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Home › Publications › Development of platforms for functional characterization and production of phenazines using a multi-chassis approach via CRAGE

Development of platforms for functional characterization and production of phenazines using a multi-chassis approach via CRAGE

Published in:

Metabolic Engineering 69 , 188-197 ( 2021)

Author(s):

Ke, Jing, Zhao, Zhiying, Coates, Cameron R, Hadjithomas, Michalis, Kuftin, Andrea, Louie, Katherine, Weller, David, Thomashow, Linda, Mouncey, Nigel J, Northen, Trent R, Yoshikuni, Yasuo

DOI:

10.1016/j.ymben.2021.11.012

Abstract:

Phenazines (Phzs), a family of chemicals with a phenazine backbone, are secondary metabolites with diverse properties such as antibacterial, anti-fungal, or anticancer activity. The core derivatives of phenazine, phenazine-1-carboxylic acid (PCA) and phenazine-1,6-dicarboxylic acid (PDC), are themselves precursors for various other derivatives. Recent advances in genome mining tools have enabled researchers to identify many biosynthetic gene clusters (BGCs) that might produce novel Phzs. To characterize the function of these BGCs efficiently, we performed modular construct assembly and subsequent multi-chassis heterologous expression using chassis-independent recombinase-assisted genome engineering (CRAGE). CRAGE allowed rapid integration of a PCA BGC into 23 diverse γ-proteobacteria species and allowed us to identify top PCA producers. We then used the top five chassis hosts to express four partially refactored PDC BGCs. A few of these platforms produced high levels of PDC. Specifically, Xenorhabdus doucetiae and Pseudomonas simiae produced PDC at a titer of 293 mg/L and 373 mg/L, respectively, in minimal media. These titers are significantly higher than those previously reported. Furthermore, selectivity toward PDC production over PCA production was improved by up to 9-fold. The results show that these strains are promising chassis for production of PCA, PDC, and their derivatives, as well as for function characterization of Phz BGCs identified via bioinformatics mining.

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