Document Type

Article

Publication Version

Published Version

Publication Date

11-2011

Journal or Book Title

Applied and Environmental Microbiology

Volume

77

Issue

22

First Page

8080

Last Page

8087

DOI

10.1128/AEM.00064-11

Abstract

The aims of this study were to determine the ability of amplified fragment length polymorphism (AFLP) to differentiate Salmonella isolates from different units of swine production and to demonstrate the relatedness of Salmonella between farms and abattoirs by AFLP. Twenty-four farms in the midwestern United States were visited four times from 2006 to 2009. At each farm or abattoir visit, 30 fecal samples or 30 mesenteric lymph nodes were collected, respectively. A total of 220 Salmonella isolates were obtained, serotyped, and genotyped by multilocus sequence typing (MLST) and AFLP. These 220 isolates clustered into 21 serotypes, 18 MLST types, and 14 predominant AFLP clusters based on a genetic similarity threshold level of 60%. To assess genetic differentiation between farms, harvest cohorts, and pigs, analysis of molecular variance was conducted using AFLP data. The results showed 65.62% of overall genetic variation was attributed to variance among pigs, 27.21% to farms, and 7.17% to harvest cohorts. Variance components at the farm (P = 0.003) and pig (P = 0.001) levels were significant, but not at the harvest cohort level (P = 0.079). A second analysis, a permutation test using AFLP data, indicated that on-farm and at-abattoir Salmonella from pigs of the same farms were more related than from different farms. Therefore, among the three subtyping methods, serotyping, MLST, and AFLP, AFLP was the method that was able to differentiate among Salmonella isolates from different farms and link contamination at the abattoir to the farm of origin.

Comments

This article is from Applied and Environmental Microbiology 77 (2011): 8080, doi:10.1128/AEM.00064-11. Posted with permission.

Copyright Owner

American Society for Microbiology

Language

en

File Format

application/pdf