Regulating gene expression using optimal control theory

Abstract

We described development of a novel genome-based model-driven strategy useful for regulating eukaryotic gene expression. In order to extract biologically meaningful information from a large volume of mRNA expression data, we built previously a PROmoter-Based Estimation (PROBE) model. The PROBE model allowed us to establish a quantitative relationship between transcription-factor binding motifs in regulatory DNA sequences and mRNA expression levels. Here, we extended PROBE formulation to derive an optimal control law for gene regulation. The responses to shear stress in human synovial cells were chosen as a model biological system, and the system dynamics was identified from the expression pattern of the genes involved in degradation and maintenance of extracellular matrix. In order to suppress the responses to mechanical stimuli, a Ricatti equation was solved and an admissible control law was derived. The approach presented here can be implemented in any biological process, and it would be useful to develop a transcription-mediated strategy for gene therapies and tissue engineering.