Stochastic modeling of inducible logical gates in Escherichia coli

Abstract

In this work, a systematic approach to the modeling of synthetic biological systems, with a focus on gene regulatory networks, is presented. We extend a previous study of a logical AND gate system by observing the effect of individual components of this system on its functionality using experimental techniques and computational models. The previous AND gate was synthesized using operator sequences from the well characterized prokaryotic Tetracycline and Lactose operons. This synthetic construct is responsive to the exogenous chemical inducers IPTG and aTc and produces green fluorescent protein (GFP) as an output signal. Experimentally, we broke down the AND gate promoter into its individual components by replacing the tet and/or lac operator sites by a non-binding E. coli DNA sequence. The individual components of the promoter were then characterized by studying the output GFP signal when varying inducer concentrations were added to the system. In addition, we have characterized systems with mutant tet operator sites to further study the regulatory circuit. Along with experimentally characterizing these systems, we have modeled the systems in detail. The models are stochastic in nature and include all the biomolecular interactions involved in transcription, translation, regulation and induction in order to quantify the influence of each individual interaction on the behavior of the system. Thus, we can quantitatively analyze the behavior of the systems, and better understand why the systems behave as they do. This approach of designing and tailoring logical regulation of gene expression can be potentially extended beyond transcriptional regulation to include other modular genetic elements, search for more complex network behaviors and assist in forward engineering of other biological circuits.