Modeling cell adhesion and proliferation: a cellular-automata based approach

• Published in: Advanced modeling and simulation in engineering sciences 2015-12, Vol.2 (1), p.32-32, Article 32
• Main Authors: Vivas, J., Garzón-Alvarado, D., Cerrolaza, M.
• Format: Article
• Language: English
• Subjects: Classical and Continuum Physics; Computational mechanics and medicine; Computational Science and Engineering; Engineering; Engineering Sciences; Research Article; Theoretical and Applied Mechanics
• ISSN: 2213-7467; 2213-7467
• DOI: 10.1186/s40323-015-0053-5

Background: Cell adhesion is a process that involves the interaction between the cell membrane and another surface, either a cell or a substrate. Unlike experimental tests, computer models can simulate processes and study the result of experiments in a shorter time and lower costs. One of the tools used to simulate biological processes is the cellular automata, which is a dynamic system that is discrete both in space and time. Method: This work describes a computer model based on cellular automata for the adhesion process and cell proliferation to predict the behavior of a cell population in suspension and adhered to a substrate. The values of the simulated system were obtained through experimental tests on fibroblast monolayer cultures. Results: The results allow us to estimate the cells settling time in culture as well as the adhesion and proliferation time. The change in the cells morphology as the adhesion over the contact surface progress was also observed. The formation of the initial link between cell and the substrate of the adhesion was observed after 100 min where the cell on the substrate retains its spherical morphology during the simulation. The cellular automata model developed is, however, a simplified representation of the steps in the adhesion process and the subsequent proliferation. Conclusion: A combined framework of experimental and computational simulation based on cellular automata was proposed to represent the fibroblast adhesion on substrates and changes in a macro-scale observed in the cell during the adhesion process. The approach showed to be simple and efficient.