A Stochastic Biofilm Disruption Model based on Quorum Sensing Mimickers

Quorum sensing (QS) mimickers can be used as an effective tool to disrupt biofilms which consist of communicating bacteria and extracellular polymeric substances. In this paper, a stochastic biofilm disruption model based on the usage of QS mimickers is proposed. A chemical reaction network (CRN) involving four different states is employed to model the biological processes during the biofilm formation and its disruption via QS mimickers. In addition, a state-based stochastic simulation algorithm is proposed to simulate this CRN. The proposed model is validated by the in vitro experimental results of Pseudomonas aeruginosa biofilm and its disruption by rosmarinic acid as the QS mimicker. Our results show that there is an uncertainty in state transitions due to the effect of the randomness in the CRN. The presented work shows how the biofilm growth and its disruption can be modeled realistically via the premature QS activation among bacteria.