| Literature DB >> 23932960 |
Vanina Varni1, Paula Ruybal1, Juan José Lauthier2, Nicolás Tomasini2, Bibiana Brihuega3, Ariel Koval4, Karina Caimi5.
Abstract
Leptospirosis is a neglected zoonosis of global importance. Several multilocus sequence typing (MLST) methods have been developed for Leptospira spp., the causative agent of leptospirosis. In this study we reassessed the most commonly used MLST schemes in a set of worldwide isolates, in order to select the loci that achieve the maximum power of discrimination for typing Leptospira spp. Global eBURST algorithm was used to detect clonal complexes among STs and phylogenetic relationships among concatenated and individual sequences were inferred through maximum likelihood (ML) analysis. The evaluation of 12 loci combined to type a subset of strains rendered 57 different STs. Seven of these loci were selected into a final scheme upon studying the number of alleles and polymorphisms, the typing efficiency, the discriminatory power and the ratio dN/dS per nucleotide site for each locus. This new 7-locus scheme was applied to a wider collection of worldwide strains. The ML tree constructed from concatenated sequences of the 7 loci identified 6 major clusters corresponding to 6 Leptospira species. Global eBURST established 8 CCs, which showed that genotypes were clearly related by geographic origin and host. ST52 and ST47, represented mostly by Argentinian isolates, grouped the higher number of isolates. These isolates were serotyped as serogroups Pomona and Icterohaemorrhagiae, showing a unidirectional correlation in which the isolates with the same ST belong to the same serogroup. In summary, this scheme combines the best loci from the most widely used MLST schemes for Leptospira spp. and supports worldwide strains classification. The Argentinian isolates exhibited congruence between allelic profile and serogroup, providing an alternative to serological methods. Published by Elsevier B.V.Entities:
Keywords: Leptospira spp.; Multilocus sequence typing; Reassessment
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Year: 2013 PMID: 23932960 DOI: 10.1016/j.meegid.2013.08.002
Source DB: PubMed Journal: Infect Genet Evol ISSN: 1567-1348 Impact factor: 3.342