Open AccessMolecular Characterization of Shigella sonnei: An Increasingly Prevalent Etiologic Agent of Shigellosis in Guizhou Province, Southwest of China
Author(s) -
Shijun Li,
Jianping Wang,
Xiaoyu Wei,
Ying Liu,
Long You,
Xia Luo,
Guangpeng Tang,
Qiang Sun,
Changyun Ye,
Jianguo Xu,
Dingming Wang
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0156020
Subject(s) - shigellosis , shigella sonnei , shigella , microbiology and biotechnology , dysentery , china , biology , geography , bacteria , genetics , salmonella , archaeology
Background Shigellosis is a serious problem in Guizhou and Shigella sonnei is an increasingly prevalent etiologic agent of local shigellosis cases. No data, however, are available about the molecular characterization of the local isolates of S . sonnei . We have conducted this study to molecularly characterize the clinical isolates of S . sonnei in Guizhou Province. Results 76 S . sonnei isolates, including four isolates from 1974–1982 and 72 isolates from 2008–2010, were used for analysis in this study. Pulsed-field gel electrophoresis (PFGE) based on XbaI digestion divided the 76 isolates into 38 PFGE patterns (PT) and 15 PTs were represented by more than one isolates with PT31 (N = 8) containing the most number of isolates, followed with PT2 (N = 6). Multiple-Locus Variable number tandem repeat (VNTR) Analysis (MLVA) based on seven VNTR loci discriminated them into 19 different MLVA types (MTs), and four MTs were represented by more than one isolate with MT4 (N = 39) containing the most number of isolates, followed with MT12 (N = 18). 15 Multilocus sequence typing (MLST) base on 15 loci differentiated the isolates into six sequence types (STs), among which four STs were novel. The most common STs are ST76 (N = 43) and ST116 (N = 25), accounting for 92.1%. Correlation between genetic relationships and geographical origins or isolation years was observed among the isolates studied. Majority of isolates were clustered in accordance with the origin of isolation years based on the genetic data, which were also from similar geographical origins. Conclusions Our results revealed the molecular characteristics including the specific genotypes such as four novel STs, clonal relationship, and genetic changes of local isolates from different years, which enhances our understanding of molecular characteristics of S . sonnei and contributes to the prevention and control of shigellosis in Guizhou Province.