Date of Award
5-2022
Document Type
Dissertation
Degree Name
Master of Medicine (MMed)
First Supervisor/Advisor
Revathi Gunturu
Second Supervisor/Advisor
Claudia Daunbenberger
Third Supervisor/Advisor
Ali Kassim
Department
Pathology (East Africa)
Abstract
Study background: non-tuberculous mycobacteria (NTM) are members of the genus Mycobacteria that are ubiquitous in the environment. They are increasingly documented to cause multi-drug resistant human and animal infections in immunocompromised as well as immunocompetent hosts and thus, they are a huge burden on public health resources. Diagnosis and treatment of these infections is particularly challenging due to their variable clinical presentation and the lack of easily accessible identification methods. MALDI-TOF MS is a proteomic method that has gained traction in the identification of microbial organisms in clinical practice due to its fast turn-around time, high resolution, and cost-effectiveness but its utility in the identification of NTMs is still an area of ongoing research.
Broad objective: this study aimed to compare the diagnostic performance of MALDI-TOF MS against 16S rRNA sequencing as the gold standard in the identification of a collection of clinical isolates of NTMs in our laboratories in Nairobi and to describe their antimicrobial susceptibility patterns.
Study design and sites: This was a prospective laboratory-based study on clinical isolates that were collected from archived samples at Aga Khan university hospital and National TB reference laboratories, obtained between 2007 and 2021. MALDI-TOF analysis was done at the Kenyatta National hospital laboratory and 16S rRNA and whole genome sequencing at the Basel university Switzerland.
Material and Methods: sixty five archived clinical isolates were revived and analyzed using the VITEK®MS platform. Species identification was done by comparing spectra generated against spectra in the Knowledge base v3.2 database. Sequencing of the 16S rRNA genes was done for the isolates as the gold standard for identification. Resistome analysis was done from whole genome sequencing data using the CARD database.
Data management: Data were input and analyzed using Microsoft excel/ Statistical Package for Social Sciences (SPSS) software.
Results: The study found agreement between MALDI TOF MS and 16S rRNA sequencing at 81.3% for RGM and 80.1% for SGM. Overall, the level of agreement for NTM speciation in this study was at 81%. v MALDI TOF, unlike sequencing, was unable to further classify the NTM isolates up to subspecies level. Chromosomal and mutational resistance genes were found against drugs recommended for first line therapy.
Conclusion: This study showed agreement between MALDI TOF MS and 16S rRNA identification for non-tuberculous mycobacteria. The presence of several molecular markers of resistance is a finding of concern that requires further investigation
Recommended Citation
Kawalya, D. E. (2022). Comparison of maldi-tof ms and 16s rrna sequencing for identification of a collection of clinical isolates of nonntuberculous mycobacteria in Kenya and describing their antimicrobial susceptibilities (Unpublished master's dissertation). Aga Khan University, East Africa.