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Rapid detection of rifampicin, isoniazid and streptomycin resistance in M ycobacterium tuberculosis clinical isolates by high‐resolution melting curve analysis
Author(s) -
Yadav R.,
Sethi S.,
Mewara A.,
Dhatwalia S.K.,
Gupta D.,
Sharma M.
Publication year - 2012
Publication title -
journal of applied microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.889
H-Index - 156
eISSN - 1365-2672
pISSN - 1364-5072
DOI - 10.1111/j.1365-2672.2012.05379.x
Subject(s) - high resolution melt , rpob , melting curve analysis , streptomycin , isoniazid , rifampicin , mycobacterium tuberculosis , drug resistance , biology , tuberculosis , microbiology and biotechnology , gene , polymerase chain reaction , genetics , antibiotics , medicine , pathology
Aims This study was carried out to evaluate high‐resolution melting ( HRM ) curve analysis assay for detection of mutations in three drug resistance–associated genes of M ycobacterium tuberculosis . Methods and Results Clinical isolates of M yco. tuberculosis phenotypically resistant to rifampicin ( n = 29), isoniazid ( n = 35) and streptomycin ( n = 34) were analysed for mutations in rpoB , katG and rpsL genes, respectively, by HRM curve analysis and DNA sequencing. HRM curve assay resulted in 11 clearly distinguishable melt curves denoting eight types of mutations responsible for drug resistance. For the three drugs, respectively, the sensitivity of HRM curve assay was found to be 93·1, 80 and 61·8% compared to the phenotypic resistance patterns, and 93·1, 93·3 and 100% in comparison with the DNA sequencing. Conclusions The sensitivity and specificity of HRM curve assay was found to be comparable to DNA sequencing. The assay offers the advantage of high throughput, single step, rapid work flow and cost effectiveness and can be utilized as a rapid screening method for detection of drug‐resistant tuberculosis. Significance and Impact of the Study HRM curve assay may prove to be an important tool for the development of rapid molecular diagnostic assays for detection of mutation‐based drug resistance.