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Lookup NU author(s): Dr Shouyong Jiang, Professor Marcus Kaiser, Professor Natalio KrasnogorORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Computational tools have been widely adopted for strain optimization in metabolic engineering, contributing to numerous success stories of producing industrially relevant biochemicals. However, most of these tools focus on single metabolic intervention strategies (either gene/reaction knockout or amplification alone) and rely on hypothetical optimality principles (e.g., maximization of growth) and precise gene expression (e.g., fold changes) for phenotype prediction. This paper introduces OptDesign, a new two-step strain design strategy. In the first step, OptDesign selects regulation candidates that have a noticeable flux difference between the wild type and production strains. In the second step, it computes optimal design strategies with limited manipulations (combining regulation and knockout), leading to high biochemical production. The usefulness and capabilities of OptDesign are demonstrated for the production of three biochemicals in Escherichia coli using the latest genome-scale metabolic model iML1515, showing highly consistent results with previous studies while suggesting new manipulations to boost strain performance. The source code is available at https://github.com/chang88ye/OptDesign.
Author(s): Jiang S, Otero-Muras I, Banga JR, Wang Y, Kaiser M, Krasnogor N
Publication type: Article
Publication status: Published
Journal: ACS Synthetic Biology
Year: 2022
Volume: 11
Issue: 4
Pages: 1531-1541
Print publication date: 15/04/2022
Online publication date: 07/04/2022
Acceptance date: 02/04/2018
Date deposited: 09/05/2022
ISSN (electronic): 2161-5063
Publisher: American Chemical Society
URL: https://doi.org/10.1021/acssynbio.1c00610
DOI: 10.1021/acssynbio.1c00610
PubMed id: 35389631
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