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Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data

Dissertation (MSc)--University of Pretoria, 2019.

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Other Authors: Reva, Oleg N.
Format: Thesis
Language:English
Published: University of Pretoria 2020
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access_status_str Open Access
author2 Reva, Oleg N.
author_browse Reva, Oleg N.
author_facet Reva, Oleg N.
collection Thesis
dc_rights_str_mv © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Dissertation (MSc)--University of Pretoria, 2019.
format Thesis
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:37:44.604Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2020
publishDateRange 2020
publishDateSort 2020
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/77865 Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data Reva, Oleg N. u17288632@tuks.co.za Muzondiwa, Dillon UCTD Mycobacterium tuberculosis (MTB) Antibiotic resistance (ABR) Whole-genome sequencing (WGS) Dissertation (MSc)--University of Pretoria, 2019. Mycobacterium tuberculosis (Mtb) remains a global challenge that has been worsened by the emergence of drug resistant strains of Mtb. We used publicly available Next Generation Sequencing (NGS) and drug susceptibility (DST) data to develop “Resistance sniffer”, an online software program for the rapid prediction of lineage and Mtb drug resistance. Based on the distribution of polymorphisms in the genomes of Mtb, we calculated the power of association between the polymorphisms in different clades of Mtb and resistance to 13 anti-TB drugs. Our data suggests that the development of drug resistance in Mtb is a stepwise process that involves the accumulation of polymorphisms in the Mtb genome. We carefully curated the polymorphisms based on their association powers to create a diagnostic key that captures patterns of these polymorphisms that can be used to predict lineage and drug resistance in Mtb. This diagnosis key was incorporated into the Resistance Sniffer tool, an online software program that we developed for the rapid diagnosis of drug resistance in Mtb. The tool was tested using sequence data from the South Africa Medical Research Council (SA-MRC). Our data suggests that the majority of the strains in SA may have been brought by the arrival of European settlers while the more resistant strains may have been introduced in the region by Asian travellers later on. We next sought to determine non-random associations between polymorphic sites in genomes of Mtb. Using the attributable risk (Ra) statistical methods, we distinguished between functional associations and associations that may have been due to genetic drift events for different Mtb clades. We then integrated the (Ra) data with drug susceptibility and annotation data to generate networks in Cytoscape 3.71. These networks were then used to infer evolutionary trajectories that drive the emergence and fixation of the drug resistant phenotype in different clades of Mtb. We demonstrate that strains from the Lineage 1.2 are associated with less complex functional associations compared to the strains from other clades such as the Asian and Euro-American clades. Our data also shows that the predisposition of strains from the Asian clades to develop multi-drug resistance may be attributed to a complex network of functional interactions of mutations in genes that are involved in several aspects of Mtb physiology such as cell wall modelling, lipid metabolism, stress response and DNA repair. Biochemistry MSc Unrestricted 2020-12-29T11:50:59Z 2020-12-29T11:50:59Z 2020/04/30 2019 Dissertation Muzondiwa, D 2019, Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/77865> A2020 http://hdl.handle.net/2263/77865 en © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Mycobacterium tuberculosis (MTB)
Antibiotic resistance (ABR)
Whole-genome sequencing (WGS)
Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data
title Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data
title_full Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data
title_fullStr Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data
title_full_unstemmed Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data
title_short Exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data
title_sort exploring the evolution of drug resistance in mycobacterium using whole genome sequencing data
topic UCTD
Mycobacterium tuberculosis (MTB)
Antibiotic resistance (ABR)
Whole-genome sequencing (WGS)
url http://hdl.handle.net/2263/77865