Collection of Mycobacterium tuberculosis samples from various countries
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB50999 | ENA |
REPOSITORIES: ENA
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Project description:Jamshidi2007 - Genome-scale metabolic network
of Mycobacterium tuberculosis (iNJ661)
This model is described in the article:
Investigating the metabolic
capabilities of Mycobacterium tuberculosis H37Rv using the in
silico strain iNJ661 and proposing alternative drug
targets.
Jamshidi N, Palsson BØ.
BMC Syst Biol 2007; 1: 26
Abstract:
BACKGROUND: Mycobacterium tuberculosis continues to be a
major pathogen in the third world, killing almost 2 million
people a year by the most recent estimates. Even in
industrialized countries, the emergence of multi-drug resistant
(MDR) strains of tuberculosis hails the need to develop
additional medications for treatment. Many of the drugs used
for treatment of tuberculosis target metabolic enzymes.
Genome-scale models can be used for analysis, discovery, and as
hypothesis generating tools, which will hopefully assist the
rational drug development process. These models need to be able
to assimilate data from large datasets and analyze them.
RESULTS: We completed a bottom up reconstruction of the
metabolic network of Mycobacterium tuberculosis H37Rv. This
functional in silico bacterium, iNJ661, contains 661 genes and
939 reactions and can produce many of the complex compounds
characteristic to tuberculosis, such as mycolic acids and
mycocerosates. We grew this bacterium in silico on various
media, analyzed the model in the context of multiple
high-throughput data sets, and finally we analyzed the network
in an 'unbiased' manner by calculating the Hard Coupled
Reaction (HCR) sets, groups of reactions that are forced to
operate in unison due to mass conservation and connectivity
constraints. CONCLUSION: Although we observed growth rates
comparable to experimental observations (doubling times ranging
from about 12 to 24 hours) in different media, comparisons of
gene essentiality with experimental data were less encouraging
(generally about 55%). The reasons for the often conflicting
results were multi-fold, including gene expression variability
under different conditions and lack of complete biological
knowledge. Some of the inconsistencies between in vitro and in
silico or in vivo and in silico results highlight specific loci
that are worth further experimental investigations. Finally, by
considering the HCR sets in the context of known drug targets
for tuberculosis treatment we proposed new alternative, but
equivalent drug targets.
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