Abstract
Managing cellular resources, especially transcription and translation machinery, constitutes a significant constraint in the effective synthesis of useful bio-compounds from synthetic gene circuits. Although light-based optogenetic control approaches provide precise temporal and spatial control that can balance growth and production. The increased complexity adds on to the competition for cellular resources such as ribosomes and RNA polymerases. The optimization of regulatory elements in bioengineering is a vital task, as the selection of promoters and ribosome binding sites (RBS) directly affects transcriptional initiation rates and translation efficiency, hence influencing resource allocation. The vast number of potential parameter combinations requires systematic approaches to narrow the design space and determine which bioparts most significantly influence system performance. Furthermore, it is crucial to ascertain the uncertainty regarding which bioparts exert the most significant influence on the performance of engineered gene expression. In this study, we conduct an exploratory analysis by combining two established global gene expression models with two optogenetic TCS regulation models within a 2×2 framework. The first resource model (McBride & Del Vecchio, 2021) illustrates resource competition via coupled transcription-translation dynamics, but the second model (Santos-Navarro, 2021) identifies translation as the primary resource-limiting factor. We illustrate the utility of Sobol Global Sensitivity Analysis (GSA) to evaluate which model parameters (bioparts) influence target gene expression in the CcaS/CcaR optogenetic system regulating GFP expression. The findings indicate that the formulation of resource competition, rather than regulatory complexity, fundamentally dictates the rankings of parameter sensitivity. The sensitivity ranking explicitly indicates which design parameters require tight control and which may be relaxed, resulting in a significant reduction in design space.