Repository of DUTH

Computational study of metabolic networks using Flux Balance Analysis (Bachelor thesis)

Σιμογιάννης, Σωτήριος/ Simogiannis, Sotirios

In an era where biotechnology is constantly evolving and the need for independence from fossil fuels is more relevant than ever, the targeted design of modified bacterial strains that produce industrially important metabolites constitutes a primary goal of metabolic engineering and, by extension, the entire field of biotechnology. In the present study, a thorough computational analysis of the core and the genome-scale (iJO1366) metabolic networks of Escherichia coli was performed. Flux Balance Analysis (FBA) (Ebrahim et al., 2013, BMC Syst. Biol.) and its thermodynamically constrained version (TFA) (Salvy et al., 2019, Nat. Commun.) were utilized to design strains that, on one hand, grow at a viable rate and, on the other hand, produce high amounts of critical metabolites, such as succinic and lactic acid, under aerobic and anaerobic conditions. The research demonstrated that the designed strains of the core model, under anaerobic conditions, achieved strong growth-coupled production and high product yields. Conversely, the strains designed to produce these specific metabolites under aerobic conditions exhibited, on average, weaker growth-coupled production and lower product yields. In contrast, the designed strains of the iJO1366 model under anaerobic conditions presented weak growth-coupled production yet maintained high product yields. Regarding aerobic conditions, the developed strains exhibited solely potential growth-coupled production, and their product yield was lower than that of the anaerobic strains, demonstrating the critical importance of anaerobic conditions for the optimal production of succinic and lactic acid.