Literature DB >> 10364169

Systems properties of the Haemophilus influenzae Rd metabolic genotype.

J S Edwards1, B O Palsson.   

Abstract

Haemophilus influenzae Rd was the first free-living organism for which the complete genomic sequence was established. The annotated sequence and known biochemical information was used to define the H. influenzae Rd metabolic genotype. This genotype contains 488 metabolic reactions operating on 343 metabolites. The stoichiometric matrix was used to determine the systems characteristics of the metabolic genotype and to assess the metabolic capabilities of H. influenzae. The need to balance cofactor and biosynthetic precursor production during growth on mixed substrates led to the definition of six different optimal metabolic phenotypes arising from the same metabolic genotype, each with different constraining features. The effects of variations in the metabolic genotype were also studied, and it was shown that the H. influenzae Rd metabolic genotype contains redundant functions under defined conditions. We thus show that the synthesis of in silico metabolic genotypes from annotated genome sequences is possible and that systems analysis methods are available that can be used to analyze and interpret phenotypic behavior of such genotypes.

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Year:  1999        PMID: 10364169     DOI: 10.1074/jbc.274.25.17410

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  107 in total

1.  The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities.

Authors:  J S Edwards; B O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2000-05-09       Impact factor: 11.205

Review 2.  Thirteen years of building constraint-based in silico models of Escherichia coli.

Authors:  Jennifer L Reed; Bernhard Ø Palsson
Journal:  J Bacteriol       Date:  2003-05       Impact factor: 3.490

Review 3.  Using the reconstructed genome-scale human metabolic network to study physiology and pathology.

Authors:  A Bordbar; B O Palsson
Journal:  J Intern Med       Date:  2012-02       Impact factor: 8.989

4.  Extreme pathway lengths and reaction participation in genome-scale metabolic networks.

Authors:  Jason A Papin; Nathan D Price; Bernhard Ø Palsson
Journal:  Genome Res       Date:  2002-12       Impact factor: 9.043

5.  Flux coupling analysis of genome-scale metabolic network reconstructions.

Authors:  Anthony P Burgard; Evgeni V Nikolaev; Christophe H Schilling; Costas D Maranas
Journal:  Genome Res       Date:  2004-01-12       Impact factor: 9.043

6.  Analysis of metabolic capabilities using singular value decomposition of extreme pathway matrices.

Authors:  Nathan D Price; Jennifer L Reed; Jason A Papin; Iman Famili; Bernhard O Palsson
Journal:  Biophys J       Date:  2003-02       Impact factor: 4.033

7.  Genome-scale metabolic model of Helicobacter pylori 26695.

Authors:  Christophe H Schilling; Markus W Covert; Iman Famili; George M Church; Jeremy S Edwards; Bernhard O Palsson
Journal:  J Bacteriol       Date:  2002-08       Impact factor: 3.490

8.  Molecular evolution in large genetic networks: does connectivity equal constraint?

Authors:  Matthew W Hahn; Gavin C Conant; Andreas Wagner
Journal:  J Mol Evol       Date:  2004-02       Impact factor: 2.395

Review 9.  A road map for the development of community systems (CoSy) biology.

Authors:  Karsten Zengler; Bernhard O Palsson
Journal:  Nat Rev Microbiol       Date:  2012-03-27       Impact factor: 60.633

Review 10.  A metabolic network approach for the identification and prioritization of antimicrobial drug targets.

Authors:  Arvind K Chavali; Kevin M D'Auria; Erik L Hewlett; Richard D Pearson; Jason A Papin
Journal:  Trends Microbiol       Date:  2012-01-31       Impact factor: 17.079

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