P3-01 Whole Genome Sequencing Provides Rapid Traceback of Clinical to Food Sources during a Foodborne Outbreak of Salmonellosis

Tuesday, July 28, 2015
Hall B (Oregon Convention Center)
Maria Hoffmann, U.S. Food and Drug Administration, College Park, MD
Yan Luo, U.S. Food and Drug Administration, College Park, MD
Steven Monday, U.S. Food and Drug Administration, College Park, MD
Tim Muruvanda, U.S. Food and Drug Administration, College Park, MD
Daniel Janies, University North Carolina, Charlotte, NC
Izzet Senturk, Ohio State University, Columbus, OH
Umit Catalyurek, Ohio State University, Columbus, OH
William Wolfgang, New York State Department of Health, Albany, NY
Robert Myers, Department of Health and Mental Hygiene, Baltimore, MD
Peter Evans, U.S. Food and Drug Administration, College Park, MD
Jianghong Meng, University of Maryland, College Park, MD
Marc Allard, U.S. Food and Drug Administration-CFSAN, College Park, MD
Eric Brown, U.S. Food and Drug Administration-CFSAN, College Park, MD
Introduction: Salmonella serovar Bareilly is responsible for numerous outbreaks among humans. In 2012 a widespread foodborne outbreak associated with scraped tuna imported from India occurred in the United States.

Purpose: A comparative genomic analysis within the serovar was performed to explore, on a global scale, how effectively whole-genome sequencing (WGS) can differentiate outbreak isolates of Salmonella Bareilly from non-outbreak isolates sharing the same Xbal PFGE pattern.

Methods: We sequenced, on different platforms, 100 Salmonella Bareilly isolates including 41 isolates from the 2012 outbreak. A single isolate was sequenced on the Pacific Biosciences RS II Sequencer to determine the first complete genome sequence of Salmonella Bareilly that served as the reference genome. Subsequent raw reads were mapped to this reference genome to build a single-nucleotide polymorphism (SNP) matrix and construct a phylogenetic tree. Pathogen genomes were linked with geography by projecting the phylogeny on a virtual globe. Using the phylogenetic tree and the pathogen metadata a transmission network was reconstructed for Salmonella Bareilly.

Results: Using SNP analyses, we were able to distinguish and separate highly clonal Salmonella Bareilly strains sharing the same XbaI PFGE pattern. The isolates from the recent 2012 outbreak clustered together, sharing only a few SNPs differences between them. Our results revealed a common origin for the outbreak strains, indicating that the patients in the U.S. were infected from sources originating at the India facility. In addition, we identified a unique arsenic resistance operon carried by many of these strains.

Significance: Our data strongly suggests that WGS, combined with geographic mapping and the novel use of transmission networks for genetic data, vastly improves the rapid source tracking and surveillance of a bacterial outbreak that are critically important for characterizing outbreak dynamics and, ultimately, protection of the public health.