2006 AIChE Annual Meeting
(627f) Deterministic and Stochastic Modeling of Genetic Networks with Positive Feedback Architecture
In this work, we present a detailed stochastic model describing the dynamics of the IPTG-inducible lac operon network. The model describes the constitutive expression of lacI repressor, the dynamics of lacY transcription and translation, the induced and facilitated transport of IPTG, and the degradation of the metabolizable species. Furthermore, we rigorously derive the equivalent deterministic model and by comparing its predictions with those of the stochastic model, we isolate the effects of intrinsic noise on system behavior. Moreover, we demonstrate how the asymptotic behavior and the phenotypic heterogeneity are affected by changes in several biomolecular parameters, such as promoter strength, binding affinities and plasmid copy numbers. Our results are expected to hold not only for the lac operon system, but for other systems with positive feedback architecture as well.