Journal
NUCLEIC ACIDS RESEARCH
Volume 42, Issue 18, Pages 11291-11303Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gku777
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Funding
- National Institute of Allergy and Infectious Diseases of the National Institutes of Health [U 19 AI10676]
- National Institute of General Medical Sciences of the National Institutes of Health [P50GM076547]
- U.S. National Science Foundation [MSB-1237267, DB-1262637, MCB-1330912]
- Div Of Biological Infrastructure
- Direct For Biological Sciences [1262637] Funding Source: National Science Foundation
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The resilience of Mycobacterium tuberculosis (MTB) is largely due to its ability to effectively counteract and even take advantage of the hostile environments of a host. In order to accelerate the discovery and characterization of these adaptive mechanisms, we have mined a compendium of 2325 publicly available transcriptome profiles of MTB to decipher a predictive, systems-scale gene regulatory network model. The resulting modular organization of 98% of all MTB genes within this regulatory network was rigorously tested using two independently generated datasets: a genome-wide map of 7248 DNA-binding locations for 143 transcription factors (TFs) and global transcriptional consequences of over-expressing 206 TFs. This analysis has discovered specific TFs that mediate conditional co-regulation of genes within 240 modules across 14 distinct environmental contexts. In addition to recapitulating previously characterized regulons, we discovered 454 novel mechanisms for gene regulation during stress, cholesterol utilization and dormancy. Significantly, 183 of these mechanisms act uniquely under conditions experienced during the infection cycle to regulate diverse functions including 23 genes that are essential to host-pathogen interactions. These and other insights underscore the power of a rational, model-driven approach to unearth novel MTB biology that operates under some but not all phases of infection.
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