Repurposing a Fully-Reducing Polyketide Synthase for 2-Methyl Guerbet-like Lipid Production

25 June 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

In Nature, thousands of diverse and bioactive polyketides are assembled by a family of multifunctional, “assembly line” enzyme complexes called Polyketide Synthases (PKS). Since the late 20th century, there have been several attempts to decode, re-arrange and “re-programme” the PKS assembly line to generate valuable materials such as biofuels and platform chemicals. By mastering the biosynthetic logic underpinning PKSs, there exists the potential to develop these enzymes into scalable biocatalysts for sustainable chemical production. Here, the first module from Mycobacterium tuberculosis (Mt) PKS12 – an unorthodox, “modularly-iterative” PKS – was modified and repurposed towards the production of 2-methyl Guerbet lipids, which have wide applications in industry. We established a robust method for the recombinant expression and purification of this modified module (named [M1*]), and we demonstrated its synthetic utility in generating several 2-methyl Guerbet-like lipids (C13-C21). Furthermore, we studied and applied the promiscuous thioesterase (TE) activity of a neighbouring β-ketoacyl synthase (KS) to release [M1*]-bound condensation products in a one-pot biosynthetic cascade. Finally, by coupling the E. coli fatty acyl-CoA synthetase FadD to [M1*], we could generate our primary target compound – 2-methyltetradecanoic acid – from lauric acid, highlighting the potential to derive valuable lipids from inexpensive fatty acids. This work demonstrates the biosynthetic potential of [M1*] in generating industrially-useful Guerbet-like chemicals, whilst also contributing to the broader exploration and application of PKS modules for sustainable chemical manufacturing.

Keywords

biocatalysis
biosynthesis
guerbet
polyketides
lipids
pks

Supplementary materials

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Supporting Information
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Details of materials and experimental methods; supporting data; predictive structural modelling and plasmid maps.
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