, the idea that Cys modification could regulate kinase activity. The senior authors have published some standout papers exploring this idea of late, and the current work adds to the picture of how active site Cys might have been favoured in evolution to serve critical regulatory functions. Second, BRSK1/2 are understudied kinases listed as part of the "dark kinome" so any knowledge of their underlying regulation is of critical importance to advancing the field.

Strengths:<br /> In this study, the author pinpoints highly-conserved, but BRSK-specific, Cys residues as key players in kinase regulation. There is a delicate balance between equating what happens in vitro with recombinant proteins relative to what the functional consequence of Cys mutation might be in cells or organisms, but the authors are very clear with the caveats relating to these connections in their descriptions and discussion. Accordingly, by extension, they present a very sound biochemical case for how Cys modification might influence kinase activity in cellular environs.

Comments on revised version:

The authors have satisfactorily addressed my concerns.

Reviewer #2 (Public Review):

Summary:

In this study by Bendzunas et al, the authors show that the formation of intra-molecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys at an unusual CPE motif at the end of the activation segment function as repressive regulatory mechanisms in BSK1 and 2. They observed that mutation of the CPE-Cys only, contrary to the double mutation of the pair, increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide-mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family. Understanding the molecular mechanisms underlying kinase regulation by redox-active Cys residues is fundamental as it appears to be widespread in signaling proteins and provides new opportunities to develop specific covalent compounds for the targeted modulation of protein kinases.

The authors demonstrate that intramolecular cysteine disulfide bonding between conserved cysteines can function as a repressing mechanism as indicated by the effect of DTT and the consequent increase in activity by BSK-1 and -2 (WT). The cause-effect relationship of why mutation of the CPE-Cys only increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells is not clear to me. The explanation given by the authors based on molecular modeling and molecular dynamics simulations is that oxidation of the CPE-Cys (that will favor disulfide bonding) destabilizes a conserved salt bridge network critical for allosteric activation. However, no functional evidence of the impact of the salt-bridge network is provided. If you mutated the two main Cys-pairs (aE-CHRD and A-loop T+2-CPE) you lose the effect of DTT, as the disulfide pairs cannot be formed, hence no repression mechanisms take place, however when looking at individual residues I do not understand why mutating the CPE only results in the opposite effect unless it is independent of its connection with the T+2residue on the A-loop.

Strengths:

This is an important and interesting study providing new knowledge in the protein kinase field with important therapeutic implications for the rationale design and development of next-generation inhibitors.

Comments on revised version:

I have one remark related to question number 5 (my question was not clear enough). I meant if the authors did look at the functional relevance of the residues implicated in the identified salt-bridge network/tethers. What happens to the proteins functionally when you mutate those residues? (represented on Fig. 8).

Otherwise, the authors have satisfactorily addressed my concerns.

Author response:

We thank the reviewers for their attention to our study and for their fair and reasonable assessment of the strengths and weaknesses of our work. We believe the reviewers adequately captured both the potential implications of our work as well as its major current limitations. As both reviewers noted, we believe the work presented in this manuscript is an exciting first step in adapting minibinders as antigen sensors for synthetic receptors but many questions remain before these new tools can be widely adopted. We hope that this work will catalyze others to try minibinders as potential antigen sensors when developing novel synthetic receptors, and we hope that future work will more thoroughly test a wide range of linkers to better optimize antigen sensor function across synthetic receptors.

In our future work, we intend to evaluate a greater diversity of minibinders across different relevant therapeutic targets. We are working to test both existing minibinders as well as generate novel minibinders using deep-learning-based de novo protein design methods. We further hope to explore additional linker modifications, especially focusing on modifications that will allow minibinder coupled-synthetic receptors to escape the glycocalyx of engineered cells. We hope to share findings on these topics in either an update to this manuscript or in future manuscripts, depending on the results of our studies in progress.

Finally, reviewers noted a mismatch in the data displayed in Figure 5A and 5C, whereby LCB-CAR-expressing cells induced higher lysis in Figure 5C than in Figure 5A. This is due to figure 5C showing only 24 hours of incubation between effector and target cells, as opposed to the 72 hours of incubation that is quantitated in 5A. These mismatched timepoints were selected because linker-dependent differences in lysis were most readily apparent at 24 hours and were negligible at 72 hours. The full-time course of lysis for this experiment can be seen in Supplemental Figure 2D.

eLife assessment

This study presents a useful investigation to test de novo-designed mini binders against the Spike protein of SARS-CoV-2 within two classes of synthetic receptors (SNIPRs and CARs). The methods and evidence supporting the focused claims are very solid, although the small-scale nature of the investigation (number of modifications, number of minibinders, etc.) makes it difficult to determine how generalizable these results and potential design principles are. This work will be of interest to synthetic biologists and cell engineers as a starting point for systematic, larger-scale analysis and optimization of synthetic receptor designs for cellular therapy and other applications.

Reviewer #1 (Public Review):

Summary:

The authors want to explore how much two known minibinder protein domains against the Spike protein of SARS-CoV-2 can function as a binding domain of 2 sets of synthetic receptors (SNIPR and CAR); the authors also want to know how some modifications of the linkers of these new receptors affect their activation profile.

Major strengths and weaknesses of the methods and results:

- Strengths include: analysis of synthetic receptor function for 2 classes of synthetic receptors, with robust and appropriate assays for both kinds of receptors. The modifications of the linkers are also interesting and the types of modifications that are often used in the field.

- Weaknesses include: none of the data analysis provides statistical interpretation of the results (that I could find). One dataset is confusing: Figures 5A and C, are said to be the same assay with the same constructs, but the results are 30% in A, and 70% in C.

An appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

Given the open-ended nature of the goal (implicit in it being an exploration), it is hard to say if the authors have reached their aims; they have done an exploration for sure; is it big enough an exploration? This reviewer is not sure.

The results are extremely clearly presented, both in the figures and in the text, both for the methods and the results. The claims put forward (with limited exceptions see below) are very solidly supported by the presented data.

A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community:

The work may stimulate others to consider minibinders as potential binding domains for synthetic receptors. The modifications that are presented although not novel, do provide a starting point for larger-scale analysis.

It is not clear how much this is generalizable to other binders (the authors don't make such claims though). The claims are very focused on the tested modifications, and the 2 receptors and minibinder used, a scope that I would define as narrow; the take-home message if one wants to try it with other minibinders or other receptors seems to be: test a few things, and your results may surprise you.

Any additional context you think would help readers interpret or understand the significance of the work:

We are at the infancy stage of synthetic receptors optimization and next-generation derivation; there is a dearth of systematic studies, as most focus is on developing a few ones that work. This work is an interesting attempt to catalyze more research with these new minibinders. Will it be picked up based on this? Not sure.

Reviewer #2 (Public Review):

Summary:

Weinberg et al. show that spike LCB minibinders can be used as the extracellular domain for SynNotch, SNIPR, and CAR. They evaluated their designs against cells expressing the target proteins and live virus.

Strengths:

This is a good fundamental demonstration of alternative use of the minibinder. The results are unsurprising but robust and solid in most cases.

Weaknesses:

The manuscript would benefit from better descriptions of the study's novelty. Given that LCB previously worked in SynNotch, what unexpected finding was uncovered by this study? It is well known that the extracellular domain of CAR is amendable to different types of binding domains (e.g., scFv, nanobody, DARPin, natural ligands). So, it is not surprising that a minibinder also works with CAR. We don't know if the minibinders are more or less likely to be compatible with CAR or SNIPR.

The demonstrations are all done using just 1 minibinder. It is hard to conclude that minibinders, as a unique class of protein binders, are generalizable in different contexts. All it can conclude is that this specific Spike minibinder can be used in synNotch, SNIPR, and CAR. The LCB3 minibinder seems to be much weaker.

The sensing of live viruses is interesting, but the output is very weak. It is difficult to imagine a utility for such a weak response.

Reviewer #3 (Public Review):

Distant metastasis is the major cause of death in patients with breast cancer. In this manuscript, Liu et al. show that RGS10 deficiency elicits distant metastasis via epithelial-mesenchymal transition in breast cancer. As a prognostic indicator of breast cancer, RGS10 regulates the progress of breast cancer and affects tumor phenotypes such as epithelial-mesenchymal transformation, invasion, and migration. The conclusions of this paper are mostly well supported by data, but some analyses need to be clarified.

(1) Because diverse biomarkers have been identified for EMT, it is recommended to declare the advantages of using RGS10 as an EMT marker.

(2) The authors utilized databases to study the upstream regulatory mechanisms of RSG10. It is recommended to clarify why the authors focused on miRNAs rather than other epigenetic modifications.

(3) The role of miR-539-5p in breast cancer has been described in previous studies. Hence, it is recommended to provide detailed elaboration on how miR-539-5p regulates the expression of RSG10.

(4) To enhance the clarity and interpretability of the Western blot results, it would be advisable to mark the specific kilodalton (kDa) values of the proteins.

eLife assessment

This study presents a valuable finding on the mechanism to promote distant metastasis in breast cancer. The evidence supporting the claims of the authors is convincing. The work will be of interest to medical biologists working on breast cancer.

Reviewer #1 (Public Review):

Strengths

The paper has shown the expression of RGS10 is related to the molecular subtype, distant metastasis, and survival status of breast cancer. The study utilizes bioinformatic analyses, human tissue samples, and in vitro and in vivo experiments which strengthen the data. RGS10 was validated to inhibit EMT through a novel mechanism dependent on LCN2 and miR-539-5p, thereby reducing cancer cell proliferation, colony formation, invasion, and migration. The study elaborated the function of RGS10 in influencing the prognosis and biological behavior which could be considered as a potential drug target in breast cancer.

Weakness<br /> The mechanism by which the miR-539-5p/RGS10/LCN2 axis may be related to the prognosis of cancer patients still needs to be elucidated. In addition, the sample size used is relatively limited. Especially, if further exploration of the related pathways and mechanisms of LCN2 can be carried out by using organoid models, as well as the potential of RGS10 as a biomarker for further clinical translation to verify its therapeutic target effect, which will make the data more convincing.

Reviewer #2 (Public Review):

Liu et al., by focusing on the regulation of G protein-signaling 10 (RGS10), reported that RGS10 expression was significantly lower in patients with breast cancer, compared with normal adjacent tissue. Genetic inhibition of RGS10 caused epithelial-mesenchymal transition, and enhanced cell proliferation, migration, and invasion, respectively. These results suggest an inhibitory role of RGS10 in tumor metastasis. Furthermore, bioinformatic analyses determined signaling cascades for RGS10-mediated breast cancer distant metastasis. More importantly, both in vitro and in vivo studies evidenced that alteration of RGS10 expression by modulating its upstream regulator miR-539-5p affects breast cancer metastasis. Altogether, these findings provide insight into the pathogenesis of breast tumors and hence identify potential therapeutic targets in breast cancer.

The conclusions of this study are mostly well supported by data. However, there is a weakness in the study that needs to be clarified.

In Figure 2A, although some references supported that SKBR3 and MCF-7 possess poorly aggressive and less invasive abilities, examining only RGS10 expression in those cells, it could not be concluded that 'RGS10 acts as a tumor suppressor in breast cancer'. It would be better to introduce a horizontal comparison of the invasive ability of these 3 types of cells using an invasion assay.

Author response:

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

We thank the reviewers for their thorough review of and overall positive comments on our manuscript. We have revised the manuscript to address most of the concerns raised. Below is a point-by-point response to the reviewers’ comments outlining these changes.

The novelty of the study is compromised due to the recently published structure of unliganded PRex1 (Chang et al. 2022). The unliganded and IP4-bound structure of P-Rex1 appear virtually identical, however, no clear comparison is presented in the manuscript. In the same paper, a very similar model of P-Rex1 activation upon binding to PIP3 membranes and Gbeta/gamma is presented.

This comparison has been added as Supplemental Figure 5. Although similar models of activation are presented in our manuscript and in that of Chang et al. 2022, our model is extended to incorporate inhibition by IP4 and other aspects of regulation not previously incorporated, shown in both schematic form (Figure 6B) and including supporting data (Figure 6A). We also point out that in the work by Chang et al. they used domain insertions to stabilize the structure, and here we present the native protein structure. It turns out that they look similar, but our work reduces concerns over possible engineering artifacts. Finally, our model is further informed by HDX-MS measurements of the enzyme bound to PIP3 in liposomes (Figure 6A and Supplemental figure 8), which reveal the regions of the protein subject to higher dynamics and are consistent with a more fully extended conformation.

The authors demonstrate that IP4 binding to P-Rex1 results in catalytic inhibition and increased protection of autoinhibitory interfaces, as judged by HDX. The relevance of this in a cellular setting is not clear and is not experimentally demonstrated. Further, mechanistically, it is not clear whether the biochemical inhibition by IP4 of PIP3 activated P-Rex1 is due to competition of IP4 with activating PIP3 binding to the PH domain of P-Rex1, or due to stabilizing the autoinhibited conformation, or both.

We feel that both occur. IP4 and PIP3 bind to the same site of the PH domain, thus they must be competitive at the very least. We also show that IP4 stabilizes the autoinhibited conformation (based on both our cryo-EM and HDX-MS data). Because PIP3 does not activate either DH/PH or DH/PH-DEP1 (nor does IP4 inhibit, see Sup. Fig. 1), it is not possible for us to tell with this suite of experiments how much the inhibition is due to competition versus stabilization of the autoinhibited conformation.

It is difficult to judge the error in the HDX experiments presented in Sup. data 1 and 2. In the method section, it is stated that the results represent the average from two samples. How is the SD error calculated in Fig.1B-C?

To clarify, the following passages have been revised:

Figure 1 legend – “Graphs show the exchange over time for select regions in the P-Rex1 (B) PH domain and (C) a IP4P region that was disordered in the P-Rex1–Gbg structure. Shown is the average of two experiments with error bars representing the mean ± standard deviation.” Methods section – “Each sample was analyzed twice by HDX-MS, and the data shown in graphs represent the average of these experiments. For each peptide, the average of all five time points was calculated and used to plot the difference data onto the coordinates.”

As mentioned, from the explanations in the manuscript it is difficult to judge the differences between the unliganded and the IP4 bound structure. A superposition, pointing to the main differences, would help. Are there any additional interactions observed that could explain a more stable autoinhibitory conformation?

Added as Supplemental Figure 5. Although there are global shifts in some of the domains, the overall structures are similar to one another. Due to the moderate resolution of both structures (~4.2 Å), accurate placement of sidechains is difficult, in some places more than others. Because of this, we cannot pinpoint many specific sidechain interactions with certainty. There are no obvious interactions observed in our IP4 bound structure compared to that of 7SYF that would explain a more stable autoinhibited conformation, and thus the evidence comes primarily from the HDX-MS data.

The cellular significance of IP4 regulation is not clear. Finding a way to manipulate intracellular IP4 levels and showing that this affects P-Rex1 cellular activity would greatly increase the significance of this finding.

We agree that this would be an informative experiment, but not one that we currently have the means to perform.

From the presented data it is not clear if inhibition by IP4 is due to competition with PIP3 or due to the proposed stabilization of P-Rex1 autoinhibition. Performing a study as shown in Fig.1D, but with the DH/PH construct could resolve this question.

First, please see our response to the similar concern from Reviewer 1 above. It is not possible for us to test the DH/PH construct and assess if there is direct competition with PIP3. To emphasize this point (and to correct the error that we never made a call to Sup. Fig. 1C in the original manuscript), we added the following lines to the first paragraph of the Results.

“Negatively charged liposomes (containing PC/PS), including those that also contain PIP3, unexpectedly inhibit the GEF activity of the DH/PH-DEP1 and DH/PH fragments (Sup. Fig. 1C). Because full-length P-Rex1 is not affected by PC/PS liposomes, it suggests this the observed inhibition represents a non-productive interaction of the DH/PH-DEP1 and DH/PH fragments with negatively charged surfaces in our assay. The lack of activation of DH/PH-DEP1 by PIP3 prevents us from testing whether IP4 can directly inhibit via direct competition with PIP3.”

If I understand correctly, the data shown in Supplementary Data 1 and 2 are averages of 2 measurements, which makes it difficult to judge real signals from outliers. Perhaps, rather than showing the average, the results from the two experiments could be shown. Also, please explain how the SD error is calculated in Fig.1B-C if the data points indeed are averages of 2 measurements.

We are sorry for the confusion. The data shown in Sup. Data 1 and 2 are not averages of two experiments. The Methods section has therefore been modified to read: “Each image in Supplemental Data 1 and 2 shows one experiment (rainbow plots) or a difference analysis from those experiments (red to blue plots). Only one of the two sets of experiments performed for each condition (+/- liposomes or +/- IP4) is shown here.” As described above, text has been added to clarify the SD error calculated in Fig. 1B and 1C.

The authors claim that the data presented in Fig 4B suggests that the salt bridge formed by K207 and E251 is important for autoinhibition. If so, the authors should explain why the K207C mutant is not activated.

Multiple reviewers had problems with this panel, and we now recognize that we misinterpreted the data, which did not help with this. Because this data is largely just supportive of our structure and SAXS data, Figure 4 was moved to the Supplement and this section of the results now reads:

“Flexibility of the hinge in the a6-aN helix of the DH/PH module is important for autoinhibition.

One of our initial goals in this project was to determine a high-resolution structure of the autoinhibited DH/PH-DEP1 core by X-ray crystallography. To this end, we started with the DH/PH-DEP1 A170K variant, which was more inhibited than wild-type but still dynamic, and then introduced S235C/M244C and K207C/E251C double mutants to completely constrain the hinge in the a6-aN helix via disulfide bond formation in a redox sensitive manner. Single cysteine variants K207C and M244C were generated as controls. The S235C/M244C variant performed as expected, decreasing the activity of the A170K variant to nearly background in the oxidized but not the reduced state (Supplemental Fig. 4). However, the M244C single mutant exhibited similar effects, suggesting that it forms disulfide bonds with cysteine(s) other than S235C. Indeed, the side chains of Cys200 and Cys234 are very close to that of M244C. The K207C/E251C mutant was similar to S235C/M244C under oxidized conditions, but ~15-fold more active (similar to WT DH/PH levels, see Fig. 3C) under reducing conditions. The K270C variant, on the other hand, exhibited higher activity than A170K on its own under oxidizing conditions, but similar activity to all the variants except K207C/E251C when reduced. These results suggest that K207C/E251C in a reduced state and K270C in an oxidized state favor a configuration where the DEP1 domain is less able to engage the DH domain and maintain the kinked state. The mechanism for this is not known. Regardless, these data show that perturbation of contacts between the kinked segments of the a6-aN helix can have profound consequences on the activity of the DH/PH-DEP1 core.”

In the low-resolution cryo-EM study, it is mentioned that only a few classes exhibit the extra density that ultimately corresponds to autoinhibited P-Rex1. If so, is this also the case in the high-resolution study and how many of the most populated classes contribute to the autoinhibited structure? It would be informative for the reader to provide this information.

Indeed, only a small subset of the particles are in the autoinhibited conformation in the Krios data set, similar to the Glacios. How many classes these particles partition to is dependent on how many classes are asked for during 2D classification and how many “garbage” particles are present at the different stages of particle stack cleaning during 2D classification. Also, because of the preferred orientation problem, many of the particles in this conformation segregate together during 2D classification. Therefore, in addition to the information show in Sup. Fig. 2, we think a more informative metric to answer the reviewer’s question is the number of particles at the start of data processing compared to at the end, which is shown in Table 1.

Page 10, line 217: "The kink .... is important for autoinhibition". It seems unlikely that there is no kink in the activated state. Perhaps it should say something like "Mobility in the kink is important ..."

Agreed. In fact, the SAXS data we reported on the DH/PH module in Ravala et al. (2020) is most consistent with a DH/PH that exhibits both extended and condensed conformations in solutions.

Fig. 4A: It would help to label helices alpha6 and alphaN.

These helices have now been labeled.

Page 11, lines 223 and 228 are contradictory: In line 223 it is stated that K207C/E251C exhibit reduced GEF activity, while on line 228 it says this has little effect under non-reducing conditions.

We thank the reviewer for this catch. We have modified the text to make it self-consistent.

In Fig.5B, it would help if the authors mention in the legend that a trans-well migration assay was used, in order to know what the increase in stained cells signifies.

The legend has been modified to include this information.

The previous work by Chang et al., 2022 (PMID: 35864164) found that the final DH domain α6 formed the hinge helix (the kink in this manuscript), which undergoes a significant conformational change between closed and opened conformations of P-Rex1. Could the authors discuss the state of the kink in the presence of IP4 and in the P-Rex1 variants A170K and L177E?

We have now included an alignment of our structure in the presence of IP4 with the Chang et al., 2022 structure (Supplemental Figure 5). There is very little difference in the kink region. Because the A170K variant exhibits reduced GEF activity and a smaller Dmax, it could be speculated that the kink might be further stabilized as compared to wild-type. The L177E variant exhibited activity similar to that of DH/PH alone, implying a relief of the kink. This interpretation is supported by our SAXS analysis of A170K and L177E in Fig. 3.

I am a bit confused about the set of experiments with the intended DH-DEP1 interface disruptive mutation A170K, which later turned out to enhance P-Rex1 activity inhibition. The authors explained that the DH K170 salt bridges with DEP1 Glu411 stabilize the DH-DEP1 interaction. Next, the authors used P-Rex1 A170K mutant as the backbone for the introduction of disulfide bonds to block the closed configuration of the DH-PH hinge region by creating some mutants S235C/M244C and K207C/E251C. The first intended C235-C244 disulfide bond did not show any effect on the GEF activity because C235 is so close to the native C234 for a potential disulfide bond. I would recommend putting the data of S235C/M244C into a supplemental figure. Also, I am wondering if the GEF activity measurements in Fig 4B could be performed in the presence or absence of IP4 to see whether the IP4-induced autoinhibition form is distinct from the natural autoinhibitory once the kink was unblocked by reducing agent DTT.

The confusion was warranted by our poor analysis of this data, rectified as discussed above.

With regards to experiments plus/minus IP4, due to the absence of the IP4P domain, IP4 had no inhibitory effect on the activity of DH/PH or DH/PH-DEP1 (Supplemental Figure 1A and 1B) and as such this experiment would not likely be informative (or at best very hard to interpret).

For the IP4 versus PIP3 activity assays, the authors indicated that P-Rex1 inhibition is dependent on the Inositol 3-phosphate. Have the authors tested and could they test with either Ins (1,3,4)P3 or Ins(1,3,5)P3?

In these assays (Figure 1D), we show that inhibition does not occur with Ins(1,4,5)P3. Based on previous structures of IP4 bound to the PH domain and supporting biochemical assays (Cash et al., 2016, Structure), the 3- and 4-phosphates are the most highly coordinated and the next most thermostabilizing headgroup other than IP4 was Ins(1,3,4)P3. Therefore, we would anticipate that Ins(1,3,4)P3 might stabilize the autoinhibited state, perhaps at higher concentrations, but we have not directly tested this.

The authors should provide the electron density maps of the P-REX1-IP4 complex in the supplemental figure and highlight the maps for two key interactions between DEP1 and DH and between PH and IP4P 4-helix bundle subdomain.

The Coulomb potential map of this complex is shown in Figure 2A. Due to the moderate resolution of the reconstruction, side chain details cannot be unambiguously modeled at these interfaces, which is why we do not highlight any observed, specific interactions between sidechains.

The manuscript was written very well and there is only one typing error in the legend of Supplemental Figure 1.

Thank you for this catch.

Details of EM density at significant domain interfaces and at the IP4 binding site should be provided as supplementary material.

Beyond our comment about interfaces above, we have now provided the map representing the bound IP4 as Figure 4B.

Line 123: It is difficult to discern in Figure 2A the "severe bend" in the helix that connects the DH and PH domains. It was not apparent (to me, at least) where this helix is located until eventually encountering Figure 4. It would be helpful to highlight or label (maybe with an asterisk) the bend site in Fig 2A.

This has been labeled in Figure 2A.

Line 125-126: likewise, It would be helpful to the reader to highlight the GTPase binding site in the DH domain.

This has been labeled in Figure 2A.

Line 159. Consider adding a supplementary figure showing a superposition of the two pREX-1 regulatory interfaces in the present structure and in 7SYF.

A superposition of the two structures has now been added as Supplemental Figure 5. Because both structures are of moderate resolution, it is difficult to place side chains with a high degree of certainty. Thus, we did not think it wise to draw conclusions from comparisons between the details of these interfaces.

Is the positioning of IP4 dictated by the EM density, prior knowledge from high-resolution structures, or both? A rendering of the EM density over the stick model as a supplementary figure would be helpful.

This was modeled based on both. This image has now been added as Figure 4B.

It should be emphasized that the jackknife model is similar to the hinge model proposed by Chang et al (2022).

Mention of similarity between our model and the model proposed by Chang et al., 2022 occurs twice in the manuscript.

Reviewer #1 (Public Review):

Summary:

The authors perform a multidisciplinary approach to describe the conformational plasticity of P-Rex1 in various states (autoinhibited, IP4 bound and PIP3 bound). Hydrogen-deuterium exchange (HDX) is used to reveal how IP4 and PIP3 binding affect intramolecular interactions. While IP4 is found to stabilize autoinhibitory interactions, PIP3 does the opposite, leading to deprotection of autoinhibitory sites. Cryo-EM of IP4 bound P-Rex1 reveals a structure in the autoinhibited conformation, very similar to the unliganded structure reported previously (Chang et al. 2022). Mutations at observed autoinhibitory interfaces result in a more open structure (as shown by SAXS), reduced thermal stability and increased GEF activity in biochemical and cellular assays. Together their work portrays a dynamic enzyme that undergoes long-range conformational changes upon activation on PIP3 membranes. The results are technically sound and the conclusions are justified. The main drawback is the limited novelty due to the recently published structure of unliganded P-Rex1, which is virtually identical to the IP4 bound structure presented here. Novel aspects suggest a regulatory role for IP4, but the exact significance and mechanism of this regulation has not been explored.

Strengths:

The authors use a multitude of techniques to describe the dynamic nature and conformational changes of P-Rex1 upon binding to IP4 and PIP3 membranes. The different approaches together fit well with the overall conclusion that IP4 binding negatively regulates P-Rex1, while binding to PIP3 membranes leads to conformational opening and catalytic activation. The experiments are performed very thoroughly and are technically sound. The results are clear and support the conclusions.

Weaknesses:

(1) The novelty of the study is compromised due to the recently published structure of unliganded P-Rex1 (Chang et al. 2022). The unliganded and IP4 bound structure of P-Rex1 appear virtually identical, however, no clear comparison is presented in the manuscript. In the same paper a very similar model of P-Rex1 activation upon binding to PIP3 membranes and Gbeta-gamma is presented.

(2) The authors demonstrate that IP4 binding to P-Rex1 results in catalytic inhibition and increased protection of autoinhibitory interfaces, as judged by HDX. The relevance of this in a cellular setting is not clear and is not experimentally demonstrated. Further, mechanistically, it is not clear whether the biochemical inhibition by IP4 of PIP3 activated P-Rex1 is due to competition of IP4 with activating PIP3 binding to the PH domain of P-Rex1, or due to stabilizing the autoinhibited conformation, or both.

(3) Fig.1B-C: To give a standard deviation from 2 data points has no statistical significance. In this case it would be better to define as range/difference of the 2 data points.

eLife assessment

This important study contributes insights into the regulatory mechanisms of a protein governing cell migration at the membrane. The integration of approaches revealing protein structure and dynamics provides convincing data for a model of regulation and suggests a new allosteric role for a solubilized phospholipid headgroup. The work will be interesting to researchers focusing on signaling mechanisms, cell motility, and cancer metathesis.

Reviewer #2 (Public Review):

Summary:

In this new paper, the authors used biochemical, structural, and biophysical methods to elucidate the mechanisms by which IP4, the PIP3 headgroup, can induce an autoinhibit form of P-Rex1 and propose a model of how PIP3 can trigger long-range conformational changes of P-Rex1 to relieve this autoinhibition. The main findings of this study are that a new P-Rex1 autoinhibition is driven by an IP4-induced binding of the PH domain to the DH domain active site and that this autoinhibit form stabilized by two key interactions between DEP1 and DH and between PH and IP4P 4-helix bundle (4HB) subdomain. Moreover, they found that the binding of phospholipid PIP3 to the PH domain can disrupt these interactions to relieve P-Rex1 autoinhibition.

Strengths:

The study provides good evidence that binding of IP4 to the P-Rex1 PH domain can make the two long-range interactions between the catalytic DH domain and the first DEP domain, and between the PH domain and the C-terminal IP4P 4HB subdomain that generate a novel P-Rex1 autoinhibition mechanism. This valuable finding adds an extra layer of P-Rex1 regulation (perhaps in the cytoplasm) to the synergistic activation by phospholipid PIP3 and the heterotrimeric Gβγ subunits at the plasma membrane. Overall, this manuscript's goal sounds interesting, the experimental data were carried out carefully and reliably.

Weakness:

The set of experiments with the disulfide bond S235C/M244C caused a bit of confusion for interpretation, it should be moved into the supplement, and the text and Figure 4 were altered accordingly.

Reviewer #3 (Public Review):

Summary:

In this report, Ravala et al demonstrate that IP4, the soluble head-group of phosphatiylinositol 3,4,5 - trisphosphate (PIP3), is an inhibitor of pREX-1, a guanine nucleotide exchange factor (GEF) for Rac1 and related small G proteins that regulate cell cell migration. This finding is perhaps unexpected since pREX-1 activity is PIP3-dependent. By way of Cryo-EM (revealing the structure of the p-REX-1/IP4 complex at 4.2Å resolution), hydrogen-deuterium mass spectrometry and small angle X-ray scattering, they deduce a mechanism for IP4 activation, and conduct mutagenic and cell-based signaling assays that support it. The major finding is that IP4 stabilizes two interdomain interfaces that block access of the DH domain, which conveys GEF activity towards small G protein substrates. One of these is the interface between the PH domain that binds to IP4 and a 4-helix bundle extension of the IP4 Phosphatase domain and the DEP1 domain. The two interfaces are connected by a long helix that extends from PH to DEP1. Although the structure of fully activated pREX-1 has not been determined, the authors propose a "jackknife" mechanism, similar to that described earlier by Chang et al (2022) (referenced in the author's manuscript) in which binding of IP3 relieves a kink in a helix that links the PH/DH modules and allows the DH-PH-DEP triad to assume an extended conformation in which the DH domain is accessible. While the structure of the activated pREX-1 has not been determined, cysteine mutagenesis that enforces the proposed kink is consistent with this hypothesis. SAXS and HDX-MS experiments suggest that IP4 acts by stiffening the inhibitory interfaces, rather than by reorganizing them. Indeed, the cryo-EM structure of ligand-free pREX-1 shows that interdomain contacts are largely retained in the absence of IP4.

Strengths:

The manuscript thus describes a novel regulatory role for IP4 and is thus of considerable significance to our understanding of regulatory mechanisms that control cell migration, particularly in immune cell populations. Specifically, they show how the inositol polyphosphate IP4 controls the activity of pREX-1, a guanine nucleotide exchange factor that controls the activity of small G proteins Rac and CDC42 . In their clearly-written discussion, the authors explain how PIP3, the cell membrane and the Gbeta-gamma subunits of heterotrimeric membranes together localize pREX-1 at the membrane and induce activation. The quality of experimental data is high and both in vitro and cell-based assays of site-directed mutants designed to test the author's hypotheses are confirmatory. The results strongly support the conclusions. The combination of cryo-EM data, that describe the static (if heterogeneous) structures with experiments (small angle x-ray scattering and hydrogen-deuterium exchange-mass spectrometry) that report on dynamics are well employed by the authors

Manuscript revision:

The reviewers noted a number of weaknesses, including error analysis of the HDX data, interpretation of the mutagenesis data, the small fraction of the total number of particles used to generate the EM reconstruction, the novelty of the findings in light of the previous report by Cheng et al, 2022, various details regarding presentation of structural results and questions regarding the interpretation of the inhibition data (Figure 1D). The authors have responded adequately to these critiques. It appears that pREX-1 is a highly dynamic molecule, and considerable heterogeneity among particles might be expected.

While, indeed, the conformation of pREX presented in this report is not novel, the finding that this inactive conformational state is stabilized by IP4 is significant and important. The evidence for this is both structural and biochemical, as indicated by micromolar competition of IP4 with PI3-enriched vesicles resulting in the inhibition of pREX-1 GEF activity.

Reviewer #3 (Public Review):

Summary:

Studying evolutionary trajectories provides important insight in genetic architecture of adaptation and provide potential contribution to evaluating the predictability (or unpredictability) in biological processes involving adaptation. While many papers in the field address adaptation to environmental challenges, the number of studies on how genomic contexts, such as large-scale variation, can impact evolutionary outcomes adaptation is relatively low. This research experimentally evolved a genome-reduced strain for ~1000 generations with 9 replicates and dissected their evolutionary changes. Using the fitness assay of OD measurement, the authors claimed there is a general trend of increasing growth rate and decreasing carrying capacity, despite a positive correlation among all replicates. The authors also performed genomic and transcriptomic research at the end of experimental evolution, claiming the dissimilarity in the evolution at the molecular level.

Strengths:

The experimental evolution approach with a high number of replicates provides a good way to reveal the generality/diversity of the evolutionary routes.

The assay of fitness, genome, and transcriptome all together allows a more thorough understanding of the evolutionary scenarios and genetic mechanisms.

Comments on revised version:

5 in the last round of comments: When the authors mentioned no overlapping in single mutation level, I thought the authors would directly use this statement to support their next sentence about no bias of these mutations. As the author's responded, I was suspecting no overlapping for 65 mutation across the entire genome is likely to be not statistically significant. In the revised version, the authors emphasized and specified their simulation and argument in the following sentences, so I do not have questions on this point anymore.

14 in the last round of comments: As what authors responded, "short-term responses" meant transcriptional or physiological changes within a few hours after environmental or genetic fluctuation. "long-term responses" involve new compensatory mutations and selection. The point was that, the authors found that "the transcriptome reorganization for fitness increase triggered by evolution differed from that for fitness decrease caused by genome reduction." That is short vs long-term responses to genetic perturbation. Some other experimental evolution did short vs long-term responses to environmental perturbation and usually also found that the short-term responses are reverted in the long-term responses (e.g., https://academic.oup.com/mbe/article/33/1/25/2579742). I hope this explanation makes more sense. And I think the authors can make their own decisions on whether they would like to add this discussion or not.

Author response:

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

Response to Reviewer #1:

Thank you for the careful reading and the positive evaluation of our manuscript. As you mentioned, the present study tried to address the question of how the lost genomic functions could be compensated by evolutionary adaptation, indicating the potential mechanism of "constructive" rather than "destructive" evolution. Thank you for the instructive comments that helped us to improve the manuscript. We sincerely hope the revised manuscript and the following point-to-point response meet your concerns.

• Line 80 "Growth Fitness" is this growth rate?

Yes. The sentence was revised as follows.

(L87-88) “The results demonstrated that most evolved populations (Evos) showed improved growth rates, in which eight out of nine Evos were highly significant (Fig. 1B, upper).”

• Line 94 a more nuanced understanding of r/K selection theory, allows for trade-ups between R and K, as well as trade-offs. This may explain why you did not see a trade-off between growth and carrying capacity in this study. See this paper https://doi.org/10.1038/s41396-023-01543-5. Overall, your evos lineages evolved higher growth rates and lower carrying capacity (Figures 1B, C, E). If selection was driving the evolution of higher growth rates, it may have been that there was no selective pressure to maintain high carrying capacity. This means that the evolutionary change you observed in carrying capacity may have been neutral "drift" of the carrying capacity trait, during selection for growth rate, not because of a trade-off between R and K. This is especially likely since carrying capacity declined during evolution. Unless the authors have convincing evidence for a tradeoff, I suggest they remove this claim.

• Line 96 the authors introduce a previous result where they use colony size to measure growth rate, this finding needs to be properly introduced and explained so that we can understand the context of the conclusion.

• Line 97 This sentence "the collapse of the trade-off law likely resulted from genome reduction." I am not sure how the authors can draw this conclusion, what is the evidence supporting that the genome size reduction causes the breakdown of the tradeoff between R and K (if there was a tradeoff)?

Thank you for the reference information and the thoughtful comments. The recommended paper was newly cited, and the description of the trade-off collapse was deleted. Accordingly, the corresponding paragraph was rewritten as follows.

(L100-115) “Intriguingly, a positive correlation was observed between the growth fitness and the carrying capacity of the Evos (Fig. 1D). It was somehow consistent with the positive correlations between the colony growth rate and the colony size of a genome-reduced strain 11 and between the growth rates and the saturated population size of an assortment of genome reduced strains 13. Nevertheless, the negative correlation between growth rate and carrying capacity, known as the r/K selection30,31 was often observed as the trade-off relationship between r and K in the evolution and ecology studies 32 33,34. As the r/K trade-off was proposed to balance the cellular metabolism that resulted from the cost of enzymes involved 34, the deleted genes might play a role in maintaining the metabolism balance for the r/K correlation. On the other hand, the experimental evolution (i.e., serial transfer) was strictly performed within the exponential growth phase; thus, the evolutionary selection was supposed to be driven by the growth rate without selective pressure to maintain the carrying capacity. The declined carrying capacity might have been its neutral "drift" but not a trade-off to the growth rate. Independent and parallel experimental evolution of the reduced genomes selecting either r or K is required to clarify the actual mechanisms.”

• Line 103 Genome mutations. The authors claim that there are no mutations in parallel but I see that there is a 1199 base pair deletion in eight of the nine evo strains (Table S3). I would like the author to mention this and I'm actually curious about why the authors don't consider this parallel evolution.

Thank you for your careful reading. According to your comment, we added a brief description of the 1199-bp deletion detected in the Evos as follows.

(L119-122) “The number of mutations largely varied among the nine Evos, from two to 13, and no common mutation was detected in all nine Evos (Table S3). A 1,199-bp deletion of insH was frequently found in the Evos (Table S3, highlighted), which well agreed with its function as a transposable sequence.”

• Line 297 Please describe the media in full here - this is an important detail for the evolution experiment. Very frustrating to go to reference 13 and find another reference, but no details of the method. Looked online for the M63 growth media and the carbon source is not specified. This is critical for working out what selection pressures might have driven the genetic and transcriptional changes that you have measured. For example, the parallel genetic change in 8/9 populations is a deletion of insH and tdcD (according to Table S3). This is acetate kinase, essential for the final step in the overflow metabolism of glucose into acetate. If you have a very low glucose concentration, then it could be that there was selection to avoid fermentation and devote all the pyruvate that results from glycolysis into the TCA cycle (which is more efficient than fermentation in terms of ATP produced per pyruvate).

Sorry for the missing information on the medium composition, which was additionally described in the Materials and Methods. The glucose concentration in M63 was 22 mM, which was supposed to be enough for bacterial growth. Thank you for your intriguing thinking about linking the medium component to the genome mutation-mediated metabolic changes. As there was no experimental result regarding the biological function of gene mutation in the present study, please allow us to address this issue in our future work.

(L334-337) “In brief, the medium contains 62 mM dipotassium hydrogen phosphate, 39 mM potassium dihydrogen phosphate, 15 mM ammonium sulfate, 15 μM thiamine hydrochloride, 1.8 μM Iron (II) sulfate, 0.2 mM magnesium sulfate, and 22 mM glucose.”

• Line 115. I do not understand this argument "They seemed highly related to essentiality, as 11 out of 49 mutated genes were essential (Table S3)." Is this a significant enrichment compared to the expectation, i.e. the number of essential genes in the genome? This enrichment needs to be tested with a Hypergeometric test or something similar.

• Also, "As the essential genes were known to be more conserved than nonessential ones, the high frequency of the mutations fixed in the essential genes suggested the mutation in essentiality for fitness increase was the evolutionary strategy for reduced genome." I do not think that there is enough evidence to support this claim, and it should be removed.

Sorry for the unclear description. Yes, the mutations were significantly enriched in the essential genes (11 out of 45 genes) compared to the essential genes in the whole genome (286 out of 3290 genes). The improper description linking the mutation in essential genes to the fitness increase was removed, and an additional explanation on the ratio of essential genes was newly supplied as follows.

(L139-143) “The ratio of essential genes in the mutated genes was significantly higher than in the total genes (286 out of 3290 genes, Chi-square test p=0.008). As the essential genes were determined according to the growth35 and were known to be more conserved than nonessential ones 36,37, the high frequency of the mutations fixed in the essential genes was highly intriguing and reasonable.”

• Line 124 Regarding the mutation simulations, I do not understand how the observed data were compared to the simulated data, and how conclusions were drawn. Can the authors please explain the motivation for carrying out this analysis, and clearly explain the conclusions?

Random simulation was additionally explained in the Materials and Methods and the conclusion of the random simulation was revised in the Results, as follows.

(L392-401) “The mutation simulation was performed with Python in the following steps. A total of 65 mutations were randomly generated on the reduced genome, and the distances from the mutated genomic locations to the nearest genomic scars caused by genome reduction were calculated. Subsequently, Welch's t-test was performed to evaluate whether the distances calculated from the random mutations were significantly longer or shorter than those calculated from the mutations that occurred in Evos. The random simulation, distance calculation, and statistic test were performed 1,000 times, which resulted in 1,000 p values. Finally, the mean of p values (μp) was calculated, and a 95% reliable region was applied. It was used to evaluate whether the 65 mutations in the Evos were significantly close to the genomic scars, i.e., the locational bias.”

(L148-157) “Random simulation was performed to verify whether there was any bias or hotspot in the genomic location for mutation accumulation due to the genome reduction. A total of 65 mutations were randomly generated on the reduced genome (Fig. 2B), and the genomic distances from the mutations to the nearest genome reduction-mediated scars were calculated. Welch's t-test was performed to evaluate whether the genomic distances calculated from random mutations significantly differed from those from the mutations accumulated in the Evos. As the mean of p values (1,000 times of random simulations) was insignificant (Fig. 2C, μp > 0.05), the mutations fixed on the reduced genome were either closer or farther to the genomic scars, indicating there was no locational bias for mutation accumulation caused by genome reduction.”

• Line 140 The authors should give some background here - explain the idea underlying chromosomal periodicity of the transcriptome, to help the reader understand this analysis.

• Line 142 Here and elsewhere, when referring to a method, do not just give the citation, but also refer to the methods section or relevant supplementary material.

The analytical process (references and methods) was described in the Materials and Methods, and the reason we performed the chromosomal periodicity was added in the Results as follows.

(L165-172) “As the E. coli chromosome was structured, whether the genome reduction caused the changes in its architecture, which led to the differentiated transcriptome reorganization in the Evos, was investigated. The chromosomal periodicity of gene expression was analyzed to determine the structural feature of genome-wide pattern, as previously described 28,38. The analytical results showed that the transcriptomes of all Evos presented a common six-period with statistical significance, equivalent to those of the wild-type and ancestral reduced genomes (Fig. 3A, Table S4).”

• Line 151 "The expression levels of the mutated genes were higher than those of the remaining genes (Figure 3B)"- did this depend on the type of mutation? There were quite a few early stops in genes, were these also more likely to be expressed? And how about the transcriptional regulators, can you see evidence of their downstream impact?

Sorry, we didn't investigate the detailed regulatory mechanisms of 49 mutated genes, which was supposed to be out of the scope of the present study. Fig. 3B was the statistical comparison between 3225 and 49 genes. It didn't mean that all mutated genes expressed higher than the others. The following sentences were added to address your concern.

(L181-185) “As the regulatory mechanisms or the gene functions were supposed to be disturbed by the mutations, the expression levels of individual genes might have been either up- or down-regulated. Nevertheless, the overall expression levels of all mutated genes tended to be increased. One of the reasons was assumed to be the mutation essentiality, which remained to be experimentally verified.”

• Line 199 onward. The authors used WGCNA to analyze the gene expression data of evolved organisms. They identified distinct gene modules in the reduced genome, and through further analysis, they found that specific modules were strongly associated with key biological traits like growth fitness, gene expression changes, and mutation rates. Did the authors expect that there was variation in mutation rate across their populations? Is variation from 3-16 mutations that they observed beyond the expectation for the wt mutation rate? The genetic causes of mutation rate variation are well understood, but I could not see any dinB, mutT,Y, rad, or pol genes among the discovered mutations. I would like the authors to justify the claim that there was mutation rate variation in the evolved populations.

Thank you for the intriguing thinking. We don't think the mutation rates were significantly varied across the nine populations, as no mutation occurred in the MMR genes, as you noticed. Our previous study showed that the spontaneous mutation rate of the reduced genome was higher than that of the wild-type genome (Nishimura et al., 2017, mBio). As nonsynonymous mutations were not detected in all nine Evos, the spontaneous mutation rate couldn't be calculated (because it should be evaluated according to the ratio of nonsynonymous and synonymous single-nucleotide substitutions in molecular evolution). Therefore, discussing the mutation rate in the present study was unavailable. The following sentence was added for a better understanding of the gene modules.

(L242-245) “These modules M2, M10 and M16 might be considered as the hotspots for the genes responsible for growth fitness, transcriptional reorganization, and mutation accumulation of the reduced genome in evolution, respectively.”

• Line 254 I get the idea of all roads leading to Rome, which is very fitting. However, describing the various evolutionary strategies and homeostatic and variable consequence does not sound correct - although I am not sure exactly what is meant here. Looking at Figure 7, I will call strategy I "parallel evolution", that is following the same or similar genetic pathways to adaptation and strategy ii I would call divergent evolution. I am not sure what strategy iii is. I don't want the authors to use the terms parallel and divergent if that's not what they mean. My request here would be that the authors clearly describe these strategies, but then show how their results fit in with the results, and if possible, fit with the naming conventions, of evolutionary biology.

Thank you for your kind consideration and excellent suggestion. It's our pleasure to adopt your idea in tour study. The evolutionary strategies were renamed according to your recommendation. Both the main text and Fig. 7 were revised as follows.

(L285-293) “Common mutations22,44 or identical genetic functions45 were reported in the experimental evolution with different reduced genomes, commonly known as parallel evolution (Fig. 7, i). In addition, as not all mutations contribute to the evolved fitness 22,45, another strategy for varied phenotypes was known as divergent evolution (Fig. 7, ii). The present study accentuated the variety of mutations fixed during evolution. Considering the high essentiality of the mutated genes (Table S3), most or all mutations were assumed to benefit the fitness increase, partially demonstrated previously 20. Nevertheless, the evolved transcriptomes presented a homeostatic architecture, revealing the divergent to convergent evolutionary strategy (Fig. 7, iii).”

Author response image 1.

• Line 327 Growth rates/fitness. I don't think this should be called growth fitness- a rate is being calculated. I would like the authors to explain how the times were chosen - do the three points have to be during the log phase? Can you also explain what you mean by choosing three ri that have the largest mean and minor variance?

Sorry for the confusing term usage. The fitness assay was changed to the growth assay. Choosing three ri that have the largest mean and minor variance was to avoid the occasional large values (blue circle), as shown in the following figure. In addition, the details of the growth analysis can be found at https://doi.org/10.3791/56197 (ref. 59), where the video of experimental manipulation, protocol, and data analysis is deposited. The following sentence was added in accordance.

Author response image 2.

(L369-371) “The growth rate was determined as the average of three consecutive ri, showing the largest mean and minor variance to avoid the unreliable calculation caused by the occasionally occurring values. The details of the experimental and analytical processes can be found at https://doi.org/10.3791/56197.”

• Line 403 Chromosomal periodicity analysis. The windows chosen for smoothing (100kb) seem big. Large windows make sense for some things - for example looking at how transcription relates to DNA replication timing, which is a whole-genome scale trend. However, here the authors are looking for the differences after evolution, which will be local trends dependent on specific genes and transcription factors. 100kb of the genome would carry on the order of one hundred genes and might be too coarse-grained to see differences between evos lineages.

Thank you for the advice. We agree that the present analysis focused on the global trend of gene expression. Varying the sizes may lead to different patterns. Additional analysis was performed according to your comment. The results showed that changes in window size (1, 10, 50, 100, and 200 kb) didn't alter the periodicity of the reduced genome, which agreed with the previous study on a different reduced genome MDS42 of a conserved periodicity (Ying et al., 2013, BMC Genomics). The following sentence was added in the Materials and Methods.

(L460-461) “Note that altering the moving average did not change the max peak.”

• Figures - the figures look great. Figure 7 needs a legend.

Thank you. The following legend was added.

(L774-777) “Three evolutionary strategies are proposed. Pink and blue arrowed lines indicate experimental evolution and genome reduction, respectively. The size of the open cycles represents the genome size. Black and grey indicate the ancestor and evolved genomes, respectively.”

Response to Reviewer #2:

Thank you for reviewing our manuscript and for your fruitful comments. We agree that our study leaned towards elaborating observed findings rather than explaining the detailed biological mechanisms. We focused on the genome-wide biological features rather than the specific biological functions. The underlying mechanisms indeed remained unknown, leaving the questions as you commented. We didn't perform the fitness assay on reconstituted (single and combinatorial) mutants because the research purpose was not to clarify the regulatory or metabolic mechanisms. It's why the RNA-Seq analysis provided the findings on genome-wide patterns and chromosomal view, which were supposed to be biologically valuable. We did understand your comments and complaints that the conclusions were biologically meaningless, as ALE studies that found the specific gene regulation or improved pathway was the preferred story in common, which was not the flow of the present study.

For this reason, our revision may not address all these concerns. Considering your comments, we tried our best to revise the manuscript. The changes made were highlighted. We sincerely hope the revision and the following point-to-point response are acceptable.

Major remarks:

(1) The authors outlined the significance of ALE in genome-reduced organisms and important findings from published literature throughout the Introduction section. The description in L65-69, which I believe pertains to the motivation of this study, seems vague and insufficient to convey the novelty or necessity of this study i.e. it is difficult to grasp what aspects of genome-reduced biology that this manuscript intends to focus/find/address.

Sorry for the unclear writing. The sentences were rewritten for clarity as follows.

(L64-70) “Although the reduced growth rate caused by genome reduction could be recovered by experimental evolution, it remains unclear whether such an evolutionary improvement in growth fitness was a general feature of the reduced genome and how the genome-wide changes occurred to match the growth fitness increase. In the present study, we performed the experimental evolution with a reduced genome in multiple lineages and analyzed the evolutionary changes of the genome and transcriptome.”

(2) What is the rationale behind the lineage selection described in Figure S1 legend "Only one of the four overnight cultures in the exponential growth phase (OD600 = 0.01~0.1) was chosen for the following serial transfer, highlighted in red."?

The four wells (cultures of different initial cell concentrations) were measured every day, and only the well that showed OD600=0.01~0.1 (red) was transferred with four different dilution rates (e.g., 10, 100, 1000, and 10000 dilution rates). It resulted in four wells of different initial cell concentrations. Multiple dilutions promised that at least one of the wells would show the OD600 within the range of 0.01 to 0.1 after the overnight culture. They were then used for the next serial transfer. Fig. S1 provides the details of the experimental records. The experimental evolution was strictly controlled within the exponential phase, quite different from the commonly conducted ALE that transferred a single culture in a fixed dilution rate. Serial transfer with multiple dilution rates was previously applied in our evolution experiments and well described in Nishimura et al., 2017, mBio; Lu et al., 2022, Comm Biol; Kurokawa et al., 2022, Front Microbiol, etc. The following sentence was added in the Materials and Methods.

(L344-345) “Multiple dilutions changing in order promised at least one of the wells within the exponential growth phase after the overnight culture.”

(3) The measured growth rate of the end-point 'F2 lineage' shown in Figure S2 seemed comparable to the rest of the lineages (A1 to H2), but the growth rate of 'F2' illustrated in Figure 1B indicates otherwise (L83-84). What is the reason for the incongruence between the two datasets?

Sorry for the unclear description. The growth rates shown in Fig. S2 were obtained during the evolution experiment using the daily transfer's initial and final OD600 values. The growth rates shown in Fig. 1B were obtained from the final population (Evos) growth assay and calculated from the growth curves (biological replication, N=4). Fig. 1B shows the precisely evaluated growth rates, and Fig. S2 shows the evolutionary changes in growth rates. Accordingly, the following sentence was added to the Results.

(L84-87) “As the growth increases were calculated according to the initial and final records, the exponential growth rates of the ancestor and evolved populations were obtained according to the growth curves for a precise evaluation of the evolutionary changes in growth.”

(4) Are the differences in growth rate statistically significant in Figure 1B?

Eight out of nine Evos were significant, except F2. The sentences were rewritten and associated with the revised Fig. 1B, indicating significance.

(L87-90) “The results demonstrated that most evolved populations (Evos) showed improved growth rates, in which eight out of nine Evos were highly significant (Fig. 1B, upper). However, the magnitudes of growth improvement were considerably varied, and the evolutionary dynamics of the nine lineages were somehow divergent (Fig. S2).”

(5) The evolved lineages showed a decrease in their maximal optical densities (OD600) compared to the ancestral strain (L85-86). ALE could accompany changes in cell size and morphologies, (doi: 10.1038/s41586-023-06288-x; 10.1128/AEM.01120-17), which may render OD600 relatively inaccurate for cell density comparison. I suggest using CFU/mL metrics for the sake of a fair comparison between Anc and Evo.

The methods evaluating the carrying capacity (i.e., cell density, population size, etc.) do not change the results. Even using CFU is unfair for the living cells that can not form colonies and unfair if the cell size changes. Optical density (OD600) provides us with the temporal changes of cell growth in a 15-minute interval, which results in an exact evaluation of the growth rate in the exponential phase. CFU is poor at recording the temporal changes of population changes, which tend to result in an inappropriate growth rate. Taken together, we believe that our method was reasonable and reliable. We hope you can accept the different way of study.

(6) Please provide evidence in support of the statement in L115-119. i.e. statistical analysis supporting that the observed ratio of essential genes in the mutant pool is not random.

The statistic test was performed, and the following sentence was added.

(L139-141) “The ratio of essential genes in the mutated genes was significantly higher than in the total genes (286 out of 3290 genes, Chi-square test p=0.008).”

(7) The assumption that "mutation abundance would correlate to fitness improvement" described in L120-122: "The large variety in genome mutations and no correlation of mutation abundance to fitness improvement strongly suggested that no mutations were specifically responsible or crucially essential for recovering the growth rate of the reduced genome" is not easy to digest, in the sense that (i) the effect of multiple beneficial mutations are not necessarily summative, but are riddled with various epistatic interactions (doi: 10.1016/j.mec.2023.e00227); (ii) neutral hitchhikers are of common presence (you could easily find reference on this one); (iii) hypermutators that accumulate greater number of mutations in a given time are not always the eventual winners in competition games (doi: 10.1126/science.1056421). In this sense, the notion that "mutation abundance correlates to fitness improvement" in L120-122 seems flawed (for your perusal, doi: 10.1186/gb-2009-10-10-r118).

Sorry for the improper description and confusing writing, and thank you for the fruitful knowledge on molecular evolution. The sentence was deleted, and the following one was added.

(L145-146) “Nevertheless, it was unclear whether and how these mutations were explicitly responsible for recovering the growth rate of the reduced genome.”

(8) Could it be possible that the large variation in genome mutations in independent lineages results from a highly rugged fitness landscape characterized by multiple fitness optima (doi: 10.1073/pnas.1507916112)? If this is the case, I disagree with the notion in L121-122 "that no mutations were specifically responsible or crucially essential" It does seem to me that, for example, the mutations in evo A2 are specifically responsible and essential for the fitness improvement of evo A2 in the evolutionary condition (M63 medium). Fitness assessment of individual (or combinatorial) mutants reconstituted in the Ancestral background would be a bonus.

Thank you for the intriguing thinking. The sentence was deleted. Please allow us to adapt your comment to the manuscript as follows.

(L143-145) “The large variety of genome mutations fixed in the independent lineages might result from a highly rugged fitness landscape 38.”

(9) L121-122: "...no mutations were specifically responsible or crucially essential for recovering the growth rate of the reduced genome". Strictly speaking, the authors should provide a reference case of wild-type E. coli ALE in order to reach definitive conclusions that the observed mutation events are exclusive to the genome-reduced strain. It is strongly recommended that the authors perform comparative analysis with an ALEed non-genome-reduced control for a more definitive characterization of the evolutionary biology in a genome-reduced organism, as it was done for "JCVI-syn3.0B vs non-minimal M. mycoides" (doi: 10.1038/s41586-023-06288-x) and "E. coli eMS57 vs MG1655" (doi: 10.1038/s41467-019-08888-6).

The improper description was deleted in response to comments 7 and 8. The mentioned references were cited in the manuscript (refs 21 and 23). Thank you for the experimental advice. We are sorry that the comparison of wild-type and reduced genomes was not in the scope of the present study and will probably be reported soon in our future work.

(10) L146-148: "The homeostatic periodicity was consistent with our previous findings that the chromosomal periodicity of the transcriptome was independent of genomic or environmental variation" A Previous study also suggested that the amplitudes of the periodic transcriptomes were significantly correlated with the growth rates (doi: 10.1093/dnares/dsaa018). Growth rates of 8/9 Evos were higher compared to Anc, while that of Evo F2 remained similar. Please comment on the changes in amplitudes of the periodic transcriptomes between Anc and each Evo.

Thank you for the suggestion. The correlation between the growth rates and the amplitudes of chromosomal periodicity was statistically insignificant (p>0.05). It might be a result of the limited data points. Compared with the only nine data points in the present study, the previous study analyzed hundreds of transcriptomes associated with the corresponding growth rates, which are suitable for statistical evaluation. In addition, the changes in growth rates were more significant in the previous study than in the present study, which might influence the significance. It's why we did not discuss the periodic amplitude.

(11) Please elaborate on L159-161: "It strongly suggested the essentiality mutation for homeostatic transcriptome architecture happened in the reduced genome.".

Sorry for the improper description. The sentence was rewritten as follows.

(L191-193) “The essentiality of the mutations might have participated in maintaining the homeostatic transcriptome architecture of the reduced genome.”

(12) Is FPKM a valid metric for between-sample comparison? The growing consensus in the community adopts Transcripts Per Kilobase Million (TPM) for comparing gene expression levels between different samples (Figure 3B; L372-379).

Sorry for the unclear description. The FPKM indicated here was globally normalized, statistically equivalent to TPM. The following sentence was added to the Materials and Methods.

(L421-422) “The resulting normalized FPKM values were statistically equivalent to TPM.”

(13) Please provide % mapped frequency of mutations in Table S3.

They were all 100%. The partially fixed mutations were excluded in the present study. The following sentence was added to the caption of Table S3.

(Supplementary file, p 9) “Note that the entire population held the mutations, i.e., 100% frequency in DNA sequencing.”

(14) To my knowledge, M63 medium contains glucose and glycerol as carbon sources. The manuscript would benefit from discussing the elements that impose selection pressure in the M63 culture condition.

Sorry for the missing information on M63, which contains 22 mM glucose as the only carbon source. The medium composition was added in the Materials and Methods, as follows.

(L334-337) “In brief, the medium contains 62 mM dipotassium hydrogen phosphate, 39 mM potassium dihydrogen phosphate, 15 mM ammonium sulfate, 15 μM thiamine hydrochloride, 1.8 μM Iron (II) sulfate, 0.2 mM magnesium sulfate, and 22 mM glucose.”

(15) The RNA-Seq datasets for Evo strains seemed equally heterogenous, just as their mutation profiles. However, the missing element in their analysis is the directionality of gene expression changes. I wonder what sort of biological significance can be derived from grouping expression changes based solely on DEGs, without considering the magnitude and the direction (up- and down-regulation) of changes? RNA-seq analysis in its current form seems superficial to derive biologically meaningful interpretations.

We agree that most studies often discuss the direction of transcriptional changes. The present study aimed to capture a global view of the magnitude of transcriptome reorganization. Thus, the analyses focused on the overall features, such as the abundance of DEGs, instead of the details of the changes, e.g., the up- and down-regulation of DEGs. The biological meaning of the DEGs' overview was how significantly the genome-wide gene expression fluctuated, which might be short of an in-depth view of individual gene expression. The following sentence was added to indicate the limitation of the present analysis.

(L199-202) “Instead of an in-depth survey on the directional changes of the DEGs, the abundance and functional enrichment of DEGs were investigated to achieve an overview of how significant the genome-wide fluctuation in gene expression, which ignored the details of individual genes.”

Minor remarks

(1) L41: brackets italicized "(E. coli)".

It was fixed as follows.

(L40) “… Escherichia coli (E. coli) cells …”

(2) Figure S1. It is suggested that the x-axis of ALE monitor be set to 'generations' or 'cumulative generations', rather than 'days'.

Thank you for the suggestion. Fig. S1 describes the experimental procedure, so the" day" was used. Fig. S2 presents the evolutionary process, so the "generation" was used, as you recommended here.

(3) I found it difficult to digest through L61-64. Although it is not within the job scope of reviewers to comment on the language style, I must point out that the manuscript would benefit from professional language editing services.

Sorry for the unclear writing. The sentences were revised as follows.

(L60-64) “Previous studies have identified conserved features in transcriptome reorganization, despite significant disruption to gene expression patterns resulting from either genome reduction or experimental evolution 27-29. The findings indicated that experimental evolution might reinstate growth rates that have been disrupted by genome reduction to maintain homeostasis in growing cells.”

(4) Duplicate references (No. 21, 42).

Sorry for the mistake. It was fixed (leaving ref. 21).

(5) Inconsistency in L105-106: "from two to 13".

"From two to 13" was adopted from the language editing. It was changed as follows.

(L119) “… from 2 to 13, …”

Response to Reviewer #3:

Thank you for reviewing our manuscript and for the helpful comments, which improved the strength of the manuscript. The recommended statistical analyses essentially supported the statement in the manuscript were performed, and those supposed to be the new results in the scope of further studies remained unconducted. The changes made in the revision were highlighted. We sincerely hope the revised manuscript and the following point-to-point response meet your concerns. You will find all your suggested statistic tests in our future work that report an extensive study on the experimental evolution of an assortment of reduced genomes.

(1) Line 106 - "As 36 out of 45 SNPs were nonsynonymous, the mutated genes might benefit the fitness increase." This argument can be strengthened. For example, the null expectation of nonsynonymous SNPs should be discussed. Is the number of observed nonsynonymous SNPs significantly higher than the expected one?

(2) Line 107 - "In addition, the abundance of mutations was unlikely to be related to the magnitude of fitness increase." Instead of just listing examples, a regression analysis can be added.

Yes, it's significant. Random mutations lead to ~33% of nonsynonymous SNP in a rough estimation. Additionally, the regression is unreliable because there's no statistical significance between the number of mutations and the magnitude of fitness increase. Accordingly, the corresponding sentences were revised with additional statistical tests.

(L123-129) “As 36 out of 45 SNPs were nonsynonymous, which was highly significant compared to random mutations (p < 0.01), the mutated genes might benefit fitness increase. In addition, the abundance of mutations was unlikely to be related to the magnitude of fitness increase. There was no significant correlation between the number of mutations and the growth rate in a statistical view (p > 0.1). Even from an individual close-up viewpoint, the abundance of mutations poorly explained the fitness increase.”

(3) Line 114 - "They seemed highly related to essentiality, as 11 out of 49 mutated genes were essential (Table S3)." Here, the information mentioned in line 153 ("the ratio of essential to all genes (302 out of 3,290) in the reduced genome.") can be used. Then a statistical test for a contingency table can be used.

(4) Line 117 - "the high frequency of the mutations fixed in the essential genes suggested the mutation in essentiality for fitness increase was the evolutionary strategy for reduced genome." What is the expected number of fixed mutations in essential genes vs non-essential genes? Is the observed number statistically significantly higher?

Sorry for the improper and insufficient information on the essential genes. Yes, it's significant. The statistical test was additionally performed. The corresponding part was revised as follows.

(L134-146) “They seemed highly related to essentiality7 (https://shigen.nig.ac.jp/ecoli/pec/genes.jsp), as 11 out of 49 mutated genes were essential (Table S3). Although the essentiality of genes might differ between the wild-type and reduced genomes, the experimentally determined 302 essential genes in the wild-type E. coli strain were used for the analysis, of which 286 were annotated in the reduced genome. The ratio of essential genes in the mutated genes was significantly higher than in the total genes (286 out of 3290 genes, Chi-square test p=0.008). As the essential genes were determined according to the growth35 and were known to be more conserved than nonessential ones 36,37, the high frequency of the mutations fixed in the essential genes was highly intriguing and reasonable. The large variety of genome mutations fixed in the independent lineages might result from a highly rugged fitness landscape 38. Nevertheless, it was unclear whether and how these mutations were explicitly responsible for recovering the growth rate of the reduced genome.”

(5) The authors mentioned no overlapping in the single mutation level. Is that statistically significant? The authors can bring up what the no-overlap probability is given that there are in total x number of fixed mutations observed (either theory or simulation is good).

Sorry, we feel confused about this comment. It's unclear to us why it needs to be statistically simulated. Firstly, the mutations were experimentally observed. The result that no overlapped mutated genes were detected was an Experimental Fact but not a Computational Prediction. We feel sorry that you may over-interpret our finding as an evolutionary rule, which always requires testing its reliability statistically. We didn't conclude that the evolution had no overlapped mutations. Secondly, considering 65 times random mutations happened to a ~3.9 Mb sequence, the statistical test was meaningful only if the experimental results found the overlapped mutations. It is interesting how often the random mutations cause the overlapped mutations in parallel evolutionary lineages while increasing the evolutionary lineages, which seems to be out of the scope of the present study. We are happy to include the analysis in our ongoing study on the experimental evolution of reduced genomes.

(6) The authors mentioned no overlapping in the single mutation level. How about at the genetic level? Some fixed mutations occur in the same coding gene. Is there any gene with a significantly enriched number of mutations?

No mutations were fixed in the same gene of biological function, as shown in Table S3. If we say the coding region, the only exception is the IS sequences, well known as the transposable sequences without genetic function. The following description was added.

(L119-122) “The number of mutations largely varied among the nine Evos, from 2 to 13, and no common mutation was detected in all nine Evos (Table S3). A 1,199-bp deletion of insH was frequently found in the Evos (Table S3, highlighted), which well agreed with its function as a transposable sequence.”

(7) Line 151-156- It seems like the authors argue that the expression level differences can be just explained by the percentage of essential genes that get fixed mutations. One further step for the argument could be to compare the expression level of essential genes with vs without fixed mutations. Also, the authors can compare the expression level of non-essential genes with vs without fixed mutations. And the authors can report whether the differences in expression level became insignificant after the control of the essentiality.

It's our pleasure that the essentiality intrigued you. Thank you for the analytical suggestion, which is exciting and valuable for our studies. As only 11 essential genes were detected here and "Mutation in essentiality" was an indication but not the conclusion of the present study, we would like to apply the recommended analysis to the datasets of our ongoing study to demonstrate this statement. Thank you again for your fruitful analytical advice.

(8) Line 169- "The number of DEGs partially overlapped among the Evos declined significantly along with the increased lineages of Evos (Figure 4B). " There is a lack of statistical significance here while the word "significantly" is used. One statistical test that can be done is to use re-sampling/simulation to generate a null expectation of the overlapping numbers given the DEGs for each Evo line and the total number of genes in the genome. The observed number can then be compared to the distribution of the simulated numbers.

Sorry for the inappropriate usage of the term. Whether it's statistically significant didn't matter here. The word "significant" was deleted as follows.

(L205--206) “The number of DEGs partially overlapped among the Evos declined along with the increased lineages of Evos (Fig. 4B).”

(9) Line 177-179- "In comparison,1,226 DEGs were induced by genome reduction. The common DEGs 177 of genome reduction and evolution varied from 168 to 540, fewer than half of the DEGs 178 responsible for genome reduction in all Evos" Is the overlapping number significantly lower than the expectation? The hypergeometric test can be used for testing the overlap between two gene sets.

There's no expectation for how many DEGs were reasonable. Not all numbers experimentally obtained are required to be statistically meaningful, which is commonly essential in computational and data science.

(10) The authors should give more information about the ancestral line used at the beginning of experimental evolution. I guess it is one of the KHK collection lines, but I can not find more details. There are many genome-reduced lines. Why is this certain one picked?

Sorry for the insufficient information on the reduced genome used for the experimental evolution. The following descriptions were added in the Results and the Materials and Methods, respectively.

(L75-79) “The E. coli strain carrying a reduced genome, derived from the wild-type genome W3110, showed a significant decline in its growth rate in the minimal medium compared to the wild-type strain 13. To improve the genome reduction-mediated decreased growth rate, the serial transfer of the genome-reduced strain was performed with multiple dilution rates to keep the bacterial growth within the exponential phase (Fig. S1), as described 17,20.”

(L331-334) “The reduced genome has been constructed by multiple deletions of large genomic fragments 58, which led to an approximately 21% smaller size than its parent wild-type genome W3110.”

(11) How was the saturated density in Figure 1 actually determined? In particular, the fitness assay of growth curves is 48h. But it seems like the experimental evolution is done for ~24 h cycles. If the Evos never experienced a situation like a stationary phase between 24-48h, and if the author reported the saturated density 48 h in Figure 1, the explanation of the lower saturated density can be just relaxation from selection and may have nothing to do with the increase of growth rate.

Sorry for the unclear description. Yes, you are right. The evolution was performed within the exponential growth phase (keeping cell division constant), which means the Evos never experienced the stationary phase (saturation). The final evolved populations were subjected to the growth assay to obtain the entire growth curves for calculating the growth rate and the saturated density. Whether the decreased saturated density and the increased growth rate were in a trade-off relationship remained unclear. The corresponding paragraph was revised as follows.

(L100-115) “Intriguingly, a positive correlation was observed between the growth fitness and the carrying capacity of the Evos (Fig. 1D). It was somehow consistent with the positive correlations between the colony growth rate and the colony size of a genome-reduced strain 11 and between the growth rates and the saturated population size of an assortment of genome reduced strains 13. Nevertheless, the negative correlation between growth rate and carrying capacity, known as the r/K selection30,31 was often observed as the trade-off relationship between r and K in the evolution and ecology studies 32 33,34. As the r/K trade-off was proposed to balance the cellular metabolism that resulted from the cost of enzymes involved 34, the deleted genes might play a role in maintaining the metabolism balance for the r/K correlation. On the other hand, the experimental evolution (i.e., serial transfer) was strictly performed within the exponential growth phase; thus, the evolutionary selection was supposed to be driven by the growth rate without selective pressure to maintain the carrying capacity. The declined carrying capacity might have been its neutral "drift" but not a trade-off to the growth rate. Independent and parallel experimental evolution of the reduced genomes selecting either r or K is required to clarify the actual mechanisms.”

(12) What annotation of essentiality was used in this paper? In particular, the essentiality can be different in the reduced genome background compared to the WT background.

Sorry for the unclear definition of the essential genes. They are strictly limited to the 302 essential genes experimentally determined in the wild-type E coli strain. Detailed information can be found at the following website: https://shigen.nig.ac.jp/ecoli/pec/genes.jsp. We agree that the essentiality could differ between the WT and reduced genomes. Identifying the essential genes in the reduced genome will be an exhaustedly vast work. The information on the essential genes defined in the present study was added as follows.

(L134-139) “They seemed highly related to essentiality7 (https://shigen.nig.ac.jp/ecoli/pec/genes.jsp), as 11 out of 49 mutated genes were essential (Table S3). Although the essentiality of genes might differ between the wild-type and reduced genomes, the experimentally determined 302 essential genes in the wild-type E. coli strain were used for the analysis, of which 286 were annotated in the reduced genome.”

(13) The fixed mutations in essential genes are probably not rarely observed in experimental evolution. For example, fixed mutations related to RNA polymerase can be frequently seen when evolving to stressful environments. I think the author can discuss this more and elaborate more on whether they think these mutations in essential genes are important in adaptation or not.

Thank you for your careful reading and the suggestion. As you mentioned, we noticed that the mutations in RNA polymerases (rpoA, rpoB, and rpoD) were identified in three Evos. As they were not shared across all Evos, we didn't discuss the contribution of these mutations to evolution. Instead of the individual functions of the mutated essential gene functions, we focused on the enriched gene functions related to the transcriptome reorganization because they were the common feature observed across all Evos and linked to the whole metabolic or regulatory pathways, which are supposed to be more biologically reasonable and interpretable. The following sentence was added to clarify our thinking.

(L268-273) “In particular, mutations in the essential genes, such as RNA polymerases (rpoA, rpoB, rpoD) identified in three Evos (Table S3), were supposed to participate in the global regulation for improved growth. Nevertheless, the considerable variation in the fixed mutations without overlaps among the nine Evos (Table 1) implied no common mutagenetic strategy for the evolutionary improvement of growth fitness.”

(14) In experimental evolution to new environments, several previous literature also show that long-term experimental evolution in transcriptome is not consistent or even reverts the short-term response; short-term responses were just rather considered as an emergency plan. They seem to echo what the authors found in this manuscript. I think the author can refer to some of those studies more and make a more throughput discussion on short-term vs long-term responses in evolution.

Thank you for the advice. It's unclear to us what the short-term and long-term responses referred to mentioned in this comment. The "Response" is usually used as the phenotypic or transcriptional changes within a few hours after environmental fluctuation, generally non-genetic (no mutation). In comparison, long-term or short-term experimental "Evolution" is associated with genetic changes (mutations). Concerning the Evolution (not the Response), the long-term experimental evolution (>10,000 generations) was performed only with the wild-type genome, and the short-term experimental evolution (500~2,000 generations) was more often conducted with both wild-type and reduced genomes, to our knowledge. Previous landmark studies have intensively discussed comparing the wild-type and reduced genomes. Our study was restricted to the reduced genome, which was constructed differently from those reduced genomes used in the reported studies. The experimental evolution of the reduced genomes has been performed in the presence of additional additives, e.g., antibiotics, alternative carbon sources, etc. That is, neither the genomic backgrounds nor the evolutionary conditions were comparable. Comparison of nothing common seems to be unproductive. We sincerely hope the recommended topics can be applied in our future work.

Some minor suggestions

• Figures S3 & Table S2 need an explanation of the abbreviations of gene categories.

Sorry for the missing information. Figure S3 and Table S3 were revised to include the names of gene categories. The figure was pasted followingly for a quick reference.

Author response image 3.

• I hope the authors can re-consider the title; "Diversity for commonality" does not make much sense to me. For example, it can be simply just "Diversity and commonality."

Thank you for the suggestion. The title was simplified as follows.

(L1) “Experimental evolution for the recovery of growth loss due to genome reduction.”

• It is not easy for me to locate and distinguish the RNA-seq vs DNA-seq files in DRA013662 at DDBJ. Could you make some notes on what RNA-seq actually are, vs what DNA-seq files actually are?

Sorry for the mistakes in the DRA number of DNA-seq. DNA-seq and RNA-seq were deposited separately with the accession IDs of DRA013661 and DRA013662, respectively. The following correction was made in the revision.

(L382-383) “The raw datasets of DNA-seq were deposited in the DDBJ Sequence Read Archive under the accession number DRA013661.”

eLife assessment

This is an important study of the recovery of genome-reduced bacterial cells in laboratory evolution experiments, to understand how they regain their fitness. Through the analysis of gene expression and a series of tests, the authors present convincing evidence indicating distinct molecular changes in the evolved bacterial strains, although the precise mechanisms remain uncharacterized. These findings imply that diverse mechanisms are employed to offset the effects of a reduced genome, offering intriguing insights into genome evolution.

Reviewer #1 (Public Review):

In this study, the authors explored how the reduced growth fitness, resulting from genome reduction, can be compensated through evolution. They conducted an evolution experiment with a strain of Escherichia coli that carried a reduced genome, over approximately 1,000 generations. The authors carried out sequencing, and found no clear genetic signatures of evolution across replicate populations. They carry out transcriptomics and a series of analyses that lead them to conclude that there are divergent mechanisms at play in individual evolutionary lineages. The authors used gene network reconstruction to identify three gene modules functionally differentiated, correlating with changes in growth fitness, genome mutation, and gene expression, respectively, due to evolutionary changes in the reduced genome.

I think that this study addresses an interesting question. Many microbial evolution experiments evolve by loss of function mutations, but presumably a cell that has already lost so much of its genome needs to find other mechanisms to adapt. Experiments like this have the potential to study "constructive" rather than "destructive" evolution.

Comments on revised version:

I think the authors have carefully gone through the manuscript and addressed all of my concerns.

Reviewer #2 (Public Review):

This manuscript describes an adaptive laboratory evolution (ALE) study with a previously constructed genome-reduced E. coli. The growth performance of the end-point lineages evolved in M63 medium was comparable to the full-length wild-type level at lower cell densities.

Subsequent mutation profiling and RNA-Seq analysis revealed many changes on the genome and transcriptomes of the evolved lineages. The authors did a great deal on analyzing the patterns of evolutionary changes between independent lineages, such as the chromosomal periodicity of transcriptomes, pathway enrichment analysis, weight gene co-expression analysis, and so on. They observed a striking diversity in the molecular characteristics amongst the evolved lineages, which, as they suggest, reflect divergent evolutionary strategies adopted by the genome-reduced organism.

As for the overall quality of the manuscript, I am rather torn. The manuscript leans towards elaborating observed findings, rather than explaining their biological significance. For this reason, readers are left with more questions than answers. For example, fitness assay on reconstituted (single and combinatorial) mutants was not performed, nor any supporting evidence on the proposed contributions of each mutants provided. This leaves the nature of mutations - be them beneficial, neutral or deleterious, the presence of epistatic interactions, and the magnitude of fitness contribution, largely elusive. Also, it is difficult to tell whether the RNA-Seq analysis in this study managed to draw biologically meaningful conclusions, or instill insight into the nature of genome-reduced bacteria. The analysis primarily highlighted the differences in transcriptome profiles among each lineage based on metrics such as 'DEG counts' and the 'GO enrichment'. However, I could not see any specific implications regarding the biology of the evolved minimal genome drawn. In their concluding remark, 'Multiple evolutionary paths for the reduced genome to improve growth fitness were likely all roads leading to Rome,' the authors observed the first half of the sentence, but the distinctive characteristics of 'all roads' or 'evolutionary paths', which I think should have been the key aspect in this investigation, remains elusive.

Comments on revised version:

I appreciate the author's responses. They responded to most of the comments, but I still think that there is room for improvement. Please refer to the following comments. Quoted below are the author's responses.

"We agree that our study leaned towards elaborating observed findings rather than explaining the detailed biological mechanisms."<br /> - Comment: I doubt if there are scientific merits in merely elaborating observed findings. The conclusion of this study suggests that evolutionary paths in reduced genomes are highly diverse. But if you think about the nature of adaptive evolution, which relies upon the spontaneous mutation event followed by selection, certain degree of divergence is always expected. The problem with current experimental setting is that there are no ways to quantitively assess whether the degree of evolutionary divergence increases as the function of genome reduction, as the authors claimed. In addition, this notion is in direct contradiction to the prediction that genome reduction constraints evolution by reducing the number of solution space. It is more logical to think and predict that genome reduction would, in turn, lead to the loss of evolutionary divergence. We are also interested to know whether solution space to the optimization problem altered in response to the genome reduction. In this regard, a control ALE experiment on non-reduced wild-type seems to be a mandatory experimental control. I highly suggest that authors present a control experiment, as it was done for "JCVI syn3.0B vs non-minimal M. mycoides" (doi: 10.1038/s41586 023 06288 x) and "E. coli eMS57 vs MG1655" (doi: 10.1038/s41467 019 08888 6).<br /> "We focused on the genome wide biological features rather than the specific biological functions."<br /> - Comment: The 'biological features' delivered in current manuscript does not give insight as to which genomic changes translated into strain fitness improvement. Rather than explaining the genotype-phenotype relationships and/or the mechanistic basis of fitness improvement, authors merely elaborated on the observed phenotypes. I question the scientific merits of such 'findings'.<br /> "Although the reduced growth rate caused by genome reduction could be recovered by experimental evolution, it remains unclear whether such an evolutionary improvement in growth fitness was a general feature of the reduced genome and how the genome wide changes occurred to match the growth fitness increase."<br /> - Comment: This response is very confusing to understand. "it remains unclear whether such an evolutionary improvement in growth fitness was a general feature of the reduced genome" - what aspects remain unclear?? What assumption led the authors to believe that reduced genome's fitness cannot be evolutionarily improved?<br /> - Comment: "and how the genome wide changes occurred to match the growth fitness increase" - this is exactly the aspect that authors should deliver, instead of just elaborating the observed findings. Why don't authors select one or two fastest-growing (or the fittest) lineages and specifically analyze underlying adaptive changes (i.e. genotype-phenotype relationships)?

Author response:

eLife assessment

In this valuable study, Kumar et al., provide evidence suggesting that the p130Cas drives the formation of condensates that sprout from focal adhesions to cytoplasm and suppress translation. Pending further substantiation, this study was found to be likely to provide previously unappreciated insights into the mechanisms linking focal adhesions to the regulation of protein synthesis and was thus considered to be of broad general interest. However, the evidence supporting the proposed model was incomplete; additional evidence is warranted to substantiate the relationship between p130Cas condensates and mRNA translation and establish corresponding functional consequences.

We thank the Elife editorial team for their positive assessment of the broad significance of our manuscript. We fully agree that the functional consequences need to be explored in more detail. We feel that many of the criticisms are valid points that are not easily addressed via available tools, thus, should be considered limitations of present approaches. We hope that readers appreciate that identification of a new class of liquid-liquid phase separations calls for much more work to fully explore their characteristics, regulation and function, which will likely advance many areas of cell biology and perhaps even medicine.

Reviewer #1 (Public Review):

Summary:

The authors demonstrated the phenomenon of p130Cas, a protein primarily localized at focal adhesions, and its formation of condensates. They identified the constituents within the condensates, which include other focal adhesion proteins, paxillin, and RNAs. Furthermore, they proposed a link between p130Cas condensates and translation.

Strengths:

Adhesion components undergo rapid exchange with the cytoplasm for some unclear biological functions. Given that p130Cas is recognized as a prominent mechanical focal adhesion component, investigating its role in condensate formation, particularly its impact on the translation process, is intriguing and significant.

We thank the reviewer for recognizing the functional significance of the work.

Weaknesses:

The authors identified the disordered region of p130Cas and investigated the formation of p130Cas condensate. They attempted to demonstrate that p130Cas condensates inhibit translation, but the results did not fully support this assertion. There are several comments below:

(1) Despite isolating p130Cas-GFP protein using GFP-trap beads, the authors cannot conclusively eliminate the possibility of isolating p130Cas from focal adhesions. While the characterization of the GFP-tagged pulls can reveal the proteins and RNAs associated with p130Cas, they need to clarify their intramolecular mechanism of localization within p130Cas droplets. Whether the protein condensates retain their liquid phase or these GFP-p130Cas pulls represent protein aggregate remains uncertain.

We agree, the isolation from cell lysates does not distinguish between focal adhesions and cytoplasmic LLPS. We note that p130Cas in focal adhesions also appears to be in LLPS. But there are no methods available to isolate them separately. We acknowledge this is a limitation of the study.

(2) The authors utilized hexanediol and ammonium acetate to highlight the phenomenon of p130Cas condensates. Although hexanediol is an inhibitor for hydrophobic interactions and ammonium acetate is a salt, a more thorough explanation of the intramolecular mechanisms underlying p130Cas protein-protein interaction is required. Additionally, given that the size of p130Cas condensates can exceed >100um2, classification is needed to differentiate between p130Cas condensates and protein aggregation.

Ammonium acetate, which works by promoting hydrophobic interactions and weak Van der Waals forces, has been widely used in phase separation studies to change ionic strength without altering intracellular pH. Conversely, hexanediol weakens hydrophobic/ Van der Walls interactions that commonly mediate phase separation of IDRs. In the case of p130Cas, the multiple tyrosines and within the scaffolding domain are obvious targets. If the reviewer is asking us to resolve the detailed hydrophobic interactions within the scaffolding domain, this is far beyond the scope of the current paper.

Protein aggregates are defined by their characteristics (e.g irreversibility, departure from spherical) not by size. Older, larger droplets remain circular and show slower but still measurable rates of exchange. Moreover, droplets are essentially absent after trypsinizing and replating cells. All these results argue against aggregates.

(3) The connection between p130Cas condensates and translation inhibition appears tenuous. The data only suggests a correlation between p130Cas expression and translation inhibition. Further evidence is required to bolster this hypothesis.

The optogenetic experiment shows that triggering LLPS by dimerizing p130Cas results in inhibition of translation. This is a causal not a correlative experiment. The reviewer may be thinking that dimerizing p130Cas could stimulate focal adhesion signaling, activating FAK or a src family kinase or other signals. However, none of these signals has been linked to inhibition of cell growth or migration. Thus, we agree that this is a limitation but consider it a low probability mechanism.

Reviewer #2 (Public Review):

Summary:

In this article, Kumar et al., report on a previously unappreciated mechanism of translational regulation whereby p130Cas induces LLPS condensates that then traffic out from focal adhesion into the cytoplasm to modulate mRNA translation. Specifically, the authors employed EGFP-tagged p130Cas constructs, endogenous p130Cas, and p130Cas knockouts and mutants in cell-based systems. These experiments in conjunction with various imaging techniques revealed that p130Cas drives assembly of LLPS condensates in a manner that is largely independent of tyrosine phosphorylation. This was followed by in vitro EGFP-tagged p130Cas-dependent induction of LLPS condensates and determination of their composition by mass spectrometry, which revealed enrichment of proteins involved in RNA metabolism in the condensates. The authors excluded the plausibility that p130Cas-containing condensates co-localize with stress granules or p-bodies. Next, the authors determined mRNA compendium of p130Cas-containing condensates which revealed that they are enriched in transcripts encoding proteins implicated in cell cycle progression, survival, and cell-cell communication. These findings were followed by the authors demonstrating that p130Cas-containing condensates may be implicated in the suppression of protein synthesis using puromycylation assay. Altogether, it was found that this study significantly advances the knowledge pertinent to the understanding of molecular underpinnings of the role of p130Cas and more broadly focal adhesions on cellular function, and to this end, it is likely that this report will be of interest to a broad range of scientists from a wide spectrum of biomedical disciplines including cell, molecular, developmental and cancer biologists.

Strengths:

Altogether, this study was found to be of potentially broad interest inasmuch as it delineates a hitherto unappreciated link between p130Cas, LLPS, and regulation of mRNA translation. More broadly, this report provides unique molecular insights into the previously unappreciated mechanisms of the role of focal adhesions in regulating protein synthesis. Overall, it was thought that the provided data sufficiently supported most of the authors' conclusions. It was also thought that this study incorporates an appropriate balance of imaging, cell and molecular biology, and biochemical techniques, whereby the methodology was found to be largely appropriate.

We thank reviewer for this positive assessment.

Weaknesses:

Two major weaknesses of the study were noted. The first issue is related to the experiments establishing the role of p130Cas-driven condensates in translational suppression, whereby it remained unclear whether these effects are affecting global mRNA translation or are specific to the mRNAs contained in the condensates. Moreover, some of the results in this section (e.g., experiments using cycloheximide) may be open to alternative interpretation. The second issue is the apparent lack of functional studies, and although the authors speculate that the described mechanism is likely to mediate the effects of focal adhesions on e.g., quiescence, experimental testing of this tenet was lacking.

We appreciate the reviewer’s insights. Assessing translational inhibition for specific genes rather than global measurement of translation is an important direction for future work.

Regarding the cycloheximide experiments, we are unsure what the reviewer means. We used it as a control for puromycin labeling but this is a very standard approach. It seems more likely that the question concerns Fig 5G, where we used it to sequester mRNAs on ribosomes to deplete from other pools. In this case, p130cas condensates decrease after 2 minutes. The reviewer may be suggesting that this effect could be due to blocked translation per se and loss of short-lived proteins. We acknowledge that this is possible but given the very rapid effect (2 min), we think it unlikely.

Lastly, we agree with the reviewer that further functional studies in quiescence or senescence are warranted; however, these are extensive, open-ended studies and we will not be able to include them as part of the current paper.

Author response:

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

eLife assessment

In this valuable study, the authors investigate the transcriptional landscape of tuberculous meningitis, revealing important molecular differences contributed by HIV co-infection. Whilst some of the evidence presented is compelling, the bioinformatics analysis is limited to a descriptive narrative of gene-level functional annotations, which are somewhat basic and fail to define aspects of biology very precisely. Whilst the work will be of broad interest to the infectious disease community, validation of the data is critical for future utility.

We appreciate with eLife’s positive assessment, although we challenge the conclusion that we ‘fail to define aspects of biology very precisely’. Our stated objective was to use bioinformatics tools to identify the biological pathways and hub genes associated with TBM pathogenesis and the eLife assessment affirms we have investigated ‘the transcriptional landscape of tuberculous meningitis’. To more precisely define aspects of the biology will require another study with different design and methods.

Reviewer #1 (Public Review):

Summary:

Tuberculous meningitis (TBM) is one of the most severe forms of extrapulmonary TB. TBM is especially prevalent in people who are immunocompromised (e.g. HIV-positive). Delays in diagnosis and treatment could lead to severe disease or mortality. In this study, the authors performed the largest-ever host whole blood transcriptomics analysis on a cohort of 606 Vietnamese participants. The results indicated that TBM mortality is associated with increased neutrophil activation and decreased T and B cell activation pathways. Furthermore, increased angiogenesis was also observed in HIV-positive patients who died from TBM, whereas activated TNF signaling and down-regulated extracellular matrix organisation were seen in the HIV-negative group. Despite similarities in transcriptional profiles between PTB and TBM compared to healthy controls, inflammatory genes were more active in HIV-positive TBM. Finally, 4 hub genes (MCEMP1, NELL2, ZNF354C, and CD4) were identified as strong predictors of death from TBM.

Strengths:

This is a really impressive piece of work, both in terms of the size of the cohort which took years of effort to recruit, sample, and analyse, and also the meticulous bioinformatics performed. The biggest advantage of obtaining a whole blood signature is that it allows an easier translational development into a test that can be used in the clinical with a minimally invasive sample. Furthermore, the data from this study has also revealed important insights into the mechanisms associated with mortality and the differences in pathogenesis between HIV-positive and HIV-negative patients, which would have diagnostic and therapeutic implications.

Weaknesses:

The data on blood neutrophil count is really intriguing and seems to provide a very powerful yet easy-to-measure method to differentiate survival vs. death in TBM patients. It would be quite useful in this case to perform predictive analysis to see if neutrophil count alone, or in combination with gene signature, can predict (or better predict) mortality, as it would be far easier for clinical implementation than the RNA-based method. Moreover, genes associated with increased neutrophil activation and decreased T cell activation both have significantly higher enrichment scores in TBM (Figure 9) and in morality (Figure 8). While I understand the basis of selecting hub genes in the significant modules, they often do not represent these biological pathways (at least not directly associated in most cases). If genes were selected based on these biologically relevant pathways, would they have better predictive values?

We conducted a sensitivity analysis including blood neutrophil as a potential predictor in the multivariate Cox elastic-net regression model for important predictor selection (Table S14). In this analysis, all six selected important predictors (genes and clinical risk factors) identified in the original analysis (Table S13) were also selected, together with blood neutrophil number. Additionally, we evaluated the predictive value of blood neutrophil alone, which demonstrated poor performance, with an optimism-corrected AUC of 0.63 for all TBM, 0.67 for HIV-negative TBM, and 0.70 for HIV-positive TBM. Even when combined with identified gene signatures, blood neutrophil did not improve the overall performance of predictive model (optimism-corrected AUC of 0.79 for all TBM, 0.76 for HIV-negative TBM, and 0.80 for HIV-positive). These results indicate that identified hub genes exhibit better predictive values compared to blood neutrophil alone or in combination. These findings have been incorporated into our manuscript results.

To test whether pathway representative genes have better predictive values than hub genes, we included all these genes in the analysis for important predictor selection. Pathway representative genes comprised ANXA3 and CXCR2 representing neutrophil activation and IL1b representing acute inflammatory response. We observed that all hub genes (MCEMP1, NELL2, ZNF354C, and CD4) consistently emerged as the most important genes with the highest selection in the models, compared to the rest, in both the HIV-negative TBM and HIV-positive TBM cohorts. Additionally, these identified hub genes were still selected when testing together with other hub genes representing relevant biological pathways associated with TBM mortality, such as CYSTM1 involved in neutrophil activation, TRAF5 involved in NF-kappa B signaling pathway, CD28 and TESPA1 involved in T cell receptor signaling. These results show that selected genes based on known biologically relevant pathways did not give better predictive values than the identified hub genes in the significant modules.

Reviewer #2 (Public Review):

Summary:

This manuscript describes the analysis of blood transcriptomic data from patients with TB meningitis, with and without HIV infection, with some comparison to those of patients with pulmonary tuberculosis and healthy volunteers. The objectives were to describe the comparative biological differences represented by the blood transcriptome in TBM associated with HIV co-infection or survival/mortality outcomes and to identify a blood transcriptional signature to predict these outcomes. The authors report an association between mortality and increased levels of acute inflammation and neutrophil activation, but decreased levels of adaptive immunity and T/B cell activation. They propose a 4-gene prognostic signature to predict mortality.

Strengths:

Biological evaluations of blood transcriptomes in TB meningitis and their relationship to outcomes have not been extensively reported previously.

The size of the data set is a major strength and is likely to be used extensively for secondary analyses in this field of research.

Weaknesses:

The bioinformatic analysis is limited to a descriptive narrative of gene-level functional annotations curated in GO and KEGG databases. This analysis cannot be used to make causal inferences. In addition, the functional annotations are limited to 'high-level' terms that fail to define biology very precisely. At best, they require independent validation for a given context. As a result, the conclusions are not adequately substantiated. The identification of a prognostic blood transcriptomic signature uses an unusual discovery approach that leverages weighted gene network analysis that underpins the bioinformatic analyses. However, the main problem is that authors seem to use all the data for discovery and do not undertake any true external validation of their gene signature. As a result, the proposed gene signature is likely to be overfitted to these data and not generalisable. Even this does not achieve significantly better prognostic discrimination than the existing clinical scoring.

As explained in response to the eLife assessment, our objective was to use bioinformatics tools to identify the biological pathways and hub genes associated with TBM pathogenesis. We agree that ‘This analysis cannot be used to make causal inferences’: that would require different study design and approaches. The proposed gene signature has higher AUC values than the existing clinical model alone or in combination with clinical risk factors (Table 4). We agree that independent validation of the gene signature will be a crucial next step for future utility. We have performed qPCR in another sample set, and have added these results in the revision (Table 4 and supplementary figure S8)

Reviewer #1 (Recommendations For The Authors):

I have a few additional comments most of which are relatively minor:

(1) Can the authors please clarify if all the PTB cases are also HIV-negative?

This has been added to the methods section.

(2) For Table 1, can the authors please list the total number of patients with microbiologically confirmed TB regardless of the methods used? And for the two TBM groups, was the positive microbiology based on CSF findings?

The total number of patients with microbiologically confirmed TB was presented in Table 2 in definite TBM group, which was microbiologically confirmed TB diagnosed using microscopy, culture, and Xpert testing in cerebrospinal fluid (CSF) samples. We have updated the note in Table 2 to provide clarity on the definition.

(3) How was the discovery and validation set selected? Was it based on randomisation?

We randomly split TBM data into two datasets, a discovery cohort (n=142) and a validation cohort (n=139) with a purpose to ensure reproducibility of data analysis. We described this in the methods section.

(4) Line 107 can be better clarified by stating that the overall 3-month mortality rate is 21.7% for TBM regardless of HIV status.

Thank you, we have restated this sentence in the results section.

(5) The authors stated that samples were collected at enrolment when patients would have received less than 6 days of anti-tubercular treatment. Is there information on the median and IQR on the number of days that the patients would have received Rx, especially between the groups? Did the authors control for this variable when analysing for DEGs?

One of criteria to enroll participants in LAST-ACT and ACT-HIV trials is that they must receive less than 6 consecutive days of two or more drugs active against M. tuberculosis. However, the information of the days that the patients would have received Rx was not recorded and we could not control this variable when performing differential expression analysis for DEGs. This has been clarified further in the methods section: ‘The samples were taken at enrollment, when patients could not have received more than 6 consecutive days of two or more drugs active against M. tuberculosis.’

(6) I am a little bit concerned with the reads mapping accuracy (57%) to the human genome, which is fairly low. Did the authors investigate the reasons behind this low accuracy?

Thank you. It was indeed a typo. We have corrected it in the results section.

(7) On Tables S2-S4, can the authors please clarify what the last column (labelled as "B") shows?

Tables S2-S4 now have been changed to S3-S5. We have updated the legend of these tables to provide clarification regarding the meaning of the last column.

Reviewer #2 (Recommendations For The Authors):

If the authors wish to revise their manuscript, I suggest the following amendments:

(1) Provide a consort diagram for the selection of samples included in the present analysis (from parent study cohorts), allocation to test and validation splits for bioinformatics analysis, and outcomes.

We have provided our consort diagram in supplementary Figure S10.

(2) Provide details of inclusion criteria for pulmonary TB cohort, and how samples from this cohort were selected for inclusion in the present analysis. Please clarify whether this cohort excluded HIV-positive participants by design or by chance.

The inclusion criteria for the pulmonary TB cohort were described in the methods section. Due to the very low prevalence of HIV in this prospective observational study, HIV-positive participants were excluded. We have clarified in the amended manuscript that the pulmonary TB cohort only included HIV-negative participants.

(3) Baseline characteristics of HIV-positive participants (Table 1) should include CD4 count, HIV viral load, and whether anti-retroviral therapy was naïve or experienced.

We have included pre-treatment CD4 cell count, information on anti-retroviral therapy, and HIV viral load data in Table 1, as well as described these information in the results section.

(4) I note that the TBM samples were derived from RCTs of adjunctive steroid therapy, but not stratified in the present analysis by treatment arm allocation. Clearly, this may affect the survival/mortality outcomes that are the central focus of this manuscript. Therefore, they should be included in the models for differential gene expression analysis and prognostic signature discovery. To do so, the authors may need to wait until they are able to unblind the trial metadata.

With permission from the trial investigators, we were able to adjust the analyses for treatment with corticosteroids. The investigators remained blind to the allocation and we have not reported any direct effects of corticosteroids on outcome – such an analysis could only be done once the LAST-ACT trial has been reported (which won’t be until the end of 2024). Treatment outcome and effect were blinded by extracting only the fold change difference between survival and death in the linear regression model, in which gene expression was outcome and survival and treatment were covariates.

(5) I understood from the methods (lines 460-461) that batch correction of the RNAseq data was necessary. However, it is not clear how the samples were batched. PCA of the transcriptomes before and after batch correction with batch and study group labels should be provided. I would also advocate for a sensitivity analysis to check the robustness of the main findings without batch correction. I assume Fig2A represents batch-corrected data, but this is not clear.

We have now added information about the RNA sequencing batch and the batch correction approach, analyses and data visualizations utilized batch-corrected data in the methods section. We have also updated results related to batch correction in Fig. 2A and Supplementary Figure S9.

(6) I would encourage the authors to include a differential gene expression analysis to directly compare the transcriptome of TBM to that of pulmonary TB. I think it would add additional value to their focus on describing the transcriptome in TBM.

We thank for reviewer’s suggestion. Conducting differential gene expression analysis to compare the transcriptome of TBM with that of PTB is beyond the scope of this manuscript and we will examine this question separately.

(7) I don't really understand the purpose of splitting their data set into test and validation for the purposes of showing that WGCNA analysis is mostly reproduced in the two halves of the data. I would advocate that they scrap this approach to maximise the statistical power of their analysis in the descriptive work.

As mentioned in response to reviewer #1 in question #3, the purpose of splitting data is to ensure the reproducibility of the data analysis as suggested by Langfelder et al. (PMID: 21283776). This approach served two purposes: (i) to affirm the existence of functional modules in an independent cohort and (ii) to validate the association of interested modules or their hub genes with survival outcomes.

(8) The authors should soften the confidence in their interpretation of the GO/KEGG annotations of WGCNA modules. At least, they should include a paragraph that explicitly details the limitations of their analyses, including (i) the accuracy GO/KEGG annotations are not validated in this context (if at all), (ii) that none of the data can be used to make causal inferences and (iii) that peripheral blood assessments that are obviously impacted by changes in cellular composition of peripheral blood do not necessarily reflect immunopathogenesis at the site of disease - in fact if circulating cells are being recruited to the site of disease or other immune compartments, then quite the opposite interpretations may be true.

We appreciate the reviewer's comment. (i) In our analysis, we initially confirmed the existence of Weighted Gene Co-expression Network Analysis (WGCNA) modules in discovery cohort and validated the association of these modules with mortality outcomes in validation cohort. We then applied GO/KEGG annotations to define the biological functions involved in WGCNA modules. Finally, we performed Qusage analysis to directly test the association of top-hit pathways of each WGCNA module with mortality outcomes (see supplementary S6). This analysis approach helped to identify and validate modules and biological pathways associated with TBM mortality in this context, avoiding potential false positives in GO/KEGG annotations of WGCNA modules. (ii) We agree with the assessment that 'This analysis cannot be used to make causal inferences,' as that would require a different study design and approach. (iii) The focus of this study is to investigate the pathogenesis of TBM in the systemic immune system. We have highlighted this focus in the title and the aim of the manuscript.

(9) For the prognostic signature discovery and validation, I strongly recommend the authors include more robust validation. For example, to undertake an 80:20 split for sequential discovery (for feature selection and derivation of a prognostic model), followed by validation of a 'locked' model in data that made no contribution to discovery. In two separate sensitivity analyses. I also suggest they split their dataset (i) by treatment allocation in the RCT and (ii) by HIV status. In addition, their method for feature selection has to be clearer- precisely how they select hub genes from their WGCNA analysis as candidate predictors is not explained. Since this is such a prominent output of their manuscript, the results of this analysis should really be included in the main manuscript, and all performance metrics for discrimination should include confidence intervals.

Employing an 80:20 split for training and testing models is a good approach for an internal validation. However, we addressed the issue of overestimating the performance of a prognostic model by bootstrapping sampling approach proposed by Steyerberg et al. (PMID: 11470385). This approach has been proven to provide stable estimates with low bias. The overall model performance for discrimination, reported in our manuscript, was corrected for “optimism” to ensure internal validity. This adjustment was achieved through a 1000-times bootstrapping approach, which effectively accounted for estimation uncertainty. As such, there is no need to present confidence intervals for these metrics.

Moreover, in our revision, to confirm prognostic signatures independently, we have evaluated the predictive value of identified gene signatures using qPCR in another set of samples. The results have been added in Table 4, supplementary Figure S8 and the results section.

For the reasons given above (comment 4), we are unable to split our dataset by treatment allocation in this analysis. But as described, we have adjusted the analysis for corticosteroid treatment. Once the primary results of the LAST ACT trial have been published, we will examine the impact of corticosteroids on TBM pathophysiology and outcomes, seeking to better understand the mechanisms by which steroids have their therapeutic effects.

Given the difference in pathogenesis and immune response by HIV-coinfection, we stratified our analysis by HIV status. As the reviewer’s suggestion, we have provided additional details in the methods section regarding the selection of hub genes from associated WGCNA modules and the feature selection process for predictive modeling.

eLife assessment

In this valuable study, the authors investigate the transcriptional landscape of tuberculous meningitis. They reveal potentially significant molecular differences contributed by HIV co-infection, and derive a prognostic model to predict mortality combining a gene expression signature with clinical parameters. Whilst some of the evidence presented is compelling, the bioinformatics analysis remains limited and cannot be used to make causal inferences and conclusions about immunopathogenesis for tuberculous meningitis. The work will be of broad interest to the infectious disease community however, further validation of the findings is critical for future utility.

Reviewer #1 (Public Review):

Summary:

Tuberculous meningitis (TBM) is one of the most severe form of extrapulmonary TB. TBM is especially prevalent in people who are immunocompromised (e.g. HIV-positive). Delays in diagnosis and treatment could lead to severe disease or mortality. In this study, the authors performed the largest ever host whole blood transcriptomics analysis on a cohort of 606 Vietnamese participants. The results indicated that TBM mortality is associated with increased neutrophil activation and decreased T and B cell activation pathways. Furthermore, increased angiogenesis was also observed in HIV-positive patients who died from TBM, whereas activated TNF signaling and down-regulated extracellular matrix organisation were seen in the HIV-negative group. Despite similarities in transcriptional profiles between PTB and TBM compared to healthy controls, inflammatory genes were more active in HIV-positive TBM. Finally, 4 hub genes (MCEMP1, NELL2, ZNF354C and CD4) were identified as strong predictors of death from TBM.

Strengths:

This is a really impressive piece of work, both in terms of the size of the cohort which took years of effort to recruit, sample and analyse and also the meticulous bioinformatics performed. The biggest advantage of obtaining a whole blood signature is that it allows an easier translational development into test that can be used in the clinical with a minimally invasive sample. Furthermore, the data from this study has also revealed important insights in the mechanisms associated with mortality and the differences in pathogenesis between HIV-positive and HIV-negative patients, which would have diagnostic and therapeutic implications.

Weaknesses:

The authors have addressed all the weaknesses in the revised version.

Reviewer #2 (Public Review):

Summary:

This manuscript describes the analysis of blood transcriptomic data from patients with TB meningitis, with and without HIV infection, with some comparison to those of patients with pulmonary tuberculosis and healthy volunteers. The objectives were to describe the comparative biological differences represented by the blood transcriptome in TBM associated with HIV co-infection or survival/mortality outcomes, and to identify a blood transcriptional signature to predict these outcomes. The authors report an association between mortality and increased levels of acute inflammation and neutrophil activation, but decreased levels of adaptive immunity and T/B cell activation. They propose a 4-gene prognostic signature to predict mortality.

Strengths:

Biological evaluations of blood transcriptomes in TB meningitis and their relationship to outcomes have not been extensively reported previously.<br /> The size of the data set is a major strength and is likely to be used extensively for secondary analyses in this field of research.<br /> The addition of a new validation cohort to evaluate the generalisability of their prognostic model in the revised manuscript is welcome.

Weaknesses:

The bioinformatic analysis is limited to a descriptive narrative of gene-level functional annotations curated in GO and KEGG databases. This analysis cannot be used to make causal inferences. In addition the functional annotations are limited to 'high-level' terms that fail to define the biology very precisely. As a result, the conclusions about the immunopathogenesis of TBM are not adequately substantiated.<br /> The lack of AUROC confidence intervals and direct comparison to the reference prognostic model in the validation cohort undermines confidence in their conclusion that their new prognostic model combing gene expression data and clinical variables performs better than the reference model.

Author response:

The following is the authors’ response to the previous reviews

We extend our sincere gratitude for the invaluable comments provided by the reviewers and yourself, along with the constructive suggestions to enhance the quality of our manuscript. In response to this invaluable feedback, we have diligently revised and resubmitted our paper as an article, introducing five primary figures, seven supplementary figures, and two supplementary data files. Importantly, this work represents a significant contribution to the field, presenting novel findings for the first time without any prior publication.

Within the enclosed document, we have provided a comprehensive response to the editor and reviewer comments, addressing each point meticulously and specifically. We extend our heartfelt thanks to the reviewers and yourself for your diligent examination of our manuscript and for offering insightful recommendations.

In our latest revision, we have taken great care to address every comment, ensuring that we clarify the manuscript and provide robust evidence where required. We have meticulously highlighted the modifications within the manuscript in yellow for your convenience, while also including the modifications made in response to each specific comment. The primary focus of these revisions was to provide additional context regarding the relationship between PARP-1 and mono-methylated histones. Substantial modifications were made to our discussion section to address this point.

Another concern raised was regarding the discrepancy in the relationship of PR-SET7 and PARP-1 between our study and the recent study by Estève et al. (PMID: 36434141). We have revised the results and discussion sections to discuss this concern.

Addressing Reviewer 2’s concern about the potential indirect role of PARP1 in the regulation of some metabolic genes despite its direct binding to loci coding for metabolic genes we revised the discussion section to highlight this possibility.

Enclosed, you will find a detailed, point-by-point response to each of the editor’s and reviewers' comments, showcasing our commitment to addressing their concerns with precision.

We firmly believe that our revisions successfully resolve all the concerns raised by the editor and the reviewers, and we are confident that this improved version of our manuscript contributes significantly to the scientific discourse. Once again, we thank you for considering our work, and please feel free to contact me if you require any additional information.

In the revised manuscript, most of the concerns raised by the reviewers have been addressed satisfactorily. However, as suggested by reviewer#2, it would have been more significant, if the PARP1-mediated reading of global mono-methylation of histone could be addressed. At least the mechanisms of selectivity of PARP1 need further convincing discussion.

We thank the editor for their valuable comments. We have extended our discussion section to discuss in more detail the relationship between PARP1 and mono-methylated histones. In our refined Discussion section, we have endeavored to articulate more clearly how PARP-1 may be selectively recruited to active chromatin domains through its interaction with mono-methylated histone marks. We propose a model wherein PARP-1 actively participates in the turnover process, contributing to the maintenance of an active chromatin environment. This mechanism entails PARP-1 selectively binding to mono-methylated active histone marks associated with highly transcribed genes. Upon activation, PARP-1 undergoes automodification, leading to its release from chromatin and facilitating the reassembly of nucleosomes carrying the mono-methylated marks. Subsequently, the enzymatic action of Poly(ADP)-ribose glycohydrolase (PARG) cleaves pADPr, enabling the restoration of PARP-1's binding affinity to mono-methylated active histone marks. This proposed hypothesis is consistent with existing research across various model organisms and aligns with the known association of PARP-1 with highly expressed genes, as well as its role in mediating nucleosome dynamics and assembly.

Our modified Discussion section unfolds as follows:

"Finally, highly transcribed genes have been reported to present a high turnover of mono-methylated modifications, maintaining a state of low methylation (50). Moreover, our previous study revealed that PARP1 preferentially binds to highly active genes (34).  Consequently, our findings suggest an active involvement of PARP-1 in the turnover process to maintain an active chromatin environment. This proposed mechanism unfolds in the following steps: 1) PARP-1 selectively binds to mono-methylated active histone marks associated with highly transcribed genes. 2) Upon activation, PARP-1 undergoes automodification and subsequently disengages from chromatin, facilitating the reassembly of nucleosomes carrying the mono-methylated marks. 3) The enzymatic action of Poly(ADP)-ribose glycohydrolase (PARG) cleaves pADPr, restoring PARP-1's binding affinity to mono-methylated active histone marks. This proposed hypothesis is consistent with existing research conducted across various model organisms, including mice, Drosophila, and Humans (7, 24, 30, 51-53). Notably, previous studies have consistently demonstrated that PARP-1 predominantly associates with highly expressed genes and plays a crucial role in mediating nucleosome dynamics and assembly. Thus, our proposed model provides a molecular framework that may contribute to understanding the relationship between PARP-1 and the epigenetic regulation of gene expression."

We trust that these revisions effectively address the editor’s comment and enhance the overall strength and clarity of our manuscript.

Furthermore, recent developments in the area are omitted, as an important publication hasn't been discussed anywhere in the work (PMID: 36434141).

We appreciate the editor's thorough review of our revised manuscript and the responses to the previous reviewer's comments. To address this important concern, we have carefully investigated the levels of PR-SET7 in parp1 hypomorphic conditions.

Supplemental Fig. S4 and S5 demonstrate that in the absence of Parp1, there were no significant changes observed in PR-SET7 RNA or protein levels, respectively. This finding supports the conclusion that Parp1 is not directly involved in the regulation of PR-SET7 in Drosophila contrasting with the findings of Estève et al.'s study (PMID: 36434141). This discrepancy may arise from differing relationships between PARP-1 and PR-SET7, which could cooperate in the context of Drosophila development while playing antagonistic roles in specific cell lines or under particular conditions.

We have updated the Results section to explicitly mention this observation:

"Interestingly, in the absence of PARP-1, neither PR-SET7 RNA nor protein levels were affected (Supplemental Fig.S4-5), indicating that PARP-1 is not directly implicated in the regulation of pr-set7. This finding contrasts with recent evidence demonstrating PARP1-induced degradation of PR-SET7/SET8 in human cells (16)."

Furthermore, we have modified the discussion section to address this discrepancy:

"A recent study demonstrated that in human cells overexpressing PARP-1, PR-SET7/SET8 is degraded, whereas depletion of PARP-1 leads to an increase in PR-SET7/SET8 levels (16). However, in our study involving parp-1 mutant in Drosophila third-instar larvae revealed a nuanced scenario: we detected a minor but not significant reduction in both PR-SET7 RNA and protein levels (Supplemental Fig.S4 and S5). This outcome stands in stark contrast to the previous study's findings. The discrepancy could be due to the distinct experimental approaches used: the previous research focused on mammalian cells and in vitro experiments, whereas our study examined the functions of PARP-1 in whole Drosophila third-instar larvae during development. Consequently, while PARP-1 may cooperate with PR-SET7 in the context of Drosophila development, it could exhibit antagonistic roles against PR-SET7 in specific cell lines and under certain biological or developmental conditions."

We believe that these modifications effectively address the raised concern and provide a more comprehensive understanding of the relationship between PARP1 and PR-SET7 in our study. We hope these clarifications enhance the overall robustness and clarity of our findings.

Reviewer #2 (Public Review):

Summary:

This study from Bamgbose et al. identifies a new and important interaction between H4K20me and Parp1 that regulates inducible genes during development and heat stress. The authors present convincing experiments that form a mostly complete manuscript that significantly contributes to our understanding of how Parp1 associates with target genes to regulate their expression.

Strengths:

The authors present 3 compelling experiments to support the interaction between Parp1 and H4K20me, including:

(1) PR-Set7 mutants remove all K4K20me and phenocopy Parp mutant developmental arrest and defective heat shock protein induction.

(2) PR-Set7 mutants have dramatically reduced Parp1 association with chromatin and reduced poly-ADP ribosylation.

(3) Parp1 directly binds H4K20me in vitro.

Weaknesses:

(1) The RNAseq analysis of Parp1/PR-Set7 mutants is reasonable, but there is a caveat to the author's conclusion (Line 251): "our results indicate H4K20me1 may be required for PARP-1 binding to preferentially repress metabolic genes and activate genes involved in neuron development at co-enriched genes." An alternative possibility is that many of the gene expression changes are indirect consequences of altered development induced by Parp1 or PR-Set7 mutants. For example, Parp1 could activate a transcription factor that represses metabolic genes. The authors counter this model by stating that Parp1 directly binds to "repressed" metabolic genes. While this argument supports their model, it does not rule out the competing indirect transcription factor model. Therefore, they should still mention the competing model as a possibility.

We appreciate Reviewer 2's insightful comments during both rounds of revision, which have significantly enriched the quality of our manuscript. The binding of PARP1 to loci encoding metabolic genes indeed suggests a direct role of PARP1 in their regulation. However, we acknowledge Reviewer 2's point that some of these targets might be regulated indirectly, with PARP1 potentially modulating the expression of intermediary transcription factors.

To address this possibility, we have revised the discussion section of our manuscript accordingly:

"Remarkably, our observations indicate a notable affinity of PARP-1 for binding to the gene bodies of these metabolic genes (34), suggesting a direct involvement of PARP1 in their regulation. Nonetheless, it remains plausible that certain genes may be indirectly regulated by PARP1 through intermediary transcription factors."

We trust that this modification adequately addresses Reviewer 2's concern.

(2) The section on inducibility of heat shock genes is interesting but missing an important control that might significantly alter the author's conclusions. Hsp23 and Hsp83 (group B genes) are transcribed without heat shock, which likely explains why they have H4K20me without heat shock. The authors made the reasonable hypothesis that this H4K20me would recruit Parp-1 upon heat shock (line 270). However, they observed a decrease of H4K20me upon heat shock, which led them to conclude that "H4K20me may not be necessary for Parp1 binding/activation" (line 275). However, their RNA expression data (Fig4A) argues that both Parp1 and H40K20me are important for activation. An alternative possibility is that group B genes indeed recruit Parp1 (through H4K20me) upon heat shock, but then Parp1 promotes H3/H4 dissociation from group B genes. If Parp1 depletes H4, it will also deplete H4K20me1. To address this possibility, the authors should also do a ChIP for total H4 and plot both the raw signal of H4K20me1 and total H4 as well as the ratio of these signals. The authors could also note that Group A genes may similarly recruit Parp1 and deplete H3/H4 but with different kinetics than Group B genes because their basal state lacks H4K20me/Parp1. To test this possibility, the authors could measure Parp association, H4K20methylation, and H4 depletion at more time points after heat shock at both classes of genes.

We sincerely appreciate Reviewer 2 for their insightful comment on our manuscript. Your hypothesis regarding the potential induction of H3/H4 dissociation from group B genes by PARP-1, leading to a reduction in H4K20me1, offers a thought-provoking perspective. However, our findings suggest an alternative interpretation.

Our data indicate that while H4K20me1 is indeed present under normal conditions at group B genes, its reduction following heat shock does not seem to impede PARP-1's role in transcriptional activation (Fig. 4A, C, and E). Instead, we propose that this decrease in H4K20me1 might signify a regulatory shift in chromatin structure, facilitating transcriptional activation during heat shock, with PARP-1 playing an independent facilitating role. Moreover, existing studies have highlighted the dual role of H4K20me1, acting as a promoter of transcription elongation in certain contexts and as a repressor in others.

The elevated enrichment of H4K20me1 in group B genes under normal conditions may indeed indicate a repressive state that requires alleviation for transcriptional activation. Additionally, we cannot discount the possibility of unique regulatory functions associated with PR-SET7, extending beyond its recognized role as a histone methylase. Non-catalytic activities and potential interactions with non-histone substrates might contribute to the nuanced control exerted by PR-SET7 on group B genes during heat stress.

Furthermore, our exploration of pr-set720 and ParpC03256 mutants reveals distinct roles for PARP-1 and H4K20me1 in modulating gene expression (Fig 3E). This reinforces the notion that the interplay between PR-SET7 and PARP-1 involves a multifaceted regulatory mechanism.

To address these points, we have revised the discussion section of our manuscript accordingly:

"Another plausible explanation could be that the recruitment of PARP-1 to group B genes loci promotes H4 dissociation and then leads to a reduction of H4K20me1. However, our findings suggest an alternative interpretation: the decrease in H4K20me1 at group B genes during heat shock does not seem to impede PARP-1's role in transcriptional activation, (Fig.4A, C and E). Rather than disrupting PARP-1 function, we propose that this reduction in H4K20me1 may signify a regulatory shift in chromatin structure, priming these genes for transcriptional activation during heat shock, with PARP-1 playing an independent facilitating role. Moreover, existing studies have highlighted the dual role of H4K20me1, acting as a promoter of transcription elongation in certain contexts and as a repressor in others (13, 26, 39, 40, 42-46). The elevated enrichment of H4K20me1 in group B genes under normal conditions may indicate a repressive state that requires alleviation for transcriptional activation. Additionally, we cannot discount the possibility of unique regulatory functions associated with PR-SET7, extending beyond its recognized role as a histone methylase. Non-catalytic activities and potential interactions with non-histone substrates might contribute to the nuanced control exerted by PR-SET7 on group B genes during heat stress (47, 48). Furthermore, our exploration of pr-set720 and parp-1C03256 mutants reveals distinct roles for PARP-1 and H4K20me1 in modulating gene expression (Fig 3E). This reinforces the notion that the interplay between PR-SET7 and PARP-1 involves a multifaceted regulatory mechanism. Understanding the intricate relationship between these molecular players is crucial for elucidating the complexities of gene expression modulation under heat stress conditions."

We believe that this modification enhances the clarity of our conclusions and adequately addresses Reviewer 2's concerns regarding the intricate relationship between PARP-1, H4K20me1, and PR-SET7 in transcriptional regulation under heat stress conditions.

eLife assessment

This valuable study presents convincing evidence for an association between PARP-1 and H4K20me1 in transcriptional regulation, supported by biochemical and ChIP-seq analyses. The work contributes significantly to our understanding of how Parp1 associates with target genes to regulate their expression.

Reviewer #2 (Public Review):

Summary:

This study from Bamgbose et al. identifies a new and important interaction between H4K20me and Parp1 that regulates inducible genes during development and heat stress. The authors present convincing experiments that form a mostly complete manuscript that significantly contributes to our understanding of how Parp1 associates with target genes to regulate their expression.

Strengths:

The authors present 3 compelling experiments to support the interaction between Parp1 and H4K20me, including:

(1) PR-Set7 mutants remove all K4K20me and phenocopy Parp mutant developmental arrest and defective heat shock protein induction.

(2) PR-Set7 mutants have dramatically reduced Parp1 association with chromatin and reduced poly-ADP ribosylation.

(3) Parp1 directly binds H4K20me in vitro.