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  GSMN-TB : a web-based genome-scale network model of Mycobacterium tuberculosis metabolism

Beste, D. J., Hooper, T., Stewart, G., Bonde, B., Avignone-Rossa, C., Bushell, M. E., et al. (2007). GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism. Genome Biology, 8: R89. doi:10.1186/gb-2007-8-5-r89.

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GenomeBiology_8_R89.pdf (Verlagsversion), 2MB
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© 2007 Beste et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License

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Beste, D. J.1, Autor
Hooper, T.1, Autor
Stewart, G.1, Autor
Bonde, B.1, Autor
Avignone-Rossa, C.1, Autor
Bushell, M. E.1, Autor
Wheeler, P.2, Autor
Klamt, S.3, Autor           
Kierzek, A. M.1, Autor
McFadden, J.1, Autor
Affiliations:
1University of Surrey, School of Biomedical and Molecular Sciences, Stag Hill, Guildford, Surrey, UK, ou_persistent22              
2Tuberculosis Research Group, Veterinary Laboratories Agency (Weybridge), Addlestone UK, ou_persistent22              
3Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738155              

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 Zusammenfassung: An impediment to the rational development of novel drugs against tuberculosis (TB) is a general paucity of knowledge concerning the metabolism of Mycobacterium tuberculosis, particularly during infection. Constraint-based modeling provides a novel approach to investigating microbial metabolism but has not yet been applied to genome-scale modeling of M. tuberculosis. Results GSMN-TB, a genome-scale metabolic model of M. tuberculosis, was constructed, consisting of 849 unique reactions and 739 metabolites, and involving 726 genes. The model was calibrated by growing Mycobacterium bovis bacille Calmette Guérin in continuous culture and steady-state growth parameters were measured. Flux balance analysis was used to calculate substrate consumption rates, which were shown to correspond closely to experimentally determined values. Predictions of gene essentiality were also made by flux balance analysis simulation and were compared with global mutagenesis data for M. tuberculosis grown in vitro. A prediction accuracy of 78% was achieved. Known drug targets were predicted to be essential by the model. The model demonstrated a potential role for the enzyme isocitrate lyase during the slow growth of mycobacteria, and this hypothesis was experimentally verified. An interactive web-based version of the model is available. Conclusion The GSMN-TB model successfully simulated many of the growth properties of M. tuberculosis. The model provides a means to examine the metabolic flexibility of bacteria and predict the phenotype of mutants, and it highlights previously unexplored features of M. tuberculosis metabolism.

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Sprache(n): eng - English
 Datum: 2007
 Publikationsstatus: Erschienen
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 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1186/gb-2007-8-5-r89
eDoc: 320932
Anderer: 28/07
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Titel: Genome Biology
Genre der Quelle: Zeitschrift
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Seiten: - Band / Heft: 8 Artikelnummer: R89 Start- / Endseite: - Identifikator: -