Typhoidal Salmonellae: Use of Multi-Locus Sequence Typing to Determine Population Structure

Citation: Sharma P, Dahiya S, Balaji V, Kanga A, Panda P, Das R, et al. (2016) Typhoidal Salmonellae: Use of Multi-Locus Sequence Typing to Determine Population Structure. PLoS ONE 11(9): e0162530. doi:10.1371/journal.pone.0162530
Published: September 12, 2016

Abstract
Enteric fever is an invasive infection predominantly caused by Salmonella enterica serovars Typhi and Paratyphi A. The pathogens have evolved from other nontyphoidal salmonellaeto become invasive and host restricted. Emergence of antimicrobial resistance in typhoidal salmonellae in some countries is a major therapeutic concern as the travelers returning from endemic countries carry resistant strains to non endemic areas. In order to understand the epidemiology and to design disease control strategies molecular typing of the pathogen is very important. We performed Multilocus Sequence Typing (MLST) of 251 S. Typhi and 18 S. Paratyphi strains isolated from enteric fever patients from seven centers across India during 2010-2013to determine the population structure and prevalence of MLST sequence types in India. MLST analysis revealed the presence of five sequence types (STs) of typhoidal salmonellae in India namely ST1, ST2 and ST3 for S. Typhi and ST85 and ST129 for S. Paratyphi A.S. Typhi strains showed monophyletic lineage and clustered in to 3 Sequence Types—ST1, ST2 and ST3 and S. Paratyphi A isolates segregated in two sequence types ST85 and ST129 respectively. No association was found between antimicrobial susceptibility and sequence types. This study found ST1 as the most prevalent sequence type of S. Typhi in India followed by ST2, which is in concordance with previous studies and MLST database. In addition a rare sequence type ST3 has been found which is reported for the first time from the Indian subcontinent. Amongst S. Paratyphi A, the most common sequence type is ST129 as also reported from other parts of world. This distribution and prevalence suggest the common spread of the sequence types across the globe and these findings can help in understanding the disease distribution.

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