Mapping and manipulating the Mycobacterium tuberculosis transcriptome using a transcription factor overexpression-derived regulatory network.

TitleMapping and manipulating the Mycobacterium tuberculosis transcriptome using a transcription factor overexpression-derived regulatory network.
Publication TypeJournal Article
Year of Publication2014
AuthorsRustad TR, Minch KJ, Ma S, Winkler JK, Hobbs S, Hickey M, Brabant W, Turkarslan S, Price ND, Baliga NS, Sherman DR
JournalGenome Biol
Volume15
Issue11
Pagination502
Date Published2014
ISSN1465-6914
Abstract

BACKGROUND: Mycobacterium tuberculosis senses and responds to the shifting and hostile landscape of the host. To characterize the underlying intertwined gene regulatory network governed by approximately 200 transcription factors of M. tuberculosis, we have assayed the global transcriptional consequences of overexpressing each transcription factor from an inducible promoter.

RESULTS: We cloned and overexpressed 206 transcription factors in M. tuberculosis to identify the regulatory signature of each. We identified 9,335 regulatory consequences of overexpressing each of 183 transcription factors, providing evidence of regulation for 70% of the M. tuberculosis genome. These transcriptional signatures agree well with previously described M. tuberculosis regulons. The number of genes differentially regulated by transcription factor overexpression varied from hundreds of genes to none, with the majority of expression changes repressing basal transcription. Exploring the global transcriptional maps of transcription factor overexpressing (TFOE) strains, we predicted and validated the phenotype of a regulator that reduces susceptibility to a first line anti-tubercular drug, isoniazid. We also combined the TFOE data with an existing model of M. tuberculosis metabolism to predict the growth rates of individual TFOE strains with high fidelity.

CONCLUSION: This work has led to a systems-level framework describing the transcriptome of a devastating bacterial pathogen, characterized the transcriptional influence of nearly all individual transcription factors in M. tuberculosis, and demonstrated the utility of this resource. These results will stimulate additional systems-level and hypothesis-driven efforts to understand M. tuberculosis adaptations that promote disease.

DOI10.1186/PREACCEPT-1701638048134699
Alternate JournalGenome Biol.
PubMed ID25380655
PubMed Central IDPMC4249609
Grant List2P50GM076547 / GM / NIGMS NIH HHS / United States
T32AI007509. / AI / NIAID NIH HHS / United States
U19 AI106761 / AI / NIAID NIH HHS / United States