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dc.contributor.advisorBalagaddé, Frederick.
dc.creatorMandizvo, Tawanda.
dc.date.accessioned2017-06-21T07:59:46Z
dc.date.available2017-06-21T07:59:46Z
dc.date.created2015
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10413/14598
dc.descriptionMaster of Medical Science in Medical Microbiology. University of KwaZulu-Natal, Medical School 2015.en_US
dc.description.abstractBackground: A number of Mycobacterium tuberculosis (Mtb) genes have been shown to be under positive selection pressure in the presence of anti-TB therapy. This results in the selection of drug resistant phenotypes associated with genetic changes—which can be point mutations, deletions and/or insertions. Some mutations from multiple genes have been documented to be associated with reduced susceptibility to anti-TB drugs such as rifampicin, ethambutol, carpreomycin and fluoroquinolones. The list is continuously updated as new mutations are discovered and validated. In principle therefore, there is an urgent need to design robust molecular diagnostics and more efficacious therapeutic strategies that are able to indicate diverse genetic mechanisms behind drug resistance in individual isolates Materials and Methods: We used the LightForge system we developed at K-RITH. This LightForge system is a fluorescence detection based, highly scalable microfluidic platform. It interrogates Mycobacterium tuberculosis strains using Real-Time PCR and High Resolution Melt Analysis (HRMA) on a chip. Results and Discussion: We have used this LightForge system to identify clinical Mtb strains resistant to rifampicin—a frontline drug used to treat tuberculosis, relative to a susceptible strain H37RV, based on mutations in the rpoB gene. This system has the potential to contribute towards a low-cost solution to diagnosis of multidrug resistant tuberculosis—a current critical global healthcare challenge. The interrogation of clinical Mtb isolates—including R35, KZN 605 and Tkk 01-062—using the LightForge system has detected mutations linked to rifampicin resistance including single nucleotide polymorphisms (SNPs) in a congruous manner with commercial systems. Conclusions: In preparation for diagnosis of clinical samples, this LightForge approach is now being expanded to incorporate detection of genetic markers linked with resistance to other TB drugs that include fluoroquinolones and isoniazid based on mutations in gyrA, katG and Mab-inhA regions of the Mtb genome. The scalability of LightForge can also be harnessed to conduct digital PCR (dPCR), a critical tool for detecting genetic heterogeneity in Mtb.en_US
dc.language.isoen_ZAen_US
dc.subjectMycobacterium tuberculosis.en_US
dc.subjectMedical technology.en_US
dc.subjectPolymerase chain reaction.en_US
dc.subjectMicrofluidics.en_US
dc.subjectTheses -- Medical microbiology.en_US
dc.subjectHigh resolution melting analysis (HRMA)en_US
dc.titleMicrofluidic technologies for genomic interrogation of mycobacterium tuberculosis clinical isolates using the polymerase chain reaction (PCR) and high resolution melting analysis (HRMA).en_US
dc.typeThesisen_US


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