Mathematical modelling of bacterial quorum sensing and biofilm extracellular polymeric substances

• Main Author: Zhang, Chaodong
• Other Authors: Tan Soon Keat
• Format: Theses and Dissertations
• Language: English
• Published: 2017
• Subjects: DRNTU::Science::Biological sciences::Microbiology; DRNTU::Science::Biological sciences::Biomathematics
• Online Access: http://hdl.handle.net/10356/73045
• Institution: Nanyang Technological University

Biofilms are surface-attached microbial communities embedded in their self-generated extracellular polymeric substance (EPS). Biofilm formation is one of the main causes of membrane biofouling, which represents a major challenge in the application of membrane technology to water treatment. Bacterial cell-to-cell communication mechanism quorum sensing (QS) plays an important role in regulating biofilm physiology and EPS synthesis. QS architectures are well studied; however the kinetic parameters are mostly unknown and they are heterogeneous among individual cells. Quorum quenching enzymes (QQ) and QS inhibitors (QSI) can inhibit QS, but their combined effects have not been studied yet. EPS production in biofilms determines cell interactions like cooperation and aggregation. Studying the population dynamics affected by EPS production helps to better understand biofilm development. Using cellular network deterministic and stochastic models, QS response curve topology was found dependent on network parameter values. Noise caused by parameter heterogeneity is comparable with network intrinsic noise. Synergy of QQ and QSI in inhibiting QS were proved by models (and have been validated by experiments). Population dynamics of EPS over producing small colony variants (SCVs) of P.aeruginosa in biofilm with wild type PAO1 was modelled using individual based modelling methods based on two kinds of EPS, i.e., Psl and Pel. The model predicted auto-aggregative property of SCV mutant and that although SCV is more stable under shear, it cannot out compete PAO1. This thesis contributed to a better understanding of QS network, proposed more effective ways of inhibiting QS, and modelled how EPS affects the dynamics of biofilm population dynamics and physiology. The outcome of this thesis contributes to the knowledge of biofouling control.