Efficient differentiation of Mycobacterium avium complex species and subspecies by use of five-target multiplex PCR.
Ontology highlight
ABSTRACT: Infections caused by the Mycobacterium avium complex (MAC) are on the rise in both human and veterinary medicine. A means of effectively discriminating among closely related yet pathogenetically diverse members of the MAC would enable better diagnosis and treatment as well as further our understanding of the epidemiology of these pathogens. In this study, a five-target multiplex PCR designed to discriminate MAC organisms isolated from liquid culture media was developed. This MAC multiplex was designed to amplify a 16S rRNA gene target common to all Mycobacterium species, a chromosomal target called DT1 that is unique to M. avium subsp. avium serotypes 2 and 3, to M. avium subsp. silvaticum, and to M. intracellulare, and three insertion sequences, IS900, IS901, and IS1311. The pattern of amplification results allowed determination of whether isolates were mycobacteria, whether they were members of the MAC, and whether they belonged to one of three major MAC subspecies, M. avium subsp. paratuberculosis, M. avium subsp. avium, and M. avium subsp. hominissuis. Analytical sensitivity was 10 fg of M. avium subsp. paratuberculosis genomic DNA, 5 to 10 fg of M. avium subsp. avium genomic DNA, and 2 to 5 fg of DNA from other mycobacterial species. Identification accuracy of the MAC multiplex was evaluated by testing 53 bacterial reference strains consisting of 28 different mycobacterial species and 12 nonmycobacterial species. Identification accuracy in a clinical setting was evaluated for 223 clinical MAC isolates independently identified by other methods. Isolate identification agreement between the MAC multiplex and these comparison assays was 100%. The novel MAC multiplex is a rapid, reliable, and simple assay for discrimination of MAC species and subspecies in liquid culture media.
SUBMITTER: Shin SJ
PROVIDER: S-EPMC3020869 | biostudies-literature | 2010 Nov
REPOSITORIES: biostudies-literature
ACCESS DATA
