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It is the best known and most promising producer of polyhydroxyalkanoates (PHAs) from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make <jats:italic>R. eutropha<\/jats:italic> H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We present the lithoautotrophic genome-scale metabolic model of <jats:italic>R. eutropha<\/jats:italic> H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of <jats:italic>R. eutropha<\/jats:italic> H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(-)-3hydroxybutyrate] (PHB) under different pH values and carbon\/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of <jats:italic>R. eutropha<\/jats:italic> when the phosphofructokinase gene was expressed. Finally, <jats:italic>in silico<\/jats:italic> gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in <jats:italic>R. eutropha<\/jats:italic> H16.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>The genome-scale metabolic model, RehMBEL1391, successfully represented metabolic characteristics of <jats:italic>R. eutropha<\/jats:italic> H16 at systems level. The reconstructed genome-scale metabolic model can be employed as an useful tool for understanding its metabolic capabilities, predicting its physiological consequences in response to various environmental and genetic changes, and developing strategies for systems metabolic engineering to improve its metabolic performance.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1752-0509-5-101","type":"journal-article","created":{"date-parts":[[2011,8,10]],"date-time":"2011-08-10T18:15:43Z","timestamp":1313000143000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":79,"title":["Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production"],"prefix":"10.1186","volume":"5","author":[{"given":"Jong Myoung","family":"Park","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tae Yong","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang Yup","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2011,6,28]]},"reference":[{"key":"717_CR1","doi-asserted-by":"publisher","first-page":"1257","DOI":"10.1038\/nbt1244","volume":"24","author":"A Pohlmann","year":"2006","unstructured":"Pohlmann A, Fricke WF, Reinecke F, Kusian B, Liesegang H, Cramm R, Eitinger T, Ewering C, Potter M, Schwartz E, et al.: Genome sequence of the bioplastic-producing \"Knallgas\" bacterium Ralstonia eutropha H16. 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