An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals



Carbonell, Pablo, Jervis, Adrian J, Robinson, Christopher J, Yan, Cunyu, Dunstan, Mark, Swainston, Neil ORCID: 0000-0001-7020-1236, Vinaixa, Maria, Hollywood, Katherine A, Currin, Andrew, Rattray, Nicholas JW
et al (show 19 more authors) (2018) An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals. COMMUNICATIONS BIOLOGY, 1 (1). 66-.

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Abstract

The microbial production of fine chemicals provides a promising biosustainable manufacturing solution that has led to the successful production of a growing catalog of natural products and high-value chemicals. However, development at industrial levels has been hindered by the large resource investments required. Here we present an integrated Design-Build-Test-Learn (DBTL) pipeline for the discovery and optimization of biosynthetic pathways, which is designed to be compound agnostic and automated throughout. We initially applied the pipeline for the production of the flavonoid (2<i>S</i>)-pinocembrin in <i>Escherichia coli</i>, to demonstrate rapid iterative DBTL cycling with automation at every stage. In this case, application of two DBTL cycles successfully established a production pathway improved by 500-fold, with competitive titers up to 88 mg L<sup>-1</sup>. The further application of the pipeline to optimize an alkaloids pathway demonstrates how it could facilitate the rapid optimization of microbial strains for production of any chemical compound of interest.

Item Type: Article
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 06 Sep 2021 07:13
Last Modified: 09 Mar 2023 05:55
DOI: 10.1038/s42003-018-0076-9
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3135971