Modeling a bacterial ecosystem through chemotaxis simulation of a single cell

Abstract

We present in this paper an artficial life ecosystem in which the genes in the genome encode chemotaxis of bacteria that aim at: detecting resources (or sensing the environment), controlling the bacteria motion and producing a foraging behavior, and allowing bacteria to communicate together to obtain more sophisticated behaviors. The chemotaxis network of a cell is modulated by a hybrid approach that uses an algebraic model for the receptor clusters activity and an ordinary differential equation for the adaptation dynamics, and a metabolism model that is based on the transformation of matter from 'food'. The results show analysis of the motion obtained by some bacteria and their effects on the population behaviors generated by evolution. This evolution allows bacteria to have the ability to adapt themselves to better growth in the environment and to survive. As future work, we aim to improve the effect of the communication between bacteria to obtain bacteria that can emerge as new species,and to integrate the concept of colonies.