Kinetics & Diffusion Model
Background
Given the inherent complexities associated with our non-linear chemical pathways to produce rosmarinic acid, achieving an optimal balance among the various constituents of the pathway posed a formidable challenge (Figure 1) [1]. To address this challenge, Li et al. explored a strategy involving the partitioning of pathway components into distinct subpopulations within a co-culture of E. coli [1], endeavoring to optimize rosmarinic acid production by modulating the subpopulation ratios of cells.
Building upon the foundation of their chemical pathway, we adapted a similar biosynthetic framework, albeit with a key deviation: we entrusted yeast cells S. cerevisiae with the synthesis of larger molecules, a task for which yeast cells have demonstrated superior efficiency compared to E. coli [2]. Our enzyme kinetics model aimed to simulate rosmarinic acid production by systematically varying enzyme concentrations, thereby identifying the optimal yeast-to-bacteria ratio for this production. Similar to our project goal, Shanthy Sundaram et al. used computational modeling and optimization to investigate the biosynthesis of Rosmarinic acid, employing Genetic Algorithm methodology [3]. While they utilized Gepasi Software with built-in reaction kinetics for simulation, we developed our own model based on information gathered from the literature.