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• W2935604967 abstract "Engineered biofilm consortia have the potential to solve important biotechnological problems that have proved difficult for monoculture biofilms and planktonic consortia, such as conversion of lignocellulosic material to useful biochemicals. While considerable experimental progress has been reported for engineering and characterizing biofilm consortia, the field still lacks in silico tools for simulation, design, and optimization of stable, robust, and productive designed consortia. We developed biofilm consortia metabolic models for two coculture systems centered around the ecological design motif of a primary cell type that utilizes a supplied electron donor and secretes acetate as a byproduct and a secondary cell type that consumes the acetate, relieving byproduct inhibition on the primary cell type and enhancing overall system biomass. The models presented in this paper predict that distinct metabolic niches for the two cell types could be established by supplying electron donors and acceptors at opposite ends of the biofilm and that acetate consumption by the secondary cell type could increase total biomass accumulation and the synthesis of valuable biochemicals, such as isobutanol, by the primary cell type. System tunability is enhanced when each cell type is supplied with a unique terminal electron acceptor at opposite ends of the biofilm rather than competing for a common electron acceptor. Our model provides good qualitative agreement with data for a synthetic Escherichia coli coculture system, suggesting that the proposed design rules may have wide applicability to engineered biofilm consortia." @default.
• W2935604967 created "2019-04-11" @default.
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• W2935604967 date "2019-05-20" @default.
• W2935604967 modified "2023-10-16" @default.
• W2935604967 title "In Silico Metabolic Design of Two‐Strain Biofilm Systems Predicts Enhanced Biomass Production and Biochemical Synthesis" @default.
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• W2935604967 doi "https://doi.org/10.1002/biot.201800511" @default.
• W2935604967 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30927492" @default.
• W2935604967 hasPublicationYear "2019" @default.
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