ABSTRACT: BACKGROUND: Microorganisms are used as cell factories to produce valuable compounds in pharmaceuticals,biofuels, and other industrial processes. Incorporating heterologous metabolic pathways intowell-characterized hosts is a major strategy for obtaining these target metabolites andimproving productivity. However, selecting appropriate heterologous metabolic pathways fora host microorganism remains difficult owing to the complexity of metabolic networks.Hence, metabolic network design could benefit greatly from the availability of an in silicoplatform for heterologous pathway searching. RESULTS: We developed an algorithm for finding feasible heterologous pathways by which nonnativetarget metabolites are produced by host microorganisms, using Escherichia coli,Cornyebacterium glutamicum, and Saccharomyces cerevisiae as templates. Using thisalgorithm, we screened heterologous pathways for the production of all possible nonnativetarget metabolites contained within databases. We then assessed the feasibility of the targetproductions using flux balance analysis, by which we could identify target metabolitesassociated with maximum cellular growth rate. CONCLUSIONS: This in silico platform, designed for targeted searching of heterologous metabolic reactions,provides essential information for cell factory improvement.FAU - Chatsurachai, Sunis.
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