Multiple Local and Global Bifurcations and Their Role in Quorum Sensing Dynamics

TL;DR

This paper presents a mathematical model revealing chaotic and oscillatory dynamics in quorum sensing networks, emphasizing complex bifurcations like homoclinic Shilnikov bifurcations that challenge predictability.

Contribution

It introduces a novel mathematical model that uncovers complex bifurcations and chaotic behavior in quorum sensing, advancing understanding of bacterial communication dynamics.

Findings

Chaotic dynamics found in quorum sensing models

Oscillatory behavior observed in autoinducer interactions

Homoclinic Shilnikov bifurcations explain complex dynamics

Abstract

Quorum sensing governs bacterial communication, playing a crucial role in regulating population behaviour. We propose a mathematical model that uncovers chaotic dynamics within quorum sensing networks, highlighting challenges to predictability. The model explores interactions between autoinducers and two bacterial subtypes, revealing oscillatory dynamics in both a constant autoinducer sub-model and the full three-component model. In the latter case, we find that the complicated dynamics can be explained by the presence of homoclinic Shilnikov bifurcations. We employed a combination of normal form analysis and numerical continuation methods to analyse the system.