Computer assisted multi-level optimization of malonyl-CoA availability in Pseudomonas putida

Abstract

Malonyl-CoA is the major precursor for the biosynthesis of diverse industrially valuable products such as fatty acids/alcohols, flavonoids, and polyketides. However, its intracellular availability is limited in most microbial hosts, hampering the biological synthesis of such chemicals. To address this limitation, we present a multi-level optimization workflow using modern metabolic engineer-ing technologies to systematically increase the malonyl-CoA levels in Pseudomonas putida. The workflow involves the identification of gene downregulations, chassis selection, and optimization of the acetyl-CoA carboxylase complex through ribosome binding site engineering. Computa-tional tools and high-throughput screening with a malonyl-CoA biosensor enabled the rapid eval-uation of numerous genetic targets. Combining the most beneficial targets led to a 5.8-fold en-hancement in the production titer of the valuable polyketide phloroglucinol. This study demon-strates the effective integration of computational and genetic technologies for engineering P. putida, opening new avenues for the development of industrially relevant strains and the investi-gation of fundamental biological questions.