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Pulsed-field gel electrophoresis subtyping database for foodborne Salmonella enterica serotype discrimination
Authors:Kérouanton Annaëlle  Marault Muriel  Lailler Renaud  Weill François-Xavier  Feurer Carole  Espié Emmanuelle  Brisabois Anne
Affiliation:Agence Fran?aise de Sécurité Sanitaire des Aliments, Laboratoire d'Etudes et de Recherches sur la Qualité des Aliments et sur les Procédés Agro-alimentaires, Unité Caractérisation et Epidémiologie Bactérienne, Maisons-Alfort, France. a.kerouanton@afssa.fr
Abstract:Nontyphoid Salmonella is one of the main causes of bacterial gastroenteritis worldwide and is responsible for 65% of reported outbreaks of foodborne diseases in France. Serotyping is widely used for isolate preliminary identification, but it poorly discriminates strains. Rapid, efficient molecular subtyping tools have therefore been developed for the investigation of outbreaks. We evaluated the performance of the pulsed-field gel electrophoresis (PFGE) method for discrimination of 31 Salmonella serotypes frequently isolated in France. We set up a genomic database of Salmonella strains isolated from food, animals, the environment, and humans to improve the management of contamination and reactions to foodborne disease outbreaks. We studied 1128 isolates by PFGE, according to the standardized PulseNet protocol. We identified 452 PFGE patterns, 67.5% of which corresponded to a single isolate. The ability of this method to distinguish between isolates was estimated by calculating the Simpson index and the 95% confidence interval. Values obtained ranged between 0.33 (0.11-0.54) to 0.99 (0.96-1.00), depending on serotype. Epidemiological information about isolates was used for analyses of intra- and interserotype diversity results and for determining whether PFGE patterns were linked to the source of the isolate. Clustering analysis of the PFGE patterns obtained confirmed that serotype and PFGE genotype were closely linked. Some PFGE patterns were identified as major patterns, each of these patterns being found in at least 10 isolates. The database generated has already proved its effectiveness in epidemiological investigations in livestock production and foodborne outbreaks.
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