title: Simple models for quorum sensing: nonlinear dynamical analysis.
abstract: Quorum sensing refers to the change in the cooperative behavior of a collection of elements in response to the change in their population size or density. This behavior can be observed in chemical and biological systems. These elements or cells are coupled via chemicals in the surrounding environment. Here we focus on the change of dynamical behavior, in particular from quiescent to oscillatory, as the cell population changes. For instance, the silent behavior of the elements can become oscillatory as the system concentration or population increases. In this work, two simple models are constructed that can produce the essential representative properties in quorum sensing. The first is an excitable or oscillatory phase model, which is probably the simplest model one can construct to describe quorum sensing. Using the mean-field approximation, the parameter regime for quorum sensing behavior can be identified, and analytical results for the detailed dynamical properties, including the phase diagrams, are obtained and verified numerically. The second model consists of FitzHugh-Nagumo elements coupled to the signaling chemicals in the environment. Nonlinear dynamical analysis of this mean-field model exhibits rich dynamical behaviors, such as infinite period bifurcation, supercritical Hopf, fold bifurcation, and subcritical Hopf bifurcations as the population parameter changes for different coupling strengths. Analytical result is obtained for the Hopf bifurcation phase boundary. Furthermore, two elements coupled via the environment and their synchronization behavior for these two models are also investigated. For both models, it is found that the onset of oscillations is accompanied by the synchronized dynamics of the two elements. Possible applications and extension of these models are also discussed.
authors.affiliation: Department of Physics, Graduate Institute of Biophysics and Center for Complex Systems, National Central University, Chungli, Taiwan 320, Republic of China.
authors.forename: Wei-Yin
authors.initials: WY
authors.lastname: Chiang
authors.forename: Yue-Xian
authors.initials: YX
authors.lastname: Li
authors.forename: Pik-Yin
authors.initials: PY
authors.lastname: Lai
mesh_terms: D003198:Computer Simulation; D008954:Models, Biological; D017711:Nonlinear Dynamics; D053038:Quorum Sensing / Q000502:physiology*