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

Batianis, C.; van Rosmalen, R.; Monino Fernandez, P.; Asin-Garcia, E.; Martin-Pascual, M.; Jeschek, M.; Weusthuis, R.; Suarez Diez, M.; Martins dos Santos, V. A.

doi:10.1101/2024.11.20.624107

bioRxiv · 10.1101/2024.11.20.624107

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

Batianis, C.·van Rosmalen, R.·Monino Fernandez, P.·Asin-Garcia, E.·Martin-Pascual, M.·Jeschek, M.·Weusthuis, R.·Suarez Diez, M.·Martins dos Santos, V. A.

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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.

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Batianis, C., van Rosmalen, R., Monino Fernandez, P., Asin-Garcia, E., Martin-Pascual, M., Jeschek, M., Weusthuis, R., Suarez Diez, M., Martins dos Santos, V. A.. 2024-11-20. Computer assisted multi-level optimization of malonyl-CoA availability in Pseudomonas putida. https://doi.org/10.1101/2024.11.20.624107

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