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OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production

[Image: see text] 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/react...

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Autores principales: Jiang, Shouyong, Otero-Muras, Irene, Banga, Julio R., Wang, Yong, Kaiser, Marcus, Krasnogor, Natalio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9016760/
https://www.ncbi.nlm.nih.gov/pubmed/35389631
http://dx.doi.org/10.1021/acssynbio.1c00610
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author Jiang, Shouyong
Otero-Muras, Irene
Banga, Julio R.
Wang, Yong
Kaiser, Marcus
Krasnogor, Natalio
author_facet Jiang, Shouyong
Otero-Muras, Irene
Banga, Julio R.
Wang, Yong
Kaiser, Marcus
Krasnogor, Natalio
author_sort Jiang, Shouyong
collection PubMed
description [Image: see text] 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.
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spelling pubmed-90167602022-04-20 OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production Jiang, Shouyong Otero-Muras, Irene Banga, Julio R. Wang, Yong Kaiser, Marcus Krasnogor, Natalio ACS Synth Biol [Image: see text] 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. American Chemical Society 2022-04-07 2022-04-15 /pmc/articles/PMC9016760/ /pubmed/35389631 http://dx.doi.org/10.1021/acssynbio.1c00610 Text en © 2022 American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Jiang, Shouyong
Otero-Muras, Irene
Banga, Julio R.
Wang, Yong
Kaiser, Marcus
Krasnogor, Natalio
OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production
title OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production
title_full OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production
title_fullStr OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production
title_full_unstemmed OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production
title_short OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production
title_sort optdesign: identifying optimum design strategies in strain engineering for biochemical production
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9016760/
https://www.ncbi.nlm.nih.gov/pubmed/35389631
http://dx.doi.org/10.1021/acssynbio.1c00610
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