Multiple-locus variable-number tandem repeat analysis for molecular typing of Aspergillus fumigatus

BACKGROUND: Multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA) is a prominent subtyping method to resolve closely related microbial isolates to provide information for establishing genetic patterns among isolates and to investigate disease outbreaks. The usefulness of MLVA was recently demonstrated for the avian major pathogen Chlamydophila psittaci. In the present study, we developed a similar method for another pathogen of birds: the filamentous fungus Aspergillus fumigatus. RESULTS: We selected 10 VNTR markers located on 4 different chromosomes (1, 5, 6 and 8) of A. fumigatus. These markers were tested with 57 unrelated isolates from different hosts or their environment (53 isolates from avian species in France, China or Morocco, 3 isolates from humans collected at CHU Henri Mondor hospital in France and the reference strain CBS 144.89). The Simpson index for individual markers ranged from 0.5771 to 0.8530. A combined loci index calculated with all the markers yielded an index of 0.9994. In a second step, the panel of 10 markers was used in different epidemiological situations and tested on 277 isolates, including 62 isolates from birds in Guangxi province in China, 95 isolates collected in two duck farms in France and 120 environmental isolates from a turkey hatchery in France. A database was created with the results of the present study http://minisatellites.u-psud.fr/MLVAnet/. Three major clusters of isolates were defined by using the graphing algorithm termed Minimum Spanning Tree (MST). The first cluster comprised most of the avian isolates collected in the two duck farms in France, the second cluster comprised most of the avian isolates collected in poultry farms in China and the third one comprised most of the isolates collected in the turkey hatchery in France. CONCLUSIONS: MLVA displayed excellent discriminatory power. The method showed a good reproducibility. MST analysis revealed an interesting clustering with a clear separation between isolates according to their geographic origin rather than their respective hosts.