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A Two-Step Strategy for Molecular Typing of Multidrug-Resistant Mycobacterium tuberculosis Clinical Isolates from Poland
Author(s) -
Tomasz Jagielski,
Ewa AugustynowiczKopeć,
Krzysztof Pawlik,
Jarosław Dziadek,
Zofia Zwolska,
Jacek Bielecki
Publication year - 2011
Publication title -
polish journal of microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.312
H-Index - 34
eISSN - 2544-4646
pISSN - 1733-1331
DOI - 10.33073/pjm-2011-033
Subject(s) - subtyping , typing , genotyping , mycobacterium tuberculosis , tuberculosis , biology , rifampicin , molecular epidemiology , virology , multiple drug resistance , polymerase chain reaction , drug resistance , microbiology and biotechnology , genotype , genetics , medicine , antibiotics , gene , pathology , computer science , programming language
Tuberculosis (TB) continues to be one of the most challenging public health problems in the world. An important contributor to the global burden of the disease is the emergence and spread of drug-resistant and particularly multidrug-resistant Mycobacterium tuberculosis strains (MDR), defined as being resistant to at least isoniazid and rifampicin. In recent years, the introduction of different DNA-based molecular typing methods has substantially improved the knowledge of the epidemiology of TB. The purpose of this study was to employ a combination of two PCR-based genotyping methods, namely spoligotyping and IS6110-Mtb1/Mtb2 PCR to investigate the clonal relatedness of MDR M. tuberculosis clinical isolates recovered from pulmonary TB patients from Poland. Among the 50 isolates examined, 28 (56%) were clustered by spoligotyping, whereas IS6110-Mtb1/Mtb2 PCR resulted in 16 (32%) clustered isolates. The isolates that clustered in both typing methods were assumed to be clonally related. A two-step strategy consisting of spoligotyping as a first-line test, performed on the entire pool of isolates, and IS6110-Mtb1/Mtb2 PCR typing as a confirmatory subtyping method, performed only within spoligotype-defined clusters, is an efficient approach for determining clonal relatedness among M. tuberculosis clinical isolates.

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