Modeling a bacterial ecosystem through chemotaxis simulation of a single cell

Abstract

We present in this paper an artificial life ecosystem in which bacteria are evolved to perform chemotaxis. In this system, surviving bacteria have to overcome the problems of detecting resources (or sensing the environment), modulating their motion to generate a foraging behavior, and communicating with their kin to produce more sophisticated behaviors. A cell's chemotactic pathway is modulated by a hybrid approach that uses an algebraic model for the receptor clusters activity, an ordinary differential equation for the adaptation dynamics, and a metabolic model that converts nutrients into biomass. The results show some analysis of the motion obtained from some bacteria and their effects on the evolved population behavior. The evolutionary process improves the bacteria's ability to react to their environment, enhancing their growth and allowing them to better survive. As future work, we propose to investigate the effect of emergent bacterial communication as new species arise, and to explore the dynamics of colonies.