Hi-ITS A NOVEL METHOD FOR IDENTIFICATION OF MYCOBACTERIA IN CLINICAL AND ENVIROMENTAL SAMPLES

Introduction: in 2015 Mycobacterium chimaera emerged as a pathogen that contaminates heater-cooler units (HCUs) in operation rooms and causes severe infections in patients. The identification of this pathogen was problematic because of lack of an appropriate kit able to separate it from a genetically close pathogen Mycobacterium intracellulare. Nevertheless, sequencing of the Internal Transcribed Spacer (ITS) gives enough resolution. Utilization of PCR and Sanger sequencing gives poor data for mixed and complex samples.

Method: we developed the Hi-ITS method that allows simultaneous NGS analysis of up to 96 samples. Our method contains the following steps: (1) amplification of the ITS sequences by PCR reactions in a 96 wells plate, (2) barcoding each sample by a second PCR reaction, (3) generation of representative DNA library of all the samples, (4) sequencing by MiSeq nano-run 250X2, (5) bioinformatics analysis by the Galaxy server.

Results: we analyzed 91 human isolates that were identified as M. intracellulare by a commercial kit and another known five Mycobacterium strains. Bioinformatics analysis correctly identified the controls. Interestingly, about 35% of all M. intracellulare samples, specifically from bronchoscopy and sputum samples were identified as M. chimaera. By utilization of Kraken analysis we were able to get information about the microbial composition of each sample. We validated our results with the newly developed GenoType NTM-DR of HAIN with a full match.

Discussion: The Hi-ITS was found to be a robust method that allows high throughput identification of Mycobacteria in clinical and environmental samples. The utilization of Kraken garnered metagenomics information from each sample, including from heavily contaminated and complex samples.