Modeling Gene Circuit Expression Dynamics in Cell and Cell-Free Systems

A detailed understanding of underlying gene circuit expression dynamics forms the basis towards achieving optimized system performances. Despite a growing wealth of experimental tools, it remains challenging to measure the reaction kinetics underlie the system of interest. Computational modelling provides an invaluable alternative to complement the experiment in a more time and cost-effective quantitative manner. These mathematical approaches, spanning from phenomenological to biophysical, discrete to continuous, stochastic to deterministic, decipher the principles govern the underlying functions and dynamics of various system components. As a case in point, in recent years, the advances in optogenetic systems enable one to control cells with unprecedented spatiotemporal precision that could be intractable using conventional chemical-triggered regulators. We have recently developed a blue light and chemical-controllable promoter system which allows rapid and reversible control of chemically inducible promoters, resolving the difficulty of achieving reversible control suffered by traditional chemical inducible systems. To fully harness the mechanistic properties of these hybrid systems, we employed an in silico kinetic modeling approach in an attempt to bridge the gap between the genotype and the observed dynamics of the two dual-input promoter systems. Our biophysically-based kinetic model accounts for the essential reactions involved in the functioning system. Indeed, the model was able to recapitulate experimental data and capture some key features, including concentration-dependent delay responses for inducible expression and blue light repression, and delay observed in temporal control behaviors. It was also inferred from the model that the affinity of blue light repression is inducer concentration-dependent, in which high inducer concentration could reduce the repression affinity. To improve the system performance, further model analyses were conducted. In parallel, we also applied the deterministic mathematical modelling approach in conjunction with experimental characterization to study an engineered one component-based blue light inducible promoter in the cell-free environment. As a proof of concept, our model was able to describe the system behaviors quantitatively and predict a blue light ON-OFF illumination pattern which allows us to generate an oscillatory waveform. These tandem experiment/modelling approaches expedite the iterative ‘design-build-test’ cycles, advancing our ability towards rapid prototyping of complex biological systems.