BACKGROUND: Succinic acid production has been studied from a metabolic engineering or a downstream processing perspective, separately. The concentration of succinic acid and other by-products obtained after the strain design influences the production cost during the recovery and purification stage. A metabolic engineering-downstream coupling evaluation is important when selecting the metabolic targets for the strain design. In this in silico study, the metabolic engineering of an Escherichia coli strain to produce succinic acid using glycerol as a carbon source in the downstream process was evaluated in terms of operational cost and energy consumption. (0.3068, 0.0576, 0.1089 h -1 ) and succinate productivity (2.7534, 6.0772, 5.5661 mmol g -1 DW h -1 ), respectively. The results showed that the succinic acid productivity constituted a central parameter when selecting the appropriate gene targets for deletion, despite the presence of organic acids in the downstream process and the biomass growth rate.
RESULTS: Three strain scenarios were selected using a bi-level linear optimization problem solved by Mixed Integer Linear Programing, and simulated in a transient fashion with dynamic flux balance analysis considering both biomass growth rate
CONCLUSION: A metabolism-downstream coupled model shows that the bioproduct productivity and fermentation timeare key points when considering the operational cost and energy consumption involved in the engineering of strains for industrial-scale production.Metabolic engineering targets were obtained using OptKnock, which is a bi-level linear optimization problem solved by MILP. 33