000078073 001__ 78073 000078073 005__ 20230421130006.0 000078073 0247_ $$2doi$$a10.1007/s10237-018-1010-2 000078073 0248_ $$2sideral$$a105791 000078073 037__ $$aART-2018-105791 000078073 041__ $$aeng 000078073 100__ $$0(orcid)0000-0001-8928-350X$$aEscribano, J.$$uUniversidad de Zaragoza 000078073 245__ $$aA hybrid computational model for collective cell durotaxis 000078073 260__ $$c2018 000078073 5060_ $$aAccess copy available to the general public$$fUnrestricted 000078073 5203_ $$aCollective cell migration is regulated by a complex set of mechanical interactions and cellular mechanisms. Collective migration emerges from mechanisms occurring at single cell level, involving processes like contraction, polymerization and depolymerization, of cell–cell interactions and of cell–substrate adhesion. Here, we present a computational framework which simulates the dynamics of this emergent behavior conditioned by substrates with stiffness gradients. The computational model reproduces the cell’s ability to move toward the stiffer part of the substrate, process known as durotaxis. It combines the continuous formulation of truss elements and a particle-based approach to simulate the dynamics of cell–matrix adhesions and cell–cell interactions. Using this hybrid approach, researchers can quickly create a quantitative model to understand the regulatory role of different mechanical conditions on the dynamics of collective cell migration. Our model shows that durotaxis occurs due to the ability of cells to deform the substrate more in the part of lower stiffness than in the stiffer part. This effect explains why cell collective movement is more effective than single cell movement in stiffness gradient conditions. In addition, we numerically evaluate how gradient stiffness properties, cell monolayer size and force transmission between cells and extracellular matrix are crucial in regulating durotaxis. 000078073 536__ $$9info:eu-repo/grantAgreement/EUR/SEP/210342844$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2015-64221-C2-1-R$$9info:eu-repo/grantAgreement/ES/MINECO/BFU2016-79916-P$$9info:eu-repo/grantAgreement/ES/MINECO/BFU2015-65074-P$$9info:eu-repo/grantAgreement/ES/MINECO/BFU2014-52586-REDT$$9info:eu-repo/grantAgreement/ES/MINECO/BES-2013-063684-FPI$$9info:eu-repo/grantAgreement/EC/FP7/616480/EU/Multiscale regulation of epithelial tension/TensionControl$$9info:eu-repo/grantAgreement/EC/FP7/306571/EU/Predictive modelling and simulation in mechano-chemo-biology: a computer multi-approach/INSILICO-CELL 000078073 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000078073 590__ $$a2.829$$b2018 000078073 591__ $$aENGINEERING, BIOMEDICAL$$b28 / 80 = 0.35$$c2018$$dQ2$$eT2 000078073 591__ $$aBIOPHYSICS$$b26 / 72 = 0.361$$c2018$$dQ2$$eT2 000078073 592__ $$a1.001$$b2018 000078073 593__ $$aBiotechnology$$c2018$$dQ1 000078073 593__ $$aModeling and Simulation$$c2018$$dQ1 000078073 593__ $$aMechanical Engineering$$c2018$$dQ1 000078073 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000078073 700__ $$aSunyer, R. 000078073 700__ $$0(orcid)0000-0002-3514-6443$$aSánchez, M.T. 000078073 700__ $$aTrepat, X. 000078073 700__ $$aRoca-Cusachs, P. 000078073 700__ $$0(orcid)0000-0002-9864-7683$$aGarcía-Aznar, J.M.$$uUniversidad de Zaragoza 000078073 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est. 000078073 773__ $$g17, 4 (2018), 1037-1052$$pBiomech. model. mechanobiol.$$tBIOMECHANICS AND MODELING IN MECHANOBIOLOGY$$x1617-7959 000078073 8564_ $$s2820578$$uhttps://zaguan.unizar.es/record/78073/files/texto_completo.pdf$$yPostprint 000078073 8564_ $$s10034$$uhttps://zaguan.unizar.es/record/78073/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000078073 909CO $$ooai:zaguan.unizar.es:78073$$particulos$$pdriver 000078073 951__ $$a2023-04-21-12:39:36 000078073 980__ $$aARTICLE