  Bacteria generally live in complicated structures called biofilms, consisting
of communicating bacterial colonies and extracellular polymeric substance
(EPS). Since biofilms are related to detrimental effects such as infection or
antibiotic resistance in different settings, it is essential to model their
formation. In this paper, a stochastic model is proposed for biofilm formation,
using bacterial quorum sensing (QS). In this model, the biological processes in
the biofilm formation are modeled as a chemical reaction network which includes
bacterial reproduction, productions of autoinducer and EPS, and their
diffusion. The modified explicit tau-leap simulation algorithm is adapted based
on the two-state QS mechanism. Our approach is validated by using the
experimental results of $\textit{Pseudomonas putida}$ IsoF bacteria for
autoinducer and bacteria concentration. It is also shown that the percentage of
EPS in the biofilm increases significantly after the state change in QS, while
it decreases before QS is activated. The presented work shows how the biofilm
growth can be modeled realistically by using the QS mechanism in stochastic
simulations of chemical reactions.
