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  1. May 2024
    1. Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      The authors present an ImageJ Macro GUI tool set for the quantification of one-dimensional repeated patterns that are commonly occurring in microscopy images of muscles.

      Major comments

      In our view the article and also software could be improved in terms of defining the scope of its applicability and user-ship. In many parts the article and software suggest that general biological patterns can be analysed, but then in other parts very specific muscle actin wordings are used. We are pointing this out in the "Minor comments" sections below. We feel that the authors could improve their work by making a clear choice here. One option would be to clearly limit the scope of the tool to the analysis of actin structures in muscles. In this case we would recommend to also rename the tool, e.g. MusclePatternJ. The other option would be to make the tool about the generic analysis of one-dimensional patterns, maybe calling the tool LinePatternJ. In the latter case we would recommend to remove all actin specific wordings from the macro tool set and also the article should be in parts slightly re-written.

      Minor/detailed comments

      Software

      We recommend considering the following suggestions for improving the software.

      File and folder selection dialogs

      In general, clicking on many of the buttons just opens up a file-browser dialog without any further information. For novel users it is not clear what the tool expects one to select here. It would be very good if the software could be rewritten such that there are always clear instructions displayed about which file or folder one should open for the different buttons.

      Extract button

      The tool asks one to specify things like whether selections are drawn "M-line-to-M-line"; for users that are not experts in muscle morphology this is not understandable. It would be great to find more generally applicable formulations.

      Manual selection accuracy

      The 1st step of the analysis is always to start from a user hand-drawn profile across intensity patterns in the image. However, this step can cause inaccuracy that varies with the shape and curve of the line profile drawn. If not strictly perpendicular to for example the M line patterns, the distance between intensity peaks will be different. This will be more problematic when dealing with non-straight and parallelly poised features in the image. If the structure is bended with a curve, the line drawn over it also needs to reproduce this curve, to precisely capture the intensity pattern. I found this limits the reproducibility and easy-usability of the software.

      Reproducibility

      Since the line profile drawn on the image is the first step and very essential to the entire process, it should be considered to save together with the analysis result. For example, as ImageJ ROI or ROIset files that can be re-imported, correctly positioned, and visualized in the measured images. This would greatly improve the reproducibility of the proposed workflow. In the manuscript, only the extracted features are being saved (because the save button is also just asking for a folder containing images, so I cannot verify its functionality).

      ? button

      It would be great if that button would open up some usage instructions.

      Easy improvement of workflow

      I would suggest a reasonable expansion of the current workflow, by fitting and displaying 2D lines to the band or line structure in the image, that form the "patterns" the author aims to address. Thus, it extracts geometry models from the image, and the inter-line distance, and even the curve formed by these sets of lines can be further analyzed and studied. These fitted 2D lines can be also well integrated into ImageJ as Line ROI, and thus be saved, imported back, and checked or being further modified. I think this can largely increase the usefulness and reproducibility of the software.

      Manuscript

      We recommend considering the following suggestions for improving the manuscript. Abstract: The abstract suggests that general patterns can be quantified, however the actual tool quantifies specific subtypes of one-dimensional patterns. We recommend adapting the abstract accordingly.

      Line 58: Gray-level co-occurrence matrix (GLCM) based feature extraction and analysis approach is not mentioned nor compared. At least there's a relatively recent study on Sarcomeres structure based on GLCM feature extraction: https://github.com/steinjm/SotaTool with publication: https://doi.org/10.1002/cpz1.462

      Line 75: "...these simple geometrical features will address most quantitative needs..." We feel that this may be an overstatement, e.g. we can imagine that there should be many relevant two-dimensional patterns in biology?!

      Line 83: "After a straightforward installation by the user, ...". We think it would be convenient to add the installation steps at this place into the manuscript.

      Line 87: "Multicolor images will give a graph with one profile per color." The 'Multicolor images' here should be more precisely stated as "multi-channel" images. Multi-color images could be confused with RGB images which will be treated as 8-bit gray value (type conversion first) images by profile plot in ImageJ.

      Line 92: "...such as individual bands, blocks, or sarcomeric actin...". While bands and blocks are generic pattern terms, the biological term "sarcomeric actin" does not seem to fit in this list. Could a more generic wording be found, such as "block with spike"?

      Line 95: "the algorithm defines one pattern by having the features of highest intensity in its centre". Could this be rephrased? We did not understand what that exactly means.

      Line 124 - 147: This part the only description of the algorithm behind the feature extraction and analysis, but not clearly stated. Many details are missing or assumed known by the reader. For example, how it achieved sub-pixel resolution results is not clear. One can only assume that by fitting Gaussian to the band, the center position (peak) thus can be calculated from continuous curves other than pixels.

      Line 407: We think the availability of both the tool and the code could be improved. For Fiji tools it is common practice to create an Update Site and to make the code available on GitHub. In addition, downloading the example file (https://drive.google.com/file/d/1eMazyQJlisWPwmozvyb8VPVbfAgaH7Hz/view?usp=drive_link) required a Google login and access request, which is not very convenient; in fact, we asked for access but it was denied. It would be important for the download to be easier, e.g. from GitHub or Zenodo.

      Significance

      The strength of this study is that a tool for the analysis of one-dimensional repeated patterns occurring in muscle fibres is made available in the accessible open-source platform ImageJ/Fiji. In the introduction to the article the authors provide an extensive review of comparable existing tools. Their new tool fills a gap in terms of providing an easy-to-use software for users without computational skills that enables the analysis of muscle sarcomere patterns. We feel that if the below mentioned limitations could be addressed the tool could indeed be valuable to life scientists interested in muscle patterning without computational skills.

      In our view there are a few limitations, including the accessibility of example data and tutorials at sites.google.com/view/patternj, which we had trouble to access. In addition, we think that the workflow in Fiji, which currently requires pressing several buttons in the correct order, could be further simplified and streamlined by adopting some "wizard" approach, where the user is guided through the steps. Another limitation is the reproducibility of the analysis; here we recommend enabling IJ Macro recording as well as saving of the drawn line ROIs. For more detailed suggestions for improvements please see the above sections of our review.

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    1. Author response:

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

      eLife assessment

      The authors discuss an effect, "diffusive lensing", by which particles would accumulate in high-viscosity regions, for instance in the intracellular medium. To obtain these results, the authors rely on agent-based simulations using custom rules performed with the Ito stochastic calculus convention. The "lensing effect" discussed is a direct consequence of the choice of the Ito convention without spurious drift which has been discussed before and is likely to be inadequate for the intracellular medium, causing the presented results to likely have little relevance for biology.

      We thank the editors and the reviewers for their consideration of our manuscript. We argue in this rebuttal and revision that our results and conclusions are in fact likely to have relevance for biology. While we use the Itô convention for ease of modeling considering its non-anticipatory nature upon discretization (see (Volpe and Wehr 2016) for the discretization schemes), we refer to Figure S1B to emphasize that diffusive lensing occurs not only under the Itô convention but across a wide parameter space. Indeed, it is absent only in the normative isothermal convention; note that even a stochastic differential equation conforming to the isothermal convention may be reformulated into the Itô convention by adding suitable drift terms, allowing for diffusive lensing to be seen even in case of the isothermal convention. We note in particular that the choice of the convention is a highly context-dependent one (Sokolov 2010); there is not a universally correct choice, and one can obtain stochastic differential equations consistent with Ito or Stratonovich interpretations in different regimes. Lastly, space-dependent diffusivity is now an experimentally well-recognized feature of the cellular interior, as noted in our references and as discussed further later in this response. This fact points towards the potential relevance of our model for subcellular diffusion.

      In our revised preprint, we have made changes to the text and minor changes to figures to address reviewer concerns.

      Responses to the Reviewers

      We thank the reviewers for their feedback and address the issues they raised in this rebuttal and in the revised manuscript. The central point that the reviewers raise concerns the validity of the drift-less Itô interpretation in modeling potential nonequilibrium types of subcellular transport arising from space-dependent diffusivity. If the drift term were considered, the resulting stochastic differential equation stochastic differential equation (SDE) is equivalent to one arising from the isothermal interpretation of heterogeneous diffusivity (Volpe and Wehr 2016), wherein no diffusive lensing is seen (as shown in Fig. S1B). That is, the isothermal interpretation and the drift-comprising Itô SDE produce the same uniform steady-state particle densities.

      While we agree with the reviewers that for a given interpretation, equivalent stochastic differential equations (SDEs) arising from other interpretations may be drawn, we disagree with the generalization that all types of subcellular diffusion conform to the isothermal interpretation. That is, there is no reason why any and all instances of nonequilibrium subcellular particle diffusion must be modeled using isothermal-conforming SDEs (such as the drift-comprising Itô SDE, for instance). We refer to (Sokolov 2010) which prescribes choosing a convention in a context-dependent manner. In this regard, we disagree with the second reviewer’s characterization of making such a choice merely a “choice of writing” considering that it is entirely dependent on the choice of microscopic parameters, as detailed in the discussion section of the manuscript. The following references have also been added to the manuscript: the reference from the first reviewer (Kupferman et al. 2004) proposes a prescription for choosing an appropriate convention based upon comparing the noise correlation time and the particle relaxation time. The reference notes that the Itô convention is appropriate when the particle relaxation time is large when compared to the noise correlation time and the Stratonovich convention is appropriate in the converse scenario. In (Rupprecht et al. 2018), active noise is considered and the resulting Fokker-Planck equation conforms to the Stratonovich convention when thermal noise was negligible. The related reference, (Vishen et al. 2019) compares three timescales: those of particle relaxation, noise correlation and viscoelastic relaxation, to make the choice. Indeed, as noted in the manuscript, lensing is seen in all but one interpretation (without drift additions); only its magnitude is altered by the interpretation/choice of the drift term. The appendix has been modified to include a subsection on the interchangeability of the conventions.

      Separately, with regards to the discussion on anomalous diffusion, the section on mean squared displacement calculation has been amended to avoid confusing our model with canonical anomalous diffusion which considers the anomalous exponent; how the anomalous exponent varies with space-dependent diffusivity offers an interesting future area of study.

      Responses to specific reviewer comments appear below.

      Reviewer #1 (Public Review):

      The manuscript "Diffusive lensing as a mechanism of intracellular transport and compartmentalization", explores the implications of heterogeneous viscosity on the diffusive dynamics of particles. The authors analyze three different scenarios:

      (i)   diffusion under a gradient of viscosity,

      (ii)  clustering of interacting particles in a viscosity gradient, and

      (iii) diffusive dynamics of non-interacting particles with circular patches of heterogeneous viscous medium.

      The implications of a heterogeneous environment on phase separation and reaction kinetics in cells are under-explored. This makes the general theme of this manuscript very relevant and interesting. However, the analysis in the manuscript is not rigorous, and the claims in the abstract are not supported by the analysis in the main text.

      Following are my main comments on the work presented in this manuscript:

      (a) The central theme of this work is that spatially varying viscosity leads to position-dependent diffusion constant. This, for an overdamped Langevin dynamics with Gaussian white noise, leads to the well-known issue of the interpretation of the noise term.

      The authors use the Ito interpretation of the noise term because their system is non-equilibrium.

      One of the main criticisms I have is on this central point. The issue of interpretation arises only when there are ill-posed stochastic dynamics that do not have the relevant timescales required to analyze the noise term properly. Hence, if the authors want to start with an ill-posed equation it should be mentioned at the start. At least the Langevin dynamics considered should be explicitly mentioned in the main text. Since this work claims to be relevant to biological systems, it is also of significance to highlight the motivation for using the ill-posed equation rather than a well-posed equation. The authors refer to the non-equilibrium nature of the dynamics but it is not mentioned what non-equilibrium dynamics to authors have in mind. To properly analyze an overdamped Langevin dynamics a clear source of integrated timescales must be provided. As an example, one can write the dynamics as Eq. (1) \dot x = f(x) + g(x) \eta , which is ill-defined if the noise \eta is delta correlated in time but well-defined when \eta is exponentially correlated in time. One can of course look at the limit in which the exponential correlation goes to a delta correlation which leads to Eq. (1) interpreted in Stratonovich convention. The choice to use the Ito convention for Eq. (1) in this case is not justified.

      We thank the reviewer for detailing their concerns with our model’s assumptions. We have addressed them in the common rebuttal.

      (b) Generally, the manuscript talks of viscosity gradient but the equations deal with diffusion which is a combination of viscosity, temperature, particle size, and particle-medium interaction. There is no clear motivation provided for focus on viscosity (cytoplasm as such is a complex fluid) instead of just saying position-dependent diffusion constant. Maybe authors should use viscosity only when talking of a context where the existence of a viscosity gradient is established either in a real experiment or in a thought experiment.

      The manuscript has been amended to use only “diffusivity” to avoid confusion.

      (c) The section "Viscophoresis drives particle accumulation" seems to not have new results. Fig. 1 verifies the numerical code used to obtain the results in the later sections. If that is the case maybe this section can be moved to supplementary or at least it should be clearly stated that this is to establish the correctness of the simulation method. It would also be nice to comment a bit more on the choice of simulation methods with changing hopping sizes instead of, for example, numerically solving stochastic ODE.

      The main point of this section and of Fig. 1 is the diffusive lensing effect itself: the accumulation of particles in lower-diffusivity areas. To the best of our knowledge, diffusive lensing has not been reported elsewhere as a specific outcome of non-isothermal interpretations of diffusion, with potential relevance to nonequilibrium subcellular motilities. The simulation method has been fully described in the Methods section, and the code has also been shared (see Code Availability).

      A minor comment, the statement "the physically appropriate convention to use depends upon microscopic parameters and timescale hierarchies not captured in a coarse-grained model of diffusion." is not true as is noted in the references that authors mention, a correct coarse-grained model provides a suitable convention (see also Phys. Rev. E, 70(3), 036120., Phys. Rev. E, 100(6), 062602.).

      This has been addressed in the common rebuttal.

      (d) The section "Interaction-mediated clustering is affected by viscophoresis" makes an interesting statement about the positioning of clusters by a viscous gradient. As a theoretical calculation, the interplay between position-dependent diffusivity and phase separation is indeed interesting, but the problem needs more analysis than that offered in this manuscript. Just a plot showing clustering with and without a gradient of diffusion does not give enough insight into the interplay between density-dependent diffusion and position-dependent diffusion. A phase plot that somehow shows the relative contribution of the two effects would have been nice. Also, it should be emphasized in the main text that the inter-particle interaction is through a density-dependent diffusion constant and not a conservative coupling by an interaction potential.

      The density-dependence has been added from the Methods to the main text. The goal of the work is to present lensing as a natural outcome of the parameter choices we make and present its effects as they relate to clustering and commonly used biophysical methods to probe dynamics within cells. A dense sampling of the phase space and how it is altered as a function of diffusivity, and the subsequent interpretation, lie beyond the scope of the present work but offer exciting future directions of study.

      (e) The section "In silico microrheology shows that viscophoresis manifests as anomalous diffusion" the authors show that the MSD with and without spatial heterogeneity is different. This is not a surprise - as the underlying equations are different the MSD should be different.

      The goal here is to compare and contrast the ways in which homogeneous and heterogeneous diffusion manifest in simulated microrheology measurements. We hope that an altered saturation MSD, as is observed in our simulations, provokes interest in considering lensing while modeling experimental data.

      There are various analogies drawn in this section without any justification:

      (i) "the saturation MSD was higher than what was seen in the homogeneous diffusion scenario possibly due to particles robustly populating the bulk milieu followed by directed motion into the viscous zone (similar to that of a Brownian ratchet, (Peskin et al., 1993))."

      In case of i), the Brownian ratchet is invoked as a model to explain directed accumulation. We have removed this analogy to avoid confusion as it is not delved into further over the course of our work.

      (ii) "Note that lensing may cause particle displacements to deviate from a Gaussian distribution, which could explain anomalous behaviors observed both in our simulations and in experiments in cells (Parry et al., 2014)." Since the full trajectory of the particles is available, it can be analyzed to check if this is indeed the case.

      This has been addressed in the common rebuttal.

      (f) The final section "In silico FRAP in a heterogeneously viscous environment ... " studies the MSD of the particles in a medium with heterogeneous viscous patches which I find the most novel section of the work. As with the section on inter-particle interaction, this needs further analysis.

      We thank the reviewer for their appreciation. In presenting these three sections discussing the effects of diffusive lensing, we intend to broadly outline the scope of this phenomenon in influencing a range of behaviors. Exploring the directions further comprise promising future directions of study that lie beyond the scope of this manuscript.

      To summarise, as this is a theory paper, just showing MSD or in silico FRAP data is not sufficient. Unlike experiments where one is trying to understand the systems, here one has full access to the dynamics either analytically or in simulation. So just stating that the MSD in heterogeneous and homogeneous environments are not the same is not sufficient. With further analysis, this work can be of theoretical interest. Finally, just as a matter of personal taste, I am not in favor of the analogy with optical lensing. I don't see the connection.

      We value the reviewer’s interest in investigating the causes underlying the differences in the MSDs and agree that it represents a promising future area of study. The main point of this section of the manuscript was to make a connection to experimentally measurable quantities.

      Reviewer #2 (Public Review):

      Summary:

      The authors study through theory and simulations the diffusion of microscopic particles and aim to account for the effects of inhomogeneous viscosity and diffusion - in particular regarding the intracellular environment. They propose a mechanism, termed "Diffusive lensing", by which particles are attracted towards high-viscosity regions where they remain trapped. To obtain these results, the authors rely on agent-based simulations using custom rules performed with the Ito stochastic calculus convention, without spurious drift. They acknowledge the fact that this convention does not describe equilibrium systems, and that their results would not hold at equilibrium - and discard these facts by invoking the fact that cells are out-of-equilibrium. Finally, they show some applications of their findings, in particular enhanced clustering in the high-viscosity regions. The authors conclude that as inhomogeneous diffusion is ubiquitous in life, so must their mechanism be, and hence it must be important.

      Strengths:

      The article is well-written, and clearly intelligible, its hypotheses are stated relatively clearly and the models and mathematical derivations are compatible with these hypotheses.

      We thank the reviewer for their appreciation.

      Weaknesses:

      The main problem of the paper is these hypotheses. Indeed, it all relies on the Ito interpretation of the stochastic integrals. Stochastic conventions are a notoriously tricky business, but they are both mathematically and physically well-understood and do not result in any "dilemma" [some citations in the article, such as (Lau and Lubensky) and (Volpe and Wehr), make an unambiguous resolution of these]. Conventions are not an intrinsic, fixed property of a system, but a choice of writing; however, whenever going from one to another, one must include a "spurious drift" that compensates for the effect of this change - a mathematical subtlety that is entirely omitted in the article: if the drift is zero in one convention, it will thus be non-zero in another in the presence of diffusive gradients. It is well established that for equilibrium systems obeying fluctuation-dissipation, the spurious drift vanishes in the anti-Ito stochastic convention (which is not "anticipatory", contrarily to claims in the article, are the "steps" are local and infinitesimal). This ensures that the diffusion gradients do not induce currents and probability gradients, and thus that the steady-state PDF is the Gibbs measure. This equilibrium case should be seen as the default: a thermal system NOT obeying this law should warrant a strong justification (for instance in the Volpe and Wehr review this can occur through memory effects in robotic dynamics, or through strong fluctuation-dissipation breakdown). In near-equilibrium thermal systems such as the intracellular medium (where, although out-of-equilibrium, temperature remains a relevant and mostly homogeneous quantity), deviations from this behavior must be physically justified and go to zero when going towards equilibrium.

      Considering that the physical phenomena underlying diffusion span a range of timescales (particle relaxation, noise, environmental correlation, et cetera), we disagree with the assertion that all types of subcellular diffusion processes can be modeled as occurring at thermal equilibrium: for example, one can easily imagine memory effects arising in the presence of an appropriate hierarchy of timescales. We have added references that describe in more detail the way in which the comparison of timescales can dictate the applicability of different conventions. We also refer the referee to the common rebuttal section of our response in which we discuss factors that govern the choice of the interpretation. The adiabatic elimination arguments highlighted in (Kupferman et al. 2004) provide a clear description of how relevant particle and environment-related timescales can inform the choice of stochastic calculus to use.

      With regards to the use of the term “anticipatory” to refer to the isothermal interpretation, we refer to the comment in (Volpe and Wehr 2016) of the Itô interpretation “not looking into the future”. In any case, whether anticipatory or otherwise, the interpretation’s effect on our model remains unchanged, as highlighted in the section in the Appendix on the conversion between different conventions; this section has been added to minimize confusion about the effects of the choice of convention on lensing.

      Here, drifts are arbitrarily set to zero in the Ito convention (the exact opposite of the equilibrium anti-Ito), which is the equilibrium equivalent to adding a force (with drift $- grad D$) exactly compensating the spurious drift. If we were to interpret this as a breakdown of detailed balance with inhomogeneous temperature, the "hot" region would be effectively at 4x higher temperature than the cold region (i.e. 1200K) in Fig 1A.

      Our work is based on existing observations of space-dependent diffusivity in cells (Garner et al., 2023; Huang et al., 2021; Parry et al., 2014; Śmigiel et al., 2022; Xiang et al., 2020). These papers support a definitive model for the existence of space-dependent diffusivity without invoking space-dependent temperature.

      It is the effects of this arbitrary force (exactly compensating the Ito spurious drift) that are studied in the article. The fact that it results in probability gradients is trivial once formulated this way (and in no way is this new - many of the references, for instance, Volpe and Wehr, mention this).

      Addressed in the common rebuttal.

      Enhanced clustering is also a trivial effect of this probability gradient (the local concentration is increased by this force field, so phase separation can occur). As a side note the "neighbor sensing" scheme to describe interactions is very peculiar and not physically motivated - it violates stochastic thermodynamics laws too, as the detailed balance is apparently not respected.

      The neighbor-sensing scheme used here is just one possible model of an effective attractive potential between particles. Other models that lead to density-dependent attraction between particles should also provide qualitatively similar results as ours; this offers an interesting prospect for future research.

      Finally, the "anomalous diffusion" discussion is at odds with what the literature on this subject considers anomalous (the exponent does not appear anomalous).

      This has been addressed in the common rebuttal, and the relevant part of the manuscript has been modified to avoid confusion.

      The authors make no further justification of their choice of convention than the fact that cells are out-of-equilibrium, leaving the feeling that this is a detail. They make mentions of systems (eg glycogen, prebiotic environment) for which (near-)equilibrium physics should mostly prevail, and of fluctuation-dissipation ("Diffusivity varies inversely with viscosity", in the introduction). Yet the "phenomenon" they discuss is entirely reliant on an undiscussed mechanism by which these assumptions would be completely violated (the citations they make for this - Gnesotto '18 and Phillips '12 - are simply discussions of the fact that cells are out-of-equilibrium, not on any consequences on the convention).

      Finally, while inhomogeneous diffusion is ubiquitous, the strength of this effect in realistic conditions is not discussed (this would be a significant problem if the effect were real, which it isn't). Gravitational attraction is also an ubiquitous effect, but it is not important for intracellular compartmentalization.

      The manuscript text has been supplemented with additional references that detail the ways in which the comparison of timescales can dictate how one can apply different conventions. We refer the reviewer to the common rebuttal section of our response where we detail factors that dictate the choice of the convention to use. As previously noted, the adiabatic elimination arguments highlighted in (Kupferman et al., 2004) provide a prescription for how different timescales are to be considered in deciding the choice of stochastic calculus to use.

      With regards to the strength of space-dependent diffusivity in subcellular milieu, various measurements of heterogeneous diffusivity have been made both across different model systems and via different modalities, as cited in our manuscript. (Garner et al. 2023) used single-particle tracking to determine over 100-fold variability in diffusivity within individual S. pombe cells. Single-molecule measurements in (Xiang et al. 2020) and (Śmigiel et al. 2022) reveal an order-of-magnitude variation in tracer diffusion in mammalian cells and multi-fold variation in E. coli cytoplasm respectively. Fluorescence correlation spectroscopy measurements in (Huang et al. 2022) have found a two-fold increase in short-range diffusion of protein-sized tracers in X. laevis extracts. We have also added a reference to a study that uses 3D single particle tracking in the cytosol of a multinucleate fungus, A. gossypii, to identify regions of low-diffusivity near nuclei and hyphal tips (McLaughlin et al. 2020). Many of these references deploy particle tracking and investigate how mesoscale-sized particles (i.e. tracers spanning biologically relevant size scales) are directly impacted by space-dependent diffusivity. Therefore, we base our model on not only space-dependent diffusivity being a well-recognized feature of the cellular interior, but also on these observations pertaining to mesoscale-sized particles’ motion along relevant timescales.

      These measurements are also relevant to the reviewer’s question about the strength of the effect, which depends directly on the variability in diffusivity: for ten- or a hundred-fold diffusivity variations, the effect would be expected to be significant. In case of using the Itô convention directly, the contrast in concentration gradient is, in fact, that of the diffusivity gradient.

      To conclude, the "diffusive lensing" effect presented here is not a deep physical discovery, but a well-known effect of sticking to the wrong stochastic convention.

      As detailed in the various responses above, we respectfully disagree with the notion that there exists a singular correct stochastic convention that is applicable for all cases of subcellular heterogeneous diffusion. Further, as detailed in (Volpe and Wehr 2016) and as detailed in the Appendix, it is possible to convert between conventions and that an isothermal-abiding stochastic differential equation may be suitably altered, by means of adding a drift term, to an Itô-abiding stochastic differential equation; therefore, one can observe diffusive lensing without discarding the isothermal convention if the latter were modified. Indeed, it is only the driftless (or canonical) isothermal convention that does not allow for diffusive lensing.

    1. Author response:

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

      Reviewer #1: 

      This is my first review of the article entitled "The canonical stopping network: Revisiting the role of the subcortex in response inhibition" by Isherwood and colleagues. This study is one in a series of excellent papers by the Forstmann group focusing on the ability of fMRI to reliably detect activity in small subcortical nuclei - in this case, specifically those purportedly involved in the hyper- and indirect inhibitory basal ganglia pathways. I have been very fond of this work for a long time, beginning with the demonstration of De Hollander, Forstmann et al. (HBM 2017) of the fact that 3T fMRI imaging (as well as many 7T imaging sequences) do not afford sufficient signal to noise ratio to reliably image these small subcortical nuclei. This work has done a lot to reshape my view of seminal past studies of subcortical activity during inhibitory control, including some that have several thousand citations.

      In the current study, the authors compiled five datasets that aimed to investigate neural activity associated with stopping an already initiated action, as operationalized in the classic stop-signal paradigm. Three of these datasets are taken from their own 7T investigations, and two are datasets from the Poldrack group, which used 3T fMRI.

      The authors make six chief points: 

      (1) There does not seem to be a measurable BOLD response in the purportedly critical subcortical areas in contrasts of successful stopping (SS) vs. going (GO), neither across datasets nor within each individual dataset. This includes the STN but also any other areas of the indirect and hyperdirect pathways.

      (2) The failed-stop (FS) vs. GO contrast is the only contrast showing substantial differences in those nodes.

      (3) The positive findings of STN (and other subcortical) activation during the SS vs. GO contrast could be due to the usage of inappropriate smoothing kernels.

      (4) The study demonstrates the utility of aggregating publicly available fMRI data from similar cognitive tasks. 

      (5) From the abstract: "The findings challenge previous functional magnetic resonance (fMRI) of the stop-signal task" 

      (6) and further: "suggest the need to ascribe a separate function to these networks." 

      I strongly and emphatically agree with points 1-5. However, I vehemently disagree with point 6, which appears to be the main thrust of the current paper, based on the discussion, abstract, and - not least - the title.

      To me, this paper essentially shows that fMRI is ill-suited to study the subcortex in the specific context of the stop-signal task. That is not just because of the issues of subcortical small-volume SNR (the main topic of this and related works by this outstanding group), but also because of its limited temporal resolution (which is unacknowledged, but especially impactful in the context of the stop-signal task). I'll expand on what I mean in the following.

      First, the authors are underrepresenting the non-fMRI evidence in favor of the involvement of the subthalamic nucleus (STN) and the basal ganglia more generally in stopping actions. 

      - There are many more intracranial local field potential recording studies that show increased STN LFP (or even single-unit) activity in the SS vs. FS and SS vs. GO contrast than listed, which come from at least seven different labs. Here's a (likely non-exhaustive) list of studies that come to mind:

      Ray et al., NeuroImage 2012 <br /> Alegre et al., Experimental Brain Research 2013 <br /> Benis et al., NeuroImage 2014 <br /> Wessel et al., Movement Disorders 2016 <br /> Benis et al., Cortex 2016 <br /> Fischer et al., eLife 2017 <br /> Ghahremani et al., Brain and Language 2018 <br /> Chen et al., Neuron 2020 <br /> Mosher et al., Neuron 2021 <br /> Diesburg et al., eLife 2021 

      - Similarly, there is much more evidence than cited that causally influencing STN via deep-brain stimulation also influences action-stopping. Again, the following list is probably incomplete: 

      Van den Wildenberg et al., JoCN 2006 <br /> Ray et al., Neuropsychologia 2009 <br /> Hershey et al., Brain 2010 <br /> Swann et al., JNeuro 2011 <br /> Mirabella et al., Cerebral Cortex 2012 <br /> Obeso et al., Exp. Brain Res. 2013 <br /> Georgiev et al., Exp Br Res 2016 <br /> Lofredi et al., Brain 2021 <br /> van den Wildenberg et al, Behav Brain Res 2021 <br /> Wessel et al., Current Biology 2022 

      - Moreover, evidence from non-human animals similarly suggests critical STN involvement in action stopping, e.g.: 

      Eagle et al., Cerebral Cortex 2008 <br /> Schmidt et al., Nature Neuroscience 2013 <br /> Fife et al., eLife 2017 <br /> Anderson et al., Brain Res 2020 

      Together, studies like these provide either causal evidence for STN involvement via direct electrical stimulation of the nucleus or provide direct recordings of its local field potential activity during stopping. This is not to mention the extensive evidence for the involvement of the STN - and the indirect and hyperdirect pathways in general - in motor inhibition more broadly, perhaps best illustrated by their damage leading to (hemi)ballism. 

      Hence, I cannot agree with the idea that the current set of findings "suggest the need to ascribe a separate function to these networks", as suggested in the abstract and further explicated in the discussion of the current paper. For this to be the case, we would need to disregard more than a decade's worth of direct recording studies of the STN in favor of a remote measurement of the BOLD response using (provably) sub ideal imaging parameters. There are myriads of explanations of why fMRI may not be able to reveal a potential ground-truth difference in STN activity between the SS and FS/GO conditions, beginning with the simple proposition that it may not afford sufficient SNR, or that perhaps subcortical BOLD is not tightly related to the type of neurophysiological activity that distinguishes these conditions (in the purported case of the stop-signal task, specifically the beta band). But essentially, this paper shows that a specific lens into subcortical activity is likely broken, but then also suggests dismissing existing evidence from superior lenses in favor of the findings from the 'broken' lens. That doesn't make much sense to me.

      Second, there is actually another substantial reason why fMRI may indeed be unsuitable to study STN activity, specifically in the stop-signal paradigm: its limited time resolution. The sequence of subcortical processes on each specific trial type in the stop-signal task is purportedly as follows: at baseline, the basal ganglia exert inhibition on the motor system. During motor initiation, this inhibition is lifted via direct pathway innervation. This is when the three trial types start diverging. When actions then have to be rapidly cancelled (SS and FS), cortical regions signal to STN via the hyperdirect pathway that inhibition has to be rapidly reinstated (see Chen, Starr et al., Neuron 2020 for direct evidence for such a monosynaptic hyperdirect pathway, the speed of which directly predicts SSRT). Hence, inhibition is reinstated (too late in the case of FS trials, but early enough in SS trials, see recordings from the BG in Schmidt, Berke et al., Nature Neuroscience 2013; and Diesburg, Wessel et al., eLife 2021). 

      Hence, according to this prevailing model, all three trial types involve a sequence of STN activation (initial inhibition), STN deactivation (disinhibition during GO), and STN reactivation (reinstantiation of inhibition during the response via the hyperdirect pathway on SS/FS trials, reinstantiation of inhibition via the indirect pathway after the response on GO trials). What distinguishes the trial types during this period is chiefly the relative timing of the inhibitory process (earliest on SS trials, slightly later on FS trials, latest on GO trials). However, these temporal differences play out on a level of hundreds of milliseconds, and in all three cases, processing concludes well under a second overall. To fMRI, given its limited time resolution, these activations are bound to look quite similar. 

      Lastly, further building on this logic, it's not surprising that FS trials yield increased activity compared to SS and GO trials. That's because FS trials are errors, which are known to activate the STN (Cavanagh et al., JoCN 2014; Siegert et al. Cortex 2014) and afford additional inhibition of the motor system after their occurrence (Guan et al., JNeuro 2022). Again, fMRI will likely conflate this activity with the abovementioned sequence, resulting in a summation of activity and the highest level of BOLD for FS trials. 

      In sum, I believe this study has a lot of merit in demonstrating that fMRI is ill-suited to study the subcortex during the SST, but I cannot agree that it warrants any reappreciation of the subcortex's role in stopping, which are not chiefly based on fMRI evidence. 

      We would like to thank reviewer 1 for their insightful and helpful comments. We have responded point-by-point below and will give an overview of how we reframed the paper here.  

      We agree that there is good evidence from other sources for the presence of the canonical stopping network (indirect and hyperdirect) during action cancellation, and that this should be reflected more in the paper. However, we do not believe that a lack of evidence for this network during the SST makes fMRI ill-suited for studying this task, or other tasks that have neural processes occurring in quick succession. What we believe the activation patterns of fMRI reflect during this task, is the large of amount of activation caused by failed stops. That is, that the role of the STN in error processing may be more pronounced that its role in action cancellation. Due to the replicability of fMRI results, especially at higher field strengths, we believe the activation profile of failed stop trials reflects a paramount role for the STN in error processing. Therefore, while we agree we do not provide evidence against the role of the STN in action cancellation, we do provide evidence that our outlook on subcortical activation during different trial types of this task should be revisited. We have reframed the article to reflect this, and discuss points such as fMRI reliability, validity and the complex overlapping of cognitive processes in the SST in the discussion. Please see all changes to the article indicated by red text.

      A few other points: 

      - As I said before, this team's previous work has done a lot to convince me that 3T fMRI is unsuitable to study the STN. As such, it would have been nice to see a combination of the subsamples of the study that DID use imaging protocols and field strengths suitable to actually study this node. This is especially true since the second 3T sample (and arguably, the Isherwood_7T sample) does not afford a lot of trials per subject, to begin with.

      Unfortunately, this study already comprises of the only 7T open access datasets available for the SST. Therefore, unless we combined only the deHollander_7T and Miletic_7T subsamples there is no additional analysis we can do for this right now. While looking at just the sub samples that were 7T and had >300 trials would be interesting, based on the new framing of the paper we do not believe it adds to the study, as the sub samples still lack the temporal resolution seemingly required for looking at the processes in the SST.

      - What was the GLM analysis time-locked to on SS and FS trials? The stop-signal or the GO-signal? 

      SS and FS trials were time-locked to the GO signal as this is standard practice. The main reason for this is that we use contrasts to interpret differences in activation patterns between conditions. By time-locking the FS and SS trials to the stop signal, we are contrasting events at different time points, and therefore different stages of processing, which introduces its own sources of error. We agree with the reviewer, however, that a separate analysis with time-locking on the stop-signal has its own merit, and now include results in the supplementary material where the FS and SS trials are time-locked to the stop signal as well.

      - Why was SSRT calculated using the outdated mean method? 

      We originally calculated SSRT using the mean method as this was how it was reported in the oldest of the aggregated studies. We have now re-calculated the SSRTs using the integration method with go omission replacement and thank the reviewer for pointing this out. Please see response to comment 3.

      - The authors chose 3.1 as a z-score to "ensure conservatism", but since they are essentially trying to prove the null hypothesis that there is no increased STN activity on SS trials, I would suggest erring on the side of a more lenient threshold to avoid type-2 error. 

      We have used minimum FDR-corrected thresholds for each contrast now, instead of using a blanket conservative threshold of 3.1 over all contrasts. The new thresholds for each contrast are shown in text. Please see below (page 12):

      “The thresholds for each contrast are as follows: 3.01 for FS > GO, 2.26 for FS > SS and 3.1 for SS > GO.”

      - The authors state that "The results presented here add to a growing literature exposing inconsistencies in our understanding of the networks underlying successful response inhibition". It would be helpful if the authors cited these studies and what those inconsistencies are. 

      We thank reviewer 1 for their detailed and thorough evaluation of our paper. Overall, we agree that there is substantial direct and indirect evidence for the involvement of the cortico-basal-ganglia pathways in response inhibition. We have taken the vast constructive criticism on board and agree with the reviewer that the paper should be reframed. We would like to thank the reviewer for the thoroughness of their helpful comments aiding the revising of the paper.

      (1) I would suggest reframing the study, abstract, discussion, and title to reflect the fact that the study shows that fMRI is unsuitable to study subcortical activity in the SST, rather than the fact that we need to question the subcortical model of inhibition, given the reasons in my public review.

      We agree with the reviewer that the article should be reframed and not taken as direct evidence against the large sum of literature pointing towards the involvement of the cortico-basal-ganglia pathway in response inhibition. We have significantly rewritten the article in light of this.

      (2) I suggest combining the datasets that provide the best imaging parameters and then analyzing the subcortical ROIs with a more lenient threshold and with regressors time-locked to the stop-signals (if that's not already the case). This would make the claim of a null finding much more impactful. Some sort of power analysis and/or Bayes factor analysis of evidence for the null would also be appreciated. 

      Instead of using a blanket conservative threshold of 3.1, we instead used only FDR-corrected thresholds. The threshold level is therefore different for each contrast and noted in the figures. We have also added supplementary figures including the group-level SPMs and ROI analyses when the FS and SS trials were time-locked to the stop signal instead of the GO signal (Supplementary Figs 4 & 5). But as mentioned above, due to the difference in time points when contrasting, we believe that time-locking to the GO signal for all trial types makes more sense for the main analysis.

      We have now also computed BFs on the first level ROI beta estimates for all contrasts using the BayesFactor package as implemented in R. We add the following section to the methods and updated the results section accordingly (page 8):

      “In addition to the frequentist analysis we also opted to compute Bayes Factors (BFs) for each contrast per ROI per hemisphere. To do this, we extracted the beta weights for each individual trial type from our first level model. We then compared the beta weights from each trial type to one another using the ‘BayesFactor’ package as implement in R (Morey & Rouder, 2015). We compared the full model comprising of trial type, dataset and subject as predictors to the null model comprising of only the dataset and subject as predictor. The datasets and subjects were modeled as random factors. We divided the resultant BFs from the full model by the null model to provide evidence for or against a significant difference in beta weights for each trial type. To interpret the BFs, we used a modified version of Jeffreys’ scale (Jeffreys, 1939; Lee & Wagenmakers, 2014).”

      (3) I suggest calculating SSRT using the integration method with the replacement of Go omissions, as per the most recent recommendation (Verbruggen et al., eLife 2019).

      We agree we should have used a more optimal method for SSRT estimation. We have replaced our original estimations with that of the integration method with go omissions replacement, as suggested and adapted the results in table 3.

      We have also replaced text in the methods sections to reflect this (page 5):

      “For each participant, the SSRT was calculated using the mean method, estimated by subtracting the mean SSD from median go RT (Aron & Poldrack, 2006; Logan & Cowan, 1984).”

      Now reads:

      “For each participant, the SSRT was calculated using the integration method with replacement of go omissions (Verbruggen et al., 2019), estimated by integrating the RT distribution and calculating the point at which the integral equals p(respond|signal). The completion time of the stop process aligns with the nth RT, where n equals the number of RTs in the RT distribution of go trials multiplied by the probability of responding to a signal.”

      Reviewer #2:

      This work aggregates data across 5 openly available stopping studies (3 at 7 tesla and 2 at 3 tesla) to evaluate activity patterns across the common contrasts of Failed Stop (FS) > Go, FS > stop success (SS), and SS > Go. Previous work has implicated a set of regions that tend to be positively active in one or more of these contrasts, including the bilateral inferior frontal gyrus, preSMA, and multiple basal ganglia structures. However, the authors argue that upon closer examination, many previous papers have not found subcortical structures to be more active on SS than FS trials, bringing into question whether they play an essential role in (successful) inhibition. In order to evaluate this with more data and power, the authors aggregate across five datasets and find many areas that are *more* active for FS than SS, specifically bilateral preSMA, caudate, GPE, thalamus, and VTA, and unilateral M1, GPi, putamen, SN, and STN. They argue that this brings into question the role of these areas in inhibition, based upon the assumption that areas involved in inhibition should be more active on successful stop than failed stop trials, not the opposite as they observed. 

      As an empirical result, I believe that the results are robust, but this work does not attempt a new theoretical synthesis of the neuro-cognitive mechanisms of stopping. Specifically, if these many areas are more active on failed stop than successful stop trials, and (at least some of) these areas are situated in pathways that are traditionally assumed to instantiate response inhibition like the hyperdirect pathway, then what function are these areas/pathways involved in? I believe that this work would make a larger impact if the author endeavored to synthesize these results into some kind of theoretical framework for how stopping is instantiated in the brain, even if that framework may be preliminary. 

      I also have one main concern about the analysis. The authors use the mean method for computing SSRT, but this has been shown to be more susceptible to distortion from RT slowing (Verbruggen, Chambers & Logan, 2013 Psych Sci), and goes against the consensus recommendation of using the integration with replacement method (Verbruggen et al., 2019). Therefore, I would strongly recommend replacing all mean SSRT estimates with estimates using the integration with replacement method. 

      I found the paper clearly written and empirically strong. As I mentioned in the public review, I believe that the main shortcoming is the lack of theoretical synthesis. I would encourage the authors to attempt to synthesize these results into some form of theoretical explanation. I would also encourage replacing the mean method with the integration with replacement method for computing SSRT. I also have the following specific comments and suggestions (in the approximate order in which they appear in the manuscript) that I hope can improve the manuscript: 

      We would like to thank reviewer 2 for their insightful and interesting comments. We have adapted our paper to reflect these comments. Please see direct responses to your comments below. We agree with the reviewer that some type of theoretical synthesis would help with the interpretability of the article. We have substantially reworked the discussion and included theoretical considerations behind the newer narrative. Please see all changes to the article indicated by red text.

      (1) The authors say "performance on successful stop trials is quantified by the stop signal reaction time". I don't think this is technically accurate. SSRT is a measure of the average latency of the stop process for all trials, not just for the trials in which subjects successfully stop. 

      Thank you for pointing this technically incorrect statement. We have replaced the above sentence with the following (page 1):

      “Inhibition performance in the SST as a whole is quantified by the stop signal reaction time (SSRT), which estimates the speed of the latent stopping process (Verbruggen et al., 2019).”

      (2) The authors say "few studies have detected differences in the BOLD response between FS and SS trials", but then do not cite any papers that detected differences until several sentences later (de Hollander et al., 2017; Isherwood et al., 2023; Miletic et al., 2020). If these are the only ones, and they only show greater FS than SS, then I think this point could be made more clearly and directly. 

      We have moved the citations to the correct place in the text to be clearer. We have also rephrased this part of the introduction to make the points more direct (page 2).

      “In the subcortex, functional evidence is relatively inconsistent. Some studies have found an increase in BOLD response in the STN in SS > GO contrasts (Aron & Poldrack, 2006; Coxon et al., 2016; Gaillard et al., 2020; Yoon et al., 2019), but others have failed to replicate this (Bloemendaal et al., 2016; Boehler et al., 2010; Chang et al., 2020; B. Xu et al., 2015). Moreover, some studies have actually found higher STN, SN and thalamic activation in failed stop trials, not successful ones (de Hollander et al., 2017; Isherwood et al., 2023; Miletić et al., 2020).

      (3) Unless I overlooked it, I don't believe that the author specified the criterion that any given subject is excluded based upon. Given some studies have significant exclusions (e.g., Poldrack_3T), I think being clear about how many subjects violated each criterion would be useful. 

      This is indeed interesting and important information to include. We have added the number of participants who were excluded for each criterion. Please see added text below (page 4):

      “Based on these criteria, no subjects were excluded from the Aron_3T dataset. 24 subjects were excluded from the Poldrack_3T dataset (3 based on criterion 1, 9 on criterion 2, 11 on criterion 3, and 8 on criterion 4). Three subjects were excluded from the deHollander_7T dataset (2 based on criterion 1 and 1 on criterion 2). Five subjects were excluded from the Isherwood_7T dataset (2 based on criterion 1, 1 on criterion 2, and 2 on criterion 4). Two subjects were excluded from the Miletic_7T dataset (1 based on criterion 2 and 1 on criterion 4). Note that some participants in the Poldrack_3T study failed to meet multiple inclusion criteria.”

      (4) The Method section included very exhaustive descriptions of the neuroimaging processing pipeline, which was appreciated. However, it seems that much of what is presented is not actually used in any of the analyses. For example, it seems that "functional data preprocessing" section may be fMRIPrep boilerplate, which again is fine, but I think it would help to clarify that much of the preprocessing was not used in any part of the analysis pipeline for any results. For example, at first blush, I thought the authors were using global signal regression, but after a more careful examination, I believe that they are only computing global signals but never using them. Similarly with tCompCor seemingly being computed but not used. If possible, I would recommend that the authors share code that instantiates their behavioral and neuroimaging analysis pipeline so that any confusion about what was actually done could be programmatically verified. At a minimum, I would recommend more clearly distinguishing the pipeline steps that actually went into any presented analyses.

      We thank the reviewer for finding this inconsistency. The methods section indeed uses the fMRIprep boilerplate text, which we included so to be as accurate as possible when describing the preprocessing steps taken. While we believe leaving the exact boilerplate text that fMRIprep gives us is the most accurate method to show our preprocessing, we have adapted some of the text to clarify which computations were not used in the subsequent analysis. As a side-note, for future reference, we’d like to add that the fmriprep authors expressly recommend users to report the boilerplate completely and unaltered, and as such, we believe this may become a recurring issue (page 7).

      “While many regressors were computed in the preprocessing of the fMRI data, not all were used in the subsequent analysis. The exact regressors used for the analysis can be found above. For example, tCompCor and global signals were calculated in our generic preprocessing pipeline but not part of the analysis. The code used for preprocessing and analysis can be found in the data and code availability statement.”

      (5) What does it mean for the Poldrack_3T to have N/A for SSD range? Please clarify. 

      Thank you for pointing out this omission. We had not yet found the possible SSD range for this study. We have replaced this value with the correct value (0 – 1000 ms).

      (6) The SSD range of 0-2000ms for deHollander_7T and Miletic_7T seems very high. Was this limit ever reached or even approached? SSD distributions could be a useful addition to the supplement. 

      Thank you for also bringing this mistake to light. We had accidentally placed the max trial duration in these fields instead of the max allowable SSD value. We have replaced the correct value (0 – 900 ms).

      (7) The author says "In addition, median go RTs did not correlate with mean SSRTs within datasets (Aron_3T: r = .411, p = .10, BF = 1.41; Poldrack_3T: r = .011, p = .91, BF = .23; deHollander_7T: r = -.30, p = .09, BF = 1.30; Isherwood_7T: r = .13, p = .65, BF = .57; Miletic_7T: r = .37, p = .19, BF = 1.02), indicating independence between the stop and go processes, an important assumption of the horse-race model (Logan & Cowan, 1984)." However, the independent race model assumes context independence (the finishing time of the go process is not affected by the presence of the stop process) and stochastic independence (the duration of the go and stop processes are independent on a given trial). This analysis does not seem to evaluate either of these forms of independence, as it correlates RT and SSRT across subjects, so it was unclear how this analysis evaluated either of the types of independence that are assumed by the independent race model. Please clarify or remove. 

      Thank you for this comment. We realize that this analysis indeed does not evaluate either context or stochastic independence and therefore we have removed this from the manuscript.

      (8) The RTs in Isherwood_7T are considerably slower than the other studies, even though the go stimulus+response is the same (very simple) stimulus-response mapping from arrows to button presses. Is there any difference in procedure or stimuli that might explain this difference? It is the only study with a visual stop signal, but to my knowledge, there is no work suggesting visual stop signals encourage more proactive slowing. If possible, I think a brief discussion of the unusually slow RTs in Isherwood_7T would be useful. 

      We have included the following text in the manuscript to reflect this observed difference in RT between the Isherwood_7T dataset and the other datasets (page 9).

      “Longer RTs were found in the Isherwood_7T dataset in comparison to the four other datasets. The only difference in procedure in the Isherwood_7T dataset is the use of a visual stop signal as opposed to an auditory stop signal. This RT difference is consistent with previous research, where auditory stop signals and visual go stimuli have been associated with faster RTs compared to unimodal visual presentation (Carrillo-de-la-Peña et al., 2019; Weber et al., 2024). The mean SSRTs and probability of stopping are within normal range, indicating that participants understood the task and responded in the expected manner.”

      (9) When the authors included both 3T and 7T data, I thought they were preparing to evaluate the effect of magnet strength on stop networks, but they didn't do this analysis. Is this because the authors believe there is insufficient power? It seems that this could be an interesting exploratory analysis that could improve the paper.

      We thank the reviewer for this interesting comment. As our dataset sample contains only two 3T and three 7T datasets we indeed believe there is insufficient power to warrant such an analysis. In addition, we wanted the focus of this paper to be how fMRI examines the SST in general, and not differences between acquisition methods. With a greater number of datasets with different imaging parameters (especially TE or resolution) in addition to field strength, we agree such an analysis would be interesting, although beyond the scope of this article.

      (10) The authors evaluate smoothing and it seems that the conclusion that they want to come to is that with a larger smoothing kernel, the results in the stop networks bleed into surrounding areas, producing false positive activity. However, in the absence of a ground truth of the true contributions of these areas, it seems that an alternative interpretation of the results is that the denser maps when using a larger smoothing kernel could be closer to "true" activation, with the maps using a smaller smoothing kernel missing some true activity. It seems worth entertaining these two possible interpretations for the smoothing results unless there is clear reason to conclude that the smoothed results are producing false positive activity. 

      We agree with the view of the reviewer on the interpretation of the smoothing results. We indeed cannot rule this out as a possible interpretation of the results, due to a lack of ground truth. We have added text to the article to reflect this view and discuss the types of errors we can expect for both smaller and larger smoothing kernels (page 15).

      “In the absence of a ground truth, we are not able to fully justify the use of either larger or smaller kernels to analyse such data. On the one hand, aberrantly large smoothing kernels could lead to false positives in activation profiles, due to bleeding of observed activation into surrounding tissues. On the other side, too little smoothing could lead to false negatives, missing some true activity in surrounding regions. While we cannot concretely validate either choice, it should be noted that there is lower spatial uncertainty in the subcortex compared to the cortex, due to the lower anatomical variability. False positives from smoothing spatially unmatched signal, are more likely than false negatives. It may be more prudent for studies to use a range of smoothing kernels, to assess the robustness of their fMRI activation profiles.”

    1. automatically calls

      wow. so if the grantType is authorization code flow type, this parseFromUrl() function actually automatically does an entire extra step which is the POST to get the token.

    2. which malicious browser extensions would not have access to

      according to the next paragraph, at least in this example case of okta, we don't need manual access to the random secret generated by frontend code.

    1. Reviewer #2 (Public Review):

      Summary:

      This study takes advantage of multiple methodological advances to perform layer-specific staining of cortical neurons and tracking of their axons to identify the pattern of their projections. This publication offers a mesoscale view of the projection patterns of neurons in the whisker primary and secondary somatosensory cortex. The authors report that, consistent with the literature, the pattern of projection is highly different across cortical layers and subtype, with targets being located around the whole brain. This was tested across 6 different mouse types that expressed a marker in layer 2/3, layer 4, layer 5 (3 sub-types) and layer 6.<br /> Looking more closely at the projections from primary somatosensory cortex into the primary motor cortex, they found that there was a significant spatial clustering of projections from topographically separated neurons across the primary somatosensory cortex. This was true for neurons with cell bodies located across all tested layers/types.

      Strengths:

      This study successfully looks at the relevant scale to study projection patterns, which is the whole brain. This is achieved thanks to an ambitious combination of mouse lines, immuno-histochemistry, imaging and image processing, which results in a standardized histological pipeline that processes the whole-brain projection patterns of layer-selected neurons of the primary and secondary somatosensory cortex.<br /> This standardization means that comparisons between cell-types projection patterns are possible and that both the large-scale structure of the pattern and the minute details of the intra-areas pattern are available.<br /> This reference dataset and the corresponding analysis code are made available to the research community.

      Weaknesses:

      One major question raised by this dataset is the risk of missing axons during the post-processing step. Indeed, it appears that the control and training efforts have focused on the risk of false positives (see Figure 1 supplementary panels). And indeed, the risk of overlooking existing axons in the raw fluorescence data id discussed in the article.

      Based on the data reported in the article, this is more than a risk. In particular, Figure 2 shows an example Rbp4-L5 mouse where axonal spread seems massive in Hippocampus, while there is no mention of this area in the processed projection data for this mouse line.

      Similarily, the Ntsr1-L6CT example shows a striking level of fluorescence in Striatum, that does not reflect in the amount of axons that are detected by the algorithms in the next figures.<br /> These apparent discrepancies may be due to non axonal-specific fluorescence in the samples. In any case, further analysis of such anatomical areas would be useful to consolidate the valuable dataset provided by the article.

    1. https://www.youtube.com/watch?v=KbzqB09ZyJQ

      Résumé de la vidéo [00:00:00][^1^][1] - [00:25:15][^2^][2]:

      Cette vidéo présente une conférence de Didier Fassin sur la faculté de punir, explorant les pratiques punitives au-delà de leur forme légale et l'impact de la peine d'emprisonnement. Fassin discute des théories de la justice rétributive et utilitariste, et analyse l'extension de la peine, notamment en termes de profondeur de l'affliction et d'élargissement du cercle des affligés.

      Points forts: + [00:00:29][^3^][3] La critique de la définition traditionnelle de la peine * Remise en question de la définition par les philosophes et juristes * Focus sur le châtiment pour comprendre les pratiques punitives * Importance de la réalité des pratiques au-delà de la loi + [00:01:54][^4^][4] L'extension de la peine * La peine affecte plus profondément et au-delà de l'intention initiale * Analyse de l'emprisonnement et son impact sur les proches des détenus * Référence aux recherches en sociologie et anthropologie + [00:03:38][^5^][5] L'influence de Cesare Beccaria sur la prison et la peine d'emprisonnement * Discussion sur l'œuvre de Beccaria et son impact sur la réforme pénale * Rejet de la justice rétributive et plaidoyer pour l'utilitarisme * L'importance de la prévention des crimes et de la proportionnalité des peines + [00:21:19][^6^][6] L'histoire de la peine d'emprisonnement en France * Introduction de l'emprisonnement dans le code pénal de 1791 * Évolution des peines et principes de la réforme pénale * Critique de l'adoucissement des peines et de la punition généralisée Résumé de la vidéo [00:25:17][^1^][1] - [00:48:46][^2^][2]:

      Cette partie de la vidéo explore l'évolution de la peine d'emprisonnement dans l'histoire française, depuis son introduction dans le code pénal en 1781 jusqu'à son utilisation contemporaine. Elle examine les changements dans la gestion des prisons, les conditions de détention et l'impact sur les détenus et le personnel pénitentiaire.

      Points forts: + [00:25:17][^3^][3] Introduction de l'emprisonnement punitif * Remplacement des peines corporelles * Emprisonnement comme sanction ordinaire * Extension progressive de l'empire carcéral + [00:29:00][^4^][4] Privatisation et conditions des prisons * Développement des manufactures carcérales * Main-d'œuvre captive pour les industriels * Dénonciation des abus par des intellectuels + [00:35:00][^5^][5] Perception de la prison par le personnel * Stratégies de défense face à la détresse des détenus * Indifférence cognitive et justification de l'agressivité * Sensibilité de certains membres du personnel + [00:41:00][^6^][6] Confinement et privation de liberté * Confinement dans le confinement * Impact de la surpopulation carcérale * Privation de la vie affective et sexuelle + [00:45:00][^7^][7] Frustrations et privation de dignité * Toutepuissance du personnel et épreuve de l'estime de soi * Fouilles corporelles et atteinte à la dignité * Difficultés liées à la cohabitation forcée Résumé de la vidéo [00:48:48][^1^][1] - [01:03:27][^2^][2]:

      Cette partie de la vidéo aborde la faculté de punir et les diverses privations subies par les détenus, allant au-delà de la simple perte de liberté. Elle met en lumière les conditions de vie difficiles en prison, l'impact de l'incarcération sur les proches des détenus et les conséquences sociales plus larges de la politique pénitentiaire.

      Points forts: + [00:48:48][^3^][3] Les conditions de détention * Les décisions du tribunal administratif et leur impact * Les restrictions sur les activités quotidiennes comme les douches * La pression exercée par les surveillants + [00:50:07][^4^][4] La privation de sens de la peine * L'absence de prise de conscience du délit commis * Le manque d'opportunités pour la réinsertion sociale et la réforme morale * La description de la prison comme un lieu qui dévalorise la personne + [00:52:17][^5^][5] Le suicide en milieu carcéral * Le taux élevé de suicide en prison en France * Les facteurs contribuant aux suicides, comme le choc de l'incarcération * L'impact des conditions carcérales sur la santé mentale des détenus + [00:55:23][^6^][6] Les répercussions sur les proches des détenus * L'effet de l'incarcération sur les familles et les communautés * Les difficultés rencontrées par les visiteurs pour accéder à la prison * La notion de "châtiment vicariant" affectant les proches des condamnés

    1. Fig. 3.5 Discharge patterns of the Rhine and Meuse rivers.

      Onderliggende gegevens? Python code voor de plot? Misschien wel aardig om ook het 10e en 90e percentiel te geven

    1. AbstractThe edible jelly fungus Dacryopinax spathularia (Dacrymycetaceae) is wood-decaying and can be commonly found worldwide. It has also been used in food additives given its ability to synthesize long-chain glycolipids. In this study, we present the genome assembly of D. spathularia using a combination of PacBio HiFi reads and Omni-C data. The genome size of D. spathularia is 29.2 Mb and in high sequence contiguity and completeness, including scaffold N50 of 1.925 Mb and 92.0% BUSCO score, respectively. A total of 11,510 protein-coding genes, and 474.7 kb repeats accounting for 1.62% of the genome, were also predicted. The D. spathularia genome assembly generated in this study provides a valuable resource for understanding their ecology such as wood decaying capability, evolutionary relationships with other fungus, as well as their unique biology and applications in the food industry.

      This work has been published in GigaByte Journal under a CC-BY 4.0 license (https://doi.org/10.46471/gigabyte.120), and has published the reviews under the same license. This is part of a thematic series presenting Data Releases from the Hong Kong Biodiversity Genomics consortium (https://doi.org/10.46471/GIGABYTE_SERIES_0006). These are as follows.

      Reviewer 1. Anton Sonnenberg

      Is the language of sufficient quality? Yes.

      Are all data available and do they match the descriptions in the paper? Yes.

      Is the data acquisition clear, complete and methodologically sound? Yes.

      Is there sufficient detail in the methods and data-processing steps to allow reproduction? Yes.

      Figure 1E could be improved by eliminating in the pie-chart the non-repeat sequences or bar-plot the repeats. That will visualize better the frequencies of each type of repeats.

      Reviewer 2. Riccardo Iacovelli

      Is the language of sufficient quality? No.

      There are several typos spread across the text, and some sentences are written in an unclear manner. I provide some suggestions in the attachment.

      Are all data available and do they match the descriptions in the paper?

      Yes, but some of the data shown is rather unclear and/or not supported by sufficient explanation. For example, what is actually Fig. 1C showing? Because the reference in the text (which contains a typo, line 197) refers to something else. What is the second set of stats in Fig. 1B? This other organism is not mentioned at all anywhere in the manuscript.

      Are the data and metadata consistent with relevant minimum information or reporting standards?

      No. NCBI TaxID of the sequenced species object of this work is missing.

      Is there sufficient detail in the methods and data-processing steps to allow reproduction?

      No. In my opinion, some of the procedures described for the processing of the sample and library prep for sequencing are reported in an unclear way. For example, lines 100-103: no details on RNAse A treatment; how do you define chloroform:IAA (24:1) washes? how much supernatant is added to how much H1 buffer to have the final volume of 6 ml? Another example, lines 180-175: what parameters did you use for EvidenceModeler to generate the final consensus genes model? The weight given to each particular prediction set is important.

      Is there sufficient data validation and statistical analyses of data quality?

      No/ While sufficient data validation and statistical analyses have been carried out with respect to DNA sequencing and genome assembly, nothing is reported about DNA extraction and quality. The authors mention several times throughout the text that DNA preps are checked via NanoDrop, Qubit, gel electrophoresis, etc. But none of this is shown in the main body or in the supplementary information. Without this information, it is difficult to assess directly the efficacy of DNA extraction and preparation methods. I recommend including this type of data.

      Additional Comments:

      In this article, the authors report the first whole genome assembly of Dacryopinax spathularia, an edible mushroom-forming fungus that is used in the food industry to produce natural preservatives. In general, I find the data of sufficiently high quality for release, and I do agree with the authors in that it will prove useful to gain further insights into the ecology of the fungus, and to better understand the genetic basis of its ability to decay wood and produce valuable compounds. This can ultimately lead to discoveries with applications in biotech and other industries.

      Nevertheless, during the review process I noticed several shortcomings with respect to unclear language, insufficient description of the experimental procedures and/or results presented, and missing data altogether. These are all discussed within the checklist available in the ReView portal. For minor comments line-by-line, see below:

      1: Dacrymycetaceae should be italicized (throughout the whole manuscript). This follows the convention established by The International Code of Nomenclature for algae, fungi, and plants (https://www.iaptglobal.org/icn). Although not binding, this allows easy recognition of taxonomic ranks when reading an article. 49: other fungus -> other fungi 56: photodynamic injury -> UV damage/radiation (photodynamic is used with respect to light-activated therapies etc.) 60: in food industry as natural preservatives in soft drinks -> in food industry to produce natural preservatives for soft drinks 68: cultivated in industry as food additives -> cultivated in industry to produce food additives 69: isolated fungal extract -> the isolated fungal extract 71: What do you mean by Pacific? It’s unclear 71-72: the genomic resource -> genomic data/ genome sequence 72: I would remove “with translational values”, it is very vague and does not add anything to the statement 78: genomic resource -> genomic data/ genome sequence 78-81: this could be rephrased in a smoother manner: e.g. something like “the genomic data will be useful to gain a better understanding of the fungus’ ecology as well as the genetic basis of its wood-decaying ability and…” 85: fruit bodies -> fruiting bodies 88-89: Grown hyphae from >2 week-old was transferred  Fungal hyphae from 2-week old colonies were transferred 90-91: validated with the DNA barcode of Translation  assigned by DNA barcoding using the sequence of Translation… 95: ~ -> Approximately (sentences are not usually started with symbols or numbers) 101-3: Procedure is not clear enough (see other comments through ReView portal) 124: for further cleanup the library -> to further clean up the library / for further cleanup of the library 132: as line 95 152: as lines 95, 132 181-5: Insufficient description of methods, see comments through ReView portal 197: Figure and 1C; Table 2 -> Figure 1C and Table 2 200: average protein length of 451 bp -> average protein-coding gene length / average protein length of ~150 amino acids 211: via the fermentation process with applications in the food industry -> via the fermentation process with potential applications in the food industry

      As a fungal biologist myself interested in fungal genomics and biotechnology, I would like to thank the authors for carrying out this work and the editor for the opportunity to review it. I am looking forward to reading the revised version of the manuscript.

      Riccardo Iacovelli, PhD GRIP, Chemical and Pharmaceutical Biology department University of Groningen, Groningen - The Netherlands

    1. AI-powered code generation tools like GitHub Copilot make it easier to write boilerplate code, but they don’t eliminate the need to consult with your organization’s domain experts to work through logic, debugging, and other complex problems.Stack Overflow for Teams is a knowledge-sharing platform that transfers contextual knowledge validated by your domain experts to other employees. It can even foster a code generation community of practice that champions early adopters and scales their learnings. OverflowAI makes this trusted internal knowledge—along with knowledge validated by the global Stack Overflow community—instantly accessible in places like your IDE so it can be used alongside code generation tools. As a result, your teams learn more about your codebase, rework code less often, and speed up your time-to-production.
    1. Reviewer #1 (Public Review):

      I thank the authors for addressing almost all my comments on the previous version of this manuscript, which studies the representation by gender and name origin of authors from Nature and Springer Nature articles in Nature News.

      The representation of author identities is an important step towards equality in science, and the authors found that women are underrepresented in news quotes and mentions with respect to the proportion of women authors.

      The research is rigorously conducted. It presents relevant questions and compelling answers. The documentation of the data and methods is thoroughly done, and the authors provide the code and data for reproduction.

    1. e 28 avril, TotalEnergies assignait en justice Greenpeace France en raison de la publication d’un rapport qui interroge les calculs effectués par la multinationale sur ses émissions de CO2. La procédure, qui présente la particularité de reposer sur des dispositions du code monétaire et financier, vise notamment à faire interrompre toute diffusion actuelle ou à venir du rapport

      TotalEnergies versucht juristisch die weitere Publikation eines Greenpeace-Berichts zu verhindern, in dem aufgezeigt wird, dass die Angaben des Konzerns zu den eigenen CO2 Emissionen Greenwashing sind. Dieses Verfahren ist ein Beispiel für das mundtot machen von Journalisten mit Journal mit juristischen Mitteln gegen das sich jetzt eine Initiative zur Wehr setzt.

      https://www.liberation.fr/idees-et-debats/tribunes/bollore-total-face-aux-procedures-baillons-on-ne-se-taira-pas-20230625_UKD2PHN6QFB5ZAK7YFYEQOR6BA/

    1. Reviewer #3 (Public Review):

      Liang and colleagues set out to test whether the human brain uses distance and grid-like codes in social knowledge using a design where participants had to navigate in a two-dimensional social space based on competence and warmth during an fMRI scan. They showed that participants were able to navigate the social space and found distance-based codes as well as grid-like codes in various brain regions, and the grid-like code correlated with behavior (reaction times).

      On the whole, the experiment is designed appropriately for testing for distant-based and grid-like codes, and is relatively well powered for this type of study, with a large amount of behavioral training per participant. They revealed that a number of brain regions correlated positively or negatively with distance in the social space, and found grid-like codes in the frontal polar cortex and posterior medial entorhinal cortex, the latter in line with prior findings on grid-like activity in entorhinal cortex. The current paper seems quite similar conceptually and in design to previous work, most notably Park et al., 2021, Nature Neuroscience.

      (1) The authors claim that this study provides evidence that humans use a spatial / grid code for abstract knowledge like social knowledge.

      This data does specifically not add anything new to this argument. As with almost all studies that test for a grid code in a similar "conceptual" space (not only the current study), the problem is that, when the space is not a uniform, square/circular space, and 2-dimensional then there is no reason the code will be perfectly grid like, i.e., show six-fold symmetry. In real world scenarios of social space (as well as navigation, semantic concepts), it must be higher dimensional - or at least more than two dimensional. It is unclear if this generalizes to larger spaces where not all part of the space is relevant. Modelling work from Tim Behrens' lab (e.g., Whittington et al., 2020) and Bradley Love's lab (e.g., Mok & Love, 2019) have shown/argued this to be the case. In experimental work, like in mazes from the Mosers' labs (e.g., Derdikman et al., 2009), or trapezoid environments from the O'Keefe lab (Krupic et al., 2015), there are distortions in mEC cells, and would not pass as grid cells in terms of the six-fold symmetry criterion.

      After revision, the authors now discuss some of this and the limitations and notes that future work is required to address the problem.

    1. match
      • types of these fields must also match, e.g., it will be removed if you provide a number to the code field.
      • 这些属性的类型也必须匹配,如果你给的code是一个number类型,它也会被筛掉。

      @github.com/mj2068

    1. Research on sexual harassment points ro w;-iysthat girls especially feel pressure to conform to gcndereJ norms or feel thehostility of gender dynamics particularly keenly

      This sort of reminds me of the dress code issues mentioned in last weeks lectures. When we discussed that female students are always at fault on what they are wearing and not what the male students are thinking. Society has always had scenarios like these come up, causing innocent individuals to be the victim.

    1. Unlike other default asset permissions, SMS code permissions can only be setup for security groups, not individual users. SMS codes are not created by users and aren't an asset type you can manage with Asset Creation controls for the security group. You can only setup default SMS code permissions for the security group at a time. You cannot grant individual users default SMS code permissions. The permissions are for the security group.
    1. The SMS Message Designer provides an easy-to-use interface to build your message content and easily add features like field merges, hyperlinks, and keywords. An SMS keyword is a word or phrase that your subscribers can text to an SMS code to interact with your SMS campaign. A code and keyword combination cannot be activated simultaneously on multiple campaigns.
    1. An SMS keyword is a word or phrase that your subscribers can text to an SMS code to interact with your SMS campaign. They are used to define actions for mobile originated (MO) messages.
    1. Author response:

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

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Pg. 3 - lines 51-53: "Once established, the canonical RdDM pathway takes over, whereby small RNAs are generated by the plant-specific polymerase IV (Pol IV). In both cases, a second plant-specific polymerase, Pol V, is an essential downstream component." The authors' intro omits an important aspect of Pol V's function in RdDM, which is quite relevant to their study. Pol V transcribes DNA to synthesize noncoding RNA scaffolds, to which AGO4-bound 24 nt siRNAs are thought to base pair, leading to DRM2 recruitment for cytosine methylation near to these nascent Pol V transcripts (Wierzbicki et al 2008 Cell; Wierzbicki et al. 2009 Nat Genet). I recommend that the authors cite these key studies.

      These citations have now been added (see line 57).

      The authors provide compelling evidence that Pol V redistributes to ectopic heterochromatin regions in h1 mutants (e.g., Fig1a browser shot). Presumably, this would allow Pol V to transcribe these regions in h1 mutants, whereas it could not transcribe them in WT plants. Have the authors detected and/or quantified Pol V transcripts in the h1 mutant compared to WT plants at the sites of Pol V redistribution (detected via NRPE1 ChIP)?

      Robust detection of Pol V transcripts can be experimentally challenging, and instead we quantify and detect NRPE1 dependent methylation at these regions (Fig 5), which occurs downstream of Pol V transcript production. However, we note detecting Pol V transcripts as a potential future direction in the discussion (see line 263).

      Pg. 5 - lines 101-102: Figure 1e - "The preferential enrichment of NRPE1 in h1 was more pronounced at TEs that overlapped with heterochromatin associated mark, H3K9me2 (Fig. 1e). Was a statistical test performed to determine that the overall differences are significant only at TE sites with H3K9me2? Can the sites without H3K9me2 also be differentiated statistically?

      Yes, there is a statistically significant difference between WT and h1 at both the H3K9me2 marked and unmarked TEs (Wilcoxon rank sum tests, see updated Fig 1e). The size of the effect is larger for the H3K9me2 marked TEs (median difference of 0.41 vs 0.16). Median values have now been added to the boxplots so that this is directly viewable to the reader (Fig 1e). This reflects the general increase in NRPE1 occupancy in h1 mutants through the genome, with the effect consistently stronger in heterochromatin. In our initial version of the manuscript, we summarise the effect as follows “We found that h1 antagonizes NRPE1 occupancy throughout the genome, particularly at heterochromatic regions” (previous version line 83, current version line 95). Although important exceptions exist (see Fig 5, NRPE1 and DNA methylation loss in h1), we now make this point even more explicit, and have updated the manuscript at several locations (abstract line 26, results line 245, discussion line 265).

      Pg. 5 - lines 108-110: The authors state, "Importantly, we found no evidence for increased NRPE1 expression at the mRNA or protein level in the h1 mutant (Suppl. Fig. 2)." But the authors did observe reduced NRPE1 transcript levels in h1 mutants, in their re-analysis of RNA-seq data and reduced NRPE1 protein signals via western blot in (Suppl. Fig. 2), which should be reported here in the results.

      As described further below, we reanalysed h1 RNA-seq from scratch, and see no evidence for significant differential gene expression of NRPE1. This table and analysis are now provided in Supplementary Table 1.

      More importantly, the above logic about NRPE1 expression in h1 mutants assumes that NRPE1 is the stoichiometrically limiting subunit for Pol V assembly and function in vivo, but this is not known to be the case:

      (1) While NRPE1's expression is somewhat reduced (and not increased) in h1 mutant plants, we cannot be certain that other genes influencing Pol V stability or recruitment are unaffected by h1 mutants. I thus recommend that the authors perform RT-qPCR directly on the WT and h1 mutant materials used in their current study, quantifying NRPE1, NRPE2, NRPE5, DRD1, DMS3, RDM1, SUVH2 and SUVH9 transcript levels.

      (2) Normalizations used to compare samples should be included with RT-qPCR and western assays. An appropriate house-keeping gene like Actin2 or Ubiquitin could be used to normalize the RT-qPCR. Protein sample loading in Suppl. Fig. 2 could be checked by Coomassie staining and/or an antibody detection of a house-keeping protein.

      We have now included a full re-analysis of h1 RNA-seq (data from Choi et al 2020) focusing on transcriptional changes of DNA methylation machinery genes in the h1 mutant. Of the 61 genes analysed, only AGO6 and AGO9 were found to be differentially expressed (2-3 fold upregulation). This analysis is now included as a table

      (Supplementary Table 1). The western blot has been moved to Supplementary Fig 3 to now illustrate antibody specificity and H1 loss in the h1 mutant lines, so NRPE1 itself serves as a loading control (Supplementary Fig 3a).

      Pg. 6 - lines 129-131: The authors state that "over NRPE1 defined peaks (where NRPE1 occupancy is strongest in WT) we observed no change in H1 occupancy in nrpe1 (Fig 2b). The results indicate that H1 does not invade RdDM regions in the nrpe1 mutant background." This conclusion assumes that the author's H1 ChIP is successfully detecting H1 occupancy. However, in Fig 2d there does not appear to be H1 enrichment or peaks as visualized across the 10766 ZF-DMS3 off-target loci, or even at the selected 451 ZFDMS3 off-target hyper DMRs, where the putative signal for H1 enrichment on the metaplot center is extremely weak/non-existent.

      As a reference for H1 enrichment in chromatin (e.g., looking where H2A.W antagonizes H1 occupancy) one can compare analyses in Bourguet et al (2021) Nat Commun, involving co-authors of the current study. Bourguet et al (2021) Fig 5b show a metaplot of H1 levels centered on H2A.W peaks with H1 ChIP signal clearly tapering away from the metaplot center point peak. To my eye, the H1 ChIP metaplots for ZF-DMS3 offtarget loci in the current manuscript (Fig 2d) resemble "shuffled peaks" controls like those in Fig 5b of Bourguet et al (2021).

      Can one definitively interpret Fig 2d as showing RdDM "not reciprocally affecting H1 localization" without first showing the specificity of the ChIP-seq results in a genotype where H1 occupancy changes? Alternatively, could this dataset be displayed with Deeptools heatmaps to strengthen the evidence that the authors are detecting H1 occupancy/enrichment genome-wide, before diving into WT/nrpe1 mutant analysis at ZF-DMS3 off-target loci?

      This is an excellent suggestion from the reviewer. We have now included several analyses that assess and demonstrate the quality of our H1 ChIP-seq profiles. First, as suggested by the reviewer, we show that our H1 profiles peak over H2A.W enriched euchromatic TEs as defined by Bourguet et al, mirroring these published findings. Next, we investigated whether our H1 profiles match Teano’s recently described pattern over genes, confirming a similar pattern with 3’ enrichment of H1 over H3K27me3 unmarked genes. Furthermore, we show that the H1 peaks defined here are similarly enriched with GFP tagged H1.2 from the Teano et al. 2023 study. These analyses that validate the quality of our H1 ChIP-seq datasets and bolster the conclusion that NRPE1 redistribution does not affect H1 occupancy. These new analysis are now presented in Supplementary Figure 3 and see line 153.

      Pg. 8 - lines 228-230: The authors state that, "As with NRPE1, SUVH1 increased in the h1 background significantly more in heterochromatin, with preferential enrichment over long TEs, cmt2 dependent hypo CHH DMRs, and heterochromatic TEs (Fig. 6b)."

      Contrary to the above statement, the violin plots in Fig. 6c show SUVH1 occupancy increasing at euchromatic TEs in the h1 mutant. What statistical test allowed the authors to determine that the increase in h1 occurs "significantly more in heterochromatin"? The authors should critically interpret Fig. 6c and 6d, which are not currently referenced in the results section. More support is needed for the claim that SUVH1 specifically encroaches into heterochromatin in the h1 mutant, rather than just TEs generally (euchromatic and heterochromatic alike).

      Similar to what we see for NRPE1, statistical tests that we have now performed show that SUVH1 is significantly enriched in h1 in all classes. Importantly however, the effect size is larger in all of the heterochromatin associated classes. We display these statistical tests and the median values on the plots so that effects are immediately viewable (see updated Fig 6).

      In addition, the authors should verify that SUVH1-3xFLAG transgenes (in the WT and h1 mutant backgrounds, respectively) and endogenous Arabidopsis genes encoding the transcriptional activator complex (SUVH1-SUVH3-DNAJ1-DNAJ2) are not overexpressed in the h1 mutant vs. WT. Higher expression of SUVH1 or limiting factors in the larger complex could explain the observation of increased SUVH1 occupancy in the h1 background.

      We do not see a difference in SUVH1/3/DNAJ1/2 complex gene expression in the h1 background (see Supplementary Table 1). However, we cannot rule out that that our SUVH1-FLAG line in h1 is more highly expressed than the corresponding SUVH1-FLAG line in WT. We now note this point in line 248.

      Pg. 8 - lines 231-232: Here the authors make a sweeping conclusion about H1 demarcating, "the boundary between euchromatic and heterochromatic methylation pathways, likely through promoting nucleosome compaction and restricting heterochromatin access." I do not see how a H1 boundary between euchromatic and heterochromatic methylation pathways is revealed based on the SUVH1-3xFLAG occupancy data, which shows increased enrichment at every category interrogated in the h1 mutant (Fig 6b,c,d) and all along the baseline too in the h1 mutant browser tracks (Fig 6a). Can the authors provide more examples of this phenomenon (similar to Fig 6a) and better explain why their SUVH1-3xFLAG ChIP supports this demarcation model?

      The general conclusion from SUVH1 about H1’s agnostic role in preventing heterochromatin access is now further supported from our findings with H3K27me3 (see Figure 6e and description from line 250). However, we agree that the demarcation model as initially presented was overly simplistic. This point was also raised by reviewer 2. We have removed the line highlighted by the reviewer in the revised version of the manuscript. In the revised version we clarify that H1 impedes RdDM and associated machinery throughout the genome (consistent with H1’s established broad occupancy across the genome) but this effect is most pronounced in heterochromatin, corresponding to maximal H1 occupancy (abstract line 26, results line 245, discussion line 265). 

      Corrections:

      Pg. 8 - lines 226-227: "We therefore wondered whether complex's occupancy might also be affected by H1." The sentence contains a typo, where I assume the authors mean to refer to occupancy by the SUVH1-SUVH3-DNAJ1-DNAJ2 transcriptional activator complex. This needs to be specified more clearly.

      The paragraph has been updated (see from line 237).

      Pg. 13 - lines 393-405: There are minor errors in the capitalization of titles and author initials in the References. I recommend that the authors proofread all the references to eliminate these issues:

      Thank you, these have been corrected.

      Choi J, Lyons DB, Zilberman D. 2021. Histone H1 prevents non-cg methylation-mediated small RNA biogenesis in arabidopsis heterochromatin. Elife 10:1-24. doi:10.7554/eLife.72676 (...)

      Du J, Johnson LM, Groth M, Feng S, Hale CJ, Li S, Vashisht A a., Gallego-Bartolome J, Wohlschlegel J a., Patel DJ, Jacobsen SE. 2014. Mechanism of DNA methylation-directed histone methylation by KRYPTONITE. Mol Cell 55:495-504. doi:10.1016/j.molcel.2014.06.009 (...)

      Du J, Zhong X, Bernatavichute Y V, Stroud H, Feng S, Caro E, Vashisht A a, Terragni J, Chin HG, Tu A, Hetzel J, Wohlschlegel J a, Pradhan S, Patel DJ, Jacobsen SE. 2012. Dual binding of chromomethylase domains to H3K9me2-containing nucleosomes directs DNA methylation in plants. Cell 151:167-80. doi:10.1016/j.cell.2012.07.034

      Reviewer #2 (Recommendations For The Authors):

      As for a normal review, here are our major and minor points.

      Major:

      (1) Lines 38 to 45 of the introduction are important for the subsequent definition of heterochromatic and non-heterochromatic transposons, but the definition is ambiguous. Is heterochromatin defined by surrounding context such as pericentromeric position or is this an autonomous definition? Can a TE with the chromosomal arms be considered heterochromatic provided that it is long enough and recruits the right machinery? These cases should be more explicitly introduced. Ideally, a supplemental dataset should provide a key to the categories, genomic locations and overlapping TEs as they were used in this analysis, even if some of the categories were taken from another study.

      We have now added all the regions used for analysis in this study to Supplementary Table 3.

      (2) Line 80: This would be the first chance to cite Teno et al. and the "encroachment" of

      PcG complexes to TEs in H1 mutants

      Done - “H1 also plays a key role in shaping nuclear architecture and preventing ectopic polycomb-mediated H3K27me3 deposition in telomeres (Teano et al., 2023).” See line 83

      (3) It is "only" a supplemental figure but S2 but it should still follow the rules: Indicate the number of biological replicates for the RNA-seq data, and perform a statistical test. In case of WB data, provide a loading control.

      We are now using the western blot to illustrate antibody specificity and H1 loss in the h1 mutant lines, so NRPE1 itself serves as a loading control (Supplementary Fig 3a). For NRPE1 mRNA expression, we have now replaced this with a more comprehensive transcriptome analysis of methylation machinery in h1 (see Supplementary Table 1). 

      (4) Lines 115 to 124 and corresponding data: Here, the goal is to exclude other changes to heterochromatin structure other than "increased access" in H1 mutants; however, only one feature, H3K9me2, is tested. Testing this one mark does not necessarily prove that the nature of the chromatin does not change, e.g. H2A.W could be differently redistributed, DDM1 may change, VIM protein, and others. Either more comprehensive testing for heterochromatin markers should be performed, or the conclusions moderated.

      We have moderated the text accordingly (see line 135).

      (5) Lines 166ff and Figure 1, a bit out of order also Figure 5: The general hypothesis is that NRPE1 redistributes to heterochromatic regions in h1 mutants (as do other chromatin modifiers), but the data seem to only support a higher occurrence at target sites.

      a. The way the NRPE1 data is displayed makes it seem like there is much more NRPE1 in the h1 samples, even at peaks that should not be recruiting more as they do not represent "long" TEs. It would be good to present more gbrowse shots of all peak classes.

      We now clarify that h1 does result in a general increase of NRPE1 throughout the genome, but the effect is strongest at heterochromatin. In our initial version of the manuscript, we summarise the effect as follows “We found that h1 antagonizes NRPE1 occupancy throughout the genome, particularly at heterochromatic regions” (previous version line 83, current version line 95). We have modified the language at several locations throughout the manuscript to make this point more clearly (abstract line 26, results line 245, discussion line 265). We include several browser shots in Supp Fig. 8.

      b. The data are "normalized" how exactly?

      c. One argument of observing "gaining" and "losing" peaks is that there is redistribution of NRPE1 from euchromatic to heterochromatic sites. There should be an analysis and figure to corroborate the point (e.g. by comparing FRIP values). Figure 1b shows lower NRPE1 signals at the TE flanking regions. This could reflect a redistribution or a flawed normalization procedure.

      The data are normalised using a standardised pipeline by log2 fold change over input, after scaling each sample by mapped read depth using the bamCompare function in deepTools. This is now described in detail in the Materials and Methods line 365, with full code and pipelines available from GitHub (https://github.com/Zhenhuiz/H1-restrictseuchromatin-associated-methylation-pathways-from-heterochromatic-encroachment).

      d. Figure 1d and f show similar profiles comparing "long" and "short" TEs or "CMT2 dependent hypo-CHH" and "DRM2 dependent CHH". How do these categories relate to each other, how many fragments are redundant?

      The short vs long TEs were defined in Liu et al 2018 (doi: 10.1038/s41477-017-0100-y) and the DMRs were defined in Zhang et al. 2018 (DOI: 10.1073/pnas.1716300115). There is likely to be some degree of overlap between the categories, but numbers are very different (short TEs (n=820), long TEs (n=155), drm2 DMRs (n=5534), CMT (n=21784)) indicating that the different categories are informative. We have now listed all the regions used for analysis in this study as in Supplementary Table 3.

      e. The purpose of the data presented in Figure 1 b is to compare changes of NRPE1 association in H3K9me3 non-overlapping and overlapping TEs between wild-type and background, yet the figure splits the categories in two subpanels and does neither provide a fold-change number nor a statistical test of the comparison. As before, the figure does not really support the idea that NPRE1 somehow redistribute from its "normal" sites towards heterochromatin as both TE classes seem to show higher NRPE1 binding in h1 mutants.

      There is a statistically significant difference between WT and h1 at both the H3K9me2 marked and unmarked TEs, however, the size of the effect is larger for the H3K9me2 marked TEs (median difference of 0.41 vs 0.16). Median values have now been added to the boxplots so that this is directly viewable to the reader (Fig 1e). Although important exceptions exist (see Fig 5 – regions that lose NRPE1 and DNA methylation), this reflects the general increase in NRPE1 occupancy in h1 mutants throughput the genome, with a consistently stronger effect in heterochromatin. As noted above, we have updated the manuscript to make this point more clearly (abstract line 26, results line 245, discussion line 265).

      f. Panel g is the only attempt to corroborate the redistribution towards heterochromatic regions, but at this scale, the apparent reduction of binding in the chromosome arms may be driven by off-peak differences and normalization problems between different ChIP samples with different signal-to-noise-ratio.

      We describe our normalisation and informatic pipeline in more detail in the Materials and Methods line 365. It is also important to note that the reduction is not only observed at the chromosomal level, but also at specific sites. We called differential peaks between WT and h1 mutant. The "Regions that gain NRPE1 in h1" peaks are more enriched in heterochromatic regions, while " Regions that lose NRPE1 in h1" peaks are more enriched outside heterochromatic regions.

      g. Figure 5: how many regions gain vs lose NRPE1 in h1 mutants? If the "redistribution causes loss" scenario applies, the numbers should overall be balanced but that does not seem the case. The loss case appears to be rather exceptional judging from the zigzagging meta-plot. Are these sites related to the sites taken over by PcG-mediated repression in h1 mutants?

      As described in line 222 (previous version of the manuscript line 206), there are 15,075 sites that gain and 1,859 sites that lose NRPE1 in h1. Comparing these sites to

      H3K27me3 in the Teano et al. study was an excellent suggestion. We compared sites that gain NRPE1 to sites that gain H3K27me3 in h1, finding a statistically significant overlap (2.4 fold enrichment over expected, hypergeometric test p-value 2.1e-71). Reciprocally, sites that lose NRPE1 were significantly enriched for overlap with H3K27me3 loss regions (1.6 fold over expected, hypergeometric test p-value 1.4e-4). This indicates that RdDM and H3K27me3 patterning are similarly modulated by H1. To directly test this, we reanalysed the H3K27me3 ChIP-seq data from Teano et al., finding coincident gain and loss of H3K27me3 at sites that gain and lose NRPE1 in h1. These results are described from line 250 and in Fig 6e, which supports a general role for H1 in preventing heterochromatin encroachment.

      (6) Lines 166ff and Figure 3: The data walk towards the scenario of pathway redistribution but actually find that RdDM plays a minor role overall as a substantial increase in heterochromatin regions occurs in all contexts and is largely independent of RdDM.

      a. How exactly are DNA-methylation data converted across regions to reach a fraction score from 0 to 1? There is no explanation in the legend for the methods that allow to recapitulate.

      We now explain our methods in full in the Materials and Methods and all the code for generating these has now been deposited on GitHub (https://github.com/Zhenhuiz/H1restricts-euchromatin-associated-methylation-pathways-from-heterochromaticencroachment). Briefly, BSMAP is used to calculate the number of reads that are methylated vs unmethylated on a per-cytosine basis across the genome. Next, the DNA methylation fraction in each region is calculated by adding all the methylation fractions per cytosine in a given window, and divided by the total number of cytosines in that same window (ie mC/(unmC+mC)) i.e. this is expressed as a fraction ranging from 0 to 1.

      “0” indicates this region is not methylated, and “1” indicates this region is fully methylated (every cytosine is 100% methylated).  

      b. Kernel plots? These are slang for experts and should be better described. In addition, nothing is really concluded from these plots in the text, although they may be quite informative.

      Kernel density plots show the proportion of TEs that gain or lose methylation in a particular mutant, rather than the overall average as depicted in the methylation metaplots above. We now describe the kernel density plots in more detail in the Figure 3 legend. 

      (7) Figure 4: This could be a very interesting analysis if the reader could actually understand it.

      a. The legend is minimal. What is the meaning of hypo and hyper regions indicated to the right of Figure 4c?

      b. The color scale represents observed/expected values. What exactly does this mean? Mutant vs WT?

      c. Some comparisons in 4a are cryptic, e.g. h1 nrpe1 nrpe1 vs CHH?

      d. Figure 4d focuses on a correlation square of relevance, but why? Interestingly the square does not correspond to any "hypo" or "hyper" label?

      Thank you, we have revised Figure 4 and legend based on these suggestions to clarify all of the above.

      (8) Lines 226 and Figure 6B. De novo (or increased) targeting of SUVH1 to heterochromatic sites in h1 mutants, similar to NRPE1, is used to support the argument that more access allows other chromatin modifiers to encroach. SUVH1 strongly depends on RdDM for its in vivo binding and may be the least conclusive factor to argue for a "general" encroachment mechanism.

      We appreciate the reviewers point here. Something that is entirely independent of RdDM following the same pattern would be stronger evidence in favour of general encroachment. Excitingly, this is exactly what we provide evidence for when investigating the interrelationship with H3K27me3 and we appreciate the reviewer’s suggestion to check this! This data is now described in Figure 6e and line 250.

      Minor:

      (1) Line 23: "Loss of H1 resulted in heterochromatic TE enrichment by NRPE1." This does not seem right. NRPE enrichment as TEs

      Modified, (line 26) thank you.

      (2) Lines 73-74: The idea that DDM1 displaces H1 in heterochromatic TEs is somewhat counterintuitive to model that heterochromatic TEs are unavailable for RdDM because of the presence of H1. Is this displacement non-permanent and directly linked to interaction with CMT2/3 Met1?

      This is a very good question and we agree with the reviewer that the effect of DDM1 may only be transient or insufficient to allow for full RdDM assembly, or indeed there may be a direct interaction between DDM1 and CMTs/MET1. During preparation of these revisions, a structure of Arabidopsis nucleosome bound DDM1 was published, which provides some insight by showing that DDM1 promotes DNA sliding. This is at least consistent with the idea of DDM1 causing transient / non-permanent displacement of H1 that would be insufficient for RdDM establishment. We incorporate discussion of these ideas at line 80.

      (3) Line 85: A bit more background on the Reader activator complex should be given. In fact, the reader may not really care that it was more recently discovered (not really recent btw) but what does it actually do?

      We have quite extensively reconfigured this paragraph to take into account our new finding with H3K27me3, such that there is less emphasis on the reader activator complex. The sentence now reads as follows:

      “We found that h1 antagonizes NRPE1 occupancy throughout the genome, particularly at heterochromatic regions. This effect was not limited to RdDM,  similarly impacting both the methylation reader complex component, SUVH1 (Harris et al., 2018) and polycomb-mediated H3K27me3 (Teano et al., 2023).” (line 95). 

      Also, when describing the experiment the results section (line 241), we now provide more background on SUVH1’s function.

      (4) Lines 80-81: Since it is already shown that RdDM associated small RNAs are more enriched in h1 at heterochromatin, help us to know what is precisely the added value of studying the enrichment of NRPE1 at these sites.

      Good point. We have the following line: ‘...small RNAs are not a direct readout of functional RdDM activity and Pol IV dependent small RNAs are abundant in regions of the genome that do not require RdDM for methylation maintenance and that do not contain Pol V (Stroud et al., 2014).’ (line 90)

      (5) Line 99: This seems to be the only time where the connection between long TEs and heterochromatic regions is mentioned but no source is cited.

      We have added the following appropriate citations: (Bourguet et al., 2021; Zemach et al., 2013). (line 110).

      (6) Line 100: DMRs is used for the first time here without explanation and full text. The abbreviation is introduced later in the text (Line 187).

      Thank you, we now describe DMRs upon first use, line 112.

      (7) Figure 2: Panels 2 c and d should show metaplots for WT and transgenes in one panel. There is something seriously wrong with the normalization in d or the scale for left and right panel is not the same. Neither legend nor methods describe how normalization was performed.

      Thank you for pointing this out, the figure has been corrected. We have updated the Materials and Methods (line 365) and have added codes and pipelines to GitHub to explain the normalisation procedure in more detail (https://github.com/Zhenhuiz/H1restricts-euchromatin-associated-methylation-pathways-from-heterochromaticencroachment).

    1. Author response:

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

      We are very grateful to the reviewers for their constructive comments. Here is a summary of the main changes we made from the previous manuscript version, based on the reviewers’ comments:

      (1) Introduction of a new model, based on a Markov chain, capturing within-trial evolution in search strategy .

      (2) Addition of a new figure investigating inter-animal variations in search strategy.

      (3) Measurement of model fit consistency across 10 simulation repetitions, to prevent the risk of model overfitting.

      (4) Several clarifications have been made in the main text (Results, Discussion, Methods) and figure legends.

      (5) We now provide processed data and codes for analyses and models at GitHub repository

      (6) Simplification of the previous modeling. We realized that the two first models in the previous manuscript version were simply special cases of the third model. Therefore, we retained only the third model, which has been renamed as the ‘mixture model’.

      (7) Modification of Figure 4-6 and Supplementary Figure 7-8 (or their creation) to reflect the aforementioned changes

      Public Reviews:

      Reviewer #1 (Public Review):

      The authors design an automated 24-well Barnes maze with 2 orienting cues inside the maze, then model what strategies the mice use to reach the goal location across multiple days of learning. They consider a set of models and conclude that one of these models, a combined strategy model, best explains the experimental data.

      This study is written concisely and the results presented concisely. The best fit model is reasonably simple and fits the experimental data well (at least the summary measures of the data that were presented).

      Major points:

      (1) One combined strategy (once the goal location is learned) that might seem to be reasonable would be that the animal knows roughly where the goal is, but not exactly where, so it first uses a spatial strategy just to get to the first vestibule, then switches to a serial strategy until it reaches the correct vestibule. How well would such a strategy explain the data for the later sessions? The best combined model presented in the manuscript is one in which the animal starts with a roughly 50-50 chance of a serial (or spatial strategy) from the start vestibule (i.e. by the last session before the reversal the serial and spatial strategies are at ~50-50m in Fig. 5d). Is it the case that even after 15 days of training the animal starts with a serial strategy from its starting point approximately half of the time? The broader point is whether additional examination of the choices made by the animal, combined with consideration of a larger range of possible models, would be able to provide additional insight into the learning and strategies the animal uses.

      Our analysis focused on the evolution of navigation strategies across days and trials. The reviewer raises the interesting possibility that navigation strategy might evolve in a specific manner within each trial, especially on the later days once the environment is learned. To address this possibility, we first examined how some of the statistical distributions, previously analyzed across days, evolved within trials. Consistent with the reviewer’s intuition, the statistical distributions changed within trials, suggesting a specific strategy evolution within trials. Second, we developed a new model, where strategies are represented as nodes of a Markov chain. This model allows potential strategy changes after each vestibule visit, according to a specific set of transition probabilities. Vestibules are chosen based on the same stochastic processes as in the previous model. This new model could be fitted to the experimental distributions and captured both the within-trial evolution and the global distributions. Interestingly, the trials were mostly initiated in the random strategy (~67% chance) and to a lesser extent in the spatial strategy (~25% chance), but rarely in the serial strategy (~8% chance). This new model is presented in Figure 6.

      (2) To clarify, in the Fig. 4 simulations, is the "last" vestibule visit of each trial, which is by definition 0, not counted in the plots of Fig. 4b? Otherwise, I would expect that vestibule 0 is overrepresented because a trial always ends with Vi = 0.

      The last vestibule visit (vestibule 0 by definition) is counted in the plots of Fig.4b. We initially shared the same concern as the reviewer. However, upon further consideration, we arrived at the following explanation: A factor that might lead to an overrepresentation of vestibule 0 is the fact that, unlike other vestibules, it has to be contained in each trial, as trials terminated upon the selection of vestibule 0. Conversely, a factor that might contribute to an underrepresentation of vestibule 0 is that, unlike other vestibules, it cannot be counted more than once per trial. Somehow these two factors seem to counterbalance each other, resulting in no discernible overrepresentation or underrepresentation of vestibule 0 in the random process. 

      Reviewer #2 (Public Review):

      This paper uses a novel maze design to explore mouse navigation behaviour in an automated analogue of the Barnes maze. Overall I find the work to be solid, with the cleverly designed maze/protocol to be its major strength - however there are some issues that I believe should be addressed and clarified.

      (1) Whilst I'm generally a fan of the experimental protocol, the design means that internal odor cues on the maze change from trial to trial, along with cues external to the maze such as the sounds and visual features of the recording room, ultimately making it hard for the mice to use a completely allocentric spatial 'place' strategy to navigate. I do not think there is a way to control for these conflicts between reference frames in the statistical modelling, but I do think these issues should be addressed in the discussion.

      It should be pointed out that all cues on the maze (visual, tactile, odorant) remained unchanged across trials, since the maze was rotated together with goal and guiding cues. Furthermore, the maze was equipped with an opaque cover to prevent mice from seeing the surrounding room (the imaging of mouse trajectories was achieved using infrared light and camera). It is however possible that some other cues such as room sounds and odors could be perceived and somewhat interfered with the sensory cues provided inside the maze. We have now mentioned this possibility in the discussion.

      (2) Somewhat related - I could not find how the internal maze cues are moved for each trial to demarcate the new goal (i.e. the luminous cues) ? This should be clarified in the methods.

      The luminous cues were fixed to the floor of the arena. Consequently, they rotated along with the arena as a unified unit, depicted in figure 1. We have added some clarifications in Figure 1 legend and methods.

      (3) It appears some data is being withheld from Figures 2&3? E.g. Days 3/4 from Fig 2b-f and Days 1-5 on for Fig 3. Similarly, Trials 2-7 are excluded from Fig 3. If this is the case, why? It should be clarified in the main text and Figure captions, preferably with equivalent plots presenting all the data in the supplement.

      The statistical distributions for all single days/trials are shown in the color-coded panels of Figure2&3. In the line plots of Figure2&3, we show only the overlay of 2-3 lines for the sake of clarity. The days/trials represented were chosen to capture the dynamic range of variability within the distributions. We have added this information in the figure legends.

      (4) I strongly believe the data and code should be made freely available rather than "upon reasonable request".

      Matrices of processed data and various codes for simulations and analyses are now available at https://github.com/ sebiroyerlab/Vestibule_sequences.

      Reviewer #3 (Public Review):

      Royer et al. present a fully automated variant of the Barnes maze to reduce experimenter interference and ensure consistency across trials and subjects. They train mice in this maze over several days and analyze the progression of mouse search strategies during the course of the training. By fitting models involving stochastic processes, they demonstrate that a model combined of the random, spatial, and serial processes can best account for the observed changes in mice's search patterns. Their findings suggest that across training days the spatial strategy (using local landmarks) was progressively employed, mostly at the expense of the random strategy, while the serial strategy (consecutive nearby vestibule check) is reinforced from the early stages of training. Finally, they discuss potential mechanistic underpinnings within brain systems that could explain such behavioral adaptation and flexibility.

      Strength:

      The development of an automated Barnes maze allows for more naturalistic and uninterrupted behavior, facilitating the study of spatial learning and memory, as well as the analysis of the brain's neural networks during behavior when combined with neurophysiological techniques. The system's design has been thoughtfully considered, encompassing numerous intricate details. These details include the incorporation of flexible options for selecting start, goal, and proximal landmark positions, the inclusion of a rotating platform to prevent the accumulation of olfactory cues, and careful attention given to atomization, taking into account specific considerations such as the rotation of the maze without causing wire shortage or breakage. When combined with neurophysiological manipulations or recordings, the system provides a powerful tool for studying spatial navigation system.

      The behavioral experiment protocols, along with the analysis of animal behavior, are conducted with care, and the development of behavioral modeling to capture the animal's search strategy is thoughtfully executed. It is intriguing to observe how the integration of these innovative stochastic models can elucidate the evolution of mice's search strategy within a variant of the Barnes maze.

      Weakness:

      (1) The development of the well-thought-out automated Barnes maze may attract the interest of researchers exploring spatial learning and memory. However, this aspect of the paper lacks significance due to insufficient coverage of the materials and methods required for readers to replicate the behavioral methodology for their own research inquiries.

      Moreover, as discussed by the authors, the methodology favors specialists who utilize wired recordings or manipulations (e.g. optogenetics) in awake, behaving rodents. However, it remains unclear how the current maze design, which involves trapping mice in start and goal positions and incorporating angled vestibules resulting in the addition of numerous corners, can be effectively adapted for animals with wired implants.

      The reviewer is correct in pointing out that the current maze design is not suitable for performing experiments with wired implant, particularly due to the maze’s enclosed structure and the access to the start/goal boxes through side holes. Instead, pharmacogenetics and wireless approaches for optogenetic and electrophysiology would need to be used. We have now mentioned this limitation in the discussion.

      (2) Novelty: In its current format, the main axis of the paper falls on the analysis of animal behavior and the development of behavioral modeling. In this respect, while it is interesting to see how thoughtfully designed models can explain the evolution of mice search strategy in a maze, the conclusions offer limited novel findings that align with the existing body of research and prior predictions.

      We agree with the reviewer that our study is weakly connected to previous researches on hippocampus and spatial navigation, as it consists mainly of animal behavior analysis and modeling and addresses a relatively unexplored topic. We hope that the combination of our behavioral approach with optogenetic and electrophysiology will allow in the future new insights that are in line with the existing body of research.

      (3) Scalability and accessibility: While the approach may be intriguing to experts who have an interest in or are familiar with the Barnes maze, its presentation seems to primarily target this specific audience. Therefore, there is a lack of clarity and discussion regarding the scalability of behavioral modeling to experiments involving other search strategies (such as sequence or episodic learning), other animal models, or the potential for translational applications. The scalability of the method would greatly benefit a broader scientific community. In line with this view, the paper's conclusions heavily rely on the development of new models using custom-made codes. Therefore, it would be advantageous to make these codes readily available, and if possible, provide access to the processed data as well. This could enhance comprehension and enable a larger audience to benefit from the methodology.

      The current approach might indeed extend to other species in equivalent environments and might also constitute a general proof of principle regarding the characterization of animal behaviors by the mixing of stochastic processes. We have now mentioned these points in the discussion.

      As suggest by the reviewer, we have now provided model/simulation codes and processed data to replicate the figures, at https://github.com/sebiroyerlab/Vestibule_sequences

      (4) Cross-validation of models: The authors have not implemented any measures to mitigate the risk of overfitting in their modeling. It would have been beneficial to include at least some form of cross-validation with stochastic models to address this concern. Additionally, the paper lacks the presence of analytics or measures that assess and compare the performance of the models.

      To avoid the risk of model overfitting, the most appropriate solution appeared to be repeating the simulations several times and examining the consistency of the obtained parameters across repetitions. For the mixture model, we now show in Supplementary figure 7 the probabilities obtained from 10 repetitions of the simulation. Similarly, for the Markov chain model, the probabilities obtained from 10 repetitions of the simulation are shown in Figure 6.

      Regarding model comparison, we have simplified our mixture model into only one model, as we realized the 2 other models in the previous manuscript version were simply special cases of the 3rd model. Nevertheless, comparison was still needed for the estimation for the best value of N (the number of consecutive segments that a strategy lasts) in the mixture model. We now show the comparison of mean square errors obtained for different values of N, using t-test across 10 repetitions of the simulations (Figure 5c).

      (5) Quantification of inter-animal variations in strategy development: It is important to investigate, and address the argument concerning the possibility that not all animals recruit and develop the three processes (random, spatial, and serial) in a similar manner over days of training. It would be valuable to quantify the transition in strategy across days for each individual mouse and analyze how the population average, reflecting data from individual mice, corresponds to these findings. Currently, there is a lack of such quantification and analysis in the paper.

      We have added a figure (Supplementary figure 8) showing the mixture model matching analyses for individual animals. A lot of variability is indeed observed across animals, with some animals displaying strong preferences for certain strategies compare to others. The average across mouse population showed a similar trend as the result obtained with the pooled data.

      Recommendations for the authors:

      Summary of Reviewer Comments:

      (1) In its present form, the manuscript lacks sufficient coverage of the materials and methods necessary for readers to replicate the behavioral methodology in their own research inquiries. For instance, it would be beneficial to clarify how the cues are rotated relative to the goal.

      (2) The models may be over-fitted, leading to spurious conclusions, and cross-validation is necessary to rule out this possibility.

      (3) The specific choice of the three strategies used to fit behavior in this model should be better justified, as other strategies may account for the observed behavior.

      (4) The study would benefit from an analysis of behavior on an animal-by-animal basis, potentially revealing individual differences in strategies.

      (5) Spatial behavior is not necessarily fully allocentric in this task, as only the two cues in the arena can be used for spatial orientation, unlike odor cues on the floor and sound cues in the room. This should be discussed.

      (6) Making the data and code fully open source would greatly strengthen the impact of this study.

      In addition, each reviewer has raised both major and minor concerns which should be addressed if possible.

      Reviewer #1 (Recommendations For The Authors):

      Minor points:

      (1) Change "tainted" to "tinted" in Fig. 1a

      (2) Should note explicitly in Fig. 2d that the goal is at vestibule 0, and also in the legend

      (3) Fig. 3 legend should say "c-e)", not "c-f)"

      (4) Supplementary Fig. 8 legend repeats "d)" twice

      Reviewer #2 (Recommendations For The Authors):

      Packard & McGaugh 1996 is cited twice as refs 5 and 14

      Reviewer #3 (Recommendations For The Authors):

      - Figure 3: Please correct the labels referenced as "c-f)" in the figure's legend.

      - Rounding numbers issue on page 4: 82.62% + 17.37% equals 99.99%, not 100%.

      We fixed all minor points. We are very thankful to the reviewers for their constructive comments.

    1. Author response:

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

      We are thankful to the reviewers and the editor for their detailed feedback, insightful suggestions, and thoughtful assessment of our work. Our point-by-point responses to the comments and suggestions are below.

      The revised manuscript has taken into account all the comments of the three reviewers. Modifications include corrections to errors in spelling and unit notation, additional quantification, improvements to the clarity of the language in some places, as well as additional detail in the descriptions of the methods, and revisions to the figures and figure legends.

      We have also undertaken additional analyses and added materials in response to reviewer suggestions. In brief:

      In response to a suggestion from Reviewer #1, we added Figure 6-1 to show examples of the calcium traces of individual fish and individual ROIs from the condensed data in Figure 6. We revised Figure 7 as follows:

      • We added an analysis of the duration of the response to shock to address comments from Reviewers #2 and #3.

      • In response to Reviewer #3, we added histograms showing the distribution of the amplitudes of the calcium signals in the gsc2 and rln3a neurons to show, without relying on the detection of peaks in the calcium trace, that the rln3a neurons have more oscillations in activity.

      We added Figure 8-2 in response to the suggestion from Reviewer #3 to analyze turning behavior in larvae with ablated rln3a neurons.

      To address Reviewer #2’s suggestion to show how the ablated transgenic animals compare to the non-ablated transgenic animals of the same genotype, we have added this analysis as Figure 8-3.

      A detailed point-by-point is as follows:

      The reviewers agree that the study of Spikol et al is important, with novel findings and exciting genetic tools for targeting cell types in the nucleus incertus. The conclusions are overall solid. Results could nonetheless be strengthened by performing few additional optogenetic experiments and by consolidating the analysis of calcium imaging and behavioral recordings as summarized below.

      (1) Light pulses used for optogenetic-mediated connectivity mapping were very long (5s), which could lead to non specific activation of numerous population of neurons than the targeted ones. To confirm their results, the authors should repeat their experiments with brief 5-50ms (500ms maximum) -long light pulses for stimulation.

      As the activity of the gsc2 neurons is already increased by 1.8 fold (± 0.28) within the first frame that the laser is activated (duration ~200 msec), it is unlikely that that the observed response is due to non-specific activation induced by the long light pulse.

      (2) In terms of analysis, the authors should improve :

      a) The detection of calcium events in the "calcium trace" showing the change in fluorescence over time by detecting the sharp increase in the signal when intracellular calcium rises;

      We have added an additional analysis to Figure 7 that does not rely on detection of calcium peaks. See response to Reviewer #3.

      b) The detection of bouts in the behavioral recordings by measuring when the tail beat starts and ends, thereby distinguishing the active swimming during bouts from the immobility observed between bouts.

      Our recordings capture the entire arena that the larva can explore in the experiment and therefore lack the spatial resolution to capture and analyze the tail beat. Rather, we measured the frequency and length of phases of movement in which the larva shows no more than 1 second of immobility. To avoid confusion with studies that measure bouts from the onset of tail movement, we removed this term from the manuscript and refer to activity as phases of movement.

      (3) The reviewers also ask for more precisions in the characterization of the newly-generated knock-in lines and the corresponding anatomy as explained in their detailed reports.

      Please refer to the point-by-point request for additional details that have now been added to the manuscript.

      Reviewer #1 (Recommendations For The Authors):

      The conclusions of this paper are mostly well supported by data, but some technical aspects, especially about calcium imaging and data analysis, need to be clarified.

      (1) Both the endogenous gsc2 mRNA expression and Tg(gsc2:QF2) transgenic expression are observed in a neuronal population in the NI, but also in a more sparsely distributed population of neurons located more anteriorly (for example, Fig. 2B, Fig. 5A). The latter population is not mentioned in the text. It would be necessary to clarify whether or not this anterior population is also considered as the NI, and whether this population was included for the analysis of the projection patterns and ablation experiments.

      The sparsely distributed neurons had been mentioned in the Results, line 134, but we have now added more detail. In line 328, we have clarified that: “As the sparsely distributed anterior group of gsc2 neurons (Fig. 2B, C) are anatomically distinct from the main cluster and not within the nucleus incertus proper, they were excluded from subsequent analyses.”

      (2) Both Tg(gsc2:QF2) and Tg(rln3a:QF2) transgenic lines have the QF genes inserted in the coding region of the targeted genes. This probably leads to knock out of the gene in the targeted allele. Can the authors mention whether or not the endogenous expression of gsc2 and rln3a was affected in the transgenic larvae? Is it possible that the results they obtained using these transgenic lines are affected by the (heterozygous or homozygous) mutation of the targeted genes?

      Figure 8-1 includes in situ hybridization for gsc2 and rln3a in heterozygous Tg(gsc2:QF2)c721; Tg(QUAS:GFP)c578 and Tg(rln3a:QF2; he1.1:YFP)c836; Tg(QUAS:GFP)c578 transgenic larvae.

      The expression of gsc2 is unaffected in Tg(gsc2:QF2)c721; Tg(QUAS:GFP)c578 heterozygotes

      (Fig. 8-1A), whereas the expression of rln3a is reduced in Tg(rln3a:QF2; he1.1:YFP)c836; Tg(QUAS:GFP)c578 heterozygous larvae (Fig. 8-1D), as mentioned in the legend for Figure 8-1. We confirmed these findings by comparing endogenous gene expression between transgenic and non-transgenic siblings that were processed for RNA in situ hybridization in the same tube.

      The behavioral results we obtained are not due to rln3a heterozygosity because comparisons were made with sibling larvae that are also heterozygous for Tg(rln3a:QF2; he1.1:YFP)c836; Tg(QUAS:GFP)c578, as stated in the Figure 8 legend.

      (3) Optogenetic activation and simultaneous calcium imaging is elegantly designed using the combination of the orthogonal Gal4/UAS and QF2/QUAS systems (Fig. 6). However, I have some concerns about the analysis of calcium responses from a technical point of view. Their definition of ΔF/F in this manuscript is described as (F-Fmin)/(Fmax-Fmin) (see line 1406). This is confusing because it is different from the conventional definition of ΔF/F, which is F-F0/F0, where F0 is a baseline GCaMP fluorescence. Their way of calculating the ΔF/F is inappropriate for measuring the change in fluorescence relative to the baseline signal because it rather normalizes the amplitude of the responses across different ROIs. The same argument applies to the analyses done for Fig. 7.

      We have taken a careful look at our analyses and replotted the data using F-F0/F0. However, this only changes Y-axis values and does not change the shape of the calcium trace or the change in signal upon stimulation. Both metrics (F-F0/F0 and (F-Fmin)/(Fmax-Fmin)) adjust the fluorescence values of each ROI to its own baseline.

      (4) The %ΔF/F plots shown in Fig.6 are highly condensed showing the average of different ROIs (cells) within one fish and then the average of multiple fish. It would be helpful to see example calcium traces of individual ROIs and individual fish to know the variability across ROIs and fish. Also, It would be helpful to know how much laser power (561 nm laser) was used to photostimulate ReaChR.

      Laser power (5%) was added to the section titled Calcium Signaling in Methods.

      In Figure 6, shading in the %ΔF/F plots (D, D’, E, E’, F, F’, G, G’, H, H’) represents the variability across ROIs, and the dot plots (D’’, E’’, F’’, G’’, H’’) show the variability across fish (where each data point represents an individual fish). We have now also added Figure 6-1 with examples of calcium traces from individual fish and individual ROIs.

      (5) Some calcium traces presented in Fig. 6 (Fig. 6D, D', F, H, H') show discontinuous fluctuations at the onset and offset of the photostimulation period. Is this caused by some artifacts introduced by switching the settings for the photostimulation? The authors should mention if there are some alternative explanations for this discontinuity.

      As noted by the reviewer, this artifact does result from switching the settings for photostimulation, which we mention in the legend for Figure 6.

      (6) In the introduction, they mention that the griseum centrale is a presumed analogue of the NI (lines 74-75). It would be helpful for the readers to better understand the brain anatomy if the authors could discuss whether or not their findings on the gsc2 and rln3a NI neurons support this idea.

      Our findings on the gsc2 and rln3a neurons support the idea that the griseum centrale of fish is the analogue of the mammalian NI. We have now edited the text in the third paragraph of the discussion, line 1271, to make this point more clearly: “By labeling with QUAS-driven fluorescent reporters, we determined that the anatomical location, neurotransmitter phenotype, and hodological properties of gsc2 and rln3a neurons are consistent with NI identity, supporting the assertion that the griseum centrale of fish is analogous to the mammalian NI. Both groups of neurons are GABAergic, reside on the floor of the fourth ventricle and project to the interpeduncular nucleus.”

      Reviewer #2 (Recommendations For The Authors):

      Major comments:

      (1) Throughout the figures a need for more precision and reference in the anatomical evidence:

      • Specify how many planes over which height were projected for each Z-projection in Figure 1,2,3, ....

      We added this information to the last paragraph of the section titled Confocal Imaging within the Materials and Methods.

      • Provide the rhombomere numbers, deliminate the ventricles & always indicate on the panel the orientation (Rostral Caudal, Left Right or Ventral Dorsal) for Figure 1 panels D-F , Figure 2-1B-G, Figure 2-2A-C in the adult brain, Figure 3.

      We annotated Figures 2-1 and 2-2 as suggested. We also indicated the orientation (anterior to the top or anterior to the left) in all figure legends. For additional context on the position of gsc2 and rln3a neurons within the larval brain, refer to Fig. 1A-C’, Fig. 1-2A, Fig. 2, Fig. 4 and Fig. 5.

      • Add close up when necessary: Figure 2-2A-C, specify in the text & in the figure where are the axon bundles from the gsc2+ neurons in the adult brain- seems interesting and is not commented on?

      We added a note to the legend of Figure 2-2: Arrowheads in B and B’ indicate mApple labeling of gsc2 neuronal projections to the hypothalamus. We also refer to Fig 2-2B, B’ in the Results section titled Distinct Projection Patterns of gsc2 and rln3a neurons.

      • keep the same color for one transgene within one figure: example, glutamatergic neurons should always be the same color in A,B,C - it is confusing as it is.

      We have followed the reviewer’s suggestion and made the color scheme consistent in Figure 3.

      • Movies: add the labels (which transgenic lines in which color, orientation & anatomical boundaries for NI, PAG, any other critical region that receives their projections and the brain ventricle boundaries) on the anatomical movies in supplemental (ex Movie 4-1 for gsc2 neurons and 4-2 for rln3 neurons: add cerebellum, IPN, raphe, diencephalon, and rostral and caudal hypothalamus, medulla for 4-1 as well as lateral hypothalamus and optic tectum for 42); add the ablated region when necessary.

      We added more detail to the movie legends. Please refer to Figure 4 for additional anatomical details.

      • for highlighting projections from NI neurons and distinguish them from the PAG neurons, the authors elegantly used 2 Photon ablation of one versus the other cluster: this method is valid but we need more resolution that the Z stacks added in supplemental by performing substraction of before and after maps.

      We are not sure what the author meant by subtraction as there are no before and after images in this experiment. Larvae underwent ablation of cell bodies and were imaged one day later in comparison to unablated larvae.

      In particular, it is not clear to me if both PAG and NI rln3a neurons project to medulla - can the authors specify this point & the comparison between intact & PAG vs NI ablation maps? The authors should resolve better the projections to all targeted regions of NI gsc2 neurons and differentiate them from other PAG gsc2 neurons, same for rln3a neurons.

      We have clarified this point on line 549.

      Make sure to mention in the result section the duration between ablation & observation that is key for the axons to degrade.

      We always assessed degeneration of neuronal processes at 1-day post-ablation.

      (“2) calcium imaging experiments:

      a) with optogenetic connectivity mapping:

      the authors combine an impressive diverse set of optogenetic actuators & sensors by taking advantage of the QUAS/QF2 and UAS/GAL4 systems to test connectivity from Hb-IPN onto gsc2 and rln3 neurons.

      The experiments are convincing but the choice of the duration of the stimulation (5s) is not adequate to test for direct connectivity: the authors should make sure that response in gsc2 neurons is observed with short duration (50ms-1s max).

      As noted above:

      “As the activity of the gsc2 neurons is already increased by 1.8 fold (± 0.28) within the first frame that the laser is activated (duration ~200 msec), it is unlikely that that the observed response is due to non-specific activation induced by the long light pulse.”

      note: Specify that the gsc2 neurons tested are in NI.

      We have edited the text accordingly in the Results section titled Afferent input to the NI from the dHb-IPN pathway.

      b) for the response to shock: in the example shown for rln3 neurons, the activity differs before and after the shock with long phases of inhibition that were not seen before. Is it representative? the authors should carefully stare at their data & make sure there is no difference in activity patterns after shock versus before.

      We reexamined the responses for each of the rln3a neurons individually and confirmed that, although oscillations in activity are frequent, the apparent inhibition (excursions below baseline) are an idiosyncratic feature of the particular example shown.

      (3) motor activity assay:

      a) there seems to be a misconception in the use of the word "bout" to estimate in panels H and I bout distance and duration and the analysis should be performed with the criterion used by all in the motor field:

      As we know now well based on the work of many labs on larval zebrafish (Orger, Baier, Engert, Wyart, Burgess, Portugues, Bianco, Scott, ...), a bout is defined as a discrete locomotor event corresponding to a distance swam of typically 1-6mm, bout duration is typically 200ms and larvae exhibit a bout every s or so during exploration (see Mirat et al Frontiers 2013; Marques et al Current Biology 2018; Rajan et al. Cell Reports 2022).

      Since the larval zebrafish has a low Reynolds number, it does not show much glide and its movement corresponds widely to the active phase of the tail beats.

      Instead of detecting the active (moving) frames as bouts, the authors however estimate these values quite off that indicate an error of calibration in the detection of a movement: a bout cannot last for 5-10s, nor can the fish swim for more than 1 cm per bout (in the definition of the authors, bout last for 5-10 s, and bout correspond to 10 cm as 50 cm is covered in 5 bouts).

      The authors should therefore distinguish the active (moving) from inactive (immobile) phase of the behavior to define bouts & analyze the corresponding distance travelled and duration of active swimming. They would also benefit from calculating the % of time spent swimming in order to test whether the fish with ablated rln3 neurons change the fraction of the time spent swimming.

      As noted above:

      Our recordings capture the entire arena that the larva can explore in the experiment and therefore lack the spatial resolution to capture and analyze the tail beat. Rather, we measured the frequency and length of phases of movement in which the larva shows no more than 1 second of immobility. To avoid confusion with studies that measure bouts from the onset of tail movement, we removed this term from the manuscript and refer to activity as phases of movement.

      Note that a duration in seconds is not a length and that the corresponding symbol for seconds in a scientific publication is "s" and not "sec".

      We have corrected this.

      b) controls in these experiments are key as many clutches differ in their spontaneous exploration and there is a lot of variation for 2 min long recordings (baseline is 115s). The authors specify that the control unablated are a mix of siblings; they should show us how the ablated transgenic animals compare to the non ablated transgenic animals of the same clutch.

      The unablated Tg(gsc2:QF2)c721; Tg(QUAS:GFP)c578 and Tg(rln3a:QF2, he1.1:YFP)c836; Tg(QUAS:GFP)c578 larvae in the control group are siblings of ablated larvae. We repeated the analyses using either the Tg(gsc2:QF2)c721; Tg(QUAS:GFP)c578 or Tg(rln3a:QF2, he1.1:YFP)c836; Tg(QUAS:GFP)c578 larvae only as controls and added the results in Figure 8-3. Although the statistical power is slightly reduced due to a smaller number of samples in the control group, the conclusions are the same, as the behavior of Tg(gsc2:QF2)c721; Tg(QUAS:GFP)c578 and Tg(rln3a:QF2, he1.1:YFP)c836; Tg(QUAS:GFP)c578 unablated larvae is indistinguishable.

      Minor comments:

      (1) Anatomy :

      • Add precision in the anatomy in Figure 1:

      • Improve contrast for cckb.

      The contrast is determined by the signal to background ratio from the fluorescence in situ hybridization. Increasing the brightness would increase both the signal and the background, as any modification must be applied to the whole image.

      • since the number of neurons seems low in each category, could you quantify the number of rln3+, nmbb+, gsc2+, cckb+ neurons in NI?

      Quantification of neuronal numbers has been added to the first Results section titled Identification of gsc2 neurons in the Nucleus Incertus, lines 219-224.

      note: indicate duration for the integral of the DF/F in s and not in frames.

      We have added this in the legends for Figures 6 and 7 and in Materials and Methods.

      (2) Genetic tools:

      To generate a driver line for the rln3+ neurons using the Q system, the authors used the promoter for the hatching gland in order to drive expression in a structure outside of the nervous system that turns on early and transiently during development: this is a very elegant approach that should be used by many more researchers.

      If the her1 construct was integrate together with the QF2 in the first exon of the rln3 locus as shown in Figure 2, the construct should not be listed with a ";" instead of a "," behind rln3a:QF2 in the transgene name. Please edit the transgene name accordingly.

      We have edited the text accordingly.

      (3) Typos:

      GABAergic neurons is misspelled twice in Figure 3.

      Thank you for catching this. We have corrected the misspellings.

      Reviewer #3 (Recommendations For The Authors):

      • More analysis should be done to better characterize the calcium activity of gsc2 and rln3a populations. Specifically:

      Spontaneous activity is estimated by finding peaks in the time-series data, but the example in Fig7 raises concerns about this process: Two peaks for the gsc2 cell are identified while numerous other peaks of apparently similar SNR are not detected. Moreover, the inset images suggest GCaMP7a expression might be weaker in the gsc2 transgenic and as such, differences in peak count might be related to the SNR of the recordings rather than underlying activity. Overall, the process for estimating spontaneous activity should be more rigorous.

      To not solely rely on the identification of peaks in the calcium traces, we also plotted histograms of the amplitudes of the calcium signals for the rln3a and gsc2 neurons. The histograms show that the amplitudes of the rln3a calcium signals frequently occur at small and large values (suggesting large fluctuations in activity), whereas the amplitudes of the gsc2 calcium signals occur most frequently at median values. We added this analysis to a revised Figure 7.

      Interestingly, there are a number of large negative excursions in the calcium data for the rln3a cell - what is the authors' interpretation of these? Could it be that presynaptic inhibition via GABA-B receptors in dIPN might influence dIPN-innervating rln3a neurons?

      As noted above:

      We reexamined the responses for each of the rln3a neurons individually and confirmed that, although oscillations in activity are frequent, the apparent inhibition (excursions below baseline) are an idiosyncratic feature of the particular example shown.

      Regarding shock-evoked activity, the authors state "rln3a neurons showed ... little response to shock", yet the immediate response after shock appears very similar in gsc2 vs rln3a cells (approx 30 units on the dF/F scale). The subsequent time-course of the response is what appears to distinguish gsc2 versus rln3a; it might thus be useful to separately quantify the amplitude and decay time constant of the shock evoked response for the two populations.

      The reviewer is correct that the difference between the gsc2 and rln3a neurons in the response to shock is dependent on the duration of time post-shock that is analyzed. Thus, the more relevant feature is the length of the response rather than the size. To reflect this, we compared the average length of responses for the gsc2 and rln3a neurons. We have now added this analysis to Figure 7 and updated the text accordingly.

      • The difference in spontaneous locomotor behavior is interesting and the example tracking data suggests there might also be differences in turn angle distribution and/or turn chain length following rln3 NI ablations. I would recommend the authors consider exploring this.

      Thank you for this suggestion. We wrote additional code to quantify turning behavior and found that larvae with rln3a NI neurons ablated do indeed have a statistically significant increase in turning compared to other groups. We now show this analysis as Figure 8-2 and we added an explanation of the quantification of turning behavior to the Methods section titled Locomotor assay.

      • I didn't follow the reasoning in the discussion that activity of rln3a cells may control transitions between phases of behavioral activity and inactivity. The events (at least those that are detected) in Fig7 occur with an average interval exceeding 30 s, yet swim bouts occur at a frequency around 1 Hz. The authors should clarify their hypothesis about how these disparate timescales might be connected.

      As noted above:

      Our recordings capture the entire arena that the larva can explore in the experiment and therefore lack the spatial resolution to capture and analyze the tail beat. Rather, we measure the frequency and length of phases of movement in which the larva shows no more than 1 second of immobility. To avoid confusion with studies that measure bouts from the onset of tail movement, we removed this term from the manuscript and refer to activity as phases of movement.

      • Fig2-2: Images are ordered from (A, B, C) anterior to (A', B', C') posterior. Its not clear what this means and images appear to be in sequence A, A', B, B'.... please clarify and consider including a cartoon of the brain in sagittal view showing location of sections indicated.

      We clarified the text in the Figure 2-2 legend and added a drawing of the brain showing the location of the sections.

      • In Fig7, why are 300 frames analyzed pre/post shock? Even for gsc2, the response appears complete in ~100 frames.

      Reviewer #2 also pointed out that the difference between the gsc2 and rln3a neurons in the response to shock is dependent on the duration of time post-shock that is analyzed. Thus, the more relevant feature is the length of the response rather than the size. To reflect this, we compared the average length of response for the gsc2 and rln3a neurons and modified the text and Figure as described above.

      • What are the large negative excursions in the calcium signal in the rln3a data (Fig7E)?

      See response to Reviewer # 2, repeated below:

      We looked through each of the responses of individual rln3a neuron and confirmed that, although oscillations in activity are frequent among the rln3a neurons, the apparent inhibition (excursions below baseline) are an idiosyncratic feature of the particular example shown.

      • There are several large and apparently perfectly straight lines in the fish tracking examples (Fig8) suggestive of tracking errors (ie. where the tracked centroid instantaneously jumps across the camera frame). Please investigate these and include analysis of the distribution of swim velocities to support the validity of the tracking data.

      The reason for this is indeed imperfect tracking resulting in frames in which the tracker does not detect the larva. The result is that the larva appears to move 1 cm or more in a single frame. However, analysis of the distribution of distances across all frames shows that these events (movement of 1 cm or more in a single frame) are rare (less than 0.04%), and there are no systematic differences that would explain the differences in locomotor behavior presented in Fig. 8. A summary of the data is as follows:

      Controls: 0.0249% of distances 1 cm or greater gsc2 neurons ablated: 0.0302% of distances 1 cm or greater rln3a NI neurons ablated: 0.0287% of distances 1 cm or greater rln3a PAG neurons ablated: 0.0241% of distance 1 cm or greater

      • Insufficient detail is provided in the methods about how swim bouts are detected (and their durations extracted) from the centroids tracking data. Please expand detail in this section.

      We added an explanation to the Methods section titled Locomotor assay.

    1. As adoption of nanopore sequencing technology continues to advance, the need to maintain large volumes of raw current signal data for reanalysis with updated algorithms is a growing challenge. Here we introduce slow5curl, a software package designed to streamline nanopore data sharing, accessibility and reanalysis. Slow5curl allows a user to fetch a specified read or group of reads from a raw nanopore dataset stored on a remote server, such as a public data repository, without downloading the entire file. Slow5curl uses an index to quickly fetch specific reads from a large dataset in SLOW5/BLOW5 format and highly parallelised data access requests to maximise download speeds. Using all public nanopore data from the Human Pangenome Reference Consortium (>22 TB), we demonstrate how slow5curl can be used to quickly fetch and reanalyse signal reads corresponding to a set of target genes from each individual in large cohort dataset (n = 91), minimising the time, egress costs, and local storage requirements for their reanalysis. We provide slow5curl as a free, open-source package that will reduce frictions in data sharing for the nanopore community: https://github.com/BonsonW/slow5curlCompeting Interest Statement

      Reviewer 2. Yunfan Fan

      Comments to Author: In this manuscript, the authors demonstrate a highly streamlined method for downloading targeted subsets of raw ONT electrical signals, for re-analysis. In my view, this will be a highly useful tool for researchers working with public nanopore data, and I hope to see its widespread adoption. The benchmarks are well-described in the manuscript, and the code is publicly available and well-documented. I have no other notes or suggestions for the authors.

    1. Dynamic functional connectivity (dFC) has become an important measure for understanding brain function and as a potential biomarker. However, various methodologies have been developed for assessing dFC, and it is unclear how the choice of method affects the results. In this work, we aimed to study the results variability of commonly-used dFC methods. We implemented seven dFC assessment methods in Python and used them to analyze fMRI data of 395 subjects from the Human Connectome Project. We measured the pairwise similarity of dFC results using several similarity metrics in terms of overall, temporal, spatial, and inter-subject similarity. Our results showed a range of weak to strong similarity between the results of different methods, indicating considerable overall variability. Surprisingly, the observed variability in dFC estimates was comparable to the expected natural variation over time, emphasizing the impact of methodological choices on the results. Our findings revealed three distinct groups of methods with significant inter-group variability, each exhibiting distinct assumptions and advantages. These findings highlight the need for multi-analysis approaches to capture the full range of dFC variation. They also emphasize the importance of distinguishing neural-driven dFC variations from physiological confounds, and developing validation frameworks under a known ground truth. To facilitate such investigations, we provide an open-source Python toolbox that enables multi-analysis dFC assessment. This study sheds light on the impact of dFC assessment analytical flexibility, emphasizing the need for careful method selection and validation, and promoting the use of multi-analysis approaches to enhance reliability and interpretability of dFC studies.Competing Interest StatementThe authors have declared no competing interest.

      Reviewer 2. Nicolas Farrugia

      Comments to Author: Summary of review This paper fills a very important gap in the literature investigating time-varying functional connectivity (or dynamic functional connectivity, dFC), by measuring analytical flexibility of seven different dFC methods. An impressive amount of work has been put up to generate a set of convincing results, that essentially show that the main object of interest of dFC, which is the temporal variability of connectivity, cannot be measured with a high consistency, as this variability is of the same order of magnitude or even higher than the changes observed across different methods on the same data. In this very controversial field, it is very remarkable to note that the authors have managed to put together a set of analysis to demonstrate this in a very clear and transparent way. The paper is very well written, the overall approach is based on a few assumptions that make it possible to compare methods (e.g. subsampling of temporal aspects of some methods, spatial subsampling), and the provided analysis is very complete. The most important results are condensed in a few figures in the main manuscript, which is enough to convey the main messages. The supplementary materials provide an exhaustive set of additional results, which are shortly discussed one by one. Most importantly, the authors have provided an open source implementation of 7 main dfc methods. This is very welcome for the community and for reproductibility, and is of course particularly suited for this kind of contribution. A few suggestions follow. Clarification questions and suggestions : 1- How was the uniform downsampling of 286 ROI to 96 done ? Uniform in which sense ? According to the RSN ? Were ROIs regrouped with spatial contiguity ? I understand this was done in order to reduce computational complexity and to harmonize across methods, but the manuscript would benefit from having an added sentence to explain what was done. 2- Table A in figure 1 shows the important hyperparameters (HP) for each method, but the motivations regarding the choice of HP for each method is only explained in the discussion (end of page 11, "we adopted the hyperparameter values recommended by the original paper or consensus among the community for each method"). It would be better to explain it in the methods, and then only discuss why this can be a limitation, in the discussion. 3- The github repository https://github.com/neurodatascience/dFC/tree/main does not reference the paper 4- The github repository https://github.com/neurodatascience/dFC/tree/main is not documented enough. There are two very large added values in this repo : open implementation of methods, and analytical flexibility tools. The demo notebook shows how to use the analytical flexibility tools, but the methods implementation is not documented. I expect that many people will want to perform analysis using the methods as well as comparison analysis, so the documentation of individual methods should not be minimized. 5 - For the reader, it would be better to include early in the manuscript (in the introduction) the presence of the code for reproductibility. Currently, the toolbox is only introduced in the final paragraph of the discussion. It comes as a very nice suprise when reading the manuscript in full, but I think the manuscript would gain a lot of value if this paragraph was included earlier, and if the development of the toolbox was included much earlier (ie. in the abstract). 6 - We have published two papers on dFC that the authors may want to include, although these papers have investigated cerebello-cerebral dFC using whole brain + cerebellum parcellations. The first paper used continuous HMM on healthy subjects, and found correlations with impulsivity scores, while the second papers used network measures on sliding window dFC matrices on a clinical cohort (patients with alcohol use disorder). I am not sure why the authors have not found our papers in their litterature, but maybe it would be good to include them. Authors need to update the final table in supplementary materials as well as the citations in the main paper. Abdallah, M., Farrugia, N., Chirokoff, V., & Chanraud, S. (2020). Static and dynamic aspects of cerebro-cerebellar functional connectivity are associated with self-reported measures of impulsivity: A resting-state fMRI study. Network Neuroscience, 4(3), 891-909. Abdallah, M., Zahr, N. M., Saranathan, M., Honnorat, N., Farrugia, N., Pfefferbaum, A., Sullivan, E. & Chanraud, S. (2021). Altered cerebro-cerebellar dynamic functional connectivity in alcohol use disorder: a resting-state fMRI study. The Cerebellum, 20, 823-835. Note that in Abdallah et al. (2020), while we did not compare HMM results with other dFC methods, we did investigate the influence of HMM hyperparameters, as well as perform internal cross validation on our sample + null models of dFC.

      Minor comments 6 - "[..] what lies behind the of methods. Instead, they reveal three groups of methods, 720 variations in dynamic functional connectivity?. " -> an extra "." was added (end of page 10).

    2. AbstractDynamic functional connectivity (dFC) has become an important measure for understanding brain function and as a potential biomarker. However, various methodologies have been developed for assessing dFC, and it is unclear how the choice of method affects the results. In this work, we aimed to study the results variability of commonly-used dFC methods. We implemented seven dFC assessment methods in Python and used them to analyze fMRI data of 395 subjects from the Human Connectome Project. We measured the pairwise similarity of dFC results using several similarity metrics in terms of overall, temporal, spatial, and inter-subject similarity. Our results showed a range of weak to strong similarity between the results of different methods, indicating considerable overall variability. Surprisingly, the observed variability in dFC estimates was comparable to the expected natural variation over time, emphasizing the impact of methodological choices on the results. Our findings revealed three distinct groups of methods with significant inter-group variability, each exhibiting distinct assumptions and advantages. These findings highlight the need for multi-analysis approaches to capture the full range of dFC variation. They also emphasize the importance of distinguishing neural-driven dFC variations from physiological confounds, and developing validation frameworks under a known ground truth. To facilitate such investigations, we provide an open-source Python toolbox that enables multi-analysis dFC assessment. This study sheds light on the impact of dFC assessment analytical flexibility, emphasizing the need for careful method selection and validation, and promoting the use of multi-analysis approaches to enhance reliability and interpretability of dFC studies.

      This work has been published in GigaScience Journal under a CC-BY 4.0 license (https://doi.org/10.1093/gigascience/giae009), and has published the reviews under the same license. These are as follows.

      Reviewer 1: Yara Jo Toenders

      Comments to Author: The authors performed an in-depth comparison of 7 dynamic functional connectivity methods. The paper includes many figures that are greatly appreciated as they clearly demonstrate the findings. Moreover, the authors developed a Python toolbox to implement these 7 methods. The results showed that the results were highly variable, although three clusters of similar methods could be detected. However, after reading the manuscript, there are some remaining questions. - The TR and timepoints of the fMR images are shown, but other acquisition parameters such as the voxel size are missing. Could all acquisition parameters please be provided? - Could more information be provided on the downsampling of the 286 to 96 ROIs? How was this done and what were the 96 ROIs that were created? - In the results it is explained that the definition of groups depended on the cutoff value of the clustering, however it is unclear how the cutoff value was determined. Could the authors elucidate this how this was done? - The difference between the subplots in Figure 3 is a bit difficult to understand because the labels of the different methods switch places. Perhaps the same colour could be used for the cluster of the continuous HMM, Clustering and Discrete HMM method to increase readability? - Figure 4b shows that the default mode network is more variable over methods than time, while the auditory and visual are not. Could the authors explain what may underlie this discrepancy? - From the introduction it became clear that many studies have used dFC to study clinical populations, while I understand that no single recommendation can be given, not every clinical study might have the capacity to use all 7 methods. What would the authors recommend these clinical studies? Would there for example be a method that would be recommended within each of the three clusters? - It could be helpful if the authors create DOIs for their toolbox code bases that could be cited in a manuscript, rather than linking to bare GitHub URLs. One potentially useful guide is: https://guides.github.com/activities/citable-code/

    1. Background Culture-free real-time sequencing of clinical metagenomic samples promises both rapid pathogen detection and antimicrobial resistance profiling. However, this approach introduces the risk of patient DNA leakage. To mitigate this risk, we need near-comprehensive removal of human DNA sequence at the point of sequencing, typically involving use of resource-constrained devices. Existing benchmarks have largely focused on use of standardised databases and largely ignored the computational requirements of depletion pipelines as well as the impact of human genome diversity.Results We benchmarked host removal pipelines on simulated Illumina and Nanopore metagenomic samples. We found that construction of a custom kraken database containing diverse human genomes results in the best balance of accuracy and computational resource usage. In addition, we benchmarked pipelines using kraken and minimap2 for taxonomic classification of Mycobacterium reads using standard and custom databases. With a database representative of the Mycobacterium genus, both tools obtained near-perfect precision and recall for classification of Mycobacterium tuberculosis. Computational efficiency of these custom databases was again superior to most standard approaches, allowing them to be executed on a laptop device.Conclusions Nanopore sequencing and a custom kraken human database with a diversity of genomes leads to superior host read removal from simulated metagenomic samples while being executable on a laptop. In addition, constructing a taxon-specific database provides excellent taxonomic read assignment while keeping runtime and memory low. We make all customised databases and pipelines freely available.Competing Interest StatementThe authors have declared no competing interest.

      Reviewer 2. Darrin Lemmer, M.S.

      Comments to Author: This paper describes a method for improving the accuracy and efficiency of extracting a pathogen of interest (M. tuberculosis in this instance, though the methods should work equally well for other pathogens) from a "clinical" metagenomic sample. The paper is well written and provides links to all source code and datasets used, which were well organized and easy to understand. The premise – that using a pangenome database improves classification -- seems pretty intuitive, but it is nice to see some benchmarking to prove it. For clarity I will arrange my comments by the three major steps of your methods: dataset generation, human read removal, and Mycobacterium read classification. 1. Dataset generation -- I appreciate that you used a real-world study (reference #8) to approximate the proportions of organisms in your sample, however I am disappointed that you generated exactly one dataset for benchmarking. Even if you use the exact same community composition, there is a level of randomness involved in generating sequencing reads, and therefore some variance. I would expect to see multiple generations and an averaging of the results in the tables, however with a sufficiently high read depth, the variance won't likely change your results much, so it would be nice, and more true to real sequencing data, to vary the number of reads generated (I didn't see where you specified to what read depth for each species you generated the reads for), as it is rare in the real world to always get this deep of coverage. Ideally it would also be nice to see datasets varying the proportions of MTBC in the sample to test the limits of detection, but that may be beyond the scope of this particular paper. 2. Human read removal -- The data provided do not really support the conclusion, as all methods benchmarked performed quite well and, particularly when using the long reads from the Nanopore simulated dataset, fairly indistinguishable with the exception of HRRT. The short Illumina reads show a little more separation between the methods, probably due to the shorter sequences being able to align to multiple sequences in the reference databases, however comparing kraken human to kraken HPRC still shows very little difference, thus not supporting the conclusion that the pangenome reference provides "superior" host removal. The run times and memory used do much more to separate the performance of the various methods, and particularly with the goal of being able to run the analysis on a personal computer where peak memory usage is important. The only methods that perform well within the memory constraints of a personal computer for both long reads and short leads are HRRT and the two kraken methods, with kraken being superior at recall, but again, kraken human and kraken HPRC are virtually indistinguishable, making it hard to justify the claim that the pangenome is superior. Also, it appears your run time and peak memory usage is again based on one single data point, these should be performed multiple times and averaged. Finally, as an aside, I did find it interesting and disturbing that HRRT had such a high false negative rate compared to the other methods, given that this is the primary method used by NCBI for publishing in the SRA database, implying there are quite a few human remaining in SRA. 3. Mycobacterium read classification -- Here we do have some pretty good support for using a pangenome reference database, particularly compared to the kraken standard databases, though as mentioned previously, a single datapoint isn't really adequate, and I'd like to see both multiple datasets and multiple runs of each method. Additionally, given the purpose here is to improve the amount of MTB extracted from a metagenomic sample, these data should be taken the one extra step to show the coverage breadth and depth of the MTB genome provided by the reads classified as MTB, as a high number of reads doesn't mean much if they are all stacked at the same region of the genome. Given that these are simulated reads, which tend to have pretty even genome coverage, this may not show much, however it is still an important piece to show the value of your recommended method. One final comment is that it should be fairly easy to take this beyond a theoretical exercise, by running some actual real world datasets through the methods you are recommending to see how well they perform in actuality. For instance, reference #8, which you used as a basis for the composition of your simulated metagenomic sample, published their actual sequenced sputum samples. It would be easy to show if you can improve the amount of Mycobacterium extracted from their samples over the methods they used, thus showing value to those lower income/high TB burden regions where whole metagenome sequencing may be the best option they have.

      Re-review.

      This is a significantly stronger paper than originally submitted. I especially appreciate that multiple runs have now been done with more than one dataset, including a "real" dataset, and the analysis showing the breadth and depth of coverage of the retained Mtb reads, proving that you can still generally get a complete genome of a metagenomic sample with these methods. However kraken's low sensitivity when using the standard database definitely impacts the results, making a stronger argument for using a pangenome database (Kraken-Standard can identify the presence of Mtb, but if you want to do anything more with it, like AMR detection, you would need to use a pangenome database). I really think that this should be emphasized more, and perhaps some or all of the data in tables S9-S12 be brought into the main paper. It is maybe worth noting, that the significant drop in breadth, I would imagine, is a result of dividing the total size of the aligned reads by the size of the genome, implying a shallow coverage, but the reality is still high coverage in the areas that are covered, but lots of complete gaps in coverage. I did also like the switch to the somewhat more standard sensitivity/specificity metrics, though I do lament the actual FN/FP counts being relegated to the supplemental tables, as I thought these numbers valuable (or at least interesting) when comparing the results of the various pipelines, particularly with human read removal, where the various pipelines perform quite similarly.

    1. Stack Overflow - Where Developers Learn, Share, & Build Careers. URL: https://stackoverflow.com/ (visited on 2023-12-08).

      As someone who has to code frequently, Stack Overflow is my best helper because people have had problems and solutions for most of the coding errors I have faced. I really like Stack Overflow as it has a great community filled with coders who are willing to help you. An interesting fact that I saw online about Stack Overflow that I found funny: "All coders have used Stack Overflow, but none of them has seen the homepage."

    1. Author response:

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

      Reviewer #1 (Public Review):

      Summary:

      The authors set up a pipeline for automated high-throughput single-molecule fluorescence imaging (htSMT) in living cells and analysis of molecular dynamics

      Strengths:

      htSMT reveals information on the diffusion and bound fraction of molecules, dose-response curves, relative estimates of binding rates, and temporal changes of parameters. It enables the screening of thousands of compounds in a reasonable time and proves to be more sensitive and faster than classical cell-growth assays. If the function of a compound is coupled to the mobility of the protein of interest, or affects an interaction partner, which modulates the mobility of the protein of interest, htSMT allows identifying the modulator and getting the first indication of the mechanism of action or interaction networks, which can be a starting point for more in-depth analysis.

      Weaknesses:

      While elegantly showcasing the power of high-throughput measurements, the authors disclose little information on their microscope setup and analysis procedures. Thus, reproduction by other scientists is limited. Moreover, a critical discussion about the limits of the approach in determining dynamic parameters, the mechanism of action of compounds, and network reconstruction for the protein of interest is missing. In addition, automated imaging and analysis procedures require implementing sensitive measures to assure data and analysis quality, but a description of such measures is missing.

      The reviewer rightly highlights both the power and complexity in high throughput assay systems, and as such the authors have spent significant effort in first developing quality control checks to support screening. We discuss some of these as part of the description and characterization of the platform. We added additional details into the manuscript to help clarify. The implementation of our workflow for image acquisition, processing and analysis relies heavily on the specifics of our lab hardware and software infrastructure. We have added additional details to the text, particularly in the Methods section, and believe we have added enough information that our results can be reproduced using the suite of tools that already exist for single molecule tracking.

      The reviewer also points out that all assays have limitations, and these have not been clearly identified as part of our discussion of the htSMT platform. We have also added some comments on the limitations of the current system and our approach.

      Reviewer #2 (Public Review):

      Summary:

      McSwiggen et al present a high throughput platform for SPT that allows them to identify pharmaceutics interactions with the diffusional behavior of receptors and in turn to identify potent new ligands and cellular mechanisms. The manuscript is well written, it provides a solid new mentor and a proper experimental foundation

      Strengths:

      The method capitalizes and extends to existing high throughput toolboxes and is directly applied to multiple receptors and ligands. The outcomes are important and relevant for society. 10^6 cells and >400 ligands per is a significant achievement.

      The method can detect functionally relevant changes in transcription factor dynamics and accurately differentiate the ligand/target specificity directly within the cellular environment. This will be instrumental in screening libraries of compounds to identify starting points for the development of new therapeutics. Identifying hitherto unknown networks of biochemical signaling pathways will propel the field of single-particle live cell and quantitative microscopy in the area of diagnostics. The manuscript is well-written and clearly conveys its message.

      Weaknesses:

      There are a few elements, that if rectified would improve the claims of the manuscript.

      The authors claim that they measure receptor dynamics. In essence, their readout is a variation in diffusional behavior that correlates to ligand binding. While ligand binding can result in altered dynamics or /and shift in conformational equilibrium, SPT is not recording directly protein structural dynamics, but their effect on diffusion. They should correct and elaborate on this.

      This is an excellent clarifying question, and we have tried to make it more explicit in the text. The reviewer is absolutely correct; we’re not using SPT to directly measure protein structural dynamics, but rather the interactions a given protein makes with other macromolecules within the cell. So when an SHR binds to ligand it adopts conformations that promote association with DNA and other protein-protein interactions relevant to transcription. This is distinct from assays that directly measure conformational changes of the protein.

      L 148 What do the authors mean 'No correlation between diffusion and monomeric protein size was observed, highlighting the differences between cellular protein dynamics versus purified systems'. This is not justified by data here or literature reference. How do the authors know these are individual molecules? Intensity distributions or single bleaching steps should be presented.

      The point we were trying to make is that the relative molecular weights for the monomer protein (138 kDa for Halo-AR, 102 kDa for ER-Halo, 122 kDa for Halo-GR, and 135 kDa for Halo-PR) is uncorrelated with its apparent free diffusion coefficient. Were we to make this measurement on purified protein in buffer, where diffusion is well described by the Stokes Einstein equation, one would expect to see monomer size and diffusion related. We’ve clarified this point in the manuscript.

      Along the same lines, the data in Figs 2 and 4 show that not only the immobile fraction is increased but also that the diffusion coefficient of the fast-moving (attributed to free) is reduced. The authors mention this and show an extended Fig 5 but do not provide an explanation.

      This is an area where there is still more work to do in understanding the estrogen receptor and other SHRs. As the reviewer says, we see not only an increase in chromatin binding but also a decrease in the diffusion coefficient of the “free” population. A potential explanation is that this is a greater prevalence of freely-diffusing homodimers of the receptor, or other protein-protein interactions (14-3-3, P300, CBP, etc) that can occur after ligand binding. Nothing in our bioactive compound screen shed light on this in particular, and so we can only speculate and have refrained from drawing further conclusions in the text.

      How do potential transient ligand binding and the time-dependent heterogeneity in motion (see comment above) contribute to this? Also, in line 216 the authors write "with no evidence" of transient diffusive states. How do they define transient diffusive states? While there are toolboxes to directly extract the existence and abundance of these either by HMM analysis or temporal segmentation, the authors do not discuss or use them.

      Throughout the analysis in this work, we consider all of tracks with a 2-second FOV as representative of a single underlying population and have not looked at changes in dynamics within a single movie. As we show in the supplemental figures we added (see Figure 3, figure supplement 1), this appears to be a reasonable assumption, at least in the cases we’ve encountered in this manuscript. For experiments involving changes in dynamics over time, these are experiments where we’ve added compound simultaneous with imaging and collect many 2-second FOVs in sequence to monitor changes in ER dynamics. In this case when we refer to “transient states,” we are pointing out that we don’t observe any new states in the State Array diagram that exist in early time points but disappear at later time point.

      The reviewer suggests track-level analysis methods like hidden Markov models or variational Bayesian approaches which have been used previously in the single molecule community. These are very powerful techniques, provided the trajectories are long (typically 100s of frames). In the case of molecules that diffuse quickly and can diffuse out of the focal plane, we don’t have the luxury of such long trajectories. This was demonstrated previously (Hansen et al 2017, Heckert el al 2022) and so we’ve adopted the State Array approach to inferring state occupations from short trajectories. As the reviewer rightly points out, this approach potentially loses information about state transitions or changes over time, but as of now we are not aware of any robust methods that work on short trajectories.

      The authors discuss the methods for extracting kinetic information of ligand binding by diffusion. They should consider the temporal segmentation of heterogenous diffusion. There are numerous methods published in journals or BioRxiv based on analytical or deep learning tools to perform temporal segmentation. This could elevate their analysis of Kon and Koff.

      We’re aware of a number of approaches for analyzing both high framerate SMT as well as long exposure residence time imaging. As we say above, we’re not aware of any methods that have been demonstrated to work robustly on short trajectories aside from the approaches we’ve taken. Similarly, for residence time imaging there are published approaches, but we’re not aware of any that would offer new insight into the experiments in this study. If the reviewer has specific suggestions for analytical approaches that we’re not aware of we would happily consider them.

      Reviewer #3 (Public Review):

      Summary:

      The authors aim to demonstrate the effectiveness of their developed methodology, which utilizes super-resolution microscopy and single-molecule tracking in live cells on a high-throughput scale. Their study focuses on measuring the diffusion state of a molecule target, the estrogen receptor, in both ligand-bound and unbound forms in live cells. By showcasing the ability to screen 5067 compounds and measure the diffusive state of the estrogen receptor for each compound in live cells, they illustrate the capability and power of their methodology.

      Strengths:

      Readers are well introduced to the principles in the initial stages of the manuscript with highly convincing video examples. The methods and metrics used (fbound) are robust. The authors demonstrate high reproducibility of their screening method (R2=0.92). They also showcase the great sensitivity of their method in predicting the proliferation/viability state of cells (R2=0.84). The outcome of the screen is sound, with multiple compounds clustering identified in line with known estrogen receptor biology.

      Weaknesses:

      • Potential overstatement on the relationship of low diffusion state of ER bound to compound and chromatin state without any work on chromatin level.

      We appreciate the reviewers caution in over-interpreting the relationship between an increase in the slowest diffusing states that we observe by SMT and bona fide engagement with chromatin. In the case of the estrogen receptor there is strong precedent in the literature showing increases in chromatin binding and chromatin accessibility (as measured by ChIP-seq and ATAC-seq) upon treatment with either estradiol or SERM/Ds. Taken together with the RNA-seq, we felt it reasonable to assume all the trajectories with a diffusion coefficient less that 0.1 µm2/sec were chromatin bound.

      • Could the authors clarify if the identified lead compound effects are novel at any level?

      Most of the compounds we characterize in the manuscript have not previously been tested in an SMT assay, but many are known to functionally impact the ER or other SHRs based on other biochemical and functional assays. We have not described here any completely novel ER-interacting compounds, but to our knowledge this is the first systematic investigation of a protein showing that both direct and indirect perturbation can be inferred by observing the protein’s motion. Especially for the HSP90 inhibitors, the observation that inhibiting this complex would so dramatically increase ER chromatin-binding as opposed to increasing the speed of the free population is counterintuitive and novel.

      • More video example cases on the final lead compounds identified would be a good addition to the current data package.

      Reviewer #1 (Recommendations For The Authors):

      General:

      • More information on the microscope setup and analysis procedures should be given. Since custom code is used for automated image registration, spot detection, tracking, and analysis of dynamics, this code should be made publicly available.

      Results:

      • line 97: more details about the robotic system and automatic imaging, imaging modalities, and data analysis procedures should be given directly in the text.

      Additional information added to text and methods

      • line 100: we generated three U2OS cell lines --> how?

      Additional information added to text and methods

      • line 101: ectopically expressing HaloTag fused proteins --> how much overexpression did cells show?

      The L30 promoter tends to produce fairly low expression levels. The same approach was used for all ectopic expression plasmids, and for the SHRs the expression levels were all comparable to endogenous levels. We have not checked this for H2B, Caax and free Halo but given that the necessary dye concentration to achieve similar spot densities is within a 10-fold range for all constructs, its reasonable to say that those clonal cell lines will also have modest Halotag expression.

      • line 107: Single-molecule trajectories measured in these cell lines yielded the expected diffusion coefficients --> how was data analysis performed?

      Additional information added to text and methods

      • line 109: how was the localization error determined?

      Additional information added to text and methods

      • line 155: define occupation-weighted average diffusion coefficient.

      Additional information added to text and methods

      • line 157: with 34% bound in basal conditions and 87% bound after estradiol treatment  contradicts figure 2b, where the bound fraction is up to 50% after estradiol treatment.

      Line 157 is the absolute fraction bound, figure 2b is change in fbound

      • line 205: Figure 2c is missing.

      Fixed

      • line 215: within minutes --> how was this data set obtained? which time bins were taken?

      Additional information added to text and methods

      • line 216: with no evidence of transient diffusive states  What is meant by transient diffusive state? It seems all time points have a diffusive component, which decreases over time.

      Additional information added to text and methods

      The diffusive peak decreases, the bound peak increases but no other peaks emerge during that time (e.g. neither super fast nor super slow)

      • line 225: it seems that fbound of GDC-0810 and GDC-0927 are rather similar in FRAP experiments, please comment, how was FRAP done?

      FRAP is in the methods section. The curves and recovery times are quite distinct, is the reviewer looking at

      • line 285: reproducibly: how often was this repeated?

      Information added to the manuscript

      • line 285: it would be necessary to name all of the compounds that were tested, e.g. with an ID number in the graph and a table. This also refers to extended data 7 and 8.

      Additional supplemental file with the list of bioactive compounds tested will be included.

      • line 290/1: what is meant by vendor-provided annotation was poorly defined?

      Additional information added to text and methods. Specifically, the “other” category is the most common category, and it includes both compounds with unknown targets/functions as well as compound where the target and pathway are reasonably well documented. Hence, we applied our own analysis to better understand the list of active compounds.

      Figures:

      • fig. 2-6: detailed statistics are missing (number of measured cells, repetitions, etc.).

      We have added clarifying information, including an “experiment design and sample size” section in the Methods.

      • fig. 3: the authors need to give a list with details about the 5067 compounds tested,

      Additional supplemental file with the list of bioactive compounds tested will be included.

      • extended data 1c: time axis does not correspond to the 1.5s of imaging in the text, results line 127.

      Axes fixed

      • extended data 3: panel c and d are mislabeled.

      Panel labels fixed

      Methods:

      • line 746: HILO microscope: the authors need to explain how they can get such large fields of view using HILO

      Additional details added to the materials and methods. The combination of the power of the lasers, the size of the incident beam out of the fiber optic coupling device and the sCMOS camera are the biggest components that enable detection over a larger field of view.

      • line 761: it is common practice to publish the analysis code. Since the authors wrote their own code, they should publish it

      Our software contains proprietary information that we cannot yet release publicly. Comparable results can be achieved with HILO data using publicly-available tools like utrack. State Arrays code is distributed and the parameters used are listed in the M&M.

      Reviewer #2 (Recommendations For The Authors):

      The writing and presentation are coherent, concise, and easy to follow.

      The authors should consider justifying the following:

      Why is 1.5s imaging time selected? Topological and ligand variations may last significantly longer than this. The authors should present at least for one condition the same effect images for longer.

      Related to the similar comment above, we added a figure examining the jump length distribution as a function of frame. Over the 6 seconds of data collection the jump length distribution is unchanged, suggesting it is reasonable to consider all the trajectories within an FOV as representative of the same underlying dynamical states.

      The authors miss the k test or T test in their graphs.

      We chose to apply the Kurskal-Wallis test in the context of the bioactive screen to assess whether a grouping of compounds based on their presumed cellular target was significantly different from the control even when individual compounds might not by themselves raise to significance. In this case many of the pathway inhibitors are subtle and not necessarily obvious in their difference. In the other cases throughout the manuscript, whether two conditions are statistically distinguishable is rarely in question and of far less importance to the conclusions in the manuscript than the magnitude of the difference. We’ve added statistical tests where appropriate.

      The overall integrated area of Fig 4a appears to reduce upon ligand addition. Data appear normalized but the authors should also add N (number of molecules) on top of the graphs.

      While the integrated area may appear to decrease, all State Array analysis is performed by first randomly sampling 10,000 trajectories from the assay well and inferring state distribution on those 10,000. This has been clarified in the figure legend and in the Methods.

      Minor

      Extended Figure 3 legend c, d appear swapped and incorrectly named in the text.

      Panel labels fixed

      L 197 but this appears not to BE a general feature of SHRs (maybe missing Be).

      Error fixed

      L205 authors refer to Figure 2c, which does not exist.

      Panel reference fixed

      Reviewer #3 (Recommendations For The Authors):

      Among minor issues:

      In Figure 1B, if the authors could specify how they discriminate the specific cell lines from the mixed context, it would enhance clarity. Could they perform additional immunofluorescence to understand how the assignment is determined? Alternatively, could they also show the case with isolated cell lines in an unmixed context?

      Immunofluorescence would be a challenge given that there is not a good epitope to distinguish the three ectopically-expressed genes from each other or from endogenous proteins in the case of H2B and CaaX. We are really reliant on the single cell dynamics to determine the likely cell identity. That said, we’ve added graphs of a number of individual cell State Arrays from the same data graphed in 1A which support the notion that it’s reasonable to assume a cells identity given the observed dynamics.

      In Extended Figure 2F: possibly a CHip-Seq experiment would be more directly qualified to state the effect of ER ligand on ER ability to bind chromatin.

      This is true. Presumably ER that is competent at activating transcription of ER-responsive genes is also capable of binding DNA. ChIP would be the more direct measure, but would not address whether the protein was functional. We chose to balance these measuring these two aspects of ER biology by pairing dynamics with the end-point transcription readout.

      In Figure 3: A representation with plate-by-plate orientation along the x-axis, with controls included in each plate, would be more appropriate to reflect the consistency of the controls used in the assay across different plates. Currently, all controls are pooled in one location, and we cannot appreciate how the controls vary from plate to plate.

      Figure added to the supplement

      Also in this figure, a general workflow of the screen down to segmentation/analysis would be a great add-on.

      New figure added to the supplement and reflected in the textual description of the platform

      In Extended Figures 3B and C an add-on of the positive and negative control would make the figure more convincing.

      Addressed as part of figure added to the supplement

      Is there any description of compound leads identified that is novel in nature in relation to impact on ER, and if so could it be stated more clearly in the text as novel finding?

      To our knowledge, the impact of HSP inhibition in increasing ER-chromatin association has never been described, neither has the link between inhibition post-translation modifying enzymes like the CDKs or mTOR and ER dynamics ever been described. We added clarifying text to the manuscript

    1. Author response:

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

      eLife assessment

      In this important paper, Blin and colleagues develop a high-throughput behavioral assay to test spontaneous swimming and olfactory preference in individual Mexican cavefish larvae. The authors present compelling evidence that the surface and cave morphs of the fish show different olfactory preferences and odor sensitivities and that individual fish show substantial variability in their spontaneous activity that is relevant for olfactory behaviour. The paper will be of interest to neurobiologists working on the evolution of behaviour, olfaction, and the individuality of behaviour.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      The authors posed a research question about how an animal integrates sensory information to optimize its behavioral outputs and how this process evolved. Their data (behavioral output analysis with detailed categories in response to the different odors in different concentrations by comparing surface and cave populations and their hybrid) partially answer this tough question. They built a new low-disturbance system to answer the question. They also found that the personality of individual fish is a good predictor of behavioral outputs against odor response. They concluded that cavefish evolved to specialize their response to alanine and histidine while surface fish are more general responders, which was supported by their data.

      Strengths:

      With their new system, the authors could generate clearer results without mechanical disturbances. The authors characterize multiple measurements to score the odor response behaviors, and also brought a new personality analysis. Their conclusion that cavefish evolved as a specialist to sense alanine and histidine among 6 tested amino acids was well supported by their data.

      Weaknesses:

      The authors posed a big research question: How do animals evolve the processes of sensory integration to optimize their behavioral outputs? I personally feel that, to answer the questions about how sensory integration generates proper (evolved) behavior, the authors at least need to show the ecological relevance of their response. For the alanine/histidine preference in cavefish, they need data for the alanine and other amino acid concentrations in the local cave water and compare them with those of surface water.

      We agree with the reviewer. This is why, in the Discussion section, we had written: “…Such significant variations in odor preferences or value may be adaptive and relate to the differences in the environmental and ecological conditions in which these different animals live. However, the reason why Pachón cavefish have become “alanine specialists” remains a mystery and prompts analysis of the chemical ecology of their natural habitat. Of note, we have not found an odor that would be repulsive for Astyanax so far, and this may relate to their opportunist, omnivorous and detritivore regime (Espinasa et al., 2017; Marandel et al., 2020).” This is also why we currently develop field work projects aimed at clarifying this question. However, such experiments and analyses are challenging, practically and technically. We hope we can reach some conclusions in the future.

      To complete the discussion we have also added an important hypothesis: “Alternatively, specialization for alanine may not need to be specific for an olfactory cue present only, or frequently, or in high amounts in caves. Bat guano for example, which is probably the main source of food in the Pachón cave, must contain many amino acids. Enhanced recognition of one of them - in the present case alanine but evolution may have randomly acted for enhanced recognition of another amino acid – should suffice to confer cavefish with augmented sensitivity to their main source of nutriment.”

      Also, as for "personality matters", I read that personality explains a large variation in surface fish. Also, thigmotaxis or wall-following cavefish individuals are exceeded to respond well to odorants compared with circling and random swimming cavefish individuals. However, I failed to understand the authors' point about how much percentages of the odorant-response variations are explained (PVE) by personality. Association (= correlation) was good to show as the authors presented, but showing proper PVE or the effect size of personality to predict the behavioral outputs is important to conclude "personality is matter"; otherwise, the conclusion is not so supported.

      From the above, I recommend the authors reconsider the title also their research questions well. At this moment, I feel that the authors' conclusions and their research questions are a little too exaggerated, with less supportive evidence.

      Thank you for this interesting suggestion, which we have fully taken into consideration. We have therefore now calculated and plotted PVE (the percentage of variation explained on the olfactory score) as a function of swimming speed or as a function of swimming pattern. The results are shown in modified Figure 8 of our revised ms and they suggest that the personality (here, swimming patterns or swimming speed) indeed predicts the olfactory response skills. Therefore, we would like to keep our title as we provide support for the fact that “personality matters”.

      Also, for the statistical method, Fisher's exact test is not appropriate for the compositional data (such as Figure 2B). The authors may quickly check it at https://en.wikipedia.org/wiki/Compositional_data or https://www.annualreviews.org/doi/pdf/10.1146/annurev-statistics-042720-124436.

      The authors may want to use centered log transformation or other appropriate transformations (Rpackage could be: https://doi.org/10.1016/j.cageo.2006.11.017). According to changing the statistical tests, the authors' conclusion may not be supported.

      Actually, in most cases, the distributions are so different (as seen by the completely different colors in the distribution graphs) that there is little doubt that swimming behaviors are indeed different between surface and cavefish, or between ‘before’ and ‘after’ odor stimulation. However, it is true that Fisher’s exact test is not fully appropriate because data can be considered as compositional type. For this kind of data, centered log transformation have been suggested. However, our dataset contains many zeros, and this is a case where log transformations have difficulty handling.

      To help us dealing with our data, the reviewer proposed to consider the paper by Greenacre (2021) (https://www.annualreviews.org/doi/pdf/10.1146/annurev-statistics-042720-124436). In his paper, Greenacre clearly wrote: "Zeros in compositional data are the Achilles heel of the logratio approach (LRA)."

      Therefore, we have now tested our data using CA (Correspondence Analysis), that can deal with table containing many zeros and is a trustable alternative to LRA (Cook-Thibeau, 2021; Greenacre, 2011).

      The results of CA analysis are shown in Supplemental figure 8 and they fully confirm the difference in baseline swimming patterns between morphs as well as changes (or absence of changes) in behavioral patterns after odor stimulation suggested by the colored bar plots in main figures, with confidence ellipses overlapping or not overlapping, depending on cases. Therefore, the CA method fully confirms and even strengthens our initial interpretations.

      Finally, we have kept our initial graphical representation in the ms (color-coded bar plots; the complete color code is now given in Suppl. Fig7), and CA results are shown in Suppl. Figure 8 and added in text.

      Reviewer #2 (Public Review):

      In their submitted manuscript, Blin et al. describe differences in the olfactory-driven behaviors of river-dwelling surface forms and cave-dwelling blind forms of the Mexican tetra, Astyanax mexicanus. They provide a dataset of unprecedented detail, that compares not only the behaviors of the two morphs but also that of a significant number of F2 hybrids, therefore also demonstrating that many of the differences observed between the two populations have a clear (and probably relatively simple) genetic underpinning.

      To complete the monumental task of behaviorally testing 425 six-week-old Astyanax larvae, the authors created a setup that allows for the simultaneous behavioral monitoring of multiple larvae and the infusion of different odorants without introducing physical perturbations into the system, thus biasing the responses of cavefish that are particularly fine-tuned for this sensory modality. During the optimization of their protocol, the authors also found that for cave-dwelling forms one hour of habituation was insufficient and a full 24 hours were necessary to allow them to revert to their natural behavior. It is also noteworthy that this extremely large dataset can help us see that population averages of different morphs can mask quite significant variations in individual behaviors.

      Testing with different amino-acids (applied as relevant food-related odorant cues) shows that cavefish are alanine- and histidine-specialists, while surface fish elicit the strongest behavioral responses to cysteine. It is interesting that the two forms also react differently after odor detection: while cave-dwelling fish decrease their locomotory activity, surface fish increase it. These differences are probably related to different foraging strategies used by the two populations, although, as the observations were made in the dark, it would be also interesting to see if surface fish elicit the same changes in light as well.

      Thank you for these nice comments.

      Further work will be needed to pinpoint the exact nature of the genetic changes that underlie the differences between the two forms. Such experimental work will also reveal how natural selection acted on existing behavioral variations already present in the SF population.

      Yes. Searching for genetic underpinnings of the sensory-driven behavioral differences is our current endeavor through a QTL study and we should be able to report it in the near future.

      It will be equally interesting, however, to understand what lies behind the large individual variation of behaviors observed both in the case surface and cave populations. Are these differences purely genetic, or perhaps environmental cues also contribute to their development? Does stochasticity provided by the developmental process has also a role in this? Answering these questions will reveal if the evolvability of Astyanax behavior was an important factor in the repeated successful colonization of underground caves.

      Yes. We will also access (at least partially) responses to most of these questions in our current QTL study.

      Reviewer #3 (Public Review):

      Summary:

      The paper explores chemosensory behaviour in surface and cave morphs and F2 hybrids in the Mexican cavefish Astyanax mexicanus. The authors develop a new behavioural assay for the longterm imaging of individual fish in a parallel high-throughput setup. The authors first demonstrate that the different morphs show different basal exploratory swimming patterns and that these patterns are stable for individual fish. Next, the authors test the attraction of fish to various concentrations of alanine and other amino acids. They find that the cave morph is a lot more sensitive to chemicals and shows directional chemotaxis along a diffusion gradient of amino acids. For surface fish, although they can detect the chemicals, they do not show marked chemotaxis behaviour and have an overall lower sensitivity. These differences have been reported previously but the authors report longer-term observations on many individual fish of both morphs and their F2 hybrids. The data also indicate that the observed behavior is a quantitative genetic trait. The approach presented will allow the mapping of genes' contribution to these traits. The work will be of general interest to behavioural neuroscientists and those interested in olfactory behaviours and the individual variability in behavioural patterns.

      Strengths:

      A particular strength of this paper is the development of a new and improved setup for the behavioural imaging of individual fish for extended periods and under chemosensory stimulation. The authors show that cavefish need up to 24 h of habituation to display a behavioural pattern that is consistent and unlikely to be due to the stressed state of the animals. The setup also uses relatively large tanks that allow the build-up of chemical gradients that are apparently present for at least 30 min.

      The paper is well written, and the presentation of the data and the analyses are clear and to a high standard.

      Thank you for these nice comments.

      Weaknesses:

      One point that would benefit from some clarification or additional experiments is the diffusion of chemicals within the behavioural chamber. The behavioural data suggest that the chemical gradient is stable for up to 30 min, which is quite surprising. It would be great if the authors could quantify e.g. by the use of a dye the diffusion and stability of chemical gradients.

      OK. We had tested the diffusion of dyes in our previous setup and we also did in the present one (not shown). We think that, due to differences of molecular weight and hydrophobicity between the tested dyes and the amino acid molecules we are using, their diffusion does not constitute a proper read-out of actual amino acid diffusion. We anticipate that amino acid diffusion is extremely complex in the test box, possibly with odor plumes diffusing and evolving in non-gradient patterns, in the 3 dimensions of the box, and potentially further modified by the fish swimming through it, the flow coming from the opposite water injection side and the borders of the box. This is the reason why we have designed the assay with contrasting “odor side” and “water control side”. Moreover, our question here is not to determine the exact concentration of amino acid to which the fish respond, but to compare the responses in cavefish, surface fish and F2 hybrids. Finally and importantly, we have performed dose/response experiments whereby varying concentrations have been presented for 3 of the 6 amino acids tested, and these experiments clearly show a difference in the threshold of response of the different morphs.

      The paper starts with a statement that reflects a simplified input-output (sensory-motor) view of the organisation of nervous systems. "Their brains perceive the external world via their sensory systems, compute information and generate appropriate behavioral outputs." The authors' data also clearly show that this is a biased perspective. There is a lot of spontaneous organised activity even in fish that are not exposed to sensory stimulation. This sentence should be reworded, e.g. "The nervous system generates autonomous activity that is modified by sensory systems to adapt the behavioural pattern to the external world." or something along these lines.

      Done

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      In addition to my comments in the "weakness" section above, here are my other comments.

      How many times fish were repeatedly assayed and what the order (alanine followed by cysteine, etc) was, is not clear (Pg 24, Materials and Methods). I am afraid that fish memorize the prior experience to get better/worse their response to the higher conc of alanine, etc. Please clarify this point.

      Many fish were tested in different conditions on consecutive days, indeed. Most often, control experiments (eg, water/nothing; water/water; nothing/nothing) were followed by odor testing. In such cases, there is no risk that fish memorize prior experience and that such previous experience interferes with response to odor. In other instances, fish were tested with a low concentration of one amino acid, followed by a high concentration of another amino acid, which is also on the safe side. Of note, on consecutive days, the odors were always perfused on alternate sides of the test box, to avoid possibility of spatial memory. Finally, in the few cases where increasing concentrations of the same amino acids were perfused consecutively, 1) they were perfused on alternate sides, 2) if the fish does not detect a low concentration below threshold / does not respond, then prior experience should not interfere for responding to higher concentrations, and 3) we have evidence (unpublished, current studies) that when a fish is given increasing concentrations of the same amino acid above detection threshold, then the behavioral response is stable and reproducible (eg does not decrease or increase).

      Minor points:

      Thygmotaxis and wall following.

      Classically, thigmotaxis and wall following are treated as the same (sharma et al., 2009; https://pubmed.ncbi.nlm.nih.gov/19093125/) but the authors discriminate it in thigmotaxis at X-axis and Y-axis because fish repeatedly swam back and forth on x-axis wall or y-axis wall. I understand the authors' point to discriminate WF and T but present them with more explanations (what the differences between them) in the introduction and result sections.

      Done

      Pg5 "genetic architecture" in the introduction.

      "Genetic architecture" analysis needs a more genomic survey, such as GWAS, QTL mapping, and Hi-C. Phenotype differences in F2 generation can be stated as "genetic factor(s)" "genetic component(s)", etc. please revise.

      Done

      Pg10 At the serine treatment, the authors concluded that "...suggesting that their detection threshold for serine is lower than for alanine." I believe that the 'threshold for serine is higher' according to the authors' data. Their threshold-related statement is correct in Pg21 "as SF olfactory concentration detection threshold are higher than CF,..." So the statement on page 10 is a just mistake, I think. Please revise.

      Done (mistake indeed)

      Pg11 After explaining Fig5, the statement "In sum, the responses of the different fish types to different concentrations of different amino acids were diverse and may reflect complex, case-bycase, behavioral outputs" does not convey any information. Please revise.

      OK. Done : “In sum, the different fish types show diverse responses to different concentrations of different amino acids.”

      For the personality analysis (Fig 7)

      The index value needs more explanation. I read the materials and methods three times but am still confused. From the equation, the index does not seem to exceed 1.0, unless the "before score" was a negative value, and the "after score" value was positive. I could not get why the authors set a score of 1.5 as the threshold for the cumulative score of these different behavior index values (= individual score). Please provide more description. Currently, I am skeptical about this index value in Fig 7.

      Done, in results and methods.

      Pg15 the discussion section

      Please discuss well the difference between the authors' finding (cavefish respond 10^-4M for position and surface fish responded 10^-4 for thig-Y; Fig 4AB), and those in Hinaux et al. 2016 (cavefish responded 10^-10M alanine but surface fish responded 10^-5M or higher). It seems that surface fish could respond to the low conc of alanine as cavefish do, which is opposed to the finding in Hinaux 2016.

      The increase in NbrtY at population level for surface fish with 10-4M alanine (~10-6M in box) was most probably due to only a few individuals. Contrarily to cavefish, all other parameters were unchanged in surface fish for this concentration. Moreover, at individual level, only 3.2% of surface fish had significant olfactory scores (to be compared to 81.3% for cavefish). Thus, we think that globally this result does not contradict our previous findings in Hinaux et al (2016), and solely represent the natural, unexplained variations inherent to the analysis of complex animal behaviors – even when we attempt to use the highest standards of controlled conditions.

      Of note, in the revised version, we have now included a full dose/response analysis for alanine concentration ranging from 10-2M to 10-10M, on cavefish. Alanine 10-5M has significant effects (now shown in Suppl Fig2 and indicated in text; a column has been added for 10-5M in Summary Table 1). Lower concentrations have milder effects (described in text) but confirm the very low detection threshold of cavefish for this amino acid.

      Pg19, "In sum, CF foraging strategy has evolved in response to the serious challenge of finding food in the dark"

      My point is the same as explained in the 'weakness' section above: how this behavior is effective in the cave life, if they conclude so? Please explain or revise this statement.

      The present manuscript reports on experiments performed in “artificial” and controlled laboratory conditions. We are fully aware that these conditions are probably distantly related to conditions encountered in the wild. Note that we had written in original version (page 20) “…for 6-week old juveniles in a rectangular box - but the link may be more elusive when considering a fish swimming in a natural, complex environment.” As the reviewer may know, we also perform field studies in a more ethological approach of animal behaviors, thus we may be able to discuss this point more accurately in the future.

      Pg20 "To our knowledge, this is the first time individual variations are taken into consideration in Astyanax behavioral studies."

      This is wrong. Please see Fernandes et al., 2022. (https://pubmed.ncbi.nlm.nih.gov/36575431/).

      OK. The sentence is wrong if taken in its absolute sense, i.e., considering inter-individual variations of a given parameter (e.g., number of neuromasts per individual or number of approaches to vibrating rod in Fernandez et al, 2022). In this same sense, Astyanax QTL studies on behaviors in the past also took into account variations among F2 individuals. Here, we wanted to stress that personality was taken into consideration. The sentence has been changed: “To our knowledge, this is the first time individual temperament is taken into consideration in Astyanax behavioral studies.”

      Figure 2B and others.

      The order of categories (R, R-TX, etc) should match in all columns (SF, F2, and CF). Currently, the category orders seem random or the larger ratio categories at the bottom, which is quite difficult to compare between SF, F2, and CF. Also, the writings in Fig 2A (times, Y-axis labels, etc), and the bargraphs' writings are quite difficult to read in Fig 2B, Fig 3B 4H, 5GN, 6EFG. Also, no need to show fish ID in Fig 2C in the current way, but identify the fish data points of the fish in Fig 2D (SF#40, CF#65, and F2#26) in Fig 2C if the authors want to show fish ID numbers in the boxplots. Fish ID numbers in other boxplot figures are recommended to be removed too.

      We have thought a lot on how to best represent the distributions of swimming patterns in graphs such as Fig 2B and others. The difficulty is due to the existence of many combinations (33 possibilities in total, see new Suppl Fig7), which are never the same in different plots/conditions because individual tested fish are different. We decided that that the best way was to represent, from bottom to top, the most used to the less used swimming patterns, and to use a color code that matches at best the different combinations. It was impossible to give the full color code on each figure, therefore it was simplified, and we believe that the results are well conveyed on the graphs. We would like to keep it as it is. To respond (partially) to the reviewer’s concern, we have now added a full color code description in a new Supplemental Figure 7 (associated to Methods).

      Size of lettering has been modified in all pattern graphs like Fig2A. Thanks for the suggestion, it reads better now.

      Finally, we would like to keep the fish ID numbers because this contributes to conveying the message of the paper, that individuality matters.

      Raw data files were not easy to read in Excel or LibreOffice. Please convert them into the csv format to support the rigor in the authors' conclusion.

      We do not understand this request. Our very large dataset must be analysed with R, not excel for stats or for plotting and pattern analysis. However, raw data files can be opened in excel with format conversion.

      Reviewer #2 (Recommendations For The Authors):

      I think most of the experimental procedures (with few exceptions, see below) are well-defined and nicely described, so the majority of my suggestions will be related to the visualization of the data. I think the authors have done a great job in presenting this complex dataset, but there are still some smaller tweaks that could be used to increase the legibility of the presented data.

      First and perhaps foremost, a better definition of the swimming pattern subsets is needed. I have no problem understanding the main behavioral types, but whereas the color codes for these suggest that there is continuous variance within each pattern, it is not clear (at least to me), what particular aspect(s) of the behaviors vary. Also, whereas the sidebars/legends suggest a continuum within these behaviors, the bar charts themselves clearly present binned data. I did not find a detailed description of how the binning was done. As this has been - according the Methods section - a manual process, more clarity about the details of the binning would be welcome. I would also suggest using binned color codes for the legends as well.

      Done, in Results and Methods. We hope it is now clear that there is no “continuum”, rather multiple combinations of discrete swimming patterns. The gradient aspect in color code in figures has been removed to avoid the idea of continuum. According to the chosen color code, WF is in red, R in blue, T in yellow and C in green. Then, combination are represented by colors in between, for example, R+WF is purple. We have now added a full color code description for the swimming patterns and their combinations in a new Supplemental Figure 7 (associated to Methods).

      Also, to better explain the definition of the swimming patterns and the graphical representation, it now reads (in Methods):

      “The determination of baseline swimming patterns and swimming patterns after odor injection was performed manually based on graphical representations such as in Figure 2A or Figure 3A. Four distinctive baseline behaviors clearly emerged: random swim (R; defined as haphazard swimming with no clear pattern, covering entirely or partly the surface of the arena), wall following (WF; defined as the fish continuously following along the 4 sides of the box and turning around it, in a clockwise or counterclockwise fashion), large or small circles (C; self explanatory), and thigmotactism (T, along the X- or the Y-axis of the box; defined as the fish swimming back and forth along one of the 4 sides of the box). On graphical representations of swimming pattern distributions, we used the following color code: R in blue, WF in red, C in green, T in yellow. Of note, many fish swam according to combination(s) of these four elementary swimming patterns (see descriptions in the legends of Supplemental figures, showing many examples). To fully represent the diversity and the combinations of swimming patterns used by individual fish, we used an additional color code derived from the “basic” color code described above and where, for example R+WF is purple. The complete combinatorial color code is shown in Suppl. Fig7.”

      It would be also easier to comprehend the stacked bar charts, presenting the particular swimming patterns in each population, if the order of different swimming patterns was the same for all the plots (e.g. the frequency of WF always presented at the bottom, R on the top, and C and T in the middle). This would bring consistency and would highlight existing differences between SF, CF, and F2s. Furthermore, such a change would also make it much easier to see (and compare) shifts in behaviors.

      We have thought a lot on how to best represent the distributions of swimming patterns in graphs such as Fig 2B and others. The difficulty is due to the existence of many combinations, which are never the same in different plots/conditions because the individual fish tested are different. We decided to keep it as it currently stands, because we think re-doing all the graphs and figures would not significantly improve the representation. In fact, we think that the differences between morphs (dominant blue in SF, dominant red in CF) and between conditions (bar charts next to each other) are easy to interpret at first glance in the vast majority of cases. Moreover, they are now completed by CA analyses (Suppl Figure 8).

      While the color coding of the timeline in the "3D" plots presented for individual animals is a nice feature, at the moment it is slightly confusing, as the authors use the same color palette as for the stacked bar charts, representing the proportionality of the particular swimming patterns. As the y-axis is already representing "time" here, the color coding is not even really necessary. If the authors would like to use a color scheme for aesthetic reasons, I would suggest using another palette, such as "grey" or "viridis".

      We would like to keep the graphical aspect of our figures as they are, for aesthetic reasons. To avoid confusion with stacked bar chart color code, we have added a sentence in Methods and in the legend of Figure 2, where the colors first appear:

      “The complete combinatorial color code is shown in Suppl. Figure 7. Of note, in all figures, the swimming pattern color code does not relate whatsoever with the time color code used in the 2D plus time representation of swimming tracks such as in Figure 2A”.

      I would also suggest changing the boxplots to violin-plots. Figure 7 clearly shows bimodality for F2 scores (something, as the authors themselves note, not entirely surprising given the probably poligenic nature of the trait), but looking at SF and CF scores I think there are also clear hints for non-normal distributions. If non-normal distribution of traits is the norm, violin-plots would capture the variance in the data in a more digestible way. (The existence of differently behaving cohorts within the population of both SF and CF forms would also help to highlight the large pre-existing variance, something that was probably exploited by natural selection as well, as mentioned briefly in the Discussion by the authors, too.)

      The bimodal distribution of scores shown by F2s in Figure 7B is indeed probably due to the polygenic nature of the trait. However, such distribution is rather the exception than the norm. Moreover, the boxplot representations we have used throughout figures include all the individual points, and outliers can be identified as they have the fish ID number next to them. This allows the reader to grasp the variance of the data. Again, redoing all graphs and figures would constitute a lot of work, for little gain in term of conveying the results. Therefore, we choose not to change the boxplot for violin plots.

      The summary data of individual scores in Table 1B shows some intriguing patterns, that warrant a bit further discussion, in my opinion. For example, we can see opposite trends in scores of SF and CF forms with increasing alanine concentration. Is there an easy explanation for this? Also, in the case of serine, the CF scores do not seem to respond in a dose-dependent manner and puzzlingly at 10^(-3)M serine concentration F2 scores are above those of both grandparental populations.

      That is true. However, we have no simple explanation for this. To begin responding to this question, we have now performed full dose/responses expts for alanine (concentrations tested from 10-2M to 10-10M on cavefish; confirm that CF are bona fide “alanine specialists”) and for serine (10-2M to 104M tested on both morphs; confirm that both morphs respond well to this amino acid). These complementary results are now included in text and figures (partially) and in the summary table 1.

      If anything is known about this, I would also welcome some discussion on how thigmotactic behavior, a marker of stress in SF, could have evolved to become the normal behavior of CF forms, with lower cortisol levels and, therefore lower anxiety.

      We actually think thigmotactism is a marker of stress in both morphs. See Pierre et al, JEB 2020, Figure S3A: in both SF and CF thigmotaxis behavior decreases after long habituation times. In our hands, the only difference between the two morphs is that surface fish (at 5 month of age) express stress by thigmotactism but also freezing and rapid erratic movements, while cavefish have a more restricted stress repertoire.

      This is why in the present paper we have carefully made the distinction between thigmotactism (= possible stress readout) and wall following (= exploratory behavior). Our finding that WF and large circles confers better olfactory response scores to cavefish is in strong support of the different nature of these two swimming patterns. Then, why is swimming along the 4 walls of a tank fundamentally different from swimming along one wall? The question is open, although the number of changes of direction is probably an important parameter: in WF the fish always swims forward in the same direction, while in T the fish constantly changes direction when reaching the corner of the tank – which is similar to erratic swim in stressed surface fish.

      Finally two smaller suggestions:

      • When referring to multiple panels on the same figure it would be better to format the reference as "Figure 4D-G" instead of "Figure 4DEFG";

      Done

      • On page 4, where the introduction reads as "although adults have a similar olfactory rosette with 2025 lamellae", in my opinion, it would be better to state that "while adults of the two forms have a similar olfactory rosette with 20-25 lamellae".

      Done

      Reviewer #3 (Recommendations For The Authors):

      Consider moving Figure 3 to be a supplement of Figure 4. This figure shows a water control and therefore best supplements the alanine experiment.

      We would like to keep this figure as a main figure: we consider it very important to establish the validity of our behavioral setup at the beginning of the ms, and to establish that in all the following figures we are recording bona fide olfactory responses.

      "sensory changes in mecano-sensory and gustatory systems " - mechano-sensory.

      Done

      Figure 2 legend: "(3) the right track is the 3D plus time (color-coded)" - shouldn't it be 2D plus time or 3D (x,y, time).

      True! Thanks for noting this, corrected.

      Figure 4 legend "E, Change in swimming patterns" should be H.

      Done

      "suggesting that their detection threshold for serine is lower than for alanine" - higher?

      Done

      In the behavioural plots, I assume that the "mean position" value represents the mean position along the X-axis of the chamber - this should be clarified and the axis label updated accordingly.

      That is correct and has been updated in Methods and Figures and legends.

      "speed, back and forth trips in X and Y, position and pattern changes (see Methods; Figure 7A)." - here it would be helpful to add an explanation like "to define an olfactory score for individual fish."

      This has been changed in Results and more detailed explanations on score calculations are now given in Methods.

      "possess enhanced mecanosensory lateral line" - mechanosensory.

      Done

    1. Author response:

      We would like to thank the eLife Editors and Reviewers for their positive assessment and constructive comments, and for the opportunity to revise our manuscript. We greatly appreciate the Reviewers’ recommendations and believe that they will further improve our manuscript.

      In revising the manuscript, our primary focus will be enhancing the clarity surrounding testing procedures and addressing corrections for multiple comparisons. Additionally, we intend to offer more explicit information about the statistical tests employed, along with the details about the number of models/comparisons for each test. We will also include an extended discussion on potential limitations of the dopaminergic receptor mapping methods used, addressing the Reviewers’ comments relating to the quality of PET imaging with different dopaminergic tracers in mesiotemporal regions such as the hippocampus. While the code used for connectopic mapping is publicly available through the ConGrads toolbox, we will provide the additional code we have used for data processing and analysis, visualization of hippocampal gradients, and the cortical projections. The data used in the current study is not publicly available due to ethical considerations concerning data sharing, but can be shared upon reasonable request from the senior author. Additional plans include clarifying and discussing which findings were successfully replicated, and addressing Reviewers’ suggestions for using other openly available cohorts for replication, and implementing alternative coordinate systems to quantify connectivity change along gradients.

    2. eLife assessment

      This fundamental work demonstrates the importance of considering overlapping modes of functional organization (i.e. gradients) in the hippocampus, showing associations between with aging, dopaminergic receptor distribution and episodic memory. The evidence supporting the conclusions is solid, although some clarifications about testing procedures and a discussion of the limitations of the dopaminergic receptor mapping techniques employed should be provided along with analysis code. The work will be of broad interest to basic and clinical neuroscientists.

    3. Reviewer #2 (Public Review):

      Summary:

      This paper derives the first three functional gradients in the left and right hippocampus across two datasets. These gradient maps are then compared to dopamine receptor maps obtained with PET, associated with age, and linked to memory. Results reveal links between dopamine maps and gradient 2, age with gradients 1 and 2, and memory performance.

      Strengths:

      This paper investigates how hippocampal gradients relate to aging, memory, and dopamine receptors, which are interesting and important questions. A strength of the paper is that some of the findings were replicated in a separate sample.

      Weaknesses

      The paper would benefit from added clarification on the number of models/comparisons for each test. Furthermore, it would be helpful to clarify whether or not multiple comparison correction was performed and - if so - what type or - if not - to provide a justification. The manuscript would furthermore benefit from code sharing and clarifying which results did/did not replicate.

    1. Author response:

      Reviewer #1 (Public Review):

      This study makes a substantial contribution to our understanding of the molecular evolutionary dynamics of microbial genomes by proposing a model that incorporates relatively frequent adaptive reversion mutations. In many ways, this makes sense from my own experience with evolutionary genomic data of microbes, where reversions are surprisingly familiar as evidence of the immense power of selection in large populations.

      One criticism is the reliance on one major data set of B. fragilis to test fits of these models, but this is relatively minor in my opinion and can be caveated by discussion of other relevant datasets for parallel investigation.

      We analyze data from 10 species of the Bacteroidales family, and we compare it to a dataset of Bacteroides fragilis. We have now added a reference to a recent manuscript from our group showing phenotypic alteration by reversion of a stop codon and further breaking of the same pathway through stop codons in other genes in Burkholderia dolosa on page 9, and have added a new analysis of codon usage in support of the reversion model on page 14.

      We have chosen not to analyze other species as there are no large data sets with rigorous and evenly-applied quality control across scales. We anticipate the reversion model would be able to fit the data in these cases. We now note that this work remains to be done in the discussion.

      Another point is that this problem isn't as new as the manuscript indicates, see for example https://journals.asm.org/doi/10.1128/aem.02002-20 .

      Loo et al puts forward an explanation similar to the purifying model proposed by Rocha et al, which we refute here. Quoting from Loo et al: “Our results confirm the observation that nonsynonymous SNPs are relatively elevated under shorter time periods and that purifying selection is more apparent over longer periods or during transmission.” While there is some linguistic similarity between the weak purifying model and our model of strong local adaptation model and strong adaptive reversion, we believe that the dynamical and predictive implications suggested by the reversion model are an important conceptual leap and correction to the literature. We now cite Loo et al and additional works cited therein. We have updated the abstract, introduction, and discussion to further emphasize the distinction of the reversion model from previous models: namely the implication of the reversion model that long-time scale dN/dS hides dynamics.

      Nonetheless, the paper succeeds by both developing theory and offering concrete parameters to illustrate the magnitudes of the problems that distinguish competing ideas, for example, the risk of mutational load posed in the absence of frequent back mutation.

      Reviewer #2 (Public Review):

      This manuscript asks how different forms of selection affect the patterns of genetic diversity in microbial populations. One popular metric used to infer signatures of selection is dN/dS, the ratio of nonsynonymous to synonymous distances between two genomes. Previous observations across many bacterial species have found dN/dS decreases with dS, which is a proxy for the divergence time. The most common interpretation of this pattern was proposed by Rocha et al. (2006), who suggested the excess in nonsynonymous mutations on short divergence times represent transient deleterious mutations that have not yet been purged by selection.

      In this study, the authors propose an alternative model based on the population structure of human gut bacteria, in which dN is dominated by selective sweeps of SNPs that revert previous mutations within local populations. The authors argue that contrary to standard population genetics models, which are based on the population dynamics of large eukaryotes, the large populations in the human gut mean that reversions may be quite common and may have a large impact on evolutionary dynamics. They show that such a model can fit the decrease of dN/dS in time at least as well as the purifying selection model.

      Strengths

      The main strength of the manuscript is to show that adaptive sweeps in gut microbial populations can lead to small dN/dS. While previous work has shown that using dN/dS to infer the strength of selection within a population is problematic (see Kryazhimskiy and Plotkin, 2008, cited in the paper) the particular mechanism proposed by the authors is new to my knowledge. In addition, despite the known caveats, dN/dS values are still routinely reported in studies of microbial evolution, and so their interpretation should be of considerable interest to the community.

      The authors provide compelling justification for the importance of adaptive reversions and make a good case that these need to be carefully considered by future studies of microbial evolution. The authors show that their model can fit the data as well as the standard model based on purifying selection and the parameters they infer appear to be plausible given known data. More generally, I found the discussion on the implications of traditional population genetics models in the context of human gut bacteria to be a valuable contribution of the paper.

      Thank you for the kind words and appreciation of the manuscript.

      Weaknesses

      The authors argue that the purifying selection model would predict a gradual loss in fitness via Muller's ratchet. This is true if recombination is ignored, but this assumption is inconsistent with the data from Garud, et al. (2019) cited in the manuscript, who showed a significant linkage decrease in the bacteria also used in this study.

      We now investigate the effect of recombination on the purifying selection model on page 8 and in Supplementary Figure S6. In short, we show that reasonable levels of recombination (obtained from literature r/m values) cannot rescue the purifying selection model from Muller’s ratchet when s is so low and the influx of new deleterious mutations is so high. We thank the reviewers for prompting this improvement.

      I also found that the data analysis part of the paper added little new to what was previously known. Most of the data comes directly from the Garud et al. study and the analysis is very similar as well. Even if other appropriate data may not currently be available, I feel that more could be done to test specific predictions of the model with more careful analysis.

      In addition to new analyses regarding recombination and compensatory mutations using the Garud et al data set, we have now added two new analyses, both using Bacteroides fragilis . First, we show that de novo mutations in Zhao & Lieberman et al dataset include an enrichment of premature stop codons (page 9). Second we show that genes expected to be under fluctuating selection in B. fragilis displays a significant closeness to stop codons, consistent with recent stop codons and reversions. We thank the reviewer for prompting the improvement.

      Finally, I found the description of the underlying assumptions of the model and the theoretical results difficult to understand. I could not, for example, relate the fitting parameters nloci and Tadapt to the simulations after reading the main text and the supplement. In addition, it was not clear to me if simulations involved actual hosts or how the changes in selection coefficients for different sites was implemented. Note that these are not simply issues of exposition since the specific implementation of the model could conceivably lead to different results. For example, if the environmental change is due to the colonization of a different host, it would presumably affect the selection coefficients at many sites at once and lead to clonal interference. Related to this point, it was also not clear that the weak mutation strong selection assumption is consistent with the microscopic parameters of the model. The authors also mention that "superspreading" may somehow make a difference to the probability of maintaining the least loaded class in the purifying selection model, but what they mean by this was not adequately explained.

      We apologize for leaving the specifics of the implementation from the paper and only accessible through the Github page and have corrected this. We have added a new section in the methods further detailing the reversion model and the specifics of how nloci and Tadapt (now tau_switch as of the edits) are implemented in the code.

      The possibility for clonal interference is indeed included in the simulation. Switching is not correlated with transmissions in our main figure simulations (Figure 4a). When we run simulations in which transmission and selection are correlated, the results remain essentially the same, barring higher variance at lower divergences (new Figure S10). We have now clarified these points in the results, and have also better clarified the selection only at transmission model in the main results.

      Reviewer #3 (Public Review):

      The diversity of bacterial species in the human gut microbiome is widely known, but the extensive diversity within each species is far less appreciated. Strains found in individuals on opposite sides of the globe can differ by as little as handfuls of mutations, while strains found in an individual's gut, or in the same household, might have a common ancestor tens of thousands of years ago. What are the evolutionary, ecological, and transmission dynamics that established and maintain this diversity?

      The time, T, since the common ancestor of two strains, can be directly inferred by comparing their core genomes and finding the fraction of synonymous (non-amino acid changing) sites at which they differ: dS. With the per-site per-generation mutation rate, μ, and the mean generation times roughly known, this directly yields T (albeit with substantial uncertainty of the generation time.) A traditional way to probe the extent to which selection plays a role is to study pairs of strains and compare the fraction of non-synonymous (amino acid or stop-codon changing) sites, dN, at which the strains differ with their dS. Small dN/dS, as found between distantly related strains, is attributed to purifying selection against deleterious mutations dominating over mutations that have driven adaptive evolution. Large dN/dS as found in laboratory evolution experiments, is caused by beneficial mutations that quickly arise in large bacterial populations, and, with substantial selective advantages, per generation, can rise to high abundance fast enough that very few synonymous mutations arise in the lineages that take over the population.

      A number of studies (including by Lieberman's group) have analyzed large numbers of strains of various dominant human gut species and studied how dN/dS varies. Although between closely related strains the variations are large -- often much larger than attributable to just statistical variations -- a systematic trend from dN/dS around unity or larger for close relatives to dN/dS ~ 0.1 for more distant relatives has been found in enough species that it is natural to conjecture a general explanation.

      The conventional explanation is that, for close relatives, the effects of selection over the time since they diverged has not yet purged weakly deleterious mutations that arose by chance -- roughly mutations with sT<1 -- while since the common ancestor of more distantly related strains, there is plenty of time for most of those that arose to have been purged.

      Torrillo and Lieberman have carried out an in-depth -- sophisticated and quantitative -- analysis of models of some of the evolutionary processes that shape the dependence of dN/dS on dS -- and hence on their divergence time, T. They first review the purifying selection model and show that -- even ignoring its inability to explain dN/dS > 1 for many closely related pairs -- the model has major problems explaining the crossover from dN/dS somewhat less than unity to much smaller values as dS goes through -- on a logarithmic scale -- the 10^-4 range. The first problem, already seen in the infinite-population-size deterministic model, is that a very large fraction of non-synonymous mutations would have to have deleterious s's in the 10^-5 per generation range to fit the data (and a small fraction effectively neutral). As the s's are naturally expected (at least in the absence of quantitative analysis to the contrary) to be spread out over a wide range on a logarithmic scale of s, this seems implausible. But the authors go further and analyze the effects of fluctuations that occur even in the very large populations: ~ >10^12 bacteria per species in one gut, and 10^10 human guts globally. They show that Muller's ratchet -- the gradual accumulation of weakly deleterious mutations that are not purged by selection - leads to a mutational meltdown with the parameters needed to fit the purifying selection model. In particular, with N_e the "effective population size" that roughly parametrizes the magnitude of stochastic birth-death and transition fluctuations, and U the total mutation rate to such deleterious mutations this occurs for U/s > log(sN_e) which they show would obtain with the fitted parameters.

      Torrillo and Lieberman promise an alternate model: that there are a modest number of "loci" at which conditionally beneficial mutations can occur that are beneficial in some individual guts (or other environmental conditions) at some times, but deleterious in other (or the same) gut at other times. With the ancestors of a pair of strains having passed through one too many individuals and transmissions, it is possible for a beneficial mutation to occur and rise in the population, only later to be reverted by the beneficial inverse mutation. With tens of loci at which this can occur, they show that this process could explain the drop of dN/dS from short times -- in which very few such mutations have occurred -- to very long times by which most have flipped back and forth so that a random pair of strains will have the same nucleotide at such sites with 50% probability. Their qualitative analysis of a minimally simple model of this process shows that the bacterial populations are plenty big enough for such specific mutations to occur many times in each individual's gut, and with modest beneficials, to takeover. With a few of these conditionally beneficial mutations or reversions occurring during an individuals lifetime, they get a reasonably quantitative agreement with the dN/dS vs dS data with very few parameters. A key assumption of their model is that genetically exact reversion mutations are far more likely to takeover a gut population -- and spread -- than compensatory mutations which have a similar phenotypic-reversion effect: a mutation that is reverted does not show up in dN, while one that is compensated by another shows up as a two-mutation difference after the environment has changed twice.

      Strengths:

      The quantitative arguments made against the conventional purifying selection model are highly compelling, especially the consideration of multiple aspects that are usually ignored, including -- crucially -- how Muller's ratchet arises and depends on the realistic and needed-to-fit parameters; the effects of bottlenecks in transmission and the possibility that purifying selection mainly occurs then; and complications of the model of a single deleterious s, to include a distribution of selective disadvantages. Generally, the author's approach of focusing on the simplest models with as few as possible parameters (some roughly known), and then adding in various effects one-by-one, is outstanding and, in being used to analyze environmental microbial data, exceptional.

      The reversion model the authors propose and study is a simple general one and they again explore carefully various aspects of it -- including dynamics within and between hosts -- and the consequent qualitative and quantitative effects. Again, the quantitive analysis of almost all aspects is exemplary. Although it is hard to make a compelling guess of the number of loci that are subject to alternating selection on the needed time-scales (years to centuries) they make a reasonable argument for a lower bound in terms of the number of known invertible promoters (that can genetically switch gene expression on and off).

      We are very grateful for the reviewer’s kind words and careful reading.

      Weaknesses:

      The primary weakness of this paper is one that the author's are completely open about: the assumption that, collectively, any of possibly-many compensatory mutations that could phenotypically revert an earlier mutation, are less likely to arise and takeover local populations than the exact specific reversion mutation. While detailed analysis of this is, reasonably enough, beyond the scope of the present paper, more discussion of this issue would add substantially to this work. Quantitatively, the problem is that even a modest number of compensatory mutations occurring as the environmental pressures change could lead to enough accumulation of non-synonymous mutations that they could cause dN/dS to stay large -- easily >1 -- to much larger dS than is observed. If, say, the appropriate locus is a gene, the number of combinations of mutations that are better in each environment would play a role in how large dN would saturate to in the steady state (1/2 of n_loci in the author's model). It is possible that clonal interference between compensatory and reversion mutations would result in the mutations with the largest s -- eg, as mentioned, reversion of a stop codon -- being much more likely to take over, and this could limit the typical number of differences between quite well-diverged strains. However, the reversion and subsequent re-reversion would have to both beat out other possible compensatory mutations -- naively less likely. I recommend that a few sentences in the Discussion be added on this important issue along with comments on the more general puzzle -- at least to this reader! -- as to why there appear to be so little adaptive genetic changes in core genomes on time scales of human lifetimes and civilization.

      We now directly consider compensatory mutations (page 14, SI text 3.2, and Supplementary Figure 12). We show that as long as true reversions are more likely than compensatory mutations overall, (adaptive) nonsynonymous mutations will still tend to revert towards their initial state and not contribute to asymptotic dN/dS, and show that true reversions are expected in a large swath of parameter space. Thank you for motivating this improvement!

      We note in the discussion that directional selection could be incorporated into the parameter alpha (assuming even more of the genome is deleterious) on page 16.

      An important feature of gut bacterial evolution that is now being intensely studied is only mentioned in passing at the end of this paper: horizontal transfer and recombination of core genetic material. As this tends to bring in many more mutations overall than occur in regions of a pair of genomes with asexual ancestry, the effects cannot be neglected. To what extent can this give rise to a similar dependence of dN/dS on dS as seen in the data? Of course, such a picture begs the question as to what sets the low dN/dS of segments that are recombined --- often from genetic distances comparable to the diameter of the species.

      We now discuss the effect of recombination on the purifying selection model on page 8 and in Supplementary Figure S6. In short, we now show that reasonable levels of recombination cannot rescue the purifying selection model from Muller’s ratchet when s is so low and the influx of new deleterious mutations is so high. We thank the reviewers for prompting this improvement

    1. We use a cost-effectiveness analysis to quantify our reasoning. Here is a summary of our analysis, using one state, Bauchi, as an example.

      The linked Google sheet is hard to parse and hard to read. This makes it less than fully transparent. E.g., the columns are frozen in a way that you can barely navigate the by-region columns.

      Linking something people can't use doesn't add transparency, it just wastes people's attention. If you feel the need put these links at the bottom, in a 'data section' or something. Anyone who wants to dig into it will need to do so as part of a separate and intensive exercise -- not just a glance while reading this. At least that's my impression.

      But also note that a code notebook based platform can be far more manageable for the reader.

    1. initializer list

      List of initialising data attached to an array by the programmer manually in the code.

      In this method of creating an array, the programmer doesn't need to specify the size of the array as it will be automatically determined (you still need to specify the data type of the data list).

    1. some of the main reasons to use multiple methods in your programs: Organization and Reducing Complexity: organize your program into small sections of code by function to reduce its complexity. Divide a problem into subproblems to solve it a piece at a time. Reusing Code: avoid repetition of code. Reuse code by putting it in a method and calling it whenever needed. Maintainability and Debugging: smaller methods are easier to debug and understand than searching through a large main method.

      Some of the main reasons to use multiple methods in your programs

    2. Procedural Abstraction

      Procedurally abstracting the details of how stuff works behind the scenes.

      It basically a word for the process of using the concept of functions on code.

    1. Reviewer #3 (Public Review):

      Summary:

      The authors consider several known aspects of PV and SOM interneurons and tie them together into a coherent single-cell model that demonstrates how the aspects interact. These aspects are:<br /> (1) While SOM interneurons target distal parts of pyramidal cell dendrites, PV interneurons target perisomatic regions.<br /> (2) SOM interneurons are associated with beta rhythms, PV interneurons with gamma rhythms.<br /> (3) Clustered excitation on dendrites can trigger various forms of dendritic spikes independent of somatic spikes. The main finding is that SOM and PV interneurons are not simply associated with beta and gamma frequencies respectively, but that their ability to modulate the activity of a pyramidal cell "works best" at their assigned frequencies. For example, distally targeting SOM interneurons are ideally placed to precisely modulate dendritic Ca-spikes when their firing is modulated at beta frequencies or timed relative to excitatory inputs. Outside those activity regimes, not only is modulation weakened, but overall firing reduced.

      Strengths:

      I think the greatest strength is the model itself. While the various individual findings were largely known or strongly expected, the model provides a coherent and quantitative picture of how they come together and interact.

      The paper also powerfully demonstrates that an established view of "subtractive" vs. "divisive" inhibition may be too soma-focused and provide an incomplete picture in cells with dendritic nonlinearities giving rise to a separate, non-somatic all-or-nothing mechanism (Ca-spike).

      Weaknesses:

      While the authors overall did an admirable job of simulating the neuron in an in-vivo-like activity regime, I think it still provides an idealized picture that it optimized for the generation of the types of events the authors were interested in. That is not a problem per se - studying a mechanism under idealized conditions is a great advantage of simulation techniques - but this should be more clearly characterized. Specifics on this are very detailed and will follow in the comments to authors.

      What disappointed me a bit was the lack of a concise summary of what we learned beyond the fact that beta and gamma act differently on dendritic integration. The individual paragraphs of the discussion often are 80% summary of existing theories and only a single vague statement about how the results in this study relate. I think a summarizing schematic or similar would help immensely.

      Orthogonal to that, there were some points where the authors could have offered more depth on specific features. For example, the authors summarized that their "results suggest that the timescales of these rhythms align with the specialized impacts of SOM and PV interneurons on neuronal integration". Here they could go deeper and try to explain why SOM impact is specialized at slower time scales. (I think their results provide enough for a speculative outlook.)

      Beyond that, the authors invite the community to reappraise the role of gamma and beta in coding. This idea seems to be hindered by the fact that I cannot find a mention of a release of the model used in this work. The base pyramidal cell model is of course available from the original study, but it would be helpful for follow-up work to release the complete setup including excitatory and inhibitory synapses and their activation in the different simulation paradigms used. As well as code related to that.

      Impact:

      Individually, most results were at least qualitatively known or at least expected. However, demonstrating that beta-modulation of dendritic events and gamma-modulation of soma spiking can work together, at the same time and in the same model can lead to highly valuable follow-up work. For example, by studying how top-down excitation onto apical compartments and bottom-up excitation on basal compartments interacts with the various rhythms; or what the impact of silencing of SOM neurons by VIP interneuron activation entails. But this requires - again - public release of the model and the code controlling the simulation setups.

      Beyond that, the authors clearly demonstrated that a single compartment, i.e., only a soma-focused view is too simple, at least when beta is considered. Conversely, the authors were able to describe the impact of most things related to the apical dendrite on somatic spiking as "going through" the Ca-spike mechanism. Therefore, the setup may serve as the basis of constraining simplified two-compartment models in the future.

    1. You don’t need to write a getter for every instance variable in a class but if you want code outside the class to be able to get the value of one of your instance variables, you’ll need to write a getter that looks like the following. class ExampleTemplate { // Instance variable declaration private typeOfVar varName; // Accessor (getter) method template public typeOfVar getVarName() { return varName; } } Notice that the getter’s return type is the same as the type of the instance variable and all the body of the getter does is return the value of the variable using a return statement.

      Making Private instance variables available for access for methods outside the class by creating a public getter method to return the value in the private instance variable.

    1. 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

      Reply to reviewer comments

      • *

      We extend our gratitude to the reviewers for their time and valuable feedback on our manuscript. We especially appreciate the insightful suggestions that have significantly contributed to refining our work and elucidating our findings. With the revisions made to the text and the inclusion of new experimental data, we believe our manuscript now effectively addresses all reviewer comments. We eagerly await your evaluation of our revised submission.

      Small ARF-like GTPases play fundamental roles in dynamic signaling processes linked with vesicular trafficking in eukaryotes. Despite of their evolutionary conservation, there is little known about the ARF-like GTPase functions in plants. Our manuscript reports the biochemical and cell biological characterization of the small ARF-like GTPase TTN5 from the model plant Arabidopsis thaliana*. Fundamental investigations like ours are mostly lacking for ARF and ARL GTPases in Arabidopsis. *

      We employed fluorescence-based enzymatic assays suited to uncover different types of the very rapid GTPase activities for TTN5. The experimental findings are now illustrated in a more comprehensive modified Figure 2 and in the form of a summary of the GTPase activities for TTN5 and its mutant variants in the NEW Figure 7A in the Discussion part. Taken together, we found that TTN5 is a non-classical GTPase based on its enzymatic kinetics. The reviewers appreciated these findings and highlighted them as being „impressive in vitro biochemical characterization" and "major conceptual advance". Since such experiments are "uncommon" for being conducted with plant GTPases, reviewers regarded this analysis as "useful addition to the plant community in general". The significance of these findings is given by the circumstance that „the ARF-like proteins are poorly addressed in Arabidopsis while they could reveal completely different function than the canonical known ARF proteins". Reviewers saw here clearly a "strength" of the manuscript.

      With regard to the cell biological investigation and initial assessment of cell physiological roles of TTN5, we now provide requested additional evidence. First of all, we provide NEW data on the localization of TTN5 by immunolocalization using a complementing HA3-TTN5 construct, supporting our initial suggestions that TTN5 may be associated with vesicles and processes of the endomembrane system. The previous preprint version had left the reviewers „less convinced" of cell biological data due to the lack of complementation of our YFP-TTN5 construct, lack of Western blot data and the low resolution of microscopic images. We fully agree that these points were of concern and needed to be addressed. We have therefore intensively worked on these „weaknesses" and present now a more detailed whole-mount immunostaining series with the complementing HA3-TTN5 transgenic line (NEW Figure 4, NEW Figure 3P), Western blot data (NEW Supplementary Figures S7C and D), and we will provide all original images upon publication of our manuscript at BioImage Archives which will provide the high quality for re-analysis. BioImage Archives is an online storage for biological image data associated with a peer-reviewed publication. This way, readers will be able to inspect each image in detail. The immunolocalization data are of particular importance as they indicate that HA3-TTN5 can be associated with punctate vesicle structures and BFA bodies as seen with YFP studies of YFP-TTN5 seedlings. We have re-phrased very carefully and emphasized those localization patterns which are backed up by immunostaining and YFP fluorescence detection of YFP-TTN5 signals. To improve the comprehension, the findings are summarized in a schematic overview in NEW Figure 7B of the Discussion. We have also addressed all other comments related to the cell biological experiments to "provide the substantial improvement" that had been requested. We emphasize that we found two cell physiological phenotypes for the TTN5T30N mutant. YFP-TTN5T30N confers phenotypes, which are differing mobility of the fluorescent vesicles in the epidermis of hypocotyls (see Video material and NEW Supplementary Video Material S1M-O), and a root growth phenotype of transgenic HA3-TTN5T30N seedlings (NEW Figure 3O). We explain the cell physiological phenotypes in relation to enzymatic GTPase data. These findings convince us of the validity of the YFP-TTN5 analysis indicative of TTN5 localization.

      *We are deeply thankful to the reviewers for judging our manuscript as "generally well written", "important" and "of interest to a wide range of plant scientists" and "for scientists working in the trafficking field" as it "holds significance" and will form the basis for future functional studies of TTN5. *

      We prepared very carefully our revised manuscript in which we address all reviewer comments one by one. Please find our revision and our detailed rebuttal to all reviewer comments below. Changes in the revised version are highlighted by yellow and green color. In the "revised version with highlighted changes".

      With these adjustments, we hope that our peer-reviewed study will receive a positive response.

      We are looking forward to your evaluation of our revised manuscript and thank you in advance,

      Sincerely

      Petra Bauer and Inga Mohr on behalf of all authors

      *

      • *

      __Reviewer #1 (Evidence, reproducibility and clarity (Required)): __

      The manuscript from Mohr and collaborators reports the characterization of an ARF-like GTPase of Arabidopsis. Small GTPases of the ARF family play crucial role in intracellular trafficking and plant physiology. The ARF-like proteins are poorly addressed in Arabidopsis while they could reveal completely different function than the canonical known ARF proteins. Thus, the aim of the study is important and could be of interest to a wide range of plant scientists. I am impressed by the biochemical characterization of the TTN5 protein and its mutated versions, this is clearly a very nice point of the paper and allows for proper interpretations of the other results. However, I was much less convinced on the cell biology part of this manuscript and aside from the subcellular localization of the TTN5 I think the paper would benefit from a more functional angle. Below are my comments to improve the manuscript:

      1- In the different pictures and movies, TTN5 is quite clearly appearing as a typical ER-like pattern. The pattern of localization further extends to dotty-like structures and structures labeled only at the periphery of the structure, with a depletion of fluorescence inside the structure. These observations raise several points. First, the ER pattern is never mentioned in the manuscript while I think it can be clearly observed. Given that the YFP-TTN5 construct is not functional (the mutant phenotype is not rescued) the ER-localization could be due to the retention at the ER due to quality control. The HA-TTN5 construct is functional but to me its localization shows a quite different pattern from the YFP version, I do not see the ER for example or the periphery-labeled structures. In this case, it will be a crucial point to perform co-localization experiments between HA-TTN5 and organelles markers to confirm that the functional TTN5 construct is labeling the Golgi and MVBs, as does the non-functional one. I am also quite sure that a co-localization between YFP-TTN5 and HA-TTN5 will not completely match... The ER is contacting so many organelles that the localization of YFP-TTN5 might not reflects the real location of the protein.

      __Our response: __

      At first, we like to state that specific detection of intracellular localization of plant proteins in plant cells is generally technically very difficult, when the protein abundance is not overly high. In this revised version, we extended immunostaining analysis to different membrane compartments, including now immunostaining of complementing HA3-TTN5 in the absence and presence of BFA, along with immunodetection of ARF1 and FM4-64 labeling in roots (NEW Figure 3P, NEW Figure 4A, B). In the revised version, we focus the analysis and conclusions on the fluorescence patterns that overlap between YFP-TTN5 detection and HA3-TTN5 immunodetection. With this, we can be most confident about subcellular TTN5 localization. Please find this NEW text in the Result section (starting Line 323):

      „For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."

      We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):

      „Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

      *And we discuss in the Discussion section (starting Line 552): *

      „We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."

      2- What are the structures with TTN5 fluorescence depleted at the center that appear in control conditions? They look different from the Golgi labeled by Man1 but similar to MVBs upon wortmannin treatment, except that in control conditions MVBs never appear like this. Are they related to any kind of vacuolar structures that would be involved in quality control-induced degradation of non-functional proteins?

      Our response:

      The reviewer certainly refers to fluorescence images from N. benthamiana leaf epidermal cells where different circularly shaped structures are visible. In these respective structures, the fluorescent circles are depleted from fluorescence in the center, e.g. in Figure 5C, YFP- fluorescent signals in TTN5T30N transformed leaf discs. We suspect that these structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al., 2020 for ANNI-GFP (reference in manuscript). The reviewer certainly does not refer to swollen MVBs that are seen following wortmannin treatment, as in Figure 5N-P, which look similar in their shape but are larger in size. Please note that we always included the control conditions, namely the images recorded before the wortmannin treatment, so that we were able to investigate the changes induced by wortmannin. Hence, we can clearly say that the structures with depleted fluorescence in the center as in Figure 5C are not wortmannin-induced swollen MVBs.To make these points clear to the reader, we added an explanation into the text (Line 385-388):

      „We also observed YFP fluorescence signals in the form of circularly shaped ring structures with a fluorescence-depleted center. These structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al. (2020) for ANNI-GFP."

      3- The fluorescence at nucleus could be due to a proportion of YFP-TTN5 that is degraded and released free-GFP, a western-blot of the membrane fraction vs the cytosolic fraction could help solving this issue.

      Our response:

      In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):

      „We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

      4- It is not so easy to conclude from the co-localization experiments. The confocal pictures are not always of high quality, some of them appear blurry. The Golgi localization looks convincing, but the BFA experiments are not that clear. The MVB localization is pretty convincing but the images are blurry. An issue is the quantification of the co-localizations. Several methods were employed but they do not provide consistent results. As for the object-based co-localization method, the authors employ in the text co-localization result either base on the % of YFP-labeled structures or the % of mCherry/mRFP-labeled structures, but the results are not going always in the same direction. For example, the proportion of YFP-TTN5 that co-localize with MVBs is not so different between WT and mutated version but the proportion of MVBs that co-localize with TTN5 is largely increased in the Q70L mutant. Thus it is quite difficult to interpret homogenously and in an unbiased way these results. Moreover, the results coming from the centroid-based method were presented in a table rather than a graph, I think here the authors wanted to hide the huge standard deviation of these results, what is the statistical meaning of these results?

      Our response:

      First of all, we like to point out that, as explained above, the BFA experiments are now more clear. We performed additional BFA treatment coupled with immunostaining using HA3-TTN5-expressing Arabidopsis seedlings and coupled with fluorescence analysis using YFP-TTN5-expressing Arabidopsis plants. In both experiments, we observed the typical BFA bodies very clearly (NEW Figure 4B, C).

      Second, we like to insist that we performed colocalization very carefully and quantified the data in three different manners. We like to state that there is no general standardized procedure that best suits the idea of a colocalization pattern. Results of colocalization are represented in stem diagrams and table format, including statistical analysis. Colocalization was carried out with the ImageJ plugin JACoP for Pearson's and Overlap coefficients and based on the centroid method. The plotted Pearson's and Overlap coefficients are presented in bar diagrams in Supplementary Figure S8A and C, including statistics. The obtained values by the centroid method are represented in table format in Supplementary Figure S8B and D, which *can be considered a standard method (see Ivanov et al., 2014). *

      Colocalization of two different fluorescence signals was performed for the two channels in a specific chosen region of interest (indicating in % the overlapping signal versus the sum of signal for each channel). The differences between the YFP/mRFP and mRFP/YFP ratios indicate that a higher percentage of ARA7-RFP signal is colocalizing with YFP-TTN5Q70L signal than with the TTN5WT or the TTN5T30N mutant form signals, while the YFP signals have a similar overlap with ARA7-positive structures. This is not a contradiction. Presumably this answers well the questions on colocalization.

      Please note that upon acceptance for publication, we will upload all original colocalization data to BioImage Archive. Hence, the high-quality data can be reanalyzed by readers.

      5- The use of FM4-64 to address the vacuolar trafficking is a hazardous, FM4-64 allows the tracking of endocytosis but does not say anything on vacuolar degradation targeting and even less on the potential function of TTN5 in endosomal vacuolar targeting. Similarly, TTN5, even if localized at the Golgi, is not necessarily function in Golgi-trafficking. __Our response: __

      *Perhaps our previous description was misleading. Thank you for pointing this out. We reformulated the text and modified the schematic representation of FM4-64 in NEW Figure 6A: *

      "(A), Schematic representation of progressive stages of FM4-64 localization and internalization in a cell. FM4-64 is a lipophilic substance. After infiltration, it first localizes in the plasma membrane, at later stages it localizes to intracellular vesicles and membrane compartments. This localization pattern reflects the endocytosis process (Bolte et al. 2004)."

      6- The manuscript lacks in its present shape of functional evidences for a role of TTN5 in any trafficking steps. I understand that the KO mutant is lethal but what are the phenotypes of the Q70L and T30N mutant plants? What is the seedling phenotype, how are the Golgi and MVBs looking like in these mutants? Do the Q70L or T30N mutants perturbed the trafficking of any cargos?

      __Our response: __

      *We agree fully that functional evidences are interesting to assign roles for TTN5 in trafficking steps. A phenotype associated with TTN5T30N and TTN5Q70L is clearly meaningful. *

      First of all, we like to emphasize that it is incorrect that the manuscript lacks functional evidences for a role of TTN5 and the two mutants. In fact, the manuscript even highlights several functional activities that are meaningful in a cellular context. These include different types of kinetic GTPase enzyme activities, subcellular localization in planta and association with different endomembrane compartments and subcellular processes such as endocytosis. We surely agree that future research can focus even more on cell physiological aspects and the physiological functions in plants to examine the proposed roles of TTN5 in intracellular trafficking steps. For such studies, our findings are the fundamental basis.

      Concerning the aspect of colocalization of the mutants with the markers we show in Figure 5C, D and G, H that YFP-TTN5T30N- and YFP-TTN5Q70L-related signals colocalize with the Golgi marker GmMan1-mCherry. Figure 5K, L and O, P show that YFP-TTN5T30N and YFP-TTN5Q70L-related signals can colocalize with the MVB marker, and this may affect relevant vesicle trafficking processes and plasma membrane protein regulation involved in root cell elongation.

      *At present, we have not yet investigated perturbed cargo trafficking. These aspects are certainly interesting but require extensive work and testing of appropriate physiological conditions and appropriate cargo targets. We discuss future perspectives in the Discussion. We agree that such functional information is of great importance, but needs to be clarified in future studies. *

      __Reviewer #1 (Significance (Required)): __

      In conclusion, I think this manuscript is a good biochemical description of an ARF-like protein but it would need to be strengthen on the cell biology and functional sides. Nonetheless, provided these limitations fixed, this manuscript would advance our knowledge of small GTPases in plants. The major conceptual advance of that study is to provide a non-canonical behavior of the active/inactive cycle dynamics for a small-GTPase. Of course this dynamic probably has an impact on TTN5 function and involvement in trafficking, although this remains to be fully demonstrated. Provided a substantial amount of additional experiments to support the claims of that study, this study could be of general interest for scientist working in the trafficking field.

      __Our response: __

      We thank reviewer 1 for the very fruitful comments. We hope that with the additional experiments, NEW Figures and NEW Supplementary Figures as well as our changes in the text, all comments by the reviewer have been addressed.

      __Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

      The manuscript by Mohr and colleagues characterizes the Arabidopsis predicted small GTPase TITAN5 in both biochemical and cell biology contexts using in vitro and in planta techniques. In the first half of the manuscript, the authors use in vitro nucleotide exchange assays to characterise the GTPase activity and nucleotide binding properties of TITAN5 and two mutant variants of it. The in vitro data they produce indicates that TITAN5 does indeed have general GTPase and nucleotide binding capability that would be expected for a protein predicted to be a small GTPase. Interestingly, the authors show that TITAN5 favors a GTP-bound form, which is different to many other characterized GTPases that favor GDP-binding. The authors follow their biochemical characterisation of TITAN with in planta experiments characterizing TITAN5 and its mutant variants association with the plant endomembrane system, both by stable expression in Arabidopsis and transient expression in N.benthamiana.

      The strength of this manuscript is in its in vitro biochemical characterisation of TITAN5 and variants. I am not an expert on in vitro GTPase characterisation and so cannot comment specifically on the assays they have used, but generally speaking this appears to have been well done, and the authors are to be commended for it. In vitro characterisation of plant small GTPases is uncommon, and much of our knowledge is inferred for work on animal or yeast GTPases, so this will be a useful addition to the plant community in general, especially as TITAN5 is an essential gene. The in planta data that follows is sadly not as compelling as the biochemical data, and suffers from several weaknesses. I would encourage the authors to consider trying to improve the quality of the in planta data in general. If improved and then combined with the biochemical aspects of the paper, this has the potential to make a nice addition to plant small GTPase and endomembrane literature.

      The manuscript is generally well written and includes the relevant literature.

      Major issues:

      1. The authors make use of a p35s: YFP-TTN5 construct (and its mutant variants) both stably in Arabidopsis and transiently in N.benthamiana. I know from personal experience that expressing small GTPases from non-endogenous promoters and in transient expression systems can give very different results to when working from endogenous promoters/using immunolocalization in stable expression systems. Strong over-expression could for example explain why the authors see high 'cytosolic' levels of YFP-TTN5. It is therefore questionable how much of the in planta localisation data presented using p35S and expression in tobacco is of true relevance to the biological function of TITAN5. The authors do present some immunolocalization data of HA3-TTN5 in Arabidopsis, but this is fairly limited and it is very difficult in its current form to use this to identify whether the data from YFP-TTN5 in Arabidopsis and tobacco can be corroborated. I would encourage the authors to consider expanding the immunolocalization data they present to validate their findings in tobacco. __Our response: __

      We are aware that endogenous promoters may be preferred over 35S promoter. However, the two types of lines we generated with endogenous promoter did both not show fluorescent signals so that we could unfortunately not use them (not shown). Besides 35S promoter-mediated expression we were also investigating inducible expression vectors for fluorescence imaging in N. benthamiana (not shown). Both inducible and constitutive expression showed very similar expression patterns so that we chose characterizing in detail the 35S::YFP-TTN5 fluorescence in both N. bethamiana*and Arabidopsis. *

      We have expanded immunolocalization using the HA3-TTN5 line and compare it now along with YFP fluorescence signal in YFP-TTN5 seedlings (NEW Figure 3P; NEW Figure 4).

      „For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."

      • *

      Many of the confocal images presented are of poor quality, particularly those from N.benthamiana.

      Our response:

      All confocal images are of high quality in their original format. To make them accessible, we will upload all raw data to BioImage Archive upon acceptance of the manuscript.

      The authors in some places see YFP-TTN5 in cell nuclei. This could be a result of YFP-cleavage rather than genuine nuclear localisation of YFP-TTN5, but the authors do not present western blots to check for this.

      __Our response: __

      As described in our response to reviewer 1, comment 3, Fluorescence signals were detected within the nuclei of root cells of YFP-TTN5 plants, while immunostaining signals of HA3-TTN5 were not detected in the nucleus. In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):

      • *

      „We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

      That YFP-TTN5 fails to rescue the ttn5 mutant indicates that YFP-tagged TTN5 may not be functional. If the authors cannot corroborate the YFP-TTN5 localisation pattern with that of HA3-TTN5 via immunolocalization, then the fact that YFP-TTN5 may not be functional calls into question the biological relevance of YFP-TTN5's localisation pattern.

      __Our response: __

      This refers to your comment 1, please check this comment for a detailed response. Please also see our answer to reviewer 1, comment 1.

      At first, we like to state that specific detection of intracellular localization of plant proteins in plant cells is generally technically very difficult, when the protein abundance is not overly high. In this revised version, we extended immunostaining analysis to different membrane compartments, including now immunostaining of complementing HA3-TTN5 in the absence and presence of BFA, along with immunodetection of ARF1 and FM4-64 labeling in roots (NEW Figure 3P, NEW Figure 4A, B). In the revised version, we focus the analysis and conclusions on the fluorescence patterns that overlap between YFP-TTN5 detection and HA3-TTN5 immunodetection. With this, we can be most confident about subcellular TTN5 localization. Please find this NEW text in the Result section (starting Line 323):

      „For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."

      We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):

      „Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

      *And we discuss in the Discussion section (starting Line 552): *

      „We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."

      • *

      Without a cell wall label/dye, the plasmolysis data presented in Figure 5 is hard to visualize.

      __Our response: __

      Figure 6E-G (previously Fig. 5) show the results of plasmolysis experiments with YFP-TTN5 and the two mutant variant constructs. It is clearly possible to observe plasmolysis when focusing on the Hechtian strands. Hechtian strands are formed due to the retraction of the protoplast as a result of the osmotic pressure by the added mannitol solution. Hechtian strands consist of PM which remained in contact with the cell wall, visible as thin filamental structures. We stained the PM and the Hechtian strands by the PM dye FM4-64. This is similary done in Yoneda et al., 2020. We could detect in the YFP-TTN5-transformed cells, colocalization with the YFP channels and the PM dye in filamental structures between two neighbouring FM4-64-labelled PMs. Although an additional labeling of the cell wall may further indicate plasmolysis, it is not needed here.

      Please consider that we will upload all original image data to BioImage Archive so that a detailed re-investigation of the images can be done.

      • *

      __Minor issues: __

      In some of the presented N.benthamiana images, it looks like YFP-TTN5 may be partially ER-localised. However, co-localisation with an ER marker is not presented.

      Our response:

      *Referring to our response to comments 1 and 3 of reviewer 2 and to comment 1 of reviewer 1: *

      We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):

      „Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

      *And we discuss in the Discussion section (starting Line 552): *

      „We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."

      • *

      There is some inconsistency within the N.benthamiana images. For example, compare Figure 4C of YFP-TTN5T30N to Figure 4O of YFP-TTN5T30N. Figure 4O is presented as being significant because wortmannin-induced swollen ARA7 compartments are labelled by YFP-TTN5T30N. However, structures very similar to these can already been seen in Figure 4C, which is apparently an unrelated experiment. This, to my mind, is likely a result of the very different expression levels between different cells that can be produced by transient expression in N.benthamiana.

      __Our response: __

      Former Figure 4 is now Figure 5. As detailed in our response to comment 2 of reviewer 1:

      The reviewer certainly refers to fluorescence images from N. benthamiana leaf epidermal cells where different circularly shaped structures are visible. In these respective structures, the fluorescent circles are depleted from fluorescence in the center, e.g. in Figure 5C, YFP- fluorescent signals in TTN5T30N transformed leaf discs. We suspect that these structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al., 2020 for ANNI-GFP (reference in manuscript). The reviewer certainly does not refer to swollen MVBs that are seen following wortmannin treatment, as in Figure 5N-P, which look similar in their shape but are larger in size. Please note that we always included the control conditions, namely the images recorded before the wortmannin treatment, so that we were able to investigate the changes induced by wortmannin. Hence, we can clearly say that the structures with depleted fluorescence in the center as in Figure 5C are not wortmannin-induced swollen MVBs.To make these points clear to the reader, we added an explanation into the text (Line 385-388):

      „We also observed YFP fluorescence signals in the form of circularly shaped ring structures with a fluorescence-depleted center. These structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al. (2020) for ANNI-GFP."

      **Referees cross-commenting**

      It sems that all of the reviewers have converged on the conclusion that the in planta characterisation of TTN5 is insufficient to be of substantial interest to the field, highlighting the fact that major improvements are required to strengthen this part of the manuscript and increase its relevance.

      __Reviewer #2 (Significance (Required)): __

      General assessment: the strengths of this work are in its in vitro characterisation of TITAN5, however, the in planta characterisation lacks depth.

      Significance: the in vitro characterisation of TITAN5 is commendable as such work is lacking for plant GTPases. However, the significance of the work would be boosted substantially by better in planta characterisation, which is where most the most broad interest will lie.

      My expertise: my expertise is in in planta characterisation of small GTPases and their interactors.

      __Our response: __

      We thank the reviewer for the kind evaluation of our manuscript. We are confident that the changes in the text and NEW Figures and NEW Supplementary Figures will be convincing to consider our work.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

      Summary: Cellular traffic is an important and well-studied biological process in animal and plant systems. While components involved in transport are known the mechanism by which these components control activity or destination remains to be studied. A critical step in regulating traffic is proper budding and tethering of vesicles. A critical component in determining this step is a family proteins with GTPase activity, which act as switches facilitating vesicle interaction between proteins, or cytoskeleton. The current manuscript by Mohr and colleagues have characterized a small GTPase TITAN5 (TTN5) and identified two residues Gln70 and Thr30 in the protein which they propose to have functional roles. The authors catalogue the localization, GTP hydrolytic activity, and discuss putative functions of TTN5 and the mutants.

      __Major comments: __

      The core of the manuscript, which is descriptive characterization of TTN5, lies in reliably demonstrating putative roles. While the GTP hydrolysis rates are well-quantified (though the claims need to be toned down), the microscopy data especially the association of TTN5 with different endomembrane compartments is not convincing due to the quality (low resolution) of the figures submitted. The manuscript text is difficult to navigate due to repetition and inconsistency in the order that the mutants are referred. I am requesting additional experiments which should be feasible considering the authors have all the materials required to perform the experiments and obtain high-quality images which support their claims.

      In general the figure quality needs to be improved for all microscopy images. I would suggest that the authors highlight 1-2 individual cells to make their point and use the current images as supplementary to establish a broader spread. __Our response: __

      *We have worked substantially on the text and figures to make the content well comprehensive. The mutants are referred to in a consistent manner in the text and figures. We have addressed requested experiments. *

      As we pointed out in the cover letter and our responses to reviewers 1 and 2, we will upload all raw image data to BioImage Archive upon acceptance of the manuscript so that they can be re-examined without any reduction of resolution. Furthermore, we have conducted new experiments on immunolocalization of HA3-TTN5 (NEW Figure 3P, NEW Figure 4A, B). The text has been improved in several places (see highlighted changes in the manuscript and as detailed in the responses to reviewer 1. We think, this addresses well the reviewers' concerns.

      Fig. S1 lacks clarity. __Our response: __

      Supplementary Figure S1 shows TTN5 gene expression in different organs and growing stages as revealed by transcriptomic data, made available through the AtGenExpress eFB tool of the Bio-Analytic Resource for Plant Biology (BAR). The figure visualizes that TTN5 is ubiquitously expressed in different plant organs and tissues, e.g. the epidermis layers that we investigated here, and throughout development including embryo development. In accordance with the embryo-lethal phenotype, this highlights well that TTN5* is needed throughout for plant growth and it emphasizes that our investigation of TTN5 localization in epidermis cells is valid. *

      We have added a better description to the figure legend. We now also mention the respective publications from which the transcriptome data-sets are derived. The modified figure legend is:

      "Supplementary Figure S1. Visualization of TTN5 gene expression levels during plant development based on transcriptome data. Expression levels in (A), different types of aerial organs at different developmental stages; from left to right and bottom to top are represented different seed and plant growth stages, flower development stages, different leaves, vegetative to inflorescence shoot apex, embryo and silique development stages; (B), seedling root tissues based on single cell analysis represented in form of a uniform manifold approximation and projection plot; (C), successive stages of embryo development. As shown in (A) to (C), TTN5 is ubiquitously expressed in these different plant organs and tissues. In particular, it should be noted that TTN5 transcripts were detectable in the epidermis cell layer of roots that we used for localization of tagged TTN5 protein in this study. In accordance with the embryo-lethal phenotype, the ubiquitous expression of TTN5 highlights its importance for plant growth. Original data were derived from (Nakabayashi et al. 2005, Schmid et al. 2005) (A); (Ryu et al. 2019) (B); (Waese et al. 2017) (C). Gene expression levels are indicated by local maximum color code, ranging from the minimum (no expression) in yellow to the maximum (highest expression) in red."

      For the supplementary videos, it is difficult to determine if punctate structures are moving or is it cytoplasmic streaming? Could this be done with a co-localized marker? Considering that such markers have been used later in Fig. 4? __Our response: __

      We had detected movement of YFP fluorescent structures in all analyzed YFP-TTN5 plant parts except the root tip. Movement of fluorescence signals in YFP-TTN5T30N seedlings was slowed in hypocotyl epidermis cells. To answer the reviewer comment, we added three NEW supplemental videos (NEW Supplementary Video Material S1M-O) generated with all the three YFP-TTN5 constructs imaged over time in N. benthamiana leaf epidermal cells upon colocalization with the cis-Golgi marker GmMan1-mCherry as requested by the reviewer. In these NEW videos, some of *the YFP fluorescent spots seem to move together with the Golgi stacks. GmMan1 is described with a stop-and-go directed movement mediated by the actino-myosin system (Nebenführ 1999) and similarly it might be the case for YFP-TTN5 signals based on the colocalization. *

      • *

      It would be good if the speed of movement is quantified, if the authors want to retain the current claims in results and the discussion. __Our response: __

      *We describe a difference in the movement of YFP fluorescent signal for the YFP-TTN5T30N variant in the hypocotyl compared to YFP-TTN5 and YFP-TTN5Q70L. In hypocotyl cells, we could observe a slowed down or arrested movement specifically of YFP-TTN5T30N fluorescent structures, and we describe this in the Results section (Line 278-291). *

      "Interestingly, the mobility of these punctate structures differed within the cells when the mutant YFP-TTN5T30N was observed in hypocotyl epidermis cells, but not in the leaf epidermis cells (Supplementary Video Material S1E, compare with S1B) nor was it the case for the YFP-TTN5Q70L mutant (Supplementary Video Material S1F, compare with S1E)."

      *The slowed movement in the YFP-TTN5T30N mutant is well visible even without quantification. We checked that the manuscript text does not contain overstatements in this regard. *

      • *

      Fig.2 I am not sure what the unit / scale is in Fig. 2D/E if each parameter (Kon, Koff, and Kd) are individually plotted? Could the authors please clarify/simplify this panel?

      __Our response: __

      We presented kinetics for nucleotide association (kon) and dissociation (koff) and the dissociation constant (Kd) in a bar diagram for each nucleotide, mdGDP (Figure 2D) and mGppNHp (Figure 2E). We modified and relabeled the bar diagram representation. It should be now very clear which are the parameters and units. Please see also the other modified figures (NEW modified Figure 2A-H). We also modified the legend of Figure 2D and E:

      "(D-E), Kinetics of association and dissociation of fluorescent nucleotides mdGDP (D) or mGppNHp (E) with TTN5 proteins (WT, TTN5T30N, TTN5Q70L) are illustrated as bar charts. The association of mdGDP (0.1 µM) or mGppNHp (0.1 µM) with increasing concentration of TTN5WT, TTN5T30N and TTN5Q70L was measured using a stopped-flow device (see A, B; data see Supplementary Figure S3A-F, S4A-E). Association rate constants (kon in µM-1s-1) were determined from the plot of increasing observed rate constants (kobs in s-1) against the corresponding concentrations of the TTN5 proteins. Intrinsic dissociation rates (koff in s-1) were determined by rapidly mixing 0.1 µM mdGDP-bound or mGppNHp-bound TTN5 proteins with the excess amount of unlabeled GDP (see A, C, data see Supplementary Figure S3G-I, S4F-H). The nucleotide affinity (dissociation constant or Kd in µM) of the corresponding TTN5 proteins was calculated by dividing koff by kon. When mixing mGppNHp with nucleotide-free TTN5T30N, no binding was observed (n.b.o.) under these experimental conditions."

      • *

      Are panels D and E representing values for mdGDP and GppNHP? This is not very clear from the figure legend.

      __Our response: __

      Yes, Figure 2D and E represent the kon, koff and Kd values for mdGDP (Figure 2D) and mGppNHP (Figure 2E). As detailed in our previous response to comment 2a, we modified figure and figure legend to make the representation more clear.

      • *

      Fig. 3 Same comments as in para above - improve resolution fo images, concentrate on a few selected cells, if required use an inset figure to zoom-in to specific compartments. Our response:

      As detailed in our responses to reviewers 1 and 2, we will upload all original image data to BioImage Archive upon acceptance of the manuscript, so that a detailed investigation of all our images is possible without any reduction of resolution.

      Please provide the non-fluorescent channel images to understand cell topography __Our response: __

      *We presented our microscopic images with the respective fluorescent channel and for colocalization with an additional merge. We did not present brightfield images as the cell topography was already well visible by fluorescent signal close to the PM. Therefore, brightfield images would not provide any benefit. Since we will upload all original data to BioImage Archive for a detailed investigation of all our images, the data can be obtained if needed. *

      Is the nuclear localization seen in transient expression (panel L-N) an artefact? If so, this needs to be mentioned in the text. Our response:

      As explained in our responses to reviewers 1 and 2, fluorescence signals were detected within the nuclei of root cells of YFP-TTN5 plants, while immunostaining signals of HA3-TTN5 were not detected in the nucleus.

      In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):

      „We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

      Fig. 4 - In addition to the points made for Fig. 3 The authors should consider reducing gain/exposure to improve image clarity. Especially for the punctate structures, which are difficult to observe in TTN5, likely because of the cytoplasmic localization as well.

      __Our response: __

      Thank you for this comment. We record image z-stacks and represent in single z-planes. Reducing the gain to decrease the cytoplasmic signal does not increase the clarity of the punctate structures as the signal strength will become weak.. As mentioned above, we will upload all original image data to BioImage Archive for a detailed investigation of all our images without any reduction of resolution.

      • *

      Reducing Agrobacterial load could be considered. OD of 0.4 is a bit much, 0.1 or even 0.05 could be tried. If available try expression in N. tabaccum, which is more amenable to microscopy. However, this is OPTIONAL, benthamiana should suffice. __Our response: __

      Thank you for the suggestion. We are routinely using N. benthamiana leaf infiltration. When setting up this method at first, we did not observe different localization results by using different ODs of bacterial cultures. Hence, an OD600 of 0.4 is routinely used in our institute. This value is comparable with the literature although some literature reports even higher OD values for infiltration (Norkunas et al., 2018; Drapal et al., 2021; Zhang et al., 2020, Davis et al., 2020; Stephenson et al., 2018).

      A standard norm now is to establish the level of colocalization is by quantifying a pearson's or Mander's correlation. Which I believe has been done in the text, I didn't find a plot representing the same? Could the data (which the authors already have) be plotted alongwith "n" as a table or graph? __Our response: __

      *Please check our response to reviewer 1, comment 4. *

      We like to insist that we performed colocalization very carefully and quantified the data in three different manners. We like to state that there is no general standardized procedure that best suits the idea of a colocalization pattern. Results of colocalization are represented in stem diagrams and table format, including statistical analysis. Colocalization was carried out with the ImageJ plugin JACoP for Pearson's and Overlap coefficients and based on the centroid method. The plotted Pearson's and Overlap coefficients are presented in bar diagrams in Supplementary Figure S8A and C, including statistics. The obtained values by the centroid method are represented in table format in Supplementary Figure S8B and D, which *can be considered a standard method (see Ivanov et al., 2014). *

      Colocalization of two different fluorescence signals was performed for the two channels in a specific chosen region of interest (indicating in % the overlapping signal versus the sum of signal for each channel). The differences between the YFP/mRFP and mRFP/YFP ratios indicate that a higher percentage of ARA7-RFP signal is colocalizing with YFP-TTN5Q70L signal than with the TTN5WT or the TTN5T30N mutant form signals, while the YFP signals have a similar overlap with ARA7-positive structures. This is not a contradiction. Presumably this answers well the questions on colocalization.

      Please note that upon acceptance for publication, we will upload all original colocalization data to BioImage Archive. Hence, the high-quality data can be reanalyzed by readers.

      The cartoons for the action of chemicals are useful, but need a bit more clarity. Our response:

      The schematic explanations of pharmacological treatments and expected outcomes are useful to readers. For a better understanding, we added additional explaining sentences to the figure legends (Figure 5E, M; Figure 6A). We also modified Figure 6A and the corresponding legend.

      "(E), Schematic representation of GmMan1 localization at the ER upon brefeldin A (BFA) treatment. BFA blocks ARF-GEF proteins which leads to a loss of Golgi cis-cisternae and the formation of BFA-induced compartments due to an accumulation of Golgi stacks up to a redistribution of the Golgi to the ER by fusion of the Golgi with the ER (Renna and Brandizzi 2020)."

      "(M), Schematic representation of ARA7 localization in swollen MVBs upon wortmannin treatment. Wortmannin inhibits phosphatidylinositol-3-kinase (PI3K) function leading to the fusion of TGN/EE to swollen MVBs (Renna and Brandizzi 2020)."

      "(A), Schematic representation of progressive stages of FM4-64 localization and internalization in a cell. FM4-64 is a lipophilic substance. After infiltration, it first localizes in the plasma membrane, at later stages it localizes to intracellular vesicles and membrane compartments. This localization pattern reflects the endocytosis process (Bolte et al. 2004)."

      • *

      Fig. 5 does the Q70L mutant show reduced endocytosis ?

      __Our response: __

      We have not investigated this question. As detailed in our response to reviewer 1, *we like to emphasize that we agree fully that functional evidences are interesting to assign role for TTN5 in trafficking steps. A phenotype associated with TTN5T30N and TTN5Q70L would be clearly meaningful. *

      Concerning the aspect of colocalization of the mutants with the markers we show in Figure 5C, D and G, H that YFP-TTN5T30N- and YFP-TTN5Q70L-related signals colocalize with the Golgi marker GmMan1-mCherry. Figure 5K, L and O, P show that YFP-TTN5T30N and YFP-TTN5Q70L-related signals can colocalize with the MVB marker, and this may affect relevant vesicle trafficking processes and plasma membrane protein regulation involved in root cell elongation.

      *At present, we have not yet investigated perturbed cargo trafficking. These aspects are certainly interesting but require extensive work and testing of appropriate physiological conditions and appropriate cargo targets. We discuss future perspectives in the Discussion. We agree that such functional information is of great importance, but needs to be clarified in future studies. *

      • *

      The main text needs to be organized in a way that a reader can separate what is the hypothesis/assumption from actual results and conclusions (see lines #143-149).

      Our response:

      *Thank you for this comment. We reformulated text throughout the manuscript. *

      The text is repeated in multiple places, while I understand that this is not plagiarism, the repetitiveness makes it difficult to read and understand the text. I highlight a couple of examples here, but please check the whole text thoroughly and edit/delete as necessary. a. Lines #124-125 with Lines #149-151 Lines #140-143

      __Our response: __

      *We checked the text and removed unnecessary repetitions. *

      • *

      • Could the authors elaborate on whether there are plan homologs of TTN5? Also, have other ARF/ARLs been compared to TTN5 beyond HsARF1? *

      Our response:

      Phylogenetic trees of the ARF family in Arabidopsis in comparison to human ARF family were already published by Vernoud et al. (2003). In this phylogenetic tree ARF, ARL and SAR proteins of Arabidopsis are compared with the members in humans and S. cervisiae. It is difficult to deduce whether the proteins are homologs or orthologs. In this setting, an ortholog of TTN5 may be HsARL2 followed by HsARL3. In Figure 1A we represented some human GTPases as closely related in sequence to TTN5, these are HsARL2, HsARF1 and AtARF1 since they are the best studied ARF GTPases. HRAS is a well-known member of the RAS superfamily which we used for kinetic comparison in Figure 2. We additionally compared published kinetics of RAC1, HsARF3, *CDC42, RHOA, ARF6, RAD, GEM, and RAS GTPases. *

      • *

      On a related note, a major problem I have with these kinetic values is the assumption of significance or not. For eg. Line#180 the values represent and 2 and 6-fold increase, if these numbers do not matter can a significance threshold be applied so as to understand how much fold-change is appreciable?

      Our response:

      The kinetics of TTN5 and its two mutant variants can be compared with those of other studied GTPases. To provide a basis for the statements about differences in GTPase activities, we modified the text and added respective references in the text for comparisons of fold changes.

      The new text is now as follows Line 175-231):

      „ We next measured the dissociation (koff) of mdGDP and mGppNHp from the TTN5 proteins in the presence of excess amounts of GDP and GppNHp, respectively (Figure 2C) and found interesting differences (Figure 2D, E; Supplementary Figures S3G-I, S4F-H). First, TTN5WT showed a koff value (0.012 s-1 for mGDP) (Figure 2D; Supplementary Figure S3G), which was 100-fold faster than those obtained for classical small GTPases, including RAC1 (Haeusler et al. 2006)and HRAS (Gremer et al. 2011), but very similar to the koff value of HsARF3 (Fasano et al. 2022). Second, the koffvalues for mGDP and mGppNHp, respectively, were in a similar range between TTN5WT (0.012 s-1 mGDP and 0.001 s-1mGppNHp) and TTN5Q70L (0.025 s-1 mGDP and 0.006 s-1 mGppNHp), respectively, but the koff values differed 10-fold between the two nucleotides mGDP and mGppNHp in TTN5WT (koff = 0.012 s-1 versus koff = 0.001 s-1; Figure 2D, E; Supplementary Figure S3G, I, S4F, H). Thus, mGDP dissociated from proteins 10-fold faster than mGppNHp. Third, the mGDP dissociation from TTN5T30N (koff = 0.149 s-1) was 12.5-fold faster than that of TTN5WT and 37-fold faster than the mGppNHp dissociation of TTN5T30N (koff = 0.004 s-1) (Figure 2D, E; Supplementary Figure S3H, S4G). Mutants of CDC42, RAC1, RHOA, ARF6, RAD, GEM and RAS GTPases, equivalent to TTN5T30N, display decreased nucleotide binding affinity and therefore tend to remain in a nucleotide-free state in a complex with their cognate GEFs (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). Since TTN5T30N exhibits fast guanine nucleotide dissociation, these results suggest that TTN5T30N may also act in either a dominant-negative or fast-cycling manner as reported for other GTPase mutants (Fiegen et al. 2004, Wang et al. 2005, Fidyk et al. 2006, Klein et al. 2006, Soh and Low 2008, Sugawara et al. 2019, Aspenström 2020).

      The dissociation constant (Kd) is calculated from the ratio koff/kon, which inversely indicates the affinity of the interaction between proteins and nucleotides (the higher Kd, the lower affinity). Interestingly, TTN5WT binds mGppNHp (Kd = 0.029 µM) 10-fold tighter than mGDP (Kd = 0.267 µM), a difference, which was not observed for TTN5Q70L (Kd for mGppNHp = 0.026 µM, Kd for mGDP = 0.061 µM) (Figure 2D, E). The lower affinity of TTN5WT for mdGDP compared to mGppNHp brings us one step closer to the hypothesis that classifies TTN5 as a non-classical GTPase with a tendency to accumulate in the active (GTP-bound) state (Jaiswal et al. 2013). The Kd value for the mGDP interaction with TTN5T30N was 11.5-fold higher (3.091 µM) than for TTN5WT, suggesting that this mutant exhibited faster nucleotide exchange and lower affinity for nucleotides than TTN5WT. Similar as other GTPases with a T30N exchange, TTN5T30Nmay behave in a dominant-negative manner in signal transduction (Vanoni et al. 1999).

      To get hints on the functionalities of TTN5 during the complete GTPase cycle, it was crucial to determine its ability to hydrolyze GTP. Accordingly, the catalytic rate of the intrinsic GTP hydrolysis reaction, defined as kcat, was determined by incubating 100 µM GTP-bound TTN5 proteins at 25{degree sign}C and analyzing the samples at various time points using a reversed-phase HPLC column (Figure 2F; Supplementary Figure S5). The determined kcat values were quite remarkable in two respects (Figure 2G). First, all three TTN5 proteins, TTN5WT, TTN5T30N and TTN5Q70L, showed quite similar kcatvalues (0.0015 s-1, 0.0012 s-1, 0.0007 s-1; Figure 2G; Supplementary Figure S5). The GTP hydrolysis activity of TTN5Q70L was quite high (0.0007 s-1). This was unexpected because, as with most other GTPases, the glutamine mutations at the corresponding position drastic impair hydrolysis, resulting in a constitutively active GTPase in cells (Hodge et al. 2020, Matsumoto et al. 2021). Second, the kcat value of TTN5WT (0.0015 s-1) although quite low as compared to other GTPases (Jian et al. 2012, Esposito et al. 2019), was 8-fold lower than the determined koff value for mGDP dissociation (0.012 s-1) (Figure 2E). This means that a fast intrinsic GDP/GTP exchange versus a slow GTP hydrolysis can have drastic effects on TTN5 activity in resting cells, since TTN5 can accumulate in its GTP-bound form, unlike the classical GTPase (Jaiswal et al. 2013). To investigate this scenario, we pulled down GST-TTN5 protein from bacterial lysates in the presence of an excess amount of GppNHp in the buffer using glutathione beads and measured the nucleotide-bound form of GST-TTN5 using HPLC. As shown in Figure 2H, isolated GST-TTN5 increasingly bonds GppNHp, indicating that the bound nucleotide is rapidly exchanged for free nucleotide (in this case GppNHp). This is not the case for classical GTPases, which remain in their inactive GDP-bound forms under the same experimental conditions (Walsh et al. 2019, Hodge et al. 2020)."

      Another issue with the kinetic measurements is the significance levels. Line #198-201. The three proteins are claimed to have similar values and in the nnext line, the Q70L mutant is claimed to be high.

      Our response:

      Please see our response and changes in the text according in our response to the previous comment 9. We have provided extra explanations and references to clarify why the kinetic behavior of TTN5 is unusual in several respects (Line 215-220).

      „First, all three TTN5 proteins, TTN5WT, TTN5T30N and TTN5Q70L, showed quite similar kcat values (0.0015 s-1, 0.0012 s-1, 0.0007 s-1; Figure 2G; Supplementary Figure S5). The GTP hydrolysis activity of TTN5Q70L was quite high (0.0007 s-1). This was unexpected because, as with most other GTPases, the glutamine mutations at the corresponding position drastic impair hydrolysis, resulting in a constitutively active GTPase in cells (Hodge et al. 2020, Matsumoto et al. 2021)."

      Provide data for conclusion in line#214-215

      Our response:

      We agree that a reference should be added after this sentence to make this sentence clearer (Line 228-231).

      "As shown in Figure 2H, isolated GST-TTN5 increasingly bonds GppNHp, indicating that the bound nucleotide is rapidly exchanged for free nucleotide (in this case GppNHp). This is not the case for classical GTPases, which remain in their inactive GDP-bound forms under the same experimental conditions (Walsh et al. 2019, Hodge et al. 2020)."

      • *

      How were the mutants studied here identified? random mutation or was it directed based on qualified assumptions?

      __Our response: __

      We used the T30N and the Q70L point mutations as such types of mutants had been reported to confer specific phenotypes in these well-conserved amino acid positions in multiple other small GTPases (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). In particular, these positions affect the interaction between small GTPases and their respective guanine nucleotide exchange factor (GEF; T30N) or on GTP hydrolysis (Q70L). We introduced the mutants and described their potential effect on the GTPase cycle in the introduction and cited exemplary literature. Please see also our response to comment 6 and the proposed text changes (Line 142-151).

      Could more simplification be provided for deifitinition of Kon/Koff values. And can these values be compared between mutants directly?

      __Our response: __

      *We introduce kon and koff in the modified Figure 2D, E, and they are described in the figure legends. Moreover, we present the data for calculations in Supplementary Figures S3, 4, where again we define the values in the respective figure legends. *

      • *

      Data provided are not convincing to claim that both the mutant forms have lower association with the Golgi.

      __Our response: __

      *Our conclusion is that both YFP-TTN5 and YFP-TTN5Q70L fluorescence signals tend to colocalize more with the Golgi-marker signals compared to YFP-TTN5T30N signals as deduced from the centroid-based colocalization method (Line 404-405). *

      "Hence, the GTPase-active TTN5 forms are likely more present at cis-Golgi stacks compared to TTN5T30N."

      The Pearson coefficients of all three YFP-TTN5 constructs were nearly identical, but we could identify differences in overlapping centers between the YFP and mCherry channel. 48 % of the GmMan1-mCherry fluorescent cis-Golgi stacks were overlapping with signal of YFP-TTN5Q70L, while for YFP-TTN5T30N an overlap of only 31 % was detected. This means that less cis*-Golgi stacks colocalized with signals in the YFP-TTN5T30N mutant than in YFP-TTN5Q70L, which is the statement in our manuscript. *

      • *

      IN general the Authors should strongly consider the claims made in the manuscript. For eg. "This study lays the foundation for studying the functional relationships of this small GTPase" (line 125) is unqualified as this is true for every protein ever studied and published. Considering that TTN was not isolated/identified in this study for the first time this claim doesn't stand.

      __Our response: __

      *We reformulated the sentence (Line 123-124). *

      "This study paves the way towards future investigation of the cellular and physiological contexts in which this small GTPase is functional."

      • *

      Line #185 - "characterestics of a dominant-negative...." What is this based on? From the text it is not clear what are the paremeters. Considering that no complementation phenotypes have been presented, this is a far-fetched claim Our response:

      Small GTPases in general are a well studied protein family and the here used mutations T30N and Q70L are conserved amino acids and commonly used for the characterization of the Ras superfamily members. We added explaining sentences with references to the text. The characteristics referred to in the above paragraph is based on the kinetic study.

      We modified the text as follows (Line 186-197 ):

      „Third, the mGDP dissociation from TTN5T30N (koff = 0.149 s-1) was 12.5-fold faster than that of TTN5WT and 37-fold faster than the mGppNHp dissociation of TTN5T30N (koff = 0.004 s-1) (Figure 2D, E; Supplementary Figure S3H, S4G). Mutants of CDC42, RAC1, RHOA, ARF6, RAD, GEM and RAS GTPases, equivalent to TTN5T30N, display decreased nucleotide binding affinity and therefore tend to remain in a nucleotide-free state in a complex with their cognate GEFs (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). Since TTN5T30N exhibits fast guanine nucleotide dissociation, these results suggest that TTN5T30N may also act in either a dominant-negative or fast-cycling manner as reported for other GTPase mutants (Fiegen et al. 2004, Wang et al. 2005, Fidyk et al. 2006, Klein et al. 2006, Soh and Low 2008, Sugawara et al. 2019, Aspenström 2020)."

      The claims in Line #224-227 are exaggerated. Please tone down or delete __Our response: __

      *We rephrased the sentence (Line 240-243). *

      "Therefore, we propose that TTN5 exhibits the typical functions of a small GTPase based on in vitro biochemical activity studies, including guanine nucleotide association and dissociation, but emphasizes its divergence among the ARF GTPases by its kinetics."

      Line#488-489 - This conclusion is not really supported. At best Authors can claim that TTN5 is associated with trafficking components, but the functional relevance of this association is not determined. Our response:

      *We toned down our statement (Line 604-608). *

      „The colocalization of FM4-64-labeled endocytosed vesicles with fluorescence in YFP-TTN5-expressing cells may indicate that TTN5 is involved in endocytosis and the possible degradation pathway into the vacuole. Our data on colocalization with the different markers support the hypothesis that TTN5 may have functions in vesicle trafficking."

      __Minor comments: __

      Line #95 - " This rolein vesicle....." - please clarify which role? Our response:

      We rephrased the sentence (Line 96-99).

      „These roles of ARF1 and SAR1 in COPI and II vesicle formation within the endomembrane system are well conserved in eukaryotes which raises the question of whether other plant ARF members are also involved in functioning of the endomembrane system."

      Line #168 - "we did not observed" please change to "not able to measure/quantify" __Our response: __

      *We changed the text accordingly (Line 169-171). *

      „A remarkable observation was that we were not able to monitor the kinetics of mGppNHp association with TTN5T30N but observed its dissociation (koff = 0.026 s-1; Figure 2E)."

      Line#179 - ARF# is human for Arabidopsis?

      Our response:

      *The study of Fasano et al., 2022 is based on human ARF3 and we added the information to the text (Line 180-181) *

      "(...) very similar to the koff value of HsARF3 (Fasano et al. 2022)."

      • *

      Line #181 - compared to what is the 10-fold difference?

      __Our response: __

      The 10-fold difference is between the nucleotides mGDP and mGppNHp, for both TTN5WT and TTN5Q70L. We added the information on specific nucleotides to this sentence for a better understanding (Line 181-185).

      „Second, the koff values for mGDP and mGppNHp, respectively, were in a similar range between TTN5WT (0.012 s-1mGDP and 0.001 s-1 mGppNHp) and TTN5Q70L (0.025 s-1 mGDP and 0.006 s-1 mGppNHp), respectively, but the koffvalues differed 10-fold between the two nucleotides mGDP and mGppNHp in TTN5WT (koff = 0.012 s-1 versus koff = 0.001 s-1; Figure 2D, E; Supplementary Figure S3G, I, S4F, H)."

      Lines #314-323 - are diffciult to understand, consider reframing. Same goes for the conclusion following these lines.

      __Our response: __

      We added an explanation to these sentences for a better understanding (Line 392-405).

      „We performed an additional object-based analysis to compare overlapping YFP fluorescence signals in YFP-TTN5-expressing leaves with GmMan1-mCherry signals (YFP/mCherry ratio) and vice versa (mCherry/YFP ratio). We detected 24 % overlapping YFP- fluorescence signals for TTN5 with Golgi stacks, while in YFP-TTN5T30N and YFP-TTN5Q70L-expressing leaves, signals only shared 16 and 15 % overlap with GmMan1-mCherry-positive Golgi stacks (Supplementary Figure S8B). Some YFP-signals did not colocalize with the GmMan1 marker. This effect appeared more prominent in leaves expressing YFP-TTN5T30N and less for YFP-TTN5Q70L, compared to YFP-TTN5 (Figure 5B-D). Indeed, we identified 48 % GmMan1-mCherry signal overlapping with YFP-positive structures in YFP-TTN5Q70L leaves, whereas 43 and only 31 % were present with YFP fluorescence signals in YFP-TTN5 and YFP-TTN5T30N-expressing leaves, respectively (Supplementary Figure S8B), indicating a smaller amount of GmMan1-positive Golgi stacks colocalizing with YFP signals for YFP-TTN5T30N. Hence, the GTPase-active TTN5 forms are likely more present at cis-Golgi stacks compared to TTN5T30N."

      Authors might consider a longer BFA treatment (3-4h) to see more clearer ER-Golgi fusion (BFA bodies)

      __Our response: __

      We perforned addtional BFA treatments for HA3-TTN5-expressing Arabidopsis seedlings followed by whole-mount immunostaining and for YFP-TTN5-expressing Arabidopsis lines. In both experiments we could obtain the typical BFA bodies. We included the NEW data in NEW Figure 4B, C

      **Referees cross-commenting**

      I agree with both my co-reviewers that the manuscript needs substantial improvement in its cell biology based experiments and conclusions thereof. I think the concensus of all reviewers points to weakness in the in-planta experiments which needs to be addressed to understand and characterize TTN5, which is the main goal of the manuscript.

      Reviewer #3 (Significance (Required)):

      Significance: The manuscript has general significance in understanding the role of small GTPases which are understudied. Although the manuscript does not advance the field of either intracellular trafficking or organization it holds significance in attempting to characterize proteins involved, which is a prerequisite for further functional studies.

      __Our response: __

      Thank you for your detailed analysis of our manuscript and positive assessment. Our study is an advance in the plant vesicle trafficking field.

    1. Figure 2: Comparing Snap! or Scratch Repeat Until Loop to Java while loop

      Difference between a Repeat Until loop and a While Loop:

      Repeat Until Loop: Executes the code as long as the given condition is False, once the condition turns to True, it stops.

      While Loop: Executes the code as long as the given condition is True, once the condition turns to False, it stops.

    1. If statements can be nested inside other if statements. Sometimes with nested ifs we find a dangling else that could potentially belong to either if statement. The rule is that the else clause will always be a part of the closest unmatched if statement in the same block of code, regardless of indentation.

      Good to know. No. Really important to know.

      Better to always use curly braces. As shown in the next highlight.

  2. inst-fs-iad-prod.inscloudgate.net inst-fs-iad-prod.inscloudgate.net
    1. Students’ testimonials reveal how exclusionary beliefs interact with school practices such as dress codes, curriculum tracking, and narrow course cur-riculum to maintain raced-gendered inequality and sexualized policing that typecasts, limits, and recreates hierarchies.

      One experience that dissimilar to the sexualize policing girls in high school both Latinas and Black girls were instantly impacted by this in school. During the hottest days of the year, where our school was located would be in 90s to 110s, and many girls would wear tank tops, shorts, skirts, and other pieces. But many of us would be dress coded because it was "showing too much skin". Our school had bad air conditioning and old classrooms, and with little ventilation being in class would be uncomfortable. However the same was not said to our male counterparts who had shorts. This demonstrated how the dress coding was because we were being sexualized and therefore targeted. The only time were we supported was when a few teachers posted on their doors they would not be taking part in dress code because it was targeting and sexualizing girls.

    1. backslash escape sequence

      Overriding the compiler's default reaction to special characters such as quotation marks and backslashes, that are used in the code with programming language specific meaning, to allow the programmer to display these special characters included with the string literals as a part of it.

    1. The code Turtle t1 = null; creates a variable t1 that refers to a Turtle object, but the null means that it doesn’t refer to an object yet. You could later create the object and set the object variable to refer to that new object (t1 = new Turtle(world1)). Or more commonly, you can declare an object variable and initialize it in the same line of code (Turtle t2 = new Turtle(world1);). World world1 = new World(); Turtle t1 = null; t1 = new Turtle(world1); // declare and initialize t2 Turtle t2 = new Turtle(world1);

      Summary: - You can declare object variables without assigning to it a new object. The assignment can be done at a later stage in code. - Null here is just Null, no special contextual meaning here. It literally just means nothing's here.

    1. à partir du milieu des 00:45:24 années 1990 la tendance inverse avec un durcissement de la législation chaque fois qu'une majorité de droite revient au pouvoir et une correction seulement partielle lorsque c'est la gauche qui 00:45:35 gouverne ainsi en 1994 on institue la rétention judiciaire autrement dit la garde à vue pour les moins de 13 ans en 1996 on permet la comparution immédiate et la comparution devant le juge des 00:45:49 enfants sans instruction préalable en 2002 on crée les centres éducatifs fermés ainsi que les établissements pénitentiaires pour mineurs et on abaisse l'âge de la responsabilité pénale de 13 à 10 ans 00:46:01 autorisant des sanctions beaucoup plus tôt dans la vie le code de la justice pénale des mineurs rétablira en fait en 2021 la limite de 13 ans en 2007 les exception 00:46:13 permettant de ne pas appliquer l'excuse de minorité pour les les mineurs de plus de 16 ans sont élargies ces dispositions seront toutefois abreugé en 2014 la pleine excuse de minorité se trouvant 00:46:25 alors rétablie en 2007 encore on supprime l'atténuation de la peine pour les mineurs de 16 ans en cas deuxèe récidif s'il commett un délit avec violence ou agression sexuelle en 00:46:38 2011 les tribunaux correctionnels pour mineurs sont créés pour juger les délits punis de plus de 3 ans d'emprisonnement en récidive par des adolescents de plus de 16 ans ils seront 00:46:50 cependant supprimé en 2016 en 2019 on permet d'appliquer au mineurs de plus de 13 la détention à domicile sous surveillance électronique progressivement ainsi avec 00:47:02 ces balancements que je vous ai indiqué le législateur érode le principe de protection de l'ordonnance de 1945 restreint les effets de la 00:47:14 présomption de non discernement et de l'excuse de minorité multiplie les lieux d'enfermement et les possibilités de peine correspondantes et rapproche la justice pénale des mineurs de la justice 00:47:27 pénale des adultes et vous aurez certainement remarqué que c'est un débat qui aujourd'hui est à nouveau sur la table
    2. les écoles n'échappent donc pas totalement au moment punitif en réalité plutôt que de se demander si la discipline y est plus sévère ou moins sévère que par le passé il faudrait s'interroger sur la manière dont la 00:35:28 discipline s'y reconfigure en permanence l'interdiction des châtiments corporels autrefois prévalent peut-être ainsi concomitante de l'apparition de nouveaux motifs de sanction au titre notamment du principe de laïcité tel que défini dans 00:35:41 la loi du 15 mars 2004 ainsi pour l'année scolaire 2022-2023 ce sont 3881 signalements qui ont été transmis au ministère de l'Éducation nationale dont environ la moitié concerne je cite des tenues qui 00:35:54 ne manifestent pas par nature une appartenance religieuse comme des jupes ou des robes longues selon les termes des bilans qui sont effectués par les dites équipe académique valeur de la 00:36:05 République ou eavr et leurs 1200 formateurs on ignore le nombre de sanctions correspondantes qui peuvent être disciplinaire au sein de l'école et même pénal dans le cadre du code de l'éducation qui prévoit une amende de 00:36:19 150 € portée à 200 en cas de récidive
    1. Likewise, the telegraph was invented in 1830 and used initially to warn train stations when multiple trains were on the track. Telegraphs allowed almost instant communication over huge distances - they sent a series of electrical impulses over a wire as "long" and "short" signals. The inventor of the telegraph, Samuel Morse, invented a code based off of those signals that could be translated into letters and, as a result, be used to sent messages. Morse Code thus enabled the first modern mass communications device. This was the first time when a message could travel faster than could a messenger on horseback, vastly increasing the speed by which information could be shared and disseminated. Simultaneously, steamships were transforming long-distance commerce. The first sailed in 1816, going about twice as fast as the fastest sailing ship could. This had obvious repercussions for trade, because it became cheaper to transport basic goods via steamship than it was to use locally-produced ones; this had huge impacts on agriculture and forestry, among other industries. Soon, it became economically viable to ship grain from the United States or Russia across oceans to reach European markets. The first transatlantic crossing was a race between two steamships going from England to New York in 1838; soon, sailing vessels became what they are today: archaic novelties.

      Morse code allowed for a quick and easy way of communicating and steamships were cheaper and faster which allowed imported goods to become a viable source of goods

    1. Author response:

      The following is the authors’ response to the previous reviews

      Reviewer #1 (Recommendations For The Authors):

      In this revision the authors address some of the key concerns, including clarification of the balanced nature of the RL driven pitch changes and conducting analyses to control for the possible effects of singing quantity on their results. The paper is much improved but still has some sources of confusion, especially around Fig. 4, that should be fixed. The authors also start the paper with a statistically underpowered minor claim that seems unnecessary in the context of the major finding. I recommend the authors may want to restructure their results section to focus on the major points backed by sufficient n and stats.

      Major issues.

      (1) The results section begins very weak - a negative result based on n=2 birds and then a technical mistake of tube clogging re-spun as an opportunity to peak at intermittent song in the otherwise muted birds. The logic may be sound but these issues detract from the main experiment, result, analysis, and interpretation. I recommend re-writing this section to home in on, from the outset, the well-powered results. How much is really gained from the n=2 birds that were muted before ANY experience? These negative results may not provide enough data to make a claim. Nor is this claim necessary to motivate what was done in the next 6 birds. I recommend dropping the claim?

      We thank the reviewer for the recommendation. We moved the information to the Methods.

      (2) Fig. 4 is very important yet remains very confusing, as detailed below.

      Fig. 4a. Can the authors clarify if the cohort of WNd birds that give rise to the positive result in Fig 4 ever experienced the mismatch in the absence of ongoing DAF reinforcement pre-deafening? Fig4a does nor the next clearly specifies this. This is important because we know that there are day timescale delays in LMAN-dependent bias away from DAF and consolidation into the HVC-RA pathway (Andalman and Fee, 2009). Thus, if birds experienced mismatch pre-deafening in the absence of DAF, then an earnly learning phase in Area X could be set in place. Then deafening occurs, but these weight changes in X could result in LMAN bias that expresses only days later -independent of auditory feedback. Such a process would not require an internal model as the authors are arguing for here. It would simply arise from delays in implementing reinforcement-driven feedback. If the birds in Fig 4 always had DAF on before deafening, then this is not an issue. But if the birds had hours of singing with DAF off before deafening, and therefore had the opportunity to associate DA error signals with the targeted time in the song (e.g. pauses on the far-from-target renditions (Duffy et al, 2022), then the return-to-baseline would be expected to be set in place independent of auditory feedback. Please clarify exactly if the pitch-contingent DAF was on or off in the WNd cohort in the hours before deafening. In Fig. 3b it looks like the answer is yes but I cannot find this clearly stated in the text.

      We did not provide DAF-free singing experience to the birds in Fig. 4 before deafening. Thus, according to the reviewer, the concern does not apply.

      Note that we disagree with the reviewer’s premise that there is ‘day timescale delay in LMAN-dependent bias away from DAF and consolidation into the HVC-RA pathway’. More recent data reveals immediate consolidation of the anterior forebrain bias without a night-time effect (Kollmorgen, Hahnloser, Mante 2020; Tachibana, Lee, Kai, Kojima 2022). Thus, the single bird in (Andalman and Fee 2009) seems to be somewhat of an outlier.

      Hearing birds can experience the mismatch regardless of whether they experience DAF-free singing (provided their song was sufficiently shifted): even the renditions followed by white noise can be assessed with regards to their pitch mismatch, so that DAF imposes no limitation on mismatch assessment.

      We disagree with their claim that no internal model would be needed in case consolidation was delayed in Area X. If indeed, Area X stores the needed change and it takes time to implement this change in LMAN, then we would interpret the change in Area X as the plan that birds would be able to implement without auditory feedback. Because pitch can either revert (after DAF stops) or shift further away (when DAF is still present), there is no rigid delay that is involved in recovering the target, but a flexible decision making of implementing the plan, which in our view amounts to using a model.

      Fig 4b. Early and Late colored dots in legend are both red; late should be yellow? Perhaps use colors that are more distinct - this may be an issue of my screen but the two colors are difficult to discern.

      We used colors yellow to red to distinguish different birds and not early and late. We modified the markers to improve visual clarity: Early is indicated with round markers and late with crosses.

      Fig 4b. R, E, and L phases are only plotted for 4c; not in 4b. But the figure legend says that R, E and L are on both panels.

      In Fig. 4b E and L are marked with markers because they are different for different birds. In Fig. 4c the phases are the same for all birds and thus we labeled them on top. We additionally marked R in Fig. 4b as in Fig. 4c.

      Fig 4e. Did the color code switch? In the rest of Fig 4, DLO is red and WND is blue. Then in 4e it swaps. Is this a typo in the caption? Or are the colors switch? Please fix this it's very confusing.

      Thank you for pointing out the typo in the caption. We corrected it.

      The y axes in Fig 4d-e are both in std of pitch change - yet they have different ylim which make it visually difficult to compare by eye. Is there a reason for this? Can the authors make the ylim the same for fig 4d-e?.

      We added dashed lines to clarify the difference in ylim.

      Fig 4d-3 is really the main positive finding of the paper. Can the others show an example bird that showcases this positive result, plotted as in Fig 3b? This will help the audience clearly visualize the raw data that go into the d' analyses and get a more intuitive sense of the magnitude of the positive result.

      We added example birds to figure 4, one for WNd and one for dLO.

      Please define 'late' in Fig.4 legend.

      Done

      Minor

      Define NRP In the text with an example. Is an NRP of 100 where the birds was before the withdrawal of reinforcement?

      We added the sentence to the results:

      "We quantified recovery in terms of 𝑵𝑹𝑷 to discount for differences in the amount of initial pitch shift where 𝑵𝑹𝑷 = 𝟎% corresponds to complete recovery and 𝑵𝑹𝑷 = 𝟏𝟎𝟎% corresponds pitch values before withdrawal of reinforcement (R) and thus no recovery."

      Reviewer #3 (Recommendations For The Authors):

      The use of "hierarchically lower" to refer to the flexible process is confusing to me, and possibly to many readers. Some people think of flexible, top-down processes as being _higher_ in a hierarchy. Regardless, it doesn't seem important, in this paper, to label the processes in a hierarchy, so perhaps avoid using that terminology.

      We reformulated the paragraph using ‘nested processes’ instead of hierarchical processes.

      In the statement "a seeming analogous task to re-pitching of zebra finch song, in humans, is to modify developmentally learned speech patterns", a few suggestions: it is not clear whether "re-pitching" refers to planning or feedback-dependent learning (I didn't see it introduced anywhere else). And if this means planning, then it is not clear why this would be analogous to "humans modifying developmentally learned speech patterns". As you mentioned, humans are more flexible at planning, so it seems re-pitching would _not_ be analogous (or is this referring to the less flexible modification of accents?).

      We changed the sentence to:

      "Thus, a seeming analogous task to feedback-dependent learning of zebra finch song, in humans, is to modify developmentally learned speech patterns."

    1. Résumé de la vidéo [00:00:20][^1^][1] - [00:22:58][^2^][2]:

      Cette vidéo présente une conférence de Luc PELLISSIER sur la complexité des textes juridiques et leur traitement calculatoire. Il explore les notions de complexité en informatique théorique, la simplification et la codification du droit, et comment ces processus affectent l'accessibilité et l'intelligibilité de la loi. Il discute également des différentes époques de la codification en France et de l'impact de l'informatisation sur la législation.

      Points forts: + [00:00:20][^3^][3] Introduction et contexte * Présentation du sujet et de l'importance de la complexité en informatique * Lien entre l'enseignement du droit et la complexité + [00:01:15][^4^][4] Complexité et droit * Exploration de la complexité en informatique théorique * Absence de la notion de complexité dans la littérature juridique + [00:04:27][^5^][5] Simplification et codification * Discussion sur la simplification du droit comme objectif constitutionnel * Relation entre simplification et codification dans l'histoire juridique française + [00:07:04][^6^][6] Les trois âges de la codification en France * Analyse des différentes méthodes de codification depuis le Consulat jusqu'à aujourd'hui * Impact de l'informatisation sur la codification et la législation + [00:17:19][^7^][7] Le droit comme système calculatoire * Proposition d'une nouvelle perspective sur le droit comme objet calculatoire * Exemple de la rémunération des heures complémentaires dans les universités françaises Résumé de la vidéo [00:23:00][^1^][1] - [00:44:29][^2^][2] : La vidéo présente une analyse détaillée des textes juridiques en tant qu'objets calculatoires, en explorant la complexité des modifications législatives et réglementaires, ainsi que leur impact sur la consolidation des textes de loi.

      Points saillants : + [00:23:00][^3^][3] Classification des dispositions législatives * Différenciation entre les dispositions substantielles et celles qui appellent à l'action d'autres autorités. * Exemples concrets de modifications législatives et leur effet direct ou indirect sur le monde réel. * Discussion sur la complexité des textes qui modifient d'autres textes. + [00:25:02][^4^][4] Modifications précises vs. générales * Comparaison entre les modifications qui indiquent exactement quel texte changer et celles qui sont plus larges et moins spécifiques. * Impact des modifications générales sur la clarté et l'interprétation des textes. * Exemple de la réforme du Conseil national des universités et ses implications. + [00:31:02][^5^][5] Citations et références dans les textes législatifs * Utilisation de citations textuelles pour lier différents codes, comme le Code de l'éducation et le Code de la santé publique. * Problèmes posés par les modifications qui ne sont pas consolidées et laissent l'utilisateur final interpréter le texte. + [00:37:00][^6^][6] Conséquences des modifications non consolidées * Difficultés rencontrées par les utilisateurs du droit en raison de modifications automatiques non reflétées dans les textes consolidés. * Questions soulevées sur la simplification du droit et l'accessibilité des informations légales actuelles. Résumé de la vidéo [00:44:31][^1^][1] - [01:03:14][^2^][2]:

      La partie 3 de la vidéo aborde la complexité du texte juridique en tant qu'objet calculatoire, en se concentrant sur les processus d'amendement, de consolidation et de codification. Luc Pellissier explore les défis théoriques et pratiques liés à la gestion des versions d'un texte de loi et la nécessité d'une approche formelle pour comprendre les modifications et leur impact sur la structure du texte.

      Points forts: + [00:44:31][^3^][3] Théorie du versionnement * Discussion sur la gestion des versions d'un fichier ou d'une loi * Importance des modifications explicites pour une théorie correcte + [00:46:11][^4^][4] Analogie avec le logiciel libre * Comparaison entre le texte juridique et le code source d'un logiciel * Le rôle de la compilation dans la compréhension du logiciel + [00:49:00][^5^][5] Questions épistémologiques * Débat sur la neutralité du droit et l'impact des hypothèses de recherche * Lien entre la simplification du droit et la qualité démocratique + [00:55:01][^6^][6] Développement d'un logiciel de versionnage * Spécification du logiciel pour la gestion des versions du droit * Défis liés à la création d'une théorie propre pour un "code spaghetti" juridique + [01:01:03][^7^][7] Structure formelle du texte juridique * Visualisation du texte de loi comme un arbre avec des branches et des modifications * Impact des outils informatiques sur la précision des modifications législatives

    2. ça 00:46:13 conclura une analogie avant de finir qui est celle du début du mouvement du logiciel libre parce que là je vous ai dit un petit peu comme s'il y avait un hiatus absolument incroyable dans le cas du droit qui est que le texte qu'on écrit c'est pas le 00:46:27 texte qu'on applique mais en fait c'est le cas de tout le logiciel fondamentalement le logiciel il est écrit sous une certaine forme qu'on appelle le code source par des expériences humains des experts humaines 00:46:40 et ensuite celui que j'exécute sur ma machine c'est pas ça c'est une autre version c'est le binaire et il y a un processus de transformation entre les deux qu'on appelle en général compilation
    1. Reviewer #2 (Public Review):

      Summary

      Recent evidence indicates that cells of the navigation system representing different directions and whole spatial routes fire in a rhythmic alternation during 5-10 Hz (theta) network oscillation (Brandon et al., 2013, Kay et al., 2020). This phenomenon of theta cycle skipping was also reported in broader circuitry connecting the navigation system with the cognitive control regions (Jankowski et al., 2014, Tang et al., 2021). Yet nothing was known about the translation of these temporally separate representations to midbrain regions involved in reward processing as well as the hypothalamic regions, which integrate metabolic, visceral, and sensory signals with the descending signals from the forebrain to ensure adaptive control of innate behaviors (Carus-Cadavieco et al., 2017). The present work aimed to investigate theta cycle skipping and alternating representations of trajectories in the lateral septum, neurons of which receive inputs from large number of CA1 and nearly all CA3 pyramidal cells (Risold and Swanson, 1995). While spatial firing has been reported in the lateral septum before (Leutgeb and Mizumori, 2002, Wirtshafter and Wilson, 2019), its dynamic aspects have remained elusive. The present study replicates the previous findings of theta-rhythmic neuronal activity in the lateral septum and reports a temporal alternation of spatial representations in this region, thus filling an important knowledge gap and significantly extending the understanding of the processing of spatial information in the brain. The lateral septum thus propagates the representations of alternative spatial behaviors to its efferent regions. The results can instruct further research of neural mechanisms supporting learning during goal-oriented navigation and decision-making in the behaviourally crucial circuits entailing the lateral septum.

      Strengths

      To this end, cutting-edge approaches for high-density monitoring of neuronal activity in freely behaving rodents and neural decoding were applied. Strengths of this work include comparisons of different anatomically and probably functionally distinct compartments of the lateral septum, innervated by different hippocampal domains and projecting to different parts of the hypothalamus; large neuronal datasets including many sessions with simultaneously recorded neurons; consequently, the rhythmic aspects of the spatial code could be directly revealed from the analysis of multiple spike trains, which were also used for decoding of spatial trajectories; and comparisons of the spatial coding between the two differently reinforced tasks.

      Weaknesses

      Without using perturbation techniques, the present approach could not identify the aspects of the spatial code actually influencing the generation of behaviors by downstream regions.

    1. Transformers give Clojurists some of the benefits of "Object Orientation" without many of the downsides Clojurists dislike about objects.

      1. Objects couple behaviors required from multiple callers into a single class, while transformers do not change existing behaviors for existing callers by default
      2. Objects push inheritance first design, whereas transformer inheritance is a function of shared structure between Clojure data structures derived from one another and design is driven by concrete implementation needs, like regular Clojure
      3. Objects couple state and methods in spaghetti ways and transformers are just immutable maps. And just like how Clojure lets you stash stateful things like atoms in functions, transformers allow you to build stateful transformers, but like Clojure the default convention is to do everything immutably
      4. Objects try to provide data hiding as a function of encapsulation whereas transformers are doing the opposite, exposing data otherwise hidden by a closure

      There are many strategies for reusing code in the software industry. In Clojure, we use what some call a "lego" method of building small, single purpose functions that just can be used in a million different contexts, because of a tasteful use of simplicity in the right places. This works tremendously well for 95% of use cases. In certain use-cases, like for building hierarchies of functions that are highly self-similar, like with UI toolkits, transformers provide a better alternative.Transformers allow you to build a UI toolkit with 25% the code of normal function composition and 25% of the code required for evolution over time for the widgets in that hierarchy. The lego method is great for vertically composing things together, but when you want to make lateral changes for only certain callers in the tree, you have to defensively copy code between duplicative implementation trees and just call them "grandpa-function-1" and "grandpa-function-2" and then make versions 1 and 2 for all functions that wrapped the grandpa-functions afterwards. Transformers provide a solution for that situation, in the rare cases we end up in them in Clojure, without the downsides of a traditional object system.

  3. Apr 2024
    1. ur la branche P3C5-solution.

      Je ne comprends pas bien dans la solution ce bout de code : .lien-conteneur-photo:hover.photo-hover { display: flex; } Pourquoi la class .photo-hover se trouve après la pseudo classe hover ?

    1. Reviewer #2 (Public Review):

      In the presented manuscript, the authors first use structured microfluidic devices with gliding filamentous cyanobacteria inside in combination with micropipette force measurements to measure the bending rigidity of the filaments. The distribution of bending rigidities is very broad.

      Next, they use triangular structures to trap the bacteria with the front against an obstacle. Depending on the length and rigidity, the filaments buckle under the propulsive force of the cells. The authors use theoretical expressions for the buckling threshold to infer propulsive force, given the measured length and (mean-) stiffnesses. They find nearly identical values for both species, 𝑓 ∼ (1.0 {plus minus} 0.6) nN∕µm, nearly independent of the velocity. These measurements have to be taken with additional care, as then inferred forces depend strongly on the bending rigidity, which already shows a broad distribution.

      Finally, they measure the shape of the filament dynamically to infer friction coefficients via Kirchhoff theory. In this section they report a strong correlation with velocity and report propulsive forces that vary over two orders of magnitude.

      From a theoretical perspective, not many new results are presented. The authors repeat the the well-known calculation for filaments buckling under propulsive load and arrive at the literature result of buckling when the dimensionless number (f L^3/B) is larger than 30.6 as previously derived by Sekimoto et al in 1995. In my humble opinion, the "buckling theory" section belongs to methods.<br /> Finally, the Authors use molecular dynamics type simulations similar to other models to reproduce the buckling dynamics from the experiments.

      Data and source code are available via trusted institutional or third-party repositories that adhere to policies that make data discoverable, accessible and usable.

    2. Author response:

      Reviewer 1:

      The paper “Quantifying gliding forces of filamentous cyanobacteria by self-buckling” combines experiments on freely gliding cyanobacteria, buckling experiments using two-dimensional V-shaped corners, and micropipette force measurements with theoretical models to study gliding forces in these organisms. The aim is to quantify these forces and use the results to perhaps discriminate between competing mechanisms by which these cells move. A large data set of possible collision events are analyzed, bucking events evaluated, and critical buckling lengths estimated. A line elasticity model is used to analyze the onset of buckling and estimate the effective (viscous type) friction/drag that controls the dynamics of the rotation that ensues post-buckling. This value of the friction/drag is compared to a second estimate obtained by consideration of the active forces and speeds in freely gliding filaments. The authors find that these two independent estimates of friction/drag correlate with each other and are comparable in magnitude. The experiments are conducted carefully, the device fabrication is novel, the data set is interesting, and the analysis is solid. The authors conclude that the experiments are consistent with the propulsion being generated by adhesion forces rather than slime extrusion. While consistent with the data, this conclusion is inferred.

      We thank the reviewer for the positive evaluation of our work.

      Summary:

      The paper addresses important questions on the mechanisms driving the gliding motility of filamentous cyanobacteria. The authors aim to understand these by estimating the elastic properties of the filaments, and by comparing the resistance to gliding under a) freely gliding conditions, and b) in post-buckled rotational states. Experiments are used to estimate the propulsion force density on freely gliding filaments (assuming over-damped conditions). Experiments are combined with a theoretical model based on Euler beam theory to extract friction (viscous) coefficients for filaments that buckle and begin to rotate about the pinned end. The main results are estimates for the bending stiffness of the bacteria, the propulsive tangential force density, the buckling threshold in terms of the length, and estimates of the resistive friction (viscous drag) providing the dissipation in the system and balancing the active force. It is found that experiments on the two bacterial species yield nearly identical values of f (albeit with rather large variations). The authors conclude that the experiments are consistent with the propulsion being generated by adhesion forces rather than slime extrusion.

      We appreciate this comprehensive summary of our work.

      Strengths of the paper:

      The strengths of the paper lie in the novel experimental setup and measurements that allow for the estimation of the propulsive force density, critical buckling length, and effective viscous drag forces for movement of the filament along its contour – the axial (parallel) drag coefficient, and the normal (perpendicular) drag coefficient (I assume this is the case, since the post-buckling analysis assumes the bent filament rotates at a constant frequency). These direct measurements are important for serious analysis and discrimination between motility mechanisms.

      We thank the reviewer for this positive assessment of our work.

      Weaknesses:

      There are aspects of the analysis and discussion that may be improved. I suggest that the authors take the following comments into consideration while revising their manuscript.

      The conclusion that adhesion via focal adhesions is the cause for propulsion rather than slime protrusion is consistent with the experimental results that the frictional drag correlates with propulsion force. At the same time, it is hard to rule out other factors that may result in this (friction) viscous drag - (active) force relationship while still being consistent with slime production. More detailed analysis aiming to discriminate between adhesion vs slime protrusion may be outside the scope of the study, but the authors may still want to elaborate on their inference. It would help if there was a detailed discussion on the differences in terms of the active force term for the focal adhesion-based motility vs the slime motility.

      We appreciate this critical assessment of our conclusions. Of course we are aware that many different mechanisms may lead to similar force/friction characteristics, and that a definitive conclusion on the mechanism would require the combination of various techniques, which is beyond the scope of this work. Therefore, we were very careful in formulating the discussion of our findings, refraining, in particular, from a singular conclusion on the mechanism but instead indicating “support” for one hypothesis over another, and emphasizing “that many other possibilities exist”.

      The most common concurrent hypotheses for bacterial gliding suggest that either slime extrusion at the junctional pore complex [A1], rhythmic contraction of fibrillar arrays at the cell wall [A2], focal adhesion sites connected to intracellular motor-microtubule complexes [A3], or modified type-IV pilus apparati [A4] provide the propulsion forces. For the slime extrusion hypothesis, which is still abundant today, one would rather expect an anticorrelation of force and friction: more slime extrusion would generate more force, but also enhance lubrication. The other hypotheses are more conformal to the trend we observed in our experiments, because both pili and focal adhesion require direct contact with a substrate. How contraction of fibrilar arrays would micromechanically couple to the environment is not clear to us, but direct contact might still facilitate force transduction. Please note that these hypotheses were all postulated without any mechanical measurements, solely based on ultra-structural electron microscopy and/or genetic or proteomic experiments. We see our work as complementary to that, providing a mechanical basis for evaluating these hypotheses.

      We agree with the referee that narrowing down this discussion to focal adhesion should have been avoided. We rewrote the concluding paragraph (page 8):

      “…it indicates that friction and propulsion forces, despite being quite vari able, correlate strongly. Thus, generating more force comes, inevitably, at the expense of added friction. For lubricated contacts, the friction coefficient is proportional to the thickness of the lubricating layer (Snoeijer et al., 2013 ), and we conjecture active force and drag both increase due to a more intimate contact with the substrate. This supports mechanisms like focal adhesion (Mignot et al., 2007 ) or a modified type-IV pilus (Khayatan et al., 2015 ), which generate forces through contact with extracellular surfaces, as the underlying mechanism of the gliding apparatus of filamentous cyanobacteria: more contacts generate more force, but also closer contact with the substrate, thereby increasing friction to the same extent. Force generation by slime extrusion (Hoiczyk and Baumeister, 1998 ), in contrast, would lead to the opposite behavior: More slime generates more propulsion, but also reduces friction. Besides fundamental fluid-mechanical considerations (Snoeijer et al., 2013 ), this is rationalized by two experimental observations: i. gliding velocity correlates positively with slime layer thickness (Dhahri et al., 2013 ) and ii. motility in slime-secretion deficient mutants is restored upon exogenous addition of polysaccharide slime. Still we emphasize that many other possibilities exist. One could, for instance, postulate a regulation of the generated forces to the experienced friction, to maintain some preferred or saturated velocity.”

      Can the authors comment on possible mechanisms (perhaps from the literature) that indicate how isotropic friction may be generated in settings where focal adhesions drive motility? A key aspect here would probably be estimating the extent of this adhesion patch and comparing it to a characteristic contact area. Can lubrication theory be used to estimate characteristic areas of contact (knowing the radius of the filament, and assuming a height above the substrate)? If the focal adhesions typically cover areas smaller than this lubrication area, it may suggest the possibility that bacteria essentially present a flat surface insofar as adhesion is concerned, leading to a transversely isotropic response in terms of the drag. Of course, we will still require the effective propulsive force to act along the tangent.

      We thank the referee for suggesting to estimate the dimensions of the contact region. Both pili and focal adhesion sites would be of sizes below one micron [A3, A4], much smaller than the typical contact region in the lubricated contact, which is on the order of the filament radius (few microns). So indeed, isotropic friction may be expected in this situation [A5] and is assumed frequently in theoretical work [A6–A8]. Anisotropy may then indeed be induced by active forces [A9], but we are not aware of measurements of the anisotropy of friction in bacterial gliding.

      For a more precise estimate using lubrication theory, rheology and extrusion rate of the secreted polysaccharides would have to be known, but we are not aware of detailed experimental characterizations.

      We extended the paragraph in the buckling theory on page 5 regarding the assumption of isotropic friction:

      “We use classical Kirchhoff theory for a uniform beam of length L and bending modulus B, subject to a force density ⃗b = −f ⃗t− η ⃗v, with an effective active force density f along the tangent ⃗t, and an effective friction proportional to the local velocity ⃗v, analog to existing literature (Fily et al., 2020; Chelakkot et al., 2014; Sekimoto et al., 1995 ). Presumably, this friction is dominated by the lubrication drag from the contact with the substrate, filled by a thin layer of secreted polysaccharide slime which is much more viscous than the surrounding bulk fluid. Speculatively, the motility mechanism might also comprise adhering elements like pili (Khayatan et al., 2015 ) or foci (Mignot et al., 2007 ) that increase the overall friction (Pompe et al., 2015 ). Thus, the drag due to the surrounding bulk fluid can be neglected (Man and Kanso, 2019 ), and friction is assumed to be isotropic, a common assumption in motility models (Fei et al., 2020; Tchoufag et al., 2019; Wada et al., 2013 ). We assume…”

      We also extended the discussion regarding the outcome of isotropic friction (page 7):

      “…Thus we plot f/v over η in Figure 4 D, finding nearly identical values over about two decades. Since f and η are not correlated with v0, this is due to a correlation between f and η. This relation is remarkable in two aspects: On the one hand, it indicates that friction is mainly isotropic. This suggests that friction is governed by an isotropic process like bond friction or lubrication from the slime layer in the contact with the substrate, the latter being consistent with the observation that mutations deficient of slime secretion do not glide but exogenous addition of slime restores motility (Khayatan et al., 2015 ). In contrast, hydrodynamic drag from the surrounding bulk fluid (Man and Kanso, 2019 ), or the internal friction of the gliding apparatus would be expected to generate strongly anisotropic friction. If the latter was dominant, a snapping-like transition into the buckling state would be expected, rather than the continuously growing amplitude that is observed in experiments. On the other hand, it indicates that friction and propulsion forces…”

      I am not sure why the authors mention that the power of the gliding apparatus is not rate-limiting. The only way to verify this would be to put these in highly viscous fluids where the drag of the external fluid comes into the picture as well (if focal adhesions are on the substrate-facing side, and the upper side is subject to ambient fluid drag). Also, the friction referred to here has the form of a viscous drag (no memory effect, and thus not viscoelastic or gel-like), and it is not clear if forces generated by adhesion involve other forms of drag such as chemical friction via temporary bonds forming and breaking. In quasi-static settings and under certain conditions such as the separation of chemical and elastic time scales, bond friction may yield overall force proportional to local sliding velocities.

      We agree with the referee that the origin of the friction is not easily resolved. Lubrication yields an isotropic force density that is proportional to the velocity, and the same could be generated by bond friction. Importantly, both types of friction would be assumed to be predominantly isotropic. We explicitly referred to lubrication drag because it has been shown that mutations deficient of slime extrusion do not glide [A4].

      Assuming, in contrast, that in free gliding, friction with the environment is not rate limiting, but rather the internal friction of the gliding apparatus, i.e., the available power, we would expect a rather different behavior during early-buckling evolution. During early buckling, the tangential motion is stalled, and the dynamics is dominated by the growing buckling amplitude of filament regions near the front end, which move mainly transversely. For geometric reasons, in this stage the (transverse) buckling amplitude grows much faster than the rear part of the filament advances longitudinally. Thus that motion should not be impeded much by the internal friction of the gliding apparatus, but by external friction between the buckling parts of the filament and the ambient. The rate at which the buckling amplitude initially grows should be limited by the accumulated compressive stress in the filament and the transverse friction with the substrate. If the latter were much smaller than the (logitudinal) internal friction of the gliding apparatus, we would expect a snapping-like transition into the buckled state, which we did not observe.

      In our paper, we do not intend to evaluate the exact origin of the friction, quantifying the gliding force is the main objective. A linear force-velocity relation agrees with our observations. A detailed analysis of friction in cyanobacterial gliding would be an interesting direction for future work.

      To make these considerations more clear, we rephrased the corresponding paragraph on page 7 & 8:

      “…Thus we plot f/v over η in Figure 4 D, finding nearly identical values over about two decades. Since f and η are not correlated with v0, this is due to a correlation between f and η. This relation is remarkable in two aspects: On the one hand, it indicates that friction is mainly isotropic. This suggests that friction is governed by an isotropic process like bond friction or lubrication from the slime layer in the contact with the substrate, the latter being consistent with the observation that mutations deficient of slime secretion do not glide but exogenous addition of slime restores motility (Khayatan et al., 2015 ). In contrast, hydrodynamic drag from the surrounding bulk fluid (Man and Kanso, 2019 ), or the internal friction of the gliding apparatus would be expected to generate strongly anisotropic friction. If the latter was dominant, a snapping-like transition into the buckling state would be expected, rather than the continuously growing amplitude that is observed in experiments. On the other hand, it indicates that friction and propulsion forces…”

      For readers from a non-fluids background, some additional discussion of the drag forces, and the forms of friction would help. For a freely gliding filament if f is the force density (per unit length), then steady gliding with a viscous frictional drag would suggest (as mentioned in the paper) f ∼ v! L η||. The critical buckling length is then dependent on f and on B the bending modulus. Here the effective drag is defined per length. I can see from this that if the active force is fixed, and the viscous component resulting from the frictional mechanism is fixed, the critical buckling length will not depend on the velocity (unless I am missing something in their argument), since the velocity is not a primitive variable, and is itself an emergent quantity.

      We are not sure what “f ∼ v! L η||” means, possibly the spelling was corrupted in the forwarding of the comments.

      We assumed an overdamped motion in which the friction force density ff (per unit length of the filament) is proportional to the velocity v0, i.e. ff ∼ η v0, with a friction coefficient η. Overdamped means that the friction force density is equal and opposite to the propulsion force density, so the propulsion force density is f ∼ ff ∼ η v0. The total friction and propulsion forces can be obtained by multiplication with the filament length

      L, which is not required here. In this picture, v0 is an emergent quantity and f and η are assumed as given and constant. Thus, by observing v0, f can be inferred up to the friction coefficient η. Therefore, by using two descriptive variables, L and v0, with known B, the primitive variable η can be inferred by logistic regression, and f then follows from the overdamped equation of motion.

      To clarify this, we revised the corresponding section on page 5 of the paper:

      “The substrate contact requires lubrication from polysaccharide slime to enable bacteria to glide (Khayatan et al., 2015 ). Thus we assume an over- damped motion with co-linear friction, for which the propulsion force f and the free gliding velocity v0 of a filament are related by f = η v0, with a friction coefficient η. In this scenario, f can be inferred both from the observed Lc ∼ (f/B)−1/3 and, up to the proportionality coefficient η, from the observed free gliding velocity. Thus, by combining the two relations, one may expect also a strong correlation between Lc and v0. In order to test this relation for consistency with our data, we include v0 as a second regressor, by setting x = (L−Lc(v0))/∆Lc in Equation 1, with Lc(v0) = (η v0/(30.5722 B))−1/3, to reflect our expectation from theory (see below). Now, η rather than f is the only unknown, and its ensemble distribution will be determined in the regression. Figure 3 E,F show the buckling behavior…”

      Reviewer 2:

      In the presented manuscript, the authors first use structured microfluidic devices with gliding filamentous cyanobacteria inside in combination with micropipette force measurements to measure the bending rigidity of the filaments.

      Next, they use triangular structures to trap the bacteria with the front against an obstacle. Depending on the length and rigidity, the filaments buckle under the propulsive force of the cells. The authors use theoretical expressions for the buckling threshold to infer propulsive force, given the measured length and stiffnesses. They find nearly identical values for both species, f ∼ (1.0 ± 0.6) nN/µm, nearly independent of the velocity.

      Finally, they measure the shape of the filament dynamically to infer friction coefficients via Kirchhoff theory. This last part seems a bit inconsistent with the previous inference of propulsive force. Before, they assumed the same propulsive force for all bacteria and showed only a very weak correlation between buckling and propulsive velocity. In this section, they report a strong correlation with velocity, and report propulsive forces that vary over two orders of magnitude. I might be misunderstanding something, but I think this discrepancy should have been discussed or explained.

      We regret the misunderstanding of the reviewer regarding the velocity dependence, which indicates that the manuscript should be improved to convey these relations correctly.

      First, in the Buckling Measurements section, we did not assume the same propulsion force for all bacteria. The logistic regression yields an ensemble median for Lc (and thus an ensemble median for f ), along with the width ∆Lc of the distribution (and thus also the width of the distribution of f ). Our result f ∼ (1.0 ± 0.6) nN/µm indicates the median and the width of the distribution of the propulsion force densities across the ensemble of several hundred filaments used in the buckling measurements. The large variability of the forces found in the second part is consistently reflected by this very wide distribution of active forces detected in the logistic regression in the first part.

      We did small modifications to the buckling theory paragraph to clarify that in the first part, a distribution of forces rather than a constant value is inferred (page 6)

      “Inserting the population median and quartiles of the distributions of bending modulus and critical length, we can now quantify the distribution of the active force density for the filaments in the ensemble from the buckling measurements. We obtain nearly identical values for both species, f ∼ (1.0±0.6) nN/µm, where the uncertainty represents a wide distribution of f across the ensemble rather than a measurement error.”

      The same holds, of course, when inferring the distribution of the friction coefficients (page 5):

      “The substrate contact requires lubrication from polysaccharide slime to enable bacteria to glide (Khayatan et al., 2015 ). Thus we assume an over- damped motion with co-linear friction, for which the propulsion force f and the free gliding velocity v0 of a filament are related by f = η v0, with a friction coefficient η. In this scenario, f can be inferred both from the observed Lc ∼ (f/B)−1/3 and, up to the proportionality coefficient η, from the observed free gliding velocity. Thus, by combining the two relations, one may expect also a strong correlation between Lc and v0. In order to test this relation for consistency with our data, we include v0 as a second regressor, by setting x = (L−Lc(v0))/∆Lc in Equation 1, with Lc(v0) = (η v0/(30.5722 B))−1/3, to reflect our expectation from theory (see below). Now, η rather than f is the only unknown, and its ensemble distribution will be determined in the regression. Figure 3 E,F show the buckling behavior…”

      The (naturally) wide distribution of force (and friction) leads to a distribution of Lc as well. However, due to the small exponent of 1/3 in the buckling threshold Lc ∼ f 1/3, the distribution of Lc is not as wide as the distributions of the individually inferred f or η. This is visualized in panel G of Figure 3, plotting Lc as a function of v0 (v0 is equivalent to f , up to a proportionality coefficient η). The natural length distribution, in contrast, is very wide. Therefore, the buckling propensity of a filament is most strongly characterized by its length, while force variability, which alters Lc of the individual, plays a secondary role.

      In order to clarify this, we edited the last paragraph of the Buckling Measurements section on page 5 of the manuscript:

      “…Within the characteristic range of observed velocities (1 − 3 µm/s), the median Lc depends only mildly on v0, as compared to its rather broad distribution, indicated by the bands in Figure 3 G. Thus a possible correlation between f and v0 would only mildly alter Lc. The natural length distribution (cf. Appendix 1—figure 1 ), however, is very broad, and we conclude that growth rather than velocity or force distributions most strongly impacts the buckling propensity of cyanobacterial colonies. Also, we hardly observed short and fast filaments of K. animale, which might be caused by physiological limitations (Burkholder, 1934 ).”

      Second, in the Profile analysis section, we did not report a correlation between force and velocity. As can be seen in Figure 4—figure Supplement 1, neither the active force nor the friction coefficient, as determined from the analysis of individual filaments, show any significant correlation with the velocity. This is also written in the discussion (page 7):

      We see no significant correlation between L or v0 and f or η, but the observed values of f and η cover a wide range (Figure 4 B, C and Figure 4—figure Supplement 1 ).

      Note that this is indeed consistent with the logistic regression: Using v0 as a second regressor did not significantly reduce the width of the distribution of Lc as compared to the simple logistic regression, indicating that force and velocity are not strongly correlated.

      In order to clarify this in the manuscript, we modified that part (page 7):

      “…We see no significant correlation between L or v0 and f or η, but the observed values of f and η cover a wide range (Figure 4 B,C and Figure 4— figure Supplement 1 ). This is consistent with the logistic regression, where using v0 as a second regressor did not significantly reduce the width of the distribution of critical lengths or active forces. The two estimates of the friction coefficient, from logistic regression and individual profile fits, are measured in (predominantly) orthogonal directions: tangentially for the logistic regression where the free gliding velocity was used, and transversely for the evolution of the buckling profiles. Thus we plot f/v over η in Figure 4 D, finding nearly identical values over about two decades. Since f and η are not correlated with v0, this is due to a correlation between f and η. This relation is remarkable in two aspects: On the one hand, it indicates that friction is mainly isotropic…”

      From a theoretical perspective, not many new results are presented. The authors repeat the well-known calculation for filaments buckling under propulsive load and arrive at the literature result of buckling when the dimensionless number (f L3/B) is larger than 30.6 as previously derived by Sekimoto et al in 1995 [1] (see [2] for a clamped boundary condition and simulations). Other theoretical predictions for pushed semi-flexible filaments [1–4] are not discussed or compared with the experiments. Finally, the Authors use molecular dynamics type simulations similar to [2–4] to reproduce the buckling dynamics from the experiments. Unfortunately, no systematic comparison is performed.

      [1]        Ken Sekimoto, Naoki Mori, Katsuhisa Tawada, and Yoko Y Toyoshima. Symmetry breaking instabilities of an in vitro biological system. Physical review letters, 75(1):172, 1995.

      [2]       Raghunath Chelakkot, Arvind Gopinath, Lakshminarayanan Mahadevan, and Michael F Hagan. Flagellar dynamics of a connected chain of active, polar, brownian particles. Journal of The Royal Society Interface, 11(92):20130884, 2014.

      [3]       Rolf E Isele-Holder, Jens Elgeti, and Gerhard Gompper. Self-propelled worm-like filaments: spontaneous spiral formation, structure, and dynamics. Soft matter, 11(36):7181–7190, 2015.

      [4]       Rolf E Isele-Holder, Julia J¨ager, Guglielmo Saggiorato, Jens Elgeti, and Gerhard Gompper. Dynamics of self-propelled filaments pushing a load. Soft Matter, 12(41):8495–8505, 2016.

      We thank the reviewer for pointing us to these publications, in particular the work by Sekimoto we were not aware of. We agree with the referee that the calculation is straight forward (basically known since Euler, up to modified boundary conditions). Our paper focuses on experimental work, the molecular dynamics simulations were included mainly as a consistency check and not intended to generate the beautiful post-buckling patterns observed in references [2-4]. However, such shapes do emerge in filamentous cyanobacteria, and with the data provided in our manuscript, simulations can be quantitatively matched to our experiments, which will be covered by future work.

      We included the references in the revision of our manuscript, and a statement that we do not claim priority on these classical theoretical results.

      Introduction, page 2:

      “…Self-Buckling is an important instability for self-propelling rod-like micro-organisms to change the orientation of their motion, enabling aggregation or the escape from traps (Fily et al., 2020; Man and Kanso, 2019; Isele-Holder et al., 2015; Isele-Holder et al., 2016 ). The notion of self-buckling goes back to work of Leonhard Euler in 1780, who described elastic columns subject to gravity (Elishakoff, 2000 ). Here, the principle is adapted to the self-propelling, flexible filaments (Fily et al., 2020; Man and Kanso, 2019; Sekimoto et al., 1995 ) that glide onto an obstacle. Filaments buckle if they exceed a certain critical length Lc ∼ (B/f)1/3, where B is the bending modulus and f the propulsion force density…”

      Buckling theory, page 5:

      “…The buckling of gliding filaments differs in two aspects: the propulsion forces are oriented tangentially instead of vertically, and the front end is supported instead of clamped. Therefore, with L < Lc all initial orientations are indifferently stable, while for L > Lc, buckling induces curvature and a resultant torque on the head, leading to rotation (Fily et al., 2020; Chelakkot et al., 2014; Sekimoto et al., 1995 ). Buckling under concentrated tangential end-loads has also been investigated in literature (de Canio et al., 2017; Wolgemuth et al., 2005 ), but leads to substantially different shapes of buckled filaments. We use classical Kirchhoff theory for a uniform beam of length L and bending modulus B, subject to a force density ⃗b = −f ⃗t − η ⃗v, with an effective active force density f along the tangent ⃗t, and an effective friction proportional to the local velocity ⃗v, analog to existing literature (Fily et al., 2020; Chelakkot et al., 2014; Sekimoto et al., 1995 )…”

      Further on page 6:

      “To derive the critical self-buckling length, Equation 5 can be linearized for two scenarios that lead to the same Lc: early-time small amplitude buckling and late-time stationary rotation at small and constant curvature (Fily et al., 2020; Chelakkot et al., 2014 ; Sekimoto et al., 1995 ). […] Thus, in physical units, the critical length is given by Lc = (30.5722 B/f)1/3, which is reproduced in particle based simulations (Appendix Figure 2 ) analogous to those in Isele-Holder et al. (2015, 2016).”

      Discussion, page 7 & 8:

      “…This, in turn, has dramatic consequences on the exploration behavior and the emerging patterns (Isele-Holder et al., 2015, 2016; Abbaspour et al., 2021; Duman et al., 2018; Prathyusha et al., 2018; Jung et al., 2020 ): (L/Lc)3 is, up to a numerical prefactor, identical to the flexure number (Isele-Holder et al., 2015, 2016; Duman et al., 2018; Winkler et al., 2017 ), the ratio of the Peclet number and the persistence length of active polymer melts. Thus, the ample variety of non-equilibrium phases in such materials (Isele-Holder et al., 2015, 2016; Prathyusha et al., 2018; Abbaspour et al., 2021 ) may well have contributed to the evolutionary success of filamentous cyanobacteria.”

      Reviewer 3:

      Summary:

      This paper presents novel and innovative force measurements of the biophysics of gliding cyanobacteria filaments. These measurements allow for estimates of the resistive force between the cell and substrate and provide potential insight into the motility mechanism of these cells, which remains unknown.

      We thank the reviewer for the positive evaluation of our work. We have revised the manuscript according to their comments and detail our replies and modifications next to the individual points below.

      Strengths:

      The authors used well-designed microfabricated devices to measure the bending modulus of these cells and to determine the critical length at which the cells buckle. I especially appreciated the way the authors constructed an array of pillars and used it to do 3-point bending measurements and the arrangement the authors used to direct cells into a V-shaped corner in order to examine at what length the cells buckled at. By examining the gliding speed of the cells before buckling events, the authors were able to determine how strongly the buckling length depends on the gliding speed, which could be an indicator of how the force exerted by the cells depends on cell length; however, the authors did not comment on this directly.

      We thank the referee for the positive assessment of our work. Importantly, we do not see a significant correlation between buckling length and gliding speeds, and we also do not see a correlation with filament length, consistent with the assumption of a propulsion force density that is more or less homogeneously distributed along the filament. Note that each filament consists of many metabolically independent cells, which renders cyanobacterial gliding a collective effort of many cells, in contrast to gliding of, e.g., myxobacteria.

      In response also to the other referees’ comments, we modified the manuscript to reflect more on the absence of a strong correlation between velocity and force/critical length. We modified the Buckling measurements section on page 5 of the paper:

      “The substrate contact requires lubrication from polysaccharide slime to enable bacteria to glide (Khayatan et al., 2015 ). Thus we assume an over-damped motion with co-linear friction, for which the propulsion force f and the free gliding velocity v0 of a filament are related by f = η v0, with a friction coefficient η. In this scenario, f can be inferred both from the observed Lc ∼ (f/B)−1/3 and, up to the proportionality coefficient η, from the observed free gliding velocity. Thus, by combining the two relations, one may expect also a strong correlation between Lc and v0. In order to test this relation for consistency with our data, we include v0 as a second regressor, by setting x = (L−Lc(v0))/∆Lc in Equation 1, with Lc(v0) = (η v0/(30.5722 B))−1/3, to reflect our expectation from theory (see below). Now, η rather than f is the only unknown, and its ensemble distribution will be determined in the regression. Figure 3 E, F show the buckling behavior…”

      Further, we edited the last paragraph of the Buckling measurements section on page 5 of the manuscript:

      “Within the characteristic range of observed velocities (1 − 3 µm/s), the median Lc depends only mildly on v0, as compared to its rather broad distribution, indicated by the bands in Figure 3 G. Thus a possible correlation between f and v0 would only mildly alter Lc. The natural length distribution (cf. Appendix 1—figure 1 ), however, is very broad, and we conclude that growth rather than velocity or force distributions most strongly impacts the buckling propensity of cyanobacterial colonies. Also, we hardly observed short and fast filaments of K. animale, which might be caused by physiological limitations (Burkholder, 1934 ).”

      We also rephrased the corresponding discussion paragraph on page 7:

      “…Thus we plot f/v over η in Figure 4 D, finding nearly identical values over about two decades. Since f and η are not correlated with v0, this is due to a correlation between f and η. This relation is remarkable in two aspects: On the one hand, it indicates that friction is mainly isotropic. This suggests that friction is governed by an isotropic process like bond friction or lubrication from the slime layer in the contact with the substrate, the latter being consistent with the observation that mutations deficient of slime secretion do not glide but exogenous addition of slime restores motility (Khayatan et al., 2015 ). In contrast, hydrodynamic drag from the surrounding bulk fluid (Man and Kanso, 2019 ), or the internal friction of the gliding apparatus would be expected to generate strongly anisotropic friction. If the latter was dominant, a snapping-like transition into the buckling state would be expected, rather than the continuously growing amplitude that is observed in experiments. On the other hand, it indicates that friction and propulsion forces…”

      Weaknesses:

      There were two minor weaknesses in the paper.

      First, the authors investigate the buckling of these gliding cells using an Euler beam model. A similar mathematical analysis was used to estimate the bending modulus and gliding force for Myxobacteria (C.W. Wolgemuth, Biophys. J. 89: 945-950 (2005)). A similar mathematical model was also examined in G. De Canio, E. Lauga, and R.E Goldstein, J. Roy. Soc. Interface, 14: 20170491 (2017). The authors should have cited these previous works and pointed out any differences between what they did and what was done before.

      We thank the reviewer for pointing us to these references. The paper by Wolgemuth is theoretical work, describing A-motility in myxobacteria by a concentrated propulsion force at the rear end of the bacterium, possibly stemming from slime extrusion. This model was a little later refuted by [A3], who demonstrated that focal adhesion along the bacterial body and thus a distributed force powers A-motility, a mechanism that has by now been investigated in great detail (see [A10]). The paper by Canio et al. contains a thorough theoretical analysis of a filament that is clamped at one end and subject to a concentrated tangential load on the other. Since both models comprise a concentrated end-load rather than a distributed propulsion force density, they describe a substantially different motility mechanism, leading also to substantially different buckling profiles. Consequentially, these models cannot be applied to cyanobacterial gliding.

      We included both citations in the revision and pointed out the differences to our work in the introduction (page 2):

      “…A few species appear to employ a type-IV-pilus related mechanism (Khayatan et al., 2015; Wilde and Mullineaux, 2015 ), similar to the better- studied myxobacteria (Godwin et al., 1989; Mignot et al., 2007; Nan et al., 2014; Copenhagen et al., 2021; Godwin et al., 1989 ), which are short, rod-shaped single cells that exhibit two types of motility: S (social) motility based on pilus extension and retraction, and A (adventurous) motility based on focal adhesion (Chen and Nan, 2022 ) for which also slime extrusion at the trailing cell pole was earlier postulated as mechanism (Wolgemuth et al., 2005 ). Yet, most gliding filamentous cyanobacteria do not exhibit pili and their gliding mechanism appears to be distinct from myxobacteria (Khayatan et al., 2015 ).”

      And in Buckling theory, page 5:

      “….The buckling of gliding filaments differs in two aspects: the propulsion forces are oriented tangentially instead of vertically, and the front end is supported instead of clamped. Therefore, with L < Lc all initial orientations are indifferently stable, while for L > Lc, buckling induces curvature and a resultant torque on the head, leading to rotation (Fily et al., 2020; Chelakkot et al., 2014; Sekimoto et al., 1995 ). Buckling under concentrated tangential end-loads has also been investigated in literature (de Canio et al., 2017; Wolgemuth et al., 2005 ), but leads to substantially different shapes of buckled filaments.”

      The second weakness is that the authors claim that their results favor a focal adhesion-based mechanism for cyanobacterial gliding motility. This is based on their result that friction and adhesion forces correlate strongly. They then conjecture that this is due to more intimate contact with the surface, with more contacts producing more force and pulling the filaments closer to the substrate, which produces more friction. They then claim that a slime-extrusion mechanism would necessarily involve more force and lower friction. Is it necessarily true that this latter statement is correct? (I admit that it could be, but is it a requirement?)

      We thank the referee for raising this interesting question. Our claim regarding slime extrusion is based on three facts: i. mutations deficient of slime extrusion do not glide, but start gliding as soon as slime is provided externally [A4]. ii. A positive correlation between speed and slime layer thickness was observed in Nostoc [A11]. iii. The fluid mechanics of lubricated sliding contacts is very well understood and predicts a decreasing resistance with increasing layer thickness.

      We included these considerations in the revision of our manuscript (page 8):

      “…it indicates that friction and propulsion forces, despite being quite variable, correlate strongly. Thus, generating more force comes, inevitably, at the expense of added friction. For lubricated contacts, the friction coefficient is proportional to the thickness of the lubricating layer (Snoeijer et al., 2013 ), and we conjecture active force and drag both increase due to a more intimate contact with the substrate. This supports mechanisms like focal adhesion (Mignot et al., 2007 ) or a modified type-IV pilus (Khayatan et al., 2015 ), which generate forces through contact with extracellular surfaces, as the underlying mechanism of the gliding apparatus of filamentous cyanobacteria: more contacts generate more force, but also closer contact with the substrate, thereby increasing friction to the same extent. Force generation by slime extrusion (Hoiczyk and Baumeister, 1998 ), in contrast, would lead to the opposite behavior: More slime generates more propulsion, but also reduces friction. Besides fundamental fluid-mechanical considerations (Snoeijer et al., 2013 ), this is rationalized by two experimental observations: i. gliding velocity correlates positively with slime layer thickness (Dhahri et al., 2013 ) and ii. motility in slime-secretion deficient mutants is restored upon exogenous addition of polysaccharide slime. Still we emphasize that many other possibilities exist. One could, for instance, postulate a regulation of the generated forces to the experienced friction, to maintain some preferred or saturated velocity.”

      Related to this, the authors use a model with isotropic friction. They claim that this is justified because they are able to fit the cell shapes well with this assumption. How would assuming a non-isotropic drag coefficient affect the shapes? It may be that it does equally well, in which case, the quality of the fits would not be informative about whether or not the drag was isotropic or not.

      The referee raises another very interesting point. Given the typical variability and uncertainty in experimental measurements (cf. error Figure 4 A), a model with a sightly anisotropic friction could be fitted to the observed buckling profiles as well, without significant increase of the mismatch. Yet, strongly anisotropic friction would not be consistent with our observations.

      Importantly, however, we did not conclude on isotropic friction based on the fit quality, but based on a comparison between free gliding and early buckling (Figure 4 D). In early buckling, the dominant motion is in transverse direction, while longitudinal motion is insignificant, due to geometric reasons. Thus, independent of the underlying model, mostly the transverse friction coefficiont is inferred. In contrast, free gliding is a purely longitudinal motion, and thus only the friction coefficient for longitudinal motion can be inferred. These two friction coefficients are compared in Figure 4 D. Still, the scatter of that data would allow to fit a certain anisotropy within the error margins. What we can exclude based on out observation is the case of a strongly anisotropic friction. If there is no ab-initio reason for anisotropy, nor a measurement that indicates it, we prefer to stick with the simplest

      assumption. We carefully chose our wording in the Discussion as “mainly isotropic” rather

      than “isotropic” or “fully isotropic”.

      We added a small statement to the Discussion on page 7 & 8:

      “... Thus we plot f/v over η in Figure 4 D, finding nearly identical values over about two decades. Since f and η are not correlated with v0, this is due to a correlation between f and η. This relation is remarkable in two aspects: On the one hand, it indicates that friction is mainly isotropic. This suggests that friction is governed by an isotropic process like bond friction or lubrication from the slime layer in the contact with the substrate, the latter being consistent with the observation that mutations deficient of slime secretion do not glide but exogenous addition of slime restores motility (Khayatan et al., 2015 ). In contrast, hydrodynamic drag from the surrounding bulk fluid (Man and Kanso, 2019 ), or the internal friction of the gliding apparatus would be expected to generate strongly anisotropic friction. If the latter was dominant, a snapping-like transition into the buckling state would be expected, rather than the continuously growing amplitude that is observed in experiments. On the other hand, it indicates that friction and propulsion forces ...”

      Recommendations for the authors

      The discussion regarding how the findings of this paper imply that cyanobacteria filaments are propelled by adhesion forces rather than slime extrusion should be improved, as this conclusion seems questionable. There appears to be an inconsistency with a buckling force said to be only weakly dependent on the gliding velocity, while its ratio with the velocity correlates with a friction coefficient. Finally, data and source code should be made publicly available.

      In the revised version, we have modified the discussion of the force generating mechanism according to the reviewer suggestions. The perception of inconsistency in the velocity dependence of the buckling force was based on a misunderstanding, as we detailed in our reply to the referee. We revised the corresponding section to make it more clear. Data and source code have been uploaded to a public data repository.

      Reviewer #2 (recommendations for the authors)

      Despite eLife policy, the authors do not provide a Data Availability Statement. For the presented manuscript, data and source code should be provided “via trusted institutional or third-party repositories that adhere to policies that make data discoverable, accessible and usable.” https://elifesciences.org/inside-elife/51839f0a/for-authors-updates- to-elife-s-data-sharing-policies

      Most of the issues in this reviewer’s public review should be easy to correct, so I would strongly support the authors to provide an amended manuscript.

      We added the Data Availability Statement in the amended manuscript.

      References

      [A1] E. Hoiczyk and W. Baumeister. “The junctional pore complex, a prokaryotic secretion organelle, is the molecular motor underlying gliding motility in cyanobacteria”. In: Curr. Biol. 8.21 (1998), pp. 1161–1168. doi: 10.1016/s0960-9822(07)00487-3.

      [A2] N. Read, S. Connell, and D. G. Adams. “Nanoscale Visualization of a Fibrillar Array in the Cell Wall of Filamentous Cyanobacteria and Its Implications for Gliding Motility”. In: J. Bacteriol. 189.20 (2007), pp. 7361–7366. doi: 10.1128/jb.00706- 07.

      [A3] T. Mignot, J. W. Shaevitz, P. L. Hartzell, and D. R. Zusman. “Evidence That Focal Adhesion Complexes Power Bacterial Gliding Motility”. In: Science 315.5813 (2007), pp. 853–856. doi: 10.1126/science.1137223.

      [A4] Behzad Khayatan, John C. Meeks, and Douglas D. Risser. “Evidence that a modified type IV pilus-like system powers gliding motility and polysaccharide secretion in filamentous cyanobacteria”. In: Mol. Microbiol. 98.6 (2015), pp. 1021–1036. doi: 10.1111/mmi.13205.

      [A5] Tilo Pompe, Martin Kaufmann, Maria Kasimir, Stephanie Johne, Stefan Glorius, Lars Renner, Manfred Bobeth, Wolfgang Pompe, and Carsten Werner. “Friction- controlled traction force in cell adhesion”. In: Biophysical journal 101.8 (2011), pp. 1863–1870.

      [A6] Hirofumi Wada, Daisuke Nakane, and Hsuan-Yi Chen. “Bidirectional bacterial gliding motility powered by the collective transport of cell surface proteins”. In: Physical Review Letters 111.24 (2013), p. 248102.

      [A7] Jo¨el Tchoufag, Pushpita Ghosh, Connor B Pogue, Beiyan Nan, and Kranthi K Mandadapu. “Mechanisms for bacterial gliding motility on soft substrates”. In: Proceedings of the National Academy of Sciences 116.50 (2019), pp. 25087–25096.

      [A8] Chenyi Fei, Sheng Mao, Jing Yan, Ricard Alert, Howard A Stone, Bonnie L Bassler, Ned S Wingreen, and Andrej Kosmrlj. “Nonuniform growth and surface friction determine bacterial biofilm morphology on soft substrates”. In: Proceedings of the National Academy of Sciences 117.14 (2020), pp. 7622–7632.

      [A9] Arja Ray, Oscar Lee, Zaw Win, Rachel M Edwards, Patrick W Alford, Deok-Ho Kim, and Paolo P Provenzano. “Anisotropic forces from spatially constrained focal adhesions mediate contact guidance directed cell migration”. In: Nature communications 8.1 (2017), p. 14923.

      [A10] Jing Chen and Beiyan Nan. “Flagellar motor transformed: biophysical perspectives of the Myxococcus xanthus gliding mechanism”. In: Frontiers in Microbiology 13 (2022), p. 891694.

      [A11] Samia Dhahri, Michel Ramonda, and Christian Marliere. “In-situ determination of the mechanical properties of gliding or non-motile bacteria by atomic force microscopy under physiological conditions without immobilization”. In: PLoS One 8.4 (2013), e61663.

    1. Reviewer #2 (Public Review):

      Pyoverdines, siderophores produced by many Pseudomonads, are one of the most diverse groups of specialized metabolites and are frequently used as model systems. Thousands of Pseudomonas genomes are available, but large-scale analyses of pyoverdines are hampered by the biosynthetic gene clusters (BGCs) being spread across multiple genomic loci and existing tools' inability to accurately predict amino acid substrates of the biosynthetic adenylation (A) domains. The authors present a bioinformatics pipeline that identifies pyoverdine BGCs and predicts the A domain substrates with high accuracy. They tackled a second challenging problem by developing an algorithm to differentiate between outer membrane receptor selectivity for pyoverdines versus other siderophores and substrates. The authors applied their dataset to thousands of Pseudomonas strains, producing the first comprehensive overview of pyoverdines and their receptors and predicting many new structural variants.

      The A domain substrate prediction is impressive, including the correction of entries in the MIBiG database. Their high accuracy came from a relatively small training dataset of A domains from 13 pyoverdine BGCs. The authors acknowledge that this small dataset does not include all substrates, and correctly point out that new sequence/structure pairs can be added to the training set to refine the prediction algorithm. The authors could have been more comprehensive in finding their training set data. For instance, the authors claim that histidine "had not been previously documented in pyoverdines", but the sequenced strain P. entomophila L48, incorporates His (10.1007/s10534-009-9247-y). The workflow cannot differentiate between different variants of Asp and OHOrn, and it's not clear if this is a limitation of the workflow, the training data, or both. The prediction workflow holds up well in Burkholderiales A domains, however, they fail to mention in the main text that they achieved these numbers by adding more A domains to their training set.

      To validate their predictions, they elucidated structures of several new pyoverdines, and their predictions performed well. However, the authors did not include their MS/MS data, making it impossible to validate their structures. In general, the biggest limitation of the submitted manuscript is the near-empty methods section, which does not include any experimental details for the 20 strains or details of the annotation pipeline (such as "Phydist" and "Syndist"). The source code also does not contain the requisite information to replicate the results or re-use the pipeline, such as the antiSMASH version and required flags. That said, skimming through the source code and data (kindly provided upon request) suggests that the workflow itself is sound and a clear improvement over existing tools for pyoverdine BGC annotation.

      Predicting outer membrane receptor specificity is likewise a challenging problem and the authors have made a promising achievement by finding specific gene regions that differentiate the pyoverdine receptor FpvA from FpvB and other receptor families. Their predictions were not tested experimentally, but the finding that only predicted FpvA receptors were proximate to the biosynthesis genes lends credence to the predictive power of the workflow. The authors find predicted pyoverdine receptors across an impressive 468 genera, an exciting finding for expanding the role of pyoverdines as public goods beyond Pseudomonas. However, whether or not these receptors can recognize pyoverdines (and if so, which structures!) remains to be investigated.

      In all, the authors have assembled a rich dataset that will enable large-scale comparative genomic analyses. This dataset could be used by a variety of researchers, including those studying natural product evolution, public good eco/evo dynamics, and NRPS engineering.

    1. Summary of Raph Levien's Blog: "Towards principled reactive UI"

      Introduction

      • Diversity of Reactive UI Systems: The blog notes the diversity in reactive UI systems primarily sourced from open-source projects. Levien highlights a lack of comprehensive literature but acknowledges existing sources offer insights into better practices. His previous post aimed to organize these diverse patterns.
        • "There is an astonishing diversity of 'literature' on reactive UI systems."

      Goals of the Inquiry

      • Clarifying Inquiry Goals: Levien sets goals not to review but to guide inquiry into promising avenues of reactive UI in Rust, likening it to mining for rich veins of ore rather than stamp collecting.
        • "I want to do mining, not stamp collecting."

      Main Principles Explored

      • Observable Objects vs. Future-like Polling: Discusses the importance of how systems manage observable objects or utilize future-like polling for efficient UI updates.
      • Tree Mutations: How to express mutation in the render object tree is crucial, focusing on maintaining stable node identities within the tree.
        • "Then I will go into deeper into three principles, which I feel are critically important in any reactive UI framework."

      Crochet: A Research Prototype

      • Introduction of Crochet: Introduces 'Crochet', a prototype exploring these principles, acknowledging its current limitations and potential for development.
        • "Finally, I will introduce Crochet, a research prototype built for the purpose of exploring these ideas."

      Goals for Reactive UI

      • Concise Application Logic: Emphasizes the need for concise, clear application logic that drives UI efficiently, with reactive UI allowing declarative state expressions of the view tree.
        • "The main point of a reactive UI architecture is so that the app can express its logic clearly and concisely."
      • Incremental Updates: Advocates for incremental updates in UI rendering to avoid performance issues related to full re-renders, highlighting the limitations of systems like imgui and the potential of systems like Conrod, despite its shortcomings.
        • "While imgui can express UI concisely, it cheats somewhat by not being incremental."

      Evaluation of Existing Systems

      • Comparison with Other Systems: Mentions SwiftUI, imgui, React, and Svelte, discussing their approaches to handling reactive UI and their adaptability to Rust.
        • "SwiftUI has gained considerable attention due to its excellent ergonomics in this regard."

      Technical Challenges and Proposals

      • Challenges in Tree Mutation and Stable Identity: Discusses the challenges in tree mutation techniques and the importance of stable identity in UI components to preserve user interaction states.
        • "Mutation of the DOM is expressed through a well-specified and reasonably ergonomic, if inefficient, interface."

      Conclusion and Future Work

      • Future Directions and Experiments: Encourages experimentation with the Crochet prototype and discusses the ongoing development and research in making reactive UIs more efficient and user-friendly.
        • "I encourage people to experiment with the Crochet code."

      This blog post encapsulates Levien's ongoing exploration into developing a principled approach to reactive UI in Rust, highlighting the complexity of the task and his experimental prototype, Crochet, as a step towards solving these challenges.

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Strengths:

      This work (almost didactically) demonstrates how to develop, calibrate, validate and analyze a comprehensive, spatially resolved, dynamical, multicellular model. Testable model predictions of (also non-monotonic) emergent behaviors are derived and discussed. The computational model is based on a widely-used simulation platform and shared openly such that it can be further analyzed and refined by the community.

      Weaknesses:

      While the parameter estimation approach is sophisticated, this work does not address issues of structural and practical non-identifiability (Wieland et al., 2021, DOI:10.1016/j.coisb.2021.03.005) of parameter values, given just tissue-scale summary statistics, and does not address how model predictions might change if alternative parameter combinations were used. Here, the calibrated model represents one point estimate (column "Value" in Suppl. Table 1) but there is specific uncertainty of each individual parameter value and such uncertainties need to be propagated (which is computationally expensive) to the model predictions for treatment scenarios.

      We thank the reviewer for the excellent suggestions and observations. The CaliPro parameterization technique applied puts an emphasis on finding a robust parameter space instead of a global optimum. To address structural non-identifiability, we utilized partial rank correlation coefficient with each iteration of the calibration process to ensure that the sensitivity of each parameter was relevant to model outputs. We also found that there were ranges of parameter values that would achieve passing criteria but when testing the ranges in replicate resulted in inconsistent outcomes. This led us to further narrow the parameters into a single parameter set that still had stochastic variability but did not have such large variability between replicate runs that it would be unreliable. Additional discussion on this point has been added to lines 623-628. We acknowledge that there are likely other parameter sets or model rules that would produce similar outcomes but the main purpose of the model was to utilize it to better understand the system and make new predictions, which our calibration scheme allowed us to accomplish.

      Regarding practical non-identifiability, we acknowledge that there are some behaviors that are not captured in the model because those behaviors were not specifically captured in the calibration data. To ensure that the behaviors necessary to answer the aims of our paper were included, we used multiple different datasets and calibrated with multiple different output metrics. We believe we have identified the appropriate parameters to recapitulate the dominating mechanisms underlying muscle regeneration. We have added additional discussion on practical non-identifiability to lines 621-623.

      Suggested treatments (e.g. lines 484-486) are modeled as parameter changes of the endogenous cytokines (corresponding to genetic mutations!) whereas the administration of modified cytokines with changed parameter values would require a duplication of model components and interactions in the model such that cells interact with the superposition of endogenous and administered cytokine fields. Specifically, as the authors also aim at 'injections of exogenously delivered cytokines' (lines 578, 579) and propose altering decay rates or diffusion coefficients (Fig. 7), there needs to be a duplication of variables in the model to account for the coexistence of cytokine subtypes. One set of equations would have unaltered (endogenous) and another one have altered (exogenous or drugged) parameter values. Cells would interact with both of them.

      Our perturbations did not include delivery of exogenously delivered cytokines and instead were focused on microenvironmental changes in cytokine diffusion and decay rates or specific cytokine concentration levels. For example, the purpose of the VEGF delivery perturbation was to test how an increase in VEGF concentrations would alter regeneration outcome metrics with the assumption that the delivered VEGF would act in the same manner as the endogenous VEGF. We have clarified the purpose of the simulations on line 410. We agree that exploring if model predictions would be altered if endogenous and exogenous were represented separately; however, we did not explore this type of scenario.

      This work shows interesting emergent behavior from nonlinear cytokine interactions but the analysis does not provide insights into the underlying causes, e.g. which of the feedback loops dominates early versus late during a time course.

      Indeed, analyzing the model to fully understand the time-varying interactions between the multiple feedback loops is a challenge in and of itself, and we appreciate the opportunity to elaborate on our approach to addressing this challenge. First: the crosstalk/feedback between cytokines and the temporal nature was analyzed in the heatmap (Fig. 6) and lines 474-482. Second: the sensitivity of cytokine parameters to specific outputs was included in Table 9 and full-time course sensitivity is included in Supplemental Figure 2. Further correlation analysis was also included to demonstrate how cytokine concentrations influenced specific output metrics at various timepoints (Supplemental Fig. 3). We agree that further elaboration of these findings is required; therefore, we added lines 504-509 to discuss the specific mechanisms at play with the combined cytokine interactions. We also added more discussion (lines 637-638) regarding future work that could develop more analysis methods to further investigate the complex behaviors in the model.

      Reviewer #2 (Public Review):

      Strengths:

      The manuscript identified relevant model parameters from a long list of biological studies. This collation of a large amount of literature into one framework has the potential to be very useful to other authors. The mathematical methods used for parameterization and validation are transparent.

      Weaknesses:>

      I have a few concerns which I believe need to be addressed fully.

      My main concerns are the following:

      (1) The model is compared to experimental data in multiple results figures. However, the actual experiments used in these figures are not described. To me as a reviewer, that makes it impossible to judge whether appropriate data was chosen, or whether the model is a suitable descriptor of the chosen experiments. Enough detail needs to be provided so that these judgements can be made.

      Thank you for raising this point. We created a new table (Supplemental table 6) that describes the techniques used for each experimental measurement.

      (2) Do I understand it correctly that all simulations are done using the same initial simulation geometry? Would it be possible to test the sensitivity of the paper results to this geometry? Perhaps another histological image could be chosen as the initial condition, or alternative initial conditions could be generated in silico? If changing initial conditions is an unreasonably large request, could the authors discuss this issue in the manuscript?

      We appreciate your insightful question regarding the initial simulation geometry in our model. The initial configuration of the fibers/ECM/microvascular structures was kept consistent but the location of the necrosis was randomly placed for each simulation. Future work will include an in-depth analysis of altered histology configuration on model predictions which has been added to lines 618-621. We did a preliminary example analysis by inputting a different initial simulation geometry, which predicted similar regeneration outcomes. We have added Supplemental Figure 5 that provides the results of that example analysis.

      (3) Cytokine knockdowns are simulated by 'adjusting the diffusion and decay parameters' (line 372). Is that the correct simulation of a knockdown? How are these knockdowns achieved experimentally? Wouldn't the correct implementation of a knockdown be that the production or secretion of the cytokine is reduced? I am not sure whether it's possible to design an experimental perturbation which affects both parameters.

      We appreciate that this important question has been posed. Yes, in order to simulate the knockout conditions, the cytokine secretion was reduced/eliminated. The diffusion and decay parameters were also adjusted to ensure that the concentration within the system was reduced. Lines 391-394 were added to clarify this assumption.

      (4) The premise of the model is to identify optimal treatment strategies for muscle injury (as per the first sentence of the abstract). I am a bit surprised that the implemented experimental perturbations don't seem to address this aim. In Figure 7 of the manuscript, cytokine alterations are explored which affect muscle recovery after injury. This is great, but I don't believe the chosen alterations can be done in experimental or clinical settings. Are there drugs that affect cytokine diffusion? If not, wouldn't it be better to select perturbations that are clinically or experimentally feasible for this analysis? A strength of the model is its versatility, so it seems counterintuitive to me to not use that versatility in a way that has practical relevance. - I may well misunderstand this though, maybe the investigated parameters are indeed possible drug targets.

      Thank you for your thoughtful feedback. The first sentence (lines 32-34) of the abstract was revised to focus on beneficial microenvironmental conditions to best reflect the purpose of the model. The clinical relevance of the cytokine modifications is included in the discussion (lines 547-558) with additional information added to lines 524-526. For example, two methods to alter diffusion experimentally are: antibodies that bind directly to the cytokine to prevent it from binding to its receptor on the cell surface and plasmins that induce the release of bound cytokines.

      (5) A similar comment applies to Figure 5 and 6: Should I think of these results as experimentally testable predictions? Are any of the results surprising or new, for example in the sense that one would not have expected other cytokines to be affected as described in Figure 6?

      We appreciate the opportunity to clarify the basis for these perturbations. The perturbations included in Figure 5 were designed to mimic the conditions of a published experiment that delivered VEGF in vivo (Arsic et al. 2004, DOI:10.1016/J.YMTHE.2004.08.007). The perturbation input conditions and experimental results are included in Table 8 and Supplemental Table 6 has been added to include experimental data and method description of the perturbation. The results of this analysis provide both validation and new predictions, because some the outputs were measured in the experiments while others were not measured. The additional output metrics and timepoints that were not collected in the experiment allow for a deeper understanding of the dynamics and mechanisms leading to the changes in muscle recovery (lines 437-454). These model outputs can provide the basis for future experiments; for example, they highlight which time points would be more important to measure and even provide predicted effect sizes that could be the basis for a power analysis (lines 639-640).

      Regarding Figure 6, the published experimental outcomes of cytokine KOs are included in Table 8. The model allowed comparison of different cytokine concentrations at various timepoints when other cytokines were removed from the system due to the KO condition. The experimental results did not provide data on the impact on other cytokine concentrations but by using the model we were able to predict temporally based feedback between cytokines (lines 474-482). These cytokine values could be collected experimentally but would be time consuming and expensive. The results of these perturbations revealed the complex nature of the relationship between cytokines and how removal of one cytokine from the system has a cascading temporal impact. Lines 533-534 have been added to incorporate this into the discussion.

      (6) In figure 4, there were differences between the experiments and the model in two of the rows. Are these differences discussed anywhere in the manuscript?

      We appreciate your keen observation and the opportunity to address these differences. The model did not match experimental results for CSA output in the TNF KO and antiinflammatory nanoparticle perturbation or TGF levels with the macrophage depletion. While it did align with the other experimental metrics from those studies, it is likely that there are other mechanisms at play in the experimental conditions that were not captured by simulating the downstream effects of the experimental perturbations. We have added discussion of the differences to lines 445-454.

      (7) The variation between experimental results is much higher than the variation of results in the model. For example, in Figure 3 the error bars around experimental results are an order of magnitude larger than the simulated confidence interval. Do the authors have any insights into why the model is less variable than the experimental data? Does this have to do with the chosen initial condition, i.e. do you think that the experimental variability is due to variation in the geometries of the measured samples?

      Thank you for your insightful observations and questions. The lower model variability is attributed to the larger sample size of model simulations compared to experimental subjects. By running 100 simulations it narrows in the confidence interval (average 2.4 and max 3.3) compared to the experiments that typically had a sample size of less than 15. If the number of simulations had been reduced to 15 the stochasticity within the model results in a larger confidence interval (average 7.1 and max 10). There are also several possible confounding variables in the experimental protocols (i.e. variations in injury, different animal subjects for each timepoint, etc.) that are kept constant in the model simulation. We have added discussion of this point to the manuscript (lines 517519). Future work with the model will examine how variations in conditions, such as initial muscle geometry, injury, etc, alter regeneration outcomes and overall variability. This discussion has been incorporated into lines 640-643.

      (8) Is figure 2B described anywhere in the text? I could not find its description.

      Thank you for pointing that out. We have added a reference for Fig. 2B on line 190.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      (1) The model code seems to be available from https://simtk.org/projects/muscle_regen but that website requests member status ("This is a private project. You must be a member to view its contents.") and applying for membership could violate eLife's blind review process. So, this reviewer liked to but couldn't run the model her/himself. To eLife: Can the authors upload their model to a neutral server that reviewers and editors can access anonymously?

      The code has been made publicly available on the following sites:

      SimTK: https://simtk.org/docman/?group_id=2635

      Zendo: https://zenodo.org/records/10403014

      GitHub: https://github.com/mh2uk/ABM-of-Muscle-Regeneration-with-MicrovascularRemodeling

      Line 121 has been updated with the new link and the additional resources were added to lines 654-657.

      (2) The muscle regeneration field typically studies 2D cross-sections and the present model can be well compared to these other 2D models but cells as stochastic and localized sources of diffusible cytokines may yield different cytokine fields in 3D vs. 2D. I would expect more broadened and smoothened cytokine fields (from sources in neighboring cross-sections) than what the 2D model predicts based on sources just within the focus cross-section. Such relations of 2D to 3D should be discussed.

      We thank the reviewer for the excellent suggestions and observations. It has been reported in other Compucell3D models (Sego et al. 2017, DOI:10.1088/17585090/aa6ed4) that the convergence of diffusion solutions between 2D and 3D model configurations had similar outcomes, with the 3D simulations presenting excessive computational cost without contributing any noticeable additional accuracy. Similarly, other cell-based ABMs that incorporate diffusion mechanisms (Marino et al. 2018, DOI:10.3390/computation6040058) have found that 2D and 3D versions of the model both predict the same mechanisms and that the 2D resolution was sufficient for determining outcomes. Lines 615-618 were added to elaborate on this topic.

      (3) Since the model (and title) focuses on "nonlinear" cytokine interactions, what would change if cytokine decay would not be linear (as modeled here) but saturated (with nonlinear Michaelis-Menten kinetics as ligand binding and endocytosis mechanisms would call for)?

      Thank you for raising an intriguing point. The model includes a combination of cytokine decay as well as ligand binding and endocytosis mechanisms that can be saturated. For a cytokine-dependent model behavior to occur the cytokines necessary to induce that action had to reach a minimum threshold. Once that threshold was reached, that amount of the cytokine would be removed at that location to simulate ligand-receptor binding and endocytosis. These ligand binding and endocytosis mechanisms behave in a saturated way, removing a set amount when above a certain threshold or a defined ratio when under the threshold. Lines 313-315 was revised to clarify this point. There were certain concentrations of cytokines where we saw a plateau in outputs likely as a result of reaching a saturation threshold (Supplemental Fig. 3). In future work, more robust mathematical simulation of binding kinetics of cytokines (e.g., using ODEs) could be included.

      (4) Limitations of the model should be discussed together with an outlook for model refinement. For example, fiber alignment and ECM ultrastructure may require anisotropic diffusion. Many of the rate equations could be considered with saturation parameters etc. There are so many model assumptions. Please discuss which would be the most urgent model refinements and, to achieve these, which would be the most informative next experiments to perform.

      We appreciate your thoughtful consideration of the model's limitations and the need for a comprehensive discussion on model refinements and potential future experiments. The future direction section was expanded to discuss additional possible model refinements (lines 635-643) and additional possible experiments for model validation (lines 630-634).

      (5) It is not clear how the single spatial arrangement that is used affects the model predictions. E.g. now the damaged area surrounds the lymphatic vessel but what if the opposite corner was damaged and the lymphatic vessel is deep inside the healthy area?

      Thank you for highlighting the importance of considering different spatial arrangements in the model and its potential impact on predictions. We previously tested model perturbations that included specifying the injury surrounding the lymphatic vessel versus on the side opposite the vessel. Since this paper focuses more on cytokine dynamics, we plan to include this perturbation, along with other injury alterations, in a follow-on paper. We added more context about this in the future efforts section lines 640-643.

      (6) It seems that not only parameter values but also the initial values of most of the model components are unknown. The parameter estimation strategy does not seem to include the initial (spatial) distributions of collagen and cytokines and other model components. Please discuss how other (reasonable) initial values or spatial arrangements will affect model predictions.

      We appreciate your thoughtful consideration of unknown initial values/spatial arrangements and their potential influence on predictions. Initial cytokine levels prior to injury had a low relative concentration compared to levels post injury and were assumed to be negligible. Initial spatial distribution of cytokines was not defined as initial spatial inputs (except in knockout simulations) but are secreted from cells (with baseline resident cell counts defined from the literature). The distribution of cytokines is an emergent behavior that results from the cell behaviors within the model. The collagen distribution is altered in response to clearance of necrosis by the immune cells (decreased collagen with necrosis removal) and subsequent secretion of collagen by fibroblasts. The secretion of collagen from fibroblast was included in the parameter estimation sweep (Supplemental Table 1).

      We are working on further exploring the model sensitivity to altered spatial arrangements and have added this to the future directions section (lines 618-621), as well as provided Supplemental Figure 5 to demonstrate that model outcomes are similar with altered initial spatial arrangements.

      (7) Many details of the CC3D implementation are missing: overall lattice size, interaction neighborhood order, and "temperature" of the Metropolis algorithm. Are the typical adhesion energy terms used in the CPM Hamiltonian and if so, then how are these parameter values estimated?

      Thank you for bringing attention to the missing details regarding the CC3D implementation in our manuscript. We have included supplemental information providing greater detail for CPM implementation (Lines 808-854). We also added two additional supplemental tables for describing the requested CC3D implementation details (Supplemental Table 4) and adhesion energy terms (Supplemental Table 5).

      (8) Extending the model analysis of combinations of altered cytokine properties, which temporal schedules of administration would be of interest, and how could the timing of multiple interventions improve outcomes? Such a discussion or even analysis would further underscore the usefulness of the model.

      In response to your valuable suggestion, lines 558-562 were added to discuss the potential of using the model as a tool to perturb different cytokine combinations at varying timepoints throughout regeneration. In addition, this is also included in future work in lines 636-637.

      (9) The CPM is only weakly motivated, just one sentence on lines 142-145 which mentions diffusion in a misleading way as the CPM just provides cells with a shape and mechanical interactions. The diffusion part is a feature of the hybrid CompuCell3D framework, not the CPM.

      Thank you for bringing up this distinction. We removed the statement regarding diffusion and updated lines 143-146 to focus on CPM representation of cellular behavior and interactions. We also added a reference to supplemental text that includes additional details on CPM.

      (10) On lines 258-261 it does not become clear how the described springs can direct fibroblasts towards areas of low-density collagen ECM. Are the lambdas dependent on collagen density?

      Thank you for highlighting this area for clarification. The fibroblasts form links with low collagen density ECM and then are pulled towards those areas based on a constant lambda value. The links between the fibroblast and the ECM will only be made if the collagen is below a certain threshold. We added additional clarification to lines 260-264.

      (11) On line 281, what does the last part in "Fibers...were regenerating but not fully apoptotic cells" mean? Maybe rephrase this.

      The last of part of that line indicates that there were some fibers surrounding the main injury site that were damaged but still had healthy portions, indicating that they were impacted by the injury and are regenerating but did not become fully apoptotic like the fiber cells at the main site of injury. We rephrased this line to indicate that the nearby fibers were damaged but not fully apoptotic.

      (12) Lines 290-293 describe interactions of cells and fields with localized structures (capillaries and lymphatic vessel). Please explain in more detail how "capillary agents...transport neutrophiles and monocytes" in the CPM model formalism. Are new cells added following rules? How is spatial crowding of the lattice around capillaries affecting these rules? Moreover, how can "lymphatic vessel...drain the nearby cytokines and cells"? How is this implemented in the CPM and how is "nearby" calculated? We appreciate your detailed inquiry into the interactions of cells and fields with localized structures. The neutrophils and monocytes are added to the simulation at the lattice sites above capillaries (within the cell layer Fig. 2B) and undergo chemotaxis up their respective gradients. The recruitment of the neutrophils and monocytes are randomly distributed among the healthy capillaries that do not have an immune cell at the capillary location (a modeling artifact that is a byproduct of only having one cell per lattice site). This approach helped to prevent an abundance of crowding at certain capillaries. Because immune cells in the simulation are sufficiently small, chemotactic gradients are sufficiently large, and the simulation space is sufficiently large, we do not see aggregation of recruited immune cells in the CPM.

      The lymphatic vessel uptakes cytokines at lattice locations corresponding to the lymphatic vessel and will remove cells located in lattice sites neighboring the lymphatic vessel. In addition, we have included a rule in our ABM to encourage cells to migrate towards the lymphatic vessel utilizing CompuCell3D External Potential Plugin. The influence of this rule is inversely proportional to the distance of the cells to the lymphatic vessel.

      We have updated lines 294-298 and 305-309 to include the above explanation.

      (13) Tables 1-4 define migration speeds as agent rules but in the typical CPM, migration speed emerges from random displacements biased by chemotaxis and other effects (like the slope of the cytokine field). How was the speed implemented as a rule while it is typically observable in the model?

      We appreciate your inquiry regarding the implementation of migration speeds. To determine the lambda parameters (Table 7) for each cell type, we tested each in a simplified control simulation with a concentration gradient for the cell to move towards. We tuned the lambda parameters within this simulation until the model outputted cell velocity aligned with the literature reported cell velocity for each cell type (Tables 1-4). We have incorporated clarification on this to lines 177-180.

      (14) Line 312 shows the first equation with number (5), either add eqn. (1-4) or renumber.

      We have revised the equation number.

      (15) Typos: Line 456, "expect M1 cell" should read "except M1 cell".

      Line 452, "thresholds above that diminish fibroblast response (Supplemental Fig 3)." remains unclear, please rephrase.

      Line 473, "at 28." should read "at 28 days.".

      Line 474, is "additive" correct? Was the sum of the individual effects calculated and did that match?

      Line 534, "complexity our model" should read "complexity in our model".

      We have corrected the typos and clarified line 452 (updated line 594) to indicate that the TNF-α concentration threshold results in diminished fibroblast response. We updated terminology line 474 (updated line 512) to indicate that there was a synergistic effect with the combined perturbation.

      (16) Table 7 defines cell target volumes with the same value as their diameter. This enforces a strange cell shape. Should there be brackets to square the value of the cell diameter, e.g. Value=(12µm)^2 ?

      The target volume parameter values were selected to reflect the relative differences in average cell diameter as reported in the literature; however, there are no parameters that directly enforce a diameter for the cells in the CPM formalism separate from the volume. We have observed that these relative cell sizes allow the ABM to effectively reproduce cell behaviors described in the literature. Single cells that are too large in the ABM would be unable to migrate far enough per time step to carry out cell behaviors, and cells that are too small in the CPM would be unstable in the simulation environment and not persist in the simulation when they should. We removed the units for the cell shape values in Table 7 since the target volume is a relative parameter and does not directly represent µm.

      (17) Table 7 gives estimated diffusion constants but they appear to be too high. Please compare them to measured values in the literature, especially for MCP-1, TNF-alpha and IL-10, or relate these to their molecular mass and compare to other molecules like FGF8 (Yu et al. 2009, DOI:10.1038/nature08391).

      We utilized a previously published estimation method (Filion et al. 2004, DOI:10.1152/ajpheart.00205.2004) for estimating cytokine diffusivity within the ECM. This method incorporates the molecular masses and accounts for the combined effects of the collagen fibers and glycosaminoglycans. The paper acknowledged that the estimated value is faster than experimentally determined values, but that this was a result of the less-dense matrix composition which is more reflective of the tissue environment we are simulating in contrast to other reported measurements which were done in different environments. Using this estimation method also allowed us to more consistently define diffusion constants versus using values from the literature (which were often not recorded) that had varied experimental conditions and techniques (such as being in zebrafish embryo Yu et al. 2009, DOI:10.1038/nature08391 as opposed to muscle tissue). This also allowed for recalculation of the diffusivity throughout the simulation as the collagen density changed within the model. Lines 318-326 were updated to help clarify the estimation method.

      (18) Many DOIs in the bibliography (Refs. 7,17,20,31,40,47...153) are wrong and do not resolve because the appended directory names are not allowed in the DOI, just with a journal's URL after resolution.

      Thank you for bringing this to our attention. The incorrect DOIs have been corrected.

      Reviewer #2 (Recommendations For The Authors):

      Minor comments:

      (9) On line 174, the authors say "We used the CC3D feature Flip2DimRatio to control the number of times the Cellular-Potts algorithm runs per mcs." What does this mean? Isn't one monte carlo timestep one iteration of the Cellular Potts model? How does this relate to physical timescales?

      We appreciate your attention to detail and thoughtful question regarding the statement about the use of the CC3D feature Flip2DimRatio. Lines 175-177 were revised to simplify the meaning of Flip2DimRatio. That parameter alters the number of times the Cellular-Potts algorithm is run, which is the limiting factor for cell movement. The physical timescale is kept to a 15-minute timestep but a high Flip2DimRatio allows more flexibility and stability to allow the cells to move faster in one timestep.

      (10) Has the costum matlab script to process histology images into initial conditions been made available?

      The Matlab script along with CC3D code for histology initialization with documentation has been made available with the source code on the following sites:

      SimTK: https://simtk.org/docman/?group_id=2635

      Zendo: https://zenodo.org/records/10403014

      GitHub: https://github.com/mh2uk/ABM-of-Muscle-Regeneration-with-MicrovascularRemodeling

      (11) Equation 5 is provided without a reference or derivation. Where does it come from and what does it mean?

      Thank you for highlighting the diffusion equation and seeking clarification on its origin and significance. Lines 318-326 were revised to clarify where the equation comes from. This is a previously published estimation method that we applied to calculate the diffusivity of the cytokines considering both collagen and glycosaminoglycans.

      (12) Line 326: "For CSA, experimental fold-change from pre-injury was compared with fold-change in model-simulated CSA". Does this step rely on the assumption that the fold change will not depend on the CSA? If so, is this something that is experimentally known, or otherwise, can it be confirmed by simulations?

      We appreciate the opportunity to clarify our rationale. The fold change was used as a method to normalize the model and experiment so that they could be compared on the same scale. Yes, this step relies on the assumption that fold change does not depend on pre-injury CSA. Experimentally it is difficult to determine the impact of initial fiber morphology on altered regeneration time course. This fold-change allows us to compare percent recovery which is a common metric utilized to assess muscle regeneration outcomes experimentally. Line 340-343 was revised to clarify.

      (13) Line 355: "The final passing criteria were set to be within 1 SD for CSA recovery and 2.5 SD for SSC and fibroblast count" Does this refer to the experimental or the simulated SD?

      The model had to fit within those experimental SD. Lines 371-372 was edited to specify that we are referring the experimental SD.

      (14) "Following 8 iterations of narrowing the parameter space with CaliPro, we reached a set that had fewer passing runs than the previous iteration". Wouldn't one expect fewer passing runs with any narrowing of the parameter space? Why was this chosen as the stopping criterion for further narrowing?

      We appreciate your observation regarding the statement about narrowing the parameter space with CaliPro. We started with a wide parameter space, expecting that certain parameters would give outputs that fall outside of the comparable data. So, when the parameter space was narrowed to enrich parts that give passing output, initially the number of passing simulations increased.

      Once we have narrowed the set of possible parameters into an ideal parameter space, further narrowing will cut out viable parameters resulting in fewer passing runs. Therefore, we stopped narrowing once any fewer simulations passed the criteria that they had previously passed with the wider parameter set. Lines 375-379 have been updated to clarify this point.

      (15) Line 516: 'Our model could test and optimize combinations of cytokines, guiding future experiments and treatments." It is my understanding that this is communicated as a main strength of the model. Would it be possible to demonstrate that the sentence is true by using the model to make actual predictions for experiments or treatments?

      This is demonstrated by the combined cytokine alterations in Figure 7 and discussed in lines 509-513. We have also added in a suggested experiment to test the model prediction in lines 691-695.

      (16) Line 456, typo: I think 'expect' should be 'except'.

      Thank you for pointing that out. The typo has been corrected.

    1. Résumé de la vidéo [00:14:07][^1^][1] - [00:37:04][^2^][2]:

      Cette vidéo présente une conférence sur le rôle de l'école en tant que territoire vivant au cœur des valeurs de la République. Les intervenants discutent de l'importance de l'école dans la transmission des valeurs républicaines, surtout dans le contexte des événements récents qui ont touché l'académie.

      Points forts: + [00:14:07][^3^][3] Introduction de la conférence * Accueil par Sébastien Jaibovski, directeur de l'INSP de l'académie de Lille * Présentation du programme et des intervenants * Contextualisation de la conférence dans les événements actuels + [00:17:01][^4^][4] Allocution d'Alain Frugère * Importance de partager et transmettre les valeurs de liberté, égalité et fraternité * Rappel historique des valeurs républicaines depuis la Révolution française * Nécessité de défendre ces valeurs face aux défis contemporains + [00:23:02][^5^][5] Intervention de Madame Lower * L'école comme vecteur de l'égalité des chances et de la lutte contre les inégalités * Rôle de l'école dans la reconnaissance de la capacité de tous les enfants à apprendre * Importance de la liberté d'éducation pour l'émancipation individuelle + [00:30:03][^6^][6] Contextualisation par Sébastien Jaibovski * L'école face au poids des attentes sociales et symboliques * Réflexion sur le rôle des institutions publiques et les moyens alloués * L'école comme lieu de partage et de construction de la citoyenneté Résumé de la vidéo [00:37:07][^1^][1] - [01:02:26][^2^][2]:

      Cette partie de la vidéo aborde le rôle de l'école dans la transmission des valeurs républicaines, en mettant l'accent sur une approche citoyenne. Elle souligne l'importance de l'éducation aux valeurs comme fondement de la République et la nécessité d'une pédagogie qui favorise la pensée critique et la participation active des élèves.

      Points forts: + [00:37:07][^3^][3] L'importance de l'éducation aux valeurs * L'école comme lieu de découverte et de compréhension des valeurs républicaines * La transmission des valeurs comme mission centrale de l'institution scolaire * Les valeurs de liberté, égalité, fraternité, laïcité et refus des discriminations + [00:47:00][^4^][4] Approche citoyenne des valeurs * Refus de l'inculcation, éducation à la liberté * Appel à la pensée critique et à l'interrogation des valeurs * Importance de l'expérience vécue des valeurs dans l'établissement scolaire + [00:57:00][^5^][5] Engagement dans la République * La valeur comme refus du réel et espace pour l'engagement * L'écart entre les valeurs et le réel comme opportunité d'action * L'importance de l'engagement citoyen de chacun dans l'éducation aux valeurs Résumé de la vidéo 01:02:28 - 01:25:00 : La vidéo explore l'évolution de la notion des valeurs de la République dans le discours public, les médias, et le droit français depuis les années 80. Elle examine l'augmentation significative de l'utilisation de cette notion dans les années 80 et 90, sa stabilisation dans les années 2010, et son absence de définition constitutionnelle. La vidéo souligne également l'importance de l'éducation à la laïcité dans les écoles françaises et comment elle est abordée dans les programmes scolaires.

      Points saillants : + [01:02:28][^1^][1] L'évolution de la notion des valeurs de la République * Augmentation dans les publications et les médias depuis les années 80 * Stabilisation dans les années 2010 * Absence de définition constitutionnelle + [01:06:02][^2^][2] L'impact sur le droit de l'éducation et le droit des étrangers * Contribution significative du code de l'éducation et du droit des étrangers * Importance de l'apprentissage et de l'intégration des valeurs + [01:10:01][^3^][3] La définition et l'enseignement de la laïcité * Présence accrue dans les programmes scolaires depuis les années 80 * Nécessité d'expliquer les règles aux élèves * Approche pédagogique pour déconstruire les oppositions + [01:18:34][^4^][4] La perception et la compréhension des élèves sur la laïcité * Bonne maîtrise de la notion par les élèves * Importance de l'éducation à la laïcité pour une société inclusive Résumé de la vidéo [01:25:02][^1^][1] - [01:38:50][^2^][2] :

      Cette partie de la vidéo aborde l'importance de l'éducation à la laïcité et aux valeurs de la République dans les écoles françaises, y compris celles à l'étranger. Elle souligne les défis culturels et les différences dans l'approche de l'enseignement des valeurs universelles.

      Points forts : + [01:25:02][^3^][3] La laïcité dans l'éducation * La laïcité n'est pas une hostilité envers les croyances religieuses * Importance de partager une vision positive de la laïcité * Nécessité d'adapter l'enseignement aux contextes culturels variés + [01:30:10][^4^][4] L'approche citoyenne à l'école * Utilisation de la pensée critique et de la liberté * Transformation des valeurs en réalité concrète pour les élèves * Engagement des élèves envers les valeurs de la République + [01:35:00][^5^][5] L'école, un territoire vivant * L'école est un lieu d'échange et d'apprentissage actif des valeurs républicaines * L'actualité influence l'enseignement et la perception des valeurs * L'importance de l'équilibre entre idéal et réalité dans l'éducation

    1. Five months later, a little over a year after the Code Yellow debacle, Google would make Prabhakar Raghavan the head of Google Search

      author mentions this as the locking in of rotting google search.

    2. n the March 2019 core update to search, which happened about a week before the end of the code yellow, was expected to be “one of the largest updates to search in a very long time. Yet when it launched, many found that the update mostly rolled back changes, and traffic was increasing to sites that had previously been suppressed by Google Search’s “Penguin” update from 2012 that specifically targeted spammy search results, as well as those hit by an update from an August 1, 2018, a few months after Gomes became Head of Search.

      The start of Google search decreasing effectiveness

    1. k12 Daisuke Wakabayashi and Sapna Maheshwari. Advertisers Boycott YouTube After Pedophiles Swarm Comments on Videos of Children. The New York Times, February 2019. URL: https://www.nytimes.com/2019/02/20/technology/youtube-pedophiles.html (visited on 2023-12-07)

      After reading this article I was reminded of assignment 3 where we did bot trolling and I thought of how difficult it would be to code to catch for people not obeying user policies. For instance the comments weren't blatantly explicit, commenting sexually inappropriate comments, but they would contain a string of sexually suggestive emoji or insinuate some form of sexual abuse. At this rate, making sure your platform is safe for children would be extremely difficult. The way we coded the automatic response in assignment 3, we had it recognize a specific sentence but harassment is a spectrum and it's intepreted a lot of the time (making it difficult to detect).

    1. We often think of software development as a ticket-in-code-out business but this is really only a very small portion of the entire thing. Completely independently of the work done as a programmer, there exists users with different jobs they are trying to perform, and they may or may not find it convenient to slot our software into that job. A manager is not necessarily the right person to evaluate how good a job we are doing because they also exist independently of the user–software–programmer network, and have their own sets of priorities which may or may not align with the rest of the system.

      Software development as a conversation

    1. Quantification is ultimately linguistic: it is a form of translation. Most of our descriptions start as ‘ordinary language’, and in some cases, we ‘code’ those descriptions using numbers rather than words

      So you do not think physical quantities exist out of our mind?

    1. a) What is the return period corresponding to an exceedance probability of 99%? b) Determine the annual maxima and rank them from highest to lowest.

      the answers to exercise 7.4a and b should also be done with Python code

    1. Reviewer #1 (Public Review):

      Summary:

      Li and colleagues describe an experiment whereby sequences of dots in different locations were presented to participants while electroencephalography (EEG) was recorded. By presenting fixed sequences of dots in different locations repeatedly to participants, the authors assumed that participants had learned the sequences during the experiment. The authors also trained classifiers using event-related potential (ERP) data recorded from separate experimental blocks of dots presented in a random (i.e., unpredictable) order. Using these trained classifiers, the authors then assessed whether patterns of brain activity could be detected that resembled the neural response to a dot location that was expected, but not presented. They did this by presenting an additional set of sequences whereby only one of the dots in the learned sequence appeared, but not the other dots. They report that, in these sequences with omitted stimuli, patterns of EEG data resembled the visual response evoked by a dot location for stimuli that could be expected, but were not presented. Importantly, this only occurred for an omitted dot stimulus that would be expected to appear immediately after the dot that was presented in these partial sequences.

      This exciting finding complements previous demonstrations of the ability to decode expected (but not presented) stimuli in Blom et al. (2020) and Robinson et al. (2020) that are cited in this manuscript. It suggests that the visual system is able to generate patterns of activity that resemble expected sensory events, approximately at times at which an observer would expect them.

      Strengths:

      The experiment was carefully designed and care was taken to rule out some confounding factors. For example, gaze location was tracked over time, and deviations from fixation were marked, in order to minimise the contributions of saccades to above-chance decoding of dot position. The use of a separate block of dots (with unpredictable locations) to train the classifiers was also useful in isolating visual responses evoked by each dot location independently of any expectations that might be formed during the experiment. A large amount of data was also collected from each participant, which is important when using classifiers to decode stimulus features from EEG data. This careful approach is commendable and draws on best practices from existing work.

      Weaknesses:

      While there was clear evidence of careful experiment design, there are some aspects of the data analysis and results that significantly limit the inferences that can be drawn from the data. Both issues raised here relate to the use of pre-stimulus baselines and associated problems. As these issues are somewhat technical and may not be familiar to many readers, I will try to unpack each line of reasoning below. Here, it should be noted that these problems are complex, and similar issues often go undetected even by highly experienced EEG researchers.

      Relevant to both issues, the authors derived segments of EEG data relative to the time at which each dot was presented in the sequences (or would have appeared when the stimuli were omitted in the partial sequences). Segments were derived that spanned -100ms to 300ms relative to the actual or expected onset of the dot stimulus. The 300ms post-stimulus time period corresponds to the duration of each dot in the sequence (100ms) plus the inter-stimulus interval (ISI) that was 200ms in duration before the next dot appeared (or would be expected to appear in the partial sequences). Importantly, a pre-stimulus baseline was applied to each of these segments of data, meaning that the average amplitude at each electrode between -100ms and 0ms relative to (actual or expected) stimulus onset was subtracted from each segment of data (i.e., each epoch in common EEG terminology). While this type of baseline subtraction procedure is commonplace in EEG studies, in this study design it is likely to cause problematic effects that could plausibly lead to the patterns of results reported in this manuscript.

      First of all, the authors compare event-related potentials (ERPs) evoked by dots in the full as compared to partial sequences, to test a hypothesis relating to attentional tuning. They reported ERP amplitude differences across these conditions, for epochs corresponding to when a dot was presented to a participant (i.e., excluding epochs time-locked to omitted dots). However, these ERP comparisons are complicated by the fact that, in the full sequences, dot presentations are preceded by the presentation of other dots in the sequence. This means that ERPs evoked by the preceding dots in the full sequences will overlap in time with the ERPs corresponding to the dots presented at the zero point in the derived epochs. Importantly, this overlap would not occur in the partial sequence conditions, where only one dot was presented in the sequence. This essentially makes any ERP comparisons between full and partial sequences very difficult to interpret, because it is unclear if ERP differences are simply a product of overlapping ERPs from previously presented dots in the full sequence conditions. For example, there are statistically significant differences observed even in the pre-stimulus baseline period for this ERP analysis, which likely reflects the contributions ERPs evoked by the preceding dots in the full sequences, which are absent in the partial sequences.

      The problems with interpreting this data are also compounded by the use of pre-stimulus baselines as described above. Importantly, the use of pre-stimulus baselines relies on the assumption that the ERPs in the baseline period (here, the pre-stimulus period) do not systematically differ across the conditions that are compared (here, the full vs. partial sequences). This assumption is violated due to the overlapping ERPs issue described just above. Accordingly, the use of the pre-stimulus baseline subtraction can produce spurious effects in the time period after stimulus onset (for examples see Feuerriegel & Bode, 2022, Neuroimage). This also makes it very difficult to meaningfully compare the ERPs following dot stimulus onset in these analyses.

      The second issue relates to the use of pre-stimulus baselines and concerns the key finding reported in the paper: that EEG patterns corresponding to expected but omitted events can be decoded in the partial sequences. In the partial sequences, there are two critical epochs that were derived: One time-locked to the presentation of the dot, and another that was time-locked to 300ms after the dot was presented (i.e. when the next dot would be expected to appear). The latter epoch was used to test for representations of expected, but omitted, stimulus locations.

      For the epochs in which the dots were presented, above-chance decoding can be observed spanning a training time range from around 100-300ms and a testing time range of a similar duration (see the plot in Figure 4b). This plot indicates that, during the time window of around 200-300ms following dot stimulus onset, the position of the dot can be decoded not only from trained classifiers using the same time windows spanning 200-300ms, but also using classifiers trained using earlier time windows of around 100-200ms.

      This is important because the 200-300ms time period after dot onset in the partial sequences is the window used for pre-stimulus baseline subtraction when deriving epochs corresponding to the first successor representation (i.e., the first stimulus that might be expected to follow from the presented dot, but did not actually appear). In other words, the 200-300ms time window from dot onset corresponds to the -100 to 0 ms time window in the first successor epochs. Accordingly, the pattern that is indicative of the preceding, actually presented dot position would be subtracted from the EEG data used to test for the successor representation. Notably, the first successor condition would always be in another visual field quadrant (90-degree rotated or the opposite quadrant) as stated in the methods. In other words, the omitted stimulus would be expected to appear in the opposite vertical and/or horizontal visual hemifield as compared to the previously presented dot in these partial sequences.

      This is relevant because ERPs tend to show reversed polarity across hemifields. For example, a stimulus presented in the right hemifield will have reversed polarity patterns at the same electrode as compared to an equivalent stimulus presented in the left hemifield (e.g., Supplementary Figure 3 in the comparable study of Blom et al., 2020). By subtracting the ERP patterns evoked by the presented dot in the partial sequences during the time period of 200-300ms (corresponding to the -100 to 0ms baseline window), this would be expected to bias patterns of EEG data in the first successor epochs to resemble stimulus positions in opposite hemifields. This could plausibly produce above-chance decoding accuracy in the time windows identified in Figure 5a, where the training time windows broadly correspond to the periods of above-chance decoding during 200-300ms from dot stimulus onset in Figure 4b.

      In other words, the above-chance decoding of the first successor representation may plausibly be an artefact of the pre-stimulus baseline subtraction procedure used when deriving the epochs. This casts some doubt as to whether genuine successor representations were actually detected in the study. Additional tests for successor representations using ERP baselines prior to the presented dot in the partial sequences may be able to get around this, but such analyses were not presented, and the code and data were not accessible at the time of this review.

      Although the study is designed well and a great amount of care was taken during the analysis stage, these issues with ERP overlap and baseline subtraction raise some doubts regarding the interpretability of the findings in relation to the analyses currently presented.

    1. Reviewer #2 (Public Review):

      Summary:

      The authors investigate axonal and synapse development in two distinct visual feature-encoding neurons (VPN), LC4 and LPLC2. They first show that they occupy distinct regions on the GF dendrites, and likely arrive sequentially. Analysis of the VPNs' morphology throughout development, and synaptic gene and protein expression data reveals the temporal order of maturation. Functional analysis then shows that LPLC2 occupancy of the GF dendrites is constrained by LC4 presence.

      Strengths:

      The authors investigate an interesting and very timely topic, which will help to understand how neurons coordinate their development. The manuscript is very well written, and data are of high quality, that generally support the conclusions drawn (but see some comments for Fig. 2 below). A thorough descriptive analysis of the LC4/LPLC2 to GF connectivity is followed by some functional assessment showing that one neuron's occupancy of the GF dendrite depend on another.<br /> The manuscripts uses versatile methods to look at membrane contact, gene and protein expression (using scRNAseq data and state-of-the art genetic tools) and functional neuronal properties. I find it especially interesting and elegant how the authors combine their findings to highlight the temporal trajectory of development in this system.

      Weaknesses:

      After reading the summary, I was expecting a more comprehensive analysis of many VPNs, and their developmental relationships. For a better reflection of the data, the summary could state that the authors investigate *two* visual projection neurons (VPNs) and that ablation *of one cell type of VPNs* results in the expansion of the remaining VPN territory.

      The manuscript is falling a bit short of putting the results into the context of what is known about synaptic partner choice/competition between different neurons during neuronal or even visual system development. Lots of work has been done in the peripheral the visual system, from the Hiesinger lab and others. Both the introduction and the discussion section should elaborate on this.

      The one thing that the manuscript does not unambiguously show is when the connections between LC4 and LPLC2 become functional.

      Figure 2:<br /> Figure 2A-C: I found the text related to that figure hard to follow, especially when talking about filopodia. Overall, life imaging would probably clarify at which time point there really are dynamic filopodia. For this study, high magnification images of what the authors define as filopodia would certainly help.<br /> L137ff: This section talks about filopodia between 24-48 hAPF, but only 36h APF is shown in A, where one could see filopodia. The other time points are shown in B and C, but number of filopodia is not quantified.<br /> L143: "filopodia were still present, but visibly shorter": This is hard to see, and again, not quantified.<br /> L144f: "from 72h APF to eclosion, the volume of GF dendrites significantly decreased": this is not actually quantified, comparisons are only done to 24, 36 and 48 h APF.<br /> Furthermore, 72h APF is not shown here, but in Figure 2D, so either show here, or call this figure panel already?

      Figure 2D/E: to strengthen the point that LC4 and LPLC2 arrive sequentially, it would help to show all time points analyzed in Figure D/E.

      L208: "significant increase ... from 60h APF to 72h APF": according to the figure caption, this comparison is marked by "+" but there is no + in the figure itself.

      Figure 3:<br /> A key point of the manuscript is the sequential arrival of different VPN classes. So then why is the scRNAseq analysis in Figure 3 shown pooled across VPNs? Certainly, the reader at this point is interested in temporal differences in gene expression. The class-specific data are somewhat hidden in Supp. Fig. 9, and actually do not show temporal differences. This finding should be presented in the main data.

      L438: "silencing LC4 by expressing Kir2.1... reduced the GF response": Is this claim backed by some quantification?

      Figure 4K: Do the control data have error bars, which are just too small to see? And what is tested against what? Is blue vs. black quantified as well? What do red, blue, and black asterisks indicate? Please clarify in figure caption.

      Optogenetics is mentioned in methods (in "fly rearing", in the genotypes, and there is an extra "Optogenetics" section in methods), but no such data are shown in the manuscripts. (If the authors have those data, it would be great to know when the VPN>GF connections become functional!)

      Methods:

      Antibody concentrations are not given anywhere and will be useful information for the reader

      Could the authors please give more details on the re-analysis of the scRNAseq dataset? How did you identify cell type clusters in there, for example?

      L785 and L794: I am curious. Why is it informative to mention what was *not* done?

      Custom-written analysis code is mentioned in a few places. Is this code publicly available?

    1. Reviewer #1 (Public Review):

      Summary:

      The manuscript gives a broad overview of how to write NeuroML, and a brief description of how to use it with different simulators and for different purposes - cells to networks, simulation, optimization, and analysis. From this perspective, it can be an extremely useful document to introduce new users to NeuroML.

      However, the manuscript itself seems to lose sight of this goal in many places, and instead, the description at times seems to target software developers. For example, there is a long paragraph on the board and user community. The discussion on simulator tools seems more for developers, not users. All the information presented at the level of a developer is likely to be distracting to readers..

      Strengths:

      The modularity of NeuroML is indeed a great advantage. For example, the ability to specify the channel file allows different channels to be used with different morphologies without redundancy. The hierarchical nature of NeuroML also is commendable, and well illustrated in Figures 2a through c.

      The number of tools available to work with NeuroML is impressive.

      The abstract, beginning, and end of the manuscript present and discuss incorporating NeuroML into research workflows to support FAIR principles.

      Having a Python API and providing examples using this API is fantastic. Exporting to NeuroML from Python is also a great feature.

      Weaknesses:

      Though modularity is a strength, it is unclear to me why the cell morphology isn't also treated similarly, i.e., specify the morphology of a multi-compartmental model in a separate file, and then allow the cell file to specify not only the files containing channels, but also the file containing the multi-compartmental morphology, and then specify the conductance for different segment groups. Also, after pynml_write_neuroml2_file, you would not have a super long neuroML file for each variation of conductances, since there would be no need to rewrite the multi-compartmental morphology for each conductance variation.

      This would be especially important for optimizations, if each trial optimization wrote out the neuroML file, then including the full morphology of a realistic cell would take up excessive disk space, as opposed to just writing out the conductance densities. As long as cell morphology must be included in every cell file, then NeuroML is not sufficiently modular, and the authors should moderate their claim of modularity (line 419) and building blocks (551). In addition, this is very important for downloading NeuroML-compliant reconstructions from NeuroMorpho.org. If the cell morphology cannot be imported, then the user has to edit the file downloaded from NeuroMorpho.org, and provenance can be lost. Also, Figure 2d loses the hierarchical nature by showing ion channels, synapses, and networks as separate main branches of NeuroML.

      In Figure 5, the difference between the core and native simulator is unclear. What is involved in helper scripts? I thought neurons could read NeuroML? If so, why do you need the export simulator-specific scripts? In addition, it seems strange to call something the "core" simulation engine, when it cannot support multi-compartmental models. It is unclear why "other simulators" that natively support NeuroML cannot be called the core. It might be more helpful to replace this sort of classification with a user-targeted description. The authors already state which simulators support NeuroML and which ones need code to be exported. In contrast, lines 369-370 mention that not all NeuroML models are supported by each simulator. I recommend expanding this to explain which features are supported in each simulator. Then, the unhelpful separation between core and native could be eliminated.

      The body of the manuscript has so much other detail that I lose sight of how NeuroML supports FAIR. It is also unclear who is the intended audience. When I get to lines 336-344, it seems that this description is too much detail for the audience. The paragraph beginning on line 691 is a great example of being unclear about who is the audience. Does someone wanting to develop NeuroML models need to understand XSD schema? If so, the explanation is not clear. XSD schema is not defined and instead explains NeuroML-specific aspects of XSD. Lines 734-735 are another example of explaining to code developers (not model developers).

    2. Reviewer #2 (Public Review):

      Summary:

      Developing neuronal models that are shareable, reproducible, and interoperable allows the neuroscience community to make better use of published models and to collaborate more effectively. In this manuscript, the authors present a consolidated overview of the NeuroML model description system along with its associated tools and workflows. They describe where different components of this ecosystem lay along the model development pathway and highlight resources, including documentation and tutorials, to help users employ this system.

      Strengths:

      The manuscript is well-organized and clearly written. It effectively uses the delineated model development life cycle steps, presented in Figure 1, to organize its descriptions of the different components and tools relating to NeuroML. It uses this framework to cover the breadth of the software ecosystem and categorize its various elements. The NeuroML format is clearly described, and the authors outline the different benefits of its particular construction. As primarily a means of describing models, NeuroML also depends on many other software components to be of high utility to computational neuroscientists; these include simulators (ones that both pre-date NeuroML and those developed afterwards), visualization tools, and model databases.

      Overall, the rationale for the approach NeuroML has taken is convincing and well-described. The pointers to existing documentation, guides, and the example usages presented within the manuscript are useful starting points for potential new users. This manuscript can also serve to inform potential users of features or aspects of the ecosystem that they may have been unaware of, which could lower obstacles to adoption. While much of what is presented is not new to this manuscript, it still serves as a useful resource for the community looking for information about an established, but perhaps daunting, set of computational tools.

      Weaknesses:

      The manuscript in large part catalogs the different tools and functionalities that have been produced through the long development cycle of NeuroML. As discussed above, this is quite useful, but it can still be somewhat overwhelming for a potential new user of these tools. There are new user guides (e.g., Table 1) and example code (e.g. Box 1), but it is not clear if those resources employ elements of the ecosystem chosen primarily for their didactic advantages, rather than general-purpose utility. I feel like the manuscript would be strengthened by the addition of clearer recommendations for users (or a range of recommendations for users in different scenarios).

      For example, is the intention that most users should primarily use the core NeuroML tools and expand into the wider ecosystem only under particular circumstances? What are the criteria to keep in mind when making that decision to use alternative tools (scale/complexity of model, prior familiarity with other tools, etc.)? The place where it seems most ambiguous is in the choice of simulator (in part because there seem to be the most options there) - are there particular scenarios where the authors may recommend using simulators other than the core jNeuroML software?

      The interoperability of NeuroML is a major strength, but it does increase the complexity of choices facing users entering into the ecosystem. Some clearer guidance in this manuscript could enable computational neuroscientists with particular goals in mind to make better strategic decisions about which tools to employ at the outset of their work.

    1. Author response:

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

      eLife assessment

      Connelly and colleagues provide convincing genetic evidence that importation from mainland Tanzania is a major source of Plasmodium falciparum lineages currently circulating in Zanzibar. This study also reveals ongoing local malaria transmission and occasional near-clonal outbreaks in Zanzibar. Overall, this research highlights the role of human movements in maintaining residual malaria transmission in an area targeted for intensive control interventions over the past decades and provides valuable information for epidemiologists and public health professionals.

      Reviewer #1 (Public Review):

      Zanzibar archipelago is close to achieving malaria elimination, but despite the implementation of effective control measures, there is still a low-level seasonal malaria transmission. This could be due to the frequent importation of malaria from mainland Tanzania and Kenya, reservoirs of asymptomatic infections, and competent vectors. To investigate population structure and gene flow of P. falciparum in Zanzibar and mainland Tanzania, they used 178 samples from mainland Tanzania and 213 from Zanzibar that were previously sequenced using molecular inversion probes (MIPs) panels targeting single nucleotide polymorphisms (SNPs). They performed Principal Component Analysis (PCA) and identity by descent (IBD) analysis to assess genetic relatedness between isolates. Parasites from coastal mainland Tanzania contribute to the genetic diversity in the parasite population in Zanzibar. Despite this, there is a pattern of isolation by distance and microstructure within the archipelago, and evidence of local sharing of highly related strains sustaining malaria transmission in Zanzibar that are important targets for interventions such as mass drug administration and vector control, in addition to measures against imported malaria.

      Strengths:

      This study presents important samples to understand population structure and gene flow between mainland Tanzania and Zanzibar, especially from the rural Bagamoyo District, where malaria transmission persists and there is a major port of entry to Zanzibar. In addition, this study includes a larger set of SNPs, providing more robustness for analyses such as PCA and IBD. Therefore, the conclusions of this paper are well supported by data.

      Weaknesses:

      Some points need to be clarified:

      (1) SNPs in linkage disequilibrium (LD) can introduce bias in PCA and IBD analysis. Were SNPs in LD filtered out prior to these analyses?

      Thank you for this point. We did not filter SNPs in LD prior to this analysis. In the PCA analysis in Figure 1, we did restrict to a single isolate among those that were clonal (high IBD values) to prevent bias in the PCA. In general, disequilibrium is minimal only over small distances <5-10kb without selective forces at play. This is much less than the average spacing of the markers in the panel. If there is minimal LD, the conclusions drawn on relative levels and connections at high IBD are unlikely to be confounded by any effects of disequilibrium.

      ( 2) Many IBD algorithms do not handle polyclonal infections well, despite an increasing number of algorithms that are able to handle polyclonal infections and multiallelic SNPs. How polyclonal samples were handled for IBD analysis?

      Thank you for this point. We added lines 157-161 to clarify. This section now reads:

      “To investigate genetic relatedness of parasites across regions, identity by descent (IBD) estimates were assessed using the within sample major alleles (coercing samples to monoclonal by calling the dominant allele at each locus) and estimated utilizing a maximum likelihood approach using the inbreeding_mle function from the MIPanalyzer package (Verity et al., 2020). This approach has previously been validated as a conservative estimate of IBD (Verity et al., 2020).”

      Please see the supplement in (Verity et al., 2020) for an extensive simulation study that validates this approach.

      Reviewer #1 (Recommendations For The Authors):

      (3) I think Supplementary Figures 8 and 9 are more visually informative than Figure 2.

      Thank you for your response. We performed the analysis in Figure 2 to show how IBD varies between different regions and is higher within a region than between.

      Reviewer #2 (Public Review):

      This manuscript describes P. falciparum population structure in Zanzibar and mainland Tanzania. 282 samples were typed using molecular inversion probes. The manuscript is overall well-written and shows a clear population structure. It follows a similar manuscript published earlier this year, which typed a similar number of samples collected mostly in the same sites around the same time. The current manuscript extends this work by including a large number of samples from coastal Tanzania, and by including clinical samples, allowing for a comparison with asymptomatic samples.

      The two studies made overall very similar findings, including strong small-scale population structure, related infections on Zanzibar and the mainland, near-clonal expansion on Pemba, and frequency of markers of drug resistance. Despite these similarities, the previous study is mentioned a single time in the discussion (in contrast, the previous research from the authors of the current study is more thoroughly discussed). The authors missed an opportunity here to highlight the similar findings of the two studies.

      Thank you for your insights. We appreciated the level of detail of your review and it strengthened our work. We have input additional sentences on lines 292-295, which now reads:

      “A recent study investigating population structure in Zanzibar also found local population microstructure in Pemba (Holzschuh et al., 2023). Further, both studies found near-clonal parasites within the same district, Micheweni, and found population microstructure over Zanzibar.”

      Strengths:

      The overall results show a clear pattern of population structure. The finding of highly related infections detected in close proximity shows local transmission and can possibly be leveraged for targeted control.

      Weaknesses:

      A number of points need clarification:

      (1) It is overall quite challenging to keep track of the number of samples analyzed. I believe the number of samples used to study population structure was 282 (line 141), thus this number should be included in the abstract rather than 391. It is unclear where the number 232 on line 205 comes from, I failed to deduct this number from supplementary table 1.

      Thank you for this point. We have included 282 instead of 391 in the abstract. We added a statement in the results at lines 203-205 to clarify this point, which now reads:

      “PCA analysis of 232 coastal Tanzanian and Zanzibari isolates, after pruning 51 samples with an IBD of greater than 0.9 to one representative sample, demonstrates little population differentiation (Figure 1A).”

      (2) Also, Table 1 and Supplementary Table 1 should be swapped. It is more important for the reader to know the number of samples included in the analysis (as given in Supplementary Table 1) than the number collected. Possibly, the two tables could be combined in a clever way.

      Thank you for this advice. Rather than switch to another table altogether, we appended two columns to the original table to better portray the information (see Table 1).

      Methods

      (3) The authors took the somewhat unusual decision to apply K-means clustering to GPS coordinates to determine how to combine their data into a cluster. There is an obvious cluster on Pemba islands and three clusters on Unguja. Based on the map, I assume that one of these three clusters is mostly urban, while the other two are more rural. It would be helpful to have a bit more information about that in the methods. See also comments on maps in Figures 1 and 2 below.

      Cluster 3 is a mix of rural/urban while the clusters 2, 4 and 5 are mostly rural. This analysis was performed to see how IBD changes in relation to local context within different regions in Zanzibar, showing that there is higher IBD within locale than between locale.

      (4) Following this point, in Supplemental Figure 5 I fail to see an inflection point at K=4. If there is one, it will be so weak that it is hardly informative. I think selecting 4 clusters in Zanzibar is fine, but the justification based on this figure is unclear.

      The K-means clustering experiment was used to cluster a continuous space of geographic coordinates in order to compare genetic relatedness in different regions. We selected this inflection point based on the elbow plot and based the number to obtain sufficient subsections of Zanzibar to compare genetic relatedness. This point is added to the methods at lines 174-178, which now reads:

      “The K-means clustering experiment was used to cluster a continuous space of geographic coordinates in order to compare genetic relatedness in different regions. We selected K = 4 as the inflection point based on the elbow plot (Supplemental Figure 5) and based the number to obtain sufficient subsections of Zanzibar to compare genetic relatedness.”

      (5) For the drug resistance loci, it is stated that "we further removed SNPs with less than 0.005 population frequency." Was the denominator for this analysis the entire population, or were Zanzibar and mainland samples assessed separately? If the latter, as for all markers <200 samples were typed per site, there could not be a meaningful way of applying this threshold. Given data were available for 200-300 samples for each marker, does this simply mean that each SNP needed to be present twice?

      Population frequency is calculated based on the average within sample allele frequency of each individual in the population, which is an unbiased estimator. Within sample allele frequency can range from 0 to 1. Thus, if only one sample has an allele and it is at 0.1 within sample frequency, the population allele frequency would be 0.1/100 = 0.001. This allele is removed even though this would have resulted in a prevalence of 0.01. This filtering is prior to any final summary frequency or prevalence calculations (see MIP variant Calling and Filtering section in the methods). This protects against errors occurring only at low frequency.

      Discussion:

      (6) I was a bit surprised to read the following statement, given Zanzibar is one of the few places that has an effective reactive case detection program in place: "Thus, directly targeting local malaria transmission, including the asymptomatic reservoir which contributes to sustained transmission (Barry et al., 2021; Sumner et al., 2021), may be an important focus for ultimately achieving malaria control in the archipelago (Björkman & Morris, 2020)." I think the current RACD program should be mentioned and referenced. A number of studies have investigated this program.

      Thank you for this point. We have added additional context and clarification on lines 275-280, which now reads:

      “Thus, directly targeting local malaria transmission, including the asymptomatic reservoir which contributes to sustained transmission (Barry et al., 2021; Sumner et al., 2021), may be an important focus for ultimately achieving malaria control in the archipelago (Björkman & Morris, 2020). Currently, a reactive case detection program within index case households is being implemented, but local transmission continues and further investigation into how best to control this is warranted (Mkali et al. 2023).”

      (7) The discussion states that "In Zanzibar, we see this both within and between shehias, suggesting that parasite gene flow occurs over both short and long distances." I think the term 'long distances' should be better defined. Figure 4 shows that highly related infections rarely span beyond 20-30 km. In many epidemiological studies, this would still be considered short distances.

      Thank you for this point. We have edited the text at lines 287-288 to indicate that highly related parasites mainly occur at the range of 20-30km, which now reads:

      “In Zanzibar, highly related parasites mainly occur at the range of 20-30km.”

      (8) Lines 330-331: "Polymorphisms associated with artemisinin resistance did not appear in this population." Do you refer to background mutations here? Otherwise, the sentence seems to repeat lines 324. Please clarify.

      We are referring to the list of Pfk13 polymorphisms stated in the Methods from lines 146-148. We added clarifying text on lines 326-329:

      “Although polymorphisms associated with artemisinin resistance did not appear in this population, continued surveillance is warranted given emergence of these mutations in East Africa and reports of rare resistance mutations on the coast consistent with spread of emerging Pfk13 mutations (Moser et al., 2021). “

      (9) Line 344: The opinion paper by Bousema et al. in 2012 was followed by a field trial in Kenya (Bousema et al, 2016) that found that targeting hotspots did NOT have an impact beyond the actual hotspot. This (and other) more recent finding needs to be considered when arguing for hotspot-targeted interventions in Zanzibar.

      We added a clarification on this point on lines 335-345, which now reads:

      “A recent study identified “hotspot” shehias, defined as areas with comparatively higher malaria transmission than other shehias, near the port of Zanzibar town and in northern Pemba (Bisanzio et al., 2023). These regions overlapped with shehias in this study with high levels of IBD, especially in northern Pemba (Figure 4). These areas of substructure represent parasites that differentiated in relative isolation and are thus important locales to target intervention to interrupt local transmission (Bousema et al., 2012). While a field cluster-randomized control trial in Kenya targeting these hotspots did not confer much reduction of malaria outside of the hotspot (Bousema et al. 2016), if areas are isolated pockets, which genetic differentiation can help determine, targeted interventions in these areas are likely needed, potentially through both mass drug administration and vector control (Morris et al., 2018; Okell et al., 2011). Such strategies and measures preventing imported malaria could accelerate progress towards zero malaria in Zanzibar.”

      Figures and Tables:

      (10) Table 2: Why not enter '0' if a mutation was not detected? 'ND' is somewhat confusing, as the prevalence is indeed 0%.

      Thank you for this point. We have put zero and also given CI to provide better detail.

      (11) Figure 1: Panel A is very hard to read. I don't think there is a meaningful way to display a 3D-panel in 2D. Two panels showing PC1 vs. PC2 and PC1 vs. PC3 would be better. I also believe the legend 'PC2' is placed in the wrong position (along the Y-axis of panel 2).

      Supplementary Figure 2B suffers from the same issue.

      Thank you for your comment. A revised Figure 1 and Supplemental Figure 2 are included, where there are separate plots for PC1 vs. PC2 and PC1 vs. PC3.

      (12) The maps for Figures 1 and 2 don't correspond. Assuming Kati represents cluster 4 in Figure 2, the name is put in the wrong position. If the grouping of shehias is different between the Figures, please add an explanation of why this is.

      Thank you for this point. The districts with at least 5 samples present are plotted in the map in Figure 1B. In Figure 2, a totally separate analysis was performed, where all shehias were clustered into separate groups with k-means and the IBD values were compared between these clusters. These maps are not supposed to match, as they are separate analyses. Figure 1B is at the district level and Figure 2 is clustering shehias throughout Zanzibar.

      The figure legend of Figure 1B on lines 410-414 now reads:

      “B) A Discriminant Analysis of Principal Components (DAPC) was performed utilizing isolates with unique pseudohaplotypes, pruning highly related isolates to a single representative infection. Districts were included with at least 5 isolates remaining to have sufficient samples for the DAPC. For plotting the inset map, the district coordinates (e.g. Mainland, Kati, etc.) are calculated from the averages of the shehia centroids within each district.”

      The figure legend of Figure 2 on lines 417-425 now reads:

      “Figure 2. Coastal Tanzania and Zanzibari parasites have more highly related pairs within their given region than between regions. K-means clustering of shehia coordinates was performed using geographic coordinates all shehias present from the sample population to generate 5 clusters (colored boxes). All shehias were included to assay pairwise IBD between differences throughout Zanzibar. Pairwise comparisons of within cluster IBD (column 1 of IBD distribution plots) and between cluster IBD (column 2-5 of IBD distribution plots) was done for all clusters. In general, within cluster IBD had more pairwise comparisons containing high IBD identity.”

      (13) Figure 2: In the main panel, please clarify what the lines indicate (median and quartiles?). It is very difficult to see anything except the outliers. I wonder whether another way of displaying these data would be clearer. Maybe a table with medians and confidence intervals would be better (or that data could be added to the plots). The current plots might be misleading as they are dominated by outliers.

      Thank you for this point and it greatly improved this figure. We changed the plotting mechanisms through using a beeswarm plot, which plots all pairwise IBD values within each comparison group.

      (14) In the insert, the cluster number should not only be given as a color code but also added to the map. The current version will be impossible to read for people with color vision impairment, and it is confusing for any reader as the numbers don't appear to follow any logic (e.g. north to south).

      Thank you very much for these considerations. We changed the color coding to a color blind friendly palette and renamed the clusters to more informative names; Pemba, Unguja North (Unguja_N), Unguja Central (Unguja_C), Unguja South (Unguja_S) and mainland Tanzania (Mainland).

      (15) The legend for Figure 3 is difficult to follow. I do not understand what the difference in binning was in panels A and B compared to C.

      Thank you for this point. We have edited the legend to reflect these changes. The legend for Figure 3 on lines 427-433 now reads:

      “Figure 3. Isolation by distance is shown between all Zanzibari parasites (A), only Unguja parasites (B) and only Pemba parasites (C). Samples were analyzed based on geographic location, Zanzibar (N=136) (A), Unguja (N=105) (B) or Pemba (N=31) (C) and greater circle (GC) distances between pairs of parasite isolates were calculated based on shehia centroid coordinates. These distances were binned at 4km increments out to 12 km. IBD beyond 12km is shown in Supplemental Figure 8. The maximum GC distance for all of Zanzibar was 135km, 58km on Unguja and 12km on Pemba. The mean IBD and 95% CI is plotted for each bin.”

      (16) Font sizes for panel C differ, and it is not aligned with the other panels.

      Thank you for pointing this out. Figure 3 and Supplemental Figure 10 are adjusted with matching formatting for each plot.

      (17) Why is Kusini included in Supplemental Figure 4, but not in Figure 1?

      In Supplemental Figure 4, all isolates were used in this analysis and isolates with unique pseudohaplotypes were not pruned to a single representative infection. That is why there are additional isolates in Kusini. The legend for Supplemental Figure 4 now reads:

      “Supplemental Figure 4. PCA with highly related samples shows population stratification radiating from coastal Mainland to Zanzibar. PCA of 282 total samples was performed using whole sample allele frequency (A) and DAPC was performed after retaining samples with unique pseudohaplotypes in districts that had 5 or more samples present (B). As opposed to Figure 1, all isolates were used in this analysis and isolates with unique pseudohaplotypes were not pruned to a single representative infection.”

      (18) Supplemental Figures 6 and 7: What does the width of the line indicate?

      The sentence below was added to the figure legends of Supplemental Figures 6 and 7 and the legends of each network plot were increased in size:

      “The width of each line represents higher magnitudes of IBD between pairs.”

      (19) What was the motivation not to put these lines on the map, as in Figure 4A? This might make it easier to interpret the data.

      Thank you for this comment. For Supplemental Figure 8 and 9, we did not put these lines that represent lower pairwise IBD to draw the reader's attention to the highly related pairs between and within shehias.

      Reviewer #2 (Recommendations For The Authors):

      (1) There is a rather long paragraph (lines 300-323) on COI of asymptomatic infections and their genetic structure. Given that the current study did not investigate most of the hypotheses raised there (e.g. immunity, expression of variant genes), and the overall limited number of asymptomatic samples typed, this part of the discussion feels long and often speculative.

      Thank you for your perspective. The key sections highlighted in this comment, regarding immunity and expression of variant genes, were shortened. This section on lines 300-303 now reads:

      “Asymptomatic parasitemia has been shown to be common in falciparum malaria around the globe and has been shown to have increasing importance in Zanzibar (Lindblade et al., 2013; Morris et al., 2015). What underlies the biology and prevalence of asymptomatic parasitemia in very low transmission settings where anti-parasite immunity is not expected to be prevalent remains unclear (Björkman & Morris, 2020).”

      (2) As a detail, line 304 mentions "few previous studies" but only one is cited. Are there studies that investigated this and found opposite results?

      Thank you for this comment. We added additional studies that did not find an association between clinical disease and COI. These changes are on lines 303-308, which now reads:

      “Similar to a few previous studies, we found that asymptomatic infections had a higher COI than symptomatic infections across both the coastal mainland and Zanzibar parasite populations (Collins et al., 2022; Kimenyi et al., 2022; Sarah-Matio et al., 2022). Other studies have found lower COI in severe vs. mild malaria cases (Robert et al., 1996) or no significant difference between COI based on clinical status (Earland et al. 2019; Lagnika et al. 2022; Conway et al. 1991; Kun et al. 1998; Tanabe et al. 2015)”

      (3) Table 2: Percentages need to be checked. To take one of several examples, for Pfk13-K189N a frequency of 0.019 for the mutant allele is given among 137 samples. 2/137 equals to 0.015, and 3/137 to 0.022. 0.019 cannot be achieved. The same is true for several other markers. Possibly, it can be explained by the presence of polyclonal infections. If so, it should be clarified what the total of clones sequenced was, and whether the prevalence is calculated with the number of samples or number of clones as the denominator.

      Thank you for this point. We mistakenly reported allele frequency instead of prevalence. An updated Table 2 is now in the manuscript. The method for calculating the prevalence is now at lines 148-151:

      “Prevalence was calculated separately in Zanzibar or mainland Tanzania for each polymorphism by the number of samples with alternative genotype calls for this polymorphism over the total number of samples genotyped and an exact 95% confidence interval was calculated using the Pearson-Klopper method for each prevalence.”

  4. inst-fs-iad-prod.inscloudgate.net inst-fs-iad-prod.inscloudgate.net
    1. “ShouldIsingadifferentsong?”Iask.“No,hijo.No singing.Allyoudoisjumpandcount,jumpandcount,okay? Everydayyoutraining,youtryingtojumpalittlemore.”

      Throughout Jaime Cortez’s short story Gordro, we find instances of where Gordo is assimilating to the mainstream image of a boy with masculine interests. This need of being masculine is pushed by his father and Cesar. The passage highlighted how Gordo quickly code switched from singing a girly song to doing something masculine hence counting. Although his father scolded him on counting, Gordo could’ve gone back to singing but he did not. As his first instinct to sing a song about being a princess. But Gordo wants to become more like or have his fathers approval, Gordo wants to please his fathers so he crosses a boundary to be accepted.

    1. if 00:05:22 you've looked at the code in your company you'll realize that wow I've got millions of millions of lines of code there and I have more than a sneaking suspicion that a lot of that code is 00:05:34 actually in my way it doesn't represent the actual bang per line of code that we'd expect from a higher-level language

      sneaking suspicion

      lot code in my way

      no bang per line of code

      // We do not get much out of higher-level languages because people do not appreciate that "that advantage of high-level languages is notational rather then computatioal" John Allen - Anatomy of Lisp

      I learn this 40 years ago.

      I only realise now that the problem with Programming Languages and with Software "Enginnering#2 which is nothing of the sort

      The lesson from the first NATO conference on the Software Crisis

      ended up identifying that it is not angineering what we doe

      that that was what was needed but clearly out of sight

      yet the pretence persisted and we were kidding ourselves that what we do is ingineering

      The reason is that programming languages constituted in terms of the means of primitives, means of abstractions and means of combinations,

      where what is needed is to raise th level of expressive power of our notations by building everything that is needed into a coherent complex self-orgamzing system that supports such complex way of arrticulatinon that the task calls for

      Articulating intent to the point where it is amenable to the pun to actuallyr un on a machine

    1. Author response:

      Reviewer #3 (Public Review):

      Software UX design is not a trivial task and a point-and-click interface may become difficult to use or misleading when such design is not very well crafted. While Phantasus is a laudable effort to bring some of the out-of-the box transcriptomics workflows closer to the broader community of point-and-click users, there are a number of shortcomings that the authors may want to consider improving.

      Thank you for such an in-depth review. We really appreciate this feedback and have tried to address all of the concerns in the new version of Phantasus.

      Here I list the ones I found running Phantasus locally through the available Bioconductor package:

      (1) The feature of loading in one click one of the thousands of available GEO datasets is great. However, one important use of any such interfaces is the possibility for the users to analyze his/her own data. One of the standard formats for storing tables of RNA-seq counts are CSV files. However, if we try to upload from the computer a CSV file with expression data, such as the counts stored in the file GSE120660_PCamerge_hg38.csv.gz from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120660, a first problem is that the system does not recognize that the CSV file is compressed. A second problem is that it does not recognize that values are separated by commas, the very original CSV format, giving a cryptic error "columnVector is undefined". If we transform the CSV format into tab-separated values (TSV) format, then it works, but this constitutes already a first barrier for the target user of Phantasus.

      Thank you for highlighting this issue of file formats support. We acknowledge the commonality of CSV and CSV.gz files in gene expression analysis. As a response, we have updated our data loading procedure to support these file formats. Moreover, the most recent version of our web application is able to recognize gzip-archived file in any of supported table formats: GCT, TSV, CSV and XLSX.

      (2) Many RNA-seq processing pipelines use Ensembl annotations, which for the purpose of downstream interpretation of the analysis, need to be translated into HUGO gene symbols. When I try to annotate the rows to translate the Ensembl gene identifiers, I get the error

      "There is no AnnotationDB on server. Ask administrator to put AnnotationDB sqlite databases in cacheDir/annotationdb folder"

      Thank you for revealing this issue. Indeed, locally installed instances of the Phantatus might lose some functionality in absence of some auxiliary files. For example, gene annotation mapping is unavailable without annotation databases. Previously, the user had to perform additional setup steps to unlock a few features, which might be confusing and unclear. In order to overcome this we have revised significantly the installation procedure. Newly added ‘setupPhantasus’ function is able to create all necessary configuration files and provides an interactive dialog with the user that helps to load all necessary data files from our official cache mirror (https://alserglab.wsutl.edu/files/phantasus/minimal-cache/). Docker-based installation follows the same approach, however it is configured to install everything by default. Thus, with help of the new installation procedure locally installed Phantasus now has the whole functionality available at the official mirrors. The comprehensive installation description is now available at https://ctlab.github.io/phantasus-doc/installation.

      (3) When trying to normalize the RNA-seq counts, there are no standard options such as within-library (RPKM, FPKM) or between-library (TMM) normalization procedures.

      Appreciating your feedback, we've expanded the available normalization options in the updated version of Phantasus. We added support for TMM normalization as suggested by the edgeR package and voom normalization from the limma package. However, certain strategies like RPKM/FPKM or TPM rely on gene-specific effective lengths, which are challenging to infer without protocol and alignment details. As Phantasus operates on gene expression matrices and doesn't execute alignment steps, the implementation of these normalization seems infeasible. On the other hand, if the user has the matrix with FPKM or TPM gene values (for example from a core facility), such a matrix can be loaded into Phantasus and used for the analysis.

      If I take log2(1+x) a new tab is created with the normalized data, but it's not easy to realize what happened because the tab has the same name as the previous one and while the colors of the heatmap changed to reflect the new scale of the data, this is quite subtle. This may cause that an unexperienced user to apply the same normalization step again on the normalized data. Ideally, the interface should lead the user through a pipeline, reducing unnecessary degrees of freedom associated with each step.

      Thank you for your comment. Indeed our approach to create a new tab for each alteration to the expression values preserving the name might be the source of confusion for a user. On the other hand, generating informative tab names without overwhelming users with too much detail is also challenging. As a compromise we have an option for the user to manually rename the tab. Still, we agree that this remains an area for improvement. We also consider it to be a part of a larger issue: for example, the loaded data can already be log-scaled, so that even one round of log-scale transformation in Phantasus would be incorrect. Accordingly, we are exploring ways to address this issue in the future by adding automated checks for the tools or, as you suggested, implementing stricter pipelines.

      (4.4) Phantasus allows one to filter out lowly-expressed genes by averaging expression of genes across samples and discarding/selecting genes using some cutoff value on that average. This strategy is fine, but to make an informed decision on that cutoff it would be useful to see a density plot of those averages that would allow one to identify the modes of low and high expression and decide the cutoff value that separates them.

      Thank you for the suggestion. Indeed a density plot might help users to make informed decisions during gene filtration. We have added such a plot into the ‘Plot/Chart’ tool as a ‘histogram’ chart type.

      It would be also nice to have an interface to the filterByExpr() function from the edgeR package, which provides more control on how to filter out lowly-expressed genes.

      Thank you for proposing the inclusion of an interface for the filterByExpr() function from the edgeR package. In the recent update we have incorporated filterByExpr() as part of the voom normalization tool. For now, for simplicity, we have decided to keep only the default parameter values. However, we will explore the addition of the dedicated filtering tool in the future.

      (5) When attempting a differential expression (DE) analysis, a popup window appears saying:

      "Your dataset is filtered. Limma will apply to unfiltered dataset. Consider using New Heat Map tool."

      One of the main purposes of filtering lowly-expressed genes is mainly to conduct a DE analysis afterwards, so it does not make sense that the tool says that such an analysis will be done on the unfiltered dataset. The reference to the "New Heat Map tool" is vague and unclear where should the user look for that other tool, without any further information or link.

      Thank you for highlighting this issue. We agree that the message in the popup window and the default action were confusing. In response to your feedback, we've updated the default behavior of our DE tools to automatically use the filtered data in a new tab. Additionally, we've clarified the warning message to ensure a better understanding of this process.

      (6) The DE analysis only allows for a two-sample group comparison, which is an important limitation in the question we may want to address. The construction of more complex designs could be graphically aided by using the ExploreModelMatrix Bioconductor package (Soneson et al, F1000Research, 2020).

      Indeed, the ability to create complex designs and various comparisons is important for many applications for gene expression analysis. Accordingly, in the latest Phantasus version, we've introduced an advanced design feature for the DE analysis, enabling the utilization of multiple column annotations for the design matrix. Combined with the existing ability to create new annotations, this update facilitates the setup of diverse design matrices. While at the moment we do not allow setting a complex contrast, we hope that the current interface will cover most of the differential expression use cases.

      (7) When trying to perform a pathway analysis with FGSEA, I get the following error:

      "Couldn't load FGSEA meta information. Please try again in a moment. Error: cannot open the connection In call: file(file, "rt")

      We hope that this issue should be resolved after we have implemented a more streamlined setup process. Among others, the new approach aims to eliminate the unexpected absence of metafiles in local installations. The latest Phantasus package version explicitly prompts the user to load necessary additional files automatically during the initial run, reducing options for an invalid setup.

      Finally, there have been already some efforts to approach R and Bioconductor transcriptomics pipelines to point-and-click users, such as iSEE (Rue-Albrecht et al, 2018) and GeneTonic (Marini et al, 2021) but they are not compared or at least cited in the present work.

      Indeed, our comparison was focused toward tools that offer non-programmatic functionalities for gene expression data analysis. While tools like iSEE and GeneTonic are adept at visualizing data and hold their own in providing extensive abilities, they do necessitate additional data preparation using R, distinguishing them from the specific scope of tools we assessed.

      One nice features of these two tools that I missed in Phantasus is the possibility of generating the R code that produces the analysis performed through the interface. This is important to provide a way to ensure the reproducibility of the analyses performed.

      The ability to generate R code within tools like these indeed aids in ensuring analysis reproducibility. Moreover, we have previously attempted implementing this functionality in Phantasus, however it proved to be hard to do in a useful fashion due to potential complex interactions between user and the client-side part of Phantasus. Nevertheless, we acknowledge the significance of such a feature and aim to introduce it in the future.

    1. Usage is a two steps process: First, a schema is constructed using the provided types and constraints: const schema = Joi.object({ a: Joi.string() }); Note that joi schema objects are immutable which means every additional rule added (e.g. .min(5)) will return a new schema object.

      Sure! Imagine you're building a structure, like a house. Before you start building, you need a plan, right? That's what a schema is in programming – it's like your blueprint.

      So, in this code, we're using a tool called Joi to make our blueprint. We want our structure to have a specific type, like a string, and maybe some rules, like a minimum length.

      Here's a simple explanation:

      1. Constructing the Schema: First, we make our blueprint using Joi. In this case, we're saying we want something called a to be a string. Think of it like saying, "In my house blueprint, I want a room called a, and it should be a string."

      javascript const schema = Joi.object({ a: Joi.string() });

      1. Adding Rules (Constraints): Now, let's say we want to add a rule to our blueprint, like saying that our room a must be at least 5 characters long. When we add rules, Joi gives us back a new blueprint with that rule added. It's like updating our original blueprint with extra details.

      javascript const schemaWithRule = schema.keys({ a: Joi.string().min(5) });

      So, in simple terms, we're creating a plan for our data, and then we can add rules to that plan to make sure our data follows certain conditions.

    1. 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

      Seleit and colleagues set out to explore the genetics of developmental timing and tissue size by mapping natural genetic variation associated with segmentation clock period and presomitic mesoderm (PSM) size in different species of Medaka fish. They first establish the extent of variation between five different Medaka species of in terms of organismal size, segmentation rate, segment size and presomitic mesoderm size, among other traits. They find that these traits are species-specific but strongly correlated. In a massive undertaking, they then perform developmental QTL mapping for segmentation clock period and PSM size in a set of ~600 F2 fish resulting from the cross of Orizyas sakaizumii (Kaga) and Orizyas latipes (Cab). Correlation between segmentation period and segment size was lost among the F2s, indicating that distinct genetic modules control these traits. Although the researchers fail to identify causal variants driving these traits, they perform proof of concept perturbations by analyzing F0 Crispants in which candidate genes were knocked out. Overall, the study introduces a completely new methodology (QTL mapping) to the field of segmentation and developmental tempo, and therefore provides multiple valuable insights into the forces driving evolution of these traits.

      Major comments: - The first sentence in the abstract reads "How the timing of development is linked to organismal size is a longstanding question". It is therefore disappointing that organismal size is not reported for the F2 hybrids. Was larval length measured in the F2s? If so, it should be reported. It is critical to understand whether the correlation between larval size and segmentation clock period is preserved in F2s or not, therefore determining if they represent a single or separate developmental modules. If larval length data were not collected, the authors need to be more careful with their wording.

      The question the reviewer raises here is indeed a very relevant one, and a question that we also were curious about ourselves. While it was not possible (logistically) to grow the 600 F2 fish to adulthood, we did measure larval length in a subset of F2 hatchling (n=72) to ask precisely the question the reviewer raises here. Our results (new Supplementary Figure 5) show that the correlation between larval length and segmentation timing (which we report across the Oryzias species) is absent in the F2s. This indeed argues that the traits represent separate developmental modules.

      In the current version of the paper, organismal size is often incorrectly equated to tissue size (e.g. PSM size, segment size). For example, in page 3 lines 33-34, the authors state that faster segmentation occurred in embryos of smaller size (Fig. 1D). However, Fig. 1D shows correlation between segmentation rate and unsegmented PSM area. The appropriate data to show would be segmentation rate vs. larval or adult length.

      The reviewer is correct. We have now linked the data more clearly to data we show in Supplementary Figure 1, which shows that adult length and adult mass are strongly correlated (S1A) and that adult mass is in turn strongly correlated with segmentation rate in the different Oryzias species (S1B). Additionally main Figure 1B shows that larval length is correlated with PSM length. We have corrected the main text to reflect these relationships more clearly.

      • Is my understanding correct in that the her7-venus reporter is carried by the Cab F0 but not the Kaga F0? Presumably only F2s which carried the reporter were selected for phenotyping. I would expect the location of the reporter in the genome to be obvious in Figure 3J as a region that is only Cab or het but never Kaga. Can the authors please point to the location of the reporter?

      The reviewer is correct. Indeed the location of our her7-venus KI is on chromosome 16 and the recombination patterns on this chromosome overwhelmingly show either Hom Cab (green) or Het Cab/Kaga (Black). This is expected as we selected fish carrying the her7-venus KI for phenotyping.

      • devQTL mapping in this study seems like a wasted opportunity. The authors perform mapping only to then hand pick their targets based on GO annotations. This biases the study towards genes known to be involved in PSM development, when part of the appeal of QTL mapping is precisely its unbiased nature and the potential to discover new functionally relevant genes. The authors need to better justify their rationale for candidate prioritization from devQTL peaks. The GO analysis should be shown as supplemental data. What criteria were used to select genes based on GO annotations?

      We have now commented on these valid points and outlined our rationale in more detail in the text (page 4, lines 20-30). Our rationale now also includes selection of differentially expressed genes (n=5 genes) that fall within segmentation timing devQTL hits (for more details see below). Essentially, while we indeed finally focused on the proof of principle using known genes, these genes were previously not known to play a role in either setting the timing of segmentation or controlling the size of the PSM. Hence, we do think our strategy demonstrates the "the potential to discover new functionally relevant genes", even though the genes themselves had been involved overall in somitogenesis. We added the GO analysis as supplemental data as requested (new Supplementary Figure 7E).

      • Analysis of the predicted functional consequence of divergent SNPs (Fig. S6B, F) is superficial. Among missense variants, which genes harbor the most deleterious mutations? Which missense variants are located in highly conserved residues? Which genes carry variants in splice donors/acceptors? Carefully assessing the predicted effect of SNPs in coding regions would provide an alternative, less biased approach to prioritize candidate genes.

      We now included our analysis of SNPs based on the Variant effect predictor (VEP) tool from ensembl. This analysis does rank the predicted severity of the SNP on protein structure and function (Impact: low, moderate, high) and does annotate which variants can affect splice donors/acceptors. The VEP analysis for both phenotypes is now added to the manuscript as supplemental data (new Supplementary Data S2, S5).

      • Another potential way to prioritize candidate genes within devQTL peaks would be to use the RNA seq data. The authors should perform differential expression analysis between Kaga and Cab RNA-seq datasets. Do any of the differentially expressed genes fall within the devQTL peaks?

      As suggested we have performed this additional experiment and report the RNAseq differential analysis in new Supplement Figure 7C-D. The analysis revealed 2606 differentially expressed genes in the PSM between Kaga and Cab, five of which were candidate genes from the devQTL analysis. We now tested all of these (5 in total, 4 new and 1 previously targeted adgrg1) for segmentation timing by CRISPR/Cas9 KO in the her7-venus background, none of which showed a timing phenotype (new Supplementary Figure 7F-F'). We provide the complete set of results in new Supplementary Figure 7 , Supplementary Data file 3 (DE-genes), all data were deposited on publicly available repository Biostudies under accession number: E-MTAB-13927.

      • The use of crispants to functionally test candidate genes is inappropriate. Crispants do not mimic the effect of divergent SNPs and therefore completely fail to prove causality. While it is completely understandable that Medaka fish are not amenable to the creation of multiple knock-in lines where divergent SNPs are interconverted between species, better justification is needed. For instance, is there enough data to suggest that the divergent alleles for the candidate genes tested are loss of function? Why was a knockout approach chosen as opposed to overexpression?

      We agree with the reviewer that we do not address the causality of SNPs with the CRISPR/Cas9 KO approach we followed. And medaka does offer the genome editing capabilities to create tailored sequence modifications. So in principle, this can be done. In practice, however, we reasoned that any given SNP will contribute only partially to the observed phenotypes and combinatorial sequence edits are simply very laborious given the current state of the art in genome editing technologies. We therefore opted for an alternative proof of principle approach that aims to "to discover new functionally relevant genes", not SNPs.

      -Along the same line, now that two candidate genes have been shown to modulate the clock period in crispants (mespb and pcdh10b), the authors should at least attempt to knock in the respective divergent SNPs for one of the genes. This is of course optional because it would imply several months of work, but it would significantly increase the impact of the study.

      As above, this is in principle the correct rationale to follow though very time, cost and labour intensive. It is for the later practical consideration that we decided not to follow this option.

      Minor Comments - It would be highly beneficial to describe the ecological differences between the two Medaka species. For example, do the northern O. sakaizumii inhabit a colder climate than the southern O. latipes? Is food more abundant or easily accessible for one species compared to the other? What, if anything, has been described about each species' ecology?

      There are indeed differences in the ecology of both species, with the northern O.sakaizumii inhabiting a colder climate than the southern O. latipes. In addition, it is known that the breeding season is shorter in the north than the south, and also there is the fact that northern species have been shown to have a faster juvenile growth rate than southern species. While it would be premature to link those ecological factors to the timing differences we observe, we can certainly speculate. A line to this effect has been added to the main text (Page 5, line 28-30).

      • The authors describe two different methods for quantifying segmentation clock period (mean vs. intercept). It is still unclear what is the difference between Figs. 3A (clock period), S4A (mean period) and S4B (intercept period). Is clock period just mean period? Are the data then shown twice? How do Fig. 3A and S4A differ?

      The clock period shown in all the main figures is the intercept period, which was also used for the devQTL analysis. Both measurements (mean and intercept) are indeed highly correlated and we include both in supplement for completeness.

      • devQTL as shorthand for developmental QTL should be defined in page 4 line 1 (where the term first appears), not later in line 12 of the same page.

      Noted and corrected, we thank the reviewer for spotting this error.

      • Python code for period quantification should be uploaded to Github and shared with reviewers.

      All period quantification code that was used in this study was obtained from the publicly available tool Pyboat (https://www.biorxiv.org/content/10.1101/2020.04.29.067744v3). All code that is used in PyBoat is available from the Github page of the creator of the tool (https://github.com/tensionhead/pyBOAT). Both are linked in the references and materials and methods sections.

      • RNA-seq data should be uploaded to a publicly accessible repository and the reviewer token shared with reviewers.

      We have uploaded all RNA-sequencing Data to public repository BioStudies under accession numbers : E-MTAB-13927, E-MTAB-13928. This information is now also added to material and methods in the manuscript text.

      Why are the maintenance (27-28C) vs. imaging (30C) temperatures different?

      Medaka fish have a wide range of temperatures they can physiologically tolerate, i.e. 17-33. The temperature 30C was chosen for practical reasons, i.e. a slightly faster developmental rate enables higher sample throughput in overnight real-time imaging experiments.

      • For Crispants, control injections should have included a non-targeting sgRNA control instead of simply omitting the sgRNA.

      We agree a non-targeting sgRNA control can be included, though we choose a different approach. For clarity, we now also include a control targeting Oca2, a gene involved in the pigmentation of the eye to probe for any injection related effect on timing and PSM size. As expected, 3 sgRNAs + Cas9 against Oca2 had no impact on timing or PSM size. This data is now shown in new Supplementary Figure 9 F-G'.

      It is difficult to keep track of the species and strains. It would be most helpful if Fig. S1 appeared instead in main figure 1.

      We agree and included an overview of the phylogenetic relationship of all species and their geographical locales in new Figure 1 A-B.

      Significance

      • The study introduces a new way of thinking about segmentation timing and size scaling by considering natural variation in the context of selection. This new framing will have an important impact on the field.
      • Perhaps the most significant finding is that the correlation between segment timing and size in wild populations is driven not by developmental constraints but rather selection pressure, whereas segment size scaling does form a single developmental module. This finding should be of interest to a broad audience and will influence how researchers in the field approach future studies.
      • It would be helpful to add to the conclusion the author's opinion on whether segmentation timing is a quantitative trait based on the number of QTL peaks identified.
      • The authors should be careful not to assign any causality to the candidate genes that they test in crispants.
      • The data and results are generally well-presented, and the research is highly rigorous.
      • Please note I do have the expertise to evaluate the statistical/bioinformatic methods used for devQTL mapping.

      Reviewer #2

      Evidence, reproducibility and clarity

      Seleit et al. investigate the correlation between segment size, presomitic mesoderm and the rhythm of periodic oscilations in the segmentation clock of developing medaka fish. Specifically, they aim to identify the genetic determinants for said traits. To do so, they employ a common garden approach and measure such traits in separate strains (F0) and in interbreedings across two generations (F1 and F2). They find that whereas presomitic mesoderm and segment size are genetically coupled, the tempo of her7 oscilations it is not. Genetic mapping of the F0 and F2 progeny allows them to identify regions associated to said traits. They go on an perturb 7 loci associated to the segmentation clock and X related to segment size. They show that 2/7 have a tempo defect, and 2/ affect size.

      Major comments: The conclusions are convincing and well supported by the data. I think the work could be published as is in its current state, and no additional experiments that I can think of are needed to support the claims in the paper.

      Minor comments: - The authors could provide a more detailed characterization of the identified SNPs associated to the clock and to PSM size. For the segmentation clock, the authors identify 46872 SNPs, most of which correspond to non-coding regions and are associated to 57 genes. They narrow down their approach to those expressed in the PSM of Cab Kaga. Was the RNA selected from F1 hybrids? I wonder if this would impact the analysis for tempo and or size in any way, as F2 are derived from these, and they show broader variability in the clock period than the F0 and F1 fishes.

      The RNA was obtained from the pure F0 strains and we have now extended this analysis by deep bulk-RNA sequencing and differential gene expression analysis. As indicated also to reviewer 1, this revealed 2606 differentially expressed genes in the unsegmented tails of Kaga and Cab embryos, some of which occurred in devQTL peaks. Based on this information we expanded our list of CRISPR/Cas9 KOs by targeting all differentially expressed genes (5 in total, 4 new and 1 previously targeted) for segmentation timing, none of which showed a timing phenotype (new Supplementary figure 7C-D). We provide the complete set of results in new Supplementary Figure 7, Supplementary Data file 3 (DE-genes). All data were deposited on publicly available repository Biostudies under accession number: E-MTAB-13927.

      It would be good if the authors could discuss if there were any associated categories or overall functional relationships between the SNPs/genes associated to size. And what about in the case of timing?

      In the case of PSM size there were no clear GO terms or functional relationships between the genes that passed the significance threshold on chromosome 3.

      For the 35 genes related to segmentation timing, there were a number of GO enrichment terms directly related to somitogenesis. We have included the GO analysis in the new Supplementary Figure 7E.

      • Have any of the candidate genes or regulatory loci been associated to clock defects (57) or segment size (204) previously in the literature?

      To the best of our knowledge none of the genes have been associated with clock or PSM size defects so far. It might be worthwhile using our results to probe their function in other systems enabling higher throughput functional analysis, such as newly developed organoid models.

      • When the authors narrow down the candidate list, it is not clear if the genes selected as expressed in the PSM are tissue specific. If they are, I wonder if genes with ubiquitous expression would be more informative to investigate tempo of development more broadly. It would be good if the authors could specifically discuss this point in the manuscript.

      We have not addressed the spatial expression pattern of the 35 identified PSM genes in this study, so we cannot speculate further. But the reviewer raises an important point, how timing of individual processes (body axis segmentation) are linked at organismal scale is indeed a fundamental, additional, question that will be addressed in future studies, indeed the in-vivo context we follow here would be ideal for such investigations.

      Can the authors speculate mechanistically why mespb or pchd10b accelerates the period of her7 oscillations?

      While we do not have a mechanistic explanation yet, an additional experiment we performed, i.e. bulk-RNAsequencing on WT and mespb mutant tails, provided additional insight, we now added this data to the manuscript . This analysis revealed 808 differentially expressed genes between wt and mespb mutants. Interestingly, many of these affected genes are known to be expressed outside of the mespb domain, i.e. in the most posterior PSM (i.e. tbxt, foxb1,msgn1, axin2, fgf8, amongst others). This indicates that the effect of mespb downregulation is widespread and possibly occurs at an earlier developmental stage. This requires more follow up studies. This data is now shown in new Supplementary figure 9A, Supplementary Data file S4. We now comment on this point in the revised manuscript.

      • Are there any size difference associated to the functionally validated clock mutants?

      We addressed this point directly and added this analysis as supplementary Figure 9H-H'. While pcdh10b mutants do not show any detectable difference in PSM size, we find a small, statistically significant reduction in PSM size (area but not length) in mespb mutants. All this data is now included in the revised manuscript.

      -Ref 27 shows a lack of correlation between body size and the segmentation period in various species of mammals. The work supports their findings, and it would be good to see this discussed in the text.

      We are not certain how best to compare our in-vivo results in externally developing fish embryos to in-vitro mammalian 2-D cell cultures. In our view, the correlation of embryo size, larval and adult size that we find in Oryzias might not necessarily hold in mammalian species, which would make a comparison more difficult. We do cite the work mentioned so the reader is pointed towards this interesting, complementary literature.

      Significance

      The work is quite remarkable in terms of the multigenerational genetic analysis performed. The authors have analysed >600 embryos from three separate generations to obtain quantitative data to answer their question (herculean task!). Moreover, they have associated this characterization to specific SNPs. Then, to go beyond the association, they have generated mutant lines and identified specific genes associated to the traits they set out to decipher.

      To my knowledge, this is the first project that aims to identify the genetic determinants for developmental timing. Recent work on developmental timing in mammals has focused on interspecies comparisons and does not provide genetic evidence or insight into how tempo is regulated in the genome. As for vertebrates, recent work from zebrafish has profiled temperature effects on cell proportions and developmental timing. However, the genetic approach of this work is quite elegant and neat.

      Conceptually, it is quite important and unexpected that overall size and tempo are not related. Body size, lifespan, basal metabolic rates and gestational period correlate positively and we tend to think that mechanistically they would all be connected to one another. This paper and Lazaro et al. 2023 (ref 27) are one of the first in which this preconception is challenged in a very methodical and conclusive manner. I believe the work is a breakthrough for the field and this work would be interesting for the field of biological timing, for the segmentation clock community and more broadly for all developmental biologists.

      My field is quantitative stem cell biology and I work on developmental timing myself, so I acknowledge that I am biased in the enthusiasm for the work. It should be noted that as an expert on the field, I have identified instances where other work hasn't been as insightful or well developed in comparison to this piece. It is also worth noting that I am not an expert in fish development, phylogenetic studies or GWAS analyses, so I am not capable to asses any pitfalls in that respect.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

      __Summary: __

      This manuscript explores the temporal and spatial regulation of vertebrate body axis development and patterning. In the early stages of vertebrate embryo development, the axial mesoderm (presomitic mesoderm - PSM) undergoes segmentation, forming structures known as somites. The exact genetic regulation governing somite and PSM size, and their relationship to the periodicity of somite formation remains unclear.

      To address this, the authors used two evolutionarily closely related Medaka species, Oryzias sakaizumii and Oryzias latipes, which, although having distinct characteristics, can produce viable offspring. Through analysis spanning parental (generation F0) and offspring (generations F1 and F2) generations, the authors observed a correlation between PSM and somite size. However, they found that size scaling does not correlate with the timing of somitogenesis.

      Furthermore, employing developmental quantitative trait loci (devQTL) mapping, the authors identified several new candidate loci that may play a role during somitogenesis, influencing timing of segment formation or segment size. The significance of these loci was confirmed through an innovative CRISPR-Cas9 gene editing approach.

      This study highlights that the spatial and temporal aspects of vertebrate segmentation are independently controlled by distinct genetic modular mechanisms.

      __Major comments: __

      1) In the main text page 3, lines 11 and 12, the authors state that the periodicity of the embryo clock of the F1 generation is the intermediate between the parental F0 lineages. However, the authors look only at the periodicity of the Cab strain (Oryzias latipes) segmentation clock. The authors should have a reporter fish line for the Kaga strain (Oryzias sakaizumii) to compare the segmentation clock of both parental strains and their offspring. Since it could be time consuming and laborious, I advise to alternatively rephrase the text of the manuscript.

      We agree a careful distinction between segment forming rate (measured based on morphology) and clock period (measured using the novel reporter we generated) is essential. We show that both measures correlate very well in Cab, in both F0 and F1 and F2 carrying the Cab allele. For Kaga F0, we indeed can only provide the rate of somite formation, which nevertheless allows comparison due to the strong correlation to the clock period we have found. We have rephrased the text accordingly.

      2) It is evident that only a few F0 and F1 animals were analyzed in comparison with the F2 generation. Could the authors kindly explain whether and how this could bias or skew the observed results?

      We provide statistical evidence through the F-test of equality that the variances between the F0, F1 and F2 samples are equal. Additionally if we sub-sample and separate the F2 data into groups of 100 embryos (instead of all 638) we get the same distribution of the F2s. We therefore believe that this is sufficient evidence against a bias or skew in the results.

      3) It would be interesting to create fish lines with the validated CRISPR-Cas9 gene manipulations in different genetic contexts (Cab or Kaga) to analyze the true impact on the segmentation clock and/or PSM & somite sizes.

      We agree with the reviewer this would in principle be of interest indeed, please see our response to reviewer 1 earlier.

      4) Please add the results of the Go Analysis as supplementary material.

      We have added the GO analysis in new Supplementary Figure 7E.

      __Minor comments: __

      1) In the main text, page 2, line 29, Supplementary Figure 1D should be referenced.

      We have added a clearer phylogeny and geographical location of the different species in new Figure 1 A-B. And reference it at the requested location.

      2) In the main text, page 2, line 32, the authors refer to Figure 1B, but it should be 1C.

      We have corrected the information.

      3) Regarding the topic "Correlation of segmentation timing and size in the Oryzias genus" the authors should also give information on the total time of development of the different Oryzias species, as well as the total number of formed somites.

      We follow this recommendation and have added this information in new Supplementary Figure 5. We also now include segment number measured in F2 embryos. We indeed view segmentation rate as a proxy for developmental rate, which however needs to be distinguished from total developmental time. The latter can be measured for instance by quantifying hatching time, which we did. These measurements show that Kaga, Cab and O.hubbsi embryos kept at constant 28 degrees started hatching on the same day while O.minutillus and O.mekongensis embryos started hatching one day earlier. We have not included this data in the manuscript because we think a distinction should be made between rate of development and total development time.

      4) In Figures 3A and B, please add info on the F1 lines for comparison.

      The information on F1 lines is provided in Supplementary Figure 3

      5) Supplementary Figures 2F shows that the generation F1 PSM is similar to Cab F0, and not an intermediate between Kaga F0 and Cab F0. This is interesting and should be discussed.

      We show that the F1 PSM is indeed closer to the PSM of Cab than it is to the Kaga PSM. This is indeed intriguing and we have now commented on this point directly in the text.

      6) Supplementary Figures 6C to H are not mentioned either in the main text or in the extended information. Please add/mention accordingly.

      We have added references to both in the text

      7) The order of Supplementary Figure 8 E to H and A to D appears to be not correct and not following the flow of the text. Please update/correct accordingly.

      We have updated the text accordingly.

      8) The authors should choose between "Fig.", "Fig", "fig.", "fig" or "Figure". All 'variants' can be found in the text.

      Noted, and updated. Fig. is used for main figures and fig. is used for supplementary figures.

      9) The color scheme of several figures (graphs with colored dots) should be revised. Several appear to be difficult to discern and analyze.

      We have enhanced the colours and increased the font on the figure panels. The colour panel was chosen to be colour-blind friendly.

      10) Please address/discuss following questions: What are the known somitogenesis regulating genes in Medaka? How do they correlate with the new candidates?

      The candidates we found and tested had not been implicated in regulating the tempo of segmentation or PSM size, while for some a role in somite formation had been previously established, hence the enrichment in GO analysis Somitogenesis.

      Reviewer #3 (Significance (Required)):

      General assessment:

      This interesting manuscript describes a novel approach to study and find new players relevant to the regulation of vertebrate segmentation. By employing this innovative methodology, the authors could elegantly demonstrate that the segmentation clock periodicity is independent from the sizes of the PSM and forming somites. The authors were further able to find new genes that may be involved in the regulation of the segmentation clock periodicity and/or the size of the PSM & somites. A limitation of this study is the fact that the results mainly rely on differences between the two species. The integration of additional Medaka species would be beneficial and may help uncover relevant genes and genetic contexts.

      Advance:

      To my best knowledge this is the first time that such a methodology was employed to study the segmentation clock and axial development. Although the topic has been extensively studied in several model organisms, such as mice, chicken, and zebrafish, none of them correlated the size of the embryonic tissues and the periodicity of the embryo clock. This study brings novel technological and functional advances to the study of vertebrate axial development.

      Audience:

      This work is particularly interesting to basic researchers, especially in the field of developmental biology and represents a fresh new approach to study a core developmental process. This study further opens the exciting possibility of using a similar methodology to investigate other aspects of vertebrate development. It is a timely and important manuscript which could be of interest to a wider scientific audience and readership.

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      Referee #1

      Evidence, reproducibility and clarity

      Seleit and colleagues set out to explore the genetics of developmental timing and tissue size by mapping natural genetic variation associated with segmentation clock period and presomitic mesoderm (PSM) size in different species of Medaka fish. They first establish the extent of variation between five different Medaka species of in terms of organismal size, segmentation rate, segment size and presomitic mesoderm size, among other traits. They find that these traits are species-specific but strongly correlated. In a massive undertaking, they then perform developmental QTL mapping for segmentation clock period and PSM size in a set of ~600 F2 fish resulting from the cross of Orizyas sakaizumii (Kaga) and Orizyas latipes (Cab). Correlation between segmentation period and segment size was lost among the F2s, indicating that distinct genetic modules control these traits. Although the researchers fail to identify causal variants driving these traits, they perform proof of concept perturbations by analyzing F0 Crispants in which candidate genes were knocked out. Overall, the study introduces a completely new methodology (QTL mapping) to the field of segmentation and developmental tempo, and therefore provides multiple valuable insights into the forces driving evolution of these traits.

      Major comments:

      • The first sentence in the abstract reads "How the timing of development is linked to organismal size is a longstanding question". It is therefore disappointing that organismal size is not reported for the F2 hybrids. Was larval length measured in the F2s? If so, it should be reported. It is critical to understand whether the correlation between larval size and segmentation clock period is preserved in F2s or not, therefore determining if they represent a single or separate developmental modules. If larval length data were not collected, the authors need to be more careful with their wording. In the current version of the paper, organismal size is often incorrectly equated to tissue size (e.g. PSM size, segment size). For example, in page 3 lines 33-34, the authors state that faster segmentation occurred in embryos of smaller size (Fig. 1D). However, Fig. 1D shows correlation between segmentation rate and unsegmented PSM area. The appropriate data to show would be segmentation rate vs. larval or adult length.
      • Is my understanding correct in that the her7-venus reporter is carried by the Cab F0 but not the Kaga F0? Presumably only F2s which carried the reporter were selected for phenotyping. I would expect the location of the reporter in the genome to be obvious in Figure 3J as a region that is only Cab or het but never Kaga. Can the authors please point to the location of the reporter?
      • devQTL mapping in this study seems like a wasted opportunity. The authors perform mapping only to then hand pick their targets based on GO annotations. This biases the study towards genes known to be involved in PSM development, when part of the appeal of QTL mapping is precisely its unbiased nature and the potential to discover new functionally relevant genes. The authors need to better justify their rationale for candidate prioritization from devQTL peaks. The GO analysis should be shown as supplemental data. What criteria were used to select genes based on GO annotations?
      • Analysis of the predicted functional consequence of divergent SNPs (Fig. S6B, F) is superficial. Among missense variants, which genes harbor the most deleterious mutations? Which missense variants are located in highly conserved residues? Which genes carry variants in splice donors/acceptors? Carefully assessing the predicted effect of SNPs in coding regions would provide an alternative, less biased approach to prioritize candidate genes.
      • Another potential way to prioritize candidate genes within devQTL peaks would be to use the RNA seq data. The authors should perform differential expression analysis between Kaga and Cab RNA-seq datasets. Do any of the differentially expressed genes fall within the devQTL peaks?
      • The use of crispants to functionally test candidate genes is inappropriate. Crispants do not mimic the effect of divergent SNPs and therefore completely fail to prove causality. While it is completely understandable that Medaka fish are not amenable to the creation of multiple knock-in lines where divergent SNPs are interconverted between species, better justification is needed. For instance, is there enough data to suggest that the divergent alleles for the candidate genes tested are loss of function? Why was a knockout approach chosen as opposed to overexpression?
      • Along the same line, now that two candidate genes have been shown to modulate the clock period in crispants (mespb and pcdh10b), the authors should at least attempt to knock in the respective divergent SNPs for one of the genes. This is of course optional because it would imply several months of work, but it would significantly increase the impact of the study.

      Minor Comments

      • It would be highly beneficial to describe the ecological differences between the two Medaka species. For example, do the northern O. sakaizumii inhabit a colder climate than the southern O. latipes? Is food more abundant or easily accessible for one species compared to the other? What, if anything, has been described about each species' ecology?
      • The authors describe two different methods for quantifying segmentation clock period (mean vs. intercept). It is still unclear what is the difference between Figs. 3A (clock period), S4A (mean period) and S4B (intercept period). Is clock period just mean period? Are the data then shown twice? How do Fig. 3A and S4A differ?
      • devQTL as shorthand for developmental QTL should be defined in page 4 line 1 (where the term first appears), not later in line 12 of the same page.
      • Python code for period quantification should be uploaded to Github and shared with reviewers.
      • RNA-seq data should be uploaded to a publicly accessible repository and the reviewer token shared with reviewers.
      • Why are the maintenance (27-28C) vs. imaging (30C) temperatures different?
      • For Crispants, control injections should have included a non-targeting sgRNA control instead of simply omitting the sgRNA.
      • It is difficult to keep track of the species and strains. It would be most helpful if Fig. S1 appeared instead in main figure 1.

      Significance

      • The study introduces a new way of thinking about segmentation timing and size scaling by considering natural variation in the context of selection. This new framing will have an important impact on the field.
      • Perhaps the most significant finding is that the correlation between segment timing and size in wild populations is driven not by developmental constraints but rather selection pressure, whereas segment size scaling does form a single developmental module. This finding should be of interest to a broad audience and will influence how researchers in the field approach future studies.
      • It would be helpful to add to the conclusion the author's opinion on whether segmentation timing is a quantitative trait based on the number of QTL peaks identified.
      • The authors should be careful not to assign any causality to the candidate genes that they test in crispants.
      • The data and results are generally well-presented, and the research is highly rigorous.
      • Please note I do have the expertise to evaluate the statistical/bioinformatic methods used for devQTL mapping.
    1. Multi-factor authentication. December 2023. Page Version ID: 1188119370. URL: https://en.wikipedia.org/w/index.php?title=Multi-factor_authentication&oldid=1188119370 (visited on 2023-12-06).

      Multifactor authentication is a system where a site will only allow access to the site when 2 or more pieces of authenticating evidence are presented. this may come in the form of a password along with a code sent through SMS or email. This allows for a site to be more secure when multiple factors of authentication are presented to avoid unwanted access.

    1. But stepping back even further, one can only see this imagined software as an enhancement to Latour’s larger model of interplay in his actor-network theory, a theory that does not need software or special equipment to exist. The activity in a spatial environment is not reliant on the digital environment. It may be enhanced by a code/text-based software, but a spatial software or protocol can be any platform that establishes variables for space as information
    2. We are not accustomed to the idea that non-human, inanimate objects possess agency and activity, just as we are not accustomed to the idea that they can carry information unless they are endowed with code/text-based information technologies. While accepting that a technology like mobile telephony has become the world’s largest shared platform for information exchange, we are perhaps less accustomed to the idea of space as a technology or medium of information—undeclared information that is not parsed as text or code. Indeed, the more ubiquitous code/text-based information devices become, the harder it is to see spatial technologies and networks that are independent of the digital. Few would look at a concrete highway system or an electrical grid and perceive agency in their static arrangement. Agency might only be ascribed to the moving cars or the electrical current. Spaces and urban arrangements are usually treated as collections of objects or volumes, not as actors. Yet the organization itself is active. It is doing something, and changes in the organization constitute information. Even so, the idea that information is carried in activity, or what we might call active form, must still struggle against many powerful habits of mind.
    1. He said no way - using haskell he was convinced he could implement anything I could implement, faster and better and with less code. We didn't test the claim - but I still wonder - is he right?

      Both are correct. This aspirational ideal - crafting a program with a small, tight, and beautiful core - is possible if a program is intended to be an artifact.

      One definition of an artifact - a program designed to serve a specific use case in a specific point of time forever. It is crafted then left untouched.

      By contrast, software to most businesses is a living, breathing beast - we have strict time constraints to implement, modify, adjust to, and tack on features or the business dies. This business of crafting a perfect, beautiful core would require a rewrite of the entire system every time you intended to add a new feature or reinvestigate the model.

      Software engineering is, then, a process of compromising - continuously declaring that edge X is the one least likely to shoot yourself in the foot.

    1. es.redirect([status,] path) Redirects to the URL derived from the specified path, with specified status, a positive integer that corresponds to an HTTP status code. If not specified, status defaults to 302 "Found". res.redirect('/foo/bar') res.redirect('http://example.com') res.redirect(301, 'http://example.com') res.redirect('../login') Redirects can be a fully-qualified URL for redirecting to a different site: res.redirect('http://google.com') Redirects can be relative to the root of the host name. For example, if the application is on http://example.com/admin/post/new, the following would redirect to the URL http://example.com/admin: res.redirect('/admin') Redirects can be relative to the current URL. For example, from http://example.com/blog/admin/ (notice the trailing slash), the following would redirect to the URL http://example.com/blog/admin/post/new. res.redirect('post/new') Redirecting to post/new from http://example.com/blog/admin (no trailing slash), will redirect to http://example.com/blog/post/new. If you found the above behavior confusing, think of path segments as directories (with trailing slashes) and files, it will start to make sense. Path-relativ

      https://expressjs.com/en/5x/api.html#res.redirect:~:text=res.redirect(%5Bstatus,redirect%20vulnerabilities.

    1. la place de la chiropraxi citons Wikipédia la Fédération Mondiale de chirropractique 00:11:12 WFC est membre de l'OMS depuis 1993 la chiropratique est reconnue comme profession de santé complémentaire par le Comité international olympique depuis 00:11:25 1992 la chiropratique est en 2009 la 3e profession de santé aux États-Unis après la médecine générale et la chirurgie dentaire en France la chyopraxie est 00:11:37 reconnue depuis la loi du 4 mars 2002 cette pratique est rattachée au code de la santé publique par l'article 75 comme profession de santé fin de citations de 00:11:48 Wikipédia
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      Reply to the reviewers

      Manuscript number: RC-2023-02218R

      Corresponding author(s): Steven, McMahon

      1. General Statements [optional]

      *We were pleased to receive the encouraging critiques and very much appreciate the Reviewer's specific comments and suggestions. In this revised version of our manuscript, we have made a number of substantive additions and modifications in response to these comments/suggestions. We hope you agree that the study is now improved to the point where it is suitable for publication. *

      2. Point-by-point description of the revisions

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

      Summary This study describes efforts to characterize differences in the roles of the two related human decapping factors Dcp1a and Dcp1b by assessing mRNA decay and protein associations in knockdown and knockout cell lines. The authors conclude that these proteins are non-redundant based on the observations that loss of DCp1a versus Dcp1b impacts the decapping complex (interactome) and the transcriptome differentially.

      Major comments • While the experiments appear to be well designed and executed and the data of generally high quality, the conclusions are drawn without sufficient consideration for the fact that these two proteins form a heterotrimeric complex. The authors assume that there are distinct homotrimeric complexes rather than a single complex with both proteins in. Homotrimers may have new/different functions not normally seen when both proteins are expressed. Thus while it is acceptable to infer that the functions of these two proteins within the decapping complex are distinct, it is not clear that they act separately, or that complexes naturally exist without one or the other. A careful evaluation of the relative ratios of Dcp1a and b overall and in decapping complexes would be informative if the authors want to make stronger statements about the roles of these two factors.

      RESPONSE: Thank you for this valuable comment. We have substantially edited the manuscript to incorporate these points. Examples include a detailed analysis of iBAQ values for the DDX6, DCP1a, and DCP1b interactomes (which now allows us to estimate the ratios of DCP1a and DCP1b in these complexes) and cellular fractionation to interrogate complex integrity (using Superose 6).

      • The concept of buffering is not adequately introduced and the interpretation of observations that RNAs with increased half life do not show increased protein abundance - that Dcp1a/b are involved in transcript buffering is nebulous. In order to support this interpretation, the mRNA abundances (NOT protein abundances) should be assessed, and even then, there is no way to rule out indirect effects. RESPONSE: Thank you for this comment. In the revised version of the manuscript, we introduced the concept of transcript buffering at an earlier stage as one of the potential explanations for our findings. We were also able to use a new algorithm (grandR) to estimate half-lives and synthesis rates from our data. These new data add strength to the argument that DCP1a and DCP1b are linked to transcript buffering pathways.

      • It might be interesting to see what happens when both factors are depleted to get an idea of the overall importance of each one.

      RESPONSE: In our work we tried to emphasize the differences between the two paralogs. We believe that doing double knockout or knockdown would mask the distinct impacts of the paralogs. In data not included in this study, we have shown that cells lacking both DCP1a and DCP1b are viable. We did check PARP cleavage in the CRISPR generated cell pools of DCP1a KO, DCP1b KO, and the double KO. The WB measuring the PARP cleavage is shown in the supplemental material (Supplementary Material: Replicates)

      • The algorithms etc used for data analysis should be included at the time of publication. Version number and settings used for SMART to define protein domains, and webgestalt should be indicated

      RESPONSE: We apologize for this oversight. Version number and settings used for the webtools (SMART, Webgestalt) are now included. The analysis pipeline for half-lives and synthesis rates estimation as well as all the files and the code needed to generate the figures in the paper are available on zenodo (https://zenodo.org/records/10725429).

      • Statistical analysis is not provided for the IP experiments, the number of replicates performed is not indicated and quantification of KD efficiency are not provided.

      RESPONSE: The number of replicates performed in each experiment is now clearly indicated and quantifications of knockdown efficiency are provided (Supplemental Figure 3A and 3B, Figure 3A, Figure 3B).

      • The possibility that the IP Antibody interferes with protein-protein interactions is not mentioned.

      RESPONSE: Thank you for this comment. The revised manuscript includes a discussion of the antibody epitope location and the potential for impact on protein-protein interactions.

      Minor comments • P4 - "This translational repression of mRNA associated with decapping can be reversed, providing another point at which gene expression can be regulated (21)" - implies that decapping can be reversed or that decapped RNAs are translated. I don't think this is technically true.

      RESPONSE: There have been several studies that document the reversal of decapping. These findings are summarized in the following reviews.

      Schoenberg, D. R., & Maquat, L. E. (2009). Re-capping the message. Trends in biochemical sciences, 34(9), 435-442.

      Trotman, J. B., & Schoenberg, D. R. (2019). A recap of RNA recapping. Wiley Interdisciplinary Reviews: RNA, 10(1), e1504.

      • P11 - how common is it for higher eukaryotes to have 2 DCP genes? *RESPONSE: Metazoans have 2 DCP1 genes. *

      • Fig S1 - says "mammalian tissues" in the text but the data is all human. The statement that "expression analyses revealed that DCP1a and DCP1b have concordant rather than reciprocal expression patterns across different mammalian tissues (Supplemental Figure 1)" is a bit misleading as no evidence for correlation or anti-correlation is provided. Also co-expression is not strong support for the idea that these genes have non-redundant functions. Both genes are just expressed in all tissues - there's no evidence provided that they are concordantly expressed. In bone marrow it may be worth noting that one is high and the other low - i.e. reciprocal. *RESPONSE: We appreciate this comment. We have corrected the interpretation of the aforementioned dataset. We have also incorporated a more detailed discussion in the text of the paper. As the Reviewer pointed out, there are a subset of tissues where their expression appears to be reciprocal. *

      • Fig 1A - it is not clear what the different colors mean. Does Sc DCP1 have 1 larger EVH or 2 distinct ones. Are the low complexity regions in Sc DCP2 the SLiMs. *RESPONSE: Thank you for this comment. We have corrected this ambiguity to reflect that Sc DCP1 has one EVH1 domain that is interconnected by a flexible hinge. The low-complexity regions typically contain short linear motifs (SLIMs), however, not all low-complexity regions have been verified to contain them. In the figure, only low-complexity regions are shown. The text of the paper refers only to verified SLIMs . *

      • P11 - why were HCT116 cells selected? RESPONSE: HCT116 cells are an easily transfectable human cell line and have been widely used in biochemical and molecular studies, including studies of mRNA decapping (see references below). Since decapping is impacted by viral proteins we avoided the use of other commonly used cell models such as HEK293T or HeLa.

      https://pubmed.ncbi.nlm.nih.gov/?term=decapping+hct116&sort=date&size=200

      • Fig 1B - what are the asterisks by the RNA names? Might be worth noting that over-expression of DCP1b reduced IP of DCP1a. There's no quantification and no indication of the number of times this experiment was repeated. Data from replicates and quantification of the knockdown efficiency in each replicate would be nice to see. *RESPONSE: Thank you for this comment. Asterisks indicate that those bands were from a second gel, as DCP1a and DCP1b run at approximately the same molecular weight. We have now included a note in our figure legend to indicate this. The knockdown efficiency is provided (Figure 3 and Supplemental Figure 3). We also noted the number of replicas for each IP in figure 1. The replicas are provided as supplementary material (Supplementary Materials: Replicates). *

      • Fig 1C/1D - why are there 3 bands in the DCP1a blot? Quantification of the IP bands is necessary to say whether there is an effect or not of over-expression/KO. RESPONSE: The additional bands in DCP1a blots are background. When we stained the whole blot for DCP1a, in cells which with complete DCP1a KO cells (clone A3), these bands still appear (Supplementary Material: Validation of the KO clones). Quantifications of the bands in the overexpression experiments is now provided.

      • Fig 3 - is it possible that differences are due to epitope positions for the antibodies used for IP? RESPONSE: We do not believe so. DCP1a antibody binds roughly 300-400 residues on DCP1a, and DCP1b antibody binds around Val202. Antibodies therefore do not bind DCP1a or DCP1b low-complexity regions (which are largely responsible for interacting with the decapping complex interactome). Antibodies don't bind the EVH1 domains or the trimerization domain, which are needed for their interaction with DCP2 and each other.

      • Fig 5A - the legend doesn't match the colors in the figure. It is not clear how the pRESPONSE: Thank you for this comment. We have corrected this issue in the revised version of the paper. High-confidence proteins are those with pRESPONSE: Thank you for this comment. We have corrected this issue in the revised version of the paper.*

      • There are a few more recent studies on buffering that should be cited and more discussion of this in the introduction is necessary if conclusions are going to be drawn about buffering. *RESPONSE: We have included a discussion of transcript buffering in the introduction. *

      • The heatmaps in figure 2 are hard to interpret. RESPONSE: To clarify the heatmaps, we included a more detailed description in the figure legends, have enlarged the heatmaps themselves, and have added more extensive labeling.

      Reviewer #1 (Significance (Required)):

      • Strengths: The experiments appear to be done well and the datasets should be useful for the field. • Limitations: The results are overinterpreted - different genes are affected by knocking down one or other of these two similar proteins but this does not really tell us all that much about how the two proteins are functioning in a cell where both are expressed. • Audience: This study will appeal most to a specialized audience consisting of those interested in the basic mechanisms of mRNA decay. Others may find the dataset useful. • This study might complement and/or be informed by another recent study in BioRXiv - https://doi.org/10.1101/2023.09.04.556219 • My field of expertise is mRNA decay - I am qualified to evaluate the findings within the context of this field. I do not have much experience of LC-MS-MS and therefore cannot evaluate the methods/analysis of this part of the study.

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

      The authors provide evidence that Dcp1a and Dcp1b - two paralogous proteins of the mRNA decapping complex - may have divergent functions in a cancer cell line. In the first part, the authors show that interaction of Dcp2 with EDC4 is diminished upon depletion of Dcp1a but not affected by depletion of Dcp1b. The results have been controlled by overexpression of Dcp1b as it may be limiting factor (i.e. expression levels too low to compensate for depletion of Dcp1a reduced interaction with EDC3/4 while depletion of Dcp1b lead to opposite and increase interactions). They then defined the protein interactome of DDX6 in parental and Dcp1a or Dcp1b depleted cells. Here, the authors show some differential association with EDC4 again, which is along results shown in the first part. The authors further performed SLAM-seq and identified subsets of mRNA whose decay rates are common but also different upon depletion with Dcp1a and Dcp1b. Interestingly, it seems that Dcp1a preferentially targets mRNAs for proteins regulating lymphocyte differentiation. To further test whether changes in RNA decay rates are also reflected at the protein levels, they finally performed an MS analysis with Dcp1a/b depleted cells. However no significant overlap with mRNAs showing altered stability could be observed; and the authors suggested that the lack of congruence reflects translational repression.

      Major comments: 1. While functional difference between Dcp1a and Dcp1b are interesting and likely true, there are overinterpretations that need correction or further evidence for support. Sentences like "DCP1a regulates RNA cap binding proteins association with the decapping complex and DCP1b controls translational initiation factors interactions (Figure 2E)" sound misleading. While differential association with proteins has been recognised with MS-data, it does not necessary implement an active process of control/regulation. To make the claim on 'control/regulation', and inducible system or introduction of mutants would be required.

      RESPONSE: This set of comments were particularly useful in helping us refine the presentation of our findings. We have edited our manuscript to be more specific about the limits of our data.

      1. The MS analysis is not clearly described in the text and it is unclear how authors selected high-confident proteins. The reader needs to consider the supplemental tables to find out what controls were used. Furthermore, the authors should show correlation plots of MS data between replicates. For instance, there seems to be limited correlation among some of the replicates (e.g. Dcp1b_ko3 sample, Fig. 2c). Any explanation in this variance?

      *RESPONSE: We have now included a clear description of how all high-confidence proteins were selected in the Methods and Results sections. The revised manuscript also includes a more thorough description of the controls used and the number of replicates for individual experiments. The PCA plots have now been included where appropriate. The variance in this sample is likely technical. *

      1. GO analysis for the proteome analysis should consider the proteome and not the genome as the background. The authors should also indicate the corrected P-values (multiple testing) FDRs.

      *RESPONSE: Webgestalt uses a reference set of IDs to recognize the input IDs, and it does not use it for the background analysis in the classical sense. We repeated a subset of our proteome analyses using the 'genome-protein coding' as background and obtained the same result as in our original analysis. All ontology analyses now include raw p-values and/or FDRs when appropriate. *

      1. Fig 2E. The figures display GO enrichments needs better explanation and additional data can be added. The enrichment ratio is not explained (is this normalised?) and p-values and FDRs, number of proteins in respective GO category should be added. *RESPONSE: More thorough explanations of the GO enrichments are now included. The supplemental data contains all p-values (raw and adjusted), as well as the number of proteins in each GO category. The Enrichment ratio is normalized and contains information about the number of proteins that are redundant in multiple groups. GO Ontology analyses are now displayed with p-values and/or FDR values, and in this case the enrichment ratio contains information regarding the number of proteins found in our input set and the number of expected proteins in the GO group. The network analysis shows the FDR values and the number of proteins found in the groups compared. *

      Minor: 5. These studies were performed in a colorectal carcinoma cell line (HCT116). The authors should justify the choice of this specialised cell line. Furthermore, one wonders whether similar conclusions can be drawn with other cell lines or whether findings are specific to this cancer line.

      RESPONSE: The study that is currently in pre-print in BioRxiv (https://doi.org/10.1101/2023.09.04.556219*) utilized HEK293Ts and found similar results to ours when examining the various relationships between the core decapping core members. *

      1. Fig. 1B. It is unclear what DCP1b* refers to? There are bands of different size that are not mentioned by the authors - are those protein isoforms or what are those referring to? A molecular marker should be added to each Blots. Uncropped Western images and markers should be provided in the Supplement. *RESPONSE: The asterisk indicates that these images came from a second western blot gel (DCP1a and DCP1b have a similar molecular weight and cannot be probed on the same membrane). Uncropped western blot images and markers (as available) are provided in the supplement. *

      2. MS data submitted to public repository with access. No. indicated in the manuscript.

      RESPONSE: MS data is submitted as supplementary datasets to the paper. It contains the analyzed data as well as the LCMSMS output. We are in the process of submitting the raw LSMSMS data to a public repository.

      Fig 3. A Venn Diagram displaying the overlap of identified proteins should be added. GO analysis should be done considering the proteome as background (as mentioned above).

      *RESPONSE: A Venn diagram showing the overlap among the proteins identified is now included in the revised version. *

      Reviewer #2 (Significance (Required)):

      Overall, this is a large-scale integrative -omics study that suggest functional difference between Dcp1 paralogues. While it seems clear that both paralogous have some different functions and impact, there are overinterpretations in place and further evidence would to be provided to substantiate conclusions made in the paper. For instance, while the interactions with Dcp2/Ddx6 in the absence of Dcp1a,b with EDC4/3 may be altered (Fig. 1, 2), the functional implications of this changed associations remains unresolved and not further discussed. As such, it remains somehow disconnected with the following experiments and compromises the flow of the study. The observed differences in decay-rates for distinct functionally related sets of mRNAs is interesting; however, it remains unclear whether those are direct or rather indirect effects. This is further obscured by the absence of any correlation to changes in protein levels, which the authors interpreted as 'transcriptional buffering'. In this regard, it is puzzling how the authors can make a statement about transcriptional buffering? While this may be an interesting aspect and concept of the discussion, there is no primary data showing such a functional impact.

      As such, the study is interesting as it claims functional differences between DCP1a/b paralogous in a cancer cell line. Nevertheless, I am not sure how trustful the MS analysis and decay measurements are as there is not further validation. It woudl be interesting if the authors could go a bit further and draw some hypothesis how the selectivty could be achieved i.e interaction with RNA-binding proteins that may add some specificity towards the target RNAs for differential decay. As such, the study remains unfortunately rather descriptive without further functional insight.

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

      Review on "Non-redundant roles for the human mRNA decapping cofactor paralogs DCP1a and DCP1b" by Steven McMahon and co-workers mRNA decay is a critical step in the regulation of gene expression. In eukaryotes, mRNA turnover typically begins with the removal of the poly(A) tail, followed by either removal of the 5' cap structure or exonucleolytic 3'-5' decay catalyzed by the exosome. The decapping enzyme DCP2 forms a complex with its co-activator DCP1, which enhances decapping activity. Mammals are equipped with two DCP1 paralogs, namely DCP1a and DCP1b. Metazoans' decapping complexes feature additional components, such as enhancer of decapping 4 (EDC4), which supports the interaction between DCP1 and DCP2, thereby amplifying the efficiency of decapping. This work focuses on DCP1a and DCP1b and investigates their distinct functions. Using DCP1a- and DCP1a-specific knockdowns as well as K.O. cell lines, the authors find surprising differences between the DCP1 paralogs. While DCP1a is essential for the assembly of EDC4-containig decapping complexes and interactions with mRNA cap binding proteins, DCP1b mediates interactions with the translational machinery. Furthermore, DCP1a and DCP1b target different mRNAs for degradation, indicating that they execute non-overlapping functions. The findings reported here expand our understanding of mRNA decapping in human cells, shedding light on the unique contributions of DCP1a and DCP1b to mRNA metabolism. The manuscript tackles an interesting subject. Historically, the emphasis has been on studying DCP1a, while DCP1b has been deemed a functionally redundant homolog of DCP1a. Therefore, it is commendable that the authors have taken on this topic and, with the help of knockout cell lines, aimed to dissect the function of DCP1a and DCP1b. Despite recognizing the significance of the subject and approach, the manuscript falls short of persuading me. Following a promising start in Figure 1 (which still has room for improvement), there is a distinct decline in overall quality, with only relatively standard analyses being conducted. However, I do not want to give the authors a detailed advice on maximizing the potential of their data and presenting it convincingly. So, here are just a few key points for improvement: Figure 1C: Upon closer examination, a faint band is still visible at the size of DCP1a in the DCP1a knockout cells. Could this be leaky expression of DCP1a? The authors should provide an in-depth characterization of their cells (possibly as supplementary material), including identification of genomic changes (e.g. by sequencing of the locus) and Western blots with longer exposure, etc.

      *RESPONSE: Thank you for this comment. The in-depth characterization of our cells is now included in the Supplementary Material. DCP1a KO cells and DCP1b KO cells indicated as single cell clones have been confirmed to have no DCP1a or DCP1b expression. In Figure 1D and Figure 3, polyclonal pool cells were used as indicated (only for DCP1a KO). *

      Figure 2: It is great to see that the effects of the KOs are also visible in the DDX6 immunoprecipitation. However, I wonder if the IP clearly confirms that the KO cells indeed do not express DCP1a or DCP1b. In the heatmap in Figure 2B, it appears as if the proteins are only reduced by a log2-fold change of approximately 1.5? Additionally, Figure 2 shows a problem that persists in the subsequent figures. The visual presentation is not particularly appealing, and essential details, such as the scale of the heatmap in 2B (is it log2 fold?), are lacking.

      *RESPONSE: The in-depth characterization of our cells is included in the Supplementary Materials and confirms the presence of single-cell clones where indicated. As noted above, only Figure 1D and Figure 3 used DCP1a KO pooled cells. The heatmap in Figure 2B is scaled by row using the pheatfunction in R studio. The actual data for the heatmap comes from protein intensities from the LC-MS/MS analysis. We have improved the visual presentation in the revised manuscript. *

      Figure 3: I wonder why there are no primary data shown here, only processed GO analyses. Wouldn't one expect that DCP2 interacts mainly with DCP1a, but less with DCP1b? Is this visible in the data? Moreover, such analyses are rather uninformative (as reflected in the GO terms themselves, for instance, "oxoglutarate dehydrogenase complex" doesn't provide much meaningful insight). The authors should rather try to derive functional and mechanistic insights from their data.

      RESPONSE: We have now revised this Figure to include primary data as well as the IP of DCP1a in DCP1b KO cells (single cell clones) and the IP of DCP1b in DCP1a KO cells (pooled cells). We identified EDC3 in the high-confidence protein pool. The EDC3:DCP1a interaction is enhanced in DCP1b KO cells. We also found that the EDC3:DCP1b interaction is less abundant in DCP1a KO cells. This is consistent with our data in Figures 1 and 2. DCP2 was not identified in the interactomes of either DCP1a or DCP1b. This is not unusual as DCP2 is highly flexible and the association between DCP1s with DCP2 is transient and facilitated by other proteins.

      In Fig. 4 the potential of the approach is not fully exploited. Firstly, I would advocate for omitting the GO analyses, as, in my opinion, they offer little insight. Again, crucial information is missing to assess the results. While 75 nt reads are mentioned in the methods, the sequencing depth remains unspecified. Figure 4b should be included in the supplements. Furthermore, I strongly recommend concentrating on insights into the mechanisms of DCP1a and DCP1b-containing complexes. E.g. what characteristics distinguish DCP1a and DCP1b-dependent mRNAs? Are these targets inherently unstable? Why are they degraded? Are they known decapping substrates?

      *RESPONSE: Thank you for this comment. We have now revised this figure and have included information about sequencing depth and other pertinent information. We have been able to use a newly available algorithm (grandR) and were able to estimate half-lives and synthesis rates. This is a significant addition to the paper. We were also able to compare significantly impacted mRNAs (by DCP1a or DCP1b loss) to the established DCP2 target list. *

      In general, I suggest the authors revise the manuscript with a focus on the potential readers. Reduce Gene Ontology (GO) analyses and heatmaps, and instead, incorporate more analyses regarding the molecular processes associated with the different decapping complexes.

      *RESPONSE: We removed selected GO analyses and heatmaps from the main body of the manuscript (included as Supplementary Figures instead). For our LC-MS/MS datasets, we added iBAQ analyses of the DDX6 IP, DCP1a IP, and DCP1b IP in the control conditions. Cellular fractionation studies (using Superose 6 chromatography) were also added to the paper and allow us to interrogate decapping complex composition in more detail. The revised version of the manuscript includes a new 4SU labeling experiment (pulse-chase) as well as estimation of half-lives and synthesis rates in our conditions. Also included is relevant information about DCP1b transcriptional regulation. *

      Reviewer #3 (Significance (Required)):

      The manuscript in its current form could benefit from substantial revisions for it to be considered impactful for researchers in the field.

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

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      Reply to the reviewers

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

      I have trialled the package on my lab's data and it works as advertised. It was straightforward to use and did not require any special training. I am confident this is a tool that will be approachable even to users with limited computational experience. The use of artificial data to validate the approach - and to provide clear limits on applicability - is particularly helpful.

      The main limitation of the tool is that it requires the user to manually select regions. This somewhat limits the generalisability and is also more subjective - users can easily choose "nice" regions that better match with their hypothesis, rather than quantifying the data in an unbiased manner. However, given the inherent challenges in quantifying biological data, such problems are not easily circumventable.

      *

      * I have some comments to clarify the manuscript:

      1. A "straightforward installation" is mentioned. Given this is a Method paper, the means of installation should be clearly laid out.*

      __This sentence is now modified. In the revised manuscript we now describe how to install the toolset and we give the link to the toolset website if further information is needed. __On this website, we provide a full video tutorial and a user manual. The user manual is provided as a supplementary material of the manuscript.

      * It would be helpful if there was an option to generate an output with the regions analysed (i.e., a JPG image with the data and the drawn line(s) on top). There are two reasons for this: i) A major problem with user-driven quantification is accidental double counting of regions (e.g., a user quantifies a part of an image and then later quantifies the same region). ii) Allows other users to independently verify measurements at a later time.*

      We agree that it is helpful to save the analyzed regions. To answer this comment and the other two reviewers' comments pointing at a similar feature, we have now included an automatic saving of the regions of interest. The user will be able to reopen saved regions of interest using a new function we included in the new version of PatternJ.

      * 3. Related to the above point, it is highlighted that each time point would need to be analysed separately (line 361-362). It seems like it should be relatively straightforward to allow a function where the analysis line can be mapped onto the next time point. The user could then adjust slightly for changes in position, but still be starting from near the previous timepoint. Given how prevalent timelapse imaging is, this seems like (or something similar) a clear benefit to add to the software.*

      We agree that the analysis of time series images can be a useful addition. We have added the analysis of time-lapse series in the new version of PatternJ. The principles behind the analysis of time-lapse series and an example of such analysis are provided in Figure 1 - figure supplement 3 and Figure 5, with accompanying text lines 140-153 and 360-372. The analysis includes a semi-automated selection of regions of interest, which will make the analysis of such sequences more straightforward than having to draw a selection on each image of the series. The user is required to draw at least two regions of interest in two different frames, and the algorithm will automatically generate regions of interest in frames in which selections were not drawn. The algorithm generates the analysis immediately after selections are drawn by the user, which includes the tracking of the reference channel.

      * Line 134-135. The level of accuracy of the searching should be clarified here. This is discussed later in the manuscript, but it would be helpful to give readers an idea at this point what level of tolerance the software has to noise and aperiodicity.

      *

      We agree with the reviewer that a clarification of this part of the algorithm will help the user better understand the manuscript.__ We have modified the sentence to clarify the range of search used and the resulting limits in aperiodicity (now lines 176-181). __Regarding the tolerance to noise, it is difficult to estimate it a priori from the choice made at the algorithm stage, so we prefer to leave it to the validation part of the manuscript. We hope this solution satisfies the reviewer and future users.

      *

      **Referees cross-commenting**

      I think the other reviewer comments are very pertinent. The authors have a fair bit to do, but they are reasonable requests. So, they should be encouraged to do the revisions fully so that the final software tool is as useful as possible.

      Reviewer #1 (Significance (Required)):

      Developing software tools for quantifying biological data that are approachable for a wide range of users remains a longstanding challenge. This challenge is due to: (1) the inherent problem of variability in biological systems; (2) the complexity of defining clearly quantifiable measurables; and (3) the broad spread of computational skills amongst likely users of such software.

      In this work, Blin et al., develop a simple plugin for ImageJ designed to quickly and easily quantify regular repeating units within biological systems - e.g., muscle fibre structure. They clearly and fairly discuss existing tools, with their pros and cons. The motivation for PatternJ is properly justified (which is sadly not always the case with such software tools).

      Overall, the paper is well written and accessible. The tool has limitations but it is clearly useful and easy to use. Therefore, this work is publishable with only minor corrections.

      *We thank the reviewer for the positive evaluation of PatternJ and for pointing out its accessibility to the users.

      *

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

      # Summary

      The authors present an ImageJ Macro GUI tool set for the quantification of one-dimensional repeated patterns that are commonly occurring in microscopy images of muscles.

      # Major comments

      In our view the article and also software could be improved in terms of defining the scope of its applicability and user-ship. In many parts the article and software suggest that general biological patterns can be analysed, but then in other parts very specific muscle actin wordings are used. We are pointing this out in the "Minor comments" sections below. We feel that the authors could improve their work by making a clear choice here. One option would be to clearly limit the scope of the tool to the analysis of actin structures in muscles. In this case we would recommend to also rename the tool, e.g. MusclePatternJ. The other option would be to make the tool about the generic analysis of one-dimensional patterns, maybe calling the tool LinePatternJ. In the latter case we would recommend to remove all actin specific wordings from the macro tool set and also the article should be in parts slightly re-written.

      *

      We agree with the reviewer that our initial manuscript used a mix of general and muscle-oriented vocabulary, which could make the use of PatternJ confusing especially outside of the muscle field. To make PatternJ useful for the largest community, we corrected the manuscript and the PatternJ toolset to provide the general vocabulary needed to make it understandable for every biologist. We modified the manuscript accordingly.

      * # Minor/detailed comments

      # Software

      We recommend considering the following suggestions for improving the software.

      ## File and folder selection dialogs

      In general, clicking on many of the buttons just opens up a file-browser dialog without any further information. For novel users it is not clear what the tool expects one to select here. It would be very good if the software could be rewritten such that there are always clear instructions displayed about which file or folder one should open for the different buttons.*

      We experienced with the current version of macOS that the file-browser dialog does not display any message; we suspect this is the issue raised by the reviewer. This is a known issue of Fiji on Mac and all applications on Mac since 2016. We provided guidelines in the user manual and on the tutorial video to correct this issue by changing a parameter in Fiji. Given the issues the reviewer had accessing the material on the PatternJ website, which we apologize for, we understand the issue raised. We added an extra warning on the PatternJ website to point at this problem and its solution. Additionally, we have limited the file-browser dialog appearance to what we thought was strictly necessary. Thus, the user will experience fewer prompts, speeding up the analysis.

      *

      ## Extract button

      The tool asks one to specify things like whether selections are drawn "M-line-to-M-line"; for users that are not experts in muscle morphology this is not understandable. It would be great to find more generally applicable formulations. *

      We agree that this muscle-oriented vocabulary can make the use of PatternJ confusing. We have now corrected the user interface to provide both general and muscle-specific vocabulary ("center-to-center or edge-to-edge (M-line-to-M-line or Z-disc-to-Z-disc)").*

      ## Manual selection accuracy

      The 1st step of the analysis is always to start from a user hand-drawn profile across intensity patterns in the image. However, this step can cause inaccuracy that varies with the shape and curve of the line profile drawn. If not strictly perpendicular to for example the M line patterns, the distance between intensity peaks will be different. This will be more problematic when dealing with non-straight and parallelly poised features in the image. If the structure is bended with a curve, the line drawn over it also needs to reproduce this curve, to precisely capture the intensity pattern. I found this limits the reproducibility and easy-usability of the software.*

      We understand the concern of the reviewer. On curved selections this will be an issue that is difficult to solve, especially on "S" curved or more complex selections. The user will have to be very careful in these situations. On non-curved samples, the issue may be concerning at first sight, but the errors go with the inverse of cosine and are therefore rather low. For example, if the user creates a selection off by 5 degrees, which is visually obvious, lengths will be affected by an increase of only 0.38%. The point raised by the reviewer is important to discuss, and we therefore added a paragraph to comment on the choice of selection (lines 94-98) and a supplementary figure to help make it clear (Figure 1 - figure supplement 1).*

      ### Reproducibility

      Since the line profile drawn on the image is the first step and very essential to the entire process, it should be considered to save together with the analysis result. For example, as ImageJ ROI or ROIset files that can be re-imported, correctly positioned, and visualized in the measured images. This would greatly improve the reproducibility of the proposed workflow. In the manuscript, only the extracted features are being saved (because the save button is also just asking for a folder containing images, so I cannot verify its functionality). *

      We agree that this is a very useful and important feature. We have added ROI automatic saving. Additionally, we now provide a simplified import function of all ROIs generated with PatternJ and the automated extraction and analysis of the list of ROIs. This can be done from ROIs generated previously in PatternJ or with ROIs generated from other ImageJ/Fiji algorithms. These new features are described in the manuscript in lines 120-121 and 130-132.

      *

      ## ? button

      It would be great if that button would open up some usage instructions.

      *

      We agree with the reviewer that the "?" button can be used in a better way. We have replaced this button with a Help menu, including a simple tutorial showing a series of images detailing the steps to follow by the user, a link to the user website, and a link to our video tutorial.

      * ## Easy improvement of workflow

      I would suggest a reasonable expansion of the current workflow, by fitting and displaying 2D lines to the band or line structure in the image, that form the "patterns" the author aims to address. Thus, it extracts geometry models from the image, and the inter-line distance, and even the curve formed by these sets of lines can be further analyzed and studied. These fitted 2D lines can be also well integrated into ImageJ as Line ROI, and thus be saved, imported back, and checked or being further modified. I think this can largely increase the usefulness and reproducibility of the software.

      *

      We hope that we understood this comment correctly. We had sent a clarification request to the editor, but unfortunately did not receive an answer within the requested 4 weeks of this revision. We understood the following: instead of using our 1D approach, in which we extract positions from a profile, the reviewer suggests extracting the positions of features not as a single point, but as a series of coordinates defining its shape. If this is the case, this is a major modification of the tool that is beyond the scope of PatternJ. We believe that keeping our tool simple, makes it robust. This is the major strength of PatternJ. Local fitting will not use line average for instance, which would make the tool less reliable.

      * # Manuscript

      We recommend considering the following suggestions for improving the manuscript. Abstract: The abstract suggests that general patterns can be quantified, however the actual tool quantifies specific subtypes of one-dimensional patterns. We recommend adapting the abstract accordingly.

      *

      We modified the abstract to make this point clearer.

      * Line 58: Gray-level co-occurrence matrix (GLCM) based feature extraction and analysis approach is not mentioned nor compared. At least there's a relatively recent study on Sarcomeres structure based on GLCM feature extraction: https://github.com/steinjm/SotaTool with publication: *https://doi.org/10.1002/cpz1.462

      • *

      We thank the reviewer for making us aware of this publication. We cite it now and have added it to our comparison of available approaches.

      * Line 75: "...these simple geometrical features will address most quantitative needs..." We feel that this may be an overstatement, e.g. we can imagine that there should be many relevant two-dimensional patterns in biology?!*

      We have modified this sentence to avoid potential confusion (lines 76-77).

      • *

      • Line 83: "After a straightforward installation by the user, ...". We think it would be convenient to add the installation steps at this place into the manuscript. *

      __This sentence is now modified. We now mention how to install the toolset and we provide the link to the toolset website, if further information is needed (lines 86-88). __On the website, we provide a full video tutorial and a user manual.

      * Line 87: "Multicolor images will give a graph with one profile per color." The 'Multicolor images' here should be more precisely stated as "multi-channel" images. Multi-color images could be confused with RGB images which will be treated as 8-bit gray value (type conversion first) images by profile plot in ImageJ. *

      We agree with the reviewer that this could create some confusion. We modified "multicolor" to "multi-channel".

      * Line 92: "...such as individual bands, blocks, or sarcomeric actin...". While bands and blocks are generic pattern terms, the biological term "sarcomeric actin" does not seem to fit in this list. Could a more generic wording be found, such as "block with spike"? *

      We agree with the reviewer that "sarcomeric actin" alone will not be clear to all readers. We modified the text to "block with a central band, as often observed in the muscle field for sarcomeric actin" (lines 103-104). The toolset was modified accordingly.

      * Line 95: "the algorithm defines one pattern by having the features of highest intensity in its centre". Could this be rephrased? We did not understand what that exactly means.*

      We agree with the reviewer that this was not clear. We rewrote this paragraph (lines 101-114) and provided a supplementary figure to illustrate these definitions (Figure 1 - figure supplement 2).

      * Line 124 - 147: This part the only description of the algorithm behind the feature extraction and analysis, but not clearly stated. Many details are missing or assumed known by the reader. For example, how it achieved sub-pixel resolution results is not clear. One can only assume that by fitting Gaussian to the band, the center position (peak) thus can be calculated from continuous curves other than pixels. *

      Note that the two sentences introducing this description are "Automated feature extraction is the core of the tool. The algorithm takes multiple steps to achieve this (Fig. S2):". We were hoping this statement was clear, but the reviewer may refer to something else. We agree that the description of some of the details of the steps was too quick. We have now expanded the description where needed.

      * Line 407: We think the availability of both the tool and the code could be improved. For Fiji tools it is common practice to create an Update Site and to make the code available on GitHub. In addition, downloading the example file (https://drive.google.com/file/d/1eMazyQJlisWPwmozvyb8VPVbfAgaH7Hz/view?usp=drive_link) required a Google login and access request, which is not very convenient; in fact, we asked for access but it was denied. It would be important for the download to be easier, e.g. from GitHub or Zenodo.

      *

      We are sorry for issues encountered when downloading the tool and additional material. We thank the reviewer for pointing out these issues that limited the accessibility of our tool. We simplified the downloading procedure on the website, which does not go through the google drive interface nor requires a google account. Additionally, for the coder community the code, user manual and examples are now available from GitHub at github.com/PierreMangeol/PatternJ, and are provided as supplementary material with the manuscript. To our knowledge, update sites work for plugins but not for macro toolsets. Having experience sharing our codes with non-specialists, a classical website with a tutorial video is more accessible than more coder-oriented websites, which deter many users.

      * Reviewer #2 (Significance (Required)):

      The strength of this study is that a tool for the analysis of one-dimensional repeated patterns occurring in muscle fibres is made available in the accessible open-source platform ImageJ/Fiji. In the introduction to the article the authors provide an extensive review of comparable existing tools. Their new tool fills a gap in terms of providing an easy-to-use software for users without computational skills that enables the analysis of muscle sarcomere patterns. We feel that if the below mentioned limitations could be addressed the tool could indeed be valuable to life scientists interested in muscle patterning without computational skills.

      In our view there are a few limitations, including the accessibility of example data and tutorials at sites.google.com/view/patternj, which we had trouble to access. In addition, we think that the workflow in Fiji, which currently requires pressing several buttons in the correct order, could be further simplified and streamlined by adopting some "wizard" approach, where the user is guided through the steps.

      *As answered above, the links on the PatternJ website are now corrected. Regarding the workflow, we now provide a Help menu with:

      1. __a basic set of instructions to use the tool, __
      2. a direct link to the tutorial video in the PatternJ toolset
      3. a direct link to the website on which both the tutorial video and a detailed user manual can be found. We hope this addresses the issues raised by this reviewer.

      *Another limitation is the reproducibility of the analysis; here we recommend enabling IJ Macro recording as well as saving of the drawn line ROIs. For more detailed suggestions for improvements please see the above sections of our review. *

      We agree that saving ROIs is very useful. It is now implemented in PatternJ.

      We are not sure what this reviewer means by "enabling IJ Macro recording". The ImageJ Macro Recorder is indeed very useful, but to our knowledge, it is limited to built-in functions. Our code is open and we hope this will be sufficient for advanced users to modify the code and make it fit their needs.*

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

      Summary In this manuscript, the authors present a new toolset for the analysis of repetitive patterns in biological images named PatternJ. One of the main advantages of this new tool over existing ones is that it is simple to install and run and does not require any coding skills whatsoever, since it runs on the ImageJ GUI. Another advantage is that it does not only provide the mean length of the pattern unit but also the subpixel localization of each unit and the distributions of lengths and that it does not require GPU processing to run, unlike other existing tools. The major disadvantage of the PatternJ is that it requires heavy, although very simple, user input in both the selection of the region to be analyzed and in the analysis steps. Another limitation is that, at least in its current version, PatternJ is not suitable for time-lapse imaging. The authors clearly explain the algorithm used by the tool to find the localization of pattern features and they thoroughly test the limits of their tool in conditions of varying SNR, periodicity and band intensity. Finally, they also show the performance of PatternJ across several biological models such as different kinds of muscle cells, neurons and fish embryonic somites, as well as different imaging modalities such as brightfield, fluorescence confocal microscopy, STORM and even electron microscopy.

      This manuscript is clearly written, and both the section and the figures are well organized and tell a cohesive story. By testing PatternJ, I can attest to its ease of installation and use. Overall, I consider that PatternJ is a useful tool for the analysis of patterned microscopy images and this article is fit for publication. However, i do have some minor suggestions and questions that I would like the authors to address, as I consider they could improve this manuscript and the tool:

      *We are grateful to this reviewer for this very positive assessment of PatternJ and of our manuscript.

      * Minor Suggestions: In the methodology section is missing a more detailed description about how the metric plotted was obtained: as normalized intensity or precision in pixels. *

      We agree with the reviewer that a more detailed description of the metric plotted was missing. We added this information in the method part and added information in the Figure captions where more details could help to clarify the value displayed.

      * The validation is based mostly on the SNR and patterns. They should include a dataset of real data to validate the algorithm in three of the standard patterns tested. *

      We validated our tool using computer-generated images, in which we know with certainty the localization of patterns. This allowed us to automatically analyze 30 000 images, and with varying settings, we sometimes analyzed 10 times the same image, leading to about 150 000 selections analyzed. From these analyses, we can provide with confidence an unbiased assessment of the tool precision and the tool capacity to extract patterns. We already provided examples of various biological data images in Figures 4-6, showing all possible features that can be extracted with PatternJ. In these examples, we can claim by eye that PatternJ extracts patterns efficiently, but we cannot know how precise these extractions are because of the nature of biological data: "real" positions of features are unknown in biological data. Such validation will be limited to assessing whether a pattern was found or not, which we believe we already provided with the examples in Figures 4-6.

      * The video tutorial available in the PatternJ website is very useful, maybe it would be worth it to include it as supplemental material for this manuscript, if the journal allows it. *

      As the video tutorial may have been missed by other reviewers, we agree it is important to make it more prominent to users. We have now added a Help menu in the toolset that opens the tutorial video. Having the video as supplementary material could indeed be a useful addition if the size of the video is compatible with the journal limits.

      * An example image is provided to test the macro. However, it would be useful to provide further example images for each of the three possible standard patterns suggested: Block, actin sarcomere or individual band.*

      We agree this can help users. We now provide another multi-channel example image on the PatternJ website including blocks and a pattern made of a linear intensity gradient that can be extracted with our simpler "single pattern" algorithm, which were missing in the first example. Additionally, we provide an example to be used with our new time-lapse analysis.

      * Access to both the manual and the sample images in the PatternJ website should be made publicly available. Right now they both sit in a private Drive account. *

      As mentioned above, we apologize for access issues that occurred during the review process. These files can now be downloaded directly on the website without any sort of authentication. Additionally, these files are now also available on GitHub.

      * Some common errors are not properly handled by the macro and could be confusing for the user: When there is no selection and one tries to run a Check or Extraction: "Selection required in line 307 (called from line 14). profile=getProfile( ;". A simple "a line selection is required" message would be useful there. When "band" or "block" is selected for a channel in the "Set parameters" window, yet a 0 value is entered into the corresponding "Number of bands or blocks" section, one gets this error when trying to Extract: "Empty array in line 842 (called from line 113). if ( ( subloc . length == 1 ) & ( subloc [ 0 == 0) ) {". This error is not too rare, since the "Number of bands or blocks" section is populated with a 0 after choosing "sarcomeric actin" (after accepting the settings) and stays that way when one changes back to "blocks" or "bands".*

      We thank the reviewer for pointing out these bugs. These bugs are now corrected in the revised version.

      * The fact that every time one clicks on the most used buttons, the getDirectory window appears is not only quite annoying but also, ultimately a waste of time. Isn't it possible to choose the directory in which to store the files only once, from the "Set parameters" window?*

      We have now found a solution to avoid this step. The user is only prompted to provide the image folder when pressing the "Set parameter" button. We kept the prompt for directory only when the user selects the time-lapse analysis or the analysis of multiple ROIs. The main reason is that it is very easy for the analysis to end up in the wrong folder otherwise.

      * The authors state that the outputs of the workflow are "user friendly text files". However, some of them lack descriptive headers (like the localisations and profiles) or even file names (like colors.txt). If there is something lacking in the manuscript, it is a brief description of all the output files generated during the workflow.*

      PatternJ generates multiple files, several of which are internal to the toolset. They are needed to keep track of which analyses were done, and which colors were used in the images, amongst others. From the user part, only the files obtained after the analysis All_localizations.channel_X.txt and sarcomere_lengths.txt are useful. To improve the user experience, we now moved all internal files to a folder named "internal", which we think will clarify which outputs are useful for further analysis, and which ones are not. We thank the reviewer for raising this point and we now mention it in our Tutorial.

      I don't really see the point in saving the localizations from the "Extraction" step, they are even named "temp".

      We thank the reviewer for this comment, this was indeed not necessary. We modified PatternJ to delete these files after they are used.

      * In the same line, I DO see the point of saving the profiles and localizations from the "Extract & Save" step, but I think they should be deleted during the "Analysis" step, since all their information is then grouped in a single file, with descriptive headers. This deleting could be optional and set in the "Set parameters" window.*

      We understand the point raised by the reviewer. However, the analysis depends on the reference channel picked, which is asked for when starting an analysis, and can be augmented with additional selections. If a user chooses to modify the reference channel or to add a new profile to the analysis, deleting all these files would mean that the user will have to start over again, which we believe will create frustration. An optional deletion at the analysis step is simple to implement, but it could create problems for users who do not understand what it means practically.

      * Moreover, I think it would be useful to also save the linear roi used for the "Extract & Save" step, and eventually combine them during the "Analysis step" into a single roi set file so that future re-analysis could be made on the same regions. This could be an optional feature set from the "Set parameters" window. *

      We agree with the reviewer that saving ROIs is very useful. ROIs are now saved into a single file each time the user extracts and saves positions from a selection. Additionally, the user can re-use previous ROIs and analyze an image or image series in a single step.

      * In the "PatternJ workflow" section of the manuscript, the authors state that after the "Extract & Save" step "(...) steps 1, 2, 4, and 5 can be repeated on other selections (...)". However, technically, only steps 1 and 5 are really necessary (alternatively 1, 4 and 5 if the user is unsure of the quality of the patterning). If a user follows this to the letter, I think it can lead to wasted time.

      *

      We agree with the reviewer and have corrected the manuscript accordingly (line 119-120).

      • *

      *I believe that the "Version Information" button, although important, has potential to be more useful if used as a "Help" button for the toolset. There could be links to useful sources like the manuscript or the PatternJ website but also some tips like "whenever possible, use a higher linewidth for your line selection" *

      We agree with the reviewer as pointed out in our previous answers to the other reviewers. This button is now replaced by a Help menu, including a simple tutorial in a series of images detailing the steps to follow, a link to the user website, and a link to our video tutorial.

      * It would be interesting to mention to what extent does the orientation of the line selection in relation to the patterned structure (i.e. perfectly parallel vs more diagonal) affect pattern length variability?*

      As answered to reviewer 1, we understand this concern, which needs to be clarified for readers. The issue may be concerning at first sight, but the errors grow only with the inverse of cosine and are therefore rather low. For example, if the user creates a selection off by 3 degrees, which is visually obvious, lengths will be affected by an increase of only 0.14%. The point raised by the reviewer is important to discuss, and we therefore have added a comment on the choice of selection (lines 94-98) as well as a supplementary figure (Figure 1 - figure supplement 1).

      * When "the algorithm uses the peak of highest intensity as a starting point and then searches for peak intensity values one spatial period away on each side of this starting point" (line 133-135), does that search have a range? If so, what is the range? *

      We agree that this information is useful to share with the reader. The range is one pattern size. We have modified the sentence to clarify the range of search used and the resulting limits in aperiodicity (now lines 176-181).

      * Line 144 states that the parameters of the fit are saved and given to the user, yet I could not find such information in the outputs. *

      The parameters of the fits are saved for blocks. We have now clarified this point by modifying the manuscript (lines 186-198) and modifying Figure 1 - figure supplement 5. We realized we made an error in the description of how edges of "block with middle band" are extracted. This is now corrected.

      * In line 286, authors finish by saying "More complex patterns from electron microscopy images may also be used with PatternJ.". Since this statement is not backed by evidence in the manuscript, I suggest deleting it (or at the very least, providing some examples of what more complex patterns the authors refer to). *

      This sentence is now deleted.

      * In the TEM image of the fly wing muscle in fig. 4 there is a subtle but clearly visible white stripe pattern in the original image. Since that pattern consists of 'dips', rather than 'peaks' in the profile of the inverted image, they do not get analyzed. I think it is worth mentioning that if the image of interest contains both "bright" and "dark" patterns, then the analysis should be performed in both the original and the inverted images because the nature of the algorithm does not allow it to detect "dark" patterns. *

      We agree with the reviewer's comment. We now mention this point in lines 337-339.

      * In line 283, the authors mention using background correction. They should explicit what method of background correction they used. If they used ImageJ's "subtract background' tool, then specify the radius.*

      We now describe this step in the method section.

      *

      Reviewer #3 (Significance (Required)):

      • Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. Being a software paper, the advance proposed by the authors is technical in nature. The novelty and significance of this tool is that it offers quick and simple pattern analysis at the single unit level to a broad audience, since it runs on the ImageJ GUI and does not require any programming knowledge. Moreover, all the modules and steps are well described in the paper, which allows easy going through the analysis.
      • Place the work in the context of the existing literature (provide references, where appropriate). The authors themselves provide a good and thorough comparison of their tool with other existing ones, both in terms of ease of use and on the type of information extracted by each method. While PatternJ is not necessarily superior in all aspects, it succeeds at providing precise single pattern unit measurements in a user-friendly manner.
      • State what audience might be interested in and influenced by the reported findings. Most researchers working with microscopy images of muscle cells or fibers or any other patterned sample and interested in analyzing changes in that pattern in response to perturbations, time, development, etc. could use this tool to obtain useful, and otherwise laborious, information. *

      We thank the reviewer for these enthusiastic comments about how straightforward for biologists it is to use PatternJ and its broad applicability in the bio community.

    2. 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 #2

      Evidence, reproducibility and clarity

      Summary

      The authors present an ImageJ Macro GUI tool set for the quantification of one-dimensional repeated patterns that are commonly occurring in microscopy images of muscles.

      Major comments

      In our view the article and also software could be improved in terms of defining the scope of its applicability and user-ship. In many parts the article and software suggest that general biological patterns can be analysed, but then in other parts very specific muscle actin wordings are used. We are pointing this out in the "Minor comments" sections below. We feel that the authors could improve their work by making a clear choice here. One option would be to clearly limit the scope of the tool to the analysis of actin structures in muscles. In this case we would recommend to also rename the tool, e.g. MusclePatternJ. The other option would be to make the tool about the generic analysis of one-dimensional patterns, maybe calling the tool LinePatternJ. In the latter case we would recommend to remove all actin specific wordings from the macro tool set and also the article should be in parts slightly re-written.

      Minor/detailed comments

      Software

      We recommend considering the following suggestions for improving the software.

      File and folder selection dialogs

      In general, clicking on many of the buttons just opens up a file-browser dialog without any further information. For novel users it is not clear what the tool expects one to select here. It would be very good if the software could be rewritten such that there are always clear instructions displayed about which file or folder one should open for the different buttons.

      Extract button

      The tool asks one to specify things like whether selections are drawn "M-line-to-M-line"; for users that are not experts in muscle morphology this is not understandable. It would be great to find more generally applicable formulations.

      Manual selection accuracy

      The 1st step of the analysis is always to start from a user hand-drawn profile across intensity patterns in the image. However, this step can cause inaccuracy that varies with the shape and curve of the line profile drawn. If not strictly perpendicular to for example the M line patterns, the distance between intensity peaks will be different. This will be more problematic when dealing with non-straight and parallelly poised features in the image. If the structure is bended with a curve, the line drawn over it also needs to reproduce this curve, to precisely capture the intensity pattern. I found this limits the reproducibility and easy-usability of the software.

      Reproducibility

      Since the line profile drawn on the image is the first step and very essential to the entire process, it should be considered to save together with the analysis result. For example, as ImageJ ROI or ROIset files that can be re-imported, correctly positioned, and visualized in the measured images. This would greatly improve the reproducibility of the proposed workflow. In the manuscript, only the extracted features are being saved (because the save button is also just asking for a folder containing images, so I cannot verify its functionality).

      ? button

      It would be great if that button would open up some usage instructions.

      Easy improvement of workflow

      I would suggest a reasonable expansion of the current workflow, by fitting and displaying 2D lines to the band or line structure in the image, that form the "patterns" the author aims to address. Thus, it extracts geometry models from the image, and the inter-line distance, and even the curve formed by these sets of lines can be further analyzed and studied. These fitted 2D lines can be also well integrated into ImageJ as Line ROI, and thus be saved, imported back, and checked or being further modified. I think this can largely increase the usefulness and reproducibility of the software.

      Manuscript

      We recommend considering the following suggestions for improving the manuscript. Abstract: The abstract suggests that general patterns can be quantified, however the actual tool quantifies specific subtypes of one-dimensional patterns. We recommend adapting the abstract accordingly.

      Line 58: Gray-level co-occurrence matrix (GLCM) based feature extraction and analysis approach is not mentioned nor compared. At least there's a relatively recent study on Sarcomeres structure based on GLCM feature extraction: https://github.com/steinjm/SotaTool with publication: https://doi.org/10.1002/cpz1.462

      Line 75: "...these simple geometrical features will address most quantitative needs..." We feel that this may be an overstatement, e.g. we can imagine that there should be many relevant two-dimensional patterns in biology?!

      Line 83: "After a straightforward installation by the user, ...". We think it would be convenient to add the installation steps at this place into the manuscript.

      Line 87: "Multicolor images will give a graph with one profile per color." The 'Multicolor images' here should be more precisely stated as "multi-channel" images. Multi-color images could be confused with RGB images which will be treated as 8-bit gray value (type conversion first) images by profile plot in ImageJ.

      Line 92: "...such as individual bands, blocks, or sarcomeric actin...". While bands and blocks are generic pattern terms, the biological term "sarcomeric actin" does not seem to fit in this list. Could a more generic wording be found, such as "block with spike"?

      Line 95: "the algorithm defines one pattern by having the features of highest intensity in its centre". Could this be rephrased? We did not understand what that exactly means.

      Line 124 - 147: This part the only description of the algorithm behind the feature extraction and analysis, but not clearly stated. Many details are missing or assumed known by the reader. For example, how it achieved sub-pixel resolution results is not clear. One can only assume that by fitting Gaussian to the band, the center position (peak) thus can be calculated from continuous curves other than pixels.

      Line 407: We think the availability of both the tool and the code could be improved. For Fiji tools it is common practice to create an Update Site and to make the code available on GitHub. In addition, downloading the example file (https://drive.google.com/file/d/1eMazyQJlisWPwmozvyb8VPVbfAgaH7Hz/view?usp=drive_link) required a Google login and access request, which is not very convenient; in fact, we asked for access but it was denied. It would be important for the download to be easier, e.g. from GitHub or Zenodo.

      Significance

      The strength of this study is that a tool for the analysis of one-dimensional repeated patterns occurring in muscle fibres is made available in the accessible open-source platform ImageJ/Fiji. In the introduction to the article the authors provide an extensive review of comparable existing tools. Their new tool fills a gap in terms of providing an easy-to-use software for users without computational skills that enables the analysis of muscle sarcomere patterns. We feel that if the below mentioned limitations could be addressed the tool could indeed be valuable to life scientists interested in muscle patterning without computational skills.

      In our view there are a few limitations, including the accessibility of example data and tutorials at sites.google.com/view/patternj, which we had trouble to access. In addition, we think that the workflow in Fiji, which currently requires pressing several buttons in the correct order, could be further simplified and streamlined by adopting some "wizard" approach, where the user is guided through the steps. Another limitation is the reproducibility of the analysis; here we recommend enabling IJ Macro recording as well as saving of the drawn line ROIs. For more detailed suggestions for improvements please see the above sections of our review.

    1. Under the new license, cloud service providers hosting Redis offerings will no longer be permitted to use the source code of Redis free of charge. For example, cloud service providers will be able to deliver Redis 7.4 only after agreeing to licensing terms with Redis, the maintainers of the Redis code. These agreements will underpin support for existing integrated solutions and provide full access to forthcoming Redis innovations.

      ¿Cómo afectará esto a los clientes finales?

      Microsoft seguramente comience a ofrecer como alternativa su propio software equivalente a Redis, https://github.com/microsoft/garnet

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this manuscript, Bell et al. provide an exhaustive and clear description of the diversity of a new class of predicted type IV restriction systems that the authors denote as CoCoNuTs, for their characteristic presence of coiled-coil segments and nuclease tandems. Along with a comprehensive analysis that includes phylogenetics, protein structure prediction, extensive protein domain annotations, and an in-depth investigation of encoding genomic contexts, they also provide detailed hypotheses about the biological activity and molecular functions of the members of this class of predicted systems. This work is highly relevant, it underscores the wide diversity of defence systems that are used by prokaryotes and demonstrates that there are still many systems to be discovered. The work is sound and backed-up by a clear and reasonable bioinformatics approach. I do not have any major issues with the manuscript, but only some minor comments.

      Strengths:

      The analysis provided by the authors is extensive and covers the three most important aspects that can be covered computationally when analysing a new family/superfamily: phylogenetics, genomic context analysis, and protein-structure-based domain content annotation. With this, one can directly have an idea about the superfamily of the predicted system and infer their biological role. The bioinformatics approach is sound and makes use of the most current advances in the fields of protein evolution and structural bioinformatics.

      Weaknesses:

      It is not clear how coiled-coil segments were assigned if only based on AF2-predicted models or also backed by sequence analysis, as no description is provided in the methods. The structure prediction quality assessment is based solely on the average pLDDT of the obtained models (with a threshold of 80 or better). However, this is not enough, particularly when multimeric models are used. The PAE matrix should be used to evaluate relative orientations, particularly in the case where there is a prediction that parts from 2 proteins are interacting. In the case of multimers, interface quality scores, such as the ipTM or pDockQ, should also be considered and, at minimum, reported.

      A description of the coiled-coil predictions has been added to the Methods. For multimeric models, PAE matrices and ipTM+pTM scores have been included in Supplementary Data File S1.

      Reviewer #2 (Public Review):

      Summary:

      In this work, using in-depth computational analysis, Bell et al. explore the diverse repertoire of type IV McrBC modification-dependent restriction systems. The prototypical two-component McrBC system has been structurally and functionally characterised and is known to act as a defence by restricting phage and foreign DNA containing methylated cytosines. Here, the authors find previously unanticipated complexity and versatility of these systems and focus on detailed analysis and classification of a distinct branch, the so-called CoCoNut, named after its composition of coiled-coil structures and tandem nucleases. These CoCoNut systems are predicted to target RNA as well as DNA and to utilise defence mechanisms with some similarity to type III CRISPR-Cas systems.

      Strengths:

      This work is enriched with a plethora of ideas and a myriad of compelling hypotheses that now await experimental verification. The study comes from the group that was amongst the first to describe, characterize, and classify CRISPR-Cas systems. By analogy, the findings described here can similarly promote ingenious experimental and conceptual research that could further drive technological advances. It could also instigate vigorous scientific debates that will ultimately benefit the community.

      Weaknesses:

      The multi-component systems described here function in the context of large oligomeric complexes. Some of the single chain AF2 predictions shown in this work are not compatible, for example, with homohexameric complex formation due to incompatible orientation of domains. The recent advances in protein structure prediction, in particular AlphaFold2 (AF2) multimer, now allow us to confidently probe potential protein-protein interactions and protein complex formation. This predictive power could be exploited here to produce a better glimpse of these multimeric protein systems. It can also provide a more sound explanation for some of the observed differences amongst different McrBC types.

      Hexameric CnuB complexes with CnuC stimulatory monomers for Type I-A, I-B, I-C, II, and III-A CoCoNuT systems have been modeled with AF2 and included in Supplementary Data File S1, albeit without the domains fused to the GTPase N-terminus (with the exception of Type I-B, which lacks the long coiled-coil domain fused to the GTPase and was modeled with its entire sequence). Attempts to model the other full-length CnuB hexamers did not lead to convincing results.

      Recommendations for the authors:

      Reviewing Editor:

      The detailed recommendations by the two reviewers will help the authors to further strengthen the manuscript, but two points seem particularly worth considering: 1. The methods are barely sketched in the manuscript, but it could be useful to detail them more closely. Particularly regarding the coiled-coil segments, which are currently just statists, useful mainly for the name of the family, more detail on their prediction, structural properties, and purpose would be very helpful. 2. Due to its encyclopedic nature, the wealth of material presented in the paper makes it hard to penetrate in one go. Any effort to make it more accessible would be very welcome. Reviewer 1 in particular has made a number of suggestions regarding the figures, which would make them provide more support for the findings described in the text.

      A description of the techniques used to identify coiled-coil segments has been added to the Methods. Our predictions ranged from near certainty in the coiled-coils detected in CnuB homologs, to shorter helices at the limit of detection in other factors. We chose to report all probable coiled-coils, as the extensive coiled-coils fused to CnuB, which are often the only domain present other than the GTPase, imply involvement in mediating complex formation by interacting with coiled-coils in other factors, particularly the other CoCoNuT factors. The suggestions made by Reviewer 1 were thoughtful and we made an effort to incorporate them.

      Reviewer #1 (Recommendations For The Authors):

      I do not have any major issues with the manuscript. I have however some minor comments, as described below.

      • The last sentence of the abstract at first reads as a fact and not a hypothesis resulting from the work described in the manuscript. After the second read, I noticed the nuances in the sentence. I would suggest a rephrasing to emphasize that the activity described is a theoretical hypothesis not backed-up by experiments.

      This sentence has been rephrased to make explicit the hypothetical nature of the statement.

      • In line 64, the authors rename DUF3578 as ADAM because indeed its function is not unknown. Did the authors consider reaching out to InterPro to add this designation to this DUF? A search in interpro with DUF3578 results in "MrcB-like, N-terminal domain" and if a name is suggested, it may be worthwhile to take it to the IntrePro team.

      We will suggest this nomenclature to InterPro.

      • I find Figure 1E hard to analyse and think it occupies too much space for the information it provides. The color scheme, the large amount of small slices, and the lack of numbers make its information content very small. I would suggest moving this to the supplementary and making it instead a bar plot. If removed from Figure 1, more space is made available for the other panels, particularly the structural superpositions, which in my opinion are much more important.

      We have removed Figure 1E from the paper as it adds little information beyond the abundance and phyletic distribution of sequenced prokaryotes, in which McrBC systems are plentiful.

      • In Figure 2, it is not clear due to the presence of many colorful "operon schemes" that the tree is for a single gene and not for the full operon segment. Highlighting the target gene in the operons or signalling it somehow would make the figure easy to understand even in the absence of the text and legend. The same applies to Supplementary Figure 1.

      The legend has been modified to show more clearly that this is a tree of McrB-like GTPases.

      • In line 146, the authors write "AlphaFold-predicted endonucelase fold" to say that a protein contains a region that AF2 predicts to fold like an endonuclease. This is a weird way of writing it and can be confusing to non-expert readers. I would suggest rephrasing for increased clarity.

      This sentence has been rephrased for greater clarity.

      • In line 167, there is a [47]. I believe this is probably due to a previous reference formatting.

      Indeed, this was a reference formatting error and has been fixed.

      • In most figures, the color palette and the use of very similar color palettes for taxonomy pie charts, genomic context composition schemes, and domain composition diagrams make it really hard to have a good understanding of the image at first. Legends are often close to each other, and it is not obvious at first which belong to what. I would suggest changing the layouts and maybe some color schemes to make it easier to extract the information that these figures want to convey.

      It seemed that Figure 4 was the most glaring example of these issues, and it has been rearranged for easier comprehension.

      • In the paragraph that starts at line 199, the authors mention an Ig-like domain that is often found at the N-terminus of Type I CoCoNuTs. Are they all related to each other? How conserved are these domains?

      These domains are all predicted to adopt a similar beta-sandwich fold and are found at the N-terminus of most CoCoNuT CnuC homologs, suggesting they are part of the same family, but we did not undertake a more detailed sequenced-based analysis of these regions.

      We also find comparable domains in the CnuC/McrC-like partners of the abundant McrB-like NxD motif GTPases that are not part of CoCoNuT systems, and given the similarity of some of their predicted structures to Rho GDP-dissociation inhibitor 1, we suspect that they have coevolved as regulators of the non-canonical NxD motif GTPase type. Our CnuBC multimer models showing consistent proximity between these domains in CnuC and CnuB GTPase domains suggest this could indeed be the case. We plan to explore these findings further in a forthcoming publication.

      • In line 210, the authors write "suggesting a role in overcrowding-induced stress response". Why so? In >all other cases, the authors justify their hypothesis, which I really appreciated, but not here.

      A supplementary note justifying this hypothesis has been added to Supplementary Data File S1.

      • At the end of the paragraph that starts in line 264, the authors mention that they constructed AF2 multimeric models to predict if 2 proteins would interact. However, no quality scores were provided, particularly the PAE matrix. This would allow for a better judgement of this prediction, and I would suggest adding the PAE matrix as another panel in the figure where the 3D model of the complex is displayed.

      The PAE matrix and ipTM+pTM scores for this and other multimer models have been added to Supplementary Data File S1. For this model in particular, the surface charge distribution of the model has been presented to support the role of the domains that have a higher PAE in RNA binding.

      • In line 306, "(supplementary data)" refers to what part of the file?

      This file has been renamed Supplementary Table S3 and referenced as such.

      • In line 464, the authors suggest that ShdA could interact with CoCoNuTs. Why not model the complex as done for other cases? what would co-folding suggest?

      As we were not able to convincingly model full-length CnuB hexamers with N-terminal coiled-coils, we did not attempt modeling of this hypothetical complex with another protein with a long coiled-coil, but it remains an interesting possibility.

      • In line 528, why and how were some genes additionally analyzed with HHPred?

      Justification for this analysis has been added to the Methods, but briefly, these genes were additionally analyzed if there were no BLAST hits or to confirm the hits that were obtained.

      • In the first section of the methods, the first and second (particularly the second) paragraphs are extremely long. I would suggest breaking them to facilitate reading.

      This change has been made.

      • In line 545, what do the authors mean by "the alignment (...) were analyzed with HHPred"?

      A more detailed description of this step has been added to the Methods.

      • The authors provide the models they produced as well as extensive supplementary tables that make their data reusable, but they do not provide the code for the automated steps, as to excise target sequence sections out of multiple sequence alignments, for example.

      The code used for these steps has been in use in our group at the NCBI for many years. It will be difficult to utilize outside of the NCBI software environment, but for full disclosure, we have included a zipped repository with the scripts and custom-code dependencies, although there are external dependencies as well such as FastTree and BLAST. In brief, it involves PSI-BLAST detection of regions with the most significant homology to one of a set of provided alignments (seals-2-master/bin/wrappers/cog_psicognitor). In this case, the reference alignments of McrB-like GTPases and DUF2357 were generated manually using HHpred to analyze alignments of clustered PSI-BLAST results. This step provided an output of coordinates defining domain footprints in each query sequence, which were then combined and/or extended using scripts based on manual analysis of many examples with HHpred (footprint_finders/get_GTPase_frags.py and footprint_finders/get_DUF2357_frags.py), then these coordinates were used to excise such regions from the query amino acid sequence with a final script (seals-2-master/bin/misc/fa2frag).

      Reviewer #2 (Recommendations For The Authors):

      (1) Page 4, line 77 - 'PUA superfamily domains' could be more appropriate to use instead of "EVE superfamily".

      While this statement could perhaps be applied to PUA superfamily domains, our previous work we refer to, which strongly supports the assertion, was restricted to the EVE-like domains and we prefer to retain the original language.

      (2) Page 5. lines 128-130 - AF2 multimer prediction model could provide a more sound explanation for these differences.

      Our AF2 multimer predictions added in this revision indeed show that the NxD motif McrB-like CoCoNuT GTPases interact with their respective McrC-like partners such that an immunoglobulin-like beta-sandwich domain, fused to the N-termini of the McrC homologs and similar to Rho GDP-dissociation inhibitor 1, has the potential to physically interact with the GTPase variants. However, we did not probe this in greater detail, as it is beyond the scope of this already highly complex article, but we plan to study it in the future.

      (3) Page 8, line 252 - The surface charge distribution of CnuH OB fold domain looks very different from SmpB (pdb3iyr). In fact, the regions that are in contact with RNA in SmpB are highly acidic in CoCoNut CnuH. Although it looks likely that this domain is involved in RNA binding, the mode of interaction should be very different.

      We did not detect a strong similarity between the CnuH SmpB-like SPB domain and PDB 3IYR, but when we compare the surface charge distribution of PDB 1WJX and the SPB domain, while there is a significant area that is positively charged in 1WJX that is negatively charged in SPB, there is much that overlaps with the same charge in both domains.

      The similarity between SmpB and the SPB domain is significant, but definitely not exact. An important question for future studies is: If the domains are indeed related due to an ancient fusion of SmpB to an ancestor of CnuH, would this degree of divergence be expected?

      In other words, can we say anything about how the function of a stand-alone tmRNA-binding protein could evolve after being fused to a complex predicted RNA helicase with other predicted RNA binding domains already present? Experimental validation will ultimately be necessary to resolve these kinds of questions, but for now, it may be safe to say that the presence of this domain, especially in conjunction with the neighboring RelE-like RTL domain and UPF1-like helicase domain, signals a likely interaction with the A-site of the ribosome, and perhaps restriction of aberrant/viral mRNA.

    1. Here is a detailed summary of the article "Super Charging Fine-Grained Reactive Performance" by Milo:

      1. Introduction to Reactivity in JavaScript

        • Definition and Importance: "Reactivity allows you to write lazy variables that are efficiently cached and updated, making it easier to write clean and fast code."
        • Introduction to Reactively: "I've been working on a new fine grained reactivity library called Reactively inspired by my work on the SolidJS team."
      2. Characteristics of Fine-Grained Reactivity Libraries

        • Library Examples and Usage: "Fine-grained reactivity libraries... Examples include new libraries like Preact Signals, µsignal, and now Reactively, as well as longer-standing libraries like Solid, S.js, and CellX."
        • Functionality and Advantages: "With a library like Reactively, you can easily add lazy variables, caching, and incremental recalculation to your typescript/javascript programs."
      3. Core Concepts in Reactively

        • Dependency Graphs: "Reactive libraries work by maintaining a graph of dependencies between reactive elements."
        • Implementation Example: "import { reactive } from '@reactively/core'; const nthUser = reactive(10);"
      4. Goals and Features of Reactive Libraries

        • Efficiency and State Consistency: "Efficient: Never overexecute reactive elements... Glitch free: Never allow user code to see intermediate state where only some reactive elements have updated."
      5. Comparison Between Lazy and Eager Evaluation

        • Evaluation Strategies: "A lazy library... will first ask B then C to update, then update D after the B and C updates have been completed."
        • Algorithm Challenges: "The first challenge is what we call the diamond problem... The second challenge is the equality check problem."
      6. Algorithm Descriptions

        • MobX: "MobX uses a two pass algorithm, with both passes proceeding from A down through its observers... MobX stores a count of the number of parents that need to be updated with each reactive element."
        • Preact Signals: "Preact checks whether the parents of any signal need to be updated before updating that signal... Preact also has two phases, and the first phase 'notifies' down from A."
        • Reactively: "Reactively uses one down phase and one up phase. Instead of version numbers, Reactively uses only graph coloring."
      7. Benchmarking Results

        • Performance Observations: "In early experiments with the benchmarking tool, what we've discovered so far is that Reactively is the fastest."
        • Framework Comparisons: "The Solid algorithm performs best on wider graphs... The Preact Signal implementation is fast and very memory efficient."

      This summary encapsulates the key concepts, methodologies, and findings presented in the article, focusing on the innovations and performance of various fine-grained reactivity libraries, especially the newly introduced Reactively.

    1. Author Response

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

      eLife assessment

      This work provides a valuable contribution and assessment of what it means to replicate a null study finding, and what are the appropriate methods for doing so (apart from a rote p-value assessment). Through a convincing re-analysis of results from the Reproducibility Project: Cancer Biology using frequentist equivalence testing and Bayes factors, the authors demonstrate that even when reducing 'replicability success' to a single criterion, how precisely replication is measured may yield differing results. Less focus is directed to appropriate replication of non-null findings.

      Reviewer #1 (Public Review):

      Summary:

      The goal of Pawel et al. is to provide a more rigorous and quantitative approach for judging whether or not an initial null finding (conventionally with p ≥ 0.05) has been replicated by a second similarly null finding. They discuss important objections to relying on the qualitative significant/non-significant dichotomy to make this judgment. They present two complementary methods (one frequentist and the other Bayesian) which provide a superior quantitative framework for assessing the replicability of null findings.

      Strengths:

      Clear presentation; illuminating examples drawn from the well-known Reproducibility Project: Cancer Biology data set; R-code that implements suggested analyses. Using both methods as suggested provides a superior procedure for judging the replicability of null findings.

      Weaknesses:

      The proposed frequentist and the Bayesian methods both rely on binary assessments of an original finding and its replication. I'm not sure if this is a weakness or is inherent to making binary decisions based on continuous data.

      For the frequentist method, a null finding is considered replicated if the original and replication 90% confidence intervals for the effects both fall within the equivalence range. According to this approach, a null finding would be considered replicated if p-values of both equivalences tests (original and replication) were, say, 0.049, whereas would not be considered replicated if, for example, the equivalence test of the original study had a p-value of 0.051 and the replication had a p-value of 0.001. Intuitively, the evidence for replication would seem to be stronger in the second instance. The recommended Bayesian approach similarly relies on a dichotomy (e.g., Bayes factor > 1).

      Thanks for the suggestions, we now emphasize more strongly in the “Methods for assessing replicability of null results” and “Conclusions” sections that both TOST p-values and Bayes factors are quantitative measures of evidence that do not require dichotomization into “success” or “failure”.

      Reviewer #2 (Public Review):

      Summary:

      The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

      Strengths:

      The study uses reliable and shareable/open data to demonstrate its findings, sharing as well the code for statistical analysis. The study provides sensitivity analysis for different scenarios of equivalence margin and alfa level, as well as for different scenarios of standard deviations for the prior of Bayes factors and different thresholds to consider. All analysis and code of the work is open and can be replicated. As well, the study demonstrates on a case-by-case basis how the different criteria can diverge, regarding one sample of a field of science: preclinical cancer biology. It also explains clearly what Bayes factors and equivalence tests are.

      Weaknesses:

      It would be interesting to investigate whether using Bayes factors and equivalence tests in addition to p-values results in a clearer scenario when applied to replication data from other fields. As mentioned by the authors, the Reproducibility Project: Experimental Philosophy (RPEP) and the Reproducibility Project: Psychology (RPP) have data attempting to replicate some original studies with null results. While the RPCB analysis yielded a similar picture when using both criteria, it is worth exploring whether this holds true for RPP and RPEP. Considerations for further research in this direction are suggested. Even if the original null results were excluded in the calculation of an overall replicability rate based on significance, sensitivity analyses considering them could have been conducted. The present authors can demonstrate replication success using the significance criteria in these two projects with initially p < 0.05 studies, both positive and non-positive.

      Other comments:

      • Introduction: The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

      • Overall picture vs. case-by-case scenario: An interesting finding is that the authors observe that in most cases, there is no substantial evidence for either the absence or the presence of an effect, as evidenced by the equivalence tests. Thus, using both suggested criteria results in a picture similar to the one initially raised by the paper itself. The work done by the authors highlights additional criteria that can be used to further analyze replication success on a case-by-case basis, and I believe that this is where the paper's main contributions lie. Despite not changing the overall picture much, I agree that the p-value criterion by itself does not distinguish between (1) a situation where the original study had low statistical power, resulting in a highly inconclusive non-significant result that does not provide evidence for the absence of an effect and (2) a scenario where the original study was adequately powered, and a non-significant result may indeed provide some evidence for the absence of an effect when analyzed with appropriate methods. Equivalence testing and Bayesian factor approaches are valuable tools in both cases.

      Regarding the 0.05 threshold, the choice of the prior distribution for the SMD under the alternative H1 is debatable, and this also applies to the equivalence margin. Sensitivity analyses, as highlighted by the authors, are helpful in these scenarios.

      Thank you for the thorough review and constructive feedback. We have added an additional “Appendix C: Null results from the RPP and EPRP” that shows equivalence testing and Bayes factor analyses for the RPP and EPRP null results.

      Reviewer #3 (Public Review):

      Summary:

      The paper points out that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. Also, it can not be considered a "replication success". The main point of the paper is rather obvious. It may be that both studies are underpowered, in which case their non-significance does not prove anything. The absence of evidence is not evidence of absence! On the other hand, statistical significance is a confusing concept for many, so some extra clarification is always welcome.

      One might wonder if the problem that the paper addresses is really a big issue. The authors point to the "Reproducibility Project: Cancer Biology" (RPCB, Errington et al., 2021). They criticize Errington et al. because they "explicitly defined null results in both the original and the replication study as a criterion for replication success." This is true in a literal sense, but it is also a little bit uncharitable. Errington et al. assessed replication success of "null results" with respect to 5 criteria, just one of which was statistical (non-)significance.

      It is very hard to decide if a replication was "successful" or not. After all, the original significant result could have been a false positive, and the original null-result a false negative. In light of these difficulties, I found the paper of Errington et al. quite balanced and thoughtful. Replication has been called "the cornerstone of science" but it turns out that it's actually very difficult to define "replication success". I find the paper of Pawel, Heyard, Micheloud, and Held to be a useful addition to the discussion.

      Strengths:

      This is a clearly written paper that is a useful addition to the important discussion of what constitutes a successful replication.

      Weaknesses:

      To me, it seems rather obvious that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. I'm not sure how often this mistake is made.

      Thanks for the feedback. We do not have systematic data on how often the mistake of confusing absence of evidence with evidence of absence has been made in the replication context, but we do know that it has been made in at least three prominent large-scale replication projects (the RPP, RPEP, RPCB). We therefore believe that there is a need for our article.

      Moreover, we agree that the RPCB provided a nuanced assessment of replication success using five different criteria for the original null results. We emphasize this now more in the “Introduction” section. However, we do not consider our article as “a little bit uncharitable” to the RPCB, as we discuss all other criteria used in the RPCB and note that our intent is not to diminish the important contributions of the RPCB, but rather to build on their work and provide constructive recommendations for future researchers. Furthermore, in response to comments made by Reviewer #2, we have added an additional “Appendix B: Null results from the RPP and EPRP” that shows equivalence testing and Bayes factor analyses for null results from two other replication projects, where the same issue arises.

      Reviewer #1 (Recommendations For The Authors):

      The authors may wish to address the dichotomy issue I raise above, either in the analysis or in the discussion.

      Thank you, we now emphasize that Bayes factors and TOST p-values do not need to be dichotomized but can be interpreted as quantitative measures of evidence, both in the “Methods for assessing replicability of null results” and the “Conclusions” sections.

      Reviewer #2 (Recommendations For The Authors):

      Given that, here follow additional suggestions that the authors should consider in light of the manuscript's word count limit, to avoid confusing the paper's main idea:

      2) Referencing: Could you reference the three interesting cases among the 15 RPCB null results (specifically, the three effects from the original paper #48) where the Bayes factor differs qualitatively from the equivalence test?

      We now explicitly cite the original and replication study from paper #48.

      3) Equivalence testing: As the authors state, only 4 out of the 15 study pairs are able to establish replication success at the 5% level, in the sense that both the original and the replication 90% confidence intervals fall within the equivalence range. Among these 4, two (Paper #48, Exp #2, Effect #5 and Paper #48, Exp #2, Effect #6) were initially positive with very low p-values, one (Paper #48, Exp #2, Effect #4) had an initial p of 0.06 and was very precisely estimated, and the only one in which equivalence testing provides a clearer picture of replication success is Paper #41, Exp #2, Effect #1, which had an initial p-value of 0.54 and a replication p-value of 0.05. In this latter case (or in all these ones), one might question whether the "liberal" equivalence range of Δ = 0.74 is the most appropriate. As the authors state, "The post-hoc specification of equivalence margins is controversial."

      We agree that the post hoc choice of equivalence ranges is a controversial issue. The margins define an equivalence region where effect sizes are considered practically negligible, and we agree that in many contexts SMD = 0.74 is a large effect size that is not practically negligible. We therefore present sensitivity analyses for a wide range of margins. However, we do not think that the choice of this margin is more controversial for the mentioned studies with low p-values than for other studies with greater p-values, since the question of whether a margin plausibly encodes practically negligible effect sizes is not related to the observed p-value of a study. Nevertheless, for the new analyses of the RPP and EPRP data in Appendix B, we have added additional sensitivity analyses showing how the individual TOST p-values and Bayes factors vary as a function of the margin and the prior standard deviation. We think that these analyses provide readers with an even more transparent picture regarding the implications of the choice of these parameters than the “project-wise” sensitivity analyses in Appendix A.

      4) Bayes factor suggestions: For the Bayes factor approach, it would be interesting to discuss examples where the BF differs slightly. This is likely to occur in scenarios where sample sizes differ significantly between the original study and replication. For example, in Paper #48, Exp #2 and Effect #4, the initial p is 0.06, but the BF is 8.1. In the replication, the BF dramatically drops to < 1/1000, as does the p-value. The initial evidence of 8.1 indicates some evidence for the absence of an effect, but not strong evidence ("strong evidence for H0"), whereas a p-value of 0.06 does not lead to such a conclusion; instead, it favors H1. It would be interesting if the authors discussed other similar cases in the paper. It's worth noting that in Paper #5, Exp #1, Effect #3, the replication p-value is 0.99, while the BF01 is 2.4, almost indicating "moderate" evidence for H0, even though the p-value is inconclusive.

      We agree that some of the examples nicely illustrate conceptual differences between p-values and Bayes factors, e.g., how they take into account sample size and effect size. As methodologists, we find these aspects interesting ourselves, but we think that emphasizing them is beyond the scope of the paper and would distract eLife readers from the main messages.

      Concerning the conceptual differences between Bayes factors and TOST p-values, we already discuss a case where there are qualitative differences in more detail (original paper #48). We added another discussion of this phenomenon in the Appendix C as it also occurs for the replication of Ranganath and Nosek (2008) that was part of the RPP.

      5) p-values, magnitude and precision: It's noteworthy to emphasize, if the authors decide to discuss this, that the p-value is influenced by both the effect's magnitude and its precision, so in Paper #9, Exp #2, Effect #6, BF01 = 4.1 has a higher p-value than a BF01 = 2.3 in its replication. However, there are cases where both p-values and BF agree. For example, in Paper #15, Exp #2, Effect #2, both the original and replication studies have similar sample sizes, and as the p-value decreases from p = 0.95 to p = 0.23, BF01 decreases from 5.1 ("moderate evidence for H0") to 1.3 (region of "Absence of evidence"), moving away from H0 in both cases. This also occurs in Paper #24, Exp #3, Effect #6.

      We appreciate the suggestions but, as explained before, think that the message of our paper is better understood without additional discussion of more general differences between p-values and Bayes factors.

      6) The grey zone: Given the above topic, it is important to highlight that in the "Absence of evidence grey zone" for the null hypothesis, for example, in Paper #5, Exp #1, Effect #3 with a p = 0.99 and a BF01 = 2.4 in the replication, BF and p-values reach similar conclusions. It's interesting to note, as the authors emphasize, that Dawson et al. (2011), Exp #2, Effect #2 is an interesting example, as the p-value decreases, favoring H1, likely due to the effect's magnitude, even with a small sample size (n = 3 in both original and replications). Bayes factors are very close to one due to the small sample sizes, as discussed by the authors.

      We appreciate the constructive comments. We think that the two examples from Dawson et al. (2011) and Goetz et al. (2011) already nicely illustrate absence of evidence and evidence of absence, respectively, and therefore decided not to discuss additional examples in detail, to avoid redundancy.

      7) Using meta-analytical results (?): For papers from RPCB, comparing the initial study with the meta-analytical results using Bayes factor and equivalence testing approaches (thus, increasing the sample size of the analysis, but creating dependency of results since the initial study would affect the meta-analytical one) could change the conclusions. This would be interesting to explore in initial studies that are replicated by much larger ones, such as: Paper #9, Exp #2, Effect #6; Goetz et al. (2011), Exp #1, Effect #1; Paper #28, Exp #3, Effect #3; Paper #41, Exp #2, Effect #1; and Paper #47, Exp #1, Effect #5).

      Thank you for the suggestion. We considered adding meta-analytic TOST p-values and Bayes factors before, but decided that Figure 3 and the results section are already quite technical, so adding more analyses may confuse more than help. Nevertheless, these meta-analytic approaches are discussed in the “Conclusions” section.

      8) Other samples of fields of science: It would be interesting to investigate whether using Bayes factors and equivalence tests in addition to p-values results in a clearer scenario when applied to replication data from other fields. As mentioned by the authors, the Reproducibility Project: Experimental Philosophy (RPEP) and the Reproducibility Project: Psychology (RPP) have data attempting to replicate some original studies with null results. While the RPCB analysis yielded a similar picture when using both criteria, it is worth exploring whether this holds true for RPP and RPEP. Considerations for further research in this direction are suggested. Even if the original null results were excluded in the calculation of an overall replicability rate based on significance, sensitivity analyses considering them could have been conducted. The present authors can demonstrate replication success using the significance criteria in these two projects with initially p < 0.05 studies, both positive and non-positive.

      Thank you for the excellent suggestion. We added an Appendix B where the null results from the RPP and EPRP are analyzed with our proposed approaches. The results are also discussed in the “Results” and “Conclusions” sections.

      9) Other approaches: I am curious about the potential impact of using an approach based on equivalence testing (as described in https://arxiv.org/abs/2308.09112). It would be valuable if the authors could run such analyses or reference the mentioned work.

      Thank you. We were unaware of this preprint. It seems related to the framework proposed by Stahel W. A. (2021) New relevance and significance measures to replace p-values. PLoS ONE 16(6): e0252991. https://doi.org/10.1371/journal.pone.0252991

      We now cite both papers in the discussion.

      10) Additional evidence: There is another study in which replications of initially p > 0.05 studies with p > 0.05 replications were also considered as replication successes. You can find it here: https://www.medrxiv.org/content/10.1101/2022.05.31.22275810v2. Although it involves a small sample of initially p > 0.05 studies with already large sample sizes, the work is currently under consideration for publication in PLOS ONE, and all data and materials can be accessed through OSF (links provided in the work).

      Thank you for sharing this interesting study with us. We feel that it is beyond the scope of the paper to include further analyses as there are already analyses of the RPCB, RPP, and EPRP null results. However, we will keep this study in mind for future analysis, especially since all data are openly available.

      11) Additional evidence 02: Ongoing replication projects, such as the Brazilian Reproducibility Initiative (BRI) and The Sports Replication Centre (https://ssreplicationcentre.com/), continue to generate valuable data. BRI is nearing completion of its results, and it promises interesting data for analyzing replication success using p-values, equivalence regions, and Bayes factor approaches.

      We now cite these two initiatives as examples of ongoing replication projects in the introduction. Similarly as for your last point, we think that it is beyond the scope of the paper to include further analyses as there are already analyses of the RPCB, RPP, and EPRP null results.

      Reviewer #3 (Recommendations For The Authors):

      I have no specific recommendations for the authors.

      Thank you for the constructive review.

      Reviewing Editor (Recommendations For the Authors):

      I recognize that it was suggested to the authors by the previous Reviewing Editor to reduce the amount of statistical material to be made more suitable for a non-statistical audience, and so what I am about to say contradicts advice you were given before. But, with this revised version, I actually found it difficult to understand the particulars of the construction of the Bayes Factors and would have appreciated a few more sentences on the underlying models that fed into the calculations. In my opinion, the provided citations (e.g., Dienes Z. 2014. Using Bayes to get the most out of non-significant results) did not provide sufficient background to warrant a lack of more technical presentation here.

      Thank you for the feedback. We added a new “Appendix C: Technical details on Bayes factors” that provides technical details on the models, priors, and calculations underlying the Bayes factors.

    1. When we’ve been accessing Reddit through Python and the “PRAW” code library. The praw code library works by sending requests across the internet to Reddit, using what is called an “application programming interface” [h3] or API for short. APIs have a set of rules for what requests you can make, what happens when you make the request, and what information you can get back.

      The explanation provided about how the PRAW library functions as a mediator between Python applications and Reddit through the use of APIs is quite illuminating. APIs, as described, serve as the bridge that facilitates these interactions under a set of defined rules and protocols. This brings to mind the essential nature of understanding the limits and capabilities of any API when developing software that depends on external services. It would be interesting to explore further how robust the error handling capabilities of the PRAW library are. Specifically, how does PRAW manage or relay errors that arise from API limitations or disruptions in Reddit's service? This is crucial for developers to ensure their applications can gracefully handle such issues and maintain a good user experience.

    2. When we’ve been accessing Reddit through Python and the “PRAW” code library. The praw code library works by sending requests across the internet to Reddit, using what is called an “application programming interface” [h3] or API for short. APIs have a set of rules for what requests you can make, what happens when you make the request, and what information you can get back.

      I am not well informed on how API works but it sounds like it has a lot of connection to the internet and other kind of information systems. Going back to the sources of social media data, one of the things that platforms could record are what users click on, when they log on or off, etc. What arises from this I think ties back in with the ethical frameworks we were talking about in chapter 2. The discussion becomes what course of action is correct because even if the platform records information on the behavior of user interaction, it boils down to the idea that even if it's to mazimize user experience, should platforms be allowed to record information that could be personal?

    1. the 31,085 lines of configure for libtool still check if <sys/stat.h> and <stdlib.h> exist, even though the Unixen, which lacked them, had neither sufficient memory to execute libtool nor disks big enough for its 16-MB source code.

      yummy

    1. One of the biggest advantages of using Cubit is simplicity. When creating a Cubit, we only have to define the state as well as the functions which we want to expose to change the state. In comparison, when creating a Bloc, we have to define the states, events, and the EventHandler implementation. This makes Cubit easier to understand and there is less code involved.

      Cubit和Bloc的区别:

      Cubit只需要定义state和能改变state的function

      Bloc要定义state,event和event handler

    1. The “DAO Model Law” guide by COALA researchers outlines 11 technical and governance requirements for DAOs to meet the requirements for legal recognition as an entity, including:1. Deployed on a blockchain,2. Provide a unique public address for others to review its operations,3. Open source software code,4. Get code audited,5. Have at least one interface for laypeople to read critical information on DAO smart contracts and tokens,6. Have by-laws that are comprehensible to lay people,7. Have governance that is technically decentralized (i.e. not controlled by a single party),8. Have at least one member at any given time,9. Have a specific way for people to contact the DAO,10. Have a binding internal dispute resolution mechanism for participants,11. Have an external dispute resolution mechanism to resolve disputes with third-parties (e.g. service providers).These factors and considerations constitute a legal basis for conceptualizing DAOs.
    1. Nicole Nguyen. Here's Who Facebook Thinks You Really Are. September 2016. Section: Tech. URL: https://www.buzzfeednews.com/article/nicolenguyen/facebook-ad-preferences-pretty-accurate-tbh (visited on 2024-01-30).

      In the article it mentioned that many non facebook sites use JavaScript code that tells the mothership what kind of content you're looking at when you're not on Facebook's site and apps. Even if done legally, that doesn't make it the most ethical choice. I think there are better and more ethical ways to understand the target market of your audience. I think this is smart to engage and understand users better but it just doesn't feel right to be about in someone's own personal life when they don't know about it.

    1. toString Returns a String representation of an object. By default, it returns the class name and a hexidecimal representation of the hashCode. That's not very useful, so it's common to override this method. hashCode Returns an int code that's used for storing an object in hashed data structures. getClass Returns the Class associated to the object. An instance of a Class contains meta-data (names, parameters, annotations) associated to a class. equals Returns a boolean that indicates if this instance is equal to another object. By default, it evaluates to true if the objects share the same memory location -- called reference equality -- they share the same reference. It's common to override this method to inspect individual values instead of comparing references.

      Object methods

    1. Instructions: Step 1: Briefly summarize the “best fit occupations” results of the combined assessment (about 100 words). Step 2: Reflect on the combined results of your assessments as they relate to your current career interest (about 400 words). Consider responding to one or more of following prompts: In the Work Interest assessment, what is your Holland Code (please use the letters and descriptive titles)? How well do these three descriptors fit your current career interest? How might these descriptors help you select a better fitting career goal? In the Leisure Interest assessment, what are your top three leisure interests? How well do these three descriptors fit your current career interest? How might these descriptors help you select a better fitting career goal? What “best fit” occupation recommendations do you agree with? What recommendations do you disagree with? Why? Which of the five assessments (work, leisure, skills, personality, values) are most important to you personally? Select three assessments and run another combined report. Are the results any different? Did the results provide you with any new insights? You may also comment on the insights gained from the Focus 2 Career Assessment and how they relate to the results of previous assessment you have completed while in LEAD Scholars including True Colors, Strengths, and 16-Personalities. Step 3: Provide one personal insight about your career path gained from this learning activity.

      delete instructions

    1. créer une liste non ordonnée

      suite à la création de la liste non ordonnée une erreur Prettier s'affiche dans la console et Prettier ne met plus en page le code comme auparavant. quelqu'un sait il pourquoi ?

    2. Vous pouvez théoriquement mettre plusieurs balises  <br>  d'affilée pour faire plusieurs sauts de lignes, mais on considère que c'est une mauvaise pratique qui rend le code délicat à maintenir.

      L'utilisation de plusieurs balises

      pour avoir le même résultat est-elle également considéré comme une mauvaise pratique ?

    3. Si besoin, voici la liste complète des codes de langue.

      Comment configurer cela pour un site utilisé a l'international ? Par exemple sur Youtube, faut-il créer un code différent pour chaque langues utilisées ?

    1. Author response:

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

      Reviewer 1

      (1) Given the low trial numbers, and the point of sequential vs clustered reactivation mentioned in the public review, it would be reassuring to see an additional sanity check demonstrating that future items that are currently not on-screen can be decoded with confidence, and if so, when in time the peak reactivation occurs. For example, the authors could show separately the decoding accuracy for near and far items in Fig. 5A, instead of plotting only the difference between them.

      We have now added the requested analysis showing the raw decoded probabilities for near and distant items separately in Figure 5A. We have also chosen to replace Figure 5B with the new figure as we think it provides more information than the previous Figure 5B. Instead, we have moved Figure 5B to the supplement. The median peak decoded accuracy for near and distant items is equivalent. We have added the following description to the figure:

      “Decoded raw probabilities for off-screen items, that were up to two steps ahead of the current stimulus cue (‘near’,) vs. distant items that were more than two steps away on the graph, on trials with correct answers. The median peak decoded probability for near and distant items was at the same time point for both probability categories. Note that displayed lines reflect the average probability while, to eliminate influence of outliers, the peak displays the median.”

      (2) The non-sequential reactivation analyses often use a time window of peak decodability, and it was not entirely clear to me what data this time window is determined on, e.g., was it determined based on all future reactivations irrespective of graph distance? This should be clarified in the methods.

      Thank you for raising this. We now clarify this in the relevant section to read: “First, we calculated a time point of interest by computing the peak probability estimate of decoders across all trials, i.e., the average probability for each timepoint of all trials (except previous onscreen items) of all distances, which is equivalent to the peak of the differential reactivation analysis”

      (3) Fig 4 shows evidence for forward and backward sequential reactivation, suggesting that both forward and backward replay peak at a lag of 40-50msec. It would be helpful if this counterintuitive finding could be picked up in the discussion, explaining how plausible it is, physiologically, to find forward and backward replay at the same lag, and whether this could be an artifact of the TDLM method.

      This is an important point and we agree that it appears counterintuitive. However, we would highlight this exact time range has been reported in previous studies, though t never for both forward and backward replay. We now include a discussion of this finding. The section now reads:

      “[… ] Even though we primarily focused on the mean sequenceness scores across time lags, there appears s to be a (non-significant) peak at 40-60 milliseconds. While simultaneous forward and backward replay is theoretically possible, we acknowledge that it is somewhat surprising and, given our paradigm, could relate to other factors such as autocorrelations (Liu, Dolan, et al., 2021).”

      (4) It is reported that participants with below 30% decoding accuracy are excluded from the main analyses. It would be helpful if the manuscript included very specific information about this exclusion, e.g., was the criterion established based on the localizer cross-validated data, the temporal generalisation to the cued item (Fig. 2), or only based on peak decodability of the future sequence items? If the latter, is it applied based on near or far reactivations, or both?

      We now clarify this point to include more specific information, which reads:

      “[…] Therefore, we decided a priori that participants with a peak decoding accuracy of below 30% would be excluded from the analysis (nine participants in all) as obtained from the cross-validation of localizer trials”

      (5) Regarding the low amount of data for the reactivation analysis, the manuscript should be explicit about the number of trials available for each participant. For example, Supplemental Fig. 1 could provide this information directly, rather than the proportion of excluded trials.

      We have adapted the plot in the supplement to show the absolute number of rejected epochs per participant, in addition to the ratio.

      (6) More generally, the supplements could include more detailed information in the legends.

      We agree and have added more extensive explanation of the plots in the supplement legends.

      (7) The choice of comparing the 2 nearest with all other future items in the clustered reactivation analysis should be better motivated, e.g., was this based on the Wimmer et al. (2020) study?

      We have added our motivation for taking the two nearest items and contrasting them with the items further away. The paragraph reads:

      “[…] We chose to combine the following two items for two reasons: First, this doubled the number of included trials; secondly, using this approach the number of trials for each category (“near” and “distant”) was more balanced. […]”

      Reviewer 2

      (1) Focus exclusively on retrieval data (and here just on the current image trials).

      If I understand correctly, you focus all your analyses (behavioural as well as MEG analyses) on retrieval data only and here just on the current image trials. I am surprised by that since I see some shortcomings due to that. These shortcomings can likely be addressed by including the learning data (and predecessor image trials) in your analyses.

      a) Number of trials: During each block, you presented each of the twelve edges once. During retrieval, participants then did one "single testing session block". Does that mean that all your results are based on max. 12 trials? Given that participants remembered, on average, 80% this means even fewer trials, i.e., 9-10 trials?

      This is correct and a limitation of the paper. However, while we used only correct trials for the reactivation analysis, the sequential analysis was conducted using all trials disregarding the response behaviour. To retain comparability with previous studies we mainly focused on data from after a consolidation phase. Nevertheless, despite the trial limitation we consider the results are robust and worth reporting. Additionally, based on the suggestion of the referee, we now include results from learning blocks (see below).

      b) Extend the behavioural and replay/reactivation analysis to predecessor images.

      Why do you restrict your analyses to the current image trials? Especially given that you have such a low trial number for your analyses, I was wondering why you did not include the predecessor trials (except the non-deterministic trials, like the zebra and the foot according to Figure 2B) as well.

      We agree it would be great to increase power by adding the predecessor images to the current image cue analysis, excluding the ambiguous trials, we did not do so as we considered the underlying retrieval processes of these trial types are not the same, i.e. cannot be simply combined. Nevertheless, we have performed the suggested analysis to check if it increases our power. We found, that the reactivation effect is robust and significant at the same time point of 220-230 ms. However, the effect size actually decreased: While before, peak differential reactivation was at 0.13, it is now at 0.07. This in fact makes conceptual sense. We suspect that the two processes that are elicited by showing a single cue and by showing a second, related, cue are distinct insofar as the predecessor image acts as a primer for the current image, potentially changing the time course/speed of retrieval. Given our concerns that the two processes are not actually the same we consider it important to avoid mixing these data.

      We have added a statement to the manuscript discussing this point. The section reads:

      “Note that we only included data from the current image cue, and not from the predecessor image cue, as we assume the retrieval processes differ and should not be concatenated.”

      c) Extend the behavioural and replay/reactivation analysis to learning trials.

      Similar to point 1b, why did you not include learning trials in your analyses?

      The advantage of including (correct and incorrect) learning trials has the advantage that you do not have to exclude 7 participants due to ceiling performance (100%).

      Further, you could actually test the hypothesis that you outline in your discussion: "This implies that there may be a switch from sequential replay to clustered reactivation corresponding to when learned material can be accessed simultaneously without interference." Accordingly, you would expect to see more replay (and less "clustered" reactivation) in the first learning blocks compared to retrieval (after the rest period).

      To track reactivation and replay over the course of learning is a great idea. We have given a lot of thought as to how to integrate these findings but have not found a satisfying solution. Thus, analysis of the learning data turned out to be quite tricky: We decided that each participant should perform as many blocks as necessary to reach at least 80% (with a limit of six and lower bound of two, see Supplement figure 4). Indeed, some participant learned 100% of the sequence after one block (these were mostly medical students, learning things by hard is their daily task). With the benefit of hindsight, we realise our design means that different blocks are not directly comparable between participants. In theory, we would expect that replay emerges in parallel with learning and then gradually changes to clustered reactivation as memory traces become consolidated/stronger. However, it is unclear when replay should emerge and when precisely a switch to clustered reactivation would happen. For this reason, we initially decided not to include the learning trials into the paper.

      Nevertheless, to provide some insight into the learning process, and to see how consolidation impacts differential reactivation and replay, we have split our data into pre and post resting state, aggregating all learning trials of each participant. While this does not allow us to track processes on a block basis, it does offer potential (albeit limited) insight into the hypothesis we outline in the discussion.

      For reactivation, we see emergence of a clear increase, further strengthening the outlined hypothesis, however, for replay the evidence is less clear, as we do not know over how many learning blocks replay is expected.

      We calculated individual trajectories of how reactivation and replay changes from learning to retrieval and related these to performance. Indeed, we see an increase of reactivation is nominally associated with higher learning performance, while an increase in replay strength is associated with lower performance (both non-significant). However, due to the above-mentioned reasons we think it would premature to add this weak evidence to the paper.

      To mitigate problems of experiment design in relation to this question we are currently implementing a follow-study, where we aim to normalize the learning process across participants and index how replay/reactivation changes over the course of learning and after consolidation.

      We have added plots showing clustered reactivation sequential replay measures during learning (Figure 5D and Supplement 8)

      The added section(s) now read:

      “To provide greater detail on how the 8-minute consolidation period affected reactivation we, post-hoc, looked at relevant measures across learning trials in contrast to retrieval trials. For all learning trials, for each participant, we calculated differential reactivation for the same time point we found significant in the previous analysis (220-260 milliseconds). On average, differential reactivation probability increased from pre to post resting state (Figure 5D). […]

      Nevertheless, even though our results show a nominal increase in reactivation from learning to retrieval (see Figure 5D), due to experimental design features our data do not enable us to test for an hypothesized switch for sequential replay (see also “limitations” and Supplement 8).”

      d) Introduction (last paragraph): "We examined the relationship of graph learning to reactivation and replay in a task where participants learned a ..." If all your behavioural analyses are based on retrieval performance, I think that you do not investigate graph learning (since you exclusively focus the analyses on retrieving the graph structure). However, relating the graph learning performance and replay/reactivation activity during learning trials (i.e., during graph learning) to retrieval trials might be interesting but beyond the scope of this paper.

      We agree. We have changed the wording to be more accurate. Indeed, we do not examine graph learning but instead examine retrieval from a graph, after graph learning. The mentioned sentence now read

      “[…] relationship of retrieval from a learned graph structure to reactivation [...]”

      e) It is sometimes difficult to follow what phase of the experiment you refer to since you use the terms retrieval and test synonymously. Not a huge problem at all but maybe you want to stick to one term throughout the whole paper.

      Thank you for pointing this out. We have now adapted the manuscript to exclusively refer to “retrieval” and not to “test”.

      (2) Is your reactivation clustered?

      In Figure 5A, you compare the reactivation strength of the two items following the cue image (i.e., current image trials) with items further away on the graph. I do not completely understand why your results are evidence for clustered reactivation in contrast to replay.

      First, it would be interesting to see the reactivation of near vs. distant items before taking the difference (time course of item probabilities).

      (copied answer from response to Reviewer 1, as the same remark was raised)

      We have added the requested analysis showing the raw decoded probabilities for near and distant items separately in Figure 5A. We have chosen to replace Figure 5B with the new figure as we think that it offers more information than the previous Figure 5B. Instead, we have moved Figure 5B to the supplement. The median peak decoded accuracy for near and distant items is equivalent. We have added the following description to the figure:

      “Decoded raw probabilities for off-screen items, that were up to two steps ahead of the current stimulus cue (‘near’,) vs. distant items that were more than two steps away on the graph, on trials with correct answers. The median peak decoded probability for near and distant items was at the same time point for both probability categories. Note that displayed lines reflect the average probability while, to eliminate influence of outliers, the peak displays the median. .”

      Second, could it still be that the first item is reactivated before the second item? By averaging across both items, it becomes not apparent what the temporal courses of probabilities of both items look like (and whether they follow a sequential pattern). Additionally, the Gaussian smoothing kernel across the time dimension might diminish sequential reactivation and favour clustered reactivation. (In the manuscript, what does a Gaussian smoothing kernel of  = 1 refer to?). Could you please explain in more detail why you assume non-sequential clustered reactivation here and substantiate this with additional analyses?

      We apologise for the unclear description. Note the Gaussian kernel is in fact only used for the reactivation analysis and not the replay analysis, so any small temporal successions would have been picked up by the sequential analysis. We now clarify this in the respective section of the sequential analysis and also explain the parameter of delta= 1 in the reactivation analysis section. The paragraph now reads

      “[…] As input for the sequential analysis, we used the raw probabilities of the ten classifiers corresponding to the stimuli. [...]

      […] Therefore, to address this we applied a Gaussian smoothing kernel (using scipy.ndimage.gaussian_filter with the default parameter of σ=1 which corresponds approximately to taking the surrounding timesteps in both direction with the following weighting: current time step: 40%, ±1 step: 25%, ±2 step: 5%, ±3 step: 0.5%) [...]”

      (3) Replay and/or clustered reactivation?

      The relationship between the sequential forward replay, differential reactivation, and graph reactivation analysis is not really apparent. Wimmer et al. demonstrated that high performers show clustered reactivation rather than sequential reactivation. However, you did not differentiate in your differential reactivation analysis between high vs. low performers. (You point out in the discussion that this is due to a low number of low performers.)

      We agree that a split into high vs low performers would have been preferably for our analysis. However, there is one major obstacle that made us opt for a correlational analysis instead: We employed criteria learning, rendering a categorical grouping conceptually biased. Even though not all participants reached the criteria of 80%, our sample did not naturally split between high and low performers but was biased towards higher performance, leaving the groups uneven. The median performance was 83% (mean ~81%), with six of our subjects (~1/4th of included participant) having this exact performance. This makes a median or mean split difficult, as either binning assignment choice would strongly affect the results. We have added a limitations section in which we extensively discuss this shortcoming and reasoning for not performing a median split as in Wimmer et al (2020). The section now reads:

      “There are some limitations to our study, most of which originate from a suboptimal study design. [...], as we performed criteria learning, a sub-group analysis as in Wimmer et al., (2020) was not feasible, as median performance in our sample would have been 83% (mean 81%), with six participants exactly at that threshold. [...]”

      It might be worth trying to bring the analysis together, for example by comparing sequential forward replay and differential reactivation at the beginning of graph learning (when performance is low) vs. retrieval (when performance is high).

      Thank you for the suggestion to include the learning segments, which we think improves the paper quite substantially. However, analysis of the learning data turned out to be quite tricky> We had decided that each participant should perform as many blocks as necessary to reach at least 80% accuracy (with a limit of six and lower bound of two, see Supplement figure 4). Some participants learned 100% of the sequence after one block (these were mostly medical students, learning things by hard is their daily task). This in hindsight is an unfortunate design feature in relation to learning as it means different blocks are not directly comparable between participants.

      In theory, we would expect that replay emerges in parallel with learning and then gradually change to clustered reactivation, as memory traces get consolidated/stronger. However, it is unclear when replay would emerge and when the switch to reactivation would happen. For this reason, we initially decided not to include the learning trials into the paper at all.

      Nevertheless, to give some insight into the learning process and to see how consolidation effects differential reactivation and replay, we have split our data into pre and post resting state, aggregating all learning trials of each participant. While this does not allow us to track measures of interest on a block basis, it gives some (albeit limited) insight into the hypothesis outlined in our discussion.

      For reactivation, we see a clear increase, further strengthening the outlined hypothesis, However, for replay the evidence is less obvious, potentially due to that fact that we do not know across how many learning blocks replay is to be expected.

      The added section(s) now read:

      “To examine how the 8-minute consolidation period affected reactivation we, post-hoc, looked at relevant measures during learning trials in contrast to retrieval trials. For all learning trial, for each participant, we calculated differential reactivation for the time point we found significant during the previous analysis (220-260 milliseconds). On average, differential reactivation probability increased from pre to post resting state (Figure 5D).

      […]

      Nevertheless, even though our results show a nominal increase in reactivation from learning to retrieval (see Figure 5D), our data does not enable us to show an hypothesized switch for sequential replay (see also “limitations” and Supplement 8).”

      Additionally, the main research question is not that clear to me. Based on the introduction, I thought the focus was on replay vs. clustered reactivation and high vs. low performance (which I think is really interesting). However, the title is more about reactivation strength and graph distance within cognitive maps. Are these two research questions related? And if so, how?

      We agree we need to be clearer on this point. We have added two sentences to the introduction, which should address this point. The section now reads:

      “[…] In particular, the question remains how the brain keeps track of graph distances for successful recall and whether the previously found difference between high and low performers also holds true within a more complex graph learning context.”

      (4) Learning the graph structure.

      I was wondering whether you have any behavioural measures to show that participants actually learn the graph structure (instead of just pairs or triplets of objects). For example, do you see that participants chose the distractor image that was closer to the target more frequently than the distractor image that was further away (close vs. distal target comparison)? It should be random at the beginning of learning but might become more biased towards the close target.

      Thanks, this is an excellent suggestion. Our analysis indeed shows that people take the near lure more often than the far lure in later blocks, while it is random in the first block.

      Nevertheless, we have decided to put these data into the supplement and reference it in the text. This is because analysis of the learning blocks is challenging and biased in general. Each participant had a different number of learning blocks based on their learning rate, and this makes it difficult to compare learning across participants. We have tried our best to accommodate and explain these difficulties in the figure legend. Nevertheless, we thank the referee for guidance here and this analysis indeed provides further evidence that participants learned the actual graph structure.

      The added section reads

      “Additionally, we have included an analysis showing how wrong answers participants provided were random in the first block and biased towards closer graph nodes in later blocks. This is consistent with participants actually learning the underlying graph structure as opposed to independent triplets (see figure and legend of Supplement 6 for details).”

      (5) Minor comments

      a) "Replay analysis relies on a successive detection of stimuli where the chance of detection exponentially decreases with each step (e.g., detecting two successive stimuli with a chance of 30% leaves a 9% chance of detecting the replay event). " Could you explain in more detail why 30% is a good threshold then?

      Thank you. We have further clarified the section. As we are working mainly with probabilities, it is useful to keep in mind that accuracy is a class metric that only provides a rough estimate of classifier ability. Alternatively, something like a Top-3-Accuracy would be preferable, but also slightly silly in the context of 10 classes.

      Nevertheless, subtle changes in probability estimates are present and can be picked up by the methods we employ. Therefore, the 30% is a rough lower bound and decided based on pilot data that showed that clean MEG data from attentive participants can usually reach this threshold. The section now reads:

      “(e.g., detecting two successive stimuli with a chance of 30% leaves a 9% chance of detecting a replay event). However, one needs to bear in mind that accuracy is a “winnertakes-all” metric indicating whether the top choice also has the highest probability, disregarding subtle, relative changes in assigned probability. As the methods used in this analysis are performed on probability estimates and not class labels, one can expect that the 30% are a rough lower bound and that the actual sensitivity within the analysis will be higher. Additionally, based on pilot data, we found that attentive participants were able to reach 30% decodability, allowing us to use decodability as a data quality check. “

      b) Could you make explicit how your decoders were designed? Especially given that you added null data, did you train individual decoders for one class vs. all other classes (n = 9 + null data) or one class vs. null data?

      We added detail to the decoder training. The section now reads

      “Decoders were trained using a one-vs-all approach, which means that for each class, a separate classifier was trained using positive examples (target class) and negative examples (all other classes) plus null examples (data from before stimulus presentation, see below). In detail, null data was.”

      c) Why did you choose a ratio of 1:2 for your null data?

      Our choice for using a higher ratio was based upon previous publications reporting better sensitivity of TDLM using higher ratios, as spatial sensor correlations are decreasing. Nevertheless, this choice was not well investigated beforehand. We have added more information to this to the manuscript

      d) You could think about putting the questionnaire results into the supplement if they are sanity checks.

      We have added the questionnaire results. However, due to the size of the tables, we have decided to add them as excel files into the supplementary files of the code repository. We have mentioned the existence file in the publication.

      e) Figure 2. There is a typo in D: It says "Precessor Image" instead of "Predecessor Image".

      Fixed typo in figure.

      f) You write "Trials for the localizer task were created from -0.1 to 0.5 seconds relative to visual stimulus onset to train the decoders and for the retrieval task, from 0 to 1.5 seconds after onset of the second visual cue image." But the Figure legend 3D starts at -0.1 seconds for the retrieval test.

      We have now clarified this. For the classifier cross-validation and transfer sanity check and clustered analysis we used trials from -0.1 to 0.5s, whereas for the sequenceness analysis of the retrieval, we used trials from 0 to 1.5 seconds

    1. Taking values near 15/11 shows nothing too unusual:

      The following code is not working getting the following error: julia> [xs i.(xs)] ERROR: UndefVarError: i not defined Stacktrace: [1] top-level scope @ REPL[41]:1

    1. All code execution happens inside the browser’s security sandbox, not on remote VMs or local binaries.

      All running in the browser not on remote WMs

    1. ons: Step 1: Briefly summarize the “best fit occupations” results of the combined assessment (about 100 words). Step 2: Reflect on the combined results of your assessments as they relate to your current career interest (about 400 words). Consider responding to one or more of following prompts: In the Work Interest assessment, what is your Holland Code (please use the letters and descriptive titles)? How well do these three descriptors fit your current career interest? How might these descriptors help you select a better fitting career goal? In the Leisure Interest assessment, what are your top three leisure interests? How well do these three descriptors fit your current career interest? How might these descriptors help you select a better fitting career goal? What “best fit” occupation recommendations do you agree with? What recommendations do you disagree with? Why? Which of the five assessments (work, leisure, skills, personality, values) are most important to you personally? Select three assessments and run another combined report. Are the results any different? Did the results provide you with any new insights? You may also comment on the insights gained from the Focus 2 Career Assessment and how they relate to the results of previous assessment you have completed while in LEAD Scholars including True Colors, Strengths, and 16-Personalities. Step 3: Provide one personal insight about your career path gained from this learning activity. My best fit occupations included a Toy designer, an Architect, an Actor/Actress, and Funeral Director. I picked the top four to discuss. It’s interesting to me because the only occupation out of those four that have really interested me would be the architect. The Toy designer occupation seems very interesting, it has to do with arts and entertainment. I consider myself a very creative person so I could see why I got this occupation. It said that my values, personality, skills, and leisure all aligned with this occupation. The second one was an Architect. This occupation has to do with Architecture and engineering. This occupation has interested me before, because of the creativity it involves. It said that my values, skills, and leisures all aligned with this occupation. The third one was an actress. This one was very cool to see, but the last time I performed in a play was 7 years ago in middle school. I was never a theater kid or interested in being one. For this one it said my personality and leisure aligned. And lastly, a funeral director. I really did not know what to think about this one when I saw it. For this one it said work, personality,  and skills all aligned. My current career interest is becoming a Pediatric Nurse Practitioner. I love to work with kids because they are so happy all the time, and I also love science and how the human body works. Lastly I want to do something in my life that is meaningful, like helping others. It was interesting to see how this assessment played out regarding my current career interest. In the leisure assessment, my top three leisure interests include Aesthetic (The creators), Correct (The Organizers) and Eager (The persuaders). I can 100% agree with these interests.It says The creators Tend to be creative and intuitive, enjoy activities like writing, painting, sculpturing, playing a musical instrument, performing, and more, enjoy working in an unstructured environment where they can use their imagination and creativity, and often described as being: open, imaginative, original, intuitive, emotional, independent, idealistic, and unconventional. It says that the The Organizers like to be involved in activities that follow set procedures and routines, like to work with data and details, have clerical or numerical ability, and carry out tasks in great detail, and often described as being conforming, practical, careful, obedient, thrifty, efficient, orderly, conscientious, and persistent. And lastly it says that The persuaders like to influence others, enjoy persuading others to see their point of view, like to work with people and ideas, rather than things, and often described as being adventurous, energetic, optimistic, agreeable, extroverted, popular, sociable, self-confident, and ambitious. All of these characteristics perfectly describe me. I don’t really think that any of the “best fit” occupations are for me. The only one I could see myself being in is an architect, but again that is nothing close to a nurse practitioner. The most important out of the five assessments to me would be values. I decided to run another report with just values, personality and skills to see what I would get. The occupation that fit me the most with those three was a clinical psychologist. Now this is more into the occupation I could see myself in. It’s more into the sciences which I liked. As I scrolled through the careers that matched, I realized the only one that was remotely close to a Nurse Practitioner was a Family Practitioner, which I would have to get a medical degree in. In conclusion, I very much enjoyed completing this assessment, and it made me realize other career options I could consider based on my personality, values, leisure, work interest, and skills.

      delete the session on your best fit occupations--that info goes into your Career Ready Portfolio, not the SLJ.

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Gap junction channels establish gated intercellular conduits that allow the diffusion of solutes between two cells. Hexameric connexin26 (Cx26) hemichannels are closed under basal conditions and open in response to CO2. In contrast, when forming a dodecameric gapjunction, channels are open under basal conditions and close with increased CO2 levels. Previous experiments have implicated Cx26 residue K125 in the gating mechanism by CO2, which is thought to become carbamylated by CO2. Carbamylation is a labile post-translational modification that confers negative charge to the K125 side chain. How the introduction of a negative charge at K125 causes a change in gating is unclear, but it has been proposed that carbamylated K125 forms a salt bridge with the side chain at R104, causing a conformational change in the channel. It is also unclear how overall gating is controlled by changes in CO2, since there is significant variability between structures of gap-junction channels and the cytoplasmic domain is generally poorly resolved. Structures of WT Cx26 gap-junction channels determined in the presence of various concentrations of CO2 have suggested that the cytoplasmatic N-terminus changes conformation depending on the concentration of the gas, occluding the pore when CO2 levels are high.

      In the present manuscript, Deborah H. Brotherton and collaborators use an intercellular dyetransfer assay to show that Cx26 gap-junction channels containing the K125E mutation, which mimics carbamylation caused by CO2, is constitutively closed even at CO2 concentrations where WT channels are open. Several cryo-EM structures of WT and mutant Cx26 gap junction channels were determined at various conditions and using classification procedures that extracted more than one structural class from some of the datasets. Together, the features on each of the different structures are generally consistent with previously obtained structures at different CO2 concentrations and support the mechanism that is proposed in the manuscript. The most populated class for K125E channels determined at high CO2 shows a pore that is constricted by the N-terminus, and a cytoplasmic region that was better resolved than in WT channels, suggesting increased stability. The K125E structure closely resembles one of the two major classes obtained for WT channels at high CO2. These findings support the hypothesis that the K125E mutation biases channels towards the closed state, while WT channels are in an equilibrium between open and closed states even in the presence of high CO2. Consistently, a structure of K125E obtained in the absence of CO2 appeared to also represent a closed state but at lower resolution, suggesting that CO2 has other effects on the channel beyond carbamylation of K125 that also contribute to stabilizing the closed state. Structures determined for K125R channels, which are constitutively open because arginine cannot be carbamylated, and would be predicted to represent open states, yielded apparently inconclusive results.

      A non-protein density was found to be trapped inside the pore in all structures obtained using both DDM and LMNG detergents, suggesting that the density represents a lipid rather than a detergent molecule. It is thought that the lipid could contribute to the process of gating, but this remains speculative. The cytoplasmic region in the tentatively closed structural class of the WT channel obtained using LMNG was better resolved. An additional portion of the cytoplasmic face could be resolved by focusing classification on a single subunit, which had a conformation that resembled the AlphaFold prediction. However, this single-subunit conformation was incompatible with a C6-symmetric arrangement. Together, the results suggest that the identified states of the channel represent open states and closed states resulting from interaction with CO2. Therefore, the observed conformational changes illuminate a possible structural mechanism for channel gating in response to CO2.

      Some of the discussion involving comparisons with structures of other gap junction channels are relatively hard to follow as currently written, especially for a general readership. Also, no additional functional experiments are carried out to test any of the hypotheses arising from the data. However, structures were determined in multiple conditions, with results that were consistent with the main hypothesis of the manuscript. No discussion is provided, even if speculative, to explain the difference in behavior between hemichannels and gap junction channels. Also, no attempt was made to measure the dimensions of the pore, which is relevant because of the importance of identifying if the structures indeed represent open or closed states of the channel.

      We have considerably revised the manuscript in an attempt to make it more tractable. We respond to the individual comments below.

      Reviewer #2 (Public Review):

      Summary:

      The manuscript by Brotherton et al. describes a structural study of connexin-26 (Cx26) gap junction channel mutant K125E, which is designed to mimic the CO2-inhibited form of the channel. In the wild-type Cx26, exposure to CO2 is presumed to close the channel through carbamylation of the residue K125. The authors mutated K125 to a negatively charged residue to mimic this effect, and they observed by cryo-EM analysis of the mutated channel that the pore of the channel is constricted. The authors were able to observe conformations of the channel with resolved density for the cytoplasmic loop (in which K125 is located). Based on the observed conformations and on the position of the N-terminal helix, which is involved in channel gating and in controlling the size of the pore, the authors propose the mechanisms of Cx26 regulation.

      Strengths:

      This is a very interesting and timely study, and the observations provide a lot of new information on connexin channel regulation. The authors use the state of the art cryo-EM analysis and 3D classification approaches to tease out the conformations of the channel that can be interpreted as "inhibited", with important implications for our understanding of how the conformations of the connexin channels controlled.

      Weaknesses:

      My fundamental question to the premise of this study is: to what extent can K125 carbamylation by recapitulated by a simple K125E mutation? Lysine has a large side chain, and its carbamylation would make it even slightly larger. While the authors make a compelling case for E125-induced conformational changes focusing primarily on the negative charge, I wonder whether they considered the extent to which their observation with this mutant may translate to the carbamoylated lysine in the wild-type Cx26, considering not only the charge but also the size of the modified side-chain.

      This is an important point. We agree that the difference in size will have a different effect on the structure. For kinases, aspartate or glutamate are often used as mimics of phosphorylated serine or threonine and these will have the same issues. The fact that we cannot resolve the relevant side-chains in the density may be indicative that the mutation doesn’t give the whole story. It may be able to shift the equilibrium towards the closed conformation, but not stably trap the molecule in that conformation. We include a comment to this effect in the revised manuscript.

      Reviewer #3 (Public Review):

      Summary:

      The mechanism underlying the well-documented CO2-regulated activity of connexin 26 (Cx26) remains poorly understood. This is largely due to the labile nature of CO2-mediated carbamylation, making it challenging to visualize the effects of this reversible posttranslational modification. This paper by Brotherton et al. aims to address this gap by providing structural insights through cryo-EM structures of a carbamylation-mimetic mutant of the gap junction protein.

      Strengths:

      The combination of the mutation, elevated PCO2, and the use of LMNG detergent resulted in high-resolution maps that revealed, for the first time, the structure of the cytoplasmic loop between transmembrane helix (TM) 2 and 3.

      Weaknesses:

      The presented maps merely reinforce their previous findings, wherein wildtype Cx26 favored a closed conformation in the presence of high PCO2. While the structure of the TM2-TM3 loop may suggest a mechanism for stabilizing the closed conformation, no experimental data was provided to support this mechanism. Additionally, the cryo-EM maps were not effectively presented, making it difficult for readers to grasp the message.

      We have extensively revised the manuscript so that the novelty of this study is more apparent. There are three major points

      (1) The carbamylation mimetic pushes the conformation towards the closed conformation. Previously we just showed that CO2 pushes the conformation towards this conformation. Though we could show this was not due to pH, and could speculate this was due to carbamylation as suggested by previous mutagenesis studies, our data did not provide any mechanism whereby Lys125 was involved.

      (2) In going from the open to closed conformations, not only is a conformational change in TM2 involved, as we saw previously, but also a conformational change in TM1, the linker to the N-terminus and the cytoplasmic loop. Thus there is a clear connection between Lys125 and the conformation of the pore-closing N-terminus.

      (3) We observe for the first time in any connexin structure, density for the cytoplasmic loop. Since this loop is important in regulation, knowing how it might influence the positions of the transmembrane helices is important information if we are to understand how connexins can be regulated.

      Reviewing Editor:

      The reviewers have agreed on a list of suggested revisions that would improve the eLife assessment if implemented, which are as follows:

      (1) For completeness, Figure 1 could be supplied with an example of how the experiment would look like in the presence of CO2 - for the wild-type and for the K125E mutant. presumably for the wild-type this has been done previously in exactly this assay format, but this control would be an important part of characterization for the mutant. Page 4, lines 105106; "unsurprisingly, Cx26K125E gap junctions remain closed at a PCO2 of 55 mmHg." The data should be presented in the manuscript.

      We have now included the data with a PCO2 of 55mmH. This is now Figure 4 in our revised manuscript.

      (2) Would AlphaFold predictions show any interpretable differences in the E125 mutant, compared to the K125 (the wild-type)?

      We tried this in response to the reviewer’s suggestion. We did not see any interpretable differences. In general AlphaFold is not recognised as giving meaningful information around point mutations.

      (3) The K125R mutant appears to be a more effective control for extracting significant features from the K125E maps. Given that the use of a buffer containing high PCO2 is essential for obtaining high-resolution maps, wildtype Cx26 is unsuitable as an appropriate control. The K125R map, obtained at a high resolution (2.1Å), supports its suitability as a robust control.

      Though we are unsure what the referee is referring to here, we have rewritten this section and compare against the K125R map (figure 5a) as well as that derived from the wild-type protein. The important point is that the K125E mutant, causes a structural change that is consistent with the closure of the gap junctions that we observe in the dye-transfer assays.

      (4) Likewise, the rationale for using wildtype Cx26 maps obtained in DDM is unclear. Wildtype Cx26 seems to yield much better cryo-EM maps in LMNG. We suggest focusing the manuscript on the higher-quality maps, and providing supporting information from the DDM maps to discuss consistency between observations and the likely possibility that the nonprotein density in the pore is lipid and not detergent.

      The rationale for comparing the mutants against the wt Cx26 maps obtained in DDM was because the mutants were also solubilised in DDM. However, taking the lead from the referees’ comments, we have now rewritten the manuscript so that we first focus on the data we obtain from protein solubilised in LMNG. We feel this makes our message much clearer.

      (5) In general, the rationale for utilizing cryo-EM maps with the entire selected particles is unclear. Although the overall resolutions may slightly improve in this approach, the regions of interest, such as the N-terminus and the cytoplasmic loop, appear to be better ordered afer further classifications. The paper would be more comprehensible if it focuses solely on the classes representing the pore-constricting N-terminus (PCN) and the pore-open flexible Nterminus (POFN) conformations. Also, the nomenclatures used in the manuscript, such as "WT90-Class1", "K125E90-1", "LMNG90-class1", "LMNG90-mon-pcn" are confusing.

      LMNG90s are also wildtype; K125E-90-1 is in Class1 for this mutant and is similar to WT90Class2, which represents the PCN conformation. More consistent and intuitive nomenclatures would be helpful.

      We agree with the referees’ comments. This should now be clearer with our rewritten manuscript where we have simplified this considerably. We now call the conformations NConst (N-terminus defined and constricting the pore) and NFlex (N-terminus not visible) and keep this consistent throughout.

      (6) A potential salt bridge between the carbamylated K125 and R104 is proposed to account for the prevalence of Class-1 (i.e., PCN) in the majority of cryo-EM particles. However, the side chain densities are not well-defined, suggesting that such an interaction may not be strong enough to trap Cx26 in a closed conformation. Furthermore, the absence of experimental data to support this mechanism makes it unclear how likely this mechanism may be. Combining simple mutagenesis, such as R104E, with a dye transfer assay could offer support for this mechanism. Are there any published experimental results that could help address this question without the need for additional experimental work? Alternatively, as acknowledged in the discussion, this mechanism may be deemed as an "over-simplification." What is an alternative mechanism?

      R104 has been mutated to alanine in gap junctions and tested in a dye transfer assay as now mentioned in the text (Nijar et al, J Physiol 2021) supporting this role. In hemichannels R104 has been mutated to both alanine and glutamate and tested through dye loading assays Meigh et al, eLife 2013). Also in hemichannels R104 and K125 have been mutated to cysteines allowing them to be cross-linked through a disulphide bond. This mutant responds to a change in redox potential in a similar way to which the wild type protein responds to CO2 (Meigh et al, Open Biol 2015). Therefore, there is no doubt that the residues are important for the mechanism and the salt-bridge interaction seems a plausible mechanism to reconcile the mutagenesis data, however we cannot be sure that there are not other interactions involved that are necessary for closure. This information has now been included in the text.

      (7) The cryo-EM maps presented in the manuscript propose that gap junctions are constitutively open under normal PCO2 as the flexible N-terminus clears the solute permeation pathway in the middle of the channel. However, hemichannels appear to be closed under normal PCO2. It is puzzling how gap junctions can open when hemichannels are closed under normal PCO2 conditions. If this question has been addressed in previous studies, the underlying mechanism should be explicitly described in the introduction. If it remains an open question, differences in the opening mechanisms between hemichannels and gap junctions should be investigated.

      We suspect this is due to the difference in flexibility of gap junctions relative to hemichannels. However, a discussion of this is beyond this paper and would be complete speculation based on hemichannel structures of other connexins, performed in different buffering systems. There are no high resolution structures of Cx26 hemichannels.

      (8) A mystery density likely representing a lipid is abruptly introduced, but the significance of this discovery is unclear. It is hard to place the lipid on Figure S6 in the wider context of everything else that is discussed in the text. It would be helpful for readers if a figure were provided to show where the density is located in relation to all the other regions that are extensively discussed in the text.

      In the revised text this section has been completely rewritten. We have now include a more informative view in a new figure (Figure 1 – figure supplement 3).

      (9) Including and displaying even tentative pore-diameter measurements for the different states - this would be helpful for readers and provide a more direct visual cue as to the difference between open and closed states.

      We have purposely avoided giving precise measurements to the pore-diameter, since this depends on how we model the N-terminus. The first three residues are difficult to model into the density without causing stearic clashes with the neighbouring subunits.

      (10) Given that no additional experiments for channel function were carried out, it would be useful if to provide a more detailed discussion of additional mutagenesis results from the literature that are related to the experimental results presented.

      We have amplified this in the discussion (see answer to point 6).

      The reviewers also agreed that improvements in the presentation of the data would strengthen the manuscript. Here is a summary list of suggestions by reviewers aimed at helping improve how the data is presented:

      (1) Why is the pipette bright green in the top image, but rather weakly green in the bottom image in Figure 1 - is this the case for all images?

      (Now figure 4) This depends on whether the pipette was in the focal plane of view or not. The important point of these images is the difference in intensity of the donor vs the recipient cell. The graphs in figure 4c illustrate clearly the difference between the wild-type and the mutant gap junctions.

      (2) In figures 2-5, labels would help a lot in understanding what is shown - while the legends do provide the information on what is presented, it would help the reader to see the models/maps with labels directly in the panel. For example, Figure 2a/b - just indicating "WT90 Cx26" in pink and "K125E90" in blue directly in the panel would reduce the work for the reader.

      We have extensively modified the labels in the figures to address this issue.

      (3) Figure 4 - magenta and pink are fairly close, and to avoid confusion it might be useful to use a different color selection. This is especially true when structures are overlayed, as in this figure - the presentation becomes rather complicated, so the less confusion the color code can introduce, the better.

      (Now Figure 2) We have now changed pink to blue.

      (4) Figure 5 - a remarkably under-labelled figure.

      Now added labels.

      (5) Figure 6 - it would be interesting to add a comparison to Cx32 here as well for completeness, since the structure has been published in the meantime.

      Cx32 has now been included.

      (6) Figure 7 - please add equivalent labels on both sides of the model, left and right. Add the connecting lines for all of the tubes TM helices - this will help trace the structural elements shown. The legend does not quite explain the colors.

      We have modified the figure as suggested and explained the colours in the legend.

      (8) Fig.1 legend; Unclear what mCherry fluorescence represents. State that Cx26 was expressed as a translational fusion with mCherry.

      Now figure 4. We have now written “Montages each showing bright field DIC image of HeLa cells with mCherry fluorescence corresponding to the Cx26K125E-mCherry fusion superimposed (leftmost image) and the permeation of NBDG from the recorded cell to coupled cells.”

      (9) Fig. 3 b); Show R104 in the figure. Also E129-R98/R99 interaction is hard to acknowledge from the figure. It seems that the side chain density of E129 is not strong enough to support the modeled orientation.

      This is now Figure 1c. While the density in this region is sufficient to be confident of the main chain, we agree that the side chain density for the E129-R98/R99 interaction is not sufficiently clear to draw attention to and have removed the associated comment from the figure legend. The density is focussed on the linker between TM1 and the N-terminus and the KVRIEG motif. We prefer to omit R104, in order to keep the focus on this region. As described in the manuscript, the density for the R104 side chain is poor.

      (10) Fig. 3 c); Label the N-terminus and KVRIEG motif in the figure.

      Now Figure 1b. We have labelled the N-terminus. The KVRIEG motif is not visible in this map.

      (11) Page 9, lines 246-248; Restate, "We note, however, density near to Lys125, between Ser19 in the TM1-N-term linker, Tyr212 of TM4 and Tyr97 on TM3 of the neighbouring subunit, which we have been unable to explain with our modelling."

      We have reworded this.

      (12) Page 14, line 399; Patch clamp recording is not included in the manuscript.

      Patch clamp recordings were used to introduce dye into the donor cell.

      (13) On the same Figure 2, clashes are mentioned but these are hard to appreciate in any of the figures shown. Perhaps would be useful to include an inset showing this.

      We have modified Figure 2b slightly and added an explanation to highlight the clash. It is slightly confusing because the residues involved belong to neighbouring subunits.

      (14) The discussion related to Figure 6 is very hard to follow for readers who are not familiar with the context of abbreviations included on the figure labels. This figure could be improved to allow a general readership to identify more clearly each of the features and structural differences that are discussed in the text.

      We have extensively changed the text and updated the labels on the figure to make it much easier for the reader to follow.

      Below, you can find the individual reviews by each of the three reviewers.

      Reviewer #1 (Recommendations For The Authors):

      (1) In Figure 2d-e, the text discusses differences between K125E 90-1 and WT 90-class2 (7QEW), yet the figure compares K125E with 7QEQ. I suggest including a figure panel with a comparison between the two structures discussed in the manuscript text.

      This has been changed in the revised manuscript.

      Other comments have been addressed above.

    1. Author response:

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

      The reviewers thoughtful comments have helped us make the manuscript both more comprehensive and clearer. Thank you for your time and effort. We know that this is a long and technical paper. In our responses we refer to three documents:

      • Original: the first original submission

      • Revision: the revised document (02 MillardFranklinHerzog2023 v2.pdf)

      • Difference: a document that shows the changes made to text (but not figures or tables) from the original to revision (03 MillardFranklinHerzog2023 diff.pdf).

      Reviewer #1 (Recommendations For The Authors):

      (1) In general, the paper is well written and addresses important questions of muscle mechanics and muscle modeling. In the current version, the model limitations are briefly summarized in the abstract. However, the discussion needs a more complete description of limitations as well as a discussion of types of data (in vivo, ex vivo, single fiber, wholes muscle, MTU, etc.) that can be modeled using this approach.

      Please see the response to comment 23 for more details of the limitations that have been added to the revised document.

      (2) The choice of a model with several tendon parameters for simulating single muscle fiber experiments is not well justified.

      A rigid-tendon model with a slack length of zero was, in fact, used for these simulations for both the VEXAT and Hill models. In case this is still not clear: a rigid-tendon model of zero length is equivalent to no tendon at all. The text that first mentions the tendon model has now been modified to make it clearer that the parameters of the model were set to be consistent with no tendon at all:

      Please see the following text:

      Original:

      • page 17, column 1, line 28 ”... rigid tendon of zero length,”

      • page 17, column 1, line 51 ”... rigid tendon of zero length.”

      Revision:

      • page 19, column 1, line 19 ”... we used a rigid-tendon of zero length (equivalent to ignoring the tendon)”

      • page 19, column 1, line 38 ”... coupled with a rigid-tendon of zero-length.”

      Difference:

      • page 21, column 1, line 19 ”... we used a rigid-tendon... ”

      • page 21, column 1, line 45 ”... rigid-tendon of zero length ...”

      (3) A table that clarifies how all model parameters were estimated needs to be included in the main part of the manuscript.

      Two tables have been added to the manuscript that detail the parameters of the elastic-tendon cat soleus model (in the main body of the text) and the rabbit psoas fibril model (in an appendix). Each table includes:

      • A plain language parameter name

      • The mathematical symbol for the parameter

      • The value and unit of the parameter

      • A coded reference to the data source that indicates both the experimental animal and how the data was used to evaluate the parameter.

      Please see the following text:

      Revision:

      • page 11

      • page 42

      Difference:

      • page 11

      • page 46

      (4) The supplemental information is not properly referenced in the main text. There are a number of smaller issues that also need to be addressed.

      Thank for your attention to detail. The following problems related to Appendix referencing have been fixed:

      • Appendices are now parenthetically referenced at the end of a sentence. However, a few references to figures (that are contained within anAppendix) still appear in the body of the sentence since moving these figure references makes the text difficult to understand.

      • All Appendices are now referenced in the main body of the text.

      (5) Abstract, line 6: While it is commonly assumed that the short range stiffness of muscle is due to cross bridges, Rack & Westbury (1974) noted that it occurs over a distance of 25-35 nm, and that many cross-bridges must be stretched even farther than this distance (their p. 348 middle). It seems unlikely that cross-bridges alone can actually account for the short-range stiffness.

      There are three parts to our response to this comment:

      (a) Rack & Westbury’s definition of short-range-stiffness and unrealistic cross-bridge stretches

      (b) Rack & Westbury’s definition of short-range-stiffness vs. linear-timeinvariant system theory

      (c) Updates to the paper

      a. Rack & Westbury’s definition of short-range-stiffness and unrealistic cross-bridge stretches.

      As you note, on page 348, Rack and Westbury write that ”If the short range stiffness is to be explained in terms of extension of cross-bridges, then many of them must be extended further than the 25-35 nm mentioned above.” Having re-read the paper, its not clear how these three factors are being treated in the 25−35 nm estimate:

      • the elasticity of the tendon and aponeurosis,

      • the elasticity of actin and myosin filaments,

      • and the cycling rate of the cross-bridges.

      Obviously the elasticity of the tendon, aponeurosis, actin, and myosin filaments will reduce the estimated amount of crossbridge strain during Rack and Westbury’s experiments. A potentially larger factor is the cycling rate of each cross-bridge. If each crossbridge cycles faster than 11 Hz (the maximum frequency Rack and Westbury used), then no single crossbridge would stretch by 25-35 nm. So why didn’t Rack and Westbury consider the cycling rate of crossbridges?

      Rack and Westbury’s reasoned that a perfectly elastic work loop would necessarily mean that all crossbridges stayed attached: as soon as a crossbridge cycles it would release its stored elastic energy and the work loop would no longer be elastic. Since Rack and Westbury measured some nearly perfect elastic work loops (the smallest loops in Fig. 2,3, and 4), I guess they assumed crossbridges remained attached during the 25-35 nm crossbridge stretch estimate. However, even Rack and Westbury note that none of the work loops they measured were perfectly elastic and so there is room to entertain the idea that crossbridges are cycling.

      Fortunately, for this discussion, crossbridge cycling rates have been measured.

      In-vitro measurements by Uyeda et al. show that crossbridges are cycling at 30 Hz when moving at 0.5-1.2 length/s. At this rate, there would be enough time for a single crossbridge to cycle nearly 2.72 times for every cycle of the 11 Hz sinusoidal perturbations, reducing its expected strain from 25-35 nm down to 9.2−12.9µm. This effect becomes even more pronounced if crossbridge cycling rate is used to explain the difference in sliding velocity between Uyeda et al.’s in-vitro data (0.5-1.2 length/s) and the maximum contraction velocity of an in-situ cat soleus (4.65 lengths/s, Scott et al.).

      b. Rack & Westbury’s definition of short-range-stiffness vs. linear-time-invariant system theory

      Rack and Westbury defined short-range-stiffness to describe a specific kind of force response of the muscle to cyclical length changes:

      • muscle force is linear with length change,

      • and independent of velocity.

      Rack and Westbury’s definition therefore fails when viscous forces become noticeable, because viscous forces are velocity dependent.

      On line 6 of the abstract the term ‘short-range-stiffness’ is not used because Rack and Westbury’s definition is too narrow for our purposes. Instead we are using the more general approach of approximating muscle as a linear-timeinvariant (LTI) system, where it is assumed that

      • the response of the system is linear

      • and time invariant.

      To unpack that a little, a muscle is considered in the ‘short-range’ in our work if it meets the criteria of a linear time-invariant (LTI) system:

      • the force response of muscle can be accurately described as a linear function of its length and velocity (its state)

      • and its response is not a function of time (which means constant stimulation, and no fatigue).

      In contrast to Rack and Westbury’s definition, the ‘short-range’ in linear systems theory is general enough to accommodate both elastic and viscous forces. In physical terms, small for an LTI approximation of muscle is larger than the short-range defined by Rack and Westbury: an LTI system can include velocity dependence, while short-range-stiffness ends when velocity dependence begins.

      c. Updates to the paper

      To make the differences between Rack and Westbury’s ‘short-range-stiffness’ and LTI system theory clearer: - We have removed all occurrences of ‘short-range’ that were associated with Kirsch et al. and have replaced this phrase with ‘small’.

      • On the first mention of Kirsch’s work we have made the wording more specific

      Revision:

      • page 1, column 1, lines 4,5

      • page 1, column 2, lines 14-21 ”Under constant activation ...”

      Difference: page 1, column 2, line 19-26

      • page 1, column 1, lines 4,5

      • page 1, column 2, lines 20-27 ”Under constant activation ...”

      • A footnote has been added to contrast the definition of ‘small’ in the context of an linear time invariant system to ‘short-range’ in the context of Rack and Westbury’s definition of short-range-stiffness.

      Revision: page 1, column 2, bottom

      Difference: page 1, column 2, bottom

      • In addition, we have added a brief overview of LTI system theory to make the analysis and results more easily understood:

      Revision: Figure 4 paragraph beginning on page 10, column 2, line 15 ”As long as ...”

      Difference: Figure 4 paragraph beginning on page 12, column 1, line 46 ”As long as ...”

      (6) Page 3, lines 6-8: It also seems unlikely that 25% of cross-bridges are attached at one time (Howard, 1997) even for supramaximal isometric stimulation. The number should be less than 20%. What would the ratio of load path stiffness be for low force movements such as changing the direction of a frictionless manipulandum or slow walking? The range of relative stiffnesses is of more interest than the upper limit.

      We have made the following updates to address this comment:

      • A 20% duty cycle now defines the upper bound stiffness of the actinmyosin load path.

      • We have also evaluated the lower bound actin-myosin stiffness when a single crossbridge is attached.

      • The stiffness of titin from Kellermayer et al. has been digitized at a length of 2 µm and 4 µm to more accurately capture the length dependence of titin’s stiffness.

      • We have added a new figure (Figure 14) to make it easier to compare the range of actin-myosin stiffness to titin-actin stiffness.

      • The text in the main body of the paper and the Appendix has been updated.

      • The script ’main ActinMyosinAndTitinStiffness.m’ used to perform the calculations and generate the figure is now a part of the code repository.

      Please see the following text:

      Revision

      • The paragraph beginning at page 2, column 2, line 45 ”The addition of a titin element ...”

      • Appendix A

      • Figure 14 (in Appendix A)

      Difference

      • The paragraph beginning at page 3, column 1, line 6: ”The addition of a titin element ...”

      • Appendix A

      • Figure 14 (in Appendix A)

      (7) Page 5, line 12: A word seems to be missing here, ”...together to further...”.

      Thank you for your attention to detail. The sentence has been corrected.

      Please see the following text:

      • Revision: page 4, column 2, line 40 ”... into a single ...”

      • Difference: page 5, column 1, line 18

      (8) Page 5, line 24-27: These ”theories” are not mutually exclusive, and it is misleading to suggest they are. There is evidence for binding of titin to actin at multiple locations and there is no reason why evidence supporting one binding location must detract from the evidence supporting other binding locations.

      The text has been modified to make it clear to readers that the different titinactin binding locations are not mutually exclusive. Please see the following text:

      • Revision: page 5, column 1, lines 17-19, the sentence beginning ”As previously mentioned, ...”

      • Difference: page 5, column 1, lines 41-44

      (9) Page 5, lines 48-51: Should cite Kellermayer and Granzier (1996) not Kellermayer et al. (1997).

      The reference to ‘Kellermayer et al.’ has been changed to ‘Kellermayer and Granzier’. The comment that the year of the reference should be changed from (1997) to (1996) is confusing: the 1996 paper is being referenced.

      For further details please see:

      • Revision: page 5, column 1, 39-40

      • Difference: page 5, column 2, line 19-22

      (10) Also, Dutta et al. (2018) should be cited as further showing that N2A titin by itself slows actin motility on myosin.

      Thank you for the suggestion. The sentence has been modified to include Dutta et al.:

      For further details please see:

      • Revision: page 5, column 1, 40

      • Difference: page 5, column 2, line 19-22

      (11) Figure 2 legend and elsewhere: it is odd to say that experiments used ”a cat soleus” when more than one cat coleus was used. Change to ”cat coleus”. See also page 15, line 15.

      Thank you for your attention to detail. All occurrences of ‘a cat soleus’ have been changed, with some sentence revision, to ‘cat soleus’.

      (12) Page 6, line 10: It is not clear why an MTU was used to simulate single muscle fiber experiments. What is the justification for choosing this particular model? Also, the choice of model might explain why the version with stiff tendon performs better than the version with an elastic tendon, but this is never mentioned. Why not use a muscle model with no tendon (e.g., Wakeling et al., 2021 J. Biomech.)?

      Please see the response to comment 2.

      (13) Millard et al.’s activation dynamics model also fails to capture the lengthdependence of activation dynamics (Shue and Crago, 1998; Sandercock and Heckman, 1997), which should be noted in the discussion along with other limitations.

      An additional limitations paragraph is in the revised manuscript that addresses this comment specifically. However, we have used Stephenson and Wendt as a reference for the shift in peak isometric force that comes with submaximal activation. In addition, we also reference Chow and Darling for the property that the maximum shortening velocity is reduced with submaximal activations.

      • Revision: page 22, column 1, line 41 ”Finally, the VEXAT model ...”

      • Difference: page 24, column 2, line 12 ”Finally, the VEXAT model ...”

      In addition, please see the response to comment 23.

      (14) Page 6, line 22: ”An underbar...”.

      Thank you for your attention to detail, this correction has been made.

      (14) Page 7, lines 27-32: This and other issues should be described in the Discussion under a heading of model limitations.

      Please see the response to comment 23.

      (15) Page 7, lines 43-44: Numerous papers from the last author’s laboratory contradict the claim that there is no force enhancement on the ascending limb by demonstrating that force enhancement does occur on the ascending limb (see e.g., Leonard & Herzog 2002, Peterson et al., 2004 and several papers from the Rassier laboratory).

      Thank you for your attention to detail. This statement is in error and has been removed. To improve this section of the paper, a paragraph has been added to briefly mention the experimental observations of residual force enhancement before proceeding to explain how this phenomena is represented by the model.

      Please see the following text:

      Revision:

      • the paragraph starting on page 7, column 2, line 43 ”When active muscle is lengthened, ...”

      • and the following paragraph starting on page 8, column 1, line 3 “To develop RFE, ”

      Difference:

      • the paragraph starting on page 8, column 2, line 15

      • and the following paragraph starting on page 9, column 1, line 6

      (17) Figure 3 legend and elsewhere: The authors use Prado et al. (2005) to determine several titin parameters, however the simulations seem to focus on cat soleus, but Prado et al.’s paper is on rabbits. More clarity is needed about which specific results from which species and muscles were used to parameterize the model.

      The new parameter table includes coded entries to indicate the literature source for experimental data, the animal it came from, and how the data was used. For example, the ‘ECM fraction’ has a source of ‘R[57]’ to show that the data came from rabbits from reference 57. For further details, please see the response to comment #3

      Please see the following text:

      • Revision: page 11, column 2, table section H: ‘ECM fraction’.

      • Difference: page 11, column 2, table section H: ‘ECM fraction’.

      To address this comment in a little more detail, we have had to use Prado et al. (2005) to give us estimates for only one parameter: P, the fraction of the passive force-length relation that is due to titin. Prado et al.’s measurements relating to P are unique to our knowledge: these are the only measurements we have to estimate P in any muscle, cat soleus or otherwise. Here we use the average of the values for P across the 5 muscles measured by Prado et al. as a plausible default value for all of our simulations.

      (18) Figure 4 seems unnecessary.

      Figure 4 has been removed.

      (19) Page 10, lines 17-18: provide the abbreviation (VAF) here with the definition (variance accounted for).

      Thank you for your attention to detail. The abbreviation has been added.

      Please see these parts of the manuscripts for details:

      • Revision: page 12, column 2, line 13

      • Difference: page 13, column 2, line 32

      (20) Page 11, lines 2-3: Here and elsewhere, it is clear that some model parameters have been optimized to fit the model. The main paper should include a table that lists all model parameters and how they were chosen or optimized, including but not limited to the information in Table 1 of the supplemental information section.

      See response to comment 3.

      (20) Page 17, lines 45 -49: Again, a substantial number of ad hoc adjustments to the model appear to be required. These should be described in the Discussion under limitations, and accounted for in the parameters table. See also legends to Fig. 12 and 13, page 19, lines 23-26.

      Please see the response to comment #3: a coded entry now appears to indicate the data source, the animal used in the experiment, and the method used to process the data. This includes entries for parameters which were estimated

      ‘E’ so that the model produced acceptable results in the simulations presented. In addition, the new discussion paragraph includes a number of sentences that use the adjustment to the active-titin-damping coefficient as an opening to discuss the limitations of the VEXAT’s titin-actin bond model and the circumstances under which the model’s parameters would need to be adjusted.

      Please see responses to comments 3 and 23 for additional details. In addition, please see the specific discussion text mentioning the change to βoPEVK:

      • Revision: page 22, column 1, line 30 ”In Sec. 3.3 we had ...”

      • Difference: page 24, column 1, line 49

      (22) Page 20, lines 50-11: It should be noted here that Tahir et al.’s (2018) model has both series and parallel elastic elements, provided by superposition of rotation (series) and translation (parallel) of a pulley.

      While it is true that Tahir et al.’s (2018) model has series and parallel elements, as do the other models mentioned, these models do not have the correct structure to yield a gain and phase response that mimics biological muscle. The text that I originally wrote attempted to explain this without going into the details. As you note, this explanation leaves something to be desired. The original text commenting on the models of Forcinito et al, Tahir et al, Haeufle et al., and Gunther et al. has been updated to be more specific.¨ Please see the parts of the following manuscripts for details:

      • Revision: page 22, column 2, line 20, the paragraph beginning ”The models of Forcinito ...”

      • Difference: page 24, column 2, line 44

      (23) Discussion: This section should include a description of model limitations, including the relatively large number of ad hoc modifications and how many parameters must be found by optimization in practice. The authors should discuss what types of data are most compatible for use with the model (ex vivo, in vivo, single fiber, whole muscle, MTU), requirements for applying the model to different types of data, and impediments to using the model on different types of data.

      An additional limitations paragraph has been added to the discussion.

      Please see the following text:

      • Revision: the paragraph beginning on page 22, column 1, line 11 ”Both the viscoelastic ...”

      • Difference: the paragraph beginning on page 24, column 1, line 27.

      Reviewer #2 (Recommendations For The Authors):

      (1) If it is possible to compare the output of this model to other more contemporary models which incorporate titin but are also simple enough to implement in whole-body simulation (such as the winding filament model), this would seem to greatly strengthen the paper.

      That’s an excellent idea, though beyond the scope of this already lengthy paper. Even though the Hill model we evaluated is a bit old it is widely used, and so, many readers will be interested in seeing the benchmark results. As benchmarking work is both difficult to fund and undertake, we do hope that others will evaluate their own models using the code and data we have provided.

      (2) I’m a little unclear on the basis for the transition between short- and midrange length changes, both in reality and in the model. And also about the range of strains that qualify as ”short”. It seems like there is potential for short range stiffness, although I would have thought more in the range of 1-2% strains than >3%, to be due to currently attached crossbridges. There is clear evidence that active titin is responsible for the low stiffness at very large strains that exceed actin-myosin overlap. But I am not clear on how a transitional stiffness on the descending limb of the force-length relationship is implemented in the model, and what aspect of physiology this is replicating. It may be helpful to clarify this further and indicate where in the model this stiffness arises.

      This question has several parts to it which I will paraphrase here:

      A Short-range stiffness acts over smaller strains than 3.8%. How is shortrange defined?

      B Where is the transition made between short-range and mid-range force response, both in reality and in the model. Also how does this change on the descending limb?

      C What components in the model contribute to the stiffness of the CE?

      A. Short-range stiffness acts over smaller strains than 3.8%. How is shortrange defined?

      The response to Reviewer 1’s comment # 5 directly addresses this question.

      B. Where is the transition made between short-range and mid-range forceresponse, both in reality and in the model. Also how does this change on the descending limb? We are going to rephrase the question because of changes in terminology that we have made in response to Reviewer 1’s comment #5.

      (i) What is the basis for the transition between the muscle behaving like an LTI system? Both in reality, and in the model. (ii) What happens outside the LTI range? (iii) Also how does this change on the descending limb?

      We will address this question one part at a time:

      (i) What is the basis for the transition between the muscle behaving like an LTI system? Both in reality, and in the model.

      A system’s response can be approximated as a linear-time-invariant (LTI) system as long as it is time-invariant, and its output can be expressed as a linear function of its input. In the context of Kirsch et al.’s experiment, the ‘system’ is the muscle, the ‘input’ is the time series of length data, and the ‘output’ is the time series of force data. Due to the requirement for timeinvariance, two experimental conditions must be met to approximate muscle as an LTI system:

      • the nominal length of the muscle stays constant over long periods of time,

      • and the nominal activation of the muscle stays constant.

      These conditions were met by default in Kirch et al.’s experiment, and also in our simulations of this experiment. The one remaining condition to assess is whether or not the muscle’s response is linear.

      To evaluate whether the muscle’s force is a linear function of the length change, Kirch et al. evaluated (Cxy)2 the coherence squared between the length and force time-series data. Even though the mathematical underpinnings of (Cxy)2 are complicated, the interpretation of (Cxy)2 is simple: muscle can be accurately approximated as a linear system if (Cxy)2 is close to 1, but the accuracy of this approximation becomes poor as (Cxy)2 approaches 0. Kirsch et al. used (Cxy)2 to identify a bandwidth in which the response of the muscle to the 1−3.8%ℓoM length changes was sufficiently linear for analysis: a lower bound of 4 Hz was identified using (Cxy)2 and the bandwidth of the input signal (15 Hz, 35 Hz, or 90 Hz) set the upper bound. In Fig. 3 of Kirsch et al. the (Cxy)2 at 4 Hz has a value of at least 0.67 for the 15 Hz and 90 Hz signals. To minimize error in our analysis and yet be consistent with Kirsch et al., we analyze the bandwidth common to both (Cxy)2 ≥ 0.67 and Kirsch et al.’s defined range. Though the bandwidth defined by the criteria (Cxy)2 ≥ 0.67 is usually larger than the one defined by Kirsch et al., there are some exceptions where the lower frequency bound of the models is higher than 4 Hz (now reported in Tables 4D and 5D).

      (ii) What happens outside the LTI range?

      When a muscle’s output cannot be considered a LTI it means that either that its length or activation is time-varying, or the relationship between length and force is no longer linear. In short, that the muscle is behaving as one would normally expect: time-varying and non-linearly. The wonderful part of Kirsch et al.’s work is that they found a surprisingly large region in the frequency domain where muscle behaves linearly and can be analyzed using the powerful tools of linear systems and signals.

      (iii) Also how does this change on the descending limb?

      Since nominal length of Kirsch et al.’s experiments is ℓoM it is not clear how the results of the perturbation experiments will change if the nominal length is moved firmly to the descending limb. However, we can see how the stiffness and damping values will change by examining Figure 9C and 9D which shows the calculated stiffness and damping of the VEXAT and Hill models as ℓM is lengthened from ℓoM down the descending limb: the stiffness and damping of the VEXAT model does not change much, while the Hill model’s stiffness changes sign and the damping coefficient changes a lot. What cannot be seen from Figure 9C and 9D is how the bandwidth over which the models are considered linear changes.

      We have made a number of updates to the text to more clearly communicate these details of our response to part (i):

      • Text has been edited so that it is clear that the terms ’short-range stiffness’ and ’small’ from Rack and Westbury’s work is not confused with ’stiffness’ and ’small’ from the LTI system’s analysis. Please see our response to comment # 5 for details.

      • We have added text to the main body of the paper to explain how the coherence squared metric was used to select a bandwidth in which the response of the system is approximately linear:

      • Revision: the paragraph that starts on page 11, column 1, line 3 ”Kirsch et al. used system identification ...”

      – Difference: page 13, column 2, line 1

      – Coherence is defined in Appendix D

      – Coherence is now also included in the example script ‘main SystemIdentificationExample.m’

      • The bandwidth over which model output can be considered linear (coherence squared > 0.67) has been added to Tables 4 and 5

      – Revision: see Table 4D, and Table 5D in Appendix E

      – Difference: see Table 4D, and Table 5D in Appendix E

      • Figures 6 and Figures 16 are annotated now if the plotted signal does not meet the linearity requirement of Cxy > 0.67.

      C. What components in the model contribute to the stiffness of the CE?

      There are three components that contribute to the stiffness of the CE which are pictured in Figure 1, appear in Eqn. 15, and are listed explicitly in Eqn. 76:

      (a) The XE, as represented by the afL(ℓ˜S+L˜M)k˜oX term in Eqn. 15.

      (b) The elasticity of the distal segment of titin, f2(ℓ˜2). Only f2(ℓ˜2) appears in Eqn. 15 because ℓ˜1 is a model state.

      (c) The extracellular matrix, as represented by the fECM(ℓ˜ECM)

      There is also a compressive element fKE, but it plays no role in the simulations presented in this work because it only begins to produce force at extremely short CE lengths (ℓ˜M < 0.1ℓoM).

      We have made the following changes to make these components clearer

      Figure 1A has been updated:

      – The symbols for a spring and a damper are now defined in Figure 1A

      – The ECM now has a spring symbol. Now all springs and dampers have the correct symbol in Figure 1A.

      – The caption now explicitly lists the rigid, viscoelastic, and elastic elements in the model

      The equations for the VEXAT’s CE stiffness and damping are now compared and contrasted to the the Hill model’s stiffness and damping in Sec. 3.1.

      – Revision: starting at page 14, column 2, line 1: Eqn. 28 and Eqn. 29 and surrounding text

      – Difference: page 17, column 1, line 22

      (3) This model appears to be an amalgamation of a phenomenological (forcelength and force-velocity relationships) and a mechanistic (crossbridge and titin stiffness and damping) model. While this may improve predictions, and so potentially be useful, it also seems like it limits the interpretation of physiological underpinnings of any findings. It may be helpful to explore in greater detail the implications of this approach.

      We have added a limitations paragraph to the discussion which addresses this comment and can be found in:

      • Revision: the paragraph beginning on page 22, column 1, line 11 ”Both the viscoelastic ...”

      • Difference: the paragraph beginning on page 24, column 1, line 27

      (4)As a biologist, I found the interpretation of phase and gain a little difficult and it may help the reader to show in greater detail the time series data and model predictions to highlight conditions under which the models do not accurately capture the magnitude and timing of force production.

      It is important that the ideas of phase and gain are understood, especially because little information can be gleaned from the time series data directly. There is some time series data in the paper already that compares each model’s response to its spring-damper of best fit: plots of the force response of each model and its spring damper of best fit can be found in Figures 6A, 6D, 6G, 6J, 16A, 16D, 16G, and 16J in the revised manuscript. While it is clear that models with a higher VAF more closely match the spring-damper of best fit, there is not much more that can be taken from time series data: the systematic differences, particularly in phase, are just not visually apparent in the time-domain but are clear in gain and phase plots in the frequency-domain.

      To make the meaning of phase and gain plots clearer, Figure 4 (Figure 5 in the first submission) has been completely re-made and includes plots that illustrate the entire process of going from two length and force timedomain signals to gain and phase plots in the frequency-domain. Included in this figure is a visual representation of transforming a signal from the time to the frequency domain (Fig. 4B and 4C), and also an illustration of the terms gain and phase (Fig. 4D). In addition, a small example file ’main SystemIdentificationExample.m’ has been added to the matlab code repository in the elife2023 branch to accompany Appendix D, which goes through the mathematics used to transform input and output time domain signals into gain and phase plots of the input-output relation. Small updates have been made to Figure 6 and 16 in the revised paper (Figures 7 and 18 in the first submission) to make the time domain signals from the spring-damper of best fit and the model output clearer. Finally, I have re-calculated the gain and phase profiles using a more advanced numerical method that trades off some resolution in frequency for more accuracy in the magnitude. This has allowed me to make Figures 6 and 16 easier to follow because the gain and phase responses are now lines rather than a scattering of points. We hope that these additions make the interpretation of gain and phase clearer.

      Please see

      Revision:

      – Figure 4 and caption on page 12

      – The opening 2 paragraphs of Sec 3.1 starting on page 10, column 2, line 4 ”In Kirsch et al.’s ...”

      – Figure 6 & 16: spring damper and model annotation added, plotted the gain and phase as lines

      – Appendix D: Updated to include coherence and the more advanced method used to evaluate the system transfer function, gain, and phase.

      Difference:

      – Figure 4 and caption on page 12

      – The opening 2 paragraphs of Sec 3.1 starting on page 12, column 1, line 34 and ending on page 13, column 2, line 29

      – Figure 6 & 16: spring damper and model annotation added

      – Appendix D

      (5) The actin-myosin and actin-titin load pathways are depicted as distinct in the model. However, given titin’s position in the center of myosin and the crossbridge connections between actin and myosin, this would seem to be an oversimplification. It seems worth considering whether the separation of these pathways is justified if it has any effect on the conclusions or interpretation.

      We have reworked one of the discussion paragraphs to focus on how our simulations would be affected by two mechanisms (Nishikawa et al.’s winding filament theory and DuVall et al.’s titin entanglement hypothesis) that make it possible for crossbridges to do mechanical work on titin.

      • Revision: the paragraph beginning on page 21, column 2, line 42 “The active titin model ...”

      • Difference: the paragraph beginning on page 23, column 2, line 48

      References

      Nishikawa KC, Monroy JA, Uyeno TE, Yeo SH, Pai DK, Lindstedt SL. Is titin a ‘winding filament’? A new twist on muscle contraction. Proceedings of the royal society B: Biological sciences. 2012 Mar 7;279(1730):981-90.

      DuVall M, Jinha A, Schappacher-Tilp G, Leonard T, Herzog W. I-Band Titin Interaction with Myosin in the Muscle Sarcomere during Eccentric Contraction: The Titin Entanglement Hypothesis. Biophysical Journal. 2016 Feb 16;110(3):302a.

    1. Author response:

      Reviewer #1 (Public Review):

      In this manuscript, Naseri et al. present a new strategy for identifying human genetic variants with recessive effects on disease risk by the genome-wide association of phenotype with long runs-of-homozygosity (ROH). The key step of this approach is the identification of long ROH segments shared by many individuals (termed "shared ROH diplotype clusters" by the authors), which is computationally intensive for large-scale genomic data. The authors circumvented this challenge by converting the original diploid genotype data to (pseudo-)haplotype data and modifying the existing positional Burrow-Wheeler transformation (PBWT) algorithms to enable an efficient search for haplotype blocks shared by many individuals. With this method, the authors identified over 1.8 million ROH diplotype clusters (each shared by at least 100 individuals) and 61 significant associations with various non-cancer diseases in the UK Biobank dataset.

      Overall, the study is well-motivated, highly innovative, and potentially impactful. Previous biobank-based studies of recessive genetic effects primarily focused on genome-wide aggregated

      ROH content, but this metric is a poor proxy for homozygosity of the recessive alleles at causal loci. Therefore, searching for the association between phenotype and specific variants in the homozygous state is a key next step towards discovering and understanding disease genes/alleles with recessive effects. That said, I have some concerns regarding the power and error rate of the methods, for both identification of ROH diplotype clusters and subsequent association mapping. In addition, some of the newly identified associations need further validation and careful consideration of potential artifacts (such as cryptic relatedness and environment sharing).

      1) Identification of ROH diplotype clusters.

      The practice of randomly assigning heterozygous sites to a homozygous state is expected to introduce errors, leading to both false positives and false negatives. An advantage that the authors claim for this practice is to reduce false negatives due to occasional mismatch (possibly due to genotyping error, or mutation), but it's unclear how much the false positive rate is reduced compared to traditional ROH detection algorithm. The authors also justified the "random allele drawing" practice by arguing that "the rate of false positives should be low" for long ROH segments, which is likely true but is not backed up with quantitative analysis. As a result, it is unclear whether the trade-off between reducing FNs and introducing FPs makes the practice worthwhile (compared to calling ROHs in each individual with a standard approach first followed by scanning for shared diplotypes across individuals using BWT). I would like to see a combination of back-of-envelope calculation, simulation (with genotyping errors), and analysis of empirical data that characterize the performance of the proposed method.

      In particular, I find the high number of ROH clusters in MHC alarming, and I am not convinced that this can be fully explained by a high density of SNPs and low recombination rate in this region. The authors may provide further support for their hypothesis by examining the genome-wide relationship between ROH cluster abundance and local recombination rate (or mutation rate).

      Thanks for this insightful comment. Through additional experiments, we confirmed that the excessive number of ROH clusters in the MHC region is due to the higher density of markers per centimorgan. As discussed above at Essential Revision 2, we took this opportunity to modify our code to search for clusters with the minimum length in terms of cM instead of sites. We have also provided the genetic distance for reported clusters in the MHC region with significant association (genetic length (cM) column in Tables 1 and 2). We include the following in the main text:

      “We searched for ROH clusters using a minimum target length of 0.1 cM (Figure 3–figure supplement 1). As shown in the figure, there is no excessive number of ROH clusters in chromosome 6 as was spotted using a minimum number of variant sites.”

      Methods section, ROH algorithm subsection:

      “We implemented ROH-DICE to allow direct use of genetic distances in addition to variant sites for L. The program can take minimum target length L directly in cM and detect all ROH clusters greater than or equal to the target length in cM. The program holds a genetic mapping table for all the available sites, and cPBWT was modified to work directly with the genetic length instead of the number of sites.”

      2) Power of ROH association. Given that the authors focused on long segments only (which is a limitation of the current method), I am concerned about the power of the association mapping strategy, because only a small fraction of causal alleles are expected to be present in long, homozygous haplotypes shared by many individuals. It would be useful to perform a power analysis to estimate what fraction of true causal variants with a given effect size can be detected with the current method. To demonstrate the general utility of this method, the authors also need to characterize the condition(s) under which this method could pick up association signals missed by standard GWAS with recessive effects considered. I suspect some variants with truly additive effects can also be picked up by the ROH association, which should be discussed in the manuscript to guide the interpretation of results.

      We added a new experiment in the Results section “Evaluation of ROH clusters in simulated data” under Power of ROH-DICE in association studies. We compared the power of the ROH cluster with additive, recessive, and dominant models. Our simulation shows that using ROH clusters outperforms standard GWAS when a phenotype is associated with a set of consecutive homozygous sites. We added the following text:

      “...We calculated the p-values for both ROH clusters and all variant sites. We used a p-value cut-off of 0.05 divided by the number of tests for each phenotype to determine whether the calculated p-value was smaller than the threshold, indicating an association. For GWAS, only one variant site within the ROH cluster, contributing to the phenotype, was required. We tested for all additive, dominant, and recessive effects (Figure 1–figure supplement 3). The figure demonstrates that ROH-DICE outperforms GWAS when a phenotype is associated with a set of consecutive homozygous sites. The maximum effect size of 0.3 resulted in ROH clusters achieving a power of 100%, whereas the additive model only achieved 11%, and the dominant and recessive models achieved 52% and 70%, respectively. The GWAS with recessive effect yields the best results among other GWAS tests, however, its power is still lower than using ROH clusters.”

      3) False positives of ROH association. GWAS is notoriously prone to confounding by population and environmental stratification. Including leading principal components in association testing alleviates this issue but is not sufficient to remove the effects of recent demographic structure and local environment (Zaidi and Mathieson 2020 eLife). Similar confounding likely applies to homozygosity mapping and should be carefully considered. For example, it is possible that individuals who share a lot of ROH diplotypes tend to be remotely related and live near each other, thus sharing similar environments. Such scenarios need to be excluded to further support the association signals.

      We acknowledge that there could be confounding factors that may affect the association's results. To address this, we utilized principal component (PC) values and additional covariates while using PHESANT after our initial Chi-square tests. We also included your comments in our Discussion section:

      "We used age, gender, and genetic principal components as confounding variables in the association analysis. Genetic principal components can reduce the confounding effect brought on by population structure but it may be insufficient to completely eliminate the effects of recent demographic structure and the local environment45. For example, individuals sharing excessive ROH diplotypes may share similar environments since they are closely related and reside close to one another. Since we did not rule out related individuals, some of the reported GWAS signals may not be attributable to ROH.”

      4) Validation of significant associations. It is reassuring that some of the top associations are indirectly corroborated by significant GWAS associations between the same disease and individual SNPs present in the ROH region (Tables 1 and 2). However, more sanity checks should be done to confirm consistency in direction of effect size (e.g., risk alleles at individual SNPs should be commonly present in risk-increasing ROH segment, and vice versa) and the presence of dominance effect.

      The beta values for effect size are now included in all reported tables. All beta values for ROH-DICE are positive indicating carriers of these ROH diplotypes may increase the risk of certain non-cancerous diseases. Moreover, we conducted the suggested sanity check to confirm the consistency of the direction of risk-inducing ROH diplotypes and risk alleles.

      We also computed D’ as a measure of linkage between the reported GWAS results and ROH clusters. We found that most of the GWAS results and ROH clusters are strongly correlated. However, in a few cases, D' is small or close to zero. In such cases, the reported p-value from GWAS was also insignificant, while the ROH cluster indicated a significant association. We included these points in the Results section.

      Reviewer #3 (Public Review):

      A classic method to detect recessive disease variants is homozygosity mapping, where affected individuals in a pedigree are scanned for the presence of runs of homozygosity (ROH) intersecting in a given region. The method could in theory be extended to biobanks with large samples of unrelated individuals; however, no efficient method was available (to the best of my knowledge) for detecting overlapping clusters of ROH in such large samples. In this paper, the authors developed such a method based on the PBWT data structure. They applied the method to the UK biobank, finding a number of associations, some of them not discovered in single SNP associations.

      Major strengths:

      •           The method is innovative and algorithmically elegant and interesting. It achieves its purpose of efficiently and accurately detecting ROH clusters overlapping in a given region. It is therefore a major methodological advance.

      •           The method could be very useful for many other researchers interested in detecting recessive variants associated with any phenotype.

      •           The statistical analysis of the UK biobank data is solid and the results that were highlighted are interesting and supported by the data.

      Major weaknesses:

      •           The positions and IDs of the ROH clusters in the UK biobank are not available for other researchers. This means that other researchers will not be able to follow up on the results of the present paper.

      We included the SNP IDs, positions, and consensus alleles for all reported loci in the main tables. Moreover, additional information including beta and D’ values were added. The current information should allow researchers to follow up on the results. Supplementary File 2 contains beta, D’ values for all reported clusters.

      Supplementary File 3 contains the SNP IDs and consensus alleles for all reported clusters in Tables 1 and 2. The consensus allele denotes the allele with the highest occurrence in the reported clusters.

      •           The vast majority of the discoveries were in regions already known to be associated with their respective phenotypes based on standard GWAS.

      We agree that a majority of the ROH regions are indeed consistent with GWAS. However, some regions were missed by standard GWAS (e.g. chr6:25969631-26108168, hemochromatosis). Our message is that our method is a complementary approach to standard GWAS and will not replace standard GWAS analysis. See our response to Reviewer #2 Point Six.

      •           The running time seems rather long (at least for the UK biobank), and therefore it will be difficult for other researchers to extensively experiment with the method in very large datasets. That being said, the method has a linear running time, so it is already faster than a naïve algorithm.

      Thank you for your input. The algorithm used to locate matching blocks is efficient and the total CPU hours it consumed was the reported run time. Since it consumes very little memory and resources, it can be executed simultaneously for all chromosomes. We also noticed that a significant time was being spent parsing the input file and slightly modified our script to improve the parsing. We also re-ran it for all chromosomes in parallel and reported the elapsed time which was only 18 hours and 54 minutes.

      “This was achieved by running the ROH-DICE program, with a wall clock time of 18 hours and 54 minutes where the program was executed for all chromosomes in parallel (total CPU hours of ~ 242.5 hours). The maximum residence size for each chromosome was approximately 180 MB.”

    1. when provided with identical source code, input data, software, and computing environment configurations, that an independent party can exactly reproduce the results of the original work -- especially published results. Thi

      The reproduction of the original source giving as a result the same source code, input data, software and configurations in the system might be considered as Computational reproducibility

    2. reproducibility, which emphasizes transparency of data analysis the logical path to scientific conclusio

      According to Patil, P et al. (2016) state that "everyone agrees that scientific studies should be reproducible and replicable. The problem is almost no one agrees upon what those terms mean. A major initiative in psychology used the term reproducibility'' to refer to completely re­doing experiments including data collection (1). In cancer biologyreproducibility'' has been used to refer to the re calculation of results using a fixed set of data and code." (pag. 1)

      A possible approach to statistical reproducibility is to re-do experiments over and over again gathering all the data available to get the findings, but emphasising in the analysis with transparency in the information to have accurate conclusions.

      References

      Prasad Patil, Roger D. Peng, Jeffrey T. Leek. (2016). A statistical definition for reproducibility and replicability. see on https://www.biorxiv.org/content/10.1101/066803v1.full.pdf

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    1. Today, we explore whether memory still has a practical place in the world of big data and computing. As a science writer, Lynne has written 18 books including The Memory Code. Her research showed that without writing, people used the most extraordinary suite of memory techniques to memorise massive amounts of practical information. This explains the purpose of monuments like Stonehenge, the Nazca Lines and the statues of Easter Island. Her next book, Unlocking The Memory Code explains the most effective memory methods from around the world and throughout time. Lynne shows how these can be invaluable in modern world.

      I need to read this book. And re-review this video with a notecard handy. (I wonder if there's a way to use hypothes.is for notes on video/audio?)

    1. Importantly, it must be pointed out that gsea-3.0.jar, utilized in protocols published by Reimand et al [37], is affected by serious security vulnerabilities due to the use of the Java-based logging utility Apache Log4j in GSEA versions earlier than 4.2.3. Moreover, as reported by the GSEA Team, version 3.0 contained microarray-specific code (mostly related to Affymetrix) that may cause issues with RNA-seq data analysis, which was removed in later GSEA updates.

      Did you do anything to account for these things in your analysis?

    2. https://github.com/juliancandia/GSEARNASeq_Benchmarks

      I get a "Page not found" error when i navigate to this URL. Is the repo still private or is there a typo in the URL? I would love to look at/give feedback on the code as well!

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this manuscript, Ngo et al. report a peculiar effect where a single base mismatch (CC) can enhance the mechanical stability of a nucleosome. In previous studies, the same group used a similar state-of-the-art fluorescence-force assay to study the unwrapping dynamics of 601-DNA from the nucleosome and observed that force-induced unwrapping happens more slowly for DNA that is more bendable because of changes in sequence or chemical modification. This manuscript appears to be a sequel to this line of projects, where the effect of CC is tested. The authors confirmed that CC is the most flexible mismatch using the FRET-based cyclization assay and found that unwrapping becomes slower when CC is introduced at three different positions in the 601 sequence. The CC mismatch only affects the local unwrapping dynamics of the outer turn of nucleosomal DNA.

      Strengths:

      These results are in good agreement with the previously established correlation between DNA bendability and nucleosome mechanical stability by the same group. This well-executed, technically sound, and well-written experimental study contains novel nucleosome unwrapping data specific to the CC mismatch and 601 sequence, the cyclizability of DNA containing all base pair mismatches, and the unwrapping of 601-DNA from xenophus and yeast histones. Overall, this work will be received with great interest by the biophysics community and is definitely worth attention.

      Weaknesses:

      The scope and impact of this study are somewhat limited due to the lack of sequence variation. Whether the conclusion from this study can be generalized to other sequences and other bendability-enhancing mismatches needs further investigation.

      Major questions:

      (1) As pointed out by the authors, the FRET signal is not sensitive to nucleosome position; therefore, the increasing unwrapping force in the presence of CC can be interpreted as the repositioning of the nucleosome upon perturbation. It is then also possible that CC-containing DNA is not positioned exactly the same as normal DNA from the start upon nucleosome assembly, leading to different unwrapping trajectories. What is the experimental evidence that supports identical positioning of the nucleosomes before the first stretch?

      We added the following and refer to our recent publication1 to address this question.

      “This is consistent with a previous single nucleotide resolution mapping of dyad position from of a library of mismatches in all possible positions along the 601 sequence or a budding yeast native sequence which showed that a single mismatch (A-A or T-T) does not affect the nucleosome position27.”

      (2) The authors chose a constant stretching rate in this study. Can the authors provide a more detailed explanation or rationale for why this rate was chosen? At this rate, the authors found hysteresis, which indicates that stretching is faster than quasi-static. But it must have been slow and weak enough to allow for reversible unwrapping and wrapping of a CC-containing DNA stretch longer than one helical turn. Otherwise, such a strong effect of CC at a single location would not be seen. I am also curious about the biological relevance of the magnitude of the force. Can such force arise during nucleosome assembly in vivo?

      To address the comment about the magnitude of force, we added the following paragraph to Introduction. “RNA polymerase II can initiate transcription at 4 pN of hindering force2 and its elongation activity continues until it stalls at ~ 10 pN of hindering force3,4. Therefore, the transcription machinery can generate picoNewtons of force on chromatin as long as both the machinery and the chromatin segment in contact are tethered to stationary objects in the nucleus. Another class of motor protein, chromatin remodeling enzymes, was also shown to induce processive and directional sliding of single nucleosomes when the DNA is under similar amount of tension (~ 5 pN)5. Therefore, measurements of nucleosomes at a few pN of force will expand our knowledge of the physiology roles of nucleosome structure and dynamics.”

      To address the comment about the stretching rate, we added the following to Results. We note that the physiological loading rate has been challenging to determine for any biomolecular interactions, and the only quantitative measurement we are aware of is that of an integrin that we are citing.

      “The force increases nonlinearly and the loading rate, i.e. the rate at which the force increases, was approximately in the range of 0.2 pN/s to 6 pN/s, similar to the cellular loading rates for a mechanosensitive membrane receptor6.”

      (3) In this study, the CC mismatch is the only change made to the 601 sequence. For readers to truly appreciate its unique effect on unwrapping dynamics as a base pair defect, it would be nice to include the baseline effects of other minor changes to the sequence. For example, how robust is the unwrapping force or dynamics against a single-bp change (e.g., AT to GC) at the three chosen positions?

      Unfortunately, we are unable to perform the suggested unwrapping experiment in a timely manner because the instrument has been disassembled during our recent move. However, we previously performed unwrapping experiments not only as a function of sequence but also as a function of cytosine modification and showed that we can detect even more subtle effects7,8. In addition, please note that we are not claiming that simply changing basepair at the chosen sites changes the mechanical stability of a nucleosome so we do not believe the requested experiment is necessary.

      (4) The last section introduces yeast histones. Based on the theme of the paper, I was expecting to see how the effect of CC is or is not preserved with a different histone source. Instead, the experiment only focuses on differences in the unwrapping dynamics. Although the data presented are important, it is not clear how they fit or support the narrative of the paper without the effect of CC.

      We apologize for giving the reviewer a wrong impression. We included the data because we believe that information on how the histone core can determine the translation of DNA mechanics into nucleosome mechanical stability will be of interest to the readers of this manuscript. We now mention explicitly that the observation was made using intact DNA, i.e. no mismatch, in the abstract and elsewhere.

      (5) It is stated that tRNA was excluded in experiments with yeast-expressed nucleosomes. What is the reason for excluding it for yeast nucleosomes? Did the authors rule out the possibility that tRNA causes the measured difference between the two nucleosome types?

      We normally include tRNA because we found that it reduces sticking of beads to the surface over several hours of experiments. In yeast nucleosomes, we found that tRNA causes the nucleosome to disassemble. Therefore, we did not include tRNA in yeast nucleosome experiments. We now mention this in Methods as reproduced below.

      “tRNA, which we normally include to reduce sticking of beads to the surface over the hours of single molecule experiments in a sealed chamber, was excluded in experiments with yeastexpressed nucleosomes because tRNA induced disassembly of nucleosomes assembled using yeast histones.”

      We cannot not formally rule out the possibility that tRNA causes the measured difference between Xenopus - vs Yeast- nucleosomes. However, we have shown in our previous publication7 that the asymmetric unwrapping in Xenopus nucleosomes was modulated by the DNA sequence. When we swapped the sequence of the inner turn between the two sides, while tRNA was included in all experiments, we observed stochastic unwrapping instead. As part of our response to another reviewer’s comments, we also added the following on the relevant differences between the species in Discussion.

      “The crystal structure of the yeast nucleosome suggests that yeast nucleosome architecture is subtly destabilized in comparison with nucleosomes from higher eukaryotes9. Yeast histone protein sequences are not well conserved relative to vertebrate histones (H2A, 77%; H2B, 73%; H3, 90%; H4, 92% identities), and this divergence likely contributes to differences in nucleosome stability. Substitution of three residues in yeast H3 a3-helix (Q120, K121, K125) very near the nucleosome dyad with corresponding human H3.1/H3.3 residues (QK…K replaced with MP…Q) caused severe growth defects, elevated nuclease sensitivity, reduced nucleosome positioning and nucleosome relocation to preferred locations predicted by DNA sequence alone 10. The yeast histone octamer harboring wild type H3 may be less capable of wrapping DNA over the histone core, leading to reduced resistance to the unwrapping force for the more flexible half of the 601positioning sequence.”

      Reviewer #2 (Public Review):

      Summary:

      Mismatches occur as a result of DNA polymerase errors, chemical modification of nucleotides, during homologous recombination between near-identical partners, as well as during gene editing on chromosomal DNA. Under some circumstances, such mismatches may be incorporated into nucleosomes but their impact on nucleosome structure and stability is not known. The authors use the well-defined 601 nucleosome positioning sequence to assemble nucleosomes with histones on perfectly matched dsDNA as well as on ds DNA with defined mismatches at three nucleosomal positions. They use the R18, R39, and R56 positions situated in the middle of the outer turn, at the junction between the outer turn and inner turn, and in the middle of the inner turn, respectively. Most experiments are carried out with CC mismatches and Xenopus histones. Unwrapping of the outer DNA turn is monitored by singlemolecule FRET in which the Cy3 donor is incorporated on the 68th nucleotide from the 5'-end of the top strand and the Cy5 acceptor is attached to the 7th nucleotide from the 5' end of the bottom strand. Force is applied to the nucleosomal DNA as FRET is monitored to assess nucleosome unwrapping. The results show that a CC mismatch enhances nucleosome mechanical stability. Interestingly, yeast and Xenopus histones show different behaviors in this assay. The authors use FRET to measure the cyclization of the dsDNA substrates to test the hypothesis that mismatches enhance the flexibility of the 601 dsDNA fragment and find that CC, CA, CT, TT, and AA mismatches decrease looping time, whereas GA, GG, and GT mismatches had little to no effect. These effects correlate with the results from DNA buckling assays reported by Euler's group (NAR 41, 2013) using the same mismatches as an orthogonal way to measure DNA kinking. The authors discuss that substitution rates are higher towards the middle of the nucleosome, suggesting that mismatches/DNA damage at this position are less accessible for repair, consistent with the nucleosome stability results.

      Strengths:

      The single-molecule data show clear and consistent effects of mismatches on nucleosome stability and DNA persistence length.

      Weaknesses:

      It is unclear in the looping assay how the cyclization rate relates to the reporting looping time. The biological significance and implications such as the effect on mismatch repair or nucleosome remodelers remain untested. It is unclear whether the mutational pattern reflects the behavior of the different mismatches. Such a correlation could strengthen the argument that the observed effects are relevant for mutagenesis.

      Reviewer #3 (Public Review):

      Summary:

      The mechanical properties of DNA wrapped in nucleosomes affect the stability of nucleosomes and may play a role in the regulation of DNA accessibility in eukaryotes. In this manuscript, Ngo and coworkers study how the stability of a nucleosome is affected by the introduction of a CC mismatched base pair, which has been reported to increase the flexibility of DNA. Previously, the group has used a sophisticated combination of single-molecule FRET and force spectroscopy with an optical trap to show that the more flexible half of a 601 DNA segment provides for more stable wrapping as compared to the other half. Here, it is confirmed with a single-molecule cyclization essay that the introduction of a CC mismatch increases the flexibility of a DNA fragment. Consistent with the previous interpretation, it also increased the unwrapping force for the half of the 601 segment in which the CC mismatch was introduced, as measured with single-molecule FRET and force spectroscopy. Enhanced stability was found up to 56 bp into the nucleosome. The intricate role of mechanical stability of nucleosomes was further investigated by comparing force-induced unwrapping profiles of yeast and Xenopus histones. Intriguingly, asymmetric unwrapping was more pronounced for yeast histones.

      Strengths:

      (1) High-quality single-molecule data.

      (2) Novel mechanism, potentially explaining the increased prominence of mutations near the dyads of nucleosomes.

      (3) A clear mechanistic explanation of how mismatches affect nucleosome stability.

      Weaknesses:

      (1) Disconnect between mismatches in nucleosomes and measurements comparing Xenopus and yeast nucleosome stability.

      (2) Convoluted data in cyclization experiments concerning the phasing of mismatches and biotin site. ---

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Specific comments:

      In Figure 1 legend, "the black diamonds on the DNA bends represent the mismatch position with R18 and R39 on minor grooves and R56 on a major groove." Minor and major grooves should be phrased as histone-facing minor and major grooves.

      We fixed the problem.

      In Materials and Methods, the sentence that describes the stretching rate cites reference 1, which does not seem to be relevant.

      We fixed the problem.

      Reviewer #2 (Recommendations For The Authors):

      (1) In the introduction, the authors should also discuss the context of mismatches occurring during homologous recombination in meiosis or somatic cells in non-allelic recombination between near identical repeats.

      Introduction now has the following.

      “DNA base-base mismatches are generated by nucleotide misincorporation during DNA synthesis, meiotic recombination, somatic recombination between nearly identical repeats, or chemical modification such as hydrolytic deamination of cytosine.”

      (2) Generally, it seems counter-intuitive in terms of biology that mismatches containing nucleosomes are more stable, as mismatches require repair and/or detection for heteroduplex rejection during recombination. Some discussion of this apparent paradox should be added.

      To address this comment, we added the following to Discussion.

      “The higher frequency of substitutions in the nucleosomal DNA may be attributed to the difficulty of accessing the extra-stable nucleosomes. We also note that even without an enhanced stability, a mismatch within a nucleosome would be more difficult to detect for mismatch repair machineries compared to a mismatch in a non-nucleosomal DNA. Because mismatch repair machineries accompany the replisome, most of nascent mismatches may be detected for repair before nucleosome deposition. Therefore, the decrease in accessibility predicted based on our data here may be important only in rare cases a mismatch is not detected prior to the deposition of a nucleosome on the nascent DNA or in cases where a mismatch is generated via a non-replicative mechanism.”

      (3) The authors discuss that the substitution rate is higher while the indel (insertion and deletion) rate is lower nearer the center of a positioned nucleosome. Are the differences between individual mismatches reported in Figure 6 reflected in the mutagenic profile?

      We cannot currently compare them because the mutagenic profile even when it is available is a complex convolution of mismatch generation, mismatch repair and selection. Mismatch generation occurs through several different processes and how they are affected by nucleosomes and their mismatch type and sequence context is unknown. Mismatch repair process itself depends on mismatch type and sequence context as recently shown by a high throughput in vivo study11. And because the population genetics does not simply reflect de novo mutation profiles due to selection, comparison between mismatch-induced DNA mechanical changes and mutagenic profiles is further complicated. We added the following to the revision.

      “If and how the mismatch type-dependent DNA mechanics affects the sequence-dependent mismatch repair efficiency in vivo, as recently determined in a high through study in E. coli11, remains to be investigated. Comparison of mismatch-type dependent DNA mechanics to population genetics data is challenging because mutation profiles reflect a combined outcome of mismatch-generation, mismatch repair and selection in addition to other mutational processes.”

      (4) The looping assay should be explained better, especially how the cyclization rate is related to the reported looping time.

      We modified Figure 5 to include examples of looping time determination through fitting of the looped fraction vs time, and added the following to the figure caption.

      “To calculate the looping time, the fraction of looped molecules (high FRET) as a function of time is fitted to an exponential function, 𝑒−𝑡⁄(𝑙𝑜𝑜𝑝𝑖𝑛𝑔 𝑡𝑖𝑚𝑒) (right panel for one run of experiments).

      Furthermore, we added the following sentence to Results.

      “The rate of loop formation, which is the inverse of looping time determined from an exponential fitting of loop fraction vs time, was used as a measure of apparent DNA flexibility influenced by a mismatch 12,13.”

      *Reviewer #3 (Recommendations For The Authors):

      I have some concerns that, when addressed upon revision, would improve the manuscript:

      (1) Page 6 and Supplementary Figure S1C: Though the FRET levels are the same for all nucleosomes, the distribution between the two levels is not. The nucleosomes with CC mismatches appear to have a larger fraction in the low-FRET population. This seems to contradict the higher mechanical stability. A comment on this should clarify it, or make this conundrum explicit.

      Thank you for the comment. The low FRET population also includes the nucleosomes that do not have an active acceptor the fraction of which varies between preparations. We now note this in the supplementary figure caption.

      (2) It is intriguing that a more stable nucleosome forms after several pulling cycles and it is argued that this might be due to shifting of the nucleosome. This seems reasonable and has important consequences both for the interpretation of the current experimental data and for the general mechanisms involved in nucleosome maintenance and remodeling. It is puzzling though how this would work mechanistically since it only seems to happen when nucleosomes are half-wrapped and when the unwrapped half contains the mismatch. From the previous work of the group and the current manuscript, it seems that shift does not occur in DNA without mismatches (Correct?). Does shifting happen for the 601-R18 and 601-R56 nucleosomes as well?

      The mismatch-containing half is the half that is mechanically less stable in an intact, mismatch-free 601 nucleosome. So indeed, that is the half that is unwrapped in an intact nucleosome. But because the introduction of mismatch makes that half more mechanically stable, it can stay wrapped until higher forces, and the resulting structural distortion may cause the shift although we acknowledge that this interpretation remains speculative. Shifting occurs for all three constructs with a mismatch but not for the intact nucleosome without a mismatch.

      (3) Could the shifting be related to the differences in sub-population distribution observed in Supplementary Figure S1C?

      /See our response to comment (1) above.

      (4) The paper would have more impact if the mechanism of possible shifting could be clarified. This can be done experimentally with a fluorescent histone, as suggested in the manuscript. But having a FRET pair on positions in the DNA that would shift to closer proximity upon shifting, either at the ED2 or at the ED1 site will also work, is in line with the current experiments and seems feasible.

      We revised the text as follows in order not to exclude labeling configurations with both fluorophores on the DNA while reporting on the shift. We are also happy to add an appropriate reference if the reviewer can help us identify an existing study that measured dyad position shifts through such a labeling configuration.

      “However, since the FRET values in our DNA construct are not sensitive to the nucleosome position, further experiments with fluorophores conjugated to strategic positions that allow discrimination between different dyad positions14 will be required to test this hypothesis.”

      (5) Figures 5 and 6: To appreciate the quality of the data, state the number of molecules that contributed to the cyclization essay, or better, share a figure of the number of looped molecules as a function of time as supplementary data.

      We added the requested figures to Figure 5 and a new supplementary Figure 2, and added the following to Methods.

      “Approximately 2500 – 3500 molecules were quantified at each timestamp during the experiment, and three independent experiments were performed for each sequence (Supplemental Figure S2).”

      (6) Page 8/9: A control is added to confirm that the phasing of the biotin relative to the end affects the observed cyclization rate. However, the mismatch sites were chosen such that they included 5 bp phase shifts. This convolutes the outcomes, as the direction of flexibility due to the phasing of the mismatch relative to the biotin may also influence the rate. Was this checked?

      We would like to clarify that the phasing of the biotin is not so much as with respect to the end, as it is with respect to the full molecule. Static curvature and poloidal angle associated with the DNA molecule (which is something that is ultimately determined by the full chemical composition of the molecule, including its sequence and the mismatch) could make the molecule prefer a looped configuration where the biotin points towards the “inside” of the molecule. Such a configuration would be sterically unfavoured during the single molecule looping reaction where the biotin is attached to a surface via avidin. However, if the biotin is moved by half the helical repeat (or an off multiple of half the helical repeat, essentially 16 nt as done in the manuscript), it would now point to the “outside” of the molecule. Therefore, to make sure that the difference between the looping rates of any two DNA constructs (say the 601-RH and 601-R18-RH) is a better reflection of differences in dynamic flexibility, we ensure that the difference persists even when the biotin is moved by an odd multiple of half the helical repeat. We revised the section as follows.

      “For example, moving the location of the biotin tether by half the helical repeat (~ 5 bp) can lead to a large change in cyclization rate15, likely due to the preferred poloidal angle of a given DNA16 that determines whether the biotin is facing towards the inside of the circularized DNA, thereby hindering cyclization due to steric hindrance caused by surface tethering.”

      (7) Page 9/10: The comparison of yeast vs Xenopus is interesting, albeit a bit disconnected. Since the single-molecule statistics are relatively small, did the nucleosomes show similar bulk FRET distributions, or did they also show a shift in FRET levels?

      We included the data because we believe that information on how the histone core can determine the translation of DNA mechanics into nucleosome mechanical stability will be of interest to the readers of this manuscript. The FRET values were similarly distributed.

      (8) The discussion calls for a more detailed analysis of the structural differences of the histones of the two species to rationalize the observed asymmetry in flexibility dependence: why would yeast nucleosomes be less sensitive to sequence asymmetries?

      We added the following to Discussion to address this comment.

      “The crystal structure of the yeast nucleosome suggests that yeast nucleosome architecture is subtly destabilized in comparison with nucleosomes from higher eukaryotes9. Yeast histone protein sequences are not well conserved relative to vertebrate histones (H2A, 77%; H2B, 73%; H3, 90%; H4, 92% identities), and this divergence likely contributes to differences in nucleosome stability. Substitution of three residues in yeast H3 3-helix (Q120, K121, K125) very near the nucleosome dyad with corresponding human H3.1/H3.3 residues (QK…K replaced with MP…Q) caused severe growth defects, elevated nuclease sensitivity, reduced nucleosome positioning and nucleosome relocation to preferred locations predicted by DNA sequence alone 10. The yeast histone octamer harboring wild type H3 may be less capable of wrapping DNA over the histone core, leading to reduced resistance to the unwrapping force for the more flexible half of the 601positioning sequence.”

      (9) It would also be interesting if the increased stability due to the introduction of mismatches observed on Xenopus nucleosomes holds in yeast. Or does the reduced stability remove this effect? This is relevant to substantiate the broad claims in the context of evolution and cancer that are discussed in the manuscript.

      Unfortunately, we are unable to perform the suggested unwrapping experiment in a timely manner because the instrument has been disassembled during our recent move. However, in terms of cancer relevance, our mismatch dependence experiments were performed using vertebrate nucleosomes (Xenopus) so repeating this for yeast nucleosomes would not provide relevant information.

      Minor comments:

      (1) Supplementary Figure S1 misses the label '(C)' in its caption.

      We fixed it.

      (2) The supplementary data sequences for the fleezer measurements contain entrees 'R39 construct' and miss the positions of the Cy3 and Cy labels; the color code (levels of grey) is not explained.

      We fixed the labeling mistake and added detailed annotations of the highlighted features.

      References

      (1) Park, S., Brandani, G.B., Ha, T. & Bowman, G.D. Bi-directional nucleosome sliding by the Chd1 chromatin remodeler integrates intrinsic sequence-dependent and ATP-dependent nucleosome positioning. Nucleic Acids Res 51, 10326-10343 (2023).

      (2) Fazal, F.M., Meng, C.A., Murakami, K., Kornberg, R.D. & Block, S.M. Real-time observation of the initiation of RNA polymerase II transcription. Nature 525, 274-7 (2015).

      (3) Galburt, E.A., Grill, S.W., Wiedmann, A., Lubkowska, L., Choy, J., Nogales, E., Kashlev, M. & Bustamante, C. Backtracking determines the force sensitivity of RNAP II in a factor-dependent manner. Nature 446, 820-3 (2007).

      (4) Schweikhard, V., Meng, C., Murakami, K., Kaplan, C.D., Kornberg, R.D. & Block, S.M. Transcription factors TFIIF and TFIIS promote transcript elongation by RNA polymerase II by synergistic and independent mechanisms. Proc Natl Acad Sci U S A 111, 6642-7 (2014).

      (5) Kim, J.M., Carcamo, C.C., Jazani, S., Xie, Z., Feng, X.A., Yamadi, M., Poyton, M., Holland, K.L., Grimm, J.B., Lavis, L.D., Ha, T. & Wu, C. Dynamic 1D Search and Processive Nucleosome Translocations by RSC and ISW2 Chromatin Remodelers. bioRxiv (2024). (6) Jo, M.H., Meneses, P., Yang, O., Carcamo, C.C., Pangeni, S. & Ha, T. Determination of singlemolecule loading rate during mechanotransduction in cell adhesion. Science (in press).

      (7) Ngo, T.T., Zhang, Q., Zhou, R., Yodh, J.G. & Ha, T. Asymmetric unwrapping of nucleosomes under tension directed by DNA local flexibility. Cell 160, 1135-44 (2015).

      (8) Ngo, T.T., Yoo, J., Dai, Q., Zhang, Q., He, C., Aksimentiev, A. & Ha, T. Effects of cytosine modifications on DNA flexibility and nucleosome mechanical stability. Nat Commun 7, 10813 (2016).

      (9) White, C.L., Suto, R.K. & Luger, K. Structure of the yeast nucleosome core particle reveals fundamental changes in internucleosome interactions. EMBO J 20, 5207-18 (2001).

      (10) McBurney, K.L., Leung, A., Choi, J.K., Martin, B.J., Irwin, N.A., Bartke, T., Nelson, C.J. & Howe, L.J. Divergent Residues Within Histone H3 Dictate a Unique Chromatin Structure in Saccharomyces cerevisiae. Genetics 202, 341-9 (2016).

      (11) Kayikcioglu, T., Zarb, J.S., Lin, C.-T., Mohapatra, S., London, J.A., Hansen, K.D., Rishel, R. & Ha, T. Massively parallel single molecule tracking of sequence-dependent DNA mismatch repair in vivo. bioRxiv, 2023.01.08.523062 (2023).

      (12) Jeong, J., Le, T.T. & Kim, H.D. Single-molecule fluorescence studies on DNA looping. Methods 105, 34-43 (2016).

      (13) Jeong, J. & Kim, H.D. Base-Pair Mismatch Can Destabilize Small DNA Loops through Cooperative Kinking. Phys Rev Lett 122, 218101 (2019).

      (14) Blosser, T.R., Yang, J.G., Stone, M.D., Narlikar, G.J. & Zhuang, X. Dynamics of nucleosome remodelling by individual ACF complexes. Nature 462, 1022-7 (2009).

      (15) Basu, A., Bobrovnikov, D.G., Qureshi, Z., Kayikcioglu, T., Ngo, T.T.M., Ranjan, A., Eustermann, S., Cieza, B., Morgan, M.T., Hejna, M., Rube, H.T., Hopfner, K.P., Wolberger, C., Song, J.S. & Ha, T. Measuring DNA mechanics on the genome scale. Nature 589, 462-467 (2021).

      (16) Yoo, J., Park, S., Maffeo, C., Ha, T. & Aksimentiev, A. DNA sequence and methylation prescribe the inside-out conformational dynamics and bending energetics of DNA minicircles. Nucleic Acids Res 49, 11459-11475 (2021).

    1. fears of thine own making

      Imagined -> religion is about consequences and punishment

      Religion to Bianca is a moral code and to the duke it is about human perceptions

    Annotators

    1. In order to loop a set number of times, we can use the range function to effectively make a list of numbers to go over, so we can loop that many times. For example, if we wanted to ask “Are we there yet?” repeatedly, 10 times, we can do this:

      Where should I put sleep in this code? Just after the print?

    1. Author response:

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

      eLife assessment

      This is a valuable computational study that applies the machine learning method of bilinear modeling to the problem of relating gene expression to connectivity. Specifically, the author attempts to use transcriptomic data from mouse retinal neurons to predict their known connectivity. The results are promising, although the reviewers felt that demonstration of the general applicability of the approach required testing it against a second data set. Hence the present results were felt to provide borderline incomplete support for a key premise of the paper.

      We thank the reviewers for their insightful and constructive feedback. In response to the reviews, we have undertaken a comprehensive revision of our manuscript, incorporating changes and improvements as outlined below:

      (1) New results have been included showcasing the application of our bilinear model to a seconddataset focusing on C. elegans gap junction connectivity. This extension validates our model with a biological context other than mouse retina and facilitates a direct comparison with the spatial connectome model (SCM).

      (2) A new section titled "Previous Approaches" has been added to background, situating our studywithin the broader landscape of existing modeling methodologies.

      (3) The discussion sections have been expanded to fully incorporate the suggestions and insightsoffered by the reviewers. This includes a deeper exploration of the implications of our findings, potential applications of our model, and a more thorough consideration of its limitations and future directions.

      (4) To streamline the main text and ensure that the core narrative remains focused and accessible, select figures and tables have been relocated to the "Supplementary Materials" section.

      Reviewer 1 (Public Review):

      Summary of what the author was trying to achieve: In this study, the author aimed to develop a method for estimating neuronal-type connectivity from transcriptomic gene expression data, specifically from mouse retinal neurons. They sought to develop an interpretable model that could be used to characterize the underlying genetic mechanisms of circuit assembly and connectivity.

      Strengths:

      The proposed bilinear model draws inspiration from commonly implemented recommendation systems in the field of machine learning. The author presents the model clearly and addresses critical statistical limitations that may weaken the validity of the model such as multicollinearity and outliers. The author presents two formulations of the model for separate scenarios in which varying levels of data resolution are available. The author effectively references key work in the field when establishing assumptions that affect the underlying model and subsequent results. For example, correspondence between gene expression cell types and connectivity cell types from different references are clearly outlined in Tables 1-3. The model training and validation are sufficient and yield a relatively high correlation with the ground truth connectivity matrix. Seemingly valid biological assumptions are made throughout, however, some assumptions may reduce resolution (such as averaging over cell types), thus missing potentially important single-cell gene expression interactions.

      Thank you for recognizing the strengths of our work, particularly the clarity of the model presentation and its foundation in recommendation systems. In the revised manuscript we have also extended the model’s capabilities to analyze gene interactions for neural connectivity at single-cell resolution, when gene expression and connectivity of each cell are known simultaneously.

      Weaknesses:

      The main results of the study could benefit from replication in another dataset beyond mouse retinal neurons, to validate the proposed method. Dimensionality reduction significantly reduces the resolution of the model and the PCA methodology employed is largely non-deterministic. This may reduce the resolution and reproducibility of the model. It may be worth exploring how the PCA methodology of the model may affect results when replicating. Figure 5, ’Gene signatures associated with the two latent dimensions’, lacks some readability and related results could be outlined more clearly in the results section. There should be more discussion on weaknesses of the results e.g. quantification of what connectivity motifs were not captured and what gene signatures might have been missed.

      We acknowledge the significance of validating our method across different datasets. In line with this, our revised manuscript now includes an expanded analysis utilizing a C. elegans gap junction connectivity dataset, which not only broadens the method’s demonstrated applicability but also underscores its versatility across varied neuronal systems.

      To address the concern of resolution and reproducibility associated with PCA preprocessing, we have conducted a comparative analysis from five replicates of the bilinear model, presenting the results in the revised manuscript (Figure S3). This analysis confirms the consistency of the solutions, as evidenced by the similarity metrics. Furthermore, we discussed alternative methodologies, such as L1 or L2 regularization, to tackle multicollinearity, offering flexibility in preprocessing choices.

      In response to feedback on the original Figure 5’s clarity, we have replaced the original Figure 5e-h with Table S4, which summarizes the gene ontology (GO) enrichment results and quantifies the number of genes associated with aspects of neural development and synaptic organization. This revision aims to improve the interpretability and accessibility of the results, ensuring a clearer presentation of the model’s insights.

      Finally, we have expanded our discussion to address the study’s limitations more comprehensively. This includes exploration of potentially missed connections and gene signatures, such as transcription factors, which might not be captured by a linear model due to its inherent preference for predictors with strong correlations to the target variable.

      The main weakness is the lack of comparison against other similar methods, e.g. methods presented in Barabási, Dániel L., and Albert-László Barabási. "A genetic model of the connectome." Neuron 105.3 (2020): 435-445. Kovács, István A., Dániel L. Barabási, and Albert-László Barabási. "Uncovering the genetic blueprint of the C. elegans nervous system." Proceedings of the National Academy of Sciences 117.52 (2020): 33570-33577. Taylor, Seth R., et al. "Molecular topography of an entire nervous system." Cell 184.16 (2021): 4329-4347.

      We value your suggestion to compare our model with established methods. The revised manuscript now includes a comparative analysis with the spatial connectome model (SCM) using the same C. elegans dataset. In addition, a section reviewing previous approaches has been included in the background part, and the discussion part has been extended for the comparison.

      Appraisal of whether the author achieved their aims, and whether results support their conclusions: The author achieved their aims by recapitulating key connectivity motifs from single-cell gene expression data in the mouse retina. Furthermore, the model setup allowed for insight into gene signatures and interactions, however could have benefited from a deeper evaluation of the accuracy of these signatures. The author claims the method sets a new benchmark for single-cell transcriptomic analysis of synaptic connections. This should be more rigorously proven. (I’m not sure I can speak on the novelty of the method)

      In the revised manuscript. we emphasized the bilinear model’s innovative application in the context of neuronal connectivity analysis, inspired by collaborative filtering in recommendation systems. We present quantitative performance metrics, such as the ROC-AUC score and Pearson correlation coefficient, as well as its comparison with the SCM, to benchmark our model’s efficacy in reconstructing connectivity matrices. We also quantified the overlap of the genetic interactions revealed by the bilinear model and the SCM (using the C. elegans dataset), and reported the percentage of the top genes associated with neural development and synaptic organization (using the mouse retina dataset). These numbers set a precedent for future methodological comparisons.

      Discussion of the likely impact of the work on the field, and the utility of methods and data to the community : This study provides an understandable bilinear model for decoding the genetic programming of neuronal type connectivity. The proposed model leaves the door open for further testing and comparison with alternative linear and/or non-linear models, such as neural networkbased models. In addition to more complex models, this model can be built on to include higher resolution data such as more gene expression dimensions, different types of connectivity measures, and additional omics data.

      We are grateful for your recognition of the study’s potential impact. The bilinear model indeed offers a foundation for future explorations, allowing for integration with more complex models, higher-resolution data, and diverse connectivity measures.

      Reviewer 1 (Recommendations For The Authors):

      The inclusion of predicted connectivity (Figure 6) of unknown BC neurons is useful as it shows that this is a strong hypothesis generation tool. This utility should potentially be showcased more as it is also brought up in the abstract, "genetic manipulation of circuit wiring", with an explanation of how the model could be leveraged as such. The discussion may benefit from a summarizing sentence regarding which key gene signatures were identified and are in line with the literature, which key gene signatures/connectivity motifs may have been missed, and which gene signatures are novel.

      Thank you for the insightful recommendation on emphasizing the model’s utility in generating hypotheses, particularly regarding predicting connectivity. In the revised manuscript, we have expanded the discussion on how our model can be leveraged to guide genetic manipulations at altering circuit wiring and highlighted its potential impact in the field.

      We have discussed key gene signatures identified from our model that are in line with existing literature, such as plexins and cadherins, which have been previously recognized for their involvement in synaptic connection formation and maintenance. We have also introduced potential new candidates, such as delta-protocadherins. In the revised manuscript, we summarized potentially missed gene signatures or synaptic connections, to provide a comprehensive view of our findings.

      Reviewer 2 (Public Review):

      Summary:

      In this study, Mu Qiao employs a bilinear modeling approach, commonly utilized in recommendation systems, to explore the intricate neural connections between different pre- and post-synaptic neuronal types. This approach involves projecting single-cell transcriptomic datasets of pre- and post-synaptic neuronal types into a latent space through transformation matrices. Subsequently, the cross-correlation between these projected latent spaces is employed to estimate neuronal connectivity. To facilitate the model training, connectomic data is used to estimate the ground-truth connectivity map. This work introduces a promising model for the exploration of neuronal connectivity and its associated molecular determinants. However, it is important to note that the current model has only been tested with Bipolar Cell and Retinal Ganglion Cell data, and its applicability in more general neuronal connectivity scenarios remains to be demonstrated.

      Strengths:

      This study introduces a succinct yet promising computational model for investigating connections between neuronal types. The model, while straightforward, effectively integrates singlecell transcriptomic and connectomic data to produce a reasonably accurate connectivity map, particularly within the context of retinal connectivity. Furthermore, it successfully recapitulates connectivity patterns and helps uncover the genetic factors that underlie these connections.

      Thank you for your positive assessment of the paper.

      Weaknesses:

      (1) The study lacks experimental validation of the model’s prediction results.

      We recognize the importance of experimental validation in substantiating the predictions made by computational models. While the primary focus of this study remains computational, we have dedicated a section in the revised manuscript, titled "Experimental Validation of Candidate Genes", to outline proposed methodologies for the empirical verification of our model’s predictions. This section specifically discusses the experimental exploration of novel candidate genes, such as deltaprotocadherins, within the mouse retina using AAV-mediated CRISPR/Cas9 genetic manipulation. We plan to collaborate with experimental laboratories to facilitate the validation. Given the extensive nature of experimental work, both in terms of time and resources, it is more pragmatic to present a comprehensive experimental investigation in a follow-up study.

      (2) The model’s applicability in other neuronal connectivity settings has not been thoroughly explored.

      The question of the model’s broader applicability is well-taken. In response, we have expanded our analysis to include additional neuronal data and connectivity settings. Specifically, the revised manuscript includes results where we apply the model to a dataset of C. elegans gap junction connectivity, demonstrating its potential in different neuronal systems. This extension serves to illustrate the model’s adaptability and potential applicability to a broader range of neuronal connectivity studies.

      (3) The proposed method relies on the availability of neuronal connectomic data for model training,which may be limited or absent in certain brain connectivity settings.

      We acknowledge the limitations posed by the model’s dependency on comprehensive connectomic data, which may not be readily available across all research contexts. To address this, we have discussed in the revised manuscript several alternative strategies to adapt our model to the available data. This includes exploring the potential of applying the model to available data such as projectome, and integrating other data modalities such as electrophysiological measurements. These initiatives aim to enhance the model’s applicability and ensure its utility in a broader spectrum of brain connectivity studies, especially in scenarios where detailed connectomic data are not available.

      Reviewer 2 (Recommendations For The Authors):

      Q1. In this work, the author has mainly been studying the retina neuronal type connectivity, it will be interesting to see whether the model works for other brain regions or other neuronal type connectivity as well.

      We value your interest in the model’s applicability to other brain regions and neuronal types. To address this, we have extended our analysis in the revised manuscript to include a study on gap junction connectivity between C. elegans neurons. This extension demonstrates the model’s versatility and its potential applicability across various nervous systems and connectivity types.

      Q2. Whether the authors can use the same transformation matrices trained from the retina data to predict neuronal connectivity in other brain regions? Or an easier case, the connectivity between RGC types to the neuronal types in SC, dLGN, or other post-RGC-synaptic brain regions. As the neuronal connection mechanisms are conserved and widely shared between different neuronal types, one would expect the same transformation matrices may work in predicting other neuronal type connectivity as well (at least to some extent).

      The idea to use the same transformation matrices for predicting connectivity in other brain regions is intriguing. While direct application of these matrices to different regions remains challenging, we discussed the potential scalability of our model to other brain areas. By applying the model to combined datasets from various regions, we could uncover conserved neuronal connection mechanisms. This approach is theoretically feasible and is supported by the demonstrated scalability of the bilinear model and its deep learning variants in industrial applications.

      Q3. Section 5.2 Connectivity metric generation: in this work, the author uses the stratification profiles of the neurons to estimate the connectivity metric, how reliable this method is? There will be a scenario where though two neuronal types project to a similar inner plexiform layer, they may not have any connection. Have the authors considered combining other experimental data (like electrophysiology data or neuron tracing data)?

      We discussed the reliability of using stratification profiles for estimating connectivity metrics, acknowledging potential limitations. In the revised manuscript, we added discussion on how the integration of additional experimental data, such as electrophysiological and neuron tracing data, could enhance the accuracy of the connectivity metrics.

      Q4. Section 6 Model training and validation: does the author have a potential hypothesis as to why 2 dimensions are the best latent feature spaces dimensionality? One would imagine with more dimensionality, the model will give better results. Could it be that the connectivity data that is used to train the model is only considering the two-dimensional space of the neuronal stratification?

      The selection of two dimensions for the latent feature space was informed by 5-fold cross-validation, aimed at optimizing model generalization to unseen data. Here while increasing dimensionality improves performance on the training set, it does not necessarily enhance generalization to the validation set. Thus, the choice of two dimensions ensures good performance without overfitting to the training data.

      Q5. Could the author provide the source code for the analysis? Or could the author make it a python/R package so that non-computational biologists can easily apply the method to their own data?

      We have included a "Data and Code Availability" section in the revised manuscript. This section provides a link to the source code with pointers to datasets used in our study, facilitating the application of our methods by researchers from various backgrounds.

      Q6. I know it may be difficult for the author to do, but is it possible to design and perform some experiments to validate the model prediction results, either connectivity partners of transcriptomicallydefined RGC types or the function of the key genetic molecules (which hasn’t been discovered before)? The author may consider collaborating with some experimental labs. The author may even consider predicting the connectivity between RGC with some of its post-synaptic neurons in the brain regions, like SC or dLGN, as recently there are a lot of single-cell sequencing data as well as connectivity data.

      We appreciate your suggestion regarding experimental validation. As a future direction, we have discussed potential experimental approaches to validate the model’s predictions in the "Experimental Validation of Candidate Genes" section. Specifically, we propose an experimental design involving the manipulation of delta-protocadherins using AAV-mediated CRISPR/Cas9 and subsequent examination of connectivity phenotypes. We are also open to collaborating with experimental labs to further explore the model’s predictions, particularly in predicting connectivity between RGCs and their post-synaptic neurons in other brain regions.

    1. Reviewer #3 (Public Review):

      Summary:

      The manuscript addresses a question inspired by the Baroceptor Hypothesis and its links to visual awareness and interoception. Specifically, the reported study aimed to determine if the effects of cardiac contraction (systole) on binocular rivalry (BR) are facilitatory or suppressive. The main experiment - relying on a technically challenging procedure of presenting stimuli synchronised with the heartbeats of participants - has been conducted with great care, and numerous manipulation checks the authors report convincingly show that the methods they used work as intended. Moreover, the control experiment allows for excluding alternative explanations related to participants being aware of their heartbeats. Therefore, the study convincingly shows the effect of cardiac activity on BR - and this is an important finding. The results, however, do not allow for unambiguously determining if this effect is facilitatory or suppressive (see details below), which renders the study not as informative as it could be.

      While the authors strongly focus on interoception and awareness, this study will be of interest to researchers studying BR as such. Moreover, the code and the data the authors share can facilitate the adoption of their methods in other labs.

      Strengths:

      (1) The study required a complex technical setup and the manuscript both describes it well and demonstrates that it was free from potential technical issues (e.g. in section 3.3. Manipulation check).

      (2) The sophisticated statistical methods the authors used, at least for a non-statistician like me, appear to be well-suited for their purpose. For example, they take into account the characteristics of BR (gamma distributions of dominance durations). Moreover, the authors demonstrate that at least in one case their approach is more conservative than a more basic one (Binomial test) would be.

      (3) Finally, the control experiment, and the analysis it enabled, allow for excluding a multitude of alternative explanations of the main results.

      (4) The authors share all their data and materials, even the code for the experiment.

      (5) The manuscript is well-written. In particular, it introduces the problem and methods in a way that should be easy to understand for readers coming from different research fields.

      Weaknesses:

      (1) The interpretation of the main result in the context of the Baroceptor hypothesis is not clear. The manuscript states: The Baroreceptor Hypothesis would predict that the stimulus entrained to systole would spend more time suppressed and, conversely, less time dominant, as cortical activity would be suppressed each time that stimulus pulses. The manuscript does not specify why this should be the case, and the term 'entrained' is not too helpful here (does it refer to neural entrainment? or to 'being in phase with'?). The answer to this question is provided by the manuscript only implicitly, and, to explain my concern, I try to spell it out here in a slightly simplified form.

      During systole (cardiac contraction), the visual system is less sensitive to external information, so it 'ignores' periods when the systole-synchronised stimulus is at the peak of its pulse. Conversely, the system is more sensitive during diastole, so the stimulus that is at the peak of its pulse then should dominate for longer, because its peaks are synchronised with the periods of the highest sensitivity of the visual system when the information used to resolve the rivalry is sampled from the environment. This idea, while indeed being a clever test of the hypothesis in question, rests on one critical assumption: that the peak of the stimulus pulse (as defined in the manuscript) is the time when the stimulus is the strongest for the visual system. The notion of 'stimulus strength' is widely used in the BR literature (see Brascamp et al., 2015 for a review). It refers to the stimulus property that, simply speaking, determines its tendency to dominate in the BR. The strength of a stimulus is underpinned by its low-level visual properties, such as contrast and spatial frequency content. Coming back to the manuscript, the pulsing of the stimuli affected at least spatial frequency (and likely other low-level properties), and it is unknown if it was in phase with the pulsing of the stimulus strength, or not. If my understanding of the premise of the study is correct, the conclusions drawn by the authors stand only if it was.

      In other words, most likely the strength of one of the stimuli was pulsating in sync with the systole, but is it not clear which stimulus it was. It is possible that, for the visual system, the stimulus meant to pulse in sync with the systole was pulsing strength-wise in phase with the diastole (and the one intended to pulse with in sync with the diastole strength-wise pulsed with the systole). If this is the case, the predictions of the Baroceptor Hypothesis hold, which would change the conclusion of the manuscript.

      (2) Using anaglyph goggles necessitates presenting stimuli of a different colour to each eye. The way in which different colours are presented can impact stimulus strength (e.g. consider that different anaglyph foils can attenuate the light they let through to different degrees). To deal with such effects, at least some studies on BR employed procedures of adjusting the colours for each participant individually (see Papathomas et al., 2004; Patel et al., 2015 and works cited there). While I think that counterbalancing applied in the study excludes the possibility that colour-related effects influenced the results, the effects of interest still could be stronger for one of the coloured foils.

      (3) Several aspects of the methods (e.g. the stimuli), are not described at the level of detail some readers might be accustomed to. The most important issue here is the task the participants performed. The manuscript says that they pressed a button whenever they experienced a switch in perception, but it is only implied that there were different buttons for each stimulus.

      Brascamp, J. W., Klink, P. C., & Levelt, W. J. M. (2015). The 'laws' of binocular rivalry: 50 years of Levelt's propositions. Vision Research, 109, 20-37. https://doi.org/10.1016/j.visres.2015.02.019<br /> Papathomas, T. V., Kovács, I., & Conway, T. (2004). Interocular grouping in binocular rivalry: Basic attributes and combinations. In D. Alais & R. Blake (Eds.), Binocular Rivalry (pp. 155-168). MIT Press<br /> Patel, V., Stuit, S., & Blake, R. (2015). Individual differences in the temporal dynamics of binocular rivalry and stimulus rivalry. Psychonomic Bulletin and Review, 22(2), 476-482. https://doi.org/10.3758/s13423-014-0695-1

    1. Gene Demby. How Code-Switching Explains The World. NPR, April 2013. URL: https://www.npr.org/sections/codeswitch/2013/04/08/176064688/how-code-switching-explains-the-world (visited on 2023-11-24).

      In the article "How Code-Switching Explains The World" from NRP, they talks about how different people "code switch" depending on the scenario. In the article, they showed famous celebrities such as Obama, Beyonce and other YouTube videos changing their tone of voice while still being themselves. This is because code switching can help benefit you depending on where you are and what situation you are in. The article also states that code switching is how we can "try to feel each other out." Code switching is a valuable skill to develope as it can give you an advantage in certain scenarios.

    2. Gene Demby. How Code-Switching Explains The World.

      I read "How Code-Switching Explains The World" from NPR. The article, in their own words, aims to "exploring are the different spaces we each inhabit and the tensions of trying to navigate between them. In one sense, code-switching is about dialogue that spans cultures." The article gives a few different examples through videos from people like Obama and Beyonce. When people code switch, they are still themselves - they are switching to a voice that suits them best in that scenario. Code-switching is one of the ways "we interact with one another and try to feel each other out."

    1. The way we present ourselves to others around us (our behavior, social role, etc.) is called our public persona [f20]. We also may change how we behave and speak depending on the situation or who we are around, which is called code-switching [f21].

      The concept of code-switching is not just limited to personal interactions but is also prevalent in professional environments. It is similar to how companies rebrand themselves in different markets, showcasing the versatility and strategic thinking individuals employ in various aspects of life.

    1. In the 1980s and 1990s, Bulletin board system (BBS) [e6] provided more communal ways of communicating and sharing messages. In these systems, someone would start a “thread” by posting an initial message. Others could reply to the previous set of messages in the thread.

      I've never seen or heard about this system. This is similar to Reddit nowadays. It allows people to communicate with each other, and provides a platform for people to share useful information. Some disadvantages in this system is that the style of this system makes it hard to look through comments, because it looks like original code. Further, I'm wondering how it manages information. Does misinformation exist in this system?

    1. Author Response

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

      Public Reviews:

      Reviewer #1 (Public Review):

      This study examined a universal fractal primate brain shape. However, the paper does not seem well structured and is not well written. It is not clear what the purpose of the paper is. And there is a lack of explanation for why the proposed analysis is necessary. As a result, it is challenging to clearly understand what novelty in the paper is and what the main findings are.

      We have now restructured the paper, including a summary of the main purpose and findings as follows:

      “Compared to previous literature, we can summarise our main contribution and advance as follows:

      (i) We are showing for the first time that representative primate species follow the exact same fractal scaling – as opposed to previous work showing that they have a similar fractal dimension [Hofman1985, Hofman1991], i.e. slope, but not necessarily the same offset, as previous methods had no consistent way of comparing offsets.

      (ii) Previous work could also not show direct agreement in morphometrics between the coarse-grained brains of primate species and other non-primate mammalian species.

      (iii) Demonstrating in proof-of-principle that multiscale morphometrics, in practice, can have much larger effect sizes for classification applications. This moves beyond our previous work where we only showed the scaling law across [Mota2015] and within species [Wang2016], but all on one (native) scale with comparable effect sizes for classification applications [Wang2021].

      In simple terms: we know that objects can have the same fractal dimension, but differ greatly in a range of other shape properties. However, we demonstrate here, that representative primate brains and mammalian brain indeed share a range of other key shape properties, on top of agreeing in fractal dimension. This suggests a universal blueprint for mammalian brain shape and a common set of mechanisms governing cortical folding. As a practical additional outcome of our study, we could show that our novel method of deriving multiscale metrics of brain shape can differentiate subtle shape changes much better than the metrics we have been using so far at a single native scale.”

      We plan to use the second paragraph as a plain-language summary of our work.

      Additionally, several terms are introduced without adequate explanation and contextualization, further complicating comprehension.

      We have now made sure that potential jargon is introduced with context and explanation. For example in Introduction: “This scaling law, relating powers of cortical thickness and surface area metrics, […]”

      Does the second section, "2. Coarse-graining procedure", serve as an introduction or a method?

      We have now renamed this section to “Coarse-graining Method” to indicate that this is a section about methods. However, to describe the methods adequately, we also expanded this section with introductory texts around the history and motivation of the method to provide context and explanations, as the reviewer rightly requested.

      Moreover, the rationale behind the use of the coarse-graining procedure is not adequately elucidated. Overall, it is strongly recommended that the paper undergoes significant improvements in terms of its structure, explanatory depth, and overall clarity to enhance its comprehensibility.

      To specifically explain the rationale behind the coarse-graining method, we added several clarifications, including the following paragraph:

      “As a starting point for such a coarse-graining procedure, we suggest to turn to a well-established method that measures fractal dimension of objects: the so-called box-counting algorithm [Kochunov2007, Madan2019]. Briefly, this algorithm fills the object of interest (say the cortex in our case) with boxes, or voxels of increasingly larger sizes and counts the number of boxes in the object as a function of box size. As the box size increases, the number of boxes decreases; and in a log-log plot, the slope of this relationship indicates the fractal dimension of the object. In our case, this method would not only provide us with the fractal dimension of the cortex, but, with increasing box size, the filled cortex would also contain less and less detail of the folded shape of the cortex. Intuitively, with increasing box size, the smaller details, below the resolution of a single box, would disappear first, and increasingly larger details will follow -- precisely what we require from a coarse-graining method. We therefore propose to expand the traditional box-counting method beyond its use to measure fractal dimension, but to also analyse the reconstructed cortices as different realisations of the original cortex at the specified spatial scale.”

      Reviewer #2 (Public Review):

      In this manuscript, Wang and colleagues analyze the shapes of cerebral cortices from several primate species, including subgroups of young and old humans, to characterize commonalities in patterns of gyrification, cortical thickness, and cortical surface area. The work builds on the scaling law introduced previously by co-author Mota, and Herculano-Houzel. The authors state that the observed scaling law shares properties with fractals, where shape properties are similar across several spatial scales. One way the authors assess this is to perform a "cortical melting" operation that they have devised on surface models obtained from several primate species. The authors also explore differences in shape properties between the brains of young (~20 year old) and old (~80) humans. My main criticism of this manuscript is that the findings are presented in too abstract a manner for the scientific contribution to be recognized.

      We recognise that our work is at the intersection of complex mathematical concepts and a perplexing biological phenomenon. Therefore, our paper has to strike a balance between scientifically accurate and succinct descriptions whilst giving sufficient space to provide context and explanations.

      Throughout, we have now added text to provide more context, but also repeat key statements in plain-english terms.

      For example, we added the following text to highlight our key contributions.

      “In simple terms: we know that objects can have the same fractal dimension, but differ greatly in a range of other shape properties. However, we demonstrate here, that representative primate brains and mammalian brain indeed share a range of other key shape properties, on top of agreeing in fractal dimension. This suggests a universal blueprint for mammalian brain shape and a common set of mechanisms governing cortical folding. As a practical additional outcome of our study, we could show that our novel method of deriving multiscale metrics of brain shape can differentiate subtle shape changes much better than the metrics we have been using so far at a single native scale.”

      (1) The series of operations to coarse-grain the cortex illustrated in Figure 1, constitute a novel procedure, but it is not strongly motivated, and it produces image segmentations that do not resemble real brains.

      To specifically explain the rationale behind the coarse-graining method, we added several clarifications, including the following paragraph:

      “As a starting point for such a coarse-graining procedure, we suggest to turn to a well-established method that measures fractal dimension of objects: the so-called box-counting algorithm [Kochunov2007, Madan2019]. Briefly, this algorithm fills the object of interest (say the cortex in our case) with boxes, or voxels of increasingly larger sizes and counts the number of boxes in the object as a function of box size. As the box size increases, the number of boxes decreases; and in a log-log plot, the slope of this relationship indicates the fractal dimension of the object. In our case, this method would not only provide us with the fractal dimension of the cortex, but, with increasing box size, the filled cortex would also contain less and less detail of the folded shape of the cortex. Intuitively, with increasing box size, the smaller details, below the resolution of a single box, would disappear first, and increasingly larger details will follow -- precisely what we require from a coarse-graining method. We therefore propose to expand the traditional box-counting method beyond its use to measure fractal dimension, but to also analyse the reconstructed cortices as different realisations of the original cortex at the specified spatial scale.”

      We also note in several places in the text that the coarse-grained brains are not to be understood as exact reconstructions of actual brains, but serve the purpose of a model:

      “[…] nor are the coarse-grained versions of human brains supposed to exactly resemble the location/pattern/features of gyri and sulci of other primates. The similarity we highlighted here are on the level of summary metrics, and our goal was to highlight the universality in such metrics to point towards highly conserved quantities and mechanisms.”

      “Note, of course, that the coarse-grained brain surfaces are an output of our algorithm alone and not to be directly/naively likened to actual brain surfaces, e.g. in terms of the location or shape of the folds. Our comparisons here between coarse-grained brains and actual brains is purely on the level of morphometrics across the whole cortex.”

      The process to assign voxels in downsampled images to cortex and white matter is biased towards the former, as only 4 corners of a given voxel are needed to intersect the original pial surface, but all 8 corners are needed to be assigned a white matter voxel (section S2). This causes the cortical segmentation, such as the bottom row of Figure 1B, to increase in thickness with successive melting steps, to unrealistic values. For the rightmost figure panel, the cortex consists of several 4.9-sided voxels and thus a >2 cm thick cortex. A structure with these morphological properties is not consistent with the anatomical organization of a typical mammalian neocortex.

      Specifically on the point on increasing cortical thickness with increased level of coarse-graining, we have now added the following paragraph:

      “The observation that with increasing voxel sizes, the coarse-grained cortices tend to be smoother and thicker is particularly interesting: the scaling law in Eq. 1 can be understood as thicker cortices (T) form larger folds (or are smoother i.e. less surface area At) when brain size is kept constant (Ae). This way of understanding has also been vividly illustrated by using the analogy of forming paper balls with papers of varying thickness in [Mota2015]: to achieve the same size of a paper ball (Ae), the one that uses thicker paper (T) will show larger folds (or is smoother i.e. less surface area At) than the one using thinner paper. The scaling law can therefore be understood as a physically and biologically plausible statement, and here, we are encouraged that our algorithm yields results in line with the scaling law.”

      (2) For the comparison between 20-year-old and 80-year-old brains, a well-documented difference is that the older age group possesses more cerebral spinal fluid due to tissue atrophy, and the distances between the walls of gyri becomes greater. This difference is born out in the left column of Figure 4c. It seems this additional spacing between gyri in 80-year-olds requires more extensive down-sampling (larger scale values in Figure 4a) to achieve a similar shape parameter K as for the 20-year-olds. A case could be made that the familiar way of describing brain tissue - cortical volume, white matter volume, thickness, etc. - is a more direct and intuitive way to describe differences between young and old adult brains than the obscure shape metric described in this manuscript. At a minimum, a demonstration of an advantage of the Figure 4a and 4b analyses over current methods for interpreting age-related differences would be valuable.

      We have demonstrated the utility of our new shape metrics in a separate paper [Wang2021]. However, we agree with the reviewer that, in this specific instance, it is much easier to understand the key message without considering the less traditional metrics. We have therefore completely revised this part of the Results section to highlight the advantage of multiscale morphometrics, and used the traditional metric of surface area to illustrate the point. The reasoning in surface area is much easier to follow, both visually and conceptually, exactly as the reviewer described.

      (3) In Discussion lines 199-203, it is stated that self-similarity, operating on all length scales, should be used as a test for existing and future models of gyrification mechanisms. First, the authors do not show, (and it would be surprising if it were true) that self-similarity is observed for length scales smaller than the acquired MRI data for any of the datasets analyzed. The analysis is restricted to coarse (but not fine)-graining.

      To clarify this point, we have added a supplementary section and the following sentence: “Note this method has also no direct dependency on the original MR image resolution, as the inputs are smooth grey and white matter surface meshes reconstructed from the images using strong (bio-)physical assumptions and therefore containing more fine-grained spatial information than the raw images (also see Suppl. Text 3).”

      We are indeed sampling at resolutions down to 0.2mm, which is below MR image resolution. The reviewer is, however, correct that we are only coarse-graining, not “fine-graining”. Coarse-graining, here, relates to more coarse than the smooth surface meshes though, not the MR image.

      Therefore, self-similarity on all length scales would seem to be too strong a constraint. Second, it is hard to imagine how this test could be used in practice. Specific examples of how gyrification mechanisms support or fail to support the generation of self-similarity across any length scale, would strengthen the authors' argument.

      We agree that spatial scales much below 0.2mm resolution may not be of interest, as these scales are only measuring the fractal properties, or “bumpiness”, of the surface meshes at the vertex level. We have therefore revised our statement in Discussion and clarified it with an example: “Finally, this dual universality is also a more stringent test for existing and future models of cortical gyrification mechanisms at relevant scales, and one that moreover is applicable to individual cortices. For example, any models that explicitly simulate a cortical surface could be directly coarse-grained with our method and compared to actual human and primate data provided here.”

      Some additional, specific comments are as follows:

      (4) The definition of the term A_e as the "exposed surface" was difficult to follow at first. It might be helpful to state that this parameter is operationally defined as the convex hull surface area.

      We agree and introduced this term now at first use: “The exposed surface area can be thought of as the surface area of a piece of cling film wrapped around the brain. Mathematically, for the remaining paper it is the convex hull of the brain surface.”

      Also, for the pial surface, A_t, there are several who advocate instead for the analysis of a cortical mid-thickness surface area, as the pial surface area is subject to bias depending on the gyrification index and the shape of the gyri. It would be helpful to understand if the same results are obtained from mid-thickness surfaces.

      This point is indeed being investigated independently of this study. Our provisional understanding is that in healthy human brains, at native scale, using the mid (or the white matter) surface introduced a systematic offset shift in the scaling law, but does not affect the scaling slope of 1.25. However, this requires a more in-depth investigation in a range of other conditions, and in the context of the coarse-grained shapes, which is on-going. Nevertheless, the scaling law, at first introduction already, has been using the pial surface area [Mota2015] and all subsequent follow-up studies followed this convention. To make our paper here accessible and directly comparable, we therefore used the same metric. Future work will investigate the utility of other metrics.

      (5) In Figure 2c, the surfaces get smaller as the coarse-graining increases, making it impossible to visually assess the effects of coarse-graining on the shapes. Why aren't all cortical models shown at the same scale?

      The purpose of rescaling the surfaces is to match the scaling plot (Fig 2A) directly, which are showing shrinking surface areas Ae and At with increasing coarse-graining. Here, we are effectively keeping the size of the box constant and resizing the cortical surface instead, which is mathematically equivalent to changing the box size and keeping the cortical surface constant.

      An alternative interpretation of the “shrinking” is, therefore, that with increasingly smaller cortical surfaces, the folding details disappear, as we require from our coarse-graining method. This is also visually apparent, as the reviewer points out. We have added this to the explanation in the text.

      If we, however, changed the box size instead, the scaling law plot would be meaningless: for example, Ae would barely change with coarse-graining. We would therefore have needed to introduce more complexity in our analysis in terms of how we can measure the scaling law. Thus, we opted to present the simpler method and interpretation here.

      Nevertheless, we agree that a direct comparison would be beneficial and have thus added the videos for each species in supplementary under this link: https://bit.ly/3CDoqZQ Upon completed peer-review, we hope to integrate these directly into eLife’s interactive displays for this figure.

      (6) Text in Section 3.2 emphasizes that K is invariant with scale (horizontal lines in Figure 3), and asserts this is important for the formation of all cortices. However, I might be mistaken, but it appears that K varies with scale in Figure 4a, and the text indicates that differences in the S dependence are of importance for distinguishing young vs. old brains. Is this an inconsistency?

      We agree that it may be confusing to emphasise a “constant K” in the first set of results across species, and then later highlight a changing K in the human ageing results. To clarify, in the first set of results, we find a constant K relative to a changing S: the range in K across melted primate brains is less than 0.1, whereas in S it is over 1.2. In other words, S changes are an order of magnitude higher than K changes. Hence, we described K as “constant” relative to S.

      Nevertheless, K shows subtle changes within individuals, which is what we were describing in the human ageing results. These changes are within the range of K values described in the across species results.

      However, in the interest of clarity, we followed the reviewer’s suggestion of simplifying the last set of results on human ageing and therefore the variable K in human ageing now only appears in Supplementary. We have now added clarifications to the supplementary on this point.

      Reviewer #3 (Public Review):

      Summary:

      Through a detailed methodology, the authors demonstrated that within 11 different primates, the shape of the brain matched a fractal of dimension 2.5. They enhanced the universality of this result by showing the concordance of their results with a previous study investigating 70 mammalian brains, and the discordance of their results with other folded objects that are not brains. They incidentally illustrated potential applications of this fractal property of the brain by observing a scale-dependent effect of aging on the human brain.

      Strengths:

      • New hierarchical way of expressing cortical shapes at different scales derived from the previous report through the implementation of a coarse-graining procedure.

      Positioning of results in comparison to previous works reinforcing the validity of the observation.

      • Illustration of scale-dependence of effects of brain aging in the human.

      Weaknesses:

      • The impact of the contribution should be clarified compared to previous studies (implementation of new coarse graining procedure, dimensionality of primate brain vs previous studies, and brain aging observations).

      We have now made these changes, particularly by adding two paragraphs to the start of Discussion. One summarising the main contributions above previous work, and one paraphrasing the former in plain English for accessibility.

      • The rather small sample sizes, counterbalanced by the strength of the effect demonstrated.

      We have now increased the sample size of the human ageing analysis substantially to over 100 subjects and observe the same trends, but with an even stronger effect. We therefore believe that this revision serves as an additional internal validation of our data and methods.

      • The use of either averaged or individual brains for the different sub-studies could be made clearer.

      We have now added this to our Suppl methods: with the exception of the Marmoset, all brain surface data were derived from healthy individual brains.

      • The model discussed hypothetically in the discussion is not very clear, and may not be state-of-the-art (axonal tension driving cortical folding? cf. https://doi.org/10.1115/1.4001683).

      We have now added this citation to our Discussion and given it context:

      “Indeed, our previously proposed model [Mota2015] for cortical gyrification is very simple, assuming only a self-avoiding cortex of finite thickness experiencing pressures (e.g. exerted by white matter pulling, or by CSF pressure). The offset K, or 'tension term', precisely relates to these pressures, leading us to speculate that subtle changes in K correlate with changes in white matter property [Wang2016, Wang2021]. In the same vein of speculation, the scale-dependence of K shown in this work might therefore be related to different types of white matter that span different length scales, such as superficial vs. deep white matter, or U-fibres vs. major tracts. However, there are also challenges to the axonal tension hypothesis [Xu2010]. Indeed, white matter tension differentials in the developed brain may not explain location of folds, but instead white matter tension may contribute to a whole-brain scale 'pressure' during development that drives the folding process overall.”

      Reviewer #3 (Recommendations For The Authors):

      Many thanks to the authors for this elegant article. I will only report here on the cosmetics of the article.

      We thank the reviewer for their kind words and attention to detail and have made all the suggested changes and revised the paper generally for readability, grammar and spelling.

      p2: last line of abstract: 'for a range of conditions in the future'.

      p3 l.37: I would not self-describe this method as elegant as this is a subjective property .

      p3 l.38: 'that will render' -> I wouldn't use the future here.

      p.4 l.59: double spacing before ref [9]?

      p.6 l.99: 'approximate a fractal' -> why is 'a' italicized?

      p.7 fig.2: I would expect the colours to be detailed in the legend. Are there two data points per species because both hemispheres are treated separately?

      p.9 l.134-135: 'similar to and in terms of the universal law 'as valid as' -> please add commas for reading comfort: 'similar to, and, in terms of the universal law, 'as valid as'.

      p.9 l. 141: For all the cortices we analysed.

      p.9 Fig 3: I find the colours a bit confusing in Figs B and C. I find Fig C a bit confusing: what are all the lines representative of, and more specifically, the two lower lines with a different trajectory?

      p.10 l.155: '1̃500' -> '~1500'.

      p.13 l. 209: either 'speculate that' of 'wonder if'.

      p.14 l.232: 'neuron numbers' -> 'number of neurons'.

      p.26 S2 second paragraph: 'gryi' -> 'gyri'.

      p.30 l.3: please refrain from starting a sentence with I.e..

      p.30 last line before S3.2: 'The algorithmic implementation in MATLAB can be found on Zenodo: TBA' - I guess this is linked to you disclosing the code upon acceptance, but please complete before final submission.

      p.34 middle/bottom of page: 'The scheme described in Sec. S3.1' -> double spacing before S3.1?

      p.35 l.1: 'We simply replace' -> 'we simply replace' (no capital).

      p.36 Fig S5.1: explicit the same colouring of the points and boxes in legend

      p.38 Fig. S6.1: briefly describe the use of colours in the legend.

      p.39 Fig. S7.1: detail colours in the legend.

      p.41 Fig. S7.3: detail colours in the legend.

    1. Author Response

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

      Public Reviews:

      Reviewer #1 (Public Review):

      The author studies a family of models for heritable epigenetic information, with a focus on enumerating and classifying different possible architectures. The key aspects of the paper are:

      • Enumerate all 'heritable' architectures for up-to 4 constituents.

      • A study of whether permanent ("genetic") or transient ("epigenetic") perturbations lead to heritable changes

      • Enumerated the connectivity of the "sequence space" formed by these heritable architectures

      • Incorporating stochasticity, the authors explore stability to noise (transient perturbations)

      • A connection is made with experimental results on C elegans.

      The study is timely, as there is a renewed interest in the last decade in non-genetic, heritable heterogeneity (e.g., from single-cell transcriptomics). Consequently, there is a need for a theoretical understanding of the constraints on such systems. There are some excellent aspects of this study: for instance, the attention paid to how one architecture "mutates" into another. Unfortunately, the manuscript as a whole does not succeed in formalising nor addressing any particular open questions in the field. Aside from issues in presentation and modelling choices (detailed below), it would benefit greatly from a more systematic approach rather than the vignettes presented.

      Despite being foundational, this work was systematic in that (1) for the simple architectures modeled using ordinary differential equations (ODEs) with continuity assumptions, parameters that support steady states were systematically determined for each architecture and then every architecture was explored using genetic changes exhaustively, although epigenetic perturbations were not examined exhaustively because of their innumerable variety; and (2) for the more realistic modeling of architectures as Entity-Sensor-Property systems, the behavior of systems with respect to architecture as well as parameter space that lead to particular behaviors (persistence, heritable epigenetic change, etc.) was systematically explored. A more extensive exploration of parameter space that also includes the many ways that the interaction between any two entities/nodes could be specified using an equation is a potentially ever-expanding challenge that is beyond the scope of any single paper.

      Specific aspects that remain to be addressed include the application of multiple notions of heritability to real networks of arbitrary size, considering different types of equations for change of each entity/node, and classifying different behavioral regimes for different sets of parameters.

      The key contribution of the paper is an articulation of the crucial questions to ask of any regulatory architecture in living systems rather than the addressing of any question that a field has recognized as ‘open’. Specifically, through the exhaustive listing of small regulatory architectures that can be heritable and the systematic analysis of arbitrary Entity-Sensor-Property systems that more realistically capture regulatory architectures in living systems, this work points the way to constrain inferences after experiments on real living systems. Currently, most experimental biologists engaged in reductionist approaches and some systems biologists examining the function or prevalence of network motifs do not explicitly constrain their models for heritability or persistence. It is hoped that this paper will raise awareness in both communities and lead to more constrained models that minimize biases introduced by incomplete knowledge of the network, which is always the case when analyzing living systems.

      Terminology

      The author introduces a terminology for networks of interacting species in terms of "entities" and "sensors" -- the former being nodes of a graph, and the latter being those nodes that receive inputs from other nodes. In the language of directed graphs, "entities" would seem to correspond to vertices, and "sensors" those vertices with positive indegree and outdegree. Unfortunately, the added benefit of redefining accepted terminology from the study of graphs and networks is not clear.

      The Entities-Sensors-Property (ESP) framework is based on underlying biology and not graph theory, making an ESP system not entirely equivalent to a network or graph, which is much less constrained. The terms ‘entity’, ‘sensor’, and ‘property’ were defined and justified in a previous paper (Jose, J R. Soc. Interface, 2020). While nodes of a network can be parsed arbitrarily and the relationship between them can also be arbitrary, entities and sensors are molecules or collections of molecules that are constrained such that the sensors respond to changes in particular properties of other entities and/or sensors. When considered as digraphs, sensors can be seen as vertices with positive indegree and outdegree. The ESP framework can be applied across any scale of organization in living systems and this specific way of parsing interactions also discretizes all changes in the values of any property of any entity. In short, ESP systems are networks, but not all networks are ESP systems. Therefore, the results of network theory that remain applicable for ESP systems need further investigation.

      The key utility of the ESP framework is that it is aligned with the development of mechanistic models for the functions of living systems while being consistent with heredity. In contrast, widely analyzed networks like protein-interaction networks, signaling networks, gene regulatory networks, etc., are not always constrained using these principles.

      Model

      The model seems to suddenly change from Figure 4 onwards. While the results presented here have at least some attempt at classification or statistical rigour (i.e. Fig 4 D), there are suddenly three values associated with each entity ("property step, active fraction, and number"). Furthermore, the system suddenly appears to be stochastic. The reader is left unsure what has happened, especially after having made the effort to deduce the model as it was in Figs 1 through 3. No respite is to be found in the SI, either, where this new stochastic model should have been described in sufficient detail to allow one to reproduce the simulation.

      The Supplementary Information section titled ‘Simulation of simple ESP systems’ provides the requested detailed information and revisions to the writing provide the biologically grounded justification for parsing interacting regulators as ESP systems.

      Perturbations

      Inspired especially by experimental manipulations such as RNAi or mutagenesis, the author studies whether such perturbations can lead to a heritable change in network output. While this is naturally the case for permanent changes (such as mutagenesis), the author gives convincing examples of cases in which transient perturbations lead to heritable changes. Presumably, this is due the the underlying multistability of many networks, in which a perturbation can pop the system from one attractor to another.

      Unfortunately, there appears to be no attempt at a systematic study of outcomes, nor a classification of when a particular behaviour is to be expected. Instead, there is a long and difficult-to-read description of numerical results that appear to have been sampled at random (in terms of both the architecture and parameter regime chosen). The main result here appears to be that "genetic" (permanent) and "epigenetic" (transient) perturbations can differ from each other -- and that architectures that share a response to genetic perturbation need not behave the same under an epigenetic one. This is neither surprising (in which case even illustrative evidence would have sufficed) nor is it explored with statistical or combinatorial rigour (e.g. how easy is it to mistake one architecture for another? What fraction share a response to a particular perturbation?)

      As an additional comment, many of the results here are presented as depending on the topology of the network. However, each network is specified by many kinetic constants, and there is no attempt to consider the robustness of results to changes in parameters.

      The systematic study of all arbitrary regulatory architectures is beyond the scope of this paper and, indeed, beyond the scope of any one paper. Nevertheless 225,000 arbitrary Entity-Sensor-Property systems were systematically explored and collections of parameters that lead to different behaviors provided (e.g., 78,285 are heritable). These ESP systems more closely mimic regulation in living systems than the coupled ODE-based specification of change in a regulatory architecture.

      The example questions raised here are not only difficult to answer, but subjective and present a moving target for future studies. One, ‘how easy is it to mistake one architecture for another?’. Mistaking one architecture for another clearly depends on the number of different types of experiments one can perform on an architecture and the resolution with which changes in entities can be measured to find distinguishing features. Two, ‘What fraction share a response to a particular perturbation?’. ‘Sharing a response’ also depends on the resolution of the measurement after perturbation.

      DNA analogy

      At two points, the author makes a comparison between genetic information (i.e. DNA) and epigenetic information as determined by these heritable regulatory architectures. The two claims the author makes are that (i) heritable architectures are capable of transmitting "more heritable information" than genetic sequences, and (ii) that, unlike DNA, the connectivity (in the sense of mutations) between heritable architectures is sparse and uneven (i.e. some architectures are better connected than others).

      In both cases, the claim is somewhat tenuous -- in essence, it seems an unfair comparison to consider the basic epigenetic unit to be an "entity" (e.g., an entire transcription factor gene product, or an organelle), while the basic genetic unit is taken to be a single base-pair. The situation is somewhat different if the relevant comparison was the typical size of a gene (e.g., 1 kb).

      Considering every base being the unit of stored information in the DNA sequence results in the maximal possible storage capacity of a genome of given length. Any other equivalence between entity and units within the genome (e.g., 1 kb gene) will only reduce the information stored in the genome.

      Nevertheless, the claim was modified to say that the information content of an ESP system can [italics added] be more extensive than the information content of the genome. This accounts for the possibility of an organism that has an inordinately large genome such that maximal information that can be stored in a particular genome sequence exceeds that stored in a particular configuration of all the contents in a cell.

      I thank the reviewer for providing further explanation of this misunderstanding in the second round of review, which helps draw future readers to the sections in the paper that discusses this important point (also see response to Recommendations for the authors).

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      I thank the author for their efforts in replying to the comments. I have updated my review accordingly; in particular, I have:

      (1) Removed my complaint that Heritability is nowhere defined

      (2) Removed issues with the presentation of the ODE model in the supplementary information.

      I thank the reviewer for raising these issues and acknowledging the improvements made.

      However, given that the manuscript is broadly unchanged from the initial one, many of my prior comments remain justified. Some key points:

      (1) The manuscript continues to be difficult to read, for the same reasons as I mentioned when reviewing the paper previously.

      (2) The utility of the "ESP" formalism is still unclear.

      • As the author notes, continuous ODEs are of course an idealisation of a system with discrete copy number.

      • However, discussing this is standard fare in any textbook dealing with chemical dynamics and stochastic processes -- see, for instance, the standard textbook by van Kampen.

      • This seems little reason to reject ODEs and implement a poorly defined formalism/simulation scheme.

      (3) The author claims that many questions raised are "beyond the scope of this study". Indeed, answering all of these questions are beyond the scope of any one study. However, as I initially wrote, the paper would be much stronger if it focused on a particular problem rather than the many vignettes depicted.

      The broad scope of this foundational paper necessitates addressing many issues, which may make it a difficult read for some readers. I hope that future work where each paper focuses on one of the aspects raised here will enable the extensive treatment of limited scope as suggested by the reviewer.

      The utility of ODEs is much appreciated and was indeed a computationally efficient way of exploring the vast space of regulatory architectures. As stated in the response to the public reviews, the Entity-Sensors-Property framework provides a biologically grounded way of parsing interacting regulators. This approach is aligned with the development of mechanistic models for the functions of living systems while being consistent with heredity. In contrast, widely analyzed networks like protein-interaction networks, signaling networks, gene regulatory networks, etc., are not always constrained using these principles.

      On a final note, on the subject of the comparison with DNA:

      Perhaps I have misunderstood something. I simply meant that comparing the "maximal information" with 4 HRAs (12.45 bits) is certainly more than the "maximal information" with 4 basepairs (8 bits), but definitely less than the "maximal information" for four 1-kb genes (4^(4000) combinations, so 8000 bits...)

      Perhaps the author means that the growth in information of HRAs is faster than exponential. If so, that should be shown and then remarked on.

      For this reason, I maintain my comment that the comparison is tenuous.

      This issue was addressed once in the results section and again in the discussion section.

      The results section states that “The combinatorial growth in the numbers of HRAs with the number of interactors can thus provide vastly more capacity for storing information in larger HRAs compared to that afforded by the proportional growth in longer genomes.”

      The discussion section states that “Despite imposing heritability, regulated non-isomorphic directed graphs soon become much more numerous than unregulated non-isomorphic directed graphs as the number of interactors increase (125 vs. 5604 for 4 interactors, Table 1). With just 10 interactors, there are >3x1020 unregulated non-isomorphic directed graphs [60] and HRAs are expected to be more numerous. This tremendous variety highlights the vast amount of information that a complex regulatory architecture can represent and the large number of changes that are possible despite sparsity of the change matrix (Fig. 3).”

      Thus, indeed as the reviewer surmises, the combinatorial explosion in information of HRAs with increases in interacting entities is faster than the proportional growth in information of genome sequence with increases in length.

      In summary, I thank the reviewers and editors for their help in improving the paper and would like to make the current manuscript the Version of Record.


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

      Public Reviews:

      Reviewer #1 (Public Review):

      The author studies a family of models for heritable epigenetic information, with a focus on enumerating and classifying different possible architectures. The key aspects of the paper are:

      • Enumerate all 'heritable' architectures for up to 4 constituents.

      • A study of whether permanent ("genetic") or transient ("epigenetic") perturbations lead to heritable changes.

      • Enumerated the connectivity of the "sequence space" formed by these heritable architectures.

      -Incorporating stochasticity, the authors explore stability to noise (transient perturbations). - A connection is made with experimental results on C elegans.

      The study is timely, as there has been a renewed interest in the last decade in nongenetic, heritable heterogeneity (e.g., from single-cell transcriptomics). Consequently, there is a need for a theoretical understanding of the constraints on such systems. There are some excellent aspects of this study: for instance:

      • The attention paid to how one architecture "mutates" into another, establishing the analogue of a "sequence space" for network motifs (Fig 3).

      • The distinction is drawn between permanent ("genetic") and transient ("epigenetic") perturbations that can lead to heritable changes.

      • The interplay between development, generational timescales, and physiological time (as in Fig. 5).

      I thank the reviewer for highlighting these aspects of the work.

      The manuscript would be very interesting if it focused on explaining and expanding these results. Unfortunately, as a whole, it does not succeed in formalising nor addressing any particular open questions in the field. Aside from issues in presentation and modelling choices (detailed below), it would benefit greatly from a more systematic approach rather than the vignettes presented.

      This first paper is foundational and therefore cannot be expected to solve all aspects of the problem of heredity. The work was nevertheless systematic in that (1) for the simple architectures modeled using ordinary differential equations (ODEs) with continuity assumptions, parameters that support steady states were systematically determined for each architecture and then every architecture was explored using genetic changes exhaustively, although epigenetic perturbations were not examined exhaustively because of their wide variety; and (2) for the more realistic modeling of architectures as Entity-Sensor-Property systems, the behavior of systems with respect to architecture as well as parameter space that lead to particular behaviors (persistence, heritable epigenetic change, etc.) was systematically explored. A more extensive exploration of parameter space that also includes the many ways that the interaction between any two entities/nodes could be specified using an equation is a potentially ever-expanding challenge that is beyond the scope of any single paper (see response to additional comments below).

      Specific aspects that remain to be addressed include the application of multiple notions of heritability to real networks of arbitrary size, considering different types of equations for change of each entity/node, and classifying different behavioral regimes for different sets of parameters. As is evident from this list of combinatorial possibilities, the space to be explored is vast and beyond the scope of this foundational paper.

      The key contribution of the paper is an articulation of the crucial questions to ask of any regulatory architecture in living systems rather than the addressing of any question that a field has recognized as ‘open’. Specifically, through the exhaustive listing for small regulatory architectures that can be heritable and the systematic analysis of arbitrary Entity-Sensor-Property systems that more realistically capture regulatory architectures in living systems, this work points the way to constrain inferences after experiments on real living systems. Currently, most experimental biologists engaged in reductionist approaches and some systems biologists examining the function or prevalence of network motifs do not explicitly constrain their models for heritability or persistence. It is hoped that this paper will raise awareness in both communities and lead to more constrained models that minimize biases introduced by incomplete knowledge of the network, which is always the case when analyzing living systems.

      Terminology

      The author introduces a terminology for networks of interacting species in terms of "entities" and "sensors" -- the former being nodes of a graph, and the latter being those nodes that receive inputs from other nodes. In the language of directed graphs, "entities" would seem to correspond to vertices, and "sensors" those vertices with positive indegree and outdegree. Unfortunately, the added benefit of redefining accepted terminology from the study of graphs and networks is not clear.

      The Entities-Sensors-Property (ESP) framework is based on underlying biology and not graph theory, making an ESP system not entirely equivalent to a network or graph, which is much less constrained. The terms ‘entity’, ‘sensor’, and ‘property’ were defined and justified in a previous paper (Jose, J R. Soc. Interface, 2020). While nodes of a network can be parsed arbitrarily and the relationship between them can also be arbitrary, entities and sensors are molecules or collections of molecules that are constrained such that the sensors respond to changes in particular properties of other entities and/or sensors. When considered as digraphs, sensors can be seen as vertices with positive indegree and outdegree. The ESP framework can be applied across any scale of organization in living systems and this specific way of parsing interactions also discretizes all changes in the values of any property of any entity. In short, ESP systems are networks, but not all networks are ESP systems. Therefore, the results of network theory that remain applicable for ESP systems need further investigation. This justification is now repeated in the paper.

      The key utility of the ESP framework is that it is aligned with the development of mechanistic models for the functions of living systems while being consistent with heredity. In contrast, widely analyzed networks like protein-interaction networks, signaling networks, gene regulatory networks, etc., are not always constrained using these principles. In addition, the language of digraphs where sensors can be seen as vertices with positive indegree and outdegree has been also added to aid readers who are familiar with graph theory.

      Heritability

      The primary goal of the paper is to analyse the properties of those networks that constitute "heritable regulatory architectures". The definition of heritability is not clearly stated anywhere in the paper, but it appears to be that the steady-state of the network must have a non-zero expression of every entity. As this is the heart of the paper, it would be good to have the definition of heritable laid out clearly in either the main text or the SI.

      I have now defined the term as used in this paper early, which is indeed as surmised by the reviewer simply the preservation of the architecture and non-zero levels of all entities. I have also highlighted additional notions of heredity that are possible, which will be the focus of future work. These can range from precise reproduction of the concentration and the localization of every entity to a subset of the entities being reproduced with some error while the rest keep varying from generation to generation (as illustrated in Fig. 2 of Jose, BioEssays, 2018). Importantly, it is currently unclear which of these possibilities reflects heredity in real living systems.

      Model

      As described in the supplementary, but not in the main text, the author first chooses to endow these networks with simple linear dynamics; something like $\partial_t \vec{x} = A x - T x$, where the vector $x$ is the expression level of each entity, $A$ has the structure of the adjacency matrix of the directed graph, and $T$ is a diagonal matrix with positive entries that determines the degradation or dilution rate of each entity. From a readability standpoint, it would greatly aid the reader if the long list of equations in the SI were replaced with the simple rule that takes one from a network diagram to a set of ODEs.

      I have abridged the description by eliminating the steady state expression for every HRA as suggested and simply pointed to the earlier version of the paper for those readers who might prefer the explicit derivations of these simple expressions. An overview is now provided for going from any network diagram to a set of ODEs.

      The implementation of negative regulation is manifestly unphysical if the "entities" represent the expression level of, say, gene products. For instance, in regulatory network E, the value of the variable z can go negative (for instance, if the system starts with z= and y=0, and x > 0).

      Negative values for any entity were avoided in simulations by explicitly setting all such values to zero. This constraint has been added as a note in the section describing the equations for the change of each node/entity in each regulatory network. Specifically, the levels of each entity/sensor was set to zero during any time step when the computed value for that entity/sensor was less than zero. This bounding of the function allows for any approach to zero while avoiding negative values. I apologize for the omission of this constraint from the supplemental material in the last submission. This constraint was used in all the simulations and therefore this change does not affect any of the results presented. In this way, it is ensured that the presence of negative regulation does not lead to negative values.

      Formally, the promotion or inhibition of an entity or sensor can be modeled using any function that is either increasing (for promotion) or decreasing (for inhibition). This diversity of possibilities is one of the challenges that prevents exhaustive exploration of all functions. In fact, the use of ODEs after assuming a continuous function is an idealization that facilitates understanding of general principles but is not in keeping with the discreteness of entities or step changes in their values (amount, localization, etc.) observed in living systems. Other commonly used continuous functions include Hill functions for the rate of production of y given as xn/(k + xn) for x activating y, which increases to ~1 as x increases, or given as k/(k + xn) for x inhibiting y, which decreases to ~0 as x increases. Increasing values of ‘n’ result in steeper sigmoidal curves. In reality, levels of all entities/sensors are expected to be discretized by measurement in living systems and the form of the function for any regulation needs empirical measurement in vivo (see response to comment below).

      The model seems to suddenly change from Figure 4 onwards. While the results presented here have at least some attempt at classification or statistical rigour (i.e. Fig 4 D), there are suddenly three values associated with each entity ("property step, active fraction, and number"). Furthermore, the system suddenly appears to be stochastic. The reader is left unsure of what has happened, especially after having made the effort to deduce the model as it was in Figs 1 through 3. No respite is to be found in the SI, either, where this new stochastic model should have been described in sufficient detail to allow one to reproduce the simulation.

      While ODEs are easier to simulate and understand, they are less realistic as explained above. I have now added more explanation justifying the need for the subsequent simulation of Entity-Sensor-Property systems. I have also expanded the information provided for each aspect of the model (previously outlined in Fig. 4A and detailed within the code) in a Supplementary Information section titled ‘Simulation of simple ESP systems’.

      Perturbations

      Inspired especially by experimental manipulations such as RNAi or mutagenesis, the author studies whether such perturbations can lead to a heritable change in network output. While this is naturally the case for permanent changes (such as mutagenesis), the author gives convincing examples of cases in which transient perturbations lead to heritable changes. Presumably, this is due the the underlying mutlistability of many networks, in which a perturbation can pop the system from one attractor to another.

      Unfortunately, there appears to be no attempt at a systematic study of outcomes, nor a classification of when a particular behaviour is to be expected. Instead, there is a long and difficult-to-read description of numerical results that appear to have been sampled at random (in terms of both the architecture and parameter regime chosen). The main result here appears to be that "genetic" (permanent) and "epigenetic" (transient) perturbations can differ from each other -- and that architectures that share a response to genetic perturbation need not behave the same under an epigenetic one. This is neither surprising (in which case even illustrative evidence would have sufficed) nor is it explored with statistical or combinatorial rigour (e.g. how easy is it to mistake one architecture for another? What fraction share a response to a particular perturbation?)

      The systematic study of all arbitrary regulatory architectures is beyond the scope of this paper and, as stated earlier, beyond the scope of any one paper. Nevertheless 225,000 arbitrary Entity-Sensor-Property systems were systematically explored and collections of parameters that lead to particular behaviors provided (e.g., 78,285 are heritable). These ESP systems more closely mimic regulation in living systems than the coupled ODE-based specification of change in a regulatory architecture.

      The example questions raised here are not only difficult to answer, but subjective and present a moving target for future studies. One, ‘how easy is it to mistake one architecture for another?’. Mistaking one architecture for another clearly depends on the number of different types of experiments one can perform on an architecture and the resolution with which changes in entities can be measured to find distinguishing features. Two, ‘What fraction share a response to a particular perturbation?’. ‘Sharing a response’ also depends on the resolution of the measurement of entities after perturbation.

      As an additional comment, many of the results here are presented as depending on the topology of the network. However, each network is specified by many kinetic constants, and there is no attempt to consider the robustness of results to changes in parameters.

      The interpretations presented are conservative determinations of heritability based on the topology of the architecture. In other words, architectures that can be heritable for some set of parameters. Of course, parameter sets can be found that make any regulatory architecture not heritable. As stated earlier, exploring all parameters for even one architecture is beyond the scope of a single study because of the infinitely many ways that the interaction between any two entities can be specified.

      DNA analogy

      At two points, the author makes a comparison between genetic information (i.e. DNA) and epigenetic information as determined by these heritable regulatory architectures. The two claims the author makes are that (i) heritable architectures are capable of transmitting "more heritable information" than genetic sequences, and (ii) that, unlike DNA, the connectivity (in the sense of mutations) between heritable architectures is sparse and uneven (i.e. some architectures are better connected than others).

      In both cases, the claim is somewhat tenuous -- in essence, it seems an unfair comparison to consider the basic epigenetic unit to be an "entity" (e.g., an entire transcription factor gene product, or an organelle), while the basic genetic unit is taken to be a single base-pair. The situation is somewhat different if the relevant comparison was the typical size of a gene (e.g., 1 kb).

      Considering every base being the unit of stored information in the DNA sequence results in the maximal possible storage capacity of a genome of given length. Any other equivalence between entity and units within the genome (e.g., 1 kb gene) will only reduce the information stored in the genome.

      Nevertheless, the claim has been modified to say that the information content of an ESP system can [italics added] be more extensive than the information content of the genome. This accounts for the possibility of an organism that has an inordinately large genome such that maximal information that can be stored in a particular genome sequence exceeds that stored in a particular configuration of all the contents in a cell.

      Reviewer #2 (Public Review):

      Summary:

      This manuscript uses an interesting abstraction of epigenetic inheritance systems as partially stable states in biological networks. This follows on previous review/commentary articles by the author. Most of the molecular epigenetic inheritance literature in multicellular organisms implies some kind of templating or copying mechanisms (DNA or histone methylation, small RNA amplification) and does not focus on stability from a systems biology perspective. By contrast, theoretical and experimental work on the stability of biological networks has focused on unicellular systems (bacteria), and neglects development. The larger part of the present manuscript (Figures 1-4) deals with such networks that could exist in bacteria. The author classifies and simulates networks of interacting entities, and (unsurprisingly) concludes that positive feedback is important for stability. This part is an interesting exercise but would need to be assessed by another reviewer for comprehensiveness and for originality in the systems biology literature. There is much literature on "epigenetic" memory in networks, with several stable states and I do not see here anything strikingly new.

      The key utility of the initial part of the paper is the exhaustive enumeration of all small heritable regulatory architectures. The implications for the abundance of ‘network motifs’ and more generally any part of a network proposed to perform a particular function is that all such parts need to be compatible with heredity. This principle is generally not followed in the literature, resulting in incomplete networks being interpreted as having motifs or modules with autonomous function. Therefore, while the need for positive feedback for stability is indeed obvious, it is not consistently applied by all. For example, the famous synthetic circuit ‘the repressilator’ (Elowitz and Leibler, “A synthetic oscillatory network of transcriptional regulators”, Nature, 2000), which is presented as an example of ‘rational network design’, has three transcription factors that all sequentially inhibit the production of another transcription factor in turn forming a feedback loop of inhibitory interactions. Therefore, the contributions of the factors that promote the expression of each entity is unknown and yet essential for heritability. The comprehensive listing of the heritable regulatory architectures that are simple provide the basis for true synthetic biology where the contributing factors for observed behavior of the network are explicitly considered only after constraining for heredity. Using this principle, the minimal autonomous architecture that can implement the repressilator is the HRA ‘Z’ (Fig. 1).

      An interesting part is then to discuss such networks in the framework of a multicellular organism rather than dividing unicellular organisms, and Figure 5 includes development in the picture. Finally, Figure 6 makes a model of the feedback loops in small RNA inheritance in C. elegans to explain differences in the length of inheritance of silencing in different contexts and for different genes and their sensitivity to perturbations. The proposed model for the memory length is distinct from a previously published model by Karin et al. (ref 49).

      I thank the reviewer for appreciating this aspect of the paper.

      Strengths:

      A key strength of the manuscript is to reflect on conditions for epigenetic inheritance and its variable duration from the perspective of network stability.

      I thank the reviewer for appreciating the importance of the overall topic.

      Weaknesses:

      • I found confusing the distinction between the architecture of the network and the state in which it is. Many network components (proteins and RNAs) are coded in the genome, so a node may not disappear forever.

      I have added language to clarify the many states of a network versus its architecture (also illustrated in Fig. 4 for ESP systems). Even loss of expression below a threshold can lead to permanent loss if there is not sufficient noise to induce re-expression. For example, consider the simple case of a transcription factor that binds to its own promoter, requiring 10 molecules for the activation of the promoter and thus production of more of the same transcription factor. If an epigenetic change (e.g., RNA interference) reduces the levels to fewer than 10 molecules and if the noise in the system never results in the numbers of the transcription factor increasing beyond 10, the transcription factor has been effectively lost permanently. In this way, reduction of a regulator can lead to permanent change despite the presence of the DNA. Many papers in the field of RNA silencing in C. elegans have provided strong experimental evidence to support this assertion.

      • From the Supplementary methods, the relationship between two nodes seems to be all in the form of dx/dt = Kxy . Y, which is just one way to model biological reactions. The generality of the results on network architectures that are heritable and robust/sensitive to change is unclear. Other interactions can have sigmoidal effects, for example. Is there no systems biology study that has addressed (meta)stability of networks before in a more general manner?

      Indeed, the relationship between any two entities can in principle be modeled using any function. Extensive exploration of the behavior of any regulatory architecture – even the simplest ones – require simplifications. For example, early work by Stuart Kauffman explored Boolean networks (see ref. 10 in the paper for history and extensive explanations). However, allowing all possible ways of specifying the interactions between components of a network makes analysis both a computational and conceptual challenge.

      • Why is auto-regulation neglected? As this is a clear cause of metastable states that can be inherited, I was surprised not to find this among the networks.

      Auto-regulation in the sense of some molecule/entity ultimately leading to the production of more of itself is present in every heritable regulatory architecture. Specifically, all auto-regulatory loops rely on a sequence of interactions between two or more kinds of molecules. For example, a transcription factor (TF) binding to the promoter of its own gene sequence, resulting in the production of more TF protein is a positive feedback loop that relies on many interacting factors (transcription, translation, nuclear import, etc.) and can be considered as ‘auto-regulation’ as it is sometimes referred to in the literature. In this sense, every HRA (A through Z) includes ‘auto-regulation’ or more appropriately positive feedback loops. For example, in the HRA ‘A’, x ‘auto-regulates’ itself via y.

      • I did not understand the point of using the term "entity-sensor-property". Are they the same networks as above, now simulated in a computer environment step by step (thus allowing delays)?

      Please see response to the other reviewer regarding the need for the Entity-SensorProperty framework and how it is distinct from generic networks. Briefly, the ODE-based simple networks, while easy to analyze, are not realistic because of the assumptions of continuity. In contrast ESP systems are more realistic with measurement discretizing changes in property values as is expected in real living systems.

      • The final part applies the network modeling framework from above to small RNA inheritance in C. elegans. Given the positive feedback, what requires explanation is how fast the system STOPs small RNA inheritance. A previous model (Karin et al., ref. 49) builds on the fact that factors involved in inheritance are in finite quantity hence the different small RNAs "compete" for amplification and those targeting a given gene may eventually become extinct.

      The present model relies on a simple positive feedback that in principle can be modulated, and this modulation remains outside the model. A possibility is to add negative regulation by factors such as HERI-1, that are known to limit the duration of the silencing.

      The duration of silencing differs between genes. To explain this, the author introduces again outside the model the possibility of piRNAs acting on the mRNA, which may provide a difference in the stability of the system for different transcripts. At the end, I do not understand the point of modeling the positive feedback.

      The previous model (Karin et al., Cell Systems, 2023) can describe populations of genes that are undergoing RNA silencing but cannot explain the dynamics of silencing particular genes. Furthermore, this model also cannot explain cases of effectively permanent silencing of genes that have been reported (e.g., Devanapally et al., Nature Communications, 2021 and Shukla et al., Current Biology, 2021). Finally, the observations of susceptibility to, recovery from, and even resistance to trans silencing (e.g., Fig. 5a in Devanapally et al., Nature Communications, 2021) require an explanation that includes modulation of the HRDE-1-dependent positive feedback loop that maintains silencing across generations.

      The specific qualitative predictions regarding the relationship between piRNA-mediated regulation genome-wide and HRDE-1-dependent silencing of a particular gene across generations could guide the discovery of potential regulators of heritable RNA silencing. The equations (4) and (5) in the paper for the extent of modulation needed for heritable epigenetic change provide specific quantitative predictions that can be tested experimentally in the future. I have also revised the title of the section to read ‘Tuning of positive feedback loops acting across generations can explain the dynamics of heritable RNA silencing in C. elegans’ to emphasize the above points.

      • From the initial analysis of abstract networks that do not rely on templating, I expected a discussion of possible examples from non-templated systems and was a little surprised by the end of the manuscript on small RNAs.

      The heritability of any entity relies on regulatory interactions regardless of whether a templated mechanism is also used or not. For example, DNA replication relies on the interactions between numerous regulators, with only the sequence being determined by the template DNA. The field of small RNA-mediated silencing facilitates analysis of epigenetic changes at single-gene resolution (Chey and Jose, Trends in Genetics, 2022). It is therefore likely to continue to provide insights into heritable epigenetic changes and how they can be modulated. Unfortunately, there are currently no known cases of epigenetic inheritance where the role of any templated mechanism has been conclusively excluded. Future research will improve our understanding of epigenetic states and their modulation in terms of changes in positive feedback loops as proposed in this study and potentially lead to the discovery of such mechanisms that act entirely independent of any template-dependent entity.

      Recommendations for the authors:

      I thank the reviewers for their specific suggestions to improve the paper.

      Reviewer #1 (Recommendations For The Authors):

      The paper has many long paragraphs that attempt to explain results, make illustrations, and give intuition. Unfortunately, these are difficult to read. It would aid the reader greatly if these were, say, converted into cartoons (even if only in the SI), or made more accessible in some other way.

      I agree with the importance of making the material accessible to readers in multiple ways. I have now added a figure with schematics in the SI titled ‘Illustrations of key concepts’ (new Fig. S2), which collects concepts that are relevant throughout the paper and might aid some readers.

      The bulk of the supplementary is currently a collection of elementary mathematics results: to whit, pages 26 to 33 of the combined manuscript carry no more information than a quick description of the general model and the diagrams in Fig 1. Similarly, pages 34 to 39 (non-zero dilution rate), and pages 39 through 58 (response to permanent changes) each express a trivial mathematical point that is more than sufficiently made with one illustrative example.

      I agree with the reviewer and have condensed these pages as suggested. I have added a pointer to the earlier version as containing further details for the readers who might prefer the explicit listing of these equations.

      Overall, the paper appears to be a collection of numerical results obtained from different models, united by uncertain terminology that is not fully defined in this paper. The most promising aspects of the paper lie either in (a) combinatorially complete enumeration of all regulatory architectures, or (b) relating experimental manipulations in C. elegans to possible underlying regulatory architectures. Focusing on one or the other might improve the readability of the paper.

      The two sections of the paper are complementary and when presented together help with the integration of concepts rather than the siloed pursuit of theory versus experimental analysis. When this work was presented at meetings before submission, it was clear that different researchers appreciated different aspects. This divergence is also apparent in the two reviews, with each reviewer appreciating different aspects. I have repeated the definitions and justifications from the earlier paper (Jose, J R Soc Interface, 2020) to provide a more fluid transition between the two complementary sections of the paper. Knowing both sides could aid in the development of models that are not only consistent with measurable quantities (e.g., anything that can be considered an entity) but are also logically constrained (e.g., entities matched with sensors while avoiding any entities that do not have a source of production – i.e., avoiding nodes with indegree = 0).

      However, having said that many results of these types are well-known in models of regulatory networks, and it is unclear what precisely warrants the new framework that the author is proposing. Indeed, it would be good to understand in what way the framework here is novel, and how it is distinguished from prior studies of regulatory networks.

      The key novelty of the work is the consideration of heritability for any regulation. With the explicit definition of the heritability for a regulatory architecture and the acknowledgement that there can be more than one notion of heredity, this paper now sets the foundation for examining many real networks in this light. I hope that the added justifications for the current framework in the revised paper strengthen these arguments. Future literature reviews on networks in general and how they address heritability or persistence will better define the prevalence of these considerations. Currently, most experimental biologists engaged in reductionist approaches and some systems biologists examining the function or prevalence of network motifs do not explicitly constrain their models for heritability or persistence. It is hoped that this work will raise awareness in both communities and lead to more constrained models that acknowledge incomplete knowledge of the network, which is always the case when analyzing living systems.

      Reviewer #2 (Recommendations For The Authors):

      Minor points/clarity

      • page 1 line 57: "transgenerational waveforms that preserve form and function" is unclear.

      This phrase was expanded upon in a previous paper (Jose, BioEssays, 2020). I have now added more explanation in this paper for completeness. The section now reads ‘For example, the localization and activity of many kinds of molecules are recreated in successive generations during comparable stages [1-3]. These recurring patterns can change throughout development such that following the levels and/or localizations of each kind of molecule over time traces waveforms that return in phase with the similarity of form and function across generations [2].’

      • page 7 line 3-6: the sentence has an ambiguous structure.

      I have now edited this long sentence to read as follows: ‘For systematic analysis, architectures that could persist for ~50 generations without even a transient loss of any entity/sensor were considered HRAs. Each HRA was perturbed (loss-of-function or gain-of-function) after five different time intervals since the start of the simulation (i.e., phases). The response of each HRA to such perturbations were compared with that of the unperturbed HRA.’

      • page 9 lines 25-27: the sentence is convoluted: are you defining epigenetic inheritance?

      I have simplified this sentence describing prior work by others (Karin et al., Cell Systems, 2023) and moved a clause to the subsequent sentence. This section now reads: ‘Recent considerations of competition for regulatory resources in populations of genes that are being silenced suggest explanations for some observations on RNA silencing in C. elegans [49]. Specifically, based on Little’s law of queueing, with a pool of M genes silenced for an average duration of T, new silenced genes arise at a rate  that is given by M = T’. I have also provided more context by preceding this section with: ‘Although the release of shared regulators upon loss of piRNA-mediated regulation in animals lacking PRG-1 could be adequate to explain enhanced HRDE-1-dependent transgenerational silencing initiated by dsRNA in prg-1(-) animals, such a competition model alone cannot explain the observed alternatives of susceptibility, recovery and resistance (Fig. 6A).’

      • page 13 lines 51-53. This last sentence of the discussion is ambiguous/unclear.

      I have now rephrased this sentence to read: ‘This pathway for increasing complexity through interactions since before the origin of life suggests that when making synthetic life, any form of high-density information storage that interacts with heritable regulatory architectures can act as the ‘genome’ analogous to DNA.’

      • Figure 2: the letters in the nodes are hard to read; the difference between full and dotted lines in the graphs also.

      I have enlarged the nodes and widened the gap in the dotted lines to make them clearer. I have also similarly edited Fig. 1 and Fig. S3 to Fig. S9.

    1. Author Response

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

      Reviewer #1 (Recommendations For The Authors):

      (1) More explanation/description of Fig 3C and 3D would be helpful for readers, including the color code of 3D and black lines shown in both panels.

      We have added more description to the legend of Figure 3, and we have used the same color code as in Figure 2, which we now specifically note in the figure legend as well.

      (2) Differences between cranial and trunk NCC could be experimentally shown or discussed. Fig 4C shows some differences between these two populations, but in situ, results using Dlc1/Sp5/Pak3 probes in the trunk region may be informative, like Fig 5 supplement 2 for cranial NCCs.

      This is an important point. The focus of our study was on cranial neural crest cells, and the single cell sequencing data is therefore truly reflective of only cranial neural crest cells. We have not functionally tested for the roles of Dlc1/Sp5/Pak3 in trunk neural crest cells, however, based on the expression and loss-of-function phenotypes of Sp5 or Pak3 knockout mice, we predict they individually may not play a significant role. It remains plausible that Dlc1 could play an important role in the delamination of trunk neural crest cells, but we have not tested that definitively. Nonetheless, Sabbir et al 2010 showed in a gene trap mouse mutant that Dlc1 is expressed in trunk neural crest cells. Regarding the similarities and differences between cranial and trunk neural crest cells as noted by the reviewer with respect to Figure 4, it’s important to recognize the temporal differences illustrated in Figure 4. Neural crest cell delamination proceeds in a progressive wave from anterior to posterior, but also that the analysis was designed to quantify cell cycle status before and during neural crest cell delamination. We have compared cranial and trunk neural crest cells in more detail in the discussion and also speculate what might happen in the trunk based on what we know from other species.

      (3) Discussion can be added about the potential functions of Dlc1 for NCC migration and/or differentiation based on available info from KO mice.

      We have added specific details regarding the published Dlc1 knockout mouse phenotype to the discussion, particularly with respect to the craniofacial anomalies which included frontonasal prominence and pharyngeal arch hyperplasia, and defects in neural tube closure and heart development. Although the study didn’t investigate the mechanisms underpinning the Dlc1 knockout phenotype, the craniofacial morphological anomalies would be consistent with a deficit in neural crest cell delamination reducing the number of migrating neural crest cells, as we observed in our Dlc1 knockdown experiments.

      Reviewer #2 (Recommendations For The Authors):

      The authors used the (Tg(Wnt1-cre)11Rth Tg(Wnt1-GAL4)11Rth/J) line but work from the Bush lab (see Lewis et al., 2013) has demonstrated fully penetrant abnormal phenotypes that affect the midbrain neuroepithelium, increased CyclinD1 expression and overt cell proliferation as measured by BrdU incorporation. The authors should explain why they used this mouse line instead of the Wnt1-Cre2 mice (129S4-Tg(Wnt1-cre)1Sor/J) in the Jackson Laboratory (which lacks the phenotypic effects of the original Wnt1-Cre line), or a "Cre-only" control, or at a minimum explain the steps they took to ensure there were no confounding effects on their study, especially since cell proliferation was a major outcome measure.

      This is an important point, and we thank the reviewer for raising it. Yes, it has been reported that the original Wnt1Cre mice exhibit a midbrain phenotype (Ace et al. 2013). However, it has also been noted that Wnt1Cre2 can exhibit recombination in the male germline leading to ubiquitous recombination (Dinsmore et al., 2022). Therefore, to avoid any potential for bias, we used an equal number of cells derived from the Wnt1 and F10N transgenic line embryos in our scRNA-seq, and this included multiple non-Cre embryos. Our scRNA-seq analysis was therefore not dependent upon Wnt1-Cre, but also because we used whole heads not fluorescence sorted cells. However, Wnt1-Cre lineage tracing was advantageous from a computational perspective to help define cells that were premigratory and migratory in concert with Mef2c-lacZ ¬based on their expression of YFP, LacZ or both. We note these specifics more clearly in the methods.

      The Results section (line 122) states that scRNA-seq was performed on dissociated cranial tissues but the Methods section (lines 583-584) implies that whole E8.5 mouse embryos were dissociated. Which was dissociated, whole embryos or just cranial tissues? Obviously, the latter would be a better strategy to enrich for cranial neural crest, but the authors also examine the trunk neural crest. This should be clarified in the text.

      We apologize that some of the details regarding the tissue isolation were confusing and we have clarified this in the methods and the text. For the record, after isolating E8.5 embryos, we then dissected the head from those embryos, and performed scRNA-seq on dissociated cranial tissues. As the reviewer correctly noted, this approach strategically enriches for cranial neural crest cells.

      The authors do not justify why they chose a knockdown strategy, which has its limitations including its systemic injection into the amniotic cavity, its likely global and more variable effects, and its need to be conducted in culture. Why the authors did not instead use a Wnt1-Cre-mediated deletion of Dlc1, which would have been "cleaner" and more specific to the neural crest, is not clear (maybe so they could specifically target different Dcl1 isoforms?). Also, the authors use Sox10 as a marker to count neural crest cells, but Sox10 may only label a subset of neural crest cells and thus some unaffected lineages may not have been counted. The authors should mention what is known about the regulation of Dcl1 by Sox10 in the neural crest. Although the data are persuasive, a second marker for counting neural crest cells following knockdown would make the analysis more robust. Can the authors explain why they did not simply use the Mef2c-F10N-LacZ line and count LacZ-positive cells (if fluorescence signal was required for the quantification workflow, then could they have used an anti-beta Galactosidase antibody to label cells)?

      We thank the reviewer for raising these important considerations. It has previously been noted that although Wnt1-Cre is the gold standard for conditional deletion analyses in neural crest cell development, especially migration and differentiation, it is not a good tool for functional studies of the specification and delamination of neural crest cells due to the timing of Wnt1 expression and Cre activation and excision (see Barriga et al., 2015). Therefore, we chose a knockdown strategy instead, and also because it allows us to more rapidly evaluate gene function. We agree that there are limitations to the approach with respect to variability, however, this is outweighed by the ability to repeatedly perform the knockdown at multiple and more relevant temporal stages such as E7.5 (which is prior to the onset of Wnt1-Cre activity), as well as target different isoforms, and also treat large numbers of embryos for quantitative analyses. The advantage of using Sox10 as a marker for counting neural crest cells is that at the time of analysis, cranial neural crest cells are still migrating towards the frontonasal prominences and pharyngeal arches, and the overwhelming majority of these cells are Sox10 positive. Moreover, we can therefore assay every Dlc1 knockdown embryo for Sox10 expression and count the number of migrating neural crest cells. The limitation of using the Mef2c-F10N-LacZ line is that this transgenic line is maintained as a heterozygote, and thus only half the embryos in a litter could reasonably be expected to be lacZ+. But combining Sox10 and Mef2c-F10N-LacZ fluorescent immunostaining for similar analyses in the future is a great idea.

      Reviewer #3 (Recommendations For The Authors):

      The putative intermediate cells differentially express mRNAs for genes involved in cell adhesion, polarity, and protrusion relative to bona fide premigratory cells (Fig. 2E). This is persuasive evidence, but only differentially expressed genes are shown. Discussing those markers that have not yet changed, e.g. Cdh1 or Zo1 (?), would be instructive and help to clarify the order of events.

      We thank the author for this suggestion and we have provided more detail about adherens junction and tight junctions. Cdh1 is not expressed, and although Myh9 and Myh10 are expressed, we did not detect any significant changes. ZO1 is a tight junction protein encoded by the gene Tjp1, which along with other tight junctions protein encoding genes, is downregulated in intermediate NCCs as shown in the Figure 2E.

      It is unclear whether the two putative intermediate state clusters differ other than their stage of the cell cycle. Based on the trajectory analysis in Fig. 3C-D, the authors state that these two populations form simultaneously and independently but then merge into a single population. However, without further differential expression, it seems more plausible that they represent a single population that is temporarily bifurcated due to cell cycle asynchrony.

      We have addressed the cell cycle question in the discussion by noting that while it is possible the transition states represent a single population that is temporarily bifurcated due to cell cycle asynchrony, if this were true, then we should expect S phase inhibition to eliminate both transition state groups. Instead, our trajectory analyses suggest that the transition states are initially independent, and furthermore, S phase inhibition did not affect delamination of the other population of neural crest cells.

      The authors do not present an in-depth comparison of these neural crest intermediate states to previously reported cancer intermediate states. This analysis would reveal how similar the signatures are and thus how extrapolatable these and future findings in delaminating neural crest are to different types of cancer.

      We have also added more detail to the discussion to address the potential for similarities and differences in neural crest intermediate states compared to previously reported cancer intermediate states. The challenge, however, is that none of the cancer intermediate states have been characterized at a molecular level. Nonetheless, with the limited molecular markers available, we have not identified any similarities so far, but our datasets are now available for comparison with future cancer EMP datasets.

      The reduction in SOX10+ cells may be in part or wholly attributable to inhibition of proliferation AFTER delamination. Showing that there are premigratory NCCs in G2/M at ~E8.0 would bolster the argument that this population is present from the earliest stages.

      The presence of premigratory neural crest cells in G2/M is shown by the scRNA-seq data and cell cycle staining data in the neural plate border.

      Lines 248-249: The pseudo-time analysis in Fig 3C/D does indicate that the two most mature cell clusters (pharyngeal arch and frontonasal mesenchyme) may arise from common or similar migratory progenitors. However, given the decades of controversy about fate restriction of neural crest cells, the statement that "EMT intermediate NCC and their immediate lineages are not fate restricted to any specific cranial NCC derivative at this timepoint" should be toned down so as to not give the impression that they have identified common progenitors of ectomesenchyme and neuro/glial/pigment derivatives.

      We appreciate this comment, because as the reviewer noted, there has been considerable literature and debate about the fate restriction and plasticity of neural crest cells, and indeed we did not intend to imply we have identified common progenitors of ectomesenchyme and neuro/glial/pigment derivatives. That can only be truly functionally demonstrated by clonal lineage tracing analyses. Rather, we interpret our pseudo-time analyses to indicate that irrespective of cell cycle status at the time of delamination, these two populations come together with equivalent mesenchymal and migratory properties, but in the absence of fate determination in the collective of cells. This does not mean that individual cells are common progenitors of both ectomesenchyme and neuro/glial/pigment derivatives. The nuance is important, and we address this more carefully in the text.

      Lines 320-321: "...this overlap in expression was notably not observed in older embryos in areas where EMT had concluded". It is unclear whether the markers no longer overlap in older embryos (i.e. segregate to distinct populations) or are simply no longer expressed.

      The data in Figure 5 demonstrates the dynamic and overlapping expression of Dlc1, Sp5 and Pak3 in the different clusters of cells as they transition from being neuroepithelial to mesenchymal. In contrast to Sp5 and Pak3, Dlc1 is not expressed by premigratory neural crest cells but is expressed at high levels in all EMT intermediate stage neural crest cells. Later as Dlc1 continues to be expressed in migrating neural crest cells, Pak3 and Sp5 are downregulated. But the absence of overlapping expression in the dorsolateral neural plate at the conclusion of EMT coincides with their downregulation in that territory.

      In the final results section on Dlc1, the previously published mutant mouse lines are referenced as having "craniofacial malformation phenotypes". The lack of detail given on what those malformations are (assuming descriptions are available) makes the argument that they may be related to insufficient delamination less persuasive. The degree of knockdown correlates so well with the percentage reduction in migratory neural crest (Fig. 6) that one would imagine a null mutant to have a very severe phenotype.

      The inference from the reviewer is correct and indeed Dlc1 null mutant mice do have a severe phenotype. We have added more specific details regarding the craniofacial and other phenotypes of the Dlc1 mutant mice to the discussion. Of note the frontonasal prominences and the pharyngeal arches are hypoplastic in E10.5 Dlc1 mutant embryos, which would be consistent with a neural crest cell deficit. Although a deficit in neural crest cells can be caused my multiple distinct mechanisms, our Dlc1 knockdown analyses suggest that the phenotype is due to an effect on neural crest cell delamination which diminishes the number of migrating neural crest cells.

      Use the same y-axis for Fig. 4C/D

      This has been corrected.

      Fig. 6C: Please note in the panel which gene is being measured by qPCR

      This has been corrected to denoted Dlc1.

      Lines 108-117: More concise language would be appropriate here.

      As requested, we were more succinct in our language and have shortened this section.

      The SABER-FISH images are very dim. I realize the importance of not saturating the pixels, but the colors are difficult to make out.

      We thank the reviewer for pointing this out and have endeavored to make the SABER-FISH images brighter and easier to see.

    1. As Smith et al. put it, most hacklabs, makerspaces, and fablabs have policies and cultural norms via which “all code, designs, and instructions in the making and repairing of something are made freely available for people to access, adopt and modify, so long as the source is acknowledged

      En el contexto colombiano, hay un gran vacío en la formación en tecnología: se nos suele formar como usuarios de dispositivos y tecnologías, y en general se busca estandarizar esta formación. La perspectiva crítica y transgresora que supone otro tipo de acciones tecnológicas, como las mencionadas acá, está supeditada a espacios alternativos y divergentes, y se convierten en apuesta política contrahegménonica de los sistemas sociotécnico imperantes.

    1. La prévention peut se faire au niveau de la médecine du travail. Malheureusement, celle-ci demeure souvent impuissante surtout depuis la réforme apportée par la loi travail qui a porté la périodicité des visites de suivi de 2 à 5 ans. Le manager quant à lui, s’il est en mesure de détecter le moindre signe avant-coureur devra alerter le service RH. Les 35 suicides au sein de France Telecom en 2008/2009 ont conduit les pouvoirs publics au lancement d’un plan d’urgence pour la prévention du stress au travail en octobre 2009. Une prise de conscience managériale devient nécessaire. L’employeur engage d’ailleurs sa responsabilité lorsqu’un salarié est victime d’un burn-out lié à la dégradation de ses conditions de travail dans l’entreprise, ce que confirme la Cour de cassation (Cass. soc 13 mars 2013 n° 11-22082). Il est alors intéressant de rappeler que dans le cadre du contrat de travail, l’employeur est tenu à une obligation de sécurité (obligation de résultat prévue à l’article L 4121-1 du Code du travail). Il doit donc prendre les mesures nécessaires pour assurer la sécurité et protéger la santé physique et mentale des travailleurs.

      Les éléments du cadre législatif et histrorique du problématique sont réutilisés pour le renforcement du premier argument épistémique et pour l'introduction du deuxième argument: la responsabilité d'employeur de veiller à la santé mentale des travailleurs, en plus de la santé physique. C'est donc le 2ème argument épistémique.

    2. En 2015 déjà, la loi relative au dialogue social et à l’emploi, dite loi Rebsamen, en son article 27 a consacré la reconnaissance des pathologies psychiques comme maladies professionnelles au niveau de la loi en modifiant l’article L461-1 du code de la sécurité sociale, précisant que « les pathologies psychiques peuvent être reconnues comme maladies professionnelles ». Le décret du 7 juin 2016 vient quant à lui mettre en place des mesures permettant de renforcer l’expertise médicale pour la reconnaissance des pathologies psychiques et précise les modalités applicables aux dossiers concernés.

      Le cadre historique et législatif du problématique qui est posé.

    1. from marking to doing.

      Invisible code here for poets or poet wannabees: all poems are phase shifters. That makes them concrete. This poem, for example, does a little turn in the middle, like a sonnet, where it moves from observing and writing down to judging and moving on. At some point you mark the phase changes as done and you share your voice. That is pretty concrete.

      One thing that this AI work with Claude has done is to make me articulate the liminality and the phase shifts in my poetry in order to make it better. Clearer and less prideful.

    1. from marking to doing.

      Invisible code here for poets or poet wannabees: all poems are phase shifters. That makes them concrete. This poem, for example, does a little turn in the middle, like a sonnet, where it moves from observing and writing down to judging and moving on. At some point you mark the phase changes as done and you share your voice. That is pretty concrete.

      One thing that this AI work with Claude has done is to make me articulate the liminality and the phase shifts in my poetry in order to make it better. Clearer and less prideful.

    1. About A simple code sandbox for playing around with HTMX. No setup needed!

      📖✍️- 🎮| 🅈 ann0te - HTMX Playground

      from - 📖✍️- 🎮| 🅈 ann0te - HTMX Playground |  🅈

    1. The inclusion of AI technology in the classroom can alleviate some aspects of a teacher’s workload and can also benefit student learning and achievement. Some AI that is available as assistive technology can be chosen and “tailored to fit individual student rates and styles of learning . . . but not replace the work of human teachers” (Johnson, 2020, para. 17), because teachers are better equipped to determine which teaching methods will meet the needs of each student. Teachers can work with machine learning technology to solve problems and challenges, and when used correctly, it can help their students become better learners and members of society (Atlantic Re:think, 2018; HubSpot, 2017).

      AI is now into classroom in multiple ways, the most recent one is ChatGPT. Many professors are not ready to let ChatGPT to be use in assignment yet, which I totally understand. I also agree to this article that AI cannot replace real teachers, because many teachers "teach students according to their aptitude" AI is pre-code which means it teach in same ways

    1. The intentional invention of any information or citation on an assignment or document.  This includes using generative Artificial Intelligence (AI) or other electronic resources in an unauthorized manner to create academic work and represent it as one's own.

      The use of generative AI in an unauthorized manner to create academic work and present it as your own may be an example of fabrication as described in the Aggie Honor Code 20.1.2.3.2 part 4.

    1. To see this for yourself, write a line of code below to print the value of the expression 0.3 == 0.1 + 0.2; it will be false!

      0.3==0.2+0.1 will show as false, but 0.5==0.4+0.1 will be shown as true???

    1. 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Le lauréat 2018 de la plus prestigieuse récompense française, Nicolas Mathieu, a remis une pièce dans la machine en s’étonnant de l’ « orgueil surprenant » avec laquelle l’éditeur du Québécois affirme que son auteur a eu recours à une « Sensitivity reader », « comme s’il s’agissait tout à la fois d’un gage de qualité littéraire, de modernité (rire) et de vertu ». 19/09/2023, 17:36 À la loupe Interviews “Je suis sans cesse rattrapé, happé par la vie.” Né en 1964 au Havre, Jean-François Jacq vit actuellement à Vierzon, où il poursuit une intense activité théâtrale et littéraire. Auteur de plusieurs biographies de rock-stars, de groupes, l’homme dévoile également un parcours de vie à la fois chaotique et douloureux à travers plusieurs livres autobiographiques, aux titres évocateurs (Heurt-limite, Hémorragie à l’errance, etc.). Propos recueillis par Etienne Ruhaud. 19/09/2023, 11:38 À la loupe Interviews Bibliocollector vise le record de cartes de bibliothèque Adolescent lyonnais de 16 ans, Adam s'est lancé dans un projet fou : battre un record du monde en collectant le plus grand nombre de cartes de bibliothèques du monde entier. Pour que sa collection soit officiellement reconnue, plusieurs critères s'imposent, mais qu'importe, le Bibliocollector est lancé dans son projet. Entretien.     01/04/2024, 11:06 À la loupe Interviews Géopolitique, conspirations : “XIII est un survivant” (Yves Sente) AnniversaireXIII – Le plus amnésique des héros apparut en 1984, sous l’impulsion du scénariste Jean Van Hamme et du dessinateur William Vance : à la recherche d’un passé fuyant, accusé d’assassinat d’un président des États-Unis et toujours pris dans une conspiration politique sans fin, XIII fête ses quarante années d’aventures, de manipulation et de faux-semblants. Retour avec Yves Sente, le scénariste qui prolonge depuis 13 ans déjà cette épopée américaine avec le dessinateur Iouri Jigounov. 14/03/2024, 15:43 À la loupe Interviews Nancy Huston : “Tout romancier qui se respecte est trans” L'autrice française d'origine canadienne, Nancy Huston et l'écrivain, réalisateur, poète et militant écologiste, Cyril Dion, se connaissent, ils sont amis. Ils éprouvent l’un pour l’autre de l’affection et de l’estime. Les éditions Actes Sud ont proposé une rencontre pour parler de Francia, le dernier texte de Nancy Huston, publié par la maison le 6 mars dernier. Propos recueillis par Estelle Lemaître. 14/03/2024, 15:24 À la loupe Interviews À Madagascar, Karné offre une évasion aux jeunes insulaires Tout sourire et pleine d’entrain, Ravaka a l’air de fonctionner à mille à l’heure. Dès qu’elle s’exprime, on sent un grand enthousiasme et une vraie curiosité. Une envie de comprendre et d’agir se dégage d’emblée de sa personnalité positive. Elle a créé Karné, un concept unique : un magazine bilingue (malgache-français), coloré, vivant, instructif, ludique qui sait prendre sa place sur ce marché. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 14/03/2024, 13:17 À la loupe Interviews Frédéric Taddeï : "L’âge est un sujet qui n’existe pas" « Quand on vous dit que François Ier a gagné la bataille de Marignan en 1515 on ne vous dit pas quel âge il avait, il avait 20 ans ». Le présentateur Frédéric Taddeï a une obsession qu’on ne lui connaissait pas encore : l’âge. Nous l’avons rencontré pour la sortie des Birthday books le 6 mars 2024, l’occasion de discourir sur ces « quartiers de la vie que l’on habite tous ensemble ». 29/02/2024, 15:46 À la loupe Interviews “Nos points communs sont simples : le territoire et le livre.” #Noshorizonsdesirables – Durant cinq années de librairie au Québec chez Pantoute, Benoît Vanbeselaere est passé de la communication et de l’événementiel à la direction générale d’une des deux succursales. Depuis avril 2023, il a pris ses fonctions comme coordinateur de l’Association des éditeurs des Hauts-de-France. En marge des Rencontres régionales du Livre et de la Lecture 2024, à Boulogne-sur-Mer, il revient avec nous sur les actions menées et à mener. 26/02/2024, 15:13 À la loupe Interviews Partage de la valeur : cette étude “apporte des éléments de compréhension” (SNE) L'étude du Syndicat national de l'édition (SNE) consacrée au partage de la valeur entre auteurs et éditeurs, présentée au début de ce mois de février, a été accueillie froidement par les organisations d'auteurs. Ces dernières reprochaient une approche « biaisée » et des résultats qui masquaient la situation économique des écrivains. Renaud Lefebvre, directeur général du SNE, répond aux critiques. 22/02/2024, 11:49 À la loupe Interviews Barbara Kingsolver, Prix Pulitzer 2023 : “Je ne crois pas au talent” Le Prix Pulitzer de la fiction, qui récompense un roman qui raconte cette démente Amérique, a été décerné à deux auteurs ex-aequo en 2023 : Hernan Diaz pour son texte sur les coulisses de la Grande Dépression des années 30, Trust, et Barbara Kingsolver. D’un côté, le gros argent, de l'autre, les prolos d'une campagne des Appalaches, à travers les aventures de Demon Copperhead. Un David Copperfield contemporain dans les terres contrariées de l'OxyconTin et des champs de tabac… 21/02/2024, 16:00 À la loupe Interviews Pour le livre de Turin, "un salon qui aide au dialogue" Du 9 du 13 mai, le Salon international du livre de Turin incarne un événement majeur autour du livre sur le territoire italien. Entre défis antérieurs et direction nouvelle, Annalena Benini, directrice du Salon pour cette édition, fait part à Actualitté des conditions à réunir, pour mener à bien les ambitions prochaines, notamment quant à la jeunesse.  19/02/2024, 12:07 À la loupe Interviews “Le livre et la lecture comme biens communs” Noshorizonsdesirables – Dans le paysage littéraire des Hauts-de-France, une révolution jusqu’alors silencieuse entend faire grand bruit. François Annycke, directeur de l’Agence Régionale du Livre Hauts-de-France (AR2L), inaugurera les 21 et 22 février deux journées professionnelles. Objectif : collaborer, en redéfinissant le rôle de l’Agence et de ses partenaires, pour plus d’efficacité. 16/02/2024, 12:00 À la loupe Interviews “Le lecteur français veut comprendre l'Italie à travers sa littérature” Dans une interview menée par Federica Malinverno, Florence Raut revient sur la création de La libreria, librairie-café parisienne cofondée aux côtés d'Andrea De Ritis en 2006, se définissant comme un « espace petit mais riche dédié à l’Italie, situé dans le cœur du IXe arrondissement de Paris ». 13/02/2024, 11:38 À la loupe Interviews “Pour être un libraire, il faut porter la casquette d’agent culturel” Pleine d’énergie et toute souriante, Prudientienne Gbaguidi est une figure de la librairie francophone en Afrique de l’Ouest. Très engagée pour faire rayonner son métier, elle suit tout ce qui se publie dans la sous-région. A la tête de la librairie Savoir d’Afrique (Bénin), elle est aussi présidente de l’Association des Libraires professionnels du Bénin (ALPB) et vice-présidente de l’Association internationale des Libraires francophones (AILF). Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 06/02/2024, 13:07 À la loupe Interviews Statut européen des artistes-auteurs : “C'est un nouvel espoir” Depuis plusieurs semaines, des organisations françaises d'auteurs de l'écrit se sont lancées dans une campagne de soutien à une initiative législative du Parlement européen. L'objectif ? Inciter la Commission européenne à agir pour améliorer les conditions de vie des artistes-auteurs, notamment par la création d'un statut.  18/01/2024, 15:15 À la loupe Interviews Résolument ancré dans la Fantasy, Leha crée Majik sa collection poche ENTRETIEN – Apparu en 2017 dans le paysage des Littératures de l’Imaginaire, Leha Editions amorce 2024 avec un gros dossier : la création d’une collection de poche, Majik. Un pari audacieux, autant qu’une nouvelle corde à l’arc de cet éditeur, installé à Marseille depuis quelques années.  17/01/2024, 10:08 À la loupe Interviews Louise Boudonnat : traduire, “c’est aussi une rencontre avec soi-même” Dans une interview menée par Federica Malinverno, Louise Boudonnat revient sur son travail de traduction (de l'italien) de l'ouvrage Absolutely Nothing. Histoires et disparitions dans les déserts américains, de Giorgio Vasta et Ramak Fazel, paru aux éditions Verdier en 2023. 02/01/2024, 14:52 À la loupe Interviews Line Papin et les Lettres Zola : "Cette démarche me garde constamment en éveil" LaLettreZola — La première Lettre Zola est toujours disponible à la prévente sur la plateforme KissKissBankBank. La première romancière à offrir aux futurs lecteurs un texte inédit, entre réel et fiction, est Blandine Rinkel. Mais chaque mois est l'occasion de découvrir une nouvelle plume, et pour ce faire, Louis Vendel, créateur de ce singulier et enthousiasmant concept, a dû façonner une véritable équipe autour de lui. Une trentaine de trentenaires, parmi lesquels Line Papin, qui triche un peu, puisqu'elle a 27 ans, mais déjà six ouvrages derrière elle. 26/12/2023, 17:06 À la loupe Interviews David Duchovny : “Les écrivains ont le devoir d'écrire tout ce qu'ils veulent”   David Duchovny, pour les plus anciens, c’est l’agent Fox Mulder, pour les plus au fait, le romancier Hank Moody de Californication. L’enfant de New York est aussi un écrivain : son premier texte fut un conte animalier, Oh la vache ! (trad. Claro, Grasset) « entre Georges Orwell et Tex Avery », rien que ça. Le second publié en France, La Reine du Pays-sous-la-Terre, est un texte étonnant, riche, non sans humour et d'un beau romantisme suranné. 20/12/2023, 18:08 À la loupe Interviews Main à plume : la résistance surréaliste sous l'Occupation Épisode aussi bref qu’intense, aujourd’hui oublié, l’aventure de la « Main à plume » constitue pourtant un des éléments majeurs de l’histoire du surréalisme. En 1940, suite au départ d’André Breton, plusieurs jeunes créateurs se regroupent pour résister à l’occupant, tout en poursuivant une intense activité créatrice, avec la publication de plaquettes, aujourd’hui introuvables. Huit de vingt-trois membres périront : déportés, fusillés, ou tombés au front. Docteure ès Lettres, mais aussi traductrice et autrice, Léa Nicolas-Teboul a retracé le parcours du groupe. Propos recueillis par Étienne Ruhaud. 06/12/2023, 15:37 À la loupe Interviews L'édition jeunesse au Maroc : rencontre avec Nadia Essalmi Nadia Essalmi est une femme de cœur et d’engagement. Une fonceuse qui ne se pose pas mille questions en amont mais qui agit pour faire bouger les lignes et surtout pour apporter aux autres.  C’est aussi une grande rêveuse qui suit son cœur, mais n’est-ce pas le moteur pour innover et avancer ? Editrice jeunesse, promotrice culturelle, militante associative, Nadia est sur tous les fronts quand il s’agit de défendre et valoriser le livre et la lecture au Maroc. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 05/12/2023, 13:07 À la loupe Interviews Malaise dans l'Éducnat : “Mes élèves me donnent matière à espérance” Qu’est-ce que la précarité ? Qu’est-ce que le démantèlement méthodique du service public ?  Qu’est-ce qu’être un professeur précaire dans le secondaire, de surcroît « (grand) remplaçant » dans les territoires abandonnés de la République ? Qu’est-ce qu’enseigner et transmettre ? Autant de questions qui interpellent notre temps. Propos recueillis par Faris Lounis. 04/12/2023, 14:54 À la loupe Interviews “Stig Dagerman va plus loin que Camus : il supprime l’espoir” Claude Le Manchec, essayiste et traducteur français,  nous parle de l’œuvre de Stig Dagerman (1923-1954), de sa place et de sa réception en France, en évoquant son étude Stig Dagerman, la vérité pressentie de tous (Éditions du Cygne, Paris, 2020). Propos recueillis par Karim El Haddady 04/12/2023, 12:22 À la loupe Interviews Pour une industrie du livre plus forte en Italie Dans un entretien accordé à ActuaLitté, le président de l'Associazione Italiana Editori dévoile ses objectifs pour l'industrie du livre en Italie. Il aborde la nécessité d'une croissance culturelle, la promotion de la lecture, l'internationalisation de l'édition italienne et les défis du dialogue avec les institutions. 27/11/2023, 15:29 À la loupe Interviews Tom Buron : "Le danger est un élément central de mon travail" Jeune poète francilien, Tom Buron pratique la boxe, écoute du jazz, écrit de brefs recueils percutants. Dernier en date, La Chambre et le Barillet (éditions « Angle mort », 2023), présente une suite de vers-libres, souvent rageurs, parfois énigmatiques. Familier de l’univers urbain, guidé par un certain rythme incantatoire, habitué des scènes poétiques, l’auteur semble refuser la tyrannie du sens, de l’intelligibilité, tout en favorisant l’oralité. Propos recueillis par Étienne Ruhaud. 27/11/2023, 10:04 À la loupe Interviews Anarchie en Haïti : “Que les Américains nous lâchent un peu” Gary Victor, « le romancier haïtien le plus lu dans son pays » selon son éditeur Mémoire d'encrier, ne peut plus aujourd'hui vivre dans sa maison, dans le quartier de Carrefour-Feuilles à Port-au-Prince, pris dans la guerre des gangs. La situation dans le pays de Dany Laferrière est cataclysmique, mais il faut continuer de vivre, et pour le Prix littéraire des Caraïbes 2008, cela passe par l'écriture : à la rentrée, il a fait paraître en France Le Violon d'Adrien, où il s'appuie sur un épisode de son enfance qui l'a particulièrement marqué... 14/11/2023, 11:40 À la loupe Interviews Tikoulou : un héros mauricien qui unit les cultures À l’Ile Maurice, Pascale Siew est devenue indissociable du personnage qu’elle a créé : Tikoulou, le petit Mauricien. Cette éditrice passionnée est depuis longtemps une référence sur l’île mais, dans ce cadre idyllique, Pascale Siew avoue se sentir très isolée professionnellement. Elle nous raconte cette belle aventure des éditions Vizavi qui dure depuis trois décennies. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 13/11/2023, 10:42 À la loupe Interviews De l'ombre du 93 à la lumière littéraire : “Je lui serai toujours redevable” (Olivier Norek) Le décès de Huguette Maure, survenu ce 29 octobre, a assombri un week-end déjà maussade. Parmi les écrivains que la responsable éditoriale avait soutenus, Olivier Norek lui rend hommage. « Elle a façonné mon parcours : elle représente les fondations de l'écrivain que je suis devenu. » Notamment grâce à la confiance qu'elle fut la première à lui témoigner, en choisissant de publier son premier roman, Code 93. 30/10/2023, 11:04 À la loupe Interviews “La consommation de l’actualité s’opère sans prise de conscience” Benoît Couzi, directeur des éditions Le Lys bleu, avait dernièrement lancé une pétition pour attirer l’attention sur le coût croissant des livres en France. Malheureusement, malgré une diffusion à près de 200.000 personnes, seulement 4 000 ont choisi de signer. Une réalité qui, selon Benoit Couzi, « dit quelque chose de l’implication de l’individu dans la société ». 26/10/2023, 17:02 À la loupe Interviews Les chiens ne se baignent jamais deux fois dans la même Rivière Décalé, mystérieux, Les chiens nus nous parle, comme son nom l’indique, de nos amis quadrupèdes. Mais loin d’avoir rédigé un (banal) traité d’éthologie, ou un énième guide sur les chiens, Alain Rivière nous embarque pour un déroutant voyage, dans lequel l’animal semble essentiellement nous renvoyer à nous, à notre condition mortelle. Propos recueillis par Étienne Ruhaud. 26/10/2023, 11:24 À la loupe Interviews “La réécriture par les ayants droit, ce n'est plus la même oeuvre” Déposée en mai 2023 à l'Assemblée nationale par le député Les Républicains Jean-Louis Thiériot (Seine-et-Marne), la proposition de loi visant à protéger l’intégrité des œuvres des réécritures idéologiques a fait son retour, au mois d'octobre. Un texte inchangé, mais cette fois soutenu par d'autres représentants de la droite, Éric Ciotti en tête. 23/10/2023, 12:24 À la loupe Interviews Elias Khoury : héraut d'un monde arabe en quête de modernité Le romancier libanais Elias Khoury publie chez Actes Sud L’Étoile de la mer, son dernier roman, et deuxième partie d’une trilogie (trad. Rania Samara). Farouk Mardam-Bey, directeur chez Actes Sud de la collection Sindbad, se souvient avec émotion de sa première rencontre avec l'écrivain, à Paris.  10/10/2023, 12:06 À la loupe Interviews Frédéric Pillot, un Roland passionnément furieux LEP23 – Dès son enfance, Frédéric Pillot a trouvé du plaisir dans le dessin. Avec le temps, cette passion s'est transformée en une évidence : allier le dessin à la narration. La réflexion s'est alors orientée vers une activité génératrice de revenus. Une constellation d'idées s'est formée, mêlant le plaisir de raconter à celui de dessiner. Malgré des doutes et des impasses, Frédéric a persévéré. Aujourd'hui, il est un illustrateur reconnu, inspirant ceux qui souhaitent transformer leur passion en métier. 08/10/2023, 17:18 À la loupe Interviews Ange Mbelle : “Tisser des liens pour le livre africain” Une approche pragmatique du marché, un parler franc et une vraie dynamique entrepreneuriale, Ange Mbelle a créé GVG, une structure de distribution. Basée à Douala (Cameroun), elle rayonne dans plusieurs pays de la région. Attentive aux pratiques des éditeurs, elle encourage les libraires et autres points de vente à développer leur offre de livres. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 02/10/2023, 15:01 À la loupe Interviews La Lettre Zola : redéfinir le lien entre écrivains et lecteurs LaLettreZola – Dans le monde de l'édition, il est rare de trouver des projets qui marient avec autant de finesse la littérature et le journalisme. Louis Vendel, fondateur de la revue "La Lettre Zola", nous parle de cette initiative unique qui fait la jonction entre ces deux univers. 28/09/2023, 15:38 À la loupe Interviews Aux Deux Magots, “la littérature est éternelle” #PrixdesDeuxMagots2023 – Le Prix des Deux Magots, l'une des récompenses littéraires les plus prestigieuses de France, a célébré son 90e anniversaire dans une ambiance festive et solennelle. Étienne de Montety, président du jury, a partagé avec nous l'essence de cette édition mémorable. 25/09/2023, 17:36 À la loupe Interviews Kevin Lambert : l’architecture, 1er art et miroir de l'époque Le jeune romancier Kevin Lambert fait l’actualité de cette rentrée littéraire : d’abord en s’inscrivant avec son troisième roman publié au Nouvel Attila, Que notre joie demeure, dans plusieurs listes de prix, dont celle du Goncourt. Le lauréat 2018 de la plus prestigieuse récompense française, Nicolas Mathieu, a remis une pièce dans la machine en s’étonnant de l’ « orgueil surprenant » avec laquelle l’éditeur du Québécois affirme que son auteur a eu recours à une « Sensitivity reader », « comme s’il s’agissait tout à la fois d’un gage de qualité littéraire, de modernité (rire) et de vertu ». 19/09/2023, 17:36 À la loupe Interviews “Je suis sans cesse rattrapé, happé par la vie.” Né en 1964 au Havre, Jean-François Jacq vit actuellement à Vierzon, où il poursuit une intense activité théâtrale et littéraire. Auteur de plusieurs biographies de rock-stars, de groupes, l’homme dévoile également un parcours de vie à la fois chaotique et douloureux à travers plusieurs livres autobiographiques, aux titres évocateurs (Heurt-limite, Hémorragie à l’errance, etc.). Propos recueillis par Etienne Ruhaud. 19/09/2023, 11:38 À la loupe Interviews Bibliocollector vise le record de cartes de bibliothèque Adolescent lyonnais de 16 ans, Adam s'est lancé dans un projet fou : battre un record du monde en collectant le plus grand nombre de cartes de bibliothèques du monde entier. Pour que sa collection soit officiellement reconnue, plusieurs critères s'imposent, mais qu'importe, le Bibliocollector est lancé dans son projet. Entretien.     01/04/2024, 11:06 À la loupe Interviews Géopolitique, conspirations : “XIII est un survivant” (Yves Sente) AnniversaireXIII – Le plus amnésique des héros apparut en 1984, sous l’impulsion du scénariste Jean Van Hamme et du dessinateur William Vance : à la recherche d’un passé fuyant, accusé d’assassinat d’un président des États-Unis et toujours pris dans une conspiration politique sans fin, XIII fête ses quarante années d’aventures, de manipulation et de faux-semblants. Retour avec Yves Sente, le scénariste qui prolonge depuis 13 ans déjà cette épopée américaine avec le dessinateur Iouri Jigounov. 14/03/2024, 15:43 À la loupe Interviews Nancy Huston : “Tout romancier qui se respecte est trans” L'autrice française d'origine canadienne, Nancy Huston et l'écrivain, réalisateur, poète et militant écologiste, Cyril Dion, se connaissent, ils sont amis. Ils éprouvent l’un pour l’autre de l’affection et de l’estime. Les éditions Actes Sud ont proposé une rencontre pour parler de Francia, le dernier texte de Nancy Huston, publié par la maison le 6 mars dernier. Propos recueillis par Estelle Lemaître. 14/03/2024, 15:24 À la loupe Interviews À Madagascar, Karné offre une évasion aux jeunes insulaires Tout sourire et pleine d’entrain, Ravaka a l’air de fonctionner à mille à l’heure. Dès qu’elle s’exprime, on sent un grand enthousiasme et une vraie curiosité. Une envie de comprendre et d’agir se dégage d’emblée de sa personnalité positive. Elle a créé Karné, un concept unique : un magazine bilingue (malgache-français), coloré, vivant, instructif, ludique qui sait prendre sa place sur ce marché. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 14/03/2024, 13:17 À la loupe Interviews Frédéric Taddeï : "L’âge est un sujet qui n’existe pas" « Quand on vous dit que François Ier a gagné la bataille de Marignan en 1515 on ne vous dit pas quel âge il avait, il avait 20 ans ». Le présentateur Frédéric Taddeï a une obsession qu’on ne lui connaissait pas encore : l’âge. Nous l’avons rencontré pour la sortie des Birthday books le 6 mars 2024, l’occasion de discourir sur ces « quartiers de la vie que l’on habite tous ensemble ». 29/02/2024, 15:46 À la loupe Interviews “Nos points communs sont simples : le territoire et le livre.” #Noshorizonsdesirables – Durant cinq années de librairie au Québec chez Pantoute, Benoît Vanbeselaere est passé de la communication et de l’événementiel à la direction générale d’une des deux succursales. Depuis avril 2023, il a pris ses fonctions comme coordinateur de l’Association des éditeurs des Hauts-de-France. En marge des Rencontres régionales du Livre et de la Lecture 2024, à Boulogne-sur-Mer, il revient avec nous sur les actions menées et à mener. 26/02/2024, 15:13 À la loupe Interviews Partage de la valeur : cette étude “apporte des éléments de compréhension” (SNE) L'étude du Syndicat national de l'édition (SNE) consacrée au partage de la valeur entre auteurs et éditeurs, présentée au début de ce mois de février, a été accueillie froidement par les organisations d'auteurs. Ces dernières reprochaient une approche « biaisée » et des résultats qui masquaient la situation économique des écrivains. Renaud Lefebvre, directeur général du SNE, répond aux critiques. 22/02/2024, 11:49 À la loupe Interviews Barbara Kingsolver, Prix Pulitzer 2023 : “Je ne crois pas au talent” Le Prix Pulitzer de la fiction, qui récompense un roman qui raconte cette démente Amérique, a été décerné à deux auteurs ex-aequo en 2023 : Hernan Diaz pour son texte sur les coulisses de la Grande Dépression des années 30, Trust, et Barbara Kingsolver. D’un côté, le gros argent, de l'autre, les prolos d'une campagne des Appalaches, à travers les aventures de Demon Copperhead. Un David Copperfield contemporain dans les terres contrariées de l'OxyconTin et des champs de tabac… 21/02/2024, 16:00 À la loupe Interviews Pour le livre de Turin, "un salon qui aide au dialogue" Du 9 du 13 mai, le Salon international du livre de Turin incarne un événement majeur autour du livre sur le territoire italien. Entre défis antérieurs et direction nouvelle, Annalena Benini, directrice du Salon pour cette édition, fait part à Actualitté des conditions à réunir, pour mener à bien les ambitions prochaines, notamment quant à la jeunesse.  19/02/2024, 12:07 À la loupe Interviews “Le livre et la lecture comme biens communs” Noshorizonsdesirables – Dans le paysage littéraire des Hauts-de-France, une révolution jusqu’alors silencieuse entend faire grand bruit. François Annycke, directeur de l’Agence Régionale du Livre Hauts-de-France (AR2L), inaugurera les 21 et 22 février deux journées professionnelles. Objectif : collaborer, en redéfinissant le rôle de l’Agence et de ses partenaires, pour plus d’efficacité. 16/02/2024, 12:00 À la loupe Interviews “Le lecteur français veut comprendre l'Italie à travers sa littérature” Dans une interview menée par Federica Malinverno, Florence Raut revient sur la création de La libreria, librairie-café parisienne cofondée aux côtés d'Andrea De Ritis en 2006, se définissant comme un « espace petit mais riche dédié à l’Italie, situé dans le cœur du IXe arrondissement de Paris ». 13/02/2024, 11:38 À la loupe Interviews “Pour être un libraire, il faut porter la casquette d’agent culturel” Pleine d’énergie et toute souriante, Prudientienne Gbaguidi est une figure de la librairie francophone en Afrique de l’Ouest. Très engagée pour faire rayonner son métier, elle suit tout ce qui se publie dans la sous-région. A la tête de la librairie Savoir d’Afrique (Bénin), elle est aussi présidente de l’Association des Libraires professionnels du Bénin (ALPB) et vice-présidente de l’Association internationale des Libraires francophones (AILF). Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 06/02/2024, 13:07 À la loupe Interviews Statut européen des artistes-auteurs : “C'est un nouvel espoir” Depuis plusieurs semaines, des organisations françaises d'auteurs de l'écrit se sont lancées dans une campagne de soutien à une initiative législative du Parlement européen. L'objectif ? Inciter la Commission européenne à agir pour améliorer les conditions de vie des artistes-auteurs, notamment par la création d'un statut.  18/01/2024, 15:15 À la loupe Interviews Résolument ancré dans la Fantasy, Leha crée Majik sa collection poche ENTRETIEN – Apparu en 2017 dans le paysage des Littératures de l’Imaginaire, Leha Editions amorce 2024 avec un gros dossier : la création d’une collection de poche, Majik. Un pari audacieux, autant qu’une nouvelle corde à l’arc de cet éditeur, installé à Marseille depuis quelques années.  17/01/2024, 10:08 À la loupe Interviews Louise Boudonnat : traduire, “c’est aussi une rencontre avec soi-même” Dans une interview menée par Federica Malinverno, Louise Boudonnat revient sur son travail de traduction (de l'italien) de l'ouvrage Absolutely Nothing. Histoires et disparitions dans les déserts américains, de Giorgio Vasta et Ramak Fazel, paru aux éditions Verdier en 2023. 02/01/2024, 14:52 À la loupe Interviews Line Papin et les Lettres Zola : "Cette démarche me garde constamment en éveil" LaLettreZola — La première Lettre Zola est toujours disponible à la prévente sur la plateforme KissKissBankBank. La première romancière à offrir aux futurs lecteurs un texte inédit, entre réel et fiction, est Blandine Rinkel. Mais chaque mois est l'occasion de découvrir une nouvelle plume, et pour ce faire, Louis Vendel, créateur de ce singulier et enthousiasmant concept, a dû façonner une véritable équipe autour de lui. Une trentaine de trentenaires, parmi lesquels Line Papin, qui triche un peu, puisqu'elle a 27 ans, mais déjà six ouvrages derrière elle. 26/12/2023, 17:06 À la loupe Interviews David Duchovny : “Les écrivains ont le devoir d'écrire tout ce qu'ils veulent”   David Duchovny, pour les plus anciens, c’est l’agent Fox Mulder, pour les plus au fait, le romancier Hank Moody de Californication. L’enfant de New York est aussi un écrivain : son premier texte fut un conte animalier, Oh la vache ! (trad. Claro, Grasset) « entre Georges Orwell et Tex Avery », rien que ça. Le second publié en France, La Reine du Pays-sous-la-Terre, est un texte étonnant, riche, non sans humour et d'un beau romantisme suranné. 20/12/2023, 18:08 À la loupe Interviews Main à plume : la résistance surréaliste sous l'Occupation Épisode aussi bref qu’intense, aujourd’hui oublié, l’aventure de la « Main à plume » constitue pourtant un des éléments majeurs de l’histoire du surréalisme. En 1940, suite au départ d’André Breton, plusieurs jeunes créateurs se regroupent pour résister à l’occupant, tout en poursuivant une intense activité créatrice, avec la publication de plaquettes, aujourd’hui introuvables. Huit de vingt-trois membres périront : déportés, fusillés, ou tombés au front. Docteure ès Lettres, mais aussi traductrice et autrice, Léa Nicolas-Teboul a retracé le parcours du groupe. Propos recueillis par Étienne Ruhaud. 06/12/2023, 15:37 À la loupe Interviews L'édition jeunesse au Maroc : rencontre avec Nadia Essalmi Nadia Essalmi est une femme de cœur et d’engagement. Une fonceuse qui ne se pose pas mille questions en amont mais qui agit pour faire bouger les lignes et surtout pour apporter aux autres.  C’est aussi une grande rêveuse qui suit son cœur, mais n’est-ce pas le moteur pour innover et avancer ? Editrice jeunesse, promotrice culturelle, militante associative, Nadia est sur tous les fronts quand il s’agit de défendre et valoriser le livre et la lecture au Maroc. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 05/12/2023, 13:07 À la loupe Interviews Malaise dans l'Éducnat : “Mes élèves me donnent matière à espérance” Qu’est-ce que la précarité ? Qu’est-ce que le démantèlement méthodique du service public ?  Qu’est-ce qu’être un professeur précaire dans le secondaire, de surcroît « (grand) remplaçant » dans les territoires abandonnés de la République ? Qu’est-ce qu’enseigner et transmettre ? Autant de questions qui interpellent notre temps. Propos recueillis par Faris Lounis. 04/12/2023, 14:54 À la loupe Interviews “Stig Dagerman va plus loin que Camus : il supprime l’espoir” Claude Le Manchec, essayiste et traducteur français,  nous parle de l’œuvre de Stig Dagerman (1923-1954), de sa place et de sa réception en France, en évoquant son étude Stig Dagerman, la vérité pressentie de tous (Éditions du Cygne, Paris, 2020). Propos recueillis par Karim El Haddady 04/12/2023, 12:22 À la loupe Interviews Pour une industrie du livre plus forte en Italie Dans un entretien accordé à ActuaLitté, le président de l'Associazione Italiana Editori dévoile ses objectifs pour l'industrie du livre en Italie. Il aborde la nécessité d'une croissance culturelle, la promotion de la lecture, l'internationalisation de l'édition italienne et les défis du dialogue avec les institutions. 27/11/2023, 15:29 À la loupe Interviews Tom Buron : "Le danger est un élément central de mon travail" Jeune poète francilien, Tom Buron pratique la boxe, écoute du jazz, écrit de brefs recueils percutants. Dernier en date, La Chambre et le Barillet (éditions « Angle mort », 2023), présente une suite de vers-libres, souvent rageurs, parfois énigmatiques. Familier de l’univers urbain, guidé par un certain rythme incantatoire, habitué des scènes poétiques, l’auteur semble refuser la tyrannie du sens, de l’intelligibilité, tout en favorisant l’oralité. Propos recueillis par Étienne Ruhaud. 27/11/2023, 10:04 À la loupe Interviews Anarchie en Haïti : “Que les Américains nous lâchent un peu” Gary Victor, « le romancier haïtien le plus lu dans son pays » selon son éditeur Mémoire d'encrier, ne peut plus aujourd'hui vivre dans sa maison, dans le quartier de Carrefour-Feuilles à Port-au-Prince, pris dans la guerre des gangs. La situation dans le pays de Dany Laferrière est cataclysmique, mais il faut continuer de vivre, et pour le Prix littéraire des Caraïbes 2008, cela passe par l'écriture : à la rentrée, il a fait paraître en France Le Violon d'Adrien, où il s'appuie sur un épisode de son enfance qui l'a particulièrement marqué... 14/11/2023, 11:40 À la loupe Interviews Tikoulou : un héros mauricien qui unit les cultures À l’Ile Maurice, Pascale Siew est devenue indissociable du personnage qu’elle a créé : Tikoulou, le petit Mauricien. Cette éditrice passionnée est depuis longtemps une référence sur l’île mais, dans ce cadre idyllique, Pascale Siew avoue se sentir très isolée professionnellement. Elle nous raconte cette belle aventure des éditions Vizavi qui dure depuis trois décennies. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 13/11/2023, 10:42 À la loupe Interviews De l'ombre du 93 à la lumière littéraire : “Je lui serai toujours redevable” (Olivier Norek) Le décès de Huguette Maure, survenu ce 29 octobre, a assombri un week-end déjà maussade. Parmi les écrivains que la responsable éditoriale avait soutenus, Olivier Norek lui rend hommage. « Elle a façonné mon parcours : elle représente les fondations de l'écrivain que je suis devenu. » Notamment grâce à la confiance qu'elle fut la première à lui témoigner, en choisissant de publier son premier roman, Code 93. 30/10/2023, 11:04 À la loupe Interviews “La consommation de l’actualité s’opère sans prise de conscience” Benoît Couzi, directeur des éditions Le Lys bleu, avait dernièrement lancé une pétition pour attirer l’attention sur le coût croissant des livres en France. Malheureusement, malgré une diffusion à près de 200.000 personnes, seulement 4 000 ont choisi de signer. Une réalité qui, selon Benoit Couzi, « dit quelque chose de l’implication de l’individu dans la société ». 26/10/2023, 17:02 À la loupe Interviews Les chiens ne se baignent jamais deux fois dans la même Rivière Décalé, mystérieux, Les chiens nus nous parle, comme son nom l’indique, de nos amis quadrupèdes. Mais loin d’avoir rédigé un (banal) traité d’éthologie, ou un énième guide sur les chiens, Alain Rivière nous embarque pour un déroutant voyage, dans lequel l’animal semble essentiellement nous renvoyer à nous, à notre condition mortelle. Propos recueillis par Étienne Ruhaud. 26/10/2023, 11:24 À la loupe Interviews “La réécriture par les ayants droit, ce n'est plus la même oeuvre” Déposée en mai 2023 à l'Assemblée nationale par le député Les Républicains Jean-Louis Thiériot (Seine-et-Marne), la proposition de loi visant à protéger l’intégrité des œuvres des réécritures idéologiques a fait son retour, au mois d'octobre. Un texte inchangé, mais cette fois soutenu par d'autres représentants de la droite, Éric Ciotti en tête. 23/10/2023, 12:24 À la loupe Interviews Elias Khoury : héraut d'un monde arabe en quête de modernité Le romancier libanais Elias Khoury publie chez Actes Sud L’Étoile de la mer, son dernier roman, et deuxième partie d’une trilogie (trad. Rania Samara). Farouk Mardam-Bey, directeur chez Actes Sud de la collection Sindbad, se souvient avec émotion de sa première rencontre avec l'écrivain, à Paris.  10/10/2023, 12:06 À la loupe Interviews Frédéric Pillot, un Roland passionnément furieux LEP23 – Dès son enfance, Frédéric Pillot a trouvé du plaisir dans le dessin. Avec le temps, cette passion s'est transformée en une évidence : allier le dessin à la narration. La réflexion s'est alors orientée vers une activité génératrice de revenus. Une constellation d'idées s'est formée, mêlant le plaisir de raconter à celui de dessiner. Malgré des doutes et des impasses, Frédéric a persévéré. Aujourd'hui, il est un illustrateur reconnu, inspirant ceux qui souhaitent transformer leur passion en métier. 08/10/2023, 17:18 À la loupe Interviews Ange Mbelle : “Tisser des liens pour le livre africain” Une approche pragmatique du marché, un parler franc et une vraie dynamique entrepreneuriale, Ange Mbelle a créé GVG, une structure de distribution. Basée à Douala (Cameroun), elle rayonne dans plusieurs pays de la région. Attentive aux pratiques des éditeurs, elle encourage les libraires et autres points de vente à développer leur offre de livres. Propos recueillis par Agnès Debiage, fondatrice d’ADCF Africa. 02/10/2023, 15:01 À la loupe Interviews La Lettre Zola : redéfinir le lien entre écrivains et lecteurs LaLettreZola – Dans le monde de l'édition, il est rare de trouver des projets qui marient avec autant de finesse la littérature et le journalisme. Louis Vendel, fondateur de la revue "La Lettre Zola", nous parle de cette initiative unique qui fait la jonction entre ces deux univers. 28/09/2023, 15:38 À la loupe Interviews Aux Deux Magots, “la littérature est éternelle” #PrixdesDeuxMagots2023 – Le Prix des Deux Magots, l'une des récompenses littéraires les plus prestigieuses de France, a célébré son 90e anniversaire dans une ambiance festive et solennelle. Étienne de Montety, président du jury, a partagé avec nous l'essence de cette édition mémorable. 25/09/2023, 17:36 À la loupe Interviews Kevin Lambert : l’architecture, 1er art et miroir de l'époque Le jeune romancier Kevin Lambert fait l’actualité de cette rentrée littéraire : d’abord en s’inscrivant avec son troisième roman publié au Nouvel Attila, Que notre joie demeure, dans plusieurs listes de prix, dont celle du Goncourt. Le lauréat 2018 de la plus prestigieuse récompense française, Nicolas Mathieu, a remis une pièce dans la machine en s’étonnant de l’ « orgueil surprenant » avec laquelle l’éditeur du Québécois affirme que son auteur a eu recours à une « Sensitivity reader », « comme s’il s’agissait tout à la fois d’un gage de qualité littéraire, de modernité (rire) et de vertu ». 19/09/2023, 17:36 À la loupe Interviews “Je suis sans cesse rattrapé, happé par la vie.” Né en 1964 au Havre, Jean-François Jacq vit actuellement à Vierzon, où il poursuit une intense activité théâtrale et littéraire. Auteur de plusieurs biographies de rock-stars, de groupes, l’homme dévoile également un parcours de vie à la fois chaotique et douloureux à travers plusieurs livres autobiographiques, aux titres évocateurs (Heurt-limite, Hémorragie à l’errance, etc.). Propos recueillis par Etienne Ruhaud. 19/09/2023, 11:38 Autres articles de la rubrique À la loupe À la loupe Reportages “Nutri-score” et autres projets d’avenir pour une édition écologique D’après Erri de Luca, l’impossible caractérise « ce qui n’a pas encore été fait » (trad. Danièle Valin). La chaîne du livre — mais par cette dénomination, ne réduit-on pas ses acteurs à des maillons ignorants les uns des autres ? — était conviée à une journée de réflexion, ce 29 janvier. Dans les locaux du groupe Bayard, on se réunissait pour « décarboner le livre et l’édition ».  29/01/2024, 20:08 À la loupe Humeurs Au-delà de la polémique Tesson, “faire vivre le Printemps des poètes” « Au-delà des polémiques de toutes sortes, il nous appartient de faire vivre cette édition du Printemps des Poètes coûte que coûte, et de penser d'abord au public », déclarent les cofondateurs des éditions Doucey. Cette réaction intervient peu après l'annonce de la démission de Sophie Nauleau, directrice artistique du Printemps des Poètes.  27/01/2024, 12:21 À la loupe Humeurs Vers le Kirghizistan, à la recherche de la fraicheur perdue #AVeloEntreLesLignes — C'est l'aventure de Zoé David-Rigot et Jaroslav Kocourek, deux cyclistes qui se sont donné pour challenge de rejoindre Oulan-Bator depuis Paris, à la force de leurs cuisses. En chemin, ils visitent autant de librairies qu'ils peuvent. ActuaLitté suit ce périple en publiant leurs récits. 26/01/2024, 14:40 À la loupe Humeurs “Nous croyons que la poésie peut captiver les coeurs” Partout dans le monde, la poésie peut exprimer l'indicible, sans en avoir l'air. Cette puissance en fait aussi une cible de tous les extrêmes, et en particulier des régimes liberticides. Dans un texte prononcé à l'Université de Lille, le 22 mars 2024, la poète, écrivaine et militante des droits des femmes en Afghanistan Somaia Ramish célèbre la poésie et appelle à la défendre, encore et toujours. 05/04/2024, 12:28 À la loupe Tribunes Livres pour malvoyants : “Il ne suffit pas d’agrandir la police de caractères” La Librairie des Grands Caractères, basée dans le 5e arrondissement de Paris, publie ici son « coup de gueule » sur certains éditeurs dont les pratiques lui semblent douteuses. L'établissement pointe notamment le fait que certaines règles à suivre dans l'édition de livres pour malvoyants sont trop régulièrement ignorées par des acteurs du secteur. 02/04/2024, 13:15 À la loupe Reportages Pause soupe de nouilles à minuit : ultimes heures avant la Mongolie #AVeloEntreLesLignes – Partir à la découverte du plus grand nombre de librairies possible, entre Paris et Oulan-Bator, le défi est de taille. À vélo, c'est confirmé : c'est de la folie douce. C’est pourtant l’aventure que Zoé David-Rigot et Jaroslav Kocourek ont démarrée en août 2022. ActuaLitté les accompagne, en publiant leur récit de ce périple, À vélo, entre les lignes. 01/04/2024, 08:03 À la loupe Humeurs “J’habite une maison vieille qui embrasse les formes de mon corps” Carnetdebord – Pour la rentrée littéraire 2024, les éditions du Tripode publieront le nouveau roman d'Audrée Wilhelmy. Pour accompagner cette parution, la romancière a trouvé dans nos colonnes une place à part : un Carnet de Bord pour raconter cette aventure, jusqu'aux librairies. 30/03/2024, 17:05 À la loupe Tribunes Pour un renouveau documentaire dans les universités françaises   L'Association des Directeurs et des personnels de direction des Bibliothèques Universitaires et de la Documentation (ADBU) et le Syndicat National de l'Édition (SNE) s'unissent pour interpeller le gouvernement et les autorités sur la nécessité critique d'un élan majeur en faveur des ressources documentaires. Ils insistent sur la nécessité d'investissements immédiats pour assurer le développement d'une documentation universitaire compétitive au niveau européen, et de maintenir la France au cœur des débats scientifiques et éducatifs mondiaux. 27/03/2024, 12:51 À la loupe Tribunes IA : un rapport “équilibré” remis à Emmanuel Macron Alors que la « Commission IA » remettait son rapport au Président de la République le 13 mars 2024, les réactions continuent d'affluer concernant le positionnement de la France face aux enjeux de l'intelligence artificielle. Si des associations de traducteurs telles que En Chair et en Os et l'Association des traducteurs littéraires de France appelaient à sauver « le geste humain », une nouvelle tribune d'un collectif rassemblant divers acteurs des milieux culturels salue, elle, « un rapport équilibré ». 27/03/2024, 10:08 À la loupe Humeurs Peau-de-sang, expérience physique et sensorielle: “Bienvenue, Audrée...” Carnetdebord – Au cours des prochaines semaines, ActuaLitté accueillera le Carnet de Bord d'Audrée Wilhelmy. Romancière québécoise, elle publiera son prochain ouvrage aux éditions du Tripode. Ce seront tout à la fois les récits d'une attente, d'un espoir, d'une envie. Ce seront les récits d'un à-venir. En guise de prélude, Frédéric Martin, fondateur de la maison, nous présente cette autrice, d'ores et déjà adoptée. 27/03/2024, 08:01 À la loupe Reportages Annonciation faite à Dati : les auteurs ressuscitent le rapport Racine Devant la Comédie française, ce 25 mars – date de l'annonce à Marie de sa maternité divine –, ils étaient près de deux cents présents pour le retour d’un vieux compagnon. La première Nuit des auteurs et autrices aura vibré au son des les mariachis qui abreuvaient la place Colette de musiques. La promesse d’un rassemblement politique, collectif et festif était tenue… mais les soirées parisiennes prennent parfois des tournures inattendues. 26/03/2024, 11:56 À la loupe Tribunes “Produire un livre écologique n’est pas possible” La Volte annonce donc son vingtième anniversaire : vingt ans d'aventures éditoriales où se retrouvent des histoires d'émancipation, de la science-fiction sociale et politique, avec une passion pour les jeux de langage. Elle avait déjà annoncé en janvier qu'elle renforcerait cette année son engagement écologique et affirmerait son identité visuelle. Maintenant, place aux projets. 23/03/2024, 15:38 À la loupe Reportages La zone secrète entre Russie et Chine, blague de géographe #AVeloEntreLesLignes – Partir à la découverte du plus grand nombre de librairies possible, entre Paris et Oulan-Bator, le défi est de taille. À vélo, c'est confirmé : c'est de la folie douce. C’est pourtant l’aventure que Zoé David-Rigot et Jaroslav Kocourek ont démarrée en août 2022. ActuaLitté les accompagne, en publiant leur récit de ce périple, À vélo, entre les lignes. 23/03/2024, 15:25 À la loupe Reportages Sacrilège ! Une histoire française de l’offense au pouvoir   Aux Archives nationales à l’Hôtel de Soubise, du 20 mars au 1er juillet prochain, plongez au cœur de l'histoire tumultueuse du sacrilège, où le spirituel et le temporel travaillent à ne faire qu’un, mais lequel ? Le dernier discours de Robespierre, l'œil de Léon Gambetta, le testament de Louis XVI… Des trésors historiques et autres documents d'archives inédits, pour une expérience solennelle, et parfois moqueuse, aux frontières du divin et du pouvoir. 22/03/2024, 17:32 À la loupe Tribunes “Faire front commun face à la massification annoncée des IA dans le travail” Après le collectif En Chair et en Os, c'est au tour de l'Association des traducteurs littéraires de France (ATLF) de réagir au rapport, IA : notre ambition pour la France, remis au Président de la République le 13 mars dernier. Ces membres, après l'avoir lu « avec beaucoup de colère », appellent les pouvoirs publics à « ne pas céder aux sirènes de la compétitivité mondiale, et l’ensemble des artistes-auteurs à faire front commun face à la massification annoncée des intelligences artificielles dans leur travail ». 22/03/2024, 13:31 À la loupe Tribunes Bastien Vivès, condamnable ou martyr de la liberté d'expression ? L’Observatoire de la liberté de création (OLC) dénonce « une loi absurde et son application ubuesque » dans l’affaire Bastien Vivès. Dans une tribune, ses membres justifient leur positionnement : à chacun de se faire un point de vue... 22/03/2024, 11:26 À la loupe Tribunes Pour une traduction humaine : “Il en va de l'avenir de nos professions” Quelques jours après la présentation du rapport de la commission IA au Président de la République, qui en salue les recommandations prônant le tout-IA dans de nombreux domaines, le collectif En Chair et en Os, « pour une traduction humaine », s'adresse aujourd'hui à toute l'édition, et appelle le monde du livre et de la culture à se mobiliser pour préserver le geste humain, sans céder au technosolutionnisme. 18/03/2024, 11:42 À la loupe Reportages De l'Altaï russe à la Mongolie en passant par l'édition kirghize #AVeloEntreLesLignes — Zoé David-Rigot et Jaroslav Kocourek ont entrepris un voyage en vélo entre Paris et Oulan-Bator en août 2022, avec l'objectif de visiter le maximum de librairies sur leur route. ActuaLitté documentera cette expédition en publiant le récit intitulé "À vélo, entre les lignes". 17/03/2024, 12:13 À la loupe Tribunes Expression, publication, lecture : des libertés à défendre Depuis la Foire du Livre de Londres, cinq organisations internationales représentant les auteurs, éditeurs, libraires et bibliothécaires cosignent une déclaration. Ce texte, reproduit en intégralité ci-dessous, constitue un appel aux gouvernements et aux sociétés dans leur ensemble à veiller sur des libertés fondamentales autour des textes et de leurs auteurs : expression, publication et lecture. 14/03/2024, 11:14 À la loupe Tribunes Traduire par l'IA, le risque d'“un appauvrissement sensible de la langue” Face à la montée de l'intelligence artificielle dans le domaine de la traduction, l'Association des Autrices et Auteurs de Suisse (AdS) tire la sonnette d'alarme. Lors de son 15e Symposium suisse, l'association a publié une prise de position vigoureuse, soulignant les limites de l'IA en matière de traduction littéraire et réclamant une régulation claire pour protéger les droits et la valeur du travail humain. 06/03/2024, 12:54 À la loupe Enquêtes Moon Knight, justicier lunaire et passablement tordu L’identité secrète est le propre du super héros – ça et les collants trop moulants. Apparu dans Werewolf by Night #32 en 1975, Marc Spector fêtera ses 50 ans de lutte contre le crime à New York : il protège les voyageurs, chers au dieu égyptien qui l’a choisi pour avatar. Non sans l’avoir sauvé de la mort. Mais ce personnage, atteint d’un trouble dissociatif, coexiste mentalement avec trois autres personnes. De quoi en faire un justicier atypique, dont les méthodes effraient. 06/03/2024, 12:16 À la loupe Reportages Où en est la lecture dans les campagnes françaises de 2024 ? En février 1967, l'ORTF diffusait un numéro de sa Bibliothèque de poche, dans lequel le journaliste disparu en 2012, Michel Polac, partait à la rencontre de bergers pour discuter de leurs lectures. ActuaLitté reprend le principe à l'occasion du Salon de l'Agriculture, en interrogeant des acteurs du secteur primaire, afin de vérifier : où en est le rapport au livre dans les campagnes de 2024 ? 01/03/2024, 18:53 À la loupe Edito Plutôt BFM que CNews : Isabelle Saporta, bientôt la porte ? Dans quel monde une salariée dénigrerait publiquement l’une des sociétés de son employeur, sans se faire tirer l’oreille ? Mieux : présenterait comme plus brillante une entreprise concurrente, du même secteur d’activité ? Eh bien… soit les anti-Bolloré reverront leur copie quant aux “méthodes” (censure, liberté de parole brimée, etc.) chez Vivendi… Soit Isabelle Saporta prépare son départ de chez Fayard ? 29/02/2024, 15:42 À la loupe Tribunes "Les IA génératives menacent aujourd’hui l’activité des auteurs des arts visuels" L'ADAGP l'affirme : « Les systèmes d’intelligence artificielle (IA) générative, capables de produire instantanément des contenus visuels à la demande des utilisateurs, menacent aujourd’hui l’activité des auteurs des arts visuels. » En réaction à ce constat, la société de perception et de répartition des droits d'auteur a publié une déclaration générale d’opposition. Elle s'explique dans un communiqué, reproduit ici par ActuaLitté. 23/02/2024, 17:08 À la loupe Tests Librimania : le jeu que toute l'édition va s'arracher #Noshorizonsdesirables – Foin des IUT et autres Masters pros Métiers du livre : voici le futur compagnon et prochain best-seller en librairie — s’il est un jour commercialisé — Librimania plonge les joueurs dans l’univers impitoyable… du monde du livre. Accrochez-vous à un dictionnaire ou une encyclopédie, ça décoiffe ! 21/02/2024, 19:22 À la loupe Tribunes Mort d'Alexeï Navalny : “Il n’a jamais reculé devant le pouvoir” Le décès d’Alexeï Navalny, survenu ce 16 février au centre pénitentiaire de Kharp à l'âge de 47 ans, provoque un soulèvement — et les regards fusent vers Vladimir Poutine, qui se serait définitivement débarrassé d’un opposant. Le Pen Club français a diffusé un hommage, ici proposé en intégralité. 17/02/2024, 10:49 À la loupe Humeurs Une nuit dans une yourte kirghize, bercés par la pluie #AVeloEntreLesLignes — Partis à la conquête de nouveaux horizons, Zoé David-Rigot et Jaroslav Kocourek pédalent à travers une odyssée littéraire. Leur défi ? Explorer le plus grand nombre possible de librairies sur un itinéraire qui les mène à vélo de Paris jusqu'à Oulan-Bator. Ils partagent avec ActuaLitté leurs aventures et découvertes dans ce journal de voyage. 16/02/2024, 15:24 À la loupe Tribunes L'étude sur le partage de la valeur du SNE, “un éclairage partiel et biaisé” Dévoilée le 1er février dernier, l'étude sur le partage de la valeur du livre, commandée par le Syndicat national de l'édition, n'a pas vraiment convaincu. La quasi-totalité des organisations d'auteurs ont dénoncé ses résultats, assimilés à une pure et simple tentative de manipulation. L'Association des traducteurs littéraires français (ATLF) ajoute sa voix revendicative, dans un texte reproduit ci-dessous. 15/02/2024, 10:03 À la loupe Tribunes Une étude sur les revenus qui “ne reflète en rien la réalité” des auteurs Le Syndicat national de l'édition, organisation patronale du secteur, a présenté le 1er février les données de son étude sur le partage de la valeur du livre entre les maisons d'édition et les auteurs. Une étude dont les méthodes et la présentation des résultats ont été largement décriées par les auteurs et leurs représentants. Le Conseil Permanent des Écrivains (CPE), dans un texte reproduit ci-dessous, signifie ses propres réserves, mais aussi ses attentes vis-à-vis du ministère de la Culture. 14/02/2024, 11:46 À la loupe Humeurs À vélo entre les montagnes et les yourtes #AVeloEntreLesLignes — Zoé David-Rigot et Jaroslav Kocourek se sont lancés dans une aventure exceptionnelle, celle de parcourir la distance entre Paris et Oulan-Bator à vélo. Tout au long de leur parcours, ils font escale dans autant de librairies que possible. Leur odyssée est couverte par ActuaLitté, qui partage leurs histoires au fur et à mesure. 14/02/2024, 10:33 À la loupe Humeurs Livres audio : saga, c'est plus fort que toi Dans un nouvel article, Nathan Hull, responsable de la stratégie de Beat Technology, s'intéresse aux sagas littéraires et à leur capacité à captiver les lecteurs sur le long terme. Comment expliquer ce succès durable ? Et, surtout, comment le reproduire dans un domaine bien particulier, celui du livre audio numérique ? 13/02/2024, 12:48 À la loupe Humeurs “Il faut tenir sur le fil, à la frontière, et c’est de là que nait la littérature” #PrixFrontieres2024 – L'édition 2024 du prix Frontières a été lancée, avec la liste des 10 titres retenus. La lauréate de 2023, la romancière Dima Abdallah avait été été saluée pour son deuxième roman Bleu nuit aux éditions Sabine Wespieser. Présidente d'honneur du jury de cette édition 2024, elle nous délivre un texte, en exclusivité pour ActuaLitté, sur ce terme étrange... frontières... 12/02/2024, 16:35 À la loupe Edito Durant les JO, il est important de rester à Paris... en télétravail Les usagers occasionnels du métro parisien n’ont pas manqué la campagne de communication orchestrée dans les rames : l’invitation au RTT – Reste chez Toi Travailler. À l’approche des Jeux olympiques, les injonctions contradictoires pleuvent : rester ou ne pas rester sur Paris, prendre ou ne pas prendre les transports, travailler ou ne pas travailler… On ne fait pas d’Hamlet, sans casser des noeuds…. 12/02/2024, 14:46 À la loupe Tribunes “La juste rémunération des auteurs et autrices est cruciale” La Ligue des auteurs professionnels a pris connaissance de l'étude du Syndicat National de l'Édition (SNE) publiée le 1er février dernier. Dans une tribune adressée à ActuaLitté, l'organisation remet en cause la méthodologie, déjà amplement pointée. Leur texte est ici diffusé dans son intégralité. 06/02/2024, 11:03 À la loupe Tribunes L'étude irréelle où “les éditeurs sont moins payés que les auteurs” Au moment même où l’Europe envisage de légiférer sur un statut professionnel pour les auteurs, incluant notamment de meilleures rémunérations et une lutte contre les contrats abusifs, le Syndicat national de l’édition a publié une enquête sur « le partage de la valeur entre auteurs et éditeurs ». Or, la présentation des données a révélé un biais tel qu’il laisse entendre que les éditeurs sont moins bien payés que les auteurs. La Charte des auteurs et illustrateurs jeunesse réagit dans les colonnes de ActuaLitté. 04/02/2024, 10:15 À la loupe Tribunes L'industrie du livre redoute le projet européen sur les délais de paiement En Belgique, l'interprofession s'est regroupée pour interpeller les députés européens, sur la question des retards de paiements. Le projet qu’examinent en effet le Parlement et le Conseil ramènerait à 30 jours le délai maximum. Une modification que l’industrie du livre ne supportera pas sans de lourdes conséquences. 31/01/2024, 10:19 À la loupe Reportages “Nutri-score” et autres projets d’avenir pour une édition écologique D’après Erri de Luca, l’impossible caractérise « ce qui n’a pas encore été fait » (trad. Danièle Valin). La chaîne du livre — mais par cette dénomination, ne réduit-on pas ses acteurs à des maillons ignorants les uns des autres ? — était conviée à une journée de réflexion, ce 29 janvier. Dans les locaux du groupe Bayard, on se réunissait pour « décarboner le livre et l’édition ».  29/01/2024, 20:08 À la loupe Humeurs Au-delà de la polémique Tesson, “faire vivre le Printemps des poètes” « Au-delà des polémiques de toutes sortes, il nous appartient de faire vivre cette édition du Printemps des Poètes coûte que coûte, et de penser d'abord au public », déclarent les cofondateurs des éditions Doucey. Cette réaction intervient peu après l'annonce de la démission de Sophie Nauleau, directrice artistique du Printemps des Poètes.  27/01/2024, 12:21 À la loupe Humeurs Vers le Kirghizistan, à la recherche de la fraicheur perdue #AVeloEntreLesLignes — C'est l'aventure de Zoé David-Rigot et Jaroslav Kocourek, deux cyclistes qui se sont donné pour challenge de rejoindre Oulan-Bator depuis Paris, à la force de leurs cuisses. En chemin, ils visitent autant de librairies qu'ils peuvent. ActuaLitté suit ce périple en publiant leurs récits. 26/01/2024, 14:40 À la loupe Humeurs “Nous croyons que la poésie peut captiver les coeurs” Partout dans le monde, la poésie peut exprimer l'indicible, sans en avoir l'air. Cette puissance en fait aussi une cible de tous les extrêmes, et en particulier des régimes liberticides. Dans un texte prononcé à l'Université de Lille, le 22 mars 2024, la poète, écrivaine et militante des droits des femmes en Afghanistan Somaia Ramish célèbre la poésie et appelle à la défendre, encore et toujours. 05/04/2024, 12:28 À la loupe Tribunes Livres pour malvoyants : “Il ne suffit pas d’agrandir la police de caractères” La Librairie des Grands Caractères, basée dans le 5e arrondissement de Paris, publie ici son « coup de gueule » sur certains éditeurs dont les pratiques lui semblent douteuses. L'établissement pointe notamment le fait que certaines règles à suivre dans l'édition de livres pour malvoyants sont trop régulièrement ignorées par des acteurs du secteur. 02/04/2024, 13:15 À la loupe Reportages Pause soupe de nouilles à minuit : ultimes heures avant la Mongolie #AVeloEntreLesLignes – Partir à la découverte du plus grand nombre de librairies possible, entre Paris et Oulan-Bator, le défi est de taille. À vélo, c'est confirmé : c'est de la folie douce. C’est pourtant l’aventure que Zoé David-Rigot et Jaroslav Kocourek ont démarrée en août 2022. ActuaLitté les accompagne, en publiant leur récit de ce périple, À vélo, entre les lignes. 01/04/2024, 08:03 À la loupe Humeurs “J’habite une maison vieille qui embrasse les formes de mon corps” Carnetdebord – Pour la rentrée littéraire 2024, les éditions du Tripode publieront le nouveau roman d'Audrée Wilhelmy. Pour accompagner cette parution, la romancière a trouvé dans nos colonnes une place à part : un Carnet de Bord pour raconter cette aventure, jusqu'aux librairies. 30/03/2024, 17:05 À la loupe Tribunes Pour un renouveau documentaire dans les universités françaises   L'Association des Directeurs et des personnels de direction des Bibliothèques Universitaires et de la Documentation (ADBU) et le Syndicat National de l'Édition (SNE) s'unissent pour interpeller le gouvernement et les autorités sur la nécessité critique d'un élan majeur en faveur des ressources documentaires. Ils insistent sur la nécessité d'investissements immédiats pour assurer le développement d'une documentation universitaire compétitive au niveau européen, et de maintenir la France au cœur des débats scientifiques et éducatifs mondiaux. 27/03/2024, 12:51 À la loupe Tribunes IA : un rapport “équilibré” remis à Emmanuel Macron Alors que la « Commission IA » remettait son rapport au Président de la République le 13 mars 2024, les réactions continuent d'affluer concernant le positionnement de la France face aux enjeux de l'intelligence artificielle. Si des associations de traducteurs telles que En Chair et en Os et l'Association des traducteurs littéraires de France appelaient à sauver « le geste humain », une nouvelle tribune d'un collectif rassemblant divers acteurs des milieux culturels salue, elle, « un rapport équilibré ». 27/03/2024, 10:08 À la loupe Humeurs Peau-de-sang, expérience physique et sensorielle: “Bienvenue, Audrée...” Carnetdebord – Au cours des prochaines semaines, ActuaLitté accueillera le Carnet de Bord d'Audrée Wilhelmy. Romancière québécoise, elle publiera son prochain ouvrage aux éditions du Tripode. Ce seront tout à la fois les récits d'une attente, d'un espoir, d'une envie. Ce seront les récits d'un à-venir. En guise de prélude, Frédéric Martin, fondateur de la maison, nous présente cette autrice, d'ores et déjà adoptée. 27/03/2024, 08:01 À la loupe Reportages Annonciation faite à Dati : les auteurs ressuscitent le rapport Racine Devant la Comédie française, ce 25 mars – date de l'annonce à Marie de sa maternité divine –, ils étaient près de deux cents présents pour le retour d’un vieux compagnon. La première Nuit des auteurs et autrices aura vibré au son des les mariachis qui abreuvaient la place Colette de musiques. La promesse d’un rassemblement politique, collectif et festif était tenue… mais les soirées parisiennes prennent parfois des tournures inattendues. 26/03/2024, 11:56 À la loupe Tribunes “Produire un livre écologique n’est pas possible” La Volte annonce donc son vingtième anniversaire : vingt ans d'aventures éditoriales où se retrouvent des histoires d'émancipation, de la science-fiction sociale et politique, avec une passion pour les jeux de langage. Elle avait déjà annoncé en janvier qu'elle renforcerait cette année son engagement écologique et affirmerait son identité visuelle. Maintenant, place aux projets. 23/03/2024, 15:38 À la loupe Reportages La zone secrète entre Russie et Chine, blague de géographe #AVeloEntreLesLignes – Partir à la découverte du plus grand nombre de librairies possible, entre Paris et Oulan-Bator, le défi est de taille. À vélo, c'est confirmé : c'est de la folie douce. C’est pourtant l’aventure que Zoé David-Rigot et Jaroslav Kocourek ont démarrée en août 2022. ActuaLitté les accompagne, en publiant leur récit de ce périple, À vélo, entre les lignes. 23/03/2024, 15:25 À la loupe Reportages Sacrilège ! Une histoire française de l’offense au pouvoir   Aux Archives nationales à l’Hôtel de Soubise, du 20 mars au 1er juillet prochain, plongez au cœur de l'histoire tumultueuse du sacrilège, où le spirituel et le temporel travaillent à ne faire qu’un, mais lequel ? Le dernier discours de Robespierre, l'œil de Léon Gambetta, le testament de Louis XVI… Des trésors historiques et autres documents d'archives inédits, pour une expérience solennelle, et parfois moqueuse, aux frontières du divin et du pouvoir. 22/03/2024, 17:32 À la loupe Tribunes “Faire front commun face à la massification annoncée des IA dans le travail” Après le collectif En Chair et en Os, c'est au tour de l'Association des traducteurs littéraires de France (ATLF) de réagir au rapport, IA : notre ambition pour la France, remis au Président de la République le 13 mars dernier. Ces membres, après l'avoir lu « avec beaucoup de colère », appellent les pouvoirs publics à « ne pas céder aux sirènes de la compétitivité mondiale, et l’ensemble des artistes-auteurs à faire front commun face à la massification annoncée des intelligences artificielles dans leur travail ». 22/03/2024, 13:31 À la loupe Tribunes Bastien Vivès, condamnable ou martyr de la liberté d'expression ? L’Observatoire de la liberté de création (OLC) dénonce « une loi absurde et son application ubuesque » dans l’affaire Bastien Vivès. Dans une tribune, ses membres justifient leur positionnement : à chacun de se faire un point de vue... 22/03/2024, 11:26 À la loupe Tribunes Pour une traduction humaine : “Il en va de l'avenir de nos professions” Quelques jours après la présentation du rapport de la commission IA au Président de la République, qui en salue les recommandations prônant le tout-IA dans de nombreux domaines, le collectif En Chair et en Os, « pour une traduction humaine », s'adresse aujourd'hui à toute l'édition, et appelle le monde du livre et de la culture à se mobiliser pour préserver le geste humain, sans céder au technosolutionnisme. 18/03/2024, 11:42 À la loupe Reportages De l'Altaï russe à la Mongolie en passant par l'édition kirghize #AVeloEntreLesLignes — Zoé David-Rigot et Jaroslav Kocourek ont entrepris un voyage en vélo entre Paris et Oulan-Bator en août 2022, avec l'objectif de visiter le maximum de librairies sur leur route. ActuaLitté documentera cette expédition en publiant le récit intitulé "À vélo, entre les lignes". 17/03/2024, 12:13 À la loupe Tribunes Expression, publication, lecture : des libertés à défendre Depuis la Foire du Livre de Londres, cinq organisations internationales représentant les auteurs, éditeurs, libraires et bibliothécaires cosignent une déclaration. Ce texte, reproduit en intégralité ci-dessous, constitue un appel aux gouvernements et aux sociétés dans leur ensemble à veiller sur des libertés fondamentales autour des textes et de leurs auteurs : expression, publication et lecture. 14/03/2024, 11:14 À la loupe Tribunes Traduire par l'IA, le risque d'“un appauvrissement sensible de la langue” Face à la montée de l'intelligence artificielle dans le domaine de la traduction, l'Association des Autrices et Auteurs de Suisse (AdS) tire la sonnette d'alarme. Lors de son 15e Symposium suisse, l'association a publié une prise de position vigoureuse, soulignant les limites de l'IA en matière de traduction littéraire et réclamant une régulation claire pour protéger les droits et la valeur du travail humain. 06/03/2024, 12:54 À la loupe Enquêtes Moon Knight, justicier lunaire et passablement tordu L’identité secrète est le propre du super héros – ça et les collants trop moulants. Apparu dans Werewolf by Night #32 en 1975, Marc Spector fêtera ses 50 ans de lutte contre le crime à New York : il protège les voyageurs, chers au dieu égyptien qui l’a choisi pour avatar. Non sans l’avoir sauvé de la mort. Mais ce personnage, atteint d’un trouble dissociatif, coexiste mentalement avec trois autres personnes. De quoi en faire un justicier atypique, dont les méthodes effraient. 06/03/2024, 12:16 À la loupe Reportages Où en est la lecture dans les campagnes françaises de 2024 ? En février 1967, l'ORTF diffusait un numéro de sa Bibliothèque de poche, dans lequel le journaliste disparu en 2012, Michel Polac, partait à la rencontre de bergers pour discuter de leurs lectures. ActuaLitté reprend le principe à l'occasion du Salon de l'Agriculture, en interrogeant des acteurs du secteur primaire, afin de vérifier : où en est le rapport au livre dans les campagnes de 2024 ? 01/03/2024, 18:53 À la loupe Edito Plutôt BFM que CNews : Isabelle Saporta, bientôt la porte ? Dans quel monde une salariée dénigrerait publiquement l’une des sociétés de son employeur, sans se faire tirer l’oreille ? Mieux : présenterait comme plus brillante une entreprise concurrente, du même secteur d’activité ? Eh bien… soit les anti-Bolloré reverront leur copie quant aux “méthodes” (censure, liberté de parole brimée, etc.) chez Vivendi… Soit Isabelle Saporta prépare son départ de chez Fayard ? 29/02/2024, 15:42 À la loupe Tribunes "Les IA génératives menacent aujourd’hui l’activité des auteurs des arts visuels" L'ADAGP l'affirme : « Les systèmes d’intelligence artificielle (IA) générative, capables de produire instantanément des contenus visuels à la demande des utilisateurs, menacent aujourd’hui l’activité des auteurs des arts visuels. » En réaction à ce constat, la société de perception et de répartition des droits d'auteur a publié une déclaration générale d’opposition. Elle s'explique dans un communiqué, reproduit ici par ActuaLitté. 23/02/2024, 17:08 À la loupe Tests Librimania : le jeu que toute l'édition va s'arracher #Noshorizonsdesirables – Foin des IUT et autres Masters pros Métiers du livre : voici le futur compagnon et prochain best-seller en librairie — s’il est un jour commercialisé — Librimania plonge les joueurs dans l’univers impitoyable… du monde du livre. Accrochez-vous à un dictionnaire ou une encyclopédie, ça décoiffe ! 21/02/2024, 19:22 À la loupe Tribunes Mort d'Alexeï Navalny : “Il n’a jamais reculé devant le pouvoir” Le décès d’Alexeï Navalny, survenu ce 16 février au centre pénitentiaire de Kharp à l'âge de 47 ans, provoque un soulèvement — et les regards fusent vers Vladimir Poutine, qui se serait définitivement débarrassé d’un opposant. Le Pen Club français a diffusé un hommage, ici proposé en intégralité. 17/02/2024, 10:49 À la loupe Humeurs Une nuit dans une yourte kirghize, bercés par la pluie #AVeloEntreLesLignes — Partis à la conquête de nouveaux horizons, Zoé David-Rigot et Jaroslav Kocourek pédalent à travers une odyssée littéraire. Leur défi ? Explorer le plus grand nombre possible de librairies sur un itinéraire qui les mène à vélo de Paris jusqu'à Oulan-Bator. Ils partagent avec ActuaLitté leurs aventures et découvertes dans ce journal de voyage. 16/02/2024, 15:24 À la loupe Tribunes L'étude sur le partage de la valeur du SNE, “un éclairage partiel et biaisé” Dévoilée le 1er février dernier, l'étude sur le partage de la valeur du livre, commandée par le Syndicat national de l'édition, n'a pas vraiment convaincu. La quasi-totalité des organisations d'auteurs ont dénoncé ses résultats, assimilés à une pure et simple tentative de manipulation. L'Association des traducteurs littéraires français (ATLF) ajoute sa voix revendicative, dans un texte reproduit ci-dessous. 15/02/2024, 10:03 À la loupe Tribunes Une étude sur les revenus qui “ne reflète en rien la réalité” des auteurs Le Syndicat national de l'édition, organisation patronale du secteur, a présenté le 1er février les données de son étude sur le partage de la valeur du livre entre les maisons d'édition et les auteurs. Une étude dont les méthodes et la présentation des résultats ont été largement décriées par les auteurs et leurs représentants. Le Conseil Permanent des Écrivains (CPE), dans un texte reproduit ci-dessous, signifie ses propres réserves, mais aussi ses attentes vis-à-vis du ministère de la Culture. 14/02/2024, 11:46 À la loupe Humeurs À vélo entre les montagnes et les yourtes #AVeloEntreLesLignes — Zoé David-Rigot et Jaroslav Kocourek se sont lancés dans une aventure exceptionnelle, celle de parcourir la distance entre Paris et Oulan-Bator à vélo. Tout au long de leur parcours, ils font escale dans autant de librairies que possible. Leur odyssée est couverte par ActuaLitté, qui partage leurs histoires au fur et à mesure. 14/02/2024, 10:33 À la loupe Humeurs Livres audio : saga, c'est plus fort que toi Dans un nouvel article, Nathan Hull, responsable de la stratégie de Beat Technology, s'intéresse aux sagas littéraires et à leur capacité à captiver les lecteurs sur le long terme. Comment expliquer ce succès durable ? Et, surtout, comment le reproduire dans un domaine bien particulier, celui du livre audio numérique ? 13/02/2024, 12:48 À la loupe Humeurs “Il faut tenir sur le fil, à la frontière, et c’est de là que nait la littérature” #PrixFrontieres2024 – L'édition 2024 du prix Frontières a été lancée, avec la liste des 10 titres retenus. La lauréate de 2023, la romancière Dima Abdallah avait été été saluée pour son deuxième roman Bleu nuit aux éditions Sabine Wespieser. Présidente d'honneur du jury de cette édition 2024, elle nous délivre un texte, en exclusivité pour ActuaLitté, sur ce terme étrange... frontières... 12/02/2024, 16:35 À la loupe Edito Durant les JO, il est important de rester à Paris... en télétravail Les usagers occasionnels du métro parisien n’ont pas manqué la campagne de communication orchestrée dans les rames : l’invitation au RTT – Reste chez Toi Travailler. À l’approche des Jeux olympiques, les injonctions contradictoires pleuvent : rester ou ne pas rester sur Paris, prendre ou ne pas prendre les transports, travailler ou ne pas travailler… On ne fait pas d’Hamlet, sans casser des noeuds…. 12/02/2024, 14:46 À la loupe Tribunes “La juste rémunération des auteurs et autrices est cruciale” La Ligue des auteurs professionnels a pris connaissance de l'étude du Syndicat National de l'Édition (SNE) publiée le 1er février dernier. Dans une tribune adressée à ActuaLitté, l'organisation remet en cause la méthodologie, déjà amplement pointée. Leur texte est ici diffusé dans son intégralité. 06/02/2024, 11:03 À la loupe Tribunes L'étude irréelle où “les éditeurs sont moins payés que les auteurs” Au moment même où l’Europe envisage de légiférer sur un statut professionnel pour les auteurs, incluant notamment de meilleures rémunérations et une lutte contre les contrats abusifs, le Syndicat national de l’édition a publié une enquête sur « le partage de la valeur entre auteurs et éditeurs ». Or, la présentation des données a révélé un biais tel qu’il laisse entendre que les éditeurs sont moins bien payés que les auteurs. La Charte des auteurs et illustrateurs jeunesse réagit dans les colonnes de ActuaLitté. 04/02/2024, 10:15 À la loupe Tribunes L'industrie du livre redoute le projet européen sur les délais de paiement En Belgique, l'interprofession s'est regroupée pour interpeller les députés européens, sur la question des retards de paiements. Le projet qu’examinent en effet le Parlement et le Conseil ramènerait à 30 jours le délai maximum. Une modification que l’industrie du livre ne supportera pas sans de lourdes conséquences. 31/01/2024, 10:19 À la loupe Reportages “Nutri-score” et autres projets d’avenir pour une édition écologique D’après Erri de Luca, l’impossible caractérise « ce qui n’a pas encore été fait » (trad. Danièle Valin). La chaîne du livre — mais par cette dénomination, ne réduit-on pas ses acteurs à des maillons ignorants les uns des autres ? — était conviée à une journée de réflexion, ce 29 janvier. Dans les locaux du groupe Bayard, on se réunissait pour « décarboner le livre et l’édition ».  29/01/2024, 20:08 À la loupe Humeurs Au-delà de la polémique Tesson, “faire vivre le Printemps des poètes” « Au-delà des polémiques de toutes sortes, il nous appartient de faire vivre cette édition du Printemps des Poètes coûte que coûte, et de penser d'abord au public », déclarent les cofondateurs des éditions Doucey. Cette réaction intervient peu après l'annonce de la démission de Sophie Nauleau, directrice artistique du Printemps des Poètes.  27/01/2024, 12:21 À la loupe Humeurs Vers le Kirghizistan, à la recherche de la fraicheur perdue #AVeloEntreLesLignes — C'est l'aventure de Zoé David-Rigot et Jaroslav Kocourek, deux cyclistes qui se sont donné pour challenge de rejoindre Oulan-Bator depuis Paris, à la force de leurs cuisses. En chemin, ils visitent autant de librairies qu'ils peuvent. ActuaLitté suit ce périple en publiant leurs récits. 26/01/2024, 14:40 Top Articles La suite de Shōgun, la saga culte derrière la série Disney La Grande Librairie : ce que “partir” veut dire Le Prix des Libraires 2024 dévoile sa liste finale Étude Babelio : les lecteurs de romance en France Lettre d'information Flux RSS Contact Qui sommes nous ? Mentions légales Connexion Politique de confidentialité Charte commentaires Furet.com Decitre.fr Edistat Publier un livre Depositphotos Tendances et Célébrités © 2007 - 2024 - Actualitte.com. Tous droits réservés.

      Rappel de la source primaire

    1. This suggests that contemporaries regarded physical injuries as a species of insult; just as lying with a man’s female slave was an affront to his honour, so too was breaking his rib.28

      So rather than having offences within Æthelberhts code. it would be more proper to refer to them as being insults, for which a compensatory sum was attached.

    1. Author Response

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

      eLife assessment

      This fundamental study provides an unprecedented understanding of the roles of different combinations of NaV channel isoforms in nociceptors' excitability, with relevance for the design of better strategies targeting NaV channels to treat pain. Although the experimental combination of electrophysiological, modeling, imaging, molecular biology, and behavioral data is convincing and supports the major claims of the work, some conclusions need to be strengthened by further evidence or discussion. The work may be of broad interest to scientists working on pain, drug development, neuronal excitability, and ion channels.

      Reviewer #1 (Public Review):

      Summary:

      In this work, Xie, Prescott, and colleagues have reevaluated the role of Nav1.7 in nociceptive sensory neuron excitability. They find that nociceptors can make use of different sodium channel subtypes to reach equivalent excitability. The existence of this degeneracy is critical to understanding neuronal physiology under normal and pathological conditions and could explain why Nav subtype-selective drugs have failed in clinical trials. More concretely, nociceptor repetitive spiking relies on Nav1.8 at DIV0 (and probably under normal conditions in vivo), but on Nav1.7 and Nav1.3 at DIV4-7 (and after inflammation in vivo).

      The conclusions of this paper are mostly well supported by data, and these findings should be of broad interest to scientists working on pain, drug development, neuronal excitability, and ion channels.

      Strengths:

      (1.1) The authors have employed elegant electrophysiology experiments (including specific pharmacology and dynamic clamp) and computational simulations to study the excitability of a subpopulation of DRGs that would very likely match with nociceptors (they take advantage of using transgenic mice to detect Nav1.8-expressing neurons). They make a strong point showing the degeneracy that occurs at the ion channel expression level in nociceptors, adding this new data to previous observations in other neuronal types. They also demonstrate that the different Nav subtypes functionally overlap and are able to interchange their "typical" roles in action potential generation. As Xie, Prescott, and colleagues argue, the functional implications of the degenerate character of nociceptive sensory neuron excitability need to be seriously taken into account regarding drug development and clinical trials with Nav subtype-selective inhibitors.

      Weaknesses:

      (1.2) The next comments are minor criticisms, as the major conclusions of the paper are well substantiated. Most of the results presented in the article have been obtained from experiments with DRG neuron cultures, and surely there is a greater degree of complexity and heterogeneity about the degeneracy of nociceptors excitability in the "in vivo" condition. Indeed, the authors show in Figures 7 and 8 data that support their hypothesis and an increased Nav1.7's influence on nociceptor excitability after inflammation, but also a higher variability in the nociceptors spiking responses. On the other hand, DRG neurons targeted in this study (YFP (+) after crossing with Nav1.8-Cre mice) are >90% nociceptors, but not all nociceptors express Nav1.8 in vivo. As shown by Li et al., 2016 ("Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity"), there is a high heterogeneity of neuron subtypes within sensory neurons. Therefore, some caution should be taken when translating the results obtained with the DRG neuron cultures to the more complex "in vivo" panorama.

      We agree that most but not all Nav1.8+ DRG cells are nociceptors and that not all nociceptors express Nav1.8. We targeted small neurons that also express (or at some point expressed) Nav1.8, thus excluding larger neurons that express Nav1.8. This allowed us to hone in on a relatively homogeneous set of neurons, which is crucial when testing different neurons to compare between conditions (as opposed to testing longitudinally in the same neuron, which is not feasible). We expect all neurons are degenerate but likely on the basis of different ion channel combinations. Indeed, even within small Nav1.8+ neurons, other channels that we did not consider likely contribute to the degenerate regulation (as now better reflected in the revised Discussion).

      That said, there are multiple sources of heterogeneity. We suspect that heterogeneity is more increased after inflammation than after axotomy because all DRG neurons experience axotomy when cultured whereas neurons experience inflammation differently in vivo depending on whether their axon innervates the inflamed area (now explained on lines 214-215). This is not so much about whether the insult occurs in vivo or in vitro, but about how homogeneously neurons are affected by the insult. Granted, neurons are indeed more likely to be heterogeneously affected in vivo since conditions are more complex. But our goal in testing PF-71 in behavioral tests (Fig. 8) was to show that changes observed in nociceptor excitability in Figure 7, despite heterogeneity, were predictive of changes in drug efficacy. In short, we establish Nav interchangeability by comparing neurons in culture (Figs 1-6), but we then show that similar Nav shifts can develop in vivo (Fig 7) with implications for drug efficacy (Fig 8). Such results should alert readers to the importance of degeneracy for drug efficacy (which is our main goal) even without a complete picture of nociceptor degeneracy or DRG neuron heterogeneity. Additions to the Discussion (lines 248-259, 304-308) are intended to highlight these considerations.

      (1.3) Although the authors have focused their attention on Nav channels, it should be noted that degeneracy concerning other ion channels (such as potassium ion channels) could also impact the nociceptor excitability. The action potential AHP in Figure 1, panel A is very different comparing the DIV0 (blue) and DIV4-7 examples. Indeed, the conductance density values for the AHP current are higher at DIV0 than at DIV7 in the computational model (supplementary table 5). The role of other ion channels in order to obtain equivalent excitability should not be underestimated.

      We completely agree. We focused on Nav channels because of our initial observation with TTX and because of industry’s efforts to develop Nav subtype-selective inhibitors, whose likelihood of success is affected by the changes we report. But other channels are presumably changing, especially given observed changes in the AHP shape (now mentioned on lines 304-308). Investigation should be expanded to include these other channels in future studies.

      Reviewer #2 (Public Review):

      Summary:

      The authors have noted in preliminary work that tetrodotoxin (TTX), which inhibits NaV1.7 and several other TTX-sensitive sodium channels, has differential effects on nociceptors, dramatically reducing their excitability under certain conditions but not under others. Partly because of this coincidental observation, the aim of the present work was to re-examine or characterize the role of NaV1.7 in nociceptor excitability and its effects on drug efficacy. The manuscript demonstrates that a NaV1.7-selective inhibitor produces analgesia only when nociceptor excitability is based on NaV1.7. More generally and comprehensively, the results show that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and NaV expression of different NaV subtypes (NaV 1.3/1.7 and 1.8). This can cause widespread changes in the role of a particular subtype over time. The degenerate nature of nociceptor excitability shows functional implications that make the assignment of pathological changes to a particular NaV subtype difficult or even impossible.

      Thus, the analgesic efficacy of NaV1.7- or NaV1.8-selective agents depends essentially on which NaV subtype controls excitability at a given time point. These results explain, at least in part, the poor clinical outcomes with the use of subtype-selective NaV inhibitors and therefore have major implications for the future development of Nav-selective analgesics.

      Strengths:

      (2.1) The above results are clearly and impressively supported by the experiments and data shown. All methods are described in detail, presumably allow good reproducibility, and were suitable to address the corresponding question. The only exception is the description of the computer model, which should be described in more detail.

      We failed to report basic information such as the software, integration method and time step in the original text. This information is now provided on lines 476-477. Notably, the full code is available on ModelDB plus all equations including the values for all gating parameters are provided in Supplementary Table 5 and values for maximal conductance densities for DIV0 and DIV7 models are provided in Supplementary Table 6. Changes in conductance densities to simulate different pharmacological conditions are reported in the relevant figure legends (now shown in red). We did not include model details in the main text to avoid disrupting the flow of the presentation, but all the model details are reported in the Methods, tables and/or figure legends.

      (2.2) The results showing that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and expression of different NaV subtypes are of great importance in the fields of basic and clinical pain research and sodium channel physiology and pharmacology, but also for a broad readership and community. The degenerate nature of nociceptor excitability, which is clearly shown and well supported by data has large functional implications. The results are of great importance because they may explain, at least in part, the poor clinical outcomes with the use of subtype-selective NaV inhibitors and therefore have major implications for the future development of Nav-selective analgesics.

      In summary, the authors achieved their overall aim to enlighten the role of NaV1.7 in nociceptor excitability and the effects on drug efficacy. The data support the conclusions, although the clinical implications could be highlighted in a more detailed manner.

      Weaknesses:

      As mentioned before, the results that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and NaV expression of different NaV subtypes are impressive. However, there is some "gap" between the DRG culture experiments and acutely dissociated DRGs from mice after CFA injection. In the extensive experiments with cultured DRG neurons, different time points after dissociation were compared. Although it would have been difficult for functional testing to examine additional time points (besides DIV0 and DIV47), at least mRNA and protein levels should have been determined at additional time points (DIV) to examine the time course or whether gene expression (mRNA) or membrane expression (protein) changes slowly and gradually or rapidly and more abruptly.

      Characterizing the time course of NaV expression changes is worthwhile but, insofar as such details are not necessary to establish that excitability is degenerate, it was not include in the current study. Furthermore, since mRNA levels do not parallel the functional changes in Nav1.7 (Figure 6A), we do not think it would be helpful to measure mRNA levels at intermediate time points. Measuring protein levels would be more informative, however, as now explained on lines 362-369, neurons were recorded at intermediate time points in initial experiments and showed a lot of variability. Methods that could track fluorescently-tagged NaV channels longitudinally (i.e. at different time points in the same cell) would be well suited for this sort of characterization, but will invariably lead to more questions about membrane trafficking, phosphorylation, etc. We agree that a thorough characterization would be interesting but we think it is best left for a future study.

      It would also be interesting to clarify whether the changes that occur in culture (DIV0 vs. DIV47) are accompanied by (pro-)inflammatory changes in gene and protein expression, such as those known for nociceptors after CFA injection. This would better link the following data demonstrating that in acutely dissociated nociceptors after CFA injection, the inflammationinduced increase in NaV1.7 membrane expression enhances the effect of (or more neurons respond to) the NaV1.7 inhibitor PF-71, whereas fewer CFA neurons respond to the NaV1.8 inhibitor PF-24.

      These are some of the many good questions that emerge from our results. We are not particularly keen to investigate what happens over several days in culture, since this is not so clinically relevant, but it would be interesting to compare changes induced by nerve injury in vivo (which usually involves neuroinflammatory changes) and changes induced by inflammation. Many previous studies have touched on such issues but we are cautious about interpreting transcriptional changes, and of course all of these changes need to be considered in the context of cellular heterogeneity. It would be interesting to decipher if changes in NaV1.7 and NaV1.8 are directly linked so that an increase in one triggers a decrease in the other, and vice versa. But of course many other channels are also likely to change (as discussed above), and they too warrant attention, which makes the problem quite difficult. We look forward to tackling this in future work.

      The results shown explain, at least in part, the poor clinical outcomes with the use of subtypeselective NaV inhibitors and therefore have important implications for the future development of Nav-selective analgesics. However, this point, which is also evident from the title of the manuscript, is discussed only superficially with respect to clinical outcomes. In particular, the promising role of NaV1.7, which plays a role in nociceptor hyperexcitability but not in "normal" neurons, should be discussed in light of clinical results and not just covered with a citation of a review. Which clinical results of NaV1.7-selective drugs can now be better explained and how?

      We wish to avoid speculating on which particular clinical results are better explained because our study was not designed for that. Instead, our take-home message (which is well supported; see Discussion on lines 309-321) is that NaV1.7-selective drugs may have a variable clinical effect because nociceptors’ reliance on NaV1.7 is itself variable – much more than past studies would have readers believe. At the end of the results (line 235), which is, we think, what prompted the reviewer’s comment, we point to the Discussion. The corollary is that accounting for degeneracy could help account for variability in drug efficacy, which would of course be beneficial. The challenge (as highlighted in the Abstract, lines 21-22) is that identifying the dominant Nav subtype to predict drug efficacy is difficult. We certainly don’t have all the answers, but we hope our results will point readers in a new direction to help answer such questions.

      Another point directly related to the previous one, which should at least be discussed, is that all the data are from rodents, or in this case from mice, and this should explain the clinical data in humans. Even if "impediment to translation" is briefly mentioned in a slightly different context, one could (as mentioned above) discuss in more detail which human clinical data support the existence of "equivalent excitability through different sodium channels" also in humans.

      We are not aware of human data that speak directly to nociceptor degeneracy but degeneracy has been observed in diverse species; if anything, human neurons are probably even more degenerate based on progressive expansion of ion channel types, splice variants, etc. over evolution. Of course species differences extend beyond degeneracy and are always a concern for translation, because of a species difference in the drug target itself or because preclinical pain testing fails to capture the most clinically important aspects of pain (which we mention on line 35). Line 39 now reiterates that these explanations for translational difficulties are not mutually exclusive, but that degeneracy deserves greater consideration that is has hitherto received. Indeed, throughout our paper we imply that degeneracy may contribute to the clinical failure of Nav subtype-specific drugs, but those failures are certainly not evidence of degeneracy. In the Discussion (line 320-321), we now cite a recent review article on degeneracy in the context of epilepsy, and point out how parallels might help inform pain research. We wish we had a more direct answer to the reviewer’s request; in the absence of this, we hope our results motivate readers to seek out these answers in future research.

      Although speculative, it would be interesting for readers to know whether a treatment regimen based on "time since injury" with NaV1.7 and NaV1.8 inhibitors might offer benefits. Based on the data, could one hypothesize that NaV1.7 inhibitors are more likely to benefit (albeit in the short term) in patients with neuropathic pain with better patient selection (e.g., defined interval between injury and treatment)?

      We like that our data prompt this sort of prediction. However, this is potentially complicated since the injury may be subtle, which is to say that the exact timing may not be known. There are scenarios (e.g. postoperative pain) where the timing of the insult is known, but in other cases (e.g. diabetic neuropathy) the disease process is quite insidious, and different neurons might have progressed through different stages depending on how they were exposed to the insult. Our own experiments with CFA are a case in point. Notwithstanding the potential difficulties about gauging the time course, any way of predicting which Nav subtype is dominant could help more strategically choose which drug to use.

      Reviewer #3 (Public Review):

      Summary:

      In this study, the authors used patch-clamp to characterize the implication of various voltagegated Na+ channels in the firing properties of mouse nociceptive sensory neurons. They report that depending on the culture conditions NaV1.3, NaV1.7, and NaV1.8 have distinct contributions to action potential firing and that similar firing patterns can result from distinct relative roles of these channels. The findings may be relevant for the design of better strategies targeting NaV channels to treat pain.

      Strengths:

      The paper addresses the important issue of understanding, from an interesting perspective, the lack of success of therapeutic strategies targeting NaV channels in the context of pain. Specifically, the authors test the hypothesis that different NaV channels contribute in a plastic manner to action potential firing, which may be the reason why it is difficult to target pain by inhibiting these channels. The experiments seem to have been properly performed and most conclusions are justified. The paper is concisely written and easy to follow.

      Weaknesses:

      (1) The most critical issue I find in the manuscript is the claim that different combinations of NaV channels result in equivalent excitability. For example, in the Abstract it is stated that: "...we show that nociceptors can achieve equivalent excitability using different combinations of NaV1.3, NaV1.7, and NaV1.8". The gating properties of these channels are not identical, and therefore their contributions to excitability should not be the same. I think that the culprit of this issue is that the authors reach their conclusion from the comparison of the (average) firing rate determined over 1 s current stimulation in distinct conditions. However, this is not the only parameter that determines how sensory neurons convey information. For instance, the time dependence of the instantaneous frequency, the actual firing pattern, may be important too. Moreover, the use of 1 s of current stimulation might not be sufficient to characterize the firing pattern if one wants to obtain conclusions that could translate to clinical settings (i.e., sustained pain). A neuron in which NaV1.7 is the main contributor is expected to have a damping firing pattern due to cumulative channel inactivation, whereas another depending mainly on NaV1.8 is expected to display more sustained firing. This is actually seen in the results of the modelling.

      This concern seems to boil down to how equivalent is equivalent? The spike shape or the full inputoutput curve for a DIV0 neuron (Nav1.8-dominant) is never equivalent to what’s seen in a DIV47 neuron (Nav1.7-dominant), but nor are any two DIV0 neurons strictly equivalent, and likewise for any two DIV4-7 neurons. Our point is that DIV0 and DIV4-7 neurons are a far more similar (less discriminable) in their excitability than expected from the qualitative difference in their TTX sensitivity (and from repeated claims in the literature that Nav1.7 is necessary for spike generation in nociceptors). Nav isoforms need not be identical to operate similarly; for instance, Nav1.8 tends to activate at “suprathreshold” voltages, but this depends on the value of threshold; if threshold increases, Nav1.8 can activate at subthreshold voltages (see Fig 5). We have modified lines 155- 175 to help clarify this.

      We completely agree that firing rate is not the only way to convey sensory information, and of course injecting current directly into the cell body via a patch pipette is not a natural stimulus. These are all factors to keep in mind when interpreting our data. Nonetheless, our data show that excitability is similar between DIV0 and DIV 4-7, so much so that data from any one neuron (without pharmacological tests or capacitance measurements) would likely not reveal if that cell is DIV0 or DIV4-7; this “indiscriminability” qualifies as “equivalent” for our purposes, and is consistent with phrasing used by other authors studying degeneracy. Notably, not every DIV4-7 neuron exhibits spike height attenuation (see Fig. 1A), likely because of concomitant changes in the AHP that were not captured in our computer model or directly tested in our experiments. This highlights that other channel changes may also contribute to degeneracy and the maintenance of repetitive spiking.

      (2) In Fig. 1, is 100 nM TTX sufficient to inhibit all TTX-sensitive NaV currents? More common in literature values to fully inhibit these currents are between 300 to 500 nM. The currents shown as TTX-sensitive in Fig. 1D look very strange (not like the ones at Baseline DIV4-7). It seems that 100 nM TTX was not enough, leading to an underestimation of the amplitude of the TTXsensitive currents.

      As now summarized in Supplementary Table 3 (which is newly added), 100 nM TTX is >20x the EC50 for Nav1.3 and Nav1.7 (but is still far below the EC50 for Nav1.8). Based on this, TTXsensitive channels are definitely blocked in our TTX experiments.

      (3) Page 8, the authors conclude that "Inflammation caused nociceptors to become much more variable in their reliance of specific NaV subtypes". However, how did the authors ensure that all neurons tested were affected by the CFA model? It could be that the heterogeneity in neuron properties results from distinct levels of effects of CFA.

      We agree with the reviewer. We also believe that variable exposure to CFA is the most likely explanation for the heightened variability in TTX-sensitivity reported in Figure 7 (now more clearly explained on lines 214-215). One could try co-injecting a retrograde dye with the CFA to label cells innervating the injection site, but differential spread of the CFA and dye are liable to preclude any good concordance. Alternatively, a pain model involving more widespread (systemic) inflammation might cause a more homogeneous effect. But, our main goal with CFA injections was to show that a Nav1.8®Nav1.7 switch can occur in vivo (and is therefore not unique to culturing), and that demonstration is true even if some neurons do not switch. Subsequent testing in Figure 8 shows that enough neurons switch to have a meaningful effect in terms of the behavioral pharmacology. So, notwithstanding tangential concerns, we think our CFA experiments succeeded in showing that Nav channels can switch in vivo and that this impacts drug efficacy.

      Recommendations for the authors:

      All reviewers agreed that these results are solid and interesting. However, the reviewers also raised several concerns that should be addressed by the authors to improve the strength of the evidence presented. Revisions considered to be essential include:

      (1) Discuss how degeneracy concerning other ion channels (such as potassium ion channels) could also impact nociceptor excitability (reviewer #1). Additionally, the translation of results from DRG neuron cultures to "in vivo" nociceptors should be better discussed.

      We have added a new paragraph to the Discussion (line 248-259) to remind readers that despite our focus on Nav channels, other ion channels likely also change (and that these changes involve diverse regulatory mechanisms that require further investigation). Likewise, despite our focus on the changes caused by culturing neurons, we remind readers that subtler, more clinically relevant in vivo perturbations can likewise cause a multitude of changes. We end that paragraph by emphasizing that although accounting for all the contributing components is required to fully understand a degenerate system, meaningful progress can be made by studying a subset of the components. We want to emphasize this because there is some middle ground between focusing on one component at a time (which is the norm) vs. trying to account for everything (which is an infeasible ideal). Additional text on lines 304-308 also addresses related points.

      (2) Discuss how different combinations of NaV channels result in equivalent excitability, in the context of the experimental conditions used (see main comment by reviewer #3). It should also be discussed in more detail which human clinical data support the existence of "equivalent excitability through different sodium channels" also in humans (reviewer #2).

      Regarding the first part of this comment, reviewer 3 wrote in the public review that “The gating properties of these channels are not identical, and therefore their contributions to excitability should not be the same.” Differences in gating properties are commonly used to argue that different Nav subtypes mediate different phases of the spike, for example, that Nav1.7 initiates the spike whereas Nav1.8 mediates subsequent depolarization because Nav1.7 and Nav1.8 activate at perithreshold and suprathrehold voltages, respectively (see lines 134-135, now shown in red). But such comparison is overly simplistic insofar as it neglects the context in which ion channels operate. For instance, if Nav1.7 is not expressed or fully inactivates, voltage threshold will be less negative, enabling Nav1.8 to contribute to spike initiation; in other words, previously “suprathreshold” voltages become “perithreshold”. Figure 5 is dedicated to explaining this context-sensitivity; specifically, we demonstrate with simulations how Nav1.8 takes over responsibility for initiating a spike when Na1.7 is absent or inactivated. Text on lines 155- 184 has been edited to help clarify this. Regarding the second part of this comment, we are not aware of any direct evidence from human sensory neurons that different sodium channels produce equivalent excitability, but that is certainly what we expect. We suggest that failure of Nav subtype-specific drugs is, at least in part, because of degeneracy, but such failures do not demonstrate degeneracy unless other contributing factors can be excluded (which they can’t). Recognizing degeneracy is difficult, and so variability that might be explained by degeneracy will go unexplained or attributed to other factors unless, by design or serendipity, experiments quantify the effects of degeneracy (as we have attempted to do here). We now cite a recent review article on degeneracy and epilepsy (line 320), which addresses relevant themes that might help inform pain research; for instance, most existing antiseizure medications act on multiple targets whereas more recently developed single-target drugs have proven largely ineffective. This is similar to but better documented than for analgesics. With this in mind, we revised the text to emphasize the circumstantial nature of existing evidence and the need to test more directly for degeneracy (lines 320-323).

      (3) Extend the discussion about the poor clinical outcomes with the use of subtype-selective NaV inhibitors. In particular, the promising role of NaV1.7, which plays a role in nociceptor hyperexcitability but not in "normal" neurons, should be discussed in light of clinical results and not just covered with a citation of a review. Which clinical results of NaV1.7-selective drugs can now be better explained and how? (reviewer #2)

      As discussed above, we are cautious avoid speculating on which clinical results are attributable to degeneracy. Instead, our take-home message (see Discussion, lines 309-323) is that NaV1.7selective drugs may have a variable clinical effect because nociceptors’ reliance on NaV1.7 is itself variable – much more than past studies would have readers believe. The corollary is that accounting for degeneracy could help account for variability in drug efficacy, which would of course be beneficial. The challenge (as highlighted in the Abstract, lines 21-22) is that identifying the dominant Nav subtype to predict drug efficacy is not trivial. Interpreting clinical data is also complicated by the fact that we are either dealing with genetic mutations (with unclear compensatory changes) or pharmacological results (where NaV1.7-selective drugs have a multitude of problems that might contribute to their lack of efficacy, separate from effects of degeneracy). We have striven to contextualize our results (e.g. last paragraph of results, lines 222-235). We think this is the most we can reasonably say based on the limitations of existing clinical data.

      (4) Provide a clearer and more detailed description of the computational model (reviewers #2 and #3).

      We added important details on line 476-477 but, in our honest opinion, we think our computational model is thoroughly explained. The issue seems to boil down to whether details are included in the Results vs. being left for the Methods, tables and figure legends. We prefer the latter.

      (5) Better clarify the effects of the CFA model, to provide further evidence relating inflammation with nociceptors variability (reviewers #2 and #3)

      As explained in response to a specific point by reviewer #3, we believe that variable exposure to CFA explains the heightened variability in TTX-sensitivity reported in Figure 7 (now explained on lines 214-215). One could try co-injecting a retrograde dye with the CFA to label cells innervating the injection site, but differential spread of the inflammation and dye are liable to preclude any good concordance. Alternatively, a pain model involving more widespread (systemic) inflammation might cause a more homogeneous effect. But, our main goal with CFA injections was to show that a Nav1.8®Nav1.7 switch can occur in vivo (and is therefore not unique to culturing); that demonstration holds true even if some neurons do not switch. Subsequent testing (Fig 8) shows that enough neurons switch to drug efficacy assessed behaviorally. This is emphasized with new text on lines 225-227. Overall, we think our CFA experiments succeed in showing that Nav channels can switch in vivo and, despite variability, that this occurs in enough neurons to impact drug efficacy.

      (6) Revise the text according to all recommendations raised by the reviewers and listed in the individual reviews.

      Detailed responses are provided below for all feedback and changes to the text were made whenever necessary, as identified in our responses.

      Reviewer #1 (Recommendations For The Authors):

      Minor points/recommendations:

      Protein synthesis inhibition by cercosporamide could be the direct cause of a smaller-thanexpected increase in Nav1.7 levels at DIV5. But for Nav1.8, there is a mitigation in the increased levels at DIV5, that only could be explained by several indirect mechanisms, including membrane trafficking and posttranslational modifications (phosphorylation, SUMOylation, etc.) on Nav1.8 or protein regulators of Nav1.8 channels. The authors suggest that "translational regulation is crucial", but also insinuate that other processes (membrane trafficking, etc.) could contribute to the observed outcome. It is difficult to assess the relative importance of these different explanations without knowing the exact mechanisms that are acting here.

      We agree. We relied on electrophysiology (and pharmacology) to measure functional changes, but we wanted to verify those data with another method. We expected mRNA levels to parallel the functional changes but, when that did not pan out, we proceeded to look at protein levels. Perhaps we should have stopped there, but by blocking protein translation, we show that there is not enough Nav1.7 protein already available that can be trafficked to the membrane. That does not explain why Nav1.8 levels drop. Our immunohistochemistry could not tease apart membrane expression from overall expression, which limits interpretation. We have enhanced the text to discuss this (lines 200-204), but further experiments are needed. Though admittedly incomplete, our initial finding help set the stage for future experiments on this matter.

      Page 15, typo: "contamination from genomic RNA" -> "contamination from genomic DNA" (appears twice).

      This has been corrected on lines 420 and 421.

      Page 17: I could not find the computer code at ModelDB (http://modeldb.yale.edu/267560). It seems to be an old web link. It should be available at some web repository.

      We confirmed that the link works. Entry is password-protected (password = excitability; see line 476). Password protection will be removed once the paper is officially published.

      Page 19, reference 36, typo: "Inhibitio of" -> "Inhibition of".

      This has been corrected (line 557).

      Page 33, typo: "are significantly larger than differences at DIV1" -> "are significantly larger than differences at DIV0".

      This has been corrected (line 796).

      Page 35, figure 6 legend. The number of experiments (n) is not indicated for panel C data.

      N = 3 is now reported (line 828).

      Reviewer #2 (Recommendations For The Authors):

      p. 3/4 and Data of Fig. 6: It should be commented on why days 1-3 were not investigated. An investigation of the time course (by higher frequency testing) would certainly have an added value because it would be possible to deduce whether the changes develop slowly and gradually, or whether the excitability induced by different NaVs changes suddenly. At least mRNA and protein levels should be determined at additional time points to examine the time course or whether gene expression (mRNA) or membrane expression (protein) changes slowly and gradually or rapidly and more abruptly. It would also be interesting to clarify whether the changes that occur in culture (DIV0 vs. DIV4-7) are accompanied by (pro-)inflammatory changes in gene and protein expression, such as those known for nociceptors after CFA injection. Or is the latter question clear in the literature?

      We now explain (lines 362-369) that intermediate time points (DIV1-3) were tested in initial current clamp recordings. Those data showed that TTX-sensitivity stabilized by DIV4 and differed from the TTX-insensitivity observed at DIV0. TTX-sensitivity was mixed at DIV1-3 and crosscell variability complicated interpretation. Subsequent experiments were prioritized to clarify why NaV1.7 is not always critical for nociceptor excitability, contrary to past studies. Our efforts to measure mRNA and protein levels were primarily to validate our electrophysiological findings; we are also interested in deciphering the underlying regulatory processes but this is an entire study on its own. Unfortunately, the existing literature does not help or point to an explanation for the Nav1.7/1.8 shift we observed.

      Our evidence that mRNA levels do not parallel functional changes argues against pursuing transcriptional changes in Nav1.7, though transcriptional changes in other factors might be important. Interpretation of immuno quantification would be complicated by the high variability we observed with the physiology at intermediate time points and, furthermore, we cannot resolve surface expression from overall expression based on available antibodies. Methods conducive to longitudinal measurements would be more appropriate (as now mentioned on line 367-369). In short, a lot more work is required to understand the mechanisms involved in the switch, but we think the existing demonstration suffices to show that NaV1.7 and NaV1.8 protein levels vary, with crucial implications for which Nav subtype controls nociceptor excitability, and important implications for drug efficacy. Explaining why and how quickly those protein levels change will be no small feat is best left for a future study.

      p. 4 and following: In order to enable the interpretation of the used concentration of PF-24, PF71, and ICA, the respective IC50 should be indicated.

      A table (now Supplementary Table 3; line 861) has been added to report EC50 values for all drugs for blocking NaV1.7, NaV1.8 and NaV1.3. The concentrations we used are included on that table for easy comparison.

      p. 5, end of the middle paragraph: Here it should be briefly explained -for less familiar readers- why NaV1.1 cannot be causative (ICA inhibits NaV1.1 and 1.3).

      We now explain (lines 117-120) that NaV1.1 is expressed almost exclusively in medium-diameter (A-delta) neurons whereas NaV1.3 is known to be upregulated in small-diameter neurons, and so the effect we observe in small neurons is most likely via blockade NaV1.3.

      p. 6, lines 4/5: At least once it should read computer model instead of model.

      “Computer” has been added the first time we refer to DIV0 or DIV4-7 computer models (lines 138-139)

      p. 6: the difference between Fig. 4B and Fig. 4 - Figure suppl. 1 should be mentioned briefly.

      We now explain (lines 150-154) that Fig. 4B involves replacing a native channel with a different virtual channel (to demonstrate their interchangeability) whereas and Fig. 4 - Figure supplement 1 involves replacing a native channel with the equivalent virtual channel (as a positive control).

      p. 6/7: the text and the conclusions regarding Figure 5 are difficult to follow. Somewhat more detailed explanations of why which data demonstrate or prove something would be helpful.

      The text describing Figure 5 (lines 155-175) has been revised to provide more detail.

      p. 7, last sentence of the first paragraph: How is this supported by the data? Or should this sentence be better moved to the discussion?

      This sentence (now lines 182-184) is designed as a transition. The first half – “a subtype’s contribution shifts rapidly (because of channel inactivation)” – summarizes the immediately preceding data (Figure 5). The second half – “or slowly (because of [changes in conductance density])” – introduces the next section. The text show in square brackets has been revised. We hope this will be clearer based on revisions to the associated text.

      p. 7, second paragraph, line 3: Please delete one "at both".

      Corrected

      p. 7, second paragraph: Please explain why different time points (DIV4-7, DIV5, or DIV7) were used or studied.

      Initial electrophysiological experiments determined that TTX sensitivity stabilized by DIV 4 (see response to opening point) and we did not maintain neurons longer than 7 days, and so neurons recorded between DIV4 and 7 were pooled. If non-electrophysiological tests were conducted on a specific day within that range, we report the specific day, but any day within the DIV4-7 range is expected to give comparable results. This is now explained on lines 365-367.

      p. 8: the text regarding Fig. 7 should also include the important data (e.g. percentage of neurons showing repetitive spinking) mentioned in the legend.

      This text (lines 216-220) has been revised to include the proportion of neurons converted by PF71 and PF-24 and the associated statistical results.

      Fig. 1: third panel (TTX-sensitive current...) of D & Fig. 2 subpanel of A (Nav1.8 current...). These panels should be explained or mentioned in the text and/or legends.

      We now explain in the figure legends (lines 708-710; 714-715; 736-738) how those currents are found through subtraction.

      Fig. 2 - figure supplement 2. One might consider taking Panel A to Fig. 2 so that the comparison to DIV0 is apparent without switching to Suppl. Figs.

      We left this unchanged so that Figures 2 and 3 are equivalently organized, with negative control data left to the supplemental figures. Elife formatting makes it easy to reach the supplementary figure from the main figure, so we hope this won’t be an impediment to readers.

      Fig. 6 C, middle graph (graph of Nav1.7): Please re-check, whether DIV5 none vs. 24 h and none vs. 120 h are really significantly different with such a low p-value.

      We re-checked the statistics and the difference pointed out by the reviewer is significant at p=0.007. We mistakenly reported p<0.001 for all comparisons, and so this p value has been corrected; all the other p values are indeed <0.001. Notably, the data are summarized as median ± quartile because of their non-Gaussian distribution; this is now explained on line 827 (as a reminder to the statement on lines 461-462). Quartiles are more comparable to SD than to SEM (in that quartiles and SD represent the distribution rather than confidence in estimating the mean, like SEM), and so medians can differ very significantly even if quartiles overlap, as in this case.

      Reviewer #3 (Recommendations For The Authors):

      (1) A critical issue in the manuscript is the use of teleological language. It is likely that this is not the intention, but careful revision of the language should be done to avoid the use of expressions that confer purpose to a biological process. Please, find below a list of statements that I consider require correction.

      • In the Abstract, the first sentence: "Nociceptive sensory neurons convey pain signals to the CNS using action potentials". Neurons do not really "use" action potentials, they have no will or purpose to do so. Action potentials are not tools or means to be "used" by neurons. Other examples of misuse of the verb "use" are found in several other sentences:

      "...nociceptors can achieve equivalent excitability using different combinations of NaV1.3, NaV1.7, and NaV1.8"

      "Flexible use of different NaV subtypes - an example of degeneracy - compromises..."

      "Nociceptors can achieve equivalent excitability using different sodium channel subtypes" "...degeneracy - the ability of a biological system to achieve equivalent function using different components..."

      "...nociceptors can achieve equivalent excitability using different sodium channel subtypes..."

      "Our results show that nociceptors can achieve similar excitability using different NaV channels" "...the spinal dorsal horn circuit can achieve similar output using different synaptic weight combinations..."

      "Contrary to the view that certain ion channels are uniquely responsible for certain aspects of neuronal function, neurons use diverse ion channel combinations to achieve similar function" "In summary, our results show that nociceptors can achieve equivalent excitability using different NaV subtypes"

      “Use” can mean to put into action (without necessarily implying intention). Based on definitions of the word in various dictionaries, we feel we are well within the realm of normal usage of this term. In trying to achieve a clear and succinct writing style, we have stuck with our original word choice.

      • At the end of page 5 and in the legend of Fig. 7, the word "encourage" is not properly used in the sentence "The ability of NaV1.3, NaV1.7 and NaV1.8 to each encourage repetitive spiking is seemingly inconsistent with the common view...". Encouraging is really an action of humans or animals on other humans or animals.

      Like for “use”, we verified our usage in various dictionaries and we do not think that most readers will be confused or disturbed by our word choice. We use “encourage” to explain that increasing NaV1.3, NaV1.7 or NaV1.8 can increase the likelihood of repetitive spiking; we avoided “cause” because the probability of repetitive spiking is not raised to 100%, since other factors must always be considered.

      • In the Abstract and other places in the manuscript, the word "responsibility" seems to be wrongly employed. It is true that one can say, for instance, on page 4 last paragraph "we sought to identify the NaV subtype responsible for repetitive spiking at each time point". However, to confer channels with the human quality of having "responsibility" for something does not seem appropriate. See also page 8 last paragraph, the first paragraph of the Discussion, and the three paragraphs of page 11.

      Again, we must respectfully disagree with the reviewer. We appreciate that this reviewer does not like our writing style but we do not believe that our style violates English norms.

      (2) In the first sentence of the Abstract, nociceptive sensory neurons do not convey "pain signals". Pain is a sensation that is generated in the brain.

      “Pain” is used as an adjective for “signal” and is used to help identify the type of signal. Nonetheless, since the word count allowed for it, we now refer to “pain-related signals” (line 10).

      (3) I do not see the point of plotting the firing rate as a function of relative stimulus amplitude (normalized to the rheobase, e.g., Fig. 1A bottom panels, Fig. 2B, bottom-right, Fig. 2 Supp2A right, Fig. 3 B bottom panels, etc) instead of as a function of the actual stimulus amplitude. I have the impression that this maneuver hides information. This is equivalent to plotting the current amplitudes as a function of the voltage normalized by the voltage threshold for current activation, which is obviously not done.

      This is how the experiments were performed, so it would be impossible to perform the statistical analysis using the absolute amplitudes post-hoc; specifically, stimulus intensities were tested at increments defined relative to rheobase rather than in absolute terms. There are pros and cons to each approach, and both approaches are commonly used. Notably, we report the value of rheobase on the figures so that readers can, with minimal arithmetic, convert to absolute stimulus intensities. No information is hidden by our approach.

      (4) On page 4 it is stated that "We show later that similar changes develop in vivo following inflammation with consequences for drug efficacy assessed behaviourally (see Fig. 8), meaning the NaV channel reconfiguration described above is not a trivial epiphenomenon of culturing". However, what happens in culture may have nothing in common with what happens in vivo during inflammation. Thus, the latter data may not serve to answer whether the culture conditions induce artifacts or not. I suggest tuning down this statement by changing "meaning" to "suggesting".

      On line 97, we now write “suggesting”.

      (5) Page 5, first paragraph, I miss a clear description of the mathematical models. Having to skip to the Methods section to look for the details of the models as the artifices introduced to simulate different conditions is rather inconvenient.

      So as not to disrupt the flow of the presentation with methodological details, we only provide a short description of the model in the Results. We have slightly expanded this to point out that the conductance-based model is also single-compartment (line 111). We provide a very thorough description of our model in the Methods, especially considering all the details provided in Supplementary Tables 1, 5 and 6. We also report conductance densities and % changes in figure legends (lines 722, 747-748; now shown in red). This is also true for Figure 3-figure supplement 2 (lines 756-759). We tried very hard to find a good balance that we hope most readers will appreciate.

      (6) Page 6, second paragraph, simulations do not serve to "measure" currents.

      The sentence been revised to indicate that simulations were used to “infer” currents during different phases of the spike (line 155).

      (7) Page 7, regarding the tile of the subsection "Control of changes in NaV subtype expression between DIV0 and DIV4-7", the authors measured the levels of expression, but not really the mechanisms "controlling" them. I suggest writing "changes in NaV subtype expression between DIV0 and DIV4-7"

      We have removed “control of” from the section title (line 185)

      (8) What was the reason for adding a noise contribution in the model?

      We now explain that noise was added to reintroduce the voltage noise that is otherwise missing from simulations (line 474). For instance, in the absence of noise, membrane potential can approach voltage threshold very slowly without triggering a spike, which does not happen under realistically noisy conditions. Of course membrane potential fluctuates noisily because of stochastic channel opening and a multitude of other reasons. This is not a major issue for this study, and so we think our short explanation should suffice.

      (9) Please, define the concept of degeneracy upon first mention.

      Degeneracy is now succinctly defined in the abstract (line 20).

    2. Reviewer #2 (Public Review):

      Summary:

      The authors have noted in preliminary work that tetrodotoxin (TTX), which inhibits NaV1.7 and several other TTX-sensitive sodium channels, has differential effects on nociceptors, dramatically reducing their excitability under certain conditions but not under others. Partly because of this coincidental observation, the aim of the present work was to re-examine or characterize the role of NaV1.7 in nociceptor excitability and the effects on drug efficacy. The manuscript demonstrates that a NaV1.7-selective inhibitor produces analgesia only when nociceptor excitability is based on NaV1.7. More generally and comprehensively, the results show that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and NaV expression of different NaV subtypes (NaV 1.3/1.7 and 1.8). This can cause widespread changes in the role of a particular subtype over time. The degenerate nature of nociceptor excitability shows functional implications that make the assignment of pathological changes to a particular NaV subtype difficult or even impossible.

      Thus, the analgesic efficacy of NaV1.7- or NaV1.8-selective agents depends essentially on which NaV subtype controls excitability at a given time point. These results explain, at least in part, the poor clinical outcomes with the use of subtype-selective NaV inhibitors and therefore have major implications for the future development of Nav-selective analgesics.

      Strengths:

      The results are clearly and impressively supported by the experiments and data shown. During the revision, the manuscript was consistently improved and the concerns of the first reviews were resolved. All methods are described in detail, and presumably, allow good reproducibility and were suitable to address the scientific question.

      The results showing that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and expression of different NaV subtypes are of great importance in the fields of basic and clinical pain research and sodium channel physiology and pharmacology, but also for a broad readership and community. The degenerate nature of nociceptor excitability, which is clearly shown and well supported by data has large functional implications. The results are of great importance because they may explain, at least in part, the poor clinical outcomes with the use of subtype-selective NaV inhibitors and therefore have major implications for the future development of Nav-selective analgesics.

      In summary, the authors achieved their overall aim to enlighten the role of the NaV1.7 in nociceptor excitability and the effects on drug efficacy. The data support the conclusions and clinical implications are highlighted as far as is currently justifiable due to the still limited experience in translation. This appears well-considered, not too speculative, and ultimately appropriate.

      The main weaknesses of the first version were fixed during the revision:

      (i) After revising the manuscript, the initial weakness that the computer model was described superficially has been fixed. Important information was added to the main text and additional information, including the full code and equations and values are deposited on ModelDB or are given in the Supplementary information (Suppl. Table 5 & 6).

      (ii) The authors now comment that corresponding studies on protein levels or e.g. neuroinflammatory changes could support the characterization of the time course of membrane expression and cellular changes, but this should be addressed in future studies, as these analyses would also raise new questions, such as about membrane trafficking, post-translational modifications, etc. This is plausible and has now been appropriately addressed in the text.

      (iii) During the initial review the authors were asked to discuss the promising role of NaV1.7 in the light of clinical results. In their response, the authors confidently state that they „wish to avoid speculating on which particular clinical results are better explained because our study was not designed for that." They, however, emphasize their take-home message, which is well supported "Instead, our take-home message (which is well supported; see Discussion on lines 309-321) is that NaV1.7-selective drugs may have a variable clinical effect because nociceptors' reliance on NaV1.7 is itself variable - much more than past studies would have readers believe. ... The challenge (as highlighted in the Abstract, lines 21-22) is that identifying the dominant Nav subtype to predict drug efficacy is difficult."

      Against the background of this argumentation, it must be admitted that the decision not to present as yet unproven speculations is probably appropriate from a scientific point of view and that this ultimately proves the critical assessment of one's own data and the limitations of the study. This is undoubtedly acceptable and - in retrospect - probably the right way to go.

    1. Reviewer #1 (Public Review):

      Summary:

      In this study, the authors distinguished afferent inputs to different cell populations in the VTA using dimensionality reduction approaches and found significantly distinct patterns between normal and drug treatment conditions. They also demonstrated negative correlations of the inputs induced by drugs with gene expression of ion channels or proteins involved in synaptic transmission and demonstrated the knockdown of one of the voltage-gated calcium ion channels caused decreased inputs.

      Weaknesses:

      (1) For quantifications of brain regions in this study, boundaries were based on the Franklin-Paxinos (FP) atlas according to previous studies (Beier KT et al 2015, Beier KT et al 2019). It has been reported significant discrepancies exist between the anatomical labels on the FP atlas and the Allen Brain Atlas (ref: Chon U et al., Nat Commun 2019). Although a summary of conversion is provided as a sheet, the authors need to describe how consistent or different the brain boundaries they defined in the manuscript with Allen Brain Atlas by adding histology images. Also, I wonder how reliable the annotations were for over a hundred of animals with manual quantification. The authors should briefly explain it rather than citing previous studies in the Material and Methods Section.

      (2) Regarding the ellipsoids in the PC, although it's written in the manuscript that "Ellipsoids were centered at the average coordinate of a condition and stretched one standard deviation along the primary and secondary axes", it's intuitively hard to understand in some figures such as Figure 2O, P and Figure S1. The authors need to make their data analysis methods more accessible by providing source code to the public.

      (3) In histology images (Figure 1B and 3K), the authors need to add dashed lines or arrows to guide the reader's attention.

      (4) In Figure 2A and G, apparently there are significant differences in other brain regions such as NAcMed or PBN. If they are also statistically significant, the authors should note them as well and draw asterisks(*).

      (5) In Figure 2N about the spatial distribution of starter cells, the authors need to add histology images for each experimental condition (i.e. saline, fluoxetine, cocaine, methamphetamine, amphetamine, nicotine, and morphine) as supplement figures.

      (6) In the manuscript, it is necessary to explain why Cacna1e was selected among other calcium ion channels.

    1. While at Regional One, a client reported that he was going to sell his medication once he was discharged. I educated him on that being illegal and he reported that he was joking with me. I did not want to take the chance, so I reported this news to my educator. She reported that the rehab team, including the pharmacist and doctor, was aware and that this was not the first time he mentioned this. Katie Heismann, OTR/L reports "Rachel adheres to AOTA's code of ethics and also adheres to any safety protocols."

      can you find a synonym for the verb "report"? You use it repetitively in this section.

    1. Author Response

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

      We want to thank the reviewers for their thoughtful analysis and questions.

      A brief overview of the changes to the manuscript is provided here, with individual responses to the reviewer comments following.

      The methods section has been expanded to better explain the techniques used in our analyses. CTCF binding data section has likewise been expanded, to include more detail on the dataset and our analysis of its contents. All other requested clarifications have been added to areas of the results.

      Beyond specific requests from the reviewers, we made the following changes.

      We felt that a particular terminology choice on our part resulted in some confusion: the use of “SNPs” to refer to genetic variants within our Diversity Outbred samples. While we used SNPs that lay closest to the center of our haplotype predictions as our representative loci for each linkage disequilibrium block, this was done for computational purposes only. We did not focus most of our analyses on the haplotypes themselves, because of the uncertainty of which variants within an LD block actually participated in the genetic-epigenetic interactions we imputed.

      Thus, we edited the text to remove mention of “SNPs” unless our analysis did directly and deliberately profile SNPs themselves. In all other cases, we now refer to “haplotypes”, “genetic variants”, or “variants”. This should help increase clarity in the manuscript as a whole.

      A small error was discovered within the labelling and processing of regression model outputs in chromosome 14. A consistency check was run on all chromosomes, finding that only Chr 14 was affected. Chr 14 was rerun in its entirety to verify its results, with the previous results now archived within our databases uploaded on Synapse (see Methods for a link). All relevant calculations and figures were regenerated, resulting in an average shift of 1% or less across the manuscript. All analyses remain highly statistically significant.

      Responses to comments from Reviewer #1

      Methods

      • Sequencing depth was retrieved from the original publication on the primary multiomics dataset. (Line 105-106)

      • A line was added regarding initial mouse genome alignment for the original publication: we explain the GigaMUGA genotyping array, used for the DO mESC samples. For our ChIP-seq data, we reword to specify: we used liftovers from imputed strain-specific genomes to B6 mm10. (Lines 108-110; 116-120; 168-170)

      • Aneuploidy removal is expanded upon in a similar fashion: the original QC identified chromosome-level gene expression differences to remove aneuploid samples. (Line 111)

      • Mention of the pre-publication use of an alternative null model has been removed, given its lack of relevance to the rest of the text. While it was interesting to compare to the standard null model, it amounts to a side note that distracts from the focus of the paper. (Line 137-139).

      • Descriptive subheadings have been added.

      Results - Line 179 (now Line 191) now points to Methods.

      • Line 189-200 (now Line 188-204): language altered to better explain our intent: We wished to perform an intrachromosomal scan across the whole genome for non-additive genetic-epigenetic interactions. However, there were computational limits to how many possible combinations of gene, haplotype, and ATAC-seq peak we could feasibly test. We thus generated a random subset of possible combinations. This was also performed to identify target regions for focused analyses.

      • Line 195 (now line 206, expanded on in Line 210): Clarification added on the significance of our result: if non-additive genetic-epigenetic interactions were not a significant explanatory factor for gene expression, we would expect to see no enrichment of low p-value results. Instead, we see 0.07% of our models coming in at adj. p < 1x10-7.

      • Line 199 (now Line 216): The requested calculations were run, and are now included in table S3. We found that within 4 Mb of a given gene, less than 10% of variants and ATAC peaks within clustered closer to each other than they did to the gene they affected.

      Please note that this figure has a level of uncertainty due to linkage disequilibrium. Thus, rather than precisely answering the question “[are there haplotype-ATAC pairs] that are in the same locality but further away from the gene?”, we asked "is the ATAC peak closer than the gene to the point where we have the highest confidence of correctly calling the interacting genotype?". The relevant code has been deposited in our Synapse repository (see Methods for link).

      • Line 205 (now restructured in Line 221-228): The text has been edited to specify our intent. We are referring to a set of TAD-focused regression models we generated (see Methods) that comprehensively included all possible interactions between genes, and all haplotypes and ATAC peaks within +/- 1 TAD of the gene.

      • (Line 227): We specified that the previously-published TAD boundary dataset we used was retrieved from the Bing Ren lab’s Hi-C projects, which imputed locations of TAD boundaries in B6 mESCs.

      • We have relabeled Figure 1 and tweaked the surrounding text to clear up some confusing aspects. The Euler plots in Figure 1D-E reflect the fact that each ATAC-seq peak and haplotype can be in multiple relationships with local genes and regulatory factors. Some of these relationships will be simple correlation between their presence and gene expression, while others may co-regulate alongside independent regulatory factors, or engage in non-additive regulatory interactions.

      Because these non-additive regulatory interactions have not been comprehensively studied, we wished to determine whether there were any regulatory factors within our data that would not be detected as significant via more conventional methods, such as correlation analysis, mediation analysis, or regression analysis without an interaction term. Our Euler plots show that there are large subsets of both ATAC-seq peaks and haplotypes that are exclusively found in non-additive interactions. Thus, our justification for focusing on non-additive interactions for the rest of the paper.

      • Line 256 (now Line 252-255): We further clarified the above in this section: correlation and mediation analyses were previously completed by the team which initially analyzed the DO mESC dataset (Skelly et al. 2020, Cell Stem Cell). They performed a correlation analysis between open chromatin and gene expression (Skelly et al. Fig. 2A), and identified expression quantitative trait loci (eQTL) (Skelly et al. Fig. 2E). We felt that more direct comparisons to the Skelly et al. data would distract readers from our focus on genetic-epigenetic interactions. Thus, we limited our discussion of non-interacting regulatory relationships to Figures 1-2, and a brief mention in Figure 5.

      • Line 290 (now Line 337): We pulled promoter locations from the FANTOM5 database of mouse promoters, and included analysis in both the text and Figure S4A-B.

      • (Line 475-476): we clarified “DO founder SNPs” to “SNPs from the non-reference DO founder strains”.

      • Line 472 (restructured in Lines 531-564): We have expanded on this section, including answers to the reviewer’s questions regarding ChIP-seq peak counts, overlap with the TAD map we used for our other analyses, and expanded upon strain-specific CTCF binding we identified in our ChIP-seq analysis.

      Responses to comments from Reviewer #2:

      (1) Typo corrected.

      (2) Lines 194-195 (now line 206, expanded on in Line 210): We have expanded upon the intent and expectations of our analysis. In summary: if non-additive genetic-epigenetic interactions were not a significant explanatory factor for gene expression, we would expect to see no enrichment of low p-value results. Thus, we would expect 0.0000001% of results to reach adj. p < 1x10-7. Instead, we see 0.07% of our models coming in at adj. p < 1x10-7, four orders of magnitude greater than expected.

      (3) Lines 226-230 (Expanded on in Lines 252-276): We have relabeled Figure 1 and tweaked the surrounding text to clear up some confusing aspects. The percentages in the text are derived from the data summarized in the Euler plots in Figure 1D-E. These plots reflect the fact that each ATAC-seq peak and haplotype can be in multiple relationships with local genes and regulatory factors. Some of these relationships will be simple correlation between their presence and gene expression, while others may co-regulate alongside independent regulatory factors, or engage in non-additive regulatory interactions.

      (4) Line 261-263 (now lines 299-300): A companion to Figure 2B has been added (Fig. S3), which provides interaction counts for each ATAC-seq peak that contributed to Figure 2B. A horizontal line is included to highlight the locations of the highly-interacting ATAC peaks.

      (5) Analysis regarding Figure 3B had been removed from its original context. It has now been restored to the manuscript (Line 368-371).

    1. ." To teacb effectively a diverse student body, I bave to learn tbese codes. And so do students

      How do you apply different “cultural codes” in one classroom setting? And why students need to adapt this code as well?

    1. We made also some a screen-recording for every chapter

      Here is the introduction to hashtag#JavaScript in LiaScript, where we had re-imagined the usage and the capabilities of JavaScript. In our case JavaScript is used as a component, that serve multiple purposes:

      • In can simply perform a calculation and directly output the result as part of the text.

      • It can also output HTML or LiaScript

      • Users can interact with scripts, since they can be combined with different input elements

      • Users can inspect every calculation by double-clicking onto the result

      • Users can modify and rerun this code

      • Scripts can be combined with animations

      • Scripts can be combined with other scripts to form an execution graph, when on script finished, its result can trigger the execution of another script

      • Scripts can be combined with the Internationalization API for optimized formatting

      • And much more ;-)

    1. Index of LiaScript Templates
      • Algebrite is a Javascript library for symbolic mathematics (technically, CoffeeScript) designed to be comprehensible and easily extensible.
      • a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis plantUML diagrams
      • Sequence Usecase Class Activity Component, State Object Deployment Timing ...

      MermaidJS - generating charts from text

      rextester - Support for 45 different programming languages

      Tau-Prolog - functional Prolog-Interpreter for JavaScript

      Curiosity-Prolog - Prolog-Interpreter implemented in 160 lines of JavaScript code.

      Skulpt: - Skulpt is an entirely in-browser implementation of Python. No preprocessing, plugins, or server-side support required, just write Python and reload.

      Pyodide: - The Python scientific stack, compiled to WebAssembly. It provides transparent conversion of objects between Javascript and Python. When inside a browser, this means Python has full access to the Web APIs.

      BiwaScheme: - a Scheme interpreter written in JavaScript.

      AlaSQL - is a lightweight client-side in-memory SQL database designed to work in browser and Node.js.

      Turtle - A port of tiny-turtle.js to LiaScript,

      Web Development - A general template that can be used to create online curses on web development including HTML, CSS, and JavaScript.

    1. This is awesome!!! The impact/relevance of your work is incredibly clear, all data/code is on GitHub (with a very robust README) and you candidly express the limitations of the predictive models (e.g. inaccuracy when predicting oxygen tolerance for certain genera or phyla, thus requiring follow-up on the relationship between AAs and metabolic niches or how the lack of precision of the models may not be helpful for cultured microorganisms). I’m looking forward to trying this out myself!

      Summary: In this manuscript, Barnum et al. created computational models — favoring simple logistic regression models — that can predict the ideal oxygen tolerance, temperature, salinity and pH conditions of novel taxonomic microbial families (requiring only an unannotated, and potentially incomplete, genome from the user).

      The authors leveraged the empirical data of 15.5k+ microbes and curated the dataset to omit microbes that did not have multiple measured values for a growth phenotype, had minor differences between the minimum and maximum value tested for the phenotype (<1.5 pH, 10C, 1.5% NaCl unless salinity was <0.5%), or had fewer than 4 total measurements recorded. Haloarchaea with a salinity optima <3.7% were also excluded and finally, the data set was further balanced to reduce taxonomic bias.

      The authors then measured correlations between DNA and protein sequence features and oxygen tolerance, temperature, salinity and pH conditions (expressed as a Spearman’s rank correlation coefficient). No correlations between the tested DNA sequence features and the four physiochemical conditions were identified but numerous correlations between protein sequence features and the physiochemical conditions were identified. For example, a negative correlation between oxygen tolerance and cysteine frequency was revealed (p=-0.49).

      Estimators were then evaluated on their ability to accurately predict the four physiochemical conditions based on 9 different sets of features and the authors found that amino acid features alone were sufficient for accurate prediction. Three models were then selected for each condition (optimum, minimum and maximum value predictions). When testing the selected models with family-level holdouts, the predictions were made with lower accuracy albeit their performance was consistent with training and cross-validation data. The models also predicted extreme growth conditions less accurately (e.g. salinity > 15% or pH > 5).

      To test the models’ vulnerability to phylogenetic bias, the selected models were compared to models where the prediction was a random value or the average value of the closest relatives. As expected, the chosen models considerably outperformed the models strongly influenced by phylogeny.

      To test the models’ vulnerability to genome completeness, protein and genome sequences were subsampled to 10-100% completeness for 20 different species in each condition range and evaluated for prediction accuracy. The selected models showed negligible differences between 10% and 100% genome completeness for oxygen tolerance, temperature and salinity. pH prediction experienced a bigger impact by genome completeness.

      The selected models were then used to predict the ideal growth conditions of 85k+ bacteria and archaea. As expected, many of the uncultivated species were predicted to grow in more extreme conditions. The ideal growth conditions of 3.3k+ metagenomes were predicted and compared to the growth conditions of the environment from which the samples were derived. Predicted growth conditions mostly aligned with the organism’s habitat but the authors found that predicted individual genomes can deviate from the conditions of the source environment.

    1. Now, there are many reasons one might be suspicious about utilitarianism as a cheat code for acting morally, but let’s assume for a moment that utilitarianism is the best way to go. When you undertake your utility calculus, you are, in essence, gathering and responding to data about the projected outcomes of a situation. This means that how you gather your data will affect what data you come up with. If you have really comprehensive data about potential outcomes, then your utility calculus will be more complicated, but will also be more realistic. On the other hand, if you have only partial data, the results of your utility calculus may become skewed. If you think about the potential impact of a set of actions on all the people you know and like, but fail to consider the impact on people you do not happen to know, then you might think those actions would lead to a huge gain in utility, or happiness.

      This passage informs me about the limitations of utilitarianism in moral decision-making, especially the importance of data collection and interpretation. It reveals an issue from a personal perspective: our decisions are often influenced by personal biases, which can lead to biases in utility calculations. This makes me aware of the importance of considering comprehensive and objective data when applying utilitarianism in practice.

    1. But the Revolutionary Theatre, even if it is Western, must be anti-Western.

      anti western revolutionary theatre results in a kind of code reversal for western conceptions of victimhood and heroism

    1. All data is a simplification of reality.

      Last quarter, I took CSE 121 and we sort of touched on how data is oversimplified. We didn't really get into the ethics of this topic in class, but I could only imagine how programming and code, exclude marginalized groups of people. I find that most of the servers and extensions I use on a daily basis, aren't user-friendly to all. And by this I mean people who are visually impaired and hard of hearing. That just goes to show that most of the companies who go on to hire programmers to make their sites and such, always don't have accommodations and the interest of people different than them in mind.

    1. Address

      I choose Address. We can store the Address by a structured object, including street address, city, state/province, country, and postal code. The constraints for Address would be it must allow for international variations in address formats.

    1. eighth century

      given that the roman legal customs of objection to written law appeared to persist, it's a fair assumption that this assembly existed before 700 AD and at the time of the creation of the code

    2. promoted peace without compromising pride. It was also more consistent with Christian teaching than revenge-killing.

      which was a key aspect ins regards to insuring that the code was actually used in practice, given the significant role that honour and reputation played within Kentish society at the time

    3. A more uniform influence from the same period was that of the Christian Church, which after the arrival of St Augustine’s mission from Rome (597 ad)

      An event which would directly influence/encourage the inception of Æthelberhts code

    1. Le télétravail a été introduit dans le Code du travail à l’article 1222-9 par la loi du 23 mars 2012 (l’article 46 de la loi dite Warsmann définit le télétravail). Cette loi prévoit des mesures de protection des données et de préservation de la vie privée.

      Deuxième argument épistémique. Le télétravail est inclus dans le Code du travail. Par conséquent, la frontière vie personnelle/professionnelle du télétravailleur devrait être respectée et davantage surveillée par le pouvoir juridique.

    1. Reviewer #2 (Public Review):

      In this manuscript, Yang et al. present a modeling framework to understand the pattern of response biases and variance observed in delayed-response orientation estimation tasks. They combine a series of modeling approaches to show that coupled sensory-memory networks are in a better position than single-area models to support experimentally observed delay-dependent response bias and variance in cardinal compared to oblique orientations. These errors can emerge from a population-code approach that implements efficient coding and Bayesian inference principles and is coupled to a memory module that introduces random maintenance errors. A biological implementation of such operation is found when coupling two neural network modules, a sensory module with connectivity inhomogeneities that reflect environment priors, and a memory module with strong homogeneous connectivity that sustains continuous ring attractor function. Comparison with single-network solutions that combine both connectivity inhomogeneities and memory attractors shows that two-area models can more easily reproduce the patterns of errors observed experimentally. This, the authors take as evidence that a sensory-memory network is necessary, but I am not convinced about the evidence in support of this "necessity" condition. A more in-depth understanding of the mechanisms operating in these models would be necessary to make this point clear.

      Strengths:

      The model provides an integration of two modeling approaches to the computational bases of behavioral biases: one based on Bayesian and efficient coding principles, and one based on attractor dynamics. These two perspectives are not usually integrated consistently in existing studies, which this manuscript beautifully achieves. This is a conceptual advancement, especially because it brings together the perceptual and memory components of common laboratory tasks.

      The proposed two-area model provides a biologically plausible implementation of efficient coding and Bayesian inference principles, which interact seamlessly with a memory buffer to produce a complex pattern of delay-dependent response errors. No previous model had achieved this.

      Weaknesses:

      The correspondence between the various computational models is not fully disclosed. It is not easy to see this correspondence because the network function is illustrated with different representations for different models and the correspondence between components of the various models is not specified. For instance, Figure 1 shows that a specific pattern of noise is required in the low-dimensional attractor model, but in the next model in Figure 2, the memory noise is uniform for all stimuli. How do these two models integrate? What element in the population-code model of Figure 2 plays the role of the inhomogeneous noise of Figure 1? Also, the Bayesian model of Figure 2 is illustrated with population responses for different stimuli and delays, while the attractor models of Figures 3 and 4 are illustrated with neuronal tuning curves but not population activity. In addition, error variance in the Bayesian model appears to be already higher for oblique orientations in the first iteration whereas it is only first shown one second into the delay for the attractor model in Figure 4. It is thus unclear whether variance inhomogeneities appear already at the perceptual stage in the attractor model, as it does in the population-code model. Of course, correspondences do not need to be perfect, but the reader does not know right now how far the correspondence between these models goes.

      The manuscript does not identify the mechanistic origin in the model of Figure 4 of the specific noise pattern that is required for appropriate network function (with higher noise variance at oblique orientations). This mechanism appears critical, so it would be important to know what it is and how it can be regulated. In particular, it would be interesting to know if the specific choice of Poisson noise in Equation (3) is important. Tuning curves in Figure 4 indicate that population activity for oblique stimuli will have higher rates than for cardinal stimuli and thus induce a larger variance of injected noise in oblique orientations, based on this Poisson-noise assumption. If this explanation holds, one wonders if network inhomogeneities could be included (for instance in neural excitability) to induce higher firing rates in the cardinal/oblique orientations so as to change noise inhomogeneities independently of the bias and thus control more closely the specific pattern of errors observed, possibly within a single memory network.

      The main conclusion of the manuscript, that the observed patterns of errors "require network interaction between two distinct modules" is not convincingly shown. The analyses show that there is a quantitative but not a qualitative difference between the dynamics of the single memory area compared to the sensory-memory two-area network, for specific implementations of these models (Figure 7 - Figure Supplement 1). There is no principled reasoning that demonstrates that the required patterns of response errors cannot be obtained from a different memory model on its own. Also, since the necessity of the two-area configuration is highlighted as the main conclusion of the manuscript, it is inconvenient that the figure that carefully compares these conditions is in the Supplementary Material.

      The proposed model has stronger feedback than feedforward connections between the sensory and memory modules. This is not a common assumption when thinking about hierarchical processing in the brain, and it is not discussed in the manuscript.

    1. La concatenación de cadenas (strings) es el proceso de unir dos o más cadenas para formar una sola cadena más larga y se realiza utilizando el operador coma

      La concatenación de cadenas (strings) es el proceso de unir dos o más cadenas para formar una sola cadena más larga y se realiza utilizando el operador coma

      Ejemplo: 'Pharo tutorial ', ' is cool', ' when i active the code '

    1. Author Response

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

      Reviewer #1 (Recommendations For The Authors):

      (1) Methods, please state the sex of the mice.

      This has now been added to the methods section:

      “Three to nine month old Thy1-GCaMP6S mice (Strain GP4.3, Jax Labs), N=16 stroke (average age: 5.4 months; 13 male, 3 female), and 5 sham (average age: 6 months; 3 male, 2 female), were used in this study.”

      (2) The analysis in Fig 3B-D, 4B-C, and 6A, B highlights the loss of limb function, firing rate, or connections at 1 week but this phenomenon is clearly persisting longer in some datasets (Fig. 3 and 6). Was there not a statistical difference at weeks 2,3,4,8 relative to "Pre-stroke" or were comparisons only made to equivalent time points in the sham group? Personally, I think it is useful to compare to "pre-stroke" which should be more reflective of that sample of animals than comparing to a different set of animals in the Sham group. A 1 sample t-test could be used in Fig 4 and 6 normalized data.

      On further analysis of our datasets, normalization throughout the manuscript was unnecessary for proper depiction of results, and all normalized datasets have been replaced with nonnormalized datasets. All within group statistics are now indicated within the manuscript.

      (3) Fig 4A shows a very striking change in activity that doesn't seem to be borne out with group comparisons. Since many neurons are quiet or show very little activity, did the authors ever consider subgrouping their analysis based on cells that show high activity levels (top 20 or 30% of cells) vs those that are inactive most of the time? Recent research has shown that the effects of stroke can have a disproportionate impact on these highly active cells versus the minimally active ones.

      A qualitative analysis supports a loss of cells with high activity at the 1-week post-stroke timepoint, and examination of average firing rates at 1-week shows reductions in the animals with the highest average rates. However, we have not tracked responses within individual neurons or quantitatively analyzed the data by subdividing cells into groups based on their prestroke activity levels. We have amended the discussion of the manuscript with the following to highlight the previous data as it relates to our study:

      “Recent research also indicates that stroke causes distinct patterns of disruption to the network topology of excitatory and inhibitory cells [73], and that stroke can disproportionately disrupt the function of high activity compared to low activity neurons in specific neuron sub-types [61]. Mouse models with genetically labelled neuronal sub-types (including different classes of inhibitory interneurons) could be used to track the function of those populations over time in awake animals.”

      (4) Fig 4 shows normalized firing rates when moving and at rest but it would be interesting to know what the true difference in activity was in these 2 states. My assumption is that stroke reduces movement therefore one normalizes the data. The authors could consider putting non-normalized data in a Supp figure, or at least provide a rationale for not showing this, such as stating that movement output was significantly suppressed, hence the need for normalization.

      On further analysis of our datasets, normalization throughout the manuscript was unnecessary for proper depiction of results, and all normalized datasets have been replaced with nonnormalized datasets.

      (5) One thought for the discussion. The fact that the authors did not find any changes in "distant" cortex may be specific to the region they chose to sample (caudal FL cortex). It is possible that examining different "distant" regions could yield a different outcome. For example, one could argue that there may have been no reason for this area to "change" since it was responsive to FL stimuli before stroke. Further, since it was posterior to the stroke, thalamocortical projects should have been minimally disturbed.

      We would like to thank the reviewer for this comment. We have amended the discussion with the following:

      “Our results suggest a limited spatial distance over which the peri-infarct somatosensory cortex displays significant network functional deficits during movement and rest. Our results are consistent with a spatial gradient of plasticity mediating factors that are generally enhanced with closer proximity to the infarct core [84,88,90,91]. However, our analysis outside peri-infarct cortex is limited to a single distal area caudal to the pre-stroke cFL representation. Although somatosensory maps in the present study were defined by a statistical criterion for delineating highly responsive cortical regions from those with weak responses, the distal area in this study may have been a site of activity that did not meet the statistical criterion for inclusion in the baseline map. The lack of detectable changes in population correlations, functional connectivity, assembly architecture and assembly activations in the distal region may reflect minimal pressure for plastic change as networks in regions below the threshold for regional map inclusion prior to stroke may still be functional in the distal cortex. Thus, threshold-based assessment of remapping may further overestimate the neuroplasticity underlying functional reorganization suggested by anaesthetized preparations with strong stimulation. Future studies could examine distal areas medial and anterior to the cFL somatosensory area, such as the motor and pre-motor cortex, to further define the effect of FL targeted stroke on neuroplasticity within other functionally relevant regions. Moreover, the restriction of these network changes to peri-infarct cortex could also reflect the small penumbra associated with photothrombotic stroke, and future studies could make use of stroke models with larger penumbral regions, such as the middle cerebral artery occlusion model. Larger injuries induce more sustained sensorimotor impairment, and the relationship between neuronal firing, connectivity, and neuronal assemblies could be further probed relative to recovery or sustained impairment in these models.”

      Minor comments:

      Line 129, I don't necessarily think the infarct shows "hyper-fluorescence", it just absorbs less white light (or reflects more light) than blood-rich neighbouring regions.

      Sentence in the manuscript has been changed to:

      “Resulting infarcts lesioned this region, and borders could be defined by a region of decreased light absorption 1 week post-stroke (Fig 1D, Top).”

      Line 130-132: the authors refer to Fig 1D to show cellular changes but these cannot be seen from the images presented. Perhaps a supplementary zoomed-in image would be helpful.

      As changes to the morphology of neurons are not one of the primary objectives of this study, and sampled resolution was not sufficiently high to clearly delineate the processes of neurons necessary for morphological assessment, we have amended the text as follows:

      “Within the peri-infarct imaging region, cellular dysmorphia and swelling was visually apparent in some cells during two photon imaging 1-week after stroke, but recovered over the 2 month poststroke imaging timeframe (data not shown). These gross morphological changes were not visually apparent in the more distal imaging region lateral to the cHL.”

      Lines 541-543, was there a rationale for defining movement as >30mm/s? Based on a statistical estimate of noise?

      Text has been altered as follows:

      “Animal movement within the homecage during each Ca2+ imaging session was tracked to determine animal speed and position. Movement periods were manually annotated on a subset of timeseries by co-recording animal movement using both the Mobile Homecage tracker, as well as a webcam (Logitech C270) with infrared filter removed. Movement tracking data was low pass filtered to remove spurious movement artifacts lasting below 6 recording frames (240ms). Based on annotated times of animal movement from the webcam recordings and Homecage tracking, a threshold of 30mm/s from the tracking data was determined as frames of animal movement, whereas speeds below 30mm/s was taken as periods of rest.”

      Lines 191-195: Note that although the finding of reduced neural activity is in disagreement with a multi-unit recording study, it is consistent with other very recent single-cell Ca++ imaging data after stroke (PMID: 34172735 , 34671051).

      Text has been altered as follows:

      “These results indicate decreased neuronal spiking 1-week after stroke in regions immediately adjacent to the infarct, but not in distal regions, that is strongly related to sensorimotor impairment. This finding runs contrary to a previous report of increased spontaneous multi-unit activity as early as 3-7 days after focal photothrombotic stroke in the peri-infarct cortex [1], but is in agreement with recent single-cell calcium imaging data demonstrating reduced sensoryevoked activity in neurons within the peri-infarct cortex after stroke [60,61].”

      Fig 7. I don't understand what the color code represents. Are these neurons belonging to the same assembly (or membership?).

      That is correct, neurons with identical color code belong to the same assembly. The legend of Fig 7 has been modified as follows to make this more explicit:

      “Fig 7. Color coded neural assembly plots depict altered neural assembly architecture after stroke in the peri-infarct region. (A) Representative cellular Ca2+ fluorescence images with neural assemblies color coded and overlaid for each timepoint. Neurons belonging to the same assembly have been pseudocolored with identical color. A loss in the number of neural assemblies after stroke in the peri-infarct region is visually apparent, along with a concurrent increase in the number of neurons for each remaining assembly. (B) Representative sham animal displays no visible change in the number of assemblies or number of neurons per assembly.”

      Reviewer #2 (Recommendations For The Authors):

      Materials and methods

      Identification of forelimb and hindlimb somatosensory cortex representations [...] Cortical response areas are calculated using a threshold of 95% peak activity within the trial. The threshold is presumably used to discriminate between the sensory-evoked response and collateral activation / less "relevant" response (noise). Since the peak intensity is lower after stroke, the "response" area is larger - lower main signal results in less noise exclusion. Predictably, areas that show a higher response before stroke than after are excluded from the response area before stroke and included after. While it is expected that the remapped areas will exhibit a lower response than the original and considering the absence of neuronal activity, assembly architecture, or functional connectivity in the "remapped" regions, a minimal criterion for remapping should be to exhibit higher activation than before stroke. Please use a different criterion to map the cortical response area after stroke.

      We would like to thank the reviewer for this comment. We agree with the reviewer’s assessment of 95% of peak as an arbitrary criterion of mapped areas. To exclude noise from the analysis of mapped regions, a new statistical criterion of 5X the standard deviation of the baseline period was used to determine the threshold to use to define each response map. These maps were used to determine the peak intensity of the forelimb response. We also measured a separate ROI specifically overlapping the distal region, lateral to the hindlimb map, to determine specific changes to widefield Ca2+ responses within this distal region. We have amended the text as follows and have altered Figure 2 with new data generated from our new criterion for cortical mapping.

      “The trials for each limb were averaged in ImageJ software (NIH). 10 imaging frames (1s) after stimulus onset were averaged and divided by the 10 baseline frames 1s before stimulus onset to generate a response map for each limb. Response maps were thresholded at 5 times the standard deviation of the baseline period deltaFoF to determine limb associated response maps. These were merged and overlaid on an image of surface vasculature to delineate the cFL and cHL somatosensory representations and were also used to determine peak Ca2+ response amplitude from the timeseries recordings. For cFL stimulation trials, an additional ROI was placed over the region lateral to the cHL representation (denoted as “distal region” in Fig 2E) to measure the distal region cFL evoked Ca2+ response amplitude pre- and post-stroke. The dimensions and position of the distal ROI was held consistent relative to surface vasculature for each animal from pre- to post-stroke.”

      Animals

      Mice used have an age that goes from 3 to 9 months. This is a big difference given that literature on healthy aging reports changes in neurovascular coupling starting from 8-9 months old mice. Consider adding age as a covariate in the analysis.

      We do not have sufficient numbers of animals within this study to examine the effect of age on the results observed herein. We have amended the discussion with the following to address this point:

      “A potential limitation of our data is the undefined effect of age and sex on cortical dynamics in this cohort of mice (with ages ranging from 3-9 months) after stroke. Aging can impair neurovascular coupling [102–107] and reduce ischemic tolerance [108–111], and greater investigation of cortical activity changes after stroke in aged animals would more effectively model stroke in humans. Future research could replicate this study with mice in middle-age and aged mice (e.g. 9 months and 18+ months of age), and with sufficient quantities of both sexes, to better examine age and sex effects on measures of cortical function.”

      Statistics

      Please describe the "normalization" that was applied to the firing rate. Since a mixedeffects model was used, why wasn't baseline simply added as a covariate? With this type of data, normalization is useful for visualization purposes.

      On further analysis of our datasets, normalization throughout the manuscript was unnecessary for the visualization of results, and all normalized datasets have been replaced with nonnormalized datasets. All within group comparisons are now indicated throughout the manuscript and in the figures.

      Introduction

      Line 93 awake, freely behaving but head-fixed. That's not freely. Should just say behaving.

      Sentence has been edited as follows:

      “We used awake, behaving but head-fixed mice in a mobile homecage to longitudinally measure cortical activity, then used computational methods to assess functional connectivity and neural assembly architecture at baseline and each week for 2 months following stroke.”

      110 - 112 The last part of this sentence is unjustified because these areas have been incorrectly identified as locations of representational remapping.

      We agree with the reviewer and have amended the manuscript as follows after re-analyzing the dataset on widefield Ca2+ imaging of sensory-evoked responses: “Surprisingly, we also show that significant alterations in neuronal activity (firing rate), functional connectivity, and neural assembly architecture are absent within more distal regions of cortex as little as 750 µm from the stroke border, even in areas identified by regional functional imaging (under anaesthesia) as ‘remapped’ locations of sensory-evoked FL activity 8-weeks post-stroke.”

      Results

      149-152 There is no observed increase in the evoked response area. There is an observed change in the criteria for what is considered a response.

      We agree with the reviewer. Text has been amended as follows:

      “Fig 2A shows representative montages from a stroke animal illustrating the cortical cFL and cHL Ca2+ responses to 1s, 100Hz limb stimulation of the contralateral limbs at the pre-stroke and 8week post-stroke timepoints. The location and magnitude of the cortical responses changes drastically between timepoints, with substantial loss of supra-threshold activity within the prestroke cFL representation located anterior to the cHL map, and an apparent shift of the remapped representation into regions lateral to the cHL representation at 8-weeks post-stroke. A significant decrease in the cFL evoked Ca2+ response amplitude was observed in the stroke group at 8-weeks post-stroke relative to pre-stroke (Fig 2B). This is in agreement with past studies [19–25], and suggests that cFL targeted stroke reduces forelimb evoked activity across the cFL somatosensory cortex in anaesthetized animals even after 2 months of recovery. There was no statistical change in the average size of cFL evoked representation 8-weeks after stroke (Fig 2C), but a significant posterior shift of the supra-threshold cFL map was detected (Fig 2D). Unmasking of previously sub-threshold cFL responsive cortex in areas posterior to the original cFL map at 8-weeks post-stroke could contribute to this apparent remapping. However, the amplitude of the cFL evoked widefield Ca2+ response in this distal region at 8-weeks post-stroke remains reduced relative to pre-stroke activation (Fig 2E). Previous studies suggest strong inhibition of cFL evoked activity during the first weeks after photothrombosis [25]. Without longitudinal measurement in this study to quantify this reduced activation prior to 8-weeks poststroke, we cannot differentiate potential remapping due to unmasking of the cFL representation that enhances the cFL-evoked widefield Ca2+ response from apparent remapping that simply reflects changes in the signal-to-noise ratio used to define the functional representations. There were no group differences between stroke and sham groups in cHL evoked intensity, area, or map position (data not shown).”

      A lot of the nonsignificant results are reported as "statistical trends towards..." While the term "trend" is problematic, it remains common in its use. However, assigning directionality to the trend, as if it is actively approaching a main effect, should be avoided. The results aren't moving towards or away from significance. Consider rewording the way in which these results are reported.

      We have amended the text to remove directionality from our mention of statistical trends.

      R squared and p values for significant results are reported in the "impaired performance on tapered beam..." and "firing rate of neurons in the peri-infarct cortex..." subsections of the results, but not the other sections. Please report the results in a consistent manner.

      R-squared and p-values have been removed from the results section and are now reported in figure captions consistently.

      Discussion

      288 Remapping is defined as "new sensory-evoked spiking". This should be the main criterion for remapping, but it is not operationalized correctly by the threshold method.

      With our new criterion for determining limb maps using a statistical threshold of 5X the standard deviation of baseline fluorescence, we have edited text throughout the manuscript to better emphasize that we may not be measuring new sensory-evoked spiking with the mesoscale mapping that was done. We have edited the discussion as follows:

      “Here, we used longitudinal two photon calcium imaging of awake, head-fixed mice in a mobile homecage to examine how focal photothrombotic stroke to the forelimb sensorimotor cortex alters the activity and connectivity of neurons adjacent and distal to the infarct. Consistent with previous studies using intrinsic optical signal imaging, mesoscale imaging of regional calcium responses (reflecting bulk neuronal spiking in that region) showed that targeted stroke to the cFL somatosensory area disrupts the sensory-evoked forelimb representation in the infarcted region. Consistent with previous studies, this functional representation exhibited a posterior shift 8-weeks after injury, with activation in a region lateral to the cHL representation. Notably, sensory-evoked cFL representations exhibited reduced amplitudes of activity relative to prestroke activation measured in the cFL representation and in the region lateral the cHL representation. Longitudinal two-photon calcium imaging in awake animals was used to probe single neuron and local network changes adjacent the infarct and in a distal region that corresponded to the shifted region of cFL activation. This imaging revealed a decrease in firing rate at 1-week post-stroke in the peri-infarct region that was significantly negatively correlated with the number of errors made with the stroke-affected limbs on the tapered beam task. Periinfarct cortical networks also exhibited a reduction in the number of functional connections per neuron and a sustained disruption in neural assembly structure, including a reduction in the number of assemblies and an increased recruitment of neurons into functional assemblies. Elevated correlation between assemblies within the peri-infarct region peaked 1-week after stroke and was sustained throughout recovery. Surprisingly, distal networks, even in the region associated with the shifted cFL functional map in anaesthetized preparations, were largely undisturbed.”

      “Cortical plasticity after stroke Plasticity within and between cortical regions contributes to partial recovery of function and is proportional to both the extent of damage, as well as the form and quantity of rehabilitative therapy post-stroke [80,81]. A critical period of highest plasticity begins shortly after the onset of stroke, is greatest during the first few weeks, and progressively diminishes over the weeks to months after stroke [19,82–86]. Functional recovery after stroke is thought to depend largely on the adaptive plasticity of surviving neurons that reinforce existing connections and/or replace the function of lost networks [25,52,87–89]. This neuronal plasticity is believed to lead to topographical shifts in somatosensory functional maps to adjacent areas of the cortex. The driver for this process has largely been ascribed to a complex cascade of intra- and extracellular signaling that ultimately leads to plastic re-organization of the microarchitecture and function of surviving peri-infarct tissue [52,80,84,88,90–92]. Likewise, structural and functional remodeling has previously been found to be dependent on the distance from the stroke core, with closer tissue undergoing greater re-organization than more distant tissue (for review, see [52]).”

      “Previous research examining the region at the border between the cFL and cHL somatosensory maps has shown this region to be a primary site for functional remapping after cFL directed photothrombotic stroke, resulting in a region of cFL and cHL map functional overlap [25]. Within this overlapping area, neurons have been shown to lose limb selectivity 1-month post-stroke [25]. This is followed by the acquisition of more selective responses 2-months post-stroke and is associated with reduced regional overlap between cFL and cHL functional maps [25]. Notably, this functional plasticity at the cellular level was assessed using strong vibrotactile stimulation of the limbs in anaesthetized animals. Our findings using longitudinal imaging in awake animals show an initial reduction in firing rate at 1-week post-stroke within the peri-infarct region that was predictive of functional impairment in the tapered beam task. This transient reduction may be associated with reduced or dysfunctional thalamic connectivity [93–95] and reduced transmission of signals from hypo-excitable thalamo-cortical projections [96]. Importantly, the strong negative correlation we observed between firing rate of the neural population within the peri-infarct cortex and the number of errors on the affected side, as well as the rapid recovery of firing rate and tapered beam performance, suggests that neuronal activity within the peri-infarct region contributes to the impairment and recovery. The common timescale of neuronal and functional recovery also coincides with angiogenesis and re-establishment of vascular support for peri-infarct tissue [83,97–100].”

      “Consistent with previous research using mechanical limb stimulation under anaesthesia [25], we show that at the 8-week timepoint after cFL photothrombotic stroke the cFL representation is shifted posterior from its pre-stroke location into the area lateral to the cHL map. Notably, our distal region for awake imaging was directly within this 8-week post-stroke cFL representation. Despite our prediction that this distal area would be a hotspot for plastic changes, there was no detectable alteration to the level of population correlation, functional connectivity, assembly architecture or assembly activations after stroke. Moreover, we found little change in the firing rate in either moving or resting states in this region. Contrary to our results, somatosensoryevoked activity assessed by two photon calcium imaging in anesthetized animals has demonstrated an increase in cFL responsive neurons within a region lateral to the cHL representation 1-2 months after focal cFL stroke [25]. Notably, this previous study measured sensory-evoked single cell activity using strong vibrotactile (1s 100Hz) limb stimulation under aneasthesia [25]. This frequency of limb stimulation has been shown to elicit near maximal neuronal responses within the limb-associated somatosensory cortex under anesthesia [101]. Thus, strong stimulation and anaesthesia may have unmasked non-physiological activity in neurons in the distal region that is not apparent during more naturalistic activation during awake locomotion or rest. Regional mapping defined using strong stimulation in anesthetized animals may therefore overestimate plasticity at the cellular level.”

      “Our results suggest a limited spatial distance over which the peri-infarct somatosensory cortex displays significant network functional deficits during movement and rest. Our results are consistent with a spatial gradient of plasticity mediating factors that are generally enhanced with closer proximity to the infarct core [84,88,90,91]. However, our analysis outside peri-infarct cortex is limited to a single distal area caudal to the pre-stroke cFL representation. Although somatosensory maps in the present study were defined by a statistical criterion for delineating highly responsive cortical regions from those with weak responses, the distal area in this study may have been a site of activity that did not meet the statistical criterion for inclusion in the baseline map. The lack of detectable changes in population correlations, functional connectivity, assembly architecture and assembly activations in the distal region may reflect minimal pressure for plastic change as networks in regions below the threshold for regional map inclusion prior to stroke may still be functional in the distal cortex. Thus, threshold-based assessment of remapping may further overestimate the neuroplasticity underlying functional reorganization suggested by anaesthetized preparations with strong stimulation. Future studies could examine distal areas medial and anterior to the cFL somatosensory area, such as the motor and pre-motor cortex, to further define the effect of FL targeted stroke on neuroplasticity within other functionally relevant regions. Moreover, the restriction of these network changes to peri-infarct cortex could also reflect the small penumbra associated with photothrombotic stroke, and future studies could make use of stroke models with larger penumbral regions, such as the middle cerebral artery occlusion model. Larger injuries induce more sustained sensorimotor impairment, and the relationship between neuronal firing, connectivity, and neuronal assemblies could be further probed relative to recovery or sustained impairment in these models. Recent research also indicates that stroke causes distinct patterns of disruption to the network topology of excitatory and inhibitory cells [73], and that stroke can disproportionately disrupt the function of high activity compared to low activity neurons in specific neuron sub-types [61]. Mouse models with genetically labelled neuronal sub-types (including different classes of inhibitory interneurons) could be used to track the function of those populations over time in awake animals. A potential limitation of our data is the undefined effect of age and sex on cortical dynamics in this cohort of mice (with ages ranging from 3-9 months) after stroke. Aging can impair neurovascular coupling [102–107] and reduce ischemic tolerance [108–111], and greater investigation of cortical activity changes after stroke in aged animals would more effectively model stroke in humans. Future research could replicate this study with mice in middle-age and aged mice (e.g. 9 months and 18+ months of age), and with sufficient quantities of both sexes, to better examine age and sex effects on measures of cortical function.”

      315 - 317 Remodelling is dependent on the distance from the stroke core, with closer tissue undergoing greater reorganization than more distant tissue. There is no evidence that the more distant tissue undergoes any reorganization at all.

      We agree with the reviewer that no remodelling is apparent in our distal area. We have removed reference to our study showing remodeling in the distal area, and have amended the text as follows:

      “Likewise, structural and functional remodeling has previously been found to be dependent on the distance from the stroke core, with closer tissue undergoing greater re-organization than more distant tissue (for review, see [52]).”

      412-414 The authors speculate that a strong stimulation under anaesthesia may unmask connectivity in distal regions. However, the motivation for this paper is that anaesthesia is a confounding factor. It appears to me that, given the results of this study, the authors should argue that the functional connectivity observed under anaesthesia may be spurious.

      The incorrect word was used here. We have corrected the paragraph of the discussion and amended it as follows:

      “Consistent with previous research using mechanical limb stimulation under anaesthesia [25], we show that at the 8-week timepoint after cFL photothrombotic stroke the cFL representation is shifted posterior from its pre-stroke location into the area lateral to the cHL map. Notably, our distal region for awake imaging was directly within this 8-week post-stroke cFL representation. Despite our prediction that this distal area would be a hotspot for plastic changes, there was no detectable alteration to the level of population correlation, functional connectivity, assembly architecture or assembly activations after stroke. Moreover, we found little change in the firing rate in either moving or resting states in this region. Contrary to our results, somatosensoryevoked activity assessed by two photon calcium imaging in anesthetized animals has demonstrated an increase in cFL responsive neurons within a region lateral to the cHL representation 1-2 months after focal cFL stroke [25]. Notably, this previous study measured sensory-evoked single cell activity using strong vibrotactile (1s 100Hz) limb stimulation under aneasthesia [25]. This frequency of limb stimulation has been shown to elicit near maximal neuronal responses within the limb-associated somatosensory cortex under anesthesia [101]. Thus, strong stimulation and anaesthesia may have unmasked non-physiological activity in neurons in the distal region that is not apparent during more naturalistic activation during awake locomotion or rest. Regional mapping defined using strong stimulation in anesthetized animals may therefore overestimate plasticity at the cellular level.”

      Figures

      Figure 1 and 2: Scale bar missing.

      Scale bars added to both figures.

      Figure 2: The representative image shows a drastic reduction of the forelimb response area, contrary to the general description of the findings. It would also be beneficial to see a graph with lines connecting the pre-stroke and 8-week datapoints.

      The data for Figure 2 has been re-analyzed using a new criterion of 5X the standard deviation of the baseline period for determining the threshold for limb mapping. Figure 2 and relevant manuscript and figure legend text has been amended. In agreement with the reviewers observation, there is no increase in forelimb response area, but instead a non-significant decrease in the average forelimb area.

    1. Reviewer #1 (Public Review):

      Summary:

      Building upon their famous tool for the deconvolution of human transcriptomics data (EPIC), Gabriel et al. implemented a new methodology for the quantification of the cellular composition of samples profiled with Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq). To build a signature for ATAC-seq deconvolution, they first created a compendium of ATAC-seq data and derived chromatin accessibility marker peaks and reference profiles for 21 cell types, encompassing immune cells, endothelial cells, and fibroblasts. They then coupled this novel signature with the EPIC deconvolution framework based on constrained least-square regression to derive a dedicated tool called EPIC-ATAC. The method was then assessed using real and pseudo-bulk RNA-seq data from human peripheral blood mononuclear cells (PBMC) and, finally, applied to ATAC-seq data from breast cancer tumors to show it accurately quantifies their immune contexture.

      Strengths:

      Overall, the work is of very high quality. The proposed tool is timely; its implementation, characterization, and validation are based on rigorous methodologies and resulted in robust results. The newly-generated, validation data and the code are publicly available and well-documented. Therefore, I believe this work and the associated resources will greatly benefit the scientific community.

      Weaknesses:

      A few aspects can be improved to clarify the value and applicability of the EPIC-ATAC and the transparency of the benchmarking analysis.

      Most of the validation results in the main text assess the methods on all cell types together, by showing the correlation, RMSE, and scatterplots of the estimated vs. true cell fractions. This approach is valuable for showing the overall method performance and for detecting systematic biases and noisy estimates. However, it provides very limited insights regarding the capability of the methods to estimate the individual cell types, which is the ultimate aim of deconvolution analysis. This limitation is exacerbated for rare cell types, which could even have a negative correlation with the ground truth fractions, but not weigh much on the overall RMSE and correlation. I would suggest integrating into the main text and figures an in-depth assessment of the individual cell types. In particular, it should be shown and discussed which cell types can be accurately quantified and which ones are less reliable.

      In the benchmarking analysis, EPIC-ATAC is compared to several deconvolution methods, most of which were originally developed for transcriptomics data. This comparison is not completely fair unless their peculiarities and the limitations of tweaking them to work with ATAC-seq data are discussed. For instance, some methods (including the original EPIC) correct for cell-type-specific mRNA bias, which is not present in ATAC-seq data and might, thus, result in systematic errors.

      On a similar note, it could be made more explicit which adaptations were introduced in EPIC, besides the ad-hoc ATAC-seq signature, to make it applicable to this type of data.

      Given that the final applicability of EPIC-ATAC is on real bulk RNA-seq data, whose characteristics might not be completely recapitulated by pseudo-bulk samples, it would be interesting to see EPIC and EPIC-ATAC compared on a dataset with matched, real bulk RNA-seq and ATAC-seq, respectively. It would nicely complement the analysis of Figure 7 and could be used to dissect the commonalities and peculiarities of these two approaches.

    1. You can think of it as the following cycle:software engineer writes codeusers get new featuresmore users use your productscompany profits from productsSo code is just a tool to get profit.

      The core software development process

    1. Since bots are computer programs, let’s look at the structure of code written in programming languages. With all languages (including programming languages), you combine pieces of the language together according to specific rules in order to create meaning. For example: Consider this sentence in English: I was at UW (University of Washington, Seattle) yesterday. In our constructing that sentence, we used a number of English language rules, such as: Putting the subject I before the verb was Ending the sentence with a period . Making a parenthetical remark with a matching opening parenthesis ( and closing parenthesis ). This parenthetical remark clarified the part of the sentence before it UW. Programming languages also have their own set of rules for combining and organizing pieces of code in order to create meaning. We will look at some of these rules in these sections:

      User Interface (UI) Input Mechanism: This is how users interact with the bot. It could be through text (as in chatbots), voice commands, or even through visual inputs in more advanced systems. Output Mechanism: This refers to how the bot communicates back to the user, which can also be text, spoken language, or images and other media.

    1. On code-authoring tasks, students in the Codex group had a significantly higher correctness score (80%) than the Baseline (44%), and overall finished the tasks significantly faster. However, on the code-modifying tasks, both groups performed similarly in terms of correctness, with the Codex group performing slightly better (66%) than the Baseline (58%).

      In a study, students who learned to code with AI made more progress during training sessions, had significantly higher correctness scores, and retained more of what they learned compared to students who didn't learn with AI.

    1. However, it is critical to know that just because one adheres to a code of ethics, it does not mean there will never be conflict. What is unfortunately inherent in all human relationships is a level of conflict, even when one has good intentions. So the question then is what happens when conflicts or perceived ethical violation occurs especially when a designer is engaged in collecting data needed for learner analysis?

      The authors highlight the importance of ethical considerations in learner analysis, noting that conflicts or perceived ethical violations can arise even when designers adhere to a code of ethics. This raises questions about how designers should address such conflicts, particularly when collecting data for learner analysis. Ethical conduct is crucial in ensuring that the design process respects the rights and dignity of learners.

  5. Mar 2024
    1. https://archive.org/details/run-de-1986-10/page/120/mode/2up

      "RUN – Unabhängiges Commodore Computermagazin", Ausgabe 10/Oktober 1986, which has a hexdump code listing of a C64 Zettelkasten

      ᔥ[Michael Gisiger[]] in mastodon: (@gisiger@nerdculture.de)

      Lust auf #Retrocomputing und #PKM mit einem #Zettelkasten? Bitte schön, in der Oktober-Ausgabe 1986 des #Commodore Magazins RUN findet sich ein Listing für den #C64 dazu. Viel Spass beim Abtippen 😅

      https://archive.org/details/run-de-1986-10/page/120/mode/2up

      See additional conversation at: https://www.reddit.com/r/c64/comments/1bg0ja1/does_anyone_have_the_zettelkasten_program_from/?utm_source=share&utm_medium=web2x&context=3

    1. 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

      Reply to Reviewers

      We are grateful to the three reviewers for their careful and constructive critiques of our preprint. We will address all of their comments and suggestions, which help to make our paper more precise and understandable. In our replies, we use 'Patterson, eLife (2021)' as shorthand for Patterson, Basu, Rees & Nurse, eLife 2021:10.

      Reviewer #1 (Evidence, reproducibility and clarity (Required)): Novák and Tyson present a model-based analysis of published data that had claimed to demonstrate bistable activation of CDK at the G2/M transition in fission yeast. They point out that the published data does not distinguish between ultra-sensitive (switch-like, but reversible) and bistable (switch-like, but irreversible) activation. They back up their intuition with robust quantitative modeling. They then point out that, with a simple experimental modification, the published experiments could be repeated in a way that would test between the ultra-sensitive and bistable possibilities.

      This is an accurate and concise summary of our paper.

      Therefore, this is a rare paper that makes a specific modeling-based prediction and proposes a straightforward way to test it. As such, it will be of interest to a broad range of workers involved in the fields cell cycle and regulatory modeling.

      We agree that our work will be of interest to a broad range of scientists studying cell cycle regulation and mathematical modeling of bistable control systems.

      Nonetheless, attention to the following points would improve the manuscript. The authors should be more careful about how they describe protein abundance. They often refer to protein level. I believe in every case they mean protein concentration, but this is not explicitly stated; it could be interpreted as number of protein molecules per cell. The authors should either explicitly state that level means concentration or, more simply, use concentration instead of level.

      A valid criticism that has been addressed in the revised version.

      The authors should explain why they include stoichiometric inhibition of CDK by Wee1 in their model. Is it required to make the model work in the wild-type case, or only in the CDK-AF case? My intuition is it should only be required in the AF case, but I would like to know for sure. Also, they should state if there is any experimental data for such regulation.

      Bistability of the Tyr-phosphorylation switch requires 'sufficient' nonlinearity, which may come from the phosphorylation and dephosphorylation reactions that interconvert Cdk1, Wee1 and Cdc25. The easiest way to model these interconversion reactions is to use Hill- or Goldbeter-Koshland functions for the phosphorylation and dephosphorylation of Wee1 and Cdc25, but this approach is not appropriate for Gillespie SSA, which assumes elementary reactions. Both Wee1 and Cdc25 are phosphorylated on multiple sites, which we approximate by double phosphorylation; but this level of nonlinearity is not sufficient to make the switch bistable. In addition, stochiometric inhibition is a well-known source of nonlinearity, and in the Wee1:Cdk1 enzyme:substrate complex, Cdk1 is inhibited because Wee1 binds to Cdk1 near its catalytic site. In our model, stoichiometric inhibition of Cdk1 by Wee1 is required for bistability even in the wild-type case because the regulations of Wee1 and Cdc25 by phosphorylation are not nonlinear enough. There is experimental evidence that stoichiometric inhibition of Cdk1 by Wee1 is significant: mik1D wee1ts double mutant cells at the restrictive temperature (Lundgren, Walworth et al. 1991) are less viable than AF-Cdk1 (Gould and Nurse 1989). Furthermore, Patterson (eLife, 2021) found weak 'bistability' when they used AF-Cdk1 to induce mitosis. This puzzling observation suggests a residual feedback mechanism in the absence of Tyr-phosphorylation. Our model accounts for this weak bistability by assuming that free CDK1 can phosphorylate and inactivate the Wee1 'enzyme' in the Wee1:Cdk1 complex, which makes CDK1 and Wee1 mutual antagonists. This reaction is based on formation of a trimer, Cdk1:Wee1:Cdk1, which is possible since CDK1 phosphorylation of Wee1 occurs in its N-terminal region, which lies outside the C-terminal catalytic domain of Wee1 (Tang, Coleman et al. 1993). These ideas have been incorporated into the text in the subsection describing the model (see lines120-125).

      The authors should explicitly state, on line 131, that the fact that "the rate of synthesis of C-CDK molecules is directly proportional to cell volume" results in a size-dependent increase in the concentration of C-CDK.

      The accumulation of C-CDK molecules in fission yeast cells is complicated. In general, we may assume that larger cells have more ribosomes and make all proteins faster than do smaller cells. Absent other regulatory effects, the number of protein molecules is proportional to cell volume, and the concentration is constant. But, in Patterson's experiments, the number of C-CDK molecules is zero at the start of induction and rises steeply thereafter (see lines 147-148), and the rate of increase (#molec/time) is proportional to the size of the growing cell.

      The authors should explain, on line 100, why they are "quite sure the bistable switch is the correct interpretation".

      Line 105-106: "Although we suspect that the mitotic switch is bistable,.."

      On line 166, include the units of volume.

      Done

      On lines 152 and 237, "smaller protein-fusion levels "should be replaced with "lower protein-fusion concentrations".

      Done

      **Referee cross-commenting** *I concur with the other two reviews. *

      Reviewer #1 (Significance (Required)): *The paper is significant in that it points out an alternative interpretation for an important result in an important paper. Specifically, it points out that the published data is consistent with activation of CDK at the G2/M transition in fission yeast could be ultra-sensitive (switch-like, but reversible) instead of bistable (switch-like, but irreversible). The distinction is important because it has been claimed, by the authors of the submitted manuscript among others, that bistability is required for robust cell-cycle directionality. *

      We agree with this assessment.

      However, activation of CDK at the G2/M transition in other species has been shown to be bistable and the authors state that they are "quite sure the bistable switch is the correct interpretation". So, the paper is more likely an exercise in rigor than an opportunity to overturn a paradigm.

      We were the first authors to predict that the G2/M switch is bistable (J. Cell Sci., 1993) and among the first to prove it experimentally in frog egg extracts (PNAS, 2004). Our models (Novak and Tyson 1995, Novak, Pataki et al. 2001, Tyson, Csikasz-Nagy et al. 2002, Gerard, Tyson et al. 2015) of fission yeast cell-cycle control rely on bistability of the G2/M transition; so, understandably, we believe that the transition in fission yeast is a bistable switch. But the 'bistable paradigm' has never been directly demonstrated by experimental observations in fission yeast cells. The Patterson paper (eLife, 2021) claims to provide experimental proof, but we demonstrate in our paper that Patterson's experiments are not conclusive evidence of bistability. Furthermore, we suggest that a simple change to Patterson's protocol could provide convincing evidence that the G2/M switch is either monostable or bistable. We are not proposing that the switch is monostable; we would be quite surprised if the experiment, correctly done, were to indicate a reversible switch. Our point is simply that the published experiments are inconclusive. The point we are making is neither a mere 'exercise in rigor' nor a suggestion to 'overturn a paradigm.' Rather it is a precise theoretical analysis of a central question of cell cycle regulation that should be of interest to both experimentalists and mathematical modelers.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)): Summary: The manuscript asks whether the data reported in Patterson et al. (2021) is consistent with a bistable switch controlling the G2/M transition in fission yeast. Patterson et al. (2021) use an engineered system to decouple a non-degradable version of Cyclin-dependent kinase (CDK) from cell growth and concomitantly measure CDK activity (by the nuclear localization of a downstream target, Cut3p). They observe cells with indistinguishable CDK levels but two distinct CDK activities, which they posit shows bistable behavior. In this study, the authors ask if other models can also explain this data. The authors use both deterministic and Gillespie based stochastic simulations to generate relationships between CDK activities and protein levels for various cell sizes. They conclude that the experiments performed in Patterson et al. are insufficient to distinguish between a bistable switch and a reversible ultrasensitive switch. They propose additional experiments involving the use a degradable CDK construct to also measure the inactivation kinetics.

      This is an accurate summary of our paper.

      They propose that a bistable switch will have different forward (OFF->ON) and backward (ON->OFF) switching rates. A reversible ultrasensitive switch will have indistinguishable switching rates.

      Our analysis of Patterson's (2021) experiments is based on the well-known fact that the threshold for turning a bistable switch on is significantly different from the threshold for turning it off (in Patterson's case, the 'threshold' is the level of fusion protein in the cell when CDK is activated), whereas for a reversible, ultrasensitive switch, the two thresholds are nearly indistinguishable. The 'rate' at which the switch is made is a different issue, which we do not address explicitly. In the experiments and in our model, the switching rates are fast, whether the switch is bistable or monostable. The results are interesting and worth publication in a computational biology specific journal, as they might only appeal to a limited audience.

      We think our results should also be brought to the attention of experimentalists studying cell cycle regulation, because Patterson's paper (eLife, 2021) presents a serious misunderstanding of the existence and implications of 'bistability' of the G2/M transition in fission yeast. Whereas Patterson's work is an elegant and creative application of genetics and molecular biology to an important problem, it is not backed up by quantitative mathematical modeling of the experimental results. In that sense, Patterson's work is incomplete, and its shortcomings need to be addressed in a highly respected journal, so that future cell-cycle experimentalists will not make the same-or similar-mistakes.

      Several ideas need to be clarified and additional information needs to be provided about the specific parameters used for the simulations: Major comments: #1 The parameters need to be made more accessible by means of a supplementary table and appropriate references need to be cited.

      Two new supplementary tables (S1 and S2) summarize the dynamic variables and parameter values.

      It is not clear why Michaelis Menten kinetics will not be applicable to this system. Has it been demonstrated that the Km s of the enzymes are much greater than the substrate concentrations for all the reactions? If yes, please cite.

      MM kinetics are not appropriate for such protein interaction networks because one protein may be both an enzyme and a substrate for a second protein (e.g., Wee1 and CDK, or Cdc25 and CDK). So, the condition for validity of MM kinetics (enzyme concen ≪ substrate concen) cannot be satisfied for both reactions. Indeed, enzyme concen ≈ substrate concen is probably true for most reactions in our network. Hence, it is advisable to stick with mass-action rate laws. Furthermore, MM kinetics are a poor choice for 'propensities' in Gillespie SSA calculations, as has been shown by many authors (Agarwal, Adams et al. 2012, Kim, Josic et al. 2014, Kim and Tyson 2020).

      It will not be surprising if the simulation with Michaelis Menten would alter the dynamics shown in this study. A reversible switch with two different enzymes (catalyzing the ON->OFF and OFF->ON transitions) having different kinetics can give asymmetric switching rates. This would directly contradict what has been shown in Figure 7A-D.

      We don't follow the reviewer's logic here. The two transitions, off → on and on → off, are already driven by different molecular processes (dephosphorylation of inactive CDK-P by Cdc25 and phosphorylation of active CDK by Wee1, respectively). Positive feedback of CDK activity on Cdc25 and Wee1 (++ and −−, respectively) causes bistability and asymmetric switching thresholds. Switching rates, which are determined by the kinetic rate constants of the up and down processes, are of secondary importance to the primary question of whether the switch is monostable or bistable.

      #2 Line 427: The authors use a half-time of 6 hours in their model as Patterson et al. used a non-degradable construct. It is not clear why dilution due to cell growth has not been considered. The net degradation rate of a protein is the sum of biochemical degradation rate and growth dilution rate. The growth dilution rate seems significant (140 mins doubling time or 0.3 h-1 dilution rate) relative to assumed degradation rate (0.12 h-1). Please clarify why was the effect of dilution neglected in the model or show by sensitivity analysis this does not change the predicted CDK activation thresholds.

      The reviewer highlights an important effect, but it is not relevant to our calculations. In the deterministic model used to calculate the bifurcation diagrams, both cell volume and the concentration of the non-degradable Cdc13:Cdk1 dimer are kept constant; therefore, there is no dilution effect. The stochastic model deals with changing numbers of molecules per cell; the dilution effect is taken into account by the appearance of cell volume, V(t), at appropriate places in the propensity functions. In other words: in the deterministic model, which is written for concentration changes, the dilution term, −(x/V)(dV/dt), is zero because V=constant; in the stochastic model, written in terms of numbers of molecules, dilution effects are implicit in the propensity functions.

      *#3 Line 402 The authors state that the production rate of the Cdk protein is 'assumed' proportional to the cell volume. The word 'assumed' is incorrect here as a simple conversion of concentration-based differential equation (with constant production rate) to molecular numbers would show that production rate is proportional to the volume. This is not an assumption. *

      Correct; we modified the text (see line 450-462). The role of cell volume in production rate is more relevant to the case of Cdc25, where we assume that its production rate, Δconcentration/Δt, is proportional to V, because the concentration of Cdc25 in the cell increases as the cell grows. We added two references (Keifenheim, Sun et al. 2017, Curran, Dey et al. 2022) to justify this assumption. In the stochastic code, the propensity for synthesis of Cdc25 molecules is proportional to V2.

      #4 Line 423 Please cite the appropriate literature that shows that fission yeast growth during cell division is exponential. If the dynamics are more complicated, involving multiple phases of growth during cell division, please state so.

      We now acknowledge that volume growth in fission yeast, rather than exponential, is bilinear with a brief non-growing phase at mitosis (Mitchison 2003). However, we suggest that our simplifying assumption of exponential growth is appropriate for the purposes of these calculations. See line 473-476: "In our stochastic simulations, we assume that cell volume is increasing exponentially, V(t) = V0eμt. Although fission yeast cells actually grow in a piecewise linear fashion (Mitchison 2003), the simpler exponential growth law (with doubling time @ 140 min) is perfectly adequate for our purposes in this paper.."

      *#5 Line 250 The authors convert the bistable version of the CDK switch to reversible sigmoidal by assuming that Wee1 and Cdc25 phosphorylation is proportional to the CDK level rather than activity, which seems biochemically unrealistic. This invokes an altered circuit architecture where inactive CDK has enough catalytic activity to phosphorylate the two modifying enzymes (Wee1/Cdc25) but not enough to drive mitosis. This might be possible if the Km of CDK for Wee1/Cdc25 is lower relative to other downstream substrates that drive mitosis. The authors can reframe this section of the paper to state this possibility, which might be interesting to experimentalists. *

      The reviewer is correct that the molecular biology underlying our 'reversible sigmoidal' model is biochemically unrealistic. But, in our opinion, this is the simplest way to convert our bistable model into a monostable, ultrasensitive switch while maintaining the basic network structure in Fig. 1. Our purpose is to show that a monostable model-only slightly changed from the bistable model-can account for Patterson's experimental data equally well. If Nurse's group modifies the experimental protocol as we suggest and their new results indicate that the G2/M transition in fission yeast is bistable, then our reversible sigmoidal model, having served its purpose, can be forgotten. If they show that the transition is not bistable, then both experimentalists and theoreticians will have to think about biochemically realistic mechanisms that can account for the new data...and everything else we already know about the G2/M transition in fission yeast.

      #6 It is difficult to phenomenologically understand a bistable switch just based on differences in activation and inactivation thresholds. For example, a reversible ultrasensitive switch also shows a difference in activation and inactivation thresholds (Figure 7D). How much of a difference should be expected of a bistable switch versus reversible switch?

      We show how much of a difference can be expected by contrasting Fig. 7 to Fig. 8. For the largest cells (panel D of both figures), the difference is small and probably undetectable experimentally. For medium-sized cells (panel C), the difference is larger but probably difficult to distinguish experimentally. Only the smallest cells (panel B) provide an opportunity for clearly distinguishing experimentally between monostable and bistable switching.

      *Moreover, as the authors clearly understand (line 275), time-delays in activation and inactivation reactions can inflate these differences. In the future, if the authors can convert the equations to potential energy space as done in Acar et al. 2005 (Nature 435:228) in Figure 3c-d, it will be useful. Also, predicting the distribution of switching rates from the Gillespie simulation might be informative and can be directly compared to experimental measurements in the future (if the Cut3p levels in nucleus and cytosol equilibrates fast enough or other CDK biosensors are developed). *

      The famous paper by Acar et al. (2005) is indeed an elegant experimental and theoretical study of bistability ('cellular memory') in the galactose-signalling network of budding yeast. We have included a comparison of Patterson et al. with Acar et al. in our Conclusions section (lines 353-368):

      "It is instructive, at this point, to compare the work of Patterson et al. (2021) to a study by Acar et al. (Acar, Becskei et al. 2005) of the galactose-signaling network of budding yeast. Combining elegant experiments with sophisticated modeling, Acar et al. provided convincing proof of bistability ('cellular memory') in this nutritional control system. They measured PGAL1-YFP expression (the response) as a function of galactose concentration in the growth medium (the signal), analogous to Patterson's measurements of CDK activity as a function of C-CDK concentration in fission yeast cells. In Acar's experiments, the endogenous GAL80 gene was replaced by PTET-GAL80 in order to maintain Gal80 protein concentration at a constant value determined by doxycycline concentration in the growth medium. The fixed Gal80p concentration in Acar's cells is analogous to cell volume in Patterson's experiments. In Fig.3b of Acar's paper, the team plotted the regions of monostable-off, monostable-on and bistable signaling in dependence on their two control parameters, external galactose concentration and intracellular Gal80p concentration, analogous to our Fig.4. Because Acar's experiments explored both the off → on and on → off transitions, they could show that their observed thresholds (the red circles) correspond closely to both saddle-node bifurcation curves predicted by their model. On the other hand, Patterson's experiments (as analyzed in our Fig.4) probe only the off → on transition."

      The purpose of our paper is to show that Patterson-type experiments can and should be done so as to probe both thresholds, as was done by van Oudenaarden's team. They went further to characterize their bistable switch in terms of 'the concept of energy landscapes'. We think it is premature to pursue this idea in the context of the G2/M transition in fission yeast until there is firm, quantitative data characterizing the nature of the 'presumptive' bistable switch in fission yeast.

      Minor comments: #1 Line 2: Please replace "In most situations" to "In favorable conditions"

      Done.

      **Referee cross-commenting** I agree with Reviewer 1 that this falls more under pointing out an alternative interpretation of a single experiment than challenging widely supported orthodoxy about how the eukaryotic cell cycle leaves mitosis.

      As we said earlier, our 1993 paper in J Cell Sci is the source of this orthodox view, and it is widely supported at present because there is convincing experimental evidence for bistability in frog egg extracts, budding yeast cells and mammalian cells. Patterson's paper is not sound evidence for bistability of the G2/M transition in fission yeast cells. It is important for experimentalists to know why the experiments fail to confirm bistability, and important for someone to do the experiment correctly in order to confirm (or, what would be really interesting, to refute) the expectation of bistability at the G2/M transition in fission yeast cells.

      Reviewer #2 (Significance (Required)): Suitable for specialist comp bio journal eg PLoS Comp Bio

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

      The paper by Novak and Tyson revisits a recent paper from Nurse group on the bistability of mitotic switch in fission yeast using mathematical modelling. The authors extend their older models of mitotic entry check point and implement both deterministic and stochastic version of new model. They show this model does indeed possess bistability and show that combined with stochastic fluctuations the model can show bimodality for the cyclin-CDK activity at a particular cell size consistent with the recent experimental data. However, the authors also show alternative model that has mono-stable ultrasensitivity can also explain the data and suggest experiments that can prove the existence of hysteresis and therefore bistability.

      Right on.

      While the biological implication of the study is well explained, the authors can improve the presentation of their model and the underlying assumptions. I have the following comments and suggestions for improvement of the paper.

        • The cartoon of the mathematical model is confusing at places, for example the wee1-CDK complex according to the equations either dissociates back to wee1 and CDK or gives rise to pCDK and wee1, the arrow below is confusing as it implies it can also give rise to wee1p, the CDK phosphorylation of wee1 is already included in the diagram. Also, the PP2A is put on the arrow for all reactions but for wee1p2 to wee1p its action shown with a dashed line. Also, I wondered if wee1p and wee1p2 can also bind CDK and sequester or phosphorylate CDK?* We are sorry for the confusion and have improved Fig. 1.
      1. The rates and variables in the ODEs are not fully described. Also sometimes unclear what is parameter and what is a variable, I had to look at the code.*

      We now include tables of variables and parameter values, with explanatory notes.

      • The model has quite a few parameters, but these are not at all discussed in the paper. How did the authors come up with these particular set of parameters, has there been some systematic fitting, or tuning by hand to produce a good fit to the data? I could only see the value of the parameters in the code, but perhaps a table with the parameters of the model, what they mean and their value (and perhaps how the values is obtained) is missing.*

      The parameters were tuned by hand to fit Patterson's data, based, of course, on our extensive experience fitting mathematical models to myriad data sets on the cell division cycles of fission yeast, budding yeast, and frog egg extracts. We now provide a table of parameter values.

      • The authors are using the Gillespie algorithm with time varying parameters (as some rates depend on volume and volume is not constant). Algorithm needs to be modified slightly to handle this (see for example Shahrezaei et al Molecular Systems Biology 2008). *

      A valid criticism, but the rate of cell volume increase is very slow compared to the propensities of the biochemical reactions. We write (lines 492-498):

      "In each step of the SSA, the volume of the cell is increasing according to an exponential function, and, consequently, the propensities of the volume-dependent steps are, in principle, changing with time; and this time-dependence could be taken into account explicitly in implementing Gillespie's SSA (Shahrezaei, Ollivier et al. 2008). However, the step-size between SSA updates is less than 1 s compared to the mass-doubling time (140 min) of cell growth. So, it is warranted to neglect the change in V(t) between steps of the SSA, as in our code."

      • The authors correctly point out, ignoring mRNA has resulted in underestimation of noise, however another point is that mRNA life times are short and that also affects the timescale of fluctuations and this may be relevant to the switching rates between the bistable states. *

      A valid point, but to include mRNA's would double the size of the model. Furthermore, we have little or no data about mRNA fluctuations in fission yeast cells, so it would be impossible to estimate the values of all the new parameters introduced into the model. Finally, the switching rates between bistable states (or across the ultrasensitive boundary) are not the primary focus of Patterson's experiments or our theoretical investigations. So, we propose to delay this improvement to the model until the relevant experimental data is available.

      • In the introduction add, "In this study" to "Intrigued by these results, we investigated their experimental observations with a model of bistability in the activation of cyclin-CDK in fission yeast." *

      Done

      Reviewer #3 (Significance (Required)): Overall, this is an interesting study that revisits an old question and some recent experimental data. The use of stochastic modelling in explaining variability and co-existence of cell populations in the context of cell cycle and comparison to experimental data is novel and of interest to the communities of cell cycle researchers, systems biologists and mathematical biologists.

      We agree. Thanks for the endorsement

      References

      Acar, M., A. Becskei and A. van Oudenaarden (2005). "Enhancement of cellular memory by reducing stochastic transitions." Nature 435(7039): 228-232.

      Agarwal, A., R. Adams, G. C. Castellani and H. Z. Shouval (2012). "On the precision of quasi steady state assumptions in stochastic dynamics." J Chem Phys 137(4): 044105.

      Curran, S., G. Dey, P. Rees and P. Nurse (2022). "A quantitative and spatial analysis of cell cycle regulators during the fission yeast cycle." Proc Natl Acad Sci U S A 119(36): e2206172119.

      Gerard, C., J. J. Tyson, D. Coudreuse and B. Novak (2015). "Cell cycle control by a minimal Cdk network." PLoS Comput Biol 11(2): e1004056.

      Gould, K. L. and P. Nurse (1989). "Tyrosine phosphorylation of the fission yeast cdc2+ protein kinase regulates entry into mitosis." Nature 342(6245): 39-45.

      Keifenheim, D., X. M. Sun, E. D'Souza, M. J. Ohira, M. Magner, M. B. Mayhew, S. Marguerat and N. Rhind (2017). "Size-Dependent Expression of the Mitotic Activator Cdc25 Suggests a Mechanism of Size Control in Fission Yeast." Curr Biol 27(10): 1491-1497 e1494.

      Kim, J. K., K. Josic and M. R. Bennett (2014). "The validity of quasi-steady-state approximations in discrete stochastic simulations." Biophys J 107(3): 783-793.

      Kim, J. K. and J. J. Tyson (2020). "Misuse of the Michaelis-Menten rate law for protein interaction networks and its remedy." PLoS Comput Biol 16(10): e1008258.

      Lundgren, K., N. Walworth, R. Booher, M. Dembski, M. Kirschner and D. Beach (1991). "mik1 and wee1 cooperate in the inhibitory tyrosine phosphorylation of cdc2." Cell 64(6): 1111-1122.

      Mitchison, J. M. (2003). "Growth during the cell cycle." Int Rev Cytol 226: 165-258.

      Novak, B., Z. Pataki, A. Ciliberto and J. J. Tyson (2001). "Mathematical model of the cell division cycle of fission yeast." Chaos 11(1): 277-286.

      Novak, B. and J. J. Tyson (1995). "Quantitative Analysis of a Molecular Model of Mitotic Control in Fission Yeast." J Theor Biol 173: 283-305.

      Patterson, J. O., S. Basu, P. Rees and P. Nurse (2021). "CDK control pathways integrate cell size and ploidy information to control cell division." Elife 10.

      Shahrezaei, V., J. F. Ollivier and P. S. Swain (2008). "Colored extrinsic fluctuations and stochastic gene expression." Mol Syst Biol 4: 196.

      Tang, Z., T. R. Coleman and W. G. Dunphy (1993). "Two distinct mechanisms for negative regulation of the Wee1 protein kinase." EMBO J 12(9): 3427-3436.

      Tyson, J. J., A. Csikasz-Nagy and B. Novak (2002). "The dynamics of cell cycle regulation." Bioessays 24(12): 1095-1109.

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      Referee #3

      Evidence, reproducibility and clarity

      The paper by Novak and Tyson revisits a recent paper from Nurse group on the bistability of mitotic switch in fission yeast using mathematical modelling. The authors extend their older models of mitotic entry check point and implement both deterministic and stochastic version of new model. They show this model does indeed possess bistability and show that combined with stochastic fluctuations the model can show bimodality for the cyclin-CDK activity at a particular cell size consistenent with the recent experimental data. However, the authors also show alternative model that has mono-stable ultrasensitivity can also explain the data and suggest experiments that can prove the existence of hysteresis and therefore bistability.

      While the biological implication of the study is well explained, the authors can improve the presentation of their model and the underlying assumptions. I have the following comments and suggestions for improvement of the paper. <br /> 1. The cartoon of the mathematical model is confusing at places, for example the wee1-CDK complex according to the equations either dissociates back to wee1 and CDK or gives rise to pCDK and wee1, the arrow below is confusing as it implies it can also give rise to wee1p, the CDK phosphorylation of wee1 is already included in the diagram. Also, the PP2A is put on the arrow for all reactions but for wee1p2 to wee1p its action shown with a dashed line. Also, I wondered if wee1p and wee1p2 can also bind CDK and sequester or phosphorylate CDK? 2. The rates and variables in the ODEs are not fully described. Also sometimes unlcear what is parameter and what is a variable, I had to look a the code. 3. The model has quite a few parameters, but these are not at all discussed in the paper. How did the authors come up with these particular set of parameters, has there been some systematic fitting, or tuning by hand to produce a good fit to the data? I could only see the value of the parameters in the code, but perhaps a table with the parameters of the model, what they mean and their value (and perhaps how the values is obtained) is missing. 4. The authors are using the Gillespie algorithm with time varying parameters (as some rates depend on volume and volume is not constant). Algorithm needs to be modified slightly to handle this (see for example Shahrezaei et al Molecular Systems Biology 2008). 5. The authors correctly point out, ignoring mRNA has resulted in underestimation of noise, however another point is that mRNA life times are short and that also affects the timescale of fluctuations and this may be relevant to the switching rates between the bistable states. 6. In the introduction add, "In this study" to "Intrigued by these results, we investigated their experimental observations with a model of bistability in the activation of cyclin-CDK in fission yeast.

      Significance

      Overall, this is an interesting study that revisits an old question and some recent experimental data. The use of stochastic modelling in explaining variability and co-existence of cell populations in the context of cell cycle and comparison to experimental data is novel and of interest to the communities of cell cycle researchers, systems biologists and mathematical biologists.