An improved multiple-locus variable number of tandem repeats analysis for Leptospira interrogans serovar Australis: a comparison with fluorescent amplified fragment length polymorphism analysis and its use to redefine the molecular epidemiology of this serovar in Queensland, Australia.

In this study, an improved multiple-locus variable number of tandem repeats analysis (MLVA) method based upon a previously published method is described. Improvements to the method included redesigned primers and PCR conditions, combined with pooled capillary electrophoresis using multicolored dyes. Allele sizes were converted into an allele string, and each unique allele string was assigned a numerical MLVA type (MVT). The improved MLVA method was then applied to 96 previously characterized Leptospira interrogans serovar Australis isolates from human and animal sources. The improved MLVA was found to have between six and 13 alleles at each locus, compared with three to eight in the original. The mean Hunter-Gaston diversity index (HGDI) for the improved MLVA method was 0.654, compared with 0.599 in the original; this increase in diversity was largely due to changes in the analysis of the variable number of tandem repeat (VNTR) data. When the improved MLVA method was compared with the fluorescent amplified fragment length polymorphism (FAFLP) method, there was a high level of concordance between the profiles; however, the MLVA method produced an additional four unique profiles amongst the subset of 30 isolates tested. Given that the improved MLVA method was found to be superior to the original MLVA method, it was subsequently used to redefine the molecular epidemiology of L. interrogans serovar Australis in Queensland, Australia. Using cluster analysis, the authors were able to demonstrate clonal links amongst rodent isolates, rodent and human isolates, and rodent and canine isolates. These results highlight the role of rodents in the disease, and also the potential role of MLVA in defining the molecular epidemiology of L. interrogans.