An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production

<p>Abstract</p> <p>Background</p> <p>Microorganisms are used as cell factories to produce valuable compounds in pharmaceuticals, biofuels, and other industrial processes. Incorporating heterologous metabolic pathways into well-characterized hosts is a major strategy for...

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Main Authors: Chatsurachai Sunisa, Furusawa Chikara, Shimizu Hiroshi
Format: Article
Language:English
Published: BMC 2012-05-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/13/93
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spelling doaj-12828390d52940a49790dc0bb418dc8e2020-11-25T00:55:22ZengBMCBMC Bioinformatics1471-21052012-05-011319310.1186/1471-2105-13-93An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite productionChatsurachai SunisaFurusawa ChikaraShimizu Hiroshi<p>Abstract</p> <p>Background</p> <p>Microorganisms are used as cell factories to produce valuable compounds in pharmaceuticals, biofuels, and other industrial processes. Incorporating heterologous metabolic pathways into well-characterized hosts is a major strategy for obtaining these target metabolites and improving productivity. However, selecting appropriate heterologous metabolic pathways for a host microorganism remains difficult owing to the complexity of metabolic networks. Hence, metabolic network design could benefit greatly from the availability of an <it>in silico</it> platform for heterologous pathway searching.</p> <p>Results</p> <p>We developed an algorithm for finding feasible heterologous pathways by which nonnative target metabolites are produced by host microorganisms, using <it>Escherichia coli</it>, <it>Corynebacterium glutamicum</it>, and <it>Saccharomyces cerevisiae</it> as templates. Using this algorithm, we screened heterologous pathways for the production of all possible nonnative target metabolites contained within databases. We then assessed the feasibility of the target productions using flux balance analysis, by which we could identify target metabolites associated with maximum cellular growth rate.</p> <p>Conclusions</p> <p>This <it>in silico</it> platform, designed for targeted searching of heterologous metabolic reactions, provides essential information for cell factory improvement.</p> http://www.biomedcentral.com/1471-2105/13/93
collection DOAJ
language English
format Article
sources DOAJ
author Chatsurachai Sunisa
Furusawa Chikara
Shimizu Hiroshi
spellingShingle Chatsurachai Sunisa
Furusawa Chikara
Shimizu Hiroshi
An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production
BMC Bioinformatics
author_facet Chatsurachai Sunisa
Furusawa Chikara
Shimizu Hiroshi
author_sort Chatsurachai Sunisa
title An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production
title_short An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production
title_full An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production
title_fullStr An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production
title_full_unstemmed An <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production
title_sort <it>in silico</it> platform for the design of heterologous pathways in nonnative metabolite production
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2012-05-01
description <p>Abstract</p> <p>Background</p> <p>Microorganisms are used as cell factories to produce valuable compounds in pharmaceuticals, biofuels, and other industrial processes. Incorporating heterologous metabolic pathways into well-characterized hosts is a major strategy for obtaining these target metabolites and improving productivity. However, selecting appropriate heterologous metabolic pathways for a host microorganism remains difficult owing to the complexity of metabolic networks. Hence, metabolic network design could benefit greatly from the availability of an <it>in silico</it> platform for heterologous pathway searching.</p> <p>Results</p> <p>We developed an algorithm for finding feasible heterologous pathways by which nonnative target metabolites are produced by host microorganisms, using <it>Escherichia coli</it>, <it>Corynebacterium glutamicum</it>, and <it>Saccharomyces cerevisiae</it> as templates. Using this algorithm, we screened heterologous pathways for the production of all possible nonnative target metabolites contained within databases. We then assessed the feasibility of the target productions using flux balance analysis, by which we could identify target metabolites associated with maximum cellular growth rate.</p> <p>Conclusions</p> <p>This <it>in silico</it> platform, designed for targeted searching of heterologous metabolic reactions, provides essential information for cell factory improvement.</p>
url http://www.biomedcentral.com/1471-2105/13/93
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