Identification of nontuberculous mycobacteria isolated from different clinical samples with DNA sequencing analysis

The aim of the study was to perform identification of non-tuberculous mycobacteria (NTM) isolated from different clinical specimens in the Mycobacteriology Laboratory of Celal Bayar University by using the DNA sequence analysis, which remains the gold standard method, and by targeting hsp65 and 16S rDNA gene regions, and also discuss the epidemiological aspects of the data obtained. Out of 5122 clinical specimens that have been sent to the laboratory with the initial diagnosis of tuberculosis in the period 2007-2011, NTM was identified in 126 (2.46%), and DNA sequence analysis was performed on 101 of these strains. DNA sequence analysis data was evaluated using RIDOM and GenBLAST data bases and consequently, M. porcinum (39.60%), M. lentiflavum (35.64%), M. abscessus (5.64%), M. peregrinum (4.95%), M. gordonae (3.96%), M. fortuitum (2.97%), M. chelonae (1.98%), M. alvei (0.99%), M. scrofulaceum (0.99%) and M kansasii-M. gastritis (0.99%) species were characterized, respectively. Another two strains could not be identified with certainty, although they were both 95-98% compatible with other mycobacteria in the data bases. The other 98 strains examined could not be proven as a cause of the disease, whereas three M. abscessus strains were considered as the cause of the disease. As a result, 99 of 101 NTM strains were successfully identified with the hsp65 gene sequence analysis in addition to 16S rDNA analysis. Distribution of most common NTM strains identified in our laboratory was slightly different according to the regions of our country. The two species most frequently isolated in our study were M. lentiflavum and M. porcinum and should be seriously considered due to their known correlation with human infections and antibiotic resistance. The isolated NTM strains could not be distinguished as the cause of the disease or a contaminant, which is the limiting factor in this study. However, considering the environmental mycobacteria may lead to hospital infections, the data obtained in this study can contribute to epidemiological data pool of NTM infections. Key words: Non-tuberculous mycobacteria, identification, DNA sequence analysis, epidemiology