(151a) Deterministic and Stochastic Population Level Simulations of An Artificial Lac Operon Genetic Network

The lac operon genetic switch is considered as a paradigm of genetic regulation. This system has a positive feedback loop due to the LacY permease boosting its own production by the facilitated transport of inducer into the cell and the subsequent de-repression of the lac operon genes. We present computational studies of an artificial lac operon network that highlights this positive feedback mechanism. Our single cell model takes into account the constitutive expression of the lacI repressor gene, the expression of LacY from an IPTG inducible promoter and the free and facilitated transport of IPTG through the cell membrane. This single cell model is incorporated into two Monte Carlo simulation frameworks that describe cell population dynamics. The first framework assumes deterministic reaction dynamics and takes into account stochastic DNA duplication, division and partitioning. The second framework takes into account stochastic reaction occurrence in addition to the aforementioned sources of stochasticity. By comparing the results of these two approaches, we elucidate the effect of genetic network structure and that of stochasticity in shaping the phenotypic distributions. We further investigate whether the salient features of these distributions can be captured with simpler single-cell models.