| Author: | Tulu, Ketema Tafess |
| Title: | Comprehensive characterization of drug-resistant mycobacterium tuberculosis using high throughput sequencing |
| Advisors: | Siu, Gilman (HTI) Leung, H. M. Polly (HTI) |
| Degree: | Ph.D. |
| Year: | 2020 |
| Subject: | Tuberculosis -- Prevention Mycobacterium tuberculosis Multidrug-resistant tuberculosis Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Health Technology and Informatics |
| Pages: | xvi, 323 pages : color illustrations |
| Language: | English |
| Abstract: | Tuberculosis remains a serious public health concern globally. The continued evolution, emergence and spread of Mycobacterium tuberculosis strains with complex drug resistance profiles present a growing threat to public health worldwide. This thesis, therefore, concerned with three major aims 1) Characterisation of the phylogenetic lineages of M. tuberculosis strains 2) Development of targeted sequencing workflows for comprehensive drug resistance profiling using Illumina MiSeq and Nanopore MinION 3) Unveiling the genetic mechanism of stepwise development of INH resistance. In the first part of this thesis, M. tuberculosis isolates (n=115) collected from Ethiopia and Hong Kong were genotyped using standard 24-MIRU-VNTR and analysed with Web-based MIRU-VNTRPlus. Of 115 isolates, 101 (87.8%) were classified into the previously known lineages and 14 (12.2%) were not assigned to any known lineages. Of the 101 isolates, 43 (42.5%) belongs to lineage 4 (Euro-American), 35 (34.7%) lineage 2 (Beijing/East-Asian), 16 (15.8%) lineage 3 (Delhi/CAS) and 7 (6.9%) lineage 1 (Indo-Oceanic/ East Africa Indian). Ethiopia isolates were highly diverse and had deep branching than the Hong Kong isolates. Our study showed the distinct phylogeographic structure of the mycobacterial population in Ethiopia and Hong Kong. In the second part of this thesis, two targeted-sequencing workflows based on Illumina MiSeq and Nanopore MinION for the prediction of drug resistance in M. tuberculosis towards 12 antibiotics were developed. A Web-based bioinformatics pipeline, BacterioChek-TB, was also developed to translate raw sequencing datasets into clinician-friendly reports. The variant calling by MiSeq and MinION could achieve 100% agreement if variants with an allele frequency of <40% reported by MinION were excluded. Both workflows achieved an average sensitivity of 94.8% and specificity of 98.0% when compared with the pDST. The turnaround times for the MiSeq and MinION workflows were 38 and 15 hours, facilitating the delivery of treatment guidance at least 17-18 days earlier than pDST, respectively. Our study demonstrated the interchangeability of MiSeq and MinION platforms for the generation of accurate and actionable results for the treatment of tuberculosis. In the third part of the thesis, genetic mechanisms of stepwise development of INH resistance mechanisms in three M. tuberculosis strains collected from a patient was revealed. As confirmed by phenotypic drug susceptibility test (pDST), pre-treatment M. tuberculosis strain was INH susceptible where post-treatment strains were resistant. MIRU-VNTR and WGS revealed that all three strains were clonally identical. Comprehensive comparative WGS analysis of 19 structural and 2 regulatory genetic regions associated with INH resistance identified a missense katG P232L and a nonsense katG Q461Stop mutations in post-treatment strains. Transformation of the katG from the three strains into isogenic katG knockout M. tuberculosis strain (GA03) has shown that the pre-treatment katG gene restored the catalase activity while transformants containing post-treatment katG remained catalase-negative and had elevated MIC. Further, 3D protein structure indicated P232L reduce INH katG binding affinity and Q461Stop truncate gene transcription, consolidating the in vitro experiments. Our results suggest that the two mutations are associated with INH resistance and the inclusion of these mutations in the design of molecular assays could increase the diagnostic performance. |
| Rights: | All rights reserved |
| Access: | open access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 991022385346303411.pdf | For All Users | 7.96 MB | Adobe PDF | View/Open |
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