Resumen de Stochastic Effects in Quorum Sensing
Marc Weber
Stochastic fluctuations, or noise, are ubiquitous in biological systems and play an important role in many cellular processes. Experimental evidences have shown that noise affects the reliability of cell coordination in populations of communicating cells. In this thesis, we study the effects of stochasticity in the emergence of collective behavior in populations of bacteria communicating by QS. We focus on the genetic switch as a paradigm of cellular decision making in both natural and synthetic bacterial systems. Our approach is based on mathematical modeling and stochastic simulations, both at the level of the single cell and at the level of the cell population. We focus on four main topics. In the first topic, we analyze the interplay between intracellular noise and the diffusion process of the QS signaling mechanism. We build a model describing the expression of the signaling molecule and its diffusion in a population of cells, focusing on the situation of very low constitutive expression rate. We show that varying the diffusion rate produces a repertoire of dynamics for the signaling molecule. Our results reveal the contribution of intrinsic noise and transcriptional noise (mRNA copy number fluctuations) in the fluctuations of the signaling molecule. We observe that the total noise exhibits a maximum as a function of the diffusion rate, in contrast to previous studies. Thus, the QS communication mechanism modifies the fluctuations of the signaling molecule inside the cell and interacts with the gene expression noise. In the second topic, we study the effects of gene expression noise on the precision of the population coordination in the QS activation of the LuxR/LuxI system. We analyze the response and dynamics of a population of cells to different levels of autoinducer. Our results show that gene expression noise in LuxR is the main factor that controls the transient variability of the QS activation. This study sheds light on the relation between the single cell stochastic dynamics and the collective behavior in a population of communicating cells. In the third topic, we analyze the effects of intrinsic noise in an autoactivating switch in an isolated single cell. We show that noise promotes the stability of the low-state phenotype of the switch and that the bistable region is extended when increasing the intensity of the fluctuations, an effect that we call stochastic stabilization. Our results show that intrinsic noise modifies the epigenetic landscape as well as the switching rate, which results in complex behavior of the stochastic switching dynamics when varying the intensity of noise. Thus, at the level of a single cell, intrinsic noise contributes to the cell-to-cell variability of the genetic switch and can modify its stable states and its dynamics. In the fourth topic, we build a model of a population of toggle switches communicating by the exchange of two diffusible QS signals. We show that increasing the diffusion rate, which increases the coupling strength between the cells, leads to a phase transition from an unordered phase where the cells randomly flip between the two states of the switch, to an ordered phase with all the cells locked into the same stable state. The same transition is found in a population of cells growing exponentially in a closed volume. Moreover, the response of the cells to a varying external signal exhibits a hysteresis loop. We show that the cell-cell coupling enhances the sensitivity of the population response to the external signal and suggest that this new mechanism could be used to increase the robustness and sensitivity of biosensors. Our results suggest a new mechanism for collective cell decision making based on the phenomenon of phase transition.
