Modelling and simulation of lac-operon gene expression using heterogeneous parallel platforms

Proper functioning of any cell depends on gene regulation. Lac operon plays a major role in regulating the cell metabolism in bacterial genes. The lac genetic switch exhibits significant stochasticity. In this study, two-state model of lac-operon is considered and a mathematical model is constructed in terms of gene regulation using the Next Reaction Method. The results show that the Next Reaction Method performs much better in simulation accuracy than other methods like first reaction method, and direct method. The software operates in Python environment with other dependencies and uses the Next Reaction Method algorithm to solve stochastic equations. GPU computing was utilized to speed up the simulation performance. The number of mRNA and protein groups of consecutive packets is formed as a function of time which corresponds to when a gene is ‘on’ (no repressor is bound). The mRNA and protein data were recorded for all the simulations over a period of time and most of the simulations took six minutes to complete using a heterogeneous platform. Finally, this model includes the processes of transcription of mRNA and protein for which majority of high-throughput data is accessible.