Browsing by Author "Da Camara, Ncite Lima"

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    Targeted deep sequencing to detect heterogeneity in Mycobacterium tuberculosis populations
    (Stellenbosch : Stellenbosch University, 2017-03) Da Camara, Ncite Lima; De Vos, Margaretha; Dippenaar, Anzaan; Warren, Robin Mark; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Biomedical Sciences: Molecular Biology and Human Genetics.
    ENGLISH ABSTRACT: Antibiotic resistance in Mycobacterium tuberculosis is a worldwide problem as it drastically affects patient treatment outcome. The development of drug resistance is due to the acquisition of mutations in drug resistance conferring genes. Early detection of drug resistance is vital to improve patient therapy and prevent the transmission of drug resistant strains. It is therefore important to develop a method that is able to accurately detect minority variants conferring drug resistance to prevent treatment failure. The aim of this study was to develop an ultrasensitive method to detect underlying resistance causing variants in specific M. tuberculosis fluoroquinolone resistance causing genes (gyrA and gyrB). Efficient primer sets were used to amplify the quinolone resistance-determining region of gyrA and gyrB. Targeted deep sequencing was done using the Ion Torrent Personal Genome Machine (PGM) and Illumina MiSeq platforms and sequencing data were analysed using the appropriate bioinformatics tools for the respective platforms. The method was validated using synthetic heterogeneous mixtures and was subsequently applied to identify underlying variants in patient isolates showing the acquisition of fluoroquinolone resistance. The Illumina MiSeq platform was shown to be superior to the Ion Torrent PGM platform as it accurately detected the correct proportion of mutant DNA to a minimum frequency of 0.1%. We also showed that targeted deep sequencing is sensitive and able to detect underlying variants emerging and fluctuating during the evolution of fluoroquinolone resistance. These results show great promise for the development of an ultrasensitive diagnostic method for the early detection of fluoroquinolone resistance that could ultimately be used to improve the tuberculosis control program.