T10-02 Molecular Subtyping of a Large Collection of Historical Listeria monocytogenes Strains Using an Improved Multiple-Locus Variable-Number Tandem Repeat Analysis (MLVA)

Wednesday, July 25, 2012: 8:45 AM
Ballroom E (Rhode Island Convention Center)
Saleema Saleh-Lakha, University of Guelph, Guelph, Canada
Vanessa Allen, Ontario Public Health, Toronto, Canada
Jiping Li, University of Guelph, Guelph, Canada
Franco Pagotto, Health Canada, Ottawa, Canada
Joseph Odumeru, Ministry of the Environment, Etobicoke, Canada
Eduardo Taboada, Public Health Agency of Canada, Lethbridge, Canada
Burton Blais, Canadian Food Inspection Agency, Ottawa, Canada
Dele Ogunremi, Canadian Food Inspection Agency, Ottawa, Canada
Gavin Downing, Ontario Ministry of Agriculture, Food & Rural Affairs, Guelph, Canada
Susan Lee, University of Guelph, Guelph, Canada
Anli Gao, University of Guelph, Guelph, Canada
Shu Chen, University of Guelph, Guelph, Canada
Introduction: Listeria monocytogenes is responsible for rare but severe and often fatal foodborne infections. Accurate and timely molecular subtyping of L. monocytogenesisolates is critical to understand the epidemiology of foodborne listeriosis, and to support efforts to minimize listeriosis and outbreak investigations.

Purpose: The purpose of this study was to characterize a large collection of L. monocytogenesstrains, isolated from Ontario’s food chain over the last 15 years, along with Ontario’s historical clinical isolates, using MLVA subtyping, to support future preventative efforts.

Methods: Two multiplex PCR reactions were established and optimized under a single condition based on eight specific VNTR loci, which provided high discriminatory power, amplification efficiency and data quality. The fluorescent PCR fragments were separated using an ABI 3730 Genetic Analyzer and analyzed using GeneMapper and BioNumerics software.

Results: Over 2,400 historical L. monocytogenes strains of poultry, bovine, swine, produce, environmental and clinical sources were analyzed using the MLVA method. A subset of the strains was also analyzed by standard Pulsed Field Gel Electrophoreses (PFGE) and the results indicated a close alignment in the number of MLVA subtypes and PFGE patterns. Statistical data analysis and strain clustering allowed for identification of distinct clusters, and several predominant and persistent L. monocytogenesgenotypes in Ontario’s food chain, as well as genetic relatedness among various strains. Shared genotypes were identified between food and clinical strains, which may or may not have had any epidemiological link. For instance, the MLVA patterns from the strains of the 2008 Canadian outbreak were also observed among a cluster of 49 strains isolated from chicken, beef, pork, retail and environmental samples between 1998 and 2009.

Significance: The simple, rapid and accurate methodology plus a standardized strain-based DNA fingerprint database will allow for proactive tracking of contamination sources and earlier human cluster detection to minimize foodborne listeriosis.