Developing customized stepwise MIRU-VNTR typing for tuberculosis surveillance in Georgia

PLOS ONE(2022)

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摘要
Introduction Mycobacterial Interspersed Repetitive Units-Variable Tandem Repeats (MIRU-VNTR) typing has been widely used for molecular epidemiological studies of tuberculosis (TB). However, genotyping tools for Mycobacterium tuberculosis (Mtb) may be limiting in some settings due to high cost and workload. In this study developed a customized stepwise MIRU-VNTR typing that prioritizes high discriminatory loci and validated this method using penitentiary system cohort in the country of Georgia. Methods We used a previously generated MIRU-VNTR dataset from recurrent TB cases (32 cases) in Georgia and a new dataset of TB cases from the penitentiary system (102 cases) recruited from 2014 to 2015. A Hunter-Gaston Discriminatory Index (HGDI) was calculated utilizing a 24 standard loci panel, to select high discriminatory power loci, subsequently defined as the customized Georgia-specific set of loci for initial typing. The remaining loci were scored and hierarchically grouped for second and third step typing of the cohort. We then compared the processing time and costs of the customized stepwise method to the standard 24-loci method. Results For the customized Georgia-specific set that was used for initial typing, 10 loci were selected with a minimum value of 0.32 to the highest HGDI score locus. Customized 10 loci (step 1) typing of 102 Mtb patient isolates revealed 35.7% clustered cases. This proportion was reduced to 19.5% after hierarchical application of 2nd and 3rd step typing with the corresponding groups of loci. Our customized stepwise MIRU-VNTR genotyping approach reduced the quantity of samples to be typed and therefore overall processing time and costs by 42.6% each. Conclusion Our study shows that our customized stepwise MIRU-VNTR typing approach is a valid alternative of standard MIRI-VNTR typing panels for molecular epidemiological investigation in Georgia that saves time, workload and costs. Similar approaches could be developed for other settings.
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