Model-driven engineering ofYarrowia lipolyticafor improved microbial oil production

Summary Extensive usage of plant-based oils, especially palm oil, has led to environmental and social issues, such as deforestation and loss of biodiversity, thus sustainable alternatives are required. Microbial oils, especially from Yarrowia lipolytica , offer a promising solution due to their similar composition to palm oil, low carbon footprint, and ability to utilize low-cost substrates. In this study, we employed the Design-Build-Test-Learn (DBTL) approach to enhance lipid production in Y. lipolytica . We systematically evaluated predictions from the genome-scale metabolic model to identify and overcome bottlenecks in lipid biosynthesis. We tested the effect of predicted medium supplements and genetic intervention targets, including the overexpression of ATP-citrate lyase ( ACL ), acetyl-CoA carboxylase ( ACC ), threonine synthase ( TS ), diacylglycerol acyltransferase( DGA1 ), the deletion of citrate exporter gene ( CEX1 ) and disruption of β-oxidation pathway ( MFE1 ). Combining TS and DGA1 overexpression in the Δmfe_Δcex background achieved a remarkable 200% increase in lipid content (56 % w/w) and a 230% increase in lipid yield on glycerol. These findings underscore the potential of Y. lipolytica as an efficient microbial cell factory for fatty acid production. Our study advances the understanding of lipid metabolism in Y. lipolytica and demonstrates a viable approach for developing sustainable and economically feasible alternatives to palm oil. Graphical Abstract We followed the Design-Build-Test-Learn approach to identify and overcome bottlenecks in lipid biosynthesis in Y. lipolytica . DBTL intertwined the predictions from the metabolic model with addressed bottlenecks, investigated the effect of genetic interventions and medium supplements on lipid content, and ultimately defined an efficient strain design strategy.