Issue |
ESAIM: ProcS
Volume 67, 2020
CEMRACS 2018 - Numerical and mathematical modeling for biological and medical applications: deterministic, probabilistic and statistical descriptions
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Page(s) | 191 - 209 | |
DOI | https://doi.org/10.1051/proc/202067012 | |
Published online | 09 June 2020 |
Cell migration in complex environments: chemotaxis and topographical obstacles
1 MAP5, Université Paris Descartes, Paris, France
e-mail: alessandro.cucchi@parisdescartes.fr
2 INRIA, Institut de Mathématiques de Bordeaux, Bordeaux, France
e-mail: christele.etchegaray@inria.fr
3 MAP5, Université Paris Descartes, Paris, & LaMME, Université Évry-Val d’Essonne, France
e-mail: nicolas.meunier@univ-evry.fr
4 Institut de Recherche Mathématique Avancée, Université de Strasbourg, Strasbourg, France
e-mail: laurent.navoret@math.unistra.fr
5 Institut Montpelliérain Alexander Grothendieck, CNRS, Université de Montpellier, Montpellier, France
e-mail: lamissabbagh1992@gmail.com
Cell migration is a complex phenomenon that plays an important role in many biological processes. Our aim here is to build and study models of reduced complexity to describe some aspects of cell motility in tissues. Precisely, we study the impact of some biochemical and mechanical cues on the cell dynamics in a 2D framework. For that purpose, we model the cell as an active particle with a velocity solution to a particular Stochastic Differential Equation that describes the intracellular dynamics as well as the presence of some biochemical cues. In the 1D case, an asymptotic analysis puts to light a transition between migration dominated by the cell’s internal activity and migration dominated by an external signal. In a second step, we use the contact algorithm introduced in [15,18] to describe the cell dynamics in an environment with obstacles. In the 2D case, we study how a cell submitted to a constant directional force that mimics the action of chemoattractant, behaves in the presence of obstacles. We numerically observe the existence of a velocity value that the cell can not exceed even if the directional force intensity increases. We find that this threshold value depends on the number of obstacles. Our result confirms a result that was already observed in a discrete framework in [3,4].
© EDP Sciences, SMAI 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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