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Rapid whole-genome sequencing for surveillance of salmonella enterica serovar Enteritidis

  • Henk C. den Bakker
  • , Marc W. Allard
  • , Dianna Bopp
  • , Eric W. Brown
  • , John Fontana
  • , Zamin Iqbal
  • , Aristea Kinney
  • , Ronald Limberger
  • , Kimberlee A. Musser
  • , Matthew Shudt
  • , Errol Strain
  • , Martin Wiedmann
  • , William J. Wolfgang

Research output: Contribution to journalArticlepeer-review

Abstract

For Salmonella enterica serovar Enteritidis, 85% of isolates can be classified into 5 pulsed-field gel electrophoresis (PFGE) types. However, PFGE has limited discriminatory power for outbreak detection. Although whole-genome sequencing has been found to improve discrimination of outbreak clusters, whether this procedure can be used in real-time in a public health laboratory is not known. Therefore, we conducted a retrospective and prospective analysis. The retrospective study investigated isolates from 1 confirmed outbreak. Additional cases could be attributed to the outbreak strain on the basis of whole-genome data. The prospective study included 58 isolates obtained in 2012, including isolates from 1 epidemiologically defined outbreak. Whole-genome sequencing identified additional isolates that could be attributed to the outbreak, but which differed from the outbreak-associated PFGE type. Additional putative outbreak clusters were detected in the retrospective and prospective analyses. This study demonstrates the practicality of implementing this approach for outbreak surveillance in a state public health laboratory.

Original languageEnglish (US)
Pages (from-to)1306-1314
Number of pages9
JournalEmerging infectious diseases
Volume20
Issue number8
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Microbiology (medical)
  • Infectious Diseases

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