Epidemiology and prevalence analysis of NTM using 16s rRNA in Johor

Abstract

The geographical distribution of nontuberculous mycobacteria (NTM) in Malaysia is unknown, however the number of cases reported is markedly increasing. Furthermore, the current Standard Operation Procedure for diagnose is time consuming and not up to the species level. This may lead to prolonged treatment, mistreatment with current Tuberculosis regime and perhaps may create multidrug resistant strains. Therefore, a new method is urgently needed to replace current identification analysis. The goal of this study was to determine the prevalence of clinical NTM cases in Johor, Malaysia using the current procedure and Runyon classification, investigate potential sources of NTM from a specific geographic area using both 16S rRNA sequencing and Runyon classification and construct a phylogenetic tree of Malaysia NTM based on species. The data was analyzed from mycobacterial cultures of sputum specimens collected from Johor Public Health Laboratory from 2011 to 2014. Water samples were collected from sputum collection center in selected Health Clinics in Johor and subjected to NTM identification analysis to investigate the potential origins of NTM. The phylogenetic tree was constructed using molecular sequencing by using MEGA-X software. In this present study, analysis of the NTM cases in Johor from year 2011 to 2014 increased with age and gender-related where male and individual of 61 years old and above are more likely to be infected respectively. Furthermore, Johor Bahru was more likely to record higher cases. There were differences in the findings from the same sources and sample collected geographically when grouped by Runyon and 16S rRNA. The Runyon classification method produced a false positive result on pathogenicity on rapidly growing NTM when compared to 16S rRNA. The precision of Runyon classification method on pathogenicity of slow grower was less. In conclusion the prevalence of NTM data for Johor were compiled and 16S rRNA sequencing was more precise in diagnosing the NTM up to the species level.