Investigating autocatalytic gene expression systems through mechanistic modeling

A structured model of gene expression, which incorporates the stochastic be havior of cellular processes, was developed to examine the "all-or-none" ph enomenon observed in autocatalytic systems (e.g. the lac operon). Autocatal ytic expression systems typically have the genes encoding the inducer trans port proteins controlled by internal inducer levels, so that transport of t he inducer increases production of the transport protein. The model was abl e to predict the unique behaviors of autocatalytic expression systems that have been experimentally observed and provided valuable insight into the ro le of population heterogeneity in these systems. The simulations substantia te the importance of stochastic processes on induction of gene expression i n autocatalytic systems. The simulation results show that the all-or-none p henomenon is governed largely by random cellular events, and that populatio n-averaged variations in gene expression are due to changes in the frequenc y of full gene induction in individual cells rather than to uniform variati ons in gene expression across the entire population In addition, the model shows how concentrations of inducer too low to induce expression in uninduc ed cells can maintain induction in pre-induced cultures. A comparison of in duction behaviors from an autocatalytic system and a system having constitu tive synthesis of the transport protein showed that transport protein level s must be decoupled from inducer control to achieve homogeneous expression of a gene of interest in all cells of a culture. (C) 1999 Academic Press.