Guidance by followers ensures long-range coordination of cell migration through α-catenin mechanoperception

Boutillon, Arthur; Escot, Sophie; Elouin, Amélie; Jahn, Diego; González-Tirado, Sebastián; Starruß, Jörn; Brusch, Lutz; David, Nicolas B.

doi:10.1016/j.devcel.2022.05.001

Cited by 21 publications

(41 citation statements)

References 98 publications

(131 reference statements)

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“…In the following, we present its core properties for a few selected models of multi-cellular processes. Several other applications to various multi-cellular problems and different data types have been published separately and are not included here (See Boutillon et al [2022] Bundgaard et al [2022]).…”

Section: Resultsmentioning

confidence: 99%

FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes

Alamoudi

Schälte

Müller

et al. 2023

Preprint

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Motivation: Biological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyze and understand the processes determining tissue dynamics. These models usually depend on parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as Approximate Bayesian Computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes. Results: Here, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology. Availability: FitMultiCell is available open-source at https://gitlab.com/fitmulticell/fit. Contact: jan.hasenauer@uni-bonn.de

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Section: Resultsmentioning

confidence: 99%

FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes

Alamoudi

Schälte

Müller

et al. 2023

Preprint

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“…When contact to following posterior axial mesoderm cells gets lost, polster cells no longer receive guidance by posterior axial mesoderm cells and increased randomness of polster cell trajectories then reduces the polster's net velocity until the following posterior axial mesoderm catches up. Information about the advancement of the posterior axial mesoderm is thereby propagating in the direction of motion faster than the individual cell velocity and polster cells at the front of the axis can therefore respond with net slowing down to perturbations at the rear, as further confirmed by laser ablation and transplantation experiments [20]. In the following, we will call the cells of the posterior axial mesoderm simply axial cells and compare them to polster cells.…”

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confidence: 89%

“…Mathematical models and computational analysis are essential to unravel the mechanisms of self-organization that underlie the emergence of collective migration from the interactions among individual cells [7][8][9][10]. Integrating experimental and theoretical approaches, different interaction mechanisms between individual migrating cells have been identified, notably chemotaxis during vasculogenesis [11,12] and during Dictyostelium aggregation and slug motion [2], self-generated gradients in the zebrafish posterior lateral line primordium [13,14], contact inhibition of locomotion during neural crest streaming [15], axis alignment (of polar/ferromagnetic or apolar/nematic type) in local neighborhood [16,17], chase-and-run between different cell types like neural crest and placodal cells [18], leader cell selection by Notch signaling and guidance of follower cells in zebrafish trunk neural crest migration [19] as well as the reverse of the previous mechanism, guidance by followers, in polster cell migration toward the animal pole followed by posterior axial mesoderm during zebrafish gastrulation [20]. An important question is how robustly each of these mechanisms can self-organise collective cell migration given variable starting conditions, perturbations and variability of individual cells.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, the motility of polster cells is tightly regulated by the left-behind axial cells. At the molecular level, the counter-intuitive propagation of information from follower cells to leading polster cells is mediated by E-cadherin-dependent cell-cell contacts [33] and by E-cadherin/α-catenin mechanotransduction which senses the contact by a moving (follower) cell and regulates front-rear cell polarity and motion orientation [20]. Thereby, the direction of motion can be transmitted from a moving cell onto another cell as it is hit by the moving cell, see Fig.…”

mentioning

confidence: 99%

“…1A. This fascinating local mechanism is known as 'guidance-by-followers' [20]. At the level of the collective, the random cell motility of polster cells gets aligned to form a compact cell cluster in contact with the following posterior axial mesoderm cells.…”

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Collective cell migration due to guidance-by-followers is robust to multiple stimuli

Mendes

Boutillon

Jahn

et al. 2023

Preprint

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Collective cell migration is an important process during biological development and tissue repair, but may turn malignant during tumor invasion. Mathematical and computational models are essential to unravel the mechanisms of self-organization that underlie the emergence of collective migration from the interactions among individual cells. Recently, guidance-by-followers was identified as one such underlying mechanism of collective cell migration in the zebrafish embryo. This poses the question how guidance stimuli are integrated when multiple cells interact simultaneously. Here, we extend a recent individual-based model by an integration step of the vectorial guidance stimuli and compare model predictions obtained for various variants of the mechanism (arithmetic mean of stimuli, dominance of stimulus with largest transmission interface, dominance of most head-on stimulus). Simulations are carried out and quantified within the modeling and simulation framework Morpheus. Collective cell migration is found to be robust and qualitatively identical for all considered variants of stimulus integration. Moreover, this study highlights the role of individual-based modeling approaches for understanding collective phenomena at the population scale that emerge from cell-cell interactions.

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A Hierarchical Mechanotransduction System: From Macro to Micro

Cao,

Tian,

Tian

et al. 2023

Advanced Science

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Mechanotransduction is a strictly regulated process whereby mechanical stimuli, including mechanical forces and properties, are sensed and translated into biochemical signals. Increasing data demonstrate that mechanotransduction is crucial for regulating macroscopic and microscopic dynamics and functionalities. However, the actions and mechanisms of mechanotransduction across multiple hierarchies, from molecules, subcellular structures, cells, tissues/organs, to the whole‐body level, have not been yet comprehensively documented. Herein, the biological roles and operational mechanisms of mechanotransduction from macro to micro are revisited, with a focus on the orchestrations across diverse hierarchies. The implications, applications, and challenges of mechanotransduction in human diseases are also summarized and discussed. Together, this knowledge from a hierarchical perspective has the potential to refresh insights into mechanotransduction regulation and disease pathogenesis and therapy, and ultimately revolutionize the prevention, diagnosis, and treatment of human diseases.

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Guidance by followers ensures long-range coordination of cell migration through α-catenin mechanoperception

Cited by 21 publications

References 98 publications

FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes

FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes

Collective cell migration due to guidance-by-followers is robust to multiple stimuli

A Hierarchical Mechanotransduction System: From Macro to Micro

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