AUTHOR=Haendiges Julie , Timme Ruth , Allard Marc W. , Myers Robert A. , Brown Eric W. , Gonzalez-Escalona Narjol TITLE=Characterization of Vibrio parahaemolyticus clinical strains from Maryland (2012–2013) and comparisons to a locally and globally diverse V. parahaemolyticus strains by whole-genome sequence analysis JOURNAL=Frontiers in Microbiology VOLUME=6 YEAR=2015 URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2015.00125 DOI=10.3389/fmicb.2015.00125 ISSN=1664-302X ABSTRACT=

Vibrio parahaemolyticus is the leading cause of foodborne illnesses in the US associated with the consumption of raw shellfish. Previous population studies of V. parahaemolyticus have used Multi-Locus Sequence Typing (MLST) or Pulsed Field Gel Electrophoresis (PFGE). Whole genome sequencing (WGS) provides a much higher level of resolution, but has been used to characterize only a few United States (US) clinical isolates. Here we report the WGS characterization of 34 genomes of V. parahaemolyticus strains that were isolated from clinical cases in the state of Maryland (MD) during 2 years (2012–2013). These 2 years saw an increase of V. parahaemolyticus cases compared to previous years. Among these MD isolates, 28% were negative for tdh and trh, 8% were tdh positive only, 11% were trh positive only, and 53% contained both genes. We compared this set of V. parahaemolyticus genomes to those of a collection of 17 archival strains from the US (10 previously sequenced strains and 7 from NCBI, collected between 1988 and 2004) and 15 international strains, isolated from geographically-diverse environmental and clinical sources (collected between 1980 and 2010). A WGS phylogenetic analysis of these strains revealed the regional outbreak strains from MD are highly diverse and yet genetically distinct from the international strains. Some MD strains caused outbreaks 2 years in a row, indicating a local source of contamination (e.g., ST631). Advances in WGS will enable this type of analysis to become routine, providing an excellent tool for improved surveillance. Databases built with phylogenetic data will help pinpoint sources of contamination in future outbreaks and contribute to faster outbreak control.