Computational framework based on individual agents to model cell aggregation and collective dynamics

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dc.catalogadorvdr
dc.contributor.advisorRavasio, Andrea
dc.contributor.authorMontenegro Rojas, Ignacio Tomás
dc.contributor.otherPontificia Universidad Católica de Chile. Escuela de Ingeniería
dc.date.accessioned2024-09-04T14:45:20Z
dc.date.available2024-09-04T14:45:20Z
dc.date.issued2024
dc.description.abstractThe study of biological systems has given way to the emergence of novel approaches to understanding the intrinsic complexity of life. In this aspect, mechanobiology has emerged as an interesting and modern new branch of the cellular sciences, using physical and engineering approaches to reverse engineer complex systems from their most basic components. Mathematical and computational models provide a powerful tool for investigating functional components and minimal requirements of biological systems. In this thesis, I present a mathematical theory and a computational model capable of describing the complex behavior of multicellular systems and, particularly, the transition from single cell to collective tissue dynamics. While this is relevant to understand, e.g., epithelial tissue dynamics, wound healing, and cancer progression, here I leverage the robustness and relative simplicity of early killifish development to investigate the minimal requirements for cell aggregation. Briefly, the killifish exhibits a unique developmental pattern where single cells aggregate into a multicellular cluster to initiate gastrulation, making it an ideal animal model for studying aggregation in vivo. Based on observation of the in vivo system, the minimal interactions presented in the system are defined, and mathematical definitions for each one are proposed. Thereafter, a fully integrated mathematical model for multicellular migration and aggregation accounting for cell motion, cellular interactions with the environment, Contact Inhibition of Locomotion (CIL), and specific 3D geometries of the embryonic environment is implemented, in absence or presence of environmental cues providing directionality to the cellular motion (taxis). The CellModeller software was used to solve partial differential equations and as a graphical output simulating cellular dynamics. The results from this model are later analyzed and interpreted. Finally, these results, which have been published in Frontiers in Cell and Developmental Biology are discussed, along with future work and potential applications for these types of in silico studies of complex multicellular systems.
dc.description.funderANID/FONDECYT Folio de beca: ACT192015
dc.fechaingreso.objetodigital2024-09-04
dc.format.extentix, 70 páginas
dc.fuente.origenSRIA
dc.identifier.doi10.7764/tesisUC/ING/87782
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/87782
dc.identifier.urihttps://doi.org/10.7764/tesisUC/ING/87782
dc.information.autorucInstituto de Ingeniería Biológica y Médica; Ravasio, Andrea; 000-0001-7835 5133; 1071356
dc.information.autorucEscuela de Ingeniería; Montenegro Rojas, Ignacio Tomás; S/I; 1045303
dc.language.isoen
dc.nota.accesocontenido completo
dc.rightsacceso abierto
dc.subjectMechanobiology
dc.subjectMathematical and computational modelling
dc.subjectCell migration
dc.subjectEmbryonic development
dc.subject.ddc620
dc.subject.deweyIngenieríaes_ES
dc.subject.ods09 Industry, innovation and infrastructure
dc.subject.odspa09 Industria, innovación e infraestructura
dc.titleComputational framework based on individual agents to model cell aggregation and collective dynamics
dc.typetesis de maestría
sipa.codpersvinculados1071356
sipa.codpersvinculados1045303
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3.01 Tesis magíster