Quorum Sensing Model Structures Inspire the Design of Quorum Quenching Strategies

Abstract

Quorum Sensing (QS) is a bacterial cell-to-cell communication mechanism allowing to share information about cell density, to adjust gene expression accordingly. Pathogens leverage QS to coordinate virulence and antimicrobial resistance, leading to distinctive population-level behaviors. To support rational design of synthetic biology strategies counteracting these mechanisms, we first mathematically model and compare two common QS architectures: one based on a single positive feedback loop to auto-induce signal molecule synthesis, the other including an additional positive feedback to increase signal molecule receptors production. Our comprehensive analysis of these QS structures and their equilibria highlights the differences in their bistable and hysteretic behaviors. An extensive sensitivity analysis is then performed, highlighting how parameter variations may lead to phenotype alterations in system behavior. Finally, building on our sensitivity analysis, we mathematically model four distinct QS inhibition strategies - signal molecule degradation, pharmaceutical inhibition, CRISPRi, and RNAi - which lead to the design of Quorum-Quenching (QQ) therapeutic approaches. Despite the underlying complex mechanisms, we demonstrate that the effect of the proposed QQ strategies can be captured by varying specific parameters within the QS models. We numerically analyze how these strategies affect the steady-state behavior of both QS models, identifying critical parameter thresholds for effective QS suppression.