https://doi.org/10.1140/epje/s10189-021-00150-6
Regular Article - Living Systems
Collective durotaxis of cohesive cell clusters on a stiffness gradient
1
Departament de Física de la Matèria Condensada, Universitat de Barcelona, Av. Diagonal 647, 08028, Barcelona, Spain
2
Universitat de Barcelona Institut of Complex Systems (UBICS), 08028, Barcelona, Spain
3
Princeton Center for Theoretical Science, Princeton University, 08544, Princeton, NJ, USA
4
Lewis-Sigler Institute for Integrative Genomics, Princeton University, 08544, Princeton, NJ, USA
5
Max Planck Institute for the Physics of Complex Systems, Nöthnitzerst. 38, 01187, Dresden, Germany
6
Center for Systems Biology Dresden, Pfotenhauerst. 108, 01307, Dresden, Germany
Received:
2
July
2021
Accepted:
15
November
2021
Published online:
24
January
2022
Many types of motile cells perform durotaxis, namely directed migration following gradients of substrate stiffness. Recent experiments have revealed that cell monolayers can migrate toward stiffer regions even when individual cells do not—a phenomenon known as collective durotaxis. Here, we address the spontaneous motion of finite cohesive cell monolayers on a stiffness gradient. We theoretically analyze a continuum active polar fluid model that has been tested in recent wetting assays of epithelial tissues and includes two types of active forces (cell–substrate traction and cell–cell contractility). The competition between the two active forces determines whether a cell monolayer spreads or contracts. Here, we show that this model generically predicts collective durotaxis, and that it features a variety of dynamical regimes as a result of the interplay between the spreading state and the global propagation, including sequential contraction and spreading of the monolayer as it moves toward higher stiffness. We solve the model exactly in some relevant cases, which provides both physical insights into the mechanisms of tissue durotaxis and spreading as well as a variety of predictions that could guide the design of future experiments.
© The Author(s) 2022
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