000147805 001__ 147805
000147805 005__ 20250923084437.0
000147805 0247_ $$2doi$$a10.1016/j.compbiomed.2024.109506
000147805 0248_ $$2sideral$$a141324
000147805 037__ $$aART-2024-141324
000147805 041__ $$aeng
000147805 100__ $$aAparicio-Yuste, Raul
000147805 245__ $$aHybrid model to simulate host cell biomechanics and infection spread during intracellular infection of epithelial monolayers
000147805 260__ $$c2024
000147805 5060_ $$aAccess copy available to the general public$$fUnrestricted
000147805 5203_ $$aMechanical signals are crucial in regulating the response of cells in a monolayer to both physiological and pathological stressors, including intracellular bacterial infections. In particular, during intracellular infection of epithelial cells in monolayer with the food-borne bacterial pathogen Listeria monocytogenes, cellular biomechanics dictates the degree of bacterial dissemination across the monolayer. This occurs through a process whereby surrounder uninfected cells mechanically compete and eventually extrude infected cells. However, the plethora of physical mechanisms involved and their temporal dynamics are still not fully uncovered, which could inform whether they benefit or harm the host. To further investigate these mechanisms, we propose a two-dimensional hybrid computational model that combines an agent-based model with a finite element method to simulate the kinematics and dynamics of epithelial cell monolayers in the absence or presence of infection. The model accurately replicated the impact of cell density on the mechanical behaviour of uninfected monolayers, showing that increased cell density reduces cell motility and coordination of motion, cell fluidity and monolayer stresses. Moreover, when simulating the intercellular spread of infection, the model successfully reproduced the mechanical competition between uninfected and infected cells. Infected cells showed a reduction in cell area, while the surrounder cells migrated towards the infection site, exerting increased monolayer stresses, consistent with our in vitro observations. This model offers a powerful tool for studying epithelial monolayers in health and disease, by providing in silico predictions of cell shapes, kinematics and dynamics that can then be tested experimentally.
000147805 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/PID2021-124271OB-I00
000147805 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000147805 590__ $$a6.3$$b2024
000147805 592__ $$a1.447$$b2024
000147805 591__ $$aBIOLOGY$$b7 / 107 = 0.065$$c2024$$dQ1$$eT1
000147805 593__ $$aHealth Informatics$$c2024$$dQ1
000147805 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b4 / 67 = 0.06$$c2024$$dQ1$$eT1
000147805 593__ $$aComputer Science Applications$$c2024$$dQ1
000147805 591__ $$aENGINEERING, BIOMEDICAL$$b22 / 124 = 0.177$$c2024$$dQ1$$eT1
000147805 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b26 / 175 = 0.149$$c2024$$dQ1$$eT1
000147805 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000147805 700__ $$aHundsdorfer, Lara
000147805 700__ $$aBastounis, Effie E.
000147805 700__ $$aGomez-Benito, Maria Jose
000147805 773__ $$g185 (2024), 109506 [13 pp.]$$pComput. biol. med.$$tComputers in biology and medicine$$x0010-4825
000147805 787__ $$tThe code implemented for the hybrid model used in this study$$wgithub.com/raparicio21/monolayer_hybrid_model.git
000147805 8564_ $$s5313405$$uhttps://zaguan.unizar.es/record/147805/files/texto_completo.pdf$$yVersión publicada
000147805 8564_ $$s2598710$$uhttps://zaguan.unizar.es/record/147805/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000147805 909CO $$ooai:zaguan.unizar.es:147805$$particulos$$pdriver
000147805 951__ $$a2025-09-22-14:47:50
000147805 980__ $$aARTICLE