The Bioinformatics Prediction Of The SRNA In The Mycobacterium Tuberculosis

Tuberculosis remains to be a major threat to human life and health. According to World Health Organization, there is an estimated of 1.3 million deaths and 9.4 million new cases in 2008 alone. Tuberculosis had once been effectively controlled during the 1960s to 1970s, but the emergence of strains of Mycobacterium tuberculosis, the causative agent of tuberculosis, that are resistant to the most widely used antibiotics (MDR-TB) or extensively drug-resistant (XDR-TB), represent a significant challenge to the control of tuberculosis. Therefore, the discovery of novel potential drug targets, which would contribute to the development of new anti-tuberculosis drugs, is of first importance to the treatment of tuberculosis.Bacterial small RNA (sRNA) is a class of regulatory RNA molecular encoded by the genome, but most of them do not produce protein product. They exert their influence on the cellular response to environmental stress either by basepairing with mRNA or by influencing the activity of protein. Under the control of the bacterial global regulators, sRNA plays a remarkable role in the implementation of many regulatory cascades and acts as nodes of some pathways. The study on sRNA gets to be a novel breakthrough point in clarifying the nature of the significant physiological processes.However, little was already known about the mycobacterial sRNA. The present study predicted the sRNAs in M.tuberculosis through bioinformatics tools, hoping to find some new sRNAs in this kind of pathogen. Identification of novel mycobacterial sRNA and characterization of their function can helps to elucidate the complicated physiological pathways involving in the intracellular survival and persistence of the M.tuberculosis, which will aid the discovery of novel potentical anti-tuberculosis drug target. In the present study, I employed two approaches to explore the sRNA in M. tuberculosis strain H37Rv, including querying the conserved intergenic region among closed related species and searching the possible promoters in the intergenic region. In using the BLAST program to analyze the predicted results, I evaluate their reliabilityies, take off the probable protein candidates and finally listed the sRNA candidates.The candidates IG318 and IG615 et cetera could be taken into experimental verification in the further work.