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Defining the Phylogenomics of Shigella Species: a Pathway to Diagnostics
Author(s) -
Jason W. Sahl,
Carolyn R. Morris,
Jennifer Emberger,
Claire M. Fraser,
John B. Ochieng,
Jane Juma,
Barry S. Fields,
Robert F. Breiman,
Matthew W. Gilmour,
James P. Nataro,
David A. Rasko
Publication year - 2015
Publication title -
journal of clinical microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.349
H-Index - 255
eISSN - 1070-633X
pISSN - 0095-1137
DOI - 10.1128/jcm.03527-14
Subject(s) - shigella , biology , shigellosis , shigella dysenteriae , clade , shigella boydii , shigella flexneri , amplicon , phylogenomics , genetics , genome , microbiology and biotechnology , pseudogene , polymerase chain reaction , phylogenetics , virology , escherichia coli , gene
Shigellae cause significant diarrheal disease and mortality in humans, as there are approximately 163 million episodes of shigellosis and 1.1 million deaths annually. While significant strides have been made in the understanding of the pathogenesis, few studies on the genomic content of the Shigella species have been completed. The goal of this study was to characterize the genomic diversity of Shigella species through sequencing of 55 isolates representing members of each of the four Shigella species: S. flexneri, S. sonnei, S. boydii, and S. dysenteriae. Phylogeny inferred from 336 available Shigella and Escherichia coli genomes defined exclusive clades of Shigella; conserved genomic markers that can identify each clade were then identified. PCR assays were developed for each clade-specific marker, which was combined with an amplicon for the conserved Shigella invasion antigen, IpaH3, into a multiplex PCR assay. This assay demonstrated high specificity, correctly identifying 218 of 221 presumptive Shigella isolates, and sensitivity, by not identifying any of 151 diverse E. coli isolates incorrectly as Shigella. This new phylogenomics-based PCR assay represents a valuable tool for rapid typing of uncharacterized Shigella isolates and provides a framework that can be utilized for the identification of novel genomic markers from genomic data.

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