In silico identification of gene targets to enhance C12 fatty acid production in Escherichia coli

The global interest in fatty acids is steadily rising due to their wealth of industrial potential ranging from cosmetics to biofuels. Unfortunately, certain fatty acids, such as monounsaturated lauric acid with a carbon atom chain length of twelve (C12 fatty acids), cannot be produced cost and energy-efficiently using conventional methods. Biosynthesis using microorganisms can overcome this drawback. However, rewiring a microbe's metabolome for increased production remains challenging. To overcome this, sophisticated genome-wide metabolic network models have become available. These models predict the effect of genetic perturbations on the metabolism, thereby serving as a guide for metabolic pathways optimization. In this work, we used constraint-based modeling in combination with the algorithm Optknock to identify gene deletions in Escherichia coli that improve C12 fatty acid production. Nine gene targets were identified that, when deleted, were predicted to increase C12 fatty acid titers. Targets play a role in anaplerotic reactions, amino acid synthesis, carbon metabolism, and cofactor-balancing. Subsequently, we constructed the corresponding (combinatorial) deletion mutants to validate the in silico predictions in vivo. Our highest producer (ΔmaeB Δndk ΔpykA) reaches a titer of 6.7 mg/L, corresponding to a 7.5-fold increase in C12 fatty acid production. This study demonstrates that model-guided metabolic engineering is a useful tool to improve C12 fatty acid production. KEY POINTS: •Escherichia coli as a promising biofactory for unsaturated C12 fatty acids. •Optknock to identify non-obvious gene deletions for increased C12 fatty acids. •7.5-fold higher C12 fatty acid production achieved by deleting maeB, ndk, and pykA.