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          Institute: MPI für Dynamik komplexer technischer Systeme     Collection: Systems Biology     Display Documents



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ID: 320932.0, MPI für Dynamik komplexer technischer Systeme / Systems Biology
GSMN-TB : a web-based genome-scale network model of Mycobacterium tuberculosis metabolism
Authors:Beste, D. J.; Hooper, T.; Stewart, G.; Bonde, B.; Avignone-Rossa, C.; Bushell, M. E.; Wheeler, P.; Klamt, S.; Kierzek, A. M.; McFadden, J.
Language:English
Date of Publication (YYYY-MM-DD):2007
Title of Journal:Genome Biology
Volume:8
Sequence Number of Article:R89
Review Status:Peer-review
Audience:Experts Only
Abstract / Description:Background

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.

© 2007 Beste et al.; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
External Publication Status:published
Document Type:Article
Communicated by:Ernst-Dieter Gilles
Affiliations:MPI für Dynamik komplexer technischer Systeme/Systems Biology
Identifiers:LOCALID:28/07
LOCALID:OA 320932
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