Hristea A, Otelea D, Paraschiv S, Macri A, Baicus C, Moldovan O, Tinischi M, Arama V, Streinu-Cercel A
Prof Dr Matei Bals National Institute for Infectious Diseases, Str Calistrat Grozovici, Nr 1, Sector 2, 021105 Bucharest, Romania.
Indian J Med Microbiol. 2010 Jul-Sep;28(3):211-6. doi: 10.4103/0255-0857.66474.
The objective of our study was to evaluate the use of a real-time polymerase chain reaction (PCR)-based technique for the prediction of phenotypic resistance of Mycobacterium tuberculosis.
We tested 67 M tuberculosis strains (26 drug resistant and 41 drug susceptible) using a method recommended for the LightCycler platform. The susceptibility testing was performed by the absolute concentration method. For rifampin resistance, two regions of the rpoB gene were targeted, while for identification of isoniazid resistance, we searched for mutations in katG and inhA genes.
The sensitivity and specificity of this method for rapid detection of mutations for isoniazid resistance were 96% (95% CI: 88% to 100%) and 95% (95% CI: 89% to 100%), respectively. For detection of rifampin resistance, the sensitivity and specificity were 92% (95% CI: 81% to 100%) and 74% (95% CI: 61% to 87%), respectively. The main isoniazid resistance mechanism identified in our isolates is related to changes in the katG gene that encodes catalase. We found that for rifampin resistance the concordance between the predicted and observed phenotype was less than satisfactory.
Using this method, the best accuracy for genotyping compared with phenotypic resistance testing was obtained for detecting isoniazid resistance mutations. Although real-time PCR assay may be a valuable diagnostic tool, it is not yet completely satisfactory for detection of drug resistance mutations in M tuberculosis.
我们研究的目的是评估基于实时聚合酶链反应(PCR)的技术在预测结核分枝杆菌表型耐药性方面的应用。
我们使用推荐用于LightCycler平台的方法对67株结核分枝杆菌菌株(26株耐药和41株敏感)进行了检测。药敏试验采用绝对浓度法进行。对于利福平耐药性,靶向rpoB基因的两个区域,而对于异烟肼耐药性的鉴定,我们搜索katG和inhA基因中的突变。
该方法快速检测异烟肼耐药性突变的敏感性和特异性分别为96%(95%置信区间:88%至100%)和95%(95%置信区间:89%至100%)。对于利福平耐药性的检测,敏感性和特异性分别为92%(95%置信区间:81%至100%)和74%(95%置信区间:61%至87%)。在我们分离的菌株中鉴定出的主要异烟肼耐药机制与编码过氧化氢酶的katG基因的变化有关。我们发现,对于利福平耐药性,预测表型与观察到的表型之间的一致性不太令人满意。
使用该方法,与表型耐药性检测相比,在检测异烟肼耐药性突变时获得了最佳的基因分型准确性。虽然实时PCR检测可能是一种有价值的诊断工具,但在检测结核分枝杆菌的耐药性突变方面尚未完全令人满意。