Computational analyses of TB pathogens to decipher adaptations to transmission (360G-Wellcome-102399_Z_13_Z)

Mycobacterium tuberculosis (MTB), causative agent of tuberculosis (TB), is oneof the most successful pathogens in the world. MTB is an obligate human pathogen, having no known reservoir outside of the human host. However, the related clinically relevant smooth tubercle bacilli (STB), such as Mycobacterium canettii, seems to survive in an unidentified environmental niche. Genome sequencing has revealed great diversity across STB compared to MTB, with large numbers of single nucleotide polymorphisms (SNPs) and insertion/deletions. This raises questions about the evolution of pathogens, their adaptation to pathogenic or opportunistic lifestyles and comparative analyses across these species offer an ideal opportunity to explore these phenomena. Our hypothesis is that by studying the transcriptomic response of MTB and STB to environmental stimuli we will shed light on the evolution of these pathogens and niche adaptation. We will incorporate transcriptome data with genome data of these species to see whether there is evidence for selection of