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.