Reviewer #2 (Public review):

Summary:

Mohanty et al. present a new deep learning method to identify intracellular allosteric modulators of GPCRs. This is an interesting field for e.g. the design of novel small molecule inhibitors of GPCR signalling. A key limitation, as mentioned by the authors, is the limited availability of data. The method presented, Gcoupler, aims to overcome these limitations, as shown by experimental validation of sterols in the inhibition of Ste2p, which has been shown to be relevant molecules in human and rat cardiac hypertrophy models.<br /> They have made their code available for download and installation, which can easily be followed to set up software on a local machine.

Strengths:

- Clear GitHub repository

- Extensive data on yeast systems

Weaknesses:

- No assay to directly determine the affinity of the compounds to the protein of interest.

In conclusion, the authors present an interesting new method to identify allosteric inhibitors of GPCRs, which can easily be employed by research labs. Whilst their efforts to characterize the compounds in yeast cells, in order to confirm their findings, it would be beneficial if the authors show their compounds are active in a simple binding assay.

iterator 방식을 사용하는 것이 bound checking을 피하기 때문에 효율적이다.

풍부한 collection들이 코드들을 이상적이고, 명확적으로 보이도록 만들어준다.

Could be an interesting problem to solve?

For example, the syntactic analysis stage builds a conventional expression tree, but this tree is expressed as objects—instances of various classes relevant to compilation: Class, Method, Message, Selector, Argument, etc. […] The code for these operations is encapsulated inside each object, and is not spread throughout the system so changes are easily made. And all these specialized classes rely heavily on reusable code inherited from more primitive classes like Object, HashTable, Symbol, Token, and LinkedList.

This is an interesting claim, given that one of the common criticisms of the classic, inheritance-heavy style of classic OOP is precisely that it leads to code that is indeed "spread throughout". Adele Goldberg commenting on the legacy of Smalltalk made a well-known quip, "In Smalltalk, everything happens somewhere else."

It's notable that although there many common word sequences between this paper and the later, similarly titled one that appeared in IEEE Software (1984), this passage doesn't appear to be present (based on a quick skim—I could be missing something), and the closest corresponding statements are significantly reworded.

This is a good example

Author response:

The following is the authors’ response to the original reviews

eLife Assessment

This valuable study investigates prey capture by archer fish, showing that even though the visuomotor behavior unfolds very rapidly (within 40-70 ms), it is not hardwired; it can adapt to different simulated physics and different prey shapes. Although there was agreement that the model system, experimental design, and main hypothesis are certainly interesting, opinions were divided on whether the evidence supporting the central claims is incomplete. A more rigorous definition and assessment of "reflex speed", more detailed evidence of stimulus control, and a more detailed analysis of individual subjects could potentially increase confidence in the main conclusions.

Thank you very much. There are several points that we had to absolutely make sure that they are very well understood. (1) Explaining in the best possible way the experiment with a fly sliding on top of a glass plate. Here, the virtual ballistic landing point can be calculated using simple high school physics. It turns out that this is where the fish turn to – even though the fly is not falling at all. Once this is understood it becomes clear that we can precisely measure latency and accuracy of the C-start turns. In the new version we explain this essential aspect in more detail and add an extra Figure (new Figure 2). This may, perhaps, help readers to notice this important background (previously covered in Fig. 1C). (2) The full experimental evidence that the VR method works is presented in more detail and all measurements necessary will be clear after the new Figure 2. They will however not be clear if this Figure is ignored. (3) We have rewritten the manuscript to make it easier to understand what we wanted to show, why we needed VR to proceed and why the archerfish highspeed decision lent itself so readily to tackle the problem. (4) We emphasize the importance of speed-accuracy tradeoffs in standard decision-making and also include data on the absence of such a relation in the archerfish highspeed decisions.

So, in summary, we have emphasized what we wanted to show and what we did not want to show, we have rewritten the text to make it easier for future readers and we have tried to add more guidance to the figures. We do hope very much that the beauty of the quite unexpected findings is more easily visible to those who take the trouble of actually reading the paper.  

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors test whether the archerfish can modulate the fast response to a falling target. By manipulating the trajectory of the target, they claim that the fish can modulate the fast response. While it is clear from the result that the fish can modulate the fast response, the experimental support for the argument that the fish can do it for a reflex-like behavior is inadequate.

Please note that we have not simply tested whether archerfish can 'modulate the fast response'. We quantitatively test specific hypotheses on the rules used by the fish. For this the accuracy of the decisions is analyzed with respect to specific points that can be calculated precisely in each of the experiments. These points are shown on the figures and in the movies that were meant to illustrate this important aspect. We had to make sure that the way we calculate the predicted point(s) is made as clear as possible in the text. We added more text and separated the fundamentally important aspects in a separate Figure 2 to make it more difficult to overlook the fundamental aspects that lay the foundation for everything that follows.

Strengths:

Overall, the question that the authors raised in the manuscript is interesting.

Thank you and we do hope very much that, with our revision, you will see the beauty of the findings.

Weaknesses:

(1) The argument that the fish can modulate reflex-like behavior relies on the claim that the archerfish makes the decision in 40 ms. There is little support for the 40 ms reaction time. The reaction time for the same behavior in Schlegel 2008, is 6070 ms, and in Tsvilling 2012 about 75 ms, if we take the half height of the maximum as the estimated reaction time in both cases. If we take the peak (or average) of the distribution as an estimation of reaction time, the reaction time is even longer. This number is critical for the analysis the authors perform since if the reaction time is longer, maybe this is not a reflex as claimed. In addition, mentioning the 40 ms in the abstract is overselling the result. The title is also not supported by the results.

Although the minimum latency is indeed 40 ms (it can be slightly less: e.g., see the evidence in the paper, for instance the plots in the new Fig. 4) the paper's statements are not dependent on a specific number. Even if minimum latency was 100 ms (which it is not) the speed of the response and the absence of a speedaccuracy relation (now shown directly in Fig. 4) is what is of importance. To show this we have completely rewritten large parts of the manuscript.

(2) A critical technical issue of the stimulus delivery is not clear. The frame rate is 120 FPS and the target horizontal speed can be up to 1.775 m/s. This produces a target jumping on the screen 15 mm in each frame. This is not a continuous motion. Thus, the similarity between the natural system where the target experiences ballistic trajectory and the experiment here is not clear. Ideally, another type of stimulus delivery system is needed for a project of this kind that requires fast-moving targets (e.g. Reiser, J. Neurosci.Meth. 2008). In addition, the screen is rectangular and not circular, so in some directions, the target vanishes earlier than others. It must produce a bias in the fish response but there is no analysis of this type.

Please note that the new Fig. 3 (former Fig. 2) reports all the evidence that is needed to just show this and in a way that could in no way have been better. We have rewritten the text to explain what needs to be shown experimentally in order to be able to proceed, what critical tests were done and what results were obtained. We also add a short comment on another unsuccessful attempt that we have tried before.

(3) The results here rely on the ability to measure the error of response in the case of a virtual experiment. It is not clear how this is done since the virtual target does not fall. How do the authors validate that the fish indeed perceives the virtual target as the falling target? Since the deflection is at a later stage of the virtual trajectory, it is not clear what is the actual physics that governs the world of the experiment. Overall, the experimental setup is not well designed.

Understanding this aspect is essential. If the glass plate experiment is not thoroughly understood (new Fig. 2 with new text to emphasize that this is absolutely essential) nothing that follows makes any sense, including what is meant by the statement that the decision could be hardwired to ballistic motion.

Reviewer #2 (Public review):

Summary:

This manuscript studies prey capture by archer fish, which observe the initial values of motion of aerial prey they made fall by spitting on them, and then rapidly turn to reach the ballistic landing point on the water surface. The question raised by the article is whether this incredibly fast decision-making process is hardwired and thus unmodifiable or can be adjusted by experience to follow a new rule, namely that the landing point is deflected from a certain amount of the expected ballistic landing point. The results show that the fish learn the new rule and use it afterward in a variety of novel situations that include height, side, and speed of the prey, and which preserve the speed of the fish's decision. Moreover, a remarkable finding presented in this work is the fact that fish that have learned to use the new rule can relearn to use the ballistic landing point for an object based on its shape (a triangle) while keeping simultaneously the 'deflected rule' for an object differing in shape (a disc); in other words, fish can master simultaneously two decisionmaking rules based on the different shape of objects.

Strengths:

The manuscript relies on a sophisticated and clever experimental design that allows changing the apparent landing point of a virtual prey using a virtual reality system. Several robust controls are provided to demonstrate the reliability and usefulness of the experimental setup.

Overall, I very much like the idea conveyed by the authors that even stimuli triggering apparently hardwired responses can be relearned in order to be associated with a different response, thus showing the impressive flexibility of circuits that are sometimes considered mediating pure reflexive responses.

Thank you so much for this precise assessment of what we have shown!

This is the case - as an additional example - of the main component of the Nasanov pheromone of bees (geraniol), which triggers immediate reflexive attraction and appetitive responses, and which can, nevertheless, be learned by bees in association with an electric shock so that bees end up exhibiting avoidance and the aversive response of sting extension to this odorant (1), which is a fully unnatural situation, and which shows that associative aversive learning is strong enough to override preprogrammed responding, thus reflecting an impressive behavioral flexibility.

That's very interesting, thanks and we are very happy to mention this important study in the revised version.

Weaknesses:

As a general remark, there is some information that I missed and that is mandatory in the analysis of behavioral changes.

Firstly, the variability in the performances displayed. The authors mentioned that the results reported come from 6 fish (which is a low sample size). How were the individual performances in terms of consistency? Were all fish equally good in adjusting/learning the new rule? How did errors vary according to individual identity? It seems to me that this kind of information should be available as the authors reported that individual fish could be recognized and tracked (see lines 620-635) and is essential for appreciating the flexibility of the system under study.

Secondly, the speed of the learning process is not properly explained. Admittedly, fish learn in an impressive way the new rule and even two rules simultaneously; yet, how long did they need to achieve this? In the article, Figure 2 mentions that at least 6 training stages (each defined as a block of 60 evaluated turn decisions, which actually shows that the standard term 'Training Block' would be more appropriate) were required for the fish to learn the 'deflected rule'. While this means 360 trials (turning starts), I was left with the question of how long this process lasted. How many hours, days, and weeks were needed for the fish to learn? And as mentioned above, were all fish equally fast in learning? I would appreciate explaining this very important point because learning dynamics is relevant to understanding the flexibility of the system.

First, it is very important to keep the question in mind that we wanted to clarify: Does the system have the potential to re-tune the decisions to other non-ballistic relations between the input variables and the output? This would have been established if one fish was found capable of doing that. We have rewritten the introduction and discussion to specifically say what our aim was. We feel that the paper is already extremely long and difficult to understand (even after we tried very hard in this revision to explain everything in detail and as good as we could), requires the establishment of a method whose success was really unexpected and finding a degree of plasticity that we did not expect at all. We also have added a section in the discussion stating what we can, and we cannot say given the number of fish examined. For instance, we do not know if there are differences in the speed at which the different individuals mastered the new rules and if social learning could play a role to speed up the acquisition. That is a brilliant idea and we are very interested in checking this - but we wanted to stick with the (quite ambitious) goal of the present study.

Reference:

(1) Roussel, E., Padie, S. & Giurfa, M. Aversive learning overcomes appetitive innate responding in honeybees. Anim Cogn 15, 135-141, doi:10.1007/s10071011-0426-1 (2012).

Thanks for this reference!

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Minor comments:

(1) What is the difference between Reinel, J. Exp. Bio. 2016 and the current study?

Clearly in that study all objects were strictly falling ballistically, and latency and accuracy of the turn decisions were determined when the initial motion was not only horizontal but had an additional vertical component of speed. The question of that study was if the need to account to an additional variable (vertical speed) in the decision would affect its latency or accuracy. The study showed that also then archerfish rapidly turn to the later impact point. It also showed that accuracy and latency were not changed by the added degree of freedom.

(2) How do Figures 2 F and G demonstrate that an accurate start is possible?

See above.

(3) Figure 4 is hard to follow, it is not clear what is presented and how it supports the claim that the new rule is represented in a way that allows immediate generalization.

Yes, this is not at all an easy experiment. Briefly, fish were re-trained at only one height level and then are tested at other levels. The strategy is as in the experiments Schuster et al. 2004 Current Biology, Vol. 14, 1565–1568, Figure 5. We have changed text and Figure (new Figure 5) to show how the predictions were reached.

Reviewer #2 (Recommendations for the authors):

Minor remarks

Lines 88-90: I was surprised to see that in this section, the authors did not mention the speed-accuracy trade-off off which has inspired numerous experiments in animal behavior (1). This could be used to back their point, namely, that speed comes with an apparent cost of a loss in accuracy.

Yes, that is a crucial aspect that was completely missing even though it demonstrates a key aspect of 'standard' versus some 'highspeed' decisions! We definitely had to include it and also to show, directly under the conditions of our present experiments (in the new Fig. 4) the absence of a significant speedaccuracy relation for the archerfish highspeed decisions! Thank you very much for emphasizing this crucial aspect!

Lines 182-184: Specify that this situation corresponds to the hatched bar in Figure (this can be specified in the caption of the figure, where the bar is not mentioned).

Thanks!

Lines 187-188: here and elsewhere (e.g. lines 224-225, etc), the error made by the fish is presented in cm (see Figure 2 where the inset shows how the error was computed). I wonder if it would not be more appropriate to present it in terms of the angular difference between the trajectory made by the fish and the food delivery location.

Angles could also be used, but because of the large variation in initial distances (that we wanted to make sure that the fish had to capture a rule, allowing them to respond from various distances) another measure was used that we found somehow more natural: it is simply how close a fish would get to the landing point if it continued in the direction assumed after the turn. Although we describe how we defined accuracy we did not discuss why this measure was used in this (and many previous studies). We are very happy to add this. Please also note that running all tests based on angular errors (which we also have done throughout to ensure that the conclusions are independent on an arbitrary measure of the error) leads to no different conclusion. We have added a brief explanation in the text and in the new Fig. 2.

Lines 299-323: Is it my impression or did fish have more trouble in generalizing their learned rule to the condition untrained larger height (see for instance red curves in Figures 4 D, E, G)? Could the authors elaborate on this point?

We changed the code to make this more clear. The red curves (before marked A to highlight impact point option A) correspond to the errors to the ballistic impact point without deflection, so what would have to be compared are the black curves (marked P to highlight the virtual impact point that should be chosen had the fish immediately generated to the untrained conditions). We have rewritten the text and the labels in the Figure (now Figure 5) to illustrate the predictions and to name them in more helpful ways and so that they can't be confused with panel labels. At any rate, what needs to be compared, to check the idea, are the black curves, and these are not statistically different between both heights (p=0.525, Mann-Whitney). Interestingly, none of the black curves from all panels (D-G) differ (p>0.3).

Line 559: if we are speaking here about luminance contrast, it should read 'Michelson Contrast' rather than 'Michelsen Contrast'.

Absolutely, thanks!

References

(1) Chittka, L., Skorupski, P. & Raine, N. E. Speed-accuracy tradeoffs in animal decision making. Trends Ecol Evol 24, 400-407, doi:10.1016/j.tree.2009.02.010 (2009).

An excellent paper that helps to stress our main question

Reviewer #1 (Public review):

Summary:

This paper examines how geometric regularities in abstract shapes (e.g., parallelograms, kites) are perceived and processed in the human brain. The manuscript contains multimodal data (behavior, fMRI, MEG) from adults and additional fMRI data from 6-year-old children. The key findings show that (1) processing geometric shapes lead to reduced activity in ventral areas in comparison to complex stimuli and increased activity in intraparietal and inferior temporal regions, (2) the degree of geometric regularity modulates activity in intraparietal and inferior temporal regions, (3) similarity in neural representation of geometric shapes can be captured early by using CNN models and later by models of geometric regularity. In addition to these novel findings, the paper also includes a replication of behavioral data, showing that the perceptual similarity structure amongst the geometric stimuli used can be explained by a combination of visual similarities (as indexed by a feedforward CNN model of the ventral visual pathway) and geometric features.

Strengths:

(1) The study incorporates multi-modal data that uses more than one task and different populations of participants (adults and children).

(2) It replicates behavioral findings of an earlier study in a larger cohort.

(3) The paper comes with openly accessible code in a well-documented GitHub repository, and the data will be published with the paper on OpenNeuro.

Weaknesses:

I wonder how task difficulty and linguistic labels interact with the current findings. Based on the behavioral data, shapes with more geometric regularities are easier to detect when surrounded by other shapes. Do shape labels that are readily available (e.g., "square") help in making accurate and speedy decisions? Can the sensitivity to geometric regularity in intraparietal and inferior temporal regions be attributed to differences in task difficulty? Similarly, are the MEG oddball detection effects that are modulated by geometric regularity also affected by task difficulty?

Isaac Ch. 27/05 - Engaged, no-code or marketing automation SaaS

I would say shopify and Wix are definitely useful for quite a few people who wouldn't otherwise make a website.

But for those who are able to do it with other means, giving up freedoms with a vendor lock-in might not be worth it will be my interpretation of this statement

profound!

dead code removed

Reviewer #3 (Public review):

Summary:

The authors used recurrent neural network modelling of spatial navigation tasks to investigate border and place cell behaviour during remapping phenomena.

Strengths:

The neural network training seemed for the most part (see comments later) well-performed, and the analyses used to make the points were thorough.

The paper and ideas were well-explained.

Figure 4 contained some interesting and strong evidence for map-like generalisation as environmental geometry was warped.

Figure 7 was striking and potentially very interesting.

It was impressive that the RNN path-integration error stayed low for so long (Fig A1), given that normally networks that only work with dead-reckoning have errors that compound. I would have loved to know how the network was doing this, given that borders did not provide sensory input to the network. I could not think of many other plausible explanations... It would be even more impressive if it was preserved when the network was slightly noisy.

Update:

The analysis of how the RNN remapped, using a context signal to switch between largely independent maps, and the examination of the border like tuning in the recurrent units of the RNN, were both thorough and interesting. Further, in the updated response I appreciated the additional appendix E which helped substantiate the claim that the RNN neurons were border cells.

Weaknesses:

The remapping results were also puzzling. The authors present convincing evidence that the recurrent units effectively form 6 different maps of the 6 different environments (e.g. the sparsity of the code, or fig 6a), with the place cells remapping between environments. Yet, as the authors point out, in neural data the finding is that some cells generalise their co-firing patterns across environments (e.g. grid cells, border cells), while place cells remap, making it unclear what correspondence to make between the authors network and the brain. There are existing normative models that capture both entorhinal's consistent and hippocampus' less consistent neural remapping behaviour (Whittington et al. and probably others), what have we then learnt from this exercise?

Update: see summary below

I felt that the neural data analysis was unconvincing. Most notably, the statistical effect was found in only one of seven animals. Random noise is likely to pass statistical tests 1 in 20 times (at 0.05 p value), this seems like it could have been something similar? Further, the data was compared to a null model in which place cell fields were randomly distributed. The authors claim place cell fields have two properties that the random model doesn't (1) clustering to edges (as experimentally reported) and (2) much more provocatively, a hexagonal lattice arrangement. The test seems to collude the two; I think that nearby ball radii could be overrepresented, as in figure 7f, due to either effect. I would have liked to see a computation of the statistic for a null model in which place cells were random but with a bias towards to boundaries of the environment that matches the observed changing density, to distinguish these two hypotheses.

Update: the authors acknowledge these shortcomings and have appropriately tempered their data related claims.

Some smaller weaknesses:<br /> - Had the models trained to convergence? From the loss plot it seemed like not, and when including regularisors recent work (grokking phenomena, e.g. Nanda et al. 2023) has shown the importance of letting the regularisor minimise completely to see the resulting effect. Else you are interpreting representations that are likely still being learnt, a dangerous business.<br /> Update: I understand that practical limitations make testing this thoroughly impossible, which is fair enough.

- The claim that this work provided a mathematical formalism of the intuitive idea of a cognitive map seems strange, given that upwards of 10 of the works this paper cite also mathematically formalise a cognitive map into a similar integration loss for a neural network.<br /> Update: the introduction of these ideas hasn't changed, and my concerns above remain.

Aim Achieved? Impact/Utility/Context of Work

I think this is a thorough exploration of how this network with these losses is able to path-integrate its position and remap. This is useful, it is good to know how another neural network with slightly different constraints learns to perform these behaviours.

In the updated version of the manuscript I am happy to say that I think there are few claims that are unsubstantiated (see weakness section above that has been significantly updated). The link to neuroscience remains the biggest shortcoming of this work in my view. The authors point to two main results in this direction. First, the ability for interactions only between border-type and place cells to produce many observed place-cell results, providing a new hypothesis. Second, a connection between grid cells, place cells, and border cells, in the production of hexagonal arrangements of place cells.

Regarding the first, as the authors discuss, current evidence suggests border cells are invariant across environments whereas this work finds border cells for specific environments (they use the words rate-remapping boundary-type cells). It seems likely to me that there are many ways a neural network can path-integrate across different environments. In other models where the same base map is re-used (e.g. TEM) grid cells emerge, in this work where the maps for different environments are disjoint these border-like cells that do not match an observed cell type in their tuning to environment are involved. I find this a really interesting alternative (I think what an RNN does is interesting in its own right), but I don't see why I should think it is what the brain does, given that it appears to match observations less well (existence of grid cells, consistent firing patterns of border cells across environments). The smoking gun in favour of the author's hypothesis would be finding these sparse border like cells, or some other evidence of gating like interactions between border and place cells as they discuss. Finding such evidence sounds difficult (so not reasonable to ask for in a rebuttal), and to reiterate, I applaud the authors for clearly outlining an alternative, but I remain unconvinced.

Regarding the second point, while the grid-like placement of field centres was cool, and I applaud the authors for including real neural data comparisons, as the authors say, the data is preliminary, and further evidence would be required to fully substantiate this claim.

As such, in my mind it is an interesting alternative hypothesis. I look forward to seeing experimental predictions or comparisons that can tighten the link, substantiating the claim that what this particular RNN is doing reflects the algorithms at work in the brain.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public Review):

Summary:

This work studies representations in a network with one recurrent layer and one output layer that needs to path-integrate so that its position can be accurately decoded from its output. To formalise this problem, the authors define a cost function consisting of the decoding error and a regularisation term. They specify a decoding procedure that at a given time averages the output unit center locations, weighted by the activity of the unit at that time. The network is initialised without position information, and only receives a velocity signal (and a context signal to index the environment) at each timestep, so to achieve low decoding error it needs to infer its position and keep it updated with respect to its velocity by path integration.

The authors take the trained network and let it explore a series of environments with different geometries while collecting unit activities to probe learned representations. They find localised responses in the output units (resembling place fields) and border responses in the recurrent units. Across environments, the output units show global remapping and the recurrent units show rate remapping. Stretching the environment generally produces stretched responses in output and recurrent units. Ratemaps remain stable within environments and stabilise after noise injection. Low-dimensional projections of the recurrent population activity forms environment-specific clusters that reflect the environment's geometry, which suggests independent rather than generalised representations. Finally, the authors discover that the centers of the output unit ratemaps cluster together on a triangular lattice (like the receptive fields of a single grid cell), and find significant clustering of place cell centers in empirical data as well.

The model setup and simulations are clearly described, and are an interesting exploration of the consequences of a particular set of training requirements - here: path integration and decodability. But it is not obvious to what extent the modelling choices are a realistic reflection of how the brain solves navigation. Therefore it is not clear whether the results generalize beyond the specifics of the setup here.

Strengths:

The authors introduce a very minimal set of model requirements, assumptions, and constraints. In that sense, the model can function as a useful 'baseline', that shows how spatial representations and remapping properties can emerge from the requirement of path integration and decodability alone. Moreover, the authors use the same formalism to relate their setup to existing spatial navigation models, which is informative.

The global remapping that the authors show is convincing and well-supported by their analyses. The geometric manipulations and the resulting stretching of place responses, without additional training, are interesting. They seem to suggest that the recurrent network may scale the velocity input by the environment dimensions so that the exact same path integrator-output mappings remain valid (but maybe there are other mechanisms too that achieve the same).

The clustering of place cell peaks on a triangular lattice is intriguing, given there is no grid cell input. It could have something to do with the fact that a triangular lattice provides optimal coverage of 2d space? The included comparison with empirical data is valuable, although the authors only show significant clustering - there is no analysis of its grid-like regularity.

First of all, we would like to thank the reviewer for their comprehensive feedback, and their insightful comments. Importantly, as you point out, our goal with this model was to build a minimal model of place cell representations, where representations were encouraged to be place-like, but free to vary in tuning and firing locations. By doing so, we could explore what upstream representations facilitate place-like representations, and even remapping (as it turned out) with minimal assumptions. However, we agree that our task does not capture some of the nuances of real-world navigation, such as sensory observations, which could be useful extensions in future work. Then again, the simplicity of our setup makes it easier to interpret the model, and makes it all the more surprising that it learns many behaviors exhibited by real world place cells.

As to the distribution of phases - we also agree that a hexagonal arrangement likely reflects some optimal configuration for decoding of location.

And we agree that the symmetry within the experimental data is important; we have revised analyses on experimental phase distributions, and included an analysis of ensemble grid score, to quantify any hexagonal symmetries within the data.

Weaknesses:

The navigation problem that needs to be solved by the model is a bit of an odd one. Without any initial position information, the network needs to figure out where it is, and then path-integrate with respect to a velocity signal. As the authors remark in Methods 4.2, without additional input, the only way to infer location is from border interactions. It is like navigating in absolute darkness. Therefore, it seems likely that the salient wall representations found in the recurrent units are just a consequence of the specific navigation task here; it is unclear if the same would apply in natural navigation. In natural navigation, there are many more sensory cues that help inferring location, most importantly vision, but also smell and whiskers/touch (which provides a more direct wall interaction; here, wall interactions are indirect by constraining velocity vectors). There is a similar but weaker concern about whether the (place cell like) localised firing fields of the output units are a direct consequence of the decoding procedure that only considers activity center locations.

Thank you for raising this point; we absolutely agree that the navigation task is somewhat niche. However, this was a conscious decision, to minimize any possible confounding from alternate input sources, such as observations. In part, this experimental design was inspired by the suggestion that grid cells support navigation/path integration in open-field environments with minimal sensory input (as they could, conceivably do so with no external input). This also pertains to your other point, that boundary interactions are necessary for navigation. In our model, using boundaries is one solution, but there is another way around this problem, which is conceivably better: to path integrate in an egocentric frame, starting from your initial position. Since the locations of place fields are inferred only after a trajectory has been traversed, the network is free to create a new or shifted representation every time, independently of the arena. In this case, one might have expected generalized solutions, such as grid cells to emerge. That this is not the case, seems to suggest that grid cells may somehow not be optimal for pure path integration, or at the very least, hard to learn (but may still play a part, as alluded to by place field locations). We have tried to make these points more evident in the revised manuscript.

As for the point that the decoding may lead to place-like representations, this is a fair point. Indeed, we did choose this form of decoding, inspired by the localized firing of place cells, in the hope that it would encourage minimally constrained, place-like solutions. However, compared to other works (Sorscher and Xu) hand tuning the functional form of their place cells, our (although biased towards centralized tuning curves) allows for flexible functional forms such as the position of the place cell centers, their tuning width, whether or not it is center-surround activity, and how they should tune to different environments/rooms. This allows us to study several features of the place cell system, such as remapping and field formation. We have revised to make this more clear in the model description.

The conclusion that 'contexts are attractive' (heading of section 2) is not well-supported. The authors show 'attractor-like behaviour' within a single context, but there could be alternative explanations for the recovery of stable ratemaps after noise injection. For example, the noise injection could scramble the network's currently inferred position, so that it would need to re-infer its position from boundary interactions along the trajectory. In that case the stabilisation would be driven by the input, not just internal attractor dynamics. Moreover, the authors show that different contexts occupy different regions in the space of low-dimensional projections of recurrent activity, but not that these regions are attractive.

We agree that boundary interactions could facilitate the convergence of representations after noise injection. We did try to moderate this claim by the wording “attractor-like”, but we agree that boundaries could confound this result. We have therefore performed a modified noise injection experiment, where we let the network run for an extended period of time, before noise injection (and no velocity signal), see Appendix Velocity Ablation in the revised text. Notably, representations converge to their pre-scrambled state after noise injection, even without a velocity signal. However, place-like representations do not converge for all noise levels in this case, possibly indicating that boundary interactions do serve an error-correcting function, also. Thank you for pointing this out.

As for the attractiveness of contexts, we agree that more analyses were required to demonstrate this. We have therefore conducted a supplementary analysis where we run the trained network with a mismatch in context/geometry, and demonstrate that the context signal fixes the representation, up to geometric distortions.

The authors report empirical data that shows clustering of place cell centers like they find for their output units. They report that 'there appears to be a tendency for the clusters to arrange in hexagonal fashion, similar to our computational findings'. They only quantify the clustering, but not the arrangement. Moreover, in Figure 7e they only plot data from a single animal, then plot all other animals in the supplementary. Does the analysis of Fig 7f include all animals, or just the one for which the data is plotted in 7e? If so, why that animal? As Appendix C mentions that the ratemap for the plotted animal 'has a hexagonal resemblance' whereas other have 'no clear pattern in their center arrangements', it feels like cherrypicking to only analyse one animal without further justification.

Thank you for pointing this out; we agree that this is not sufficiently explained and explored in the current version. We have therefore conducted a grid score analysis of the experimental place center distributions, to uncover possible hexagonal symmetries. The reason for choosing this particular animal was in part because it featured the largest number of included cells, while also demonstrating the most striking phase distribution, while including all distributions in the supplementary. Originally, this was only intended as a preliminary analysis, suggesting non-uniformity in experimental place field distributions, but we realize that these may all provide interesting insight into the distributional properties of place cells.

We have explained these choices in the revised text, and expanded analyses on all animals to showcase these results more clearly.

Reviewer #2 (Public Review):

Summary:

The authors proposed a neural network model to explore the spatial representations of the hippocampal CA1 and entorhinal cortex (EC) and the remapping of these representations when multiple environments are learned. The model consists of a recurrent network and output units (a decoder) mimicking the EC and CA1, respectively. The major results of this study are: the EC network generates cells with their receptive fields tuned to a border of the arena; decoder develops neuron clusters arranged in a hexagonal lattice. Thus, the model accounts for entorhinal border cells and CA1 place cells. The authors also suggested the remapping of place cells occurs between different environments through state transitions corresponding to unstable dynamical modes in the recurrent network.

Strengths:

The authors found a spatial arrangement of receptive fields similar to their model's prediction in experimental data recorded from CA1. Thus, the model proposes a plausible mechanisms to generate hippocampal spatial representations without relying on grid cells. This result is consistent with the observation that grid cells are unnecessary to generate CA1 place cells.

The suggestion about the remapping mechanism shows an interesting theoretical possibility.

We thank the reviewer for their kind feedback.

Weaknesses:

The explicit mechanisms of generating border cells and place cells and those underlying remapping were not clarified at a satisfactory level.

The model cannot generate entorhinal grid cells. Therefore, how the proposed model is integrated into the entire picture of the hippocampal mechanism of meｍory processing remains elusive.

We appreciate this point, and hope to clarify: From a purely architectural perspective, place-like representations are generated by linear combinations of recurrent unit representations, which, after training, appear border-like. During remapping, the network is simply evaluated/run in different geometries/contexts, which, it turns out, causes the network to exhibit different representations, likely as solutions to optimally encoding position in the different environments. We have attempted to revise the text to make some of these interpretations more clear. We have also conducted a supplementary analysis to demonstrate how representations are determined by the context signal directly, which helps to explain how recurrent and output units form their representations.

We also agree that our model does not capture the full complexity of the Hippocampal formation. However, we would argue that its simplicity (focusing on a single cell type and a pure path integration task), acts as a useful baseline for studying the role of place cells during spatial navigation. The fact that our model captures a range of place cell behaviors (field formation, remapping and geometric deformation) without grid cells also point to several interesting possibilities, such that grid cells may not be strictly necessary for place cell formation and remapping, or that border cells may account for many of the peculiar behaviors of place cells. However, we wholeheartedly agree that including e.g. sensory information and memory storage/retrieval tasks would prove a very interesting extension of our model to more naturalistic tasks and settings. In fact, our framework could easily accommodate this, e.g. by decoding contexts/observations/memories from the network state, alongside location.

Reviewer #3 (Public Review):

Summary:

The authors used recurrent neural network modelling of spatial navigation tasks to investigate border and place cell behaviour during remapping phenomena.

Strengths:

The neural network training seemed for the most part (see comments later) well-performed, and the analyses used to make the points were thorough.

The paper and ideas were well explained.

Figure 4 contained some interesting and strong evidence for map-like generalisation as environmental geometry was warped.

Figure 7 was striking, and potentially very interesting.

It was impressive that the RNN path-integration error stayed low for so long (Fig A1), given that normally networks that only work with dead-reckoning have errors that compound. I would have loved to know how the network was doing this, given that borders did not provide sensory input to the network. I could not think of many other plausible explanations... It would be even more impressive if it was preserved when the network was slightly noisy.

Thank you for your insightful comments! Regarding the low path integration error, there is a slight statistical signal from the boundaries, as trajectories tend to turn away from arena boundaries. However, we agree, that studying path integration performance in the face of noise would make for a very interesting future development.

Weaknesses:

I felt that the stated neuroscience interpretations were not well supported by the presented evidence, for a few reasons I'll now detail.

First, I was unconvinced by the interpretation of the reported recurrent cells as border cells. An equally likely hypothesis seemed to be that they were positions cells that are linearly encoding the x and y position, which when your environment only contains external linear boundaries, look the same. As in figure 4, in environments with internal boundaries the cells do not encode them, they encode (x,y) position. Further, if I'm not misunderstanding, there is, throughout, a confusing case of broken symmetry. The cells appear to code not for any random linear direction, but for either the x or y axis (i.e. there are x cells and y cells). These look like border cells in environments in which the boundaries are external only, and align with the axes (like square and rectangular ones), but the same also appears to be true in the rotationally symmetric circular environment, which strikes me as very odd. I can't think of a good reason why the cells in circular environments should care about the particular choice of (x,y) axes... unless the choice of position encoding scheme is leaking influence throughout. A good test of these would be differently oriented (45 degree rotated square) or more geometrically complicated (two diamonds connected) environments in which the difference between a pure (x,y) code and a border code are more obvious.

Thank you for pointing this out. This is an excellent point, that we agree could be addressed more rigorously. Note that there is no position encoding in our model; the initial state of the network is a vector of zeros, and the network must infer its location from boundary interactions and context information alone. So there is no way for positional information to leak through to the recurrent layer directly. However, one possible reason for the observed symmetry breaking, is the fact that the velocity input signal is aligned with the cardinal directions. To investigate this, we trained a new model, wherein input velocities are rotated 45 degrees relative to the horizontal, as you suggest. The results, shown and discussed in appendix E (Learned recurrent representations align with environment boundaries), do indicate that representations are tuned to environment boundaries, and not the cardinal directions, which hopefully improves upon this point.

Next, the decoding mechanism used seems to have forced the representation to learn place cells (no other cell type is going to be usefully decodable?). That is, in itself, not a problem. It just changes the interpretation of the results. To be a normative interpretation for place cells you need to show some evidence that this decoding mechanism is relevant for the brain, since this seems to be where they are coming from in this model. Instead, this is a model with place cells built into it, which can then be used for studying things like remapping, which is a reasonable stance.

This is a great point, and we agree. We do write that we perform this encoding to encourage minimally constrained place-like representations (to study their properties), but we have revised to make this more evident.

However, the remapping results were also puzzling. The authors present convincing evidence that the recurrent units effectively form 6 different maps of the 6 different environments (e.g. the sparsity of the code, or fig 6a), with the place cells remapping between environments. Yet, as the authors point out, in neural data the finding is that some cells generalise their co-firing patterns across environments (e.g. grid cells, border cells), while place cells remap, making it unclear what correspondence to make between the authors network and the brain. There are existing normative models that capture both entorhinal's consistent and hippocampus' less consistent neural remapping behaviour (Whittington et al. and probably others), what have we then learnt from this exercise?

Thanks for raising this point! We agree that this finding is surprising, but we hold that it actually shows something quite important: that border-type units are sufficient to create place-like representations, and learns several of the behaviors associated with place cells and remapping (including global remapping and field stretching). In other words, a single cell type known to exist upstream of place cells is sufficient to explain a surprising range of phenomena, demonstrating that other cell types are not strictly necessary. However, we agree that understanding why the boundary type units sometimes rate remap, and whether that can be true for some border type cells in the brain (either directly, or through gating mechanisms) would be important future developments. Related to this point, we also expanded upon the influence of the context signal for representation selection (appendix F)

Concerning the relationship to other models, we would argue that the simplicity of our model is one of its core strengths, making it possible to disentangle what different cell types are doing. While other models, including TEM, are highly important for understanding how different cell types and brain regions interact to solve complex problems, we believe there is a need for minimal, understandable models that allows us to investigate what each cell type is doing, and this is where we believe our work is important. As an example, our model not only highlights the sufficiency of boundary-type cells as generators of place cells, its lack of e.g. grid cells also suggest that grid cells may not be strictly necessary for e.g. open-field/sensory-deprived navigation, as is often claimed.

One striking result was figure 7, the hexagonal arrangement of place cell centres. I had one question that I couldn't find the answer to in the paper, which would change my interpretation. Are place cell centres within a single clusters of points in figure 7a, for example, from one cell across the 100 trajectories, or from many? If each cluster belongs to a different place cell then the interpretation seems like some kind of optimal packing/coding of 2D space by a set of place cells, an interesting prediction. If multiple place cells fall within a single cluster then that's a very puzzling suggestion about the grouping of place cells into these discrete clusters. From figure 7c I guess that the former is the likely interpretation, from the fact that clusters appear to maintain the same colour, and are unlikely to be co-remapping place cells, but I would like to know for sure!

This is a good point, and you are correct: one cluster tends to correspond to one unit. To make this more clear, we have revised Fig. 7, so that each decoded center is shaded by unit identity, which makes this more evident. And yes, this is, seemingly in line with some form of optimal packing/encoding of space, yes!

I felt that the neural data analysis was unconvincing. Most notably, the statistical effect was found in only one of seven animals. Random noise is likely to pass statistical tests 1 in 20 times (at 0.05 p value), this seems like it could have been something similar? Further, the data was compared to a null model in which place cell fields were randomly distributed. The authors claim place cell fields have two properties that the random model doesn't (1) clustering to edges (as experimentally reported) and (2) much more provocatively, a hexagonal lattice arrangement. The test seems to collude the two; I think that nearby ball radii could be overrepresented, as in figure 7f, due to either effect. I would have liked to see a computation of the statistic for a null model in which place cells were random but with a bias towards to boundaries of the environment that matches the observed changing density, to distinguish these two hypotheses.

Thanks for raising this point. We agree that we were not clear enough in our original manuscript. We included additional analyses in one animal, to showcase one preliminary case of non-uniform phases. To mitigate this, we have performed the same analyses for all animals, and included a longer discussion of these results (included in the supplementary material). We have also moderated the discussion on Ripley’s H to encompass only non-uniformity, and added a grid score analysis to showcase possible rotational symmetries in the data. We hope this gets our findings across more clearly

Some smaller weaknesses:

- Had the models trained to convergence? From the loss plot it seemed like not, and when including regularisors recent work (grokking phenomena, e.g. Nanda et al. 2023) has shown the importance of letting the regularisor minimise completely to see the resulting effect. Else you are interpreting representations that are likely still being learnt, a dangerous business.

Longer training time did not seem to affect representations. However, due to the long trajectories and statefulness involved, training was time-intensive and could become unstable for very long training. We therefore stopped training at the indicated time.

- Since RNNs are nonlinear it seems that eigenvalues larger than 1 doesn't necessarily mean unstable?

This is a good point; stability is not guaranteed. We have updated the text to reflect this.

- Why do you not include a bias in the networks? ReLU networks without bias are not universal function approximators, so it is a real change in architecture that doesn't seem to have any positives?

We found that bias tended to have a detrimental effect on training, possibly related to the identity initialization used (see e.g. Le et al. 2015), and found that training improved when biases were fixed to zero.

- The claim that this work provided a mathematical formalism of the intuitive idea of a cognitive map seems strange, given that upwards of 10 of the works this paper cite also mathematically formalise a cognitive map into a similar integration loss for a neural network.

We agree that other works also provide ways of formalizing this concepts. However, our goal by doing so was to elucidate common features across these seemingly disparate models. We also found that the concept of a learned and target map made it easier to come up with novel models, such as one wherein place cells are constructed to match a grid cell label.

Aim Achieved? Impact/Utility/Context of Work

Given the listed weaknesses, I think this was a thorough exploration of how this network with these losses is able to path-integrate its position and remap. This is useful, it is good to know how another neural network with slightly different constraints learns to perform these behaviours. That said, I do not think the link to neuroscience was convincing, and as such, it has not achieved its stated aim of explaining these phenomena in biology. The mechanism for remapping in the entorhinal module seemed fundamentally different to the brain's, instead using completely disjoint maps; the recurrent cell types described seemed to match no described cell type (no bad thing in itself, but it does limit the permissible neuroscience claims) either in tuning or remapping properties, with a potentially worrying link between an arbitrary encoding choice and the responses; and the striking place cell prediction was unconvincingly matched by neural data. Further, this is a busy field in which many remapping results have been shown before by similar models, limiting the impact of this work. For example, George et al. and Whittington et al. show remapping of place cells across environments; Whittington et al. study remapping of entorhinal codes; and Rajkumar Vasudeva et al. 2022 show similar place cell stretching results under environmental shifts. As such, this papers contribution is muddied significantly.

Thank you for this perspective; we agree that all of these are important works that arrive at complementary findings. We hold that the importance of our paper lies in its minimal nature, and its focus on place cells, via a purpose-built decoding that enables place-like representations. In doing so, we can point to possibly under explored relationships between cell types, in particular place cells and border cells, while challenging the necessity of other cell types for open-field navigation (i.e. grid cells). In addition, our work points to a novel connection between grid cells, place cells and even border cells, by way of the hexagonal arrangement of place unit centers. However, we agree that expanding our model to include more biologically plausible architectures and constraints would make for a very interesting extension in the future.

Thank you again for your time, as well as insightful comments.  

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Even after reading Methods 5.3, I found it hard to understand how the ratemap population vectors that produce Fig 3e and Fig 5 are calculated. It's unclear to me how there can be a ratemap at a single timestep, because calculating a ratemap involves averaging the activity in each location, which would take a whole trajectory and not a single timestep. But I think I've understood from Methods 5.1 that instead the ratemap is calculated by running multiple 'simultaneous' trajectories, so that there are many visited locations at each timestep. That's a bit confusing because as far as I know it's not a common way to calculate ratemaps in rodent experiments (probably because it would be hard to repeat the same task 500 times, while the representations remain the same), so it might be worth explaining more in Methods 5.3.

We understand the confusion, and have attempted to make this more clear in the revised manuscript. We did indeed create ratemaps over many trajectories for time-dependent plots, for the reasons you mentioned. We also agree that this would be difficult to do experimentally, but found it an interesting way to observe convergence of representations in our simulated scenario.

Fig 3b-d shows multiple analyses to support output unit global remapping, but no analysis to support the claim that recurrent units remap by rate changes. The examples in Fig 3ai look pretty convincing, but it would be useful to also have a more quantitative result.

We agree, and only showed that units turn off/become silent using ratemaps. We have therefore added an explicit analysis, showcasing rate remapping in recurrent units (see appendix G; Recurrent units rate remap)

Reviewer #2 (Recommendations For The Authors):

Some parts of the current manuscript are hard to follow. Particularly, the model description is not transparent enough. See below for the details.

Major comments:

(1) Mathematical models should be explained more explicitly and carefully. I had to guess or desperately search for the definitions of parameters. For instance, define the loss function L in eq.(1). Though I can assume L represents the least square error (in A.8), I could not find the definition in Model & Objective. N should also be defined explicitly in equation (3). Is this the number of output cells?

Thank you for pointing this out, we have revised to make it more clear.

(2) In Fig. 1d, how were the velocity and context inputs given to individual neurons in the network? The information may be described in the Methods, but I could not identify it.

This was described in the methods section (Neural Network Architecture and Training), but we realize that we used confusing notation, when comparing with Fig. 1d. We have therefore changed the notation, and it should hopefully be clearer now. Thanks for pointing out this discrepancy.

(3) I took a while to understand equations (3) and (4) (for instance, t is not defined here). The manuscript would be easier to read if equations (5) and (6) are explained in the main text but not on page 18 (indeed, these equations are just copies of equations 3 and 4). Otherwise, the authors may replace equations (3) and (4) with verbal explanations similar to figure legend for Fig. 1b.

(4) Is there any experimental evidence for uniformly strong EC-to-CA1 projections assumed in the non-trainable decoder? This point should be briefly mentioned.

Thank you for raising this point. The decoding from EC (the RNN) to CA1 (the output layer) consists of a trainable weight matrix, and may thus be non-uniform in magnitude. The non-trainable decoding acts on the resulting “CA1” representation only. We hope that improvements to the model description also makes this more evident.  

(5) The explanation of Fig. 3 in the main text is difficult to follow because subpanels are explained in separate paragraphs, some of which are very short, as short as just a few lines.

This presentation style makes it difficult to follow the logical relationships between the subpanels. This writing style is obeyed throughout the manuscript but is not popular in neuroscience.

Thanks for pointing this out, we have revised to accommodate this.

(6) Why do field centers cluster near boundaries? No underlying mechanisms are discussed in the manuscript.

This is a good point; we have added a note on this; it likely reflects the border tuning of upstream units.

(7) In Fig. 4, the authors presented how cognitive maps may vary when the shape and size of open arenas are modified. The results would be more interesting if the authors explained the remapping mechanism. For instance, on page 8, the authors mentioned that output units exhibit global remapping between contexts, whereas recurrent units mainly rate remapping.

Why do such representational differences emerge?

We agree! Thanks for raising this point. We have therefore expanded upon this discussion in section 2.4.

(8) In the first paragraph of page 10, the authors stated ".. some output units display distinct field doubling (see both Fig. 4c), bottom right, and Fig. 4d), middle row)". I could not understand how Fig. 4d, middle row supports the argument. Similarly, they stated "..some output units reflect their main boundary input (with greater activity near one boundary)." I can neither understand what the authors mean to say nor which figures support the statement. Please clarify.

This is a good point, there was an identifier missing; we have updated to refer to the correct “magnification”. Thanks!

(9) The underlying mechanism of generating the hexagonal representation of output cells remains unclear. The decoder network uses a non-trainable decoding scheme based on localized firing patterns of output units. To what extent does the hexagonal representation depend on the particular decoding scheme? Similarly, how does the emergence of the hexagonal representation rely on the border representation in the upstream recurrent network? Showing several snapshots of the two place representations during learning may answer these questions.

This is an interesting point, and we have added some discussion on this matter. In particular, we speculate whether it’s an optimal configuration for position reconstruction, which is demanded by the task and thus highly likely dependent on the decoding scheme. We have not reached a conclusive method to determine the explicit dependence of the hexagonal arrangement on the choice of decoding scheme. Still, it seems this would require comparison with other schemes. In our framework, this would require changing the fundamental operation of the model, which we leave as inspiration for future work. We have also added additional discussion concerning the relationship between place units, border units, and remapping in our model. As for exploring different training snapshots, the model is randomly initialized, which suggests that earlier training steps should tend to reveal unorganized/uninformative phase arrangements, as phases are learned as a way of optimizing position reconstruction. However, we do call for more analysis of experimental data to determine whether this is true in animals, which would strongly support this observation. We also hope that our work inspires other models studying the formation and remapping of place cells, which could serve as a starting point for answering this question in the future.

(10) Figure 7 requires a title including the word "hexagonal" to make it easier to find the results demonstrating the hexagonal representations. In addition, please clarify which networks, p or g, gave the results shown here.

We agree, and have added it!

Minor comments:

(11) In many paragraphs, conclusions appear near their ends. Stating the conclusion at the beginning of each paragraph whenever possible will improve the readability.

We have made several rewrites to the manuscript, and hope this improves readability.

(12) Figure A4 is important as it shows evidence of the CA1 spatial representation predicted by the model. However, I could not find where the figure is cited in the manuscript. The authors can consider showing this figure in the main text.

We agree, and we have added more references to the experimental data analyses in the main text, as well as expanded this analysis.

(13) The main text cites figures in the following format: "... rate mapping of Fig. 3a), i), boundary ...." The parentheses make reading difficult.

We have removed the overly stringent use of double parentheses, thanks for letting us know.

(14) It would be nice if the authors briefly explained the concept of Ripley's H function on page 14.

Yes, we have added a brief descriptor.

No support of ach yet. Let's pls do for cards. Forgot to check code snippets in some other pages. Please ensure we are using cards in all snippets

use Razorpay Payment Links. Create a link from the dashboard and start collecting payments from your customers.

where is code to add data to f??

이러한 보일러플레이트 코드는 다루기 힘든데, 새로운 필드가 추가되면 모든 장소의 코드를 업데이트해줘야 하기 때문이다.

struct의 모든 필드 값이 초기화 되는 것을 강제하고 있다. 이는 코드 안정성을 보장하지만 장황한 보일러플레이트 코드를 유발한다.

df = pd.read_csv("../datasets/penguins_classfication.csv")

The concept of using games in learning, though fun for students and teachers, seems to be a gateway to distractions if not applied correctly. In the schools I sub at there is a platform called Blooket that allows students to play games together or independently and solve math, reading, or science problems interspliced with video games designed to foster friendly competition to get to the top of a leaderboard. From what I've seen students usually focus more on the leaderboards than they do the actual content they are there to learn. This makes me question the context that platforms like Blooket should be used in (maybe it's better for test review than it is for learning new concepts).

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

Reviewer #1

Evidence, reproducibility, and clarity

The work by Pinon et al describes the generation of a microvascular model to study Neisseria meningitidis interactions with blood vessels. The model uses a novel and relatively high throughput fabrication method that allows full control over the geometry of the vessels. The model is well characterized. The authors then study different aspects of Neisseria-endothelial interactions and benchmark the bacterial infection model against the best disease model available, a human skin xenograft mouse model, which is one of the great strengths of the paper. The authors show that Neisseria binds to the 3D model in a similar geometry that in the animal xenograft model, induces an increase in permeability short after bacterial perfusion, and induces endothelial cytoskeleton rearrangements. Finally, the authors show neutrophil recruitment to bacterial microcolonies and phagocytosis of Neisseria. The article is overall well written, and it is a great advancement in the bioengineering and sepsis infection field, and I only have a few major comments and some minor.

Major comments:

Infection-on-chip. I would recommend the authors to change the terminology of "infection on chip" to better reflect their work. The term is vague and it decreases novelty, as there are multiple infection on chips models that recapitulate other infections (recently reviewed in https://doi.org/10.1038/s41564-024-01645-6) including Ebola, SARS-CoV-2, Plasmodium and Candida. Maybe the term "sepsis on chip" would be more specific and exemplify better the work and novelty. Also, I would suggest that the authors carefully take a look at the text and consider when they use VoC or to current term IoC, as of now sometimes they are used interchangeably, with VoC being used occasionally in bacteria perfused experiments.

We thank Reviewer #1 for this suggestion. Indeed, we have chosen to replace the term "Infection-on-Chip" by "infected Vessel-on-chip" to avoid any confusion in the title and the text. Also, we have removed all the terms "IoC" which referred to "Infection-on-Chip" and replaced with "VoC" for "Vessel-on-Chip". We think these terms will improve the clarity of the main text.

Fig 3 and Suppmentary 3: Permeability. The authors suggest that early 3h infection with Neisseria do not show increase in vascular permeability in the animal model, contrary to their findings in the 3D in vitro model. However, they show a non-significant increase in permeability of 70 KDa Dextran in the animal xenograft early infection. This seems to point that if the experiment would have been done with a lower molecular weight tracer, significant increases in permeability could have been detected. I would suggest to do this experiment that could capture early events in vascular disruption.

Comparing permeability under healthy and infected conditions using Dextran smaller than 70 kDa is challenging. Previous research [1] has shown that molecules below 70 kDa already diffuse freely in healthy tissue. Given this high baseline diffusion, we believe that no significant difference would be observed before and after N. meningitidis infection and these experiments were not carried out. As discussed in the manuscript, bacteria induced permeability in mouse occurs at later time points, 16h post infection as shown previoulsy [2]. As discussed in the manuscript, this difference between the xenograft model and the chip likely reflect the absence in the chip of various cell types present in the tissue parenchyma.

The authors show the formation of actin of a honeycomb structure beneath the bacterial microcolonies. This only occurred in 65\% of the microcolonies. Is this result similar to in vitro 2D endothelial cultures in static and under flow? Also, the group has shown in the past positive staining of other cytoskeletal proteins, such as ezrin in the ERM complex. Does this also occur in the 3D system?

We thank the Reviewer #1 for this suggestion. - According to this recommendation, we imaged monolayers of endothelial cells in the flat regions of the chip (the two lateral channels) using the same microscopy conditions (i.e., Obj. 40X N.A. 1.05) that have been used to detect honeycomb structures in the 3D vessels in vitro. We showed that more than 56% of infected cells present these honeycomb structures in 2D, which is 13% less than in 3D, and is not significant due to the distributions of both populations. Thus, we conclude that under both in vitro conditions, 2D and 3D, the amount of infected cells exhibiting cortical plaques is similar. We have added the graph and the confocal images in Figure S4B and lines 418-419 of the revised manuscript. - We recently performed staining of ezrin in the chip and imaged both the 3D and 2D regions. Although ezrin staining was visible in 3D (Fig. 1 of this response), it was not as obvious as other markers under these infected conditions and we did not include it in the main text. Interpretation of this result is not straight forward as for instance the substrate of the cells is different and it would require further studies on the behaviour of ERM proteins in these different contexts.

One of the most novel things of the manuscript is the use of a relatively quick photoablation system. I would suggest that the authors add a more extensive description of the protocol in methods. Could this technique be applied in other laboratories? If this is a major limitation, it should be listed in the discussion.

Following the Reviewer's comment, we introduced more detailed explanations regarding the photoablation: - L157-163 (Results): "Briefly, the chosen design is digitalized into a list of positions to ablate. A pulsed UV-LASER beam is injected into the microscope and shaped to cover the back aperture of the objective. The laser is then focused on each position that needs ablation. After introducing endothelial cells (HUVEC) in the carved regions,.." - L512-516 (Discussion): "The speed capabilities drastically improve with the pulsing repetition rate. Given that our laser source emits pulses at 10kHz, as compared to other photoablation lasers with repetitions around 100 Hz, our solution could potentially gain a factor of 100. Also,..." - L1082-1087 (Materials and Methods): "…, and imported in a python code. The control of the various elements is embedded and checked for this specific set of hardware. The code is available upon request."

Adding these three paragraphs gives more details on how photoablation works thus improving the manuscript.

Minor comments:

Supplementary Fig 2. The reference to subpanels H and I is swapped.

The references to subpanels H and I have been correctly swapped back in the reviewed version.

Line 203: I would suggest to delete this sentence. Although a strength of the submitted paper is the direct comparison of the VoC model with the animal model to better replicate Neisseria infection, a direct comparison with animal permeability is not needed in all vascular engineering papers, as vascular permeability measurements in animals have been well established in the past.

The sentence "While previously developed VoC platforms aimed at replicating physiological permeability properties, they often lack direct comparisons with in vivo values." has been removed from the revised text.

Fig 3: Bacteria binding experiments. I would suggest the addition of more methodological information in the main results text to guarantee a good interpretation of the experiment. First, it would be better that wall shear stress rather than flow rate is described in the main text, as flow rate is dependent on the geometry of the vessel being used. Second, how long was the perfusion of Neisseria in the binding experiment performed to quantify colony doubling or elongation? As per figure 1C, I would guess than 100 min, but it would be better if this information is directly given to the readers.

We thank Reviewer #1 for these two suggestions that will improve the text clarity (e.g., L316). (i) Indeed, we have changed the flow rate in terms of shear stress. (ii) Also, we have normalized the quantification of the colony doubling time according to the first time-point where a single bacteria is attached to the vessel wall. Thus, early adhesion bacteria will be defined by a longer curve while late adhesion bacteria by a shorter curve. In total, the experiment lasted for 3 hours (modifications appear in L318 and L321-326).}

Fig 4: The honeycomb structure is not visible in the 3D rendering of panel D. I would recommend to show the actin staining in the absence of Neisseria staining as well.

According to this suggestion, a zoom of the 3D rendering of the cortical plaque without colony had been added to the figure 4 of the revised manuscript.

Line 421: E-selectin is referred as CD62E in this sentence. I would suggest to use the same terminology everywhere.

We have replaced the "CD62E" term with "E-selectin" to improve clarity.}

Line 508: "This difference is most likely associated with the presence of other cell types in the in vivo tissues and the onset of intravascular coagulation". Do the authors refer to the presence of perivascular cells, pericytes or fibroblasts? If so, it could be good to mention them, as well as those future iterations of the model could include the presence of these cell types.

By "other cell types", we refer to pericytes [3], fibroblasts [4], and perivascular macrophages [5], which surround endothelial cells and contribute to vessel stability. The main text was modified to include this information (Lines 548 and 555-570) and their potential roles during infection disussed.

Discussion: The discussion covers very well the advantages of the model over in vitro 2D endothelial models and the animal xenograft but fails to include limitations. This would include the choice of HUVEC cells, an umbilical vein cell line to study microcirculation, the lack of perivascular cells or limitations on the fabrication technique regarding application in other labs (if any).

We thank Reviewer #1 for this suggestion. Indeed, our manuscript may lack explaining limitations, and adding them to the text will help improve it: - The perspectives of our model include introducing perivascular cells surrounding the vessel and fibroblasts into the collagen gel as discussed previously and added in the discussion part (L555-570). - Our choice for HUVEC cells focused on recapitulating the characteristics of venules that respect key features such as the overexpression of CD62E and adhesion of neutrophils during inflammation. Using microvascular endothelial cells originating from different tissues would be very interesting. This possibility is now mentioned in the discussion lines 567-568. - Photoablation is a homemade fabrication technique that can be implemented in any lab harboring an epifluorescence microscope. This method has been more detailed in the revised manuscript (L1085-1087).

Line 576: The authors state that the model could be applied to other systemic infections but failed to mention that some infections have already been modelled in 3D bioengineered vascular models (examples found in https://doi.org/10.1038/s41564-024-01645-6). This includes a capillary photoablated vascular model to study malaria (DOI: 10.1126/sciadv.aay724).

Thes two important references have been introduced in the main text (L84, 647, 648).}

Line 1213: Are the 6M neutrophil solution in 10ul under flow. Also, I would suggest to rewrite this sentence in the following line "After, the flow has been then added to the system at 0.7-1 μl/min."

We now specified that neutrophils are circulated in the chip under flow conditions, lines 1321-1322.

Significance

The manuscript is comprehensive, complete and represents the first bioengineered model of sepsis. One of the major strengths is the carful characterization and benchmarking against the animal xenograft model. Its main limitations is the brief description of the photoablation methodology and more clarity is needed in the description of bacteria perfusion experiments, given their complexity. The manuscript will be of interest for the general infection community and to the tissue engineering community if more details on fabrication methods are included. My expertise is on infection bioengineered models.

Reviewer #2

Evidence, reproducibility, and clarity

Summary The authors develop a Vessel-on-Chip model, which has geometrical and physical properties similar to the murine vessels used in the study of systemic infections. The vessel was created via highly controllable laser photoablation in a collagen matrix, subsequent seeding of human endothelial cells and flow perfusion to induce mechanical cues. This vessel could be infected with Neisseria meningitidis, as a model of systemic infection. In this model, microcolony formation and dynamics, and effects on the host were very similar to those described for the human skin xenograft mouse, which is the current gold standard for these studies, and were consistent with observations made in patients. The model could also recapitulate the neutrophil response upon N. meningitidis systemic infection.

Major comments:

I have no major comments. The claims and the conclusions are supported by the data, the methods are properly presented and the data is analyzed adequately. Furthermore, I would like to propose an optional experiment could improve the manuscript. In the discussion it is stated that the vascular geometry might contribute to bacterial colonization in areas of lower velocity. It would be interesting to recapitulate this experimentally. It is of course optional but it would be of great interest, since this is something that can only be proven in the organ-on-chip (where flow speed can be tuned) and not as much in animal models. Besides, it would increase impact, demonstrating the superiority of the chip in this area rather than proving to be equal to current models.

We have conducted additional experiments on infection in different vascular geometries now added these results figure 3/S3 and lines 288-305. We compared sheared stress levels as determined by Comsol simulation and experimentally determined bacterial adhesion sites. In the conditions used, the range of shear generated by the tested geometries do not appear to change the efficiency of bacterial adhesion. These results are consistent with a previous study from our group which show that in this range of shear stresses the effect on adhesion is limited [6] . Furthermore, qualitative observations in the animal model indicate that bacteria do not have an obvious preference in terms of binding site.

Minor comments:

I have a series of suggestions which, in my opinion, would improve the discussion. They are further elaborated in the following section, in the context of the limitations.

• How to recapitulate the vessels in the context of a specific organ or tissue? If the pathogen is often found in the luminal space of other organs after disseminating from the blood, how can this process be recapitulated with this mode, if at all?

• For reasons that are not fully understood, postmortem histological studies reveal bacteria only inside blood vessels but rarely if ever in the organ parenchyma. The presence of intravascular bacteria could nevertheless alter cells in the tissue parenchyma. The notable exception is the brain where bacteria exit the bacterial lumen to access the cerebrospinal fluid. The chip we describe is fully adapted to develop a blood brain barrier model and more specific organ environments. This implies the addition of more cell types in the hydrogel. A paragraph on this topic has been added (Lines 548 and 552-570).

• Similarly, could other immune responses related to systemic infection be recapitulated? The authors could discuss the potential of including other immune cells that might be found in the interstitial space, for example.

• This important discussion point has been added to the manuscript (L623-636). As suggested by Reviewer #2, other immune cells respond to N. meningitis and can be explored using our model. For instance, macrophages and dendritic cells are activated upon N. meningitis infection, eliminate the bacteria through phagocytosis, produce pro-inflammatory cytokines and chemokines potentially activating lymphocytes [7]. Such an immune response, yet complex, would be interesting to study in our model as skin-xenograft mice are deprived of B and T lymphocytes to ensure acceptance of human skin grafts.

• A minor correction: in line 467 it should probably be "aspects" instead of "aspect", and the authors could consider rephrasing that sentence slightly for increased clarity.

• We have corrected the sentence with "we demonstrated that our VoC strongly replicates key aspects of the in vivo human skin xenograft mouse model, the gold standard for studying meningococcal disease under physiological conditions." in lines 499-503.

  Strengths and limitations

The most important strength of this manuscript is the technology they developed to build this model, which is impressive and very innovative. The Vessel-on-Chip can be tuned to acquire complex shapes and, according to the authors, the process has been optimized to produce models very quickly. This is a great advancement compared with the technologies used to produce other equivalent models. This model proves to be equivalent to the most advanced model used to date, but allows to perform microscopy with higher resolution and ease, which can in turn allow more complex and precise image-based analysis. However, the authors do not seem to present any new mechanistic insights obtained using this model. All the findings obtained in the infection-on-chip demonstrate that the model is equivalent to the human skin xenograft mouse model, and can offer superior resolution for microscopy. However, the advantages of the model do not seem to be exploited to obtain more insights on the pathogenicity mechanisms of N. meningitidis, host-pathogen interactions or potential applications in the discovery of potential treatments. For example, experiments to elucidate the role of certain N. meningiditis genes on infection could enrich the manuscript and prove the superiority of the model. However, I understand these experiments are time-consuming and out of the scope of the current manuscript. In addition, the model lacks the multicellularity that characterizes other similar models. The authors mention that the pathogen can be found in the luminal space of several organs, however, this luminal space has not been recapitulated in the model. Even though this would be a new project, it would be interesting that the authors hypothesize about the possibilities of combining this model with other organ models. The inclusion of circulating neutrophils is a great asset; however it would also be interesting to hypothesize about how to recapitulate other immune responses related to systemic infection.

We thank Reviewer #2 for his/her comment on the strengths and limitations of our work. The difficulty is that our study opens many futur research directions and applications and we hope that the work serves as the basis for many future studies but one can only address a limited set of experiments in a single manuscript. - Experiments investigating the role of N. meningitidis genes require significant optimization of the system. Multiplexing is a potential avenue for future development, which would allow the testing of many mutants. The fast photoablation approach is particularly amenable to such adaptation. - Cells and bacteria inside the chambers could be isolated and analyzed at the transcriptomic level or by flow cytometry. This would imply optimizing a protocol for collecting cells from the device via collagenase digestion, for instance. This type of approach would also benefit from multiplexing to enhance the number of cells. - As mentioned above, the revised manuscript discusses the multicellular capabilities of our model, including the integration of additional immune cells and potential connections to other organ systems. We believe that these approaches are feasible and valuable for studying various aspects of N. meningitidis infection.

Advance

The most important advance of this manuscript is technical: the development of a model that proves to be equivalent to the most complex model used to date to study meningococcal systemic infections. The human skin xenograft mouse model requires complex surgical techniques and has the practical and ethical limitations associated with the use of animals. However, the Infection-on-chip model is completely in vitro, can be produced quickly, and allows to precisely tune the vessel's geometry and to perform higher resolution microscopy. Both models were comparable in terms of the hallmarks defining the disease, suggesting that the presented model can be an effective replacement of the animal use in this area.

Other vessel-on-chip models can recapitulate an endothelial barrier in a tube-like morphology, but do not recapitulate other complex geometries, that are more physiologically relevant and could impact infection (in addition to other non-infectious diseases). However, in the manuscript it is not clear whether the different morphologies are necessary to study or recapitulate N. meningitidis infection, or if the tubular morphologies achieved in other similar models would suffice.

We thank Reviewer #2 for his/her comment, also raised by reviewer 1. To answer this question, we have now infected vessel-on-chips of different geometries, to dissect the impact of flow distribution in N. meningitidis infection (Figures 3 and S3, explained in lines 288-307). In this range of shear stress, we show that bacterial infection is not strongly affected by geometry-induced shear stress variation. These observations are constistent with observations in flow chambers and qualitative observations of human cases and in the xenograft model [6].

Audience

This manuscript might be of interest for a specialized audience focusing on the development of microphysiological models. The technology presented here can be of great interest to researchers whose main area of interest is the endothelium and the blood vessels, for example, researchers on the study of systemic infections, atherosclerosis, angiogenesis, etc. Thus, the tool presented (vessel-on-chip) can have great applications for a broad audience. However, even when the method might be faster and easier to use than other equivalent methods, it could still be difficult to implement in another laboratory, especially if it lacks expertise in bioengineering. Therefore, the method could be more of interest for laboratories with expertise in bioengineering looking to expand or optimize their toolbox. Alternatively, this paper present itself as an opportunity to begin collaborations, since the model could be used to test other pathogen or conditions.

Field of expertise: Infection biology, organ-on-chip, fungal pathogens.

I lack the expertise to evaluate the image-based analysis.

References:

1. Gyohei Egawa, Satoshi Nakamizo, Yohei Natsuaki, Hiromi Doi, Yoshiki Miyachi, and Kenji Kabashima. Intravital analysis of vascular permeability in mice using two-photon microscopy. Scientific Reports, 3(1):1932, Jun 2013. ISSN 2045-2322. doi: 10.1038/srep01932.

2. Valeria Manriquez, Pierre Nivoit, Tomas Urbina, Hebert Echenique-Rivera, Keira Melican, Marie-Paule Fernandez-Gerlinger, Patricia Flamant, Taliah Schmitt, Patrick Bruneval, Dorian Obino, and Guillaume Duménil. Colonization of dermal arterioles by neisseria meningitidis provides a safe haven from neutrophils. Nature Communications, 12(1):4547, Jul 2021. ISSN 2041-1723. doi:10.1038/s41467-021-24797-z.

3. Mats Hellström, Holger Gerhardt, Mattias Kalén, Xuri Li, Ulf Eriksson, Hartwig Wolburg, and Christer Betsholtz. Lack of pericytes leads to endothelial hyperplasia and abnormal vascular morphogenesis. Journal of Cell Biology, 153(3):543–554, Apr 2001. ISSN 0021-9525. doi: 10.1083/jcb.153.3.543.

4. Arsheen M. Rajan, Roger C. Ma, Katrinka M. Kocha, Dan J. Zhang, and Peng Huang. Dual function of perivascular fibroblasts in vascular stabilization in zebrafish. PLOS Genetics, 16(10):1–31, 10 2020. doi: 10.1371/journal.pgen.1008800.

5. Huanhuan He, Julia J. Mack, Esra Güç, Carmen M. Warren, Mario Leonardo Squadrito, Witold W. Kilarski, Caroline Baer, Ryan D. Freshman, Austin I. McDonald, Safiyyah Ziyad, Melody A. Swartz, Michele De Palma, and M. Luisa Iruela-Arispe. Perivascular macrophages limit permeability. Arteriosclerosis, Thrombosis, and Vascular Biology, 36(11):2203–2212, 2016. doi: 10.1161/ATVBAHA. 116.307592.

6. Emilie Mairey, Auguste Genovesio, Emmanuel Donnadieu, Christine Bernard, Francis Jaubert, Elisabeth Pinard, Jacques Seylaz, Jean-Christophe Olivo-Marin, Xavier Nassif, and Guillaume Dumenil. Cerebral microcirculation shear stress levels determine Neisseria meningitidis attachment sites along the blood–brain barrier . Journal of Experimental Medicine, 203(8):1939–1950, 07 2006. ISSN 0022-1007. doi: 10.1084/jem.20060482.

7. Riya Joshi and Sunil D. Saroj. Survival and evasion of neisseria meningitidis from macrophages. Medicine in Microecology, 17:100087, 2023. ISSN 2590-0978. doi: https://doi.org/10.1016/j.medmic.2023.100087.

test after? still no TDD, what a shame

the key word is 'obviously' here.

Isaac Ch. 25/05 - Engaged, No-code platform SaaS

synthèse détaillée basée sur les extraits fournis de la conférence de Nathalie Bajos avec Camille Lance :

NOTE DE SYNTHÈSE : La production sociale des inégalités de santé (8) - Nathalie Bajos avec Camille Lance

Intervenant(e)s : Nathalie Bajos (modératrice, charte de santé publique), Camille Lance (sociologue, spécialiste des inégalités sociales en matière de santé mentale)

Date de la présentation : Année universitaire 2024-2025

Objet : Réflexion sur la production sociale des inégalités de santé, en particulier en matière de santé mentale en prison, à travers l'exemple des transformations institutionnelles.

Points clés :

La "Prison Asile" : Un Concept pour Décrire une Réalité Pénitentiaire L'expression "prison asile" s'est imposée autour des années 2000 en France pour décrire l'augmentation significative du nombre de personnes présentant des troubles psychiatriques en prison. Des rapports parlementaires (Sénat et Assemblée nationale, 2000) ont souligné ce phénomène, parlant d'une population pénale en mutation conférant à la prison "une vocation asilaire que l'hôpital psychiatrique n'a plus". Ce constat ébranle le principe historique de séparation entre la prison (pour les condamnés/prévenus) et la psychiatrie (pour les aliénés), tel qu'énoncé par la loi de 1838. Des études épidémiologiques rigoureuses confirment la prévalence très élevée des troubles psychiatriques (humeur, anxiété, stress post-traumatique, psychotiques, usage de substances) en population carcérale par rapport à la population générale du même âge et sexe. Les prévalences sont "toujours supérieures et parfois très supérieures". L'étude du professeur Falissard (2006) estime qu'environ 36% des personnes détenues présentent un trouble de gravité marquée à sévère. Ces chiffres sont cohérents avec les études internationales. Cette réalité nourrit l'impression chez les professionnels que la prison est devenue "le dernier asile" et qu'une partie des personnes incarcérées n'y auraient "pas leur place". Transformations Institutionnelles à la Croisée de l'État Social et de l'État Pénal Les prisons se situent au carrefour de transformations multiples, loin d'être le fruit d'une unique rationalité étatique, qui produisent deux processus combinés : Un processus de responsabilisation des personnes avec des troubles psychiatriques :Déshospitalisation de la psychiatrie publique : Depuis les années 1960, la psychiatrie publique a connu une diminution importante du nombre de lits et la multiplication de structures extrahospitalières. Cependant, ce tournant ambulatoire inachevé rend les trajectoires des patients plus dépendantes de leurs ressources propres (financières, familiales, sociales). La psychiatrie est questionnée sur sa capacité à ne pas "abandonner sans filer les malades mentaux dans la société de la précarité". Évolution du regard des tribunaux : Si au 19ème siècle, les troubles mentaux (démence) exemptaient de prison (article 64 du code pénal), le regard a évolué. Les troubles psychiatriques "exemptent de moins en moins de prison les personnes qui en souffrent". Des travaux montrent que "Les malades qui se soignent sont protégés de la prison tandis que les malades qui ne se soignent pas ils sont plus souvent directement conduits". Inflation carcérale : La population carcérale a explosé en France, passant d'environ 29 000 en 1970 à plus de 80 000 aujourd'hui. Ce quasi-triplement est dû à l'allongement des longues peines et l'accélération des courtes peines (comparution immédiate), où les troubles psychiatriques passent souvent inaperçus. Cette "nasse carcérale" capture de nombreux hommes (96,5% de la population carcérale) et femmes avec des troubles, les prenant dans un cercle vicieux de "portes tournantes de la prison" (revolving doors) entre courts séjours et précarité. Ce phénomène est encore plus marqué aux États-Unis. Développement des soins psychiatriques en prison : L'existence, bien que limitée, d'une offre de soins psychiatriques organisée par le service public hospitalier en prison (consultations, hospitalisation de jour, unités d'hospitalisation complète) devient "une justification de plus en plus invoquée par certains magistrats à l'heure de prononcer une peine de prison avec l'argument qu'il ou elle y trouvera des soins adaptés". Un processus de psychologisation des personnes qui ont commis des infractions pénales :La peine comme moyen de "traiter" le crime : Dès le 19ème siècle, le projet de la prison moderne inclut l'idée de "méthode curative" pour "traiter le crime comme les autres espèces de folie". Cette ambition thérapeutique persiste, reposant sur le postulat que le délinquant/criminel souffre d'une "folie partielle", "dégénérescence", "altération morale", ou "trouble de la personnalité ou du comportement". Généralisation de la psychologisation des rapports sociaux : Cette ambition s'inscrit aujourd'hui dans un mouvement plus large de psychologisation de la société. Soins pénalement ordonnés : Des dispositifs tels que les soins pénalement ordonnés (étudiés par Virginie Gautron) obligent des personnes (initialement auteurs d'infractions sexuelles, puis violences aggravées, terrorisme) à un suivi psychiatrique/psychothérapeutique après leur peine. Le soin devient un "auxiliaire de la peine", une façon de garder les individus "sous main de justice" et potentiellement justifier un retour en prison. Cette logique est devenue "presque un automatisme pour les juges d'application des peines". Injonction à se soigner en prison : Ce processus crée en prison une "injonction permanente" aux condamnés, même sans diagnostic, à "entreprendre des soins" avec l'idée que la détention devrait être "un temps de traitement". Des programmes de prévention de la récidive se développent. Résistances professionnelles : Ce projet psychocriminologique rencontre des résistances, notamment de la part des conseillers pénitentiaires d'insertion et de probation (CPIP), dont la mission s'est judiciarisée, et des équipes psychiatriques hospitalières qui ont le sentiment d'être "enrôlées malgré eux dans une mission de contrôle pénal" et voient leur file active de patients augmenter. Ces deux processus modifient la composition de la population pénale et le regard porté sur elle. Une Institution Fragmentée : L'Illustration du Cas de Monsieur Cadar Contrairement à l'idée d'une hybridation harmonieuse ("Le vilain métier de punir serait ainsi retourné dans le beau métier de guérir", Foucault), la prison est une institution fragmentée où les logiques institutionnelles se superposent plus qu'elles ne s'articulent. Le cas de Monsieur Cadar, un homme en état de "décompensation psychotique" agressant un surveillant, illustre cette superposition dramatique : Il est hospitalisé sans consentement (incapable de consentir aux soins). Il est sanctionné disciplinairement (détenu violent à punir). Il est condamné pénalement (justiciable devant répondre de ses actes). Cette vignette montre comment différentes logiques (sanitaire, disciplinaire, judiciaire) s'appliquent à une même personne, parfois de manière contradictoire. La Composition Sociale de la Population Carcérale et les Inégalités de Santé "Il n'y a pas d'égalité devant la prison". L'incarcération procède d'une "sélection sociale", déterminée par les politiques pénales et l'activité de la chaîne pénale et médico-sociale. Les statistiques pénitentiaires montrent une composition très spécifique : hommes (96,5%), jeunes (moitié < 30 ans), d'origine populaire, issus des minorités racisées, forte représentation d'étrangers, souvent sans diplôme ni emploi officiel. Les chiffres de l'étude de Camille Lance montrent que 75% des hommes détenus ont subi des formes de négligence ou d'abus dans l'enfance (85% des femmes). Ce sont "certains individus" qui sont pris dans les "parcours de soins entre prison, précarité et psychiatrie". Ce "cercle vicieux" est difficile à briser, comme l'illustre le cas de Boris, un homme pris dans des allers-retours entre prison et tentatives de suivi psychiatrique/social. Dialogue entre Épidémiologie et Sociologie : Questions Soulevées par les Chiffres L'étude sur la santé mentale des sortants de prison, à laquelle Camille Lance a participé en tant que chef de projet, est "très psychiatrique, très médicale". Ses chiffres sont "révélateur[s] de la position qu'occupe[nt] les psychiatres qui l'ont mené". Ils "ne sont pas neutres". Ces chiffres : "Ne disent rien des associations possibles entre troubles psychiatriques et motifs d'incarcération". "N'explore[nt] d'ailleurs pas les possibles troubles de la personnalité ou du comportement qui pourrait être associé à des infractions sanctionnées d'une peine de prison". "Prennent position qui refusent de participer au processus de psychologisation des auteurs d'infraction pénale". "Suggèrent une stricte délimitation médicale du mandat de la psychiatrie en milieu pénitentiaire". Proposent de "porter le regard sur la sortie de prison" (moment de forte surmortalité) pour "visibiliser voire même de construire un problème de santé publique" et convaincre les autorités d'investir (équipes mobiles, mobilisation de la psychiatrie publique extérieure). La sociologie peut venir "étouffer" cette mesure épidémiologique en soulevant des questions : Place et rôle de la prison dans l'émergence des troubles : Les troubles préexistent-ils ou sont-ils produits/attisés par la détention ? Il faut penser l'articulation entre souffrance psychique et expérience carcérale. Les travaux d'Alexis Van Nasbrook sur les suicides en prison (risque 10x supérieur chez les hommes, 40x chez les femmes) montrent le rôle précipitant des événements carcéraux (quartier disciplinaire x20, première semaine x7, annonce condamnation, transfert). Il faut compléter en réfléchissant à la construction des "carrières de malades" en prison, façonnée par des facteurs sociaux et institutionnels. Existence des troubles mesurés pour les personnes concernées : Les chiffres épidémiologiques reposent sur des questionnaires structurés basés sur des classifications (DSM/CIM) et des comptages de symptômes ("objectivation statistique"). Ils "ne dit rien des subjectivités", des "réalités vécues", des troubles tels qu'ils sont vécus. La question est de savoir si "Les troubles mesurés existent-ils toujours pour les personnes concernées ?". Compte tenu du profil social des détenus (hommes jeunes, faiblement diplômés, classes populaires) ayant une "certaine distance aux soins de santé mentale", il existe une "très grande hétérogénéité des usages sociaux de la santé mentale en prison". Certains refusent les soins/contestent la pathologisation, rejetant la stigmatisation. D'autres saisissent l'offre pour se raconter, comprendre, trouver du réconfort. Il est important d'explorer les "masculinités des groupes populaires" face à la santé mentale dans un contexte (la prison) de "tension constante entre une incitation à se soigner (...) et une pénurie de soin". Conclusion : L'Intérêt du Dialogue Épidémiologie-Sociologie La recherche sur les inégalités de santé a "beaucoup à gagner du dialogue entre épidémiologie et sociologie". Ce dialogue prend du temps et doit se faire dans le "respect mutuel des cadres épistémologiques de chaque discipline". Ensemble, ces disciplines peuvent "décrire ces inégalités mais également de tenter de les expliquer", ce qui est une tâche complexe. Citations clés :

"La prison pour asile" "une vocation asilaire que l'hôpital psychiatrique n'a plus" (rapports parlementaires) Prévalences en prison "toujours supérieures et parfois très supérieures" à la population générale. Psychiatrie questionnée sur sa capacité à "ne pas abandonner sans filer les malades mentaux dans la société de la précarité". "Les malades qui se soignent sont protégés de la prison tandis que les malades qui ne se soignent pas ils sont plus souvent directement conduits" (La Ramaï). "portes tournantes de la prison" (revolving doors) Soins en prison : "une justification de plus en plus invoquée par certains magistrats à l'heure de prononcer une peine de prison avec l'argument qu'il ou elle y trouvera des soins adaptés". "Le vilain métier de punir serait ainsi retourné dans le beau métier de guérir." (Foucault) "Il n'y a pas d'égalité devant la prison" (Didier Fassin) "une injonction permanente (...) à entreprendre des soins avec l'idée que la détention devrait être (...) un temps de traitement". Chiffres épidémiologiques : "Ces chiffres par exemple ne disent rien des associations possibles entre troubles psychiatriques et motifs d'incarcération". Objectivation statistique vs subjectivités : "Les troubles mesurés existent-ils toujours pour les personnes concernées ?". "une très grande hétérogénéité des usages sociaux de la santé mentale en prison". "une tension constante entre une incitation à se soigner (...) et une pénurie de soin". "la recherche sur les inégalités de santé a beaucoup pas gagner du dialogue entre épidémiologie et sociologie". Implications / Perspectives :

La compréhension de la santé mentale en prison nécessite une approche interdisciplinaire (épidémiologie, sociologie, psychiatrie, histoire, droit). Les transformations institutionnelles de l'État social et pénal ont des conséquences directes sur la population carcérale et la santé mentale. La sélection sociale en amont de l'incarcération est un facteur déterminant des inégalités de santé observées en prison. Les chiffres épidémiologiques, bien qu'utiles pour documenter la prévalence, ne suffisent pas à expliquer la complexité des expériences vécues et l'interaction entre santé mentale et contexte carcéral. La sociologie peut éclairer les parcours individuels, l'impact des conditions de détention et les usages sociaux des soins en milieu carcéral. La collaboration entre chercheurs et professionnels de différents champs est essentielle pour aborder la problématique des inégalités de santé en prison.

NOTE D'INFORMATION

Objet : Analyse des enjeux et des défis de l'orientation au collège et au lycée en France, selon un rapport de la Cour des comptes et les réponses du Ministère de l'Éducation nationale et de l'Association Régions de France.

Date : 19 mars 2025

Sources :

Excerpts from "https://www.ccomptes.fr/sites/default/files/2025-03/20250319-RPA2025-volume1-orientation-college-lycee.pdf"

1. Introduction : L'orientation au cœur du système éducatif – Enjeux et Contexte

L'orientation des élèves au collège et au lycée est un processus essentiel qui les guide à travers leur parcours scolaire et vers l'insertion professionnelle.

Ce processus est décrit comme un "cheminement qui court sur plusieurs années".

Les moyens publics consacrés à cette politique sont estimés à environ 400 M€ et 8 000 équivalents temps-plein.

Les enjeux de l'orientation sont considérables, tant au niveau individuel que collectif. Ils visent à garantir l'équité, en dépassant les déterminismes sociaux, de genre et territoriaux, et à répondre aux besoins en compétences du marché de l'emploi et de la société.

La loi du 5 septembre 2018 a établi une compétence partagée sur l'information à l'orientation entre les régions académiques et les régions, entraînant une réorganisation de l'Onisep.

Cependant, la loi "ne permet pas d’aboutir à une situation claire". Une "multitude d’acteurs, publics et privés, ont émergé et jouent un rôle croissant".

Les jeunes et leurs parents se sentent souvent "en manque de repères face à une offre de formation foisonnante, aux règles du jeu opaques et instables".

Un sondage de mai 2024 par la Cour indique que 35 % des collégiens et 25 % des lycéens se disent insatisfaits des informations et conseils reçus. De plus, près de 20 % des bacheliers qui poursuivent leurs études regrettent leur choix d'inscription.

2. Déterminismes et Inégalités dans l'Orientation

Le processus d'orientation est fortement influencé par les résultats scolaires, l'image sociale des filières et l'offre de formation.

Déterminismes sociaux et territoriaux : L'orientation "tend donc plutôt à amplifier le déterminisme social". Après la classe de troisième, près d'un tiers des élèves (32% en 2022) rejoignent la voie professionnelle.

Les élèves issus de milieux peu favorisés sont davantage représentés dans les lycées professionnels.

"À notes équivalentes, les familles de milieux défavorisés font beaucoup moins souvent des choix d’orientation vers la seconde générale et technologique" et les décisions des équipes éducatives peuvent être influencées par le contexte social de l'élève.

Le lieu de résidence joue également un rôle, notamment pour les élèves en zone rurale éloignée où la voie professionnelle est plus souvent choisie en raison de difficultés de mobilité et d'un attachement au marché du travail local.

Le dispositif des Cordées de la réussite, bien que non évalué de manière exhaustive, semble avoir un impact positif sur le taux de proposition d'admission dans Parcoursup pour les élèves participants.

Déterminismes de genre : Les choix d'orientation "restent très genrés à tous les niveaux de formation". Les parents jouent un rôle majeur dans cette reproduction sociale.

Malgré des actions visant à sensibiliser et à lutter contre les stéréotypes, la mixité nécessite "une action concertée et continue de l’enseignement supérieur et du monde du travail dans les secteurs traditionnellement très genrés".

3. La Valorisation des Enseignements Professionnels et Technologiques

Un objectif prioritaire du gouvernement est de "Refonder l’orientation des élèves", en mesurant le nombre de métiers connus en fin de troisième et le taux d'élèves ayant bénéficié de la découverte des métiers.

La découverte des métiers est généralisée "dans toute la mesure du possible" dans tous les collèges depuis la rentrée 2023.

La part des élèves en voie professionnelle a diminué globalement (de 38% en 2007 à 32% en 2022), mais les demandes des familles pour cette voie ont augmenté récemment (de 32,5% en 2020 à 36,2% en 2024), témoignant d'une "réels progrès dans la valorisation de la voie professionnelle".

Cependant, le secteur industriel souffre encore d'un "déficit d’image".

La coexistence des voies professionnelle et technologique, avec une "image de relégation attachée à la voie professionnelle auprès des familles et des enseignants", contribue à ce sentiment.

Un rapprochement entre ces voies est suggéré, comme le modèle suisse où la filière professionnelle est "fortement valorisée" et suivie par 70 % des élèves, incluant les enfants de cadres.

4. L'Accompagnement à l'Orientation : Un Besoin Insatisfait

Il existe un "important besoin d’accompagnement à l’orientation insatisfait" qui a conduit à l'émergence d'une "multitude d’intervenants".

Les lycéens s'informent principalement via les forums/salons de l'étudiant (41%), les journées portes ouvertes/immersions dans les établissements d'enseignement supérieur (38%) et le site de l'Onisep (36%).

Le marché privé du conseil en orientation se développe en réponse à ce besoin, "accroissant en retour les inégalités entre les jeunes".

5. L'Organisation et les Moyens de l'Orientation dans les Établissements Scolaires

Le corps des psychologues de l'éducation nationale (psyEN), remplaçant les conseillers d'orientation-psychologues, s'est recentré sur le suivi psychologique des élèves.

Le ratio d'élèves par psyEN est de 1 147 élèves par psychologue de l’Éducation nationale, ne permettant pas une action individualisée.

Le transfert des missions des psyEN vers les régions est jugé "peu praticable, à l’heure actuelle".

La mission d'éducation à l'orientation, confiée aux enseignants, est "insuffisamment accompagnée".

Bien que l'orientation fasse partie de leur référentiel de compétences, les maquettes de formation initiale ne comportent pas de "formation obligatoire sur ce sujet".

Les heures d'accompagnement à l'orientation prévues au collège et au lycée général et technologique ne sont pas des "moyens fléchés" et sont perçues comme "non financées et non obligatoires".

La Cour estime le besoin de financement complémentaire pour sécuriser ces heures à entre 134 M€ et 309 M€ selon les modalités.

Deux outils sont en développement pour appuyer les enseignants : le programme Avenir(s) de l'Onisep (doté de 20 M€ sur 10 ans) qui vise à structurer l'outillage pédagogique et à créer un portfolio pour les élèves, et le module MonProjetSup (développé par le ministère de l'enseignement supérieur en lien avec l'Onisep) pour aider les lycéens à préparer leurs vœux dans Parcoursup.

L'absence de transparence des critères de décision dans Parcoursup est soulignée comme une difficulté.

6. La Répartition des Compétences entre l'État et les Régions

La répartition actuelle des compétences entre l'État et les régions "prête à confusion".

Les régions ont la responsabilité de la coordination et de l'animation de l'orientation tout au long de la vie pour les adultes, mais leur compétence pour les publics scolaires, étudiants et apprentis se limite à "l'information sur les métiers et les formations".

La phrase de la loi "la région organise des actions d’information", et non "les actions d’information", est jugée limitée.

Les régions revendiquent un "transfert plein et entier de la compétence « orientation »", mais contestent l'analyse de la Cour selon laquelle cela impliquerait de leur confier les décisions d'orientation et d'affectation.

Elles estiment que ces décisions relèvent de l'Éducation nationale.

La profusion de sites d'information et d'orientation (avec des exemples de sites publics et privés) illustre cette complexité.

Le développement de la plateforme Avenir(s) par l'Onisep est perçu par les régions comme faisant "doublon avec la compétence régionale sur l’information métiers" et rendant "invisibles les sites que toutes les régions ont développés".

Les régions demandent une clarification en remplaçant "des actions" par "les actions" dans le code du travail et un transfert global des missions et moyens nécessaires.

L'enveloppe actuelle de 8 M€ transférée aux régions pour l'information territorialisée est jugée "très insuffisante" au regard de leur engagement réel (plus de 170 M€ en 2024).

La mise en synergie des nombreuses structures accueillant les jeunes (CIO, bureaux Information Jeunesse, missions locales, structures régionales, chambres consulaires) est nécessaire pour améliorer l'efficience et la lisibilité pour le public.

Le "bassin d’éducation et de formation apparaît comme le niveau pertinent pour que les acteurs se connaissent et travaillent de manière harmonisée".

7. La Transformation de l'Offre de Formation Professionnelle

L'offre de formation "détermine pour une large part l’orientation des jeunes".

Les taux d'emploi à six mois des diplômés du baccalauréat professionnel (48%) et du CAP (33%) sont relativement bas (mais plus élevés que pour les bacheliers généraux ou technologiques n'ayant pas poursuivi d'études supérieures).

L'application Inserjeunes vise à fournir des informations sur les taux de poursuite d'études et d'insertion.

La "transformation indispensable de l'offre de formation professionnelle" est une priorité pour une meilleure insertion des jeunes en lien avec les besoins des territoires.

L'affectation dépend des capacités disponibles, et 25% à 30% des élèves n’obtiennent pas leur premier vœu, ce qui "peut renforcer le sentiment d’orientation subie".

La baisse prévue des effectifs de lycéens à partir de 2028 offre une "opportunité de conduire cette transformation".

Les campus des métiers et des qualifications sont un exemple d'articulation entre offre de formation et orientation, mais leur impact est variable.

8. Conclusions et Recommandations de la Cour des Comptes

Malgré les efforts, l'orientation reste marquée par de forts déterminismes sociaux, territoriaux et de genre.

L'éducation à l'orientation au collège est difficile à mettre en place en raison du manque de formation des enseignants et de l'absence de moyens fléchés pour les heures dédiées.

La répartition des compétences entre l'État et les régions doit être clarifiée, et une meilleure articulation locale des acteurs est nécessaire.

L'orientation est indissociable de l'offre de formation professionnelle, qui doit s'adapter aux besoins locaux.

La Cour formule les recommandations suivantes :

• Insérer dans les maquettes de formation initiale des enseignants un module obligatoire sur la compétence orientation.
• Adapter l'emploi du temps des professeurs principaux ou référents pour leur permettre d'assurer leur mission d'orientation.
• Expérimenter avec une ou plusieurs régions volontaires un rapprochement entre les voies du lycée, professionnelle, technologique et générale.

9. Réponses et Perspectives

Le Ministère de l'Éducation nationale signale qu'une concertation nationale sur l'orientation est en cours (novembre 2024 - mars 2025) pour "faire de la politique d’orientation un levier de réussite et d’égalité des chances".

Il souligne l'importance du programme Avenir(s) pour créer un "service public national, gratuit, exhaustif et égalitaire de l’orientation".

Concernant la recommandation 1, le ministère indique que la compétence d'orientation est déjà incluse dans le référentiel de formation des enseignants et que la réforme de la formation initiale permettra de réfléchir à l'évolution des contenus.

Il souligne également l'effort en matière de formation continue sur l'orientation (50 294 journées en 2023-2024).

Concernant la recommandation 2, le ministère ne prévoit pas de quantifier le volume horaire de la mission d'orientation pour éviter la rigidité et ne pas nuire à la mission de coordination.

Il précise que le dispositif actuel permet l'intervention de divers personnels et que tous les professeurs ont un rôle en matière d'orientation.

Concernant la recommandation 3, le ministère y voit un intérêt pour une perspective décloisonnée et travaillera en articulation avec l'enseignement supérieur.

Le ministère mentionne également une expérimentation d'"option santé" dans les lycées de déserts médicaux pour lutter contre les déterminismes territoriaux.

Il précise que MonProjetSup est intégré à Avenir(s) et vise à fournir des suggestions personnalisées basées sur les données de Parcoursup.

Il rappelle le rôle des psyEN en matière d'orientation, malgré une charge de travail accrue sur d'autres missions.

Régions de France partage le constat de la confusion des compétences et le manque de repères pour les jeunes et les parents.

Elles souscrivent aux objectifs de lutte contre les déterminismes et de valorisation des métiers.

Elles partagent aussi le constat de l'émergence des acteurs privés.

Cependant, elles contestent l'idée que leur demande de compétence pleine et entière implique de prendre les décisions d'orientation et d'affectation, qui relèvent selon elles de l'Éducation nationale.

Elles demandent une clarification législative en remplaçant "des actions" par "les actions" dans le code du travail.

Elles voient la plateforme Avenir(s) comme un doublon.

Elles réclament un transfert global des missions et moyens nécessaires, incluant les équipes des directions territoriales ONISEP et les directeurs de CIO, et jugent l'enveloppe actuelle transférée pour l'information "très insuffisante".

Elles soulignent que les moyens dédiés aux CIO diminuent et que les psyEN se concentrent davantage sur le suivi psychosocial, déportant l'accompagnement de l'affectation vers les régions sans moyens additionnels.

Régions de France souhaite que le rapport de la Cour contribue à une clarification de la compétence et regrette l'absence de recommandation sur ce sujet.

Elles souscrivent à l'expérimentation de rapprochement des voies au lycée et partagent le constat de l'inadéquation entre orientation et besoins réels des territoires.

En synthèse, les points clés à retenir sont :

Le système d'orientation actuel est complexe, coûteux, et manque de clarté, entraînant une insatisfaction chez les jeunes et leurs parents.

L'orientation est fortement marquée par les déterminismes sociaux, de genre et territoriaux, avec un besoin de renforcer l'équité.

La valorisation de la voie professionnelle est un enjeu majeur, avec un modèle comme la Suisse cité en exemple.

Le besoin d'accompagnement à l'orientation est important mais insuffisamment satisfait par le système éducatif public, favorisant l'émergence d'acteurs privés et l'accroissement des inégalités.

La formation des enseignants à l'orientation est jugée insuffisante.

Les heures dédiées à l'orientation dans les établissements manquent de moyens fléchés et ne sont pas toujours concrétisées.

La répartition des compétences entre l'État et les régions est source de confusion, et les régions réclament une compétence pleine et entière sur l'information et l'orientation métiers, mais pas sur les décisions d'affectation.

La profusion d'outils et de structures d'information et d'orientation nécessite une meilleure synergie et lisibilité locale.

L'offre de formation professionnelle doit être transformée pour mieux s'adapter aux besoins locaux et offrir des parcours d'insertion réussie.

Des expérimentations, comme le rapprochement des voies au lycée et l'option santé, sont des pistes explorées pour améliorer le système.

Cette note d'information résume les principaux éléments et les divergences de points de vue entre les acteurs sur la manière d'améliorer l'orientation des jeunes en France.

I don't know if this was mentioned in previous chapters but on windows I actually needed to install ounit2 with opam first...

The modern incarnation of the fallacy of bulk-is-better is judging the quality of a project (esp. a component) by being overly concerned with whether it is more or less "active" than some other project.

The question posed here is an obvious response for when you encounter instances of the bulk-is-better mindset (although it's not as easy to automate as Cox suggests here).

I've often mused about the thought of pulling a Reddit* and automating some level of churn within a codebase for a project that's hosted on e.g. GitHub for the sole purpose of making sure that it appears "active".

* A story about the early days of Reddit has become well-known after the creators volunteered some information about the early days when they made use of a bunch of "fake" accounts to submit links that the creators had aggregated/curated for the purpose of seeding the site.

It's strange that this basic truth is something that has to be taught/explained. It indicates a failure in analytical thinking, esp. regarding those parts of the question which the quoted passage is supposed to be a response to.

added boilerplate code

check other version of openAI

Reproduced the bug

reviewed the code

asked for code review

IMPLEMENTATION

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 reviewer for their constructive comments and the fair and interesting discussion between reviewers.

__Reviewer #1 __

We are delighted to read that the reviewer finds the manuscript “very clear and of immediate impact […] and ready for publication” regarding this aspect. We have toned down the conclusion, proposing rather than concluding that “the incapacitation of Cmg2[KO] intestinal stem cells to function properly […] is due to their inability to transduce Wnt signals”.

We have addressed the 3 points that were raised as well as the minor comments.

Point #1

The mouse mutant is just described as 'KO', referring to the previous work by the authors. The cited work simply states that this is a zygotic deletion of exon 3, which somehow leads to a decrease in protein abundance that is almost total in the lung but not so clear in the uterus. Exon 3 happens to be 72 bp long [https://www.ncbi.nlm.nih.gov/nuccore/NM_133738], so its deletion (assuming there are no cryptic splicing sites used) leads to an internal in-frame deletion of 24 amino acids. So, at best, this 'KO' is not a null, but a hypomorphic allele of context-dependent strength.

Unfortunately, neither the previous work nor this paper (unless I have missed it!) contains information provided about the expression levels of Cmg2 in the intestine of KO mice - nor which cell types usually express it (see below). I think that using anti Cmg2 in WB and immunohistofluorescence of with ISC markers with intestine homogenate/sections of wild-type and mutant mice would be necessary to set the stage for the rest of the work.

We now provide and explanation and characterization the Cmg2KO mice. Exon 3 indeed only encodes a short 24 amino acid sequence. This exon however encodes a ß-strand that is central to the vWA domain of CMG2, and therefore critical for the folding of this domain. As now shown in Fig. S1c, CMG2Dexon3 is produced in cells but cleared by the ER associated degradation pathway, therefore it is only detectable in cells treated with the proteasome inhibitor MG132, at a slightly lower molecular weight than the full-length protein. This is consistent, and was inspired by the fact that multiple Hyaline Fibromatosis missense mutations that map to the vWA domain lead to defective folding of CMG2, further illustrating that this domain is very vulnerable to modifications. In Fig. S1c, we moreover now show immunoprecipitation of Cmg2 from colonic tissue of wild-type (WT) and knockout (KO) mice, which confirm the absence of Cmg2 protein in Cmg2KO samples.

Point #2

Connected to the previous point, the expression pattern of Cmg2 in the intestine is not described. Maybe this is already established in the literature, but the authors do not refer to the data. This is important when considering that the previous work of the authors suggests that Cmg2 might contribute to Wnt signalling transduction through physical, cis interactions with the Wnt co-receptor LRP6. Therefore, one would expect that Cmg2 would be cell-autonomously required in the intestinal stem cells.

The expression pattern of Cmg2 in the gut has not been characterized and is indeed essential to understanding its function. To address this gap, we now added a figure (Fig. 1) providing data from publicly available RNA-seq datasets and from our RNAscope experiments on Cmg2WT mice. Of note, we unfortunately have never managed to detect Cmg2 protein expression by immunohistochemistry of mouse tissue with any of the antibodies available, commercial or generated in the lab.

In the RESULTS section we now mention:

To investigate Cmg2 expression in the gut, we first analyzed publicly available spatial and scRNA-seq datasets to identify which cell types express Cmg2 across different gut regions. Spatial transcriptomic data from the mouse small intestine and colon revealed that Cmg2 is broadly expressed throughout the gut, including in the muscular, crypt, and epithelial layers (Fig. 1A–C). To validate these findings, we performed RNAscope in situ hybridization targeting Cmg2 in the duodenum and colon of wild-type mice. The expression pattern observed was consistent with the spatial transcriptomics data (Fig. 1D–E). We then analyzed scRNA-seq data from the same dataset to assess cell-type-specific expression in the mouse colon. Cmg2 was detected at varying levels across multiple cell types, including enterocytes and intestinal stem cells, as well as mesenchymal cells, notably fibroblasts.

Of note for the reviewer, not mentioned in the manuscript, this wide-spread distribution of Cmg2 across the different cell types is not true for all organs. We have recently investigated the expression of Cmg2 in muscle and found that it is almost exclusively expressed in fibroblasts (so-called fibro-adipocyte progenitors) and very little in any other muscle cells, in particular fibers.

Interestingly also, as now mentioned in the manuscript and shown in Fig. S1,the ANTXR1 protein, which is highly homologous to Cmg2 at the protein level and share its function of anthrax toxin receptor, displayed a much more restricted expression pattern, being confined primarily to fibroblasts and mural cells, and notably absent from epithelial cells. This differential expression highlights a potentially unique and epithelial-specific role for Cmg2 in maintaining intestinal homeostasis.

Point #3

The authors establish that the regenerating crypts of Cmg2[KO] mice are unable to transduce Wnt signalling, but it is not clear whether this situation is provoked by the DSS-induce injury or existed all along. Can Cmg2[KO] intestinal stem cells transduce Wnt signalling before the DSS challenge? If they were, it might suggest that the 'context-dependence' of the Cmg2 role in Wnt signalling is contextual not only because of the tissue, but because of the history of the tissue or its present structure. It would also suggest that Cmg2 mutant mice, unless reared in a germ-free facility for life, would eventually lose intestinal homeostasis, and maybe suggest the level of intervention/monitoring that HFS patients would require. It might also provide an explanation in case Cmg2 was not expressed in ISCs - if the state of the tissue was as important as the presence of the protein, then the effect on Wnt transduction could be indirect and therefore it might not be required cell-autonomously.

We agree that understanding whether Cmg2KO intestinal stem cells are intrinsically unable to transduce Wnt signals, or whether this defect is contextually induced following injury (such as DSS treatment), is a critical point.

As a first line of evidence, we show than under homeostatic condition, Wnt signaling appears largely intact in Cmg2KO crypts, with comparable levels of ß-catenin and expression levels of canonical Wnt target genes (e.g., Axin2, Lgr5) to those observed in WT animals (Figs. S1j-l and S3d-e). This indicates that Cmg2 is not essential for basal Wnt signaling under steady-state conditions.

These findings thus support the idea that the requirement for Cmg2 in Wnt signal transduction is context-dependent—not only at the tissue level but also temporally, being specifically required during regenerative processes or in altered microenvironments such as during inflammation or epithelial damage. This context-dependence may reflect changes in the composition or accessibility of Wnt ligands, receptors, or matrix components during repair, where Cmg2 could play a scaffolding or stabilizing role.

These aspects are now discussed in the text.

I think points 1 and 2 are absolutely fundamental in a reverse genetics investigation. Point 3 would be nice to know but the outcome would not change the tenet of the paper. I believe that the work needed to deal these points can be performed on archival material. I do not think the mechanism proposed can be taken from 'plausible' to 'proven' without proposing substantial additional investigation, so I will not suggest any of it, as it could well be another paper.

We have addressed points 1 and 2, and provided evidence and discussion for Point 3.

__Minor points __

1- Figure 1 legend says "In (c), results are mean {plus minus} SEM" - this seems applicable to (d) as (c) does not show error whiskers.

We thank the reviewer for picking up this error. We modified : “In (c), results are median” and “In (d, f and g) Results are mean ± SEM.”

2- Figure 1 legend says "(d) Body weight loss, (f) the aspect of the feces and presence of occult blood were monitored and used for the (e) DAI. Results are mean {plus minus} SEM. Each dot represents the mean of n = 12 mice per genotype". This part looks like has suffered some rearrangement of words. The first instance of (f) should be (e), I guess, and I am not sure what "(e) DAI" means. And for (e), "mean {plus minus} SEM" does not seem applicable. This needs some light revision.

The legend was clarified as followed : “(d) __Body weight loss, and (e) aspect of the feces and presence of occult blood were monitored and used to evaluate Disease activity index in (f).__

3 - Figure 1H legend does not say which statistical test was made in the survival experiment in (h) - presumably log-rank? A further comment on the survival statistics: euthanised animals should not be counted towards true mortality when that is what is recorded as an 'event'. They should be right-censored. However, in this case, reaching the euthanasia criterion is just as good an indicator of health as mortality itself. So, simply by changing the Y axis from 'survival' to 'event-free survival' (or something to that effect), where 'events' are either death or reaching the euthanasia criterion, leaves the analysis as it is, and authors do not need to clarify that figure 1H shows "apparent mortality", as it is straightforward "complication-free survival" (just not entirely orthogonal to weight loss).

The Y axis was changed from 'survival' to “percentage of mice not reaching the euthanasia criterion”.

4 - Some density measurements are made unnecessarily on arbitrary units (per field of view) - this should be simple to report in absolute measures (i.e. area of tissue screened or, better still, length of epithelium screened).

Because the aera of tissue can vary significantly between damages, regenerating and undamaged tissue, we reported the length of epithelium screened as suggested : “per 800um tissue screened” in Fig S1c and Fig 2b.

5 - Figure 2E should read "percent involvement"

This has been corrected.

6 - Figure 2J should read "lipocalin..."

This has been corrected.

7 - In section "CMG2 Is Dispensable for YAP/TAZ-Mediated Reprogramming to Fetal-Like Stem Cells", the authors write ""We measured the mRNA levels of two additional YAP target genes, Cyr61 and CTGF...". I presume the "additional" is because Ly6a is also a target of YAP/TAZ, but if the reader does not know, it is puzzling. I would suggest to make this link explicit.

We added : “In addition to the fetal-like stem cell marker Ly6a, which is a YAP/TAZ target gene, we measured the mRNA levels of two others YAP target genes, Cyr61 and CTGF”

8 - In Figures S2, 3 and S3, I think that the measures expressed as "% of homeostatic X in WT" really mean "% of average homeostatic X in WT". This should be made clear somewhere.

We added: “Dotted line represents the average homeostatic levels of Cmg2 WT” in figure legends

9 - In panel C, the nature of the data is not entirely clear. First, the corresponding part of the legend says "Representative images of n=4 mice per genotype" which I presume should refer to panel B. Then, the graph plots 4 data points, which suggests that they correspond to 4 mice - but how many fields of view? Also, the violin plot outline is not described - I presume it captures all the data points from the coarse-grained pixel analysis, but it should be clarified.

It was modified as suggested : “(c) Results are presented as violin plot of the Ly6a mean intensity of all data points from the coarse-grain analysis. Each symbol represents the mean per mice of n=4 mice per condition. Results are mean ± SEM. Dotted line represents the average homeostatic levels of Cmg2WT. P values obtained by two-tailed unpaired t test.”

10 - In Figure 3H and 3I, I would suggest to add the 7+3 timepoint where the data come from.

We unfortunately do not understand the suggestion of the reviewer, given that these panels show the 7+3 time point.

11 - In section "CMG2 Is Critical for Restoring the Lgr5+ Intestinal Stem Cell Pool", the authors say "...The mRNA levels of ... LRP6, β-catenin (Fig. S3a-b), and Wnt ligands (Wnt5a, 5b, and 2b) were comparable between the colons of Cmg2WT and Cmg2KO mice (Fig. S3c)..." without clarifying in which context - one needs to read the figure legend to realise this is "timepoint 7+3". I suggest to add "in the recovery phase" or "in regenerating colons" or something shorter, just to guide the reader.

We added : “Initially, we quantified the expression of key molecular components involved in Wnt signaling in mice colon 3 days after DSS withdrawal using qPCR.”

12 - Like with the previous point, it is not clear when the immunohistofluorescence of B-catenin is made - not even in the legend, as far as I could see. The only hint is that authors say "the nuclei of cells in the atrophic crypts of Cmg2KO..." with 'atrophic' probably indicating again the 7+3 timepoint.

We have changed the text and now mention “Next, we analyzed β-catenin activation in the colon of Cmg2WT and Cmg2KO mice during the recovery phase.”

13 - A typo in the discussion: tunning for tuning.

This has been corrected.

14 - In the discussion, the authors talk about the 'CMG2' protein (all caps - formatting convention for human proteins) but before they were referring to 'Cmg2' (formatting convention for mouse proteins). That is fine but some of the statements where "CMG2" is used clearly refer to observations made in the mouse.

We have now used Cmg2, whenever referring to the mouse protein.

15 - Typos in methods: "antigen retrieval by treating [with] Proteinase K"; "Image acquisition and analyze [analysis]"; "All details regarding code used for immunofluorescence analysis”.

This has been corrected.

__Reviewer #2 __

We are very pleased to read that the reviewer found the study “overall well designed, meticulously carried out, and with clear and convincing results that are most reasonably and thoughtfully interpreted”.

For this reader, one additional thought comes to mind. If I understand the field correctly it would be informative to know with greater confidence where - in what cell type, epithelial or mesenchymal - the CMG2-LRP6-WNT interaction occurs.

This point was also raised by Reviewer I, and we have now added a new Figure 1, that describes Cmg2 expression in the gut, based both on from publicly available RNA-seq datasets and our RNAscope experiments on Cmg2WT mice. Of note, we unfortunately have never managed to detect Cmg2 protein expression by immunohistochemistry of mouse tissue with any of the antibodies available, commercial or generated in the lab.

After injury the CMG2-KO mouse epithelium exhibits defective WNT signal transduction - as evidenced by failure of b-catenin to translocate into the nucleus. At first glance, this result is a disconnect with the paper by van Rijin that claims the defect in Hyaline Fibromatosis Syndrome cannot be due to loss of CMG2 expression/function in the barrier epithelial cell - a claim based on the mostly normal phenotypes of human CMG2 KO duodenal organoids. But the human organoids studied in the van Rijin paper, like all others, are established and cultured in very high WNT conditions, perhaps obscuring the lack of the CMG2-LRP6-WNT interaction. And in fact, the phenotypes of these human CMG2-KO duodenoids were not entirely normal - the CMG2-KO stem-like organoids (even when cultured in high WNT/R-spondin conditions) developed abnormal intercellular blisters consistent with a defect in epithelial structure/function - of unknown cause and not investigated.

We thank the reviewer for raising this point and we fully agree. We now specify in the text that the human CMG2-KO duodenoids showed blisters, indeed consistent with a defect in epithelial structure/function, and that they were grown on high Wnt media which likely obscure the CMG2 requirement.

I think it would be informative to prepare colon organoids (and duodenoids) from WT and CMG2-KO mice to quantify their WNT dependency during establishment and maintenance of the stem-like (and WNT-dependent) state. If CMG2 acts within the epithelial cell to affect WNT signaling (regardless of WNT source), organoids prepared from colons of CMG2-KO mice would require more WNT in culture media to establish and maintain the stem cell proliferative state - when compared to organoids prepared from WT mice. This can be quantified (and confirmed molecularly by transgene expression if successful). Enhanced dependency of high concentrations of exogenous WT would be evidence for a primary defect in WNT-(LRP2)-CMG2 signal transduction localized to the epithelial barrier cell - thus addressing the apparent discrepancy with the van Rijin paper - and for my part, advancing the field. And the discovery of a defect in the epithelium itself for WNT signal transduction would implicate a biologically most plausible mechanism for development of protein losing enteropathy.

By no means do I consider these experiments to be required for publication (especially if considered to be incremental or already defined - WNT-CMG2 is not my field of research). This study already makes a meaningful contribution to the field as I state above. But in the absence of new experimentation, the issue should probably be discussed in greater depth.

We are working out conditions to grow colon organoids that from WT and Cmg2 KO mice, indeed playing around with the concentrations of Wnt in the various media to identify those that would best mimic the regeneration conditions. This is indeed a study in itself. We have however included a discussion on this point in the manuscript as suggested.

__Reviewer #3: __

We thank the reviewer for her/his insightful comments.

The premise is that the causative germline mutated gene, CMG2/ANTRX2, may have a functional role in colonic epithelium in addition to controlling the ECM composition. There is little background information but one study has shown no primary defect in epithelial organoids grown from patients with the syndrome. This leads the authors to wonder if non-homeostatic, conditions might reveal a function role for the gene in regeneration.

Reviewer 2 commented on the fact that “human organoids studied in the van Rijin paper, like all others, are established and cultured in very high WNT conditions, perhaps obscuring the lack of the CMG2-LRP6-WNT interaction. And in fact, the phenotypes of these human CMG2-KO duodenoids were not entirely normal - the CMG2-KO stem-like organoids (even when cultured in high WNT/R-spondin conditions) developed abnormal intercellular blisters consistent with a defect in epithelial structure/function - of unknown cause and not investigated”.

We have now added a discussion on this point in the manuscript.

The authors' approach to test the hypothesis is to use a mouse germline knockout model and to induce colitis and regeneration by the established protocol of introducing dextran sodium sulfate (DSS) into the drinking water for five days. In brief there is no phenotype apparent in the untreated knockout (KO) but these animals show a more severe response to DSS that requires them to be killed by 10 days after the start of treatment. This effect following phenotypic characterisation of the colonic epithelium is interpreted as showing the CMG2 is a Wnt modifier required for the restoration of the intestinal stem cell population in the final stages of repair.

The experiment and analysis seem reasonably well executed - although a few specific comments follow below. The narrative is simple and easy to understand. However, there are significant caveats that cast doubts on the interpretation made that loss of CMG2 impairs the transition of colonic epithelial cells from a fetal like state to adult ISCs.

First there is only a single approach and single type of experiment performed. There is a lack of independent validation of the phenotype and how it is mediated.

We do not fully understand what type of independent validation of the phenotype the reviewer would have liked to see. Is it the induction of intestinal damage using a stress other than DSS?

The DSS dose in this kind of experiment is often determined empirically in individual units. Here the 3% used is within published range but at upper end. The control animals show a typical response with symptoms of colitis worsening for 2-3 days after the removal of DSS and then recovery commonly over another 5-7 days. Here the CMG2 KO mice fail to recover and are killed by 9 or 10 days. The authors attempt to exploit the time course by identifying normal initial (7days) and defective late (10days) repair phases in KO animals when compared to controls. It is from this comparison that conclusions are drawn. However, the alternative interpretation might be that the epithelium of KO animals is so badly damaged, and indeed non-existent (from viewing Fig2a), that it is incapable of mounting any other response other than death and that the profiling shown is of an epithelium in extremis. The repair capability and dynamics of the KO would have been better tested under more moderate DSS challenge, if this experiment had been regarded as a pilot rather than as definitive.

The choice of 3% DSS was in fact based on a pilot experiment. As now shown in Fig. S4, we tested different concentrations and found that 3% DSS was the lowest concentration that reliably induced the full spectrum of colitis-associated symptoms, including significant body weight loss, diarrhea, rectal bleeding (summarized in the Disease Activity Index), as well as macroscopic signs such as colon shortening and spleen enlargement. Based on these criteria, we selected 3% DSS for the study described in the manuscript.

In this model, WT mice showed a typical progression: body weight stabilized rapidly after DSS withdrawal, with resolution of diarrhea and rectal bleeding. Histological analysis at day 9 revealed signs of epithelial regeneration, including hypertrophic crypts and increased epithelial proliferation.

In contrast, Cmg2KO mice failed to initiate this recovery phase. Clinical signs such as weight loss, diarrhea, and bleeding persisted after DSS withdrawal, ultimately necessitating euthanasia at day 9–10 due to humane endpoint criteria. Unfortunately, this prevented us from exploring later timepoints to determine whether regeneration was delayed or completely abrogated in the absence of Cmg2.

Regarding the severity of epithelial damage, as raised by Reviewer 1, we now provide detailed histological scoring in the supplementary data. This analysis shows that the severity of inflammation and crypt damage was similar between WT and KO animals, as were inflammatory markers such as Lipocalin-2. The key difference lies in the extent of tissue involvement. While the lesions in WT mice were more localized, Cmg2KO mice displayed widespread and diffuse damage with no sign of regeneration as shown by the absence of hypertrophic crypts and a marked reduction in both epithelial coverage and proliferative cells. Importantly, at day 7, the percentage of epithelial and proliferating cells was comparable between genotypes, further supporting the idea that Cmg2KO mice failed to initiate this recovery phase and present a defective repair response.

The animals used were young (8 weeks) and lacked any obvious defect in collagen deposition. Does this change with treatment? Even if not, is it possible that there is a defect in peristalsis or transit time of gut contents, resulting in longer dwell times and higher effective dose of DSS to the KO epithelium?

Collagen deposition, particularly of collagen VI, is known to increase in response to intestinal injury and plays a critical role in promoting tissue repair following DSS-induced damage (Molon et al., PMID: 37272555). As suggested, we investigated whether Cmg2KO mice exhibit abnormal collagen VI accumulation following DSS treatment.

Our results show that, consistent with published data, WT mice exhibit a marked increase in collagen VI expression during the acute phase of colitis, with levels returning toward baseline following DSS withdrawal. A similar expression pattern was observed in Cmg2KO mice, with no significant differences in Col6a1 mRNA levels between WT and KO animals throughout the entire time course of the experiment. This observation was further confirmed at the protein level by western blot and immunohistochemistry analyses, suggesting that the impaired regenerative capacity observed in Cmg2KO mice is independent of Collagen VI.

Regarding the possibility of altered peristalsis or intestinal transit time contributing to increased DSS exposure in KO mice, this is indeed a possibility. Although we did not directly measure gut motility in this study, we did not observe any signs of intestinal obstruction or fecal retention in Cmg2KO mice. Indeed, during the experiment, animals were single caged for 30min in order to collect feces and no difference in the amount of feces collected was observed between WT and KO mice, arguing against a substantial difference in transit time (see figure below). The possible altered peristalsis and these observations are now mentioned in the discussion.

Is CMG2 RNA and protein expressed in the colonic epithelium? It is not indicated or tested in the submitted manuscript. This reviewer struggled to find evidence, notably it did not seem to be referenced in the organoid paper they reference in introduction (ref 13).

This very valid point was also raised by Reviewers 1 and 2. The expression pattern of Cmg2 in the gut has indeed not been characterized and is essential to understanding its function. To address this gap, we added a figure (Fig. 1) providing data from publicly available RNA-seq datasets and from our RNAscope experiments on Cmg2WT mice. Of note, we unfortunately have never managed to detect Cmg2 protein expression by immunohistochemistry of mouse tissue with any of the antibodies available, commercial or generated in the lab.

__Specific comments: __

Figure 3 c-e and associated text are confusing. In c the Y scale seems inappropriate to show percentages up to 15,000%.

In this graph values are normalized to homeostatic level of WT mice which represent 100%

In d and e the use of percentages may by correct. However, it is claimed in text that Cty61 and CTFG are upregulated in the KO. That is not what the plots appear to show as the compare to WT untreated cells, in which case the KO have not downregulated these genes in the way the controls have.

As clarified in the text, under regenerative conditions, a transient activation of YAP signaling is crucial to induce a fetal-like reversion of intestinal stem cells. However, in a subsequent phase, the downregulation of YAP and the reactivation of Wnt signaling are necessary to complete intestinal regeneration. Several studies have highlighted a strong interplay between the Wnt and YAP pathways, suggesting that their coordinated regulation is essential for effective gut repair. Nevertheless, the precise mechanisms governing this interaction remain incompletely understood.

In our model, this critical transition—YAP downregulation and Wnt reactivation—appears to be impaired. CMG2 may either hinder Wnt reactivation directly, or lead to sustained YAP signaling, which in turn suppresses activation of the Wnt pathway. Further studies, using in-vivo model and organoid models, will be necessary to understand the mechanistic role of Cmg2 in this regulatory process.

A precision of the figure has been updated as followed: both of which were significantly upregulated in the injured colons of Cmg2KO mice compared to DSS-injured Cmg2WT mice

__**Referees cross-commenting** __

Rev2 Points 1 and 2 made by Referee 1 (and point 4 of Referee 3) appear most reasonable, and if not already done should be.

We have indeed addressed these 2 points.

I also noted the more severe morphology of DSS damaged epithelium shown in Fig 2a noted by Referee 3 - and this I agree is a confounding factor. […] For my part, the concern is understandable but likely not operating in a confounding way. And the evidence for the reprogramming of the damaged epithelium into "fetal-like stem cells" (the 1st step in restitution of lost stem cells) occurs in both WT and KO mice - and these data are strong. For this reader, the block convincingly shows up for KO mouse at the WNT dependent step

The representative image has been updated, and a transverse section has been added to better illustrate that, although both epithelium and crypt structures can be present, the epithelial morphology differs significantly. Indeed, the regenerating epithelium of Cmg2WT mice displays a thick epithelial layer with well-polarized epithelial cells, whereas in cmg2KO mice, the epithelium appears atrophic, characterized by a thinner epithelial layer and elongated epithelial cells.

__Rev 3 __

This reviewer remains sceptical. I agree the authors performed the experiment well to confirm that DSS dosing was as equivalent as possible across the study. But DSS acts to induce colitis because it is concentrated in the colonic lumen as water is absorbed. Also ECM responses and remodelling are a central part of colitis models. And my concern is that the actual exposure in the KO group is influenced by transit of faeces/DSS is secondary to the known action of CMG2 on collagen deposition. The consequence of this being a protracted damage phase in which a restoration of adult stem cells would not be expected and leading to epithelial failure.

However, we differ. I might propose that the authors are asked to investigate and confirm expression of CMG2 in the epithelium and to repeat the analysis of collagen levels they performed on untreated CMG2 KO mice on colons from CMG2 KO mice having received DSS to see if these differ from controls.

This has now been done.

__Rev 1 __

Both reviewer #2 and reviewer #3 make relevant points, from the point of view of extracting as much biological knowledge as we can from the observations reported in the manuscript.

Reviewer #2 suggestion to use Cmg2[KO] organoids to investigate the dependence of Wnt transduction on Cmg2 is the type of experiments I refrained to propose. However, I think the "skeleton" of the mechanism is there and is reasonably solid. Fleshing it out may well be another paper.

I agree with Reviewer #3 objections to the timing and severity of the DSS damage. However, I am not sure how much they invalidate the main tenet of the paper:

• DSS may affect Cmg2[KO] more severely, but the overall disease score is comparable during the DSS treatment. If this severity was enough to be the main driver of the phenotype, it should have left a mark in the Histological and Disease activity scores. In this regard, I think it would be helpful if the authors provided an expanded version of Figure 2A with examples of the different levels of "Crypt damage" scored, and the proportions for each. This could be in the supplementary material and would balance the impressions induced by a single image.

As suggested, we included a detail of histological score including the crypt damage score in Supplementary Fig 3i showing no significant differences in crypt damage between Cmg2WT and Cmg2KO mice.

• If DSS affected the recovery, this would also be compatible with having a more severe histological phenotype (which is not shown overall, just in Fig 2A) because one would also expect the tissue to attempt regeneration during the 7 days of DSS treatment.

This is an interesting point, and we now allude to this aspect in the manuscript.

• The only objection that I find difficult to argue is the effective duration of the treatment. If indeed peristalsis is affected, it may be that during the 'recovery' phase there is still DSS in the intestine. This could be perhaps verified using a DS detection assay (e.g. https://arxiv.org/pdf/1703.08663) on the intestinal contents or the faeces of the mice during the 3-day recovery period.

We have attempted to obtain and purchase Heparin Red to perform this assay. Unfortunately, we have not obtained the reagent, which has never been delivered. We now also mention the following in the Discussion:

One could envision that Cmg2KO mice have a defect in peristalsis resulting in longer dwell times and possibly higher effective dose of DSS to the KO epithelium. We however did not observe any signs of intestinal obstruction or fecal retention in Cmg2KO mice. Animals were single-caged for 30 min to collect feces. We did not observe any difference in amounts collected from WT and KO mice, arguing against a substantial difference in transit time of gut contents. Moreover, if DSS affected the recovery, one would have expected a more severe histological phenotype in the colon of Cmg2KO since the tissue likely already attempts regeneration during the 7 days of DSS treatment. But this was not the case. Therefore, while we cannot formally rule out the presence of residual DSS in Cmg2KO mice during the DSS withdrawal phase, there is currently no indication that this was the case.

I think of what the aim of scholarly publication is, with this paper, and I find myself going back to a statement of the authors' discussion - that this work suggests that infants risking death may be offered (compassionate, I guess) IBD treatment. What does this hinge upon? I think, on the basic observation that diarrhoea (in the mouse model) is not intrinsic but caused by an inflammation-promoting insult. Is this substantiated? I think it is. Could we learn more biology from this disease model, about Wnt and about how ECM affects tissue regeneration? Certainly. Can this learning wait? I believe it can.

We thank the reviewer for this statement.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

In this work, Bracq and colleagues provide clear evidence that the persistent diarrhoea seen in a mouse model of Hyaline Fibromatosis Syndrome is related to the inability of their intestinal epithelium to properly regenerate. This is very clear and of immediate impact. This aspect of the paper, I think, is ready for publication, and would merit immediate dissemination on its own. It is great that the manuscript is in bioRxiv already.

I am not so thoroughly convinced about the mechanism that the author propose to explain the incapacitation of Cmg2[KO] intestinal stem cells to function properly. The authors propose that it is due to their inability to transduce Wnt signals, and while this is plausible, I think there are few things that the paper should contain before this can be proposed firmly:

Point #1

The mouse mutant is just described as 'KO', referring to the previous work by the authors. The cited work simply states that this is a zygotic deletion of exon 3, which somehow leads to a decrease in protein abundance that is almost total in the lung but not so clear in the uterus. Exon 3 happens to be 72 bp long [https://www.ncbi.nlm.nih.gov/nuccore/NM_133738], so its deletion (assuming there are no cryptic splicing sites used) leads to an internal in-frame deletion of 24 amino acids. So, at best, this 'KO' is not a null, but a hypomorphic allele of context-dependent strength. Unfortunately, neither the previous work nor this paper (unless I have missed it!) contains information provided about the expression levels of Cmg2 in the intestine of KO mice - nor which cell types usually express it (see below). I think that using anti Cmg2 in WB and immunohistofluorescence of with ISC markers with intestine homogenate/sections of wild-type and mutant mice would be necessary to set the stage for the rest of the work.

Point #2

Connected to the previous point, the expression pattern of Cmg2 in the intestine is not described. Maybe this is already established in the literature, but the authors do not refer to the data. This is important when considering that the previous work of the authors suggests that Cmg2 might contribute to Wnt signalling transduction through physical, cis interactions with the Wnt co-receptor LRP6. Therefore, one would expect that Cmg2 would be cell-autonomously required in the intestinal stem cells.

Point #3

The authors establish that the regenerating crypts of Cmg2[KO] mice are unable to transduce Wnt signalling, but it is not clear whether this situation is provoked by the DSS-induce injury or existed all along. Can Cmg2[KO] intestinal stem cells transduce Wnt signalling before the DSS challenge? If they were, it might suggest that the 'context-dependence' of the Cmg2 role in Wnt signalling is contextual not only because of the tissue, but because of the history of the tissue or its present structure. It would also suggest that Cmg2 mutant mice, unless reared in a germ-free facility for life, would eventually lose intestinal homeostasis, and maybe suggest the level of intervention/monitoring that HFS patients would require. It might also provide an explanation in case Cmg2 was not expressed in ISCs - if the state of the tissue was as important as the presence of the protein, then the effect on Wnt transduction could be indirect and therefore it might not be required cell-autonomously.

I think points 1 and 2 are absolutely fundamental in a reverse genetics investigation. Point 3 would be nice to know but the outcome would not change the tenet of the paper. I believe that the work needed to deal these points can be performed on archival material. I do not think the mechanism proposed can be taken from 'plausible' to 'proven' without proposing substantial additional investigation, so I will not suggest any of it, as it could well be another paper.

A few minor points picked along the way:

1. Figure 1 legend says "In (c), results are mean {plus minus} SEM" - this seems applicable to (d) as (c) does not show error whiskers.
2. Figure 1 legend says "(d) Body weight loss, (f) the aspect of the feces and presence of occult blood were monitored and used for the (e) DAI. Results are mean {plus minus} SEM. Each dot represents the mean of n = 12 mice per genotype". This part looks like has suffered some rearrangement of words. The first instance of (f) should be (e), I guess, and I am not sure what "(e) DAI" means. And for (e), "mean {plus minus} SEM" does not seem applicable. This needs some light revision.
3. Figure 1H legend does not say which statistical test was made in the survival experiment in (h) - presumably log-rank? A further comment on the survival statistics: euthanised animals should not be counted towards true mortality when that is what is recorded as an 'event'. They should be right-censored. However, in this case, reaching the euthanasia criterion is just as good an indicator of health as mortality itself. So, simply by changing the Y axis from 'survival' to 'event-free survival' (or something to that effect), where 'events' are either death or reaching the euthanasia criterion, leaves the analysis as it is, and authors do not need to clarify that figure 1H shows "apparent mortality", as it is straightforward "complication-free survival" (just not entirely orthogonal to weight loss).
4. Some density measurements are made unnecessarily on arbitrary units (per field of view) - this should be simple to report in absolute measures (i.e. area of tissue screened or, better still, length of epithelium screened).
5. Figure 2E should read "percent involvement"
6. Figure 2J should read "lipocalin..."
7. In section "CMG2 Is Dispensable for YAP/TAZ-Mediated Reprogramming to Fetal-Like Stem Cells", the authors write ""We measured the mRNA levels of two additional YAP target genes, Cyr61 and CTGF...". I presume the "additional" is because Ly6a is also a target of YAP/TAZ, but if the reader does not know, it is puzzling. I would suggest to make this link explicit.
8. In Figures S2, 3 and S3, I think that the measures expressed as "% of homeostatic X in WT" really mean "% of average homeostatic X in WT". This should be made clear somewhere.
9. In panel C, the nature of the data is not entirely clear. First, the corresponding part of the legend says "Representative images of n=4 mice per genotype" which I presume should refer to panel B. Then, the graph plots 4 data points, which suggests that they correspond to 4 mice - but how many fields of view? Also, the violin plot outline is not described - I presume it captures all the data points from the coarse-grained pixel analysis, but it should be clarified.
10. In Figure 3H and 3I, I would suggest to add the 7+3 timepoint where the data come from.
11. In section "CMG2 Is Critical for Restoring the Lgr5+ Intestinal Stem Cell Pool", the authors say "...The mRNA levels of ... LRP6, β-catenin (Fig. S3a-b), and Wnt ligands (Wnt5a, 5b, and 2b) were comparable between the colons of Cmg2WT and Cmg2KO mice (Fig. S3c)..." without clarifying in which context - one needs to read the figure legend to realise this is "timepoint 7+3". I suggest to add "in the recovery phase" or "in regenerating colons" or something shorter, just to guide the reader.
12. Like with the previous point, it is not clear when the immunohistofluorescence of B-catenin is made - not even in the legend, as far as I could see. The only hint is that authors say "the nuclei of cells in the atrophic crypts of Cmg2KO..." with 'atrophic' probably indicating again the 7+3 timepoint.
13. A typo in the discussion: tunning for tuning.
14. In the discussion, the authors talk about the 'CMG2' protein (all caps - formatting convention for human proteins) but before they were referring to 'Cmg2' (formatting convention for mouse proteins). That is fine but some of the statements where "CMG2" is used clearly refer to observations made in the mouse.
15. Typos in methods: "antigen retrieval by treating [with] Proteinase K"; "Image acquisition and analyze [analysis]"; "All details regarding code[s] used for immunofluorescence analysis"

Referees cross-commenting

*this session contains comments from ALL the reviewers"

Rev2

Points 1 and 2 made by Referee 1 (and point 4 of Referee 3) appear most reasonable, and if not already done should be.

I also noted the more severe morphology of DSS damaged epithelium shown in Fig 2a noted by Referee 3 - and this I agree is a confounding factor. But overall, multiple lines of evidence were assembled to show that the KO mice and WT mice suffered DSS-induced colitis with equal severity - and with closely equal severity of damage to the intestinal epithelium (though the image in Fig 2a is disturbing). For my part, the concern is understandable but likely not operating in a confounding way. And the evidence for the reprogramming of the damaged epithelium into "fetal-like stem cells" (the 1st step in restitution of lost stem cells) occurs in both WT and KO mice - and these data are strong. For this reader, the block convincingly shows up for KO mouse at the WNT dependent step

Rev 3 This reviewer remains sceptical. I agree the authors performed the experiment well to confirm that DSS dosing was as equivalent as possible across the study. But DSS acts to induce colitis because it is concentrated in the colonic lumen as water is absorbed. Also ECM responses and remodelling are a central part of colitis models. And my concern is that the actual exposure in the KO group is influenced by transit of faeces/DSS is secondary to the known action of CMG2 on collagen deposition. The consequence of this being a protracted damage phase in which a restoration of adult stem cells would not be expected and leading to epithelial failure.

However, we differ. I might propose that the authors are asked to investigate and confirm expression of CMG2 in the epithelium and to repeat the analysis of collagen levels they performed on untreated CMG2 KO mice on colons from CMG2 KO mice having received DSS to see if these differ from controls.

Rev 1 Both reviewer #2 and reviewer #3 make relevant points, from the point of view of extracting as much biological knowledge as we can from the observations reported in the manuscript.

Reviewer #2 suggestion to use Cmg2[KO] organoids to investigate the dependence of Wnt transduction on Cmg2 is the type of experiments I refrained to propose. However, I think the "skeleton" of the mechanism is there and is reasonably solid. Fleshing it out may well be another paper.

I agree with Reviewer #3 objections to the timing and severity of the DSS damage. However, I am not sure how much they invalidate the main tenet of the paper:

• DSS may affect Cmg2[KO] more severely, but the overall disease score is comparable during the DSS treatment. If this severity was enough to be the main driver of the phenotype, it should have left a mark in the Histological and Disease activity scores. In this regard, I think it would be helpful if the authors provided an expanded version of Figure 2A with examples of the different levels of "Crypt damage" scored, and the proportions for each. This could be in the supplementary material and would balance the impressions induced by a single image.

• If DSS affected the recovery, this would also be compatible with having a more severe histological phenotype (which is not shown overall, just in Fig 2A) because one would also expect the tissue to attempt regeneration during the 7 days of DSS treatment.

• The only objection that I find difficult to argue is the effective duration of the treatment. If indeed peristalsis is affected, it may be that during the 'recovery' phase there is still DSS in the intestine. This could be perhaps verified using a DS detection assay (e.g. https://arxiv.org/pdf/1703.08663) on the intestinal contents or the faeces of the mice during the 3-day recovery period.

I think of what the aim of scholarly publication is, with this paper, and I find myself going back to a statement of the authors' discussion - that this work suggests that infants risking death may be offered (compassionate, I guess) IBD treatment. What does this hinge upon? I think, on the basic observation that diarrhoea (in the mouse model) is not intrinsic but caused by an inflammation-promoting insult. Is this substantiated? I think it is. Could we learn more biology from this disease model, about Wnt and about how ECM affects tissue regeneration? Certainly. Can this learning wait? I believe it can.

Significance

In this work, Bracq and colleagues provide clear evidence that the persistent diarrhoea seen in a mouse model of Hyaline Fibromatosis Syndrome is related to the inability of their intestinal epithelium to properly regenerate. This is very clear and of immediate impact. For instance, the authors themselves point at the possibility of applying treatments for Inflammatory Bowel Disease to HFS patients. While what happens in a mouse model is not necessarily the same as in human patients, the fact that persistent diarrhoea is a life-threatening symptom in HFS make this proposal, at least in compassionate use of the therapies and until its efficacy is disproven, very plausible. This is a clear gap of knowledge that addresses an unmet medical need.

I find that the work shows clearly that HFS mouse model subjects have normal intestinal function until challenged with a standard chemically-induced colitis. Then, the histological and health deterioration of the HFS mouse model is clear in comparison with normal mice, which can regenerate appropriately. This is shown with a multiplicity of orthogonal techniques spanning molecular, histological and organismal, which are standard and very well reported in the paper.

The authors propose a specific cellular and molecular mechanism to explain the incapacity of the intestinal epithelium in the mouse model of HFS to regenerate. According to this mechanism, the protein Cmg2, whose mutation causes HFS in humans, would be necessary for intestinal stem cells to transduce the signal of Wnt ligands and therefore support their behaviour as regenerative cells. This mechanism is plausible, but more basic and advanced work would be needed to take it as proven.

This work would be of interest to both the clinical, biomedical, and basic research communities interested in rare diseases, the gastrointestinal system, collagen and extracellular matrix, and Wnt signalling.

My general expertise is in developmental and stem cell biology using reverse genetics, transgenesis and immunohistological and molecular methods of data production, and lineage tracing, digital imaging and bioinformatic analytical methods; I work with Drosophila melanogaster and its adult gastrointestinal system.

HC4 Motivatie Grit (Angela Duckworth): Mensen met grit geven niet snel op, blijven gemotiveerd ondanks tegenslag, en blijven jarenlang werken aan iets wat ze belangrijk vinden.

Motivatie bestaat uit 3 factoren: 1. direction: wat doet de persoon 2. intensity (hoe hard een persoon werkt) 3. persistence (hoe lang doen ze het)

Process van een iemand motiveren: eerst energizing the behavior= het activeren van onderliggende behoeften en drives daarna directing behavior naar het doel toe als laatste moet het gedrag nog volgehouden worden Sustaining behavior (door bijvoorbeeld een reward). Voor de motivatie om effectief te zijn is feedback ook nog nodig, want dan gaat het weer terug naar energizing behavior.

Goal setting: a goal without a plan is just a wish> SMART goal setting (specific, measurable, achievable, relevant, time-based)

Maslow's hierarchy of needs: Mensen hebben een hierarchie in motivatie: 1. belangrijkste eerst fysieke benodigdheden (honger, huis, drinken)-een lower order need 2. veiligheid (fysiek en emotioneel)-lower order 3. sociale benodigdheden (vriendschap en belonging)- higher order 4. esteem needs (status en recognition from others)-higher order 5. self-actualization: je volle potentie als een persoon willen behalen - higher order GEEN bewijs voor deze theorie

McClelland: stelt 3 fundamentele behoeften: achievement, power en affiliation (close personal relationships), deze worden aangeleerd in de jeugd en deze behoeften kunnen dus niet op latere leeftijd nog meer worden.

Hertzberg's motivator-hygiene theory (two-factor theory): Hygiene is wat mensen niet leuk vinden aan hun werk en wat de werk tevredenheid omlaag brengt. Motivator is het tegenovergestelde.

Regulatory focus theory RFT: promotion focused (oriented towards growth and development, becoming their ideal self > learning goals orientation (LGO) prevention focused (vigilant and careful, emphasize fears, focus on avoiding threats and set prevention goals. Ze willen alleen dingen doen die binnen hun kunnen vallen om stress te voorkomen.

Job characteristics theory: niet alleen andere mensen maar ook het werk zelf kan mensen motiveren. Er zijn vijf core job dimensies: 1. skill variety 2. task identity 3. task significance 4. autonomy 5. feedback

The job charcteristics model: core job charcteristics-critical psychological states- personal and work outcomes

Skill variety, task idenity en task significance > experiended meaningfullness of the work

Job characteristics theory-designed jobs give internal rewards Individual's growth needs are moderating factors motivating jobs must: be autonomous, provide feedback, have at least one of the three meaningfulness factors (Skill variety, task idenity en task significance )

Om de motivatie voor werk hoger te maken gebruiken organisaties: work redesign of job enrichment (horizontaal toevoegen, meer taken toedienen op hetzelfde level OF verticaal meer vertrouwen in keuzes maken, dus job loading.

VB horizontaal: job rotation (iemand een keer een ander soort baan geven) en combining tasks (nieuwe taak leren die toegevoegd kan worden aan de taak die diegene al deed)

Vertical: prosocial motivation (iemand krijgt de kans om met de klant te praten die voordelen heeft van de moeite die diegene in zijn werk stopt) en meer autonomy krijgen

Job crafting: de hoeveelheid initiatief dat iemand toont in het vormgeven van zijn of haar werk. (changing job responsibilities, changing interactions with others, changing how the work is seen)

Importance of fairness -equity theory (minder motivatie als werknemers vinden dat ze meer geven dan ze krijgen): distributive justice bestaat uit balans, underpayment inequity en overpayment inequity

There are 4 types of organisational justice: (it is the members semse of the moral propriety of how they are treated) 1. distributive: is de uitkomst goed vergeleken met je performance? 2. procedural: kan je je mening en behoeften uitspreken bij het proces? 3. interpersonal: respect? 4. informational: heeft de leider alles goed uitgelegd?

Expectancy theory: (the valance-instrumentality-expectancy (VIE) theory: deze theorie stelt dat de self-efficacy van de werknemer sterker gemaakt moet worden door de leider. 3 principes: 1. werknemers doen meer hun best als ze geloven dat de effort tot een goede performance leidt (E-P) 2. De werknemers performance wordt goed geevalueerd en het leidt tot bonussen (P-O)- instrumentally 3. de werknemers hechten waarden aan de rewards (V van Valences)

DUS expectancy + instrumentally +valance = high effort and motivation

De expectancy theorie = vanuit het perspectief van de werknemer

The Pygmalion effect= perspectief vanjuit de leider

Het Pygmalion-effect is een psychologisch fenomeen waarbij hogere verwachtingen leiden tot betere prestaties. Het wordt ook wel een zelfvervullende voorspelling genoemd (self-fulfilling prophecy)

The galatea effect (gaat over de verwachtingen van de werknemer zelf):individually-set high expectations and then performs to these expectations

Het tegenovergestelde is het Golem-effect: lage verwachtingen leiden tot slechtere prestaties. De-golemization > reversing golem effect

Who will lead: motivation to lead (MTL) 1. affective identity MTL: een natuurlijke neigin gom mensen te leiden 2. Social-normative MTL: leiden omdat je een gevoel van verantwoordelijkheid hebt (volgens sociale normen) 3. noncalculative MTL: willen leiden zonder de voordelen en nadelen van het leiderschap hebben afgewogen: altruism

H9 motivatie: applications

The reinforcement theory: De Law of Effect (de wet van het effect) is een psychologisch principe dat werd geformuleerd door Edward Thorndike in 1898. Het is een fundamenteel principe binnen het behaviorisme.

Definitie: De Law of Effect stelt dat: Gedrag dat gevolgd wordt door een bevredigend gevolg, zal in de toekomst vaker voorkomen. Gedrag dat gevolgd wordt door een onaangenaam gevolg, zal minder vaak voorkomen. (operant conditioneren)

Punishment by application of punishment by removal (van iets positief) Negative reinforcement (iets negatief niet doen) of positive reinforcement (beloning)

Social learning theory: extends operant conditioning, people can learn from watching other people succed or fail. (modeling of observational learning) Bestaat uit 4 stappen: 1. attention 2. retention (informatie moet gesorteerd worden om later te gebruiken) 3. reproduction (imiteren van het gedrag en oefenen zodat je beter wordt) 4. motivation: je moet gemotiveerd zijn om te imiteren (als je ziet dat iemand anders een beloning er voor krijgt wil je het sneller ook)

Intrinsieke vs extrinsieke beloningen

Self-determination theory: SDT stelt dat deze intrinsieke motivatie vooral wordt bevorderd wanneer aan drie basisbehoeften wordt voldaan: -1. Autonomy (Zelfbeschikking) Betekenis: de behoefte om je eigen keuzes te maken en handelen in overeenstemming met je eigen waarden en interesses.

Voorbeeld: in het onderwijs krijgen leerlingen de vrijheid om een onderwerp voor hun project te kiezen. Omdat ze zelf de koers bepalen, voelen ze meer eigenaarschap en zijn ze gemotiveerder om er iets van te maken.

1. Competence (Bekwaamheid) Betekenis: de behoefte om effectief en vaardig te zijn in wat je doet, en het gevoel te hebben dat je kunt groeien door uitdagingen te overwinnen.

Voorbeeld: een softwareontwikkelaar die steeds nieuwe technieken leert en ziet hoe zijn code écht werkt in een product, ervaart dat hij steeds capabeler wordt. Dat stimuleert hem om door te gaan met leren en verbeteren.

1. Relatedness (Verwantschap) Betekenis: de behoefte aan warme, ondersteunende relaties en het gevoel ergens bij te horen.

Voorbeeld: op de werkvloer vormt een team dat open communiceert en elkaar steunt een sociale basis. Medewerkers voelen zich dan verbonden en gewaardeerd, wat hun betrokkenheid vergroot.

Motivation wrk cylcle match: er zijn inverschillende fases van het werk andere vormen van motivatie nodig: intrinsieke motivatie voorspeld kwaliteit van de performance en extrinsieke motivatie voorspeld kwantiteit van de performance

reply to u/highspeed_steel at https://reddit.com/r/typewriters/comments/1krspvh/im_totally_blind_and_new_to_typewriters_wax/

Your question is a great one, but I'll go another direction since I'd dug into some of the history and details of Helen Keller's mid-century typewriters a while back. You can find some details and descriptions here (and in the associated links which includes an accessible video of Ms. Keller using a solid and sexy black Remington Noiseless standard typewriter): https://www.reddit.com/r/typewriters/comments/1ihot96/helen_kellers_typewriters/

She managed on both her Remington as well as her brailler as well as any sighted person, though obviously had someone to check her printed work.

I recently saw another heavily modified midcentury typewriter for someone who, if I recall correctly was not only blind, but had no arms. It was set up so that they could move a selector and type using a custom chin rest. Sadly, I didn't index it at the time, but it's interesting to know that such things existed for accessibility reasons.

As for Braillers, you might appreciate this recent article about a repairman in Britain who was retiring: https://www.theguardian.com/society/2025/jan/02/wed-be-stuck-alarm-as-uks-last-braille-typewriter-repairer-ponders-retirement

I've got my own brailler, which is a sleek-looking art-deco industrial piece of art with the loveliest shade of dark shiny gray paint I've ever seen on a typewriter. (I'm both a mathematician and information theorist into the areas of coding and cryptography, so Morse code, Braille, etc. are professionally fascinating to me.) I still need to take it apart and repair a few portions to get it back to perfection, but it generally works well.

As for the aesthetics, I personally enjoy the solid industrial look and feel of the machines from the 1930s-1960s. The early 30s and some 40s have glossy black enamel and machines like the Corona Standard/Silent from the 30s are low slung with flat tops that sort of resemble small pianos and just scream out "I'm a writer" with a flair for dark academia and just a hint of classical Roman design. Many of these machines come with gold tinged water-slide decals which really set themselves off against the black enamel, though on the majority of machines the gold is beginning to dim from time, wear, and uncareful application of cleaning solutions.

I love the Royal KMM, KMG, and the Remington 17, Standard, and Super-Riter for their industrial chonkiness and (usually) their glass keytops. One of my favorites is the Henry Dreyfuss designed Royal Quiet De Luxe from 1948 which always gives me the feel of what it would look like if a typewriter wore a tuxedo or the 1948 gray and chrome model which is similar but has the feel of a sleek gray flannel suit on a 1950s advertising executive prone to wearing dapper hats, smoking cigarettes, and always with a cocktail in his hand. Into the 50s and 60s almost everyone had moved to plastic keytops which I don't think are as pretty as the older glass keytops with the polished metal rings around them.

At the opposite end of that spectrum are the late 50s Royal FP and Futura 800s which have some colorful roundness which evokes the aesthetic of the coming space age. They remind me of the modern curves and star shapes of the television show The Jetsons. Similarly space-aged are the sexy curves of the silver metalic spray paint on wooden cases for the Olympia SM3 from the same period. These to me are quintessential typewriter industrial design. In gray, green, maroon, brown, and sometimes yellow crinkle paint with just a hint of sparkle in their keytops I really love the combination of roundedness and slight angularity these German designed machines provide. They have a definite understated sort of elegance most other typewriters just miss. I suspect that late-in-life Steve Jobs would have had an Olympia SM3.

There's something comforting about the 40s and 50s sports-car vibe of the smaller Smith-Corona portables of the 5 series machines in the 1950s with their racing stripes on the hood. They feel like the sort of typewriter James Dean would have used as a student—just hip enough to be cool while still be solid and functional.

Sadly into the 70s, while machines typically got a broader range of colors outside of the typical black, gray, and browns things became more plastic and angular. They also begin to loose some of the industrial mid-century aesthetic that earlier machines had. They often feel very 70s in an uncomplimentary way without the fun color combinations or whimsy that art and general design of of that period may have had in the music or fashion spaces. They make me think of politics and war rather than the burgeoning sexual revolution of the time period.

Interestingly, for me, I feel like most typewriter design was often 10-20 years behind the general design aesthetic/zeitgeist for the particular decades in which they were made.

Good luck in your search for the right typewriter(s) for your own collection.

Briefing sur le programme d'Éducation à la Vie Affective, Relationnelle et à la Sexualité (EVARS)

Contexte et Objectifs

Ce briefing est basé sur un podcast produit par l'Institut des hautes études de l'éducation et de la formation (I2F), abordant l'éducation à la vie affective, relationnelle et à la sexualité (EVARS) en milieu scolaire en France.

L'émission met en lumière l'historique, les enjeux, le nouveau programme et sa mise en œuvre.

L'éducation à la sexualité en milieu scolaire est une préoccupation du Ministère de l'Éducation depuis plus de 50 ans, jalonnée par des événements importants comme Mai 68, les lois sur la contraception (1967) et l'IVG (1975), et la circulaire Fontana (1973).

Un tournant majeur a été la loi de 2001 sur l'IVG, instaurant l'obligation de trois séances annuelles d'éducation à la sexualité par tranche d'âge.

Le contexte actuel, marqué par le développement des réseaux sociaux, l'accès facile à l'information (et à la désinformation), le partage d'images sexuellement explicites, l'accès à la pornographie, et la prise de conscience accrue des violences sexuelles (y compris intrafamiliales et entre jeunes, avec des statistiques alarmantes sur les agressions sexuelles d'enfants et de jeunes), a souligné la nécessité de réinterroger la mise en œuvre de ces séances.

Le constat a été fait que ces trois séances annuelles ne sont pas totalement mises en place sur le terrain.

L'Inspection Générale de l'Éducation, du Sport et de la Recherche a identifié la clarification des objectifs de formation des élèves comme un levier essentiel.

C'est dans ce cadre que le Ministre a souhaité l'élaboration d'un programme spécifique.

Le Nouveau Programme EVARS

Le nouveau programme EVARS, élaboré par le Conseil Supérieur des Programmes et fortement soutenu (voté 60 voix pour et 0 contre au Conseil Supérieur de l'Éducation fin janvier 2025), vise à clarifier les objectifs de formation des élèves de la maternelle au lycée.

Il a été conçu avec un large éventail d'experts et a fait l'objet d'une consultation nationale.

Ses intentions principales, clarifiées dans le préambule, visent à trouver un équilibre entre les enjeux de citoyenneté et de santé.

Le programme encourage le développement de l'esprit critique des élèves pour construire des relations respectueuses et acquérir des connaissances scientifiques objectives leur permettant de faire des choix éclairés pour leur santé et celle des autres.

Le programme est décliné en :

• Éducation à la vie affective et relationnelle pour le premier degré (maternelle et élémentaire), axée sur les émotions et les relations.

• Éducation à la vie affective et relationnelle et à la sexualité pour le second degré (collège et lycée), incluant des questionnements plus avancés adaptés à l'âge et à la maturité des élèves.

Il est structuré autour de trois grands axes, présents de la maternelle au lycée :

• Se connaître, vivre et grandir avec son corps.

• Construire des relations, s'y épanouir.

• Trouver sa place dans la société, s'y sentir libre et responsable.

Ces axes sont déclinés en objectifs d'apprentissage par tranche d'âge, avec un souci de progressivité.

Un tableau synoptique est proposé pour visualiser ces objectifs et inspirer les personnels.

Points de Vue et Enjeux Clés

• Sociologie et Utilité des Programmes :

Yael Am Salem Mingi, sociologue, souligne que les pays ayant mis en place l'éducation à la sexualité en milieu scolaire légitiment ces questions et la reconnaissance sociale de la sexualité des jeunes.

Cela permet une prévention des violences (intrafamiliales, sexuelles) et facilite l'accès à l'information sur la contraception, les relations, et la place des jeunes.

Les pays prônant l'abstinence ont de moins bons résultats en matière de grossesses adolescentes et d'IST. L'éducation à la sexualité a des effets positifs sur la connaissance et les pratiques.

• Point de Vue des Élèves :

Les élèves considèrent l'école comme un espace légitime pour parler de la vie affective, relationnelle et sexuelle, à condition que l'école ne juge pas leur comportement, écoute leurs questionnements et adapte le discours. Ils attendent de l'école des informations scientifiques et documentées, pas des jugements de valeur.

Les questionnements évoluent avec l'âge, allant de "c'est quoi l'amour ou l'amitié" au premier degré à la définition de termes liés à la sexualité à l'adolescence (pansexualité, plurisexualité, LGBTQ+).

Ils veulent un langage collectif et une définition collective des termes.

• Intégration et Adaptabilité :

Le programme est conçu pour être inclusif et s'adapter aux questionnements spécifiques de chaque classe et groupe d'élèves, influencés par le contexte géographique, social et de genre.

Il peut être décliné dans différentes matières (arts plastiques, musique, sport, français, SES, SVT, etc.) et à différents niveaux, soulignant son lien avec les autres disciplines et la promotion de l'égalité et des rapports de genre.

• Postulat des Pratiques :

Yael Am Salem Mingi précise que les élèves ne souhaitent pas que l'école aborde les pratiques sexuelles, considérées comme relevant de la sphère intime.

En revanche, ils attendent des outils pour la lecture critique de contenu, notamment sur les réseaux sociaux, pour discerner le vrai du faux.

• Rôle des Personnels et Mise en Œuvre :

L'EVARS est l'affaire de tous les personnels de l'éducation nationale. La co-animation est encouragée là où elle est possible pour croiser les regards.

Il est essentiel de réfléchir à la posture de l'enseignant.

Les chefs d'établissement et directeurs d'école ont un rôle déterminant dans le pilotage, la constitution d'équipes, la désignation éventuelle de référents, l'organisation de la formation et la gestion des partenariats (associations agréées, de préférence au second degré, avec un travail préparatoire conjoint et une co-animation).

• Freins et Leviers :

Les freins incluent les peurs de certaines familles et des défis organisationnels.

Les leviers incluent l'existant (ce qui est déjà fait), l'appui des pilotes académiques, des directeurs d'école et chefs d'établissement, les référents égalité, et les instances (conseils de maître, conseils d'école, conseils école-collège).

La conscientisation des personnels sur l'enjeu de santé publique et la nécessité de fournir des repères aux élèves sont cruciales.

• Mise en Œuvre Opérationnelle :

La mise en œuvre se traduit par des plans de formation pour les personnels.

Il s'agit d'accompagner les enseignants dans l'appropriation du programme et l'utilisation des ressources.

Dans le premier degré, l'organisation des séances est facilitée par le format classe unique pour l'enseignant.

Dans le second degré, la coordination est essentielle, impliquant les conseils pédagogiques et les CESCE (Comités d'éducation à la santé, à la citoyenneté et à l'environnement).

L'interdisciplinarité (lettres, philosophie, EPS, EMC, etc.) est un élément clé.

Les heures de vie de classe peuvent être mobilisées.

• Accompagnement et Formation :

L'accompagnement des personnels est une priorité.

Des groupes de formateurs experts existent dans les académies.

Des formations d'établissement et des parcours inter-degrés sont envisagés.

Des personnels ressources de proximité (infirmières, CPE, professeurs documentalistes, etc.) peuvent intervenir en co-animation.

Un plan national de formation et un parcours Magistère en ligne sont en cours de déploiement, complétés par des livrets de séances types.

• Communication :

La communication avec les familles est cruciale pour lever les appréhensions.

Le conseil d'école est une instance importante pour communiquer.

Il est essentiel de communiquer de manière positive sur la légitimité de l'école dans ce domaine, en soulignant qu'il ne s'agit pas d'aborder l'intime.

En cas de contestation ou de refus d'enseignement, il est important d'engager le dialogue, de rappeler l'obligation de cet enseignement et de s'appuyer sur les ressources académiques (cellules valeurs de la République).

Une page Eduscol dédiée et une page education.gouv.fr pour les familles sont disponibles, avec des éléments de langage, des plaquettes et une FAQ.

• Cadre Juridique :

Un point juridique rappelle que la notion de droit à la sexualité des mineurs n'est pas reconnue par les textes. La majorité sexuelle en France est fixée à 15 ans (article 227-25 du code pénal).

Toute relation sexuelle avec un mineur de moins de 15 ans est considérée comme une atteinte sexuelle, même si elle est consentie.

La loi du 21 avril 2021 a posé un seuil de non-consentement pour les mineurs de moins de 15 ans avec des majeurs et a renforcé la lutte contre l'inceste et la sexorsion.

Une clause dite "Roméo et Juliette" permet de préserver les relations entre mineurs de moins de 5 ans d'écart, sauf inceste, absence de consentement ou prostitution.

La notion de consentement valable implique plusieurs exigences cumulatives (volontaire, libre, éclairé, spécifique, réversible, exprimé, perçu).

Le contrôle des intervenants extérieurs est également mentionné comme un point délicat.

En Synthèse

L'introduction de ce programme marque une étape historique en France, offrant une opportunité institutionnelle précieuse pour l'éducation des élèves sur des sujets fondamentaux.

Il répond à un besoin criant de clarification et d'équité dans l'accès à cette éducation.

Au-delà de la prévention, le programme vise à développer la réflexion des élèves et à construire une culture commune sur ces sujets.

Sa mise en œuvre requiert une intelligence et une inventivité collectives, un accompagnement soutenu des personnels et une communication proactive avec les familles.

Il s'agit également d'un programme qui écoute les questionnements des élèves et leur offre un espace pour forger leur liberté.

Franck Durbage résume l'importance de ce programme comme une opportunité de "désinquiétude" pour les familles et les établissements privés, une chance pour la "culture" en offrant un espace de pensée et de réflexion, une occasion pour l'"intelligence collective" et l'"inventivité collective" des équipes pédagogiques, et un engagement envers la "liberté" des élèves en accueillant leurs questions et en leur permettant de cheminer.

Das verstehe ich gar nicht!

An if, elif, else block is created

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

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __ Summary In this work, the authors present a careful study of the lattice of the indirect flight muscle (IFM) in Drosophila using data from a morphometric analysis. To this end, an automated tool is developed for precise, high-throughput measurements of sarcomere length and myofibril width, and various microscopy techniques are used to assess sub-sarcomeric structures. These methods are applied to analyze sarcomere structure at multiple stages in the process of myofibrillogenesis. In addition, the authors present various factors and experimental methods that may affect the accurate measurement of IFM structures. Although the comprehensive structural study is appreciated, there are major issues with the presentation/scope of the work that need to be addressed: Major Comments 1. The main weakness of the paper is in its claim of presenting a model of the sarcomere. Indeed, the paper reports a structural study that is drawn onto a 3D schematic. There is no myofibrillogenesis model that would provide insights into mechanisms. Therefore, the use of the word model is grossly overstated.

In biology, the term “model” is used in various contexts, but it generally refers to a simplified representation of a biological system, a structure or a process. Accordingly, we consider “model” the most fitting phrase for what we present in Figure 4 (Figure 7 in the revised manuscript). These are not arbitrary 3D schematics; they are scaled representations in which the length, the number and the relative three-dimensional arrangement of thin and thick filaments are based on measurements. These measurements are primarily based on our own data (presented in the main text and provided in the supplementary materials), as published data were either lacking or inconsistent. Moreover, we would like to highlight that we do not claim to present a conceptual or mechanistic model of myofibrillogenesis, but we do present structural reconstructions or models for four developmental time points. Therefore, we disagree with the remark that “the use of the word model is grossly overstated”, as our wording fully corresponds to the common sense.

In general, the major focus and contribution of the work is unclear. How does the comprehensive nature of the measurements contribute to existing literature?

We significantly revised the text to highlight the main points more firmly, and added an additional section to help non-specialist readers to better understand our aims and findings.

Figure labels are often rather confusing - for example it is unclear why there is a B, B', B' etc instead of B,C,D, etc.

The figure labels have been revised in accordance with the reviewer’s recommendation.

Some comments in the text are not clearly tied to the figures. For example, in lines 108-109, are the authors referring to the shadow along the edges of the myofibril when saying they are not clearly defined (Figure 1C)?

The lines refer to the fact that identifying the boundary of an “object” in a fluorescence microscopy image is inherently challenging - even under ideal conditions where the object’s image is not affected by nearby signals or background noise. To improve clarity, we revised this section and now it reads: The other key parameter - myofibril diameter - is typically measured using phalloidin staining. However, accurately delineating their boundaries in micrographs is difficult - even under optimal conditions (high signal‑to‑noise ratio, no overlapping fibers, etc.; Fig. 1C). This limitation arises from the fundamental nature of light microscopy as the image produced is a blurred version of the actual structure, due to convolution with the microscope’s point spread function.

In line 116, it is unclear what "surrounding structures" the authors are referring to if the myofibrils are isolated.

We revised the text for clarity. It now states: Once isolated, myofibrils lie flat on the coverslip, aligning with the focal plane of the objective lens. This orientation allows for high-resolution, undistorted imaging and accurate two-dimensional measurements, free from interference by neighboring biological structures (e.g.: other myofibrils).

In lines 141-142, there is no reference of data to back up the claim of validation.

We addressed this mistake by including a reference to Fig. S1E (Fig. S1D in the revised manuscript).

In line 170, the authors mention the mef2-Gal4/+ strain as a Gal4 driver line but do not clearly state how this strain is different from the wildtypes or how this impacts their results.

Mef2-Gal4 is a muscle-specific Gal4 driver, often used in Drosophila muscle studies. It is a convention between Drosophila geneticists that presence of a transgene (i.e. Mef2-Gal4) changes the genetic background, and although it does not necessariliy cause any phenotypic effect, it is clearly distinguished from the wild type situation, and whenever relevant, Mef2-Gal4/+ is the preferred choice (if not the correct choice) as a control instead of wild type. As clear from our data, presence of the Mef2-Gal4 driver line does not affect the length or width of IFM sarcomeres as compared to wild type.

In lines 182-185, the authors discuss the effects of tissue embedding on morphometrics. Were factors such as animal sex, age, fiber type, etc. conserved in these experiments? If not, any differences in results may be confounding.

We fully agree with the reviewer that when testing the effect of a single variable, all other variables should remain constant. This is actually one of the main points emphasized in the results section. Additionally, this information is already provided in the Source Data files for each panel.

In lines 199-201, the authors discuss results of myofibril diameter using different preparation methods, yet no data is cited to support the claims. In line 220, the phrase "6 independent experiments" is unclear. Is each independent experiment performed using a different animal? Furthermore, are 6 experiments performed for each time point?

We substantially revised the relevant paragraphs and ensured that the corresponding data (Figure 2A in the revised manuscript) is cited each time when it is discussed. We conducted six independent experiments at each time point. This is consistently indicated in the figures and can be verified in the SourceData files (specifically, Fig3SourceData in this case). To clarify what we mean by "independent experiments," we added the following sentence to the Methods section: Experiments were considered independent when specimens came from different parental crosses, and each experiment included approximately six animals to capture individual variability.

In line 254, the authors refer to "number of sarcomeres". It must be clearly stated if this refers to sarcomeres per myofibril, image area, etc.

It is now clearly stated as: "number of sarcomeres per myofibril".

In line 274, the authors refer to "myofilament number". It must be clearly stated if this refers to myofilaments per myofibril, image area, etc.

We counted the number of myofilaments in developing myofibrils, and this is now clearly stated in the text and in the legend of Figure 3 (Figure 4 in the revised manuscript).

In line 299, the authors mention that thin filaments measured less than 560 nm in length, yet no data is cited to support this.

The previously missing reference to Figure 4 (Figure 7 in the revised manuscript) has now been added in addition to the revised Supplementary Figure 5.

In the "Quantifying sarcomere growth dynamics" section of the summary (starting from line 402) the authors introduce data that would be more naturally placed in the results and discussion section.

As suggested by the reviewer, we incorporated the key aspects of sarcomere growth dynamics into the Results and Discussion section.

In lines 422-423, it is not mentioned what the controls are for.

This was already explained in the main text between lines 167 and 173.

In the caption of Figure 1C, it is not mentioned what the red dashed lines in the microscope images represent.

The caption has been updated to include the following clarification: The red dashed lines border the ROI used for generating the intensity profiles.

In the caption of Figure 1D, the difference between the lighter and darker grey points is not mentioned.

This was already explained in each relevant figure legend. In this specific case, it is stated between lines 850 and 852: “Light gray dots represent individual measurements of sarcomere length and myofibril diameter, while the larger dots indicate the mean values from independent experiments.”

In line 849, the stated p-value (0.003) does not match that mentioned in the figure (0.0003).

We thank the reviewer for noticing this small mistake; correction was made to display the accurate p-value of 0.0003 at both places.

In line 874, it is not clear what an "independent experiment" refers to (different animal, etc.?).

We refer the reviewer to point 9, where this question has already been addressed.

Figure 2A is hard to read. Using different colored dots for different time points might help.

As suggested by the reviewer, we generated a plot with the individual points color-coded by time.

The significant figures presented in Figure 4 give a completely inaccurate representation of the variability of the measurements achieved with these techniques.

Certainly, each measured parameter exhibits inherent biological and technical variability. We have made all the raw data available to the reader through the SourceData files, and this variability is also evident in Figures 1, 2, 3, Supplementary Figure 1, 3, and 5 (Figure 1, 2, 3, 4, 6, and Supplementary Figure 1 in the revised manuscript). Also we have included an additional plot (Supplementary Figure 5 in the revised manuscript) that presents the calculated thin and thick filament lengths and their uncertainty. However, in Figure 4 (Figure 7 in the revised manuscript), our goal was to present an easily understandable visual representation of the sarcomeric structures for each time point, based on the averages of the relevant measurements.

In line 877, it should be mentioned that the number of filaments is counted per myofibril. The y-axes in the figure should also be adjusted to clarify this.

As suggested by the reviewer, both the figure legend and the plot have been updated to clearly indicate that the filament count refers to the number per myofibril.

In line 883, it is not clear what an "independent experiment" refers to (different animal, etc.?).

We refer the reviewer to point 9, where this question has already been addressed.

The statement of sample sizes in all figures is a little confusing.

Following general guidelines, we used SuperPlots to effectively present the data, as nicely demonstrated in the JCB viewpoint article by Lord et al., 2020 (PMID: 32346721). Individual measurements are shown as pooled data points, allowing readers to appreciate the spread, distribution and number of measurements. Overlaid on these pooled dot plots are the mean values from each independent experiment, with error bars representing variability between independent experiments. Sample sizes are provided for both individual measurements and independent experiments. This is now clearly explained in the Materials and Methods section, and we corrected the legends to improve clarity (“n” indicates the number of independent experiments/individual measurements).

In lines 1007-1008, the authors imply that the lattice model is needed for calculation of myofilament length. However, from the equations and previous data, it seems that this can be estimated using the confocal and dSTORM images.

As the reviewer correctly noted, myofilament length can be estimated using measurements from confocal and dSTORM images, following the equations provided. However, constructing even a simplified model requires multiple constraints to be defined and applied in a specific order. In practice, one must first determine the number and arrangement of myofilaments in a cross-sectional view of an “average sarcomere” before attempting to build a longitudinal model, where length calculations become relevant. This is now clarified in the text.

A more specific discussion of future directions is needed to put this paper in context. For example: Can anything from the overall process be used to better understand sarcomere dynamics in larger animals/humans? Can this be applied to disease modelling?

To address these questions, we have added a section titled STUDY LIMITATIONS, which states: “Our study is focused on describing the growth of IFM sarcomeres during myofibrillogenesis at the level of individual myofilaments. Additionally, we developed a user-friendly software tool for precise sarcomere size measurements and demonstrate that these measurements are sensitive to varying conditions. Whereas, this tool can be used successfully on whole muscle fiber preparations as well, our pipeline was intentionally optimized for individual IFM myofibrils ensuring higher measurement precision in our hands than other type of preparations. Thus, we predict that future work will be required to extend it to sarcomeres from other muscle tissues or species. Nevertheless, our study exemplifies a workflow how to measure sarcomere dimensions precisely. With some variations, it should be possible to adopt it for other muscles, including vertebrate and human striated muscles. To facilitate this and to enhance the accessibility and usability of this dataset, we welcome any feedback and suggestions from researchers in the field.”

One of the major claims of the paper is that there is a measurable variability with sex and other parameters. However, this data is never clearly summarized, presented (except for supplement), or discussed for its implications.

We followed the suggestion of the reviewer, and we moved this supplementary data into a main figure, and thoroughly revised the corresponding paragraphs to present and discuss the findings more clearly.

Minor Comments: 1. Lines 60-65 seem to break the flow of the introduction. As the authors discuss existing methods in literature for IFM analysis in the previous couple sentences, the following sentences should clearly state the limitations of existing methods/current gap in literature and a general idea of what the current work is contributing.

We agree with this remark, and we substantially revised the Introduction to clearly define the existing gap in the literature and to articulate how our work addresses this gap.

In line 104, the acronym for ZASPs is not spelled out.

The acronym has now been spelled out for clarity.

**Referee Cross-commenting**

I agree as well.

Reviewer #1 (Significance (Required)):

In summary, this paper provides a multi-scale characterization of Drosophila flight muscle sarcomere structure under a variety of conditions, which is potentially a significant contribution for the field. However, the paper scope is overstated in that it does not provide an actual sarcomere model. Further, there are multiple issues with data presentation that impact the readability of the manuscript.

Although it is somewhat unclear what would be “an actual sarcomere model” for the reviewer, but we cannot accept that we made on overstatement by using the word “model”, because one of the main outcomes of our work are indeed the myofilament level sarcomere models depicted in Figure 4 (Figure 7 in the revised manuscript). As said above, we do not claim that these would be molecular models, or mechanistic models or developmental models, but it makes absolutely nonsense (even in common terms!) that our scaled graphical representations (based on a wealth of measurements) should not be or cannot be called models.

As to the comment with data presentation, we thank the reviewer for the numerous suggestions, and we substantially revised the manuscript to increase clarity and overall readability.

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __ Summary: In this manuscript titled "A myofilament lattice model of Drosophila flight muscle sarcomeres based on multiscale morphometric analysis during development," Görög et al. perform a detailed analysis of morphological parameters of the indirect flight muscle (IFM) of D. melanogaster. The authors start by illustrating the range of measurements reported in the literature for mature IFM sarcomere length and width, showing a need to revisit and determine a standardized measurement. They develop a new Python-based tool, IMA, to analyze sarcomere lengths from confocal micrographs of isolated myofibrils stained with phalloidin and a z-disc marker. Using this tool, they demonstrate that sample preparation (especially mounting medium), as well as fiber type, sex, and age influence sarcomere measurements. Combining IMA, TEM, and STORM data, they measure sarcomere parameters across development, providing a comprehensive and up-to-date set of "standardized" sarcomere measurements. Using these data, they generate a model integrating all of the parameters to model sarcomeres at four discrete timepoints of development, recapitulating key phases of sarcomere formation and growth.

Major comments: Line 200 & 901 - Figure S1B - The authors make a strong statement about the use of liquid versus hardening media, and it is clear from the image provided in Figure S1 that there is a difference in the apparent sarcomere width. The identity of the "liquid media" versus the "hardening media" should be clearly identified in the Results, in addition to the legend for Figure S1. The authors show that "glycerol-based solutions" increase sarcomere width, but the Materials only list 90% glycerol and PBS. However, a frequently used liquid mounting media is Vectashield. Based on the literature, measurements in liquid Vectashield show diameters significantly less than 2.2 microns observed here with presumably 90% glycerol or PBS. Can the authors qualify this statement, or provide data that all forms of liquid mounting media cause this effect? Does this also apply to hemi-thorax and sectioned preparations, or just isolated myofibrils?

We used a PBS-based solution containing 90% glycerol as our liquid medium, as now stated in the main text. In response to the reviewer’s suggestion, we also tested a non-hardening version of Vectashield (H-1000). Myofibrils in Vectashield were significantly thicker than those in ProLong Gold but still thinner than those in the 90% glycerol–PBS solution, shown in Figure 2B. The mechanisms that could potentially explain these observations have been described in several studies (Miller et al., 2008; Tanner et al., 2011, 2012). Briefly, IFM is a densely packed macromolecular assembly. Upon removal of the cell membrane, myofibrillar proteins attract water, leading to overhydration of the myofilament lattice. This increases the spacing between filaments, resulting in an expansion of overall myofibril diameter. The extent of hydration depends on the osmolarity of the surrounding medium, as the system eventually reaches osmotic equilibrium. While both liquid media induced significant swelling, the observed differences likely reflect variations in their osmotic properties. In contrast, dehydration - an essential step in electron microscopy sample preparation - reduces the spacing between filaments, making myofibrils appear thinner. This explains why EM micrographs consistently show significantly smaller myofibril diameters (Chakravorty et al., 2017).

        Hardening media such as ProLong Gold introduce additional artifacts: during polymerization, these media shrink, exerting compressive forces on the tissue (Jonkman et al., 2020). We therefore propose that isolated myofibrils first expand due to overhydration in the dissection solution, and are then compressed back toward their *in vivo* dimensions during incubation in ProLong Gold. The average *in vivo* diameter of IFM myofibrils can be estimated without direct measurements, as it is determined by two key factors: (i) the number of myofilaments, which has been quantified in EM cross-sections in several studies (Fernandes & Schöck, 2014; Shwartz et al., 2016; Chakravorty et al., 2017) including our own, and (ii) the spacing between filaments, which can be measured by X-ray diffraction even in live *Drosophila* or under various experimental conditions (Irving & Maughan, 2000; Miller et al., 2008; Tanner et al., 2011, 2012). Our findings suggest that the effects of lattice overhydration and media-induced shrinkage are most pronounced in isolated myofibrils. In larger tissue preparations, the inter-myofibrillar space likely acts as a mechanical and osmotic buffer, reducing the extent of such distortions

Can the authors comment on whether the length of fixation or fixation buffer solution, in addition to the mounting medium, make a difference on sarcomere length and diameter measurements? This is another source of variation in published protocols.

The effect of fixation time on sarcomere morphometrics in whole-mount IFM preparations has been previously demonstrated by DeAguero et al. (2019), as briefly noted in our manuscript. To extend these findings, we performed a comparison using isolated myofibrils, assessing morphometric parameters after fixation for 10, 20 (standard) and 60 minutes. We found no difference between the 10- and 20-minute fixation conditions; however, fixation for 60 minutes resulted in significantly increased myofibril diameter (and these data are now shown in Supplementary Figure 1C). A comparable increase in thickness was also observed when using a glutaraldehyde-based fixative. These results suggest that more extensively fixed myofibrils may better resist the compressive forces exerted by hardening media.

Line 237-238. The authors conclude that premyofibrils are much thinner than previously measured. The use of Airyscan to more accurately measure myofibril width at this timepoint is a good contribution, as indeed diffraction and light scatter likely contribute to increased width measured in light microscopy images. I also wonder, though, how well the IMP software performs in measuring width at 36h APF, given how irregular the isolated myofibrils at this stage look (wide z-lines but thinner and weaker H and I bands as shown in Fig. 2B)?

The reviewer is correct that measurements during the early stages of myofibrillogenesis require additional effort. However, in addition to its automatic mode, IMA can also operate in semi-automatic or manual modes, ensuring complete control over the measurements. Myofibril width is determined from the phalloidin channel at the Z-line (as described in the software’s User Guide and Supplementary Figure 2), where it is at its thickest.

Also, how much of the difference in sarcomere width arises due to effects of "stripping" components off of the sarcomere at the earliest timepoint (for example alpha-actinin or Zasp proteins)?

A comparison between isolated myofibrils and those from microdissected muscles (Supplementary Figure 3B, Figure 3C in the revised manuscript) shows that the isolation process does not alter the morphometric measurements of sarcomeres. Moreover, the measured myofibril width aligns well with what we expect based on the number of myofilaments observed in TEM cross-sections of myofibrils at 36 hours APF (Figure 3A, now Figure 4A in the revised manuscript), supporting the consistency of our model.

Myofibrils at early timepoints do contain more than 4-12 sarcomeres in a line (they extend the full length of the myofiber), so it is possible they are breaking due to the detergent and mechanical disruption induced by the isolation method.

The reviewer is correct - myofibrils likely span the full length of the myofiber from the onset of myofibrillogenesis. However, during the isolation of individual myofibrils, they often break, and even mature myofibrils typically fragment into pieces of about 300 µm in length (illustrated in Figure 1E, now Figure 2A in the revised manuscript). Importantly, our measurements show that this fragmentation does not affect the assessed sarcomere length or width (as shown in Supplementary Figure 3B, now Figure 3C in the revised manuscript).

Line 312 - What does "stable association" mean in this context? The authors mention early timepoints lack stable association of alpha-Actinin or Zasp52, and they reference Fig. S4C, but this figure only shows 72h and 24 AE, not 36h and 48 h APF. Previous reports have seen localization of both alpha-Actinin and Zasp52, so presumably the detergent or mechanical isolation is stripping these components off of the isolated myofibrils up until 72h.

In agreement with previous reports, we also detected both α-Actinin (as shown in former Supplementary Figure 3B, now Figure 3C) and Zasp52 in microdissected IFM starting from 36 hours APF. However, these markers were largely absent from the isolated myofibrils of young pupae (36 to 60 hours APF). By 60 hours APF, strong α-Actinin and Zasp52 staining became evident in isolated myofibrils, whereas dTitin epitopes were clearly detectable from the earliest time point examined. This indicates that some proteins, such as α-Actinin and Zasp52, can be lost during the isolation process, whereas others like dTitin are retained and this differential sensitivity appears to depend on developmental stage. A likely explanation is that α-Actinin and Zasp52 are recruited early to Z-bodies but are only fully incorporated as more mature Z-disks form between 48 and 60 hours APF. This incomplete incorporation at the earlier stages could account for their loss during the isolation process. This interpretation is supported by our morphological analysis of the Z-discs, as shown in the dSTORM dataset (former Figure 3B, B’’, now Figure 4C, E) and in longitudinal TEM sections (former Supplementary Figure 5B, now in Figure 6B). Because α-Actinin and Zasp52 are not detected in isolated myofibrils at 36 and 48 hours APF, they are not included in Figure S4C (Figure 5C in the revised manuscript). This is explained in the updated figure legend.

This same type of issue comes up again in Lines 325-334, where the authors talk about 3E8 and MAC147. They state that 3E8 signal significantly declines in later stages and that MAC147 is not suitable to label myofibrils in young pupae, but they only show data from 72 APF and 24 AE (which looks to have decent staining for both 3E8 and MAC147). A clearer explanation here would be helpful.

To put it simply: we used one myosin antibody to label the A-band in the IFM of 36h APF and 48h APF animals, and a different antibody for the 72h APF and 24h AE stages. In more detail: Myosin 3E8 is a monoclonal antibody targeting the myosin heavy chain and labels the entire length of mature thick filaments except for the bare zone (former Supplementary Figure 4D, now in Figure 5D), suggesting its epitope is near the head domain. As a result, we expect a uniform A-band staining - excluding the bare zone - which is exactly what we observe in the IFM of young pupae (36h APF and 48h APF; formerly Figure 3B, now Figure 4C in the revised manuscript). However, at 72h APF and 24h AE, Myosin 3E8 produces a different staining pattern: two narrow stripes flanking the bare zone and two broader, more diffuse stripes near the A/I band junction (former Supplementary Figure 4D, now Figure 5D). This change is likely due to restricted antigen accessibility at these later developmental stages - a common issue in the densely packed IFM - making this antibody unsuitable for reliably measuring thick filament length in these stages.

MAC147 is another monoclonal antibody against Mhc that recognizes an epitope near the head domain. However, it only works reliably in more mature myofibrils (72h APF and 24h AE; formerly Figure 3B, now Figure 4C in the revised manuscript), likely due to its specificity for a particular Mhc isoform. This is why we do not include images from earlier developmental stages using this antibody. We added a revised, concise explanation in the main text for general readers, and provided a more detailed description for specialist readers in the legend of Supplementary Figure 4D (updated as Figure 5D in the revised manuscript).

Figure 3B. The authors show the H, Z, and I lengths in B', B', and B' and discuss these lengths in the text (lines 305-320). It would also be nice to actually have the plots showing the measured/calculated lengths for thin and thick filaments. These are mentioned in the results, but I cannot find the plots in the figures and there is no panel reference.

A summary table of the measured and calculated parameters is provided in Fig4SourceData (Fig7Source Data in the revised manuscript). However, following the reviewer’s suggestion, we also generated an additional plot (Supplementary Figure 5 in the revised manuscript) that displays the calculated thin and thick filament lengths.

Line 400. Does the model in Figure 4 actually have molecular resolution as the authors claim? From these views, thick and thin filaments appear to be represented by cylindrical objects. Localization of specific molecules would require further modeling with individual proteins. Or do the authors mean localization from STORM imaging relative to the ends of the thick and/or thin filaments? The model itself is a useful contribution, but based on Figure 4, resolution of individual molecules is not evident.

The reviewer is correct; and we fully agree that we do not present a molecular model of sarcomeres in this study - nor do we claim to. Instead we present a myofilament level model. Nevertheless, the scaled myofilament lattice model we introduce could serve as a geometric constraint when constructing supramolecular models of sarcomeres. As the reviewer rightly notes, implementing such an approach would require additional effort.

The main Results section of the text is condensed into 4 figures. However, I found myself flipping back and forth between the main figures and the supplement continuously, especially parts of Supplemental Figures 1, 3, 4, and 5. With such large amounts of detail in the Results relying on the supplement, it may be worth considering reorganizing the main and supplemental figures, and having 7 main figures, to include important panels that are currently in the supplement (esp. Fig S1B, S1C, S1D, S3B, S4, S5).

We found it a very useful suggestion, and we substantially reorganized the figures in the revised manuscript according to the recommendations of the reviewer.

Minor comments: On the plots in Fig. S1B, D, and F, it is hard to see the color of the dots because the red error bars are on top of them. Can the other distribution dots be tinted the correct color or the x-axis labels be added, so it is clear which dataset is which?

We significantly enlarged the dots to enhance visual clarity.

Line 142 needs a reference to Figure S1, Panel E, which shows the accuracy and precision measurements.

The requested panel reference has now been included in the revised manuscript.

Lines 198 - is this range from the above publications? Needs to be clearly cited.

The range has indeed been estimated using measurements from the aforementioned publications, and this point is now further clarified in the revised text.

Figure S3B is confusing - why do the blow-ups overlap both the top (presumably microdissected) and the bottom (presumably isolated) images? The identity of microdissected images should be labeled, as they are hard to see underneath of the blown-up images and the identity of individual image planes wasn't immediately obvious.

We refined the panel structure of Figure S3B (Figure 3C in the revised manuscript) to enhance clarity as the reviewer suggested.

Line 298. By "misaligned," do the authors mean the pointed ends are not uniformly anchored in the z-disc, leading to the wide z-disc measurements? At this early stage, I'm not sure "misaligned" is the right word - perhaps "were not yet aligned in register at the z-disc" or something similar.

We revised the text for clarity. It now reads: At 36 hours APF, thin filaments had not yet aligned in perfect register at the Z-disc, with most measuring less than 560 nm in length - and exhibiting considerable variability.

Figure S6 - spelling mistake in label of panel A, "sarcomer" should be "sarcomere"

The typo is corrected.

Line 487. Spelling "Zaps52" should be "Zasp52"

The typo is corrected.

Line 887. Spelling "Myofilement" should be "Myofilament"

The typo is corrected.

Line 946-947. In the legend for Supp. Fig. 3., the authors should specify which published datasets on sarcomere length are shown in the figure by including the references in the legend. Presumably the "isolated individual myofibrils" are the blue "this study" lines, leaving the "microdissected muscles" as the magenta "previous reports" on the figure. Without the reference, it is not clear if these are microdissected, isolated myofibrils, hemi-thorax sections, cryosections, or another preparation method for the "previous reports" data.

The references have now been added to both the figure and its legend.

**Referee Cross-commenting**

I agree with the comments from the other reviewers. Many of the major themes are consistent across the reviews, including regarding the model, preparation methods, and the software tool.

Reviewer #2 (Significance (Required)):

Strengths: This manuscript is an important contribution to the field of sarcomere development. The authors use modern technologies to revisit variation in morphometric measurements in the literature, and they identify parameters that influence this variation. Notably, sex-specific differences, DLM versus DVM measurements, and mouting media are potential contributors to the variability. Combining TEM and STORM with a confocal timecourse of isolated myofibrils, they refine previously published values of sarcomere length and width, and add more comprehensive data for filament length, number and spacing. This highly accurate timecourse demonstrates continual growth of sarcomeres after 48 h APF, and correct some inconsistencies from previous large-scale timecourse datasets. These data are very valuable to the field, especially Drosophila muscle biologists, and will serve as a comparative resource for future studies. Weaknesses: At early timepoints, loss of sarcomere components through mechanical or detergent-mediated artifacts may influence the authors' measurements. In addition, isolating myofibrils is not always the most ideal approach, as it loses information on myofiber structure as well as organization and structure of the myofibrils in vivo.

We believe that the control experiments we presented here adequately demonstrate that sarcomere measurements are not affected by the myofibril isolation process at early timepoints (Figure 3C). Nevertheless, we certainly agree with the reviewer that isolated myofibrils alone cannot capture the entire complexity of muscle tissues, and additional approaches should also be applied in complex projects. Yet, we are confident that our approach offers the most reliable and efficient method for precise morphometric analysis of the sarcomeres, and although alone it is very unlikely to be sufficient to address all questions of a muscle development project, it can still be applied as a very useful and robust tool.

The point regarding liquid versus hardening mounting media is valuable, but remains to be tested and validated with the diverse liquid and hardening media used by other labs.

Whereas it would not be feasible for us to test all possible liquid and hardening media used by others in all possible conditions, we tested the effect of Vectashield (the most commonly used liquid media) according to the suggestion of the reviewer, and the results are now included in the manuscript. We think that this is a valuable extension of the list of the materials and conditions we tested, although we need to point out that our primary goal was not necessarily to test as many conditions as possible (because the number of those conditions is virtually endless), rather to raise awareness among colleagues that these variables can significantly impact the data obtained and affect their comparability.

The IMA software seems to be designed specifically for analysis of isolated myofibrils, and it is unclear if it would work for other types of IFM preparations.

As stated in the manuscript, IMA is a specialized tool designed for the analysis of individual myofibrils. While it can also process other types of IFM preparations in semi-automatic or manual modes, we believe these approaches compromise both efficiency and accuracy. This is further clarified in the revised manuscript.

A last point is that TEM and STORM may not be available on a regular basis to many labs, hindering wide implementation of the approach used in this manuscript to generate very accurate and detailed measurements of sarcomere morphometrics.

Regarding the availability of TEM and STORM, we acknowledge that these techniques are not universally accessible. However, that is exactly one major value of our work that our open-source software tool now allows researchers to generate valuable data using only a confocal microscope in combination with our published datasets.

Audience: Scientists who study sarcomerogenesis or Drosophila muscle biology.

My expertise: I study muscle development in the Drosophila model.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __ Summary: This manuscripts presents a computational tool to quantify sarcomere length and myofibril width of the Drosophila indirect flight muscles, including developmental samples. This tool was applied to confocal and STORM super-resolution images of isolated myofibrils from adult and developing flight muscles. Thick filament numbers per myofibril were counted during development of flight muscles. A myofilament model of developing flight muscle myofibrils is presented that remains speculative for the early developmental stages.

Major comments: 1. The title of the manuscript appears unclear. What is a lattice model? Lattice is an ordered array. The filament array parameters for mature flight muscles was aready measured. It appears that the authors speculate how this order might be generated during sarcomere assembly, which is not studied in this manuscript as it is limited to periodic arrays after 36h APF.

As the reviewer correctly points out, a lattice refers to an ordered array - in the case of IFM sarcomeres, this includes both thin and thick filaments. Therefore, the phrase "myofilament lattice model of Drosophila flight muscle sarcomeres" specifically describes a model representing the spatial organization of these filament arrays within the sarcomere. To provide additional clarity for readers, we have revised the title to include more context. It now reads: Developmental Remodeling of Drosophila Flight Muscle Sarcomeres: A Scaled Myofilament Lattice Model Based on Multiscale Morphometrics

To create a model of these arrays, three essential pieces of information are required:

1) The length of the filaments,

2) The number of filaments, and

3) The relative position of the filaments.

While some direct measurements are available in the literature, and others can be used to calculate the necessary values, available data is often contradictory or simply different from each other (as described in our ms) making them unsuitable for constructing scaled models of the myofilament arrays. In contrast to that, here we present a comprehensive and consistent set of measurements that enabled us to build models not only of mature sarcomeres but also of sarcomeres at three other significant developmental time points.

Regarding the mention of "sarcomere assembly" in line 37, we intended it to refer to the growth of the sarcomeres, not their initial formation. We do not speculate about sarcomere assembly anywhere in the text. In fact, we have clearly stated multiple times that our focus is on the growth of the IFM myofilament array during myofibrillogenesis. Nevertheless, to avoid confusion, we revised the phrase in line 37 to "sarcomere growth".

The authors review the flight muscle sarcomere length literature and conclude it is variable because of imprecise measurements. Likely this is partially true, however, more importantly is that the sarcomere length and width changes during isolation methods of the myofibrils, as well as by various embedding methods, as the authors show here as well in Figure 1B-E.

We dedicated two sections of the Results - “An automated method to accurately measure sarcomeric parameters” and “IFM sarcomere morphometrics are affected by sex, age, fiber type, and sample preparation” - to exploring potential sources of variability in published IFM sarcomere measurements. Based on these analyses, we conclude that such variability stems from both measurement imprecision and biological or technical factors, including sex, age, fiber type and, of foremost, sample preparation. Because it is difficult to quantify the relative impact of each variable across published studies, we have refrained from speculations about the relative contribution of the different factors in the revised manuscript.

Hence, I find the strongly claims the authors make here surprising, while they are isolating the myofibrils. Hence, these myofibrils are ruptured at the ends, relaxed or contracted, depending on buffer choice and passive tension is released. On page 8, the authors correctly state that the embedding medium causes shrinkage of the myofibrils. While isolation is state of the art for electron microscopy techniques, other methods including sectioning or even whole mount preparation have been developed for high resolution microscopy of IFMs that avoid these artifacts. Unfortunately, this manuscript only uses isolated myofibrils that were fixed and then mechanically dissociated by pipetting. This method likely induces variations as seen by the large spread of sarcomere length reported in Figure 1C (2.8-3.9µm?) and even bigger spreads for myofibril widths. Are these also seen in tissue without dissections? Unfortunately, no comparision to intact flight muscles are reported with the here presented quantification tool. The sarcomere length spread in the developmental samples is even larger.

The major issue raised in this paragraph is the use of isolated myofibril versus intact flight muscle preparations. The reviewer claims that the latter might be superior because the isolated myofibrils are ruptured at their ends. Clearly, the intact IFMs cannot be imaged in vivo by light microscopy because the adult fly cuticle is opaque. To visualize these muscles, one must open the thorax, but neither microdissection nor sectioning preserves them perfectly, even the cleanest longitudinal cuts sever some myofibrils, and dissection itself can damage the tissue. Although published images often show only the most pristine regions, the practice of selective cropping cannot be taken as a scientific argument. Here, by comparing sarcomere lengths measured in isolated myofibrils with those from whole-mount longitudinal DLM sections and microdissected IFM myofibers, we demonstrate that isolation does not alter sarcomere length (Figure 1E, now Figure 2A in the revised manuscript). As to myofibril width, it is determined by two parameters: the number of myofilaments and the spacing between them. In vivo filament spacing has been measured directly, and filament counts can be obtained from EM cross-sections of DLM fibers. Combining these values gives an expected in vivo myofibril diameter. While isolated myofibrils measure thinner than those in whole-mount or microdissected samples (Figure 1E, now Figure 2A in the revised manuscript), their diameter closely matches this in vivo estimate (see manuscript, lines 187–198). Therefore, we conclude that isolated myofibrils (even if it seems counterintuitive for this reviewer) are superior for sarcomere measurements than whole-mount preparations - and that is why we primarily rely on them here.

Despite that, we certainly recognize that isolated myofibrils cannot recapitulate every aspect of an IFM fiber, and the need for whole-mount preparations during our IFM studies is not questioned by us.

        In addition to this general answer to the issues raised in the above paragraph of the reviewer, we would like to specifically reflect for some of the remarks:

„Unfortunately, this manuscript only uses isolated myofibrils that were fixed and then mechanically dissociated by pipetting.”

This is a false statement that “this manuscript only uses isolated myofibrils” as we used different preparation methods for initial comparisons (see Figure 1E, now Figure 2A in the revised manuscript). Additionally, unlike the reviewer assumed, the myofibrils were first dissociated and then fixed, and not vice versa (as described in the Materials and Methods section).

„This method likely induces variations as seen by the large spread of sarcomere length reported in Figure 1C (2.8-3.9µm?) and even bigger spreads for myofibril widths. Are these also seen in tissue without dissections?”

This remark makes absolutely no sense, as we do not report sarcomere length values in Figure 1C at all. By assuming that the reviewer meant to refer to Figure 1B, it still remains a misunderstanding or a false statement, because that panel refers to the variations found in published data (not in our current data), and this is clearly explained both in the figure legend and the main text. Regardless of that, the stated spread does not appear unusual. In the article by Spletter et al. (2018), the authors report a similar spread (2.576–3.542 µm) for sarcomere length in mature IFM using whole-mount DLM cross-sections. As to the second question here, we do observe a comparable spread in other preparations as well (see Figure 1E, now Figure 2A in the revised manuscript), which is again the opposite conclusion as compared to the (clearly false) assumption of the reviewer.

„Unfortunately, no comparision to intact flight muscles are reported with the here presented quantification tool. „

This is also a false statement; as we do report comparison to whole mount cross sections which we belive the reviewer considers „intact” in Figure 1E (Figure 2A in the revised manuscript).

„The sarcomere length spread in the developmental samples is even larger.”

The spread is not larger at all than in previous reports, as clearly shown in Supplementary Figure 3A.

The authors suggest that there are sex differences in sarcomere length and pupal development duration. This is potentially interesting, unfortunately they then use mixed sex samples to analyse sarcomeres during flight muscle development.

In the revised manuscript, we now provide a more detailed description of a subtle post-eclosion difference in IFM sarcomere metrics between male and female Drosophila. We attribute this variation to the well-established observation that female pupae develop slightly faster than males, a property that may last till shortly after eclosion. Confirming this experimentally would require considerable effort with limited scientific benefit. Nonetheless, the subtle nature of this sex-linked variation reinforced our decision to include IFM sarcomeres from both male and female flies in our comprehensive developmental analysis.

The IMA software tool lacks critical assessment of its performance compared to other tools and the validation presented is too limited. IMA seems to generate systematic errors, based on Fig S1E, as it does not report the ground truth. These have to be discussed and compared to available tools. The principles of fitting used in IMA seem well adapted to IFM myofibrils in low noise conditions, but may not be usable in other situations. This should be assessed and discussed.

IMA is a specialized software tool developed to address a specific need, notably, to accurately and efficiently measure sarcomere length and myofibril diameter in individual IFM myofibril images labeled with both phalloidin and Z-disc markers. For our purposes, it remains the most suitable and reliable option, and we are confident that IMA outperforms all other available tools. To demonstrate this, we have included a table comparing the few alternatives (MyofibrilJ, SarcGraph, and sarcApp) capable of both measurements, which further supports our conclusion. Given IMA's focused application, extensive validation under artificially low signal-to-noise conditions is unnecessary. While IMA may introduce minor systematic errors (~0.01 µm for sarcomere length and ~0.03 µm for myofibril diameter), these are negligible errors relative to the limitations of the simulated ground truth data used for benchmarking. This point is now addressed in the manuscript.

It is claimed that validation was achieved on simulated IFM images: do the authors rather mean simulated isolated IFM myofibril images? This is not quite the same in terms of algorithm complexity and this should be corrected if this is the case.

Indeed, we used simulated individual IFM myofibril images, where both phalloidin labeling and Z-disc labeling are present. This is clearly shown in Supplementary Figure 1A, and stated in the text when first introduced: „we generated artificial images of IFM myofibrils with known dimensions, simulating the image formation process”

The authors need to revise their comparison to other tools. It is incomplete and seemingly incorrect. It should be clearly stated that IMA is limited to isolated myofibrils, which is a far easier segmentation task than what other tools can do, such as sarcApp (Neininger-Castro et al. 2023, PMID: 37921850). Defining the acronym would be valuable in that sense. The claim line 129-130 "none can adequately measure myofibril diameter from regular side view images" is unclear. What do the authors refer to as "side view images"? Sarc-Graph from Zhao et al 2021, PMID: 34613960, and sarcApp from Neininger-Castro et al. 2023 provide sarcomere width, in conditions that are very similar to what IMA does, e.g. on xy images based on the documentation provided on github. A performance comparison with these tools would be valuable. Does installation and use of IMA require computational skills?

Motivated by the reviewer’s comments, we revised the section introducing IMA. However, we chose not to include an extensive comparison with other software tools, as this would divert the manuscript’s focus without impacting the main conclusions. Instead, we added a summary table highlighting the key requirements for analyzing IFM sarcomere morphometrics from Z-stacks of phalloidin- and Z-line-labeled individual myofibrils and compared the available tools accordingly. In our experience, most software tools are developed to address very specific problems, even those marketed as general-purpose solutions. Consequently, applying them beyond their intended scope often results in reduced efficiency and suboptimal performance. Although sarcApp was initially available as a free tool, one of its dependencies (PySimpleGUI 5) has since adopted a commercial license model. Using a trial version of PySimpleGUI 5, we evaluated sarcApp on our dataset. The software is limited to single-plane image input, hence raw image stacks must be preprocessed into a suitable format, which is a time consuming step. Furthermore, implementation requires basic programming proficiency, as parameter adjustments must be performed directly within the source code to accommodate dataset-specific configurations. Once appropriately configured, sarcApp reliably quantifies both sarcomere length and myofibril width with accuracy comparable to that of IMA. However, it lacks built-in diagnostic feedback or visualization tools to facilitate measurement verification or troubleshooting during batch processing. SarcGraph also supports only single-plane image inputs and requires prior image preprocessing. Additionally, images must be loaded manually one by one, which further reduces processing efficiency. Parameter optimization relies on direct code modification through a trial-and-error process, demanding a certain level of programming proficiency. Even with these adjustments, the software frequently introduces artifacts - such as Z-line splitting - when applied to our dataset. Even when segmentation is successful, sarcomere length is often overestimated, whereas myofibril diameter is consistently underestimated. As compared to these issues, IMA was designed for ease of use and does not require any programming experience to install or operate. It can automatically handle raw microscopic image formats without the need for preprocessing. Segmentation is fully automated, with no requirement for parameter tuning. The tool provides visual feedback during both the segmentation and fitting steps, allowing users to confidently assess and validate the results. IMA produces accurate and precise measurements of sarcomere length and diameter. Batch processing is enabled by default, significantly improving efficiency when analyzing multiple images. Finally, unlike the reviewer stated, IMA is not limited to isolated myofibrils. It is optimized for isolated myofibrils (i.e. full performance is achieved on these samples), but it can also work on whole-mount preparations in semi-automatic and manual mode, which still allow precise measurements (with some reduction in processing efficiency).

As to the minor comments, the acronym IMA was already defined in lines 541 and 917–918 of the original submission, as well as on the software’s GitHub page. Additionally, we replaced the phrase "side view images" with "longitudinal myofibril projections" to improve clarity.

How do the authors know that the bright phallodin signal visible that the Z-disc at 36h and 48h APF is due to actin filament overlap, as suggested? An alternative solution are more short actin filaments at the early Z-discs.

It is widely accepted that the bright phalloidin signal at the Z-line in mature sarcomeres reflects actin filament overlap (e.g., Littlefield and Fowler, 2002; PMID: 11964243). Accordingly, in slightly stretched myofibrils, this bright signal diminishes, and in more significantly stretched myofibrils, a small gap appears (e.g., Kulke et al., 2001; PMID: 11535621). The width of this bright phalloidin signal corresponds to the electron-dense band seen in longitudinal EM sections (Figure 3B and Supplementary Figure 5B, now Figure 4B and Figure 6B in the revised manuscript) and matches the actin filament overlap observed in Z-disc cryo-EM reconstructions from other species (Yeganeh et al., 2023; Rusu et al., 2017), where individual thin filaments can be resolved. By extension, we interpret the bright phalloidin signals at the Z-discs observed at 36 h and 48 h APF as arising from similar actin filament overlaps, given their comparable width to the electron-dense Z-bodies described both in our study (Supplemantary Figure 5B, now Figure 6B in the revised manuscript) and by Reedy and Beall (1993). While we cannot fully rule out the reviewer’s alternative interpretation, for the time being it remains a bold speculation without supporting evidence, and therefore we prefer to stay with the conventional view.

The authors seem to doubt their own interpretation that actin filaments shrink when reading line 304 and following. This is obviously critical for the "model" presented.

Unlike the reviewer implies, we certainly do not doubt our own interpretation, but to avoid confusion we revised the corresponding paragraph in the manuscript and provided more details on our explanation, and we also provide a brief overview of it here. Between 36 h and 48 h APF we observe a pronounced structural transition in the IFM sarcomeres. In EM cross-sections, the previously irregular myofilament lattice becomes organized into a regular hexagonal pattern (Figure 3A, now Figure 4A in the revised manuscript) with filament spacing typical of mature myofibrils (Supplementary Figure 5A, now Figure 6A in the revised manuscript). In longitudinal EM sections, the elongated, amorphous Z-bodies condense along the myofibril axis to form well-defined, adult-like Z-discs (Supplementary Figure 5B, now Figure 6B in the revised manuscript). Similarly, dSTORM imaging shows that the Z-disc associated D-Titin epitopes become more compact and organized during this period (Supplementary Figure 4E, now Figure 5E in the revised manuscript). The edges of the thick filament arrays also become more sharply defined, and the appearance of a distinct bare zone indicates the establishment of a regular register (Figure 3B, now Figure 4B in the revised manuscript). By assuming that a similar reorganization occurs within the thin filament array, the apparent length of the thin filament array would decrease—not due to shortening of individual filaments, rather due to improved alignment. Although we cannot directly resolve single thin filaments, this reorganization offers the most plausible explanation for the observed change.

Minor comments: 1. Figure S1B is not called out in the text.

The reviewer might have missed this, but in fact, it is explicitly called out in line 181.

Fig. 1: Please state whenever images are simulations?

We appreciate the reviewer’s observation that the simulated IFM myofibril images are indistinguishable from the real ones, as this confirms the adequacy of these images for testing our software tool. However, this is already clearly indicated: Figure 1B features simulated images, as noted in the figure legend (line 824), and Supplementary Figure 1A similarly shows simulated images, as stated both in the legend (line 886) and in the figure.

Fig. 2: Length-width correlation - please provide individual points color-coded by time point?

As suggested by the reviewer, we generated a plot with the individual points color-coded by time.

"newly eclosed males and females, we observed that males have slightly shorter sarcomeres and narrower myofibrils". Please provide a statistical test supporting the difference.

In the revised manuscript, we compared sarcomere length and myofibril width between males and females from 0 to 96 hours AE using a two-way ANOVA with Sidak’s multiple comparisons test. We expanded our description of these observations in the main text, and details of the statistical analysis are now included in the revised figure legend (Figure 1E). Briefly, newly eclosed males showed slightly shorter sarcomeres than females - a consistent but non-significant trend (p = 0.9846) - which resolved by 12 h AE, with sarcomere lengths remaining similar thereafter (p = 0.1533; Figure 1E). In contrast, myofibril width was significantly narrower in the newly eclosed males (p = 0.0374), but this difference disappeared between 24 and 48 h AE as myofibrils expanded in diameter during post-eclosion development (p

Were statistical tests performed using animals as sample numbers? Please clarify in the images what are animal and what are sarcomere numbers.

Following standard guidelines, statistical tests were performed using the means of independent experiments, as noted in the figure legends. For each experiment, we used approximately 6 animals, and this information is now included in the Materials and Methods section.

mef2-Gal4 should be spelled Mef2-GAL4 according to Flybase.

This has been corrected in the revised text and figures.

Are the images shown in Figure 2B representative? 96h AE appears thicker than 24h AE but the graph reports no difference.

We aimed to show representative images, however, in the case of 96h APF we may have selected a wrong example. We now changed the image for a more appropriate one.

The authors only found Zasp52 and alpha-Actinin at the Z-discs from 72h APF onwards, which is different to what others have reported.

Similarly to former reports, we detected both α-Actinin (see Supplementary Figure 3B, now Figure 3C in the revised manuscript) and Zasp52 in microdissected IFMs as early as 36 hours APF. However, these markers were largely absent in isolated myofibrils from the early pupal stages (36–60 hours APF). By 60 hours APF, strong α-Actinin and Zasp52 signals were clearly visible in isolated myofibrils (the closest timepoint captured by dSTORM is 72h APF). As discussed in the manuscript, a likely explanation is that α-Actinin and Zasp52 are recruited to developing Z-bodies early on but are only fully incorporated into mature Z-discs between 48 and 60 hours APF. Their incomplete integration at earlier stages may lead to their loss during the isolation procedure.

Thick filament length during development has also been estimated by Orfanos and Sparrow, which should be cited (PMID: 23178940)

Contrary to the reviewer’s claim, the article 'Myosin isoform switching during assembly of the Drosophila flight muscle thick filament lattice' does not provide any measurements or estimates of thick filament length; it only includes a schematic illustration where the length of the thick filaments is not based on empirical data.

**Referee Cross-commenting**

I also agree with my colleagues comments, which are largely consistent.

Reviewer #3 (Significance (Required)):

This paper introduces a tool to measure sarcomere length. Easy to use tools that do this as well already exist. The tool can also measure sarcomere width, which it claims as unique point, which is not the case, see above comment.

We are aware that other tools exist to measure sarcomere parameters (and we did not claim the opposite in our ms), nevertheless, we need to emphasize that based on our comparisons, IMA is superior to all three alternatives. Three software tools could, in principle, be used to measure both sarcomere length and myofibril diameter: MyofibrilJ, SarcGraph, and sarcApp. However, two of them - MyofibrilJ and SarcGraph - consistently under- or overestimate these values. The only tool capable of performing these measurements reliably, sarcApp, is no longer freely available, it requires programming expertise, and it does not support raw image file formats, making it difficult to use in practice (see above comments for more details). In contrast, IMA is user-friendly and does not require any programming expertise to install or operate. It can automatically process raw microscopic image formats without the need for preprocessing. Segmentation is fully automated, and no parameter tuning is necessary. The tool offers visual feedback on both the segmentation and fitting processes, enabling users to validate results with confidence. IMA delivers accurate and precise measurements of sarcomere length and diameter. Additionally, batch processing is enabled by default, significantly enhancing workflow efficiency.

This manuscript shows that depending on the isolation and embedding media sarcomere and myofibrils width changes and hence artifacts can be introduced. While this is not suprising, it has not been well controlled in a number of previous publications.

Furthermore, this paper measures sarcomere length and width during flight muscle development and consolidates what was already known from previous publications. Sarcomeres are added until 48 h APF, then they grow in diameter. Despite strong claims in the text, I do not see any significant novel findings how sarcomeres grow in length or width or any significant deviations from what has been published before. This is even documented in the supplementary graphs by comparing to published data. It is close to identical.

The overall process has been quantitatively described in four previous studies (Reedy and Beall, 1993, Orfanos et al., 2015, Spletter et al., 2018, Nikonova et al., 2024). While there is general agreement on the pattern of sarcomere development, significant discrepancies exist among these datasets; differences that become particularly problematic when attempting to build structural models. More specifically: Reedy and Beall (1993) report substantially shorter sarcomeres compared to all other datasets, including ours. This discrepancy likely stems from two factors: (i) their use of longitudinal EM sections, where sample preparation is known to cause considerable tissue shrinkage; and (ii) the maintenance of their flies at 23 °C, a temperature that clearly delays development relative to the more commonly used 25 °C. Interestingly, Spletter et al. (2018) and Nikonova et al. (2024) conducted their experiments at 27 °C, which also deviates from standard conditions and may complicate comparisons. Orfanos et al. (2015) suggested that mature sarcomere length is reached by approximately 88 hours after puparium formation (APF). In contrast, our measurements show that sarcomeres continue to elongate beyond this point, reaching mature length between 12 and 24 hours post-eclosion. All four earlier studies report a mature sarcomere length around 3.2-3.3 µm, only slightly longer than the ~3.2 µm length of thick filaments (Katzemich et al., 2012; Gasek et al., 2016). This would imply an I-band length below ~100 nm, which is an implausibly short distance. In contrast, our data, along with several recent studies (González-Morales et al., 2019; Deng et al., 2021; Dhanyasi et al., 2020; DeAguero et al., 2019), support a mature sarcomere length of approximately 3.45 µm, placing the length of the I-band at around 250 nm. This estimate is more consistent with high-resolution structural observations from longitudinal EM sections and fluorescent nanoscopy (Szikora et al., 2020; Schueder et al., 2023). Although Reedy and Beall (1993) provide limited data on myofibril diameter during myofibrillogenesis, a more detailed quantitative analysis is presented by Spletter et al. (2018) and by Nikonova et al. (2024). Interestingly, Spletter et al. report two separate datasets - one based on longitudinal sections and another on cross-sections of DLM fibers. While the measurements are consistent during early pupal stages, they diverge significantly in mature IFMs (1.116 ± 0.1025 µm vs. 1.428 ± 0.0995 µm), a discrepancy that is not addressed in their publication. Nikonova et al. (2024) report even narrower myofibril widths (0.9887 ± 0.1273 µm). Moreover, the reported diameters of early myofibrils in all three datasets are nearly twice as large as those reported by Reedy and Beall (1993) and in our own measurements, directly contradicting the reviewer's claim that the values are “close to identical.” Finally, our data clearly demonstrate that both the length and diameter of IFM sarcomeres reach a plateau in young adults, which is a key developmental feature not examined in previous studies.

In summary, we did not and we do not intend to claim that our conclusions are novel as to the general mechanisms of myofibril and sarcomere growth. Rather, our contribution lies in providing a high-precision, robust analysis of the growth process using a state-of-the-art toolkit, resulting in a comprehensive description that aligns with structural data obtained from TEM and dSTORM. We therefore believe that expert readers will recognize numerous valuable aspects of our approaches that will advance research in the field.

Counting the total number of thick filaments during myofibril development is nice, however, this also has been done (REEDY, M. C. & BEALL, C. 1993, PMID: 8253277). In this old study, the authors reported the amount of filament across one myofibril. How does this compare to the new data here counting all filaments? Unfortunatley, this is not discussed.

Indeed, the study by Reedy and Beall (1993) was primarily based on longitudinal DLM sections, which were used to estimate myofibril width and count the number of thick filaments on this lateral view images (e.g., ~15 thick filaments wide at 75 hours APF), but total thick filament numbers were not provided. While such data could theoretically be used to estimate the number of myofilaments per myofibril, these estimations would depend on the unverified assumption that the section includes the full width of the myofibril. Additionally, the study did not provide standard deviations or the number of measurements, limiting the interpretability and reproducibility of their findings. These points highlight the need for a more rigorous and quantitative approach. For these reasons, we chose to quantify myofilament number using cross-sections, providing more accurate and reliable assessments.

Besides the difference between the lateral versus cross sections, a direct comparison of our studies is further complicated by differences in the developmental time points and experimental conditions used. Reedy and Beall (1993) reports data from pupae aged 42, 60, 75 and 100 hours, as well as from adults, whereas we present data from 36, 48, and 72 hours APF, and from 24 hours after eclosion, which corresponds to approximately 124 hours APF. Moreover, their experiments were carried out at 23 °C, a temperature that somewhat slows down pupal development and results in adult eclosion at around 112 hours APF, as stated in their study. In contrast, our experiments were carried out at the more commonly used 25 °C, where adults typically emerge around 100 hours APF.

Collectively, these differences prevented meaningful comparisons between the two datasets, and therefore we preferred to avoid lengthy discussions on this issue.

Đã thử sử dụng Android Studio Cloud, nhưng sau phiên làm việc thì không thể Bookmark URL nên chưa biết lưu Project ở đâu 17/05/2025 : Sẽ thử nghiệm lại sau

Author response:

The following is the authors’ response to the original reviews

Reviewer #1 (Public review):

The ventral nerve cord (VNC) of organisms like Drosophila is an invaluable model for studying neural development and organisation in more complex organisms. Its well-defined structure allows researchers to investigate how neurons develop, differentiate, and organise into functional circuits. As a critical central nervous system component, the VNC plays a key role in controlling motor functions, reflexes, and sensory integration.

Particularly relevant to this work, the VNC provides a unique opportunity to explore neuronal hemilineages - groups of neurons that share molecular, genetic, and functional identities. Understanding these hemilineages is crucial for elucidating how neurons cooperate to form specialized circuits, essential for comprehending normal brain function and dysfunction.<br /> A significant challenge in the field has been the lack of developmentally stable, hemilineage-specific driver lines that enable precise tracking and measurement of individual VNC hemilineages. The authors address this need by generating and validating a comprehensive, lineage-specific split-GAL4 driver library.

Strengths and weaknesses

The authors select new marker genes for hemilineages from previously published single-cell data of the VNC. They generate and validate specific and temporally stable lines for almost all the hemilineages in the VNC. They successfully achieved their aims, and their results support their conclusions. This will be a valuable resource for investigating neural circuit formation and function.

We thank the reviewer for her/his positive comments and time reviewing our manuscript. We are pleased that the reviewer recognized the value of our work in generating a comprehensive, lineage-specific split-GAL4 driver library for VNC hemilineages. We agree that this will be a critical resource for investigating neural circuit formation and function, and we are encouraged by the positive comments regarding the novelty and potential impact of our approach.

Reviewer #1 (Recommendations for the authors):

I have no suggestions for further experiments, data, or analyses. There are some grammatical errors and referencing issues throughout, but the editors will hopefully catch them.

We appreciate the reviewer’s comments regarding the grammatical errors and referencing issues and have carefully checked the revised manuscript.

Reviewer #2 (Public review):

It is my pleasure to review this manuscript from Soffers, Lacin, and colleagues, in which they identify pairs of transcription factors unique to (almost) every ventral nerve cord hemilineage in Drosophila and use these pairs to create reagents to label and manipulate these cells. The advance is sold as largely technical-as a pipeline for identifying durably expressed transcription factor codes in postmitotic neurons from single cell RNAseq data, generating knock-in alleles in the relevant genes, using these to match transcriptional cell types to anatomic cell types, and then using the alleles as a genetic handle on the cells for downstream explication of their function. Yet I think the work is gorgeous in linking the expression of genes that are causal for neuron-type-specific characteristics to the anatomic instantiations of those neurons. It is astounding that the authors are able to use their deep collective knowledge of hemilineage anatomy and gene expression to match 33 of 34 transcriptional profiles. Together with other recent studies, this work drives a major course correction in developmental biology, away from empirically identified cell type "markers" (in Drosophila neuroscience, often genomic DNA fragments that contain enhancers found to be expressed in specific neurons at specific times), and towards methods in which the genes that generate neuronal type identity are actually used to study those neurons. Because the relationship between fate and form/function is built into the tools, I believe that this approach will be a trojan horse to integrate the fields of neural development and systems neuroscience.

We thank the reviewer for their time reviewing our manuscript, generous compliments, and appreciation of the potential of our study to drive a major shift in developmental biology, moving away from traditional marker-based methods toward utilizing the genes that mark neuronal type identity in “omics” datasets. Much like the Trojan Horse, which, though initially a concealed and subtle tool, we hope that the strategy outlined here will have continued impact, as we and others plan to leverage future high-resolution and developmental series of scRNAseq datasets to generate driver lines to target neuronal cell types with uttermost precision.

Reviewer #2 (Recommendations for the authors):

Line 126-127: I'm not sure if it is true to say "most TFs in the CNS are expressed in a hemilineage-specific manner." As the authors haven't formally interrogated how different neuronal features relate to expression patterns of all ~600 Drosophila TFs, how about replacing "most" with "many?"

The reviewer makes an excellent point. Work by Lacin and colleagues has demonstrated via genetic studies that lineage-specific transcription factors that regulate the specification and differentiation of postembryonic neurons are stably expressed during development. This was documented for 15 transcription factors in Lacin et al., 2014, and our lab has identified additional examples since. When we refer to the stable expression of transcription factors, we refer to such transcription factors, not the complete set of ~600 transcription factors described to date. We have added this citation to clarify this statement and replaced p6 line 135 ”Most”  by “Many”. We have also address this now in the introduction (p5 line 109-116). Of note, as we conducted this study, we found that is closer to be a rule than an exception that if a transcription factor acted cluster as marker, it was also stably expressed during development. Thus, a growing number of transcription factors is now documented to be stably expressed in a hemilineage-specific manner

Line 265: Typo? 334 should be 34?

We thank the reviewer for noting this type error. We have corrected this typographical error.

Line 522: Refs 56, 57 here related to chinmo, mamo, br-c don't show br-c or mamo mark temporal cohorts of postmitotic neurons. Consider adding PMID: 19883497, 18510932, and 31545163.

We thank the reviewer for pointing this out and have added these references that demonstrate that broad, Mamo and Chinmo mark temporal cohorts in the developing adult CNS (p17 line 535).

Reviewer #3 (Public review):

Soffers et al. developed a comprehensive genetic toolkit that enables researchers to access neuronal hemilineages during developmental and adult time points using scRNA-seq analysis to guide gene cassette exchange-based or CRISPR-based tool building. Currently, research groups studying neural circuit development are challenged with tying together findings in the development and mature circuit function of hemilineage-related neurons. Here, authors leverage publicly available scRNA-seq datasets to inform the development of a split-Gal4 library that targets 32 of 34 hemilineages in development and adult stages. The authors demonstrated that the split-Gal4 library, or genetic toolkit, can be used to assess the functional roles, neurotransmitter identity, and morphological changes in targeted cells. The tools presented in this study should prove to be incredibly useful to Drosophila neurobiologists seeking to link neural developmental changes to circuit assembly and mature circuit function. Additionally, some hemilineages have more than one split-Gal4 combination that will be advantageous for studies seeking to disrupt associated upstream genes.

Strengths:

Informing genetic tool development with publicly available scRNA-seq datasets is a powerful approach to creating specific driver lines. Additionally, this approach can be easily replicated by other researchers looking to generate similar driver lines for more specific subpopulations of cells, as mentioned in the Discussion.

The unification of optogenetic stimulation data of 8B neurons and connectomic analysis of the Giant-Fiber-induced take-off circuit was an excellent example of the utility of this study. The link between hemilineage-specific functional assays and circuit assembly has been limited by insufficient genetic tools. The tools and data present in this study will help better understand how collections of hemilineages develop in a genetically constrained manner to form circuits amongst each other selectively.

Weaknesses:

Although cell position, morphology (to some extent), and gene expression are good markers to track cell identity across developmental time, there are genetic tools available that could have been used to permanently label cells that expressed genes of interest from birth, ensuring that the same cells are being tracked in fixed tissue images.

Although gene activation is a good proxy for assaying neurochemical features, relying on whether neurochemical pathway genes are activated in a cell to determine its phenotype can be misleading given that the Trojan-Gal4 system commandeers the endogenous transcriptional regulation of a gene but not its post-transcriptional regulation. Therefore, neurochemical identity is best identified via protein detection. (strong language used in this section of the paper).

The authors mainly rely on the intersectional expression of transcription factors to generate split-Gal4 lines and target hemilineages specifically. However, the Introduction (Lines 97-99) makes a notable point about how driver lines in the past, which have also predominantly relied on the regulatory sequences of transcription factors, lack the temporal stability to investigate hemilineages across time. This point seems to directly conflict with the argument made in the Results (Lines 126-127) that states that most transcription factors are stably expressed in hemilineage neurons that express them. It is generally known that transcription factors can be expressed stably or transiently depending on the context. It is unclear how using the genes of transcription factors in this study circumvents the issue of creating temporally stable driver lines.<br />

We thank the reviewer for their time to thoroughly and carefully review our manuscript. We appreciate the reviewer’s comments on its strengths, and we to hope that this body of work will prove to be incredibly useful to Drosophila neurobiologists seeking to link neural developmental changes to circuit assembly and mature circuit function. Likewise, we also appreciate the reviews careful consideration of its weaknesses, as the reviewer raises valid points. We have addressed these in our revised manuscript and believe this has significantly improved our manuscript.

Weakness 1: Although cell position, morphology (to some extent), and gene expression are good markers to track cell identity across developmental time, there are genetic tools available that could have been used to permanently label cells that expressed genes of interest from birth, ensuring that the same cells are being tracked in fixed tissue images.

The reviewer is fully correct, and we are aware of techniques developed by the laboratories of U. Banerjee, T. Lee, and J. Truman that can make transient GAL4 expression permanent, such as G-TRACE and lineage filtering. A common feature of these techniques is that effector activity is permanent (FLP-mediated removal of the FRT-flanked stop codon preceding GFP in G-TRACE or LexA in lineage filtering) but not the GAL4 activity, which is needed to take advantage of the vast UAS based effector lines such as RNAi libraries. For example, the study of Harris et al., 2015 from the Truman lab beautifully showed the strength of this kind of approaches for labeling the hemilineages but their approach cannot be used for functional studies for the reasons mentioned above. Fly lines using these approaches already have several transgenes and require the addition of several more to be used for functional studies. Our approach requires only two transgenes and is compatible with all UAS lines. One additional advantage of the splitGAL4 combinations that we identify here is that they are inserted in genes that are stably expressed throughout larval and pupal development in postmitotic cells, such that they can be used for functional manipulations during development. We emphasized this point in the discussion on page 16 under the heading “Mapping and manipulating morphological outgrowth patterns of hemilineages during development”. 

Weakness 2: Although gene activation is a good proxy for assaying neurochemical features, relying on whether neurochemical pathway genes are activated in a cell to determine its phenotype can be misleading given that the Trojan-Gal4 system commandeers the endogenous transcriptional regulation of a gene but not its post-transcriptional regulation. Therefore, neurochemical identity is best identified via protein detection. (strong language used in this section of the paper).

We thank the reviewer for bringing up this important point. We agree that the Trojan-GAL4 approach will not faithfully recapitulate expression of genes that undergo posttranscriptional regulation. Our previous eLife paper (Lacin et al., 2019) showed that this is the case for Trojan driver lines for the ChAT gene. This study demonstrated that ChAT drivers unexpectedly but strongly labeled many GABAergic and Glutamatergic neurons in both the brain and VNC. With RNA in situ hybridization and immunostainings approaches, we showed that these neurons indeed express ChAT mRNA but not the protein. After our publication, another group showed a class of miRNA binds to the 3’UTR of the ChAT gene and regulates its expression post-transcriptionally (Griffith 2023). We believe that one major reason the Trojan driver lines do not faithfully recapitulate this expression pattern is due to the presence of the Hsp70 transcriptional terminator located at the 5’ end of the trojan exon which prematurely ends the transcript and affects the host gene’s 3’ UTR regulation. For this reason, we have recently generated new Trojan plasmids which allow the retention of the 3’UTR of the host gene in the transcript. We have revised the result section “Neurotransmitter use on pages 11-12 to address this point and have modified the language.

Weakness 3: The authors mainly rely on the intersectional expression of transcription factors to generate split-Gal4 lines and target hemilineages specifically. However, the Introduction (Lines 97-99) makes a notable point about how driver lines in the past, which have also predominantly relied on the regulatory sequences of transcription factors, lack the temporal stability to investigate hemilineages across time. This point seems to directly conflict with the argument made in the Results (Lines 126-127) that states that most transcription factors are stably expressed in hemilineage neurons that express them. It is generally known that transcription factors can be expressed stably or transiently depending on the context. It is unclear how using the genes of transcription factors in this study circumvents the issue of creating temporally stable driver lines.

We thank the reviewer for pointing out this apparent paradox, which we have clarified in the manuscript (p4. lines 94-102). Driver lines in the past have relied on the intersection of genes to label a defined set of neurons, which helped marking more narrow cell populations compared to enhancer traps in the adult CNS. Elegant and elaborate screening methods have been devised to identify hemidriver combinations that mark specific subset of neurons in the adult (Meissner et al, 2025 (eLife 98405.2) and citations therein). However, these hemidrivers do not leverage the expression pattern of hemilineage marker genes. Instead, their expression is controlled by random 2-3 kb genomic fragments. We and others observed that these drivers are not stably expressed during development. Hence, hemidrivers combinations that work beautifully to target adult neuronal cel populations can oftentimes not be directly used for developmental studies. Work by Lacin et al. 2014 has demonstrated that transcription factors that mark hemilineages are oftentimes stably expressed in the embryo larvae and even adult. When we made driver lines for these TF, using artificial exons, its complete endogenous enhancers elements remain intact. Consequently, we find that Trojan driver lines recapitulate the expression pattern of the transcription factor gene in which it was inserted, and the hemidrivers are stably expressed during development. Hence, leveraging scRNAseq cluster markers for hemilineages and converting them to Trojan driver lines, the approach we took in this paper, has proven a powerful method to generate stable driver lines for developmental studies.

Reviewer #3 (Recommendations for the authors):

(1) Line 14: Affiliations typo should be correct to "St. Louis".

We thank the reviewer for catching this and have corrected the typo.

(2) Line 26: "model systems have focused on only on a few".

We have replaced the words “a few regions” by “select regions” to better contrast that studies to date have been performed, but not at CNS level, due to the lack of genetic driver lines.

(3) Line 52: The use of "medium" here is ambiguous without a comparison.

We agree that the term “medium” in line 52 could be ambiguous without context, and we appreciate your suggestion to clarify this. The revised sentence now reads: “Drosophila has served as a powerful model system to investigate how neuronal circuits function due to its medium complexity compared to vertebrate models”

(4) Line 91-92: Consider shortening to "of behavioral circuit assembly".

Thank you for this suggestion, we have revised p4 lines 90-91 to: “Thus, taking a hemilineage-based approach is essential for a systematic and comprehensive understanding of behavioral circuit assembly during development in complex nervous systems.”

(5) Line 216-217: Consider establishing what the expected morphology and neurochemical phenotype for 2A neurons is before presenting findings.

This suggestion is well-taken, and agree that this paragraph did not fully get the point across we were trying to make. This purpose of this paragraph is to explain our workflow of how we assigned 16 hemilineages to orphan clusters, which is why we present the data in this order and present the morphology of hemilineage 2A last. To accommodate the reviewer’s suggestion, we have now clarified our approach before diving into the results to improve the flow of this paragraph (p8 lines 218-223). Briefly, the starting point to annotate the 16 orphan scRNAseq clusters was each time taking one orphan scRNAseq cluster, picking its top cluster marker genes that had not been established yet as marker genes for any hemilineage, and visualizing the morphology of the neurons that expressed such cluster marker using a reporter line for the cluster marker or an antibody stain for its protein. We then compared this to documented hemilineage morphologies, and to narrow down our search, we compared the observed trajectories to those of unannotated hemilineages that used the same neurotransmitter as the orphan scRNAseq. The evaluation of the documented morphologies of the hemilineages came at the last part of our method to annotate the hemilineages to orphan scRNAseq clusters, which is why we chose to present the expected morphology of a hemilineage at the end.

(6) If "neurochemical" phenotype and "neurotransmitter" identity are sometimes used interchangeably but seem to mean the same thing. Consider choosing one term throughout.

We thank the reviewer for this suggestion and have changed the terminology to “neurotransmitter use” (p11-12 lines 326-359).

(7) Line 235: MARCM technique citation needed.

We thank the reviewer for pointing this out, the citation (no. 37, p9 line 249) was present in the method section, but we had inadvertently omitted it in the main text and we have now corrected this.

(8) Line 281: typo, should be "patterns".

We thank the reviewer for noting this and have corrected this.

(9) Line 469: End of sentence needs a ".".

We have added the punctuation mark.

(10) Line 516: "driver line combinations to express...".

We have inserted the word “to” to correct it.

(11) Please make sure that the correct genotypes are matched in the figure legends and Table 1. For instance, knot-GAL4-DBD is listed as the hemi driver for 10B neurons in Figure 3 but only knot-p65.AD is listed in Table 1.

We thank the reviewer for catching this, we made a mistake and the correct hemidriver combination used in Figure 3L i: knot-GAL4-AD with hb9-GAL4-DBD. We have updated the legend and carefully checked the legends and tables.

(12) Consider making different color choices for readability when possible and be consistent with labeling CadN. For instance, in Figure 1 the magenta color has three separate meanings: CadN, Acj6, and unc-4. Either of the three genes can be mistaken for the other for a reader mainly paying attention to the magenta color. I find that one color can mean two things in a figure if organized properly but any more begs for confusion. Also, CadN can be easily labeled if used in a new figure (e.g. Figure 1-Supplment 1).

We thank the reviewer for this insightful observation and have adjusted figure 1 so that cadN is displayed in blue and reporter genes expressing Acj6, Unc-4 or their intersection in green. The legend is modified to reflect these changes.

(13) If Seurat object changes or additional quality control steps were taken from the original studies, please provide these changes. Similarly, provide any scRNA-seq code used or cite code used for readers to access. Also, provide a section in the methods briefly describing how genes were chosen (criteria) for tool development.

We thank the reviewer for nothing we had not described our scRNA analysis pipeline and criteria to select transcription factors in the methods section of the manuscript. We have added this section at p19 lines 548-558. Briefly, we used the Seurat object generated by Allen et al., 2015, and did not change quality control steps, normalizations or scaling. Candidate genes to make split-GAL4 drivers from were chosen based on their ability to mark the clusters defined by Allen et al. We did not use computer-based algorithms and made a list of the top cluster markers. Then, we made binary combinations amongst these cluster markers and with hemilineages markers we had identified before (Lacin et al, 2014; Lacin et al 2019), and used the code generated by Allen et al., 2015 (deposited on Github) with Seurat v5 to test if these combinations marked unique clusters. We then prioritized testing these combinations based on the availability of antibodies, BAC lines and CRiMIC/MiMIC constructs to validate their expression pattern prior to creating split-GAL4 lines for these candidates.

(14) In regard to the seemingly contradictory argument that most transcription factors are stably expressed when most drivers of the past used regulatory elements of transcription factors: the paper could be strengthened by either a) describing how older driver lines differ from the lines presented in the paper or b) remarking on the endogenous temporal stability of the transcription factors used in this study.

We thank the reviewer for pointing this out, and we agree that it is necessary to clarify this apparent paradox since it is essential for understanding the impact of the present work. We have revised our manuscript described in our response to weakness 1.

DOI: 10.1038/s41467-025-59529-0

Resource: RRID:IMSR_JAX:000058

Curator: @dhovakimyan1

SciCrunch record: RRID:IMSR_JAX:000058

What is this?

DOI: 10.1038/s41467-025-59529-0

Resource: RRID:IMSR_JAX:000664

Curator: @dhovakimyan1

SciCrunch record: RRID:IMSR_JAX:000664

What is this?

DOI: 10.1016/j.isci.2025.112584

Resource: (IMSR Cat# CRL_028,RRID:IMSR_CRL:028)

Curator: @areedewitt04

SciCrunch record: RRID:IMSR_CRL:028

What is this?

DOI: 10.1016/j.isci.2025.112584

Resource: (IMSR Cat# CRL_572,RRID:IMSR_CRL:572)

Curator: @areedewitt04

SciCrunch record: RRID:IMSR_CRL:572

What is this?

DOI: 10.1016/j.celrep.2025.115674

Resource: RRID:IMSR_CRL:194

Curator: @areedewitt04

SciCrunch record: RRID:IMSR_CRL:194

What is this?

remove code

remove code

remove code

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

This manuscript is a focused investigation of the phosphor-regulation of a C. elegans kinesin-2 motor protein, OSM-3. In C-elegans sensory ciliary, kinesin-2 motor proteins Kinesin-II complex and OSM-3 homodimer transport IFT trains anterogradely to the ciliary tip. Kinesin-II carries OSM-3 as an inactive passenger from the ciliary base to the middle segment, where kinesin-II dissociates from IFT trains and OSM-3 gets activated and transports IFT trains to the distal segment. Therefore, activation/inactivation of OSM-3 plays an essential role in its ciliary function.

Strengths:

In this study, using mass spectrometry, the authors have shown that the NEKL-3 kinase phosphorylates a serine/threonine patch at the hinge region between coiled coils 1 and 2 of an OSM-3 dimer, referred to as the elbow region in ubiquitous kinesin-1. Phosphomimic mutants of these sites inhibit OSM-3 motility both in vitro and in vivo, suggesting that this phosphorylation is critical for the autoinhibition of the motor. Conversely, phospho-dead mutants of these sites hyperactivate OSM-3 motility in vitro and affect the localization of OSM3 in C. elegans. The authors also showed that Alanine to Tyrosine mutation of one of the phosphorylation rescues OS-3 function in live worms.

Weaknesses:

Collectively, this study presents evidence for the physiological role of OSM-3 elbow phosphorylation in its autoregulation, which affects ciliary localization and function of this motor. Overall, the work is well performed, and the results mostly support the conclusions of this manuscript. However, the work will benefit from additional experiments to further support conclusions and rule out alternative explanations, filling some logical gaps with new experimental evidence and in-text clarifications, and improving writing before I can recommend publication.

We appreciate Reviewer #1’s comments and suggestions. We have now provided additional evidences and discussions to further support our conclusions and fill the logical gaps. We have also provided alternative explanations to our data and improved writing.

Reviewer #2 (Public review):

Summary:

The regulation of kinesin is fundamental to cellular morphogenesis. Previously, it has been shown that OSM-3, a kinesin required for intraflagellar transport (IFT), is regulated by autoinhibition. However, it remains totally elusive how the autoinhibition of OSM-3 is released. In this study, the authors have shown that NEKL-3 phosphorylates OSM-3 and releases its autoinhibition.

The authors found NEKL-3 directly phosphorylates OSM-3 (although the method is not described clearly) (Figure 1). The phophorylated residue is the "elbow" of OSM-3. The authors introduced phospho-dead (PD) and phospho-mimic (PM) mutations by genome editing and found that the OSM-3(PD) protein does not form cilia, and instead, accumulates to the axonal tips. The phenotype is similar to another constitutive active mutant of OSM-3, OSM-3(G444A) (Imanishi et al., 2006; Xie et al., 2024). osm-3(PM) has shorter cilia, which resembles with loss of function mutants of osm-3 (Figure 3). The authors did structural prediction and showed that G444E and PD mutations change the conformation of OSM-3 protein (Figure 3). In the single-molecule assays G444E and PD mutations exhibited increased landing rate (Figure 4). By unbiased genetic screening, the authors identified a suppressor mutant of osm-3(PD), in which A489T occurs. The result confirms the importance of this residue. Based on these results, the authors suggest that NEKL-3 induces phosphorylation of the elbow domain and inactivates OSM-3 motor when the motor is synthesized in the cell body. This regulation is essential for proper cilia formation.

Strengths:

The finding is interesting and gives new insight into how the IFT motor is regulated.

Weaknesses:

The methods section has not presented sufficient information to reproduce this study.

We appreciate that Reviewer #2 is also positive to our study. We have now provided sufficient information in the revised Methods section.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Major Concerns

(1) Why do the authors think that NEKL-3 phosphorylates OSM-3 in the first place? This seems to come out of nowhere and prior evidence indicating that NEKL-3 may be phosphorylating OSM-3 is not even mentioned in the Introduction.

We thank the Reviewer for raising this important point. Our hypothesis that NEKL-3 phosphorylates OSM-3 stems from prior findings in our lab. In a previous study (Yi et al., Traffic, 2018, PMID: 29655266), we identified NEKL-4, a member of the NIMA kinase family, as a suppressor of the OSM-3(G444E) hyperactive mutation. This discovery prompted us to explore the broader role of NIMA kinases in regulating OSM3. Subsequent genetic screens (Xie et al., EMBO J, 2024, PMID: 38806659) revealed that both NEKL-3 and NEKL-4 suppress multiple OSM-3 mutations, further supporting their functional interaction. Given the established role of NIMA kinases in phosphorylation-dependent processes (Fry et al., JCS, 2012, PMID: 23132929; Chivukula et al., Nat. Med., 2020, PMID: 31959991; Thiel, C. et al. Am. J. Hum. Genet. 2011, PMID: 21211617; Smith, L. A. et al., J. Am. Soc. Nephrol., 2006, PMID: 16928806), we hypothesized that NEKL-3/4 may directly phosphorylate OSM-3 to modulate its activity.

To test this hypothesis, we expressed recombinant C. elegans NEKL-3 and OSM-3 proteins and conducted in vitro phosphorylation assays. While we were unable to obtain active recombinant NEKL-4 (limitations noted in the revised text), our experiments with NEKL-3 revealed phosphorylation at residues 487-490 (YSTT motif) in OSM-3’s tail region, as confirmed by mass spectrometry. These findings are now explicitly contextualized in the Introduction and Results sections of the revised manuscript.

Page #4, Line #11:

“...In our previous study (Yi et al., Traffic, 2018, PMID: 29655266), a genetic screen targeting the OSM-3(G444E) hyperactive mutation identified NEKL-4, a member of the NIMA kinase family, as a suppressor of this phenotype. This finding, combined with reports that NIMA kinases regulate ciliary processes independently of their canonical mitotic roles (Fry et al., JCS, 2012, PMID: 23132929; Chivukula et al., Nat. Med., 2020, PMID: 31959991; Thiel, C. et al. Am. J. Hum. Genet. 2011, PMID: 21211617; Smith, L. A. et al., J. Am. Soc. Nephrol., 2006, PMID: 16928806), prompted us to investigate whether NIMA kinases modulate OSM-3-driven intraflagellar transport. We hypothesized that NEKL-3/4, as paralogs within this family, might directly phosphorylate OSM-3 to regulate its motility...”

Page #4, line #26:  

“... To determine whether NIMA kinase family members could directly phosphorylate

OSM-3, we purified prokaryotic recombinant C. elegans NEKL-3/NEKL-4 and OSM3 protein in order to perform in vitro phosphorylation assays. We were able to obtain active recombinant NEKL-3 but not NEKL-4. The in vitro phosphorylation assays showed that NEKL-3, directly phosphorylates OSM-3 (Fig. 1A-B, Appendix Table S1). Subsequent mass spectrometric analysis revealed phosphorylation at residues 487-490, which localize to the conserved "YSTT" motif within OSM-3’s C-terminal tail region ...”

(2) The authors need to characterize the proteins they expressed and purified for in vitro ATPase and motility assays. Are these proteins monomers or dimers?

For our in vitro ATPase and motility assays, OSM-3 was expressed in E. coli BL21(DE3) and purified using established protocols (Xie et al., EMBO J, 2024, PMID: 38806659; Imanishi et al., JCB, 2006, PMID: 17000874). To confirm its oligomeric state, we analyzed recombinant OSM-3 by size-exclusion chromatography coupled with multiangle light scattering (SEC-MALS). As reported in Xie et al. (2024), OSM-3 (~80 kDa monomer) elutes with a molecular weight of 173–193 kDa under physiological buffer conditions, consistent with a homodimeric assembly. These findings confirm that the functional unit used in our assays is the biologically relevant dimer. This characterization has been added to the revised manuscript on Page #35, Line #7.

“…OSM-3 was expressed in E. coli BL21(DE3) and purified for in vitro assays using established protocols (REFs). Size-exclusion chromatography coupled with multiangle light scattering (SEC-MALS) (Xie et al., EMBO J., 2024) confirmed that recombinant OSM-3 forms a homodimer (173–193 kDa) under physiological conditions, ensuring its dimeric state remained intact....” 

(3) The authors primarily used PD and PM mutations, which affect all four amino acids in the region. This may or may not be physiologically relevant. Figure 5 indicates that T489 is a critical regulatory site. However, this conclusion is undermined by reliance on PD mutations, which affect all four amino acids. Creating PM (T489E) and PD (T489A) mutations based on WT OSM-3 would better reflect physiological relevance. In vitro assays with a single phosphomimic or phosphor-dead mutation at residue 489 are missing at the end of this story. This would better link Figure 5 with the rest of the manuscript.

We thank the reviewer for this constructive critique. Below, we address the concerns and integrate new data to strengthen the link between T489 and autoinhibition:

To probe the regulatory role of T489 phosphorylation, we generated osm-3(T489E) (phosphomimetic, PM) and osm-3(T489A) (phospho-dead, PD) mutant animals. Strikingly, both mutants formed axonal puncta (Figure S7), recapitulating the hyperactive phenotype of the OSM-3G444E mutant. While the similar puncta formation in PM and PD mutants initially appeared paradoxical, this observation underscores the necessity of dynamic phosphorylation cycling at T489 for proper autoinhibition. Specifically, the PD mutant (T489A) likely disrupts phosphorylationdependent autoinhibition stabilization, leading to constitutive activation, where as the PM mutant (T489E) may mimic a "locked" phosphorylated state, preventing dephosphorylation-dependent release of autoinhibition in cilia and trapping OSM-3 in an aggregation-prone conformation. These results highlight T489 as a structural linchpin whose post-translational modification dynamically regulates motor activity. While the precise molecular mechanism—such as how phosphorylation modulates tailmotor domain interactions—remains to be elucidated, our data conclusively demonstrate that perturbing T489 (even in isolation) destabilizes autoinhibition, driving puncta formation and the constitutive activity.

We have integrated the above paragraph in the revised manuscript on page #8, line #27.

(4) There seems to be a disconnect between the MT gliding assays in Figure 4C and single molecule motility assays in Figure 4E. The gliding assays show that all constructs can glide microtubules at near WT speeds. Yet, the motility assays show that WT and PM cannot land or walk on MTs. The authors need to explain why this is the case. Is this because surface immobilization of kinesin from its tail disrupts autoinhibition? Alternatively, the protein preparation may include monomers that cannot be autoinhibited and cannot land and processively walk on surface-immobilized microtubules (because they only have one motor domain) but can glide microtubules when immobilized on the surface from their tail.

The surface immobilization of OSM-3 via its tail domain disrupts autoinhibition, a phenomenon previously observed in other kinesins such as kinesin-1 (Nitzsche et al, Methods Cell Biol., 2010, PMID: 20466139). In our assays, OSM-3 was nonspecifically immobilized on glass surfaces, enabling microtubule gliding by motors whose autoinhibition was relieved through tail anchoring. Critically, the PD and PM mutations reside in the tail region and do not alter the intrinsic properties of the motor head domain. Consequently, once autoinhibition is released via immobilization, the gliding velocities reflect the conserved motor head activity, which is expected to remain comparable across all constructs. While we cannot entirely rule out the presence of monomeric OSM-3 in solution, several lines of evidence argue against this possibility. First, the mutations are located in the elbow region, which is dispensable for motor dimerization. Second, SEC-MALS analysis from prior studies confirms that purified OSM-3 exists predominantly as dimers in solution. 

We have discussed these issues in the revised text on page #10, line #18: 

“…In our gliding assays, OSM-3PM has an increased gliding speed of 0.69 ± 0.07 μm/s (Fig. 4 C-D), similar to PD mutant. PD and PM mutations are confined to the elbow region, leaving the motor head’s mechanochemical properties intact. Upon tail immobilization—which releases autoinhibition—the gliding speeds reflect motor head activity. Single-molecule assays, however, directly resolve their native regulatory states: PD mutants are constitutively active, whereas PM mutants persist in an autoinhibited state (Fig. 4E-G). Although monomeric OSM-3 could theoretically mediate singlemotor gliding, the previous SEC-MALS data demonstrate that OSM-3 purifies as stable dimers (Xie et al., EMBO J, 2024, PMID: 38806659). Thus, dimeric OSM-3 is perhaps the predominant functional species in our assays…”

(5) An alternative explanation for the data is that both PD and PM mutations result in loss-of-function effects, disrupting OSM-3 activity. For instance:

a) In Figure 2C, both mutations cause shorter cilia than the wild type (WT).

b) In Figure 4A, both mutations result in higher ATPase activity than WT.

c) In Figure 4D, both mutations show increased gliding velocity compared to WT. These results suggest the observed effects could stem from loss of function rather than phosphorylation-specific regulation.

Although PD and PM mutations exhibit superficially similar "loss-of-function" phenotypes in certain assays, they mechanistically disrupt motor regulation in distinct ways:

a) Ciliary Length (Figure 2C) PD Mutants: Hyperactivation causes OSM-3-PD to prematurely aggregate into axonal puncta, preventing ciliary entry. Consequently, cilia are built solely by the weaker Kinesin-II motor, which only constructs shorter middle segments.

PM Mutants: OSM-3-PM retains autoinhibition during transport (enabling ciliary entry) but cannot be dephosphorylated in cilia. This blocks activation, leaving OSM-3-PM partially functional and resulting in cilia intermediate in length between WT and PD.

We have discussed this issue in the revised text on page #5, line #30:

“…These findings indicate that OSM-3-PM is in an autoinhibited state capable of ciliary delivery, yet fails to achieve full activation due to defective dephosphorylation. This incomplete activation results in suboptimal motor function and intermediate ciliary length phenotypes (Fig.2 B-C). In contrast, OSM-3-PD exhibits constitutive activation leading to aggregation into axonal puncta, which completely abolishes its ciliary entry capacity (Fig.2 A-B)...”

b) ATPase Activity (Figure 4A)

PD Mutants: Fully autoinhibition-released (98.15% of KHC ATPase activity), consistent with constitutive activation.

PM Mutants: Show partial ATPase activity (34.28% of KHC), reflecting imperfect phosphomimicry. While the DDEE substitution introduces negative charges, it fails to fully replicate the steric/kinetic effects of phosphorylated tyrosine (Y486; phenyl ring absent), resulting in incomplete autoinhibition stabilization. Despite this, the residual inhibition is sufficient to phenocopy shorter cilia in vivo.

We have discussed this issue in the revised text on page #7, line#19:

“…The PM mutant’s partial ATPase activity (34.28% of KHC) might arise from imperfect phosphomimicry—while the DDEE substitution introduces negative charges, it lacks the steric bulk of phosphorylated tyrosine (pY487). And this incomplete mimicry allows residual autoinhibition, sufficient to limit ciliary construction in vivo...”

c) Microtubule Gliding Velocity (Figure 4D)

Gliding Assay Limitation: Tail immobilization artificially releases autoinhibition, masking regulatory differences. Thus, all constructs (PD, PM) exhibit similar velocities (~0.7 µm/s), reflecting conserved motor head activity.

Single-Molecule Assay (Figure 4E): Directly resolves native autoinhibition states:

PD mutants show robust motility (autoinhibition released).

PM mutants remain largely inactive (autoinhibition retained).

We have discussed this issue in the revised text on page #10, line#18:

“…In our gliding assays, OSM-3PM has an increased gliding speed of 0.69 ± 0.07 μm/s (Fig. 4 C-D), similar to PD mutant. PD and PM mutations are confined to the elbow region, leaving the motor head’s mechanochemical properties intact. Upon tail immobilization—which releases autoinhibition—the gliding speeds reflect motor head activity. Single-molecule assays, however, directly resolve their native regulatory states: PD mutants are constitutively active, whereas PM mutants persist in an autoinhibited state (Fig. 4E-G)...”

Minor Suggestions and Concerns

(1) Lines 60-66: References that support these observations are missing from this section.

We have added the relevant references.

(2) Lines 66-67: I would revise this sentence as "It remains unclear how OSM-3 becomes enriched...".

We have made the changes.

(3) Line 85: The authors should describe how they perform these assays (i.e. recombinantly expressed NEKL-3 and OSM-3, are these C. elegans proteins, and which expression system was used...).

We have described them in the main text and methods

Page #4 line #26

“...To determine whether NIMA kinase family members could directly phosphorylate OSM-3, we purified prokaryotic recombinant C. elegans NEKL-3/NEKL-4 and OSM-3 protein in order to perform in vitro phosphorylation assays...”

Page #35 line#12

“...Basically, point mutations was introduced in to pET.M.3C OSM-3-eGFP-His6 plasmid for prokaryotic expression. Plasmid transformed E. coli (BL21) was cultured at 37°C and induced overnight at 23°C with 0.2 mM IPTG. Cells were lysed in lysis buffer (50 mM NaPO4 pH8.0, 250 mM NaCl, 20 mM imidazole, 10 mM bME, 0.5 mM ATP, 1 mM MgCl¬2, Complete Protease Inhibitor Cocktail (Roche)) and Ni-NTA beads were applied for affinity purification. After incubation, beads were washed with wash buffer (50 mM NaPO4 pH6.0, 250 mM NaCl, 10 mM bME, 0.1 mM ATP, 1 mM MgCl¬2) and eluted with elute buffer (50 mM NaPO4 pH7.2, 250 mM NaCl, 500 mM imidazole, 10 mM bME, 0.1 mM ATP, 1 mM MgCl¬2). Protein concentration was determined by standard Bradford assay. C elegans nekl-3 cDNA was cloned in to pGEX-6P GST vector and expressed in E. coli BL21 (DE3) and purified for in vitro phosphorylation assays. Plasmid transformed E. coli (BL21) was cultured at 37°C and induced overnight at 18°C with 0.5 mM IPTG. Cells were lysed in lysis buffer (50 mM NaPO4 pH8.0, 250 mM NaCl, 1 mM DTT, Complete Protease Inhibitor Cocktail (Roche)) and GST beads were applied for affinity purification. After incubation, beads were washed with wash buffer (50 mM NaPO4 pH6.0, 250 mM NaCl, 1 mM DTT) and eluted with elute buffer (50 mM NaPO4 pH7.2, 150 mM NaCl, 10 mM GSH, 1 mM DTT). Purified proteins were dialyzed against storge buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl). Protein concentration was determined by standard Bradford assay...”

(4) Line 141: The first sentence of this paragraph lacks motivation. I would start this sentence with "To directly observe the effects of phosphor mutants in the elbow region in microtubule binding and motility of OSM-3, we...".

We have made the change.

(5) Figure 1B: The mass spectrometry data in Figure 1B lacks adequate explanation. The Methods section should detail the experimental protocol, data interpretation, and any databases used. Additionally, the manuscript should list all identified phosphorylation sites on OSM-3 to provide context, including whether Y487_T490 is the major site.

We have provided the detailed experimental protocol, data interpretation, and databases used in methods. We have provided all identified sites as Appendix table S1.

(6) Figure 1C: Is it possible to model the effect of PM and PD mutations using AlphaFold? The authors should also show PAE or pLDDT scores of their model.

AlphaFold cannot well model the effect of mutants, but we conducted the Rosetta relax to capture their possible conformational changes, as shown in the revised Figure 3. We have provided PAE and pLDDT as a new figure, Figure S2.

(7) Figure 2D: The unit for speed should use a lowercase "s" for seconds.

We have fixed it.

(8) Figure 3: I am not sure whether this figure stands for a main text figure on its own, as it is only a Rosetta prediction and is not supported by any experimental data. In addition, it remains unclear what the labels on the x-axis mean.

We have updated the figure and explain the labels on the x-axis in Figure S4 to make it more reader-friendly.

(9) Figure 4: NEKL-3-treated OSM-1 should be included as a positive control in the in vitro experiments.

We suspect that the Reviewer asked for NEKL-3-treated OSM-3. 

In our other study which has just been accepted by the Journal of Cell Biology, NEKL3-treated OSM-3 significantly reduced the affinity between OSM-3 motor and microtubules and showed very low ATPase activity. We have cited and discussed this in the revised text on page #10, line #28: 

“…As demonstrated in our recent study (Huang et al., JCB, 2025, In press, attached), phosphorylation of OSM-3 by NEKL-3 at two distinct regions—Ser96 and the conserved "elbow" motif—differentially regulates its activity and localization. Phosphorylation at Ser96 reduces OSM-3’s ATPase activity and alters its ciliary distribution from the distal segment to a uniform localization, while elbow phosphorylation induces autoinhibition, retaining OSM-3 in the cell body. Strikingly, in vitro phosphorylation of OSM-3 by NEKL-3 significantly reduces its microtubulebinding affinity, likely arising from combined modifications at both sites. We propose a model wherein elbow phosphorylation ensures anterograde ciliary transport, while Ser96 phosphorylation fine-tunes distal segment targeting. This multistep regulation may involve distinct phosphatases to reverse phosphorylation at specific sites, a hypothesis warranting further investigation….”

(10) Figure 4C, D, and F: The unit of velocity is wrong. The authors should use the same units they used in the table shown in Figure 4B.

We have fixed these errors

(11) Figure 4F: The velocity of PD is a lot lower than G444E. Therefore, it would be more appropriate to refer to PD as partially active, rather than hyperactive.

We have made the change. 

(12) Figure 5: There is too much genetics jargon on this figure (EMF, F2, 100%Dyf,...). How are the alleles numbered? Is it OK to refer to them as Alleles 1 and 2 for simplicity?

According to the established C. elegans allele nomenclature, each worm allele has a unique number named after the lab code for identification. We have simplified the labels and updated the figure to make it more reader-friendly.

(13) Figure 5E: A plot would be more reader-friendly than a table. Additionally, the legend for Fig. 5E mistakenly refers to it as "D."

We have changed the table to a plot and fixed the mistakes. We thank the Reviewer for pointing them out.

Reviewer #2 (Recommendations for the authors):

(1) The model appears as if NEKL-3 induces dephosphorylation of OSM-3 (Figure 6). This is not consistent with the conclusions described in the Discussion and is confusing.

We have updated the model figure and fixed the error.

(2) It should be described why the authors hypothesized NEKL-3 phosphorylates OSM3. Was there genetic evidence? Did the authors screened cilia-related kinases? or Did the authors identify it incidentally? Providing this information would help readers to understand the context of the research.

We appreciate both Reviewers for pointing out this issue. 

Our hypothesis that NEKL-3 phosphorylates OSM-3 stems from prior findings in our lab. In a previous study (Yi et al., Traffic, 2018, PMID: 29655266), we identified NEKL-4, a member of the NIMA kinase family, as a suppressor of the OSM-3(G444E) hyperactive mutation. This discovery prompted us to explore the broader role of NIMA kinases in regulating OSM-3. Subsequent genetic screens (Xie et al., EMBO J, 2024, PMID: 38806659) revealed that both NEKL-3 and NEKL-4 suppress multiple OSM-3 mutations, further supporting their functional interaction. Given the established role of NIMA kinases in phosphorylation-dependent processes (Fry et al., JCS, 2012, PMID: 23132929; Chivukula et al., Nat. Med., 2020, PMID: 31959991; Thiel, C. et al. Am. J. Hum. Genet. 2011, PMID: 21211617; Smith, L. A. et al., J. Am. Soc. Nephrol., 2006, PMID: 16928806), we hypothesized that NEKL-3/4 may directly phosphorylate OSM3 to modulate its activity.

To test this hypothesis, we expressed recombinant C. elegans NEKL-3 and OSM-3 proteins and conducted in vitro phosphorylation assays. While we were unable to obtain active recombinant NEKL-4 (limitations noted in the revised text), our experiments with NEKL-3 revealed phosphorylation at residues 487-490 (YSTT motif) in OSM-3’s tail region, as confirmed by mass spectrometry. These findings are now explicitly contextualized in the Introduction and Results sections of the revised manuscript.

Page #4, Line #11:

“... In our previous study (Yi et al., Traffic, 2018, PMID: 29655266), a genetic screen targeting the OSM-3(G444E) hyperactive mutation identified NEKL-4, a member of the NIMA kinase family, as a suppressor of this phenotype. This finding, combined with reports that NIMA kinases regulate ciliary processes independently of their canonical mitotic roles (Fry et al., JCS, 2012, PMID: 23132929; Chivukula et al., Nat. Med., 2020, PMID: 31959991; Thiel, C. et al. Am. J. Hum. Genet. 2011, PMID: 21211617; Smith, L. A. et al., J. Am. Soc. Nephrol., 2006, PMID: 16928806), prompted us to investigate whether NIMA kinases modulate OSM-3-driven intraflagellar transport. We hypothesized that NEKL-3/4, as paralogs within this family, might directly phosphorylate OSM-3 to regulate its motility...”

Page #4, line #26: 

“... To determine whether NIMA kinase family members could directly phosphorylate OSM-3, we purified prokaryotic recombinant C. elegans NEKL-3/NEKL-4 and OSM3 protein in order to perform in vitro phosphorylation assays. We were able to obtain active recombinant NEKL-3 but not NEKL-4. The in vitro phosphorylation assays showed that NEKL-3, directly phosphorylates OSM-3 (Fig. 1A-B, Appendix Table S1). Subsequent mass spectrometric analysis revealed phosphorylation at residues 487-490, which localize to the conserved "YSTT" motif within OSM-3’s C-terminal tail region...”

(3) It is curious the authors have not addressed the cilia phenotype and the localization of OSM-3 in nekl-3 mutant. Regardless of whether these observations agrees with the proposed mechanisms, it is essential for the authors to show and discuss the cilia phenotype and OSM-3 localization in nekl-3 mutants.

We thank the Reviewer for highlighting this critical point. Indeed, nekl-3 null mutants are inviable due to essential mitotic roles (Barstead et al., 2012, PMID: 23173093), precluding direct analysis of ciliary phenotypes. To bypass this limitation, we recently generated nekl-3 conditional knockouts (cKOs) in ciliated neurons (Huang et al., JCB, 2025 in press, attached). In these mutants, OSM-3—which is normally enriched in the ciliary distal segment—becomes uniformly distributed along the cilium. This redistribution correlates with premature activation of OSM-3-driven anterograde motility in the ciliary middle region, consistent with our proposed model where NEKL3 phosphorylation suppresses OSM-3 activity. We have now integrated this result and discussion into the revised manuscript, reinforcing the physiological relevance of NEKL-3-mediated regulation in ciliary transport. 

Page #6 line #10

“… While nekl-3 null mutants are inviable due to essential mitotic roles (Barstead et al., 2012, PMID: 23173093), conditional knockout (cKO) of nekl-3 in ciliated neurons (Huang et al., JCB, 2025 in press, attached) revealed its critical role in regulating OSM3 dynamics. In nekl-3 cKO animals, OSM-3—normally enriched in the ciliary distal segment—redistributed uniformly along the cilium, concomitant with premature activation of anterograde motility in the middle ciliary region. This phenotype aligns with our model wherein NEKL-3 phosphorylation suppresses OSM-3 activity, ensuring spatiotemporal regulation of IFT.…”

(4) The methods section lacks some information, which is critical to reproducing this study.

We have now provided detailed information in the methods section in the revised manuscript.

(a) It is not described how the authors determined phosphorylation of OSM-3 by NEKL-3. In methods, nothing is described about the assay.

We performed in vitro phosphorylation assays using recombinant OSM-3 and NEKL3 purified from bacteria. We then used LC-MS/MS for identification of phosphorylation sites. We have now updated the methods section to include all the information.

Page #4 line #26

“... To determine whether NIMA kinase family members could directly phosphorylate OSM-3, we purified prokaryotic recombinant C. elegans NEKL-3/NEKL-4 and OSM3 protein in order to perform in vitro phosphorylation assays. We were able to obtain active recombinant NEKL-3 but not NEKL-4. The in vitro phosphorylation assays showed that NEKL-3, directly phosphorylates OSM-3 (Fig. 1A-B, Appendix Table S1). Subsequent mass spectrometric analysis revealed phosphorylation at residues 487-490, which localize to the conserved "YSTT" motif within OSM-3’s C-terminal tail region...”

Page #36, line #19

“In vitro phosphorylation assay 20 μM purified OSM-3 was incubated with 1 μM GST-NEKL-3 at 30 °C in 100 μL reaction buffer (50 mM Tris-HCl pH 8.0, 10 mM MgCl2, 150 mM NaCl, and 2 mM ATP) for 30 min. The reaction was terminated by boiling for 5 min with an SDS-sample buffer.

Mass spectrometry

Following NEKL-3 treatment, OSM-3 proteins were resolved by SDS-PAGE and visualized with Coomassie Brilliant Blue staining. Protein bands corresponding to OSM-3 were excised and subjected to digestion using the following protocol: reduction with 5 mM TCEP at 56°C for 30 min; alkylation with 10 mM iodoacetamide in darkness for 45 min at room temperature, and tryptic digestion at 37°C overnight with a 1:20 enzyme-to-protein ratio. The resulting peptides were subjected to mass spectrometry analysis. Briefly, the peptides were analyzed using an UltiMate 3000 RSLCnano system coupled to an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific). We applied an in-house proteome discovery searching algorithm to search the MS/MS data against the C. elegans database. Phosphorylation sites were determined using PhosphoRS algorithm with manual validation of MS/MS spectra.”

(b) The method of structural prediction by Alfafold2 and LocalColabFold needs clarification. In general, the prediction gives several candidates. How did the authors choose one of these candidates?

We generated five candidate models and all of them showed similar conformation. We thus chose the model with the highest confidence. We have provided PAE and pLDDT as additional data in Figure S2 and discussed them in the revised text on, Page #4, line #32: 

“...To gain structural insights from this motif, we employed LocalColabFold based on AlphaFold2 to predict the dimeric structure of OSM-3 (Evans et al., 2022; Jumper et al., 2021; Mirdita et al., 2022). The highest-confidence model was selected for further analysis (Fig. 1C, Fig. S2)...”

(c) The methods to predict conformational changes by introducing various point mutations are interesting (Figure 3). However, the methods require more detailed descriptions. In the current form, the manuscript only lists the tools used. The pipelines and parameters need to be described. This information is important because AlphaFoldbased predictions often give folded conformations because the training data are mainly composed of folded proteins. It is surprising that the methods applied here give open conformations induced by point mutations.

We have described the pipelines in the revised Methods section on page#34, line#25: 

“…OSM-3 model was predicted using LocalColabFold (Evans et al., 2022; Jumper et al., 2021; Mirdita et al., 2022). Mutated proteins were designed by Pymol 2.6, choosing the rotamer of the mutated residues in G444E, PM and PD models with the least clash as the initial conformation. To predict mutation-induced conformational changes, the initial models were subjected to Pyrosetta (Chaudhury et al., 2010). The energies of pre-relaxed models were evaluated with Rosetta Energy Function 2015 (Alford et al., 2017), and then the relax procedure were applied to the models with default parameters to obtain the relaxed models visualized by Pymol to minimize the energy of these models. In detail, to obtain the relaxed models visualized by Pymol and minimize the energy of these models, the classic relax mover was used in the procedure mentioned above with default settings. The relax script has been uploaded to Github: https://github.com/young55775/RosettaRelax_for_OSM3...”

(5) The authors have purified proteins. Do they show different properties in gel filtration that are consistent with the structural prediction? It is anticipated that open-form mutants are eluted from earlier than closed forms.

We thank the reviewer for this insightful suggestion. Indeed, our recent study supported that the open-from of the active OSM-3 G444E mutation were eluted earlier than the wild-type closed form (Xie et al., EMBO J., 2024). While the current study did not perform gel filtration chromatography (SEC) to directly compare the hydrodynamic properties of the OSM-3 mutants, our functional assays provide robust evidence for conformational changes predicted by structural modeling. For example: ATPase activity assays revealed that the open-state mutants (e.g., G444E and PD muatnts) exhibited significantly enhanced enzymatic activity (Figure 4A), consistent with structural predictions of an active, destabilized autoinhibitory interface (Figure 3A). These functional readouts collectively validate the predicted structural states. While SEC could further corroborate these findings by distinguishing compact (closed) versus extended (open) conformations, we prioritized assays that directly link structural predictions to in vitro enzymatic activity and in vivo ciliary transport dynamics. Future studies incorporating SEC or cryo-EM will provide additional biophysical validation of these states.

We have revised the text in the manuscript (Page #7, Lines #22): 

“…Notably, the open-state OSM-3 mutants (e.g., G444E) displayed elevated ATPase activity, consistent with structural predictions of autoinhibition release (Fig. 3A, Fig. 4A) (Xie et al., 2024). While hydrodynamic profiling (e.g., SEC) could further resolve conformational states, our functional assays directly connect predicted structural changes to altered biochemical and cellular activity...”

Minor point

(1) Line 85 "MIMA kinase family" should be "NIMA kinase family".

We have corrected the typo and appreciate that the Reviewer for pointing it out. 

(2) M.S. and D.S. need to be defined in Figure 2D.

We have updated the figures.

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

Manuscript number: RC-2025-02887

Corresponding author(s): Philippe Bastin

1. General Statements [optional]

• *

We thank the reviewers for their constructive suggestions. We are delighted to see that they appreciated our work and its interest for the broad cell biology community, as well as the potential impact of the inducible expression of tagged tubulin as a new tool to investigate microtubule assembly at large.

We are now providing a full revision that contains two major modifications and that addresses all the minor points detailed below. The two major modifications are:

• A simplification and a shortening of the text as requested by reviewers 1 and 3
• The addition of a new experiment evaluating the role of the locking protein CEP164C to gain insight into the mechanism, as suggested by reviewers 1 and 2 Briefly, CEP164C is a protein localised to the transition fibres (structures that dock the basal body of the flagellum to the membrane) of only the old flagellum. Its depletion leads to an excessive elongation of the old flagellum and the production of a shorter new flagellum, suggesting competition between the two flagella for tubulin incorporation (Atkins et al., 2021). In the new figure 5, we have expressed tagged tubulin in the CEP164CRNAi cell line and formally demonstrated simultaneous incorporation in both flagella. Unexpectedly, the new flagellum incorporated more tubulin than the old one, suggesting a bias of tubulin targeting in favour of the new flagellum and the existence of additional contributors to the Grow-and-Lock model.

2. Point-by-point description of the revisions

This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

• *

Reviewer #1

Evidence, reproducibility and clarity

The manuscript by Daniel Abbühl on "A novel approach to tagging tubulin reveals MT assembly dynamics of the axoneme in Trypanosoma brucei" uses an innnovative approach to label tubulin, which allows the authors to unveil new mechanisms in flagellar length regulation.

The manuscript is very nice and will be very interesting for the cell biology community and therefore should be accepted. In some parts it becames a bit complex with all the models and complex phrasing, I wonder whether the text could be simplified to be more appealing. I have a few minor comments:

We agree that some of the explanations are lengthy and complex. We have simplified the explanations and hopefully made the models more accessible. Complexity comes from the fact that trypanosomes do not have a synchronized cell cycle.

-From the model the authors show in Figure 8- there should be a way of pulsing the cells in G1 for a short amount of time -2 hours- and getting both flagella tips labelled. But the authors seem to require longer labelling to get that result. This should be better explained.

We are not quite sure what is meant here with both flagella as in G1-phase, all cells are mono-flagellated. We do see mono-flagellated cells with a labelled tip after 2 hours, both with the HALO-tag or the Ty-1-tubulin system.

In regard to bi-flagellate cells, we believe that incorporation in the OF happened at the beginning of G1-phase when the cell was mono-flagellated. If tubulin is present at that point, it will be incorporated at the tip. This cell then approaches the end of G1-phase and starts to initiate NF assembly. Since tagged tubulin is already present it will be incorporated along the whole length of the NF.

A short induction of 2h would not suffice as it wouldn't cover the duration of the G1-phase and the initiation of a NF (duration of G1-phase is ~4h). We attempted to explain this in Fig. 4 and reworked the text to make this clearer.

-Why do some cells not express the construct? Weren´t they all selected?

We never managed to get a cell line where inducible expression is present in 100% of cells. Here, around 95% of cells were positive for Ty-1-tubulin after 24h of induction. Non-expression is not a phenomenon restricted to this tubulin cell line but also observed with other ectopically expressed proteins (e.g. Sunter et al. JCS 2015, Bastin et al. MCB 1999). All these cell lines represent clonal populations and are resistant to antibiotic treatment, however not all cells express the respective protein. For each experiment where we believed the number of expressing cells matter (for example the washout), we quantified in how many cells Ty-1-tubulin was present in the cell body microtubules.

-"The linear regression line in Fig. 3C was corrected by subtracting 45 minutes from each timepoint due to the previously reported delay between addition of tetracycline and the expression of the respective protein". However, in the authors data the delay may amount to one hour (western analysis- S4). Shouldn´t they use their data.

Indeed, the western blot shows expression after 1-hour, however we did not take a 45-minute timepoint, so we don't know if the protein was detectable at that time. In addition, IFA is more sensitive than western blot. We cannot say exactly when the average cell starts to express the induced protein.

-Fig 3: To measure the timepoints of flagella growth, wouldn´t it be better to do it with NF that started to grow before induction, rather than starting to grow after induction, to be sure that the timing of incorporation is fully accounted for?

We indeed did consider only NFs, which started to grow before induction, as suggested by the reviewer. In the revised version the description of the experiment can be found on page 9 line 22 - 28.

-Although it is not the focus of the manuscript it would have been very interesting to use the CEP164C mutant to see whether it would change the dynamics of incorporation and fully test their model and discussion.

This is a great suggestion, so we performed some experiments to address this issue. When CEP164C was knocked down before Ty-1-tubulin expression, integration is seen at the distal tip of both NF and OF. This is coherent with the idea of removal of the locking protein from the OF. However, lengths of the green segments in NF and OF do not have the same length (NF ~6 µm, OF ~2 µm), which indicates that CEP164C might not be the only protein involved in regulating flagellum length. A new figure explaining this experiment was added (Fig. 5, Fig. S6). We believe this data provides novel insight on the locking mechanism and strengthens the manuscript.

-In some parts of the manuscript/supplemental material the authors say they insert the Ty-1- tag one aminoacid after the acetylated lysine- other parts they say two aminoacids after- this should be consistent.

We thank the reviewer for spotting these mistakes, we have changed the text accordingly.

-Fig. S1: 'Binding epitope of the TAT-1 antibody is highlighted in red'. There is no highlighting in red in this figure?

This sentence was removed.

-Fig. S2: Western blots are not very clear. What is the 'X' present in the C (first lane)? Weight of markers should be shown also in S4.

Molecular weight markers have been added. X is an empty lane, we have now indicated this in the figure legend.

-Fig 5: 'C: Frequency of bi-flagellated cells grouped by the different types of' The authors didn't finish the sentence.

Previous Fig. 5 is now Fig. 6. Sentence has been completed. "Frequency of bi-flagellated cells grouped by different types of old flagella"

-Fig. S7: The 'B' is missing in both picture and legend.

This has been added

Significance

This study advances our knowledge of flagellar length regulation and maintenance. Moreover, the tools designed in this work will be very useful for the cell biology community in general.

---

Reviewer #2

Evidence, reproducibility and clarity

Summary: The length of the old flagellum of Trypanosome is constant during G1 phase as well as during cell cycle progression when the new flagellum is assembled. The authors have previously proposed a "Grow and Lock" model for the flagellar length control in which no flagellar building blocks are incorporated. To test this hypothesis, the authors used a tagging strategy for alpha-tubulin and tracking its incorporation. The authors showed that the new flagellum incorporates new tubulins, as is expected. For the mature flagellum, tubulins are incorporated at the flagellar tip and only when the cells start to assemble the new flagellum. Thus, it shows that old flagellum is stable but not completely locked for the incorporation of tubulins.

Major comments: The study is methodologically rigorous, integrating fluorescence microscopy, biochemical approaches, and proteomic analyses to validate the functionality of the tagged tubulin. The use of both inducible expression and endogenous protein tagging (HaloTag) strengthens the conclusions. This study has supported the "Grow-and-Lock" model" that the authors previously proposed. In addition, they have revealed that the stability of the old flagellum is temporally controlled.

The data showed that brief incorporation of tubulins at the tip of the old flagellum occurs when the cells start to form the new flagellum. I thought the assembly of the new flagellum occurs during the cell division. However, in the abstract, it says that "The restriction is lifted briefly after the bi-flagellated cell has divided." Is my understanding wrong?

We believe incorporation at the tip of the "OF" occurred after the cell has divided, when the OF daughter is mono-flagellated. It happens before this daughter cells starts assembling its new flagellum is formed. Of course, when looking at biflagellated cells, the NF as well as the tip of the OF will be green, but our data supports that incorporation happened in G1-phase and not during the biflagellated stage as the lock seals the OF before the NF emerges. To clarify on terminology: The bi-flagellate stage begins when basal bodies are duplicated, shortly after the beginning of S-phase and ends with cytokinesis. This means G1-phase and the mono-flagellated stage are nearly the same (Woodward and Gull, JCS1990) and occupy ~40% of the cell cycle.

P12, "The cartoon in Fig. 5A illustrates the progression of the cells in scenario 2 (Fig. 4A) over the duration of one cell cycle (~9 hours)" I thought that one cell cycle should start with cell with only one flagellum, followed by assembly of a new flagellum during cell division, the cell then divides when the new flagellum is almost completely assembled. If my understanding is correct, perhaps the cartoon should be modified accordingly.

Indeed, the cell cycle starts with a cell in G1-phase. Here, we have chosen the initiation of a NF assembly as our starting point because we focused the investigation on bi-flagellated cells. We have now illustrated the cell cycle (adapted from Woodward and Gull 1990) and when cells are biflagellated in Fig. 6A (revised version).

Minor comments:

1) Several references are not correctly formatted. P3: (Flavin and Slaughter, 1974) (Rosenbaum 1969). P10, (Sherwin et al., 1987)(Sheriff et al., 2014) 2) In several places there are no space between the number and the unit. For eample, P3, 9 - 24µm/h. 7, 1μg/m; P8, 50kDa; P9, 1M; 8-9h; P11, 2.9µm/h and etc. 3) P11, Flagella were extracted. I thought the cells were extracted.

Thank you for pointing these out, we have changed these in the text.

Significance

Cilia and eukaryotic flagella are considered dynamic structures in which the flagellar components especially tubulins under constant turnovers even in steady state. This work demonstrates that in Trypanosome the stable old flagellum is temporally controlled for tubulin turnovers, suggesting a tight regulation of microtubule dynamics. Future elucidation of the regulatory mechanism will be more interesting. This work will be interesting to the field of cilia and microtubules. In addition, the new technique used for tracking tubulins will also be interesting.

I am an expert on ciliary biology.

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

Summary:

This study seeks to investigate the mechanism by which the length of an eukaryotic cilium is set and maintained in a constant state. The flagellated protist Trypanosoma brucei serves as the study model and the authors take advantage of the genetic tools that allow precise modification and tagging of flagellar proteins and they build on prior knowledge about the well-characterised flagellar assembly cycle, which allows tracking the assembly of a new flagellum alongside an existing old one in the course of one cell cycle. The group of Bastin has previously reported a very interesting "Grow-and-Lock Model for the Control of Flagellum Length in Trypanosomes" and this current manuscript provides a test of this model, and a refinement. Key to this is an advance in technique, reported here, namely expression of an epitope tagged version of alpha tubulin. The epitope is inserted in an internal loop, which apparently for the first time provides a traceable tubulin that is reliably incorporated into the cytoskeleton (subpellicular array, spindle and cilium). Expressing an inducible version of this Ty-1-tubulin allows for a set of experiments that measure the place and timing of tubulin incorporation into cilia. The results are largely confirmatory of previous findings (incorporation exclusively into the new flagellum, at the distal end, linear growth rate that matches previous estimates). Examination of tubulin incorporation patterns then reveal additional information about the old flagellum: evidence from Ty-1-tubulin labelling, corroborated by incorporation patterns of another ciliary protein (RSP 4/6) suggest that the "lock" on the old flagellum is relieved for short periods after cell division, leading to a refined model presented in Figure 8.

Major comments:

This study provides an elegant test of the grow-and-lock model and the major conclusions are supported by the data. I have no major concerns.

Minor comments:

There are several minor points that could be addressed to make the manuscript easier to follow (and adding line numbers to the manuscript would help with reviewing).

The introduction is quite long. Some of the well-established background information on the T. brucei cell cycle could be shortened. If the paper is intended for a broader audience, it would be valuable instead to cite studies that have succeeded in tagging tubulin and tracing its incorporation in other cilia. Could the Ty-1-tubulin approach be relevant more broadly or are simpler methods already established?

The introduction has been shortened, we now also cite two published studies that tracked tubulin integration in Chlamydomonas and C. elegans respectively.

On p.6 the rationale for endogenous tagging was to "reduce the risk of artifacts portentially due to untimely expression or unnatural protein levels". However most of the experiments were done with ectopically expressed inducible Ty-1-tubulin. For the experiments it is crucial to use an inducible system but the authors may wish to comment why the risk of artifacts was no longer a concern.

The reasoning here was that in case the Ty-1-tubulin would not have been incorporated into MTs, we could have attributed it solely to the presence of the tag and no other factors, but this was not the case. This therefore allowed us to move to the inducible expression system.

On p.7 / Fig S2A-B there appears to be a mistake in the presentation. Spindles are mentioned in the text - I can't see any in the figure. Fig S2A and B both show cytoskeletons, but the text suggests only B is about cytoskeletons. None of the blot shows BB2 staining of different cell fractions, contrary to statements in the text. The letter codes in the panel (T, C, D) don't match the codes in the legend (T, P, S).

We thank the reviewer for spotting the mistakes. A panel with the spindle was added in Fig. S2. We did not stain fraction blots of the in-situ tagged cell lines with BB2. However, this was done with the inducible cell line and is shown in Fig. 1D. Letter code in the legend was adapted to match the figure.

Figure 1. The evidence for incorporation into spindles is not strong. The structure indicated by the arrive could be a spindle but it's not very clear. There is a great example of a labelled spindle only in figure S5A. Here, at the start, it would be good to show a panel of cells in successive cell cycle stages (best, whole cells and cytoskeletons) to clearly show the structures that are labelled with Ty-1-tubulin.

The current Fig. 1B (Fig. 1A before) depicts whole cells of an induced and a non-induced culture; we show whole cells to provide a complete picture of tubulin integration. A panel with detergent extracted cytoskeletons from the in situ tagged cell line has been added to Fig. 1A. We chose to show cytoskeletons or isolated flagella instead of whole cells because (1) the flagella are easier to see and (2) it formally demonstrates that tagged tubulin is incorporated in MTs.

In general, tubulin labelling of the spindle was more consistently observed in whole cells as we did not use spindle preserving extraction buffers when preparing cytoskeletons. However, we did observe clear spindles in cytoskeletons as well (see Fig. S5 for example). The same was observed for the beta-tubulin specific KMX1 antibody in the past which is the gold standard to visualize the spindle (Sasse and Gull JCS1988). Regardless, a panel depicting spindle progression through mitosis using staining of Ty-1-tubulin has been added in Fig. S2 (The panel is a mix of whole cells and cytoskeletons).

On p.8 (end of first paragraph) there is reference to cell cycle analyses, but no data is shown. Also on p.8, please clarify what the evidence is that "a fraction of cells did not respond to tetracycline". The fact that they remain unstained by Ty-1-tubulin is not in itself evidence they did not respond to tetracycline.

We did not show the cell cycle data as it was similar to non-induced and does not provide any new information in our opinion. Hence, the sentence has been removed.

The reviewer is correct that we do not have evidence that these cells did not respond to tetracycline. Some cells remained completely devoid of Ty-1-tubulin even after multiple days of induction. This was typically between 5-10% of cells. In experiments where the exact number is important, we counted the amount of "non-expressers" in whole cells.

Figure S4A. The blot for the soluble fraction is not of great quality. I don't see how the conclusion was reached that the Ty-1-tubulin bands were faint.

The blot of the soluble fraction that was stained with BB2 had to be exposed a lot longer compared to the blot stained with TAT-1. The soluble blots were repeated with the same result (lots of background noise when using BB2, a clear blot with TAT-1). In the TAT-1 blot only the endogenous tubulin band is clearly visible, with some very faint signal above corresponding to the Ty-1-tubulin. Soluble Ty-1-tubulin with BB2 or TAT-1 is visible in Fig. 1D after longer inductions.

On p.11, it would be interesting to compare measured elongation rates with previously measured estimates for flagellum growth, comparing the growth rates, and relating them to cell cycle times in the corresponding experiments (which vary slightly between labs and studies).

We attempted to address this in the discussion by comparing our experiments to the assembly rate measured with the PFR as reporter (Bastin et al. 1999). We could mention the corresponding doubling times in correlation to how many cells are bi-flagellated, but this was only done with the Ty-1-tubulin cell line and not with the PFR. In our experiments the average doubling time was ~9 hours with 52% of cells being bi-flagellated. This was measured with FTZC (marker of the transition zone at the base of the flagellum) and Mab25 (marker of the axoneme of the flagellum) which will lead to a slight underestimate of the real number of bi-flagellated cells, as the NF is initially very close which makes it difficult to notice/differentiate from the old one.

Figure S6. I find the presentation of this figure confusing. It should be revised with clearer labelling of "cell cycle 1", "cell cycle 2", and the precise meaning of "type 3" should be clarified. There are two instances of "type 1" in the drawing, but one of these seems to fulfil the criteria of "type 3" (OF 1-4µm).

We agree with the reviewer and therefore decided to remove this figure. We also considered the comments of the other two reviewers about complexity of the manuscript and changed the text of figure 5 to make it more approachable. This includes a simpler explanation for the expected amounts of flagella.

Figure 7. In panel A, the absence of label at the NF distal end is not total, a purple line is still visible. Was any quantitation attempted (signal intensity, changes in length of labelled fragments over time?). Minimally, say how many cells were analysed for the numbers in panels D and E, and how many times this experiment was done.

We agree with the reviewer that the decrease in the TMR signal in the NF of the cell in the original Fig. 7A (currently Fig. 8A) is gradual and not abrupt. Similarly to the Ty-1-tubulin experiments where the tagged protein becomes progressively more available (increasing intensity), the intensity of TMR-ligand becomes progressively less abundant (gradually decreasing intensity) as new (not TMR labelled) protein gets synthesized during the period of NF construction, progressively diluting the initially fully labeled population of RSP4/6. The slope of the gradient may differ between axonemal constituents, as it reflects the kinetics of protein synthesis, degradation, its incorporation into the axoneme, as well as the size of the soluble protein pool in the cytosol. We classify this type of signal as gradients, as opposed to the sharp decrease. At initial times after TMR-ligand washout (e.g. 4 hours in Fig. 8C), this long gradient is observed at the distal end of NFs and in some uniflagellated cells (NF-inheriting daughters). The distal ends of OFs in these experiments (if not fully labelled) display a sharp decrease, as do frequent uniflagellated cells, likely OF-inheriting daughters. The existence of these two different patterns demonstrates that two different mechanisms are responsible for incorporation of fresh RSP4/6 into the NF and OF axoneme, respectively. While incorporation into the NF is gradual, incorporation into the distal region of the OF is stepwise (restricted in time). Numbers of cells quantified for the table in Fig. 8 have been added. The NFs and OFs displaying the patterns of the gradient and sharp decrease, respectively, were observed in multiple experiments.

Reviewer #3 (Significance (Required)):

• General assessment: strengths and limitations

Strengths: Trypanosoma brucei is a powerful model system in which to ask detailed questions about the assembly dynamics and hierarchy of microtubule-based cytoskeletal structures in general and cilia in particular. This elegant and well-designed study overcomes a previous technical limitation by allowing for the direct labelling of alpha tubulin, one of the main building blocks of the ciliary axoneme. The study sets out to test a specific hypothesis (grow-and-lock model) and provides evidence in support, leading to a refined model for cilia length regulation in trypanosomes.

Limitations: With this system, visualisation of new tubulin incorporation requires de novo synthesis. There is a time lag between inducing expression of Ty-1-tubulin with tetracycline and being able to visualize the tagged proteins that needs to be taken into consideration. This time lag was estimated based on previous studies and the relatively quick appearance of Ty-1-tubulin on Western blots (within hours). This inevitably creates a situation where levels of tagged tubulin change rapidly, creating gradients of signal intensity (and variations in levels) that lead to some uncertainty in estimations of length of labelled microtubule fragments. Furhtermore, the epitope label is not compatible with live cell imaging, restricting analyses to fixed cells. The Ty-1-tubulin data is well ducmented; the RSP4/6 data appear to corroborate these findings but are less extensively documented.

• Advance: The results succeed in integrating several recent findings from different research groups into a refined coherent model about cilia length regulation in trypanosomes. The tubulin tagging method could be gainfully transferred to other systems (although the state of the field in tubulin tagging in other systems is not clearly laid out in the paper).

This paper could be of interest to a broad cell biology community interested in cilia and cytoskeletal dynamics.

Reviewer #2 (Public review):

Summary:

The authors assemble 222 publicly available bone marrow single-cell RNA sequencing samples from healthy donors and primary AML, including pediatric, adolescent, and adult patients at diagnosis. Focusing on one specific subtype, t(8;21), which, despite affecting all age classes, is associated with better prognosis and drug response for younger patients, the authors investigate if this difference is reflected also in the transcriptomic signal. Specifically, they hypothesize that the pediatric and part of the young population acquires leukemic mutations in utero, which leads to a different leukemogenic transformation and ultimately to differently regulated leukemic stem cells with respect to the adult counterpart. The analysis in this work heavily relies on regulatory network inference and clustering (via SCENIC tools), which identifies regulatory modules believed to distinguish the pre-, respectively, post-natal leukemic transformation. Bulk RNA-seq and scATAC-seq datasets displaying the same signatures are subsequently used for extending the pool of putative signature-specific TFs and enhancer elements. Through gene set enrichment, ontology, and perturbation simulation, the authors aim to interpret the regulatory signatures and translate them into potential onset-specific therapeutic targets. The putative pre-natal signature is associated with increased chemosensitivity, RNA splicing, histone modification, stem-ness marker SMARCA2, and potentially maintained by EP300 and BCLAF1.

Strengths:

The main strength of this work is the compilation of a pediatric AML atlas using the efficient Cellxgene interface. Also, the idea of identifying markers for different disease onsets, interpreting them from a developmental angle, and connecting this to the different therapy and relapse observations, is interesting. The results obtained, the set of putative up-regulated TFs, are biologically coherent with the mechanisms and the conclusions drawn. I also appreciate that the analysis code was made available and is well documented.

Weaknesses:

There were fundamental flaws in how methods and samples were applied, a general lack of critical examination of both the results and the appropriateness of the methods for the data at hand, and in how results were presented. In particular:

(1) Cell type annotation:

a) The 2-phase cell type annotation process employed for the scRNA-seq sample collection raised concerns. Initially annotated cells are re-labeled after a second round with the same cell types from the initial label pool (Figure 1E). The automatic annotation tools were used without specifying the database and tissue atlases used as a reference, and no information was shown regarding the consensus across these tools.

b) Expression of the CD34 marker is only reported as a selection method for HSPCs, which is not in line with common practice. The use of only is admitted as a surface marker, while robust annotation of HSPCs should be done on the basis of expression of gene sets.

c) During several analyses, the cell types used were either not well defined or contradictory, such as in Figure 2D, where it is not clear if pySCENIC and AUC scores were computed on HSPCs alone or merged with CMPs. In other cases, different cell type populations are compared and used interchangeably: comparing the HSPC-derived regulons with bulk (probably not enriched for CD34+ cells) RNA samples could be an issue if there are no valid assumptions on the cell composition of the bulk sample.

(2) Method selection:

a) The authors should explain why they use pySCENIC and not any other approach. They should briefly explain how pySCENIC works and what they get out in the main text. In addition they should explain the AUCell algorithm and motivate its usage.

b) The obtained GRN signatures were not critically challenged on an external dataset. Therefore, the evidence that supports these signatures to be reliable and significant to the investigated setting is weak.

(3) There are some issues with the analysis & visualization of the data.

(4) Discussion:

a) What exactly is the 'regulon signature' that the authors infer? How can it be useful for insights into disease mechanisms?

b) The authors write 'Together this indicates that EP300 inhibition may be particularly effective in t(8;21) AML, and that BCLAF1 may present a new therapeutic target for t(8;21) AML, particularly in children with inferred pre-natal origin of the driver translocation.' I am missing a critical discussion of what is needed to further test the two targets. Put differently: Would the authors take the risk of a clinical study given the evidence from their analysis?

Author response:

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors performed an integration of 48 scRNA-seq public datasets and created a single-cell transcriptomic atlas for AML (222 samples comprising 748,679 cells). This is important since most AML scRNA-seq studies suffer from small sample size coupled with high heterogeneity. They used this atlas to further dissect AML with t(8;21) (AML-ETO/RUNX1-RUNX1T1), which is one of the most frequent AML subtypes in young people. In particular, they were able to predict Gene Regulatory Networks in this AML subtype using pySCENIC, which identified the paediatric regulon defined by a distinct group of hematopoietic transcription factors (TFs) and the adult regulon for t(8;21). They further validated this in bulk RNA-seq with AUCell algorithm and inferred prenatal signature to 5 key TFs (KDM5A, REST, BCLAF1, YY1, and RAD21), and the postnatal signature to 9 TFs (ENO1, TFDP1, MYBL2, KLF1, TAGLN2, KLF2, IRF7, SPI1, and YXB1). They also used SCENIC+ to identify enhancer-driven regulons (eRegulons), forming an eGRN, and found that prenatal origin shows a specific HSC eRegulon profile, while a postnatal origin shows a GMP profile. They also did an in silico perturbation and found AP-1 complex (JUN, ATF4, FOSL2), P300, and BCLAF1 as important TFs to induce differentiation. Overall, I found this study very important in creating a comprehensive resource for AML research.

Strengths:

(1) The generation of an AML atlas integrating multiple datasets with almost 750K cells will further support the community working on AML.

(2) Characterisation of t(8;21) AML proposes new interesting leads.

We thank the reviewer for a succinct summary of our work and highlighting its strengths.

Weaknesses:

Were these t(8;21) TFs/regulons identified from any of the single datasets? For example, if the authors apply pySCENIC to any dataset, would they find the same TFs, or is it the increase in the number of cells that allows identification of these?

The purpose of our study was to gain biological insights by integrating multiple datasets, to overcome limitations from small sample size. We expect that the larger dataset would improve network inference, which is what we implemented in the manuscript, hence we have not looked at individual datasets. However, we will investigate this further in the revised manuscript by running pySCENIC on individual datasets and comparing to the results drawn from the whole atlas.

Reviewer #2 (Public review):

Summary:

The authors assemble 222 publicly available bone marrow single-cell RNA sequencing samples from healthy donors and primary AML, including pediatric, adolescent, and adult patients at diagnosis. Focusing on one specific subtype, t(8;21), which, despite affecting all age classes, is associated with better prognosis and drug response for younger patients, the authors investigate if this difference is reflected also in the transcriptomic signal. Specifically, they hypothesize that the pediatric and part of the young population acquires leukemic mutations in utero, which leads to a different leukemogenic transformation and ultimately to differently regulated leukemic stem cells with respect to the adult counterpart. The analysis in this work heavily relies on regulatory network inference and clustering (via SCENIC tools), which identifies regulatory modules believed to distinguish the pre-, respectively, post-natal leukemic transformation. Bulk RNA-seq and scATAC-seq datasets displaying the same signatures are subsequently used for extending the pool of putative signature-specific TFs and enhancer elements. Through gene set enrichment, ontology, and perturbation simulation, the authors aim to interpret the regulatory signatures and translate them into potential onset-specific therapeutic targets. The putative pre-natal signature is associated with increased chemosensitivity, RNA splicing, histone modification, stem-ness marker SMARCA2, and potentially maintained by EP300 and BCLAF1.

Strengths:

The main strength of this work is the compilation of a pediatric AML atlas using the efficient Cellxgene interface. Also, the idea of identifying markers for different disease onsets, interpreting them from a developmental angle, and connecting this to the different therapy and relapse observations, is interesting. The results obtained, the set of putative up-regulated TFs, are biologically coherent with the mechanisms and the conclusions drawn. I also appreciate that the analysis code was made available and is well documented.

We thank the reviewer for reviewing our work, and highlighting its key features, including creation of AML atlas, downstream analysis and interpretation for t(8;21) subtype.

We also appreciate useful critique of our paper provided below.

Weaknesses:

There were fundamental flaws in how methods and samples were applied, a general lack of critical examination of both the results and the appropriateness of the methods for the data at hand, and in how results were presented. In particular:

(1) Cell type annotation:

a) The 2-phase cell type annotation process employed for the scRNA-seq sample collection raised concerns. Initially annotated cells are re-labeled after a second round with the same cell types from the initial label pool (Figure 1E). The automatic annotation tools were used without specifying the database and tissue atlases used as a reference, and no information was shown regarding the consensus across these tools.

We believe that most of the reviewer’s criticisms stem from a misunderstanding, and we apologize for not explaining certain aspects of our work more clearly.

The two types of cell type annotation applied were different and served distinct purposes:

• One was using general bone marrow/blood reference datasets to annotate blood subtype lineage clusters.

• The other was using a CD34 purified AML specific reference dataset which included leukaemia-associated annotations, to identify HSPC subpopulations. We also implemented this on a single-cell level to allow more robust identification of these rare populations in a large dataset.

This is probably not well explained in the methods and figure presentation. We will clearly indicate in the revised manuscript that different HSPC annotations represent separate analysis and will update the figures to highlight this. We will provide a comprehensive review of the annotation strategies implemented, including the automated tool outputs, which may be useful for the single-cell community.

b) Expression of the CD34 marker is only reported as a selection method for HSPCs, which is not in line with common practice. The use of only is admitted as a surface marker, while robust annotation of HSPCs should be done on the basis of expression of gene sets.

We used CD34 expression in conjunction with other cell type annotations and marker sets to identify LSCs, although results are same when we use HSPC annotated cells without condition on CD34 expression.  In the revised manuscript, we will simplify this analysis to use HSPC clusters as suggested by the reviewer.

c) During several analyses, the cell types used were either not well defined or contradictory, such as in Figure 2D, where it is not clear if pySCENIC and AUC scores were computed on HSPCs alone or merged with CMPs. In other cases, different cell type populations are compared and used interchangeably: comparing the HSPC-derived regulons with bulk (probably not enriched for CD34+ cells) RNA samples could be an issue if there are no valid assumptions on the cell composition of the bulk sample.

As mentioned in the Methods, we only excluded lymphoid cell types from the pySCENIC analysis to overcome the bias that some samples were enriched using CD34 selection when preparing them for scRNA-seq. We will make this clearer in the text and figures of the revised manuscript. It is difficult to overcome this bias when using bulk RNA samples, which may explain why some of our samples do not fit into our defined signature groups. However, as we do not have access to primary samples ourselves, we cannot provide a better matched experimental cohort for validation.

(2) Method selection:

a) The authors should explain why they use pySCENIC and not any other approach. They should briefly explain how pySCENIC works and what they get out in the main text. In addition they should explain the AUCell algorithm and motivate its usage.

pySCENIC is state-of-the-art method for network inference from scRNA data and is widely used within the single-cell community (over 5000 citations for both versions of the SCENIC pipeline). The pipeline has been benchmarked as one of the top performers for GRN analysis (Nguyen et al, 2021. Briefings in Bioinformatics). AUCELL is a module within the pySCENIC pipeline to summarise the activity of a set of genes (a regulon) into a single number which helps compare and visualise different regulons. We agree with reviewer that this could have been more clearly explained within the manuscript. We will update text in the revised manuscript to add more explanation.

b) The obtained GRN signatures were not critically challenged on an external dataset. Therefore, the evidence that supports these signatures to be reliable and significant to the investigated setting is weak.

These signatures were inferred from the best suitable AML single-cell RNA datasets available to date, and we used two independent datasets to validate our findings (the TARGET AML bulk RNA sequencing cohort, and the Lambo et al. scRNA-seq dataset). To our knowledge, there are no other better suited datasets for validation. Experimental validations on patient samples are beyond the scope of this study.

(3) There are some issues with the analysis & visualization of the data.

We will provide new statistical tests to improve robustness of the analysis as well as presentation and visualization of the data in the revised manuscript.

(4) Discussion:

a) What exactly is the 'regulon signature' that the authors infer? How can it be useful for insights into disease mechanisms?

The ’regulon signature’ here refers to a gene regulatory program (multiple gene modules, each defined by a transcription factor and its targets) which are specific to different age groups. Further investigation into this can be useful for understanding why patients of different ages confer a different clinical course. We will add more text on the utility of our discovered 'regulon signature' in the discussion section of revised manuscript.

b) The authors write 'Together this indicates that EP300 inhibition may be particularly effective in t(8;21) AML, and that BCLAF1 may present a new therapeutic target for t(8;21) AML, particularly in children with inferred pre-natal origin of the driver translocation.' I am missing a critical discussion of what is needed to further test the two targets. Put differently: Would the authors take the risk of a clinical study given the evidence from their analysis?

Of course, many extensive studies would be required before these findings are clinically translatable. We can include some perspectives on what further work is required in terms of further experimental validation and potential subsequent clinical study.

Author response:

The following is the authors’ response to the original reviews

Reviewer #1 (Recommendations for the authors):

We appreciate the reviewers' thoughtful comments and suggestions. Below, we provide point-by-point responses to the recommendations and outline the updates made to the manuscript.

(1) Discussion, "the obvious experiment is to manipulate a neuron's anatomical embedding while leaving stimulus information intact."] The epiphenomenon can arise from the placement and types of a neuron's neurotransmitters and neuromodulators, too.

The content of vesicles released by a neuron is obviously of great importance in determining postsynaptic impact. However, we’re suggesting that (assuming vesicular content is held constant) the anatomically-relevant patterning of spiking might additionally affect the postsynaptic neuron’s integration of the presynaptic input. To avoid confusion, we updated the text accordingly: “the obvious experiment is to manipulate a neuron's anatomical embedding while minimally impacting external and internal variables, such as stimulus information and levels of neurotransmitters or neuromodulators” (Line 594 - 596).

(2) “In all conditions, the slope of the input duration versus sensitivity line was still positive at 1,800 seconds (Fig. 3B)". This may suggest that the estimate of the calculated statistics (ISI, PSTH) is more reliable with more data, rather than (or in addition to) specific information being extracted from faraway time points. Another potential confound is the training statistics were calculated from all training data, so the test data is a better match to training data when test statistics are calculated from more data. Overall, the validity of the conclusions following this observation is not clear to me.

This is a great point. Accordingly, we revised the text to include this possibility: “Because the training data were of similar duration, this could be explained by either of two possibilities. First, the signal is relatively short, but noisy—in this case, extended sampling will increase reliability. Second, the anatomical signal is, itself, distributed over time scales of tens to hundreds of seconds.” (Line 252 - 255).

(3) "This further suggests that there is a latent neural code for anatomical location embedded within the spike train, a feature that could be practically applied to determining the brain region of a recording electrode without the need for post-hoc histology". The performance of the model at the subregion level, which is a typical level of desired precision in locating cells, does not seem to support such a practical application. Please clarify to avoid confusion.

The current model should not be considered a replacement for traditional methods, such as histology. Our intention is to convey that, with the inclusion of multimodal data and additional samples, a computational approach to anatomical localization has great promise. We updated the manuscript to clarify this point: “While significantly above chance, the structure-level model still lacks the accuracy for immediate practical application. However, it is highly likely that the incorporation of datasets with diverse multi-modal features and alternative regions from other research groups will increase the accuracy of such a model. In addition, a computational approach can be combined with other methods of anatomical reconstruction.” (Line 355 - 359).

Additionally, we directly addressed this point in our original manuscript (Discussion section: Line 498 - 505 in the current version). Furthermore, following the release of our preprint, independent efforts have adopted a multimodal strategy with qualitatively similar results (Yu et al., 2024). Other recent work expands on the idea of utilizing single-neuron features for brain region/structure characterization (La Merre et al., 2024).

Yu, H., Lyu, H., Xu, E. Y., Windolf, C., Lee, E. K., Yang, F., ... & Hurwitz, C. (2024). In vivo cell-type and brain region classification via multimodal contrastive learning. bioRxiv, 2024-11.

Le Merre, P., Heining, K., Slashcheva, M., Jung, F., Moysiadou, E., Guyon, N., ... & Carlén, M. (2024). A Prefrontal Cortex Map based on Single Neuron Activity. bioRxiv, 2024-11.

(4) "These results support the notion the meaningful computational division in murine visuocortical regions is at the level of VISp versus secondary areas.". The use of the word "meaningful" is vague and this conclusion is not well justified because it is possible that subregions serve different functional roles without having different spiking statistics.

Precisely! It is well established that different subregions serve different functional purposes - but they do not necessitate different regional embeddings. It is important to note the difference between stimulus encoding and the embedding that we are describing. As a rough analogy, the regional embedding might be considered a language, while the stimulus is the content of the spoken words. However, to avoid vague words, we revised the sentence to “These results suggest that the computational differentiability of murine visuocortical regions is at the level of VISp versus secondary areas.” (Line 380 - 381)

(5) Figure 3D left/right halves look similar. A measure of the effect size needs to accompany these p-values.

We assume the reviewer is referring to Figure 3E. Although some of the violin plots in Figure 3E look similar, they are not identical. In the revision, we include effect sizes in the caption.

(6) Figure 3A, 3F: Could uncertainty estimates be provided?

Yes. We added uncertainty estimates to the text (Line 272 - 294) and to the caption of Figure S2, which displays confusion matrices corresponding to Figure 3A. The inclusion of similar estimates for 3F would be so unwieldy as to be a disservice to the reader—there are 240 unique combinations of stimulus parameters and structures. In the context of the larger figure, 3F serves to illustrate a relationship between stimulus, region, and the anatomical embedding.

(7) Page 21. "semi-orthogonal". Please reword or explain if this usage is technical.

We replaced “semi-orthogonal” with “dissociable” (Line 549).

(8) Page 11, "This approach tested whether..."] Unclear sentence. Please reword.

We changed “This approach tested whether the MLP’s performance depended on viewing the entire ISI distribution or was enriched in a subset of patterns” to “This approach identified regions of the ISI distribution informative for classification” (Line 261).

Reviewer #2 (Recommendations for the authors):

We appreciate the reviewer’s comments and summary of the results. We agree that the introductory results (Figs. 1-3) are not particularly compelling when considered in isolation. They provide a baseline of comparison for the subsequent results. Our intention was to approach the problem systematically, progressing from well-established, basic methods to more advanced approaches. This allows us to clearly test a baseline and avoid analytical leaps or untested assumptions. Specifically:

● Figure 1 provides an evaluation of the standard dimensionality reduction methods. As expected, these methods yield minimal results, serving as a clear baseline. This is consistent, for example, with an understanding of single units as rate-varying Poisson processes.

● Figures 2 and 3 then build upon these results with spiking features frequent in neuroscience literature such as firing rate, coefficient of variation, etc using linear supervised and more detailed spiking features such as ISI distribution using nonlinear supervised machine learning methods.

By starting from the standpoint of the status quo, we are better able to contextualize the significance of our later findings in Figures 4–6.

Response to Specific Points in the Summary

(6) Separability of VISp vs. Secondary Visual Areas

I found the entire argument about visual areas somewhat messy and unclear. The stimuli used might not drive the secondary visual areas particularly well and might necessitate task engagement.

We appreciate your feedback that the dissection of visual cortical structures is unclear. To summarize, as shown in the bottom three rows of Figure 6, there is a notable lack of diagonality in visuocortical structures. This means that our model was unable to learn signatures to reliably predict these classes. In contrast, visuocortical layer is returned well above chance, and superstructures (primary and secondary areas) are moderately well identified, albeit still well above chance.

Consider a thought experiment, if Charlie Gross had not shown faces to monkeys to find IT, or Newsome and others shown motion to find MT and Zeki and others color stimuli to find V4, we would conclude that there are no differences.

The thought experiment is misleading. The results specifically do not arise from stimulus selectivity—much of Newsome’s own work suggests that the selectivity of neurons in IT etc. is explained by little more than rate varying Poisson processes. In this case, there should be no fundamental anatomical difference in the “language” of the neurons in V4 and IT, only a difference in the inputs driving those neurons. In contrast, our work suggests that the “language” of neurons varies as a function of some anatomical divisions. In other words, in contrast to a Poisson rate code, our results predict that single neuron spike patterns might be remarkably different in MT and IT— and that this is not a function of stimulus selectivity. Notably, the anatomical (and functional) division between V1 and secondary visual areas does not appear to manifest in a different “language”, thus constituting an interesting result in and of itself.

We regret a failure to communicate this in a tight and compelling fashion on the first submission, but hope that the revision is limpid and accessible.

Barberini, C. L., Horwitz, G. D., & Newsome, W. T. (2001). A comparison of spiking statistics in motion sensing neurones of flies and monkeys. Motion Vision: Computational, Neural, and Ecological Constraints, 307-320.

Bair, W., Zohary, E., & Newsome, W. T. (2001). Correlated firing in macaque visual area MT: time scales and relationship to behavior. Journal of Neuroscience, 21(5), 1676-1697.

Similarly, why would drifting gratings be a good example of a stimulus for the hippocampus, an area thought to be involved in memory/place fields?

The results suggest that anatomical “language” is not tied to stimuli. It is imperative to recall that neurons are highly active absent experimentally imposed stimuli, such as when an animal is at rest, when an animal is asleep, and when an animal is in the dark (relevant to visual cortices). With this in mind, also recall that, despite the lack of stimuli tailored to the hippocampus, neurons therein were still reliably separable from neurons in seven nuclei in the thalamus, 6 of which are not classically considered visual regions. Should these regions (including hippocampus) have been inert during the presentation of visual stimuli, there would have been very little separability.

(7) Generalization across laboratories

“[C]omparison across laboratories was somewhat underwhelming. It does okay but none of the results are particularly compelling in terms of performance.

Any result above chance is a rejection of the null hypothesis: that a model trained on a set of animals in Laboratory A will be ineffective in identifying brain regions when tested on recordings collected in Laboratory B (in different animals and under different experimental conditions). As an existence proof, the results suggest conserved principles (however modest) that constrain neuronal activity as a function of anatomy. That models fail to achieve high accuracy (in this context) is not surprising (given the limitations of available recordings)---that models achieve anything above chance, however, is.

Thus, after reading the paper many times, I think part of the problem is that the study is not cohesive, and the authors need to either come up with a tool or demonstrate a scientific finding.

We demonstrate that neuronal spike trains carry robust anatomical information. We developed an ML architecture for this and that architecture is publicly available.

They try to split the middle and I am left somewhat perplexed about what exact scientific problem they or other researchers are solving.

We humbly suggest that the question of a neurons “language” is highly important and central to an understanding of how brains work. From a computational perspective, there is no reason for a vast diversity of cell types, nor a differentiation of the rules that dictate neuronal activity in one region versus another. A Turing Complete system can be trivially constructed from a small number of simple components, such as an excitatory and inhibitory cell type. This is the basis of many machine learning tools.

Please do not confuse stimulus specificity with the concept of a neuron’s language. Neurons in VISp might fire more in response to light, while those in auditory cortex respond to sound. This does not mean that these neurons are different - only that their inputs are. Given the lack of a literature describing our main effect—that single neuron spiking carries information about anatomical location—it is difficult to conclude that our results are either commonplace or to be expected.

I am also unsure why the authors think some of these results are particularly important.

See above.

For instance, has anyone ever argued that brain areas do not have different spike patterns?

Yes. In effect, by two avenues. The first is a lack of any argument otherwise (please do not conflate spike patterns with stimulus tuning), and the second is the preponderance of, e.g., rate codes across many functionally distinct regions and circuits.

Is that not the premise for all systems neuroscience?

No. The premise for all systems neuroscience (from our perspective) is that the brain is a) a collection of interacting neurons and b) the collective system of neurons gives rise to behavior, cognition, sensation, and perception. As stated above, these axiomatic first principles fundamentally do not require that neurons, as individual entities, obey different rules in different parts of the brain.

I could see how one could argue no one has said ISIs matter but the premise that the areas are different is a fundamental part of neuroscience.

Based on logic and the literature, we fundamentally disagree. Consider: while systems neuroscience operates on the principle that brain regions have specialized functions, there is no a priori reason to assume that these functions must be reflected in different underlying computational rules. The simplest explanation is that a single language of spiking exists across regions, with functional differences arising from processing distinct inputs rather than fundamentally different spiking rules. For example, an identical spike train in the amygdala and Layer 5 of M1 would have profoundly different functional impacts, yet the spike timing itself could be identical (even as stimulus response). Until now, evidence for region-specific spiking patterns has been lacking, and our work attempts to begin addressing this gap. There is extensive further work to be conducted in this space, and it is certain that models will improve, rules will be clarified, and mechanisms will be identified.

Detailed major comments

(1) Exploratory trends in spiking by region and structure across the population:

The argument in this section is that unsupervised analyses might reveal subtle trends in the organization of spiking patterns by area. The authors show 4 plots from t-SNE and claim to see subtle organization. I have concerns. For Figure 1C, it is nearly impossible to see if a significant structure exists that differentiates regions and structures. So this leads certain readers to conclude that the authors are looking at the artifactual structure (see Chari et al. 2024) - likely to contribute to large Twitter battles. Contributing to this issue is that the hyperparameter for tSNE was incorrectly chosen. I do think that a different perplexity should be used for the visualization in order to better show the underlying structure; the current visualization just looks like a single "blob". The UMAP visualizations in the supplement make this point more clearly. I also think the authors should include a better plot with appropriate perplexity or not include this at all. The color map of subtle shades of green and yellow is hard to see as well in both Figure S1 and Figure 1.

In response to the feedback, we replaced t-SNE/UMAP with LDA, while keeping PCA for dimensionality reduction.

As stated in the original methods, t-SNE/UMAP hyperparameters were chosen based on the combination that led to the greatest classifiable separability of the regions/structures in the space (across a broad range of possible combinations). It just so happens that the maximally separable structure from a regions/structures perspective is the “blob”. This suggests that perhaps the predominant structure the t-SNE finds in the data is not driven by anatomy. If we selected hyperparameters in some other way that was not based specifically on regions/structures (e.g. simple visual inspection of the plots) the conformation would of course be different and not blob-like. However, we removed the t-SNE and UMAP to avoid further confusion.

The “muddy appearance” is not an issue with the color map. As seen in Figure 1B, the chosen colors are visibly distinct. Figure 1C (previous version) appeared muddy yellow/green because of points that overlap with transparency, resulting in a mix of clearly defined classes (e.g., a yellow point on top of a blue point creating green). This overlap is a meaningful representation of the separability observed in this analysis. We also tried using 2D KDE for visualization, but it did not improve the impression of visual separability.

We are removing p-values from the figures because they lead to the impression that we over-interpret these results quantitatively. However, we calculated p-values based on label permutation similar to the way R2 suggests (see previous methods). The conflation with the Wasserstein distances is an understandable misunderstanding. These are unrelated to p-values and used for the heatmaps in S1 only (see previous methods).

Instead of p-values, we now use the adjusted rand index, which measures how accurately neurons within the same region are clustered together (see Line 670 - 671, Figure 1C, and Figure S1) (Hubert & Arabie 1985). This quantifies the extent to which the distribution of points in dimensionally-reduced space is shaped by region/structure.

Hubert, L., & Arabie, P. (1985). Comparing partitions. Journal of Classification, 2(1), 193–218. https://doi.org/10.1007/BF01908075

(2) Logistic classifiers:

The results in this section are somewhat underwhelming. Accuracy is around 40% and yes above chance but I would be very surprised if someone is worried about separating visual structures from the thalamus. Such coarse brain targeting is not difficult. If the authors want to include this data, I recommend they show it as a control in the ISI distribution section. The entire argument here is that perhaps one should not use derived metrics and a nonlinear classifier on more data is better, which is essentially the thrust of the next section.

As outlined above, our work systematically increases in model complexity. The logistic result is an intermediate model, and it returns intermediate results. This is an important stepping stone between the lack of a result based on unsupervised linear dimensionality reduction and the performance of supervised nonlinear models.

From a purely utilitarian perspective, the argument could be framed as “one should not use derived metrics, and a nonlinear classifier on more data is better.” However, please see all of our notes above.

(3) MLP classifiers:

Even in this section, I was left somewhat underwhelmed that a nonlinear classifier with large amounts of data outperforms a linear classifier with small amounts of data. I found the analysis of the ISIs and which timescales are driving the classifier interesting but I think the classifier with smoothing is more interesting. So with a modest chance level decodability of different brain areas in the visual system, I found it somewhat grandiose to claim a "conserved" code for anatomy in the brain. If there is conservation, it seems to be at the level of the coarse brain organization, which in my opinion is not particularly compelling.

The sample size used for both the linear and nonlinear classifiers is the same; however, the nonlinear classifier leverages the detailed spiking time information from ISIs. Our goal here was to systematically evaluate how classical spike metrics compare to more detailed temporal features in their ability to decode brain areas. We chose a linear classifier for spike metrics because, with fewer features, nonlinear methods like neural networks often offer very modest advantages over linear methods, less interpretability, and are prone to overfitting.

Respectfully, we stand by our word choice. The term “conserved” is appropriate given that our results hold appreciably, i.e., statistically above chance, across animals.

(4) Generalization section:

The authors suggest that a classifier learned from one set of data could be used for new data. I was unsure if this was a scientific point or the fact that they could use it as a tool.

It can be both. We are more driven by the scientific implications of a rejection of the null.

Is the scientific argument that ISIs are similar across areas even in different tasks?

It appears so - despite heterogeneity in the tuning of single neurons, their presynaptic inputs, and stimuli, there is identifiable information about anatomical location in the spike train.

Why would one not learn a classifier from every piece of available data: like LFP bands, ISI distributions, and average firing rates, and use that to predict the brain area as a comparison?

Because this would obfuscate the ability to conclude that spike trains embed information about anatomy.

Considering all features simultaneously and adding additional data modalities—such as LFP bands and spike waveforms—has potential to improve classification accuracy at the cost of understanding the contribution of each feature. The spike train as a time series is the most fundamental component of neuronal communication. As a result, this is the only feature of neuronal activity of concern for the present investigation.

Or is the argument that the ISIs are a conserved code for anatomy? Unfortunately, even in this section, the data are underwhelming.

We appreciate the reviewer’s comments, but arrive at a very different conclusion. We were quite surprised to find any generalizability whatsoever.

Moreover, for use as a tool, I think the authors need to seriously consider a control that is either waveforms from different brain areas or the local field potentials. Without that, I am struggling to understand how good this tool is. The authors said "because information transmission in the brain arises primarily from the timing of spiking and not waveforms (etc)., our studies involve only the timestamps of individual spikes from well-isolated units ". However, we are not talking about information transmission and actually trying to identify and assess brain areas from electrophysiological data.

While we are not blind to the “tool” potential that is suggested by our work, this is not the primary motivation or content in any section of the paper. As stated clearly in the abstract, our motivation is to ask “whether individual neurons [...] embed information about their own anatomical location within their spike patterns”. We go on to say “This discovery provides new insights into the relationship between brain structure and function, with broad implications for neurodevelopment, multimodal integration, and the interpretation of large-scale neuronal recordings. Immediately, it has potential as a strategy for in-vivo electrode localization.” Crucially, the last point we make is a nod to application. Indeed, our results suggest that in-vivo electrode localization protocols may benefit from the incorporation of such a model.

In light of the reviewer’s concerns, we have further dampened the weight of statements about our model as a consumer-ready tool.

Example 1: The final sentence of the abstract now reads: “Computational approximations of anatomy have potential to support in-vivo electrode localization.”

Example 2: The results sections now contains the following text: “While significantly above chance, the structure-level model still lacks the accuracy for immediate practical application. However, it is highly likely that the incorporation of datasets with diverse multi-modal features and alternative regions from other research groups will increase the accuracy of such a model. In addition, a computational approach can be combined with other methods of anatomical reconstruction.” (Line 355 - 359).

Example 3: We replaced the phrase "because information transmission in the brain arises primarily from the timing of spiking and not waveforms (etc) " with the phrase “because information is primarily encoded by the firing rate or the timing of spiking and not waveforms (etc)” (Line 116 - 118).

(5) Discussion section:

In the discussion, beginning with "It is reasonable to consider . . ." all the way to the penultimate paragraph, I found the argumentation here extremely hard to follow. Furthermore, the parts of the discussion here I did feel I understood, I heavily disagreed with. They state that "recordings are random in their local sampling" which is almost certainly untrue when it comes to electrophysiology which tends to oversample task-modulated excitatory neurons (https://elifesciences.org/articles/69068). I also disagree that "each neuron's connectivity is unique, and vertebrate brains lack 'identified neurons' characteristic of simple organisms. While brains are only eutelic and "nameable" in only the simplest organisms (C. elegans), cell types are exceedingly stereotyped in their connectivity even in mammals and such connectivity defines their computational properties. Thus I don't find the premise the authors state in the next sentence to be undermined ("it seems unlikely that a single neuron's happenstance imprinting of its unique connectivity should generalize across stimuli and animals"). Overall, I found this subsection to rely on false premises and in my opinion it should be removed.

At the suggestion of R2, we removed the paragraph in question. However, we would like to address some points of disagreement:

We agree that electrophysiology, along with spike-sorting, quality metrics, and filtering of low-firing neurons, leads to oversampling of task-modulated neurons. However, when we stated that recordings are random in their local sampling, we were referring to structural (anatomical) randomness, not functional randomness. In other words, the recorded neurons were not specifically targeted (see below).

Electrode arrays, such as Neuropixels, record from hundreds of neurons within a small volume relative to the total number of neurons and the volume of a given brain region. For instance, the paper R2 referenced includes a statement supporting this: “... assuming a 50-μm ‘listening radius’ for the probes (radius of half-cylinder around the probe where the neurons’ spike amplitude is sufficiently above noise to trigger detection) …, the average yield of 116 regular-spiking units/probe (prior to QC filtering) would imply a density of 42,000 neurons/mm³, much lower than the known density of ~90,000 neurons/mm³ for excitatory cells in mouse visual cortex….”

If we take the estimated volume of V1 to be approximately 3 mm³, this region could theoretically be subdivided into multiple cylinders with a 100-μm diameter. While stereotaxic implantation of the probe mitigates some variability, the natural anatomical variability across individual animals introduces spatially random sampling. This was the randomness we were referring to, and thus, we disagree with the assertion that our claim is “almost certainly untrue.”

Additionally, each cortical pyramidal neuron is understood to have ~ 10,000 presynaptic partners. It is highly unlikely that these connections are entirely pre-specified, perfectly replicated within the same animal, and identical across all members of species. Further, there is enormous diversity in the activity properties of even neighboring cells of the same type. Consider pyramidal neurons in V1. Single neuron firing rates are log normally distributed, there are many of combinations of tuning properties (i.e., direction, orientation) that must occupy each point in retinotopic space, and there is powerful experience dependent change in the connectivity of these cells. We suggest that it is inconceivable that any two neurons, even within a small region of V1, have identical connectivity.

Minor Comments:

(1) Although the description of confusion matrices is good from a didactic perspective, some of this could be moved to methods to simplify the paper.

We thank the reviewer for the suggestion. However, given the broad readership of eLife, we gently suggest that confusion matrices are not a trivial and universally appreciated plotting format. For the purpose of accessibility, a brief and didactic 2-sentence description will make the paper far more comprehensible to many readers at little cost to experts.

(2) Figure 3A: It is concluded in their subsequent figure that the longer the measured amount of time, the better the decoding performance. Thus it makes sense why the average PSTHs do not show significant decoding of areas or structures

That is a good observation. However, all features were calculated from the same duration of data, except in Figure 3B, where we tested the effect of duration. The averaged PSTH was calculated from the same length of data as the ISI distribution and binned to have the same number of feature lengths as the ISI distribution (refer to Methods section). Therefore, we interpreted this as an indication of information degradation through averaging, rather than an effect of data length (Line 234 - 237).

(3) Figure 3D: A Gaussian is used to fit the ISI distributions here but ISI distributions do not follow a normal distribution, they follow an inverse gamma distribution.

We agree with the reviewer and we are familiar with the literature that the ISI distribution is best fitted by a gamma family distribution (as a recent, but not earliest example: Li et al. 2018). However, we did not fit a gaussian (or any distribution) to the data, we just calculated the sample mean and variance. Reporting sample mean and variance (or standard deviation) is not something that is only done for Gaussian distributions. They are broadly used metrics that simply have additional intrinsic meaning for Gaussian distributions. We used the schematic illustration in Fig 3D because mean and variance are much more familiar in Gaussian distribution context, but ultimately that does not affect our analyses in Fig 3 E-F. Alternatively, the alpha and beta intrinsic parameters of a gamma distribution could have been used, but they are known by a much smaller portion of neuroscientists.

Li, M., Xie, K., Kuang, H., Liu, J., Wang, D., Fox, G. E., ... & Tsien, J. Z. (2018). Spike-timing pattern operates as gamma-distribution across cell types, regions and animal species and is essential for naturally-occurring cognitive states. Biorxiv, 145813(10.1101), 145813.

(4) Figure 3G: Something is wrong with this figure as each vertical bar is supposed to represent a drifting grating onset but yet, they are all at 5 hz despite the PSTH being purportedly shown at many different frequencies from 1 to 15 hz.

We appreciate your attention to detail, but we are not representing the onset of individual drifting gratings in this. We just meant to represent the overall start\end of the drifting grating session. We did not intend to signal the temporal frequency of the drifting gratings (or the spatial frequency, orientation, or contrast).

In this passage the goddess makes her case for the eventual penalty leveled against Hippolytus by the wrathful goddess. The audience is presented with the transgression as well as the intended punishment. Just as Greek society had a strict code of laws regarding civil responsibilities they also had a moral code from the Gods. The reiteration of these standards in this form promotes general acceptance among the masses.

Fixing the style of the code

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

This study examined the interaction between two key cortical regions in the mouse brain involved in goal-directed movements, the rostral forelimb area (RFA) - considered a premotor region involved in movement planning, and the caudal forelimb area (CFA) - considered a primary motor region that more directly influences movement execution. The authors ask whether there exists a hierarchical interaction between these regions, as previously hypothesized, and focus on a specific definition of hierarchy - examining whether the neural activity in the premotor region exerts a larger functional influence on the activity in the primary motor area than vice versa. They examine this question using advanced experimental and analytical methods, including localized optogenetic manipulation of neural activity in either region while measuring both the neural activity in the other region and EMG signals from several muscles involved in the reaching movement, as well as simultaneous electrophysiology recordings from both regions in a separate cohort of animals.

The findings presented show that localized optogenetic manipulation of neural activity in either RFA or CFA resulted in similarly short-latency changes in the muscle output and in firing rate changes in the other region. However, perturbation of RFA led to a larger absolute change in the neural activity of CFA neurons. The authors interpret these findings as evidence for reciprocal, but asymmetrical, influence between the regions, suggesting some degree of hierarchy in which RFA has a greater effect on the neural activity in CFA. They go on to examine whether this asymmetry can also be observed in simultaneously recorded neural activity patterns from both regions. They use multiple advanced analysis methods that either identify latent components at the population level or measure the predictability of firing rates of single neurons in one region using firing rates of single neurons in the other region. Interestingly, the main finding across these analyses seems to be that both regions share highly similar components that capture a high degree of variability of the neural activity patterns in each region. Single units' activity from either region could be predicted to a similar degree from the activity of single units in the other region, without a clear division into a leading area and a lagging area, as one might expect to find in a simple hierarchical interaction. However, the authors find some evidence showing a slight bias towards leading activity in RFA. Using a two-region neural network model that is fit to the summed neural activity recorded in the different experiments and to the summed muscle output, the authors show that a network with constrained (balanced) weights between the regions can still output the observed measured activities and the observed asymmetrical effects of the optogenetic manipulations, by having different within-region local weights. These results put into question whether previous and current findings that demonstrate asymmetry in the output of regions can be interpreted as evidence for asymmetrical (and thus hierarchical) inputs between regions, emphasizing the challenges in studying interactions between any brain regions.

Strengths:

The experiments and analyses performed in this study are comprehensive and provide a detailed examination and comparison of neural activity recorded simultaneously using dense electrophysiology probes from two main motor regions that have been the focus of studies examining goal-directed movements. The findings showing reciprocal effects from each region to the other, similar short-latency modulation of muscle output by both regions, and similarity of neural activity patterns without a clear lead/lag interaction, are convincing and add to the growing body of evidence that highlight the complexity of the interactions between multiple regions in the motor system and go against a simple feedforward-like network and dynamics. The neural network model complements these findings and adds an important demonstration that the observed asymmetry can, in theory, also arise from differences in local recurrent connections and not necessarily from different input projections from one region to the other. This sheds an important light on the multiple factors that should be considered when studying the interaction between any two brain regions, with a specific emphasis on the role of local recurrent connections, that should be of interest to the general neuroscience community.

Weaknesses:

While the similarity of the activity patterns across regions and lack of a clear leading/lagging interaction are interesting observations that are mostly supported by the findings presented (however, see comment below for lack of clarity in CCA/PLS analyses), the main question posed by the authors - whether there exists an endogenous hierarchical interaction between RFA and CFA - seems to be left largely open. 

The authors note that there is currently no clear evidence of asymmetrical reciprocal influence between naturally occurring neural activity patterns of the two regions, as previous attempts have used non-natural electrical stimulation, lesions, or pharmacological inactivation. The use of acute optogenetic perturbations does not seem to be vastly different in that aspect, as it is a non-natural stimulation of inhibitory interneurons that abruptly perturbs the ongoing dynamics.

We do believe that our optogenetic inactivation identifies a causal interaction between the endogenous activity patterns in the excitatory projection neurons, which we have largely silenced, and the downstream endogenous activity that is perturbed. The effect in the downstream region results directly from the silencing of activity in the excitatory projection neurons that mediate each region’s interaction with other regions. Here we have performed a causal intervention common in biology: a loss-of-function experiment. Such experiments generally reveal that a causal interaction of some sort is present, but often do not clarify much about the nature of the interaction, as is true in our case. By showing that a silencing of endogenous activity in one motor cortical region causes a significant change to the endogenous activity in another, we establish a causal relationship between these activity patterns. This is analogous to knocking out the gene for a transcription factor and observing causal effects on the expression of other genes that depend on it. 

Moreover, our experiments are, to our knowledge, the first that localize a causal relationship to endogenous activity in motor cortex at a particular point during a motor behavior. Lesion and pharmacological or chemogenetic inactivation have long-lasting effects, and so their consequences on firing in other regions cannot be attributed to a short-latency influence of activity at a particular point during movement. Moreover, the involvement of motor cortex in motor learning and movement preparation/initiation complicates the interpretation of these consequences in relation to movement execution, as disturbance to processes on which execution depends can impede execution itself. Stimulation experiments generate spiking in excitatory projection neurons that is not endogenous.

That said, we would agree that the form of the causal interaction between RFA and CFA remains unaddressed by our results. These results do not expose how the silenced activity patterns affect activity in the downstream region, just as knocking out a transcription factor gene does not expose how the transcription factor influences the expression of other genes. To show evidence for a specific type of interaction dynamics between RFA and CFA, a different sort of experiment would be necessary. See Jazayeri and Afraz, Neuron, 2017 for more on this issue.

Furthermore, the main finding that supports a hierarchical interaction is a difference in the absolute change of firing rates as a result of the optogenetic perturbation, a finding that is based on a small number of animals (N = 3 in each experimental group), and one which may be difficult to interpret. 

Though N = 3, we do show statistical significance. Moreover, using three replicates is not uncommon in biological experiments that require a large technical investment.

As the authors nicely demonstrate in their neural network model, the two regions may differ in the strength of local within-region inhibitory connections. Could this theoretically also lead to a difference in the effect of the artificial light stimulation of the inhibitory interneurons on the local population of excitatory projection neurons, driving an asymmetrical effect on the downstream region? 

We (Miri et al., Neuron, 2017) and others (Guo et al., Neuron, 2014) have shown that the effect of this inactivation on excitatory neurons in CFA is a near-complete silencing (90-95% within 20 ms). There thus is not much room for the effects on projection neurons in RFA to be much larger. We have measured these local effects in RFA as part of other work (Kristl et al., biorxiv, 2025), verifying that the effects on RFA projection neuron firing are not larger.

Moreover, the manipulation was performed upon the beginning of the reaching movement, while the premotor region is often hypothesized to exert its main control during movement preparation, and thus possibly show greater modulation during that movement epoch. It is not clear if the observed difference in absolute change is dependent on the chosen time of optogenetic stimulation and if this effect is a general effect that will hold if the stimulation is delivered during different movement epochs, such as during movement preparation.

We agree that the dependence of RFA-CFA interactions on movement phase would be interesting to address in subsequent experiments. While a strong interpretation of lesion results might lead to a hypothesis that premotor influence on primary motor cortex is local to, or stronger during, movement preparation as opposed to execution, at present there is to our knowledge no empirical support from interventional experiments for this hypothesis. Moreover, existing results from analysis of activity in these two regions have produced conflicting results on the strength of interaction between these regions during preparation. Compare for example BachschmidRomano et al., eLife, 2023 to Kaufman et al., Nature Neuroscience, 2014.

That said, this lesion interpretation would predict the same asymmetry we have observed from perturbations at the beginning of a reach - a larger effect of RFA on CFA than vice versa.

Another finding that is not clearly interpretable is in the analysis of the population activity using CCA and PLS. The authors show that shifting the activity of one region compared to the other, in an attempt to find the optimal leading/lagging interaction, does not affect the results of these analyses. Assuming the activities of both regions are better aligned at some unknown groundtruth lead/lag time, I would expect to see a peak somewhere in the range examined, as is nicely shown when running the same analyses on a single region's activity. If the activities are indeed aligned at zero, without a clear leading/lagging interaction, but the results remain similar when shifting the activities of one region compared to the other, the interpretation of these analyses is not clear.

Our results in this case were definitely surprising. Many share the intuition that there should be a lag at which the correlations in activity between regions may be strongest. The similarity in alignment across lags we observed might be expected if communication between regions occurs over a range of latencies as a result of dependence on a broad diversity of synaptic paths that connect neurons. In the Discussion, we offer an explanation of how to reconcile these findings with the seemingly different picture presented by DLAG.

Reviewer #2 (Public review):

Summary:

While technical advances have enabled large-scale, multi-site neural recordings, characterizing inter-regional communication and its behavioral relevance remains challenging due to intrinsic properties of the brain such as shared inputs, network complexity, and external noise. This work by Saiki-Ishkawa et al. examines the functional hierarchy between premotor (PM) and primary motor (M1) cortices in mice during a directional reaching task. The authors find some evidence consistent with an asymmetric reciprocal influence between the regions, but overall, activity patterns were highly similar and equally predictive of one another. These results suggest that motor cortical hierarchy, though present, is not fully reflected in firing patterns alone.

Strengths:

Inferring functional hierarchies between brain regions, given the complexity of reciprocal and local connectivity, dynamic interactions, and the influence of both shared and independent external inputs, is a challenging task. It requires careful analysis of simultaneous recording data, combined with cross-validation across multiple metrics, to accurately assess the functional relationships between regions. The authors have generated a valuable dataset simultaneously recording from both regions at scale from mice performing a cortex-dependent directional reaching task.

Using electrophysiological and silencing data, the authors found evidence supporting the traditionally assumed asymmetric influence from PM to M1. While earlier studies inferred a functional hierarchy based on partial temporal relationships in firing patterns, the authors applied a series of complementary analyses to rigorously test this hierarchy at both individual neuron and population levels, with robust statistical validation of significance.

In addition, recording combined with brief optogenetic silencing of the other region allowed authors to infer the asymmetric functional influence in a more causal manner. This experiment is well designed to focus on the effect of inactivation manifesting through oligosynaptic connections to support the existence of a premotor to primary motor functional hierarchy.

Subsequent analyses revealed a more complex picture. CCA, PLS, and three measures of predictivity (Granger causality, transfer entropy, and convergent cross-mapping) emphasized similarities in firing patterns and cross-region predictability. However, DLAG suggested an imbalance, with RFA capturing CFA variance at a negative time lag, indicating that RFA 'leads' CFA. Taken together these results provide useful insights for current studies of functional hierarchy about potential limitations in inferring hierarchy solely based on firing rates.

While I would detail some questions and issues on specifics of data analyses and modeling below, I appreciate the authors' effort in training RNNs that match some behavioral and recorded neural activity patterns including the inactivation result. The authors point out two components that can determine the across-region influence - 1) the amount of inputs received and 2) the dependence on across-region input, i.e., the relative importance of local dynamics, providing useful insights in inferring functional relationships across regions.

Weaknesses:

(1) Trial-averaging was applied in CCA and PLS analyses. While trial-averaging can be appropriate in certain cases, it leads to the loss of trial-to-trial variance, potentially inflating the perceived similarities between the activity in the two regions (Figure 4). Do authors observe comparable degrees of similarity, e.g., variance explained by canonical variables? Also, the authors report conflicting findings regarding the temporal relationship between RFA and CFA when using CCA/PLS versus DLAG. Could this discrepancy be due to the use of trial-averaging in former analyses but not in the latter?

We certainly agree that the similarity in firing patterns is higher in trial averages than on single trials, given the variation in single-neuron firing patterns across trials. Here, we were trying to examine the similarity of activity variance that is clearly movement dependent, as trial averages are, and to use an approach aligned with those applied in the existing literature. We would also agree that there is more that can be learned about interactions from trial-by-trial analysis. It is possible that the activity components identified by DLAG as being asymmetric somehow are not reflected strongly in trial averages. In our Discussion we offer another potential explanation that is based on other differences in what is calculated by DLAG and CCA/PLS.

We also note here that all of the firing pattern predictivity analysis we report (Figure 6) was done on single trial data, and in all cases the predictivity was symmetric. Thus, our results in aggregate are not consistent with symmetry purely being an artifact of trial averaging.

(2) A key strength of the current study is the precise tracking of forelimb muscle activity during a complex motor task involving reaching for four different targets. This rich behavioral data is rarely collected in mice and offers a valuable opportunity to investigate the behavioral relevance of the PM-M1 functional interaction, yet little has been done to explore this aspect in depth. For example, single-trial time courses of inter-regional latent variables acquired from DLAG analysis can be correlated with single-trial muscle activity and/or reach trajectories to examine the behavioral relevance of inter-regional dynamics. Namely, can trial-by-trial change in inter-regional dynamics explain behavioral variability across trials and/or targets? Does the inter-areal interaction change in error trials? Furthermore, the authors could quantify the relative contribution of across-area versus within-area dynamics to behavioral variability. It would also be interesting to assess the degree to which across-area and within-area dynamics are correlated. Specifically, can acrossarea dynamics vary independently from within-area dynamics across trials, potentially operating through a distinct communication subspace?

These are all very interesting questions. Our study does not attempt to parse activity into components predictive of muscle activity and others that may reflect other functions. Distinct components of RFA and CFA activity may very well rely on distinct interactions between them.

(3) While network modeling of RFA and CFA activity captured some aspects of behavioral and neural data, I wonder if certain findings such as the connection weight distribution (Figure 7C), across-region input (Figure 7F), and the within-region weights (Figure 7G), primarily resulted from fitting the different overall firing rates between the two regions with CFA exhibiting higher average firing rates. Did the authors account for this firing rate disparity when training the RNNs?

The key comparison in Figure 7 is shown in 7F, where the firing rates are accounted for in calculating the across-region input strength. Equalizing the firing rates in RFA and CFA would effectively increase RFA rates. If the mean firing rates in each region were appreciably dependent on across-region inputs, we would then expect an off-setting change in the RFA→CFA weights, such that the RFA→CFA distributions in 7F would stay the same. We would also expect the CFA→RFA weights would increase, since RFA neurons would need more input. This would shift the CFA→RFA (blue) distributions up. Thus, if anything, the key difference in this panel would only get larger. 

We also generally feel that it is a better approach to fit the actual firing rates, rather than normalizing, since normalizing the firing rates would take us further from the actual biology, not closer.

(4) Another way to assess the functional hierarchy is by comparing the time courses of movement representation between the two regions. For example, a linear decoder could be used to compare the amount of information about muscle activity and/or target location as well as time courses thereof between the two regions. This approach is advantageous because it incorporates behavior rather than focusing solely on neural activity. Since one of the main claims of this study is the limitation of inferring functional hierarchy from firing rate data alone, the authors should use the behavior as a lens for examining inter-areal interactions.

As we state above, we agree that examining interactions specific to movement-related activity components could reveal interesting structure in interregional interactions. Since it remains a challenge to rigorously identify a subset of neural activity patterns specifically related to driving muscle activity, any such analysis would involve an additional assumption. It remains unclear how well the activity that decoders use for predicting muscle activity matches the activity that actually drives muscle activity in situ.

To address this issue, which related to one raised by Reviewer #3 below, we have added an additional paragraph to the Discussion (see “Manifestations of hierarchy in firing patterns”).

Reviewer #3 (Public review):

This study investigates how two cortical regions that are central to the study of rodent motor control (rostral forelimb area, RFA, and caudal forelimb area, CFA) interact during directional forelimb reaching in mice. The authors investigate this interaction using

(1) optogenetic manipulations in one area while recording extracellularly from the other, (2) statistical analyses of simultaneous CFA/RFA extracellular recordings, and (3) network modeling.

The authors provide solid evidence that asymmetry between RFA and CFA can be observed, although such asymmetry is only observed in certain experimental and analytical contexts.

The authors find asymmetry when applying optogenetic perturbations, reporting a greater impact of RFA inactivation on CFA activity than vice-versa. The authors then investigate asymmetry in endogenous activity during forelimb movements and find asymmetry with some analytical methods but not others. Asymmetry was observed in the onset timing of movement-related deviations of local latent components with RFA leading CFA (computed with PCA) and in a relatively higher proportion and importance of cross-area latent components with RFA leading than CFA leading (computed with DLAG). However, no asymmetry was observed using several other methods that compute cross-area latent dynamics, nor with methods computed on individual neuron pairs across regions. The authors follow up this experimental work by developing a twoarea model with asymmetric dependence on cross-area input. This model is used to show that differences in local connectivity can drive asymmetry between two areas with equal amounts of across-region input.

Overall, this work provides a useful demonstration that different cross-area analysis methods result in different conclusions regarding asymmetric interactions between brain areas and suggests careful consideration of methods when analyzing such networks is critical. A deeper examination of why different analytical methods result in observed asymmetry or no asymmetry, analyses that specifically examine neural dynamics informative about details of the movement, or a biological investigation of the hypothesis provided by the model would provide greater clarity regarding the interaction between RFA and CFA.

Strengths:

The authors are rigorous in their experimental and analytical methods, carefully monitoring the impact of their perturbations with simultaneous recordings, and providing valid controls for their analytical methods. They cite relevant previous literature that largely agrees with the current work, highlighting the continued ambiguity regarding the extent to which there exists an asymmetry in endogenous activity between RFA and CFA.

A strength of the paper is the evidence for asymmetry provided by optogenetic manipulation. They show that RFA inactivation causes a greater absolute difference in muscle activity than CFA interaction (deviations begin 25-50 ms after laser onset, Figure 1) and that RFA inactivation causes a relatively larger decrease in CFA firing rate than CFA inactivation causes in RFA (deviations begin <25ms after laser onset, Figure 3). The timescales of these changes provide solid evidence for an asymmetry in the impact of inactivating RFA/CFA on the other region that could not be driven by differences in feedback from disrupted movement (which would appear with a ~50ms delay).

The authors also utilize a range of different analytical methods, showing an interesting difference between some population-based methods (PCA, DLAG) that observe asymmetry, and single neuron pair methods (granger causality, transfer entropy, and convergent cross mapping) that do not. Moreover, the modeling work presents an interesting potential cause of "hierarchy" or "asymmetry" between brain areas: local connectivity that impacts dependence on across-region input, rather than the amount of across-region input actually present.

Weaknesses:

There is no attempt to examine neural dynamics that are specifically relevant/informative about the details of the ongoing forelimb movement (e.g., kinematics, reach direction). Thus, it may be preemptive to claim that firing patterns alone do not reflect functional influence between RFA/CFA. For example, given evidence that the largest component of motor cortical activity doesn't reflect details of ongoing movement (reach direction or path; Kaufman, et al. PMID: 27761519) and that the analytical tools the authors use likely isolate this component (PCA, CCA), it may not be surprising that CFA and RFA do not show asymmetry if such asymmetry is related to the control of movement details. 

An asymmetry may still exist in the components of neural activity that encode information about movement details, and thus it may be necessary to isolate and examine the interaction of behaviorally-relevant dynamics (e.g., Sani, et al. PMID: 33169030).

To clarify, we are not claiming that firing patterns in no way reflect the asymmetric functional influence that we demonstrate with optogenetic inactivation. Instead, we show that certain types of analysis that we might expect to reflect such influence, in fact, do not. Indeed, DLAG did exhibit asymmetries that matched those seen in functional influence (at least qualitatively), though other methods we applied did not.

As we state above, we do think that there is more that can be gleaned by looking at influence specifically in terms of activity related to movement. However, if we did find that movement-related activity exhibited an asymmetry following functional influence, our results imply that the remaining activity components would exhibit an opposite asymmetry, such that the overall balance is symmetric. This would itself be surprising. We also note that the components identified by CCA and PLS do show substantial variation across reach targets, indicating that they are not only reflecting condition-invariant components. These analyses were performed on components accounting for well over 90% of the total activity variance, suggesting that both conditiondependent and condition-invariant components should be included.

To address the concern about condition-dependent and condition-invariant components, we have added a sentence to the Results section reporting our CCA and PLS results: “Because our results here involve the vast majority of trial-averaged activity variance, we expect that they encompass both components of activity that vary for different movement conditions (condition-dependent), and those that do not (condition-invariant).” To address the general concerns about potential differences in activity components specifically related to muscle activity, we have also added an additional paragraph to the Discussion (see “Manifestations of hierarchy in firing patterns”).

The idea that local circuit dynamics play a central role in determining the asymmetry between RFA and CFA is not supported by experimental data in this paper. The plausibility of this hypothesis is supported by the model but is not explored in any analyses of the experimental data collected. Given the focus on this idea in the discussion, further experimental investigation is warranted.

While we do not provide experimental support for this hypothesis, the data we present also do not contradict this hypothesis. Here we used modeling as it is often used - to capture experimental results and generate hypotheses about potential explanation. We do feel that our Discussion makes clear where the hypothesis derives from and does not misrepresent the lack of experimental support. We expect readers will take our engagement with this hypothesis with the appropriate grain of salt. The imaginable experiments to support such a hypothesis would constitute another substantial study, requiring numerous controls - a whole other paper in itself.

Recommendations for the authors:  

Reviewer #1 (Recommendations for the authors):

(1) There are a few small text/figure caption modifications that can be made for clarity of reading:

(2) Unclear sentence in the second paragraph of the introduction: "For example, stimulation applied in PM has been shown to alter the effects on muscles of stimulation in M1 under anesthesia, both in monkeys and rodents."

This sentence has been rephrased for clarity: “For example, in anesthetized monkeys34 and rodents35, stimulation in PM alters the effects of stimulation in M1 on muscles.”

(3) The first section of the results presents the optogenetic manipulation. However, the critical control that tests whether this was strictly a local manipulation that did not affect cells in the other region is introduced only much later. It may be helpful to add a comment in this section noting that such a control was performed, even if it is explained in detail later when introducing the recordings.

We have added the following to the first Results section: “we show below that direct optogenetic effects were only seen in the targeted forelimb area and not the other.”

(4) Figure 1D - I imagine these averages are from a single animal, but this is not stated in the figure caption.

“For one example mouse,” has been added to the beginning of the Figure 1D legend.

(5) Figure 2F - N=6 is not stated in the panel's caption (though it can make it clearer), while it is stated in the caption of 2H.

“n = 6 mice” has been added to the Figure 2F legend.

(6) There's some inconsistency with the order of RFA/CFA in the figures, sometimes RFA is presented first (e.g., Figure 1D and 1F), and sometimes CFA is presented first (e.g., panels of Figure 2).

We do not foresee this leading to confusion.

(7) "As expected, the majority of recorded neurons in each region exhibited an elevated average firing rate during movement as compared to periods when forelimb muscles were quiescent (Figure 2D,E; Figure S1A,B)" - Figure S1A,B show histograms of narrow vs. wide waveforms, is this the relevant figure here?

We apologize for the cryptic reference. The waveform width histograms were referred to here because they enabled the separation of narrow- and wide-waveform cells shown in Figure 2D,E. We have added the following clause to the referenced sentence to make this explicit:  “, both for narrow-waveform, putative interneurons and wide-waveform putative pyramidal neurons.”

(8) Figure 2I caption - "The fraction of activity variance from 150 ms before reach onset to 150 ms after it that occurs before reach onset" - this sentence is not clear.

The Figure 2I legend has been updated to “The activity variance in the 150 ms before muscle activity onset, defined as a fraction of the total activity variance from 150 ms before to 150 ms after muscle activity onset, for each animal (circles) and the mean across animals (black bars, n = 6 mice).”

(9) Figure 4B-G - is this showing results across the 6 animals? Not stated clearly.

Yes - the 21 sessions we had referred to are drawn from all six mice. We have updated the legend here to make this explicit.

(10) DLAG analysis - is there any particular reasoning behind choosing four across-region and four within-region components?

In actuality, we completed this analysis for a broad range of component numbers and obtained similar results in all cases. Four fell in the center of our range, and so we focused the illustrations shown in the figure on this value. In general, the number of components is arbitrary. The original paper from Gokcen et al. describes a method for identifying a lower bound on the number of distinct components the method can identify. However, this method yields different results for each individual recording session. For the comparisons we performed, we needed to use the same range of values for each session.

(11) Figure 5A seems to show 11 across-session components, it's unclear from the caption but I imagine this should show 12 (4 components times 3 sessions?)

As we state in the Methods, any across-region latent variable with a lag that failed to converge between the boundary values of ±200 ms was removed from the analysis. In the case illustrated in this panel, the lag for one of the components failed to converge and is not shown. We have now clarified this both in the relevant Results paragraph and in the figure legend.

(12) Figure 5B - is each marker here the average variance explained by all across/within components that were within the specified lag criteria across sessions per mouse? In other words, what does a single marker here stand for?

We apologize for the lack of clarity here. These values reflect the average across sessions for each mouse. We have updated the legend to make this explicit.

Reviewer #2 (Recommendations for the authors):

As I have addressed most of my major recommendations in the public review, I will use this section to include relatively minor points for the authors to consider.

(1) The EMG data in Figure 1C shows distinct patterns across spouts, both in the magnitude and complexity of muscle activations. It would be interesting to investigate whether these differences in muscle activity lead to behavioral variations (e.g., reaction time, reach duration) and how they relate to the relative involvement of the two areas.

We agree that it would be interesting to examine how the interactions between areas vary as behavior varies. While the differences between reaches here are limited, we have addressed this question for two substantially different motor behaviors (reaching and climbing) in a follow-up study that was recently preprinted (Kristl et al., biorxiv, 2025).

(2) How do the authors account for the lingering impact of RFA inactivation on muscle activity, which persists for tens of milliseconds after laser offset? Could this effect be due to compensatory motor activity following the perturbation? A further illustration of how the raw limb trajectories and/or muscle activity are perturbed and recovered would help readers better understand the impact of motor cortical inactivation.

To clarify the effects of inactivation on a longer timescale, we have added a new supplemental figure showing the plots from Figure 1D over a longer time window extending to 500 ms after trial onset (new Figure S1). Lingering effects do persist, at least in certain cases. In general, we find it hard to ascertain the source of optogenetic effects on longer timescales like this. On the shortest timescales, effects will be mediated by relatively direct connections between regions. However, on these longer timescales, effects could be due to broader changes in brain and behavioral state that can influence muscle activity. For example, attempts to compensate for the initial disturbance to muscle activity could cause divergence from controls on these longer timescales. Muscle tissue itself is also known to have long timescale relaxation dynamics, and it would not be surprising if the relevant control circuits here also had long timescales dynamics, such that we would not expect an immediate return to control when the light pulse ends. Because of this ambiguity, we generally avoid interpretation of optogenetic effects on these longer timescales.

Reviewer #3 (Recommendations for the authors):

(1) Page 9: ". We measured the time at which the activity state deviated from baseline preceding reach onset," - I cannot find how this deviation was defined (neither the baseline nor the threshold).

We have added text to the Figure 2G legend that explicitly states how the baseline and activity onset time were defined.

(2) Given the shape of the curves in Figure 2G, the significance of this result seems susceptible to slight modifications of what defines a baseline or a deviation threshold. For example, it looks like the circle for CFA has a higher y-axis value, suggesting the baseline deviance is higher, but it is unclear why that would be from the plot. If the threshold for deviation in neural activity state were held uniform between CFA and RFA is the difference still significant across animals?

We have repeated the analysis using the same absolute threshold for each region. We used the higher of the two thresholds from each region. The difference remains significant. This is now described in the last paragraph of the Results section for Figure 2.

(3) Since summed deviation of the top 3 PCs is used to show a difference in activity onset between CFA/RFA, but only a small proportion of variance is explained pre-movement (<2% in most animals), it seems relevant to understand what percentage of CFA/RFA neuron activity actually is modulated and deviates from baseline prior to movement and to show the distribution of activity onsets at the single neuron level in CFA/RFA. Can an onset difference only be observed using PCA? 

Because many neurons have low firing rates, estimating the time at which their firing rate begins to rise near reach onset is difficult to do reliably. It is also true that not all neurons show an increase around onset - some show a decrease and others show no discernible change. Using PCs to measure onset avoids both of these problems, since they capture both increases and decreases in individual neuron firing rates and are much less noisy than individual neuron firing rates. 

However, based on this comment, we have repeated this analysis on a single-neuron level using only neurons with relatively high average firing rates. Specifically, we analyzed neurons with mean firing rates above the 90th percentile across all sessions within an animal. Neurons whose activity never crossed threshold were excluded. Results matched those using PCs, with RFA neurons showing an earlier average activity onset time. This is now described in the last paragraph of the Results section for Figure 2.

(4) It is stated that to study the impact of inactivation on CFA/RFA activity, only the 50 highest average firing rate neurons were used (and maybe elsewhere too, e.g., convergent cross mapping). It is unclear why this subselection is necessary. It is justified by stating that higher firing rate neurons have better firing rate estimates. This may be supportable for very low firing rate units that spike sorting tools have a hard time tracking, but I don't think this is supported by data for most of the distribution of firing rates. It therefore seems like the results might be biased by a subselection of certain high firing rate neuron populations. It would be useful to also compute and mention if the results for all neurons/neuron pairs are the same. If there is worry about low-quality units being those with low firing rates, a threshold for firing rate as used elsewhere in the paper (at least 1 spike / 2 trials) seems justified.

The issue here is that as firing rates decrease and firing rate estimates get noisier, estimates of the change in firing rate get more variable. Here we are trying to estimate the fraction of neurons for which firing rates decreased upon inactivation of the other region. Variability in estimates of the firing rate change will bias this estimate toward 50%, since in the limit when the change estimates are entirely based on noise, we expect 50% to be decreases. As expected, when we use increasingly liberal thresholds for this analysis, the fraction of decreases trends closer to 50%. 

As a consequence of this, we cannot easily distinguish whether higher firing rate neurons might for some reason have a greater tendency to exhibit decreases in firing compared to lower firing rate neurons. However, we see no positive reason to expect such a difference. We have added a sentence noting this caveat in interpreting our findings to the relevant paragraph of the Results.

The lack of min/max axis values in Figure 3B-F makes it hard to interpret - are these neurons almost silent when near the bottom of the plot or are they still firing a substantial # of spikes?

To aid interpretation of the relative magnitude of firing rate changes, we have added minimum firing rates for the averages depicted in Figure 3B,C,E and F to the legend. Our original thinking was that the plots in Figure 3G and H would provide an indication of the relative changes in firing.

It would be interesting to know if the impact of optogenetic stimulation changed with exposure to the manipulation. Are all results presented only from the first X number of sessions in each animal? Or is the effect robust over time and (within the same animal) you can get the same results of optogenetic inactivation over time? This information seems critical for reproducibility.

We have now performed brief optogenetic inactivations in several brain areas in several different behavioral paradigms, and have found that inactivation effects are stable both within and across sessions, almost surprisingly so. This includes cases where the inactivations were more frequent (every ~1.25 s on average) and more numerous (>15,000 trials per animal) than in the present manuscript. Thus we did not restrict our analysis here to the first X sessions or trials within a session. We have added additional plots as Figure S3T-AA showing the stability of optogenetic effects both within and across sessions.

Given that it can be difficult to record from interneurons (as the proportion of putative interneurons in Figure S1 attests), the SALT analyses would be more convincing if a few recordings had been performed in the same region as optogenetic stimulation to show a "positive control" of what direct interneuron stimulation looks like. Could also use this to validate the narrow/wide waveform classification.

We have verified that using SALT as we have in the present manuscript does detect vGAT+ interneurons directly responding to light. This is included in a recent preprint from the lab (Kristl et al., biorxiv, 2025). We (Warriner et al., Cell Reports, 2022) and others (Guo et al., Neuron, 2014) have previously used direct ChR2 activation to validate waveform-based classification.

Simultaneous CFA/RFA recordings during optogenetic perturbation would also allow for time courses of inhibition to be compared in RFA/CFA. Does it take 25ms to inhibit locally, and the cross-area impact is fast, or does it inactivate very fast locally and takes ~25ms to impact the other region?

Latencies of this sort are difficult to precisely measure given the statistical limits of this sort of data, but there does appear to be some degree of delay between local and downstream effects. We do not have a statistical foundation as of yet for concluding that this is the case. It will be interesting to examine this issue more rigorously in the future.

Given the difference in the analytical methods, the authors should share data in a relatively unprocessed format (e.g., spike times from sorted units relative to video tracking + behavioral data), along with analysis code, to allow others to investigate these differences.

We plan to post the data and code to our lab’s Github site once the Version of Record is online.

Briefing : Utiliser l'IA dans le monde associatif avec Yann Ferguson (LaborIA)

Source : Extraits de "Parlez-moi d’IA #67 Utiliser l'IA dans le monde associatif avec Yann Ferguson (LaborIA)", podcast animé par Jean-Philippe Clément, avec la participation de Yann Ferguson, chercheur et sociologue, directeur du laboratoire Laboria.

Contexte : Ce briefing est basé sur des extraits d'une table ronde organisée par la Maison de la Vie Associative et Citoyenne du 13ème arrondissement de Paris, abordant les enjeux, risques et bonnes pratiques de l'utilisation de l'IA dans le monde associatif.

Yann Ferguson, spécialiste de l'IA dans le monde du travail, y a partagé son expertise.

Thèmes Principaux :

• Origines et évolution de l'Intelligence Artificielle (IA).
• Impact de l'IA sur le monde du travail, notamment dans le secteur associatif.
• La crise récurrente de l'intelligence face aux nouvelles technologies.
• Avantages et risques de l'IA générative (ChatGPT) et l'émergence du "Shadow AI".
• Alternatives aux grands modèles d'IA et l'importance de l'Open Source et de l'IA frugale.
• Utilisation de l'IA dans l'éducation et le développement des compétences humaines.

Idées Clés et Faits Importants :

Définition et histoire de l'IA :

L'IA est avant tout une discipline de recherche formalisée à partir du milieu des années 1950.

Le terme "Intelligence Artificielle" a été choisi dès 1955 pour son pouvoir accrocheur et marketing, permettant d'attirer des financements.

Les fondateurs avaient pour ambition de créer des machines capables de réaliser des tâches nécessitant des processus mentaux de haut niveau, jusqu'alors mieux réalisées par les humains (raisonnement, organisation de la mémoire, pensée critique, apprentissage perceptuel).

Citation : "l'intelligence artificielle c'est une discipline de recherche avant d'être des outils et des applications qui... a commencé à se formaliser à partir de la deuxième moitié des années 50 donc 1950."

Citation : "Ils cherchaient un terme assez accrocheur... un peu qui avait une dimension marketing assez forte." Deux approches historiques de l'IA : Initialement, deux grandes voies ont été explorées :

L'imitation du raisonnement humain (IA logique ou symbolique) : reproduire les logiques des experts face aux problèmes. Cette approche a dominé jusqu'aux années 2000.

L'imitation de l'apprentissage humain (apprentissage machine - machine learning) : fabriquer des machines qui apprennent à partir d'exemples, comme les humains. Cette approche a connu un renouveau important depuis 2010, notamment grâce à l'avènement du Big Data.

Citation : "Le premier chemin consiste à imiter le raisonnement humain... La deuxième manière qu'ils ont imaginé c'est plutôt d'imiter le l'apprentissage humain."

Citation : "depuis 2010 on connaît un renouveau de l'intelligence artificielle mais plus autour de l'approche de limitation du raisonnement humain bien plus autour de l'approche de limitation de l'apprentissage humain."

Citation : "une des raisons pour lesquelles on a une accélération... ça a été le big data vous savez toutes ces données que l'on retrouve sur internet."

L'apprentissage profond (Deep Learning) et le problème de la boîte noire : Le Deep Learning, un courant du machine learning, a permis d'obtenir d'excellents résultats (conversation, reconnaissance d'images) mais souffre d'un problème d'opacité dans son fonctionnement, appelé "problème de l'explicabilité et de la boîte noire".

Citation : "un courant du machine learning qui est le deep learning l'apprentissage profond... avec un problème c'est que la façon dont la machine parvient à apprendre est assez opaque."

IA et le monde du travail : L'IA s'inscrit dans la révolution informatique, aux côtés de l'intelligence augmentée (l'ordinateur comme outil d'assistance) et de l'intelligence distribuée (réseau, Web, intelligence collective). L'IA, ou intelligence automatisée, est la machine capable de raisonner seule.

Citation : "l'intelligence artificielle elle prend place dans la dans la révolution informatique à partir des années 50 et autour de cette de ces nouvelles machines les ordinateurs il y a en fait trois promesses d'intelligence Il y a l'intelligence augmentée... l'intelligence distribué... la troisième l'intelligence artificielle qui était plutôt l'intelligence automatisée."

Les cinq scénarios du futur du travail face à l'IA : Yann Ferguson a identifié cinq grands récits sur l'impact de l'IA sur le travail :

• Le travailleur remplacé : la machine prend la place de l'humain.

• Le travailleur dominé : l'humain est commandé par la machine ou dépend de plateformes sans protection sociale ("uberisation").

• Les travailleurs divisés : apparition d'une classe de travailleurs pauvres avec des emplois peu intéressants et mal payés.

• Le travailleur augmenté : l'IA libère l'humain des tâches répétitives, lui permettant de se concentrer sur des tâches plus créatives et relationnelles. Le travailleur réhumanisé : Recentrage de l'humain sur des tâches dignes de son humanité.

Citation : "j'avais proposé cinq grandes directions à ce récit... Il y a évidemment le récit du travailleur remplacé... la deuxième le deuxième élément un peu dystopique aussi hein c'est le travailleur dominé... 3ème scénario négatif c'est ce que j'avais appelé les travailleurs divisés...

Il y avait quand même deux scénarios beaucoup plus optimistes Il y avait le scénario du travailleur euh du travailleur augmenté... Après le dernier c'est ce qu'on appelle le travailleur réhumanisé."

Le rôle essentiel du secteur associatif ("tiers secteur non marchand") : Jeremy Rifkin, dans les années 90, anticipait que le logiciel remplacerait de nombreux emplois, mais que le "tiers secteur non marchand" (l'associatif), essentiel pour vivre ensemble et non adressé par les logiques marchandes, prendrait une part importante de notre activité.

Citation : "il y a plein d'activités dont on a absolument besoin pour vivre ensemble Et il a appelé ça le tiers secteur non marchand."

Citation : "l'associatif c'est tout ce dont on a besoin pour vivre ensemble mais que le marché n'adresse pas."

L'impact de l'IA générative (ChatGPT) : La sortie de ChatGPT en novembre 2022 a transformé l'usage de l'IA, passant d'initiatives majoritairement patronales à une adoption par les employés eux-mêmes ("Shadow AI"). Plus de la moitié des Français utilisant l'IA au travail le font sans l'accord de leur manager.

Citation : "Lia générative ça change tout... Avant ChatGPT les études montraient que il y avait entre 1 et 10 % des Français qui pouvaient dire j'ai travaillé avec lire Voilà au moins une fois avec Chat GPT on a dépassé les 20 %."

Citation : "on est beaucoup plus dans moi employé j'utilise chat GPT et c'est mon employeur qui veut pas mais je le fais quand même Voilà on appelle ça le shadow AI."

La crise récurrente de l'intelligence face aux technologies : L'histoire montre une résistance récurrente aux nouvelles technologies de l'intelligence, de l'écriture (critiquée par Socrate) à l'imprimerie, la télévision, internet et Wikipédia, toutes accusées de "nous rendre idiot" ou de détruire le lien social. Cette crainte se manifeste aujourd'hui avec l'IA.

Citation : "Qu'est-ce qu'une technologie de l'intelligence c'est un un artefact qui va intervenir d'une façon ou d'une autre dans nos raisonnements Et un artefact très noble extrêmement valorisé dans les universités c'est l'écriture."

Citation : "on a eu différents moments de crise de l'intelligence en lien avec les technologies de l'intelligence L'imprimerie a été une crise dans l'intelligence majeure... Lorsque j'étais jeune c'était la la télévision hein qui était qui nous rendait idiot... internet non seulement devait nous rendre idiot mais aussi de mettre devait mettre fin au lien social... Wikipédia... lorsque Tiag GPT est arrivé on a dit il cite pas ses sources."

Citation : "on a une espèce de crise récurrente de l'intelligence qui amène souvent à considérer que la nouvelle technologie l'intelligence ça nous rend idiot." Perte de facultés versus développement de compétences supérieures : L'utilisation de technologies de l'intelligence peut entraîner une perte de certaines facultés (ex: mémorisation avec les smartphones), mais la question est de savoir si cette perte permet de se déplacer vers des facultés cognitives supérieures (raisonnement, interprétation).

Citation : "il y a toujours une perte de faculté euh lorsqu'on ne mobilise pas la compétence... Montigne nous dit il vaut mieux une tête bien faite qu'une tête bien pleine."

Le risque de la médiocrité généralisée par l'IA générative :

L'IA générative peut rendre un travail "moyen" accessible sans effort, ce qui est gratuit et peut satisfaire le marché (y compris associatif).

Le risque est d'accepter cette médiocrité intellectuelle au détriment d'un travail de meilleure qualité. Les experts sont mieux placés pour utiliser l'IA pour aller au-delà de la moyenne.

Citation : "l' générative dont on parle beaucoup de ce soir elle peut facilement rendre tout le monde moyen sans effort." Citation : "quand vous êtes très performant dans votre sujet et bien vous êtes finalement un bien meilleur utilisateur de lien." Citation : "l'escroquerie c'est de dire que tout le monde peut tout faire avec liagénérative Ça c'est le mensonge." Citation : "le risque c'est plutôt cette espèce de satisfaction générale pour des choses de médiocre qualité intellectuelle."

Alternatives Open Source et IA frugale : Face aux grands modèles propriétaires (comme ChatGPT d'OpenAI), il existe des alternatives Open Source dont le code est public et modifiable. Des modèles spécialisés et "frugaux" (moins consommateurs de ressources énergétiques) sont développés, permettant d'installer l'IA localement sur son ordinateur (ex: LM Studio).

Des acteurs comme Perplexity proposent des modèles qui citent leurs sources (même si la vérification reste nécessaire). Des initiatives françaises comme Playas entraînent des modèles Open Source sur des corpus de données transparents.

Citation : "il y a une une troisième voix qui est en train de s'ouvrir... J'ai il y a un acteur qui je trouve fait un travail fantastique en France qui s'appelle Playas qui est un acteur qui qui entraîne ses modèles ce qu'on appelle en open source."

Citation : "Les solutions commencent à émerger... il n'y a pas que les grands modèles générals qui sont après on va revenir peut-être à un moment donné mais qui sont très très consommateurs de ressources d'énergie On peut il y a il y a désormais une école de développement de l'IA qui est euh très frugal très spé spécial très spécifique à des sujets."

Citation : "Open AI est une solution privée où on ne connaît pas la source... Et il y a plein de modèles qui sont open source c'est-à-dire que le code il est publié en ligne."

L'éthique et l'écologie de l'IA : La course au "scaling" (augmenter l'échelle des modèles) des grands acteurs est très énergivore.

L'IA frugale, qui se concentre sur des tâches spécifiques et minimise les ressources, est une approche plus responsable. Une spécification AFNOR sur l'IA Frugale existe pour guider les développeurs.

Citation : "J'ai pas pu m'empêcher de faire mon petit coup de gueule sur l'usage des modèles généraux énormes et leur fabrication euh versus les petits modèles frugo et et open source."

Citation : "vous avez une spécification de l'AFNOR donc vraiment un truc officiel quand même qui s'appelle IA Frugal et qui donne des méthodes aux gens qui développent sur l'IA pour s'interroger sur la manière de le faire de la manière la plus la plus frugale."

Utilisation de l'IA comme outil d'amélioration dans l'éducation :

L'exemple de l'utilisation de l'IA pour aider une lycéenne à améliorer son devoir montre comment l'IA peut servir non pas à faire le travail à la place de l'humain, mais à le perfectionner et à développer des compétences critiques.

Citation : "on a plutôt essayé de voir comment Lia pouvait l'aider à faire mieux qu'à faire moins."

Conclusion Principale :

L'IA représente une évolution majeure de l'intelligence, inscrite dans une histoire longue de technologies qui ont suscité des craintes récurrentes.

Son impact sur le monde du travail, y compris dans le secteur associatif, est multiforme, avec des scénarios allant du remplacement à l'augmentation et à la réhumanisation du travail.

L'avènement de l'IA générative a démocratisé son usage, mais soulève des questions éthiques, écologiques et de qualité.

Il est crucial de ne pas se limiter aux grands modèles propriétaires et de considérer les alternatives Open Source et les approches d'IA frugale.

L'enjeu n'est pas nécessairement de "déléguer l'intelligence humaine à une machine", mais de comprendre comment l'IA peut être un outil pour améliorer et développer les compétences humaines, notamment en s'appuyant sur les forces relationnelles et créatives de l'humain, particulièrement importantes dans le monde associatif.

Être un "bon utilisateur" de l'IA, capable d'interpréter et de contextualiser ses réponses, est essentiel.

Author response:

We will revise the statements of novelty in the introduction by more clearly emphasizing how our model addresses gaps in the existing literature. In addition, we will clarify the description of the dispersal process. Briefly, we use the same dispersal gene β to represent the likelihood an individual will either leave or join a group, thereby quantifying both dispersal and immigration using the same parameter. Specifically, individuals with higher β are more likely to remain as floaters (i.e., disperse from their natal group to become a breeder elsewhere), whereas those with lower β are either more likely to remain in their natal group as subordinates (i.e., queue in a group for the breeding position) or join another group if they dispersed. Immigrants that join a group as a subordinate help and queue for a breeding position, as does any natal subordinate born into the group. To follow the suggestion of the referee and more fully explore the impact of competition between subordinates born in the group and subordinate immigrants, we will explore extending our model to allow dispersers to leave their natal group and join another as subordinates, by incorporating a reaction norm based on their age or rank (D = 1 / (1 + exp (β_t * t – β₀)) . This approach will allow individuals to adjust also their dispersal strategy to their competitiveness and to avoid kin competition by remaining as a subordinate in another group.

We apologize that there was some confusion with terminology. We use the term “disperser” to describe individuals that disperse from their natal group. Dispersers can assume one of three roles: (1) they can migrate to another group as "subordinates"; (2) they can join another group as "breeders" if they successfully outcompete other candidates; or (3) they can remain as "floaters" if they fail to join a group. "Floaters" are individuals who persist in a transient state without access to a breeding territory, waiting for opportunities to join a group in an established territory. Therefore, dispersers do not work when they are floaters, but they may later help if they immigrate to a group as a subordinate. Consequently, immigrant subordinates have no inherent competitive advantage over natal subordinates (as step 2.2. “Join a group” is followed by step 3. “Help”, which occurs before step 5. “Become a breeder”). Nevertheless, floaters can potentially outcompete subordinates of the same age if they attempt to breed without first queuing as a subordinate (step 5) when subordinates are engaged in work tasks. We believe that this assumption is realistic and constitutes part of the costs associated with work tasks. However, floaters are at a disadvantage for becoming a breeder because: (1) floaters incur higher mortality than individuals within groups (eq. 3); and (2) floaters may only attempt to become breeders in some breeding cycles (versus subordinate groups members, who are automatically candidates for an open breeding position in the group in each cycle). Therefore, due to their higher mortality, floaters are rarely older than individuals within groups, which heavily influences dominance value and competitiveness. Additionally, any competitive advantage that floaters might have over other subordinate group members is unlikely to drive the kin selection-only results because subordinates would preferably choose defense tasks instead of work tasks so as not to be at a competitive disadvantage compared to floaters.

We note that reviewers also mention that floaters often aren't usually high resource holding potential (RHP) individuals and, therefore, our assumptions might be unrealistic. As we explain above, floaters are not inherently at a competitive advantage in our model. In any case, empirical work in a number of species has shown that dispersers are not necessarily those of lower RHP or of lower quality. In fact, according to the ecological constraints hypothesis, one might predict that high quality individuals are the ones that disperse because only individuals in good condition (e.g., larger body size, better energy reserves) can afford the costs associated with dispersal (Cote et al., 2022). By adding a reaction norm approach to explore the role of age or rank in the revised version, we can also determine whether higher or lower quality individuals are the ones dispersing. We will address the issues of terminology and clarity of the relative competitive advantage of floaters versus subordinates, and also include more information in the Supplementary Tables (e.g., the number of floaters). As a side note, the “scramble context” we mention was an additional implementation that we decided to remove from the final manuscript, but we forgot to remove from Table 1 before submission.

The reviewers also raised a question about asexual reproduction and relatedness more generally. As we showed in the Supplementary Tables and the section on relatedness in the SI (“Kin selection and the evolution of division of labor"), high relatedness does not appear to explain our results. In evolutionary biology generally and in game theory specifically (with the exception of models on sexual selection or sex-specific traits), asexual reproduction is often modelled because it reduces unnecessary complexity. To further study the effect of relatedness on kin structures more closely resembling those of vertebrates, however, we will create an additional “relatedness structure level”, where we will shuffle half of the philopatric offspring using the same method used to remove relatedness completely. This approach will effectively reduce relatedness structure by half and overcome the concerns with our decision to model asexual reproduction.

Briefly, we will elaborate on the concept of division of labor and the tasks that cooperative breeders perform. In nature, multiple tasks are often necessary to successfully rear offspring. For example, in many cooperatively breeding birds, the primary reasons that individuals fail to produce offspring are (1) starvation, which is mitigated by the feeding of offspring, and (2) nest depredation, which is countered by defensive behavior. Consequently, both types of tasks are necessary to successfully produce offspring, and focusing solely on one while neglecting the other is likely to result in lower reproductive success than if both tasks are performed by individuals within the group. We simplify this principle in the model by maximizing reproductive output when both tasks are carried out to a similar extent, allowing for some flexibility from the mean. In response to the reviewer suggestion about making fecundity a function of work tasks and offspring survival as a function of defensive tasks, these are actually equivalent in model terms, as it’s the same whether breeders produce three offspring and two die, or if they only produce one. This represents, of course, a simplification of the natural context, where breeding unsuccessfully is more costly (in terms of time and energy investment) than not breeding at all, but this is approach is typically used in models of this sort.

The scope of this paper was to study division of labor in cooperatively breeding species with fertile workers, in which help is exclusively directed towards breeders to enhance offspring production (i.e., alloparental care). Our focus is in line with previous work in most other social animals, including eusocial insects and humans, which emphasizes how division of labor maximizes group productivity. Other forms of “general” help are not considered in the paper, and such forms of help are rarely considered in cooperatively breeding vertebrates or in the division of labor literature, as they do not result in task partitioning to enhance productivity.

How do we model help? Help provided is an interaction between H (total effort) and T (proportion of total effort invested in each type of task). We will make this definition clearer in the revised manuscript. Thank you for pointing out an error in Eq. 1. This inequality was indeed written incorrectly in the paper (but is correct in the model code); it is dominance rank instead of age (see code in Individual.cpp lines 99-119). We will correct this mistake in the revision.

There was also a question about bounded and unbounded helping costs. The difference in costs is inherent to the nature of the different task (work or defense): while survival is naturally bounded, with death as the lower bound, dominance costs are potentially unbounded, as they are influenced by dynamic social contexts and potential competitors. Therefore, we believe that the model’s cost structure is not too different to that in nature.

Thank you for your comments about the parameter landscape. It is important to point out that variations in the mutation rate do not qualitatively affect our results, as this is something we explored in previous versions of the model (not shown). Briefly, we find that variations in the mutation rates only alter the time required to reach equilibrium. Increasing the step size of mutation diminishes the strength of selection by adding stochasticity and reducing the genetic correlation between offspring and their parents. Population size could, in theory, affect our results, as small populations are more prone to extinction. Since this was not something we planned to explore in the paper directly, we specifically chose a large population size, or better said, a large number of territories (i.e. 5000) that can potentially host a large population.

During the exploratory phase of the model development, various parameters and values were also assessed. However, the manuscript only details the ranges of values and parameters where changes in the behaviors of interest were observed, enhancing clarity and conciseness. For instance, variation in y_h (the cost of help on dominance when performing “work tasks”) led to behavioral changes similar to those caused by changes in x_h (the cost of help in survival when performing “defensive tasks”), as both are proportional to each other. Specifically, since an increase in defense costs raises the proportion of work relative to defense tasks, while an increase in the costs of work task has the opposite effect, only results for the variation of x_h were included in the manuscript to avoid redundancy. We will make this clearer in the revision.

Finally, following the advice from the reviewers, we will add the symbols of the variables to the figure axes, and clarify whether the values shown represent a genetic or phenotypic trait. In Figure 2, the x-axis is H and the y-axis is T. In Figure 3A, the subindex t in x-axis is incorrect; it should be subindex R (reaction norm to dominance rank instead of age), the y-axis is T. In Figure 3B, the x-axis is R, and the y-axis is T. All values of T, H and R are phenotypic expressed values (see Table 1). For instance, T values are the phenotypic expressed values from the individuals in the population according to their genetic gamma values and their current dominance rank at a given time point.

References

Cote, J., Dahirel, M., Schtickzelle, N., Altermatt, F., Ansart, A., Blanchet, S., Chaine, A. S., De Laender, F., De Raedt, J., & Haegeman, B. (2022). Dispersal syndromes in challenging environments: A cross‐species experiment. Ecology Letters, 25(12), 2675–2687.

In this passage, the author shares the challenges of and consequences of youth who do not conform to gender norms, specifically gender nonconforming or transgender youth. Gender play can extend the possibilities of self-expression, but it often triggers adult worries and institutional bias. The text reflects not only ignorance but also an attempt to contain youth identities. The schools expel the 14-year-old who painted her face and wore makeup, and there was no dress code. In this scenario, the school systems, which depend heavily on rigid gender norms, behave unjustifiably. Schools pay greater reaction to perceived threats to gender roles than to the rules that are actually being broken.

This passage refers to how school dress codes are enforced unfairly to reinforce traditional gender expectations even though the written policies themselves might not necessarily ban expressions such as the use of cosmetics or gender-nonconformist clothing. The examples show that students, both LGBTQ+ and non-LGBTQ+, will be disciplined for simply appearing in a way that subverts stereotypical masculine and feminine expectations. It represents a more fundamental problem in which student individuality is policed on the guise of "dress code infractions" in a strict enforcement of gender roles and hostility to student diversity of identity.

Implement active learning

Note de Synthèse : Analyse du Rapport sur Parcoursup et Mon Master (Extrait)

Date : 2025

Objet : Examen des plateformes d'accès à l'enseignement supérieur (Parcoursup et Mon Master), focus sur les algorithmes, les bacheliers STMG et la région Nouvelle-Aquitaine.

Source : Extraits du rapport "rapport parcoursup 2025-297809.pdf" du Comité éthique et scientifique de Parcoursup et Mon Master (CESPM).

Introduction :

Ce rapport, le 7ème du CESPM, offre un éclairage approfondi sur les mécanismes et les enjeux des plateformes d'accès à l'enseignement supérieur Parcoursup et Mon Master.

Il s'appuie sur des analyses générales, des entretiens avec les acteurs de terrain et une étude de cas spécifique portant sur les bacheliers de la filière Sciences et technologies du management et de la gestion (STMG) et la région Nouvelle-Aquitaine.

L'objectif est de garantir la transparence, l'équité et l'efficacité de ces processus d'admission.

Thèmes Principaux et Idées Clés :

Rôle et Fonctionnement des Algorithmes dans Parcoursup et Mon Master (Section 1.1, 1.2, 1.4):

Clarification fondamentale : Le rapport insiste sur le fait que ce ne sont pas les plateformes ou leurs algorithmes qui prennent les décisions d'admission, mais bien les responsables et enseignants des formations réunis en commissions d'examen.

Algorithme d'Appariement : L'algorithme gère la mise en relation entre les vœux des candidats et les classements des formations. Il ne classe pas les candidats lui-même mais utilise les classements fournis par les formations. Son code est publié pour assurer la transparence.

Différences entre Parcoursup et Mon Master : Parcoursup applique des quotas (boursiers, géographiques pour les licences) qui peuvent modifier les classements initiaux des formations, dans un souci de réduction des inégalités sociales. Mon Master n'applique aucun quota. "Algorithmes Locaux" (Classement par les Formations) :

Le rapport dénonce l'appellation impropre "algorithmes locaux". Les formations utilisent des outils (souvent des tableurs) basés sur des critères définis par les équipes pédagogiques pour pré-classer les candidatures, facilitant le travail de délibération des commissions. Transparence des Critères de Classement : Le Comité recommande vivement la publication précise et quantifiable des critères de classement utilisés par les formations. Cette transparence est jugée essentielle pour l'équité.

Inégalités d'Accès : Le rapport affirme que les algorithmes d'appariement n'amplifient pas les inégalités sociales ou géographiques.

Au contraire, les quotas dans Parcoursup visent à les réduire.

Les inégalités d'accès existent mais sont liées à d'autres facteurs.

Sélection à l'Entrée de l'Enseignement Supérieur (Section 1.3, 1.6):

Formations Sélectives : Ces formations ne classent pas toujours tous les candidats, refusant certains d'emblée selon leurs critères.

Le rapport critique le "malthusianisme" de certaines formations attractives qui ne classent pas suffisamment de candidats pour remplir leurs capacités d'accueil, entraînant une perte de places.

Recommandation : Pour lutter contre cette pratique, le rapport suggère d'exiger une publication très précise des critères de refus ou d'obliger les formations à classer tous les candidats. Une autre idée serait de réduire la capacité d'accueil des formations qui ne remplissent pas sur plusieurs années.

Accompagnement des Étudiants : La loi ORE a prévu des dispositifs "oui si" pour les licences non sélectives, mais rien n'est prévu pour les formations sélectives, même si certaines d'entre elles mettent en place un accompagnement.

Utilisation des Données Publiques (Section 1.5): Richesse des Données : Les données publiques issues des plateformes sont une ressource précieuse pour analyser la réalité de l'accès à l'enseignement supérieur.

Manque de Documentation : Le rapport souligne un manque de documentation précise pour de nombreux indicateurs (comme le "taux de poursuite"), rendant difficile l'interprétation et l'utilisation de ces données pour le pilotage.

Recommandation : Améliorer la documentation des données publiques pour permettre des analyses robustes et éclairer les politiques publiques. Focus sur les Bacheliers STMG (Chapitre 2): Filière Hétérogène et Parfois Subie : La filière STMG accueille des élèves d'origines sociales plus défavorisées que les autres filières technologiques et générales. L'orientation en STMG est souvent plus importante que les demandes des familles et peut servir de "voie de délestage".

Méconnaissance de la Filière : Le rapport pointe une méconnaissance des enseignements et des débouchés de la filière STMG par les professeurs et les parents, ce qui peut impacter négativement l'orientation.

Difficultés d'Accès à l'Enseignement Supérieur : Les bacheliers STMG rencontrent des difficultés pour entrer dans l'enseignement supérieur, caractérisées par une "volatilité" importante, un sur cinq quittant Parcoursup après avoir reçu une proposition.

Réussite en Études Supérieures : La réussite des bacheliers STMG en licence est faible. Elle est meilleure en formations courtes professionnalisées (BTS, BUT), mais reste inférieure à celle des autres bacheliers technologiques et généraux.

Recommandations :Créer des parcours de licence adaptés aux bacheliers technologiques (notamment STMG). Mettre en place ou développer des parcours de consolidation et des dispositifs d'accompagnement en BUT et L1 pour favoriser la "persévérance" et éviter les décrochages précoces. Accès à l'Enseignement Supérieur en Nouvelle-Aquitaine (Chapitre 3):

Impact de l'Éloignement Géographique : L'étude de la Nouvelle-Aquitaine, région étendue et rurale, montre l'impact significatif de l'éloignement des pôles d'enseignement supérieur sur les vœux et les admissions des candidats. Les candidats éloignés sont moins souvent admis dans les formations sélectives des grands pôles et plus souvent dans des formations courtes professionnalisantes plus proches.

Contraintes de Transport et de Logement : Les contraintes financières liées au transport et au logement sont identifiées comme des facteurs majeurs d'inégalité. Le logement est particulièrement problématique dans les zones tendues de la côte atlantique.

Critères d'Attribution des Logements Étudiants : Les critères actuels d'attribution des logements CROUS, trop axés sur les revenus, sont jugés inadaptés pour prendre correctement en compte la distance.

Recommandations :Définir des critères spécifiques pour l'attribution des logements étudiants qui prennent mieux en compte les distances.

Expérimenter l'attribution des logements étudiants par la procédure Parcoursup pour certains types de formations dans les régions rurales, à l'instar des internats de CPGE. Partager les internats dans les lycées qui offrent CPGE et BTS, et intégrer les demandes dans Parcoursup pour les BTS.

Mon Master (Chapitre 4): * Plateforme Utile et Bien Acceptée : Mon Master est généralement bien perçue par les formations, facilitant le travail de classement des candidatures. Elle sert également d'observatoire pour l'adaptation de l'offre de formation. * Introduction de la Phase Complémentaire (PC) : L'ajout de la PC en 2024 est unanimement salué, permettant de mieux gérer les places vacantes et d'offrir de nouvelles opportunités aux candidats. * Sélection et Taux de Remplissage : L'entrée en master reste sélective. Des places vacantes persistent, avec des disparités selon les territoires et les mentions. Les candidats issus de BUT ou de licences professionnelles ont un taux d'admission plus faible que les titulaires de licence générale. * Saisine du Recteur : Le dispositif de saisine pour les titulaires d'une licence générale n'ayant reçu aucune proposition est détaillé. Le rapport recommande d'informer plus clairement les étudiants sur les restrictions de conditions pour cette saisine. * Périmètre de la Plateforme : Le rapport recommande de ne pas étendre la plateforme Mon Master aux formations ne conduisant pas à un Diplôme National de Master (DNM), mais d'y ajouter à titre informatif les masters qui ne recrutent qu'en formation continue. * Transparence et Équité : Le rapport réitère la nécessité de transparence sur les critères de sélection et la publication de rapports de jury, comme pour Parcoursup. * Alternance : Le recrutement en alternance via Mon Master présente des spécificités (calendrier, absence de classement des candidats). Le rapport suggère de permettre aux établissements de gérer la fongibilité des capacités d'accueil entre statut étudiant et apprentissage. * Nombre de Vœux : Le nombre élevé de vœux possibles sur Mon Master (15 par type de formation) alourdit le travail des commissions et peut inciter à des candidatures non mûries. * Sécurité et Protection des Données : Le code de l'algorithme de Mon Master est publié, ce qui est une avancée. Le rapport suggère de renforcer la sécurité des accès privilégiés par une authentification à double facteur et d'améliorer la remontée sécurisée des notes des candidats étudiant en France. * Partage d'Expérience entre Parcoursup et Mon Master : Le Comité recommande d'amplifier le partage d'expérience et de perspectives entre les deux plateformes et d'unifier la présentation de leurs algorithmes.

Recommandations Clés du Rapport :

Le rapport émet plusieurs recommandations concrètes pour améliorer les processus d'admission et l'accès à l'enseignement supérieur, notamment :

• Améliorer la transparence des critères de classement et, pour les formations sélectives, les critères de refus (Recommandation 1).
• Mieux documenter les données publiques pour permettre des analyses fines et éclairer les politiques publiques (Recommandation 2).
• Créer des parcours de licence adaptés aux bacheliers technologiques (notamment STMG) et développer des dispositifs d'accompagnement en L1 et BUT pour favoriser la persévérance des STMG (Recommandations 4 et 5).
• Définir des critères spécifiques pour l'attribution des logements étudiants prenant mieux en compte les distances et expérimenter l'attribution via Parcoursup (Recommandation 7).
• Partager les internats dans les lycées offrant CPGE et BTS et intégrer les demandes dans Parcoursup pour les BTS (Recommandation 8).
• Mieux informer les parents et les élèves sur Parcoursup, les filières d'études, les aides sociales et au logement (Recommandation 9).
• Doter les établissements d'outils statistiques robustes et partagés pour suivre les parcours des jeunes (Recommandation 10).
• Avertir clairement les étudiants des restrictions concernant la saisine du recteur sur Mon Master (Recommandation 14).
• Ne pas ouvrir Mon Master aux formations ne conduisant pas à un DNM, mais ajouter les masters qui ne recrutent qu'en formation continue (Recommandation 15).
• Permettre aux établissements de gérer la fongibilité entre les capacités d'accueil des formations en statut étudiant et en apprentissage sur Mon Master (Recommandation 20).
• Amplifier le partage d'expérience et de perspectives entre Mon Master et Parcoursup et unifier la présentation des algorithmes (Recommandation 23).

Conclusion du Comité :

Le CESPM estime que ses travaux ont contribué à éclairer la décision publique pour l'amélioration de Parcoursup et espère faire de même pour Mon Master.

Le rapport met en lumière le renoncement de nombreux lycéens, notamment STMG, à leurs aspirations en raison de l'éloignement géographique et d'une dévalorisation perçue de leur filière.

L'amélioration de l'accès au logement étudiant, une meilleure information sur l'orientation et un suivi accru de la réussite des bacheliers STMG sont des pistes essentielles pour l'avenir.

Le Comité prévoit de poursuivre son analyse de Mon Master l'année prochaine, avec un focus approfondi sur des disciplines spécifiques et la question de la saisine du recteur.

We're at the point in humanity's development of computing infrastructure where the source code for program texts (e.g. a module definition) should be rich text and not just ASCII/UTF-8.

Forget that I said "rich text" for a moment and pretend that I was just narrowly talking about the inclusion of, say, graphical diagrams in source code comments.

Could we do this today? Answer: yes.

"Sure, you could define a format, but what should it look like? You're going to have to deal with lots of competing proposals for how to actually encode those documents, right?" Answer: no, not really. We have a ubiquitous, widely supported format that is capable of encoding this and more: HTML.

Now consider what else we could do with that power. Consider a TypeScript alternative that works not by inserting inline type annotations into the program text, but instead by encoding the type of a given identifier via the HTML class attribute.

Now consider program parametrization where a module includes multiple options for the way that you use it, and you configure it as the programmer by opening up the module definition in your program editor, gesturing at the thing it is that you want to concretely specify, selecting one of those options, and have the program text for the module react accordingly—without erasing or severing the mechanism for configuration, so if another programmer wants to change the module parameters to satisfy some future need—or lift that module from your source tree and use it in another one for a completely different program—then they can reconfigure it with the same mechanism that you used.

code formatting (minor_

I was expecting a github repository with code, but sadly that wasn't the case.

Author response:

The following is the authors’ response to the original reviews

Response to the public reviews:

We are very pleased to see these positive reviews of our preprint.

Reviewers 1 and 3 raise issues around PIP-PP1 interactions.

(1) Role of the “RVxF-ΦΦ-R-W string”

Most PIPs interact with the globular PP1 catalytic core through short linear interaction motifs (SLiMs) and Choy et al (PNAS 2014) previously showed that many PIPs interact with PP1 through conserved trio of SLiMs, RVxF-ΦΦ-R, which is also present in the Phactrs.

Previous structural analysis showed the trajectory of the PPP1R15A/B, Neurabin/Spinphilin (PPP1R9A/B), and PNUTS (PPP1R10) PIPs across the PP1 surface encompasses not only the RVxF-ΦΦ-R trio, but also additional sequences C-terminal to it (Chen et al, eLife, 2015). This extended trajectory is maintained in the Phactr1-PP1 complex (Fedoryshchak et al, eLife (2020). Based on structural alignment we proposed the existence of an additional hydrophobic “W” SLiM that interacts with the PP1 residues I133 and Y134.

The extended “RVxF-ΦΦ-R-W” interaction brings sequences C-terminal to the “W” SLiM into the vicinity of the hydrophobic groove that adjoins the PP1 catalytic centre. In the Phactr1/PP1 complex, these sequences remodel the groove, generating a novel pocket that facilitates sequence-specific substrate recognition.

This raises the possibility that sequences C-terminal to the extended “RVxF-ΦΦ-R-W string” in the other complexes also confer sequence-specific substrate recognition, and our study aims to test this hypothesis. Indeed, the hydrophobic groove structures of the Neurabin/Spinophilin/PP1 and Phactr1/PP1 complexes differ significantly (Ragusa et al, 2010; see Fedoryshchak et al 2020, Fig2 FigSupp1).

(2) Orientation of the W side chain

Reviewer 1 points out that in the substrate-bound PP1/PPP1R15A/Actin/eIF2 pre-dephosphorylation complex the W sidechain is inverted with respect to its orientation in  PP1-PPP1R15B complex (Yan et al, NSMB 2021). The authors proposed that this may reflect the role of actin in assembly of the quaternary complex. This does not necessarily invalidate the notion that sequences C-terminal to the “W” motif might play a role in actin-independent substrate recognition, and we therefore consider our inclusion of the R15A/B fusions in our analysis to be reasonable.

(3) Conservation of W

The motif ‘W’ does not mandate tryptophan - Phactrs and PPP1R15A/B indeed have W at this position but Neurabin/spinophilin contain VDP, which makes similar interactions. Similarly the “RVxF” motifs in Phactr1, Neurabin/Spinophilin, PPP1R15A/B and PNUTS are LIRF, KIKF, KV(R/T)F and TVTW respectively.

In our revision, we will present comparisons of the differentially remodelled/modified PP1 hydrophobic groove in the various complexes, discuss the different orientations of the tryptophan in the previously published PPP1R15A/PP1 and PPP1R15B/PP1 structures. We will also address the other issues raised by the referees.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Comments and suggestions for revisions

(1) The authors do not provide strong evidence that the interactions of the 'W' of the RVxF- øø -R-W string with the hydrophobic groove of PP1 is conserved in PIPs. Whereas the RVxF motif is well conserved and validated since its discovery in 1997, as are the øø - (an extension of the RVxF motif), and the 'R', the conservation of the Trp residue in the RVxF-øø-R-W string is not conserved.

We did not mean to imply that the W motif is conserved amongst all PIPs.

Most PIPs interact with the globular PP1 catalytic core through short linear interaction motifs (SLiMs). Choy et al (PNAS 2014) previously showed that many PIPs interact with PP1 through a conserved trio of SLiMs, RVxF-ΦΦ-R, which is also present in the Phactrs.

Previous structural analysis showed that the PPP1R15A/B, Neurabin/Spinophilin (PPP1R9A/B), and PNUTS (PPP1R10) PIPs share a trajectory across the PP1 surface that encompasses not only the RVxF-ΦΦ-R SLIMs, but also additional sequences C-terminal to the R SLIM (Chen et al, eLife, 2015). This trajectory is also shared by the Phactr1-PP1 complex (Fedoryshchak et al, eLife, 2020). Based on this structural alignment we proposed the existence of an additional hydrophobic “W” SLiM that interacts with the PP1 residues I133 and Y134 (See Fedoryshchak et al, 2020, Figure 1 figure supplement 2).

Introduction, paragraph 2 is rewritten to make this clearer.

The sequence and positions of W differ in amino acid type and position relative to the RVxF-øø-R string.

The motif ‘W’ does not mandate tryptophan, it is our name for a common structurally aligned motif: although the Phactrs and PPP1R15A/B indeed have W at this position, Neurabin and spinophilin contain VDP, which nevertheless makes similar interactions. Similarly the _“_RVxF” motifs in Phactr1, Neurabin/Spinophilin, PPP1R15A/B and PNUTS are LIRF, KIKF, KV(R/T)F and TVTW respectively.

In the Discussion the authors state that the hydrophobic groove of PP1 is remodelled by Neurabin. However, details of this are not described or shown in the manuscript.

The shared trajectory determined by the RVxF-øø-R-W string brings the sequences C-terminal to the W SLIM into the vicinity of the PP1 hydrophobic groove. In the Phactr1/PP1 holoenzyme this generates a novel pocket required for substrate recognition (Fedoryshchak et al, 2020). These observations raised the possibility that sequences C-terminal to the “W” motif in the other RVxF-øø-R-W PIPs also play a role in substrate recognition.

Introduction paragraph 3 now cites a new Figure 1-S2, which shows how the hydrophobic groove is remodelled in the various different PIP/PP1 complexes. A revised Figure 1A now indicates the hydrophobic residues defining the hydrophobic groove by grey shading.

(2) To add to the confidence of the structure, the authors should include a 2Fo-Fc simulated annealing omit map, perhaps showing the R and W interactions of the RVxF-øø-R-W string.

This is now included as new Figure 6 Figure supplement 1. Note that in Neurabin, the W motif is VDP, where the valine and proline sidechains interact similarly to the tryptophan (see also new Figure 1-S2G,H).

We also add a new supplementary Figure 6-S1 comparing our PBM-liganded Neurabin PDZ domain with the previously published unliganded structure (Ragusa et al 2010).

(3) Page 16. The authors state that spinophilin remodels the PP1 hydrophobic groove differently from Phactrs. Arguably spinophilin does not remodel the PP1 hydrophobic groove at all. There are no contacts between spinophilin and the PP1 hydrophobic groove in the spinophilin-PP1 structure, correlating with the absence of 'W" in the RVxF-øø-R-W string in spinophilin.

The VDP sequence corresponding to the W motif in spinophilin and neurabin makes analogous contacts to those made by the W in Phactr1 (see Fedoryshchak et al 2020).

Remodelling is meant in the sense of altering the structure of the major groove by bringing new sequences into its vicinity rather than necessarily directly interacting with it. The spinophilin/PP1 and Phactr/PP1 hydrophobic grooves are compared in new Figure 1-S2 (see also Fedoryshchak et al 2020, Figure 2 figure supplement 1)

(4) Page 8. For the cell-based/proteomics-dephosphorylation assay in Figure 2, it isn't clear why there were no dephosphorylation sites detected for the PPP1R15A/B-PP1 fusion (except PPP6R1 S531 for PPP1R15B). One might have expected a correlation with PP1 alone. Does this imply that PPP1R15A/B are inhibiting PP1 catalytic activity? Was the activity tested in vitro?

The R15A/B data are compared to average abundance of all the phosphosites in the dataset, including those of PP1.

We have not tested for a general inhibitory effect of R15A/B on PP1 activity. Many PIPs including R15A/B do occlude one or more of the PP1 substrate groove and therefore generally act as inhibitors of PP1 activity against some potential substrates, while enhancing activities against others.

Other points 

(4) Figure S1: Colour sequence similarities/identities.

Done

(6) Figures: Structure figures lacked labels:

Figure 1A, label PP1, Phactrs etc.

Done

Figure 6, label PP1, Neurabin, previous Neurabin structure (Fig. 6C), hydrophobic groove, PDZ domain, etc.

Done

(7) Statistical analysis. p values should be shown for data in:

Figure 5.

To avoid cluttering the Figure, a new sheet, “statistical significance” has been added to Supplementary Table 3, summarizing the analysis.

Figure 1.

Figure amended (now figure 1-S1).

(8) Some inconsistency with labels, eg '34-WT' used in Fig. 5C, whereas '34A-WT' (better) in Methods.

Now changed to 34A etc where used.

(9) Page 6. PPP1R9A/B is not shown in Figure 1A and Figure S1A.

PPP1R9A/B are Neurabin and spinophilin - now clarified in Introduction paragraph 2, Results paragraph 1, Discussion paragraph 1.

(10) Page 7: lines 4, 'site' not 'side'.

Done

(11) Page 9: DTL and CAMSAP3 were found to be dephosphorylated in the PP1-Neurabin/spinophilin screen. Are these PDZ-binding proteins?

Neither DTL nor CAMSAP3 contain C-terminal hydrophobic residues characteristic of classical PBMs. Sentence added in Discussion, paragraph 5

(12) Page 12 and Figure 5 and S5: The synthetic p4E-BP1 and IRSp53WT peptides with PBM should be given more specific names to indicate the presence of the PBM.

We have renamed 4E-BP1^WT and IRSp53^WT to 4E-BP1^PBM and  IRSp53^PBM respectively, emphasising the inclusion of the wildtype or mutated PBM from 4E-BP1 on these peptides.

Text, Figure 5, and Figure S5 all revised accordingly.

(13) Give PDB code for spinophilin-PP1 complex coordinates shown in Figure 6C.

PDB codes for the various PIP/PP1 complexes now given in new Figure 1-S2 and revised Figure 6C.

Reviewer #2 (Recommendations for the authors):

The work undertaken by the authors is extensive and robust, however, I believe that some improvement in the writing and some detailed explanation of certain results sections would help with the presentation of the work and clarity for the readers.

(1) The introduction should contain more information about the interaction between PP1 and Neurabin, given that this is the focus of the paper. This would give the reader the necessary background required to follow the paper.

Introduction paragraph 2 revised to describe the different SLIMs in more detail. New Figure 1-S2 shows detail of the different remodelled hydrophobic grooves in the various PIP/PP1 complexes.

(2) More information on PP1-IRSp53L460A has to be added before discussing results in S1B.

Sentence explaining that IRSp53 L460 docks with the remodelled PP1 hydrophobic groove in the Phactr1/PP1 holoenzyme added in Results paragraph 2.

(3) Page 6: "as expected, the +5 residue L460A mutation, which impairs dephosphorylation by the intact Phactr1/PP1 holoenzyme, impaired sensitivity to all the fusions, indicating that they recognise phosphorylated IRSp53 in a similar way (Figure S1B)". Statistics between IRSp53 and IRSp53L460A across PP1-PIPs need to be conducted before concluding the above. From the graph and the images, the impairment to dephosphorylation is not convincing.

For each of the four PP1-Phactr fusions, the IRSp53 L460A peptide shows significantly less reactivity than the IRSp53WT peptide (p<0.05 for each fusion).

Since the proteomics studes in Figure 2 show that the substrate specificity of the four PP1-Phactr1 fusions is virtually identical, we combined the data for the four different fusions. The IRSp53 L460A peptide shows significantly less reactivity than the IRSp53WT peptide in this analysis (p< 0.0001). This result shown in revised Figure S1B and legend.

(4) mCherry-4E-BP1(118+A), in which an additional C-terminal alanine should still allow TOSmediated phosphorylation, but prevent PDZ interaction. Does 4EBP1 (118+A) actually prevent interaction between PP1-Neurabin? This interaction needs to be validated, especially since spinophilin was shown to bind to multiple regions of PP1.

It is not clear what the referee is asking for here. The biochemical analysis in Figure 4C shows that the C-terminus of 4E-BP1 constitutes a classical PBM. The X-ray crystallography in Figure 6 confirms this, demonstrating H-bond interactions between the 4E-BP1 C-terminal carboxylate and main chain amides of L514, G515 and I516.

We consider the possibility that the 4E-BP1(118+A) mutant inhibits the activity of PP1-neurabin via a mechanism other than direct blocking 4E-BP1 / PDZ interaction to be unlikely for the following reasons:

(1) Addition of a C-terminal alanine will disrupt the PBM interaction because the extra residue sterically blocks access to the PBM-binding groove. This is the most parsimonious explanation, and is based on our solid structural and biochemical evidence that the 4E-BP1 C-terminus is a classical PBM.

(2) Alphafold3 modelling predicts Neurabin PDZ / 4E-BP1 PBM interaction with high confidence (shown in Figure 6-S2E), but it does not predict any PDZ interaction with 4E-BP1(118+A). Note added in Figure 6-S2 legend.

(3) Recognition of the 4E-BP1(118+A) mutation without loss of binding affinity would require that the mutant becapable of binding formally equivalent to recognition of an “internal” PDZ-binding peptide. Recognition of such “internal peptides” is dependent on their adopting a specifically constrained conformation, which typically requires reorganisation of the PDZ carboxylate-binding GLGF loop. Such “internal site” recognition typically involves more than one residue C-terminal to the conventional PDZ “0” position (see Penkert et al NSMB 2004, doi:10.1038/nsmb839; Gee et al JBC 1998, DOI: 10.1074/jbc.273.34.21980; Hillier et al 1999, Science PMID: 10221915).

(5) It is nice to see that the various PP1-Phactr fusions have around 60% substrate overlap between them. Would it be possible to compare these results with previously published mass spec data of Phactr1XXX from the group? There is mention of some substrates being picked up, but a comparison much like in Figure 2E would be more informative about the extent to which the described method captures relevant information.

This is difficult to do directly as the PP1-Phactr fusion data are from human cells while that in Fedoryshchak et al 2020 is from mouse.

However, manual curation shows that of the 28 top hits seen in our previous analysis of Phactr1XXX in NIH3T3 cells, 18 were also detectable in the HEK293 system; of these, 13 were also detected as as PP1-Phactr fusion hits. Data summarised in new Figure 2-S1C. Text amended in Results, “Proteomic analysis...”, paragraph 2.

(6) Figure 3D Why are the levels of pT70, pT37/46 and total protein in vector controls much lower as compared to 0nM Tet in PP1-Neurabin conditions? It is also weird that given total protein is so low, why are the pS65/101 levels high compared to the rest?

We think it likely these phenomena reflect a low level expression of PP1-Neurabin expression in uninduced cells. Now noted in Figure 3D legend, basal PP1-Neurabin expression shown in new Figure 3-S1C. This alters the relative levels of the different species detected by the total 4E-BP1 antibody in favour of the faster migrating forms, which are less phosphorylated than the slower ones, and the total amount increases about 2-fold (Figure 3D, compare 0nM Tet lanes).

The altered p65/101-pT70 ratio is also likely to reflect the leaky PP1-Neurabin expression, since the relative intensities of the various phosphorylated species are dependent on both the relative rates of phosphorylation and dephosphorylation. Expression of a phosphatase would therefore be expected to differentially affect the phosphorlyation levels of different sites according to their reactivity.

(7) Figure 3E: Does inhibiting mTORC further reduce translation when PP1-Neurabin is expressed? If this is the case, this might suggest that they might not necessarily be mTORC inhibitors?

We have not done this experiment. Since Rapamycin cannot be guaranteed to completely block 4E-BP1 phosphorylation, and PP1-Neurabin cannot be guaranteed to completely dephosphorylate 4E-BP1, any further reduction upon their combination would be hard to interpret.

(8) Substrate interactions with the remodelled PP1 hydrophobic groove do not affect PP1-Neurabin specificity. Is there evidence that PP1-Neurabin remodels the hydrophobic groove? Is it not possible that Neurabin does not remodel the PP1 groove to begin with and hence there is no effect observed with the various mutants? If this is not the case, it should be explained in a bit more detail.

Comparison of the Neurabin/PP1 and Phactr1/PP1 structures shows that the hydrophobic groove is remodelled differently in the two complexes. Now shown in new Figure 1-S2B,C,G.

(9) Figure 5B has a lot of interesting information, which I believe has not been discussed at all in the results section.

To help interpretation of the enzymology in Figure 5 we have renamed 4E-BP1WT and IRSp53WT to 4E-BP1PBM and IRSp53PBM respectively, emphasising the inclusion of the wildtype or mutated PBM from 4E-BP1 on these peptides. Text in Results, “PDZ domain interaction…”, paragraph 1, and Figures 5 and S5 revised accordingly.

Why does the 4E-BP1Mut affect catalytic efficiency of PP1 alone when compared with WT, while no difference is observed with IRSp53WT and mutant?

We do not understand the basis for the differential reactivity of 4E-BP1PBM and 4E-BP1MUT with PP1 alone; we suspect that it reflects the hydrophobicity change resulting from the MDI -> SGS substitution. However this is unlikely to be biologically significant as PP1 is sequestered in PIP-PP1 complexes.

Importantly, the two PP1 fusion proteins behave consistently in this assay – the presence of the intact PBM increases reactivity with PP1-Neurabin, but has no effect on dephosphorylation by PP1-Phactr1.

Why does PP1 alone not have a difference between IRSp53WT and mutant, while PP1-Neurabin does have a difference?

This is due to the presence of the PBM in IRSp53WT (now renamed IRSp53PBM), which affects increases affinity for PP1 Neurabin, but not PP1 alone. Likewise, PP1-Phactr1, which does not possess a PDZ domain, is also unaffected by the integrity of the PBM.

(7) “Strikingly, alanine substitutions at +1 and +2 in 4E-BP1WT increased catalytic efficiency by both fusions, perhaps reflecting changes at the catalytic site itself (Figure 5E, Figure S5E)”. This could be expanded upon, because this suggests a mechanism that makes the substrate refractory to PDZ/hydrophobic groove remodelling?

We favour the idea that this reflects a requirement to balance dephosphorylation rates between the multiple 4E-BP1 phosphorylation sites, especially if multiple rounds of dephosphorylation occur for each PBM—PDZ interaction. Additional sentences added in Discussion paragraph 7.

(8) Typographical errors and minor comments:

a) PIPs can target PP1 to specific subcellular locations, and control substrate specificity through autonomous substrate-binding domains, occupation or extension of the substrate grooves, or modification of PP1 surface electrostatics.

b) Phosphophorylation side site abundances within triplicate samples from the same cell line were comparable between replicates (Figure 2B).

c) While the alanine substitutions had little effect, conversion of +4 to +6 to the IRSp534E-BP1 sequence LLD increased catalytic efficiency some 20-fold (Figure 5C, Figure S5C). 

d) Figure 3E labels are not clear. The graph can be widened to make the labels of the conditions clearer.

All corrected

Reviewer #3 (Recommendations for the authors):

This was a very well-written manuscript.

However, I was looking for a summary mechanistic figure or cartoon to help me navigate the results.

I noted a few typos in the text.

New summary Figure 5-S2 added, cited in results, and discussed in Discussion paragraph 6,7.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public Review):

Summary:

This article presents a meta-analysis that challenges established abundance-occupancy relationships (AORs) by utilizing the largest known bird observation database. The analysis yields contentious outcomes, raising the question of whether these findings could potentially refute AORs.

We thank the Reviewer for their positive comments.

Strengths:

The study employed an extensive aggregation of datasets to date to scrutinize the abundance-occupancy relationships (AORs).

We thank the Reviewer for their positive comments.

Weaknesses:

While the dataset employed in this research holds promise, a rigorous justification of the core assumptions underpinning the analytical framework is inadequate. The authors should thoroughly address the correlation between checklist data and global range data, ensuring that the foundational assumptions and potential confounding factors are explicitly examined and articulated within the study's context.

We thank the Reviewer for these comments. We agree that more justification and transparency is needed of the core assumptions that form the foundation of our methods. In our revised version, we have taken the following steps to achieve this:

- Altered the title to be more explicit about the core assumptions, which now reads: “Local-scale relative abundance is decoupled from global range size”

- We have added more details on why and how we treat global range size as a measure of ‘occupancy.’

- We have added a section that discusses the limitations of using eBird relative abundance

Reviewer #2 (Public Review):

Summary:

The goal is to ask if common species when studied across their range tend to have larger ranges in total. To do this the authors examined a very large citizen science database which gives estimates of numbers, and correlated that with the total range size, available from Birdlife. The average correlation is positive but close to zero, and the distribution around zero is also narrow, leading to the conclusion that, even if applicable in some cases, there is no evidence for consistent trends in one or other direction.

We thank the Reviewer for these comments.

Strengths:

The study raises a dormant question, with a large dataset.

We thank the Reviewer for these comments. We intended to take a longstanding question and attempt to apply novel datasets that were not available mere decades ago. While we do not imply that we have ‘solved’ the question, we hope this work highlights the potential for further interrogation using these large datasets.

Weaknesses:

This study combines information from across the whole world, with many different habitats, taxa, and observations, which surely leads to a quite heterogeneous collection.

We agree that there is a heterogeneous collection of data across many habitats, taxa, and observations. However, rather than as a weakness, we see this as a significant strength. Our work assumes we are averaging over this variability to assess for a large-scale pattern in the relationship - something that was potentially a limitation of previous work, as these large datasets were often focused on particular contexts (e.g., much work focused solely on the UK), which we believe could limit some of the generalizability of the previous work. However, the reviewer makes a fair point in regard to the heterogeneity of data collection. We have now added some text in the discussion which is explicit about this - see the new section named “Potential limitations of current work and future work –-although our findings challenge some long-held assumptions about the consistency of the abundance-occupancy relationship, our work only deals with interspecific AORs among birds, synthesizing observations of potentially heterogeneous locations, context and quality”.

First, scale. Many of the earlier analyses were within smaller areas, and for example, ranges are not obviously bounded by a physical barrier. I assume this study is only looking at breeding ranges; that should be stated, as 40% of all bird species migrate, and winter limitation of populations is important. Also are abundances only breeding abundances or are they measured through the year? Are alien distributions removed?

Second, consider various reasons why abundance and range size may be correlated (sometimes positively and sometimes negatively) at large scales. Combining studies across such a large diversity of ecological situations seems to create many possibilities to miss interesting patterns. For example:

(1) Islands are small and often show density release.

See comment below.

(2) North temperate regions have large ranges (Rapoport's rule) and higher population sizes than the tropics.

See comment below.

(3) Body size correlates with global range size (I am unsure if this has recently been tested but is present in older papers) and with density. For example, cosmopolitan species (barn owl, osprey, peregrine) are relatively large and relatively rare.

See comment below.

(4) In the consideration of alien species, it certainly looks to me as if the law is followed, with pigeon, starling, and sparrow both common and widely distributed. I guess one needs to make some sort of statement about anthropogenic influences, given the dramatic changes in both populations and environments over the past 50 years.

See comment below. We also added a sentence in the methods that highlighted we did not remove alien ranges and provided reasons why. Still, we do acknowledge the dramatic changes in populations and environments over the past 50 years (see the new section  “Potential limitations of current work and futur work”)

(5) Wing shape correlates with ecological niche and range size (e.g. White, American Naturalist). Aerial foraging species with pointed wings are likely to be easily detected, and several have large ranges reflecting dispersal (e.g. barn swallow).

We agree that all of the points above are interesting data explorations. As said above, our main purpose was to highlight the potential for further interrogation using these large datasets. However, we have added some additional text in the discussion that explicitly mentions/encourages these additional data explorations. We hope people will pick up on the potential for these data and explore them further.

Third, biases. I am not conversant with ebird methodology, but the number appearing on checklists seems a very poor estimate of local abundance. As noted in the paper, common species may be underestimated in their abundance. Flocking species must generate large numbers, skulking species few. The survey is often likely to be in areas favorable to some species and not others. The alternative approach in the paper comes from an earlier study, based on ebird but then creating densities within grids and surely comes with similar issues.

We agree that if we were interested in the absolute abundance of a given species, the local number on an eBird checklist would be a poor representation. However, our study aims not to estimate absolute abundance but to examine relative abundance among species on each checklist. By focusing on relative abundance, we leverage eBird data's strengths in detecting the presence and frequency of species across diverse locations and times, thereby capturing community composition trends that can provide meaningful insights despite individual checklist biases. This approach allows us to assess the comparative prominence of species in the community as reported by the observer, providing a consistent metric of relative abundance. Despite detectability biases, the structure of eBird checklists reflects the observer’s encounter rates with each species under similar conditions, offering a valuable snapshot of relative species composition across sites and times. The key to our assumption is that these biases discussed are not directional and, therefore, random throughout the sampling process, which would translate to no ‘real’ bias in our effect size of interest.

Range biases are also present. Notably, tropical mountain-occupying species have range sizes overestimated because holes in the range are not generally accounted for (Ocampo-Peñuela et al., Nature Communications). These species are often quite rare, too.

We thanks the reviewer for pointing to this issue and reference. We included a discussion on these biases in our limitations section and reference Ocampo-Peñuela et al. to emphasize the need for improved spatial resolution in range data for more accurate AOR assessments.”More precise range-size estimates would also improve the accuracy of AOR assessments, since species range data are often overestimated due to the failure to capture gaps in actual distributions ”

Fourth, random error. Random error in ebird assessments is likely to be large, with differences among observers, seasons, days, and weather (e.g. Callaghan et al. 2021, PNAS). Range sizes also come with many errors, which is why occupancy is usually seen as the more appropriate measure.

If we consider both range and abundance measurements to be subject to random error in any one species list, then the removal of all these errors will surely increase the correlation for that list (the covariance shouldn't change but the variances will decrease). I think (but am not sure) that this will affect the mean correlation because more of the positive correlations appear 'real' given the overall mean is positive. It will definitely affect the variance of the correlations; the low variance is one of the main points in the paper. A high variance would point to the operation of multiple mechanisms, some perhaps producing negative correlations (Blackburn et al. 2006).

We agree random errors can affect estimates, but as we wrote above, random errors, regardless of magnitudes, would not bias estimates. After accounting for sampling error (a part of random errors), little variance is left to be explained as we have shown in the MS. This suggests that many of the random errors were part of the sampling errors. And this is where meta-analysis really shines.

On P.80 it is stated: "Specifically, we can quantify how AOR will change in relation to increases in species richness and sampling duration, both of which are predicted to reduce the magnitude of AORs" I haven't checked the references that make this statement, but intuitively the opposite is expected? More species and longer durations should both increase the accuracy of the estimate, so removing them introduces more error? Perhaps dividing by an uncertain estimate introduces more error anyway. At any rate, the authors should explain the quoted statement in this paper.

It would be of considerable interest to look at the extreme negative and extreme positive correlations: do they make any biological sense?

Extremely high correlations would not make any biological sense if these observations were based on large sample sizes. However, as shown in Figure 2, all extreme correlations come from small sample sizes (i.e., low precision), as sampling theory expects (actually our Fig 2 a text-book example of the funnel shape). Therefore, we do not need to invoke any biological explanations here.

Discussion:

I can see how publication bias can affect meta-analyses (addressed in the Gaston et al. 2006 paper) but less easily see how confirmation bias can. It seems to me that some of the points made above must explain the difference between this study and Blackburn et al. 2006's strong result.

We agree. Now, we extended an explanation of why confirmation bias could result in positive AOR. Yet, we point out confirmation bias is a very common phenomena which we cite relevant citations in the original MS. The only way to avoid confirmation bias is to conduct a study blind but this is not often possible in ecological work.

“Meta-research on behavioural ecology identified 79 studies on nestmate recognition, 23 of which were conducted blind. Non-blind studies confirmed a hypothesis of no aggression towards nestmates nearly three times more often. It is possible that confirmation bias was at play in earlier AOR studies.”

Certainly, AOR really does seem to be present in at least some cases (e.g. British breeding birds) and a discussion of individual cases would be valuable. Previous studies have also noted that there are at least some negative and some non-significant associations, and understanding the underlying causes is of great interest (e.g. Kotiaho et al. Biology Letters).

We agree. And yes, we pointed out these in our introduction.

Reviewer #3 (Public Review):

Summary:

This paper claims to overturn the longstanding abundance occupancy relationship.

Strengths:

(1) The above would be important if true.

(2) The dataset is large.

We have clarified this point by changing the title to emphasize that we do not suggest overturning AORs entirely but instead provide a refined view of the relationship at a global scale. Our results suggest a weaker and more context-dependent AOR than previously documented. We hope our revised title and additional clarifications in the text convey our intent to contribute to a more nuanced understanding rather than a whole overturning of the AOR framework.

Weaknesses:

(1) The authors are not really measuring the abundance-occupancy relationship (AOR). They are measuring abundance-range size. The AOR typically measures patches in a metapopulation, i.e. at a local scale. Range size is not an interchangeable notion with local occupancy.

We have refined this in our revision to be more explicitly focused on global range size. However, we note that the classic paper by Bock and Richlefs (1983, Am Nat) also refers to global (species entire) range size in the context of the AOR. Importantly, Bock and Richlefs pointed out the importance of using species’ entire ranges; without such uses, there will be sampling artifacts creating positive AORs when using arbitrary geographical ranges, which were used in some studies of AORs. So we highlight that our work is well in line with the previous work, allowing us to question the longstanding macroecological work. One of the issues of AOR has been how to define occupancy and global range size, which provides a relatively ambiguous measure, which is why we used this measure.

(2) Ebird is a poor dataset for this. The sampling unit is non-standard. So abundance can at best be estimated by controlling for sampling effort. Comparisons across space are also likely to be highly heterogenous. They also threw out checklists in which abundances were too high to be estimated (reported as "X"). As evidence of the biases in using eBird for this pattern, the North American Breeding Bird Survey, a very similar taxonomic and geographic scope but with a consistent sampling protocol across space does show clear support for the AOR.

Yes, we agree the sampling unit is non-standard. However, this is a significant strength in that it samples across much heterogeneity (as discussed in response to Reviewer 2, above). We were interested in relative abundance and not direct absolute abundance per se, which is accurate, especially since we did control for sampling effort.

We appreciate the reviewer’s attention to our data selection criteria. We excluded checklists containing ‘X’ entries to minimize biases in our abundance estimates. The 'X' notation is often used for the most common species, reflecting the observer's identification of presence without specifying a count. This approach was chosen to avoid disproportionately inflating presence data for these abundant species, which could distort the relative abundance calculations in our analysis. By excluding such checklists, we aimed to retain consistency and ensure that local abundance estimates were representative across all species on each checklist. We have revised our manuscript to clarify this methodological choice and hope this explanation addresses the reviewer’s concern. We modified our text in the methods to make the entries ‘X’ clearer (see the Method section).

(3) In general, I wonder if a pattern demonstrated in thousands of data sets can be overturned by findings in one data set. It may be a big dataset but any biases in the dataset are repeated across all of those observations.

Overturning a major conclusion requires careful work. This paper did not rise to this level.

We appreciate the reviewer’s caution regarding broad conclusions based on a single dataset, even one as large as eBird. Our intention was not to definitively overturn the abundance-occupancy relationship (AOR) but to re-evaluate it with the most extensive and globally representative dataset currently available. We recognise that potential biases in citizen science data, such as observer variation, may influence our findings, and we have taken steps to address these in our methodology and limitations sections. We see this work as a contribution to an ongoing discourse, suggesting that AOR may be less universally consistent than previously believed, mainly when tested with large-scale citizen science data. We hope this study will encourage additional research that tests AORs using other expansive datasets and approaches, further refining our understanding of this classic macroecological relationship. However, we have left our broad message about instigating credible revolution and also re-examining ecological laws.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

(1) The investigation focuses solely on interspecific relationships among birds; thus, the extrapolation of these conclusions to broader ecological contexts requires further validation.

We have now added this point to our new section: “Although our findings challenge some long-held assumptions about the consistency of the abundance-occupancy relationship, our work only deals with interspecific AORs among birds, so we hope this work serves as a foundation for further investigations that utilize such comprehensive datasets.”

(2) The rationale for combining data from eBird - a platform predominantly representing individual observations from urban North America - with the more globally comprehensive BirdLife International database needs to be substantiated. The potential underrepresentation of global abundance in the eBird checklist data could introduce a sampling bias, undermining the foundational premises of AORs.

We agree with the limitation of ebird sampling coverage, but it should not bias our results. In statistical definitions, bias is directional, and if not directional, it will become statistical noise, making it difficult to detect the signal. In fact, our meta-analyses adjust what statisticians call sampling bias and it is the strength of meta-analysis.

(3) In the full mixed-effect model, checklist duration and sampling variance (inversely proportional to sample size N) are treated as fixed effects. However, these variables are likely to be negatively correlated, which could introduce multicollinearity, inflating standard errors and diminishing the statistical significance of other factors, such as the intercept. This calls into question the interpretation of insignificance in the results.

Multicollinearity is an issue with sample sizes. For example, with small datasets, correlations of 0.5 could be an issue, and such an issue would usually show up as a large SE. We do not have such an issue with ~ 17 million data points. Please refer to this paper.

Freckleton, Robert P. "Dealing with collinearity in behavioural and ecological data: model averaging and the problems of measurement error." Behavioral Ecology and Sociobiology 65 (2011): 91-101.

(4) The observed low heterogeneity may stem from discrepancies in sampling for abundance versus occupancy, compounded by uncertainties in reporting behavior.

If we assume everybody underreports common species or overreports rare species, this could happen. However, such an assumption is unlikely. If some people report accurately (but not others), we should see high heterogeneity, which we do not observe).  We have touched upon this point in our original MS.

(5) The contribution and implementation of phylogenetic comparative analysis remain ambiguous and were not sufficiently clarified within the study.

We need to add more explanation for the global abundance analysis

“To statistically test whether there was an effect of abundance and occupancy at the macro-scale, we used phylogenetic comparative analysis.  This analysis also addresses the issue of positive interspecific AORs potentially arising from not accounting for phylogenetic relatedness among species examined ”

(6) The use of large N checklists could skew the perceived rarity or commonality of species, potentially diminishing the positive correlation observed in AORs. A consistent observer effect could lead to a near-zero effect with high precision.

Regardless of the number of N species in checklists (seen in Fig 2), correlations are distributed around zero. This means there is nothing special about large N checklists. 

(7) The study should acknowledge and discuss any discrepancies or deviations from previous literature or expected outcomes.

We felt we had already done this as we discussed the previous meta-analysis and what we expected from this meta-analysis.  Nevertheless, we have added some relevant sentences in the new version of MS.

In addition to these major points, there are several minor concerns:

(1) Figure 2B lacks discussion, and the metric for the number of observations is not clarified. Furthermore, the labeling of the y-axis appears to be incorrect.

Thank you very much for pointing out this shortcoming. Now, the y-axis label has been fixed and we mention 2B in the main text.

(2) The study should provide a clear, mathematical expression of the multilevel random effect models for greater transparency.

Many thanks for this point, and now we have added relevant mathematical expressions in Table S6.

(3) On Line 260, the term "number of species" should be refined to "number of species in a checklist," ideally represented by a formula for precision.

This ambiguity has been mended as suggested.

Please provide the data and R code linked to the outputs.

The referee must have missed the link (https://github.com/itchyshin/AORs) in our original MS. In addition to our GitHub repository link, we now have added a link to our Zenodo repository (https://doi.org/10.5281/zenodo.14019900).

Reviewer #3 (Recommendations For The Authors):

The authors cite Rabinowitz's 7 forms of rarity paper as a suggestion that previous findings also break the AOR. In fact empirical studies of the 7 forms of rarity typically find that all three forms of rareness vs commonness are heavily correlated (e.g. Yu & Dobson 2000).

We thank the reviewer for drawing attention to Yu & Dobson (2000) and similar studies that find positive correlations among the axes of rarity. Ref 3 is correct in that Rabinowitz’s (1981) framework does not require that local abundance and geographic range size be uncorrelated for every species; instead, it highlights conceptual scenarios where a species may be common locally yet have a restricted distribution (or vice versa).

Empirical analyses such as Yu & Dobson (2000) show that, on average, these axes can be correlated, which may align with conventional AOR findings in some taxonomic groups. However, Rabinowitz’s key insight was that exceptions do occur, so these exceptions demonstrate that strong positive AORs may not be universally applicable. Our results do not claim that Rabinowitz’s framework “breaks” the AOR outright; instead, we use it to underscore that local abundance can, in principle, be “decoupled” from global occupancy.  Whether the correlation found by Yu & Dobson (2000) implies a positive AOR, requires a detailed simulation study, which is an interesting avenue for future research. 

Thus, citing Rabinowitz serves to highlight the potential heterogeneity and complexity of abundance–occupancy relationships rather than to refute every positive correlation reported in the literature. Our findings suggest that when examined at large spatiotemporal scales (with unbiased sampling), the overall AOR signal may be less robust than traditionally believed. This is consistent with Rabinowitz’s view that local abundance and global range can vary along independent axes. Now we added

“Although studies using her framework found positive correlations between species range and local abundance.”

Reviewer #1 (Public review):

Summary:

This manuscript assesses the utility of spatial image correlation spectroscopy (ICS) for measuring physiological responses to DNA damage. ICS is a long-established (~1993) method, similar to fluorescence correlation spectroscopy, for deriving information about the fluorophore density that underlies the intensity distributions of images.

The revisions to the current manuscript have improved the understanding of the strengths and limitations of the spatial ICS method. In particular, since the measurements are obtaining complementary information to traditional focus counting, one does not expect a simple linear relationship between the quantities obtained by ICS and by immunostaining. The explanations are satisfactory to me and, I expect, to the interested reader.

Additionally, I am satisfied with the code availability now that it is placed on Github.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

This manuscript assesses the utility of spatial image correlation spectroscopy (ICS) for measuring physiological responses to DNA damage. ICS is a long-established (~1993) method similar to fluorescence correlation spectroscopy, for deriving information about the fluorophore density that underlies the intensity distributions of images. The authors first provide a technical but fairly accessible background to the theory of ICS, then compare it with traditional spot-counting methods for its ability to analyze the characteristics of γH2AX staining. Based on the degree of aggregation (DA) value, the authors then survey other markers of DNA damage and uncover some novel findings, such as that RPA aggregation inversely tracks the sensitivity to PARP inhibitors of different cell lines.

The need for a more objective and standardized tool for analyzing DNA damage has long been felt in the field and the authors argue convincingly for this. The data in the manuscript are in general well-supported and of high quality, and show promise of being a robust alternative to traditional focus counting. However, there are a number of areas where I would suggest further controls and explanations to strengthen the authors' case for the robustness of their ICS method.

Strengths:

The spatial ICS method the authors describe and demonstrate is easy to perform and applicable to a wide variety of images. The DDR was well-chosen as an arena to showcase its utility due to its well-characterized dose-responsiveness and known variability between cell types. Their method should be readily useable by any cell biologist wanting to assess the degree of aggregation of fluorescent tags of interest.

Weaknesses:

The spatial ICS method, though of longstanding history, is not as intuitive or well-known as spot-based quantitation. While the Theory section gives a standard mathematical introduction, it is not as accessible as it could be. Additionally, the values of TNoP and DA shown in the Results are not discussed sufficiently with regard to their physical and physiological interpretation.

We agree that a major limitation in adaption of this approach is a deeper understanding of the theory and results. We have updated the theory section to include further discussion (Page 4 line 132)

The correlation of TNoP with γH2AX foci is high (Figure 2) and suggestive that the ICS method is suitable for measuring the strength of the DDR. The authors correctly mention that the number of spots found using traditional means can vary based on the parameters used for spot detection. They contrast this with their ICS detection method; however, the actual robustness of spatial ICS is not given equal consideration.

We found it difficult to give equal consideration of robustness to ICS. The major limitation of traditional approaches is proper selection of an intensity threshold that is necessary to define and separate foci from background intensity. However, ICS does not employ a threshold, therefore we could not test different thresholding applications in ICS as we did with traditional methods. In our view the absence of the need for a threshold is profoundly advantageous. The only inputs we employ in the ICS analysis are used to segment cell nuclei, yet these have no impact on the ICS calculation and are necessary for any analysis of the DDR.

Reviewer #2 (Public review):

Summary:

Immunostaining of chromatin-associated proteins and visualization of these factors through fluorescence microscopy is a powerful technique to study molecular processes such as DNA damage and repair, their timing, and their genetic dependencies. Nonetheless, it is well-established that this methodology (sometimes called "foci-ology") is subject to biases introduced during sample preparation, immunostaining, foci visualization, and scoring. This manuscript addresses several of the shortcomings associated with immunostaining by using image correlation spectroscopy (ICS) to quantify the recruitment of several DNA damage response-associated proteins following various types of DNA damage.

The study compares automated foci counting and fluorescence intensity to image correlation spectroscopy degree of aggregation study the recruitment of DNA repair proteins to chromatin following DNA damage. After validating image correlation spectroscopy as a reliable method to visualize the recruitment of γH2AX to chromatin following DNA damage in two separate cell lines, the study demonstrates that this new method can also be used to quantify RPA1 and Rad51 recruitment to chromatin following DNA damage. The study further shows that RPA1 signal as measured by this method correlates with cell sensitivity to Olaparib, a widely-used PARP inhibitor.

Strengths:

Multiple proof-of-concept experiments demonstrate that using image correlation spectroscopy degree of aggregation is typically more sensitive than foci counting or foci intensity as a measure of recruitment of a protein of interest to a site of DNA damage. The sensitivity of the SKOV3 and OVCA429 cell lines to MMS and the PARP inhibitors Olaparib and Veliparib as measured by cell viability in response to increasing amounts of each compound is a valuable correlate to the image correlation spectroscopy degree of aggregation measurements.

Weaknesses:

The subjectivity of foci counting has been well-recognized in the DNA repair field, and thus foci counts are usually interpreted relative to a set of technical and biological controls and across a meaningful time period. As such:

(1) A more detailed description of the numerous prior studies examining the immunostaining of proteins such as γH2AX, RAD51, and RPA is needed to give context to the findings presented herein.

We apologize for not providing enough detail. We have added further references and discussion. γH2AX foci counting, in particular, has been used in thousands of previous studies. (Pages 18 line 513 and 517)

(2) The benefits of adopting image correlation spectroscopy should be discussed in comparison to other methods, such as super-resolution microscopy, which may also offer enhanced sensitivity over traditional microscopy.

Thank you for raising this point. We have added this discussion (page 19 line 553). The limiting factor that ICS addresses is the partition coefficient of signal in a foci or cluster versus outside the cluster. Super-resolution will not necessarily improve this unless it is resolved down to single molecule counting. However, one would still need to evaluate how to define a cluster or foci in the background of non-cluster distribution.

(3) Additional controls demonstrating the specificity of their antibodies to detection of the proteins of interest should be added, or the appropriate citations validating these antibodies included.

We have added text stating that we only use validated antibodies (page 6 line 193). One thing to note is that we are measuring differences between treatment conditions, thus, if an antibody has non-specific labeling of proteins of cellular structures that do not change upon treatment, our approach would overcome this limitation.

Reviewer #3 (Public review):

Summary:

This paper described a new tool called "Image Correlation Spectroscopy; ICS) to detect clustering fluorescence signals such as foci in the nucleus (or any other cellular structures). The authors compared ICS DA (degree of aggregation) data with Imaris Spots data (and ImageJ Find Maxima data) and found a comparable result between the two analyses and that the ICS sometimes produced a better quantification than the Imaris. Moreover, the authors extended the application of ICS to detect cell-cycle stages by analyzing the DAPI image of cells. This is a useful tool without the subjective bias of researchers and provides novel quantitative values in cell biology.

Strengths:

The authors developed a new tool to detect and quantify the aggregates of immunofluorescent signals, which is a center of modern cell biology, such as the fields of DNA damage responses (DDR), including DNA repair. This new method could detect the "invisible" signal in cells without pre-extraction, which could prevent the effect of extracted materials on the pre-assembled ensembles, a target for the detection. This would be an alternative method for the quantification of fluorescent signals relative to conventional methods.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Major comments:

(1) The ICS theory section is essential and based on an excellent review from one of the authors. It would benefit greatly from a diagram showing where the quantities 𝒈(𝟎, 𝟎), 𝝎𝟎, and 𝒈inf come from in the 2D Gaussian fit, ideally for two cases where these quantities differ (i.e., how they correspond to different DA or TNoP values). In my opinion, this addition would greatly increase the manuscript's accessibility for DDR researchers. The citation of the review at the beginning would also be a plus.

We have added the review citation at the front of the theory section (page 3 line 87).We have highlighted where g(0,0), the most critical measurement for determination of TNoP and DA, derives from in Figure 2D. However, it is difficult to describe all the curve fit parameters in an image as they have some interdependency on each other and thus labeling one in a single image would not independently capture how they might be observed in a different curve fit.

(2) The TNoP measured in Figure 2 is a quantity about 2000-3000 times greater than the number of "traditionally detected" foci by both methods and the linear relations have very low Y intercepts. Can the authors comment explicitly on the physical interpretation of this number - are 2 to 3 thousand independent particles present within each "focus" detected by traditional means? If so, then what might one "particle" correspond to? (a single secondary antibody or fluorophore? a nucleosome?). In a similar vein, the X intercepts lie at around 25 foci, meaning that in images with fewer than that number of foci detected by ImageJ or Imaris, the ICS method should detect zero TNoP - is this in line with the authors' predictions? Is it possible that a first-order line fit is not the most appropriate relation between the two methods?

We apologize for our brevity here. Since DA proved to be a more useful metric we did not spend much effort discussing TNoP. TNoP correlates to the number of clustered particles, or non-diffuse fluorophores. TNoP is the inverse of the number of individual particles per nucleus, but the value is not a direct measure of foci. If a sample had no clustering at all, the number of individual particles would be at a maximum and the TNoP would be at a minimum. However, as fluorophores cluster, the number of individual particles (i.e. non-clustered fluorophores) decreases, which increases the TNoP value. Therefore, TNoP has a correlation to the number of foci detected through traditional measurements, as we found here. Yet, TNoP is a relative measurement and cannot be compared across different conditions. Similar to foci counting, TNoP is unable to factor the size or intensity of each cluster, thus DA is a more appropriate quantification of the DNA damage response.

The value of TNoP is dependent on the fitted point spread function and the area of the nucleus. The y=0 intercept of TNoP is defined by the optical setup and is not expected to necessarily go through x=0. Intriguingly, other groups have found that some foci identified through traditional measurements are actually clusters of multiple smaller foci, thus the concept of what a foci represents is difficult to interpret. Thus, here we aimed to show a general correlation of TNoP with foci count through traditional methods to reflect how ICS is similar to foci counting, then employed DA to overcome the limitations of defining a foci.

We have tried to clarify this in the text (page 8, line 266)

(3) Some suggestions to address the robustness of ICS:

For a given sample (i.e. one segmented nucleus), the calculation of DA and TNoP should be similar between different images of that same nucleus taken at different times, similar to how the number of traditionally detected foci would be fairly invariant. In particular, it should be shown that these values are not just scaling with the higher normalized intensity seen in stronger DDR responses. In the same vein, the linear relationship between TNoP and "foci" should not change even if the confocal settings are slightly different (i.e., higher/lower illumination intensity) as long as the condition stipulated by the authors in the Discussion holds ("ICS can be implemented on any fluorescence image as long as the square relative fluorescence intensity fluctuations are detectable above noise fluctuations."). To show, as the title states, that spatial ICS is a robust tool, it would be desirable to demonstrate this with a series of images of the same cell at the same or varying excitation intensities.

Thank you for your suggestions. Indeed, the calculation will be the same over sequential images of the same cell. Observations of dose dependent DA that does not correlate with intensity for RPA1 and RAD51 results (Fig. S5) directly demonstrates that DA does not just scale with intensity.

We would not expect the TNoP to change with confocal setting, however we show in Figure 1 that the number of foci does indeed change with intensity settings as captured by thresholds. Therefore, any interpretation of TNoP vs. foci count would be very difficult to make at different microscope settings. To ensure we are fairly comparing ICS to existing analysis we keep the settings the same and measure changes between conditions.

(4) More information is needed on how intensity normalization was performed. The Methods states "Measurements across experiments were normalized by the control in each dataset." The DMSO (0mM drug) plots all appear to have a mean of 1.0, so it appears the values for each set of control nuclei were divided by their own mean, and then the values for each set of experimental nuclei were divided by the mean value of all 3 controls as an aggregate; is this correct?

We apologize for not being more clear. Thank you for raising this point. We normalized data to a control from each experimental group. Thus, in figures 3,4 and 5 data were collected over multiple experiments with one control per experiment and each treatment condition included in each experiment. Therefore, we normalized each result to the corresponding control from that imaging session. However, in Figure 8 we ran experiments at much higher throughput with multiple controls per experiment, thus the data were normalized to the overall average of the controls, which is why the control averages are not all at a value of 1. We have clarified this in the text. (Page 7 line 218).

(5) Some more information about the ICS analysis should be given if the full code is not provided - in particular, how the nucleus mask was implemented on the "signal" channel (were the edges abruptly set to zero or was a window function introduced to avoid edge effects in the discrete FFT?

Thank you for raising this point. We have added the code to GitHub - github.com/ dubachLab/ics. The signal region was established by simply applying the nuclear mask from the DAPI channel to the IF channel. Each region is padded with average intensity value at the edges for 2x the dimensions of the ROI to remove edge effects in the FFT.

Minor comments:

(1) Figure 3, 4, 5: I think it would aid figure readability if channels were labeled in the images themselves, not just in the legend.

Thank you for the suggestion, we tried doing this and struggle to fit a label with the layout of the images. We were also concerned about interpretation of data in each column and the potential to assign data to each figure if they were so prominently labeled.

(2) Supplemental Figures are mislabeled; the order given in the legends is S1, S2, S3, S2, S3. S4 is called out in the main text where it should be S5.

Thank you for catching this error. We have made the necessary corrections. S4 contains data on cellular response to the drugs, while S5 contains intensity data in response to MMS.

(3) It should be stated for each Figure what kind of microscopy was performed - I assume that it is confocal for everything except when widefield is explicitly stated, but for clarity please add this information.

Indeed, this is correct, we have indicated which microscopy was used for each figure.

(4) The MATLAB code and full (uncropped) Western blots should be provided as supplemental data if possible.

We have included a GitHub link for the code and un-cropped western blots.

(5) The p values from significance tests should indicate whether multiple comparisons correction was necessary (if suggested by Prism) and performed.

Apologies for a lack of clarity but this was not necessary, significance was calculated vs. the next lower dose (e.g. 10 micromolar vs. 1 micromolar). We have clarified this in the methods (page 7 line 221).

Reviewer #2 (Recommendations for the authors):

Major points:

In addition to the weaknesses noted above, to encourage widespread adoption of this method, the authors should make the tools that they used for their analysis publicly available. In a few instances (e.g., compare Figures 3J and 3L), other methods outperform DA. It would be meaningful to discuss when especially DA may be a better measure than others (such as intensity or number of foci).

We have made code available on Github. We expect results, such as those in Figures 3J and 3L where intensity is significantly higher at the highest concentration but DA is not are reflective of the underlying biology and this may be interpreted differently under different experimental conditions. Imaris spots (Fig. 3K) also does not capture a significant increase at the highest dose of olaparib, suggesting that intensity may raise but it doesn’t not generate more foci. These results are likely highly dependent on the mechanism of olaparib at such a high concentration and the DDR response. We are hesitant to draw biological conclusions from these results and instead would like to highlight the capacity of ICS to evaluate the DDR, therefore we don’t want to make any broad comments about different applications.

Minor points:

(1) Pg. 12: "We used MMS to induce DNA damage in SKOV3 and OVCA429 cells. As expected, normalized intensity for RPA1 and RAD51 values (Figure S5) did not display a dose dependence on MMS concentration."

Please provide a citation for the claim that RPA1 and RAD51 normalized intensities do not display a dose dependence on MMS concentration.

These were data that we generated. We were not expecting an intensity change as that would presumably require increased protein generation in response to MMS, compared to gH2AX where the phospho-specific H2AX is generated in the DDR.

(2) Pg. 12: "Similar to RPA1, RAD51 does not form distinguishable foci in the nuclei in cells without preextraction (Fig. 5)." Please provide a citation for this claim.

We did not do pre-extraction and our results don’t produce changes in distinguishable foci. We provided citations discussing how, without pre extraction, foci formation for these proteins is not obvious (REF 38 and 39).

(3) I noted that the authors cite one paper [38] apparently showing that RPA and Rad51 do not always form foci, however, this is in the C. elegans germline in response to micro irradiation, therefore I am not sure that it is applicable to human cells.

We apologize for referencing a paper on C elegans. Most papers looking at RPA and RAD51 in the DDR use pre-extraction as it seems necessary to observe foci. Therefore, there are not as many papers, that we could find, that do not use pre-extraction. Reference 39 is in Hela cells.

Reviewer #3 (Recommendations for the authors):

Major points:

(1) Page 8, the second paragraph: In the Result section, it is better to describe how the authors carried out immuno-staining (without pre-extract subtraction) and ICS briefly, although the method is described in detail in the Method section.

Thank you for the suggestion, we have added this description (page 8, line 259)

(2) In Figure 5K-P: The authors analyzed "invisible" RAD51 foci on the image (Fig. 5L, M, O, and P) without pre-extraction. As a control experiment, it is useful to check whether pre-extraction would provide "visible" RAD51 foci and to examine the similar MMS concentration dependency shown in Figure 5R (or 5T). This would strengthen the power of the ICS analysis.

Thank you for the suggestion. In our hands, pre-extraction is extremely subjective. We have tried performing pre-extraction but find highly variable results depending on conditions. Therefore, we did not include any pre-extraction here. We expect that performing these experiments may or may not agree with results in Figure 5 largely because we are unable to achieve repeatable pre-extraction foci counting.

(3) Figure 6D (and 6C) looks very interesting. It would be important to show the interpretation of this correlation shown in the graph. Although the authors argued that ICS analysis results shown in the graph could provide new insight into the DDR (page 14, last line 5), as shown in another part, it is important to carry out the same analysis by using Imaris Spots. Moreover, it is interesting to apply the analysis to RAD51 foci (shown in Figure 5), given that the PARPi effect is enhanced in the absence of RAD51mediated recombination.

We completely agree that this analysis may generate interesting results to help interpret the DDR response to PARP inhibition. These experiments are part of an ongoing follow up study where we extend the use of ICS to other parts of the DDR and investigate protein clustering across several proteins with impact on PARPi response. Therefore, since the focus of this manuscript is introducing ICS as a tool to study the DDR, we believe that omitting those data here does not deter from the central points of the manuscript. We including results in Figure 6 because we wanted to show how ICS could impact DDR research. Furthermore, combined with our advances shown in Figures 7 and 8, we are currently working on adapting ICS to be high-throughput and much simpler than Imaris spots for handling large datasets needed to generate results like those in Figure 6.

Minor points:

(1) Figure 1I, blue arrows: These showed an area with a higher background. Because of a low magnification, it is very hard to see the difference from the other areas of the background. It is better to show a magnified image of the representative region with a higher background.

We hope that readers can see the higher intensity in the diffuse area. We attempted to construct a zoomed in area, but that either blocked a significant portion of the nonzoomed image or added complexity to the figure. We have noted that images in Figure S1 are larger and more obviously capture an increase in background intensity.

(2) Figure 2 legend, line 5, the same as "A)": This should be "B".

Here, the number of independent particle clusters is intended to be the same as A, the difference is that the independent particles are clusters in C and individual fluorophores in A.

(3) Page 9, the first paragraph, last line, foci formation, and foci composition: These should be "focus formation and focus composition".

We have changed this.

(4) Page 15, the first paragraph, line 5, palbociclib, camptothecin, or etoposide: please explain what kinds of the drugs are.

We have added that these drugs cause cells to stall at different cell cycle stages. Explaining the drugs would take considerable room in the text.

(5) Page 16, the first paragraph, line 1, bleomycin: Please explain what this drug is.

Similar to above, we have stated that this drug causes DNA damage, going into detail would take several sentences.

Author response:

The following is the authors’ response to the original reviews

Public reviews:

Reviewer #1:

(1) This manuscript introduces a useful curation pipeline of antibody-antigen structures downloaded from the PDB database. The antibody-antigen structures are presented in a new database called AACDB, alongside annotations that were either corrected from those present in the PDB database or added de-novo with a solid methodology. Sequences, structures, and annotations can be very easily downloaded from the AACDB website, speeding up the development of structure-based algorithms and analysis pipelines to characterize antibody-antigen interactions. However, AACDB is missing some key annotations that would greatly enhance its usefulness.

Here are detailed comments regarding the three strengths above:

I think potentially the most significant contribution of this database is the manual data curation to fix errors present in the PDB entries, by cross-referencing with the literature. However, as a reviewer, validating the extent and the impact of these corrections is hard, since the authors only provided a few anecdotal examples in their manuscript.

I have personally verified some of the examples presented by the authors and found that SAbDab appears to fix the mistakes related to the misidentification of antibody chains, but not other annotations.

(a) "the species of the antibody in 7WRL was incorrectly labeled as "SARS coronavirus B012" in both PDB and SabDab" → I have verified the mistake and fix, and that SAbDab does not fix is, just uses the pdb annotation.

(b) "1NSN, the resolution should be 2.9 , but it was incorrectly labeled as 2.8" → I have verified the mistake and fix, and that sabdab does not fix it, just uses the PDB annotation.

(c) "mislabeling of antibody chains as other proteins (e.g. in 3KS0, the light chain of B2B4 antibody was misnamed as heme domain of flavocytochrome b2)" → SAbDab fixes this as well in this case.

(d) "misidentification of heavy chains as light chains (e.g. both two chains of antibody were labeled as light chain in 5EBW)" → SAbDab fixes this as well in this case.

I personally believe the authors should make public the corrections made, and describe the procedures - if systematic - to identify and correct the mistakes. For example, what was the exact procedure (e.g. where were sequences found, how were the sequences aligned, etc.) to find mutations? Was the procedure run on every entry?

We appreciate the reviewer’s valuable feedback. Our correction procedures combined manual curation with systematic sequence analysis. While most metadata discrepancies were resolved through cross-referencing original literature, we implemented a structured approach for identifying mutations in specific cases. For PDB entries labeled as variants (e.g., "Bevacizumab mutant" or "Ipilimumab variant Ipi.106") where the "Mutation(s)" field was annotated as "NO," we retrieved the canonical therapeutic antibody sequence from Thera-SAbDab, then performed pairwise sequence alignment against the PDB entry using BLAST program to identified mutated residues.

This procedure was not applied to all entries, as mutations are context-dependent. Therapeutic antibodies have well-defined reference sequences, enabling systematic alignment. For antibodies lacking unambiguous wild-type references (e.g., research-grade or non-therapeutic antibodies), mutation annotations were directly inherited from the PDB or literature.

All corrections have been publicly archived in AACDB. We have added a detailed discussion of this issue in the section “2.3 Metadata” of revised manuscript.

(2) I believe the splitting of the pdb files is a valuable contribution as it standardizes the distribution of antibody-antigen complexes. Indeed, there is great heterogeneity in how many copies of the same structure are present in the structure uploaded to the PDB, generating potential artifacts for machine learning applications to pick up on. That being said, I have two thoughts both for the authors and the broader community. First, in the case of multiple antibodies binding to different epitopes on the same antigen, one should not ignore the potentially stabilizing effect that the binding of one antibody has on the complex, thereby enabling the binding of the second antibody. In general, I urge the community to think about what is the most appropriate spatial context to consider when modeling the stability of interactions from crystal structure data. Second, and in a similar vein, some antigens occur naturally as homomultimers - e.g. influenza hemagglutinin is a homotrimer. Therefore, to analyze the stability of a full-antigen-antibody structure, I believe it would be necessary to consider the full homo-trimer, whereas, in the current curation of AACDB with the proposed data splitting, only the monomers are present.

We sincerely appreciate the reviewer’s insightful comments regarding the splitting of PDB files and we appreciate the opportunity to address the reviewer’s thoughtful concerns.

Firstly, when two antibodies bind to distinct epitopes on the same antigen, we would like to clarify that this scenario can be divided into two cases based on the experimental context: Case1: When two antibodies bind to distinct epitopes on the same antigen, and their complexes are determined in separate structures. For example, SAR650984 (PDB: 4CMH) and daratumumab (PDB: 7DHA) target CD38 at non-overlapping epitopes. These two antibody-antigen complexes were determined independently, and their structures do not influence each other. Case 2 : When the crystal structure contains a ternary complex with two antibodies and an antigen, as in the example of 6OGE discussed in Section 2.2 of our manuscript. After reviewing the original literature, the experiment confirmed that the order of Fab binding does not affect the formation of the ternary complex, and the binding of one antibody does not enhance the binding of the other. This supports the rationale for splitting 6OGE into two separate structures. However, we acknowledge that not all ternary complexes in the PDB provide such detailed experimental descriptions in their original literature. We agree with the reviewer that in some cases, one antibody may stabilize the structure to facilitate the binding of a second antibody. For instance, in 3QUM, the 5D5A5 antibody stabilizes the structure, enabling the binding of the 5D3D11 antibody to human prostate-specific antigen. Such sandwich complexes are indeed valuable for identifying true epitopes and paratopes. Importantly, splitting the structure does not alter the interaction sites.

Secondly, we fully agree with the reviewer that for antigens that naturally exist as homomultimers (e.g., influenza hemagglutinin as a homotrimer), the full multimeric structure should be considered when analyzing stability. In such cases, users can directly utilize the original PDB structures provided in their multimeric form. Our splitting approach is intended to provide an additional option for cases where monomeric analysis is sufficient or preferred, but it does not preclude the use of the original multimeric structures when necessary.

(3) I think the manuscript is lacking in justification about the numbers used as cutoffs (1A^2 for change in SASA and 5A for maximum distance for contact) The authors just cite other papers applying these two types of cutoffs, but the underlying physico-chemical reasons are not explicit even in these papers. I think that, if the authors want AACDB to be used globally for benchmarks, they should provide direct sources of explanations of the cutoffs used, or provide multiple cutoffs. Indeed, different cutoffs are often used (e.g. ATOM3D uses 6A instead of 5A to determine contact between a protein and a small molecule https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/c45147dee729311ef5b5c3003946c48f-Abstract-round1.html). I think the authors should provide a figure with statistics pertaining to the interface atoms. I think showing any distribution differences between interface atoms determined according to either strategy (number of atoms, correlation between change in SASA and distance...) would be fundamental to understanding the two strategies. I think other statistics would constitute an enhancement as well (e.g. proportion of heavy vs. light chain residues).

Some obvious limitations of AACDB in its current form include:

AACDB only contains entries with protein-based antigens of at most 50 amino acids in length. This excludes non-protein-based antigens, such as carbohydrate- and nucleotide-based, as well as short peptide antigens.

AACDB does not include annotations of binding affinity, which are present in SAbDab and have been proven useful both for characterizing drivers of antibody-antigen interactions (cite https://www.sciencedirect.com/science/article/pii/S0969212624004362?via%3Dihub) and for benchmarking antigen-specific antibody-design algorithms (cite https://www.biorxiv.org/content/10.1101/2023.12.10.570461v1)).

We thank the reviewer for raising this critical point about the cutoff values used in AACDB. In the current study, the selection of the threshold value is very objective; the threshold chosen in the manuscript is summarized based on existing literature, and we have provided more literature support in the manuscript. The criteria for defining interacting amino acids in established tools, typically do not set the ΔSASA exceed 1 Å2 and the distance exceed 6 Å. While our manuscript emphasizes widely accepted thresholds for consistency with prior benchmarks, AACDB explicitly provides raw ΔSASA and distance values for all annotated residues. Users can dynamically filter the data from downloaded files by excluding entries exceeding their preferred thresholds (e.g., selecting 5Å instead of 6Å). This ensures adaptability to diverse research needs. In the revised version, we reset the distance threshold to 6 Å and calculated the interacting amino acids in order to give the user a wider range of choices. In the section “3.2 Database browse and search” of revised manuscript, we provide a description of the flexible choice of thresholds for practical use.

Furthermore, distance and ΔSASA are two distinct metrics for evaluating interactions. Distance directly quantifies spatial proximity between atoms, reflecting physical contacts such as van der Waals interactions or hydrogen bonds, and is ideal for identifying direct spatial adjacency. ΔSASA, on the other hand, measures changes in solvent accessibility of residues during binding, capturing the contribution of buried surfaces to binding free energy. Even for residues not in direct contact, reduced SASA due to conformational changes may indicate indirect functional roles.

As demonstrated through comparisons on the detailed information pages, the sets of interacting amino acids defined by these two methods differ by only a few residues, with no significant variation in their overall distributions. However, since interaction patterns vary significantly across different complexes, analyzing residue distributions across all structures using both criteria is not feasible.

We thank the reviewer for highlighting these limitations. AACDB currently focuses on protein-based antigens ≤50 amino acids to prioritize structural consistency, which excludes non-protein antigens and shorter peptides. While affinity annotations are critical for benchmarking antibody design tools, these data were not integrated in this release due to insufficient data verification caused by internal team constraints. We acknowledge these gaps and plan to expand antigen diversity and incorporate affinity metrics in future updates.

Reviewer #2:

Summary:

Antibodies, thanks to their high binding affinity and specificity to cognate protein targets, are increasingly used as research and therapeutic tools. In this work, Zhou et al. have created, curated, and made publicly available a new database of antibody-antigen complexes to support research in the field of antibody modelling, development, and engineering.

Strengths:

The authors have performed a manual curation of antibody-antigen complexes from the Protein Data Bank, rectifying annotation errors; they have added two methods to estimate paratope-epitope interfaces; they have produced a web interface that is capable of both effective visualisation and of summarising the key useful information in one page. The database is also cross-linked to other databases that contain information relevant to antibody developability and therapeutic applications.

Weaknesses:

The database does not import all the experimental information from PDB and contains only complexes with large protein targets.

Thank you for the valuable feedback. As previously responded to Reviewer 1, due to limitations within our team, comprehensive data integration from PDB has not been achieved in the current version. We acknowledge the significance of expanding the database to encompass a broader range of experimental information and complexes with diverse target sizes. Regrettably, immediate updates to address these limitations are not feasible at this time. Nevertheless, we are committed to enhancing the database in upcoming upgrades to provide users with a more comprehensive and inclusive resource

Recommendations for the authors:

Reviewer #1:

(1) Line 194: "produce" → "produced"

We thank the reviewer for the feedback. We have checked the grammar and spelling carefully in the revised manuscript.

(2) As mentioned in the public review, I think adding binding affinity annotations would greatly enhance the use cases for the database.

We thank the reviewer for the suggestion. As the response in “Public review”. Due to team constraints, these data are not integrated into this release but are being collated. We recognize these gaps and plan to expand antigenic diversity and incorporate affinity metrics in future updates.

(3) I think adding a visualization of interface atoms and contacts on an entry's webpage would be useful for someone exploring specific entries. It also would be useful if the authors provided a pymol command to select interface residues since that's a procedure any structural biologist is likely to do.

We sincerely appreciate the reviewer’s constructive suggestions. In response to the request for enhanced visualization and accessibility of interface residue information, we have implemented the following improvements: (1) Web Interface Visualization. On the entry-specific webpage, we have added an interactive visualization window that highlights the antigen-antibody interaction interface using distinct colors. The interaction interface visualization has been incorporated into Figure 5 of the revised manuscript, with a detailed description. (2) PyMOL Command Accessibility. The “Help” page now provides step-by-step PyMOL commands to select and visualize interface residues.

(4) I think the authors should provide headers to the files containing interface residues according to the change-in-SASA criterion, as they do for those computed according to contact. This would avoid unnecessary confusion - however slight - and make parsing easier. I was initially confused by the meaning of the last column, though after a minute I understood it to be the change in SASA.

We thank the reviewer for providing such detailed feedback. We thank the reviewer for the comment and the suggestion. We have provided headers for the files of the interacting residues defined by ΔSASA.

(5) Line 233: "AACDB's data processing pipeline supports mmCIF files" → The meaning and implications of this statement are not obvious to me, and are mentioned nowhere else in the paper. Do you mean that in AACDB there are structure entries that the RCSB PDB database only has in mmCIF file format, and not .pdb format? So, effectively, there are some entries in AACDB that are not in any other antibody-specific database?I checked and, as of Dec 3rd, 2024, there are 41 structures in AACDB that are NOT in SAbDab. Manually checking 5 of those 41 structures, none are mmCIF-only structures.

We thank the reviewer for the valuable comment. Because of the size of the structures within certain entries, representing them in a single PDB format data file is not feasible due to the excessive number of atoms and polymer chains they contain. As a result, PDB stores these structures in “mmcif” format files. In AACDB, 47 entries, such as 7SOF, 7NKT, 7B27, and 6T9D, are only available in the “mmCIF” format from the PDB. The “.pdb” and “.cif” files contain atomic coordinates in distinct text formats, and the segmentation of these structure files is automatically conducted based on manually annotated antibody-antigen chains. To accommodate this, we have incorporated these considerations into our file processing pipeline, thereby enabling a fully automated file segmentation process. Additionally, we employed Naccess to calculate interatomic distances. However, since this software only accepts .pdb format files as input, we also converted all split .cif files into .pdb format within our fully automated pipeline. We apologize for the lack of clarity in the original manuscript and have included a more detailed explanation in the "2.2 PDB Splitting" section of the revised manuscript.

Reviewer #2:

(1) In SabDab and PDB, experimental binding affinities are also reported: could the authors comment on whether they also imported this information and double-checked it against the original paper? If it wasn't imported, that might discourage some users and should be considered as an extension for the future.

We thank the reviewer for the comment and the suggestion. As the response in “Public review”. Due to current resource constraints, quantitative affinity data has not been incorporated into this release but is undergoing systematic curation. We explicitly recognize these limitations and propose a two-pronged strategy for future iterations: (1) broadening antigen diversity coverage through expanded structural sampling, and (2) integrating quantitative binding affinity measurements. In the Discussion section, we have included description outlining the planned enhancements.

(2) Line 49-50: the references mentioned in connection to deep learning methods for antibody-antigen predictions seem a bit limited given the amount of articles in this field, with 3 of 4 references on one method only (SEPPA), could the authors expand this list to reflect a bit more the state of the art?

We thank the reviewer for the suggestion. We agree that more relevant studies should be listed and therefore more references are provided in the revised manuscript.

When mentioning the limitations of the existing databases, it feels a bit that the criticism is not fully justified. For instance:

Line 52-53: could the authors elaborate on the reasons why such an identification is challenging? (Isn't it possible to make an efficient database-filtered search? Or rather, should one highlight that a more focussed resource is convenient and why?)

Thank you for feedback. In this study, the keywords "antibody complex," "antigen complex," and "immunoglobulin complex," were employed during data collection. PDB returned over 30,000 results, of which only one-tenth met our criteria after rigorous filtering. This demonstrates that keyword searches, while useful, inherently limit result precision and introduce substantial redundancy, likely due to the PDB's search mechanism. That’s why we illustrated the significant challenges in identifying antibody-antigen complexes from general protein structures in the PDB.

Line 55: reading the website http://www.abybank.org/abdb/, it would be fairer to say that the web interface lacks updates, as the database and the code have gone through some updates. Could the authors provide a concrete example of the reason why: 'The AbDb database currently lacks proper organization and management of this valuable data.'?

We thank the reviewer for highlighting this issue. In our original manuscript, the statement that the AbDb database "lacks proper organization and management" was based on the absence of explicit statement regarding data updates on its official website at the time of submission, even though internal updates to its content may have occurred. We fully respect the long-standing contributions of AbDb to antibody structural research, and our comments were solely directed at the specific state of the database at that time. As the reviewer noted, following the release of our preprint, we have also taken note of AbDb's recent updates. To reflect the latest developments and avoid potential misinterpretation, we have revised the original statement in revised manuscript.

Also 'this rapid updating process may inadvertently overlook a significant amount of information that requires thorough verification,': it's difficult for me to understand what this means in practice. Could the authors clarify if they simply mean that SabDab collects information from PDB and therefore tends to propagate annotation errors from there? If yes, I think it's enough to state it in these terms, and for sure I agree that the reason is that correcting these annotation errors requires a substantial amount of work.

We thank the reviewer for providing such detailed feedback on the manuscript. We acknowledge that SabDab represents a highly valuable contribution to the field, and its rapid update mechanism has significantly advanced related research areas. However, as stated by the reviewer, we aim to clarify that SabDab primarily relies on automated metadata extraction from the PDB for annotation, and its rapid update process inherently inherits raw data from upstream sources. According to their paper, manual curation is only applied when the automated pipeline fails to resolve structural ambiguities. This workflow—dependent on PDB annotations with limited manual verification—may propagate errors provided by PDB. Examples include species misannotation and mutation status misinterpretation. We fully agree with the reviewer's observation that correcting errors in such cases necessitates labor-intensive manual curation, which is a core motivation for our study.

Line 86: why 'Structures that consisted solely of one type of antibody were excluded'? Why exclude complexes with antigens shorter than 50 amino acids? These complexes are genuine antibody-antigen complexes.

We thank the reviewer for the valuable question. The AACBD database is dedicated to curating structural data of antigen-antibody complexes. Structures featuring only a single antibody type are classified as free antibodies and systematically excluded from the database due to the absence of protein-bound partners. During data screening , we retained sequences shorter than 50 amino acids by categorizing them as peptides rather than eliminating them outright. The current release exclusively encompasses complexes with protein-based antigens. Meanwhile, complexes involving peptide, haptens, and nucleic acid antigens are undergoing systematic curation, with planned inclusion in future updates to broaden antigen category representation.

Line 96 needs a capital letter at the beginning.

Line 107: 'this would generate' → 'this generates' (given it is something that has been implemented, correct?).

Line 124: missing an 'of'.

Line 163: inspiring by -> inspired by.

Thank you for feedback. All of the above grammatical or spelling errors have been revised in the manuscript.

Line 109-111: apart from the example, it would be good to spell out the general rule applied to anti-idiotypic antibodies.

We thank the reviewer for the valuable feedback. For anti-idiotypic antibodies complex. the partner antibody is treated as a dual-chain antigen, , necessitating individual evaluation of heavy chain and light chain interactions with the anti-idiotypic component. We have given a general rule for anti-idiotypic antibodies in section “2.2 PDB splitting” of revised manuscript.

Line 155-159: could the authors provide references for the two choices (based on sasa and any-atom distance) that they adopted to define interacting residues?

We thank the reviewer for the comment and the suggestion. As the same as the response to reviewer #1 in Public review. The interacting residues definition and the threshold chosen in the manuscript is summarized based on existing literature. We have added additional references for support in section “1.Introduction”. Our resource does not provide a fixed amino acid list. Instead, all interacting residues are explicitly documented alongside their corresponding ΔSASA (solvent-accessible surface area changes) and intermolecular distances, allowing researchers to flexibly select residue pairs based on customized thresholds from downloadable datasets. Furthermore, aligning with widely adopted criteria in current literature—where interactions are defined by ΔSASA >1 Ų and atomic distances <6 Å, we have recalibrated our analysis in the revised version. Specifically, we replaced the previous 5 Å distance threshold with a 6 Å cutoff to recalculate interacting residues.

Line 176-178: could the authors re-phrase this sentence to clarify what they mean by 'change in the distribution'?

We thank the reviewer for the suggestion. Our search was conducted with an end date of November 2023. However, Figure 3B includes an entry dated 2024. Upon reviewing this record, we identified that the discrepancy arises from the supersession of the 7SIX database entry (originally released in December 2022) by the 8TM1 version in January 2024. This version update explains the apparent chronological inconsistency. We regret any lack of clarity in our original description and have revised the corresponding section in the manuscript to explicitly clarify this change of database.

Caption Figure 3: please spell out all the acronyms in the figure. Provide the date when the last search was performed (i.e., the date of the last update of these statistics).

We thank the reviewer for the comment. We have systematically expanded all acronyms and included update dates for statistics in the legend of Figure 3. Corresponding changes have also been made to the statistical pages on the website.

Finally, it would be advisable to do a general check on the use of the English language (e.g. I noted a few missing articles). In Figure 5 DrugBank contains typos.

We sincerely appreciate the reviewer's meticulous attention to linguistic precision. We have corrected the typographical error in Figure 5 and conducted a comprehensive review of the entire manuscript to ensure accuracy and clarity.

The idea that girls’ clothing could be a “distraction” implies that boys’ inability to focus is the responsibility of girls, shifting blame onto female students and reinforcing sexist double standards. The enforcement of these rules disproportionately impacts Latinas, who are already sexualized by cultural stereotypes.

This greatly explains how many men think it's unfair that a woman could get away with wearing a shirt with a woman and gun, where if they wore the same shirt, they probably would get the same reaction from the school as their counterpart. But there are so many regulations that they DON'T have to think about because they only align to women, and those are only felt by the people they restrain. Now I do think having a dress code isn't a bad thing, but there are many schools that abuse the rules and twist it to sexualize clothes young girls should be able to wear normally.

This has given me some new ideas about the objectization of students in schools. Behind such requirements and policies lies actually the division and control of gender and race, which intensifies the control of gender and leads to a vicious circle. This reminds me of school uniforms. In China, all students are required to wear uniform clothing. I think this has some special differences from the dresscode. What China demands is collectivism that is for all genders, but the dress code for girl is a kind of materialization of women themselves.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public Review):

The authors investigate how the viscoelasticity of the fingertip skin can affect the firing of mechanoreceptive afferents and they find a clear effect of recent physical skin state (memory), which is different between afferents. The manuscript is extremely well-written and well-presented. It uses a large dataset of low threshold mechanoreceptive afferents in the fingertip, where it is particularly noteworthy that the SA-2s have been thoroughly analyzed and play an important role here. They point out in the introduction the importance of the non-linear dynamics of the event when an external stimulus contacts the skin, to the point at which this information is picked up by receptors. Although clearly correlated, these are different processes, and it has been very well-explained throughout. I have some comments and ideas that the authors could think about that could further improve their already very interesting paper. Overall, the authors have more than achieved their aims, where their results very much support the conclusions and provoke many further questions. This impact of the previous dynamics of the skin affecting the current state can be explored further in so many ways and may help us to better understand skin aging and the effects of anatomical changes of the skin.

At the beginning of the Results, it states that FA-2s were not considered as stimuli did not contain mechanical events with frequency components high enough to reliably excite them. Was this really the case, did the authors test any of the FA-2s from the larger dataset? If FA-2s were not at all activated, this is also relevant information for the brain to signal that it is not a relevant Pacinian stimulus (as they respond to everything). Further, afferent receptive fields that were more distant to the stimulus were included, which likely fired very little, like the FA-2s, so why not consider them even if their contribution was low?

Thank you for bringing this up, we have now clarified in the text that while FA-2s did respond at a low rate during the experiment, their responses were not reliably driven by the force stimuli. In the Methods section we have included the following text:

“Initially, 10 FA-2 neurons were also included in the analysis. But their responsiveness during the experiment was remarkably low, and unlike the other neuron types, their responses were rarely affected by force stimuli. Specifically, only one of the observed FA-2 neurons responded during the force protraction phases. Due to the lack of clear stimulus-driven responses, FA-2 neurons were subsequently excluded from further analysis.”

One question that I wondered throughout was whether you have looked at further past history in stimulation, i.e. not just the preceding stimulus, but 2 or 3 stimuli back? It would be interesting to know if there is any ongoing change that can be related back further. I do not think you would see anything as such here, but it would be interesting to test and/or explore in future work (e.g. especially with sticky, forceful, or sharp indentation touch). However, even here, it could be that certain directions gave more effects.

This is a very interesting question! A discernible effect from the previous stimulus could persist at the end of the current stimulation (see Figure 4C), potentially influencing the next one—a 2-stimuli-back effect. Unfortunately, our experimental design did not allow for rigorous testing of this effect. While all possible pairs of stimulus directions were included in immediately consecutive trials, this was not the case for pairs separated by additional trials. Hence, the combination of a likely weak effect and limited variation in history precluded a thorough analysis of a 2-stimuli-back effect. Future work should delve into the time course of the viscoelastic effect in greater detail.

Did the authors analyze or take into account the difference between receptive field locations? For example, did afferents more on the sides have lower responses and a lesser effect of history?

An investigation into the potential impact of the relationship between the receptive field location on the fingertip skin and the primary contact site of the stimulus surface revealed no discernible influence for SA-1 and SA-2 neurons. In contrast, FA-1 neurons, particularly those predominantly sensitive to the previous stimulation or displaying mixed sensitivity, exhibited a tendency to terminate near the primary stimulation site. We have added these observations to the text:

“We found no straightforward relationship between a neuron's sensitivity to current and previous stimulation and its termination site in fingertip skin. Specifically, there was no statistically significant effect of the distance between a neuron's receptive field center and the primary contact site of the stimulus surface on whether neurons signaled current, prior, or mixed information for SA-1 (Kruskal-Wallis test H(2)=3.86, p= 0.15) or SA-2 neurons (H(2)=0.75, p=0.69). However, a significant difference emerged for FA-1 neurons (H(2)=8.66, p=0.01), indicating that neurons terminating closer to the stimulation site on the flat part of the fingertip were more likely to signal past or mixed information.”

Was there anything different in the firing patterns between the spontaneous and non-spontaneously active SA-2s? For example, did the non-spontaneous show more dynamic responses?

The firing patterns of both spontaneously and non-spontaneously active SA-2 neurons shared similarities in terms of adaptation and range of firing rate modulation in response to force stimuli, i.e., ‘dynamic response’. The distinction lay in the pattern of modulation of the firing rate associated with stimulus presentations. For spontaneously active SA-2 neurons, this modulation occurred around a significant background discharge, implying that a force stimulus could either decrease or increase the firing rate, depending on how it deformed the fingertip. This characteristic is well illustrated by the firing pattern of the neuron depicted in the lower panels of Figure 3D. Conversely, in non-spontaneously active SA-2 neurons, a force stimulus could only induce an increase in the firing rate or no change. Although the neuron depicted in the upper panels of Figure 3D exhibited some background activity, it serves to exemplify this characteristic. In the text, we have elucidated the dynamics of the SA-2 neuron response by highlighting that force stimulation can either decrease or increase the firing rate in neurons with spontaneous activity through the following addition/change:

“This increased variability was most evident during the force protraction phase where most neurons exhibited the most intense responses. Increased variability was also observed in instances where the dynamic response to force stimulation involved a decrease in the firing rate (lower panels of Figure 3D). This phenomenon was observed in SA-2 neurons that maintained an ongoing discharge during intertrial periods (cf. Fig. 2A). In these cases, the response to a force stimulus constituted a modulation of the firing rate around the background discharge, signifying that a force stimulus could either decrease or increase the firing rate depending on the prevailing stimulus direction.”

Were the spontaneously active SA-2 afferents firing all the time or did they have periods of rest - and did this relate to recent stimulation? Were the spontaneously active SA-2s located in a certain part of the finger (e.g. nail) or were they randomly spread throughout the fingertip? Any distribution differences could indicate a more complicated role in skin sensing.

SA-2 neurons, in general, are well-known for undergoing significant post-stimulation depression (e.g., Knibestöl and Vallbo, 1970; Chambers et al., 1972; Burgess and Perl, 1973). In our force stimulations, this post-excitatory depression manifested as a reduced or absent response during the latter part of the stimulus retraction period for stimuli in directions that markedly excited the neuron. The excitability recovered when the fingertip relaxed during the subsequent intertrial period, and for "spontaneously active" neurons, the firing resumed (see examples in Figure 7A). Furthermore, some “spontaneously active” neurons could be silenced or exhibit a near-silent period during force stimulation for certain force directions, while the spontaneous firing returned during the upcoming intertrial period when the fingertip shape recovered (for example, see responses to stimulation in the proximal and especially ulnar directions in the top panel in Figure 7A).

Regarding the location of the receptive field centres of spontaneously active and non-spontaneously active SA-2 neurons on the fingertip we did not observe any obvious spatial segregation. To illustrate this, we have revised Figure 1A by color-marking SA-2 neurons that exhibited ongoing activity in intertrial periods, and the figure caption has been modified accordingly:

“Figure 1. Experimental setup. A. Receptive field center locations shown on a standardized fingertip for all first-order tactile neurons included in the study, categorized by neuron type. Purple symbols denote spontaneously active SA-2 neurons exhibiting ongoing activity without external stimulation.”

Did the authors look to see if the spontaneous firing in SA-2s between trials could predict the extent to which the type 1 afferents encode the proceeding stimulus? Basically, does the SA-2 state relate to how the type 1 units fire?

We found no clear indications that the responses of FA-1 and SA-1 could be readily anticipated based on the firing patterns of SA-2 neurons.

In the discussion, it is stated that "the viscoelastic memory of the preceding loading would have modulated the pattern of strain changes in the fingertip differently depending on where their receptor organs are situated in the fingertip". Can the authors expand on this or make any predictions about the size of the memory effect and the distance from the point of stimulation?

We have explored this topic further in the text, referring to recent studies modeling essential aspects of fingertip mechanics. However, in our view, current models lack the capability to predict the specific nature sought by the reviewer. These models should include a detailed understanding of the intricate networks of collagen fibers anchoring the pulp tissue at the distal phalangeal bone and the nail. They should also consider potential inherent directional preferences of the receptor organs, attributed to their microanatomy. The text modifications are as follows:

“In addition to the receptor organ locations, the variation in sensitivity among neurons to fingertip deformations in response to both previous and current loadings would stem from the fingertip’s geometry and its complex composite material properties. Possible inherent directional preferences of the receptor organs, attributed to their microanatomy, could also be significant. However, mechanical anisotropy, particularly within the viscoelastic subcutaneous tissue of the fingertip induced by intricately oriented collagen fiber strands forming fat columns in the pulp (Hauck et al., 2004), are likely to play a crucial role. This anisotropy would shape the dynamic pattern of strain changes at neurons' receptor sites, intricately influencing a neuron's sensitivity not only to current but also to preceding loadings. Indeed, recent modeling efforts suggest that such mechanical anisotropy strongly influences the spatiotemporal distribution of stresses and strains across the fingertip (Duprez et al., 2024).”

Relatedly, we have included additional text to provide a more comprehensive explanation of the “bulk deformation” of the fingertip that occurs during the loadings:

“As pressure increases in the pulp, the pulp tissue bulges at the end and sides of the fingertip. Simultaneously, the tangential force component amplifies the bulging in the direction of the force while stretching the skin on the opposite side.”

In the discussion, it would be good if the authors could briefly comment more on the diversity of the mechanoreceptive afferent firing and why this may be useful to the system.

The diversity in responses among neurons is instrumental in enhancing the information transmitted to the brain by averting redundancy in information acquisition. This diversity thereby contributes to an overall increase in information. We've included a brief statement, along with several references, underscoring this concept:

"The resulting diversity in the sensitivities of neurons might enhance the overall information collected and relayed to the brain by the neuronal population, facilitating the discrimination between tactile stimuli or mechanical states of the fingertip (see Rongala et al., 2024; Corniani et al., 2022; Tummala et al., 2023, for more extensive explorations of this idea)."

Also, the authors could briefly discuss why this memory (or recency) effect occurs - is it useful, does it serve a purpose, or it is just a by-product of our skin structure? There are examples of memory in the other senses where comparisons could be drawn. Is it like stimulus adaptation effects in the other senses (e.g. aftereffects of visual motion)?

We have expanded the concluding paragraph of the discussion, specifically delving into the question of whether the mechanical memory effect serves a deliberate purpose or is simply an incidental byproduct of our skin structure:

“In any case, the viscoelastic deformability of the fingertips plays a pivotal role in supporting the diverse functions of the fingers. For example, it allows for cushioned contact with objects featuring hard surfaces and allows the skin to conform to object shapes, enabling the extraction of tactile information about objects' 3D shapes and fine surface properties. Moreover, deformability is essential for the effective grasping and manipulation of objects. This is achieved, among other benefits, by expanding the contact surface, thereby reducing local pressure on the skin under stronger forces and enabling tactile signaling of friction conditions within the contact surface for control of grasp stability. Throughout, continuous acquisition of information about various aspects of the current state of the fingertip and its skin by tactile neurons is essential for the functional interaction between the brain and the fingers. In light of this, the viscoelastic memory effect on tactile signaling of fingertip forces can be perceived as a by-product of an overall optimization process within prevailing biological constraints.”

One point that would be nice to add to the discussion is the implications of the work for skin sensing. What would you predict for the time constant of relaxation of fingertip skin, how long could these skin memory effects last? Two main points to address here may be how the hydration of the skin and anatomical skin changes related to aging affect the results. If the skin is less viscoelastic, what would be the implications for the firing of mechanoreceptors?

It is likely that the time constant depends to some extent on mechanical factors of the skin, which will likely change due to age or environmental factors. However, while these questions are intriguing, they fall outside the scope of the current study and we are not aware of studies that have addressed these issues directly in experiments either.

How long does it take for the effect to end? Again, this will likely depend on the skin's viscoelasticity. However, could the authors use it in a psychophysical paradigm to predict whether participants would be more or less sensitive to future stimuli? In this way, it would be possible to test whether the direction modifies touch perception.

Time constants for tissue viscoelasticity have been estimated to extend up to several seconds (see citations in the introduction). While direct perceptual effects could indeed be explored through psychophysical experimental paradigms, we are currently unaware of any studies specifically addressing the type of effect described in this study. In addition to the statement that, concerning manipulation and haptic tasks, "to our knowledge, a possible influence of fingertip viscoelasticity on task performance has not been systematically investigated," we have now also addressed tactile psychophysical tasks conducted during passive touch with the following sentence in the text:

“Similarly, there is a lack of systematic investigation of potential effects of fingertip viscoelasticity on performance in tactile psychophysical tasks conducted during passive touch.”

Reviewer #2 (Public Review):

Summary:

The authors sought to identify the impact skin viscoelasticity has on neural signalling of contact forces that are representative of those experienced during normal tactile behaviour. The evidence presented in the analyses indicates there is a clear effect of viscoelasticity on the imposed skin movements from a force-controlled stimulus. Both skin mechanics and evoked afferent firing were affected based on prior stimulation, which has not previously been thoroughly explored. This study outlines that viscoelastic effects have an important impact on encoding in the tactile system, which should be considered in the design and interpretation of future studies. Viscoelasticity was shown to affect the mechanical skin deflections and stresses/strains imposed by previous and current interaction force, and also the resultant neuronal signalling. The result of this was an impaired coding of contact forces based on previous stimulation. The authors may be able to strengthen their findings, by using the existing data to further explore the link between skin mechanics and neural signalling, giving a clearer picture than demonstrating shared variability. This is not a critical addition, but I believe would strengthen the work and make it more generally applicable.

Strengths:

- Elegant design of the study. Direct measurements have been made from the tactile sensory neurons to give detailed information on touch encoding. Experiments have been well designed and the forces/displacements have been thoroughly controlled and measured to give accurate measurements of global skin mechanics during a set of controlled mechanical stimuli.

- Analytical techniques used. Analysis of fundamental information coding and information representation in the sensory afferents reveals dynamic coding properties to develop putative models of the neural representation of force. This advanced analysis method has been applied to a large dataset to study neural encoding of force, the temporal dynamics of this, and the variability in this.

Weaknesses:

- Lack of exploration of the variation in neural responses. Although there is a viscoelastic effect that produces variability in the stimulus effects based on prior stimulation, it is a shame that the variability in neural firing and force-induced skin displacements have been presented, and are similarly variable, but there has been no investigation of a link between the two. I believe with these data the authors can go beyond demonstrating shared variability. The force per se is clearly not faithfully represented in the neural signal, being masked by stimulation history, and it is of interest if the underlying resultant contact mechanics are.

Thank you for this suggestion. We have added a new section investigating the link between skin deformation and neural firing in more depth via a simple neural model. Please see our answer below in the ‘Recommendations’ section for further details.

Validity of conclusions:

The authors have succeeded in demonstrating skin viscoelasticity has an impact on skin contact mechanics with a given force and that this impacts the resultant neural coding of force. Their study has been well-designed and the results support their conclusions. The importance and scope of the work is adequately outlined for readers to interpret the results and significance.

Impact:

This study will have important implications for future studies performing tactile stimulation and evaluating tactile feedback during motor control tasks. In detailed studies of tactile function, it illustrates the necessity to measure skin contact dynamics to properly understand the effects of a force stimulus on the skin and mechanoreceptors.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

(Very) minor comments

- The authors say at the beginning of the Results that, "The fourth type of tactile neurons in the human glabrous skin, fast adapting type II neurons...". Although generally written that there are four types of afferent in the glabrous skin, it would be better to state that these are low-threshold A-beta myelinated mechanoreceptive afferents, at least one time, as there are other types of afferent in the glabrous skin that respond to mechanical stimulation (e.g. low and high threshold C-fibers).

This is now clarified at the start of the Results section:

“We recorded action potentials in the median nerve of individual low-threshold A-beta myelinated first-order human tactile neurons innervating the glabrous skin of the fingertip…”

- Fig. 3: Could you add '(N)' as the measurement of force for Fig. 3A for Fz, Fy, and Fz? Also, please change 'Data was recorded' to 'Data were recorded' in the legend.

Fixed.

- At the beginning of the Methods, you say that your study conforms to the Declaration of Helsinki, which actually requires pre-registration in a database. If you did not pre-register your study, please can you add '... in accordance with the Declaration of Helsinki, apart from pre-registration in a database'.

Thanks for making us aware of this. We have added the suggested qualifier to the ethics statement.

Reviewer #2 (Recommendations For The Authors):

The neural representation/encoding of the actual displacement vectors would be a useful addition to the analyses. These vectors have been demonstrated to systematically change with the condition in the irregular series (Figure 2E) and will thus significantly act on the dynamics of induced mechanical changes in the skin with a given interaction force. Thus, it could be examined how the neurons code the magnitude of displacements as well as their direction. An evaluation of the extent to which the imposed displacement magnitudes are encoded in the neural responses would be a useful addition in explaining the signalling of the force events and how the central nervous system decodes these. Evaluating an alternative displacement encoding for comparison to pure force encoding may reveal more about how contact events are represented in the tactile system, which must decode these variable afferent signals to reconstruct a percept of the interaction. It could then be explored how the central nervous system may then scale the dynamic afferent responses based on the background viscoelastic state likely to be present in the SA-II afferent signals (Figure 7) for a context in which to evaluate the dynamic contact forces. This may of course be a complex relationship for the type-I afferents, where the underlying mechanical events evoking the firing (microslips not represented in global forces) have not been measured here. Such a model could be more widely applicable, as the skin viscoelasticity and displacement magnitudes are a straightforward measurement metric and could perhaps be used as a better proxy for neural signalling. This would allow the investigation of a wider variety of forces, and the study of the timing of the viscoelastic effect, both of which have been fixed here. This would give the work a broader impact, rather than just highlighting that this effect produces variability, it could reveal if this mechanical feature is structured in the neural representation. The categorical encoding/decoding tested here is specific to the stimuli used (magnitudes, intervals), but there is the possibility that this may be more generally applicable (within the bounds of forces/speeds) if the underlying basis of the variability in the signalling produced by the viscoelasticity is identified. Since the time course of the viscoelasticity has not been measured here (fixed forces and intervals), further study is required to fully understand the implications this has for a wider variety of situations.

We agree that a better understanding of how the mechanical deformations are reflected in the resulting spike trains would be valuable. While ultimately a full understanding will need precise measurements of skin deformation across the whole fingertip to account for mechanical propagation to mechanoreceptor locations, relating the deformations at the contact location with neural firing patterns directly can provide useful hints into which aspects of deformation are encoded and how. To this end, we ran a new analysis that aimed to predict the time-varying neural responses directly from the recorded mechanical movements of the contactor.

Below we have reproduced the new results and methods text along with the additional figures for this analysis. Note that we have also added text in the Discussion to interpret these findings in the context of our other results.

New section in Results titled Predicting neural responses from contactor movements: “The similarity in the history-dependent variation in neural firing and fingertip deformation at a given force stimulus suggests that neuronal firing is determined by how the fingertip deforms rather than the applied force itself. However, this similarity does not clarify the relationship between fingertip deformation dynamics and neural signaling. To investigate further, we fit cross-validated multiple linear regression models to evaluate how well distinct aspects of contactor movement could predict the time-varying firing rates of individual neurons during the protraction phases of the irregular sequence. The models used predictors based on (1) the three-dimensional position of the contactor, (2) its three-dimensional velocity, (3) a combination of position and velocity signals, and, finally, (4) position and velocity signals along with all possible two-way interactions between them, capturing potentially complex relationship between fingertip deformations and neural signaling.

Comparing the variance explained (R²) by each regression model for each neuron type revealed clear differences between the models (Figure 5A). A two-way mixed design ANOVA, with regression model as within-group effects and neuron type as a between-group effect revealed a main effect of model on variance explained (F(3,462) = 815.5, p < 0.001, η_p² = 0.84). Model prediction accuracy overall increased with the number of predictors, with the two-way interaction model outperforming all others (p < 0.001 for all comparisons, Tukey’s HSD). Additionally, a significant main effect of neuron type (F(2,154) = 29.8, p < 0.001, η_p² = 0.28) and a significant interaction between regression model and neuron type were observed (F(6,462) = 50.8, p < 0.001, η_p² = 0.40).

For neuron type, model predictions were most accurate for SA-2 neurons, followed by SA-1 neurons, with FA-1 neurons showing the lowest accuracy (p < 0.003 for all comparisons, Tukey’s HSD). The interaction between model and neuron type revealed distinct patterns. For SA-1 and SA-2 neurons, position-only and velocity-only models had similar prediction accuracy (p ≥ 0.996, Tukey’s HSD) with no significant differences between these neuron types (p ≥ 0.552, Tukey’s HSD). FA-1 neurons performed poorly with the position-only model but showed higher accuracy with the velocity-only model (p < 0.001, Tukey’s HSD) and better than SA-1 neurons (p = 0.006, Tukey’s HSD). Models combining position and velocity predictors (without interactions) surpassed both position-only and velocity-only models for SA-1 and SA-2 neurons (p < 0.001, Tukey’s HSD). Overall, the differences between neuron types broadly match their tuning to static and dynamic stimulus properties.

The two-way interaction model, accounting for most variance in neural responses, produced mean R² values of 0.75 for FA-1, 0.88 for SA-1, and 0.91 for SA-2 neurons (Figure 5A). To evaluate the contribution of the different predictors, we ranked them using the permutation feature importance method, focusing on the six most important ones. Regression analyses using only these variables explained almost all of the variance explained by the full model, with a median R² reduction of just 0.055 across all neurons. Across all neuron types, at least half included all three velocity components (dPx, dPy, dPz) among the top six, with FA-1 neurons showing the highest prevalence (Figure 5B). Interactions between normal position (Pz) and each velocity component were also frequently observed, while interactions involving tangential position and velocity components were less common. Interactions among velocity components were relatively well represented, followed by interactions limited to position components. Position signals were generally less represented, except for normal position (Pz) in slowly adapting neurons, where it appeared in 50% of SA-1 and 68% of SA-2 neurons. Despite these broad trends, important predictors varied widely across ranks even within a given neuron class (see Figure 5-figure supplement 1), and even the most frequent variables appeared in only a subset of cases, suggesting broad variability in sensitivity across neurons.”

New methods paragraph titled Predicting time-varying firing rates from skin deformations:

“This analysis was conducted in Python (v3.13) with pandas for data handling, numpy for numerical operations, and scikit-learn for model fitting and evaluation.

To assess how well individual neurons' time-varying firing rates could be predicted from simultaneous contactor movements, we fitted multiple linear regression models (see Khamis et al., 2015, for a similar approach}. This analysis focused on the force protraction phase of the irregular sequence, where neurons were most responsive and sensitive to stimulation history. Data from 100 ms before to 100 ms after the protraction phase (between -0.100 s and 0.225 s relative to protraction onset) were included for each trial. Neurons were included if they fired at least two action potentials during the force protraction phase and the following 100 ms in at least five of the 25 trials. This ensured sufficient variability in firing rates for meaningful regression analysis, resulting in 68 SA-1, 38 SA-2, and 51 FA-1 neurons being included.

Contractor position signals digitized at 400 Hz were linearly interpolated to 1000 Hz. Instantaneous firing rates, derived from action potentials sampled at 12.8 kHz, were resampled at 1000 Hz to align with position signals. A Gaussian filter (σ = 10 ms, cutoff ~16 Hz) was applied to the firing rate as well as to the position signals before differentiation. To account for axonal conduction (8–15 ms) and sensory transduction delays (1–5 ms), firing rates were advanced by 15 ms to align approximately with independent variables.

Regressions were performed using scikit-learn's Ridge and RidgeCV regressors, which apply L2 regularization to mitigate overfitting. Hyperparameter tuning for the regularization parameter (alpha) was performed using GridSearchCV with a predefined range (0.001–1000.0), incorporating five-fold cross-validation to select the best value. To minimize overfitting risks, model performance was further validated with independent five-fold cross-validation (KFold), and R² scores were computed using cross_val_score.

We constructed four linear regression models with increasing complexity: (1) Position-only, using three-dimensional contactor positions (Px, Py, Pz); (2) Velocity-only, using three-dimensional velocities (dPx, dPy, dPz); (3) Combined, including all position and velocity signals (6 predictors); and (4) Interaction, including all signals and their two-way interactions (21 predictors). All features were standardized using StandardScaler to improve regularization and model convergence. PolynomialFeatures generated second-order interaction terms for the interaction model. Feature importance was evaluated with permutation_importance, and simpler models were built using the most important features. These models were validated through cross-validation to assess retained explanatory power.”

Minor:

- It would be useful to add a brief description of the material aspects of the contactor tip to the methods (as per Birznieks 2001).

We have added the following statement:

“To ensure that friction between the contactor and the skin was sufficiently high to prevent slips, the surface was coated with silicon carbide grains (50–100 μm), approximating the finish of smooth sandpaper.”

- The axes labelling on Figure 3A and legend description is ambiguous, probably placing the Px, Py, and Pz labels on the far left axes and the Fx, Fy, and Fz on the right side of the far right axes would make this clearer.

Label placement has been improved along with some other minor fixes.

- For the quasi-static phase analysis, the phrase "absence of loading" used in reference to the interstimulus period and SA-II afferents does not seem to be a correct description. The finger is still loaded (at least in the normal direction), with a magnitude of imposed displacement that counteracts the viscoelastic force exerted by the skin mechanics of the fingertip. Although there is a zero net-force load, a mechanical stimulus is still being actively applied to the skin.

We have changed the wording throughout the text and now consistently refer either to the “interstimulus period” directly or to an “absence of externally applied stimulation” to avoid confusion.

Document de Briefing : Examen des Enjeux de l'Éducation dans la Région Hauts-de-France

Source : Extraits de "🔴 Xavier Bertrand sur la réponse de l’État face aux violences dans les établissements scolaires"

Date :2025

Intervenant Principal : Xavier Bertrand, Président du Conseil Régional des Hauts-de-France

Contexte : Audition dans le cadre d'une commission d'enquête parlementaire sur la réponse de l'État face aux violences dans les établissements scolaires.

L'audition se concentre notamment sur le contrôle exercé par les autorités, le financement des établissements scolaires (publics, privés sous contrat et hors contrat), et spécifiquement sur le cas du lycée privé Averroès de Lille dont le contrat d'association avec l'État a été résilié.

Principaux Thèmes Abordés :

Financement des Établissements Scolaires par la Région Hauts-de-France :

• Montants : Xavier Bertrand détaille les subventions versées par la région pour l'année scolaire en cours.
• Dotation globale de fonctionnement (établissements publics et privés sous contrat) : 90,2 millions d'euros.
• Subventions pour les actions éducatives : 3,2 millions d'euros.
• Politiques volontaires (prêts à taux zéro, garanties d'emprunt, etc.) : 10 millions d'euros (suspendus ou en année blanche pour les établissements privés sous contrat à la prochaine rentrée).
• Dépenses assurées en maîtrise d'ouvrage région (maintenance) : un peu plus de 5 millions d'euros.
• Distinction Public/Privé :Établissements publics : Les 90,2 millions d'euros (dotation globale) s'appliquent également aux établissements publics.
• Établissements privés sous contrat : 50 millions d'euros font l'objet de dépenses obligatoires. 10 millions d'euros concernent des politiques non obligatoires (politiques volontaires/facultatives).
• Établissements Privés Hors Contrat : La région Hauts-de-France ne subventionne actuellement aucun établissement privé hors contrat. Xavier Bertrand n'interdit pas cette possibilité par principe si cela présente un intérêt avéré pour la région, nécessitant un débat en assemblée plénière. La position de la région sur le hors contrat est connue, et aucune demande de subvention de la part de ces établissements n'a été reçue. Xavier Bertrand a été sollicité pour visiter de tels établissements mais a refusé, expliquant ne pas avoir de relations établies avec eux.
• Subventions Facultatives (10 millions d'euros) : Ces subventions relèvent d'un projet et d'une volonté politique. Elles servent principalement à financer des travaux ou des achats d'équipement (numérique, rénovation énergétique, etc.).

L'attribution se fait souvent via des protocoles d'accord, notamment avec l'enseignement diocésain, et peut prendre la forme d'avances remboursables, de prêts à taux zéro ou d'annuités d'emprunt.

La loi Falloux limite ces subventions à 10% des dépenses annuelles pour certains types d'établissements (sauf pour l'enseignement technique, professionnel, agricole et les maisons familiales rurales - loi Acier de 1919). Un contrôle sur pièces et sur place est systématiquement effectué pour vérifier l'engagement des travaux avant le versement des fonds. Ces subventions facultatives ne concernent pas la vie scolaire ou l'animation éducative, mais du bâtiment et du technique.

Rôle et Compétences de la Région en matière de Contrôle et d'Inspection :

• Absence d'Association et d'Information : Le Conseil Régional n'est ni associé ni informé lorsque l'État effectue un contrôle ou une inspection dans les lycées (académique, administratif, audit des finances publiques). Xavier Bertrand souhaiterait que l'information soit systématique et que les services régionaux dédiés aux lycées y soient associés, surtout si cela touche aux compétences régionales (fonctionnement financier, gestion des agents).

• Personnel Non-Enseignant : La question de l'inspection du personnel non enseignant (relevant de la responsabilité de la région) est soulevée. Bien que ces agents fassent partie de la communauté éducative, Xavier Bertrand souligne qu'il n'a pas l'autorité fonctionnelle sur eux, ce qu'il considère "anormal" et méritant l'attention du législateur. Il estime qu'une inspection générale serait fondée à s'intéresser à ce personnel, mais insiste sur la nécessité d'une collaboration étroite avec les services régionaux.

• Contrôle d'Honorabilité du Personnel : La région procède systématiquement aux contrôles préalables autorisés par la loi pour le recrutement du personnel (casier judiciaire B2). Cependant, elle ne fait pas partie des employeurs qui peuvent demander une attestation d'honorabilité pour certaines fonctions réglementées. Xavier Bertrand est demandeur de cette possibilité, le B2 étant le document utilisé pour vérifier le passé judiciaire, un casier judiciaire rendant impossible de travailler auprès des jeunes.

• Le Cas du Lycée Privé Averroès de Lille : Ce cas est central dans l'audition et illustre les problématiques de contrôle et de relations entre l'État et la Région.

• Contexte : Averroès est le deuxième établissement sous contrat en France dont le contrat d'association a été rompu (en 2023). Cette rupture est possible selon l'article L442-10 du code de l'éducation, à l'initiative de l'État ou sur demande d'une collectivité.

• Rôle de Xavier Bertrand : Xavier Bertrand se considère comme un "lanceur d'alerte" dans ce dossier depuis novembre 2017, date à laquelle il a sollicité l'État (le rectorat puis le ministère de l'éducation nationale) pour savoir si les conditions du contrat d'association étaient toujours réunies. Il a suspendu le versement du forfait d'externat (dépense obligatoire) à partir de novembre 2019, dans l'attente des conclusions des inspections et audits diligentés par l'État, et ce malgré plusieurs condamnations par le tribunal administratif. Il assume pleinement cette décision politique, la considérant comme le seul moyen d'alerter.

• Demande de Résiliation du Contrat : Bien que le code de l'éducation l'autorise à demander la résiliation au préfet, Xavier Bertrand a choisi de ne pas le faire, arguant qu'il respecte les principes de responsabilité définis par la loi. Il souhaiterait cependant que la Région ait plus de responsabilités et de compétences sur de telles questions.

• Commission de Concertation : La résiliation intervient après avis de la commission de concertation (article R442-64 du code de l'éducation), composée notamment de trois conseillers régionaux. Xavier Bertrand a participé à la réunion de cette commission en novembre 2023, invité par le préfet pour être entendu et présenter la position de la Région. Il a quitté la salle avant le vote. Il ne pense pas avoir enfreint l'article du code, étant invité pour exposer sa position et non pour voter. Il a assumé dire que pour lui, Averroès n'était "pas le cas d'un lycée républicain", ce qui, selon le rapporteur, a fortement influencé le vote de la commission en faveur de la résiliation.

Motivations et Chronologie :

Xavier Bertrand détaille la chronologie de ses actions et motivations :

• 2015 : Visite de l'établissement après les attentats, témoignage de soutien aux victimes par l'établissement.
• 2017 : Saisine du recteur pour clarifier la place du religieux (rapport de 2015). Absence de réponse.
• 2019 : Révélations dans "Qatar Papers" sur des financements étrangers. Saisine du ministre de l'éducation nationale. Le ministre envisage une inspection et un audit financier. Suspension du forfait d'externat.
• 2020 : Réception du rapport d'inspection confirmant un prêt remboursé par un don de Qatar Charity. Saisine à nouveau du ministre pour obtenir des précisions sur les conditions du don et le rôle d'une mosquée ayant reçu des financements étrangers. Pas de réponse précise.
• 2023 : Rapport de la Chambre Régionale des Comptes (CRC) du 30 juin 2023. Le préfet convoque la commission de concertation, qui vote la résiliation. Le tribunal administratif annule la résiliation, et le gouvernement fait appel.

Décalage avec le Rapport de l'Inspection Générale :

Le rapporteur souligne que le rapport de l'Inspection Générale de 2020 concluait que l'établissement respectait "parfaitement les valeurs de la République". Xavier Bertrand conteste cette conclusion, se basant sur le rapport de la CRC qui, selon lui, met en évidence des contenus d'enseignement contraires aux valeurs républicaines (cours d'éthique musulmane basé sur les 40 hadiths de l'imam An-Nawawi). Il exprime son trouble que la CRC ait vu ce que l'IGESR n'aurait pas vu, estimant que l'attitude de l'Éducation Nationale revenait à dire "circulez, il n'y a rien à voir".

• Arguments de la CRC : Xavier Bertrand cite explicitement les points soulevés par la CRC dans son rapport : proximité de l'association Averroès avec Musulmans de France (lié aux Frères Musulmans), présence d'une personne liée à ce mouvement dans les organes décisionnels, financement étranger significatif (1,9 million d'euros) provenant de divers pays (Koweït, Arabie Saoudite, Bahreïn), et le contenu du cours d'éthique musulmane jugé en contradiction avec les valeurs de la République (interdiction pour une femme de se faire ausculter par un homme, évitement de la mixité, prohibition de l'apostasie, prééminence de la loi divine).

Autres Cas et Proactivité de la Région :

• La Région n'a pas été saisie d'autres cas de lycées sous sa responsabilité qui l'auraient amenée à se poser les mêmes questions.
• Concernant le cas de Riomont (qui ne concerne pas un lycée géré ou financé par la Région), Xavier Bertrand a saisi la procureure de la République de Lille en janvier 2024 pour attirer son attention et exprimer le soutien de la Région aux victimes. Il est disposé à rencontrer le collectif de victimes.
• Il a également mentionné l'établissement Notre Dame de Riyaumont - Saint-Jean de Bosco à Liin, précisant que la région ne l'a jamais financé.
• La Région a mené des actions contre le harcèlement scolaire (appels à projet, cellules d'intervention rapide), notamment une initiative avec le procureur d'Amiens pour une cellule d'intervention immédiate dans la Somme incluant un délégué du procureur. Il reconnaît cependant la difficulté à intégrer la dimension spécifique du handicap dans ces dispositifs.

Recommandations et Souhaits pour l'Avenir :

• Xavier Bertrand souhaite une coopération renforcée et une information systématique des collectivités locales (Régions pour les lycées, Départements pour les collèges) lors des inspections et contrôles de l'État dans les établissements scolaires qu'elles financent, particulièrement sur les aspects financiers et de gestion des personnels régionaux.
• Il est demandeur de la possibilité pour les Régions de solliciter une attestation d'honorabilité pour le personnel qu'elles recrutent.
• Il estime que les collectivités territoriales devraient être davantage associées aux commissions de concertation pour la résiliation des contrats d'association.
• Plus globalement, il plaide pour une place plus importante des Régions dans la gestion et la protection des lycées, estimant qu'elles pourraient intervenir plus efficacement sur l'environnement sécuritaire (à l'intérieur et autour du lycée), sur les dimensions psychologiques et physiques des violences, même si le contenu pédagogique et la direction relèvent de l'État.

Citations Clés :

• "Aujourd'hui, ça n'est pas le cas non plus et que les services régionaux y soient associés notamment ceux dédiés au lycée je trouve que ce serait effectivement une bonne chose à partir du moment où ça va toucher les compétences régionales que ce soit le fonctionnement financier la gestion des agents régionaux." (Xavier Bertrand sur l'association de la région aux inspections de l'État)
• "Je pense que d'ailleurs à un moment ou un autre il serait quand même utile que le législateur se penche sur cette question [l'autorité fonctionnelle sur les agents régionaux dans les lycées]. C'est effectivement bien souvent l'agent comptable qui donne des instructions Mais en tout état de cause moi président de région je n'ai absolument pas l'autorité fonctionnelle sur ces agents." (Xavier Bertrand sur son manque d'autorité sur le personnel régional)
• "Je pense que si la région pouvait parce qu'on est en contact avec des jeunes pouvoir établir une attestation enf pardon pouvoir solliciter une attestation d'honorabilité je suis pas preneur je suis demandeur." (Xavier Bertrand sur l'attestation d'honorabilité)
• "clairement je le dis et je l'assume ces subventions facultatives relèvent donc bel et bien d'un projet et d'une volonté politique." (Xavier Bertrand sur les subventions facultatives)
• "J'ai avant tout et surtout sollicité l'État depuis novembre 2017 pour savoir si oui ou non les conditions étaient réunies pour qu'un contrat d'association entre l'État et ce lycée soit toujours accordé (...) et je n'ai eu de cesse de me considérer comme un lanceur d'alerte et si c'était à refaire je referais tout depuis le départ." (Xavier Bertrand sur son rôle dans l'affaire Averroès)
• "Au fond ne pas verser le forfait externa au fond c'est rompre le contrat de l'association qui garantit le financement euh de la part de la région aussi de cet établissement Ma question est est très simple Pourquoi ne pas être allé peut-être au bout donc de cette démarche que vous avez engagé en suspendant le versement du forfait externa en demandant au préfet comme le code de l'éducation là encore le permettre de de rompre ce contrat" (Rapporteur questionnant la stratégie de Xavier Bertrand)
• "on peut financer je vous cite je le dis l'enseignement libre et je continuerai à vouloir le faire mais on peut le faire pour des lycées qui sont vraiment républicains et pour moi ce n'est pas le cas du lycée aouest" (Citation rapportée des propos de Xavier Bertrand lors de la commission de concertation)
• "Je pense avoir montré depuis effectivement des années quelle avait été la position de la région que j'ai assumé notamment devant les interpellations de monsieur le rapporteur Concernant le lycée Jean-Paul II il faut savoir une chose c'est qu'il y a une enquête préliminaire donc une instruction judiciaire qui est clairement ouverte Je crois que le proviseur a également démissionné et qu'encore une fois permettez-moi de le dire avec cet exemple vous apportez de l'eau à mon moulin comme le disait madame la présidente tout à l'heure elle me questionnait là-dessus Oui je souhaiterais qu'on soit avisé des enquêtes qui sont faites ou des inspections parce que c'est ça vos références Oui Oui Non non mais je je voulais pas vous interrompre mais vous pouvez lire médi pouvez connaître pas besoin d'être averti un article" (Xavier Bertrand sur d'autres cas potentiels et la nécessité d'être informé des inspections)
• "cette commission d'enquête j'ai pas besoin de le dire mais elle est particulièrement importante parce qu'elle touche à ce pour qui on est prêt à faire effectivement tous les efforts cette question des violences (...) Le vrai problème que nous avons nous les conseils régionaux c'est qu'au final on finance les établissements la structure le personnel d'entretien de restauration mais on a beau être paraît-il chez nous nous ne le sommes pas vraiment" (Xavier Bertrand en conclusion sur l'importance de la commission et les limites des compétences régionales)

Points de Discussion Potentiels pour les Auditions Futures :

• Approfondir le manque d'autorité fonctionnelle des Présidents de Région sur le personnel qu'ils financent dans les lycées.
• Explorer la faisabilité et l'opportunité d'étendre la possibilité de demander une attestation d'honorabilité aux Régions.
• Examiner les raisons du décalage entre les conclusions du rapport de l'IGESR et celles du rapport de la CRC dans l'affaire Averroès.
• Évaluer l'efficacité actuelle des inspections et audits de l'État et les moyens de les améliorer, y compris la question de l'information et de l'association des collectivités locales.
• Discuter des modalités d'intervention des collectivités locales dans la lutte contre le harcèlement, particulièrement pour les élèves en situation de handicap.
• Analyser les critères et le processus de subventionnement des établissements privés sous contrat et hors contrat par les Régions et l'opportunité d'une plus grande formalisation.
• Ce document de briefing résume les points clés de l'audition, mettant en lumière les préoccupations de Xavier Bertrand concernant le contrôle de l'État, le financement des établissements, et les limites actuelles des compétences régionales face aux enjeux de sécurité et de respect des valeurs républicaines dans le système éducatif. Le cas Averroès sert d'étude de cas détaillée pour illustrer ces défis.

Synthèse de la réunion : Élisabeth Guigou et représentants de Départements de France sur les violences en milieu scolaire

Date de la réunion: 2025

Objectif: Examiner la prise en compte par l'institution judiciaire (Mme Guigou, ancienne Ministre de la Justice) et le rôle des départements (Départements de France) des violences en milieu scolaire, avec un focus particulier sur les cas de violences sexuelles commises par des adultes.

Participants:

• Élisabeth Guigou: Ancienne Ministre de la Justice (1997-2000)
• Représentants de Départements de France: François Sauvadet (Président), Florence d'Abin (Vice-présidente), Anne-Sophie Abgral (Directrice générale adjointe), Yves Lebreton (Directeur général), Paul-Étienne Koffman (Conseiller éducation), Bris Lacourieux (Conseiller relation avec le Parlement), Steven Brunetta (membre du cabinet de Mme Davin).

Principaux thèmes abordés:

• Évolution de la prise en compte des violences sexuelles en milieu scolaire par la justice: Témoignage de Mme Guigou sur son action en tant que Ministre de la Justice, notamment l'élaboration et le vote de la loi du 17 juin 1998.
• Le cas de l'affaire Caricar (Bétarram): Analyse des flux d'information au sein du Ministère de la Justice à l'époque des faits et la question de la transmission des informations entre la justice et le Ministère de l'Éducation Nationale.
• Rôle des départements en matière de protection de l'enfance: Clarification des compétences et des pratiques des départements, en particulier concernant les violences en milieu scolaire.
• Gestion des informations préoccupantes (IP) et des signalements: Examen des procédures, des difficultés rencontrées et des axes d'amélioration dans la transmission des informations entre les différents acteurs (enseignants, CRIP, éducation nationale, justice).

Idées et faits les plus importants:

• Action de Mme Guigou (1997-2000): Mme Guigou a souligné l'importance qu'elle a accordée à la lutte contre les violences sexuelles sur les enfants dès son arrivée au Ministère de la Justice. Elle a trouvé un projet de loi existant mais a décidé de le réorienter pour inclure la protection des victimes et revoir l'approche centrée uniquement sur les auteurs. Cette démarche a abouti à la loi du 17 juin 1998.
• Citation: "J'ai trouvé en juin 97 j'étais loin d'imaginer ce que nous savons maintenant 28 ans après et ce que nous avons découvert petit à petit mais j'ai trouvé un projet de loi qui avait été préparé par mon prédécesseur et qui traitait de la lutte contre les les auteurs de crimes sexuel de de délit ou de crime sexuel je me suis dit que c'était un sujet dont il fallait s'emparer sans tarder c'est en juin 97..."
• Citation: "...nous avons élaboré un projet de loi qui a été voté vous pourrez comprendre à quel point c'est quand même enfin j'en étais contente en 1 an ça a donné lieu à la loi du 17 juin 1998 sur euh la prévention la répression des infractions sexuelles ainsi qu'à la protection des mineurs victimes."
• Cette loi visait notamment à prévenir et réprimer les infractions sexuelles et à mieux protéger les mineurs victimes. Une circulaire a suivi pour préconiser l'enregistrement des premières déclarations des enfants afin d'éviter qu'ils n'aient à répéter leur traumatisme.
• Citation: "...une circulaire dans laquelle je préconisais je demandais qu'on procède à l'enregistrement des premières déclarations des enfants victimes d'abus sexuel pour qu'il n'ait pas à répéter le récit de leur traumatisme évidemment c'était encore plus douloureux donc voilà alors je pourrais revenir sur le contelé de la loi si vous voulez ce qui me semble intéressant de remarquer parce que c'était c'est assez révélateur de l'état d'esprit de l'époque c'est que cette loi elle est passée inaperçu elle est passée sous les radars médiatiques..."
• Indépendance de la justice et flux d'information sous Mme Guigou: Mme Guigou a mis en place une rupture avec les pratiques antérieures en instaurant une règle stricte de non-interférence politique dans les affaires individuelles. Elle a indiqué que les procureurs généraux étaient encouragés à communiquer les affaires sensibles à la Direction des affaires criminelles et des grâces (DACG), et c'était au directeur de la DACG de décider de la transmission au cabinet du Ministre.
• Citation: "quand je suis arrivée au ministère j'ai dit tout de suite ce ministère ne sera plus le ministère des affaires il sera le ministère du droit et donc j'ai fait savoir publiquement à l'Assemblée au Sénat au conseil des ministres et naturellement au au membres du corps judiciaire et parajudiciaire que désormais nous opérer une rupture nette avec les pratiques qui étaient séculaires quand même de absolument tous les gouvernements précédents..."
• Citation: "j'avais demandé à ce que les rapports arrivent directement à la direction des affaires criminelles et des grâces c'était le directeur qui était chargé d'apprécier si oui ou non ces rapports méritait d'être porté à mon attention c'est-à-dire d'être envoyé ou communiqué ou bien dont la teneur était communiquée aux membres de mon cabinet voilà c'est comme ça que ça se passait..."
• Le cas Caricar et la non-information de Mme Guigou: Mme Guigou a affirmé n'avoir aucun souvenir d'avoir été informée de l'affaire Bétarram (Caricar) à l'époque, malgré la transmission de courriers par le procureur général de Pau à la DACG. Elle a appris l'existence de ces documents récemment, dans le cadre de cette audition et de sollicitations médiatiques.
• Citation: "Je dois vous dire tout de suite que je n'ai aucun souvenir d'avoir été informé de l'affaire de l'institution BRAM Bouquin..."

• Citation: "...dans mon souvenir parce que j'ai certainement eu communication euh on m'a certainement on a dû m'informer en tout cas on a informé la direction des affaires criminales des grasses des enquêtes préliminaires ou des ouvertures d'instruction lorsqu'il y avait les plaintes et lorsqu'on pouvait soupçonner de de teles enfin des infractions à la loi tout simplement notamment lorsqu'il s'agissait de crime mais ne m'était communiqué que les affaires qui pouvaient d'effrayer si vous voulez sur lesquelles j'étais susceptible d'être interrogé en réalité voilà c'est-à-dire soit que il y a un écho médiatique important soit qu' ell elles aient été estimées de nature systémique..."

• Absence d'obligation légale de transmission justice-Éducation Nationale avant 2016: Mme Guigou a expliqué que, selon la loi en vigueur à son époque, il n'était pas possible pour le Ministre de la Justice ou les magistrats de transmettre des informations couvertes par le secret professionnel et le secret de l'instruction au Ministère de l'Éducation Nationale, même en cas de suspicion de violences graves en milieu scolaire. Cette possibilité n'a été introduite qu'avec la loi de 2016 (article 11-2 du Code de procédure pénale), avec des précautions importantes.

• Citation: "je vais malheureusement vous répondre non et ça a été le cas jusque en 2016 jusqu'à une loi de 2016 pourquoi ? parce que en tout cas il ne pouvait pas être question ni pour l'administration du ministère de la justice ni pour mon cabinet ni pour moi de déroger à l'application de la loi et la loi nous imposait à la fois de respecter le secret professionnel s'agissant de moi le secret de l'instruction s'agissant des magistrats et la présomption d'innocence..."

• Citation: "C'est vrai que cette ceci a été assoupli en 2016 donc j'ai j'ai pris connaissance de ça à l'occasion de de cette invitation que vous que vous me faites j'ai recherché comment ça avait évolué et j'ai vu que dans cette loi de 2016 madame Tobira à l'époque et madame Valkassem avait ensemble annoncé que dorén avant il pouvait y avoir dans certaines conditions madame Tobéin insistait sur le respect de la préstation d'innocence il pouvait y avoir communication du ministère de la justice au ministère de l'éducation nationale d'information concernant des enquêtes préliminaires..."

• Rôle et limites des départements en matière de protection de l'enfance: Les représentants de Départements de France ont rappelé que la compétence principale des départements en matière de protection de l'enfance concerne l'intrafamilial. Ils sont responsables des collèges sur les aspects fonctionnels (bâtiments, personnel technique, restauration) et financent les établissements privés sous contrat dans certaines limites.

La protection de l'enfant en danger relève de l'autorité parentale en premier lieu, puis des services départementaux en cas de défaillance.

• Citation: "nous avons la charge des collèges mais mais on est une charge des collèges des départements sur le plan strictement fonctionnel c'est-à-dire c'est le bâtis scolaire ce sont nos personnels techniques et puis la la restauration l'exception des établissements privés sauf exception pour lequel la restauration relève de l'établissement..."
• Citation: "le premier responsable lorsque il n'est pas défaillant et que en l'occurrence c'est le l'autorité parentale est assumée par les départements le premier protecteur de l'enfant c'est le parent et je veux le redire tout simplement donc si un enfant subit des violences au sein d'un établissement scolaire c'est le c'est le détenteur de l'autorité parentale qui doit le protéger en prémilieux parce que c'est lui qui l'exerce..."
• Flux d'information entre l'Éducation Nationale et les départements: Les violences commises par des adultes ayant autorité en milieu scolaire relèvent de la responsabilité de l'Éducation Nationale, qui est censée saisir directement l'autorité judiciaire (signalement Article 40) et en adresser une copie au président du département pour information.
• Citation: "et donc les violences qui font l'objet de cette commission d'enquête ne relèvent pas de la de la compétence des départements puisque nous n'exerçons pas d'autorité sur les personnels d'abord sur les enfants évidemment parce qu'ils ont des parents et en plus sur les personnels de ces établissements quels que soient d'ailleurs les établissements en dehors pour les établissements publics hein..."
• Citation: "en cas de violence l'éducation nationale et les fondé à nous adresser en direct un signalement ou en tout cas un direct en signal à l'autorité judiciaire elle peut saisir elle-même l'autorité judiciaire lorsqu'il y a des faits qui ont été commis par l'enseignant une personne qui est autorité dans l'établissement elle fondé adresser en direct un signalement à l'autorité judiciaire elle doit en adresser une copie au président du département concerné pour son pour son information en tant que chef de fil de la protection de l'enfance..."
• Difficultés et pistes d'amélioration dans la gestion des informations préoccupantes (IP): Les départements constatent une hausse des IP. Il existe une sensibilisation croissante de l'Éducation Nationale aux signalements. Cependant, des difficultés persistent, notamment des délais dans la transmission des informations (parfois transmises juste avant les vacances scolaires) et un manque de clarté pour certains enseignants sur les procédures de signalement (distinction entre Article 40 et IP).
• Citation: "on note une hausse significative en ce moment des informations préoccupantes reçues par les cripes je vous l'ai dit nous avons aussi de plus en plus d'enfants à protéger sans doute qu'il y a une prise de conscience qui est salvatrice mais qui voilà qui qui nécessite une réponse c'est beaucoup plus adapté..."
• Citation: "...est-ce que c'est parce que les enseignants se sentent bien seuls parfois ? est-ce qu'il craent la réaction des parents ou les représaillent lorsqu'il y a un signalement ? donc le signal avant les vacances voilà donc on a signalé cela aussi à l'éducation nationale..."
• Rôle des CRIP en cas d'IP atypique: En cas d'IP reçue par la CRIP concernant une violence en milieu scolaire qui devrait normalement relever de l'Éducation Nationale et de l'Article 40, le département procède en principe à un signalement Article 40 auprès du parquet et informe le DSDEN (ou l'inspection académique). Il y a un dialogue pour vérifier les faits et la connaissance par l'Éducation Nationale. Le rôle du département est aussi de voir si les parents sont informés et en capacité d'agir, et de les accompagner si nécessaire.
• Citation (Florence d'Abin): "...si nous sommes réceptacle d'une information quelle qu'elle soit via la cryppe évidemment ça peut être via la cryppe mais quel qu'elle soit puisque au titre de l'article 40 en tant que fonctionnaire et à forcerie en tant que fonctionnaire départementaux chargé de la protection de l'enfance Nous sommes chargés de signaler au parquet toute information et donc si le cas que vous citez par exemple ce qui se passerait... c'est que le collègue qui reçoit l'information donc à la cri tous les jours toutes les informations qui arrivent sont lues... si c'est urgent on traite en priorité dans dans un délai de 24 heures on va saisir le parquet et donc le professionnel qui verrait ça il appellerait immédiatement l'éducation nationale et il dirait voilà est-ce que vous avez besoin d'un soutien pour formaliser euh le signalement puisque normalement effectivement le signalement doit être formalisé par eux..."
• Besoin de formation et de clarification des procédures: Un besoin de formation des enseignants, particulièrement ceux du premier degré, sur les procédures de signalement et le rôle des différents acteurs a été souligné pour sécuriser les professionnels et améliorer la circulation de l'information.
• Citation (Florence d'Abin): "je vais vous rejoindre madame la rapporteur sur euh l'information ou le besoin de sécuriser aussi les enseignants les professeurs et peut-être différentes lectures à la fois les professeurs du premier degré et les professeurs du second degré... on voit bien qu'il y a une faille... sur le besoin spécifique des enseignants du premer degré à être formé acculturé sur le sujet des informations préoccupantes comment ça doit fonctionner ? Vers qui je me tourne ma chef d'établissement mon chef d'établissement et qu'est-ce qui en découle pour justement éviter ce que pointait le président Sauvadet à savoir l'influx des informations préoccupantes souvent fin juin début juillet..."
• Fragilité de la médecine scolaire: La faiblesse de la médecine scolaire en France a été soulignée comme un enjeu majeur pour le suivi de la santé des enfants et la prévention.

Points de divergence / Nuances:

• Mme Guigou a exprimé sa surprise et son regret de ne pas avoir été informée de l'affaire Caricar à l'époque, tout en réaffirmant que cela ne l'aurait pas conduite à donner d'instructions individuelles mais potentiellement à émettre une circulaire de politique pénale générale sur le sujet.

• Les représentants de Départements de France ont insisté sur le fait que la responsabilité première des violences en milieu scolaire incombe à l'Éducation Nationale, même s'ils agissent en cas d'IP pour ne pas laisser une situation de danger sans réponse.

Questions en suspens / Recommandations implicites:

• Comment assurer une transmission fluide et systématique des informations entre tous les acteurs concernés (Éducation Nationale, justice, départements, familles) en cas de violences en milieu scolaire ?
• Comment mieux former et sécuriser les enseignants dans les procédures de signalement ?
• Comment renforcer la médecine scolaire et la prise en charge de la santé mentale des jeunes ?
• Faut-il revoir ou préciser les textes réglementaires pour clarifier les rôles et obligations de chacun, notamment concernant la transmission d'informations sensibles ? (La loi de 2016 a été un pas, mais son application et ses limites doivent être évaluées).
• Faut-il harmoniser les systèmes d'alerte et de protection en cas de danger dans les établissements scolaires ?

Conclusion:

• Ces auditions ont mis en lumière la complexité des circuits d'information et des responsabilités en matière de violences en milieu scolaire.

Si des progrès ont été réalisés dans la prise de conscience et la réponse judiciaire (loi de 1998, loi de 2016), des dysfonctionnements persistent dans la transmission des informations et la coordination entre les différents acteurs.

Les départements, bien que leur compétence principale soit l'intrafamilial, jouent un rôle essentiel dans la protection de l'enfance et sont souvent en première ligne face aux informations préoccupantes.

Des efforts de formation, de clarification des procédures et de renforcement des liens entre les institutions semblent nécessaires pour mieux protéger les enfants victimes de violences.

Prochaines étapes:

• La commission d'enquête continuera ses travaux en auditionnant d'autres acteurs pour approfondir ces questions et formuler des propositions concrètes.