It is the role of those who have intellect to spread that intellect and foster it in future generations. According to Anthropology (the study of humans), we are social creatures; in ages past, we passed down our history orally from generation to generation. With the emergence of the internet and social media, that onus to pass on our wisdom has not changed and it becomes more critical now than ever. If we allow misinformation to creep into the societal consensus for truth, then the disadvantaged will only become more disadvantaged as literacy rate plummet, and access to jobs that are AI-proof evaporate due to demand and more skilled applicants seeking entry. Education and skill are both tools we can use to navigate a highly competitive society and break the damning cycle of oppression.

Design idea to disrupt fatalism: mastery paths, revision cycles, and public products build efficacy and purpose. The ability to track progress and revise work helps individuals build toward their goals. According to Marzano, goal setting is best practice for K12 students to understand the purpose of the day's lessons. It is my supposition that goal setting would naturally extend to adults; however, this requires further research. Although the supposition seems reasonable since goal setting is that reflective carrot we dangle before ourselves to urge us ever onwards.

Thinking of life's situations as problems that require a solution fuels innovation within our societal framework and births creativity (Bloom's Revised Pyramid's pinnacle). The ability to think outside of the standard deviation of thoughts further enhances human potential.

Adult learning identity work: include reflective e-portfolios that show growth over time rather than teaching to criterion-referenced tests. Design and Development (as well as personal growth) is an iterative and lifelong process. If we consider Lean Six Sigma principles, a majority of problems people face in an institution are Process problems, and rarely people problems; therefore, the process of learning aims to eliminate inefficiencies that hold us back from becoming the best people we are capable of being.

Instructor presence should scaffold autonomy (choice boards, contract grading, portfolios) rather than enforce compliance for its own sake.

Center sense-making. Use simulations and data-driven inquiries instead of information dumps. Memorizing facts only applies to Bloom's Revised Taxonomy's lowest levels of cognition (Remembering and Understanding) rather than more mentally onerous levels like (Analysis and Evaluation).

Dialogue as method. Operationalize via protocols (Socratic circles, peer review rubrics) that make turn-taking and questioning explicit.

Beware trainings that target attitudes while leaving structures intact. Pair mindset work with structural change projects. This also illustrates the struggle we face in Capitalism; the struggle between Wealthy and Impoverished.

This reminds me of power dynamics in design. Who decides what knowledge counts in curriculum development? As LDT practitioners, we need to ensure co-design with learners and stakeholders so that knowledge emerges collaboratively.

The banking model can be critiqued through heutagogy (self-determined learning). This makes me think of how corporate LMS systems often "deposit" compliance modules without engaging learners in authentic practice. How can we shift these designs to be more problem-posing, even within restrictive corporate or K-12 mandates?

This is analogous to drill-and-kill software in edtech that promotes rote learning. It's a reminder to incorporate Gagne's conditions of learning--especially feedback, practice, application--to present surface-level memorization.

Friere critiques the traditional model where teachers merely deliver information. In instructional design terms, this aligns with transmission-focused pedagogy, which ignores learner agency. As an LDT student, I recognize the parallels modern critiques of lecture-based elearning modules that fail to foster interactivty or meaningful engagement.

"The ISIN code of the selected Instrument (Instrument of Series investment unit) and the currency are automatically filled from the Instrument's base data."

Ezek a nyelvesítetlen képek szörnyen néznek ki. Szóljatok, miben segíthetek ennek a megoldására.

Helyes angol szöveg: "The condition for registration is that the investment unit is registered as an instrument. "

Helyes angol fordítás: "For each investment fund or unit based portfolio at least one series needs to be registered."

A perquisition for data recording is, if the valuation of Funds or Insurance portfolios are unit-based, than the related units are recorded as Instruments.

A helyes nagol fordítás: "On the Share classes tab, the characteristics of investment fund series, and in the case of Funds or Insurance companies, the units of portfolios can be specified."

A helyes angol szöveg: "The displayed fields on modal are as follows:"

Helyes angol szöveg: "In this field the Client can be selected, then the Account recorded in its base data."

Módosított magyar szöveg: "Portfólió neve: Portfólió neve mezőre kattintva pop-up ablak jelenik meg."

Helyes angol fordítás: "After filling the data on the General data tab, the data can be saved with the Save button, after that further tabs of the portfolio appear."

Helyes angol fordítás: "NAV reconciliation group: Group of portfolio at the Asset Manager/Custodian partner to which the net asset value checking applies. Identifies the NAV reconciliation file . Values: Client-specific"

Helyes angol fordítás: The identifier code for the portfolio for MNB 30 reports

Helyesangol fordítás: Helyes angol szöveg: "In case of investment fund units, the ISIN code of the first series (even if it is closed) In case of other funds or insurance, portfolios, the code provided by the fund or insurer"

I completely agree with this statement. After reading a text the first time, I can recall what it was about, but I often fail to identify any of the writing choices that the author made in regards to their personal style. It usually takes reading the text a few times to notice the hidden meanings behind some of their descriptions, or to comment on the style of writing that was employed.

Active reading is more than just going through the words. It is about paying attention to what is being said and how it is being said. This conscious effort to pay attention helps you notice the patterns in the text and the choices the writer makes, helping you discern what they mean when making such choices. It definitely takes focus. For example, when you are tired and reading the same paragraph over and over again, you are not taking in the text and reading actively. This is a mostly universal experience that stresses the importance of active reading.

I love that GAI is mentioned as I see it everywhere and the clear boundaries are set on when it is allowed and not.

I'm glad everyone is welcome in our environment. I cannot wait to participate in our space. (I cannot figure out how to annotate, this is the best I got)

Tin Tin wandering a primitive jungle temple, innocent, unclothed and free

Rolling down grassy hills

Snuggling into a nest of pillows and duvets when you're experiencing bad excrement before

Soft sighs and snuggles

This is something that I have always enjoyed about writing. It allows you to incorporate new information into any previous experiences you might have. The combination of these things often leads to new insights and ways of thinking.

This statement is great in setting expectations for our writing, ensuring it has meaning both for ourselves and others. This will help immensely in any projects that we have this semester.

This is an extremely helpful resource, as a handful of classes I have taken in the past have not introduced how to format work. Including an example is a great tool as well, ensuring that we can verify we have the correct formatting before turning in an assignment.

eLife Assessment

This important study presents a cross-species and cross-disciplinary analysis of cortical folding. The authors use a combination of physical gel models, computational simulations, and morphometric analysis, extending prior work in human brain development to macaques and ferrets. The findings support the hypothesis that mechanical forces driven by differential growth can account for major aspects of gyrification. The evidence presented, though limited in certain species-specific and parametric details, is overall strong and convincingly supports the central claims; the findings will be of broad interest in developmental neuroscience.

Reviewer #1 (Public review):

The manuscript by Yin and colleagues addresses a long-standing question in the field of cortical morphogenesis, regarding factors that determine differential cortical folding across species and individuals with cortical malformations. The authors present work based on a computational model of cortical folding evaluated alongside a physical model that makes use of gel swelling to investigate the role of a two-layer model for cortical morphogenesis. The study assesses these models against empirically derived cortical surfaces based on MRI data from ferret, macaque monkey, and human brains.

The manuscript is clearly written and presented, and the experimental work (physical gel modeling as well as numerical simulations) and analyses (subsequent morphometric evaluations) are conducted at the highest methodological standards. It constitutes an exemplary use of interdisciplinary approaches for addressing the question of cortical morphogenesis by bringing together well-tuned computational modeling with physical gel models. In addition, the comparative approaches used in this paper establish a foundation for broad-ranging future lines of work that investigate the impact of perturbations or abnormalities during cortical development.

The cross-species approach taken in this study is a major strength of the work. However, correspondence across the two methodologies did not appear to be equally consistent in predicting brain folding across all three species. The results presented in Figures 4 (and Figures S3 & S4) show broad correspondence in shape index and major sulci landmarks across all three species. Nevertheless, the results presented for the human brain lack the same degree of clear correspondence for the gel model results as observed in the macaque and ferret. While this study clearly establishes a strong foundation for comparative cortical anatomy across species and the impact of perturbations on individual morphogenesis, further work that fine-tunes physical modeling of complex morphologies, such as that of the human cortex, may help to further understand the factors that determine cortical functionalization and pathologies.

Reviewer #2 (Public review):

This manuscript explores the mechanisms underlying cerebral cortical folding using a combination of physical modelling, computational simulations, and geometric morphometrics. The authors extend their prior work on human brain development (Tallinen et al., 2014; 2016) to a comparative framework involving three mammalian species: ferrets (Carnivora), macaques (Old World monkeys), and humans (Hominoidea). By integrating swelling gel experiments with mathematical differential growth models, they simulate sulcification instability and recapitulate key features of brain folding across species. The authors make commendable use of publicly available datasets to construct 3D models of fetal and neonatal brain surfaces: fetal macaque (ref. [26]), newborn ferret (ref. [11]), and fetal human (ref. [22]).

Using a combination of physical models and numerical simulations, the authors compare the resulting folding morphologies to real brain surfaces using morphometric analysis. Their results show qualitative and quantitative concordance with observed cortical folding patterns, supporting the view that differential tangential growth of the cortex relative to the subcortical substrate is sufficient to account for much of the diversity in cortical folding. This is a very important point in our field, and can be used in the teaching of medical students.

Brain folding remains a topic of ongoing debate. While some regard it as a critical specialization linked to higher cognitive function, others consider it an epiphenomenon of expansion and constrained geometry. This divergence was evident in discussions during the Strüngmann Forum on cortical development (Silver et al., 2019). Though folding abnormalities are reliable indicators of disrupted neurodevelopmental processes (e.g., neurogenesis, migration), their relationship to functional architecture remains unclear. Recent evidence suggests that the absolute number of neurons varies significantly with position-sulcus versus gyrus-with potential implications for local processing capacity (e.g., https://doi.org/10.1002/cne.25626). The field is thus in need of comparative, mechanistic studies like the present one.

This paper offers an elegant and timely contribution by combining gel-based morphogenesis, numerical modelling, and morphometric analysis to examine cortical folding across species. The experimental design - constructing two-layer PDMS models from 3D MRI data and immersing them in organic solvents to induce differential swelling - is well-established in prior literature. The authors further complement this with a continuum mechanics model simulating folding as a result of differential growth, as well as a comparative analysis of surface morphologies derived from in vivo, in vitro, and in silico brains.

I offer a few suggestions here for clarification and further exploration:

Major Comments

(1) Choice of Developmental Stages and Initial Conditions

The authors should provide a clearer justification for the specific developmental stages chosen (e.g., G85 for macaque, GW23 for human). How sensitive are the resulting folding patterns to the initial surface geometry of the gel models? Given that folding is a nonlinear process, early geometric perturbations may propagate into divergent morphologies. Exploring this sensitivity-either through simulations or reference to prior work-would enhance the robustness of the findings.

(2) Parameter Space and Breakdown Points

The numerical model assumes homogeneous growth profiles and simplifies several aspects of cortical mechanics. Parameters such as cortical thickness, modulus ratios, and growth ratios are described in Table II. It would be informative to discuss the range of parameter values for which the model remains valid, and under what conditions the physical and computational models diverge. This would help delineate the boundaries of the current modelling framework and indicate directions for refinement.

(3) Neglected Regional Features: The Occipital Pole of the Macaque

One conspicuous omission is the lack of attention to the occipital pole of the macaque, which is known to remain smooth even at later gestational stages and has an unusually high neuronal density (2.5× higher than adjacent cortex). This feature is not reproduced in the gel or numerical models, nor is it discussed. Acknowledging this discrepancy-and speculating on possible developmental or mechanical explanations-would add depth to the comparative analysis. The authors may wish to include this as a limitation or a target for future work.

(4) Spatio-Temporal Growth Rates and Available Human Data

The authors note that accurate, species-specific spatio-temporal growth data are lacking, limiting the ability to model inhomogeneous cortical expansion. While this may be true for ferret and macaque, there are high-quality datasets available for human fetal development, now extended through ultrasound imaging (e.g., https://doi.org/10.1038/s41586-023-06630-3). Incorporating or at least referencing such data could improve the fidelity of the human model and expand the applicability of the approach to clinical or pathological scenarios.

(5) Future Applications: The Inverse Problem and Fossil Brains

The authors suggest that their morphometric framework could be extended to solve the inverse growth problem-reconstructing fetal geometries from adult brains. This speculative but intriguing direction has implications for evolutionary neuroscience, particularly the interpretation of fossil endocasts. Although beyond the scope of this paper, I encourage the authors to elaborate briefly on how such a framework might be practically implemented and validated.

Conclusion

This is a well-executed and creative study that integrates diverse methodologies to address a longstanding question in developmental neurobiology. While a few aspects-such as regional folding peculiarities, sensitivity to initial conditions, and available human data-could be further elaborated, they do not detract from the overall quality and novelty of the work. I enthusiastically support this paper and believe that it will be of broad interest to the neuroscience, biomechanics, and developmental biology communities.

Note: The paper mentions a companion paper [reference 11] that explores the cellular and anatomical changes in the ferret cortex. I did not have access to this manuscript, but judging from the title, this paper might further strengthen the conclusions.

Author response:

Reviewer 1 (Public review):

The manuscript by Yin and colleagues addresses a long-standing question in the field of cortical morphogenesis, regarding factors that determine differential cortical folding across species and individuals with cortical malformations. The authors present work based on a computational model of cortical folding evaluated alongside a physical model that makes use of gel swelling to investigate the role of a two-layer model for cortical morphogenesis. The study assesses these models against empirically derived cortical surfaces based on MRI data from ferret, macaque monkey, and human brains.

The manuscript is clearly written and presented, and the experimental work (physical gel modeling as well as numerical simulations) and analyses (subsequent morphometric evaluations) are conducted at the highest methodological standards. It constitutes an exemplary use of interdisciplinary approaches for addressing the question of cortical morphogenesis by bringing together well-tuned computational modeling with physical gel models. In addition, the comparative approaches used in this paper establish a foundation for broad-ranging future lines of work that investigate the impact of perturbations or abnormalities during cortical development.

The cross-species approach taken in this study is a major strength of the work. However, correspondence across the two methodologies did not appear to be equally consistent in predicting brain folding across all three species. The results presented in Figures 4 (and Figures S3 and S4) show broad correspondence in shape index and major sulci landmarks across all three species. Nevertheless, the results presented for the human brain lack the same degree of clear correspondence for the gel model results as observed in the macaque and ferret. While this study clearly establishes a strong foundation for comparative cortical anatomy across species and the impact of perturbations on individual morphogenesis, further work that fine-tunes physical modeling of complex morphologies, such as that of the human cortex, may help to further understand the factors that determine cortical functionalization and pathologies.

We thank the reviewer for positive opinions and helpful comments. Yes, the physical gel model of the human brain has a lower similarity index with the real brain. There are several reasons.

First, the highly convoluted human cortex has a few major folds (primary sulci) and a very large number of minor folds associated with secondary or tertiary sulci (on scales of order comparable to the cortical thickness), relative to the ferret and macaque cerebral cortex. In our gel model, the exact shapes, positions, and orientations of these minor folds are stochastic, which makes it hard to have a very high similarity index of the gel models when compared with the brain of a single individual.

Second, in real human brains, these minor folds evolve dynamically with age and show differences among individuals. In experiments with the gel brain, multiscale folds form and eventually disappear as the swelling progresses through the thickness. Our physical model results are snapshots during this dynamical process, which makes it hard to have a concrete one-to-one correspondence between the instantaneous shapes of the swelling gel and the growing human brain.

Third, the growth of the brain cortex is inhomogeneous in space and varying with time, whereas, in the gel model, swelling is relatively homogeneous.

We agree that further systematic work, based on our proposed methods, with more fine-tuned gel geometries and properties, might provide a deeper understanding of the relations between brain geometry, and growth-induced folds and their functionalization and pathologies. Further analysis of cortical pathologies using computational and physical gel models can be found in our companion paper (Choi et al., 2025), also submitted to eLife:

G. P. T. Choi, C. Liu, S. Yin, G. Sejourn´ e, R. S. Smith, C. A. Walsh, L. Mahadevan, Biophysical basis for´ brain folding and misfolding patterns in ferrets and humans. Preprint, bioRxiv 2025.03.05.641682.

Reviewer 2 (Public review):

This manuscript explores the mechanisms underlying cerebral cortical folding using a combination of physical modelling, computational simulations, and geometric morphometrics. The authors extend their prior work on human brain development (Tallinen et al., 2014; 2016) to a comparative framework involving three mammalian species: ferrets (Carnivora), macaques (Old World monkeys), and humans (Hominoidea). By integrating swelling gel experiments with mathematical differential growth models, they simulate sulcification instability and recapitulate key features of brain folding across species. The authors make commendable use of publicly available datasets to construct 3D models of fetal and neonatal brain surfaces: fetal macaque (ref. [26]), newborn ferret (ref. [11]), and fetal human (ref. [22]).

Using a combination of physical models and numerical simulations, the authors compare the resulting folding morphologies to real brain surfaces using morphometric analysis. Their results show qualitative and quantitative concordance with observed cortical folding patterns, supporting the view that differential tangential growth of the cortex relative to the subcortical substrate is sufficient to account for much of the diversity in cortical folding. This is a very important point in our field, and can be used in the teaching of medical students.

Brain folding remains a topic of ongoing debate. While some regard it as a critical specialization linked to higher cognitive function, others consider it an epiphenomenon of expansion and constrained geometry. This divergence was evident in discussions during the Strungmann Forum on cortical development (Silver¨ et al., 2019). Though folding abnormalities are reliable indicators of disrupted neurodevelopmental processes (e.g., neurogenesis, migration), their relationship to functional architecture remains unclear. Recent evidence suggests that the absolute number of neurons varies significantly with position-sulcus versus gyrus-with potential implications for local processing capacity (e.g., https://doi.org/10.1002/cne.25626). The field is thus in need of comparative, mechanistic studies like the present one.

This paper offers an elegant and timely contribution by combining gel-based morphogenesis, numerical modelling, and morphometric analysis to examine cortical folding across species. The experimental design - constructing two-layer PDMS models from 3D MRI data and immersing them in organic solvents to induce differential swelling - is well-established in prior literature. The authors further complement this with a continuum mechanics model simulating folding as a result of differential growth, as well as a comparative analysis of surface morphologies derived from in vivo, in vitro, and in silico brains.

We thank the reviewer for the very positive comments.

I offer a few suggestions here for clarification and further exploration:

Major Comments

(1)   Choice of Developmental Stages and Initial Conditions

The authors should provide a clearer justification for the specific developmental stages chosen (e.g., G85 for macaque, GW23 for human). How sensitive are the resulting folding patterns to the initial surface geometry of the gel models? Given that folding is a nonlinear process, early geometric perturbations may propagate into divergent morphologies. Exploring this sensitivity-either through simulations or reference to prior work-would enhance the robustness of the findings.

The initial geometry is one of the important factors that decides the final folding pattern. The smooth brain in the early developmental stage shows a broad consistency across individuals, and we expect the main folds to form similarly across species and individuals.

Generally, we choose the initial geometry when the brain cortex is still relatively smooth. For the human, this corresponds approximately to GW23, as the major folds such as the Rolandic fissure (central sulcus), arise during this developmental stage. For the macaque brain, we chose developmental stage G85, primarily because of the availability of the dataset corresponding to this time, which also corresponds to the least folded.

We expect that large-scale folding patterns are strongly sensitive to the initial geometry but fine-scale features are not. Since our goal is to explain the large-scale features, we expect sensitivity to the initial shape.

Enclosed are some results from other researchers that are consistent with this idea. Below are some images of simulations from Wang et al. obtained by perturbing the geometry of a sphere to an ellipsoid. We see that the growth-induced folds mostly maintain their width (wavelength), but change their orientations.

Reference:

Wang, X., Lefevre, J., Bohi, A., Harrach, M.A., Dinomais, M. and Rousseau, F., 2021. The influence of` biophysical parameters in a biomechanical model of cortical folding patterns. Scientific Reports, 11(1), p.7686.

Related results from the same group show that slight perturbations of brain geometry, cause these folds also tend to change their orientations but not width/wavelength (Bohi et al., 2019).

Reference:

Bohi, A., Wang, X., Harrach, M., Dinomais, M., Rousseau, F. and Lefevre, J., 2019, July. Global per-` turbation of initial geometry in a biomechanical model of cortical morphogenesis. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 442-445). IEEE.

Finally, a systematic discussion of the role of perturbations on the initial geometries and physical properties can be seen in our work on understanding a different system, gut morphogenesis (Gill et al., 2024).

We have added the discussion about geometric sensitivity in the section Methods-Numerical Simulations:

“Small perturbations on initial geometry would affect minor folds, but the main features of major folds, such as orientations, width, and depth, are expected to be conserved across individuals [49, 50]. For simplicity, we do not perturb the fetal brain geometry obtained from datasets.”

(2) Parameter Space and Breakdown Points

The numerical model assumes homogeneous growth profiles and simplifies several aspects of cortical mechanics. Parameters such as cortical thickness, modulus ratios, and growth ratios are described in Table II. It would be informative to discuss the range of parameter values for which the model remains valid, and under what conditions the physical and computational models diverge. This would help delineate the boundaries of the current modelling framework and indicate directions for refinement.

Exploring the valid parameter space is a key problem. We have tested a series of growth parameters and will state them explicitly in our revision. In the current version, we chose the ones that yield a relatively high similarity index to the animal brains. More generally, folding patterns are largely regulated by geometry as well as physical parameters, such as cortical thickness, modulus ratios, growth ratios, and inhomogeneity. In our previous work on a different system, gut morphogenesis, where similar folding patterns are seen, we have explored these features (Gill et al., 2024).

Reference:

Gill, H.K., Yin, S., Nerurkar, N.L., Lawlor, J.C., Lee, C., Huycke, T.R., Mahadevan, L. and Tabin, C.J., 2024. Hox gene activity directs physical forces to differentially shape chick small and large intestinal epithelia. Developmental Cell, 59(21), pp.2834-2849.

(3) Neglected Regional Features: The Occipital Pole of the Macaque

One conspicuous omission is the lack of attention to the occipital pole of the macaque, which is known to remain smooth even at later gestational stages and has an unusually high neuronal density (2.5× higher than adjacent cortex). This feature is not reproduced in the gel or numerical models, nor is it discussed. Acknowledging this discrepancy-and speculating on possible developmental or mechanical explanationswould add depth to the comparative analysis. The authors may wish to include this as a limitation or a target for future work.

Yes, we have added that the omission of the Occipital Pole of the macaque is one of our paper’s limitations. Our main aim in this paper is to explore the formation of large-scale folds, so the smooth region is neglected. But future work could include this to make the model more complete.

The main text has been modified in Methods, 3D model reconstruction, pre-processing:

“To focus on fold formation, we neglected some smooth regions such as the Occipital Pole of the macaque.”

(4) Spatio-Temporal Growth Rates and Available Human Data

The authors note that accurate, species-specific spatio-temporal growth data are lacking, limiting the ability to model inhomogeneous cortical expansion. While this may be true for ferret and macaque, there are high-quality datasets available for human fetal development, now extended through ultrasound imaging (e.g., https://doi.org/10.1038/s41586-023-06630-3). Incorporating or at least referencing such data could improve the fidelity of the human model and expand the applicability of the approach to clinical or pathological scenarios.

We thank the reviewer for pointing out the very useful datasets that exist for the exploration of inhomogeneous growth driven folding patterns. We have referred to this paper to provide suggestions for further work in exploring the role of growth inhomogeneities.

We have referred to this high-quality dataset in our main text, Discussion:

“...the effect of inhomogeneous growth needs to be further investigated by incorporating regional growth of the gray and white matter not only in human brains [29, 31] based on public datasets [45], but also in other species.”

A few works have tried to incorporate inhomogeneous growth in simulating human brain folding by separating the central sulcus area into several lobes (e.g., lobe parcellation method, Wang, PhD Thesis, 2021). Since our goal in this paper is to explain the large-scale features of folding in a minimal setting, we have kept our model simple and show that it is still capable of capturing the main features of folding in a range of mammalian brains.

Reference:

Xiaoyu Wang. Modelisation et caract´ erisation du plissement cortical. Signal and Image Processing. Ecole´ nationale superieure Mines-T´ el´ ecom Atlantique, 2021. English.´ 〈NNT : 2021IMTA0248〉.

(5) Future Applications: The Inverse Problem and Fossil Brains

The authors suggest that their morphometric framework could be extended to solve the inverse growth problem-reconstructing fetal geometries from adult brains. This speculative but intriguing direction has implications for evolutionary neuroscience, particularly the interpretation of fossil endocasts. Although beyond the scope of this paper, I encourage the authors to elaborate briefly on how such a framework might be practically implemented and validated.

For the inverse problem, we could use the following strategies:

a. Perform systematic simulations using different geometries and physical parameters to obtain the variation in morphologies as a function of parameters.

b. Using either supervised training or unsupervised training (physics-informed neural networks, PINNs) to learn these characteristic morphologies and classify their dependence on the parameters using neural networks. These can then be trained to determine the possible range of geometrical and physical parameters that yield buckled patterns seen in the systematic simulations.

c. Reconstruct the 3D surface from fossil endocasts. Using the well-trained neural network, it should be possible to predict the initial shape of the smooth brain cortex, growth profile, and stiffness ratio of the gray and white matter.

As an example in this direction, supervised neural networks have been used recently to solve the forward problem to predict the buckling pattern of a growing two-layer system (Chavoshnejad et al., 2023). The inverse problem can then be solved using machine-learning methods when the training datasets are the folded shape, which are then used to predict the initial geometry and physical properties.

Reference:

Chavoshnejad, P., Chen, L., Yu, X., Hou, J., Filla, N., Zhu, D., Liu, T., Li, G., Razavi, M.J. and Wang, X., 2023. An integrated finite element method and machine learning algorithm for brain morphology prediction. Cerebral Cortex, 33(15), pp.9354-9366.

Conclusion

This is a well-executed and creative study that integrates diverse methodologies to address a longstanding question in developmental neurobiology. While a few aspects-such as regional folding peculiarities, sensitivity to initial conditions, and available human data-could be further elaborated, they do not detract from the overall quality and novelty of the work. I enthusiastically support this paper and believe that it will be of broad interest to the neuroscience, biomechanics, and developmental biology communities.

Note: The paper mentions a companion paper [reference 11] that explores the cellular and anatomical changes in the ferret cortex. I did not have access to this manuscript, but judging from the title, this paper might further strengthen the conclusions.

The companion paper (Choi et al., 2025) has also been submitted to Elife and can be found on bioXiv here:

G. P. T. Choi, C. Liu, S. Yin, G. Sejourn´ e, R. S. Smith, C. A. Walsh, L. Mahadevan, Biophysical basis for´ brain folding and misfolding patterns in ferrets and humans. bioRxiv 2025.03.05.641682.

Before this, I would have never guessed the publishing industry was so profitable. It makes sense though with the vast amount of students each year.

With the number of things that Google is connected to, I am surprised that this isn't higher.

This stat doesn't surprise me with Apple's business models, and high consumption rate. Still way higher than most others' average profit percentage.

eLife Assessment

This valuable study introduces a novel experimental and modeling framework to quantify passive joint torques in Drosophila, revealing that passive forces are insufficient to support body weight, contrary to prior assumptions based on larger insects. The approach is technically impressive, combining genetic silencing, kinematic tracking, and biomechanical modeling. However, the strength of evidence is incomplete, limited by concerns about the specificity of the genetic tools, simplifications in the mechanical model, and limited functional interpretation.

Reviewer #1 (Public review):

Summary:

In this work, Wang et al. use a combination of genetic tools, novel experimental approaches and biomechanical models to quantify the contribution of passive leg forces in Drosophila. They also deduce that passive forces are not sufficient to support the body weight of the animal. Overall, the contribution of passive forces reported in this work is much less than what one would expect based on the size of the organism and previous literature from larger insects and mammals. This is an interesting finding, but some major caveats in their approach remain unanswered.

Strengths:

(1) The authors combine experimental measurements and modeling to quantify the contributions of passive forces at limb joints in Drosophila.

(2) The authors replicate a previous experimental strategy (Hooper et al 2009, J. Neuro) to suspend animals in air for measuring passive forces and, as in previous studies, find that passive forces are much stronger than gravitational forces acting on the limbs. While in these previous studies using large insects, a lot of invasive approaches for accurately quantifying passive forces are possible (e.g., physically cutting of nerves, directly measuring muscle forces in isolated preparations, etc), the small size of Drosophila makes this difficult. The authors overcome this using a novel approach where they attach additional weight to the leg (changes gravitational force) and inactivate motor neurons (remove active forces). With a few approximations and assumptions, the authors then deduce the contribution of passive forces at each joint for each leg.

(3) The authors find interesting differences in passive forces across different legs. This could have behavioral implications.

(4) Finally, the authors compare experimental results of how a free-standing Drosophila is lowered ("falls down") on silencing motor neurons, to a biomechanical "OpenSim" model for deducing the role of passive forces in supporting the body weight of the fly. Using this approach, they conclude that passive forces are not sufficient to support the body weight of the fly.

Weaknesses:

(1) Line 65 "(Figure 1A). Inactivation causes a change in the leg's rest position; however, in preliminary experiments, the body rotation did not have a large effect on the rest positions of the leg following inactivation. This result is consistent with the one already reported for stick insects and shows that passive forces within the leg are much larger than the gravitational force on a leg and dominate limb position [1]." This is the direct replication of the previous work by Hooper et al 2009 and therefore authors should ideally show the data for this condition (no weight attached).

(2) The authors use vglut-gal4, a very broad driver for inactivating motor neurons. The driver labels all glutamatergic neurons, including brain descending neurons and nerve cord interneurons, in addition to motor neurons. Additionally, the strength of inactivation might differ in different neurons (including motor neurons) depending on the expression levels of the opsins. As a result, in this condition, the authors might not be removing all active forces. This is a major caveat that authors do not address. They explore that they are not potentially silencing all inputs to muscles by using an additional octopaminergic driver, but this doesn't address the points mentioned above. At the very least, the authors should try using other motor neuron drivers, as well as other neuronal silencers. This driver is so broad that authors couldn't even use it for physiology experiments. Additionally, the authors could silence VGlut-labeled motor neurons and record muscle activity (potentially using GCaMP as has been done in several recent papers cited by the authors, Azevedo et al, 2020) as a much more direct readout.

(3) Figure 4 uses an extremely simplified OpenSim model that makes several assumptions that are known to be false. For example, the Thorax-Coxa joint is assumed to be a ball and socket joint, which it is not. Tibia-tarsus joint is completely ignored and likely makes a major contribution in supporting overall posture, given the importance of the leg "claw" for adhering to substrates. Moreover, there are a couple of recent open-source neuromechanical models that include all these details (NeuromechFly by Lobato-Rios et al, 2022, Nat. Methods, and the fly body model by Vaxenburg et al, 2025, Nature). Leveraging these models to rule in or rule out contributions at other joints that are ignored in the authors' OpenSim model would be very helpful to make their case.

(4) Figure 5 shows the experimental validation of Figure 4 simulations; however, it suffers from several caveats.

a) The authors track a single point on the head of the fly to estimate the height of the fly. This has several issues. Firstly, it is not clear how accurate the tracking would be. Secondly, it is not clear how the fly actually "falls" on VGlut silencing; do all flies fall in a similar manner in every trial? Almost certainly, there will be some "pitch" and "role" in the way the fly falls. These will affect the location of this single-tracked point that doesn't reflect the authors' expectations. Unless the authors track multiple points on the fly and show examples of tracked videos, it is hard to believe this dataset and, hence, any of the resulting interpretations.

b) As described in the previous point, the "reason" the fly falls on silencing all glutamatergic neurons could be due to silencing all sorts of premotor/interneurons in addition to the silencing of motor neurons.

c) (line 175) "The first finding is that there was a large variation in the initial height of the fly (Figure 5C), consistent with a recent study of flies walking on a treadmill[20]." The cited paper refers to how height varies during "walking". However, in the current study, the authors are only looking at "standing" (i.e. non-walking) flies. So it is not the correct reference. In my opinion, this could simply reflect poor estimation of the fly's height based on poor tracking or other factors like pitch and role.

d) "The rate at which the fly fell to the ground was much smaller in the experimental flies than it was in the simulated flies (Figure 5E). The median rate of falling was 1.3 mm/s compared to 37 mm/s for the simulated flies (Figure 5F). (Line 190) The most likely reason for the longer than expected time for the fly to fall is delays associated with motor neuron inactivation and muscle inactivation." I don't believe this reasoning. There are so many caveats (which I described in the above points) in the model and the experiment, that any of those could be responsible for this massive difference between experiment and modeling. Simply not getting rid of all active forces (inadequate silencing) could be one obvious reason. Other reasons could be that the model is using underestimates of passive forces, as alluded to in point 3.

(5) Final figure (Figure 6) focuses on understanding the time course of neuronal silencing. First of all, I'm not entirely sure how relevant this is for the story. It could be an interesting supplemental data. But it seems a bit tangential. Additionally, it also suffers from major caveats.

a) The authors now use a new genetic driver for which they don't have any behavioral data in any previous figures. So we do not know if any of this data holds true for the previous experiments. The authors perform whole-cell recordings from random unidentified motor neurons labeled by E49-Gal4>GtACR1 to deduce a time constant for behavioral results obtained in the VGlut-Gal4>GtACR1 experiments.

b) The DMD setup is useful for focal inactivation, however, the appropriate controls and data are not presented. Line 200 "A spot of light on the cell body produces as much of the hyperpolarization as stimulating the entire fly (mean of 11.3 mV vs 13.1 mV across 9 neurons). Conversely, excluding the cell body produces only a small effect on the MN (mean of 2.6 mV)." First of all, the control experiment for showing that DMD is indeed causing focal inactivation would be to gradually move the spot of light away from the labeled soma, i.e. to the neighboring "labelled" soma and show that there is indeed focal inactivation. Instead authors move it quite a long distance into unlabeled neuropil. Secondly, I still don't get why the authors are doing this experiment. Even if we believe the DMD is functioning perfectly, all this really tells us is that a random subset motor neurons (maybe 5 or 6 cells, legend is missing this info) labeled by E49-Gal4 is strongly hyperpolarized by its own GtACR1 channel opening, rather than being impacted because of hyperpolarizations in other E49-Gal4 labeled neurons. This has no relevance to the interpretation of any of the VGlut-Gal4 behavioral data. VGLut-Gal4 is much broader and also labels all glutamatergic neurons, most of which are inhibitory interneurons whose silencing could lead to disinhibition of downstream networks.

Reviewer #2 (Public review):

Summary:

The authors aim to quantify passive muscle forces in the legs of Drosophila, and test the hypothesis that these forces would be sufficient to support body weight in small insects. They take advantage of the genetic tools available in Drosophila, and use a combination of genetic silencing (optogenetic inactivation of motor neurons), kinematic measurements, and simulations using OpenSim. This integrative toolkit is used to examine the role of passive torques across multiple leg joints. They find that passive forces are weaker than expected - in particular, passive forces were found to be too weak to support the body weight of the fly. This challenges previous scaling assumptions derived from studies in larger insects and has potential implications for our understanding of motor control in small animals.

Strengths:

The primary strength of this work lies in its integration of multiple analyses. By pulling together simulations, kinematic measurements from high-resolution videos, and genetic manipulation, they are able to overcome limitations of past studies. In particular, optogenetic manipulation allowed for measurements to be made in whole animals, and the modeling component is valuable because it both validates experimental findings and elucidates the mechanism behind some of the observed dynamic consequences (e.g., the rapid fall after motor inactivation). The conclusions made in the study are well-supported by the data and could have an impact on a number of fields, including invertebrate neurobiology and bioinspired design.

Weaknesses:

While (as mentioned above) the study's conclusions are well-supported by the results and modeling, limitations arise because of the assumptions made. For instance, using a linear approximation may not hold at larger joint angles, and future studies would benefit from accounting for nonlinearities. Future studies could also delve into the source of passive forces, which is important for more deeply understanding the anatomical and physical basis of the results in this study. For instance, assessments of muscle or joint properties to correlate stiffness values with physical structure might be an area of future consideration

Reviewer #3 (Public review):

Summary:

The authors present a novel method to measure passive joint torques - torques due to internal forces other than active muscle contraction - in the fruit fly: genetically inactivating all motor neurons in intact limb acted upon by a gravitational load results in a change in limb configuration; evaluating the moment equilibrium condition about the limb joints then yields a direct estimate of the passive joint torques. Deactivating all motor neurons in an intact standing fly provided two further conclusions: First, because deactivation causes the fly to drop to the floor, the passive joint torques are deemed insufficient to maintain rotational equilibrium against the body weight; using a multi-body-dynamics simulation, the authors estimate that the passive torques would need to be about 40-80 times higher to maintain a typical posture without active muscle action. Second, a delay between the motor neuron inactivation and the onset of the "free fall" motivates the authors to invoke a simple exponential decay model, which is then used to derive a time constant for muscle deactivation, in robust agreement with direct electro-physiological recordings.

Strengths:

The experimental design that permits determination of passive joint torques is elegant, effective, novel, and altogether excellent; it permits measurements previously impossible. A careful error analysis is presented, and a spectrum of technically challenging methods, including multi-body dynamics and e-phys, is deployed to further interpret and contextualise the results.

Weaknesses:

(1) Passive torques are measured, but only some short speculative statements, largely based on previous work, are offered on their functional significance; some of these claims are not well supported by experimental evidence or theoretical arguments. Passive forces are judged as "large" compared to the weight force of the limb, but the arguably more relevant force is the force limb muscles can generate, which, even in equilibrium conditions, is already about two orders of magnitude larger. The conclusion that passive forces are dynamically irrelevant seems natural, but contrasts with the assertion that "passive forces [...] will have a strong influence on limb kinematics". As a result, the functional significance of passive joint torques in the fruit fly, if any, remains unclear, and this ambiguity represents a missed opportunity. We now know the magnitude of passive joint torques - do they matter and for what? Are they helpful, for example, to maintain robust neuronal control, or a mechanical constraint that negatively impacts performance, e.g., because they present a sink for muscle work?

(2) The work is framed with a scaling argument, but the assumptions that underpin the associated claims are not explicit and can thus not be evaluated. This is problematic because at least some arguments appear to contradict textbook scaling theory or everyday experience. For example, active forces are assumed to scale with limb volume, when every textbook would have them scale with area instead; and the asserted scaling of passive forces involves some hidden assumptions that demand more explicit discussion to alert the reader to associated limitations. Passive forces are said to be important only in small animals, but a quick self-experiment confirms that they are sufficient to stabilize human fingers or ankles against gravity, systems orders of magnitude larger than an insect limb, in seeming contradiction with the alleged dominance of scale. Throughout the manuscript, there are such and similar inaccuracies or ambiguities in the mechanical framing and interpretation, making it hard to fairly evaluate some claims, and rendering others likely incorrect.

Author response:

Reviewer 1:

(1) Line 65 "(Figure 1A). Inactivation causes a change in the leg's rest position; however, in preliminary experiments, the body rotation did not have a large effect on the rest positions of the leg following inactivation. This result is consistent with the one already reported for stick insects and shows that passive forces within the leg are much larger than the gravitational force on a leg and dominate limb position [1]." This is the direct replication of the previous work by Hooper et al 2009 and therefore authors should ideally show the data for this condition (no weight attached).

We did not present this data – the effect of inactivation on the leg’s rest position in unweighted leg - because it was already reported in the case of stick insects. However, we understand the reviewer’s point that it is important to present the data showing this replication. We will do the same in the revised version.

(2) The authors use vglut-gal4, a very broad driver for inactivating motor neurons. The driver labels all glutamatergic neurons, including brain descending neurons and nerve cord interneurons, in addition to motor neurons. Additionally, the strength of inactivation might differ in different neurons (including motor neurons) depending on the expression levels of the opsins. As a result, in this condition, the authors might not be removing all active forces. This is a major caveat that authors do not address. They explore that they are not potentially silencing all inputs to muscles by using an additional octopaminergic driver, but this doesn't address the points mentioned above. At the very least, the authors should try using other motor neuron drivers, as well as other neuronal silencers. This driver is so broad that authors couldn't even use it for physiology experiments. Additionally, the authors could silence VGlut-labeled motor neurons and record muscle activity (potentially using GCaMP as has been done in several recent papers cited by the authors, Azevedo et al, 2020) as a much more direct readout.

This reviewer critique is related to the use of vglut-gal4 –a broad driver– to inactivate motor neurons (MNs). The reviewer argues that the use of a broad driver might result in some effects that are not due to MN inactivation. Conversely, it is possible that not all MNs are inactivated. These critiques raise important points that we will address in the revision by 1) performing experiments with other MN drivers as suggested by the reviewer, 2) performing experiments in flies that are inactivated by freezing. These measurements will provide other estimates of passive forces allowing us to better triangulate the range of values for the passive forces. Moreover, it appears that one of the reviewer’s main concern is that the passive forces are overestimated because of the residual active forces. We will discuss this possibility in detail. It is important to note that in the end what we hope to accomplish is to provide a useful estimate of the passive forces. It is unlikely that the passive force will be a precise number like a physical constant as the passive forces likely depend on recent history.

(3) Figure 4 uses an extremely simplified OpenSim model that makes several assumptions that are known to be false. For example, the Thorax-Coxa joint is assumed to be a ball and socket joint, which it is not. Tibia-tarsus joint is completely ignored and likely makes a major contribution in supporting overall posture, given the importance of the leg "claw" for adhering to substrates. Moreover, there are a couple of recent open-source neuromechanical models that include all these details (NeuromechFly by Lobato-Rios et al, 2022, Nat. Methods, and the fly body model by Vaxenburg et al, 2025, Nature). Leveraging these models to rule in or rule out contributions at other joints that are ignored in the authors' OpenSim model would be very helpful to make their case.

Our OpenSim model predates the newer mechanical model. In the revised manuscript, we will revisit the model in light of recent developments.

(4) Figure 5 shows the experimental validation of Figure 4 simulations; however, it suffers from several caveats.

a) The authors track a single point on the head of the fly to estimate the height of the fly. This has several issues. Firstly, it is not clear how accurate the tracking would be. Secondly, it is not clear how the fly actually "falls" on VGlut silencing; do all flies fall in a similar manner in every trial? Almost certainly, there will be some "pitch" and "role" in the way the fly falls. These will affect the location of this single-tracked point that doesn't reflect the authors' expectations. Unless the authors track multiple points on the fly and show examples of tracked videos, it is hard to believe this dataset and, hence, any of the resulting interpretations.

b) As described in the previous point, the "reason" the fly falls on silencing all glutamatergic neurons could be due to silencing all sorts of premotor/interneurons in addition to the silencing of motor neurons.

c) (line 175) "The first finding is that there was a large variation in the initial height of the fly (Figure 5C), consistent with a recent study of flies walking on a treadmill[20]." The cited paper refers to how height varies during "walking". However, in the current study, the authors are only looking at "standing" (i.e. non-walking) flies. So it is not the correct reference. In my opinion, this could simply reflect poor estimation of the fly's height based on poor tracking or other factors like pitch and role.

d) "The rate at which the fly fell to the ground was much smaller in the experimental flies than it was in the simulated flies (Figure 5E). The median rate of falling was 1.3 mm/s compared to 37 mm/s for the simulated flies (Figure 5F). (Line 190) The most likely reason for the longer than expected time for the fly to fall is delays associated with motor neuron inactivation and muscle inactivation." I don't believe this reasoning. There are so many caveats (which I described in the above points) in the model and the experiment, that any of those could be responsible for this massive difference between experiment and modeling. Simply not getting rid of all active forces (inadequate silencing) could be one obvious reason. Other reasons could be that the model is using underestimates of passive forces, as alluded to in point 3.

(4a) Although we agree that measuring different points on the body would allow us to estimate the moments, we disagree that the height of the fly cannot be evaluated from the measurement of a single point. The measurements have been performed using the same techniques that we used to assess the fly’s height in a different study where we estimated the resolution of our imaging system to be ~20 mm(Chun et. al. 2021). We will include these details in the revised manuscript. The video showing the falling experiments are not available or referenced in the manuscript. These will be made available.

b) We will repeat the “falling” experiment with a more restrictive driver.

c) We disagree with the reviewer on this point. The system has a resolution of ~20 mm and is sufficient to make conclusion about the difference in the height of the fly. We will clarify this point in the revised manuscript.

d) We do not follow the reviewer’s rationale here. The passive forces in the model (along with any residual forces) are the same in the model as well as in the experiment. Moreover, there will be a delay between light onset, neuronal inactivation and muscle inactivation. These processes are not instantaneous. In Figure 6, we estimate these delays and have concluded that they will cause substantial delay. In the revised manuscript, we will discuss other reasons for the delay suggested by the reviewer.

(5) Final figure (Figure 6) focuses on understanding the time course of neuronal silencing. First of all, I'm not entirely sure how relevant this is for the story. It could be an interesting supplemental data. But it seems a bit tangential. Additionally, it also suffers from major caveats.

a) The authors now use a new genetic driver for which they don't have any behavioral data in any previous figures. So we do not know if any of this data holds true for the previous experiments. The authors perform whole-cell recordings from random unidentified motor neurons labeled by E49-Gal4>GtACR1 to deduce a time constant for behavioral results obtained in the VGlut-Gal4>GtACR1 experiments.

b) The DMD setup is useful for focal inactivation, however, the appropriate controls and data are not presented. Line 200 "A spot of light on the cell body produces as much of the hyperpolarization as stimulating the entire fly (mean of 11.3 mV vs 13.1 mV across 9 neurons). Conversely, excluding the cell body produces only a small effect on the MN (mean of 2.6 mV)." First of all, the control experiment for showing that DMD is indeed causing focal inactivation would be to gradually move the spot of light away from the labeled soma, i.e. to the neighboring "labelled" soma and show that there is indeed focal inactivation. Instead authors move it quite a long distance into unlabeled neuropil. Secondly, I still don't get why the authors are doing this experiment. Even if we believe the DMD is functioning perfectly, all this really tells us is that a random subset motor neurons (maybe 5 or 6 cells, legend is missing this info) labeled by E49-Gal4 is strongly hyperpolarized by its own GtACR1 channel opening, rather than being impacted because of hyperpolarizations in other E49-Gal4 labeled neurons. This has no relevance to the interpretation of any of the VGlut-Gal4 behavioral data. VGLut-Gal4 is much broader and also labels all glutamatergic neurons, most of which are inhibitory interneurons whose silencing could lead to disinhibition of downstream networks.

(5 a) However, we can address the reviewer critique by recording from the Vglut line while using a MN line to target the recordings to MNs.

b) Once we use the Vglut driver to perform these recordings, it will help assess how much of the MN inactivation is due to the GtACR expressed in the MN versus other neurons.

Reviewer 2:

While (as mentioned above) the study's conclusions are well-supported by the results and modeling, limitations arise because of the assumptions made. For instance, using a linear approximation may not hold at larger joint angles, and future studies would benefit from accounting for nonlinearities. Future studies could also delve into the source of passive forces, which is important for more deeply understanding the anatomical and physical basis of the results in this study. For instance, assessments of muscle or joint properties to correlate stiffness values with physical structure might be an area of future consideration.

We agree with these comments but believe that these studies represent avenues for future work.

Reviewer 3:

(1) Passive torques are measured, but only some short speculative statements, largely based on previous work, are offered on their functional significance; some of these claims are not well supported by experimental evidence or theoretical arguments. Passive forces are judged as "large" compared to the weight force of the limb, but the arguably more relevant force is the force limb muscles can generate, which, even in equilibrium conditions, is already about two orders of magnitude larger. The conclusion that passive forces are dynamically irrelevant seems natural, but contrasts with the assertion that "passive forces [...] will have a strong influence on limb kinematics". As a result, the functional significance of passive joint torques in the fruit fly, if any, remains unclear, and this ambiguity represents a missed opportunity. We now know the magnitude of passive joint torques - do they matter and for what? Are they helpful, for example, to maintain robust neuronal control, or a mechanical constraint that negatively impacts performance, e.g., because they present a sink for muscle work?

To us, measuring passive forces was the first step to understanding neural/biomechanical control of limb. In general, we agree with these comments and would like to understand the role of passive forces in overall control of limb. A complete discussion of the role of the significance of passive forces in the control of limb is beyond the scope of this study. We would like to note that it is unlikely that the active forces are two orders of magnitude larger during unloaded movement of the limb. However, these issues will have to be settled in future work.

(2) The work is framed with a scaling argument, but the assumptions that underpin the associated claims are not explicit and can thus not be evaluated. This is problematic because at least some arguments appear to contradict textbook scaling theory or everyday experience. For example, active forces are assumed to scale with limb volume, when every textbook would have them scale with area instead; and the asserted scaling of passive forces involves some hidden assumptions that demand more explicit discussion to alert the reader to associated limitations. Passive forces are said to be important only in small animals, but a quick self-experiment confirms that they are sufficient to stabilize human fingers or ankles against gravity, systems orders of magnitude larger than an insect limb, in seeming contradiction with the alleged dominance of scale. Throughout the manuscript, there are such and similar inaccuracies or ambiguities in the mechanical framing and interpretation, making it hard to fairly evaluate some claims, and rendering others likely incorrect.

We interpret this comment as making two separate points. The first one is that the reviewer says that our statement that active forces depend on the third power of the limb or L³ is incorrect. We agree and apologize for this oversight. Specifically, on L6-7 we say, “both inertial forces and active forces scale with the mass if the limb which in turn scales with the volume of the limb and therefore depends on the third power of limb length (L³)”. Instead, this statement should read “inertial forces scale with the mass if the limb which in turn scales with the volume of the limb and therefore depends on the third power of limb length (L³)”. However, this oversight does not affect the scaling argument as the scaling arguments in the rest of the manuscript only involves inertial forces and not active forces.

The second point is about the scaling law that governs passive forces. In the current manuscript, we have assumed that the passive forces scale as L² based on previous work. The reviewer has pointed out that this assumption might be incorrect or at the very least needs a rationale. We agree with this assessment: passive forces that arise in the muscle are likely to scale as L² but passive forces that arise in the joint might not. In the revised manuscript, we will discuss this concern.

Response to the public comment:

There was a comment from a reader: “None of our work cited in various places in this preprint (i.e., Zakotnik et al. 2006, Guschlbauer et al. 2007, Page et al. 2008, Hooper et al. 2009, Hooper 2012, Ache and Matheson 2012, Blümel et al. 2012, Ache and Matheson 2013, von Twickel et al. 2019, and Guschlbauer et al. 2022) claims or implies that passive forces could be sufficient to support the weight of an insect or any animal. To claim or suggest otherwise (as done in lines 33-35) is incorrect and sets up a misleading straw man that misrepresents our work. All statements in the preprint regarding our work related to this specific matter need to be removed or edited accordingly. For instance, the investigations, calculations, and interpretations in Hooper et al. 2009 are solely about limbs that are not being used in stance or other loaded tasks (indeed, the article's title specifically refers to "unloaded" leg posture and movements). Trying to use this work to predict whether passive muscle forces alone can support a stick insect against gravity requires considering much more than the oversimplified calculation given in lines 290-292. Other “back of the envelope calculations” (lines 299-300) are likely also insufficient and erroneous. The discussion in lines 289-304 needs to be edited accordingly”

We thank the reader for their comment. However, we interpret these studies differently. The studies above rightly focused on unloaded legs because it would be difficult to study passive forces in an intact insect without genetic tools. The commenter correctly points out that these studies do not comment on whether passive forces are strong enough to support the weight of the fly. However, we disagree that our arguments based on their results are unreasonable or strawman. We think that our interpretation of their measurements is correct. Moreover, we were motivated by Yox et. el. 1982 who states in so many words: “Stiffness of the muscles in the joints of all the legs might be sufficient to support a resting arthropod. A more rigorous analysis of all supporting limbs and joint angles would be required to prove this hypothesis”. We were inspired by this comment. In the revised manuscript, we will make it clear that the statement made in Line 33 is based on Yox. et. al. and our interpretation of measurements made by others.

Each year, they are being developed and designed to be faster and engaging. How much longer till we are all truly captured by technology 24/7?

Over the last 5 years, we have seen significant changes in 3D printing. With the implications of better material and faster speeds, 3D printing has introduced itself and is being used by multiple industries right now.

Again one of those things that is considered a modern "Standard" to function in the present world, so to see that about 2 billion dont have that availability again opens my eyes to the amount of people living completely different way of life.

The college library has everything I might need, or if not, knows where to find it.

Education aside, just by a simple connection with someone, you can gain more access to info than others, and this can range from anything. It's all about who you know in the world nowadays.

Explains why so many Mexicans still adopt cowboy culture today.

Yet another form of slavery.

War and slaughter are one thing. But this is another key component of colonialism and conquest.

This from the folks who enslaved both Africans and Native Americans. How rich.

Was his skin bleached?

Colonialism seems to often be hidden behind religion. Another recurring theme throughout history.

...and effect.

Cause...

A sad recurring theme throughout history that continues to repeat itself today.

I've seen this photo on social media for years. Crazy finally learning the context behind it.

Sometimes it's more of the sizzle than the steak.

Imagine killing Native Americans in servitude to white people who also want to kill you.

eLife Assessment

This important study characterises the morphogenesis of cortical folding in the ferret and human cerebral cortex using complementary physical and computational modelling. Notably, these approaches are applied to charting, in the ferret model, known abnormalities of cortical folding in humans. The study finds that variation in cortical thickness and expansion account for deviations in morphology, and supports these findings using cutting-edge approaches from both physical gel models and numerical simulations. The strength of evidence is convincing, and although it could benefit from more quantitative assessment, the study will be of broad interest to the field of developmental neuroscience.

Reviewer #1 (Public review):

The manuscript by Choi and colleagues investigates the impact of variation in cortical geometry and growth on cortical surface morphology. Specifically, the study uses physical gel models and computational models to evaluate the impact of varying specific features/parameters of the cortical surface. The study makes use of this approach to address the topic of malformations of cortical development and finds that cortical thickness and cortical expansion rate are the drivers of differences in morphogenesis.

The study is composed of two main sections. First, the authors validate numerical simulation and gel model approaches against real cortical postnatal development in the ferret. Next, the study turns to modelling malformations in cortical development using modified tangential growth rate and cortical thickness parameters in numerical simulations. The findings investigate three genetically linked cortical malformations observed in the human brain to demonstrate the impact of the two physical parameters on folding in the ferret brain.

This is a tightly presented study that demonstrates a key insight into cortical morphogenesis and the impact of deviations from normal development. The dual physical and computational modeling approach offers the potential for unique insights into mechanisms driving malformations. This study establishes a strong foundation for further work directly probing the development of cortical folding in the ferret brain. One weakness of the current study is that the interpretation of the results in the context of human cortical development is at present indirect, as the modelling results are solely derived from the ferret. However, these modelling approaches demonstrate proof of concept for investigating related alterations more directly in future work through similar approaches to models of the human cerebral cortex.

Reviewer #2 (Public review):

Summary:

Based on MRI data of the ferret (a gyrencephalic non-primate animal, in whom folding happens postnatally), the authors create in vitro physical gel models and in silico numerical simulations of typical cortical gyrification. They then use genetic manipulations of animal models to demonstrate that cortical thickness and expansion rate are primary drivers of atypical morphogenesis. These observations are then used to explain cortical malformations in humans.

Strengths:

The paper is very interesting and original, and combines physical gel experiments, numerical simulations, as well as observations in MCD. The figures are informative, and the results appear to have good overall face validity.

Weaknesses:

On the other hand, I perceived some lack of quantitative analyses in the different experiments, and currently, there seems to be rather a visual/qualitative interpretation of the different processes and their similarities/differences.

Ideally, the authors also quantify local/pointwise surface expansion in the physical and simulation experiments, to more directly compare these processes. Time courses of eg, cortical curvature changes, could also be plotted and compared for those experiments.

I had a similar impression about the comparisons between simulation results and human MRI data. Again, face validity appears high, but the comparison appeared mainly qualitative.

I felt that MCDs could have been better contextualized in the introduction.

Author response:

Reviewer 1 (Public review):

The manuscript by Choi and colleagues investigates the impact of variation in cortical geometry and growth on cortical surface morphology. Specifically, the study uses physical gel models and computational models to evaluate the impact of varying specific features/parameters of the cortical surface. The study makes use of this approach to address the topic of malformations of cortical development and finds that cortical thickness and cortical expansion rate are the drivers of differences in morphogenesis.

The study is composed of two main sections. First, the authors validate numerical simulation and gel model approaches against real cortical postnatal development in the ferret. Next, the study turns to modelling malformations in cortical development using modified tangential growth rate and cortical thickness parameters in numerical simulations. The findings investigate three genetically linked cortical malformations observed in the human brain to demonstrate the impact of the two physical parameters on folding in the ferret brain.

This is a tightly presented study that demonstrates a key insight into cortical morphogenesis and the impact of deviations from normal development. The dual physical and computational modeling approach offers the potential for unique insights into mechanisms driving malformations. This study establishes a strong foundation for further work directly probing the development of cortical folding in the ferret brain. One weakness of the current study is that the interpretation of the results in the context of human cortical development is at present indirect, as the modelling results are solely derived from the ferret. However, these modelling approaches demonstrate proof of concept for investigating related alterations more directly in future work through similar approaches to models of the human cerebral cortex.

We thank the reviewer for the very positive comments. While the current gel and organismal experiments focus on the ferret only, we want to emphasize that our analysis does consider previous observations of human brains and morphologies therein (Tallinen et al., Proc. Natl. Acad. Sci. 2014; Tallinen et al., Nat. Phys. 2016), which we compare and explain. This allows us to analyze the implications of our study broadly to understand the explanations of cortical malformations in humans using the ferret to motivate our study. Further analysis of normal human brain growth using computational and physical gel models can be found in our companion paper (Yin et al., 2025), also submitted to eLife:

S. Yin, C. Liu, G. P. T. Choi, Y. Jung, K. Heuer, R. Toro, L. Mahadevan, Morphogenesis and morphometry of brain folding patterns across species. bioRxiv 2025.03.05.641692.

In future work, we plan to obtain malformed human cortical surface data, which would allow us to further investigate related alterations more directly.

Reviewer 2 (Public review):

Summary:

Based on MRI data of the ferret (a gyrencephalic non-primate animal, in whom folding happens postnatally), the authors create in vitro physical gel models and in silico numerical simulations of typical cortical gyrification. They then use genetic manipulations of animal models to demonstrate that cortical thickness and expansion rate are primary drivers of atypical morphogenesis. These observations are then used to explain cortical malformations in humans.

Strengths:

The paper is very interesting and original, and combines physical gel experiments, numerical simulations, as well as observations in MCD. The figures are informative, and the results appear to have good overall face validity.

We thank the reviewer for the very positive comments.

Weaknesses:

On the other hand, I perceived some lack of quantitative analyses in the different experiments, and currently, there seems to be rather a visual/qualitative interpretation of the different processes and their similarities/differences. Ideally, the authors also quantify local/pointwise surface expansion in the physical and simulation experiments, to more directly compare these processes. Time courses of eg, cortical curvature changes, could also be plotted and compared for those experiments. I had a similar impression about the comparisons between simulation results and human MRI data. Again, face validity appears high, but the comparison appeared mainly qualitative.

We thank the reviewer for the comments. Besides the visual and qualitative comparisons between the models, we would like to point out that we have included the quantification of the shape difference between the real and simulated ferret brain models via spherical parameterization and the curvature-based shape index as detailed in main text Fig. 4 and SI Section 3. We have also utilized spherical harmonics representations for the comparison between the real and simulated ferret brains at different maximum order N. In our revision, we plan to further include the curvature-based shape index calculations for the comparison between the real and simulated ferret brains at more time points.

As for the comparison between the malformation simulation results and human MRI data in the current work, since the human MRI data are two-dimensional while our computational models are threedimensional, we focus on the qualitative comparison between them. In future work, we plan to obtain malformed human cortical surface data, from which we can then perform the parameterization-based and curvature-based shape analysis for a more quantitative assessment.

I felt that MCDs could have been better contextualized in the introduction.

We thank the reviewer for the comment and will include a more detailed introduction to MCDs in our revision.

eLife Assessment

This is an important study reporting a new phenotype for a gene cluster that has previously been associated with the responses of the Gram-negative opportunistic pathogen Pseudomonas aeruginosa to flow fluid. Expression of the froABCD gene cluster is induced by HOCl in vitro and by activated immune cells, which produce these types of reactive chlorine species. Overall, the evidence presented by the authors is solid; however, the mechanism of fro-induction by HOCl remains unclear, and the evidence in support of the authors' claims is descriptive, which needs to be improved. This study is of interest to infection biologists interested in mechanisms of bacterial pathogenicity.

Reviewer #1 (Public review):

Summary:

Foik et al. report that hypochlorous acid, a reactive chlorine species generated during host defense, activates the transcription of the froABCD in P. aeruginosa. This gene cluster had previously been associated with a potential role during the flow of fluids and appears to be regulated by the sigma factor FroR and its anti-sigma factor FroI. In the present study, the authors show that froABCD is expressed both in neutrophils and macrophages, which they claim is likely a result of HOCl but not H2O2 production. Fro expression is also induced in a murine model of corneal infection, which is characterized by immune cell invasion. Expression of the fro system can be quenched by several antioxidants, such as methionine, cysteine, and others. FroR-deficient cells that lack froABCD expression during HOCl stress appear more sensitive to the oxidant.

Strengths:

The authors provide a number of data supporting their claim that transcription of the froABCD system is induced by reactive chlorine species. This was shown by RNAseq, qRT-PCR, and through microscopy using a transcriptional reporter fusion. Likewise, elevated expression of froABCD was shown in vitro and in vivo, excluding potential in vitro artifacts. The manuscript, while mostly descriptive, is easy to follow, and the data were presented clearly.

Weaknesses:

(1) Lines 60-62: Some of the authors' conclusions are not supported by the data and thus appear unfounded. One example: "we determine that fro upregulation.....These data suggest a novel mechanism..." Their data do not show that MSR upregulation is a direct effect of FroABCD. Instead, it could be possible that the FroR sigma factor also controls the expression of msr genes, which would be independent of froABCD.

(2) The authors show increased fro transcription both in neutrophils and macrophages; however, the two types of immune cells differ quite dramatically with respect to myeloperoxidase activation and HOCl production. Neither has this been discussed nor considered here.

(3) With respect to the activation of fro expression upon challenge with conditioned media from stimulated neutrophils, does the conditioned media contain detectable amounts of HOCl? Do chloramines, which are byproducts of HOCl oxidation with amines, also stimulate expression?

(4) A better control to prove that this fro expression is indeed induced by HOCl in activated neutrophils would be to conduct the experiments in the presence of a myeloperoxidase inhibitor.

(5) The work was conducted with two different P. aeruginosa strains (i.e. AL143 and PAO1F). None of the figure legends provides details on which strain was used. For instance, in line 111, the authors refer to Figure S1B for data that I thought were done with PAO1F, while in 154, data were presented in the context of the infection model, which was conducted with the other strain.

(6) It would be good if immune cell recruitment at 2hrs and 20hrs PI could be quantified.

(7) The conclusions of Figure 4 are, in my opinion, weak (line 187-188; "It is possible that ....."). These antioxidants likely quench the low amounts of NaOCl directly. This would significantly reduce the NaOCl concentrations to a level that no longer activates expression of fro. There is no direct evidence provided that oxidized methionine induces fro expression. Do the authors postulate that this is free methionine, or could methionine and/or cysteine oxidation in FroR increase the binding affinity of the sigma factor to the promoter? Another possibility is that NaOCl deactivates the anti-sigma factor. None of these scenarios has been considered here.

(8) Line 184: The reaction constants of HOCl with Cys and Met are similar.

(9) Treatment with 16 uM NaOCl caused a growth arrest of ~15 hrs in the WT (Figure 5A), whereas no growth at all was recorded with 7.5 uM in Figure 3A.

(10) The concentration range of NaOCl causing fro expression is extremely narrow, while oxidative burst rapidly generates HOCl at much higher concentrations. This should be discussed in more detail.

Reviewer #2 (Public review):

Summary:

Foik et al. studied the regulation of the fro operon in response to HOCl, an oxidant derived from immune cells, especially neutrophils. They use a transcriptional fusion of YFP to the froA promoter in an mCherry-expressing P. aeruginosa strain to determine fro-induction under the microscope. They use this system to study fro expression in medium, in the presence of neutrophils and macrophages, neutrophil-conditioned medium, and several chemical stimuli, including NaCl, HOCl, hydrogen peroxide, nitric acid, hydrochloric acid, and sodium hydroxide. They also use a corneal infection model to demonstrate that froA is upregulated in P. aeruginosa 20 h post-infection and perform transcriptional analyses in WT and a froR mutant in response to HOCl.

Strengths:

Their data clearly shows that HOCl is a strong inducer of the fro Operon. The addition of HOCl-quenching chemicals together with HOCl abrogates the response. They also show that a froR mutant is more susceptible to HOCl than WT. Their transcriptomic data reveal genes under control of the FroR/FroI sigma factor/anti sigma factor system.

Weaknesses:

Although the presented evidence is mostly solid, some of their findings need to be evaluated more carefully; explaining the rationale behind some of the experiments might enhance the article, and some of the models proposed by the authors seem far-fetched, as outlined below:

(1) In line 76 the authors claim "Relative to P. aeruginosa that were incubated in host cell-free media, P. aeruginosa in close proximity to human neutrophils or that were engulfed in mouse macrophages appeared to increase fro expression (Fig. 1C)". Counting bacterial cells in Figure 1C shows that 1 in 17 bacteria (5.8%) induce the froA-promotor in media in the absence of immune cells, while 4 in 72 bacteria (only 5.5%) do the same in the presence of neutrophils. Contrary to the authors' claims, it appears that P. aeruginosa actually decreases fro-expression in close proximity to neutrophils. There is a slight increase in fro-expression in bacteria co-incubated with macrophages (3 in 21, or 14.3%). A more rigorous statistical analysis might substantiate the authors' claim, but, as is, the claim "neutrophils increase fro expression" is untenable.

(2) The authors should explain the rationale behind some of the chemicals used. Why did they use nitric acid? Especially at these high concentrations, a strong acid such as nitric acid might have a significant influence on the medium pH. I understand that the medium is phosphate-buffered, but 25 mM nitric acid in an unbuffered medium would shift the pH well below 2. Similar considerations apply to hydrochloric acid and sodium hydroxide.

(3) In line 187, the authors state that "It is possible that oxidized methionine increases fro expression" and they suggest a model to that effect in Figure 5D. It is unclear why the authors singled out methionine sulfoxide, since a number of other things get oxidized by HOCl. In line 184, the authors state, in the same vein, that "HOCl oxidizes methionine residues 100-fold more rapidly than other cellular components". The authors should state which other cellular compounds they are referring to. Certainly not cysteine and other thiols, which react equally fast and are highly abundant in the cell: P. aeruginosa contains 340 µM GSH, 140 µM CoA-SH (https://doi.org/10.1074/jbc.RA119.009934) plus free cysteine and cysteines in proteins (based on codon usage, 1.34% of amino acids in proteins are cysteine, while methionine is only slightly more present at 2.10%, although a number of starting methionines are removed from mature proteins).

(4) Overall (and this is probably not addressable with the authors' data), some very interesting questions remain unanswered: what is the molecular mechanism of fro-induction? How is the FroR/FroI system modulated by HOCl? Does the system sense free or protein-bound methionine-sulfoxide? Are certain methionine residues in these proteins directly oxidized by HOCl? Many "HOCl-sensing" proteins are also modified at cysteine residues or amino groups; could those play a role? And lastly: what is the connection between shear/fluid flow and HOCl, or are these totally separate mechanisms of fro-induction?

Author response:

We greatly appreciate the efforts of the reviewers, which have provided insightful and helpful comments to improve the manuscript. The feedback touches upon a number of topics, focusing on clarification or justification of experimental techniques and on understanding the mechanism by which P. aeruginosa detects HOCl. All reviewers raised the issue of how HOCl activates fro expression, including whether free or protein-bound methionine, cysteine, or other HOCl byproducts induce this expression. For the upcoming revision, we plan to perform experiments that address this issue and will discuss potential mechanistic models in light of the new data. In addition, we plan to perform additional experiments to address a reviewer’s concerns regarding the dependence of the fro response on HOCl production by neutrophils. The revision will correct imprecise statements pointed out by reviewers, and address all remaining issues requiring clarification or further discussion, including the range of HOCl sensitivity, relationship between HOCl and flow sensitivity, and justification for testing the fro response to nitric acid.

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Reply to the reviewers

GENERAL COMMENTS

We thank the three reviewers for their comments on the paper.

We are pleased to see that they consider it be a comprehensive and well-executed study, which clearly establishes a previously overlooked connection between MRTF-SRF signalling and proliferation, and that its conclusions require no further experimentation.

As review 3 points out, this work has implications for cancer biology, and suggests new research routes to understand the relation between cell adhesion, proliferation, and transformation.

However, two referees raise significant concerns about its impact

Review 1 suggests that the paper lacks impact without exploration the wider biological significance of our observations, although it considers it to be a good basic cell biology study. It suggests further work extending the findings to tissue- or tumor-based systems. While we consider such studies worthwhile – indeed we are currently pursuing these directions – we consider them beyond the scope of the present paper.

Review 2 questions the novelty of our findings. We strongly disagree. This is is the first study to show that MRTF-SRF signalling is required for the proliferation of both primary and immortalised fibroblasts, and epithelial cells. We show that MRTF inactivation leads cells to enter a quiescence-like state under conditions that would permit efficient cell cycle progression in wildtype cells. The study will alter the field's perspective on the role of MRTF-SRF signalling, previously viewed as concerned with cell adhesion, morphology, and motility.

Responses to individual reviews (italic) follow in regular text.

RESPONSE TO INDIVIDUAL REVIEWS (comments in italic, response in regular, changes made)

__Reviewer #1 __

*(Evidence, reproducibility and clarity (Required)): *

*The manuscript by Neilsen et al. presents a thorough and well-structured study showing that Myocardin-related transcription factors (MRTF-A/B), via MRTF-SRF, are essential for the proliferation of both primary and immortalized fibroblasts and epithelial cells. Using a combination of knockouts/rescue experiments, cytoskeletal analysis, and transcriptomics, the authors demonstrate that MRTF-SRF signalling controls actin dynamics and contractility-key drivers of cell cycle progression. Notably, they show that the proliferative arrest caused by MRTF loss is reversible, distinguishing it from classical senescence. **

Major points*

• The link between MRTF-SRF activity, cytoskeletal organisation, and cell proliferation is clearly established. The fact that disrupting contractility phenocopies MRTF loss strengthens the case that the pathway acts through mechanical control.*
• The authors support their conclusions using multiple cell types (MEFs, primary fibroblasts, epithelial cells), a range of complementary assays (RNA-seq, traction force microscopy, adhesion/spreading), and genetic tools (CRISPR, inducible rescue).*
• The ability to restore proliferation by re-expressing MRTF-A argues against true senescence and instead suggests a quiescence-like state driven by cytoskeletal disruption.*
• This work particularly highlights how mechanical inputs feed into transcriptional programs to regulate proliferation, with implications for understanding anchorage-dependent growth.**

Suggestions While the authors argue convincingly against classical senescence, elevated SA-βGal and SASP expression suggest a more nuanced arrest state. It not really clear what this state is or is not, therefore a deeper discussion of possible hybrid or intermediate states would be helpful - maybe potential additional experiments to include or exclude potential explanations - e.g. how does it differ from G0 exit?* Our findings show that MRTF inactivation inhibits cell proliferation under conditions that would permit efficient cell cycle progression in wildtype cells, inducing a state with some features associated with classical senescence, and others conventionally associated with reversible cell cycle arrest/quiescence. The reviewer correctly points out that this raises problems with accurately defining the nature of the MRTF-null proliferation defect.

To our knowledge there are no rigorously defined unambiguous markers for senescence, quiescence, or G0. Indeed, recent studies have shown that senescence and quiescence / G0 states are not as distinct as previously assumed (Anwar et al, 2018; Ashraf et al 2023) as we reviewed in detail in Discussion p27, §2; p28 §3. We therefore do not consider it a productive endeavour to define markers for the MRTF-null state as opposed to defining its mechanistic basis. However, we agree that we should have been clearer about how the phenotypes we observe relate to classical cell arrest states.

We have therefore revised the presentation of the Results to make it clear which features of the non-proliferative state associated with MRTF inactivation are seen in classical senescence, and which are found in reversible cell cycle exit or quiescence.

Things done:

• __Results pp16-17 and Fig 1. Figure panels and presentation are reordered to present “senescence” features together before marker expression (panel G is now panel I). Text now explicitly points out that the spectrum of cell cycle markers, specifically p27 upregulation, is not that associated with classical senescence (p16, p21,etc) but previously linked to reversible arrest or quiescence. Lines 371-380 have been moved up from the succeeding paragraph; statement added re p27 and reversible cell cycle exit on lines 387-389; summary sentence added in lines 398-401). __
• Statement added that reversibility distinguishes the MRTF defect from classical senescence p20§1 line 454-455.

• Note that p27 is associated with reversible arrest included on p20§2 line 460. We also explicitly summarised the features of the phenotype at the start of the Discussion.

• Sentences added p27§1 lines 626-631.

• Emphasis that p27 protein upregulation is associated with reversible cell cycle inhibition and quiescence is added on p28 line 668-669.

• The transcriptomic data are strong, but the paper would benefit from zooming in on specific MRTF-SRF targets (e.g., actin isoforms, adhesion molecules) that directly link cytoskeletal regulation to cell cycle control.*

We have now clarified presentation of the RNAseq data in Figure 5 and the data summary tables. Figure 5B now identifies which of those genes showing deficits in MRTF-null MEFs were previously identified as direct genomic targets for MRTF-SRF, and that the majority are cytoskeletal.

• __Additional columns added in Table 1 to indicate whether genes are candidate genomic MRTF-SRF targets; Table 2 now show gene symbol lists as well as ENSMBL IDs for GO categories and NCBI Entrez IDs for GSEA categories, respectively. __
• __Figure 5B revised to point out cytoskeletal genes that are genomic MRTF-SRF targets in bold, legend clarified p40 lines 920-922. __
• Now noted____ p23 lines 527-529 that cytoskeletal genes affected include many direct MRTF-SRF targets. Our data confirms that in MEFs, MRTF inactivation affects fibroblast cell morphology, adhesion, spreading, motility and contractility (Figures 5, 6), as seen in many other settings.

A critical question remains as to whether these effects a reflect limitation in one MRTF target gene or several, and how this defect relates to proliferation.

Concerning specific MRTF-SRF gene targets:

Cells lacking cytoplasmic actins are reported to exhibit defective proliferation, (__now noted in Results p23 lines 529-532). __We are currently evaluating whether this defect has similarities with the MRTF-null proliferation phenotype (see Discussion p31, §2).

Previous findings suggest that defective cytoplasmic actin expression may underlie most MRTF knockout phenotypes (Salvany et al, 2014; Maurice et al., 2024) previously noted in the Discussion (see p31, §2).

The myoferlin gene promotes growth of liver cancer cells by inhibiting ERK activation and oncogene induced senescence. We showed that myoferlin expression does not promote proliferation of MRTF-null MEFs in the original submission (see Figure S5E). Additionally, we now point out that the RNAseq data show that myoferlin expression is not significantly affected in MRTF-null MEFs __(new text p23, lines 532-534). __

• It depends on where what target journal would be, but this is is a very well executes mechanistic study that doesn't really have an impact. Extending the discussion to human systems-or tissues where contractility is critical-could broaden the impact and applicability of the findings.*

We interpret this comment as indicating that our paper does not address the wider biological implications of our findings by extension to studies in tissue or tumour systems.

As outlined in our response to review 3, our study provides strong evidence that MRTF-SRF will be required for cell proliferation in settings where physical progression through cell cycle transitions requires high contractility, either owing to intrinsic factors or external physical constraints such as tissue stiffness, fibrosis, or tumour microenvironment.

Discussion now explicitly addresses potential roles for tissue stiffness (pp30§2 lines 717-718, and p32§1 725-727). However, we feel that resolution of this question is beyond the scope of the present paper.

• As above, the paper briefly mentions transformation, but it would be valuable to elaborate on whether MRTF-SRF acts as a barrier or enabler in tumorigenesis under different conditions. This I feel is the main weakness remaining - e.g. it would be fine with enabling different effects driven by other transcription events in emerging tumour cells (oncogenic in context of RAS, suppressive in context of p53) but I think the manuscript fails to be definitive on this points. Addressing this would make a much stronger and impactful study. I believe they have an impact peice of science that outlines how mechanical events impact cell fate decisions, but this is unlikely to be the driver - ie it facilitates cell fate decisions in context of tissue stiffness.*

We find it difficult to understand the precise points being made here.

However, transformation has long been known to bypass physical constraints on proliferation such as the requirement for adhesion. Moreover, MRTF-SRF activity is not necessarily required for proliferation of all transformed cells (Hampl et al, 2013; Medjkane et al, 2009; our unpublished data). The relation of our findings to transformation is thus an open question, which we are actively pursuing. Now noted in revised Discussion p32, lines 752-755.

MRTF-independent proliferation of tumor cells could reflect oncogenic signals substituting for MRTF-dependent ones (eg from focal adhesions), or from relief of cytoskeletal contraints on proliferation (adhesion independent proliferation). In contrast, in proliferation of DLC1-deleted cancer cells is dependent on suppression of oncogene-induced senescence by MRTF-SRF signalling (Hampl et al, 2013). These points were already made in Discussion p28, pp30-31.

Although our current work is focussed on cell transformation, we would respectfully suggest the in-depth resolution of this complex question is beyond the scope of the present paper.

See also response to (3) above.

*Reviewer #1 (Significance (Required)): *

*Overall *

This is a well-executed and insightful study that deepens our understanding of how cytoskeletal signals drive proliferation through MRTF-SRF. It broadens the role of this pathway beyond motility and offers new perspectives on mechanotransduction and cellular plasticity. If is weak in its demonstration of biological significance, but if the aim to to present a pure basic cell biology story it is good.

The vast majority of work with the SRF system has led to the common perception that its role is exclusively with cell motility and adhesive processes, not proliferation. The results presented in the paper, even if limited to cell culture models, are therefore novel.

Reviewer #2

(Evidence, reproducibility and clarity (Required)):

*In this manuscript, Nielsen and colleagues examine the impact of MRTF-A/B and SRF gene inactivation on cell proliferation. They performed an extensive body of work (using multiple cell types and multiple clones) to show that MRTF inactivation causes cell cycle arrest and senescence (mimicking the phenotype of SRF knockout cells) although the changes in the expression of various CDK inhibitors were cell-type specific. *

*Very interestingly, simultaneous inactivation of all three major CDK inhibitors failed to rescue MRTF knockout cells from their proliferation defect. Expectedly, MRTF knockout cells exhibited defects in actin cytoskeleton, adhesion, and contractility. Interestingly, hyperactivating Rho also failed to rescue MRTF knockout cells from proliferation defect. The main conclusion of the paper was derived from experiments which showed that inhibition of either ROCK or myosin caused wild-type cells to behave like MRTF knockout cells rather than demonstration of any molecular perturbation that could reverse the proliferation defect of MRTF knockout cells. *

While the experimental studies are thorough and rigorous, a vast majority of the core findings related to the loss-of-function of MRTF that are reported herein (i.e. defects in cell proliferation, elevation of CDK inhibitors, migration, actin cytoskeleton, contractility) are not conceptually new and have been previously reported in other cell systems by several investigators including this research group.

This is the first study showing that MRTF-SRF signalling is required for the proliferation of both primary and immortalised fibroblasts, and epithelial cells. We show that the MRTF-SRF non-proliferative state combines features of both classical senescence and reversible cell cycle exit / quiescence.

The vast majority of previous work with the SRF system has led to the common perception that its role is exclusively related to cell motility and adhesive processes and not proliferation (see Olson and Nordheim 2010). Where proliferation has been examined directly, both others and our own previous studies of the MRTFs in immune cells and cancer cells lines have revealed no direct role in proliferation (Schratt et al, 2001;Medjkane et al 2009; Maurice et al, 2024).

The results presented here are therefore novel.

In the reviewer's opinion, since the authors have not been able to identify a molecular strategy to reverse the proliferation phenotype of MRTF knockout cells, the underlying mechanisms of MRTF-dependent regulation of cell proliferation remain largely unanswered.

Indeed, our attempts to rescue the phenotype (knockouts of the CKIs, and overexpression of different downregulated factors) did not restore proliferation. We therefore now aim to attack the problem (i) through overexpression screens, and (ii) by identifying differences between MRTF-SRF dependent and -independent (eg transformed) cells. However, these are new projects that are beyond the scope of a revised paper.

• *

Other comments: Majority of the immunoblot data have not been quantified.

P16 data in Fig 1G vs Fig S1A are not similar (although the authors mention that the findings are similar)

We have addressed these issues by reorganisation and quantification the immunoblotting data as follows:

• Figure S1A has been moved to new Figure 1I, replacing the limited analysis shown in old Figure 1G. This more comprehensive, and displays data from all three WT and Mrtfab-/-
• Figure 1I data is quantified. Marker expression in each Mrtfab-/- pool is evaluated relative its mean expression in the three WT pools treated in parallel.
• A new Figure S1A shows mean marker expression across the three Mrtfab-/- pools, drawn from 5 independent analyses (not all markers included in each analysis). Different analyses of marker expression may exhibit variation, resulting from differences in handling, culture medium, plating density, relative confluence, etc. However, Mrtfab-/- cells exhibit markedly increased p27 and TLR2 expression, while expression of the other markers tested, including p16, consistently decreases.
• Spearman comparisons among the WT and Mrtfab-/- pools show that relative marker expression is indeed well correlated between the pools of each genotype. Note on quantitation added in Methods p10 lines 209-213.

Figure 1I moved from former Figure S1A, to replace former Figure 1G. New legend now includes quantitation, and reference to Spearman correlations, p44 lines 834-841.

New Figure S1A displays data from multiple independent experiments with all 3 Mrtfab-/- pools. New legend, p44 lines 997-1002.

Figure S1B legend notes correlation between relative marker expression in untreated WT and Mrtfab-/- cells, p44, lines 1005-1008.

Results text rewritten p17 lines 383-391; no reference to “similar”.

*Reviewer #2 (Significance (Required)): *

*This study aims to investigate a fundamental biological question of how an actin-regulated transcription machinery regulates cell proliferation and is therefore of broad significance. Strengths and limitations of this study are described above. *

Reviewer #3

*(Evidence, reproducibility and clarity (Required)): *

Summary

*The manuscript by Nielsen et al. (Treisman lab) entitled "MRTF-dependent cytoskeletal dynamics drive efficient cell cycle progression" investigates the effects on cell proliferation elicited upon cellular depletion of the transcription factors MRTF-A and MRTF-B. The MRTFs are actin-dependent co-factors of SRF, which direct the transcription of SRF target genes. The MRTF-SRF regulatory circuit defines both the functioning and the control of actin-driven cytoskeletal dynamics. *

*The work presented identifies essential molecular links that interconnect cytoskeleton-dependent cellular activities (cell-cell adhesion, cell-substrate contact, cell spreading) and cell proliferation. *

*General assessment on used methodology. *

*The presented comprehensive body of work is performed competently; it includes all relevant and necessary state-of-the-art technologies. *

• *

Reviewer #3 (Significance (Required)):

Advance

Previously published evidence by others (including the Treisman group) had indicated that SRF does not seem essential for the proliferation of some cell types (i. e., embryonic (stem) cells, activation-dependent immune cells, etc.). In regard to this, the authors discuss in the current manuscript: "Although further work is needed to elucidate the basis for these context-dependent dfferences, our data show that MRTF-SRF signalling is likely to play a more general role in proliferation than previously thought." The current manuscript already delineates this "general role": MRTF-SRF signalling impinges on cell proliferation whenever proliferative activities are dependent upon cytoskeletal dynamics.

We of course support the view that it is MRTF-SRF's role in cytoskeletal dynamics, especially contractility, that is a limiting factor for cell cycle progression in our cells; however, this may not be the cases or other cell types or settings, such adhesion-independent or transformed cells, and/or stiff tissue environments.

We have stated this view more strongly, modifying the abstract and discussion, and rewording the sentence quoted above.

The major point is that MRTF-SRF-dependent proliferation may be more common than previously thought, the field having focussed on its role in cytoskeletal dynamics rather than proliferation.

Abstract lines 48-49; Discussion p28, line 668-669; pp30-31, lines 713-714, 725-727. See also last para pp31/32, __added lines 752-755. __

*The work has implications for cancer biology. It offers new directions to investigate the regulation of proliferative activities of anchorage-independent tumor cells. **

Audience *

*The insights generated serve the wide interests of a large and diverse group of cell and tumor biologists. *

*Reviewers field of expertise (keywords). *

Cytoskeletal dynamics, transcriptional con*

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Referee #3

Evidence, reproducibility and clarity

Summary

The manuscript by Nielsen et al. (Treisman lab) entitled "MRTF-dependent cytoskeletal dynamics drive efficient cell cycle progression" investigates the effects on cell proliferation elicited upon cellular depletion of the transcription factors MRTF-A and MRTF-B. The MRTFs are actin-dependent co-factors of SRF, which direct the transcription of SRF target genes. The MRTF-SRF regulatory circuit defines both the functioning and the control of actin-driven cytoskeletal dynamics. The work presented identifies essential molecular links that interconnect cytoskeleton-dependent cellular activities (cell-cell adhesion, cell-substrate contact, cell spreading) and cell proliferation.

General assessment on used methodology.

The presented comprehensive body of work is performed competently; it includes all relevant and necessary state-of-the-art technologies.

Significance

Advance

Previously published evidence by others (including the Treisman group) had indicated that SRF does not seem essential for the proliferation of some cell types (i. e., embryonic (stem) cells, activation-dependent immune cells, etc.). In regard to this, the authors discuss in the current manuscript: "Although further work is needed to elucidate the basis for these context-dependent dfferences, our data show that MRTFSRF signalling is likely to play a more general role in proliferation than previously thought." The current manuscript already delineates this "general role": MRTF-SRF signalling impinges on cell proliferation whenever proliferative activities are dependent upon cytoskeletal dynamics.

The work has implications for cancer biology. It offers new directions to investigate the regulation of proliferative activities of anchorage-independent tumor cells.

Audience

The insights generated serve the wide interests of a large and diverse group of cell and tumor biologists.

Reviewers field of expertise (keywords).

Cytoskeletal dynamics, transcriptional control.

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

In this manuscript, Nielsen and colleagues examine the impact of MRTF-A/B and SRF gene inactivation on cell proliferation. They performed an extensive body of work (using multiple cell types and multiple clones) to show that MRTF inactivation causes cell cycle arrest and senescence (mimicking the phenotype of SRF knockout cells) although the changes in the expression of various CDK inhibitors were cell-type specific. Very interestingly, simultaneous inactivation of all three major CDK inhibitors failed to rescue MRTF knockout cells from their proliferation defect. Expectedly, MRTF knockout cells exhibited defects in actin cytoskeleton, adhesion, and contractility. Interestingly, hyperactivating Rho also failed to rescue MRTF knockout cells from proliferation defect. The main conclusion of the paper was derived from experiments which showed that inhibition of either ROCK or myosin caused wild-type cells to behave like MRTF knockout cells rather than demonstration of any molecular perturbation that could reverse the proliferation defect of MRTF knockout cells. While the experimental studies are thorough and rigorous, a vast majority of the core findings related to the loss-of-function of MRTF that are reported herein (i.e. defects in cell proliferation, elevation of CDK inhibitors, migration, actin cytoskeleton, contractility) are not conceptually new and have been previously reported in other cell systems by several investigators including this research group. In the reviewer's opinion, since the authors have not been able to identify a molecular strategy to reverse the proliferation phenotype of MRTF knockout cells, the underlying mechanisms of MRTF-dependent regulation of cell proliferation remain largely unanswered.

Other comments: Majority of the immunoblot data have not been quantified. P16 data in Fig 1G vs Fig S1A are not similar (although the authors mention that the findings are similar)

Significance

This study aims to investigate a fundamental biological question of how an actin-regulated transcription machinery regulates cell proliferation and is therefore of broad significance. Strengths and limitations of this study are described above.

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 #1

Evidence, reproducibility and clarity

The manuscript by Neilsen et al. presents a thorough and well-structured study showing that Myocardin-related transcription factors (MRTF-A/B), via MRTF-SRF, are essential for the proliferation of both primary and immortalized fibroblasts and epithelial cells. Using a combination of knockouts/rescue experiments, cytoskeletal analysis, and transcriptomics, the authors demonstrate that MRTF-SRF signalling controls actin dynamics and contractility-key drivers of cell cycle progression. Notably, they show that the proliferative arrest caused by MRTF loss is reversible, distinguishing it from classical senescence.

Major points

1. The link between MRTF-SRF activity, cytoskeletal organisation, and cell proliferation is clearly established. The fact that disrupting contractility phenocopies MRTF loss strengthens the case that the pathway acts through mechanical control.
2. The authors support their conclusions using multiple cell types (MEFs, primary fibroblasts, epithelial cells), a range of complementary assays (RNA-seq, traction force microscopy, adhesion/spreading), and genetic tools (CRISPR, inducible rescue).
3. The ability to restore proliferation by re-expressing MRTF-A argues against true senescence and instead suggests a quiescence-like state driven by cytoskeletal disruption.
4. This work particularly highlights how mechanical inputs feed into transcriptional programs to regulate proliferation, with implications for understanding anchorage-dependent growth.

Suggestions

1. While the authors argue convincingly against classical senescence, elevated SA-βGal and SASP expression suggest a more nuanced arrest state. It not really clear what this state is or is not, therefore a deeper discussion of possible hybrid or intermediate states would be helpful - maybe potential additional experiments to include or exclude potential explanations - e.g. how does it differ from G0 exit?
2. The transcriptomic data are strong, but the paper would benefit from zooming in on specific MRTF-SRF targets (e.g., actin isoforms, adhesion molecules) that directly link cytoskeletal regulation to cell cycle control.
3. It depends on where what target journal would be, but this is is a very well executes mechanistic study that doesn't really have an impact. Extending the discussion to human systems-or tissues where contractility is critical-could broaden the impact and applicability of the findings.
4. As above, the paper briefly mentions transformation, but it would be valuable to elaborate on whether MRTF-SRF acts as a barrier or enabler in tumorigenesis under different conditions. This I feel is the main weakness remaining - e.g. it would be fine with enabling different effects driven by other transcription events in emerging tumour cells (oncogenic in context of RAS, suppressive in context of p53) but I think the manuscript fails to be definitive on this points. Addressing this would make a much stronger and impactful study. I believe they have an impact peice of science that outlines how mechanical events impact cell fate decisions, but this is unlikely to be the driver - ie it facilitates cell fate decisions in context of tissue stiffness.

Significance

Overall

This is a well-executed and insightful study that deepens our understanding of how cytoskeletal signals drive proliferation through MRTF-SRF. It broadens the role of this pathway beyond motility and offers new perspectives on mechanotransduction and cellular plasticity. If is weak in its demonstration of biological significance, but if the aim to to present a pure basic cell biology story it is good.

this is the first comment

Brug gerne newtype når vi bare skal "wrappe" en underliggende datatype (i det her tilfælde Double) med en anden datatype (som her er Q der er vores value constructor til højre for =)

Vigtig: forklaring af phantom type

Fra Learn You Haskell...: "Once again, it's very important to distinguish between the type constructor and the value constructor. When declaring a data type, the part before the = is the type constructor and the constructors after it (possibly separated by |'s) are value constructors." Så Q til vnstre er type constructoren med type parameteret unit, og Q til højre er valu constructor, som tager en Double

Husk at value constructors for en type er til højre for =

Faktisk rigtig fin forklaring for at forstå forskel på type og type constructor

Vigtigt!

rationalisme = denk aan rationeel nadenken, via rede niet emoties.

ezelsbrug: nativisme = natuur. dus aangeboren kwaliteiten, nature

à retirer

à expliciter et illustrer davantage

à placer peut-être plus haut lorsqu'il est question du pouvoir du lecteur·e à poursuivre la pensée du livre

expliciter davantage en quelques lignes le contenu du texte pour les personnes qui ne le connaissent pas

Il me semble que la famille était également intéressée par cette publication du texte

l'historienne

Suzanne Citron

de cette femme

elles n'ont pas été collègues (à enlever de l'énumération)

Laurence De Cock

Suzanne Citron

remplacer par "sciences sociales"

Suzanne Citron

peut-être ajouter une ou deux phrases pour expliquer comment il a été versé et quand

remplacer par "l'historienne"

idem

idem

Ajouter Suzanne devant le nom pour éviter la confusion avec Pierre

No idea what this means, but agree that string based management of a system is bad

To ourselves

Eyey on the ball

paid attention

Dao of the ancestors

Conservation of complexity

Unspeakable

Bedrock

Made of language

Felt experience

adrift

What's going on

Grip on the outline?

Swarn

Imagined

Edge running

X

ISWYM

Share view points

Language seen

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eLife Assessment

This study provides valuable insights into the host's variable susceptibility to Mycobacterium tuberculosis, using a novel collection of wild-derived inbred mouse lines from diverse geographic locations, along with immunological and single-cell transcriptomic analyses. While the data are convincing, a deeper mechanistic investigation into neutrophil subset functions would have further enhanced the study. This work will interest microbiologists and immunologists in the tuberculosis field.

Reviewer #1 (Public review):

Summary:

This study investigated the heterogeneous responses to Mycobacterium tuberculosis (Mtb) in 19 wild-derived inbred mouse strains collected from various geographic locations. The goal of this study is to identify novel mechanisms that regulate host susceptibility to Mtb infection. Using the genetically resistant C57BL/6 mouse strain as the control, they successfully identified a few mouse strains that revealed higher bacterial burdens in the lung, implicating increased susceptibility in those mouse strains. Furthermore, using flow cytometry analysis, they discovered strong correlations between CFU and various immune cell types, including T cells and B cells. The higher neutrophil numbers correlated with significantly higher CFU in some of the newly identified susceptible mouse strains. Interestingly, MANB and MANC mice exhibited comparable numbers of neutrophils but showed drastically different bacterial burdens. The authors then focused on the neutrophil heterogeneity and utilized a single-cell RNA-seq approach, which led to identifying distinct neutrophil subsets in various mouse strains, including C57BL/6, MANA, MANB, and MANC. Pathway analysis on neutrophils in susceptible MANC strain revealed a highly activated and glycolytic phenotype, implicating a possible mechanism that may contribute to the susceptible phenotype. Lastly, the authors found that a small group of neutrophil-specific genes are expressed across many other cell types in the MANC strain.

Strengths:

This manuscript has many strengths.

(1) Utilizing and characterizing novel mouse strains that complement the current widely used mouse models in the field of TB. Many of those mouse strains will be novel tools for studying host responses to Mtb infection.

(2) The study revealed very unique biology of neutrophils during Mtb infection. It has been well-established that high numbers of neutrophils correlate with high bacterial burden in mice. However, this work uncovered that some mouse strains could be resistant to infection even with high numbers of neutrophils in the lung, indicating the diverse functions of neutrophils. This information is important.

Weaknesses:

The weaknesses of the manuscript are that the work is relatively descriptive. It is unclear whether the neutrophil subsets are indeed functionally different. While single-cell RNA seq did provide some clues at transcription levels, functional and mechanistic investigations are lacking. Similarly, it is unclear how highly activated and glycolytic neutrophils in MANC strain contribute to its susceptibility.

Reviewer #2 (Public review):

Summary:

These studies investigate the phenotypic variability and roles of neutrophils in tuberculosis (TB) susceptibility by using a diverse collection of wild-derived inbred mouse lines. The authors aimed to identify new phenotypes during Mycobacterium tuberculosis infection by developing, infecting, and phenotyping 19 genetically diverse wild-derived inbred mouse lines originating from different geographic regions in North America and South America. The investigators achieved their main goals, which were to show that increasing genetic diversity increases the phenotypic spectrum observed in response to aerosolized M. tuberculosis, and further to provide insights into immune and/or inflammatory correlates of pulmonary TB. Briefly, investigators infected wild-derived mice with aerosolized M. tuberculosis and assessed early infection control at 21 days post-infection. The time point was specifically selected to correspond to the period after infection when acquired immunity and antigen-specific responses manifest strongly, and also early susceptibility (morbidity and mortality) due to M. tuberculosis infection has been observed in other highly susceptible wild-derived mouse strains, some Collaborative Cross inbred strains, and approximately 30% of individuals in the Diversity Outbred mouse population. Here, the investigators normalized bacterial burden across mice based on inoculum dose and determined the percent of immune cells using flow cytometry, primarily focused on macrophages, neutrophils, CD4 T cells, CD8 T cells, and B cells in the lungs. They also used single-cell RNA sequencing to identify neutrophil subpopulations and immune phenotypes, elegantly supplemented with in vitro macrophage infections and antibody depletion assays to confirm immune cell contributions to susceptibility. The main results from this study confirm that mouse strains show considerable variability to M. tuberculosis susceptibility. Authors observed that enhanced infection control correlated with higher percentages of CD4 and CD8 T cells, and B cells, but not necessarily with the percentage of interferon-gamma (IFN-γ) producing cells. High levels of neutrophils and immature neutrophils (band cells) were associated with increased susceptibility, and the mouse strain with the most neutrophils, the MANC line, exhibited a transcriptional signature indicative of a highly activated state, and containing potentially tissue-destructive, mediators that could contribute to the strain's increased susceptibility and be leveraged to understand how neutrophils drive lung tissue damage, cavitation, and granuloma necrosis in pulmonary TB.

Strengths:

The strengths are addressing a critically important consideration in the tuberculosis field - mouse model(s) of the human disease, and taking advantage of the novel phenotypes observed to determine potential mechanisms. Notable strengths include,

(1) Innovative generation and use of mouse models: Developing wild-derived inbred mice from diverse geographic locations is innovative, and this approach expands the range of phenotypic responses observed during M. tuberculosis infection. Additionally, the authors have deposited strains at The Jackson Laboratory making these valuable resources available to the scientific community.

(2) Potential for translational research: The findings have implications for human pulmonary TB, particularly the discovery of neutrophil-associated susceptibility in primary infection and/or neutrophil-mediated disease progression that could both inform the development of therapeutic targets and also be used to test the effectiveness of such therapies.

(3) Comprehensive experimental design: The investigators use many complementary approaches including in vivo M. tuberculosis infection, in vitro macrophage studies, neutrophil depletion experiments, flow cytometry, and a number of data mining, machine learning, and imaging to produce robust and comprehensive analyses of the wild-derives d strains and neutrophil subpopulations in 3 weeks after M. tuberculosis infection.

Weaknesses:

The manuscript and studies have considerable strengths and very few weaknesses. One minor consideration is that phenotyping is limited to a single limited-time point; however, this time point was carefully selected and has a strong biological rationale provided by investigators. This potential weakness does not diminish the overall findings, exciting results, or conclusions.

Author response:

Reviewer #1 (Public review):

[…] Strengths:

This manuscript has many strengths.

(1) Utilizing and characterizing novel mouse strains that complement the current widely used mouse models in the field of TB. Many of those mouse strains will be novel tools for studying host responses to Mtb infection.

(2) The study revealed very unique biology of neutrophils during Mtb infection. It has been well-established that high numbers of neutrophils correlate with high bacterial burden in mice. However, this work uncovered that some mouse strains could be resistant to infection even with high numbers of neutrophils in the lung, indicating the diverse functions of neutrophils. This information is important.

We are grateful for the reviewer’s thoughtful consideration of our work and appreciate their comment that our mouse strains can benefit the models available in the TB field. We further appreciate the recognition of the importance of neutrophil diversity during Mtb infection.

Weaknesses:

The weaknesses of the manuscript are that the work is relatively descriptive. It is unclear whether the neutrophil subsets are indeed functionally different. While single-cell RNA seq did provide some clues at transcription levels, functional and mechanistic investigations are lacking.

We appreciate this comment and agree that further research needs to be done on the functionality of the neutrophils to discover mechanistic differences between the mouse genotypes. Out attempts at extracting sufficient RNA from sorted neutrophils from the mouse lungs were unsuccessful. However, future attempts at comparing RNA expression between mouse genotypes as well as proteomic data are necessary to determine the mechanistic differences in neutrophil biology in these mice.

Similarly, it is unclear how highly activated and glycolytic neutrophils in MANC strain contribute to its susceptibility.

This is a fair comment and we agree that it is still unclear how these neutrophils contribute to MANC susceptibility. Growing the neutrophils ex vivo and infecting them with Mtb is technically challenging, due to the slow growth of Mtb and the short lifespan of the neutrophils. As mentioned in the comment above, future in vivo characterization and RNA expression studies will be necessary to address these questions.

Reviewer #2 (Public review):

[…] Strengths:

The strengths are addressing a critically important consideration in the tuberculosis field - mouse model(s) of the human disease, and taking advantage of the novel phenotypes observed to determine potential mechanisms. Notable strengths include,

(1) Innovative generation and use of mouse models: Developing wild-derived inbred mice from diverse geographic locations is innovative, and this approach expands the range of phenotypic responses observed during M. tuberculosis infection. Additionally, the authors have deposited strains at The Jackson Laboratory making these valuable resources available to the scientific community.

(2) Potential for translational research: The findings have implications for human pulmonary TB, particularly the discovery of neutrophil-associated susceptibility in primary infection and/or neutrophil-mediated disease progression that could both inform the development of therapeutic targets and also be used to test the effectiveness of such therapies.

(3) Comprehensive experimental design: The investigators use many complementary approaches including in vivo M. tuberculosis infection, in vitro macrophage studies, neutrophil depletion experiments, flow cytometry, and a number of data mining, machine learning, and imaging to produce robust and comprehensive analyses of the wild-derives d strains and neutrophil subpopulations in 3 weeks after M. tuberculosis infection.

We thank the reviewer for their thorough and thoughtful assessment of our study. We appreciate the recognition that this mouse model can become a resource and can benefit the study of different immune responses to Mtb infection as well as be informative for studying human TB. We further appreciate their comment that the complementary approaches we have used to characterized the mouse phenotypes strengthens this study.

Weaknesses:

The manuscript and studies have considerable strengths and very few weaknesses. One minor consideration is that phenotyping is limited to a single limited-time point; however, this time point was carefully selected and has a strong biological rationale provided by investigators. This potential weakness does not diminish the overall findings, exciting results, or conclusions.

We thank the reviewer for pointing out that a single time point has been studied, and that this time point is biologically relevant. We agree that additional time points, including later time points that address systemic dissemination, should be included in future studies.

Open MT_LayeredEarth on Binder:

https://mybinder.org/v2/gh/geoscixyz/em-apps/main?filepath=notebooks/em/MT_LayeredEarth.ipynb

Humans are social animals and isolation from others is the basic principle of some of the most inhumane torture methods (solitary confinement). Assuming that such dissociation leads to anguish, does the speaker recommend we conquer this anguish and that there is a light on the other end of the tunnel?

回收垃圾，新瓶装旧酒

A jó magyar szöveg: A Portfólió NAV tabfüleket Portfólió NAV menüpontban a Portfóliók listában adott soron dupla klikkre érhetőek el, ill. a sorvégi (...) ikonra kaattintva a Megtekint funkcióval hívhatóek elő:

During viewing the Portfolio NAV data by double-clicking on the valuation row by default, the detailed data of the first tab are displayed. The detailed data of the other tabs can be accessed by clicking on the names of the tabs. The currently displayed tab page name is marked in underlined, blue letters.

可以嵌套的

eLife Assessment

In this important study, the authors develop a microfluidic "Vessel-on-Chip" model to study Neisseria meningitidis interactions in an in vitro vascular system. Compelling evidence demonstrates that endothelial cell-lined channels can be colonized by N. meningitidis, triggering neutrophil recruitment with advantages over complex surgical xenograft models. This system offers potential for follow-on studies of N. meningitidis pathogenesis, though it lacks the cellular complexity of true vasculature including smooth muscle cells and pericytes.

[Editors' note: this paper was reviewed by Review Commons.]

Reviewer #1 (Public review):

Summary:

The work by Pinon et al describes the generation of a microvascular model to study Neisseria meningitidis interactions with blood vessels. The model uses a novel and relatively high throughput fabrication method that allows full control over the geometry of the vessels. The model is well characterized from the vascular standpoint and shows improvements when exposed to flow. The authors show that Neisseria binds to the 3D model in a similar geometry that in the animal xenograft model, induces an increase in permeability short after bacterial perfusion, and endothelial cytoskeleton rearrangements including a honeycomb actin structure. Finally, the authors show neutrophil recruitment to bacterial microcolonies and phagocytosis of Neisseria.

Strengths:

The article is overall well written, and it is a great advancement in the bioengineering and sepsis infection field. The authors achieved their aim at establishing a good model for Neisseria vascular pathogenesis and the results support the conclusions. I support the publication of the manuscript. I include below some clarifications that I consider would be good for readers.

One of the most novel things of the manuscript is the use of a relatively quick photoablation system. Could this technique be applied in other laboratories? While the revised manuscript includes more technical details as requested, the description remains difficult to follow for readers from a biology background. I recommend revising this section to improve clarity and accessibility for a broader scientific audience.

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

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

Significance:

The manuscript is comprehensive, complete and represents the first bioengineered model of sepsis. One of the major strengths is the carful characterization and benchmarking against the animal xenograft model. Beyond the technical achievement, the manuscript is also highly quantitative and includes advanced image analysis that could benefit many scientists. The authors show a quick photoablation method that would be useful for the bioengineering community and improved the state-of-the-art providing a new experimental model for sepsis.

My expertise is on infection bioengineered models.

Reviewer #2 (Public review):

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

The claims and the conclusions are supported by the data, the methods are properly presented, and the data is analyzed adequately. The most important strength of this manuscript is the technology developed to build this model, which is impressive and very innovative. The Vessel-on-Chip can be tuned to acquire complex shapes and, according to the authors, the process has been optimized to produce models very quickly. This is a great advancement compared with the technologies used to produce other equivalent models. This model proves to be equivalent to the most advanced model used to date (skin xenograft mouse model). The human skin xenograft mouse model requires complex surgical techniques and has the practical and ethical limitations associated with the use of animals. However, the Vessel-on-chip model is free of ethical concerns, can be produced quickly, and allows to precisely tune the vessel's geometry and to perform higher resolution microscopy. Both models were comparable in terms of the hallmarks defining the disease, suggesting that the presented model can be an effective replacement of the animal use in this area. In addition, the Vessel-on-Chip allows to perform microscopy with higher resolution and ease, which can in turn allow more complex and precise image-based analysis.

A limitation of this model is that it lacks the multicellularity that characterizes other similar models, which could be useful to research disease more extensively. However, the authors discuss the possibilities of adding other cells to the model, for example, fibroblasts. It is also not clear whether the technology presented in the current paper can be adopted by other labs. The methodology is complex and requires specialized equipment and personnel, which might hinder its widespread utilization of this model by researchers in the field.

This manuscript will be of interest for a specialized audience focusing on the development of microphysiological models. The technology presented here can be of great interest to researchers whose main area of interest is the endothelium and the blood vessels, for example, researchers on the study of systemic infections, atherosclerosis, angiogenesis, etc. This manuscript can have great applications for a broad audience and it can present an opportunity to begin collaborations, aimed at answering diverse research questions with the same model.

Reviewer #3 (Public review):

Summary:

In this manuscript Pinon et al. describe the development of a 3D model of human vasculature within a microchip to study Neisseria meningitidis (Nm)- host interactions and validate it through its comparison to the current gold-standard model consisting of human skin engrafted onto a mouse. There is a pressing need for robust biomimetic models with which to study Nm-host interactions because Nm is a human-specific pathogen for which research has been primarily limited to simple 2D human cell culture assays. Their investigation relies primarily on data derived from microscopy and its quantitative analysis, which support the authors' goal of validating their Vessel-on-Chip (VOC) as a useful tool for studying vascular infections by Nm, and by extension, other pathogens associated with blood vessels.

Strengths:<br /> • Introduces a novel human in vitro system that promotes control of experimental variables and permits greater quantitative analysis than previous models<br /> • The VOC model is validated by direct comparison to the state-of-the-art human skin graft on mouse model<br /> • The authors make significant efforts to quantify, model, and statistically analyze their data<br /> • The laser ablation approach permits defining custom vascular architecture<br /> • The VOC model permits the addition and/or alteration of cell types and microbes added to the model<br /> • The VOC model permits the establishment of an endothelium developed by shear stress and active infusion of reagents into the system

Weaknesses:<br /> • The work presented here is mostly descriptive, with little new information that is learned about the biology of Nm or endothelial cells. However, the goal of this study was to establish the VOC model, and the validation presented here is necessary for follow-on studies on Nm pathogenesis and host response.<br /> • The VOC model contains one cell type, human umbilical cord vascular endothelial cells (HUVECs), while true vasculature contains a number of other cell types that associate with and affect the endothelium, such as smooth muscle cells, pericytes, and components of the immune system. These and other shortcomings of the VOC model as it currently stands warrant additional discussion.

Impact:<br /> The VOC model presented by Pinon et al. is an exciting advancement in the set of tools available to study human pathogens interacting with the vasculature. This manuscript focuses on validating the model, and as such sets the foundation for impactful research in the future. Of particular value is the photoablation technique that permits the custom design of vascular architecture without the use of artificial scaffolding structures described in previously published works.

Author response:

Point-by-point description of the revisions

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

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

Major comments:

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

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

Author response image 1.

F-actin (red) and ezrin (yellow) staining after 3h of infection with N. meningitidis (green) in 2D (top) and 3D (bottom) vessel-on-chip models.

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

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

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

We thank the Reviewer #1 for this suggestion.

• According to this recommendation, we imaged monolayers of endothelial cells in the flat regions of the chip (the two lateral channels) using the same microscopy conditions (i.e., Obj. 40X N.A. 1.05) that have been used to detect honeycomb structures in the 3D vessels in vitro. We showed that more than 56% of infected cells present these honeycomb structures in 2D, which is 13% less than in 3D, and is not significant due to the distributions of both populations. Thus, we conclude that under both in vitro conditions, 2D and 3D, the amount of infected cells exhibiting cortical plaques is similar. We have added the graph and the confocal images in Figure S4B and lines 418-419 of the revised manuscript.

• We recently performed staining of ezrin in the chip and imaged both the 3D and 2D regions. Although ezrin staining was visible in 3D (Fig. 1 of this response), it was not as obvious as other markers under these infected conditions and we did not include it in the main text. Interpretation of this result is not straight forward as for instance the substrate of the cells is different and it would require further studies on the behaviour of ERM proteins in these different contexts.

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

Following the Reviewer’s comment, we introduced more detailed explanations regarding the photoablation:

• L157-163 (Results): "Briefly, the chosen design is digitalized into a list of positions to ablate. A pulsed UV-LASER beam is injected into the microscope and shaped to cover the back aperture of the objective. The laser is then focused on each position that needs ablation. After introducing endothelial cells (HUVEC) in the carved regions,…"

• L512-516 (Discussion): "The speed capabilities drastically improve with the pulsing repetition rate. Given that our laser source emits pulses at 10kHz, as compared to other photoablation lasers with repetitions around 100 Hz, our solution could potentially gain a factor of 100."

• L1082-1087 (Materials and Methods): "…, and imported in a python code. The control of the various elements is embedded and checked for this specific set of hardware. The code is available upon request." Adding these three paragraphs gives more details on how photoablation works thus improving the manuscript.

Minor comments:

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

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

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

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

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

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

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

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

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

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

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

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

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

We thank Reviewer #1 for this suggestion. Indeed, our manuscript may lack explaining limitations, and adding them to the text will help improve it:

• The perspectives of our model include introducing perivascular cells surrounding the vessel and fibroblasts into the collagen gel as discussed previously and added in the discussion part (L555-570).

• Our choice for HUVEC cells focused on recapitulating the characteristics of venules that respect key features such as the overexpression of CD62E and adhesion of neutrophils during inflammation. Using microvascular endothelial cells originating from different tissues would be very interesting. This possibility is now mentioned in the discussion lines 567-568.

• Photoablation is a homemade fabrication technique that can be implemented in any lab harboring an epifluorescence microscope. This method has been more detailed in the revised manuscript (L1085-1087).

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

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

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

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

Significance

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

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

Summary:

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

Major comments:

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

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

Minor comments:

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

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

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

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

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

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

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

Strengths and limitations

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

We thank Reviewer #2 for his/her comment on the strengths and limitations of our work. The difficulty is that our study opens many futur research directions and applications and we hope that the work serves as the basis for many future studies but one can only address a limited set of experiments in a single manuscript.

• Experiments investigating the role of N. meningitidis genes require significant optimization of the system. Multiplexing is a potential avenue for future development, which would allow the testing of many mutants. The fast photoablation approach is particularly amenable to such adaptation.

• Cells and bacteria inside the chambers could be isolated and analyzed at the transcriptomic level or by flow cytometry. This would imply optimizing a protocol for collecting cells from the device via collagenase digestion, for instance. This type of approach would also benefit from multiplexing to enhance the number of cells.

• As mentioned above, the revised manuscript discusses the multicellular capabilities of our model, including the integration of additional immune cells and potential connections to other organ systems. We believe that these approaches are feasible and valuable for studying various aspects of N. meningitidis infection.

Advance

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

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

Audience

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

Field of expertise:

Infection biology, organ-on-chip, fungal pathogens.

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

References

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

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

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

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

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

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

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

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