High-Res Sequencing Data Differentiates Outbreak Clusters

Whole genome sequencing (WGS) was able to improve discrimination of subclusters of patients as part of an epidemiologic investigation of a 2014 Salmonella outbreak linked to contaminated cucumbers, according to a study published Feb. 20 in Morbidity and Mortality Weekly Report.
A multistate cluster was detected in August 2014 through PulseNet, the national molecular subtyping network for foodborne disease surveillance. The infections, Salmonella enterica serotype Newport infections, were indistinguishable using pulse-field gel electrophoresis (PFGE). But, WGS was able to further characterize PFGE pattern JJPX01.0061 isolates from a subset of 58 clinical specimens taken from the total 275 sickened patients in 29 states and the District of Columbia.
WGS results identified 12 distinct illness subclusters across four states, ranging in size from two to six cases. A primary group of genetically-related isolates was seen from cases in Delaware, Maryland, Ohio, Pennsylvania, and Virginia. Phylogenetic analysis also showed that an additional group of highly-related isolates from patients in New York was distinct from the primary phylogenetic group.
"Advanced molecular detection methods, including WGS, might improve discrimination of subclusters during outbreak investigations," write the authors led by Kristina Angelo, D.O., from the U.S. Centers for Disease Control and Prevention. For more information on how high-resolution data generated from next-generation sequencing (NGS) is being used for pathogen identification, outbreak detection, and infection control efforts, please see Inside the Diagnostics Industry on page 5.