Kathirvel Maruthai1, Thirumurugan Ravibalan2, Kommoju Vallayyachari3, Surendar Kesavan4, Antony V Samrot5, Muthuraj Muthaiah6. 1. Department of Microbiology, Intermediate Reference Laboratory, Government Hospital for Chest Diseases, Gorimedu, Puducherry 605006, India. Electronic address: katkin14@gmail.com. 2. Department of Microbiology, Intermediate Reference Laboratory, Government Hospital for Chest Diseases, Gorimedu, Puducherry 605006, India; Department of Biotechnology, Sathyabama University, Chennai 600119, Tamilnadu, India. Electronic address: thirumuruganphd@gmail.com. 3. Department of Microbiology, Intermediate Reference Laboratory, Government Hospital for Chest Diseases, Gorimedu, Puducherry 605006, India. Electronic address: k.vallayyachari@gmail.com. 4. Department of Microbiology, Intermediate Reference Laboratory, Government Hospital for Chest Diseases, Gorimedu, Puducherry 605006, India. Electronic address: surenmicro39@gmail.com. 5. Department of Biotechnology, Sathyabama University, Chennai 600119, Tamilnadu, India. Electronic address: antonysamrot@gmail.com. 6. Department of Microbiology, Intermediate Reference Laboratory, Government Hospital for Chest Diseases, Gorimedu, Puducherry 605006, India. Electronic address: stdcirlpdy@gmail.com.
Abstract
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.
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 aviuminfection 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.
Authors: Grace Muzanyi; Y Mulumba; Paul Mubiri; Harriet Mayanja; John L Johnson; Ezekiel Mupere Journal: Afr Health Sci Date: 2019-06 Impact factor: 0.927