Determination of minimal target indices for cyanobacteria-based biorefineries and optimal design of the metabolic network

Abstract

In this work, we propose a mixed-integer nonlinear multiobjective optimization framework for the determination of minimal target indices for the sustainable design of an integrated cyanobacteria-based biorefinery and its heat exchanger network (HEN). The potential production of phycocyanin and zeaxanthin, poly (3-hydroxybutyrate) (PHB), fourth-generation bioethanol, biogas, hydrogen and diethyl ether is analyzed. The main objective is to determine the minimal target indices (productivity, yield, titer) for Synechocystis sp. that must be reached to achieve a sustainable biorefinery design, by imposing lower bounds on an economic parameter (Net Present Value) and a multi-criteria sustainability metric (Sustainability Net Present Value).For in silico strains, a bilevel optimization framework identifies gene knockouts in a genome-scale metabolic model of Synechocystis sp. PCC 6803 that couple product synthesis to growth. The resulting strain-specific performance indices are compared with their minimum feasible targets obtained from the process-level optimization. This integrated approach extends previous studies by combining genome-scale metabolic modelling with techno-economic and sustainability analysis within a unified optimization framework. Numerical results indicate that the minimal target indices are largely surpassed by two of the in silico strains, the wild-type and the coupled ethanol-producing, as well as by the in vivo strains. The proposed framework provides a quantitative basis to assess the feasibility of cyanobacteria-based biorefineries and to guide future metabolic engineering and process design strategies.