4.7 Article

Distribution of virulence factors, determinants of antibiotic resistance and molecular fingerprinting of Salmonella species isolated from cattle and beef samples: suggestive evidence of animal-to-meat contamination

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 25, Issue 32, Pages 32694-32708

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-018-3231-4

Keywords

Antibiotic resistance; 16S rRNA gene; fljB gene; fliC gene; RFLP; Salmonella; Virulence genes (spvC and invA)

Funding

  1. North-West University, Mafikeng Campus, South Africa
  2. National Research Foundation

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In this study, three hundred presumptive Salmonella strains isolated from cattle faeces and raw beef samples were subjected to both preliminary and confirmatory tests specific for Salmonella. PCR assays revealed that 100%, 20% and 26.7% of the isolates were positive for 16S rRNA, fliC and fljB gene fragments, respectively. Large proportions (62.4 to 94.3%) of these isolates were multiple antibiotic resistant (MAR) strains that were resistant to three or more antibiotics belonging to different classes. MAR phenotypes Ab1, Ab2, Ab3, Ab7, Ab8, Ab9, Ab26 and Ab27 were dominant among the isolates. Cluster analysis of antibiotic inhibition zone diameter data revealed two major clusters (clusters 1 and 2), and each cluster contained two sub-clusters (1A, 1B, 2A and 2B). PCR data revealed that 27.1% and 30.7% of the isolates possessed the spvC and invA virulent genes, respectively. There was a significant correlation between the possession of MAR phenotypes and virulent gene determinants. Analysis of restriction fragment length polymorphism (RFLP) of 16S rRNA gene fragments using EcoRI and HaeIII showed that large proportions of isolates from beef and cattle faeces produced similar genetic fingerprints. From these results, it is suggested that Salmonella species in cattle are transmitted to beef and, therefore, the consumption of undercooked beef could pose severe health complications on consumers. These findings provide baseline data that could be of great epidemiological importance and, thus, the need to utilise more sensitive typing tools in determining the genetic relatedness of isolates from different sources.

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