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

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

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.

Apa Reference Jiang, S., Otero-Muras, I., Banga, J. R., Wang, Y., Kaiser, M., & Krasnogor, N. (2022). OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production. ACS Synthetic Biology, 11(4), 1531–1541. 10.1021/acssynbio.1c00610
Doi 10.1021/acssynbio.1c00610
Publication Date 7 Apr 2022
Publication Type Article
Researcher Julio Rodriguez Banga
Ontology Transcriptomics, Model organisms, Expression Profiling, Metabolic modelling
Research Groups Computational Biology Lab at MBG
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