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Subtyping Escherichia coli Virulence Genes Isolated from Feces of Beef Cattle and Clinical Cases in Alberta.

Research paper by Renata R Tostes, Noriko N Goji, Kingsley K Amoako, Linda L Chui, John J Kastelic, Rebekah R DeVinney, Kim K Stanford, Tim T Reuter

Indexed on: 18 Nov '16Published on: 18 Nov '16Published in: Foodborne pathogens and disease



Abstract

Clinical outcomes of Shiga toxin (stx)-producing Escherichia coli infection are largely determined by virulence gene subtypes. This study used a polymerase chain reaction (PCR)-pyrosequencing assay to analyze single-nucleotide polymorphisms for subtyping three major virulence genes (stx1, stx2, eae) of pathogenic E. coli (O157, O26, O111, and O103) isolated from cattle over a 2-year interval (n = 465) and human clinical cases (n = 42) in western Canada. Most bovine isolates were PCR positive for at least one target virulence gene (367/465), whereas 100% of human isolates harbored eae in combination with at least one stx gene. Four Shiga toxin (1a, 2a, 2c, and 2e) and four eae (λ/γ1-eae, ɛ-eae, θ/γ2-eae, and β-eae) subtypes were identified in over 25 distinct virulence genotypes. Among cattle isolates, every serogroup, but O103, presented a dominant genotype (O157: stx1a+stx2a+λ/γ1-eae, O26: β-eae alone, and O111: stx1a+θ/γ2-eae). Similar patterns were found in human isolates, although it was not possible to establish a clear genotypic association between the two sources. Many O157 and non-O157 cattle isolates lacked stx genes; the absence was greater in non-O157 (75/258) and O157:non-H7 (19/40) than in O157:H7 strains (1/164). In addition, there was a greater diversity of virulence genotypes of E. coli isolated from cattle than those of human diseases, which could be due to sample characteristics (e.g., source and clinical condition). However, the majority of cattle strains had virulence profiles identical to those of clinical cases. Consequently, determining the presence of certain stx (stx1a and stx2a) and eae (λ/γ1-eae) subtypes known to cause human disease would be a valuable tool for risk assessment and prediction of disease outcome along the farm-to-fork continuum.