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• W2896098760 startingPage "e00080" @default.
• W2896098760 abstract "Conversion of renewable biomass to useful molecules in microbial cell factories can be approached in a rational and systematic manner using constraint-based reconstruction and analysis. Filtering for high confidence in silico designs is critical because in vivo construction and testing of strains is expensive and time consuming. As such, a workflow was devised to analyze the robustness of growth-coupled production when considering the biosynthetic costs of the proteome and variability in enzyme kinetic parameters using a genome-scale model of metabolism and gene expression (ME-model). A collection of 2632 unfiltered knockout designs in Escherichia coli was evaluated by the workflow. A ME-model was used in the workflow to test the designs' growth-coupled production in addition to a less complex genome-scale metabolic model (M-model). The workflow identified 634 M-model growth-coupled designs which met the filtering criteria and 42 robust designs, which met growth-coupled production criteria using both M and ME-models. Knockouts were found to follow a pattern of controlling intermediate metabolite consumption such as pyruvate consumption and high flux subsystems such as glycolysis. Kinetic parameter sampling using the ME-model revealed how enzyme efficiency and pathway tradeoffs can affect growth-coupled production phenotypes." @default.
• W2896098760 created "2018-10-26" @default.
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• W2896098760 date "2018-12-01" @default.
• W2896098760 modified "2023-10-12" @default.
• W2896098760 title "Identification of growth-coupled production strains considering protein costs and kinetic variability" @default.
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• W2896098760 doi "https://doi.org/10.1016/j.mec.2018.e00080" @default.
• W2896098760 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6199775" @default.
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• W2896098760 hasPublicationYear "2018" @default.
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