DOI: 10.1523/ENEURO.0083-24.2024

Resource: (Thermo Fisher Scientific Cat# O-11033, RRID:AB_2539797)

Curator: @scibot

SciCrunch record: RRID:AB_2539797

What is this?

DOI: 10.1016/j.devcel.2024.12.037

Resource: (BD Biosciences Cat# 557915, RRID:AB_396936)

Curator: @scibot

SciCrunch record: RRID:AB_396936

What is this?

Author response:

Public Reviews:

Reviewer #1 (Public review):

This a comprehensive study that sheds light on how Wag31 functions and localises in mycobacterial cells. A clear link to interactions with CL is shown using a combination of microscopy in combination with fusion fluorescent constructs, and lipid specific dyes. Furthermore, studies using mutant versions of Wag31 shed light on the functionalities of each domain in the protein. My concerns/suggestions for the manuscript are minor:

(1) Ln 130. A better clarification/discussion is required here. It is clear that both depletion and overexpression have an effect on levels of various lipids, but subsequent descriptions show that they affect different classes of lipids.

We thank the reviewer for the comments. We will improve Ln130 in the manuscript. The lipid classes that get impacted by the depletion of Wag31 vs overexpression are different. Wag31 is an adaptor protein that interacts with proteins of the ACCase complex (Meniche et al., 2014; Xu et al., 2014) that synthesize fatty acid precursors and regulate their activity (Habibi Arejan et al., 2022).

The varied response to lipid homeostasis could be attributed to a change in the stoichiometry of these interactions with Wag31. While Wag31 depletion would prevent such interactions from occurring and might affect lipid synthesis that directly depends on Wag31-protein partner interactions, its overexpression would lead to promiscuous interactions and a change in the stoichiometry of native interactions, ultimately modulating lipid synthesis pathways.

(2) The pulldown assays results are interesting, but links are tentative.

The interactome of Wag31 was identified through the immunoprecipitation of Flag-tagged Wag31 complemented at an integrative locus in Wag31 mutant background to avoid overexpression artifacts. We used Msm::gfp expressing an integrative copy (at L5 locus) of FLAG-GFP as a control to subtract non-specific interactions. The experiment was performed in biological triplicates, and interactors that appeared in all replicates were selected for further analysis. Although we identified more than 100 interactors of Wag31, we analyzed only the top 25 hits, with a PSM cut-off ≥18 and unique peptides≥5. Additionally, two of Wag31's established interactors, AccD5 and Rne, were among the top five hits, thus validating our data.

Though we agree that the interactions can either be direct or through a third partner, the fact that we obtained known interactors of Wag31 makes us believe these interactions are genuine. Moreover, we performed pulldown experiments for validation by mixing E. coli lysates expressing His-Wag31 full-length or truncated protein with M. smegmatis lysates expressing FLAG-tagged interacting proteins. The wash conditions used were quite stringent for these pull-down assays—the wash buffer contained 1% Triton X100, eliminating all non-specific and indirect interactions.  However, we agree that we cannot conclusively state that the interactions are direct without purifying the proteins and performing the experiment. We will describe this caveat in the revised manuscript. 

(3) The authors may perhaps like to rephrase claims of effects lipid homeostasis, as my understanding is that lipid localisation rather than catabolism/breakdown is affected.

In this manuscript, we are trying to convey that Wag31 is a spatiotemporal regulator of lipid metabolism. It is a peripheral protein that is hooked to the membrane via Cardiolipin and forms a scaffold at the poles, which helps localize several enzymes involved in lipid metabolism.

Homeostasis is the process by which an organism maintains a steady-state of balance and stability in response to changes.  Depletion of Wag31 not only results in delocalisation of lipids in intracellular lipid inclusions but also leads to changes in the levels of various lipid classes. Advancement in the field of spatial biology underscores the importance of native localization of various biological molecules crucial for maintaining a steady-cell of the cell. Hence, we have used the word “homeostasis” to describe both the changes observed in lipid metabolism.

Reviewer #2 (Public review):

Summary

Kapoor et. al. investigated the role of the mycobacterial protein Wag31 in lipid and peptidoglycan synthesis and sought to delineate the role of the N- and C- terminal domains of Wag31. They demonstrated that modulating Wag31 levels influences lipid homeostasis in M. smegmatis and cardiolipin (CL) localisation in cells. Wag31 was found to preferentially bind CL-containing liposomes, and deleting the N-terminus of the protein significantly decreased this interaction. Novel interactions between Wag31 and proteins involved in lipid metabolism and cell wall synthesis were identified, suggesting that Wag31 recruits proteins to the intracellular membrane domain by direct interaction.

Strengths:

(1) The importance of Wag31 in maintaining lipid homeostasis is supported by several lines of evidence.

(2) The interaction between Wag31 and cardiolipin, and the role of the N-terminus in this interaction was convincingly demonstrated.

Weaknesses:

(1) MS experiments provide some evidence for novel protein-protein interactions. However, the pull-down experiments lack a valid negative control.

We thank the reviewer for the comments. We will include a valid negative control in the experiment. We would choose ~2 mycobacterial proteins that are not a part of our interactome study and perform a similar pull-down experiment with them and a positive control (known interactor of Wag31).

(2) The role of the N-terminus in the protein-protein interaction has not been ruled out.

Previously, we attempted to express the N-terminal (1-60 aa) and the C-terminal (60-212 aa) proteins in various mycobacterial shuttle vectors to perform MS/MS experiments. Despite numerous efforts, neither was expressed with the N/C-terminal FLAG tag nor without any tag in episomal or integrative vectors due to the instability of the protein. Eventually, we successfully expressed the C-terminal Wag31 with an N and C-terminal hexa-His tag. However, this expression was not sufficient or stable enough for us to perform Ni affinity pull-down experiments for mass spectrometry.  The N-terminal of Wag31 could not be expressed in M. smegmatis even with N and C-terminal Hexa-His tags.

To rule out the role of the N-terminal in mediating protein-protein interactions, we plan to attempt to express N-terminal of Wag31with N and C-terminal hexa-His tag in E. coli. If this clone successfully expresses in E. coli, we will perform pull-down experiments as described in Figure 7.

Reviewer #3 (Public review):

Summary:

This manuscript describes the characterization of mycobacterial cytoskeleton protein Wag31, examining its role in orchestrating protein-lipid and protein-protein interactions essential for mycobacterial survival. The most significant finding is that Wag31, which directs polar elongation and maintains the intracellular membrane domain, was revealed to have membrane tethering capabilities.

Strengths:

The authors provided a detailed analysis of Wag31 domain architecture, revealing distinct functional roles: the N-terminal domain facilitates lipid binding and membrane tethering, while the C-terminal domain mediates protein-protein interactions. Overall, this study offers a robust and new understanding of Wag31 function.

Weaknesses:

The following major concerns should be addressed.

• Authors use 10-N-Nonyl-acridine orange (NAO) as a marker for cardiolipin localization. However, given that NAO is known to bind to various anionic phospholipids, how do the authors know that what they are seeing is specifically visualizing cardiolipin and not a different anionic phospholipid? For example, phosphatidylinositol is another abundant anionic phospholipid in mycobacterial plasma membrane.

We thank the reviewer for the comments. Despite its promiscuous binding to other anionic phospholipids, 10-N-Nonyl-acridine orange is widely used to stain Cardiolipin and determine its localisation in bacterial cells and mitochondria of eukaryotes (Garcia Fernandez et al., 2004; Mileykovskaya & Dowhan, 2000; Renner & Weibel, 2011).  This is because it has a stronger affinity for Cardiolipin than other anionic phospholipids with the affinity constant being 2 × 10⁶ M⁻¹ for Cardiolipin association and 7 × 10⁴ M⁻¹ for that of phosphatidylserine and phosphatidylinositol association (Petit et al., 1992). Additionally, there is not yet another stain available for detecting Cardiolipin. Our protein-lipid binding assays suggest that Wag31 preferentially binds to Cardiolipin over other anionic phospholipids (Fig. 4b), hence it is likely that the majority of redistribution of NAO fluorescence that we observe might be contributed by Cardiolipin mislocalization due to altered Wag31 levels, with smaller degree of NAO redistribution intensity coming indirectly from other anionic phospholipids displaced from the membrane due to the loss of membrane integrity and cell shape changes due to Wag31.

• Authors' data show that the N-terminal region of Wag31 is important for membrane tethering. The authors' data also show that the N-terminal region is important for sustaining mycobacterial morphology. However, the authors' statement in Line 256 "These results highlight the importance of tethering for sustaining mycobacterial morphology and survival" requires additional proof. It remains possible that the N-terminal region has another unknown activity, and this yet-unknown activity rather than the membrane tethering activity drives the morphological maintenance. Similarly, the N-terminal region is important for lipid homeostasis, but the statement in Line 270, "the maintenance of lipid homeostasis by Wag31 is a consequence of its tethering activity" requires additional proof. The authors should tone down these overstatements or provide additional data to support their claims.

We agree with the reviewer that there exists a possibility for another function of the N-terminal that may contribute to sustaining mycobacterial physiology and survival. We would revise our statements in the paper to accurately reflect the data. Results shown suggest that the tethering activity of the N-terminal region may contribute to mycobacterial morphology and survival. However, additional functions of this region can’t be ruled out. Similarly, the maintenance of lipid homeostasis by Wag31 may be associated with its tethering activity, although other mechanisms could also contribute to this process. 

• Authors suggest that Wag31 acts as a scaffold for the IMD (Fig. 8). However, Meniche et. al. has shown that MurG as well as GlfT2, two well-characterized IMD proteins, do not colocalize with Wag31 (DivIVA) (https://doi.org/10.1073/pnas.1402158111). IMD proteins are always slightly subpolar while Wag31 is located to the tip of the cell. Therefore, the authors' biochemical data cannot be easily reconciled with microscopic observations in the literature. This raises a question regarding the validity of protein-protein interaction shown in Figure 7. Since this pull-down assay was conducted by mixing E. coli lysate expressing Wag31 and Msm lysate expression Wag31 interactors like MurG, it is possible that the interactions are not direct. Authors should interpret their data more cautiously. If authors cannot provide additional data and sufficient justifications, they should avoid proposing a confusing model like Figure 8 that contradicts published observations.

In the literature, MurG and GlfT2 have been shown to have polar localization (Freeman et al., 2023; Hayashi et al., 2016; Kado et al., 2023), and two groups have shown slightly sub-polar localization of MurG (García-Heredia et al., 2021; Meniche et al., 2014). Additionally, (Freeman et al., 2023) they showed SepIVA to be a spatio-temporal regulator of MurG. MS/MS analysis of Wag31 immunoprecipitation data yielded both MurG and SepIVA to be interactors of Wag31 (Fig. 3). Given Wag31 also displays polar localisation, it likely associates with the polar MurG. However, since a sub-polar localization of MurG has also been reported, it is possible that they do not interact directly, and another protein mediates their interaction. We will modify the model proposed in Fig. 8 based on the above.

We agree that for validation of interaction, we performed pulldown experiments by mixing E. coli lysates expressing His-Wag31 full-length or truncated protein with M. smegmatis lysates expressing FLAG-tagged interacting proteins. The wash conditions used were quite stringent for these pull-down assays—the wash buffer containing 1% Triton X100, which eliminates all non-specific and indirect interactions.  However, we agree that we cannot conclusively state that the interactions are direct without purifying the proteins and performing the experiment. We will describe this caveat in the revised manuscript and propose a model reflecting our results.

References:

Freeman, A. H., Tembiwa, K., Brenner, J. R., Chase, M. R., Fortune, S. M., Morita, Y. S., & Boutte, C. C. (2023). Arginine methylation sites on SepIVA help balance elongation and septation in Mycobacterium smegmatis. Mol Microbiol, 119(2), 208-223. https://doi.org/10.1111/mmi.15006

Garcia Fernandez, M. I., Ceccarelli, D., & Muscatello, U. (2004). Use of the fluorescent dye 10-N-nonyl acridine orange in quantitative and location assays of cardiolipin: a study on different experimental models. Anal Biochem, 328(2), 174-180. https://doi.org/10.1016/j.ab.2004.01.020

García-Heredia, A., Kado, T., Sein, C. E., Puffal, J., Osman, S. H., Judd, J., Gray, T. A., Morita, Y. S., & Siegrist, M. S. (2021). Membrane-partitioned cell wall synthesis in mycobacteria. eLife, 10. https://doi.org/10.7554/eLife.60263

Habibi Arejan, N., Ensinck, D., Diacovich, L., Patel, P. B., Quintanilla, S. Y., Emami Saleh, A., Gramajo, H., & Boutte, C. C. (2022). Polar protein Wag31 both activates and inhibits cell wall metabolism at the poles and septum. Front Microbiol, 13, 1085918. https://doi.org/10.3389/fmicb.2022.1085918

Hayashi, J. M., Luo, C. Y., Mayfield, J. A., Hsu, T., Fukuda, T., Walfield, A. L., Giffen, S. R., Leszyk, J. D., Baer, C. E., Bennion, O. T., Madduri, A., Shaffer, S. A., Aldridge, B. B., Sassetti, C. M., Sandler, S. J., Kinoshita, T., Moody, D. B., & Morita, Y. S. (2016). Spatially distinct and metabolically active membrane domain in mycobacteria. Proc Natl Acad Sci U S A, 113(19), 5400-5405. https://doi.org/10.1073/pnas.1525165113

Kado, T., Akbary, Z., Motooka, D., Sparks, I. L., Melzer, E. S., Nakamura, S., Rojas, E. R., Morita, Y. S., & Siegrist, M. S. (2023). A cell wall synthase accelerates plasma membrane partitioning in mycobacteria. eLife, 12, e81924. https://doi.org/10.7554/eLife.81924

Meniche, X., Otten, R., Siegrist, M. S., Baer, C. E., Murphy, K. C., Bertozzi, C. R., & Sassetti, C. M. (2014). Subpolar addition of new cell wall is directed by DivIVA in mycobacteria. Proc Natl Acad Sci U S A, 111(31), E3243-3251. https://doi.org/10.1073/pnas.1402158111

Mileykovskaya, E., & Dowhan, W. (2000). Visualization of phospholipid domains in Escherichia coli by using the cardiolipin-specific fluorescent dye 10-N-nonyl acridine orange. J Bacteriol, 182(4), 1172-1175. https://doi.org/10.1128/JB.182.4.1172-1175.2000

Petit, J. M., Maftah, A., Ratinaud, M. H., & Julien, R. (1992). 10N-nonyl acridine orange interacts with cardiolipin and allows the quantification of this phospholipid in isolated mitochondria. Eur J Biochem, 209(1), 267-273. https://doi.org/10.1111/j.1432-1033.1992.tb17285.x

Renner, L. D., & Weibel, D. B. (2011). Cardiolipin microdomains localize to negatively curved regions of Escherichia coli membranes. Proc Natl Acad Sci U S A, 108(15), 6264-6269. https://doi.org/10.1073/pnas.1015757108

Xu, W. X., Zhang, L., Mai, J. T., Peng, R. C., Yang, E. Z., Peng, C., & Wang, H. H. (2014). The Wag31 protein interacts with AccA3 and coordinates cell wall lipid permeability and lipophilic drug resistance in Mycobacterium smegmatis. Biochem Biophys Res Commun, 448(3), 255-260. https://doi.org/10.1016/j.bbrc.2014.04.116

貸し切りを取りたい →コースを作る →コース予約はライト以上なので プランを上げましょう

めちゃくちゃテコ入れしましょう、お店 →BPだと 春の乾杯キャンペーン

ウェディングのプラン どうせ露出するならBP→無料で参加できる

二か月半額キャンペーンもやってるのでＢＰの提案

カメラマンのフック

ＭＥＯ対策

ＧＢＰ →4.2あるのに口コミの返信一度もない →ここ整備すると売り上げに直結するのでやりましょう

ぐるなびＳＰ→ＧＢＰかける めんどくさがり屋 媒体やってない

o

use a semicolon when introducing lists, and also add commas

need to have a passive tone when writting methods

Lucas 6.35 - O amor aos inimigos

Jesus se refere a Deus como: - Altíssimo

Lucas 6.22 - Bençãos e ais

Jesus diz aos discípulos que eles serão bem aventurados quando forem odiados, expulsos, insultados ou tratados com desprezo por causa do: - Filho do homem (Jesus)

Lucas 6.5 - O Senhor do sábado

Jesus refere-se como - Filho do Homem - Senhor do Sábado

Marcos 3.11 - Jesus é procurado por uma multidão

Os espíritos imundos se referem a Jesus como: - Filho de Deus

Mateus 12.18 - O servo escolhido de Deus

Mateus, Citando Isaías, diz que Jesus é: - O servo escolhido de Deus - O amado de Deus

Mateus 12.8 - O Senhor do Sábado

Jesus refere-se como: - Filho do homem - Senhor do sábado

Mateus 5.16-30 - Vida por meio do filho

Jesus refere-se como Filho e a Deus como Pai

Mateus 5.7 - A cura junto ao tanque de Betesda

O paralítico se refere a Jesus como: - Senhor

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

This study asks whether the phenomenon of crossmodal temporal recalibration, i.e. the adjustment of time perception by consistent temporal mismatches across the senses, can be explained by the concept of multisensory causal inference. In particular, they ask whether the explanation offered by causal inference better explains temporal recalibration better than a model assuming that crossmodal stimuli are always integrated, regardless of how discrepant they are.

The study is motivated by previous work in the spatial domain, where it has been shown consistently across studies that the use of crossmodal spatial information is explained by the concept of multisensory causal inference. It is also motivated by the observation that the behavioral data showcasing temporal recalibration feature nonlinearities that, by their nature, cannot be explained by a fixed integration model (sometimes also called mandatory fusion).

To probe this the authors implemented a sophisticated experiment that probed temporal recalibration in several sessions. They then fit the data using the two classes of candidate models and rely on model criteria to provide evidence for their conclusion. The study is sophisticated, conceptually and technically state-of-the-art, and theoretically grounded. The data clearly support the authors’ conclusions.

I find the conceptual advance somewhat limited. First, by design, the fixed integration model cannot explain data with a nonlinear dependency on multisensory discrepancy, as already explained in many studies on spatial multisensory perception. Hence, it is not surprising that the causal inference model better fits the data.

We have addressed this comment by including an asynchrony-contingent model, which is capable of predicting the nonlinearity of recalibration effects by employing a heuristic approximation of the causal-inference process (Fig. 3). We also updated the previous competitor model with a more reasonable asynchrony-correction model as the baseline of model comparison, which assumes recalibration aims to restore synchrony whenever the sensory measurement of SOA indicates an asynchrony. The causal-inference model outperformed both models, as indicated by model evidence (Fig. 4A). Furthermore, model predictions show that the causal-inference model more accurately captures recalibration at large SOAs at both the group (Fig. 4B) and the individual levels (Fig. S4).

Second, and again similar to studies on spatial paradigms, the causal inference model fails to predict the behavioral data for large discrepancies. The model predictions in Figure 5 show the (expected) vanishing recalibration for large delta, while the behavioral data don’t decay to zero. Either the range of tested SOAs is too small to show that both the model and data converge to the same vanishing effect at large SOAs, or the model's formula is not the best for explaining the data. Again, the studies using spatial paradigms have the same problem, but in my view, this poses the most interesting question here.

We included an additional simulation (Fig. 5B) to show that the causal-inference model can predict non-zero recalibration for long adapter SOAs, especially in observers with a high common-cause prior and low sensory precision. This ability to predict a non-zero recalibration effect even at large SOA, such as 0.7 s, is one key feature of the causal-inference model that distinguishes it from the asynchrony-contingent model.

In my view there is nothing generally wrong with the study, it does extend the 'known' to another type of paradigm. However, it covers little new ground on the conceptual side.

On that note, the small sample size of n=10 is likely not an issue, but still, it is on the very low end for this type of study.

This study used a within-subject design, which included 3 phases each repeated in 9 sessions, totaling 13.5 hours per participant. This extensive data collection allows us to better constrain the model for each participant. Our conclusions are based on the different models’ ability to fit individual data.

Reviewer #2 (Public Review):

Summary:

Li et al.’s goal is to understand the mechanisms of audiovisual temporal recalibration. This is an interesting challenge that the brain readily solves in order to compensate for real-world latency differences in the time of arrival of audio/visual signals. To do this they perform a 3-phase recalibration experiment on 9 observers that involves a temporal order judgment (TOJ) pretest and posttest (in which observers are required to judge whether an auditory and visual stimulus were coincident, auditory leading or visual leading) and a conditioning phase in which participants are exposed to a sequence of AV stimuli with a particular temporal disparity. Participants are required to monitor both streams of information for infrequent oddballs, before being tested again in the TOJ, although this time there are 3 conditioning trials for every 1 TOJ trial. Like many previous studies, they demonstrate that conditioning stimuli shift the point of subjective simultaneity (pss) in the direction of the exposure sequence.

These shifts are modest - maxing out at around -50 ms for auditory leading sequences and slightly less than that for visual leading sequences. Similar effects are observed even for the longest offsets where it seems unlikely listeners would perceive the stimuli as synchronous (and therefore under a causal inference model you might intuitively expect no recalibration, and indeed simulations in Figure 5 seem to predict exactly that which isn't what most of their human observers did). Overall I think their data contribute evidence that a causal inference step is likely included within the process of recalibration.

Strengths:

The manuscript performs comprehensive testing over 9 days and 100s of trials and accompanies this with mathematical models to explain the data. The paper is reasonably clearly written and the data appear to support the conclusions.

Weaknesses:

While I believe the data contribute evidence that a causal inference step is likely included within the process of recalibration, this to my mind is not a mechanism but might be seen more as a logical checkpoint to determine whether whatever underlying neuronal mechanism actually instantiates the recalibration should be triggered.

We have addressed this comment by replacing the fixed-update model with an asynchrony-correction model, which assumes that the system first evaluates whether the measurement of SOA is asynchronous, thus indicating a need for recalibration (Fig. 3). If it does, it shifts the audiovisual bias by a proportion of the measured SOA. We additionally included an asynchrony-contingent model, which is capable of replicating the nonlinearity of recalibration effects by a heuristic approximation of the causal-inference process.

Model comparisons indicate that the causal-inference model of temporal recalibration outperforms both alternative models (Fig. 4A). Furthermore, the model predictions demonstrate that the causal-inference model more accurately captures recalibration at large SOAs at both the group level (Fig. 4B) and individual level (Fig. S4).

The authors’ causal inference model strongly predicts that there should be no recalibration for stimuli at 0.7 ms offset, yet only 3/9 participants appear to show this effect. They note that a significant difference in their design and that of others is the inclusion of longer lags, which are unlikely to originate from the same source, but don’t offer any explanation for this key difference between their data and the predictions of a causal inference model.

We added further simulations to show that the causal-inference model can predict non-zero recalibration also for longer adapter SOAs, especially in observers with a large common-cause prior (Fig. 5A) and low sensory precision (Fig. 5B). This ability to predict a non-zero recalibration effect even at longer adapter SOAs, such as 0.7 s, is a key feature of the causal-inference model that distinguishes it from the asynchrony-contingent model.

I’m also not completely convinced that the causal inference model isn’t ‘best’ simply because it has sufficient free parameters to capture the noise in the data. The tested models do not (I think) have equivalent complexity - the causal inference model fits best, but has more parameters with which to fit the data. Moreover, while it fits ‘best’, is it a good model? Figure S6 is useful in this regard but is not completely clear - are the red dots the actual data or the causal inference prediction? This suggests that it does fit the data very well, but is this based on predicting held-out data, or is it just that by having more parameters it can better capture the noise? Similarly, S7 is a potentially useful figure but it's not clear what is data and what are model predictions (what are the differences between each row for each participant; are they two different models or pre-test post-test or data and model prediction?!).

I'm not an expert on the implementation of such models but my reading of the supplemental methods is that the model is fit using all the data rather than fit and tested on held-out data. This seems problematic.

We recognize the risk of overfitting with the causal-inference model. We now rely on Bayesian model comparisons, which use model evidence for model selection. This method automatically incorporates a penalty for model complexity through the marginalization over the parameter space (MacKay, 2003).

Our design is not suitable for cross-validation because the model-fitting process is computationally intensive and time-consuming. Each fit of the causal-inference model takes approximately 30 hours, and multiple fits with different initial starting points are required to rule out that the parameter estimates correspond to local minima.

I would have liked to have seen more individual participant data (which is currently in the supplemental materials, albeit in a not very clear manner as discussed above).

We have revised Supplementary Figures S4-S6 to show additional model predictions of the recalibration effect for individual participants, and participants’ temporal-order judgments are now shown in Supplement Figure S7. These figures confirm the better performance of the causal-inference model.

The way that S3 is described in the text (line 141) makes it sound like everyone was in the same direction, however, it is clear that 2 /9 listeners show the opposite pattern, and 2 have confidence intervals close to zero (albeit on the -ve side).

We have revised the text to clarify that the asymmetry occurs in both directions and is idiosyncratic (lines 168-171). We summarized the distribution of the individual asymmetries of the recalibration effect across visual-leading and auditory-leading adapter SOAs in Supplementary Figure S2.

Reviewer #3 (Public Review):

Summary:

Li et al. describe an audiovisual temporal recalibration experiment in which participants perform baseline sessions of ternary order judgments about audiovisual stimulus pairs with various stimulus-onset asynchronies (SOAs). These are followed by adaptation at several adapting SOAs (each on a different day), followed by post-adaptation sessions to assess changes in psychometric functions. The key novelty is the formal specification and application/fit of a causal-inference model for the perception of relative timing, providing simulated predictions for the complete set of psychometric functions both pre and post-adaptation.

Strengths:

(1) Formal models are preferable to vague theoretical statements about a process, and prior to this work, certain accounts of temporal recalibration (specifically those that do not rely on a population code) had only qualitative theoretical statements to explain how/why the magnitude of recalibration changes non-linearly with the stimulus-onset asynchrony of the adapter.

(2) The experiment is appropriate, the methods are well described, and the average model prediction is a fairly good match to the average data (Figure 4). Conclusions may be overstated slightly, but seem to be essentially supported by the data and modelling.

(3) The work should be impactful. There seems a good chance that this will become the go-to modelling framework for those exploring non-population-code accounts of temporal recalibration (or comparing them with population-code accounts).

(4) A key issue for the generality of the model, specifically in terms of recalibration asymmetries reported by other authors that are inconsistent with those reported here, is properly acknowledged in the discussion.

Weaknesses:

(1) The evidence for the model comes in two forms. First, two trends in the data (non-linearity and asymmetry) are illustrated, and the model is shown to be capable of delivering patterns like these. Second, the model is compared, via AIC, to three other models. However, the main comparison models are clearly not going to fit the data very well, so the fact that the new model fits better does not seem all that compelling. I would suggest that the authors consider a comparison with the atheoretical model they use to first illustrate the data (in Figure 2). This model fits all sessions but with complete freedom to move the bias around (whereas the new model constrains the way bias changes via a principled account). The atheoretical model will obviously fit better, but will have many more free parameters, so a comparison via AIC/BIC or similar should be informative

In the revised manuscript, we switched from AIC to Bayesian model selection, which approximates and compares model evidence. This method incorporates a strong penalty for model complexity through marginalization over the parameter space (MacKay, 2003).

We have addressed this comment by updating the former competitor model into a more reasonable version that induces recalibration only for some measured SOAs and by including another (asynchrony-contingent) model that is capable of predicting the nonlinearity and asymmetry of recalibration (Fig. 3) while heuristically approximating the causal inference computations. The causal-inference model outperformed the asynchrony-contingent model, as indicated by model evidence (Fig. 4A). Furthermore, model predictions show that the causal-inference model more accurately captures recalibration at large SOAs at both the group (Fig. 4B) and the individual level (Fig. S4).

(2) It does not appear that some key comparisons have been subjected to appropriate inferential statistical tests. Specifically, lines 196-207 - presumably this is the mean (and SD or SE) change in AIC between models across the group of 9 observers. So are these differences actually significant, for example via t-test?

We statistically compared the models using Bayes factors (Fig. 4A). The model evidence for each model was approximated using Variational Bayesian Monte Carlo. Bayes factors provided strong evidence in support of the causal-inference model relative to the other models.

(3) The manuscript tends to gloss over the population-code account of temporal recalibration, which can already provide a quantitative account of how the magnitude of recalibration varies with adapter SOA. This could be better acknowledged, and the features a population code may struggle with (asymmetry?) are considered.

We simulated a population-code model to examine its prediction of the recalibration effect for different adapter SOAs (lines 380–388, Supplement Section 8). The population-code model can predict the nonlinearity of recalibration, i.e., a decreasing recalibration effect as the adapter SOA increases. However, to capture the asymmetry of recalibration effects across auditory-leading and visual-leading adapter stimuli, we would need to assume that the auditory-leading and visual-leading SOAs are represented by neural populations with unequal tuning curves.

(4) The engagement with relevant past literature seems a little thin. Firstly, papers that have applied causal inference modeling to judgments of relative timing are overlooked (see references below). There should be greater clarity regarding how the modelling here builds on or differs from these previous papers (most obviously in terms of additionally modelling the recalibration process, but other details may vary too). Secondly, there is no discussion of previous findings like that in Fujisaki et al.’s seminal work on recalibration, where the spatial overlap of the audio and visual events didn’t seem to matter (although admittedly this was an N = 2 control experiment). This kind of finding would seem relevant to a causal inference account.

References:

Magnotti JF, Ma WJ and Beauchamp MS (2013) Causal inference of asynchronous audiovisual speech. Front. Psychol. 4:798. doi: 10.3389/fpsyg.2013.00798

Sato, Y. (2021). Comparing Bayesian models for simultaneity judgement with different causal assumptions. J. Math. Psychol., 102, 102521.

We have revised the Introduction and Discussion to better situate our study within the existing literature. Specifically, we have incorporated the suggested references (lines 66–69) and provided clearer distinctions on how our modeling approach builds on or differs from previous work on causal-inference models, particularly in terms of modeling the recalibration process (lines 75–79). Additionally, we have discussed findings that might contradict the assumptions of the causal-inference model (lines 405–424).

(5) As a minor point, the model relies on simulation, which may limit its take-up/application by others in the field.

Upon acceptance, we will publicly share the code for all models (simulation and parameter fitting) to enable researchers to adapt and apply these models to their own data.

(6) There is little in the way of reassurance regarding the model’s identifiability and recoverability. The authors might for example consider some parameter recovery simulations or similar.

We conducted a model recovery for each of the six models described in the main text and confirmed that the asynchrony-contingent and causal-inference models are identifiable (Supplement Section 11). Simulations of the asynchrony-correction model were sometimes best fit by causal-inference models, because the latter behaves similarly when the prior of a common cause is set to one.

We also conducted a parameter recovery for the winning model, the causal-inference model with modality-specific precision (Supplement Section 13).

Key parameters, including audiovisual bias  , amount of auditory latency noise  , amount of visual latency noise  , criterion, lapse rate  showed satisfactory recovery performance. The less accurate recovery of  is likely due to a tradeoff with learning rate  .

(7) I don't recall any statements about open science and the availability of code and data.

Upon acceptance of the manuscript, all code (simulation and parameter fitting) and data will be made available on OSF and publicly available.

Recommendations for the authors:

Reviewing Editor (Recommendations For The Authors):

In addition to the comments below, we would like to offer the following summary based on the discussion between reviewers:

The major shortcoming of the work is that there should ideally be a bit more evidence to support the model, over and above a demonstration that it captures important trends and beats an account that was already known to be wrong. We suggest you:

(1) Revise the figure legends (Figure 5 and Figure 6E).

We revised all figures and figure legends.

(2) Additionally report model differences in terms of BIC (which will favour the preferred model less under the current analysis);

We now base the model comparison on Bayesian model selection, which approximates and compares model evidence. This method incorporates a strong penalty for model complexity through marginalization over the parameter space (MacKay, 2003).

(3) Move to instead fitting the models multiple times in order to get leave-one-out estimates of best-fitting loglikelihood for each left-out data point (and then sum those for the comparison metric).

Unfortunately, our design is not suitable for cross-validation methods because the model-fitting process is computationally intensive and time-consuming. Each fit of the causal-inference model takes approximately 30 hours, and multiple fits with different initial starting points are required to rule out local minima.

(4) Offering a comparison with a more convincing model (for example an atheoretical fit with free parameters for all adapters, e.g. as suggested by Reviewer 3.

We updated the previous competitor model and included an asynchrony-contingent model, which is capable of predicting the nonlinearity of recalibration (Fig. 3). The causal-inference model still outperformed the asynchrony-contingent model (Fig. 4A). Furthermore, model predictions show that only the causal-inference model captures non-zero recalibration effects for long adapter SOAs at both the group level (Fig. 4B) and individual level (Figure S4).

Reviewer #1 (Recommendations For The Authors):

A larger sample size would be better.

This study used a within-subject design, which included 9 sessions, totaling 13.5 hours per participant. This extensive data collection allows us to better constrain the model for each participant. Our conclusions are based on the different models’ ability to fit individual data rather than on group statistics.

It would be good to better put the study in the context of spatial ventriloquism, where similar model comparisons have been done over the last ten years and there is a large body of work to connect to.

We now discuss our model in relation to models of cross-modal spatial recalibration in the Introduction (lines 70–78) and Discussion (lines 324–330).

Reviewer #2 (Recommendations For The Authors):

Previous authors (e.g. Yarrow et al.,) have described latency shift and criterion change models as providing a good fit of experimental data. Did the authors attempt a criterion shift model in addition to a shift model?

We have considered criterion-shift variants of our atheoretical recalibration models in Supplement Section 1. To summarize the results, we varied two model assumptions: 1) the use of either a Gaussian or an exponential measurement distribution, and 2) recalibration being implemented either as a shift of bias or a criterion. We fit each model variant separately to the ternary TOJ responses of all sessions. Bayesian model comparisons indicated that the bias-shift model with exponential measurement distributions best captured the data of most participants.

Figure 4B - I'm not convinced that the modality-independent uncertainty is anything but a straw man. Models not allowed to be asymmetric do not show asymmetry? (the asymmetry index is irrelevant in the fixed update model as I understand it so it is not surprising the model is identical?).

We included the assumption that temporal uncertainty might be modality-independent for several reasons. First, there is evidence suggesting that a central mechanism governs the precision of temporal-order judgments (Hirsh & Sherrick, 1961), indicating that precision is primarily limited by a central mechanism rather than the sensory channels themselves. Second, from a modeling perspective, it was necessary to test whether an audio-visual temporal bias alone, i.e., assuming modality-independent uncertainty, could introduce asymmetry across adapter SOAs. Additionally, most previous studies implicitly assumed symmetric likelihoods, i.e., modality-independent latency noise, by fitting cumulative Gaussians to the psychometric curves derived from 2AFC-TOJ tasks (Di Luca et al., 2009; Fujisaki et al., 2004; Harrar & Harris, 2005; Keetels & Vroomen, 2007; Navarra et al., 2005; Tanaka et al., 2011; Vatakis et al., 2007, 2008; Vroomen et al., 2004).

Why does a zero SOA adapter shift the pss towards auditory leading? Is this a consequence of the previous day’s conditioning - it’s not clear from the methods whether all listeners had the same SOA conditioning sequence across days.

The auditory-leading recalibration effect for an adapter SOA of zero has been consistently reported in previous studies (e.g., Fujisaki et al., 2004; Vroomen et al., 2004). This effect symbolizes the asymmetry in recalibration. This asymmetry can be explained by differences across modalities in the noisiness of the latencies (Figure 5C) in combination with audiovisual temporal bias (Figure S8).

We added details about the order of testing to the Methods section (lines 456–457).

Reviewer #3 (Recommendations For The Authors):

Abstract

“Our results indicate that human observers employ causal-inference-based percepts to recalibrate cross-modal temporal perception” Your results indicate this is plausible. However, this statement (basically repeated at the end of the intro and again in the discussion) is - in my opinion - too strong.

We have revised the statement as suggested.

Intro and later

Within the wider literature on relative timing perception, the temporal order judgement (TOJ) task refers to a task with just two response options. Tasks with three response options, as employed here, are typically referred to as ternary judgments. I would suggest language consistent with the existing literature (or if not, the contrast to standard usage could be clarified).

Ref: Ulrich, R. (1987). Threshold models of temporal-order judgments evaluated by a ternary response task. Percept. Psychophys., 42, 224-239.

We revised the term for the task as suggested throughout the manuscript.

Results, 2.2.2

“However, temporal precision might not be due to the variability of arrival latency.” Indeed, although there is some recent evidence that it might be.

Ref: Yarrow, K., Kohl, C, Segasby, T., Kaur Bansal, R., Rowe, P., & Arnold, D.H. Neural-latency noise places limits on human sensitivity to the timing of events. Cognition, 222, 105012 (2022).

We included the reference as suggested (lines 245–248).

Methods, 4.3.

Should there be some information here about the order of adaptation sessions (e.g. random for each observer)?

We added details about the order of testing to the Methods section (lines 456–457).

Supplemental material section 1.

Here, you test whether the changes resulting from recalibration look more like a shift of the entire psychometric function or an expansion of the psychometric function on one side (most straightforwardly compatible with a change of one decision criterion). Fine, but the way you have done this is odd, because you have introduced a further difference in the models (Gaussian vs. exponential latency noise) so that you cannot actually conclude that the trend towards a win for the bias-shift model is simply down to the bias vs. criterion difference. It could just as easily be down to the different shapes of psychometric functions that the two models can predict (with the exponential noise model permitting asymmetry in slopes). There seems to be no reason that this comparison cannot be made entirely within the exponential noise framework (by a very simple reparameterization that focuses on the two boundaries rather than the midpoint and extent of the decision window). Then, you would be focusing entirely on the question of interest. It would also equate model parameters, removing any reliance on asymptotic assumptions being met for AIC.

We revised our exploration of atheoretical recalibration models. To summarize the results, we varied two model assumptions: 1) the use of either a Gaussian or an exponential measurement distribution, and 2) recalibration being implemented either as a shift of the cross-modal temporal bias or as a shift of the criterion. We fit each model separately to the ternary TOJ responses of all sessions. Bayesian model comparisons indicated that the bias-shift model with exponential measurement distributions best described the data of most participants.

References

Di Luca, M., Machulla, T.-K., & Ernst, M. O. (2009). Recalibration of multisensory simultaneity:

cross-modal transfer coincides with a change in perceptual latency. Journal of Vision, 9(12), Article 7.

Fujisaki, W., Shimojo, S., Kashino, M., & Nishida, S. ’ya. (2004). Recalibration of audiovisual simultaneity. Nature Neuroscience, 7(7), 773–778.

Harrar, V., & Harris, L. R. (2005). Simultaneity constancy: detecting events with touch and vision. Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale, 166(3-4), 465–473.

Hirsh, I. J., & Sherrick, C. E., Jr. (1961). Perceived order in different sense modalities. Journal of Experimental Psychology, 62(5), 423–432.

Keetels, M., & Vroomen, J. (2007). No effect of auditory-visual spatial disparity on temporal recalibration. Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale, 182(4), 559–565.

MacKay, D. J. (2003). Information theory, inference and learning algorithms.https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=201b835c3f3a3626ca07b e68cc28cf7d286bf8d5

Navarra, J., Vatakis, A., Zampini, M., Soto-Faraco, S., Humphreys, W., & Spence, C. (2005). Exposure to asynchronous audiovisual speech extends the temporal window for audiovisual integration. Brain Research. Cognitive Brain Research, 25(2), 499–507.

Tanaka, A., Asakawa, K., & Imai, H. (2011). The change in perceptual synchrony between auditory and visual speech after exposure to asynchronous speech. Neuroreport, 22(14), 684–688.

Vatakis, A., Navarra, J., Soto-Faraco, S., & Spence, C. (2007). Temporal recalibration during asynchronous audiovisual speech perception. Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale, 181(1), 173–181.

Vatakis, A., Navarra, J., Soto-Faraco, S., & Spence, C. (2008). Audiovisual temporal adaptation of speech: temporal order versus simultaneity judgments. Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale, 185(3), 521–529.

Vroomen, J., Keetels, M., de Gelder, B., & Bertelson, P. (2004). Recalibration of temporal order perception by exposure to audio-visual asynchrony. Brain Research. Cognitive Brain Research, 22(1), 32–35.

The King may show his smile but you best know his true intentions. The King tells Hamlet that he must go and make retributions for his father's actions. The ghost of the King reminds me of the Holy Spirit in a sense that he is watching over Hamlet and guiding him.

《约基别将摩西带到尼罗河边》（Jocabed levando Moisés até o Nilo）是巴西艺术家佩德罗·阿梅里科于1884年创作的一幅油画。这幅画描绘了圣经《出埃及记》中的一个关键场景：摩西的母亲约基别为了拯救幼小的摩西，将他放在蒲草箱里，并放置在尼罗河边的芦苇丛中。

圣经背景 (Contexto Bíblico):

为了更好地理解这幅画，我们需要回顾《出埃及记》中的相关故事：

• 埃及的压迫： 以色列人在埃及受到法老的奴役和迫害。法老下令杀死所有新出生的希伯来男婴。
• 约基别的决定： 摩西的母亲约基别为了保护自己的孩子，把他藏了三个月。当无法再藏匿时，她用蒲草编了一个箱子，涂上沥青和石漆，把孩子放在里面，然后把箱子放在尼罗河边的芦苇丛中。
• 法老女儿的发现： 法老的女儿来到尼罗河边洗澡，她看到了芦苇丛中的箱子，就叫一个婢女拿过来。她打开箱子，看到里面是个哭泣的婴孩，就动了慈心，决定收养他，并给他取名为摩西（意思是“从水里拉出来”）。

作品描述 (Descrição da Obra):

《约基别将摩西带到尼罗河边》描绘了约基别即将把摩西放入尼罗河的瞬间。画面充满了母爱、忧虑和希望的复杂情感。

• 约基别： 画面中心是约基别，她抱着幼小的摩西，神情悲伤而坚定。她的眼神中既有对儿子的不舍和担忧，也有为了拯救他而不得不这样做的决心。她的姿势既温柔又充满力量，体现了一个母亲的伟大和牺牲。
• 摩西： 摩西还是一个襁褓中的婴儿，他安静地躺在母亲的怀抱里，对即将发生的事情一无所知。
• 蒲草箱： 画面前景是已经准备好的蒲草箱，箱子上涂着沥青和石漆，以确保它能够漂浮在水面上。
• 尼罗河和背景： 画面背景是尼罗河和远处的埃及风光。尼罗河象征着生命和希望，但也象征着危险和未知。背景的处理相对简洁，突出了前景的人物形象。
• 光线和色彩： 画面运用了柔和的光线和温暖的色彩，营造出一种温馨而略带忧伤的氛围。光线主要集中在约基别和摩西身上，突出了他们的重要性。

象征意义和解读 (Simbolismo e Interpretação):

这幅画作蕴含着丰富的象征意义：

• 母爱： 画作的核心主题是母爱，约基别为了拯救自己的孩子，不惜冒着巨大的风险，展现了母爱的伟大和无私。
• 希望： 即使在最绝望的时刻，约基别仍然没有放弃希望，她相信她的孩子能够得到拯救。蒲草箱象征着希望的载体，它将承载着摩西走向新的生活。
• 命运： 这幅画也暗示了命运的安排，摩西的命运从他被放入尼罗河的那一刻起就发生了改变，他将走向一条不同寻常的道路。

艺术风格 (Estilo Artístico):

《约基别将摩西带到尼罗河边》体现了佩德罗·阿梅里科典型的学院派风格，同时也融入了一些浪漫主义的元素：

• 学院派的严谨： 画面构图严谨，人物造型准确，体现了艺术家扎实的绘画功底。
• 浪漫主义的情感： 画中人物的表情和姿态都充满了情感，例如约基别的悲伤和坚定。
• 对历史和宗教题材的偏爱： 佩德罗·阿梅里科对历史和宗教题材情有独钟，他通过描绘这些题材来表达自己的思想和情感。

重要性 (Relevância):

《约基别将摩西带到尼罗河边》是佩德罗·阿梅里科的重要作品之一，它不仅展现了艺术家精湛的绘画技巧，也表达了他对人类情感和宗教故事的深刻理解。这幅画作是巴西学院派艺术的代表作之一，也为我们了解19世纪巴西的艺术和文化提供了一个重要的窗口。

总结 (Conclusão):

《约基别将摩西带到尼罗河边》是佩德罗·阿梅里科创作的一幅充满情感和象征意义的画作。它通过描绘约基别将摩西放入尼罗河的场景，展现了母爱、希望和命运等主题。这幅作品是巴西艺术史上的重要组成部分，也是佩德罗·阿梅里科艺术生涯的重要里程碑。

希望以上信息对您有所帮助。

《埃洛伊萨的誓言》（O Voto de Heloísa）是巴西艺术家佩德罗·阿梅里科于1887年创作的一幅油画。这幅作品取材于中世纪阿伯拉尔和埃洛伊萨的悲剧爱情故事，描绘了埃洛伊萨在丈夫阿伯拉尔被阉割后决定遁入修道院的场景。

故事背景：阿伯拉尔与埃洛伊萨 (Contexto da História: Abelardo e Heloísa)

在详细介绍画作之前，了解阿伯拉尔和埃洛伊萨的故事至关重要：

• 阿伯拉尔（Pierre Abélard，1079-1142）： 是一位著名的中世纪经院哲学家、神学家和逻辑学家。
• 埃洛伊萨（Héloïse d'Argenteuil，约1100-1164）： 是一位才华横溢的年轻女子，以其智慧和学识而闻名。
• 爱情与悲剧： 阿伯拉尔是埃洛伊萨的家庭教师，两人坠入爱河并秘密结婚。然而，这段恋情被埃洛伊萨的叔叔富尔伯特发现后，引发了悲剧。富尔伯特派人袭击并阉割了阿伯拉尔。
• 遁入修道院： 遭受如此打击后，阿伯拉尔进入了圣丹尼修道院，而埃洛伊萨则进入了阿让特伊修道院。两人虽然分隔两地，但仍通过书信保持着联系，这些书信成为了中世纪重要的文学作品，展现了他们深沉的爱情和痛苦。

作品描述 (Descrição da Obra):

《埃洛伊萨的誓言》描绘了埃洛伊萨在修道院宣誓的场景。画面构图庄严而肃穆，人物形象刻画细腻，色彩运用沉稳。

• 埃洛伊萨： 画面中心是年轻的埃洛伊萨，她身穿修女的黑色长袍，跪在祭坛前，神情庄重而悲伤。她的目光略微向上，似乎在向上帝祈祷或寻求安慰。她的姿态既表现出对信仰的虔诚，也流露出内心的痛苦和无奈。
• 修女们： 一群修女站在埃洛伊萨身后，她们的表情各异，有的悲伤，有的同情，有的则显得平静而肃穆。她们的存在强调了修道院的氛围，也暗示了埃洛伊萨即将开始的新生活。
• 祭坛和宗教象征： 画面背景是祭坛，上面摆放着十字架、圣经和其他宗教物品，这些都突出了场景的宗教性。
• 光线和色彩： 画面运用了柔和的光线和沉稳的色彩，营造出一种庄重而肃穆的氛围。光线主要集中在埃洛伊萨身上，突出了她的重要性。

象征意义和解读 (Simbolismo e Interpretação):

这幅画作蕴含着丰富的象征意义：

• 爱情与牺牲： 埃洛伊萨的誓言象征着她对阿伯拉尔深沉的爱，以及为了这段爱情所做出的巨大牺牲。她放弃了世俗的生活和爱情的希望，选择了将自己奉献给上帝。
• 痛苦与救赎： 画中埃洛伊萨的悲伤表情反映了她内心的痛苦，而她向上看的目光则暗示了她对精神救赎的渴望。
• 女性的命运： 这幅画也反映了中世纪女性的命运，她们在社会和宗教的约束下，往往面临着许多无奈和选择。

艺术风格 (Estilo Artístico):

《埃洛伊萨的誓言》体现了佩德罗·阿梅里科典型的学院派风格，同时也融入了一些浪漫主义的元素：

• 学院派的严谨： 画面构图严谨，人物造型准确，体现了艺术家扎实的绘画功底。
• 浪漫主义的情感： 画中人物的表情和姿态都充满了情感，例如埃洛伊萨的悲伤和虔诚，修女们的同情和肃穆。
• 历史题材的偏爱： 佩德罗·阿梅里科对历史题材情有独钟，他通过描绘历史事件或文学故事来表达自己的思想和情感。

重要性 (Relevância):

《埃洛伊萨的誓言》是佩德罗·阿梅里科的重要作品之一，它不仅展现了艺术家精湛的绘画技巧，也表达了他对人类情感和历史事件的深刻思考。这幅画作是巴西学院派艺术的代表作之一，也为我们了解19世纪巴西的艺术和文化提供了一个重要的窗口。

总结 (Conclusão):

《埃洛伊萨的誓言》是佩德罗·阿梅里科创作的一幅充满悲剧色彩和象征意义的画作。它通过描绘埃洛伊萨宣誓的场景，展现了爱情与牺牲、痛苦与救赎等主题，并反映了中世纪女性的命运。这幅作品是巴西艺术史上的重要组成部分，也是佩德罗·阿梅里科艺术生涯的重要里程碑。

希望以上信息对您有所帮助。

Lucas 1.68 - O cântico de Zacarias

• Senhor
• Deus de Israel

Lc 1.76 - O cântico de Zacarias - Altíssimo

Lucas 1.49 - O cântico de Maria - Poderoso - Santo

Lucas 1.47 - O cântico de Maria - Meu Salvador

Lc 1.28-33 - O nascimento de Jesus é predito

Do anjo, para Maria, sobre Jesus: - Filho do Altíssimo - Filho de Davi

This shows that sometimes students/individuals need a push or someone along side them to advocate and notice their potential. After this experience, the student was more willing to participate and expressed more encouragement, resulting in higher grades and positive feedback.

Lc 1.46 - O cântico de Maria

Maria se refere a Deus como: - Meu Salvador

Lc 1.35 - Anúncio do nascimento de Cristo

O anjo diz a Maria que Jesus é: - Santo - Filho de Deus

Lucas 1.31-33 - Anuncio do Nascimento de Jesus

O anjo anuncia que Maria ficará grávida e seu filho se chamará Jesus que será chamado: - Filho do Altíssimo

Ele é: - Filho de Davi

I think good sleep is the most important form of self-care, and so many people (especially college students) fail to get good sleep and it shows clearly negative results in day-to-day life. This obviously would affect attendance, as if you're going to o bed late you're getting up later, so probably won't show up to class as much

Đánh giá thô sử dụng Likert (1-5) thường có xu hướng ngả về điểm qua vì thuế sự làm tròn. Ngược lại, đánh giá mịn giải quyết vấn đề ở mức câu và các thông tin quan trọng (key-fact), tính điểm trung thực, đầy đủ và tính ngắn gọn thông qua tỉ lệ bao phủ ở mức câu và key-fact, từ đó cho thấy điểm phần trăm có tương quan tốt với feedback của con người.

Glycosidic bonds are a covalent bond formed between a carbohydrate and another molecule.

This happens when the OH of one monosaccharide combines with the H of another, releasing H2O and being joined by O.

These disaccharides can have different structures, functions, and purposes!

To identify carbohydrates (and lipids in general besides phospholipids), you can count the number of C, H, and O present in the molecule.

The number of carbons and oxygens should be equal, whereas the number of hydrogens should be double this amount.

You can also identify lipids by looking for the polar "head" and nonpolar "tail"!

La cartografía nos ayuda a entender cómo un paisaje cambia y evoluciona con el tiempo, mostrando tanto lo que está pasando en un momento específico como los procesos históricos detrás de esos cambios. Más que solo describir la realidad, la cartografía también la construye, ya que incluye diferentes puntos de vista y reflexiones. Es un proceso en el que comprender un lugar o situación implica trabajar juntos y adaptarse a los contextos en los que ocurre

ili barem da ne napiše ništa pozitivno, jer pripadnici jugoslavenske komunističke nomenklature ne zaslužuju da se o njima pozitivno piše

Jakovina o Lončaru i Klasić o Špiljku su »recentni pokušaji ideološke, političke i moralne rehabilitacije najviših dužnosnika jugoslavenskog komunističkog režima«, kao i Dragojevićeva knjiga o Šuvaru. A to je nemoguće jer su jugoslaveni i komunisti u svojoj ideološkoj, političkoj i moralnoj suštini zločinci kao što pokazuje Pandžić knjigom o Supeku. živio zaključak!

okej, ipak je liberalna demokracija telos nacionalne povijesti hrvata

šuvarica je problematična jer je socijalistička, ali dualno obrazovanje u zemljama kapitalizma -- ili kad se žele uvesti u post-socijalističkim državama -- nije problematično. to jako podsjeća na epizodu iz knjige o Supeku kad je komunistički princip odumiranja države very bad, ali su zato zagovornici države noćobdije (recenzenti Polšek i Sesardić te Supekova nevina žrtva Friedrich Hayek) very good.

za razliku od Pandžićeve knjige o Supeku koja nije »politički i ideološki nabrušena« i ne može služiti za »započinjanje polemika protiv svojih suvremenika neistomišljenika i zauzimanje strana u današnjim političkim raspravama.«

Pandžićeva pedanterija je stvarno uzorna i za svaku pohvalu!

na isti način, prava je šteta da se Pandžić na početku svoje knjige o Supeku ne deklarira kao nacionalist i liberal, nego svoju perspektivu predstavlja kao »neproblematično znanje o povijesti i društvu«.

Nepřetržitě usilujeme o posouvání technologických možností v oblasti e-commerce inteligence.

Získejte okamžitý přehled o trhu díky detailním informacím o nabídce konkurence, nových produktech a struktuře portfolií. Využijte DeepScout k tomu, abyste dělali rozhodnutí o cenách a sortimentu na základě reálných dat a hlubokého porozumění trhu.

Mc 2.28 - o Senhor do Sábado

Jesus afirma aos fariseus que ele é: - Senhor até mesmo do sábado.

Marcos 2.19 - Jesus é interrogado acerca do Jejum

Jesus afirma aos que o questionaram, diante dos discípulos de João Batista e dos fariseus, que ele é:

• o Noivo

Marcos 2.10-11 - Jesus cura um paralítico

Jesus identifica-se para os mestres da lei, diante da multidão que presenciou a cura de um paralítico, em sua casa, que Ele é: - o Filho do homem

João 4.42 - Muitos samaritanos creem

Os samaritanos referem-se a Jesus como: - o Salvador do mundo

João 4.26 - Jesus conversa com uma Samaritana

Jesus se identifica para a mulher samaritana como: - o Messias

João 3.34 - O testemunho de João Batista acerca de Jesus

João Batista afirma aos seus discípulos que Jesus é: - aquele que Deus enviou - o Filho

João 3.28-29 - O testemunho de João Batista acerca de Jesus.

João Batista afirma aos seus discípulos que Jesus é: - o Cristo - o noivo

João 3.16 - O encontro de Jesus com Nicodemus

Jesus se identifica para Nicodemus como: - Filho Unigenito de Deus

João 3.13 - O encontro de Jesus com Nicodemus

Jesus identifica-se como: - o filho do Homem

João 3.2 - O encontro de Jesus com Nicodemus

Nicodemus trata Jesus como: - Mestre

João 2.16 - Jesus purifica o templo

Ao chegar no templo, Jesus declara que está na casa de seu Pai - Pai

João 1.49 - Jesus chama Filipe e Natanael

Natanael reconhece que Jesus é: - o Filho de Deus - o Rei de Israel

João 1.41 - Os primeiros discípulos de Jesus

André, irmão de Simão Pedro, que havia ouvido João Batista falar sobre Jesus, apresentou Jesus a Simão como: - o Messias (isto é, o Cristo)

João 1.29 - Jesus, o Cordeiro de Deus

João Batista apresenta Jesus como: - o Cordeiro de Deus, que tira o pecado do mundo

Lucas 5.35 - Jesus é interrogado acerca do jejum

Jesus intitula-se como: - o Noivo

Lucas 3.38 - O batismo e a genealogia de Jesus

Lucas cita que Jesus é: - filho de Adão - filho de Deus

Lucas 3.31 - O batismo e a genealogia de Jesus

Lucas diz que Jesus é: - filho de Davi

Marcos 1.24 - Jesus expulsa um espírito imundo

Um espírito imundo chama Jesus de: - o Santo de Deus

Marcos 1.1 - João Batista prepara o caminho

Marcos se refere a Jesus como: - o Filho de Deus

Mateus 3.17 - O batismo de Jesus

O Espírito de Deus desce como uma pomba e chama Jesus de: - meu Filho amado, de quem me agrado

Mateus 2.23 - A volta para Israel

Citando Isaías 11.1, Jesus é chamado de: - Nazareno

Mateus 2.15 - A fuga para o Egito

Citando Oseias 11.1, onde Jesus é chamado por Deus de: - meu filho

Mateus 2.2 - A visita dos Magos

Os magos do Oriente se referem a Jesus como: - rei dos judeus

Lucas 2.29 - Jesus é apresentado no Templo

Simeão se refere a Deus como: - Soberano

Lucas 2.11 - Os pastores e os anjos

O anjo se refere a Jesus como: - Salvador - Cristo - Senhor

Lucas 2.26 - Jesus é apresentado no templo - Simeão

O Espírito Santo se referiu a Jesus como: - O Cristo do Senhor

Mateus 1.23 - O nascimento de Jesus Cristo - Emanuel, Deus conosco (cit. Isaías 7.14)

Invalid kelimesi, geçersiz, hatalı veya geçerliliği olmayan anlamına gelir. Bir şeyin "invalid" olması, o şeyin geçerli olmadığını, doğru veya kabul edilebilir olmadığını belirtir.

,

how to get the T(n) equation

As n becomes larger the most dominant part of the equation becomes n^2 so its O(n^2).

Jackson criticizes tracking for sorting students early based on biases rather than their actual abilities, which usually perpetuates the existing inequalities. What struck me most was here is something so seemingly neutral, like ability grouping, which may have a long-lasting, negative impact. By labeling students early, tracking not only limits their opportunities but also shapes how they see themselves and their potential. It made me think about how these systems create self-fulfilling prophecies, where students internalize low expectations and perform accordingly, perpetuating cycles of disadvantage. This raises serious questions about whether schools truly provide equal opportunities or simply mirror societal inequalities.

I think change is good and needed as the education system grows and taking things you learn from colleges to implement in your classroom continues to deepen the knowlege and education. change can be scary since these teachers know what works for them and change can mean that something can fail but without trying new things and trying for change then that limits how a topic can grow and evolve.

This passage demonstrates how actions that may appear harmless can be negatively charged. This professor is only portraying what appears to be valuable; "white men." This brings me to a time in high school. My senior year I took an African American Lit class, but the person who was instructing the class was a white male with blue eyes. The teacher was well aware of his place and knew the confusion that would strike within students upon finding out that it was him that was teaching the class. Although, he had no ill-intent, since the teacher was white, I don't believe he truly could've fully understood the material to that extent... As in, he has never had to experience it.

1. Cuja autoria é ratificada.
2. De origem comprovada.
3. Diz-se de qualquer documento digno de fé ou confiança; fidedigno, legítimo.
4. Jur Revestido de formalidades legais; certificado por testemunho público e solene.
5. Que tem validade, autoridade.
6. Que não é falso ou imitativo; original.
7. Que é incontestável: Narração autêntica.
8. Diz-se do indivíduo que se assume tal qual é, que se apresenta socialmente sem falsidade ou de forma a dissimular sua verdadeira identidade.
9. Do próprio punho da pessoa: Assinatura autêntica.
10. Que imita ou copia fielmente; que se produziu em fiel conformidade com o original: A aparência de sua nova casa era a de um autêntico castelo alemão.

I am not too sure if I agree with ability-based design over universal design as it might result in an unequal view in design depending on the user. I also wonder if the approach is entirely practical for individuals who have multiple support needs as it seems the approach would result in detecting a specific action and adapting to it. Furthermore, I think there may be problems with this approach when contexts/information is self-adapting to individuals with cognitive disabilities.

Maybe we should explore this separately as well for our online feature store and not just for embeddings

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

We thank the reviewers for their general comment and for the critical evaluation of our analyses and results interpretation. Their comments greatly helped us to improve the manuscript.

• *

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary: An analysis of an Arabidopsis VSP13 presumed lipid transport is provided. The analysis pretty much follows similar studies done on yeast and human homologs. Key findings are the identification of multiple products from the locus due to differential splicing, analysis of lipid binding and transport properties, subcellular location, tissue specific promoter activity, mutant analysis suggesting a role in lipid remodeling following phosphate deprivation, but no physiological or growth defects of the mutants. Major points: The paper is generally written and documented, the experiments are well conducted and follow established protocols. The following major points should be considered:

1. There are complementary lipid binding assays that should be considered such as liposome binding assays, or lipid/western dot blots. All of these might give slightly different results and may inform a consensus. Of course, non-membrane lipids such as TAG cannot be tested in a liposome assay.

Concerning lipid transfer proteins (LTPs), it is important to differentiate the lipid binding capacity related to the transport specificity (which lipids are transported by a LTP?) from the lipid binding capacity linked to the targeting of a LTP to a specific membrane (a LTP can bind a specific lipid via a domain distinct from the lipid transfer domain to be targeted in cells, but will not transport this lipid). Both aspects are of high interest to be determined. Our goal here was to focus on the identification of the lipids bound to AtVPS13M1 and to be likely transported, which is why we used a truncation (1-335) corresponding to the N-term part of the hydrophobic tunnel. Liposome binding assays and lipid dot blots are necessary to answer the question of the membrane binding capacity of the protein. We think that this aspect is out of the scope of the current article as it will require to express and purify other AtVPS13M1 domains that are known to bind lipids such as the two PH domains and the C2. This will be the scope of future investigations in our lab.

Similarly, lipid transfer based only on fluorophore-labeled lipids may be misleading because the fluorophore could affect binding. It is mentioned that the protein in this assay is tethered by 3xHis to the liposomes. Un less I ma missing something, I do not understand how that should work. This needs to be better explained.

We truly agree with Reviewer 1 that the presence of a fluorophore could affect lipid binding to the protein. In this assay, lipids are labeled on their polar head and it is therefore difficult to conclude about the specificity of our protein in term of transport. This assay is used as a qualitative assay to show that AtVPS13M1(1-335) is able to transfer lipids in vitro, and in the manuscript, we did not make any conclusion about its transport specificity based on this assay, but rather used the binding assay to assess the binding, and likely transport, specificity of AtVPS13M1. FRET-based assay is a well-accepted assay in the lipid transfer community to easily probe lipid transport in vitro and has been used in the past to assess transfer capacity of different proteins, including for VPS13 proteins (for examples, see (Kumar et al., 2018; Hanna et al., 2022; Valverde et al., 2019)).

To be able to transfer lipids from one liposome to another, both liposomes have to be in close proximity. Therefore, we attached our protein on donor acceptors, to favor the transport of the fluorescent lipids from the donor to the acceptor liposomes. Then, we progressively increased acceptor liposomes concentration to favor liposome proximity and the chance to have lipid transfer. We added a scheme on Figure 3B of the revised version of the manuscript to clarify the principle of the assay. In addition, we provided further control experiments suggested by Reviewers 2 and 3 showing that the fluorescence signal intensity depend on AtVPS13M1(1-335) protein concentration and that no fluorescence increase is measured with a control protein (Tom20.3) (see Figure 3C-D of the revised manuscript).

The in vivo lipid binding assay could be obscured by the fact that the protein was produced in insect cells and lipid binding occurs during the producing. What is the evidence that added plants calli lipids can replace lipids already present during isolation.

Actually we don’t really know whether the insect cells lipids initially bound to AtVPS13M1(1-335) are replaced by calli lipids or whether they bound to still available lipid binding sites on the protein. But we have two main lines of evidence showing that our purified protein can bind plant lipids even in the presence of insect cells lipids: 1) our protein can bind SQDG and MGDG, two plants specific lipids, and 2) as explained p.8 (lines 243-254), lipids coming from both organisms have a specific acyl-chain composition, with insect cells fatty acids mainly composed of C16 and C18 with 0 or 1 unsaturation whereas plant lipids can have up to 3 unsaturations. By analyzing and presenting on the histograms lipid species from insect cells, calli and those bound to AtVPS13M1(1-335), we were able to conclude that for all the lipid classes besides PS, a wide range of lipid species deriving from both organisms was bound to our protein. The data about the lipid species bound to AtVPS13M1(1-335) are presented in Figure 2E and S2.

The effects on lipid composition of the mutants are not very drastic from what I can tell. Furthermore, how does this fit with the lipid composition of mitochondria where the protein appears to be mostly located?

It is true that lipid composition variations in the mutants are not drastic but still statistically significant. As a general point in the field of lipid transfer, it is not very common to have major changes in total lipidome on single mutants of lipid transfer proteins because of a high redundancy of lipid transport pathway in cells. This is particularly true for VPS13 proteins, as exemplified by multiple studies. Major lipid phenotypes can be revealed in specific conditions, such as phosphate starvation in our case, or when looking at specific organelles or specific tissues and/or developmental stages. This is explained and illustrated by examples in the discussion part p. 16 (line 526-532). In addition, as suggested by Reviewer 3, we performed further lipid analysis on calli and also on rosettes under Pi starvation and found a similar trend (Figure 4 and S4 of the revised version of the manuscript). Thus, we believe that, even if not drastic, these variations during Pi starvation are a real phenotype of our mutants.

As we found that our protein is located at the mitochondrial surface, we agree that Reviewer 1’s suggestion to perform lipidomic analyses on isolated mitochondria will be of high interest but this will be the scope of future studies that we will performed in our lab. First, we would like to identify all the organelles at which AtVPS13M1 is localized before performing subfractionations of these different organelles from the same pool of cell cultures grown in presence or absence of phosphate.

For the localization of the fusion protein, has it been tested whether the furoin is functional? This should be tested (e.g. by reversion of lipid composition).

As we did not observe major developmental phenotypes in our mutants, complementation should be indeed tested by performing lipidomic analyses in calli or plants grown in presence or absence of Pi, which is a time-consuming and expensive experiment. Because we used the fusions mainly for tissue expression study and subcellular localization and not for functional analyses, we believe that this is not an essential control to be performed for this work.

It is speculated that different splice forms are located to different compartments. Can that be tested and used to explain the observed subcellular location patterns?

Indeed some splice forms can modify the sequence of domains putatively involved in protein localization. This could be tested by producing synthetic constructs with one specific exon organization, which is challenging according to the size of AtVPS13M1 cDNA (around 12kb). In addition, our long-read sequencing experiment and PCR analyses revealed the existence of six transcripts, a major one representing around 92% and the five others representing less than 2.5% (Figure 1D). Among the five less abundant transcripts, four produce proteins with a premature stop codon and are likely to arise from splicing defects as explained in the discussion part p. 15 (lines 488-496). One produces a full-length protein with an additional loop in the VAB domain but because of the low abundance of this alternative transcript (1.4%), we believe it does not contribute significantly to the major localization we observed in plants and did not attend to analyze its localization.

GUS fusion data only probe promoter activity but not all levels of gene expression. That caveat should be discussed.

We are aware of this drawback and that is the reason why we fused the GUS enzyme directly to our protein expressed under its native locus (i.e. with endogenous promoter and exons/introns) as depicted in Figure 5A. Therefore, our construction allows to assess directly AtVPS13M1 protein level in plant tissues.

Minor points: 1. Extraplastidic DGDG and export from chloroplasts following phosphate derivation was first reported in PMID: 10973486.

We added this reference in the text.

Check throughout the correct usage of gene expression as genes are expressed and proteins produced.

Many thanks for this remark, we modified the text accordingly

In general, the paper is too long. Redundancies between introduction, results and discussion should be removed to streamline.

We reduced the text to avoid redundancy.

I suggest to redraw the excel graphs to increase line thickness and enlarge font size to increase presentation and readability.

We tried as much as we can to enlarge graphs and font size increasing readability.

Reviewer #1 (Significance (Required)):

Significance: Interorganellar lipid trafficking is an important topic and especially under studied in plants. Identifying components involved represents significant progress in the field. Similarly, lipid remodeling following phosphate derivation is an important phenomenon and the current advances our understanding.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary: The manuscript "AtVPS13M1 is involved in lipid remodelling in low phosphate and is located at the mitochondria surface in plants" by Leterme et al. identifies the protein VPS13M1 as a lipid transporter in Arabidopsis thaliana with important functions during phosphate starvation. The researchers were able to localise this protein to mitochondria via GFP-targeting in Arabidopsis. Although VPS13 proteins are well described in yeast and mammals, highlighting their importance in many vital cellular processes, there is very little information on them in plants. This manuscript provides new insights into plant VPS13 proteins and contributes to a better understanding of these proteins and their role in abiotic stress responses, such as phosphate starvation.

Major points: - Please describe and define the domains of the VPS13M1 protein in detail, providing also a figure for that. Figure 1 is mainly describing possible splice variants, whereas the characteristics of the protein are missing.

We have added information on AtVPS13M1 domain organization in the introduction (p.4, lines 103-109) and referred to Figure 1A that described protein domain organization. We did not added too much details as plant VPS13 protein domains organization was extensively described in two previous studies cited several times in the manuscript (Leterme et al., 2023; Levine, 2022).

• Please compare the expression level of VPS13M1 in the presence and in the absence of phosphate.

Many thanks for this suggestion. We performed qRT-PCR analyses of AtVPS13M1 from mRNA extracted from calli grown six days in presence and absence of phosphate. The results obtained did not reveal variations in mRNA level. The results were added in Figure S1A of the revised version of the manuscript and discussed in p.5 (lines 154-156).

• Page 9, second paragraph: Here, the lipid transport capability of AtVPS13M1 is described. Varying concentrations of this recombinant protein should be used in this test. Further, it is not highlighted, that a truncated version of VSP13M1 is able to transport lipids. This is surprising, since this truncated version is less than 10% of the total protein (only aa 1-335).

We agree with reviewer 2 that increasing protein concentration is an important control to perform. We included an experiment with an increasing quantity of protein (2X and 4X) in the revised version of the manuscript and showed that the signal intensity increased faster when protein concentration is higher (Figure 3D of the revised manuscript). As requested by Reviewer 3, we also included a negative control with Tom20.3 to show that the signal increase after the addition of AtVPS13M1(1-335) is specific to this protein (Figure 3C of the revised manuscript).

The transport ability of the N-terminal part of VPS13 was demonstrated in yeast and mammals VPS13D (Kumar et al., 2018; Wang et al., 2021). We highlighted this p. 7 (lines 213-218) of the revised version of the manuscript. This is explained by the inherent structure of VPS13 proteins that are composed of several repeats of the same domain type called RBG (for repeating β-groove), each forming a β-sheet with a hydrophobic surface. The higher the number of RBG repeats, the longer the hydrophobic tunnel is. The (1-335) N-terminal region corresponds to two RBG unit repeats forming a “small” tunnel able to bind and transfer lipids. The number of RBG repeats has influence on the quantity of lipids bound per protein in vitro, the longest the protein is, the highest the number of lipid molecules bound is (Kumar et al., 2018), but the effect on protein length on in vitro lipid transfer capacity has not been investigated yet to the best of our knowledge.

• Also, for phenotype analysis, T-DNA insertion mutants are used that still contain VPS13M1 transcripts. Although protein fragments where not detected by proteomic analysis, this might be due to low sensitivity of the proteomic assay. Further the lipid transport domain of VPS13M1 (aa 1-335) might not be affected by the T-DNA insertions at all. Here more detailed analysis needs to be done to prove that indeed loss-of protein function occurs in the mutants.

We do not have other methods than proteomic to test whether our mutants are KO or not. We tried unsuccessfully to produce antibodies. Mass spectrometry is the most sensitive method but the absence of detection indeed does not mean the absence of the protein. From proteomic data, we can conclude that at least, our mutants present a decrease in AtVPS13M1 protein level, thus we called them “knock down” in the revised version of the manuscript and added the following sentence p. 9 (lines 297-300): “As the absence of detection of a protein by mass spectrometry-based proteomics does not allow us to strictly claim the absence of this protein in the sample, we concluded that AtVPS13M1 expression in both atvps13m1-1 and atvps13m1-4 was below the detection limit and consider them as knock down (KD) for AtVPS13M1.”

• Localisation in mitochondria: As the Yepet signal is very weak, a control image of not transfected plant tissue needs to be included. Otherwise, it might be hard to distinguish the Yepet signal from background signal. The localisation data presented in Figure 5 does not allow the conclusion that VPS13M1 is localized at the surface of mitochondria as stated in the title. It only indicates (provided respective controls see above) that VPS13M1 is in mitochondria. Please provide more detailed analysis such as targeting to tobacco protoplasts, immunoblots or in vitro protein import assays. Also test +Pi vs. -Pi to see if VPS13M1 localisation is altered in dependence of Pi.

Indeed our Yepet signal is not very strong but on the experiments we performed on Col0 non-transformed plants, we did not very often see fluorescence background in the leaves’ vascular tissue, that is why we focused our study on this tissue. We sometimes observed some background signals in some cells that are clearly different from AtVPS13M1-3xYepet signals and never co-localized with mitochondria. Examples of these aspecific signals are presented in Figure S6E of the revised version of the manuscript.

We agree with reviewer 2 that our confocal images suggested, but not demonstrated, a localization at the surface of mitochondria. To confirm the localization, we generated calli cell cultures from AtVPS13M1-3xYepet lines and performed subcellular fractionations and western blot analyses confirming that AtVPS13M1 was indeed enriched in mitochondria and also in microsomal fractions (Figure 6G of the revised version). Then we performed mild proteolytic digestion of the isolated mitochondria with thermolysin and show that AtVPS13M1 was degraded, as the outer membrane protein Tom20.3, but not the inner membrane protein AtMic60, showing that AtVPS13M1 is indeed at the surface of mitochondria (Figure 5H of the revised manuscript). We believe that this experiment, in addition to the confocal images showing a signal around mitochondria, convincingly demonstrates that AtVPS13M1 is located at the surface of mitochondria.

The localization of AtVPS13M1 under Pi starvation is a very important question that we tried to investigate without success. Indeed, we intended to perform confocal imaging on seedlings grown in liquid media to easily perform Pi starvation as described for the analysis of AtVPS13M1 tissue expression with β-glucuronidase constructs. However, the level of fluorescence background was very high in seedlings and no clear differences between non-transformed and AtVPS13M1-3xYepet lines were observed, even in root tips where the protein is supposed to be the most highly expressed according to β-glucuronidase assays. Example of images obtained are presented in Figure R1. We concluded that the level of expression of our construct was too low in seedlings. The constructions of lines with a higher AtVPS13M1 expression level, by changing the promotor, to better analyze AtVPS13M1 in different tissues or in response to Pi starvation will be the scope of future work in our laboratory in order to investigate AtVPS13M1 localization under low Pi.

Phenotype analysis needs to be done under Pi stress and not under cold stress! Further, root architecture and root growth should also be done under Pi depletion. Here the title is also misleading, it is not at all clear why the authors switch from phosphate starvation to cold stress.

In the revised version of the manuscript, we analyzed the seedlings root growth of two mutants (atvps13m1-3 and m1-4) under low Pi and did not notice significant differences (Figure 7E, S7D of the revised version). We analyzed growth under cold stress because this stress also promotes remodeling of lipids, but we agree that it goes beyond the scope of this article that is focused on Pi starvation and we removed this part from the revised manuscript.

Minor points: Page 3, line 1: what does the abbreviation VPS stand for?

The definition of VPS (Vacuolar Protein Sorting) was added.

Page 3, line 1: change "amino acids residues" to "amino acid residues"

This was done.

Page 3, line 8 - 12: please rewrite this sentence. You write, that because of their distribution VPS13 proteins do exhibit many important physiological roles. The opposite is true: They are widely distributed in the cell because of their involvement in many physiological processes.

We changed the sentence to “ VPS13 proteins localize to a wide variety of membranes and membrane contact sites (MCSs) in yeast and human (Dziurdzik and Conibear, 2021). This broad distribution on different organelles and MCSs is important to sustain their important roles in numerous cellular and organellar processes such as meiosis and sporulation, maintenance of actin skeleton and cell morphology, mitochondrial function, regulation of cellular phosphatidylinositol phosphates level and biogenesis of autophagosome and acrosome (Dziurdzik and Conibear, 2021; Hanna et al., 2023; Leonzino et al., 2021).”

Page 6, line6: change "cDNA obtained from A. thaliana" to "cDNA generated from A. thaliana.

This was done.

Page 6, line 10: change" 7.6kb" to "7.6 kb"

This was done.

Page 7: address this question: can the isoforms form functional VPS13 proteins? This might help to postulate whether these isoforms are a result of defective splicing events.

We addressed this aspect in the discussion p.15 at lines 486-502.

Figure 2 B: Change "AtVPS13M1"to "AtVPS13M1(1-335)"

This was done.

Figure 2, legend: -put a blank before µM in each case.

This was done.

-Change 0,125µM to 0.125 µM

This was done.

-what does "in absence (A-0µM)" mean?

This means that the Acceptor liposomes are at 0 µM. To clarify, we changed it to “Acceptor 0 µM” in the revised version of the manuscript (Figure 3C).

-Which statistical analysis was employed?

We performed a non-parametric Mann-Whitney test in the revised version of the manuscript. This was indicated in the legend.

-Further, rewrite the sentence "Mass spectrometry (MS) analysis of lipids bound to AtVPS13M1(1-335) or Tom20 (negative control) after incubation with calli total lipids. Results are expresses in nmol of lipids per nmol of proteins (C) or in mol% (D)". -"C" and "D" are not directly comparable, as in "C" no Tom20 was used and in "C" no insect cells were used.

-Further, in "D" the experimental setup is not clear. AtVPS13(1-335) is supposed to be purified protein after incubation with calli lipids (figure 2, A). Further, in the same figure, lipid composition of "insect cells" and "calli-Pi" are compared àwhy? Please clarify this.

C and D are two different representations of the same results providing different types of information. In C., the results are expressed in nmol of lipids / nmol of proteins to assess 1) that the level of lipids found in AtVPS13M1(1-335) purifications is significantly higher than what we can expect from the background (assessed using Tom20) and 2) what are the classes of lipids that associate or not to AtVPS13M1(1-335). In D. the lipid distribution in mol% is presented for AtVPS13M1(1-335) as well as for total extracts from calli and insect cells to be able to compare if one lipid class is particularly enriched or not in AtVPS13M1(1-335) purifications compared to the initial extracts with which the protein was incubated. As an example, it allows to deduce that the absence of DGDG detected in the AtVPS13M1(1-335) purifications is not linked to a low level of DGDG in the calli extract, because it represented around 15 mol%, but likely to a weak affinity of the protein for this lipid. We did not represent the Tom20 lipid distribution on this graph because it represents background of lipid binding to the purification column and might suggest that Tom20 binds lipids. We changed the legend in this way and hope that it is clearer now: “C-D. Mass spectrometry (MS) analysis of lipids bound to AtVPS13M1(1-335) or Tom20 (negative control) after incubation with calli total lipids and repurification. Results are expresses in nmol of lipids per nmol of proteins in order to analyze the absolute quantity of the different lipid classes bound to AtVPS13M1(1-335) compared to Tom20 negative control (C), and in mol% to assess the global distribution of lipid classes in AtVPS13M1(1-335) purifications compared to the total lipid extract of insect cells and calli (D).”

Figure 3: -t-test requires a normal distribution of the data. This is not possible for an n=3. Please use an adequate analysis.

We performed more replicates and used non-parametric Mann-Whitney analyses in the revised version of the manuscript.

-Please clarify the meaning of the letters on the top of the bars in the legend.

This corresponded to the significance of t-tests performed in the first version of the manuscript that were reported in Table S3. As in the new version we performed Mann-Whitney tests, we highlighted the significance by stars and in the figure legends.

Please, make it clear that two figures belong to C.

This was clarified in the legend.

-Reorganise the order of figure 3 (AàBàCàD)

Because of the configuration of the different histograms presented in the figure, we were not able to change the order but we believed that the graphs can be easily red this way.

Page 10, 3. Paragraph: since the finding, that no peptides were found in the VSP13M1 ko lines, although transcription was not altered, is surprising, please include the proteomic data in the supplement

Proteomic data were deposited on PRIDE with the identifier PXD052019. They will remain not publicly accessible until the acceptance of the manuscript.

Page 11, line 17: The in vitro experiments showed a low affinity of VSP13M1 towards galactolipids. It is further claimed that this is consistent with the finding of the AtVSP13M1 Ko line in vivo, that in absence of PI, no change in DGDG content could be observed. However, the "absence" of VSP13M1 in vivo might still result in a bigger VSP13M1 protein, than the truncated form (1-335) used for the in vitro experiments

It is true that our in vitro experiments were performed only with a portion of AtVPS13M1 and that the length of the protein could influence protein binding specificity. We removed this assessment from the manuscript.

Page 13, lane 8: you should reconsider the use of a triple Yepet tag: If two or more identical fluorescent molecules are in close proximity, their fluorescence emission is quenched, which results in a weak signal (as the one that you obtained). See: Zhuang et al. 2000 (PNAS) Fluorescence quenching: A tool for single-molecule protein-folding study

Many thanks to point this paper. We use a triple Yepet because AtVPS13M1 has a very low level of expression and because this strategy was used successfully to visualize proteins for which the signal was below the detection level with a single GFP (Zhou et al., 2011). The quenching of the 3xYepet might also depend on the conformation they adopt on the targeting protein.

Page 13, line 14: change 1µm to 1 µm

This was done.

Page 13, line 29: please reduce the sentence to the first part: if A does not colocalize with B, it is not necessary to mention that B does not colocalise with A.

The sentence was modified accordingly.

Page 14, 2. Paragraph: it is not conclusive that phenotype analysis is suddenly conducted with plants under cold stress, since everything was about Pi-starvation and the role of VSP13M1. Lipid remodelling under Pi stress completely differs from the lipid remodelling under cold stress.

We eliminated this part in the revised version of the manuscript.

Page 14, line 20: change figure to Figure

This was done.

Page 07, line 17: change artifact to artefact

This was done.

Reviewer #2 (Significance (Required)):

General assessment: The paper is well written and technically sound. However, some points could be identified, that definitely need a revision. Overall, we got the impression that so far, the data gathered are still quite preliminary and need some more detailed investigations prior to publication (see major points).

Advance: The study definitely fills a gap of knowledge since not much is known on the function of plant VPS13 proteins so far.

Audience: The study is of very high interest to the plant lipid community but as well of general interest for Plant Molecular Biology and intracellular transport.

Our expertise: Plant membrane transport and lipid homeostasis.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

The manuscript by Leterme et al. (2024) describes the characterization of VPS13M1 from Arabidopsis. VPS13 proteins have been analyzed in yeast and animals, where they establish lipid transfer connections between organelles, but not much is known about VPS13 proteins in plants. First, different splicing forms were characterized, and the form A was identified as the most relevant one with 92% of the transcripts. The protein (just N-terminal 335 amino acids out of ca. 3000 amino acids) was expressed in insect cells and purified. Next, the protein was used for lipid binding assays with NBD-labeled lipids followed by analysis in polyacrylamide gel electrophoresis. VPS13M1 bound to PC, PE, PS and PA. Then, the protein from insect cells was incubated with Arabidopsis callus lipids, and lipids bound to VPS13M1 analyzed by LC-MS/MS. Lipid transfer between liposomes was measured by the change in fluorescence in donor liposomes derived from two labeled lipids after addition of the protein caused by lipid transfer and dilution to acceptor liposomes. T-DNA insertion mutants were isolated and the lipids measured in callus derived from these mutants. Protein localization in different plant organs was recorded with a GUS fusion construct transferred into transgenic plants. The protein was localized to mitochondria using a VPS13M1-Yepet fusion construct transferred into mutant plants. The mutant plants show no visible difference to wild type, even when the plants were grown under stress conditions like low temperature. The main message of the title is that VPS13M1 localizes to the mitochondria which is well documented, and it is involved in lipid remodeling under low phosphate conditions.

The lipid transfer assay shown in Figure 2F lacks a negative control. This would be the experiment with donor and acceptor liposomes in the presence of another protein like Tom20.

Many thanks for this suggestion. In the revised version of the manuscript, we performed a fluorescent lipid transport assay with Tom20.3 in the presence of 25 µM of donor liposomes and 1.5 mM of acceptor liposomes, the condition for which we observed a maximum of transport for AtVPS13M1(1-335). As expected, no fluorescence increase was observed. The results are presented in the Figure 3C of the revised manuscript.

The lipid data (Fig. 3 and Fig. S4) do not sufficiently support the second claim, i.e. that the protein is involved in lipid remodeling under low P. Data in Fig. 3C are derived from only 3 replicates and in Fig. S4 from only 2 replicas with considerable error bars. Having only 2 replicates is definitely not sufficient. Fig. 3C shows a suppression in the decrease in PE and PC at 4 d of P deprivation (significant for two mutants for PE, for only one for PC). Fig. S4A shows suppression of the decrease in PC at 6 d after P deprivation (significant for both mutants), but no significant effect on PE. Fig. 4SB shows no significant change in PE or PC at -P after 8 d of P deprivation. The data are not consistent. There are also problems with the statistics in Fig. 3 and Fig. S4. The authors used T-test, but place letters a, b, c on top of the bars. Usually, asterisks should be used to indicate significant differences. Data indicate medians and ranges, not mean and SD. In Fig. S4, how can you indicate median and range if you have only 2 replicates? Why did the authors use callus for lipid measurements? Why not use leaves and root tissues? What does adjusted nmol mean? What does the dashed line at 1.05 on the y axis mean? Taken together, I suggest to repeat lipid measurements with leaves and roots from plantets grown under +P and -P conditions in tissue culture with 5 replcates. Significant differences can be analyzed on the level of absolute (nmol per mg FW/DW) or relative (%) amounts.

Here are our answers to concerns about the design of our lipidomics experiments:

We used calli for lipid measurement because it is very easy to control growth conditions and to performed phosphate starvation from this cell cultures. The second reason is that it is a non-photosynthetic tissue with a high level of phospholipids and a low level of galactoglycerolipids and it is easier to monitor the modification of the balance phospholipids/galactoglycerolipids in this system. The lipid analysis on calli at 4 days of growth in presence or absence of Pi were performed on 3 biological replicates but on two different mutants (atvps13m-1 and m1-3) and we drew our conclusions based on variations that were significant for both mutants. In the revised version of the manuscript, we performed further lipidomic analyses on calli from Col0 and another mutant (atvps13m1-2) after 6 days of growth in presence or absence of Pi (Figure 4E, S4A-C, n=4-5) and added new data on a photosynthetic tissue (rosettes) from Col0 and atvps13m1-3 mutant. For rosettes analysis, seeds were germinated 4 days in plates with 1 mM Pi and then transferred on plates with 1 mM or 5 µM of Pi. Rosettes were harvested and lipids analyzed after 6 days (Figure 4F-G, S4D, n=4-5). All the data were represented with medians and ranges because we believe that median is less sensitive to extreme values than mean and might better represent what is occurring. Ranges highlight the minimal and maximal value of the data analyzed and we believe it is a representative view of the variability we obtained between biological samples.

Lipid measurement are done by mass spectrometry. As it was already reported, mass spectrometry quantification is not trivial as the intensity of the response depends on the nature of the molecule (for a review, see (Jouhet et al., 2024)). To counteract this ionisation problem, we developed a method with an external standard that we called Quantified Control (QC) corresponding to an A. thaliana callus lipid extract for which the precised lipid composition was determined by TLC and GC-FID. All our MS signals were “adjusted” to the signal of this QC as described in (Jouhet et al., 2017). Therefore our lipid measurement are in adjusted nmol. In material and method we modified the sentence accordingly p22 lines 720-723: “Lipid amounts (pmol) were adjusted for response differences between internal standards and endogenous lipids and by comparison with a quality control (QC).” This allows to represent all the lipid classes on a same graph and to have an estimation of the lipid classes distribution. To assess the significance of our results, we used in the revised version of the manuscript non-parametric Mann-Whitney tests and added stars representing the p-value on charts. This was indicated in the figure legends.

Here are our answers to concerns about the interpretation of our lipidomics experiments:

To summarize, in the revised version of the manuscript, lipid analyses were performed in calli from 3 different mutants (two at day 4, one at day 6) and in the rosettes from one of these mutants. All the results are presented in Figure 4 and S4. In all the experiments, we found that in +Pi, there is no major modifications in the lipid content or composition. In –Pi, we found that the total glycerolipid content is always higher in the mutant compared to the Col0, whatever the tissue or mutant considered (Figure 4A and S4A, D). In calli, this higher increase in lipid content is mainly due to an accumulation of phospholipids and in rosettes, of galactolipids. Because of high variability between our biological replicates, we did not always found significant differences in the absolute amount of lipids in –Pi. However, the analysis of the fold change in lipid content in –Pi vs +Pi always pointed toward a reduced extent of phospholipid degradation. We also added in these graphs the fold change for the total phospholipids and total galactolipids contents in the revised version of the manuscript. We believe that the new analyses we performed strengthen our conclusion about the role of AtVPS13M1 in phospholipid degradation and not on the recycling of precursors backbone to feed galactoglycerolipids synthesis at the chloroplast envelope.

Page 9, line 15: Please use the standard form of abbreviations of lipid molecular species with colon, e.g. PC32:0, not PC32-0

The lipid species nomenclature has been changed accordingly.

Page 11, line 4, (atvps13m1.1 and m1.3: please indicate the existence of mutant alleles with dashes, i.e. (atvps13m1-1 and atvps13m1-3

Names of the mutants have been changed accordingly.

Page 14, line 21: which line is indicated by atvps13m1.2-4? What does -4 indicate here?

This indicates that mutants m1-2 to m1-4 were analyzed.

Page 16, line 25: many abbreviations used here are very specific and not well known to the general audience e.g. ONT, IR, PTC, NMD etc. I think it is OK to mention them here, but still use the full terms, given that they are not used very frequently in the manuscript.

We kept ONT abbreviation because it was cited many times in both the results and discussion part. IR, PTC and NMD were cited only in the discussion and were eliminated.

Page 19, line 11. The authors cite Hsueh et al and Yang et al for LPTD1 playing a role in lipid homeostasis during P deficiency. But Yang et al. described the function of a SEC14 protein in Arabidopsis and rice during P deficiency. Is SEC14 related to LPTD1?

Many thanks for noticing this mistake. We removed the citation Yang et al. in the revised version of the manuscript.

Reference Tangpranomkorn et al. 2022: In the text, it says that this is a preprint, but in the Reference list, this is indicated with "Plant Biology" as Journal. In the internet, I could only find this manuscript in bioRxiv.

This manuscript was accepted in “New Phytologist” in December 2024 and is now cited accordingly in the new version of the manuscript.

Reviewer #3 (Significance (Required)):

The manuscript by Leterme et al describes the characterization of the lipid binding and transport protein VTPS13M1 from Arabidopsis. I think that the liposome assay needs to be done with a negative control. Furthermore, I have major concerns with the lipid data in Fig. 3C and Fig. S4. These lipid data of the current manuscript need to be redone. I do not agree that the lipid data allow the conclusion that "AtVPS13M1 is involved in lipid remodeling in low phosphate" as stated in the title.

References cited in this document:

Dziurdzik, S.K., and E. Conibear. 2021. The Vps13 Family of Lipid Transporters and Its Role at Membrane Contact Sites. Int J Mol Sci. 22:2905. doi:10.3390/ijms22062905.

Hanna, M., A. Guillén-Samander, and P. De Camilli. 2023. RBG Motif Bridge-Like Lipid Transport Proteins: Structure, Functions, and Open Questions. Annu Rev Cell Dev Biol. 39:409–434. doi:10.1146/annurev-cellbio-120420-014634.

Hanna, M.G., P.H. Suen, Y. Wu, K.M. Reinisch, and P. De Camilli. 2022. SHIP164 is a chorein motif lipid transfer protein that controls endosome–Golgi membrane traffic. Journal of Cell Biology. 221:e202111018. doi:10.1083/jcb.202111018.

Jouhet, J., E. Alves, Y. Boutté, S. Darnet, F. Domergue, T. Durand, P. Fischer, L. Fouillen, M. Grube, J. Joubès, U. Kalnenieks, J.M. Kargul, I. Khozin-Goldberg, C. Leblanc, S. Letsiou, J. Lupette, G.V. Markov, I. Medina, T. Melo, P. Mojzeš, S. Momchilova, S. Mongrand, A.S.P. Moreira, B.B. Neves, C. Oger, F. Rey, S. Santaeufemia, H. Schaller, G. Schleyer, Z. Tietel, G. Zammit, C. Ziv, and R. Domingues. 2024. Plant and algal lipidomes: Analysis, composition, and their societal significance. Progress in Lipid Research. 96:101290. doi:10.1016/j.plipres.2024.101290.

Jouhet, J., J. Lupette, O. Clerc, L. Magneschi, M. Bedhomme, S. Collin, S. Roy, E. Maréchal, and F. Rébeillé. 2017. LC-MS/MS versus TLC plus GC methods: Consistency of glycerolipid and fatty acid profiles in microalgae and higher plant cells and effect of a nitrogen starvation. PLoS ONE. 12:e0182423. doi:10.1371/journal.pone.0182423.

Kumar, N., M. Leonzino, W. Hancock-Cerutti, F.A. Horenkamp, P. Li, J.A. Lees, H. Wheeler, K.M. Reinisch, and P. De Camilli. 2018. VPS13A and VPS13C are lipid transport proteins differentially localized at ER contact sites. J Cell Biol. 217:3625–3639. doi:10.1083/jcb.201807019.

Leonzino, M., K.M. Reinisch, and P. De Camilli. 2021. Insights into VPS13 properties and function reveal a new mechanism of eukaryotic lipid transport. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1866:159003. doi:10.1016/j.bbalip.2021.159003.

Leterme, S., O. Bastien, R.A. Cigliano, A. Amato, and M. Michaud. 2023. Phylogenetic and Structural Analyses of VPS13 Proteins in Archaeplastida Reveal Their Complex Evolutionary History in Viridiplantae. Contact (Thousand Oaks). 6:1–23. doi:10.1177/25152564231211976.

Levine, T.P. 2022. Sequence Analysis and Structural Predictions of Lipid Transfer Bridges in the Repeating Beta Groove (RBG) Superfamily Reveal Past and Present Domain Variations Affecting Form, Function and Interactions of VPS13, ATG2, SHIP164, Hobbit and Tweek. Contact. 5:251525642211343. doi:10.1177/25152564221134328.

Valverde, D.P., S. Yu, V. Boggavarapu, N. Kumar, J.A. Lees, T. Walz, K.M. Reinisch, and T.J. Melia. 2019. ATG2 transports lipids to promote autophagosome biogenesis. J Cell Biol. 218:1787–1798. doi:10.1083/jcb.201811139.

Wang, J., N. Fang, J. Xiong, Y. Du, Y. Cao, and W.-K. Ji. 2021. An ESCRT-dependent step in fatty acid transfer from lipid droplets to mitochondria through VPS13D−TSG101 interactions. Nat Commun. 12:1252. doi:10.1038/s41467-021-21525-5.

Zhou, R., L.M. Benavente, A.N. Stepanova, and J.M. Alonso. 2011. A recombineering-based gene tagging system for Arabidopsis. Plant J. 66:712–723. doi:10.1111/j.1365-313X.2011.04524.x.

DEFINICIÓN

PROF NOTES - Political structures are crumbling and this is a transformative age for the youth. - Leans to Psychology (with AI and Environnment[Climate Change, Genetically modified food]) - Knows more on Asia, Europe & US. On Africa selectively. - Probably leans more left (mention of important issues such as Congo, Gaza) - Emphasizes why things are happening, find solutions, - Looking at different perspectives (racially and according to gender) - (indegenous communities & environmental crisis) - Born in France (did the whole nearly died thing) - A lot of grobe trotting, hiking around world - Background in Harvard, Stanford - Advisor for SPPH - Is a Farmer

K - Poli Sci heavily involved - Hiking

S - U of T - Colonialism - Baking

O - Honours - Environmental & Comparative - Close with Prof

There was a study by the U.S. Marine Corps comparing all-male units vs. mixed units(including one or two women) in marksanship, loading artillery shells, and similar. In 93 out of 134 tests, the all-male units won-In 2 o f the tests, the women won.

Câu trên sử dụng giọng điệu lạnh lùng để khắc họa cảm giác bất lực trước sự chia ly của Takaki. Cụm từ "vô ích vẫn hoàn vô ích" nhấn mạnh sự tuyệt vọng và bất khả kháng. Với câu"con người trở nên quen dần với mất mát" như để thể hiện tâm trạng đau buồn và chợt hiểu của bản thân anh.

Đoạn văn thể hiện dòng chảy nội tâm tinh tế qua những phút giây bất chợt nhận thức sâu sắc. Hình ảnh "Không phải nơi này" mang tính ám chỉ, phản ánh sự xa cách tinh thần giữa hai nhân vật. Không gian bình dị như bãi đậu xe càng tô đậm nỗi cô đơn và khát vọng tìm kiếm sự đồng điệu.

Tác gỉa sử dụng câu trên nhằm nhấn mạnh lên sự mong mỏi, nhớ nhung của Takaki khi anh không còn được ở bên Akari. Điều này được thể hiện qua nghệ thuật so sánh việc đọc như "thuộc lòng", cũng như điệp ngữ "Đọc" nhằm bộc lộ lên niềm mong nhớ của anh.

Qua câu n thể hiện một cảm xúc đầy buồn bã, âu sầu, như một lời luyến tiếc của chủ thể trữ tình. Tác giả kết hợp điệp ngữ "Quên chuyện đó đi..." cùng với dấu ba chấm ở cuối câu vừa để nhấn mạnh lên nỗi buồn của nhân vật, cũng như để thể hiện lên sự luyến tiếc.

Ponto central da crítica do trabalho

Whatup

DOI: 10.1126/science.adr0510

Resource: (BioLegend Cat# 393204, RRID:AB_2750089)

Curator: @scibot

SciCrunch record: RRID:AB_2750089

What is this?

Sobre #retos/sociopoliticos/pec3 > El desarrollo en África no puede estar medido por aquello que dicta Occidente. Cada contexto ha de poder decidir sobre lo que considera desarrollo. Además la cuestión de sostenibilidad es fundamental en África. [[Felwine Sarr]] no cree que el concepto sea puramente occidental ya que en África se tiene en cuenta la sostenibilidad -> la negociación con la naturaleza para ver qué sustracción, plantación o desarrollo se hace. Concepto de #epistemicidio como eso que ha ocurrido en África con la llegada de otra forma de mirar aquello que es importante en el saber, el compartir, el hacer.

Composição observa o limite máximo. De 9 a 55 Sempre um número ímpar. Aumenta de 2 em 2.

Lo primero sería establecer el conjunto de dependencias que hacen esta narrativa de datos reproducible, similar a como lo hacemos en la narrativa de cartofonías.

Por lo pronto se recomienda copiar los prerrequisitos faltantes en este documento de la otra narrativa y adaptarlos a esta. La reflexión a continuación aborda cómo podría hacerse desde las transclusiones.

La información podría ser transcluida en distintos documentos una vez le demos soporte a HastyScribe como exportador por omisión para los documentos de Grafoscopio/MiniDocs. Lo ideal sería que un documento inicial de prerrequisitos tenga copias en los repositorios de otros documentos, para facilitar la transclusión, pero que distintas copias apunten a ese documento original, de modo que se puedan coordinar entre sí, o mirar las bifurcaciones que ellos han tenido en la medida en que los documentos avanzan.

Una posibilidad sería combinar los alias de los documentos con el Hjson front matter, propuesto en la primera carta a Fabio, definiéndolas allí para que nifty sepa cómo descargarlas:

yaml tranclusions: { prerrequisites: https://external-repo.tld/prerrequisites--id.md }

Y luego se puedan insertar como snippets en una celda preambulo, pre-creada por MiniDocs (similar a la celda inicial de configuración de LiveBook):

{{ prerrequisitos -> prerrequisites--id.md}}

Para ser usada dentro del documento como:

{@ {{prerrequisitos}} @}

Nótese que acá estamos suponiendo que los prerrequisitos no necesitan offset y que HastyScribe soporta anidado de intrucciones, llamando un snippet dentro de una transclusión

Reviewer #2 (Public review):

Summary:

This paper aimed to determine the role EP sst+ neurons play in a probabilistic switching task.

Strengths:

- The in vivo recording of the EP sst+ neurons activity in the task is one of the strongest parts of this paper. Previous work had recorded from the EP-LHb population in rodents and primates in head fixed configurations, the recordings of this population in a freely moving context is a valuable addition to these studies and has highlighted more clearly that these neurons respond both at the time of choice and outcome.

- The use of a refined intersectional technique to record specifically the EP sst+ neurons is also an important strength of the paper. This is because previous work has shown that there are two genetically different types of glutamatergic EP neurons that project to the LHb. Previous work had not distinguished between these types in their recordings so the current results showing that the bidirectional value signaling is present in the EP sst+ population is valuable.

Weaknesses:

- One of the main weaknesses of the paper is to do with how the effect of the EP sst+ neurons on the behavior was assessed.

o All the manipulations (blocking synaptic release and blocking glutamatergic transmission) are chronic and more importantly the mice are given weeks of training after the manipulation before the behavioral effect is assessed. This means that as the authors point out in their discussion the mice will have time to adjust to the behavioral manipulation and compensate for the manipulations. The results do show that mice can adapt to these chronic manipulations and that the EP sst+ are not required to perform the task. What is unclear is whether the mice have compensated for the loss of EP sst+ neurons and whether they play a role in the task under normal conditions. Acute manipulations or chronic manipulations without additional training would be needed to assess this.

o Another weakness is that the effect of the manipulations was assessed in the 90/10 contingency version of the task. Under these contingencies, mice integrate past outcomes over fewer trials to determine their choice and animals act closer to a simple win-stay-lose switch strategy. Due to this it is unclear if the EP sst+ neurons would play a role in the task when they must integrate over a larger number of conditions in the less deterministic 70/30 version of the task. Indeed it is not clear that lesioning any other regions involved in evaluation of action outcomes such as VTA dopamine neurons, that encode reward prediction errors, would have any deficit when assessed in this way. Due to this, it's not clear if the mice have adapted to solve the task without evaluating action outcomes at all and are just acting in a more deterministic lose switch manner that would not presumably involve any of the circuitry in evaluating action outcomes.

- The authors conclude that they do not see any evidence for bidirectional prediction errors. It is not possible to conclude this. First, they see a large response in the EP sst+ neurons to the omission of an expected reward. This is what would be expected of a negative reward prediction error. There are much more specific well controlled tests for this that are commonplace in head-fixed and freely moving paradigms that could be tested to probe this. The authors do look at the effect of previous trials on the response and do not see strong consistent results, but this is not a strong formal test of what would be expected of a prediction error, either a positive or negative. The other way they assess this is by looking at the size of the responses in different recording sessions with different reward contingencies. They claim that the size of the reward expectation and prediction error should scale with the different reward probabilities. If all the reward probabilities were present in the same session this should be true as lots of others have shown for RPE. Because however this data was taken from different sessions it is not expected that the responses should scale, this is because reward prediction errors have been shown to adaptively scale to cover the range of values on offer (Tobler et al., Science 2005). A better test of positive prediction error would be to give a larger than expected reward on a subset of trials. Either way there is already evidence that responses reflect a negative prediction error in their data and more specific tests would be needed to formally rule in or out prediction error coding especially as previous recordings have shown it is present in previous primate and rodent recordings.

- There are a lot of variables in the GLM that occur extremely close in time such as the entry and exit of a port. If two variables occur closely in time and are always correlated it will be difficult if not impossible for a regression model to assign weights accurately to each event. This is not a large issue, but it is misleading to have regression kernels for port entry and exits unless the authors can show these are separable due to behavioral jitter or a lack of correlation under specific conditions, which does not seem to be the case.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The manuscript by Bell et. al. describes an analysis of the effects of removing one of two mutually exclusive splice exons at two distinct sites in the Drosophila CaV2 calcium channel Cacophony (Cac). The authors perform imaging and electrophysiology, along with some behavioral analysis of larval locomotion, to determine whether these alternatively spliced variants have the potential to diversify Cac function in presynaptic output at larval neuromuscular junctions. The author provided valuable insights into how alternative splicing at two sites in the calcium channel alters its function.

Strengths:

The authors find that both of the second alternatively spliced exons (I-IIA and I-IIB) that are found in the intracellular loop between the 1st and second set of transmembrane domains can support Cac function. However, loss of the I-IIB isoform (predicted to alter potential beta subunit interactions) results in 50% fewer channels at active zones and a decrease in neurotransmitter release and the ability to support presynaptic homeostatic potentiation. Overall, the study provides new insights into Cac diversity at two alternatively spliced sites within the protein, adding to our understanding of how regulation of presynaptic calcium channel function can be regulated by splicing.

Weaknesses:

The authors find that one splice isoform (IS4B) in the first S4 voltage sensor is essential for the protein's function in promoting neurotransmitter release, while the other isoform (IS4A) is dispensable. The authors conclude that IS4B is required to localize Cac channels to active zones. However, I find it more likely that IS4B is required for channel stability and leads to the protein being degraded, rather than any effect on active zone localization. More analysis would be required to establish that as the mechanism for the unique requirement for IS4B.

(1) We thank the reviewer for this important point. In fact, all three reviewers raised the same question, and the reviewing editor pointed out that caution or additional experiments were required to distinguish between IS4 splicing being important for cac channel localization versus channel stability/degradation. We provide multiple sets of experiments as well as text and figure revisions to strengthen our claim that the IS4B exon is required for cacophony channels to enter motoneuron presynaptic boutons and localize to active zones.

a. If IS4B was indeed required for cac channel stability (and not for localization to active zones) IS4A channels should be instable wherever they are. This is not the case because we have recorded somatodendritic cacophony currents from IS4A expressing adult motoneurons that were devoid of cac channels with the IS4B exon. Therefore, IS4A cac channels are not instable but underlie somatodendritic voltage dependent calcium currents in these motoneurons. These new data are now shown in the revised figure 3C and referred to in the text on page 7, line 42 to page 8 line 9.

b. Similarly, if IS4B was required for channel stability, it should not be present anywhere in the nervous system. We tested this by immunohistochemistry for GFP tagged IS4A channels in the larval CNS. Although IS4A channels are sparsely expressed, which is consistent with low expression levels seen in the Western blots (Fig. 1E), there are always defined and reproducible patterns of IS4A label in the larval brain lobes as well as in the anterior part of the VNC. This again shows that the absence of IS4A from presynaptic active zones is not caused by channel instability, because the channel is expressed in other parts of the nervous system. These data are shown in the new supplementary figure 1 and referred to in the text on page 15, lines 3 to 8.

c. As suggested in a similar context by reviewers 1 and 2, we now show enlargements of the presence of IS4B channels in presynaptic active zones as well as enlargements of the absence of IS4A channels in presynaptic active zones in the revised figures 2A-C and 3A. In these images, no IS4A label is detectable in active zones or anywhere else throughout the axon terminals, thus indicating that IS4B is required for expressing cac channels in the axon terminal boutons and localizing it to active zones. Text and figure legends have been adjusted accordingly.

d. Related to this, reviewer 1 also recommended to quantify the IS4A and ISB4 channel intensity and co-localization with the active zone marker brp (recommendation for authors). After following the reviewers’ suggestion to adjust the background values in IS4A and IS4B immunolabels to identical (revised Figs. 2A-C), it becomes obvious that IS4A channel are not detectable above background in presynaptic terminals or active zones, thus intensity is close to zero. We still calculated the Pearsons co-localization coefficient for both IS4 variants with the active zone marker brp. For IS4B channels the Pearson’s correlation coefficient is control like, just above 0.6, whereas for IS4A channels we do not find colocalization with brp (Pearson’s below 0.25). These new analyses are now shown in the revised figure 2D and referred to on page 6, lines 33 to 38.

e. Consistent with our finding that IS4B is required for cac channel localization to presynaptic active zones, upon removal of IS4B we find no evoked synaptic transmission (Fig. 2 in initial submission, now Fig. 3B).

Together these data are in line with a unique requirement of IS4B at presynaptic active zones (not excluding additional functions of IS4B), whereas IS4A containing cac isoforms are not found in presynaptic active zones and mediate different functions.

Reviewer #2 (Public Review):

This study by Bell et al. focuses on understanding the roles of two alternatively spliced exons in the single Drosophila Cav2 gene cac. The authors generate a series of cac alleles in which one or the other mutually exclusive exons are deleted to determine the functional consequences at the neuromuscular junction. They find alternative splicing at one exon encoding part of the voltage sensor impacts the activation voltage as well as localization to the active zone. In contrast, splicing at the second exon pair does not impact Cav2 channel localization, but it appears to determine the abundance of the channel at active zones.

Together, the authors propose that alternative splicing at the Cac locus enables diversity in Cav2 function generated through isoform diversity generated at the single Cav2 alpha subunit gene encoded in Drosophila.

Overall this is an excellent, rigorously validated study that defines unanticipated functions for alternative splicing in Cav2 channels. The authors have generated an important toolkit of mutually exclusive Cac splice isoforms that will be of broad utility for the field, and show convincing evidence for distinct consequences of alternative splicing of this single Cav2 channel at synapses. Importantly, the authors use electrophysiology and quantitative live sptPALM imaging to determine the impacts of Cac alternative splicing on synaptic function. There are some outstanding questions regarding the mechanisms underlying the changes in Cac localization and function, and some additional suggestions are listed below for the authors to consider in strengthening this study. Nonetheless, this is a compelling investigation of alternative splicing in Cav2 channels that should be of interest to many researchers.

(2) We believe that the additional data on cac IS4A isoform localization and function as detailed above (response to public review 1) has strengthened the manuscript and answered some of the remaining questions the reviewer refers to. We are also grateful for the specific additional reviewer suggestions which we have addressed point-by-point and refer to below (section recommendations for authors).

Reviewer #3 (Public Review):

Summary:

Bell and colleagues studied how different splice isoforms of voltage-gated CaV2 calcium channels affect channel expression, localization, function, synaptic transmission, and locomotor behavior at the larval Drosophila neuromuscular junction. They reveal that one mutually exclusive exon located in the fourth transmembrane domain encoding the voltage sensor is essential for calcium channel expression, function, active zone localization, and synaptic transmission. Furthermore, a second mutually exclusive exon residing in an intracellular loop containing the binding sites for Caβ and G-protein βγ subunits promotes the expression and synaptic localization of around ~50% of CaV2 channels, thereby contributing to ~50% of synaptic transmission. This isoform enhances release probability, as evident from increased short-term depression, is vital for homeostatic potentiation of neurotransmitter release induced by glutamate receptor impairment, and promotes locomotion. The roles of the two other tested isoforms remain less clear.

Strengths:

The study is based on solid data that was obtained with a diverse set of approaches. Moreover, it generated valuable transgenic flies that will facilitate future research on the role of calcium channel splice isoforms in neural function.

Weaknesses:

(1) Based on the data shown in Figures 2A-C, and 2H, it is difficult to judge the localization of the cac isoforms. Could they analyze cac localization with regard to Brp localization (similar to Figure 3; the term "co-localization" should be avoided for confocal data), as well as cac and Brp fluorescence intensity in the different genotypes for the experiments shown in Figure 2 and 3 (Brp intensity appears lower in the dI-IIA example shown in Figure 3G)? Furthermore, heterozygous dIS4B imaging data (Figure 2C) should be quantified and compared to heterozygous cacsfGFP/+.

According to the reviewer’s suggestion, we have quantified cac localization relative to brp localization by computing the Pearson’s correlation coefficient for controls and IS4A as well as IS4B animals. These new data are shown in the revised Fig. 2D and referred to on page 6, lines 33-38. Furthermore, we now confirm control-like Pearson’s correlation coefficients for all exon out variants except ΔIS4B and show Pearson’s correlation coefficients for all genotypes side-by-side in the revised Fig. 4D (legend has been adjusted accordingly). In addition, in response to the recommendations to authors, we now provide selective enlargements for the co-labeling of Brp and each exon out variant in the revised figures 2-4. We have also adjusted the background in Fig. 2C (ΔIS4B) to match that in Figs. 2A and B (control and ΔIS4A). This allows a fair comparison of cac intensities following excision of IS4B versus excision of IS4A and control (see also Fig 3). Together, this demonstrates the absence of IS4A label in presynaptic active zones much clearer. As suggested, we have also quantified brp puncta intensity on m6/7 across homozygous exon excision mutants and found no differences (this is now stated for IS4A/IS4B in the results text on page 6, lines 37/38 and for I-IIA/I-IIB on page 8, lines 42-44.). We did not quantify the intensity of cacophony puncta upon excision of IS4B because the label revealed no significant difference from background (which can be seen much better in the images now), but the brp intensities remained control-like even upon excision of IS4B.

(2) They conclude that I-II splicing is not required for cac localization (p. 13). However, cac channel number is reduced in dI-IIB. Could the channels be mis-localized (e.g., in the soma/axon)? What is their definition of localization? Could cac be also mis-localized in dIS4B? Furthermore, the Western Blots indicate a prominent decrease in cac levels in dIS4B/+ and dI-IIB (Figure 1D). How do the decreased protein levels seen in both genotypes fit to a "localization" defect? Could decreased cac expression levels explain the phenotypes alone?

We have now precisely defined what we mean by cac localization, namely the selective label of cac channels in presynaptic active zones that are defined as brp puncta, but no cac label elsewhere in the presynaptic bouton (page 6, lines 18 to 20). On the level of CLSM microscopy this corresponds to overlapping cac puncta and brp puncta, but no cac label elsewhere in the bouton. Based on the additional analysis and data sets outlined in our response 1 (see above) we conclude that excision of IS4B does not cause channel mislocalization because we find reproducible expression patterns elsewhere in the nervous system as well as somatodendritic cac current in ΔIS4B (for detail see above). Therefore, the isoforms containing the mutually exclusive IS4A exon are expressed and mediate other functions, but cannot substitute IS4B containing isoforms at the presynaptic AZ. In fact, our Western blots are in line with reduced cac expression if all isoforms that mediate evoked release are missing, again indicating that the presynapse specific cac isoforms cannot be replaced by other cac isoforms. This is also in line with the sparse expression of IS4A throughout the CNS as seen in the new supplementary figure 1 (for detail see above).

(3) Cac-IS4B is required for Cav2 expression, active zone localization, and synaptic transmission. Similarly, loss of cac-I-IIB reduces calcium channel expression and number. Hence, the major phenotype of the tested splice isoforms is the loss of/a reduction in Cav2 channel number. What is the physiological role of these isoforms? Is the idea that channel numbers can be regulated by splicing? Is there any data from other systems relating channel number regulation to splicing (vs. transcription or post-transcriptional regulation)?

Our data are not consistent with the idea that splicing regulates channel numbers. Rather, splicing can be used to generate channels with specific properties that match the demand at the site of expression. For the IS4 exon pair we find differences in activation voltage between IS4A and IS4B channels (revised Fig. 3C), with IS4B being required for sustained HVA current. IS4A does not localize to presynaptic active zones at the NMJ and is only sparsely expressed elsewhere in the NS (new supplementary Fig. 1). By contrast, IS4B is abundantly expressed in many neuropils. Therefore, taking out IS4B takes out the more abundant IS4 isoform. This is consistent with different expression levels for IS4 isoforms that have different functions, but we do not find evidence for splicing regulating expression levels per se.

Similarly, the I-II mutually exclusive exon pair differs markedly in the presence or absence of G-protein βγ binding sites that play a role in acute channel regulation as well the conservation of the sequence for β-subunit binding (see page 5, lines 9-17). Channel number reduction in active zones occurs specifically if expression of the cac channels with the G_βγ-binding site as well as the more conserved β-subunit binding is prohibited by excision of the I-IIB exon (see Fig. 5F). Vice versa, excision of I-IIA does not result in reduced channel numbers. This scenario is consistent with the hypothesis that conserved β-subunit binding affects channel number in the active zone (see page 17, lines 3 to 6 and lines 33-36), but we have no evidence that I-II splicing per se affects channel number.

(4) Although not supported by statistics, and as appreciated by the authors (p. 14), there is a slight increase in PSC amplitude in dIS4A mutants (Figure 2). Similarly, PSC amplitudes appear slightly larger (Figure 3J), and cac fluorescence intensity is slightly higher (Figure 3H) in dI-IIA mutants. Furthermore, cac intensity and PSC amplitude distributions appear larger in dI-IIA mutants (Figures 3H, J), suggesting a correlation between cac levels and release. Can they exclude that IS4A and/or I-IIA negatively regulate release? I suggest increasing the sample size for Canton S to assess whether dIS4A mutant PSCs differ from controls (Figure 2E). Experiments at lower extracellular calcium may help reveal potential increases in PSC amplitude in the two genotypes (but are not required). A potential increase in PSC amplitude in either isoform would be very interesting because it would suggest that cac splicing could negatively regulate release.

There are several possibilities to explain this, but as none of the effects is statistically significant, we prefer to not investigate this in further depth. However, given that we cannot find IS4A in presynaptic active zones (revised figures 2C and 3A plus the new enlargements 2Ci and 3Ai, revised text page 6, lines 22 to 24 and 29 to 31, and page 7, second paragraph, same as public response 1D) IS4A channels cannot have a direct negative effect on release probability. Nonetheless, given that IS4A containing cac isoforms mediate functions in other neuronal compartments (see revised Fig. 3C) it may regulate release indirectly by affecting e.g. action potential shape. Moreover, in response to the more detailed suggestions to authors we provide new data that give additional insight.

(5) They provide compelling evidence that IS4A is required for the amplitude of somatic sustained HVA calcium currents. However, the evidence for effects on biophysical properties and activation voltage (p. 13) is less convincing. Is the phenotype confined to the sustained phase, or are other aspects of the current also affected (Figure 2J)? Could they also show the quantification of further parameters, such as CaV2 peak current density, charge density, as well as inactivation kinetics for the two genotypes? I also suggest plotting peaknormalized HVA current density and conductance (G/Gmax) as a function of Vm. Could a decrease in current density due to decreased channel expression be the only phenotype? How would changes in the sustained phase translate into altered synaptic transmission in response to AP stimulation?

Most importantly, sustained HVA current is abolished upon excision of IS4B (not IS4A, we think the reviewer accidentally mixed up the genotype) and presynaptic active zones at the NMJ contain only cac isoforms with the IS4B exon. This indicates that the cac isoforms that mediate evoked release encode HVA channels. The somatodendritic currents shown in the revised figure 3C (previously 2J) that remain upon excision of IS4B are mediated by IS4A containing cac isoforms. Please note that these never localize to the presynaptic active zone, and thus do not contribute to evoked release. Therefore, the interpretation is that specifically sustained HVA current encoded by IS4B cac isoforms is required for synaptic transmission. Reduced cac current density due to decreased channel expression is not the cause for impaired evoked release upon IS4B excision, but instead, the cause is the absence of any cac channels in active zones. IS4B-containing cac isoforms encode sustained HVA current, and we speculate that this might be a well suited current to minimize cacophony channel inactivation in the presynaptic active zone. Given that HVA current shows fast voltage dependent activation and fast inactivation upon repolarization, it is useful at large intraburst firing frequencies as observed during crawling (Kadas et al., 2017) without excessive cac inactivation (see page 15, Kadas, lines 16 to 20).

However, we agree with the reviewer that a deeper electrophysiological analysis of splice isoform specific cac currents will be instructive. We have now added traces of control and ΔIS4B from a holding potential of -90 mv (revised Fig. 3C, bottom traces and revised text on page 7, line 43 to page 8, lines 1 to 10), and these are also consistent with IS4B mediating sustained HVA cac current. However, further analysis of activation and inactivation voltages and kinetics suffers form space clamp issues in recordings from the somata of such complex neurons (DLM motoneurons of the adult fly contain roughly 6000 µm of dendrites with over 4000 branches, Ryglewski et al., 2017, Neuron 93(3):632-645). Therefore, we will analyze the currents in a heterologous expression system and present these data to the scientific community as a separate study at a later time point.

(6) Why was the STED data analysis confined to the same optical section, and not to max. intensity z-projections? How many and which optical sections were considered for each active zone? What were the criteria for choosing the optical sections? Was synapse orientation considered for the nearest neighbor Cac - Brp cluster distance analysis? How do the nearest-neighbor distances compare between "planar" and "side-view" Brp puncta?

Maximum intensity z-projections would be imprecise because they can artificially suggest close proximity of label that is close by in x and y but far away in z. Therefore, the analysis was executed in xy-direction of various planes of entire 3D image stacks. We considered active zones of different orientations (Figs. 5C, D) to account for all planes. In fact, we searched the entire z-stacks until we found active zones of all orientations within the same boutons, as shown in figures 5C1-C6. The same active zone orientations were analyzed for all exon-out mutants with cac localization in active zones. The distance between cac and brp did not change if viewed from the side or any other orientation. We now explain this in more clarity in the results text on page 9, lines 23/24.

(7) Cac clusters localize to the Brp center (e.g., Liu et al., 2011). They conclude that Cav2 localization within Brp is not affected in the cac variants (p. 8). However, their analysis is not informative regarding a potential offset between the central cac cluster and the Brp "ring". Did they/could they analyze cac localization with regard to Brp ring center localization of planar synapses, as well as Brp-ring dimensions?

In the top views (planar) we did not find any clear offset in cac orientation to brp between genotypes. In such planar synapses (top views, Fig. 5D, left row) we did not find any difference in Brp ring dimensions. We did not quantify brp ring dimensions rigorously, because this study focusses on cac splice isoform-specific localization and function. Possible effects of different cac isoforms on brp-ring dimensions or other aspects of scaffold structure are not central to our study, in particular given that brp puncta are clearly present even if cac is absent from the synapse (Fig. 3A), indicating that cac is not instructive for the formation of the brp scaffold.

(8) Given the accelerated PSC decay/ decreased half width in dI-IIA (Fig. 5Q), I recommend reporting PSC charge in Figure 3, and PPR charge in Figures 5A-D. The charge-based PPRs of dI-IIA mutants likely resemble WT more closely than the amplitude-based PPR. In addition, miniature PSC decay kinetics should be reported, as they may contribute to altered decay kinetics. How could faster cac inactivation kinetics in response to single AP stimulation result in a decreased PSC half-width? Is there any evidence for an effect of calcium current inactivation on PSC kinetics? On a similar note, is there any evidence that AP waveform changes accelerate PSC kinetics? PSC decay kinetics are mainly determined by GluR decay kinetics/desensitization. The arguments supporting the role of cac splice isoforms in PSC kinetics outlined in the discussion section are not convincing and should be revised.

We agree that reporting charge in figure 3 is informative and do so in the revised text. Since the result (no significant difference in the PSCs between between CS, cac^GFP, ^ΔI-IIA, and transheterozygous I-IIA/I-IIB, but significantly smaller values in ΔI-IIB) remained unchanged no matter whether charge or amplitude were analyzed, we decided to leave the figure as is and report the additional analysis in the text (page 8, lines 40 to 42). This way, both types of analysis are reported. Please note that EPSC amplitude is slightly but not significantly increased upon excision of I-IIA (Fig. 4J), whereas EPSC half amplitude width is significantly smaller (Fig. 5Q, now revised Fig 6R). Together, a tendency of increased EPSC amplitudes and smaller half amplitude width result in statistically insignificant changes in EPSC in ∆I-IIA (now discussed on page 15, lines 37 to 40). We also understand the reviewer’s concern attributing altered EPSC kinetics to presynaptic cac channel properties. We have toned down our interpretation in the discussion and list possible alterations in presynaptic AP shape or cac channel kinetics as alternative explanations (not conclusions; see revised discussion on page 15, line 40 to page 16, line 2). Moreover, we have quantified postsynaptic GluRIIA abundance to test whether altered PSC kinetics are caused by altered GluRIIA expression. In our opinion, the latter is more instructive than mini decay kinetic analysis because this depends strongly on the distance of the recording electrode to the actual site of transmission in these large muscle cells. Although we find no difference in GluRIIA expression levels we now clearly state that we cannot exclude other changes in GluR receptor fields, which of course, could also explain altered PSC kinetics. We have updated the discussion on page 16, lines 2/3 accordingly.

(9) Paired-pulse ratios (PPRs): On how many sweeps are the PPRs based? In which sequence were the intervals applied? Are PPR values based on the average of the second over the first PSC amplitudes of all sweeps, or on the PPRs of each sweep and then averaged? The latter calculation may result in spurious facilitation, and thus to the large PPRs seen in dI-IIB mutants (Kim & Alger, 2001; doi: 10.1523/JNEUROSCI.21-2409608.2001).

We agree that the PP protocol and analyses had to be described more precisely in the methods and have done so on page 23, lines 31 to 37 in the methods. Mean PPR values are based on the PPRs of each sweep and then averaged. We are aware of the study of Kim and Alger 2001 and have re-analyzed the PP data in both ways outlined by the reviewer. We get identical results with either analyses method. Spurious facilitation is thus not an issue in our data. We now explain this in the methods section along with the PPR protocol. The large spread seen in dI-IIB is indeed caused by reduced calcium influx into active zones with fewer channels, as anticipated by the reviewer (see next point).

(10) Could the dI-IIB phenotype be simply explained by a decrease in channel number/ release probability? To test this, I propose investigating PPRs and short-term dynamics during train stimulation at lower extracellular Ca2+ concentration in WT. The Ca2+ concentration could be titrated such that the first PSC amplitude is similar between WT and dI-IIB mutants. This experiment would test if the increased PPR/depression variability is a secondary consequence of a decrease in Ca2+ influx, or specific to the splice isoform.

In fact, the interpretation that decreased PSC amplitude upon I-IIB excision is caused mainly by reduced channel number is precisely our interpretation (see discussion page 14, last paragraph to page 15, first paragraph in the original submission, now page 16, second paragraph paragraph). In addition, we are grateful for the reviewer’s suggestion to triturate the external calcium such that the first PSC amplitude in matches in ∆I-IIB and control. This experiment tests whether altered short term plasticity is solely a function of altered channel number or whether additional causes, such as altered channel properties, also play into this. We triturated the first pulse amplitude in ∆I-IIB to match control and find that paired pulse ratio and the variance thereof are not different anymore. Therefore, the differences observed in identical external calcium can be fully explained by altered channel numbers. This additional dataset is shown in the revised figures 6D and E and referred to in the results section on page 10, lines 14 to 25 and the discussion on page16, lines 36 to 38.

(11) How were the depression kinetics analyzed? How many trains were used for each cell, and how do the tau values depend on the first PSC amplitude? Time constants in the range of a few (5-10) milliseconds are not informative for train stimulations with a frequency of 1 or 10 Hz (the unit is missing in Figure 5H). Also, the data shown in Figures 5E-K suggest slower time constants than 5-10 ms. Together, are the data indeed consistent with the idea that dIIIB does not only affect cac channel number, but also PPR/depression variability (p. 9)?

For each animal the amplitudes of all subsequent PSCs in each train were plotted over time and fitted with a single exponential. For depression at 1 and 10 Hz, we used one train per animal, and 5-6 animals per genotype (as reflected in the data points in Figs. 6I, M). This is now explained in more detail in the revised methods section (page 23, lines 39 to 41). The tau values are not affected by the amplitude of the first PSC. First, we carefully re-fitted new and previously presented depression data and find that the taus for depression at low stimulation frequencies (1 and 10Hz) are not affected by exon excisions at the I-II site. We thank the reviewer for detecting our error in units and tau values in the previous figure panels 5H and L (this has now been corrected in the revised figure panels 6I and M). Given that PSC amplitude upon I-IIB excision is significantly smaller than in controls and following I-IIA excision, we suspected that the time course of depression at low stimulation frequency is not significantly affected by the amount of calcium influx during the first PSC. To further test this, we followed the reviewer ’s suggestion and re-measured depression at 1 and 10 Hz for cac-GFP controls and for delta I-IIB in a higher external calcium concentration (1.8 mM), so that the first PSC was increased in amplitude in both genotypes (1.8 mM external calcium triturates the PSC amplitude in delta I-IIB to match that of controls measured in 0.5 mM external calcium, see revised Figs. 6H, L). Neither in control, nor in delta I-IIB did this affect the time course of synaptic depression (see revised Figs. 6I, M). This indicates that at low stimulation frequencies (1 and 10Hz) the time course of depression is not affected by mean quantal content. This is consistent with the paired pulse ratio at 100 ms interpulse interval shown in figures 6A-D. However, for synaptic depression at 1 Hz stimulation the variability of the data is higher for delta I-IIB (independent of external calcium concentration, see rev. Fig. 6I), which might also be due to reduced channel number in this genotype. Taken together, the data are in line with the idea that altered cac channel numbers in active zones are sufficient to explain all effects that we observe upon I-IIB excision on PPRs and synaptic depression at low stimulation frequencies. This is now clarified in the revised text on page 12, lines 3 to 7.

(12) The GFP-tagged I-IIA and mEOS4b-tagged I-IIB cac puncta shown in Figure 6N appear larger than the Brp puncta. Endogenously tagged cac puncta are typically smaller than Brp puncta (Gratz et al., 2019). Also, the I-IIA and I-IIB fluorescence sometimes appear to be partially non-overlapping. First, I suggest adding panels that show all three channels merged. Second, could they analyze the area and area overlap of I-IIA and I-IIB with regard to each other and to Brp, and compare it to cac-GFP? Any speculation as to how the different tags could affect localization? Finally, I recommend moving the dI-IIA and dI-IIB localization data shown in Figure 6N to an earlier figure (Figure 1 or Figure 3).

We now show panels with the two I-II cac isoforms merged in the revised figure 7H (previously 6N). We also tested merging all three labels as suggested, but found this not instructive for the reader. We thank the reviewer for pointing out that the Brp puncta appeared smaller than the cac puncta in some panels. We carefully went through the data and found that the Brp puncta are not systematically smaller than the cac puncta. Please note that punctum size can appear quite differently, depending on different staining qualities as well as different laser intensities and different point spread in different imaging channels. The purpose of this figure was not to analyze punctum size and labeling intensity, but instead, to demonstrate that I-IIA and I-IIB are both present in most active zones, but some active zones show only I-IIB labeling, as quantified in figure 7I. We did not follow the suggestion to conduct additional co-localization analyses and compare it with cac-GFP controls, because Pearson co-localization coefficients for cac-GFP and all exon-out variants analyzed, including delta I-IIA and delta I-IIB are presented in the revised figure 4D. Moreover, delta I-IIA and delta I-IIB show similar Manders 1 and 2 co-localization coefficients with Brp (see Figs. 4E, F). We do not want to speculate whether the different tags have any effect on localization precision. Artificial differences in localization precision can also be suggested by different antibodies, but we know from our STED analyses with identical tags and antibodies for all isoforms that I-IIA and I-IIB co-localize identically with Brp (see Figs. 5A-E). Finally, we prefer to not move the figure because we believe it is informative to show our finding that active zones usually contain both splice I-II variants together with the finding that only I-IIB is required for PHP.

Recommendations for the authors:

Reviewing Editor Comments:

We thank you for your submission. All three reviewers urge caution in interpreting the S4 splice variant playing a role specifically in Cac localization, as opposed to just leading to instability and degradation. There are other issues with the electrophysiological experiments, a need for improved imaging and analyses, and some areas of interpretation detailed in the reviews.

We agree that additional data was required to conclude that IS4 splicing plays a specific role in cac channel localization and is not just leading to channel instability and degradation. As outlined in detail in our response to reviewer 1, comment 1, we conducted several sets of experiments to support our interpretation. First, electrophysiological experiments show that upon removal of IS4B, which eliminates synaptic transmission at the larval NMJ and cac positive label in presynaptic active zones, somatodendritic cac current is reliably recorded (new data in revised figure 3C). This is not in line with a channel instability or degradation effect, but instead with IS4B containing isoforms being required and sufficient for evoked release from NMJ motor terminals, whereas IS4A isoforms are not sufficient for evoked release from axon terminals, but IS4A isoforms alone can mediate a distinct component of somatodendritic calcium current. Second, immunohostochemical analyses reveal that IS4A, which is not present in NMJ presynaptic active zones, is expressed sparsely, but in reproducible patterns in the larval brain lobes and in specific regions of the anterior VNC parts (new supplementary figure 1). Again, the absence of a IS4A-containing cac isoform from presynaptic active zones but their simultaneous presence in other parts of the nervous system is in accord with isoform specific localization, but not with general channel isoform instability. Third, enlargements of NMJ boutons with brp positive presynaptic active zones confirm the absence of IS4A and the presence of IS4B in active zones (these enlargements are now shown in the revised figures 2A-C, 3A, and 4A-C). Fourth, as suggested we have quantified the Pearson co-localization of IS4 isoforms with Brp in presynaptic active zones (revised Fig. 2D). This confirms quantitatively similar co-localization of IS4B and control with Brp, but no co-localization of IS4A with Brp. In fact, the labeling intensity of IS4A in presynaptic active zones is quantitatively not significantly different from background, no IS4A label is detected anywhere in the axon terminals at the NMJ, but we find IS4 label in the CNS. Together, these data strongly support our interpretation that the IS4 splice site plays a distinct role in cac channel localization. Figure legends as well as results and discussion section have been modified accordingly (the respective page and line numbers are listed in our-point-by-point responses).

In addition, we have carefully addressed all other public comments as well as all other recommendations for authors by providing multiple new data sets, new image analyses, and revising text. Addressing the insightful comments of all three reviewers and the reviewing editor has greatly helped to make the manuscript better.

Reviewer #1 (Recommendations For The Authors):

The conclusion that the IS4B exon controls Cac localization to active zones versus simply being required for channel abundance is not well supported. The authors need to either mention both possibilities or provide stronger support for the active zone localization model if they want to emphasize this point.

We agree and have included several additional data sets as outlined in our response to point 1 of reviewer 1 and to the reviewing editor (see above). These new data strongly support our interpretation that the IS4B exon controls Cac localization to active zones and is not simply required for channel abundance. The additions to the figures and accompanying text (including the respective figure panel, page, and line numbers) are listed in the point-bypoint responses to the reviewers’ public suggestions.

Figure 2C staining for Cac localization in the delta 4B line is difficult to compare to the others, as the background staining is so high (muscles are green for example). As such, it is hard to determine whether the arrows in C are just background.

We had over-emphasized the green label to show that there really is no cacophony label in active zones. However, we agree that this hampered image interpretation. Thus, we have adjusted brightness such that it matches the other genotypes (see new figure panel 2C, and figure 3A, bottom). Revising the figure as suggested by the reviewer shows much more clearly that IS4B puncta are detected exclusively in presynaptic active zones, whereas IS4A channels are not detectable in active zones or anywhere else in the axon terminal boutons. Quantification of IS4A label in brp positive active zones confirms that labeling intensity is not significantly above background (page 6, lines 29 to 31 and page 7, lines 19 to 21). Therefore, IS4A is not detectable in active zones at the NMJ.

It seems more likely that the removal of the 4B exon simply destabilizes the protein and causes it to be degraded (as suggested by the Western), rather than mislocalizing it away from active zones. It's hard to imagine how some residue changes in the S4 voltage sensor would control active zone localization to begin with. The authors should note that the alternative explanation is that the protein is just degraded when the 4B exon is removed.

Based on additional data and analyses, we disagree with the interpretation that removal of IS4B disrupts protein integrity and present multiple lines of evidence that support sparse expression of IS4A channels (ΔIS4B). As outlined in our response to reviewer 1 and to the reviewing editor, we show (1) in new immunohistochemical stainings (new supplementary figure 1) that upon removal of IS4B, sparse label is detectable in the VNC and the brain lobes (for detail see above). (2) In our new figure 3C, we show cacophony-mediated somatodendritic calcium currents recorded from adult flight motoneurons in a control situation and upon removal of IS4B that leaves only IS4A channels. This clearly demonstrates that IS4A underlies a substantial component of the HVA somatodendritic calcium current, although it is absence from axon terminals. This is in line with isoform specific functions at different locations, but not with IS4A instability/degradation. (3) We do not agree with the reviewer’s interpretation of the Western Blot data in figure 1E (formerly figure 1D). Together with our immunohistochemical data that show sparse cacophony IS4A expression, we think that the faint band upon removal of IS4B in a heterozygous background (that reduces labeled channels even further) reflects the sparseness of IS4A expression. This sparseness is not due to channel instability, but to IS4A functions that are less abundant than the ubiquitously expressed cac^IS4B channels at presynaptic active zones of fast chemical synapses (see page 15, lines 24 to 29).

If they really want to claim the 4B exon governs active zone localization, much higher quality imaging is required (with enlarged views of individual boutons and their AZs, rather than the low-quality full NMJ imaging provided). Similarly, higher resolution imaging of Cac localization at Muscle 12 (Figure 2H) boutons would be very useful, as the current images are blurry and hard to interpret. Figure 6N shows beautiful high-resolution Cac and Brp imaging in single boutons for the I-II exon manipulations - the authors should do the same for the 4B line. For all immuno in Figure 2, it is important to quantify Cac intensity as well. There is no quantification provided, just a sample image. The authors should provide quantification as they do for the delta I-II exons in Figure 3.

We did as suggested and added figure panels to figure 2A-C and to new figures 3A (formerly part of figure 2 and 4A-C (formerly figure 3) showing magnified label at the NMJ AZs to better judge on cacophony expression after exon excision. These data are now referred to in the results section on page 6, lines 22 to 24, page 7, lines 18 to 21 and page 8, lines 17/18.

As suggested, we now also provide quantification of co-localization with brp puncta as Pearson’s correlation coefficient for control, IS4B, and IS4A in the new figure panel 2D (text on page 6, lines 34 to 38). This further underscores control-like active zone localization of IS4B but no significant active zone localization of IS4A. As suggested, we quantified now also the intensity of IS4B label in active zones, and it was not different from control (see revised figure 4H and text on page 8, lines 38/39). We did not quantify the intensity of IS4A label, because it was not over background (text, page 6, lines 30/31).

Reviewer #2 (Recommendations For The Authors):

(1a) Questions about the engineered Cac splice isoform alleles:

The authors using CRISPR gene editing to selectively remove the entire alternatively spliced exons of interest. Do the authors know what happens to the cac transcript with the deleted exon? Is the deleted exon just skipped and spliced to the next exon? Or does the transcript instead undergo nonsense-mediated decay?

We do not believe that there is nonsense mediated mRNA decay, because for all exon excisions the respective mRNA and protein are made. Protein has been detected on the level of Western blotting and immunocytochemistry. Therefore, we are certain that the mRNA is viable for each exon excision (and we have confirmed this for low abundance cac protein isoforms by rt-PCR), but only subsets of cac isoforms can be made from mRNAs that are lacking specific exons. However, we can not make any statements as to whether the lack of specific protein isoforms exerts feedback on mRNA stability, the rate of transcription and translation, or other unknown effects.

(1b) While it is clear that the IS4 exons encode part of the voltage sensor in the first repeat, are there studies in Drosophila to support the putative Ca-beta and G-protein beta-gamma binding sites in the I-II loop? Or are these inferred from Mammalian studies?

To the best of our knowledge, there are no studies in Drosophila that unambiguously show Caβ and Gβγ binding sites in the I-II loop of cacophony. However, sequence analysis strongly suggests that I-IIB contains both, a Caβ as well as a Gβγ binding site (AID: α-interacting domain) because the binding motif QXXER is present. In mouse Cav2.1 and Ca_v2.2 channels the sequence is QQIER, while in Drosophila cacophony I-IIB it is QQLER. In the alternative IIIA, this motif is not present, strongly suggesting that G_βγ subunits cannot interact at the AID. However, as already suggested by Smith et al. (1998), based on sequence analysis, Ca_β should still be able to bind, although possibly with a lower affinity. We agree that this information should be given to the reader and have revised the text accordingly on page 5, lines 9 to 17.

(1c) The authors assert that splicing of Cav2/cac in flies is a means to encode diversity, as mammals obviously have 4 Cav2 genes vs 1 in flies. However, as the authors likely know, mammalian Cav2 channels also have various splice isoforms encoded in each of the 4 Cav2 genes. The authors should discuss in more detail what is known about the splicing of individual mammalian Cav2 channels and whether there are any homologous properties in mammalian channels controlled by alternative splicing.

We agree and now provide a more comprehensive discussion of vertebrate Ca_v2 splicing and its impact on channel function. In line to what we report in Drosophila, properties like G_βγ binding and activation voltage can also be affected by alternative splicing in vertebrate Ca_v2 channel, through the exon patterns are quite different from Drosophila. We integrated this part on page 14, first paragraph) in the revised discussion. The respective text is below for the reviewer’s convenience:

“However, alternative splicing increases functional diversity also in mammalian Ca_v2 channels. Although the mutually exclusive splice site in the S4 segment of the first homologous repeat (IS4) is not present in vertebrate Cav channels, alternative splicing in the extracellular linker region between S3 and S4 is at a position to potentially change voltage sensor properties (Bezanilla 2002). Alternative splice sites in rat Ca_v2.1 exon 24 (homologous repeat III) and in exon 31 (homologous repeat IV) within the S3-S4 loop modulate channel pharmacology, such as differences in the sensitivity of Ca_v2.1 to Agatoxin. Alternative splicing is thus a potential cause for the different pharmacological profiles of P- and Q-channels (both Ca_v2.1; Bourinet et al. 1999). Moreover, the intracellular loop connecting homologous repeats I and II is encoded by 3-5 exons and provides strong interaction with G_βγ-subunits (Herlitze et al. 1996). In Ca_v2.1 channels, binding to G_βγ subunits is potentially modulated by alternative splicing of exon 10 (Bourinet et al. 1999). Moreover, whole cell currents of splice forms α1A-a (no Valine at position 421) and α1A-b (with Valine) represent alternative variants for the I-II intracellular loop in rat Ca_v2.1 and Ca_v2.2 channels. While α1A-a exhibits fast inactivation and more negative activation, α1A-b has delayed inactivation and a positive shift in the IV-curve (Bourinet et al. 1999). This is phenotypically similar to what we find for the mutually exclusive exons at the IS4 site, in which IS4B mediates high voltage activated cacophony currents while IS4A channels activate at more negative potentials and show transient current (Fig. 3; see also Ryglewski et al. 2012). Furthermore, altered Ca_β interaction have been shown for splice isoforms in loop III (Bourinet et al. 1999), similar to what we suspect for the I-II site in cacophony. Finally, in mammalian VGCCs, the C-terminus presents a large splicing hub affecting channel function as well as coupling distance to other proteins. Taken together, Ca_v2  channel diversity is greatly enhanced by alternative splicing also in vertebrates, but the specific two mutually exclusive exon pairs investigated here are not present in vertebrate Ca_v2 genes.”

(1d) In Figure 1, it would be helpful to see the entire cac genomic locus with all introns/exons and the 4 specific exons targeted for deletion.

We agree and have changed figure 1 accordingly.

(2a) Cav2.IS4B deletion alleles:

More work is necessary to explain the localization of Cac controlled by the IS4B exon. First, can the authors determine whether actual Cac channels are present at NMJ boutons? The authors seem to indicate that in the IS4B deletion mutants, some Cac (GFP) signal remains in a diffuse pattern across NMJ boutons. However, from the imaging of wild-type Cac-GFP (and previous studies), there is no Cac signal outside of active zones defined by the BRP signal. It would benefit the study to a) take additional, higher resolution images of the remaining Cac signal at NMJs in IS4B deletion mutants, and b) comment on whether the apparent remaining signal in these mutants is only observed in the absence of IS4Bcontaining Cac channels, or if the IS4A-positive channels are normally observed (but perhaps mis-localized?).

We have conducted additional analyses to show convincingly that IS4A channels (that remain upon IS4B deletion) are absent from presynaptic active zone. Please see also responses to reviewers 1 and 3. By adjusting the background values in of CLSM images to identical values in control, delta IS4A, and delta IS4B, as well as by providing selective enlargements as suggested, the figure panels 2C, Ci and 3A now show much clearer, that upon deletion of IS4B no cac label remains in active zones or anywhere else in the axon terminal boutons (see text on page 6, lines 22 to 24). This is further confirmed by quantification showing the in IS4B mutants cac labeling intensity in active zones is not above background (see text on page 6, lines 27 to 31). We never intended to indicate that there was cac signal outside of active zones defined by the brp signal, and we now carefully went through the text to not indicate this possibility unintentionally anywhere in the manuscript.

(2b) Do the authors know whether any presynaptic Ca2+ influx is contributed by IS4Apositive Cac channels at boutons, given the potential diffuse localization? There are various approaches for doing presynaptic Ca2+ imaging that could provide insight into this question.

We agree that this is an interesting question. However, based on the revisions made, we now show with more clarity that IS4A channels are absent from the presynaptic terminal at the NMJ. IS4A labeling intensities within active zones and anywhere else in the axon terminals are not different from background (see text on page 6, lines 27 to 31 and revised Figs. 2C, Ci, and 3A with new selective enlargements in response to comments of both other reviewers). This is in line with our finding that evoked synaptic transmission from NMJ axon terminals to muscle cells is mostly absent upon excision of IS4B (see Fig. 3B). The very small amplitude EPSC (below 5 % of the normal amplitude of evoked EPSCs) that can still be recorded in the absence of IS4B is similar to what is observed in cac null mutant junctions and is mediated by calcium influx through another voltage gated calcium channels, a Ca_v1 homolog named Dmca1D, as we have previously published (Krick et al., 2021, PNAS 118(28):e2106621118. Gathering additional support for the absence of IS4A from presynaptic terminals by calcium imaging experiments would suffer significantly from the presence of additional types of VGCCs in presynaptic terminals (for sure Dmca1D (Krick et al., 2021) and potentially also the Ca_v3 homolog DmαG or Dm-α1T). Such experiments would require mosaic null mutants for cac and DmαG channels in a mosaic IS4B excision mutant, which, if feasible at all, would be very hard and time consuming to generate. In the light of the additional clarification that IS4A is not located in NMJ axon terminal boutons, as shown by additional labeling intensity analysis, revised figures with selective enlargement, and revised text, we feel confident to state that IS4A is not sufficient for evoked SV release.

(2c) Mechanistically, how are amino acid changes in one of the voltage sensing domains in Cac related to trafficking/stabilization/localization of Cac to AZs?

This is an exciting question that has occupied our discussions a lot. Some sorting mechanism must exist that recognizes the correct protein isoforms, just as sorting and transport mechanisms exist that transport other synaptic proteins to the synapse. We do not think that the few amino acid changes in the voltage sensor are directly involved in protein targeting. We rather believe that the cacophony variants that happen to contain this specific voltage sensor are selected for transport out to the synapse. There are possibilities to achieve this cell biological, but we have not further addressed potential mechanisms because we do not want enter the realms of speculation.

(3) How are auxiliary subunits impacted in the Cac isoform mutants?

Recent work by Kate O'Connor-Giles has shown that both Stj and Ca-Beta subunits localize to active zones along with Cac at the Drosophila NMJ. Endogenously tagged Stj and CaBeta alleles are now available, so it would be of interest to determine if Stj and particular Cabeta levels or localization change in the various Cac isoform alleles. This would be particularly interesting given the putative binding site for Ca-beta encoded in the I-II linker.

We agree that the synthesis of the work of Kate O'Connor-Giles group and our study open up new avenues to explore exciting hypotheses about differential coupling of specific cacophony splice isoforms with distinct accessory proteins such as Caβ and α₂δ subunits. However, this requires numerous full sets of additional experiments and is beyond the scope of this study.

(4a) Interpretation of short-term plasticity in the I-IIB exon deletion:

The changes in short-term plasticity presented in Figure 5 are interpreted as an additional phenotype due to the loss of the I-IIB exon, but it seems this might be entirely explained simply due to the reduced Cac levels. Reduced Cac levels at active zones will obviously reduce Ca2+ influx and neurotransmitter release. This may be really the only phenotype/function of the I-IIB exon. Hence, to determine whether loss of the I-IIB exon encodes any functions in short-term plasticity, separate from reduced Cac levels, the authors should compare short-term plasticity in I-IIB loss alleles compared to wild type with starting EPSC amplitudes are equal (for example by reducing extracellular Ca2+ levels in wild type to achieve the same levels at in Cac I-IIB exon deleted alleles). Reduced release probability, simply by reduced Ca2+ influx (either by reduced Cac abundance or extracellular Ca2+) should result in more variability in transmission, so I am not sure there is any particular function of the I-IIB exon in maintaining transmission variability beyond controlling Cac abundance at active zones.

For two reasons we are particularly grateful for this comment. First, it shows us that we needed to explain much clearer that our interpretation is that changes in paired pulse ratios (PPRs) and in depression at low stimulation frequencies are a causal consequence of lower channel numbers upon I-IIB exon deletion, precisely as pointed out by the reviewer. We have carefully revised the text accordingly on page 10, lines 14-25, page 11, lines 3-7 and 22-28; page 16, lines 36-38. Second, the experiment suggested by the reviewer is superb to provide additional evidence that the cause of altered PPRs is in fact reduced channel number, but not altered channel properties. Accordingly, we have conducted additional TEVC recordings in elevated external calcium (1.8 mM) so that the single PSC amplitudes in I-IIB excision animals match those of controls in 0.5 mM extracellular calcium. This makes the amplitudes and the variance of PPR for all interpulse intervals tested control-like (see revised Figs. 6D, E). This strongly indicates that differences observed in PPRs as well as the variance thereof were caused by the amount of calcium influx during the first EPSC, and thus by different channel numbers in active zones.

(4b) Another point about the data in Figure 5: If "behaviorally relevant" motor neuron stimulation and recordings are the goal, the authors should also record under physiological Ca2+ conditions (1.8 mM), rather than the highly reduced Ca2+ levels (0.5 mM) they are using in their protocols.

Although we doubt that the effective extracellular calcium concentration that determines the electromotoric force for calcium to enter the ensheathed motoneuron terminals in vivo during crawling is known, we followed the reviewer’s suggestion partly and have repeated the high frequency stimulation trains for ΔI-IIB in 1.8 mM calcium. As for short-term plasticity this brings the charge conducted to values as observed in control and in ΔI-IIA in 0.5 mM calcium. Therefore, all difference observed in previous figure 5 (now revised figure 6) can be accounted to different channel numbers in presynaptic active zones. This is now explained on page 11, lines 19-28. For controls recordings at high frequency stimulation in higher external calcium (e.g. 2 mM) have previously been published and show significant synaptic depression (e.g. Krick et al., 2021, PNAS). Given that in the exon out variants we do not expect any differences except from those caused by different channel numbers, we did not repeat these experiments for control and ΔI-IIA.

(5a) Mechanism of Cac's role in PHP :

As the authors likely know, mutations in Cac were previously reported to disrupt PHP expression (see Frank et al., 2006 Neuron). Inexplicably, this finding and publication were not cited anywhere in this manuscript (this paper should also be cited when introducing PhTx, as it was the first to characterize PhTx as a means of acutely inducing PHP). In the Frank et al. paper (and in several subsequent studies), PHP was shown to be blocked in mutations in Cac, namely the CacS allele. This allele, like the I-IIB excision allele, reduces baseline transmission presumably due to reduced Ca2+ influx through Cac. The authors should at a minimum discuss these previous findings and how they relate to what they find in Figure 6 regarding the block in PHP in the Cac I-IIB excision allele.

We thank the reviewer for pointing this out and apologize for this oversight. We agree that it is imperative to cite the 2006 paper by Frank et al. when introducing PhTx mediated PHP as well as when discussing cac the effects of cac mutants on PHP together with other published work. We have revised the text accordingly on page 12, lines 9-11 and 21-23 and on page 17, lines 29-33.

In terms of data presentation in Fig. 6, as is typical in the field, the authors should normalize their mEPSC/QC data as a percentage of baseline (+PhTx/-PhTx). This makes it easier to see the reduction in mEPSC values (the "homeostatic pressure" on the system) and then the homeostatic enhancement in QC. Similarly, in Fig. 6M, the authors should show both mEPSC and QC as a percentage of baseline (wild type or non-GluRIIA mutant background).

We agree and have changed figure presentation accordingly. Figure 7 (formerly figure 6) was updated as was the accompanying results text on page 12, lines 23-40.

(6) Cac I-IIA and I-IIB excision allele colocalization at AZs:

These are very nice and important experiments shown in Figures 6N and O, which I suggest the authors consider analyzing in further detail. Most significantly:

(6i) The authors nicely show that most AZs have a mix of both Cac IIA and IIB isoforms. Using simple intensity analysis, can the authors say anything about whether there is a consistent stoichiometric ratio of IIA vs IIB at single AZs? It is difficult to extract actual numbers of IIA vs IIB at individual AZs without having both isoforms labeled mEOS4b, but as a rough estimate can the authors say whether the immunofluorescence intensity of IIA:IIB is similar across each AZ? Or is there broad heterogeneity, with some AZs having low vs high ratios of each isoform (as the authors suggest across proximal to distal NMJ AZs)?

We agree and have conducted experiments and analyses to provide these data. We measured the cac puncta fluorescence intensities for heterozygous cac^sfGFP/cac, cacIIIA^sfGFP/cacI-IIB, and cacI-IIB^sfGFP/cacI-IIA animals. We preferred this strategy, because intensity was always measured from cac puncta with the same GFP tag. Next, we normalized all values to the intensities obtained in active zones from heterozygous cac^sfGFP/cac controls and then plotted the intensities of I-IIA versus I-IIB containing active zones side by side. Across junctions and animals, we find a consistent ratio 2:1 in the relative intensities of I-IIB and I-IIA, thus indicating on average roughly twice as many I-IIB as compared to I-IIA channels across active zones. This is consistent with the counts in our STED analysis (see Fig. 5F). These new data are shown in the new figure panel 7J and referred to on page 13, lines 10-16 in the revised text.

(6ii) Intensity analysis of Cac IIA vs IIB after PHP: Previous studies have shown Cac abundance increases at NMJ AZs after PHP. Can the authors determine whether both Cac IIA vs IIB isoforms increase after PHP or whether just one isoform is targeted for this enhancement?

We already show that PHP is not possible in the absence of I-IIB channels (see figure 7). However, we agree that it is an interesting question to test whether I-IIA channel are added in the presence of I-IIB channels during PHP, but we consider this a detail beyond the scope of this study.

Minor points:

(1) Including line numbers in the manuscript would help to make reviewing easier.

We agree and now provide line numbers.

(2) Several typos (abstract "The By contrast", etc).

We carefully double checked for typos.

(3) Throughout the manuscript, the authors refer to Cac alleles and channels as "Cav2", which is unconventional in the field. Unless there is a compelling reason to deviate, I suggest the authors stick to referring to "Cac" (i.e. cacdIS4B, etc) rather than Cav2. The authors make clear in the introduction that Cac is the sole fly Cav2 channel, so there shouldn't be a need to constantly reinforce that cac=Cav2.

We agree and have changed all fly Ca_v2 reference to cac.

(4) In some figures/text the authors use "PSC" to refer to "postsynaptic current", while in others (i.e. Figure 6) they switch to the more conventional terms of mEPSC or EPSC. I suggest the authors stick to a common convention (mEPSC and EPSC).

We have changed PSC to EPSC throughout.

Reviewer #3 (Recommendations For The Authors):

(1) The abstract could focus more on the results at the expense of the background.

We agree and have deleted the second introductory background sentence and added information on PPRs and depression during low frequency stimulation.

(2) What does "strict" active zone localization refer to? Could they please define the term strict?

Strict active zone localization means that cac puncta are detected in active zones but no cac label above background is found anywhere else throughout the presynaptic terminal, now defined on page 6, lines 27-29.

(3) Single boutons/zoomed versions of the confocal images shown in Figures 2A-C, 2H, and 3A-C would be very helpful.

We have provided these panels as suggested (see above and revised figures 2-4). Figure 3 is now figure 4.

(4) The authors cite Ghelani et al. (2023) for increased cac levels during homeostatic plasticity. I recommend citing earlier work making similar observations (Gratz et al., 2019; DOI: 10.1523/JNEUROSCI.3068-18.2019), and linking them to increased presynaptic calcium influx (Müller & Davis, 2012; DOI: 10.1016/j.cub.2012.04.018).

We agree and have added Gratz et al. 2019 and Davis and Müller 2012 to the results section on page 12, lines 17/18 and lines 21-23, in the discussion on page 17, lines 29-33.

(5) The data shown in Figure 3 does not directly support the conclusion of altered release probability in dI-IIB. I therefore suggest changing the legend's title.

We have reworded to “Excisions at the I-II exon do not affect active zone cacophony localization but can alter cacsfGFP label intensity in active zones and PSC amplitude” as this is reflecting the data shown in the figure panels more directly.

(6) It would be helpful to specify "adult flight muscle" in Figure 2J.

We agree that it is helpful to specify in the figure (now revised figure 3C) that the voltage clamp recordings of somatodendritic calcium current were conducted in adult flight motoneurons and have revised the headline of figure panel 3C and the legend accordingly. Please note, these are not muscle cells but central neurons.

(7) Do dIS4B/Cav2null MNs indeed show an inward or outward current at -90 to -70 mV/-40 and -50 mV, or is this an analysis artifact?

No, this is due to baseline fluctuations as typical for voltage clamp in central neurons with more than 6000 µm dendritic length and more than 4000 dendritic branches.

(8) Loss of several presynaptic proteins, including Brp (Kittel et al., 2006), and RBP (Liu et al., 2011), induce changes in GluR field size (without apparent changes in miniature amplitude). The statement regarding the Cav2 isoform and possible effects on GluR number (p. 8) should be revised accordingly.

We understand and have done two things. First, we measured the intensity of GluRIIA immunolabel in ΔI-IIA, ΔI-IIB, and controls and found no differences. Second, we reworded the statement. It now reads on page 9, lines 1-6: “It seems unlikely that presynaptic cac channel isoform type affects glutamate receptor types or numbers, because the amplitude of spontaneous miniature postsynaptic currents (mEPSCs, Fig. 4K) and the labeling intensity of postsynaptic GluRIIA receptors are not significantly different between controls, I-IIA, and I-IIB junctions (see suppl. Fig. 2, p = 0.48, ordinary one-way ANOVA, mean and SD intensity values are 61.0 ± 6.9 (control), 55.8 ± 8.5 (∆I-IIA), 61.1 ± 17.3 (∆I-IIB)). However, we cannot exclude altered GluRIIB numbers and have not quantified GluR receptor field sizes.”

(9) The statement relating miniature frequency to RRP size is unclear (p. 8). Is there any evidence for a correlation between miniature frequency to RRP size? Could the authors please clarify?

We agree that this statement requires caution. Although there is some published evidence for a correlation of RRP size and mini frequency (Neuron, 2009 61(3):412-24. doi: 10.1016/j.neuron.2008.12.029 and Journal of Neuroscience 44 (18) e1253232024; doi: 10.1523/JNEUROSCI.1253-23.2024), which we now refer to on page 9, it is not clear whether this is true for all synapses and how linear such a relationship may be. Therefore, we have revised the text on page 9, lines 6-9. It now reads: “Similarly, the frequency of miniature postsynaptic currents (mEPSCs) remains unaltered. Since mEPSCs frequency has been related to RRP size at some synapses (Pan et al., 2009; Ralowicz et al., 2024) this indicates unaltered RRP size upon I-IIB excision, but we have not directly measured RRP size.”

(10) Please define the "strict top view" of synapses (p. 8).

Top view is what this reviewer referred to as “planar view” in the public review points 6 and 7. In our responses to these public review points we now also define “strict top view”, see page 9, lines 17-19.

(11) Two papers are cited regarding a linear relationship between calcium channel number and release probability (p. 15). Many more papers could be cited to demonstrate a supralinear relationship (e.g., Dodge & Rahaminoff, 1967; Weyhersmüller et al., 2011 doi: 10.1523/JNEUROSCI.6698-10.2011). The data of the present study were collected at an extracellular calcium concentration of 0.5 mM, whereas Meideiros et al. (2023) used 1.5 mM. The relationship between calcium and release is supra-linear around 0.5 mM extracellular calcium (Weyhersmüller et al. 2011). This should be discussed/the statements be revised. Also, the reference to Meideiros et al. (2023) should be included in the reference list.

We have now updated the Medeiros reference (updated version of that paper appeared in eLife in 2024) in the text and reference list. We agree that the relationship of the calcium concentration and P_r can also be non-linear and refer to this on page 16, lines 26-32, but the point we want to make is to relate defined changes in calcium channel number (not calcium influx) as assessed by multiple methods (CLSM intensity measures and sptPALM channel counting) to release probability. We now also clearly state that we measured at 0.5 mM external calcium (page 16, lines 27/28) whereas Medeiros et al. 2024 measured at 1.5 mM calcium (page 16, lines 31/32).

(12) Figure 6: Quantal content does not have any units - please remove "n vesicles".

We have revised this figure in response to reviewer 2 (comment 5) and quantal content is now expressed as percent baseline, thus without units (see revised figure 7).

(13) Figure 6C should be auto-scaled from zero.

This has been fixed by revising that figure in response to reviewer 2 (comment 5)

(14) The data supporting the statement on impaired motor behavior and reduced vitality of adult IS4A should be either shown, or the statement should be removed (p. 13). Any hypotheses as to why IS4A is important for behavior and or viability?

As suggested, we have removed that statement.

(15) They do not provide any data supporting the statement that changes in PSC decay kinetics "counteract" the increase in PSC amplitude (p. 14). The sentence should be changed accordingly.

We agree and have down toned. It now reads on page 16, lines 7-9: “During repetitive firing, the median increase of PSC amplitude by ~10 % is potentially counteracted by the significant decrease in PSC half amplitude width by ~25 %...”.

(16) How do they explain the net locomotion speed increase in dI    -IIA larvae? Although the overall charge transfer is not affected during the stimulus protocols used, could the accelerated PSC decay affect PSP summation (I would actually expect a decrease in summation/slower speed)? Independent of the voltage-clamp data, is muscle input resistance changed in dI-IIA mutants?

Muscle input resistance is not altered in I-II mutants. We refer to potential causes of the locomotion effects of I-IIA excision in the discussion. On page 16, lines 12 to 21 it reads: “there is no difference in charge transfer from the motoneuron axon terminal to the postsynaptic muscle cell between ∆I-IIA and control. Surprisingly, crawling is significantly affected by the removal of I-IIA, in that the animals show a significantly increased mean crawling speed but no significant change in the number of stops. Given that the presynaptic function at the NMJ is not strongly altered upon I-IIA excision, and that I-IIA likely mediates also Ca_v2 functions outside presynaptic AZs (see above) and in other neuron types than motoneurons, and that the muscle calcium current is mediated by Ca_v1>/i> and Ca_v3, the effects of I-IIA excision of increasing crawling speed is unlikely caused by altered pre- or postsynaptic function at the NMJ. We judge it more likely that excision of I-IIA has multiple effects on sensory and pre-motor processing, but identification of these functions is beyond the scope of this study.”

DOI: 10.1158/0008-5472.can-24-2589

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DOI: 10.1016/j.scr.2024.103648

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DOI: 10.1016/j.celrep.2024.115125

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British Museum, inv. 132962

• REFERENCES NEEDED

Author response:

Reviewer #1 (Public review):

Summary:

In cells undergoing Flavivirus infection, cellular translation is impaired but the viruses themselves escape this inhibition and are efficiently translated. In this study, the authors use very elegant and direct approaches to identify the regions in the 5' and 3' UTRs that are important for this phenomenon and then use them to retrieve two cellular proteins that associate with them and mediate translational shutoff evasion (DDX3 and PABP1). A number of experimental approaches are used with a series of well-controlled experiments that fully support the authors' conclusions.

Strengths:

The work identifies the regions in the 5' and 3' UTRs of the viral genome that mediate the escape of JEV from cellular transcriptional shutoff, they evaluate the infectivity of the mutant viruses bearing or not these structures and even explore their pathogenicity in mice. They then identify the cellular proteins that bind to these regions (DDX3 and PABP1) and determine their role in translation blockade escape, in addition to examining and assessing the conservation of the stem-loop identified in JEV in other Flaviviridae.

In almost all of their systematic analyses, translational effects are put in parallel with the replication kinetics of the different mutant viruses. The experimental thread followed in this study is rigorous and direct, and all experiments are truly well-controlled, fully supporting the authors' conclusions.

We greatly appreciate the reviewer's recognition of this study. We elucidated the role of UTR in translation blockade escape of JEV from the perspective of the RNA structure of the UTR and its interaction with host proteins (DDX3 and PABP1), and we hope that this study could gain wider recognition.

Reviewer #2 (Public review):

Summary:

The authors use a combination of techniques including viral genetics, in vitro reporters, and purified proteins and RNA to interrogate how the Japanese encephalitis virus maintains translation of its RNA to produce viral proteins after the host cell has shut down general translation as a means to block viral replication. They report a role for the RNA helicase DDX3 in promoting virus translation in a cap-independent manner through binding a dumbbell RNA structure in the 3' untranslated region previously reported to drive Japanese encephalitis virus cap-independent translation and a stem-loop at the viral RNA 5' end.

Strengths:

The authors clearly show that the Japanese encephalitis virus does not possess an IRES activity to initiate translation using a range of mono- and bi-cistronic mRNAs. Surprisingly, using a replicon system, the translation of a capped or uncapped viral RNA is reported to have the same translation efficiency when transfected into cells. The authors have applied a broad range of techniques to support their hypotheses.

We are grateful for the reviewer’s recognition of the thoroughness and multi-faceted nature of our study.

Weaknesses:

(1) The authors' original experiments in Figure 1 where the virus is recovered following transfection of in vitro transcribed viral RNA with alternative 5' ends such as capped or uncapped ignore that after a single replication cycle of that transfected RNA, the subsequent viral RNA will be capped by the viral capping proteins making the RNA in all conditions the same.

Thank you for your suggestion. We share the same viewpoint as the reviewer. After the first round of translation of the uncapped viral RNA, the subsequent viral RNA will inevitably be capped by the viral capping proteins. However, there is no doubt that the transfected cells do not contain viral capping proteins in the initial transfection stage, which directly proved that JEV possesses a cap-independent translation initiation mechanism.

(2) The authors report that deletion of the dumbbell and the large 3' stem-loop RNA reduce replication of a Japanese encephalitis virus replicon. These structures have been reported for other flaviviruses to be important respectively for the accumulation of short flaviviral RNAs that can regulate replication and stability of the viral RNA that lacks a polyA tail. The authors don't show any assessment of RNA stability or degradation state.

Thank you for your suggestion. We agree that a rigorous supplementary experiment for the assessment of RNA stability or degradation state is desirable. To address this, the relative amounts of viral RNA with the deletion of DB2 or sHP-SL will be determined by real-time RT-PCR analysis in transfected cells at multiple time points, which will allow us to test whether the deletion of the dumbbell and the large 3' stem-loop RNA reduce the RNA stability of JEV.

(3) The authors propose a model for DDX3 to drive 5'-3' end interaction of the Japanese encephalitis virus viral genome but no direct evidence for this is presented.

Thank you for your suggestion. In this study, we did not have direct evidence to suggest that DDX3 can drive the 5'-3' end interaction of the Japanese encephalitis virus viral genome, which is indeed a limitation of our research. In the revision, we will more explicitly discuss the interrelationship between DDX3 and 5'-3' UTR, as well as incorporate a discussion of these points into the main text, acknowledging the limitations of our current models.

(4) The authors' final model in Figure 10 proposes a switch from a cap-dependent translation system in early infection to cap-independent DDX3-driven translation system late in infection. The replicon data that measures translation directly however shows identical traces for capped and uncapped RNAs in all untreated conditions so that which mechanism is used at different stages of the infection is not clear.

Thank you for your suggestion. The replicon transfection system was used to evaluate the key viral element for cap-independent translation. We only monitored reporter gene expression from 2 hpt to 12 hpt, which can’t fully recapitulate the different stages of JEV infection. In the experimental results Figure 1 and Figure 1-figure supplement 1, we demonstrated that JEV significantly induced the host translational shutoff at 36 hpi, while the expression level of viral protein gradually increased as infection went on, suggesting that JEV translation could evade the shutoff of cap-dependent translation initiation at the late stage of infection. As shown in the growth curves in Figure 5Q, JEV replicated to similar virus titers in WT and DDX3-KO cells from 12 hpi to 36 hpi, but higher level virus yields were observed in WT cells from 48 hpi, suggesting that DDX3 is important for JEV infection at the late stage. DDX3 was demonstrated to be critical for JEV cap-independent translation. Based on these data, we proposed that the DDX3-dependent cap-independent translation is employed by JEV to maintain efficient infection at the late stage when the cap-dependent translation imitation was suppressed.

Reviewer #3 (Public review):

Summary:

This work is a valuable study that aims to decipher the molecular mechanisms underlying the translation process in Japanese encephalitis virus (JEV), a relevant member of the genus Flavivirus. The authors provide evidence that cap-independent translation, which has already been demonstrated for other flaviviruses, could also account in JEV. This process depends on the genomic 3' UTR, as previously demonstrated in other flaviviruses. Further, the authors find that cellular proteins such as DDX3 or PABP1 could contribute to JEV translation in a cap-independent way. Both DDX3 and PABP1 had previously been described to have a role in cellular protein synthesis and also in the translation step of other flaviviruses distinct from JEV; therefore, this work would expand the cap-independent translation in flaviviruses as a general mechanism to bypass the translation repression exerted by the host cell during viral infection. Further, the findings can be relevant for the development of specific drugs that could interfere with flaviviral translation in the future. Nevertheless, the conclusions are not fully supported by the provided results.

Strengths:

The results provide a good starting point to investigate the molecular mechanism underlying the translation in flaviviruses, which even today is an area of knowledge with many limitations.

Thank you to the reviewer for providing positive feedback. The research on the molecular mechanism underlying cap-independent translation is still a limited field in the flaviviruses, and its mechanism has not been well elucidated at present. We only hope that this study could reveal a novel mechanism of translation initiation for flaviviruses.

Weaknesses:

The main limit of the work is related to the fact that the role of the 3' UTR structural elements and DDX3 is not only circumscribed to translation, but also to replication and encapsidation. In fact, some of the provided results suggest this idea. Particularly, it is intriguing why the virus titer can be completely abrogated while the viral protein levels are only partially affected by the knockdown of DDX3. This points to the fact that many of the drawn conclusions could be overestimated or, at least, all the observed effect cannot be attributed only to the DDX3 effect on translation. Finally, it is noteworthy that the use of uncapped transcripts could be misleading, since this is not the natural molecular context of the viral genome.

Thank you for your suggestion. We agree with the reviewer's comments that the role of the 3' UTR structural elements and DDX3 may not only be circumscribed to translation. However, not as described by the reviewer, DDX3 knockdown did not completely abrogate JEV infection. As indicated in Figure 5E-5F, the recombinant virus was successfully rescued at 36 hpt and 48 hpt using the uncapped viral genomic RNA, although the viral titer rescued with the uncapped genomic RNA at 24 hpt was below the limit of detection. We have confirmed that the DB2 and sHP-SL elements in 3' UTR play a decisive role in the replication of viral RNA in our research (Figure 2G and Figure 2-figure supplement 4C), and we will further analyze the role of DDX3 in viral RNA replication and encapsidation, thereby clarifying the multiple functions of DDX3 in JEV life cycle. Meanwhile, we will incorporate a discussion of these points into the main text, acknowledging the limitations of our current research.

To eliminate the misleading effects of using uncapped transcripts, we will use a natural molecular background of the viral genome with cap methylation deficiency. The methyltransferase (MTase) of the flavivirus NS5 protein catalyzes  N-7 and 2’-O methylations in the formation of the 5’-end cap of the genome, and the E218 amino acid of the NS5 protein MTase domain is one of the active sites of flavivirus methyltransferase (PLoS Pathogens. 2012. PMID:22496660; Journal of Virology. 2007. PMID: 1866096). We will construct a mutant virus of the E218A mutation to abolish 2'-O methylation activity and significantly reduce N-7 methylation activity and then analyze the roles of UTR structure and DDX3 in recombinant viruses with the type-I cap structure functional deficiency.

.

Author response:

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

The revised manuscript contains new results and additional text. Major revisions:

(1) Additional simulations and analyses of networks with different biophysical parameters and with identical time constants for E and I neurons (Methods, Supplementary Fig. 5).

(2) Additional simulations and analyses of networks with modifications of connectivity parameters to further analyze effects of E/I assemblies on manifold geometry (Supplementary Fig. 6).

(3) Analysis of synaptic current components (Figure 3 D-F; to analyze mechanism of modest amplification in Tuned networks). 

(4) More detailed explanation of pattern completion analysis (Results).

(5) Analysis of classification performance of Scaled networks (Supplementary Fig.8).

(6) Additional analysis (Figure 5D-F) and discussion (particularly section “Computational functions of networks with E/I assemblies”) of functional benefits of continuous representations in networks with E-I assemblies. 

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

Meissner-Bernard et al present a biologically constrained model of telencephalic area of adult zebrafish, a homologous area to the piriform cortex, and argue for the role of precisely balanced memory networks in olfactory processing. 

This is interesting as it can add to recent evidence on the presence of functional subnetworks in multiple sensory cortices. It is also important in deviating from traditional accounts of memory systems as attractor networks. Evidence for attractor networks has been found in some systems, like in the head direction circuits in the flies. However, the presence of attractor dynamics in other modalities, like sensory systems, and their role in computation has been more contentious. This work contributes to this active line of research in experimental and computational neuroscience by suggesting that, rather than being represented in attractor networks and persistent activity, olfactory memories might be coded by balanced excitation-inhibitory subnetworks. 

Strengths: 

The main strength of the work is in: (1) direct link to biological parameters and measurements, (2) good controls and quantification of the results, and (3) comparison across multiple models. 

(1) The authors have done a good job of gathering the current experimental information to inform a biological-constrained spiking model of the telencephalic area of adult zebrafish. The results are compared to previous experimental measurements to choose the right regimes of operation. 

(2) Multiple quantification metrics and controls are used to support the main conclusions and to ensure that the key parameters are controlled for - e.g. when comparing across multiple models.  (3) Four specific models (random, scaled I / attractor, and two variant of specific E-I networks - tuned I and tuned E+I) are compared with different metrics, helping to pinpoint which features emerge in which model. 

Weaknesses: 

Major problems with the work are: (1) mechanistic explanation of the results in specific E-I networks, (2) parameter exploration, and (3) the functional significance of the specific E-I model. 

(1) The main problem with the paper is a lack of mechanistic analysis of the models. The models are treated like biological entities and only tested with different assays and metrics to describe their different features (e.g. different geometry of representation in Fig. 4). Given that all the key parameters of the models are known and can be changed (unlike biological networks), it is expected to provide a more analytical account of why specific networks show the reported results. For instance, what is the key mechanism for medium amplification in specific E/I network models (Fig. 3)? How does the specific geometry of representation/manifolds (in Fig. 4) emerge in terms of excitatory-inhibitory interactions, and what are the main mechanisms/parameters? Mechanistic account and analysis of these results are missing in the current version of the paper. 

We agree that further mechanistic insights would be of interest and addressed this issue at different levels:

(1) Biophysical parameters: to determine whether network behavior depends on specific choices of biophysical parameters in E and I neurons we equalized biophysical parameters across neuron types. The main observations are unchanged, suggesting that the observed effects depend primarily on network connectivity (see also response to comment [2]).

(2) Mechanism of modest amplification in E/I assemblies: analyzing the different components of the synaptic currents demonstrate that the modest amplification of activity in Tuned networks results from an “imperfect” balance of recurrent excitation and inhibition within assemblies (see new Figures 3D-F and text p.7). Hence, E/I co-tuning substantially reduces the net amplification in Tuned networks as compared to Scaled networks, thus preventing discrete attractor dynamics and stabilizing network activity, but a modest amplification still occurs, consistent with biological observations.

(3) Representational geometry: to obtain insights into the network mechanisms underlying effects of E/I assemblies on the geometry of population activity we tested the hypothesis that geometrical changes depend, at least in part, on the modest amplification of activity within E/I assemblies (see Supplementary Figure 6). We changed model parameters to either prevent the modest amplification in Tuned networks (increasing I-to-E connectivity within assemblies) or introduce a modest amplification in subsets of neurons by other mechanisms (concentration-dependent increase in the excitability of pseudo-assembly neurons; Scaled I networks with reduced connectivity within assemblies). Manipulations that introduced a modest, input-dependent amplification in neuronal subsets had geometrical effects similar to those observed in Tuned networks, whereas manipulations that prevented a modest amplification abolished these effects (Supplementary Figure 6). Note however that these manipulations generated different firing rate distributions. These results provide a starting point for more detailed analyses of the relationship between network connectivity and representational geometry (see p.12).

In summary, our additional analyses indicate that effects of E/I assemblies on representational geometry depend primarily on network connectivity, rather than specific biophysical parameters, and that the resulting modest amplification of activity within assemblies makes an important contribution. Further analyses may reveal more specific relationships between E/I assemblies and representational geometry, but such analyses are beyond the scope of this study.

(2) The second major issue with the study is a lack of systematic exploration and analysis of the parameter space. Some parameters are biologically constrained, but not all the parameters. For instance, it is not clear what the justification for the choice of synaptic time scales are (with E synaptic time constants being larger than inhibition: tau_syn_i = 10 ms, tau_syn_E = 30 ms). How would the results change if they are varying these - and other unconstrained - parameters? It is important to show how the main results, especially the manifold localisation, would change by doing a systematic exploration of the key parameters and performing some sensitivity analysis. This would also help to see how robust the results are, which parameters are more important and which parameters are less relevant, and to shed light on the key mechanisms.  

We thank the reviewer for raising this point. We chose a relatively slow time constant for excitatory synapses because experimental data indicate that excitatory synaptic currents in Dp and piriform cortex contain a prominent NMDA component. Nevertheless, to assess whether network behavior depends on specific choices of biophysical parameters in E and I neurons, we have performed additional simulations with equal synaptic time constants and equal biophysical parameters for all neurons. Each neuron also received the same number of inputs from each population (see revised Methods). Results were similar to those observed previously (Supplementary Fig.5 and p.9 of main text). We therefore conclude that the main effects observed in Tuned networks cannot be explained by differences in biophysical parameters between E and I neurons but is primarily a consequence of network connectivity.

(3) It is not clear what the main functional advantage of the specific E-I network model is compared to random networks. In terms of activity, they show that specific E-I networks amplify the input more than random networks (Fig. 3). But when it comes to classification, the effect seems to be very small (Fig. 5c). Description of different geometry of representation and manifold localization in specific networks compared to random networks is good, but it is more of an illustration of different activity patterns than proving a functional benefit for the network. The reader is still left with the question of what major functional benefits (in terms of computational/biological processing) should be expected from these networks, if they are to be a good model for olfactory processing and learning. 

One possibility for instance might be that the tasks used here are too easy to reveal the main benefits of the specific models - and more complex tasks would be needed to assess the functional enhancement (e.g. more noisy conditions or more combination of odours). It would be good to show this more clearly - or at least discuss it in relation to computation and function. 

In the previous manuscript, the analysis of potential computational benefits other than pattern classification was limited and the discussion of this issue was condensed into a single itemized paragraph to avoid excessive speculation. Although a thorough analysis of potential computational benefits exceeds the scope of a single paper, we agree with the reviewer that this issue is of interest and therefore added additional analyses and discussion.

In the initial manuscript we analyzed pattern classification primarily to investigate whether Tuned networks can support this function at all, given that they do not exhibit discrete attractor states. We found this to be the case, which we consider a first important result.

Furthermore, we found that precise balance of E/I assemblies can protect networks against catastrophic firing rate instabilities when assemblies are added sequentially, as in continual learning. Results from these simulations are now described and discussed in more detail (see Results p.11 and Discussion p.13).

In the revised manuscript, we now also examine additional potential benefits of Tuned networks and discuss them in more detail (see new Figure 5D-F and text p.11). One hypothesis is that continuous representations provide a distance metric between a given input and relevant (learned) stimuli. To address this hypothesis, we (1) performed regression analysis and (2) trained support vector machines (SVMs) to predict the concentration of a given odor in a mixture based on population activity. In both cases, Tuned E+I networks outperformed Scaled and _rand n_etworks in predicting the concentration of learned odors across a wide range mixtures (Figure 5D-F).  E/I assemblies therefore support the quantification of learned odors within mixtures or, more generally, assessments of how strongly a (potentially complex) input is related to relevant odors stored in memory. Such a metric assessment of stimulus quality is not well supported by discrete attractor networks because inputs are mapped onto discrete network states.

The observation that Tuned networks do not map inputs onto discrete outputs indicates that such networks do not classify inputs as distinct items. Nonetheless, the observed geometrical modifications of continuous representations support the classification of learned inputs or the assessment of metric relationships by hypothetical readout neurons. Geometrical modifications of odor representations may therefore serve as one of multiple steps in multi-layer computations for pattern classification (and/or other computations). In this scenario, the transformation of odor representations in Dp may be seen as related to transformations of representations between different layers in artificial networks, which collectively perform a given task (notwithstanding obvious structural and mechanistic differences between artificial and biological networks). In other words, geometrical transformations of representations in Tuned networks may overrepresent learned (relevant) information at the expense of other information and thereby support further learning processes in other brain areas. An obvious corollary of this scenario is that Dp does not perform odor classification per se based on inputs from the olfactory bulb but reformats representations of odor space based on experience to support computational tasks as part of a larger system. This scenario is now explicitly discussed (p.14).

Reviewer #2 (Public Review): 

Summary: 

The authors conducted a comparative analysis of four networks, varying in the presence of excitatory assemblies and the architecture of inhibitory cell assembly connectivity. They found that co-tuned E-I assemblies provide network stability and a continuous representation of input patterns (on locally constrained manifolds), contrasting with networks with global inhibition that result in attractor networks. 

Strengths: 

The findings presented in this paper are very interesting and cutting-edge. The manuscript effectively conveys the message and presents a creative way to represent high-dimensional inputs and network responses. Particularly, the result regarding the projection of input patterns onto local manifolds and continuous representation of input/memory is very Intriguing and novel. Both computational and experimental neuroscientists would find value in reading the paper. 

Weaknesses: 

that have continuous representations. This could also be shown in Figure 5B, along with the performance of the random and tuned E-I networks. The latter networks have the advantage of providing network stability compared to the Scaled I network, but at the cost of reduced network salience and, therefore, reduced input decodability. The authors may consider designing a decoder to quantify and compare the classification performance of all four networks. 

We have now quantified classification by networks with discrete attractor dynamics (Scaled) along with other networks. However, because the neuronal covariance matrix for such networks is low rank and not invertible, pattern classification cannot be analyzed by QDA as in Figure 5B. We therefore classified patterns from the odor subspace by template matching, assigning test patterns to one of the four classes based on correlations (see Supplementary Figure 8). As expected, Scaled networks performed well, but they did not outperform Tuned networks. Moreover, the performance of Scaled networks, but not Tuned networks, depended on the order in which odors were presented to the network. This hysteresis effect is a direct consequence of persistent attractor states and decreased the general classification performance of Scaled networks (see Supplementary Figure 8 for details). These results confirm the prediction that networks with discrete attractor states can efficiently classify inputs, but also reveal disadvantages arising from attractor dynamics. Moreover, the results indicate that the classification performance of Tuned networks is also high under the given task conditions, which simulate a biologically realistic scenario.

We would also like to emphasize that classification may not be the only task, and perhaps not even a main task, of Dp/piriform cortex or other memory networks with E/I assemblies. Conceivably, other computations could include metric assessments of inputs relative to learned inputs or additional learning-related computations. Please see our response to comment (3) of reviewer 1 for a further discussion of this issue. 

Networks featuring E/I assemblies could potentially represent multistable attractors by exploring the parameter space for their reciprocal connectivity and connectivity with the rest of the network. However, for co-tuned E-I networks, the scope for achieving multistability is relatively constrained compared to networks employing global or lateral inhibition between assemblies. It would be good if the authors mentioned this in the discussion. Also, the fact that reciprocal inhibition increases network stability has been shown before and should be cited in the statements addressing network stability (e.g., some of the citations in the manuscript, including Rost et al. 2018, Lagzi & Fairhall 2022, and Vogels et al. 2011 have shown this).  

We thank the reviewer for this comment. We now explicitly discuss multistability (see p. 12) and refer to additional references in the statements addressing network stability.

Providing raster plots of the pDp network for familiar and novel inputs would help with understanding the claims regarding continuous versus discrete representation of inputs, allowing readers to visualize the activity patterns of the four different networks. (similar to Figure 1B). 

We thank the reviewer for this suggestion. We have added raster plots of responses to both familiar and novel inputs in the revised manuscript (Figure 2D and Supplementary Figure 4A).

Reviewer #3 (Public Review): 

Summary: 

This work investigates the computational consequences of assemblies containing both excitatory and inhibitory neurons (E/I assembly) in a model with parameters constrained by experimental data from the telencephalic area Dp of zebrafish. The authors show how this precise E/I balance shapes the geometry of neuronal dynamics in comparison to unstructured networks and networks with more global inhibitory balance. Specifically, E/I assemblies lead to the activity being locally restricted onto manifolds - a dynamical structure in between high-dimensional representations in unstructured networks and discrete attractors in networks with global inhibitory balance. Furthermore, E/I assemblies lead to smoother representations of mixtures of stimuli while those stimuli can still be reliably classified, and allow for more robust learning of additional stimuli. 

Strengths: 

Since experimental studies do suggest that E/I balance is very precise and E/I assemblies exist, it is important to study the consequences of those connectivity structures on network dynamics. The authors convincingly show that E/I assemblies lead to different geometries of stimulus representation compared to unstructured networks and networks with global inhibition. This finding might open the door for future studies for exploring the functional advantage of these locally defined manifolds, and how other network properties allow to shape those manifolds. 

The authors also make sure that their spiking model is well-constrained by experimental data from the zebrafish pDp. Both spontaneous and odor stimulus triggered spiking activity is within the range of experimental measurements. But the model is also general enough to be potentially applied to findings in other animal models and brain regions. 

Weaknesses: 

I find the point about pattern completion a bit confusing. In Fig. 3 the authors argue that only the Scaled I network can lead to pattern completion for morphed inputs since the output correlations are higher than the input correlations. For me, this sounds less like the network can perform pattern completion but it can nonlinearly increase the output correlations. Furthermore, in Suppl. Fig. 3 the authors show that activating half the assembly does lead to pattern completion in the sense that also non-activated assembly cells become highly active and that this pattern completion can be seen for Scaled I, Tuned E+I, and Tuned I networks. These two results seem a bit contradictory to me and require further clarification, and the authors might want to clarify how exactly they define pattern completion. 

We believe that this comment concerns a semantic misunderstanding and apologize for any lack of clarity. We added a definition of pattern completion in the text: “…the retrieval of the whole memory from noisy or corrupted versions of the learned input.”. Pattern completion may be assessed using different procedures. In computational studies, it is often analyzed by delivering input to a subset of the assembly neurons which store a given memory (partial activation). Under these conditions, we find recruitment of the entire assembly in all structured networks, as demonstrated in Supplementary Figure 3. However, these conditions are unlikely to occur during odor presentation because the majority of neurons do not receive any input.

Another more biologically motivated approach to assess pattern completion is to gradually modify a realistic odor input into a learned input, thereby gradually increasing the overlap between the two inputs. This approach had been used previously in experimental studies (references added to the text p.6). In the presence of assemblies, recurrent connectivity is expected to recruit assembly neurons (and thus retrieve the stored pattern) more efficiently as the learned pattern is approached. This should result in a nonlinear increase in the similarity between the evoked and the learned activity pattern. This signature was prominent in Scaled networks but not in Tuned or rand networks. Obviously, the underlying procedure is different from the partial activation of the assembly described above because input patterns target many neurons (including neurons outside assemblies) and exhibit a biologically realistic distribution of activity. However, this approach has also been referred to as “pattern completion” in the neuroscience literature, which may be the source of semantic confusion here. To clarify the difference between these approaches we have now revised the text and explicitly described each procedure in more detail (see p.6). 

The authors argue that Tuned E+I networks have several advantages over Scaled I networks. While I agree with the authors that in some cases adding this localized E/I balance is beneficial, I believe that a more rigorous comparison between Tuned E+I networks and Scaled I networks is needed: quantification of variance (Fig. 4G) and angle distributions (Fig. 4H) should also be shown for the Scaled I network. Similarly in Fig. 5, what is the Mahalanobis distance for Scaled I networks and how well can the Scaled I network be classified compared to the Tuned E+I network? I suspect that the Scaled I network will actually be better at classifying odors compared to the E+I network. The authors might want to speculate about the benefit of having networks with both sources of inhibition (local and global) and hence being able to switch between locally defined manifolds and discrete attractor states. 

We agree that a more rigorous comparison of Tuned and Scaled networks would be of interest. We have added the variance analysis (Fig 4G) and angle distributions (Fig. 4H) for both Tuned I and Scaled networks. However, the Mahalanobis distances and Quadratic Discriminant Analysis cannot be applied to Scaled networks because their neuronal covariance matrix is low rank and not invertible_. To nevertheless compare these networks, we performed template matching by assigning test patterns to one of the four odor classes based on correlations to template patterns (Supplementary Figure 8; see also response to the first comment of reviewer 2). Interestingly, _Scaled networks performed well at classification but did not outperform Tuned networks, and exhibited disadvantages arising from attractor dynamics (Supplementary Figure 8; see also response to the first comment of reviewer 2). Furthermore, in further analyses we found that continuous representational manifolds support metric assessments of inputs relative to learned odors, which cannot be achieved by discrete representations. These results are now shown in Figure 5D-E and discussed explicitly in the text on p.11 (see also response to comment 3 of reviewer 1).

We preferred not to add a sentence in the Discussion about benefits of networks having both sources of inhibition_,_ as we find this a bit too speculative.

At a few points in the manuscript, the authors use statements without actually providing evidence in terms of a Figure. Often the authors themselves acknowledge this, by adding the term "not shown" to the end of the sentence. I believe it will be helpful to the reader to be provided with figures or panels in support of the statements.  

Thank you for this comment. We have provided additional data figures to support the following statements:

“d_M was again increased upon learning, particularly between learned odors and reference classes representing other odors (Supplementary Figure 9)”

“decreasing amplification in assemblies of Scaled networks changed transformations towards the intermediate behavior, albeit with broader firing rate distributions than in Tuned networks (Supplementary Figure 6 B)”  

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors): 

Meissner-Bernard et al present a biologically constrained model of telencephalic area of adult zebrafish, a homologous area to the piriform cortex, and argue for the role of precisely balanced memory networks in olfactory processing. 

This is interesting as it can add to recent evidence on the presence of functional subnetworks in multiple sensory cortices. It is also important in deviating from traditional accounts of memory systems as attractor networks. Evidence for attractor networks has been found in some systems, like in the head direction circuits in the flies. However, the presence of attractor dynamics in other modalities, like sensory systems, and their role in computation has been more contentious. This work contributes to this active line of research in experimental and computational neuroscience by suggesting that, rather than being represented in attractor networks and persistent activity, olfactory memories might be coded by balanced excitation-inhibitory subnetworks. 

The paper is generally well-written, the figures are informative and of good quality, and multiple approaches and metrics have been used to test and support the main results of the paper. 

The main strength of the work is in: (1) direct link to biological parameters and measurements, (2) good controls and quantification of the results, and (3) comparison across multiple models. 

(1) The authors have done a good job of gathering the current experimental information to inform a biological-constrained spiking model of the telencephalic area of adult zebrafish. The results are compared to previous experimental measurements to choose the right regimes of operation. 

(2) Multiple quantification metrics and controls are used to support the main conclusions and to ensure that the key parameters are controlled for - e.g. when comparing across multiple models.   (3) Four specific models (random, scaled I / attractor, and two variant of specific E-I networks - tuned I and tuned E+I) are compared with different metrics, helping to pinpoint which features emerge in which model. 

Major problems with the work are: (1) mechanistic explanation of the results in specific E-I networks, (2) parameter exploration, and (3) the functional significance of the specific E-I model. 

(1) The main problem with the paper is a lack of mechanistic analysis of the models. The models are treated like biological entities and only tested with different assays and metrics to describe their different features (e.g. different geometry of representation in Fig. 4). Given that all the key parameters of the models are known and can be changed (unlike biological networks), it is expected to provide a more analytical account of why specific networks show the reported results. For instance, what is the key mechanism for medium amplification in specific E/I network models (Fig. 3)? How does the specific geometry of representation/manifolds (in Fig. 4) emerge in terms of excitatory-inhibitory interactions, and what are the main mechanisms/parameters? Mechanistic account and analysis of these results are missing in the current version of the paper. 

Precise balancing of excitation and inhibition in subnetworks would lead to the cancellation of specific dynamical modes responsible for the amplification of responses (hence, deviating from the attractor dynamics with an unstable specific mode). What is the key difference in the specific E/I networks here (tuned I or/and tuned E+I) which make them stand between random and attractor networks? Excitatory and inhibitory neurons have different parameters in the model (Table 1). Time constants of inhibitory and excitatory synapses are also different (P. 13). Are these parameters causing networks to be effectively more excitation dominated (hence deviating from a random spectrum which would be expected from a precisely balanced E/I network, with exactly the same parameters of E and I neurons)? It is necessary to analyse the network models, describe the key mechanism for their amplification, and pinpoint the key differences between E and I neurons which are crucial for this. 

To address these comments we performed additional simulations and analyses at different levels. Please see our reply to comment (1) of the public review (reviewer 1) for a detailed description. We thank the reviewer for these constructive comments.

(2) The second major issue with the study is a lack of systematic exploration and analysis of the parameter space. Some parameters are biologically constrained, but not all the parameters. For instance, it is not clear what the justification for the choice of synaptic time scales are (with E synaptic time constants being larger than inhibition: tau_syn_i = 10 ms, tau_syn_E = 30 ms). How would the results change if they are varying these - and other unconstrained - parameters? It is important to show how the main results, especially the manifold localisation, would change by doing a systematic exploration of the key parameters and performing some sensitivity analysis. This would also help to see how robust the results are, which parameters are more important and which parameters are less relevant, and to shed light on the key mechanisms.  

We thank the reviewer for this comment. We have now carried out additional simulations with equal time constants for all neurons. Please see our reply to the public review for more details (comment 2 of reviewer 1).

(3) It is not clear what the main functional advantage of the specific E-I network model is compared to random networks. In terms of activity, they show that specific E-I networks amplify the input more than random networks (Fig. 3). But when it comes to classification, the effect seems to be very small (Fig. 5c). Description of different geometry of representation and manifold localization in specific networks compared to random networks is good, but it is more of an illustration of different activity patterns than proving a functional benefit for the network. The reader is still left with the question of what major functional benefits (in terms of computational/biological processing) should be expected from these networks, if they are to be a good model for olfactory processing and learning. 

One possibility for instance might be that the tasks used here are too easy to reveal the main benefits of the specific models - and more complex tasks would be needed to assess the functional enhancement (e.g. more noisy conditions or more combination of odours). It would be good to show this more clearly - or at least discuss it in relation to computation and function.

Please see our reply to the public review (comment 3 of reviewer 1).

Specific comments: 

Abstract: "resulting in continuous representations that reflected both relatedness of inputs and *an individual's experience*" 

It didn't become apparent from the text or the model where the role of "individual's experience" component (or "internal representations" - in the next line) was introduced or shown (apart from a couple of lines in the Discussion) 

We consider the scenario that that assemblies are the outcome of an experience-dependent plasticity process. To clarify this, we have now made a small addition to the text: “Biological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons.”.

P. 2: "The resulting state of "precise" synaptic balance stabilizes firing rates because inhomogeneities or fluctuations in excitation are tracked by correlated inhibition" 

It is not clear what the "inhomogeneities" specifically refers to - they can be temporal, or they can refer to the quenched noise of connectivity, for instance. Please clarify what you mean. 

The statement has been modified to be more precise: “…“precise” synaptic balance stabilizes firing rates because inhomogeneities in excitation across the population or temporal variations in excitation are tracked by correlated inhibition…”.

P. 3 (and Methods): When odour stimulus is simulated in the OB, the activity of a fraction of mitral cells is increased (10% to 15 Hz) - but also a fraction of mitral cells is suppressed (5% to 2 Hz). What is the biological motivation or reference for this? It is not provided. Is it needed for the results? Also, it is not explained how the suppressed 5% are chosen (e.g. randomly, without any relation to the increased cells?). 

We thank the reviewer for this comment. These changes in activity directly reflect experimental observations. We apologize that we forgot to include the references reporting these observations (Friedrich and Laurent, 2001 and 2004); this is now fixed.

In our simulation, OB neurons do not interact with each other, and the suppressed 5% were indeed randomly selected. We changed the text in Methods accordingly to read: “An additional 75 randomly selected mitral cells were inhibited” 

P. 4, L. 1-2: "... sparsely connected integrate-and-fire neurons with conductance-based synapses (connection probability {less than or equal to}5%)." 

Specify the connection probability of specific subtypes (EE, EI, IE, II).  

We now refer to the Methods section, where this information can be found. 

“... conductance-based synapses (connection probability ≤5%, Methods)”  

P. 4, L. 6-7: "Population activity was odor-specific and activity patterns evoked by uncorrelated OB inputs remained uncorrelated in Dp (Figure 1H)" 

What would happen to correlated OB inputs (e.g. as a result of mixture of two overlapping odours) in this baseline state of the network (before memories being introduced to it)? It would be good to know this, as it sheds light on the initial operating regime of the network in terms of E/I balance and decorrelation of inputs.  

This information was present in the original manuscript at (Figure 3) but we improved the writing to further clarify this issue: “ (…) we morphed a novel odor into a learned odor (Figure 3A), or a learned odor into another learned odor (Supplementary Figure 3B), and quantified the similarity between morphed and learned odors by the Pearson correlation of the OB activity patterns (input correlation). We then compared input correlations to the corresponding pattern correlations among E neurons in Dp (output correlation). In rand networks, output correlations increased linearly with input correlations but did not exceed them (Figure 3B and Supplementary Figure 3B)”

P. 4, L. 12-13: "Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of ~80%, .."   Where is this shown? 

(There are other occasions too in the paper where references to the supporting figures are missing). 

We now provide the statistics: “Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of 0.79 ± 0.20”

P. 4: "In each network, we created 15 assemblies representing uncorrelated odors. As a consequence, ~30% of E neurons were part of an assembly ..." 

15 x 100 / 4000 = 37.5% - so it's closer to 40% than 30%. Unless there is some overlap? 

Yes: despite odors being uncorrelated and connectivity being random, some neurons (6 % of E neurons) belong to more than one assembly.

P. 4: "When a reached a critical value of ~6, networks became unstable and generated runaway activity (Figure 2B)." 

Can this transition point be calculated or estimated from the network parameters, and linked to the underlying mechanisms causing it? 

We thank the reviewer for this interesting question. The unstability arises when inhibitions fails to counterbalance efficiently the increased recurrent excitation within Dp. The transition point is difficult to estimate, as it can depend on several parameters, including the probability of E to E connections, their strength, assembly size, and others. We have therefore not attempted to estimate it analytically.

P. 4: "Hence, non-specific scaling of inhibition resulted in a divergence of firing rates that exhausted the dynamic range of individual neurons in the population, implying that homeostatic   global inhibition is insufficient to maintain a stable firing rate distribution." 

I don't think this is justified based on the results and figures presented here (Fig. 2E) - the interpretation is a bit strong and biased towards the conclusions the authors want to draw. 

To more clearly illustrate the finding that in Scaled networks, assembly neurons are highly active (close to maximal realistic firing rates) whereas non-assembly neurons are nearly silent we have now added Supplementary Fig. 2B. Moreover, we have toned down the text: “Hence, non-specific scaling of inhibition resulted in a large and biologically unrealistic divergence of firing rates (Supplementary Figure 2B) that nearly exhausted the dynamic range of individual neurons in the population, indicating that homeostatic global inhibition is insufficient to maintain a stable firing rate distribution”

P. 5, third paragraph: Description of Figure 2I, inset is needed, either in the text or caption. 

The inset is now referred to in the text: ”we projected synaptic conductances of each neuron onto a line representing the E/I ratio expected in a balanced network (“balanced axis”) and onto an orthogonal line (“counter-balanced axis”; Figure 2I inset, Methods).”

P. 5, last paragraph: another example of writing about results without showing/referring to the corresponding figures: 

"In rand networks, firing rates increased after stimulus onset and rapidly returned to a low baseline after stimulus offset. Correlations between activity patterns evoked by the same odor at different time points and in different trials were positive but substantially lower than unity, indicating high variability ..." 

And the continuation with similar lack of references on P. 6: 

"Scaled networks responded to learned odors with persistent firing of assembly neurons and high pattern correlations across trials and time, implying attractor dynamics (Hopfield, 1982; Khona and Fiete, 2022), whereas Tuned networks exhibited transient responses and modest pattern correlations similar to rand networks." 

Please go through the Results and fix the references to the corresponding figures on all instances. 

We thank the reviewer for pointing out these overlooked figure references, which are now fixed.

P. 8: "These observations further support the conclusion that E/I assemblies locally constrain neuronal dynamics onto manifolds." 

As discussed in the general major points, mechanistic explanation in terms of how the interaction of E/I dynamics leads to this is missing. 

As discussed in the reply to the public review (comment 3 of reviewer 1), we have now provided more mechanistic analyses of our observations.

P. 9: "Hence, E/I assemblies enhanced the classification of inputs related to learned patterns."   The effect seems to be very small. Also, any explanation for why for low test-target correlation the effect is negative (random doing better than tuned E/I)? 

The size of the effect (plearned – pnovel = 0.074; difference of means; Figure 5C) may appear small in terms of absolute probability, but it is substantial relative to the maximum possible increase (1 – p_novel =  0.133; Figure 5C). The fact that for low test-target correlations the effect is negative is a direct consequence of the positive effect for high test-target correlations and the presence of 2 learned odors in the 4-way forced choice task. 

P. 9: "In Scaled I networks, creating two additional memories resulted in a substantial increase   in firing rates, particularly in response to the learned and related odors"   Where is this shown? Please refer to the figure. 

We thank the reviewer again for pointing this out. We forgot to include a reference to the relevant figure which has now been added in the revised manuscript (Figure 6C).

P. 10: "The resulting Tuned networks reproduced additional experimental observations that were not used as constraints including irregular firing patterns, lower output than input correlations, and the absence of persistent activity" 

It is difficult to present these as "additional experimental observations", as all of them are negative, and can exist in random networks too - hence cannot be used as biological evidence in favour of specific E/I networks when compared to random networks. 

We agree with the reviewer that these additional experimental observations cannot be used as biological evidence favouring Tuned E+I networks over random networks. We here just wanted to point out that additional observations which we did not take into account to fit the model are not invalidating the existence of E-I assemblies in biological networks. As assemblies tend to result in persistent activity in other types of networks, we feel that this observation is worth pointing out.

Methods: 

P. 13: Describe the parameters of Eq. 2 after the equation. 

Done.

P. 13: "The time constants of inhibitory and excitatory synapses were 10 ms and 30 ms, respectively." 

What is the (biological) justification for the choice of these parameters? 

How would varying them affect the main results (e.g. local manifolds)? 

We chose a relatively slow time constant for excitatory synapses because experimental data indicate that excitatory synaptic currents in Dp and piriform cortex contain a prominent NMDA component. We have now also simulated networks with equal time constants for excitatory and inhibitory synapses and equal biophysical parameters for excitatory and inhibitory neurons, which did not affect the main results (see also reply to the public review: comment 2 of reviewer 1).

P. 14: "Care was also taken to ensure that the variation in the number of output connections was low across neurons"   How exactly?

More detailed explanations have now been added in the Methods section: “connections of a presynaptic neuron y to postsynaptic neurons x were randomly deleted when their total number exceeded the average number of output connections by ≥5%, or added when they were lower by ≥5%.“

Reviewer #2 (Recommendations For The Authors): 

Congratulations on the great and interesting work! The results were nicely presented and the idea of continuous encoding on manifolds is very interesting. To improve the quality of the paper, in addition to the major points raised in the public review, here are some more detailed comments for the paper: 

(1) Generally, citations have to improve. Spiking networks with excitatory assemblies and different architectures of inhibitory populations have been studied before, and the claim about improved network stability in co-tuned E-I networks has been made in the following papers that need to be correctly cited: 

• Vogels TP, Sprekeler H, Zenke F, Clopath C, Gerstner W. 2011. Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks. Science 334:1-7. doi:10.1126/science.1212991 (mentions that emerging precise balance on the synaptic weights can result in the overall network stability) 

• Lagzi F, Bustos MC, Oswald AM, Doiron B. 2021. Assembly formation is stabilized by Parvalbumin neurons and accelerated by Somatostatin neurons. bioRxiv doi: https://doi.org/10.1101/2021.09.06.459211 (among other things, contrasts stability and competition which arises from multistable networks with global inhibition and reciprocal inhibition)   • Rost T, Deger M, Nawrot MP. 2018. Winnerless competition in clustered balanced networks: inhibitory assemblies do the trick. Biol Cybern 112:81-98. doi:10.1007/s00422-017-0737-7 (compares different architectures of inhibition and their effects on network dynamics) 

• Lagzi F, Fairhall A. 2022. Tuned inhibitory firing rate and connection weights as emergent network properties. bioRxiv 2022.04.12.488114. doi:10.1101/2022.04.12.488114 (here, see the eigenvalue and UMAP analysis for a network with global inhibition and E/I assemblies) 

Additionally, there are lots of pioneering work about tracking of excitatory synaptic inputs by inhibitory populations, that are missing in references. Also, experimental work that show existence of cell assemblies in the brain are largely missing. On the other hand, some references that do not fit the focus of the statements have been incorrectly cited. 

The authors may consider referencing the following more pertinent studies on spiking networks to support the statement regarding attractor dynamics in the first paragraph in the Introduction (the current citations of Hopfield and Kohonen are for rate-based networks): 

• Wong, K.-F., & Wang, X.-J. (2006). A recurrent network mechanism of time integration in perceptual decisions. Journal of Neuroscience, 26(4), 1314-1328. https://doi.org/10.1523/JNEUROSCI.3733-05.2006 

• Wang, X.-J. (2008). Decision making in recurrent neuronal circuits. Neuron, 60(2), 215-234. https://doi.org/10.1016/j.neuron.2008.09.034  

• F. Lagzi, & S. Rotter. (2015). Dynamics of competition between subnetworks of spiking neuronal networks in the balanced state. PloS One. 

• Goldman-Rakic, P. S. (1995). Cellular basis of working memory. Neuron, 14(3), 477-485. 

• Rost T, Deger M, Nawrot MP. 2018. Winnerless competition in clustered balanced networks: inhibitory assemblies do the trick. Biol Cybern 112:81-98. doi:10.1007/s00422-017-0737-7. 

• Amit DJ, Tsodyks M (1991) Quantitative study of attractor neural network retrieving at low spike rates: I. substrate-spikes, rates and neuronal gain. Network 2:259-273. 

• Mazzucato, L., Fontanini, A., & La Camera, G. (2015). Dynamics of Multistable States during Ongoing and Evoked Cortical Activity. Journal of Neuroscience, 35(21), 8214-8231. 

We thank the reviewer for the references suggestions. We have carefully reviewed the reference list and made the following changes, which we hope address the reviewer’s concerns:

(1) We adjusted References about network stability in co-tuned E-I networks.

(2) We added the Lagzi & Rotter (2015), Amit et al. (1991), Mazzucato et al. (2015) and GoldmanRakic (1995) papers in the Introduction as studies on attractor dynamics in spiking neural networks. We preferred to omit the two X.J Wang papers, as they describe attractors in decision making rather than memory processes.

(3) We added the Ko et al. 2011 paper as experimental evidence for assemblies in the brain. In our view, there are few experimental studies showing the existence of cell assemblies in the brain, which we distinguish from cell ensembles, group of coactive neurons. 

(4) We also included Hennequin 2018, Brunel 2000, Lagzi et al. 2021 and Eckmann et al. 2024, which we had not cited in the initial manuscript.

(5) We removed the Wiechert et al. 2010 reference as it does not support the statement about geometry-preserving transformation by random networks.

(2) The gist of the paper is about how the architecture of inhibition (reciprocal vs. global in this case) can determine network stability and salient responses (related to multistable attractors and variations) for classification purposes. It would improve the narrative of the paper if this point is raised in the Introduction and Discussion section. Also see a relevant paper that addresses this point here: 

Lagzi F, Bustos MC, Oswald AM, Doiron B. 2021. Assembly formation is stabilized by Parvalbumin neurons and accelerated by Somatostatin neurons. bioRxiv doi: https://doi.org/10.1101/2021.09.06.459211 

Classification has long been proposed to be a function of piriform cortex and autoassociative memory networks in general, and we consider it important. However, the computational function of Dp or piriform cortex is still poorly understood, and we do not focus only on odor classification as a possibility. In fact, continuous representational manifolds also support other functions such as the quantification of distance relationships of an input to previously memorized stimuli, or multi-layer network computations (including classification). In the revised manuscript, we have performed additional analyses to explore these notions in more detail, as explained above (response to public reviews, comment 3 of reviewer 1). Furthermore, we have now expanded the discussion of potential computational functions of Tuned networks and explicitly discuss classification but also other potential functions. 

(3) A plot for the values of the inhibitory conductances in Figure 1 would complete the analysis for that section. 

In Figure 1, we decided to only show the conductances that we use to fit our model, namely the afferent and total synaptic conductances. As the values of the inhibitory conductances can be derived from panel E, we refrained from plotting them separately for the sake of simplicity. 

(4) How did the authors calculate correlations between activity patterns as a function of time in Figure 2E, bottom row? Does the color represent correlation coefficient (which should not be time dependent) or is it a correlation function? This should be explained in the Methods section. 

The color represents the Pearson correlation coefficient between activity patterns within a narrow time window (100 ms). We updated the Figure legend to clarify this: “Mean correlation between activity patterns evoked by a learned odor at different time points during odor presentation. Correlation coefficients were calculated between pairs of activity vectors composed of the mean firing rates of E neurons in 100 ms time bins. Activity vectors were taken from the same or different trials, except for the diagonal, where only patterns from different trials were considered.”

(5) Figure 3 needs more clarification (both in the main text and the figure caption). It is not clear what the axes are exactly, and why the network responses for familiar and novel inputs are different. The gray shaded area in panel B needs more explanation as well.  

We thank the reviewer for the comment. We have improved Figure 3A, the figure caption, as well as the text (see p.6). We hope that the figure is now clearer.

(6) The "scaled I" network, known for representing input patterns in discrete attractors, should exhibit clear separation between network responses in the 2D PC space in the PCA plots. However, Figure 4D and Figure 6D do not reflect this, as all network responses are overlapped. Can the authors explain the overlap in Figure 4D? 

In Figure 4D, activity of Scaled networks is distributed between three subregions in state space that are separated by the first 2 PCs. Two of them indeed correspond to attractor states representing the two learned odors while the third represents inputs that are not associated with these attractor states. To clarify this, please see also the density plot in Figure 4E. The few datapoints between these three subregions are likely outliers generated by the sequential change in inputs, as described in Supplementary Figure 8C.

(7) The reason for writing about the ISN networks is not clear. Co-tuned E-I assemblies do not necessarily have to operate in this regime. Also, the results of the paper do not rely on any of the properties of ISNs, but they are more general. Authors should either show the paradoxical effect associated with ISN (i.e., if increasing input to I neurons decreases their responses) or show ISN properties using stability analysis (See computational research conducted at the Allen Institute, namely Millman et al. 2020, eLife ). Currently, the paper reads as if being in the ISN regime is a necessary requirement, which is not true. Also, the arguments do not connect with the rest of the paper and never show up again. Since we know it is not a requirement, there is no need to have those few sentences in the Results section. Also, the choice of alpha=5.0 is extreme, and therefore, it would help to judge the biological realism if the raster plots for Figs 2-6 are shown.

We have toned down the part on ISN and reduced it to one sentence for readers who might be interested in knowing whether activity is inhibition-stabilized or not. We have also added the reference to the Tsodyks et al. 1997 paper from which we derive our stability analysis. The text now reads “Hence, pDp_sim entered a balanced state during odor stimulation (Figure 1D, E) with recurrent input dominating over afferent input, as observed in pDp (Rupprecht and Friedrich, 2018). Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of 0.79 ± 0.20, demonstrating that activity was inhibition-stabilized (Sadeh and Clopath, 2020b, Tsodyks et al., 1997).”  

We have now also added the raster plots as suggested by the reviewer (see Figure 2D, Supplementary Figure 1 G, Supplementary Figure 4). We thank the reviewer for this comment.

(8) In the abstract, authors mention "fast pattern classification" and "continual learning," but in the paper, those issues have not been addressed. The study does not include any synaptic plasticity. 

Concerning “continual learning” we agree that we do not simulate the learning process itself. However, Figure 6 show results of a simulation where two additional patterns were stored in a network that already contained assemblies representing other odors. We consider this a crude way of exploring the end result of a “continual learning” process. “Fast pattern classification” is mentioned because activity in balanced networks can follow fluctuating inputs with high temporal resolution, while networks with stable attractor states tend to be slow. This is likely to account for the occurrence of hysteresis effects in Scaled but not Tuned networks as shown in Supplementary

Fig. 8.

(9) In the Introduction, the first sentence in the second paragraph reads: "... when neurons receive strong excitatory and inhibitory synaptic input ...". The word strong should be changed to "weak".

Also, see the pioneering work of Brunel 2000. 

In classical balanced networks, strong excitatory inputs are counterbalanced by strong inhibitory inputs, leading to a fluctuation-driven regime. We have added Brunel 2000.

(10) In the second paragraph of the introduction, the authors refer to studies about structural co-tuning (e.g., where "precise" synaptic balance is mentioned, and Vogels et al. 2011 should be cited there) and functional co-tuning (which is, in fact, different than tracking of excitation by inhibition, but the authors refer to that as co-tuning). It makes it easier to understand which studies talk about structural co-tuning and which ones are about functional co-tuning. The paper by Znamenski 2018, which showed both structural and functional tuning in experiments, is missing here. 

We added the citation to the now published paper by Znamenskyi et al. (2024).  

(11) The third paragraph in the Introduction misses some references that address network dynamics that are shaped by the inhibitory architecture in E/I assemblies in spiking networks, like Rost et al 2018 and Lagzi et al 2021. 

These references have been added.

(12) The last sentence of the fourth paragraph in the Introduction implies that functional co-tuning is due to structural co-tuning, which is not necessarily true. While structural co-tuning results in functional co-tuning, functional co-tuning does not require structural co-tuning because it could arise from shared correlated input or heterogeneity in synaptic connections from E to I cells.  

We generally agree with the reviewer, but we are uncertain which sentence the reviewer refers to.

We assume the reviewer refers to the last sentence of the second (rather than the fourth paragraph), which explicitly mentions the “…structural basis of E/I co-tuning…”. If so, we consider this sentence still correct because the “structural basis” refers not specifically to E/I assemblies, but also includes any other connectivity that may produce co-tuning, including the connectivity underlying the alternative possibilities mentioned by the reviewer (shared correlated input or heterogeneity of synaptic connections).

(13) In order to ensure that the comparison between network dynamics is legit, authors should mention up front that for all networks, the average firing rates for the excitatory cells were kept at 1 Hz, and the background input was identical for all E and I cells across different networks.

We slightly revised the text to make this more clear “We (…) uniformly scaled I-to-E connection weights by a factor of χ until E population firing rates in response to learned odors matched the corresponding firing rates in rand networks, i.e., 1 Hz”

(14) In the last paragraph on page 5, my understanding was that an individual odor could target different cells within an assembly in different trials to generate trial to trail variability. If this is correct, this needs to be mentioned clearly. 

This is not correct, an odor consists of 150 activated mitral cells with defined firing rates. As now mentioned in the Methods, “Spikes were then generated from a Poisson distribution, and this process was repeated to create trial-to-trial variability.”

(15) The last paragraph on page 6 mentions that the four OB activity patterns were uncorrelated but if they were designed as in Figure 4A, dues to the existing overlap between the patterns, they cannot be uncorrelated. 

This appears to be a misunderstanding. We mention in the text (and show in Figure 4B) that the four odors which “… were assigned to the corners of a square…” are uncorrelated.  The intermediate odors are of course not uncorrelated. We slightly modified the corresponding paragraph (now on page 7) to clarify this: “The subspace consisted of a set of OB activity patterns representing four uncorrelated pure odors and mixtures of these pure odors. Pure odors were assigned to the corners of a square and mixtures were generated by selecting active mitral cells from each of the pure odors with probabilities depending on the relative distances from the corners (Figure 4A, Methods).”

(16) The notion of "learned" and "novel" odors may be misleading as there was no plasticity in the network to acquire an input representation. It would be beneficial for the authors to clarify that by "learned," they imply the presence of the corresponding E assembly for the odor in the network, with the input solely impacting that assembly. Conversely, for "novel" inputs, the input does not target a predefined assembly. In Figure 2 and Figure 4, it would be especially helpful to have the spiking raster plots of some sample E and I cells.  

As suggested by the reviewer, we have modified the existing spiking raster plots in Figure 2, such that they include examples of responses to both learned and novel odors. We added spiking raster plots showing responses of I neurons to the same odors in Supplementary Figure 1F, as well as spiking raster plots of E neurons in Supplementary Figure 4A. To clarify the usage of “learned” and “novel”, we have added a sentence in the Results section: “We thus refer to an odor as “learned” when a network contains a corresponding assembly, and as “novel” when no such assembly is present.”.

(17) In the last paragraph of page 8, can the authors explain where the asymmetry comes from? 

As mentioned in the text, the asymmetry comes from the difference in the covariance structure of different classes. To clarify, we have rephrased the sentence defining the Mahalanobis distance: 

“This measure quantifies the distance between the pattern and the class center, taking into account covariation of neuronal activity within the class. In bidirectional comparisons between patterns from different classes, the mean dM may be asymmetric if neural covariance differs between classes.”

(18) The first paragraph of page 9: random networks are not expected to perform pattern classification, but just pattern representation. It would have been better if the authors compared Scaled I network with E/I co-tuned network. Regardless of the expected poorer performance of the E/I co-tuned networks, the result would have been interesting. 

Please see our reply to the public review (reviewer 2).

(19) Second paragraph on page 9, the authors should provide statistical significance test analysis for the statement "... was significantly higher ...". 

We have performed a Wilcoxon signed-rank test, and reported the p-value in the revised manuscript (p < 0.01). 

(20) The last sentence in the first paragraph on page 11 is not clear. What do the authors mean by "linearize input-output functions", and how does it support their claim? 

We have now amended this sentence to clarify what we mean: “…linearize the relationship between the mean input and output firing rates of neuronal populations…”.

(21) In the first sentence of the last paragraph on page 11, the authors mentioned “high variability”, but it is not clear compared with which of the other 3 networks they observed high variability.

Structurally co-tuned E/I networks are expected to diminish network-level variability. 

“High variability” refers to the variability of spike trains, which is now mentioned explicity in the text. We hope this more precise statement clarifies this point.

(22) Methods section, page 14: "firing rates decreased with a time constant of 1, 2 or 4 s". How did they decrease? Was it an implementation algorithm? The time scale of input presentation is 2 s and it overlaps with the decay time constant (particularly with the one with 4 s decrease).  

Firing rates decreased exponentially. We have added this information in the Methods section.

Reviewer #3 (Recommendations For The Authors): 

In the following, I suggest minor corrections to each section which I believe can improve the manuscript. 

- There was no github link to the code in the manuscript. The code should be made available with a link to github in the final manuscript. 

The code can be found here: https://github.com/clairemb90/pDp-model. The link has been added in the Methods section.

Figure 1: 

- Fig. 1A: call it pDp not Dp. Please check if this name is consistent in every figure and the text. 

Thank you for catching this. Now corrected in Figure 1, Figure 2 and in the text.

- The authors write: "Hence, pDpsim entered an inhibition-stabilized balanced state (Sadeh and Clopath, 2020b) during odor stimulation (Figure 1D, E)." and then later "Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of ~80%, demonstrating that activity was indeed inhibition-stabilized. These results were robust against parameter variations (Methods)." I would suggest moving the second sentence before the first sentence, because the fact that the network is in the ISN regime follows from the shuffled spike timing result. 

Also, I'd suggest showing this as a supplementary figure. 

We thank the reviewer for this comment. We have removed “inhibition-stabilized” in the first sentence as there is no strong evidence of this in Rupprecht and Friedrich, 2018. And removed “indeed” in the second sentence. We also provided more detailed statistics. The text now reads “Hence, pDpsim entered a balanced state during odor stimulation (Figure 1D, E) with recurrent input dominating over afferent input, as observed in pDp (Rupprecht and Friedrich, 2018). Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of 0.79 ± 0.20, demonstrating that activity was inhibition-stabilized (Sadeh and Clopath, 2020b).”

Figure 2: 

- "... Scaled I networks (Figure 2H." Missing ) 

Corrected.

- The authors write "Unlike in Scaled I networks, mean firing rates evoked by novel odors were indistinguishable from those evoked by learned odors and from mean firing rates in rand networks (Figure 2F)." 

Why is this something you want to see? Isn't it that novel stimuli usually lead to high responses? Eg in the paper Schulz et al., 2021 (eLife) which is also cited by the authors it is shown that novel responses have high onset firing rates. I suggest clarifying this (same in the context of Fig. 3C). 

In Dp and piriform cortex, firing rates evoked by learned odors are not substantially different from firing rates evoked by novel odors. While small differences between responses to learned versus novel odors cannot be excluded, substantial learning-related differences in firing rates, as observed in other brain areas, have not been described in Dp or piriform cortex. We added references in the last paragraph of p.5. Note that the paper by Schulz et al. (2021) models a different type of circuit.  

- Fig. 2B: Indicate in figure caption that this is the case "Scaled I" 

This is not exactly the case “Scaled I”, as the parameter 𝝌𝝌 (increased I to E strength) is set to 1.

- Suppl Fig. 2I: Is E&F ever used in the manuscript? I couldn't find a reference. I suggest removing it if not needed. 

Suppl. Fig 2I E&F is now Suppl Fig.1G&H. We now refer to it in the text: “Activity of networks with E assemblies could not be stabilized around 1 Hz by increasing connectivity from subsets of I neurons receiving dense feed-forward input from activated mitral cells (Supplementary Figure 1GH; Sadeh and Clopath, 2020).”

Figure 3: 

- As mentioned in my comment in the public review section, I find the arguments about pattern completion a little bit confusing. For me it's not clear why an increase of output correlations over input correlations is considered "pattern completion" (this is not to say that I don't find the nonlinear increase of output correlations interesting). For me, to test pattern completion with second-order statistics one would need to do a similar separation as in Suppl Fig. 3, ie measuring the pairwise correlation at cells in the assembly L that get direct input from L OB with cells in the assembly L that do not get direct input from OB. If the pairwise correlations of assembly cells which do not get direct input from OB increase in correlations, I would consider this as pattern completion (similar to the argument that increase in firing rate in cells which are not directly driven by OB are considered a sign of pattern completion). 

Also, for me it now seems like that there are contradictory results, in Fig. 3 only Scaled I can lead to pattern completion while in the context of Suppl. Fig. 3 the authors write "We found that assemblies were recruited by partial inputs in all structured pDpsim networks (Scaled and Tuned) without a significant increase in the overall population activity (Supplementary Figure 3A)."   I suggest clarifying what the authors exactly mean by pattern completion, why the increase of output correlations above input correlations can be considered as pattern completion, and why the results differs when looking at firing rates versus correlations. 

Please see our reply to the public review (reviewer 3).

- I actually would suggest adding Suppl. Fig. 3 to the main figure. It shows a more intuitive form of pattern completion and in the text there is a lot of back and forth between Fig. 3 and Suppl. Fig. 3 

We feel that the additional explanations and panels in Fig.3 should clarify this issue and therefore prefer to keep Supplementary Figure 3 as part of the Supplementary Figures for simplicity.  

- In the whole section "We next explored effects of assemblies ... prevented strong recurrent amplification within E/I assemblies." the authors could provide a link to the respective panel in Fig. 2 after each statement. This would help the reader follow your arguments. 

We thank the reviewer for pointing this out. The references to the appropriate panels have been added. 

- Fig. 3A: I guess the x-axis has been shifted upwards? Should be at zero. 

We have modified the x-axis to make it consistent with panels B and C.  

- Fig. 3B: In the figure caption, the dotted line is described as the novel odor but it is actually the unit line. The dashed lines represent the reference to the novel odor. 

Fixed.

- Fig. 3C: The " is missing for Pseudo-Assembly N

Fixed.

- "...or a learned odor into another learned odor." Have here a ref to the Supplementary Figure 3B.

Added.

Figure 4:   

- "This geometry was largely maintained in the output of rand networks, consistent with the notion that random networks tend to preserve similarity relationships between input patterns (Babadi and Sompolinsky, 2014; Marr, 1969; Schaffer et al., 2018; Wiechert et al., 2010)." I suggest adding here reference to Fig. 4D (left). 

Added.

- Please add a definition of E/I assemblies. How do the authors define E/I assemblies? I think they consider both, Tuned I and Tuned E+I as E/I assemblies? In Suppl. Fig. 2I E it looks like tuned feedforward input is defined as E/I assemblies. 

We thank the reviewer for pointing this out. E/I assemblies are groups of E and I neurons with enhanced connectivity. In other words, in E/I assemblies, connectivity is enhanced not only between subsets of E neurons, but also between these E neurons and a subset of I neurons. This is now clarified in the text: “We first selected the 25 I neurons that received the largest number of connections from the 100 E neurons of an assembly. To generate E/I assemblies, the connectivity between these two sets of neurons was then enhanced by two procedures.”. We removed “E/I assemblies” in Suppl. Fig.2, where the term was not used correctly, and apologize for the confusion.

- Suppl. Fig. 4: Could the authors please define what they mean by "Loadings" 

The loadings indicate the contribution of each neuron to each principal component, see adjusted legend of Suppl. Fig. 4: “G. Loading plot: contribution of neurons to the first two PCs of a rand and a Tuned E+I network (Figure 4D).”

- Fig. 4F: The authors might want to normalize the participation ratio by the number of neurons (see e.g. Dahmen et al., 2023 bioRxiv, "relative PR"), so the PR is bound between 0 and 1 and the dependence on N is removed. 

We thank the reviewer for the suggestion, but we prefer to use the non-normalized PR as we find it more easily interpretable (e.g. number of attractor states in Scaled networks).

- Fig. 4G&H: as mentioned in the public review, I'd add the case of Scaled I to be able to compare it to the Tuned E+I case. 

As already mentioned in the public review, we thank the reviewer for this suggestion, which we have implemented.

- Figure caption Fig. 4H "Similar results were obtained in the full-dimensional space." I suggest showing this as a supplemental panel. 

Since this only adds little information, we have chosen not to include it as a supplemental panel to avoid overloading the paper with figures.

Figure 5: 

- As mentioned in the public review, I suggest that the authors add the Scaled I case to Fig. 5 (it's shown in all figures and also in Fig. 6 again). I guess for Scaled I the separation between L and M will be very good? 

Please see our reply to the public review (reviewer 3).

- Fig. 5A&B: I am a bit confused about which neurons are drawn to calculate the Mahalanobis distance. In Fig. 5A, the schematic indicates that the vector B from which the neurons are drawn is distinct from the distribution Q. For the example of odor L, the distribution Q consists of pure odor L with odors that have little mixtures with the other odors. But the vector v for odor L seems to be drawn only from odors that have slightly higher mixtures (as shown in the schematic in Fig. 5A). Is there a reason to choose the vector v from different odors than the distribution Q? 

The distribution Q and the vector v consist of activity patterns across the same neurons in response to different odors. The reason to choose a different odor for v was to avoid having this test datapoint being included in the distribution Q. We also wanted Q to be the same for all test datapoints. 

What does "drawn from whole population" mean? Does this mean that the vectors are drawn from any neuron in pDp? If yes, then I don't understand how the authors can distinguish between different odors (L,M,O,N) on the y-axis. Or does "whole population" mean that the vector is drawn across all assemblies as shown in the schematic in Fig. 5A and the case "neurons drawn from (pseudo-) assembly" means that the authors choose only one specific assembly? In any case, the description here is a bit confusing, I think it would help the reader to clarify those terms better.  

Yes, “drawn from whole population” means that we randomly draw 80 neurons from the 4000 E neurons in pDp. The y-axis means that we use the activity patterns of these neurons evoked by one of the 4 odors (L, M, N, O) as reference. We have modified the Figure legend to clarify this: “d_M was computed based on the activity patterns of 80 E neurons drawn from the four (pseudo-) assemblies (top) or from the whole population of 4000 E neurons (bottom). Average of 50 draws.”

- Suppl Fig. 5A: In the schematic the distance is called d_E(\bar{Q},\bar{V}) while the colorbar has d_E(\bar{Q},\bar{Q}) with the Qs in different color. The green Q should be a V. 

We thank the reviewer for spotting this mistake, it is now fixed.

- Fig. 5: Could the authors comment on the fact that a random network seems to be very good in classifying patterns on it's own. Maybe in the Discussion? 

The task shown in Figure 5 is a relatively easy one, a forced-choice between four classes which are uncorrelated. In Supplementary Figure 9, we now show classification for correlated classes, which is already much harder.

Figure 6: 

- Is the correlation induced by creating mixtures like in the other Figures? Please clarify how the correlations were induced. 

We clarified this point in the Methods section: “The pixel at each vertex corresponded to one pure odor with 150 activated and 75 inhibited mitral cells (…) and the remaining pixels corresponded to mixtures. In the case of correlated pure odors (Figure 6), adjacent pure odors shared half of their activated and half of their inhibited cells.”. An explicit reference to the Methods section has also been added to the figure legend.

- Fig. 6C (right): why don't we see the clear separation in PC space as shown in Fig. 4? Is this related to the existence of correlations? Please clarify. 

Yes. The assemblies corresponding to the correlated odors X and Y overlap significantly, and therefore responses to these odors cannot be well separated, especially for Scaled networks. We added the overlap quantification in the Results section to make this clear. “These two additional assemblies had on average 16% of neurons in common due to the similarity of the odors.”

- "Furthermore, in this regime of higher pattern similarity, dM was again increased upon learning, particularly between learned odors and reference classes representing other odors (not shown)." Please show this (maybe as a supplemental figure). 

We now show the data in Supplementary Figure 9.

Discussion: 

- The authors write: "We found that transformations became more discrete map-like when amplification within assemblies was increased and precision of synaptic balance was reduced. Likewise, decreasing amplification in assemblies of Scaled networks changed transformations towards the intermediate behavior, albeit with broader firing rate distributions than in Tuned networks (not shown)." 

Where do I see the first point? I guess when I compare in Fig. 4D the case of Scaled I vs Tuned E+I, but the sentence above sounds like the authors showed this in a more step-wise way eg by changing the strength of \alpha or \beta (as defined in Fig. 1). 

Also I think if the authors want to make the point that decreasing amplification in assemblies changes transformation with a different rate distribution in scaled vs tuned networks, the authors should show it (eg adding a supplemental figure). 

The first point is indeed supported by data from different figures. Please note that the revised manuscript now contains further simulations that reinforce this statement, particularly those shown in Supplementary Figure 6, and that this point is now discussed more extensively in the Discussion. We hope that these revisions clarify this general point.

The data showing effects of decreasing amplification in assemblies is now shown in Supplementary Figure 6 (Scaled[adjust])

- I suggest adding the citation Znamenskiy et al., 2024 (Neuron; https://doi.org/10.1016/j.neuron.2023.12.013), which shows that excitatory and inhibitory (PV) neurons with functional similarities are indeed strongly connected in mouse V1, suggesting the existence of E/I assembly structure also in mammals.

Done.

Author response:

Reviewer #1 (Public review):

This manuscript presents an interesting exploration of the potential activation mechanisms of DLK following axonal injury. While the experiments are beautifully conducted and the data are solid, I feel that there is insufficient evidence to fully support the conclusions made by the authors.

In this manuscript, the authors exclusively use the puc-lacZ reporter to determine the activation of DLK. This reporter has been shown to be induced when DLK is activated. However, there is insufficient evidence to confirm that the absence of reporter activation necessarily indicates that DLK is inactive. As with many MAP kinase pathways, the DLK pathway can be locally or globally activated in neurons, and the level of DLK activation may depend on the strength of the stimulation. This reporter might only reflect strong DLK activation and may not be turned on if DLK is weakly activated. The results presented in this manuscript support this interpretation. Strong stimulation, such as axotomy of all synaptic branches, caused robust DLK activation, as indicated by puc-lacZ expression. In contrast, weak stimulation, such as axotomy of some synaptic branches, resulted in weaker DLK activation, which did not induce the puc-lacZ reporter. This suggests that the strength of DLK activation depends on the severity of the injury rather than the presence of intact synapses. Given that this is a central conclusion of the study, it may be worthwhile to confirm this further. Alternatively, the authors may consider refining their conclusion to better align with the evidence presented.

We wish to further clarify a striking aspect of puc-lacZ induction following injury: it is bimodal. It is either induced (in various injuries that remove all synaptic boutons), or not induced, including in injuries that spared only 1-2 remaining boutons. This was particularly evident for injuries that spared the NMJ on muscle 29, which is comprised of only a few boutons. In some instances, only a single bouton was evident on muscle 29. While our injuries varied enormously in the number of branches and boutons that were lost, we did not see a comparable variability in puc-lacZ induction.  In the revision we will include additional images to better demonstrate this observation.

The reviewer (and others) fairly point out that our current study focuses on puc-lacZ as a reporter of Wnd signaling in the cell body. We consider this to be a downstream integration of events in axons that are more challenging to detect. It is striking that this integration appears strongly sensitized to the presence of spared synaptic boutons. Examination of Wnd’s activation in axons and synapses is a goal for our future work.

As noted by the authors, DLK has been implicated in both axon regeneration and degeneration. Following axotomy, DLK activation can lead to the degeneration of distal axons, where synapses are located. This raises an important question: how is DLK activated in distal axons? The authors might consider discussing the significance of this "synapse connection-dependent" DLK activation in the broader context of DLK function and activation mechanisms.

While it has been noted that inhibition of DLK can mildly delay Wallerian degeneration (Miller et al., 2009), this does not appear to be the case for retinal ganglion cell axons following optic nerve crush (Fernandes et al., 2014). It is also not the case for Drosophila motoneurons and NMJ terminals following peripheral nerve injury (Xiong et al., 2012; Xiong and Collins, 2012). Instead, overexpression of Wnd or activation of Wnd by a conditioning injury leads to an opposite phenotype - an increase in resiliency to Wallerian degeneration for axons that have been previously injured (Xiong et al., 2012; Xiong and Collins, 2012). The downstream outcome of Wnd activation is highly dependent on the context; it may be an integration of the outcomes of local Wnd/DLK activation in axons with downstream consequences of nuclear/cell body signaling.  The current study suggests some rules for the cell body signaling, however, how Wnd is regulated at synapses and why it promotes degeneration in some circumstances but not others are important future questions.

For the reviewer’s suggestion, it is interesting to consider DLK’s potential contributions to the loss of NMJ synapses in a mouse model of ALS (Le Pichon et al., 2017; Wlaschin et al., 2023). Our findings suggest that the synaptic terminal is an important locus of DLK regulation, while dysfunction of NMJ terminals is an important feature of the ‘dying back’ hypothesis of disease etiology (Dadon-Nachum et al., 2011; Verma et al., 2022). We propose that the regulation of DLK at synaptic terminals is an important area for future study, and may reveal how DLK might be modulated to curtail disease progression. Of note, DLK inhibitors are in clinical trials (Katz et al., 2022; Le et al., 2023; Siu et al., 2018), but at least some have been paused due to safety concerns (Katz et al., 2022). Further understanding of the mechanisms that regulate DLK are needed to understand whether and how DLK and its downstream signaling can be tuned for therapeutic benefit.

Reviewer #2 (Public review):

Summary:

The authors study a panel of sparsely labeled neuronal lines in Drosophila that each form multiple synapses. Critically, each axonal branch can be injured without affecting the others, allowing the authors to differentiate between injuries that affect all axonal branches versus those that do not, creating spared branches. Axonal injuries are known to cause Wnd (mammalian DLK)-dependent retrograde signals to the cell body, culminating in a transcriptional response. This work identifies a fascinating new phenomenon that this injury response is not all-or-none. If even a single branch remains uninjured, the injury signal is not activated in the cell body. The authors rule out that this could be due to changes in the abundance of Wnd (perhaps if incrementally activated at each injured branch) by Wnd, Hiw's known negative regulator. Thus there is both a yet-undiscovered mechanism to regulate Wnd signaling, and more broadly a mechanism by which the neuron can integrate the degree of injury it has sustained. It will now be important to tease apart the mechanism(s) of this fascinating phenomenon. But even absent a clear mechanism, this is a new biology that will inform the interpretation of injury signaling studies across species.

Strengths:

(1) A conceptually beautiful series of experiments that reveal a fascinating new phenomenon is described, with clear implications (as the authors discuss in their Discussion) for injury signaling in mammals.

(2) Suggests a new mode of Wnd regulation, independent of Hiw.

Weaknesses:

(1) The use of a somatic transcriptional reporter for Wnd activity is powerful, however, the reporter indicates whether the transcriptional response was activated, not whether the injury signal was received. It remains possible that Wnd is still activated in the case of a spared branch, but that this activation is either local within the axons (impossible to determine in the absence of a local reporter) or that the retrograde signal was indeed generated but it was somehow insufficient to activate transcription when it entered the cell body. This is more of a mechanistic detail and should not detract from the overall importance of the study

We agree. The puc-lacZ reporter tells us about signaling in the cell body, but whether and how Wnd is regulated in axons and synaptic branches, which we think occurs upstream of the cell body response, remains to be addressed in future studies.

(2) That the protective effect of a spared branch is independent of Hiw, the known negative regulator of Wnd, is fascinating. But this leaves open a key question: what is the signal?

This is indeed an important future question, and would still be a question even if Hiw were part of the protective mechanism by the spared synaptic branch. Our current hypothesis (outlined in Figure 4) is that regulation of Wnd is tied to the retrograde trafficking of a signaling organelle in axons. The Hiw-independent regulation complements other observations in the literature that multiple pathways regulate Wnd/DLK (Collins et al., 2006; Feoktistov and Herman, 2016; Klinedinst et al., 2013; Li et al., 2017; Russo and DiAntonio, 2019; Valakh et al., 2013). It is logical for this critical stress response pathway to have multiple modes of regulation that may act in parallel to tune and restrain its activation.

Reviewer #3 (Public review):

Summary:

This manuscript seeks to understand how nerve injury-induced signaling to the nucleus is influenced, and it establishes a new location where these principles can be studied. By identifying and mapping specific bifurcated neuronal innervations in the Drosophila larvae, and using laser axotomy to localize the injury, the authors find that sparing a branch of a complex muscular innervation is enough to impair Wallenda-puc (analogous to DLK-JNK-cJun) signaling that is known to promote regeneration. It is only when all connections to the target are disconnected that cJun-transcriptional activation occurs.

Overall, this is a thorough and well-performed investigation of the mechanism of spared-branch influence on axon injury signaling. The findings on control of wnd are important because this is a very widely used injury signaling pathway across species and injury models. The authors present detailed and carefully executed experiments to support their conclusions. Their effort to identify the control mechanism is admirable and will be of aid to the field as they continue to try to understand how to promote better regeneration of axons.

Strengths:

The paper does a very comprehensive job of investigating this phenomenon at multiple locations and through both pinpoint laser injury as well as larger crush models. They identify a non-hiw based restraint mechanism of the wnd-puc signaling axis that presumably originates from the spared terminal. They also present a large list of tests they performed to identify the actual restraint mechanism from the spared branch, which has ruled out many of the most likely explanations. This is an extremely important set of information to report, to guide future investigators in this and other model organisms on mechanisms by which regeneration signaling is controlled (or not).

Weaknesses:

The weakest data presented by this manuscript is the study of the actual amounts of Wallenda protein in the axon. The authors argue that increased Wnd protein is being anterogradely delivered from the soma, but no support for this is given. Whether this change is due to transcription/translation, protein stability, transport, or other means is not investigated in this work. However, because this point is not central to the arguments in the paper, it is only a minor critique.

We agree and are glad that the reviewer considers this a minor critique; this is an area for future study. In Supplemental Figure 1 we present differences in the levels of an ectopically expressed GFP-Wnd-kinase-dead transgene, which is strikingly increased in axons that have received a full but not partial axotomy. We suspect this accumulation occurs downstream of the cell body response because of the timing. We observed the accumulations after 24 hours (Figure S1F) but not at early (1-4 hour) time points following axotomy (data not shown). Further study of the local regulation of Wnd protein and its kinase activity in axons is an important future direction.

As far as the scope of impact: because the conclusions of the paper are focused on a single (albeit well-validated) reporter in different types of motor neurons, it is hard to determine whether the mechanism of spared branch inhibition of regeneration requires wnd-puc (DLK/cJun) signaling in all contexts (for example, sensory axons or interneurons). Is the nerve-muscle connection the rule or the exception in terms of regeneration program activation?

DLK signaling is strongly activated in DRG sensory neurons following peripheral nerve injury (Shin et al., 2012), despite the fact that sensory neurons have bifurcated axons and their projections in the dorsal spinal cord are not directly damaged by injuries to the peripheral nerve. Therefore it is unlikely that protection by a spared synapse is a universal rule for all neuron types. However the molecular mechanisms that underlie this regulation may indeed be shared across different types of neurons but utilized in different ways. For instance, nerve growth factor withdrawal can lead to activation of DLK (Ghosh et al., 2011), however neurotrophins and their receptors are regulated and implemented differently in different cell types. We suspect that the restraint of Wnd signaling by the spared synaptic branch shares a common underlying mechanism with the restraint of DLK signaling by neurotrophin signaling. Further elucidation of the molecular mechanism is an important next step towards addressing this question.

Because changes in puc-lacZ intensity are the major readout, it would be helpful to better explain the significance of the amount of puc-lacZ in the nucleus with respect to the activation of regeneration. Is it known that scaling up the amount of puc-lacZ transcription scales functional responses (regeneration or others)? The alternative would be that only a small amount of puc-lacZ is sufficient to efficiently induce relevant pathways (threshold response).

While induction of puc-lacZ expression correlates with Wnd-mediated phenotypes, including sprouting of injured axons (Xiong et al., 2010), protection from Wallerian degeneration (Xiong et al., 2012; Xiong and Collins, 2012) and synaptic overgrowth (Collins et al., 2006), we have not observed any correlation between the degree of puc-lacZ induction (eg modest, medium or high) and the phenotypic outcomes (sprouting, overgrowth, etc). Rather, there appears to be a striking all-or-none difference in whether puc-lacZ is induced or not induced. There may indeed be a threshold that can be restrained through multiple mechanisms. We posit in figure 4 that restraint may take place in the cell body, where it can be influenced by the spared bifurcation.

References Cited:

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Dadon-Nachum M, Melamed E, Offen D. 2011. The “dying-back” phenomenon of motor neurons in ALS. J Mol Neurosci 43:470–477.

Feoktistov AI, Herman TG. 2016. Wallenda/DLK protein levels are temporally downregulated by Tramtrack69 to allow R7 growth cones to become stationary boutons. Development 143:2983–2993.

Fernandes KA, Harder JM, John SW, Shrager P, Libby RT. 2014. DLK-dependent signaling is important for somal but not axonal degeneration of retinal ganglion cells following axonal injury. Neurobiol Dis 69:108–116.

Ghosh AS, Wang B, Pozniak CD, Chen M, Watts RJ, Lewcock JW. 2011. DLK induces developmental neuronal degeneration via selective regulation of proapoptotic JNK activity. J Cell Biol 194:751–764.

Hao Y, Frey E, Yoon C, Wong H, Nestorovski D, Holzman LB, Giger RJ, DiAntonio A, Collins C. 2016. An evolutionarily conserved mechanism for cAMP elicited axonal regeneration involves direct activation of the dual leucine zipper kinase DLK. Elife 5. doi:10.7554/eLife.14048

Huntwork-Rodriguez S, Wang B, Watkins T, Ghosh AS, Pozniak CD, Bustos D, Newton K, Kirkpatrick DS, Lewcock JW. 2013. JNK-mediated phosphorylation of DLK suppresses its ubiquitination to promote neuronal apoptosis. J Cell Biol 202:747–763.

Katz JS, Rothstein JD, Cudkowicz ME, Genge A, Oskarsson B, Hains AB, Chen C, Galanter J, Burgess BL, Cho W, Kerchner GA, Yeh FL, Ghosh AS, Cheeti S, Brooks L, Honigberg L, Couch JA, Rothenberg ME, Brunstein F, Sharma KR, van den Berg L, Berry JD, Glass JD. 2022. A Phase 1 study of GDC-0134, a dual leucine zipper kinase inhibitor, in ALS. Ann Clin Transl Neurol 9:50–66.

Klinedinst S, Wang X, Xiong X, Haenfler JM, Collins CA. 2013. Independent pathways downstream of the Wnd/DLK MAPKKK regulate synaptic structure, axonal transport, and injury signaling. J Neurosci 33:12764–12778.

Le K, Soth MJ, Cross JB, Liu G, Ray WJ, Ma J, Goodwani SG, Acton PJ, Buggia-Prevot V, Akkermans O, Barker J, Conner ML, Jiang Y, Liu Z, McEwan P, Warner-Schmidt J, Xu A, Zebisch M, Heijnen CJ, Abrahams B, Jones P. 2023. Discovery of IACS-52825, a potent and selective DLK inhibitor for treatment of chemotherapy-induced peripheral neuropathy. J Med Chem 66:9954–9971.

Le Pichon CE, Meilandt WJ, Dominguez S, Solanoy H, Lin H, Ngu H, Gogineni A, Sengupta Ghosh A, Jiang Z, Lee S-H, Maloney J, Gandham VD, Pozniak CD, Wang B, Lee S, Siu M, Patel S, Modrusan Z, Liu X, Rudhard Y, Baca M, Gustafson A, Kaminker J, Carano RAD, Huang EJ, Foreman O, Weimer R, Scearce-Levie K, Lewcock JW. 2017. Loss of dual leucine zipper kinase signaling is protective in animal models of neurodegenerative disease. Sci Transl Med 9. doi:10.1126/scitranslmed.aag0394

Li J, Zhang YV, Asghari Adib E, Stanchev DT, Xiong X, Klinedinst S, Soppina P, Jahn TR, Hume RI, Rasse TM, Collins CA. 2017. Restraint of presynaptic protein levels by Wnd/DLK signaling mediates synaptic defects associated with the kinesin-3 motor Unc-104. Elife 6. doi:10.7554/eLife.24271

Miller BR, Press C, Daniels RW, Sasaki Y, Milbrandt J, DiAntonio A. 2009. A dual leucine kinase-dependent axon self-destruction program promotes Wallerian degeneration. Nat Neurosci 12:387–389.

Nihalani D, Merritt S, Holzman LB. 2000. Identification of structural and functional domains in mixed lineage kinase dual leucine zipper-bearing kinase required for complex formation and stress-activated protein kinase activation. J Biol Chem 275:7273–7279.

Russo A, DiAntonio A. 2019. Wnd/DLK is a critical target of FMRP responsible for neurodevelopmental and behavior defects in the Drosophila model of fragile X syndrome. Cell Rep 28:2581–2593.e5.

Shin JE, Cho Y, Beirowski B, Milbrandt J, Cavalli V, DiAntonio A. 2012. Dual leucine zipper kinase is required for retrograde injury signaling and axonal regeneration. Neuron 74:1015–1022.

Siu M, Sengupta Ghosh A, Lewcock JW. 2018. Dual Leucine Zipper Kinase Inhibitors for the Treatment of Neurodegeneration. J Med Chem 61:8078–8087.

Valakh V, Walker LJ, Skeath JB, DiAntonio A. 2013. Loss of the spectraplakin short stop activates the DLK injury response pathway in Drosophila. J Neurosci 33:17863–17873.

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Wlaschin JJ, Donahue C, Gluski J, Osborne JF, Ramos LM, Silberberg H, Le Pichon CE. 2023. Promoting regeneration while blocking cell death preserves motor neuron function in a model of ALS. Brain 146:2016–2028.

Xiong X, Collins CA. 2012. A conditioning lesion protects axons from degeneration via the Wallenda/DLK MAP kinase signaling cascade. J Neurosci 32:610–615.

Xiong X, Hao Y, Sun K, Li J, Li X, Mishra B, Soppina P, Wu C, Hume RI, Collins CA. 2012. The Highwire ubiquitin ligase promotes axonal degeneration by tuning levels of Nmnat protein. PLoS Biol 10:e1001440.

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DOI: 10.1111/jnc.16291

Resource: None

Curator: @scibot

SciCrunch record: RRID:IMSR_RBRC05638

What is this?

Dg diferenciales de encefalopatía hipertensiva: * Isquemia cerebral * ACV hemorrágico o trombótico * Trastorno convulsivo * Efecto de masa * Pseudotumor cerebral * Delirium tremens * Meningitis * Porfiria intermitente aguda * Lesión cerebral traumática o química * Encefalopatía urémica

Receptores adrenérgicos:

a1: ppalmente NA. Ubicados en células postsinápticas del músculo listo -> Vasoconstricción - Intensifican reabsorción renal de Na - Antihipertensivos inhiben receptores a1

a2: ppalmente por catecolaminas. Ubicados en mb presinápticas que sintetizan NA. -> Inhibe liberación de NA - Antihipertensivos inhiben receptores a2

b1: Ubicados en miocardio. Inotrópico y cronotrópico -> Aumenta GC - Estimula liberación de renina renal. - Antihipertensivos inhiben receptores b1

b2: en músculo liso. Estimulada por adrenalina. -> relaja músculo liso y vasodilatación.

La insuficiencia suprarrenal secundaria (hipotálamo - hipófisis) es más común que la insuficiencia suprarrenal primaria (enfermedad de Addison)

La insuficiencia suprarrenal secundaria es causada común mente por una supresión del eje hipotálamo - hipófisis por tratamiento exógeno con glucocorticoides

La enfermedad de Addison es causada principalmente por destrucción autoinmunitaria de las glándulas suprarrenales (suprarrenalitis autoinmunitaria) * APS1 → mutación en AIRE * APS2 (más común) → mutación en HLA-DR3

Otras causas de insuficiencia suprarrenal primaria son las infecciones, hemorragias o infiltración * Tuberculosis (sigue siendo común en paises subdesarrollados)

把脉

热烈欢迎

Note: This response was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

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1. General Statements

We thank the reviewers for their thorough and positive evaluation of the manuscript.

2. Point-by-point description of the revisions

We revised the manuscript following the suggestions of the reviewers to make the article more concise and comprehensible to a wider audience. Specifically, we rearranged Section 5, rewrote the difficult-to-understand sections 5 and 6, and removed unnecessary or overlapping text in Introduction and Discussion. We have also addressed the specific points raised by the reviewers. The responses to individual points are detailed below.

Reviewer 1:

The reviewer did not ask for any changes to the manuscript.

We thank the reviewer for the positive evaluation of the manuscript.

Reviewer 2:

1/ Title: Structure-based mechanism of RyR channel operation by calcium and magnesium ions

The authors may consider using an alternative term instead of "operation".

Thank you for the suggestion. We considered and discussed the term "RyR channel operation" very thoroughly with several colleagues, including native English speakers, and we found it to represent the complex RyR behavior in situ and in experiments most exactly. Alternative terms such as "control" suggest a one-way deterministic action from the ion binding to the protein state, which is not the case. The terms such as "modulation" implicate the presence of a higher RyR state-governing principle, such as phosphorylation, nitrosylation, binding of auxiliary proteins, etc.

2/ Abstract: Please spell out CFF and MWC theorem.

Thank you for the proposal. CFF was changed to caffeine; MWC was changed to Monod-Wyman-Changeaux

3/ Line 87-88: "In striated muscle cells, RyR channels cluster at discrete sites of sarcoplasmic reticulum attached to the sarcolemma where electrical excitation triggers transient calcium release by activation of RyRs."

There is no attachment between sarcoplasmic reticulum and sarcolemma, please rewrite.

We respectfully disagree, since there is strong evidence for the existence of discrete contact sites between the sarcolemma and sarcoplasmic reticulum both at triads of skeletal muscle (Rossi et al., 2019) and at dyads of cardiac muscle (Mackrill, 2022), at which both membranes are firmly attached.

However, to avoid potential misunderstanding, we changed the sentence to "In striated muscle cells, RyR channels cluster at the discrete sites of sarcoplasmic reticulum attached to the sarcolemma in triads or dyads, where electrical excitation triggers transient calcium release by activation of RyRs" (lines 86-87).

4/ Lines 104-107: "Recently, mathematical modeling of the cardiac calcium release site (Iaparov et al., 2022) confirmed that Mg2+ ions could at the same time act as the negative competitor at the calcium activation site and as an inhibitor at the inhibition site. Unfortunately, the structural counterpart of RyR inactivation, an inhibitory binding site for divalent ions, has not been located yet in RyR structures."

Note that the exact structural counterpart exists (Nayak et al., 2022, 2024), where Ca and Mg were found both at the activation and inhibition sites. The paragraph should be updated accordingly.

We respectfully disagree. In the cited works of Nayak et al. (2022; 2024) it was shown that Ca and Mg ions bind firmly at the activation site. Both atoms were also observed at the ACP molecule bound at the ATP binding site. However, they were not observed at the divalent ion-binding inhibition site, which is distinct from the ATP binding site and resides in the loops of the EF-hand region.

However, to clarify the meaning of the disputed sentence, we have changed it to: "Although binding of Ca2+ or Mg2+ to an inhibitory binding site has not been observed yet in RyR structures, a consensus is emerging that the EF-hand loops constitute this site (Gomez et al., 2016; Zheng and Wen, 2020; Nayak et al., 2024; Chirasani et al., 2024 )" (lines 107-109).

5/ Lines 108-110: The activation of RyR by agonists was shown to be accompanied by a conformational change around the Ca2+ binding site that leads to a decrease in the free energy and to a concomitant increase of the Ca2+ binding affinity and a population shift between the closed and open conformations (Dashti et al., 2020).

Please clarify to what state does the "decrease in free energy" refer, to the open or to the closed state?

Thank you for the proposal. The text was changed to: "The activation of RyR by agonists was shown to be accompanied by a conformational change around the Ca2+ binding site that leads to a decrease in the free energy of the open state and concomitantly to an increase of the Ca2+ binding affinity of the activation site. As a result, the occurrence probability of a RyR state/conformation shifts from the closed toward the open (Dashti et al., 2020)" (lines 110-113).

6/ Figure 2: please indicate if distances were measured between the C-alphas or side chains.

Thank you for the proposal. The figure legend was modified to "Distances D1 between the Cα atoms of E4075 and R4736 or equivalent. Right - Distances D2 between the Cα atoms of K4101 and D4730 or equivalent."

7/ Line 353-357: "These data suggest that interactions between the basic arginine residue R4736 and the acidic residues at the start of the initial helix E of the EF1-hand are specific for Ca2+-dependent inactivation in RyR1, whereas the interactions between the lysine K4101 that immediately follows the F helix of EF1 and the middle of the S23 loop (corresponding to D4730 and I4731 in RyR1) may play a part in the inactivation of both RyR1 and RyR2 isoforms.

Sentence is unclear; please rewrite. Overall, the entire section "Spatial interactions between the EF-hand and S23* regions" should be simplified and shortened.

Thank you for the proposal. The text was changed to: "These data suggest that interactions between the basic arginine residue R4736 and the acidic residues E4075 and D4079 are specific for Ca2+-dependent inactivation in RyR1, whereas the interactions between the lysine K4101 and the residues D4730 and I4731 (rRyR1 notation)* may play a part in the inactivation of both RyR1 and RyR2 isoforms." (lines 334-337).

We did not find a way how to make the whole section simpler and shorter at the same time without losing clarity.

8/ Lines 246-249 and Table 1. "all structures corresponding to rRyR1 residues 4063-4196 were<br /> subjected to energy minimization and submitted to the MIB2 server for evaluation of the ion binding score (IBS) of individual amino acid residues and the number of ion binding poses (NIBP) for Ca and Mg ions."

Please elaborate on the "ion binding score" and "number of ion binding poses" concepts and provide reference for the MIB2 server.

Thank you for the proposal. We added the reference for the server (Lu et al., 2022) (line 228) and added the information: "IBS values of individual residues are determined using sequence and structure conservation comparison with 409 and 209 respective templates from the PDB database for Ca2+ and Mg2+ (Lin et al., 2016) and assessing the similarity of the configuration of the residue to its configurations in known structures of its complexes with the given metal (Lu et al., 2012). Ion binding sites are determined by locally aligning the query protein with the metal ion-binding templates and calculating its score as the RMSD-weighted scoring function Z. The site is accepted if it has a scoring function Z>1, and based on the local 3D structure alignment between the query protein and the metal ion-binding template, the metal ion in the template is transformed into the query protein structure (Lin et al., 2016). The larger the IBS value, the higher the tendency of the residue to bind the ion. The larger the NIBP value, the larger the number of such complexes with acceptable structure" (lines 224-234).

9/ Lines 460-466: Nine structural models of RyR were selected, and then these are referred to in the text only with the pdb code. The reviewer understands that it would be difficult to recapitulate all conditions but either a table in the main manuscript file or a minimal description in the text following the pdb code would increase clarity and help readers to follow the content.

Thank you for the proposal. We added a new Table 2 "Model structures used for identifying the allosteric pathways" on line 452 that contains the required information, and inserted a reference to it in the text at line 446 "According to these criteria we selected five RyR1 model structures (Table 2)..."

10/ Line 467: "In the selected structures, we identified residues with high allosteric coupling intensities (ACI) for both the inhibition and activation network and compared them with residues important for ligand binding and gating of RyR (Table 2)."

Please define further the concept of "allosteric coupling intensities". The corresponding methods section appears to focus on the outputs of the OHM server without delving too much on the algorithm or principles followed. Is the allosteric coupling between neighboring residues, or reflect movement of the residues due to ligand binding? Is there a "reference" state or are the comparisons carried out within each allosteric state? This would help to introduce better the sections "The inhibition network" and "The activation network".

Thank you for this suggestion. We have lately realized, considering both the server output and the original work of Wang et al. (2020), that a better term for the variable depicting the role of the residue in the allosteric pathway would be the residue importance RI rather than the ACI. The allosteric pathway is determined on the basis of the network of contacts between pairs of residues in the given structure. The more contacts are present between two residues, the higher is the probability that a perturbation will be propagated from one to the other residue (Eq. 3 of Wang et al. (2020)). An allosteric pathway is then defined as the pathway that transmits the signal the whole way from the allosteric site to the active site.

Based on this we have changed in the manuscript the term "allosteric coupling intensity" to "residue importance" throughout the text and figures of the manuscript. It should be underlined, that this change has no effect whatsoever on presented data and conclusions. We inserted the following formulation in the Results section:

"The term residue importance defines the extent to which the given residue is involved in the propagation of a perturbation from the allosteric site to the active site, i.e., the fraction of simulated perturbations transmitted through this particular residue. The more contacts are present between two residues, the higher is the probability that a perturbation will be propagated from one to the other residue (Wang et al., 2020)." (lines 439-443).

We also inserted the following formulations into the Methods section: "The simulation of the perturbation propagation was performed 10 000 times per structure and pathway to estimate the values of residue importance." (lines 1093-1095), and we expanded the relevant sentence: "Allosteric pathways were traced using the server OHM (https://dokhlab.med.psu.edu/ohm/#/home, (Wang et al., 2020)), in which the allosteric pathway is determined on the basis of the network of contacts between pairs of residues in the given structure." (lines 1082-1084).

11/ Figure 8: The figure would be more meaningful if the pathways were drawn in the context of the 3D structure.

Thank you for the proposal. The pathways described in Fig. 8 are too complex for description in the RyR 3D structure, therefore they were not presented in the original manuscript. However, to follow the reviewer's proposal we have illustrated the pathways observed in the inactivated RyR1 channel (7tdg) and the open RyR2 channel (7u9) in Expanded View Figure EV1 and added the corresponding Expanded View Movie EV1 and EV2. These RyR structures were selected for displaying both the intra- and inter-monomeric inactivation pathways.

12/ Lines 610-612: "The structure of the inactivated RyR2 has not been determined yet; however, it is plausible to suppose that it exists at high concentrations of divalent ions and differs from the inactivated RyR1 structure by the extent of EF-hand - S23* coupling. "

The speculation would be more fit for the discussion section.

Thank you for the proposal; however, the sentence introduces a logical supposition, necessary there for reasoning on the construction of the model. We reformulated the sentence to: "In the absence of a structure of the inactivated RyR2, the model assumes that such a structure exists at high concentrations of divalent ions and differs from the inactivated RyR1 structure by the extent of EF-hand - S23* coupling." (lines 573-575).

13/ Lines 617-619: Closed and primed macrostates could be combined into a single closed macrostate of the model since both are closed and cannot be functionally distinguished at a constant ATP concentration.

The rationale for combining closed with primed does not seem a good idea, especially since the authors also mention that "the primed state is structurally very close to the open state" (lines 925-926). If the COI model is based on the structural findings, in principle it seems that primed should be treated separately.

Thank you for the proposal. The use of both the closed and primed states was crucial for solving the model. As a matter of fact, although the primed and closed states are in part structurally different, functionally they are identical, that is, closed. Consequently, to be distinguished in a functional model we would need to incorporate single-channel data obtained under conditions when the ratio of closed and primed channels was modulated under otherwise identical conditions. Unfortunately, such a set of data, for instance at a varying ATP concentration for a range of cytosolic Ca2+ concentrations, does not exist for either RyR1 or RyR2 channels. Moreover, while there are several RyR1 high-resolution structures in the primed state (such as the 7tzc that we used; 2.45 Å; Melville et al. (2022)), the resolution of the corresponding RyR2 structures (6jg3, 6jh6, 6jhn; 4.5 - 6.1 Å; Chi et al. (2019)) is not sufficient for determination of allosteric pathways. Fortunately, however, the two sets of conditions for RyR2 open probability data that were available in the literature turned out to represent activation of channels either selectively from the closed state (Fig. 10C), or almost selectively from the primed state (Fig. 10A, B). This allowed us to interpret the difference in the allosteric coefficients as a consequence of this fact.

To better clarify the idea, the corresponding text of the Discussion was modified as follows (lines 926-931): "RyR channels can be considered mostly in the primed state under these conditions since the binding of ATP analogs induces the primed structural macrostate in RyRs even in the absence of Ca2+ (Cholak et al., 2023). Fortunately, the two sets of conditions for RyR2 open probability data that were available in the literature turned out to represent activation of channels either selectively from the closed state (Fig. 10C), or selectively from the primed state (Fig. 10A, B).", and "construction of such a model is at present hampered by the lack of open probability data at a sufficiently wide range of experimental conditions and the absence of high-resolution structures of WT RyR2 in the primed state" (lines 934-937).

14/ Line 619. Please define the "COI" acronym. I assume it is closed, open and inactivated but this is not mentioned.

We thank the reviewer for noticing the insufficiency. We expanded the specific sentence as follows: Therefore, we constructed the model of RyR operation, termed the COI (closed-open-inactivated) model, in which we assigned a functional macrostate corresponding to each of the closed, open, and inactivated structural macrostates (Figure 9A)" (line 582).

15/ Figure 9: The diagrams are difficult to follow. Something that could improve it is to differentiate more between open and closed gates, but further elaboration would help the reader.

We thank the reviewer for paying attention to details. The open state was differentiated in Figure 9 (after line 603) by adding a pore opening to the gate.

To elaborate on the gating transitions and to keep the manuscript concise, we added a new Expanded View Figure EV2, which illustrates the relationship between the ion binding within macrostates and the transitions between macrostates.

Nevertheless, for the complexity of the model, which would need a multidimensional presentation, we had to limit the illustration to only the binding of the first ions at the binding sites. We hope that it will help the reader to grasp the principle of the model function more easily.

16/ One comment is that the manuscript is too long; the manuscript exceeds the typical length required by most journals. To enhance its suitability for publication, the content needs to be synthesized and streamlined. The manuscript is written for an audience specialized in the RyR field and may be challenging for outsiders or for readers unfamiliar with structure and/or biophysical models.

We thank the reviewer for opening this problem. The specific contribution to the understanding of RyR operation communicated by this manuscript was achieved by the synergy of approaches coming from different fields of RyR research - the structural, the functional, and the synthetic/systems ones. This needed deep immersion into complex studies performed over several decades to unwrap their complementary contributions. Only then we could synthesize the stepwise advances and integrate the mosaic of partial discoveries into the COI model. When conceptualizing the manuscript we were also considering a two-paper version, one on structural aspects and the other on modeling aspects. We realized that the two papers would need to have a very high overlap at the allosteric mechanism to be understandable in separation and would be difficult to publish in the same journal. We also anticipated a typical side effect that structuralists and modelers would read just their parts and would not appreciate enough the feedback from alternative views - how to design and interpret future structural, functional, and modeling studies.

Compacting the manuscript would be extremely difficult for us. In our view, the dense text would make it even more challenging for readers unfamiliar with some of the numerous approaches used here, as often happens to prominent multidisciplinary journals. Maybe it would be possible with the help of AI, but for now, we prefer to remain authentic.

Nevertheless, we made some effort. To shorten the manuscript, we have removed the paragraph describing the timeline of the search for the RyR inhibition site that was originally on lines 126-151 and replaced it with the paragraph on lines 129-134: "The regulatory domains involved in both, activation and inactivation of RyRs (Figure 1) are located in the C-terminal quarter of the RyR. The Central domain participates in the Ca2+ binding activation site; the C-terminal domain bears several residues of Ca-, ATP- and caffeine-binding activation sites; the U-motif participates at the ATP- and caffeine-binding sites; the EF-hand region contains the putative Ca-binding pair EF1 and EF2; and the S23 loop bears one residue of the caffeine-binding site and two residues interacting with the EF-hand region of a neighboring monomer (Samso, 2017; Hadiatullah et al., 2022)". We also removed the statements about the proposed kinetic mechanism of inactivation by Nayak et al. (2022), originally on lines 175-184. Finally, we removed the discussion of the work of Gomez et al. (2016) originally on lines 882-889, since it fully overlapped with the statements in Results on lines 358-367 (now lines 338-347). We also moved the text of the subsection "Relationship between the COI model and RyR allosteric pathways" (originally lines 670-685) into subsection "Construction of the model of RyR operation", lines 592-603 and 645-662 of the revised version.

17/ Another comment is the limited consideration of two relevant published works. One is by Chirasani et al. (2024), focused on allosteric pathways similar to the ones described here. The other work is by Nayak et al (2024), with cryo-EM structures of RyR1 focused on the interplay with Mg2+ and Ca2+. Overall, the manuscript would be strengthened by incorporating such related results in the literature.

We thank the reviewer for the concerns, but we cannot fully agree. The paper of Chirasani et al. (2024 ) was cited in the manuscript as its online-first version, Chirasani et al. (2023). The manuscript now refers to the printed version proposed by the reviewer. The Chirasani et al. work was discussed on lines 870-881. The paper concentrates on the interaction between the EF-hand region and the S23 segment and its effect on RyR inactivation, which we referenced in the manuscript, but not on the allosteric pathways as mentioned by the reviewer. To broaden the consideration of this important work, we have introduced a more detailed discussion of Chirasani et al. (2024 ) by adding the following text to the manuscript: Lines 881-888: "Based on their structural analysis of the open RyR1 structure 5tal, Chirasani et al. (2024 ) proposed that narrowing the gap between the EF-hand domain and S23 loop, resulting in H-bonding interactions between the EF-hand residue K4101 and the S23 loop residue D4730, and those between the EF-hand residues E4075, Q4076, D4079 and the S23 loop residue R4736, is a consequence of the binding of Ca2+ to the EF-hands. However, our PDBePISA analysis revealed a similar number of interactions between the EF-hand region and the S23 loop not only in open and inactivated but also in primed RyR1 structures (Figure 3). The presence of EF hand-S23 hydrogen bonds in the primed and open RyR1 structures suggests that the proximity of the EF-hand domain and S23 loop is a structural trait distinguishing RyR1 from RyR2, not a consequence of Ca2+ binding to the EF hand.*"

The data and ideas of the illuminating work of Nayak et al. (2024) were discussed and referred to in the manuscript in several places, originally lines 74, 77, 164 (Introduction), 311, 340 (Results), 892-893, and 971 (Discussion). To broaden consideration of this work, we have expanded the discussion of this paper by adding the text shown in bold into the Introduction: "Recent studies reporting RyR structure at a high divalent ion concentration provide only indirect support for the molecular mechanism of Ca2+/Mg2+-dependent inactivation. Wei et al. (2016) and Nayak et al. (2024) observed a change in the conformation of the RyR1 EF-hands in the presence of 100 µM Ca2+ and 10 mM Mg2+, respectively, compared to low-calcium or low-magnesium conditions." (lines 135-138) and in the Discussion (lines 889-891): "The recent RyR1 structure 7umz (Nayak et al., 2024) provided evidence of Mg2+ ion bound in the RyR activation site, thus confirming the functional studies that established competition between Ca2+ and Mg2+ at this activation site (Laver et al., 1997; Zahradnikova et al., 2003; Zahradnikova et al., 2010)."

Reviewer 3:

Minor comment: While I am not an expert in allosteric model construction and therefore cannot fully assess their methodological approach, I observed that the authors fixed a number of parameters to achieve model convergence. A more detailed explanation of the rationale behind these fixed parameters would enhance clarity. Currently, these parameters are not clearly specified in the text and are somewhat obscured by the broader description of all parameters included in the model.

We thank the reviewer very much for this comment, which made us realize that the relevant sections were written in a too technical manner, without sufficient explanation of the ideas behind the derivation and optimization of the model. To clarify the rationale of this process, we have rewritten the subsection "Derivation of the model open probability equation" and the section "Description of RyR operation by the COI model". In the subsection "Derivation of the model open probability equation", we have explained the simplification of the full set of equations (Eqs. 3A-C) into Eqs. 4A-C (lines 642 - 666). In the section "Description of RyR operation by the COI model", we have explained the extent of over-parametrization and the rationale of reducing it by three methods: combining the data into groups with common parameter values; eliminating parameter interdependence by fixation of one parameter at a preset value taken from the literature or postulated a priori; and sharing parameter values between data groups when no significant difference between these values was observed (lines 683-685, 702-710, 719-740).

We hope that these changes make the manuscript more comprehensible.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility____,____ and clarity)

This manuscript by Tsai et al. shows that phage resistance mutations (LPS truncation) confer a cost during interbacterial competition. The authors show that various phage resistant mutants of S. enterica are inhibited by E. cloacae in a contact-dependent manner (on a solid surface but not in liquid). Further experiments showed that this inhibition of S. enterica was mediated by T6SS in E. cloacae. The authors then dissect which parts of the LPS are required for resistance against T6SS attacks and show that a similar resistance is conferred against T6SS of B. thailandensis and C. rodentium. Moreover, the authors show that enzymatic degradation of LPS by a phage enzyme can also increase sensitivity to T6SS (including when such enzymes are on phage particles). Finally, the authors suggest that the change in the thickness of the LPS surface layer could be the reason for changes in T6SS susceptibility. Overall, the manuscript is very well-written. The experiments and controls are explained in sufficient detail and in a logical order. The figures are clear and easy to navigate. The findings are very interesting and important for the T6SS field but also for general understanding how different evolutionary pressures combine and influence each other. I believe that this manuscript will initiate further research in this direction.

• We thank the reviewer for their positive remarks on our manuscript and the valuable suggestions for its improvement. Major comments

The only major point that I would like to raise is that I am not generally convinced that the 2 nm difference in the thickness of LPS is the main reason for the observed differences in T6SS-mediated killing of S. enterica. Based on what we know about T6SS mode of action, we expect that it is potentially pushing effectors by up to several hundreds of nanometers. Therefore, the change in the LPS thickness by a few nanometers (as measured by AFM) seems insufficient to provide enough spacing between the attacker and the prey to significantly decrease T6SS effector delivery. While it is clear that understanding the exact reason for the LPS mediated resistance is beyond the scope of this manuscript, I would suggest that the authors consider the fact that T6SS is known to deliver proteins even to the cytoplasm of target gram-negative cells and discuss the mode of action of the machine in the context of their finding. If the T6SS was drawn to scale in the model figure, it would become apparent that 2 nm change in the distance between two cells has probably no major impact on killing by T6SS and the actual reason for the observed phenotype is likely more complicated than what is proposed.

We appreciate the reviewer's comments and acknowledge that our manuscript leaves open questions regarding the exact mechanisms underlying LPS-mediated resistance. We have now moderated the Discussion in our revised manuscript to reflect the complexity of this phenomenon (Lines 410-423). Although we agree that the nanometer difference in LPS thickness may not fully explain the observed protective phenotype, we believe it remains a plausible contributing factor that is worth considering.

To fully understand how LPS influences T6SS effector delivery, future studies will need to address key mechanistic questions regarding the T6SS injection process. For example, 1) how deeply does the T6SS apparatus penetrate the target Gram-negative cells during injection; 2) what is the magnitude of the injection force generated by the T6SS; and 3) does the structural integrity of the T6SS apparatus remain intact throughout and after contraction? While it is well documented that some T6SS effectors act in the cytosol of target cells, there is evidence to suggest that cytosolic effectors are initially delivered into the periplasm and subsequently translocated into the cytosol for intoxication1,2. Furthermore, although contraction of the T6SS apparatus occurs within milliseconds3,4, this rapid action does not preclude the possibility that the injection force could be influenced by the thickness of the LPS layer. In addition, the stability of T6SS structural or delivered proteins-such as PAAR, VgrG, and Hcp-within the delivery complex might be compromised upon encountering physical barriers such as the LPS layer and the outer membrane of target cells. These potential interactions could affect the efficiency of effector delivery, leading to reduced competitiveness during interbacterial antagonism, as shown in our study.

• We appreciate the reviewer's suggestions and acknowledge that the precise reasons for LPS-mediated resistance likely involve a combination of factors beyond those proposed here. We are actively pursuing these questions as part of an ongoing, long-term effort to better elucidate the mechanisms of T6SS action. Minor comments

Specify which T6SS of B. thailandensis was tested.

• We now cite studies by Schwarz, S., et al., 20105 and LeRoux, M., et al., 20156, from which we used the tssM (BTH_I2954) gene deletion strain abrogating the T6SS-1 of the B. thailandensis E264 (Line 234, Supplementary Table 1). Use a different naming of the two strains used in competition assays than "donor" and "recipient".

• Thank you for this suggestion. In the revised manuscript, we have replaced the terms "donor" and "recipient" with "attacker" and "prey" for clarity. This change has been applied to the text (Lines 441, and 649-667) and to revised Figures 2c-h, Figures 3b, d, g, i, j, Figures 4f, g, Figures 5b, e, g, h, Supplementary Figures 3d-f, and Supplementary Figures 4b-d. Indicate in the material and methods ODs of bacterial mixtures used in the "Bacterial competition assays".

• We apologize for this oversight. The ODs of bacterial mixtures used in the "Bacterial competition assays" have now been specified in the revised Methods section (Line 6____51). Reviewer #1 (Significance)

This manuscript is interesting for researchers who study T6SS, phage predation and other evolutionary pressures shaping bacterial interactions. The work provides new and interesting insights. My expertise in LPS biology is limited.

• We sincerely appreciate the reviewer's interest in and support of our study. Reviewer #____2____ (Evidence, reproducibility____,____ and clarity)

This work investigates the fitness trade-offs in Salmonella enterica resistant to phages. The authors performed co-culture experiments with S. enterica, E. coli, and E. cloacae and found that phage-resistant S. enterica strains displayed reduced fitness in the presence of E. cloacae. Further experiments demonstrated that phage-resistant S. enterica strains were more susceptible to the type VI secretion system (T6SS) of E. cloacae. The authors then examined the role of the O-antigen of lipopolysaccharide (LPS) in T6SS-mediated interbacterial antagonism. By constructing S. enterica mutants with varying O-antigen chain lengths, the authors demonstrated that the O-antigen protects S. enterica from T6SS attack. They then demonstrated that the O-antigen-deficient S. enterica, E. coli, and C. rodentium strains were more susceptible to T6SS attack by E. cloacae. Finally, the authors showed that phage tail spike proteins (TSPs) with endoglycosidase activity could cleave the bacterial O-antigen, thereby increasing susceptibility to T6SS attack.

The study is well-designed and the experiments are well-executed. The findings are significant and have implications for the understanding of microbial community dynamics.

• We thank the reviewer for their positive comments regarding our original submission. Major comments

While the study elegantly demonstrates the link between phage resistance, LPS structure, and T6SS susceptibility, we must remember that these LPS-defective strains are likely at a significant disadvantage in real-world environments without the influence of competing bacteria. Whether it's the gut or external environments, Salmonella needs its LPS for protection against a myriad of host and environmental factors. It seems a bit redundant for T6SS mediated antagonism to select for LPS structures when those structures are essential for bacterial survival outside of this very specific context. It would benefit some discussion about the likelihood of these phage-resistant, LPS-defective strains actually persisting and competing effectively in a more natural setting.

• We thank the reviewer for their insightful comments and appreciate the opportunity to clarify this point. We agree that LPS-defective bacterial strains face significant disadvantages in natural environments, where they must contend with various host and environmental stresses. Consequently, we did not intend to suggest that T6SS-mediated antagonism is the primary driving force in selecting specific LPS structures. Rather, our study highlights an additional role for LPS during interbacterial interactions, complementing its well-established functions. This notion aligns with the hypotheses proposed in prior studies7-9. The reviewer's comments raise an intriguing question about the essentiality of LPS in Gram-negative bacteria under natural conditions. During our revision process, we identified several examples in the literature demonstrating that LPS may not always be indispensable. For instance, LPS-depleted Neisseria meningitidis strains with an early block in lipid A biosynthesis have been shown to remain viable10,11. These strains may possess adaptive advantages under specific circumstances12. Similarly, some pathogenic bacteria produce truncated LPS structures lacking O-antigen or introduce modified LPS to evade host immune responses13. Additionally, evolutionary pressures, such as phage predation, often drive mutations in O-antigen biosynthesis pathways, resulting in alterations to or an absence of O-antigen14. Furthermore, recent studies have also indicated that trade-offs between abiotic and biotic stresses can influence LPS integrity. For instance, LPS-deficient strains may exhibit selective advantages in extreme environments15,16. These findings underscore the context-dependent nature of LPS functionality and its potential dispensability in certain ecological niches.We sincerely appreciate the reviewer's thought-provoking comments. Our current study aims to provide evidence for the role of interbacterial antagonism as an additional factor influencing LPS integrity. However, we did not mean to overstate the contribution of this mechanism. Instead, we only seek to contribute to a broader understanding of the multifaceted functions of LPS in bacterial survival and adaptation. We have modified the Discussion in our revised manuscript to clarify this idea (Lines 453-466). Minor comments

Figure 5 could be more effective is panels b and c are together

• We appreciate this suggestion. We have revised the manuscript accordingly, so panels b and c have been combined in revised Figure 5, __and the respective figure legends have been modified for improved clarity (__Lines 810-823).

69 Authors should define mucoid

• The term "mucoid" has now been defined in the revised manuscript (Lines 69-70).

155 Authors should explain that this result is expected since T6SS acts on solid surface while CDI works in liquid cultures

• Thank you for this comment. Prior studies have demonstrated that while CDI-mediated antibacterial activity is less efficient in liquid environments, it can still occur on both solid surfaces and in liquid cultures, provided the competitors possess the necessary CdiA binding unit, such as BamA17,18. This understanding supports our initial hypothesis that T6SS and/or CDI contribute to the observed protective phenotype in S. enterica phage-resistant variants (Figure 2).

clarify what it is meant by unicellular cultures. Should it be monocultures?

• We apologize for this error and have now replaced "unicellular cultures" with "monocultures" in the revised manuscript (Lines 137, 180, and 258).

618 add to the text how much dead phage was added per bacterial cell

• Apologies for this oversight. The multiplicity of infection (MOI) describing the amount of inactivated phages used to treat bacterial cells has now been included in the revised Methods section (Line 661).

364 references needed for "consistent with predictions for intact LPS structures "

• We thank the reviewer for pointing out this omission. The relevant reference has now been added to the revised manuscript19 (Line 368). Reviewer #____2____ (Significance)

This study offers a new perspective on the interplay between phage resistance and bacterial fitness in the context of microbial communities. While the concept of fitness trade-offs associated with antibiotic resistance is well-established, the authors extend this paradigm to phage resistance. They demonstrate that phage-resistant Salmonella enterica strains exhibit reduced fitness in the presence of Enterobacter cloacae due to increased susceptibility to the type VI secretion system (T6SS). This finding is significant as it highlights the potential for interbacterial antagonism to shape the evolution of phage resistance. The authors further show that the O-antigen of lipopolysaccharide (LPS) plays a crucial role in protecting S. enterica from T6SS attack. This observation provides mechanistic insights into the fitness trade-offs associated with phage resistance.

The study's strength lies in its elegant experimental design and the comprehensive analysis of the interplay between phage resistance, T6SS susceptibility, and O-antigen structure. The authors employ a combination of co-culture experiments, genetic manipulations, and structural analyses to dissect the underlying mechanisms. The findings are robust and have implications for understanding the evolution of bacterial communities in the presence of phages and competing bacterial species.

This research will be of interest to a broad audience, including researchers in microbiology, synthetic biology, and microbial ecology. The findings have implications for understanding the evolution of phage resistance, and the dynamics of microbial communities. The study's insights into the role of the O-antigen in T6SS susceptibility could also inform the design of novel antimicrobial strategies.

My expertise is microbial physiology

• We thank the reviewer for their positive remarks and careful reading of our manuscript. Reviewer #____3____ (Evidence, reproducibility____,____ and clarity)

Tsai et al. describe LPS biosynthesis mutants arising in selection for phage resistance that increase susceptibility to T6SS-mediated interbacterial antagonism. Phage-derived LPS degrading enzymes also contribute to T6SS susceptibility, which may be due to weakening of the physical barrier of LPS. The mechanisms of this fitness trade-off are elucidated with well-executed and presented experiments.

• We are grateful to the reviewer for their kind words and critical reading of the manuscript. Major comments

No major critiques.

Minor comments

Others have described two T6SS in Enterobacter cloacae ATCC 13047 (PMID 33072020). Please clarify which of the two are inactivated by the tssM deletion in this study and either provide compelling evidence that both are inactive or change the text throughout to indicate T6SS-1 or T6SS-2 being inactivated.

• We thank the reviewer for this comment. In our study, we refer to the work by Whitney, J., et al., 201420, from which we used the tssM (ECL_01536) gene deletion strain in which T6SS-1 of the E. cloacae ATCC 13047 is abrogated. Consistent with this detail, we have now clarified in the revised manuscript (Line 155, Supplementary Table 1) that T6SS-1 is inactivated. Moreover, the reference suggested by the reviewer provides additional evidence supporting that T6SS-1, but not T6SS-2, is involved in bacterial competition21, which we also now specify in the revised manuscript. It seems the authors used EHEC EDL933, which has T6SS, in co-culture experiments (Figure 1C). Why do the authors think the S. enterica LPS mutants don't have a competitive disadvantage against EHEC? It seems to run counter to the conclusion that LPS is broadly protective against T6SS.

• We thank the reviewer for raising this point. While it is true that EHEC O157:H7 strain EDL933 possesses a T6SS gene cluster in its genome, a prior study has shown that the T6SS in this strain appears to be inactivated under laboratory conditions, likely due to repression by the global regulator H-NS22. Consistent with these findings, our data indicate that the S. enterica LPS mutants did not exhibit a competitive disadvantage against EHEC EDL933. These results support the conclusion that, under the conditions tested, the truncated LPS in S. enterica does not affect its fitness against EHEC (Figure 1c), likely due to the inactivity of the EHEC T6SS22. It's not clear if the only Felix O1 and P22 phage-resistant transposon hits were in LPS-related genes, or if that pattern was observed in a more complete transposon sequencing dataset and selected for further study. A complete list of the sequence-identified hits, including the non-LPS related variants, would help clarify this and provide a useful resource to the research community.

• We thank the reviewer for the opportunity to clarify this point. For each phage, we initially isolated nine phage-resistant transposon variants, which were subsequently used for co-culture assays and transposon insertion site identification, as described in the original manuscript (Figure 1a __and Supplementary Figure 2a__). We agree with the reviewer that a broader screening approach could reveal non-LPS-related variants and provide a more comprehensive resource for the research community. To address this point, during the manuscript revision period, we followed the same procedure and isolated an additional nine phage-resistant variants for each phage (Supplementary Table 1). Interestingly, from this expanded isolation dataset, the transposon insertions were again found exclusively in LPS-related genes (Author Response Figure 1). We have now included this new dataset in the revised manuscript and believe it strengthens the robustness of our findings. This expanded data has been made available below for further reference. The fact that 8 of the 9 Felix O1 resistant variants all have transposon insertions in waaO should be stated in the results. The initial impression of showing R1-R9 is that 9 disrupted genes are being tested - in this case it's really only two. This is a minor critique because clean deletions by allelic exchange are shown for a more extensive set of genes anyway.

• We thank the reviewer for this comment. As suggested, we have revised the Results section (Lines 126-131) to explicitly state that Felix O1-resistant variants harbor transposon insertions in only two genes (waaO and dagR), which were initially tested in the competition assay (Figure 2). The S. enterica serovar Typhimurium transposon mutagenesis library could benefit from clarification on details. The results section suggests use of a pre-existing "established" transposon library, but the methods and Figure 1 seem to indicate a new library was created based on prior methods. In either case, what is the genome coverage and redundancy of the library? If this is not known or saturation is not reached, the implications of potentially missing phage resistance genes with this approach should be discussed.

• We thank the reviewer for the opportunity to clarify this point. For our study, we created a transposon library following previously established methods23. The library comprises approximately 12,000 variants, as noted in Figure 1a. While doing so provided substantial genome coverage, it did not achieve full saturation. We have now revised the Results section (Lines 93-94, and 115-117) to better describe the potential limitations of this approach, including by stating the possibility that some phage-resistance genes may have been missed during the screening. There is some variation in phenotype among the strains with transposon insertion into the same gene, such as P22 resistant strain R7 which macroscopically agglutinates while the other waaJ insertions R5 and R1 don't. Is this due to polar effects on waaO, or could it be genetic alterations at other sites driven by stringent phage selection?

• We thank the reviewer for this comment. We also suspect that the variation in the macroscopically agglutinative phenotypes among P22-resistant strains, such as strain R7 compared to R5 and R1, may be caused by polar effects on waaO. Additionally, the possibility of genetic alterations at other loci driven by stringent phage selection cannot be excluded. To address this potential variability and ensure consistency, we used clean deletions of each LPS biogenesis gene in all subsequent experiments. This approach eliminates the confounding effects of polar mutations or secondary genetic alterations, thereby providing more robust and interpretable data. Figure S1- The graphs with 12 growth curves are difficult to decipher, and the error bars would suggest maybe there are subtle growth differences among the mutants. Quantifying curve parameter(s) and applying a statistical test may clarify. The CFU counts in panel D seem to be not in log scale. Likewise in Figure S3 panel A, the authors say there are no significant growth defects, but the growth curves are modestly right-shifted for several mutants. This is a point of precision rather than a major critique, because the reversal of competitive growth phenotypes by donor T6SS inactivation indicate the potential minor growth defects aren't playing a major role in competition.

• We thank the reviewer for these suggestions and corrections. We have now revised the manuscript accordingly, including in Supplementary Figures 1 and 3. Quantitative analysis of growth curve parameters and statistical tests have been included below to clarify the observed differences (Author Response Figure 2). The slight right-shift of the growth curves for some mutants, as noted in Supplementary Figure 3, may be attributable to cell aggregation, as shown in Supplementary Figures 2e, f. The growth rate measurements were conducted in a 96-well plate with steady shaking at 200 rpm using a plate reader, which does not fully account for the aggregated cell phenotype. Despite these subtle growth differences, we agree with the reviewer that they do not appear to play a major role in the competitive growth phenotypes, as evidenced by the reversal of phenotypes upon donor T6SS inactivation (Supplementary Figure 3). Figure 3f - The authors say fepE is responsible for very long O-antigen chains, but it is not clear that the delta fepE LPS PAGE differs from wild type, which would fit with the lack of competitive disadvantage against E. cloacae in Figure 3g. The increased VL-modal O-antigen upon fepE overexpression in Figure 3h and increase protection in competition (figure 3i) are convincing. Is there another pathway(s) compensating for fepE deletion?

• We thank the reviewer for this thoughtful comment. We have repeated the experiment independently at least three times and consistently observed a reduction in the VL-modal O-antigen in the ∆fepE strain. To provide additional clarity, we have included supplementary LPS profiles and quantifications below (Author Response Figure 3). We currently do not have evidence from the literature or our experiments to identify an alternative pathway compensating for the deletion of fepE. Nonetheless, we acknowledge this as a possibility and appreciate the reviewer's insight into this topic. Lines 199-200 - I believe the conclusion from wzzB deletion would be that L-modal O-antigen is necessary for protection against T6SS, and not necessarily sufficient.

• We thank the reviewer for pointing out this important distinction. The respective sentence has now been revised in the manuscript (Line 204). Do the environmentally isolated phages As2 and As4 encode TSP homologs?

• We thank the reviewer for this question. We did not identify TSP homologs in the genome of As2 and As4 phages. The genome sequences of As1 to As4 have been uploaded to NCBI's BioProject resource under accession number PRJNA1199570 (Lines 535-544, 741-743). Reviewer #____3____ (Significance)

This manuscript provides a substantial advance in the field's understanding of how phages affect bacterial community interactions. To my knowledge, it is the first to bring together phage and T6SS defense with a strong mechanistic link. It's a conceptual advance in this regard that will stimulate more thought and experimentation on the roles of phage in bacterial communities like gut and environmental microbiomes. The manuscript's strengths include rigorous overall design, clarity of the communication, and depth of mechanistic investigation, all the way down to atomic force microscopy measurements. There are some minor revisions suggested, but these are addressable with minimal/no additional experiments.

As someone with expertise in bacterial secretion systems and interbacterial interactions, I think this work will be of interest to microbiologists generally, and specifically in the fields of phage biology, bacterial secretion systems, and microbiome research. While the phage virology components are straightforward and well described, I think a review from someone with more expertise in this specific area would be beneficial.

• We thank the reviewer for their careful reading of our manuscript and for the suggestions to improve it. References

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• Schwarz, S., West, T.E., Boyer, F., Chiang, W.C., Carl, M.A., Hood, R.D., Rohmer, L., Tolker-Nielsen, T., Skerrett, S.J., and Mougous, J.D. (2010). Burkholderia type VI secretion systems have distinct roles in eukaryotic and bacterial cell interactions. PLoS Pathog 6, e1001068. 10.1371/journal.ppat.1001068.
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• Toska, J., Ho, B.T., and Mekalanos, J.J. (2018). Exopolysaccharide protects Vibrio cholerae from exogenous attacks by the type 6 secretion system. Proc Natl Acad Sci U S A 115, 7997-8002. 10.1073/pnas.1808469115.
• Steeghs, L., den Hartog, R., den Boer, A., Zomer, B., Roholl, P., and van der Ley, P. (1998). Meningitis bacterium is viable without endotoxin. Nature 392, 449-450. 10.1038/33046.
• Steeghs, L., de Cock, H., Evers, E., Zomer, B., Tommassen, J., and van der Ley, P. (2001). Outer membrane composition of a lipopolysaccharide-deficient Neisseria meningitidis mutant. EMBO J 20, 6937-6945. 10.1093/emboj/20.24.6937.
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• Yu, J., Zhang, H., Ju, Z., Huang, J., Lin, C., Wu, J., Wu, Y., Sun, S., Wang, H., Hao, G., and Zhang, A. (2024). Increased mutations in lipopolysaccharide biosynthetic genes cause time-dependent development of phage resistance in Salmonella. Antimicrob Agents Chemother 68, e0059423. 10.1128/aac.00594-23.
• Burmeister, A.R., Fortier, A., Roush, C., Lessing, A.J., Bender, R.G., Barahman, R., Grant, R., Chan, B.K., and Turner, P.E. (2020). Pleiotropy complicates a trade-off between phage resistance and antibiotic resistance. Proc Natl Acad Sci U S A 117, 11207-11216. 10.1073/pnas.1919888117.
• Carretero-Ledesma, M., Garcia-Quintanilla, M., Martin-Pena, R., Pulido, M.R., Pachon, J., and McConnell, M.J. (2018). Phenotypic changes associated with Colistin resistance due to Lipopolysaccharide loss in Acinetobacter baumannii. Virulence 9, 930-942. 10.1080/21505594.2018.1460187.
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Referee #3

Evidence, reproducibility and clarity

Summary:

Tsai et al. describe LPS biosynthesis mutants arising in selection for phage resistance that increase susceptibility to T6SS-mediated interbacterial antagonism. Phage-derived LPS degrading enzymes also contribute to T6SS susceptibility, which may be due to weakening of the physical barrier of LPS. The mechanisms of this fitness trade-off are elucidated with well-executed and presented experiments.

Major comments:

• No major critiques.

Minor comments:

• Others have described two T6SS in Enterobacter cloacae ATCC 13047 (PMID 33072020). Please clarify which of the two are inactivated by the tssM deletion in this study and either provide compelling evidence that both are inactive or change the text throughout to indicate T6SS-1 or T6SS-2 being inactivated.
• It seems the authors used EHEC EDL933, which has T6SS, in co-culture experiments (Figure 1C). Why do the authors think the S. enterica LPS mutants don't have a competitive disadvantage against EHEC? It seems to run counter to the conclusion that LPS is broadly protective against T6SS.
• It's not clear if the only Felix O1 and P22 phage-resistant transposon hits were in LPS-related genes, or if that pattern was observed in a more complete transposon sequencing dataset and selected for further study. A complete list of the sequence-identified hits, including the non-LPS related variants, would help clarify this and provide a useful resource to the research community.
• The fact that 8 of the 9 Felix O1 resistant variants all have transposon insertions in waaO should be stated in the results. The initial impression of showing R1-R9 is that 9 disrupted genes are being tested - in this case it's really only two. This is a minor critique because clean deletions by allelic exchange are shown for a more extensive set of genes anyway.
• The S. enterica serovar Typhimurium transposon mutagenesis library could benefit from clarification on details. The results section suggests use of a pre-existing "established" transposon library, but the methods and Figure 1 seem to indicate a new library was created based on prior methods. In either case, what is the genome coverage and redundancy of the library? If this is not known or saturation is not reached, the implications of potentially missing phage resistance genes with this approach should be discussed.
• There is some variation in phenotype among the strains with transposon insertion into the same gene, such as P22 resistant strain R7 which macroscopically agglutinates while the other waaJ insertions R5 and R1 don't. Is this due to polar effects on waaO, or could it be genetic alterations at other sites driven by stringent phage selection?
• Figure S1- The graphs with 12 growth curves are difficult to decipher, and the error bars would suggest maybe there are subtle growth differences among the mutants. Quantifying curve parameter(s) and applying a statistical test may clarify. The CFU counts in panel D seem to be not in log scale. Likewise in Figure S3 panel A, the authors say there are no significant growth defects, but the growth curves are modestly right-shifted for several mutants. This is a point of precision rather than a major critique, because the reversal of competitive growth phenotypes by donor T6SS inactivation indicate the potential minor growth defects aren't playing a major role in competition.
• Figure 3f - The authors say fepE is responsible for very long O-antigen chains, but it is not clear that the delta fepE LPS PAGE differs from wild type, which would fit with the lack of competitive disadvantage against E. cloacae in Figure 3g. The increased VL-modal O-antigen upon fepE overexpression in Figure 3h and increase protection in competition (figure 3i) are convincing. Is there another pathway(s) compensating for fepE deletion?
• Lines 199-200 - I believe the conclusion from wzzB deletion would be that L-modal O-antigen is necessary for protection against T6SS, and not necessarily sufficient.
• Do the environmentally isolated phages As2 and As4 encode TSP homologs?

Significance

This manuscript provides a substantial advance in the field's understanding of how phages affect bacterial community interactions. To my knowledge, it is the first to bring together phage and T6SS defense with a strong mechanistic link. It's a conceptual advance in this regard that will stimulate more thought and experimentation on the roles of phage in bacterial communities like gut and environmental microbiomes. The manuscript's strengths include rigorous overall design, clarity of the communication, and depth of mechanistic investigation, all the way down to atomic force microscopy measurements. There are some minor revisions suggested, but these are addressable with minimal/no additional experiments.

As someone with expertise in bacterial secretion systems and interbacterial interactions, I think this work will be of interest to microbiologists generally, and specifically in the fields of phage biology, bacterial secretion systems, and microbiome research. While the phage virology components are straightforward and well described, I think a review from someone with more expertise in this specific area would be beneficial.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #2

Evidence, reproducibility and clarity

This work investigates the fitness trade-offs in Salmonella enterica resistant to phages. The authors performed co-culture experiments with S. enterica, E. coli, and E. cloacae and found that phage-resistant S. enterica strains displayed reduced fitness in the presence of E. cloacae. Further experiments demonstrated that phage-resistant S. enterica strains were more susceptible to the type VI secretion system (T6SS) of E. cloacae. The authors then examined the role of the O-antigen of lipopolysaccharide (LPS) in T6SS-mediated interbacterial antagonism. By constructing S. enterica mutants with varying O-antigen chain lengths, the authors demonstrated that the O-antigen protects S. enterica from T6SS attack. They then demonstrated that the O-antigen-deficient S. enterica, E. coli, and C. rodentium strains were more susceptible to T6SS attack by E. cloacae. Finally, the authors showed that phage tail spike proteins (TSPs) with endoglycosidase activity could cleave the bacterial O-antigen, thereby increasing susceptibility to T6SS attack.

The study is well-designed and the experiments are well-executed. The findings are significant and have implications for the understanding of microbial community dynamics.

Major comments:

While the study elegantly demonstrates the link between phage resistance, LPS structure, and T6SS susceptibility, we must remember that these LPS-defective strains are likely at a significant disadvantage in real-world environments without the influence of competing bacteria. Whether it's the gut or external environments, Salmonella needs its LPS for protection against a myriad of host and environmental factors. It seems a bit redundant for T6SS mediated antagonism to select for LPS structures when those structures are essential for bacterial survival outside of this very specific context. It would benefit some discussion about the likelihood of these phage-resistant, LPS-defective strains actually persisting and competing effectively in a more natural setting.

Minor comments

Figure 5 could be more effective is panels b and C are together

69 Authors should define mucoid

155 Authors should explain that this result is expected since T6SS acts on solid surface while CDI works in liquid cultures

clarify what it is meant by unicellular cultures. Should it be monocultures?

618 add to the text how much dead phage was added per bacterial cell

364 references needed for "consistent with predictions for intact LPS structures "

Significance

This study offers a new perspective on the interplay between phage resistance and bacterial fitness in the context of microbial communities. While the concept of fitness trade-offs associated with antibiotic resistance is well-established, the authors extend this paradigm to phage resistance. They demonstrate that phage-resistant Salmonella enterica strains exhibit reduced fitness in the presence of Enterobacter cloacae due to increased susceptibility to the type VI secretion system (T6SS). This finding is significant as it highlights the potential for interbacterial antagonism to shape the evolution of phage resistance. The authors further show that the O-antigen of lipopolysaccharide (LPS) plays a crucial role in protecting S. enterica from T6SS attack. This observation provides mechanistic insights into the fitness trade-offs associated with phage resistance.

The study's strength lies in its elegant experimental design and the comprehensive analysis of the interplay between phage resistance, T6SS susceptibility, and O-antigen structure. The authors employ a combination of co-culture experiments, genetic manipulations, and structural analyses to dissect the underlying mechanisms. The findings are robust and have implications for understanding the evolution of bacterial communities in the presence of phages and competing bacterial species. This research will be of interest to a broad audience, including researchers in microbiology, synthetic biology, and microbial ecology. The findings have implications for understanding the evolution of phage resistance, and the dynamics of microbial communities. The study's insights into the role of the O-antigen in T6SS susceptibility could also inform the design of novel antimicrobial strategies.

My expertise is microbial physiology

Reviewer #1 (Public review):

Summary:

In this study, Tiang et al. explore the role of ubiquitination of non-structural protein 16 (nsp16) in the SARS-CoV-2 life cycle. nsp16, in conjunction with nsp10, performs the final step of viral mRNA capping through its 2'-O-methylase activity. This modification allows the virus to evade host immune responses and protects its mRNA from degradation. The authors demonstrate that nsp16 undergoes ubiquitination and subsequent degradation by the host E3 ubiquitin ligases UBR5 and MARCHF7 via the ubiquitin-proteasome system (UPS). Specifically, UBR5 and MARCHF7 mediate nsp16 degradation through K48- and K27-linked ubiquitination, respectively. Notably, degradation of nsp16 by either UBR5 or MARCHF7 operates independently, with both mechanisms effectively inhibiting SARS-CoV-2 replication in vitro and in vivo. Furthermore, UBR5 and MARCHF7 exhibit broad-spectrum antiviral activity by targeting nsp16 variants from various SARS-CoV-2 strains. This research advances our understanding of how nsp16 ubiquitination impacts viral replication and highlights potential targets for developing broadly effective antiviral therapies.

Strengths:

The proposed study is of significant interest to the virology community because it aims to elucidate the biological role of ubiquitination in coronavirus proteins and its impact on the viral life cycle. Understanding these mechanisms will address broadly applicable questions about coronavirus biology and enhance our overall knowledge of ubiquitination's diverse functions in cell biology. Employing in vivo studies is a strength.

Weaknesses:

While the conclusions are generally well-supported by the data, additional work is needed to confirm that NSP16 is ubiquitinated in a biologically relevant context and to better define the roles of the reported E3 ligases. Clarifications regarding aspects of data acquisition, data analysis, and text editing could notably strengthen the manuscript and its conclusions.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

Previous studies have shown that treatment with 17α-estradiol (a stereoisomer of the 17β-estradiol) extends lifespan in male mice but not in females. The current study by Li et al, aimed to identify cell-specific clusters and populations in the hypothalamus of aged male rats treated with 17α-estradiol (treated for 6 months). This study identifies genes and pathways affected by 17α-estradiol in the aged hypothalamus.

Strengths:

Using single-nucleus transcriptomic sequencing (snRNA-seq) on the hypothalamus from aged male rats treated with 17α-estradiol they show that 17α-estradiol significantly attenuated age-related increases in cellular metabolism, stress, and decreased synaptic activity in neurons.

Thanks.

Moreover, sc-analysis identified GnRH as one of the key mediators of 17α-estradiol's effects on energy homeostasis. Furthermore, they show that CRH neurons exhibited a senescent phenotype, suggesting a potential side effect of the 17α-estradiol. These conclusions are supported by supervised clustering by neuropeptides, hormones, and their receptors.

Thanks.

Weaknesses:

However, the study has several limitations that reduce the strength of the key claims in the manuscript. In particular:

(1) The study focused only on males and did not include comparisons with females. However, previous studies have shown that 17α-estradiol extends lifespan in a sex-specific manner in mice, affecting males but not females. Without the comparison with the female data, it's difficult to assess its relevance to the lifespan.

This study was originally designed based on previous findings indicating that lifespan extension is only effective in males, leading to the exclusion of females from the analysis. The primary focus of our research was on the transcriptional changes and serum endocrine alterations induced by 17α-estradiol in aged males compared to untreated aged males. We believe that even in the absence of female subjects, the significant effects of 17α-estradiol on metabolism in the hypothalamus, synapses, and endocrine system remain evident, particularly regarding the expression levels of GnRH and testosterone. Notably, lower overall metabolism, increased synaptic activity, and elevated levels of GnRH and testosterone are strong indicators of health and well-being in males, supporting the validity of our primary conclusions. However, including female controls would enhance the depth of our findings. If female controls were incorporated, we propose redesigning the sample groups to include aged male control, aged female control, aged female treated, aged male treated, as well as young male control, young male treated, young female control, and young female treated. We regret that we cannot provide this data in the short term. Nevertheless, we believe this presents a valuable avenue for future research on this topic. In this study, we emphasize the role of 17α-estradiol in overall metabolism, synaptic function, GnRH, and testosterone in aged males and underscore the importance of supervised clustering of neuropeptide-secreting neurons in the hypothalamus.

(2) It is not known whether 17α-estradiol leads to lifespan extension in male rats similar to male mice. Therefore, it is not possible to conclude that the observed effects in the hypothalamus, are linked to the lifespan extension.

Thanks for the reminding. 17α-estradiol was reported to extend lifespan in male rats similar to male mice (PMID: 33289482). We have added the valuable reference to introduction in the new version.  

(3) The effect of 17α-estradiol on non-neuronal cells such as microglia and astrocytes is not well-described (Figure 1). Previous studies demonstrated that 17α-estradiol reduces microgliosis and astrogliosis in the hypothalamus of aged male mice. Current data suggest that the proportion of oligo, and microglia were increased by the drug treatment, while the proportions of astrocytes were decreased. These data might suggest possible species differences, differences in the treatment regimen, or differences in drug efficiency. This has to be discussed.

We have reviewed reports describing changes in cell numbers following 17α-estradiol treatment in the brain, using the keywords "17α-estradiol," "17alpha-estradiol," and "microglia" or "astrocyte." Only a limited amount of data was obtained. We found one article indicating that 17α-estradiol treatment in Tg (AβPP(swe)/PS1(ΔE9)) model mice resulted in a decreased microglial cell number compared to the placebo (AβPP(swe)/PS1(ΔE9) mice), but this change was not significant when compared to the non-transgenic control (PMID: 21157032). The transgenic AβPP(swe)/PS1(ΔE9) mouse model may differ from our wild-type aging rat model in this context.

Moreover, the calculation of cell numbers was based on visual observation under a microscope across several brain tissue slices. This traditional method often yields controversial results. For example, oligodendrocytes in the corpus callosum, fornix, and spinal cord have been reported to be 20-40% more numerous in males than in females based on microscopic observations (PMID: 16452667). In contrast, another study found no significant difference in the number of oligodendrocytes between sexes when using immunohistochemistry staining (PMID: 18709647). Such discrepancies arising from traditional observational methods are inevitable.

We believe the data presented in this article are reliable because the cell number and cell ratio data were derived from high-throughput cell counting of the entire hypothalamus using single-cell suspension and droplet wrapping (10x Genomics).

(4) A more detailed analysis of glial cell types within the hypothalamus in response to drugs should be provided.

We provided more enrichment analysis data of differentially expressed genes between Y, O, and O.T in microglia and astrocytes in Figure 2—figure supplement 3. In this supplemental data, we found unlike that in neurons, Micro displayed lower levels of synapse-related cellular processes in O.T. compared to O.

(5) The conclusion that CRH neurons are going into senescence is not clearly supported by the data. A more detailed analysis of the hypothalamus such as histological examination to assess cellular senescence markers in CRH neurons, is needed to support this claim.

We also noticed the inappropriate claim and we have changed "senescent phenotype" to "stressed phenotype" and "abnormal phenotype" in abstract and in results.

Reviewer #2 (Public Review):

Summary:

Li et al. investigated the potential anti-ageing role of 17α-Estradiol on the hypothalamus of aged rats. To achieve this, they employed a very sophisticated method for single-cell genomic analysis that allowed them to analyze effects on various groups of neurons and non-neuronal cells. They were able to sub-categorize neurons according to their capacity to produce specific neurotransmitters, receptors, or hormones. They found that 17α-Estradiol treatment led to an improvement in several factors related to metabolism and synaptic transmission by bringing the expression levels of many of the genes of these pathways closer or to the same levels as those of young rats, reversing the ageing effect. Interestingly, among all neuronal groups, the proportion of Oxytocin-expressing neurons seems to be the one most significantly changing after treatment with 17α-Estradiol, suggesting an important role of these neurons in mediating its anti-ageing effects. This was also supported by an increase in circulating levels of oxytocin. It was also found that gene expression of corticotropin-releasing hormone neurons was significantly impacted by 17α-Estradiol even though it was not different between aged and young rats, suggesting that these neurons could be responsible for side effects related to this treatment. This article revealed some potential targets that should be further investigated in future studies regarding the role of 17α-Estradiol treatment in aged males.

Strengths:

(1) Single-nucleus mRNA sequencing is a very powerful method for gene expression analysis and clustering. The supervised clustering of neurons was very helpful in revealing otherwise invisible differences between neuronal groups and helped identify specific neuronal populations as targets.

Thanks.

(2) There is a variety of functions used that allow the differential analysis of a very complex type of data. This led to a better comparison between the different groups on many levels.

Thanks.

(3) There were some physiological parameters measured such as circulating hormone levels that helped the interpretation of the effects of the changes in hypothalamic gene expression.

Thanks.

Weaknesses

(1) One main control group is missing from the study, the young males treated with 17α-Estradiol.

Given that the treatment period lasts six months, which extends beyond the young male rats' age range, we aimed to investigate the perturbation of 17α-Estradiol on the normal aging process. Including data from young males could potentially obscure the treatment's effects in aged males due to age effects, though similar effects between young and aged animals may exist. Long-term treatment of hormone may exert more developmental effects on the young than the old. Consequently, we decided to exclude this group from our initial sample design. We apologize for this omission.

(2) Even though the technical approach is a sophisticated one, analyzing the whole rat hypothalamus instead of specific nuclei or subregions makes the study weaker.

The precise targets of 17α-Estradiol within the hypothalamus remain unresolved. Selecting a specific nucleus for study is challenging. The supervised clustering method described in this manuscript allows us to identify the more sensitive neuron subtypes influenced by 17α-Estradiol and aging across the entire hypothalamus, without the need to isolate specific nuclei in a disturbed hypothalamic environment.

(3) Although the authors claim to have several findings, the data fail to support these claims. You may mean the claim as the senescent phenotype in Crh neuron induced by 17a-estradiol.

Thanks. We have changed the "senescent phenotype" to "stressed phenotype"  or "abnormal phenotype" in the abstract and results to avoid such claim.

(4) The study is about improving ageing but no physiological data from the study demonstrated such a claim with the exception of the testes histology which was not properly analyzed and was not even significantly different between the groups.

The primary objective of this study is to elucidate the effects of 17α-Estradiol on the endocrine system in the aging hypothalamus; exploring anti-aging effects is not the main focus. From the characteristics of the aging hypothalamus, we know that down-regulated GnRH and testosterone levels, along with elevated mTOR signaling, are indicators of aging in these organs (PMID: 37886966, PMID: 37048056, PMID: 22884327). The contrasting signaling networks related to metabolism and synaptic processes significantly differentiate young and aging hypothalami, and 17α-Estradiol helps rebalance these networks, suggesting its potential anti-aging effects.

(5) Overall, the study remains descriptive with no physiological data to demonstrate that any of the effects on hypothalamic gene expression are related to metabolic, synaptic, or other functions.

The study focuses on investigating cellular responses and endocrine changes in the aging hypothalamus induced by 17α-estradiol, utilizing single-nucleus RNA sequencing (snRNA-seq) and a novel data mining methodology to analyze various neuron subtypes. It is important to note that this study does not mainly aim to explore the anti-aging effects. Consequently, we have revised the claim in the abstract from “the effects of 17α-estradiol in anti-aging in neurons” to “the effects of 17α-estradiol on aging neurons.” We observed that the lower overall metabolism and increased expression levels of cellular processes in the synapses align with findings previously reported regarding 17α-estradiol. To address the lack of physiological data and the challenges in measuring multiple endocrine factors due to their volatile nature, we employed several bidirectional Mendelian analyses of various genome-wide association study (GWAS) data related to these serum endocrine factors to identify their mutual causal effects.

Reviewing Editor Comment:

Based on the Public Reviews and Recommendations for Authors, the Reviewers strongly recommend that revisions include an experimental demonstration of the physiological effects of the treatment on ageing in rats as well as the CRH-senescence link. Additional analysis of the glia would greatly strengthen the study, as would inclusion of females and young male controls. The important point was also raised that the work linking 17a-estradiol was performed in mice, and the link with lifespan in rats is not known. Discussion of this point is recommended.

We acknowledge that 17α-estradiol has been reported to extend lifespan in male rats, similar to findings in male mice (PMID: 33289482), and we have noted this in the Introduction. We apologize for not conducting further experiments to validate this point.

Additionally, we have revised the description of the phenotype of senescent CRH neurons to “stressed phenotype” without carrying out further experiments to confirm the senescent phenotype. To provide more clarity on the performance of glial cells during treatment, we have included additional enrichment analysis data of differentially expressed genes among young (Y), old (O), and old treated (O.T) microglia and astrocytes in Figure 2—figure supplement 3. Notably, the behavior of microglia contrasts with that of total neurons concerning synapse-related cellular processes. We apologize for being unable to include female and young controls in this study.

Reviewer #2 (Recommendations For The Authors)

General comments:

(1) The manuscript is very hard to read. Proofreading and editing by software or a professional seems necessary. The words "enhanced", "extensive" etc. are not always used in the right way.

Thanks for the suggestion. We have revised the proofreading and editing. The words "enhanced" and "extensive" were also revised in most sentences.

(2) The numbers of animals and samples are not well explained. Is it 9 rats overall or per group? If there are 8 testes samples per group, should we assume that there were 4 rats per group? The pooling of the hypothalamic how was it done? Were all the hypothalamic from each group pooled together? A small table with the animals per group and the samples would help.

We appreciate your reminder regarding the initial mistake in our manuscript preparation. In the preliminary submission, we reported 9 rats based solely on sequencing data and data mining. The revised version (v1) now includes additional experimental data, with an effective total of 12 animals (4 per group). Unfortunately, we overlooked updating this information in the v1 submission. We have since added detailed information in the Materials and Methods sections: Animals, Treatment and Tissues, and snRNA-seq Data Processing, Batch Effect Correction, and Cell Subset Annotation.

(3) The Clustering is wrong. There are genes in there that do not fall into any of the 3 categories: Neurotransmitters, Receptors, Hormones.

We have changed the description to “Vast majority of these subtypes were clustered by neuropeptides, hormones, and their receptors within all the neurons”.

(4) The coloring of groups in the graphs is inconsistent. It must be more homogeneous to make it easier to identify.

We have changed the colors of groups in Fig. 1D to make the color of cell clusters consistent in Fig. 1A-D.

(5) The groups c1-c4 are not well explained. How did the authors come up with these?

We have added more descriptions of c1-c4 in materials and methods in the new version.

(6) In most cases it's not clear if the authors are talking about cell numbers that express a certain mRNA, the level of expression of a certain mRNA, or both. They need to do a better job using more precise descriptions instead of using general terms such as "signatures", "expression profiles", "affected neurons" etc. It is very hard to understand if the number of neurons is compared between the groups or the gene expression.

We have changed the "signatures" to "gene signatures" to make it more accurate in meaning. The "affected neurons" were also changed to "sensitive neurons". But sorry that we were not able to find better alternatives to the "expression profiles".

(7) Sometimes there are claims made without justification or a reference. For example, the claim about the senescence of CRH neurons due to the upregulation of mitochondrial genes and downregulation of adherence junction genes (lines 326-328) should be supported by a reference or own findings.

The "senescence" here is not appropriate. We have changed it to "stressed phenotype" or "aberrant changes" in abstract and results.

(8) Young males treated with Estradiol as a control group is necessary and it is missing.

Your suggestion is appreciated; however, the treatment duration for aged mice (O.T) was set at 6 months, while the young mice were only 4 months old. This disparity makes it challenging to align treatment timelines for the young animals. The primary aim of this study is to investigate the perturbation of 17α-estradiol on the aging process, and any distinct effects due to age effect observed in young males might complicate our understanding of its role in aged males, though similar endocrine effects may exist in the young animals. Long-term treatment of hormone may exert more developmental effects on the young than the old. Therefore, we made the decision to exclude the young samples in our initial study design. We apologize for any confusion this may have caused.

Specific Comments:

Line 28: "elevated stresses and decreased synaptic activity": Please make this clearer. Can't claim changes in synaptic activity by gene expression.

We have changed it to "the expression level of pathways involved in synapse".

Line 32: "increased Oxytocin": serum Oxytocin.

We have added the “serum”.

Line 52 - 54: Any studies from rats?

Thanks. In rats there is also reported that 17α-estradiol has similar metabolic roles as that in mice (PMID: 33289482) and we have added it to the refences. It’s very useful for this manuscript.

Line 62 - 65: It wasn't investigated thoroughly in this paper so why was it suggested in the introduction?

We have deleted this sentence as being suggested.

Line 70: "synaptic activity" Same as line 28.

We have changed it to "pathways involved in synaptic activity".

Line 79: Why were aged rats caged alone and young by two? Could that introduce hypothalamic gene expression effects?

The young males were bred together in peace. But the aged males will fight and should be kept alone.

Lines 78, 99, 109-110: It is not clear how many animals per group were used and how many samples per group were used separately and/or grouped. Please be more specific.

We have added these information to Materials and methods/Animals, treatment and tissues and Materials and methods/snRNA-seq data processing, batch effect correction, and cell subset annotation.

Line 205: "in O" please add "versus young.".

We have changed accordingly.

Line 207: replace "were" with "was" .

We have alternatively changed the "proportion" to "proportions".

Line 208: replace "that" with "compared to" and after "in O.T." add "compared to?"

We have changed accordingly.

Line 223: "O.T." compared to what? Figure?

We have changed it accordingly.

Line 227: Figure?

We have added (Figure 1E) accordingly.

Line 229: "synaptic activity" Same as line 28.

We have revised it.

Line 235: "synaptic activity" and "neuropeptide secretion" Same as line 28.

We have revised it.

Line 256:" interfered" please revise.

We changed to "exerted".

Line 263: "on the contrary" please revise.

We have changed "on the contrary" to "opposite".

Line 270: "conversed" did you mean "conserved"?

We have changed "conversed" to "inversed".

Line 296-298: Please explain. Why would these be side effects?

It’s hard to explain, therefore, we deleted the words "side effects".

Line 308: "synaptic activity" Same as line 28.

We have changed it to "expression levels of synapse-related cellular processes".

Line 314: "and sex hormone secretion and signaling"Isn't this expected?

Yes, it is expected. We have added it to the sentence "and, as expected, sex hormone secretion and signaling".

Line 325-328: Why is this senescence? Reference?

We have added “potent” to it.

Line 360-361: This doesn't show elevated synaptic activity.

"elevated synaptic activity" was changed to "The elevated expression of synapse-related pathways"

Line 363-364: "Unfortunately" is not a scientific expression and show bias.

We have changed it to "Notably".

Line 376: Similar as above.

Yes, we have change it to "in contrast".

Lines 382-385: This is speculation. Please move to discussion.

Sorry for that. We think the causal effects derived from MR result is evidence. As such, we have not changed it.

Line 389: Please revise "hormone expressing".

We have changed it accordingly.

Line 401: Isn't this effect expected due to feedback inhibition of the biochemical pathway? Please comment.

The binding capability of 17alpha-estradiol to estrogen receptors and its role in transcriptional activation remain core questions surrounded by controversy. Earlier studies suggest that 17alpha-estradiol exhibits at least 200 times less activity than 17beta-estradiol (PMID: 2249627, PMID: 16024755). However, recent data indicate that 17alpha-estradiol shows comparable genomic binding and transcriptional activation through estrogen receptor α (Esr1) to that of 17beta-estradiol (PMID: 33289482). Additionally, there is evidence that 17alpha-estradiol has anti-estrogenic effects in rats (PMID: 16042770). These findings imply possible feedback inhibition via estrogen receptors. Furthermore, 17alpha-estradiol likely differs from 17beta-estradiol due to its unique metabolic consequences and its potential to slow aging in males, an effect not attributed to 17beta-estradiol. For instance, neurons are also targets of 17alpha-estradiol, with Esr1 not being the sole target (PMID: 38776045). Nevertheless, the precise effective targets of 17alpha-estradiol are still unresolved.

Line 409: This conclusion cannot be made because the effect is not statistically significant. Can say "trend" etc.

Thanks for the recommendation. We have added "potential" in front of the conclusion.

Line 426: "suggesting" please revise.

sorry, it’s a verb.

Lines 426-428: This is speculation. Please move to discussion.

The elevated GnRH levels in O.T., observed through EIA analysis, suggest a deduction regarding the direct causal effects of 17alpha-estradiol on various endocrine factors related to feeding, energy homeostasis, reproduction, osmotic regulation, stress response, and neuronal plasticity through MR analysis. Thus, we have not amended our position. We apologize for any confusion.

Lines 431-432: improved compared to what?

The statement have been revised as " The most striking role of 17α-estradiol treatment revealed in this study showed that HPG axis was substantially improved in the levels of serum Gnrh and testosterone".

Line 435: " Estrogen Receptor Antagonists". Please revise.

Thanks for the recommendation. We have changed it to "estrogen receptor antagonists".

Line 438" "Secrete". Please revise.

Sorry, it is "secret".

Lines 439-449: None of this has been demonstrated. Please remove these conclusions.

These are not conclusions but rather intriguing topics for discussion. Given the role of 17alpha-estradiol in promoting testosterone and reducing estradiol levels in males, we believe it is worthwhile to explore the potential application of 17alpha-estradiol in increasing testosterone levels in aged males, particularly those with hypogonadism.

Lines 450-457: No females were included in this study. Why? Also, why is this discussed? It is relevant but doesn't belong in this manuscript since it was not studied here.

Testosterone levels are crucial for male health, while estradiol levels are essential for the health and fertility of females. Previous studies have demonstrated that 17α-estradiol does not contribute to lifespan extension in females. Given the effects of 17α-estradiol on males—specifically, its role in promoting testosterone and reducing estradiol levels—we believe it is important to discuss the potential sex-biased effects of 17α-estradiol, as this could inform future investigations. Therefore, we have chosen not to make changes to this section.

Lines 458-459: This was not demonstrated in this article. Please remove.

We have restricted the claim to "expression level of energy metabolism in hypothalamic neurons".

Line 464: "Promoted lifespan extension" Not demonstrated. Please remove.

At the end of the sentence it was revised as "which may be a contributing factor in promoting lifespan extension".

Line 466: "Showed" No.

The whole sentence was deleted in the new version.

Line 483: "the sex-based effects". Not studied here.

Since the changes in testosterone levels are significant in this dataset and this hormone has a sex-biased nature, we find it worthwhile to suggest this as a topic for future investigation. We have added "which needs further verification in the future" at the end of this sentence.

I found this quote to be very interesting considering that it is written in the perspective of a colored woman. Iin the past, interracial relationships between white and balck people were frowned upon. As someone who comes from interracial parents, it is so heartbreaking to see a comment like this in writing. By no means am I hurt by what Langston wrote. Moreso, I am hurt by the historical context of this comment. Not only were interracial relationships frowned upon by white people, but black people were also often cautious of them because of the social issues and turmoil they could bring about.