Systems biology-based identification of Mycobacterium tuberculosis persistence genes in mouse lungs.

ABSTRACT:

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Identifying Mycobacterium tuberculosis persistence genes is important for developing novel drugs to shorten the duration of tuberculosis (TB) treatment. We developed computational algorithms that predict M. tuberculosis genes required for long-term survival in mouse lungs. As the input, we used high-throughput M. tuberculosis mutant library screen data, mycobacterial global transcriptional profiles in mice and macrophages, and functional interaction networks. We selected 57 unique, genetically defined mutants (18 previously tested and 39 untested) to assess the predictive power of this approach in the murine model of TB infection. We observed a 6-fold enrichment in the predicted set of M. tuberculosis genes required for persistence in mouse lungs relative to randomly sel

SUBMITTER: Dutta NK 

PROVIDER: S-EPMC3944818 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature