A CELLULAR-AUTOMATON MODEL FOR THE PROLIFERATION OF MIGRATING CONTACT-INHIBITED CELLS

A cellular automaton is used to develop a model describing the prolife ration dynamics of populations of migrating, contact-inhibited cells. Simulations are carried out on two-dimensional networks of computation al sites that are finite-state automata. The discrete model incorporat es all the essential features of the cell locomotion and division proc esses, including the complicated dynamic phenomena occurring when cell s collide. In addition, model parameters can be evaluated by using dat a from long-term tracking and analysis of cell locomotion. Simulation results are analyzed to determine how the competing processes of conta ct inhibition and cell migration affect the proliferation rates. The r elation between cell density and contact inhibition is probed by follo wing the temporal evolution of the population-average speed of locomot ion. Our results show that the seeding cell density, the population-av erage speed of locomotion, and the spatial distribution of the seed ce lls are crucial parameters in determining the temporal evolution of ce ll proliferation rates. The model successfully predicts the effect of cell motility on the growth of isolated megacolonies of keratinocytes, and simulation results agree very well with experimental data. Model predictions also agree well with experimentally measured proliferation rates of bovine pulmonary artery endothelial cells (BPAE) cultured in the presence of a growth factor (bFGF) that up-regulates cell motilit y.