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Multiplex PCR Assay for Typing of Staphylococcal Cassette Chromosome Mec Types I to V in Methicillin-resistant Staphylococcus aureus
Published on: September 5, 2013
Molecular typing and differentiation of Mycobacterium tuberculosis clinical isolates using Double Repetitive Element
Kathirvel Maruthai1, Thirumurugan Ravibalan2, Kommoju Vallayyachari1
1Department of Microbiology, Intermediate Reference Laboratory, Government Hospital for Chest Diseases, Gorimedu, Puducherry 605006, India.
Background:
To date, the advancements in polymerase chain reaction (PCR) assures accurate, fast identification and mycobacterial speciation in clinical settings, which promotes a better tuberculosis (TB) treatment regimen.
Methods:
In this study, a total of 78 clinically suspected cases of TB were processed for the detection of Mycobacterial infections by standard Ziehl Neelsen (ZN) staining, conventional Lowenstein-Jensen (LJ) and BACTEC MGIT-960™ liquid culture. Strain typing was performed by using Double Repetitive Element PCR (DRE-PCR) and Duplex PCR (DPCR) to differentiate Mycobacterium tuberculosis complex (MTB) from non-tuberculous mycobacteria (NTM), respectively.
Results:
Of 78 clinical isolates, 25 (32%) were drug-susceptible, and 53 (68%) were resistant to at least one drug. The BACTEC MGIT-960™ showed the highest (88.5%) positivity rate, compared with conventional LJ (82%) and ZN smear (61.5%). The mean time detection and drug susceptibility for MTB was 28 and 40days in LJ culture, and 10 and 13 days in BACTEC MGIT-960™ culture. Using DPCR, Mycobacterium avium infection was identified in HIV-positive (2.56%) and MTB in HIV-negative patients (97.4%), and the DRE-PCR system divulged 15 unique genotype patterns, and an institutional-based epidemiology database was created.
Conclusions:
The combination of an in-house DRE-DPCR system could possibly identify and differentiate MTB from other mycobacterial species in a single reaction. In addition, restriction polymorphism analysis and DNA sequencing of NTM could assist in species identification directly from clinical isolates.
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