Combining metabolic evolution and systematic fed-batch optimization for efficient single-cell oil production from sugarcane bagasse

Abstract

We developed in this study an efficient production process of SCO from sugarcane bagasse hydrolysates using Y. lipolytica. We described a dynamic flux balance model strategy based on a genome-scale metabolic model of Y. lipolytica and SCO fermentation kinetics that applied for rational design of optimized fed-batch process with high single cell oil accumulation. Furthermore, metabolic evolution approach with buoyancy screening was implemented for selecting a high lipid producing yeast strain. The efficient conversion process combined model-based fed-batch process design and evolution-based strain optimization enabling high SCO titer of 45 g/L and 0.25 g-SCO/g-glucose yield from hydrolysates, a 6-fold improvement in titer and 1.4-fold improvement in yield over batch wild-type process. Through this combinatorial optimization effort, we demonstrated the cost-effective, lignocellulose-based SCO process that could meet techno-economic feasibility providing a sustainable alternative to vegetative oils for biofuels and oleochemicals synthesis.