Molecular diagnostics, based on the identification of resistance-causing mutations, hold great promise for diagnosing drug resistant tuberculosis (TB). However, these diagnostics require prior knowledge of which polymorphisms in the genome of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, associate with drug resistance. Currently, we do not have full knowledge of drug associated polymorphisms. This is due, in part, to our previous inability to systematically evaluate large sequence polymorphisms (LSPs) in the Mtb genome including deletions, insertions and substitutions.
To expand our understanding of the polymorphisms associated with drug resistance, we report the first systematic study of LSPs in Mtb. A key challenge in performing this study is that the variant detection algorithm used to call LSPs often represents the same LSP differently across strains, which reduces our ability to associate specific LSPs with drug resistance. To address this, we developed an algorithm that normalizes different representations of the same LSP and applied it to the genomes of a collection of 71 phenotypically diverse Mtb strains from South Africa. After normalization, we observed 1,358 unique LSPs (34% deletions, 48% insertions, and 18% substitutions) evenly distributed throughout the Mtb genome that ranged in size from a few base pairs to 24,000 base pairs.
While some LSPs affiliate with particular Mtb lineages, we were able to detect associations between specific LSPs and drug resistance. This finding suggests that LSPs may play a previously unappreciated role in the evolution of drug resistance in Mtb.
PROJECT: The role of large sequence polymorphisms in Mycobacterium tuberculosis
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