A novel cellular automaton approach for modeling genotypic and phenotypic heterogeneity in cell systems

Abstract Cellular automaton models have long been used to study cellular processes, but may be challenging for incorporating synchronization, migratory, and high-density effects. In this work, we introduce an extension of the classic lattice-gas cellular automata, a framework which allows to consider changes in cell numbers, cell–cell interactions, migration, and evolution of genotypic and phenotypic heterogeneity. To demonstrate the utility of our approach, we consider a growing population of cells whose genotype—passed on at birth from the mother cell and subject to stochastic mutations—determines their individual proliferation rates. Using spatial simulations, we show that the model exhibits traveling-wave invasion patterns, where the fastest-growing cells accumulate at the leading edge, accelerating population expansion. We predict this behavior using a mathematical analysis based on a mean-field assumption.