Genome-wide identification of the context-dependent sRNA expression in Mycobacterium tuberculosis

Tuberculosis remains one of the leading causes of morbidity and mortality worldwide. Therefore, understanding the pathophysiology of Mycobacterium tuberculosis is imperative for developing new drugs. Post-transcriptional regulation plays a significant role in microbial adaptation to different growth conditions. While the proteins associated with gene expression regulation have been extensively studied in the pathogenic strain M. tuberculosis H37Rv, post-transcriptional regulation involving small RNAs (sRNAs) remains poorly understood.

We developed a novel moving-window based approach to detect sRNA expression using RNA-Seq data. Overlaying ChIP-seq data of RNAP (RNA Polymerase) and NusA suggest that these putative sRNA coding regions are significantly bound by the transcription machinery. Besides capturing many experimentally validated sRNAs, we observe the context-dependent expression of novel sRNAs in the intergenic regions of M. tuberculosis genome. For example, ncRv11806 shows expression only in the stationary phase, suggesting its role in mycobacterial latency which is a key attribute to long term pathogenicity. Also, ncRv11875C showed expression in the iron-limited condition, which is prevalent inside the macrophages of the host cells.

The systems level analysis of sRNA highlights the condition-specific expression of sRNAs which might enable the pathogen survival by rewiring regulatory circuits.