Determination of Genotypic Diversity of Mycobacterium avium Subspecies from Human and Animal Origins by Mycobacterial Interspersed Repetitive-Unit-Variable-Number Tandem-Repeat and IS1311 Restriction Fragment Length Polymorphism Typing Methods

Members of the Mycobacterium avium complex (MAC) are ubiquitous bacteria that can be found in water, food, and other environmental samples and are considered opportunistic pathogens for numerous animal species, mainly birds and pigs, as well as for humans. We have recently demonstrated the usefulness of a PCR-based mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing for the molecular characterization of M. avium subsp. paratuberculosis and M. avium strains exclusively isolated from AIDS patients. In the present study we extended our analysis, based on eight MIRU-VNTR markers, to a strain collection comprehensively comprising the other M. avium subspecies, including M. avium subsp. avium, M. avium subsp. hominissuis, and M. avium subsp. silvaticum, isolated from numerous animal species, HIV-positive and HIV-negative humans, and environmental sources. All strains were fully typeable, with the discriminatory index being 0.885, which is almost equal to that obtained by IS1311 restriction fragment length polymorphism (RFLP) typing as a reference. In contrast to IS1311 RFLP typing, MIRU-VNTR typing was able to further discriminate M. avium subsp. avium strains. MIRU-VNTR alleles strongly associated with or specific for M. avium subspecies were detected in several markers. Moreover, the MIRU-VNTR typing-based results were consistent with a scenario of the independent evolution of M. avium subsp. avium/M. avium subsp. silvaticum and M. avium subsp. paratuberculosis from M. avium subsp. hominissuis, previously proposed on the basis of multilocus sequence analysis. MIRU-VNTR typing therefore appears to be a convenient typing method capable of distinguishing the three main subspecies and strains of the complex and providing new epidemiological knowledge on MAC.