Genome-Wide De Novo Prediction of Cis-Regulatory Binding Sites in Mycobacterium tuberculosis H37Rv.

• Main Authors: Wei Wu, Xian Sun, Yun Gao, Jun Jiang, Zhenling Cui, Baoxue Ge, Hai Wu, Lu Zhang, Yao Li
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2016-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC4757040?pdf=render

The transcription regulatory system of Mycobacterium tuberculosis (M. tb) remains incompletely understood. In this study, we have applied the eGLECLUBS algorithm to a group of related prokaryotic genomes for de novo genome-wide prediction of cis-regulatory binding sites (CRBSs) in M. tb H37Rv. The top 250 clusters from our prediction recovered 83.3% (50/60) of all known CRBSs in extracted inter-operonic sequences of this strain. We further demonstrated that the integration of our prediction results with the ChIP-Seq datasets is very effective in identifying true binding sites of TFs. Using electrophoretic mobility shift assays and real-time RT-PCR, we experimentally verified our prediction of CRBSs for Rv0081, an important transcription factor thought to be involved in regulation of M. tb under hypoxia.