Dynamics of the quorum sensing switch: stochastic and non-stationary effects

Abstract

Background: A wide range of bacteria species are known to communicate through the so called quorum sensing (QS) mechanism by means of which they produce a small molecule that can freely diffuse in the environment and in the cells. Upon reaching a threshold concentration, the signalling molecule activates the QS-controlled genes that promote phenotypic changes. This mechanism, for its simplicity, has become the model system for studying the emergence of a global response in prokaryotic cells. Yet, how cells precisely measure the signal concentration and act coordinately, despite the presence of fluctuations that unavoidably affects cell regulation and signalling, remains unclear. Results: We propose a model for the QS signalling mechanism in Vibrio fischeri based on the synthetic strains lux01 and lux02. Our approach takes into account the key regulatory interactions between LuxR and LuxI, the autoinducer transport, the cellular growth and the division dynamics. By using both deterministic and stochastic models, we analyze the response and dynamics at the single-cell level and compare them to the global response at the population level. Our results show how fluctuations interfere with the synchronization of the cell activation and lead to a bimodal phenotypic distribution. In this context, we introduce the concept of precision in order to characterize the reliability of the QS communication process in the colony. We show that increasing the noise in the expression of LuxR helps cells to get activated at lower autoinducer concentrations but, at the same time, slows down the global response. The precision of the QS switch under non-stationary conditions decreases with noise, while at steady-state it is independent of the noise value. Conclusions:Our in silico experiments show that the response of the LuxR/LuxI system depends on the interplay between non-stationary and stochastic effects and that the burst size of the transcription/translation noise at the level of LuxR controls the phenotypic variability of the population. These results, together with recent experimental evidences on LuxR regulation in wild-type species, suggest that bacteria have evolved mechanisms to regulate the intensity of those fluctuations.

Mathematical Modelling of Bacterial Quorum Sensing: A Review

“…They argued that such core principles do exist, which is why mathematical modelling remains a powerful tool for understanding the regulation of QS. Employing mathematical tools to study QS has given rise to a wide range of mathematical models: while the autoinducer production and its binding to the regulator protein may be explained deterministically (Dockery and Keener 2001;Nilsson et al 2001), binding of the autoinducer/regulator protein to a promoter region of DNA is often examined stochastically (Goryachev et al 2005;Müller et al 2008;Weber and Buceta 2013). Models involving the spatial effects of the environment, e.g.…”

The cellular Ising model: a framework for phase transitions in multicellular environments

“…The latter can be experimentally achieved by different means such as modifying the affinity of the ribosome binding sites and/or modulating the so-called bursting size [29]. In fact, an intriguing question is how cells can robustly coordinate in a population in the presence of noise [30][31][32].…”

Role of quorum-sensing molecules in infections caused by Gram-negative bacteria and host cell response

“…Two proteins named LuxI and LuxR have been proved to be essential in quorum-sensing activity and control of bioluminescence in V. fischeri. This LuxI/LuxR regulatory system controls gene expression by quorum sensing in many Gram-negative bacteria [7]. There are also various types of homologous regulatory system in different bacterial species that have been shown to work as quorum-sensing systems controlling global cell density-dependent gene expression [2].…”