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The emergence of multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) strains is a major health problem for high Tuberculosis (TB) incidence countries. Therefore, it is of interest to identify antibiotic resistant bacteria by mismatch detection using DNA hybridization. We generated PCR products for five genes (rpoB, inhA, katG, gyrA and rrs) associated with drug resistance TB from MDR and XDR Mycobacterium tuberculosis (MTB) DNA samples. These were hybridized to PCR products from MTB H37Rv (pansusceptible laboratory strain) to generate DNA hetero-duplex products, which was digested by Detection Enzyme (GeneArt Genomic Cleavage Detection Kit) and visualized by agarose gel electrophoresis. Results show different bands with sizes of 400 bp and 288 bp (rpoB), 280 bp (inhA), 310 bp (katG), 461 bp (gyrA) and 427 bp (rrs) suggesting mutations in DNA heteroduplex for each gene. Detection Enzyme specifically cleaves DNA hetero-duplex with mismatch. The technique helps in the improved detection of MDR (mutations in rpoB, inhA and katG) and XDR (mutations in rpoB, inhA katG, gyrA and rrs) MTB strains. Moreover, the technique is customized without expensive specialized equipment to detect mutations. It is also fast, efficient and easy to implement in standard molecular biology laboratories.

Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis (TB), has a vast diversity of genotypes including Beijing, CAS, EAI, Haarlem, LAM, X, Ural, T, AFRI1 and AFRI2. However, genotyping can be expensive, time consuming and in some cases, results may vary depending on methodology used. Here, we proposed a new set of 10 SNPs using a total of 249 MTB genomes, and selected by first the inclusion/ exclusion (IE) criteria using spoligotyping and phylogenies, followed by the selection of the nonsynonymous SNPs present in the most conserved cluster of orthologous groups (COG) of each genotype of MTB. Genotype assignment of the new set of 10 SNPs was validated using an additional of 34 MTB genomes and results showed 100% correlation with their known genotypes. Our set of 10 SNPs have not been previously reported and cover the MTB genotypes that are prevalent worldwide. This set of SNPs could be used for molecular epidemiology with drug resistant markers.