Shiga Toxin-Producing Escherichia coli: a Public Health Challenge in the Pre-Harvest Stage of the Farm-to-Table Continuum

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Date

2016-06-06

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Virginia Tech

Abstract

Escherichia coli is part of the normal gastrointestinal microbiota of many animals, especially cattle. While most strains are commensal, Shiga toxin-producing E. coli (STEC) can cause severe human illness.

Pathogenicity of STEC is associated with genes such as those encoding Shiga toxins, enterohemolysin, and intimin. By targeting these genes, highly sensitive molecular-based techniques help detect potentially harmful STEC.

Persistent carriers and environmental contamination may be responsible for maintenance of STEC in cattle farms. Prevalence may be further influenced by diet, distance to contaminated water-sources, wildlife contact, slurry application to pasture, and population density. Relevance in environmental contamination is expected proportional to the amount of STEC shed in feces, but there is no consensus as to which production stage/age is most important.

Distribution and transmission of STEC O157 are widely studied, but risk factors for non-O157 STEC are not as well defined. Understanding what contributes for contamination of animals prior to concentration in high-density feedlots may reveal opportunities for upstream control of shedding and transmission.

Our purpose was to: (a) determine prevalence of STEC in fecal samples from animals in a cow-calf pasture-based production system; (b) describe effects of age class (dam, calf), spatial distribution of cattle, and time-point of sampling on distribution of strains positive for virulence genes stx1, stx2, eaeA, and hlyA; (c) isolate and identify serotypes present in stx-positive samples; and (d) assess genetic similarity of isolates.

Understanding factors that influence distribution of STEC strains may help support on-farm management strategies with potential to yield safer beef products.

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Keywords

Escherichia coli, animal husbandry, cattle, zoonoses, microbiology, virulence, molecular, characterization, fingerprinting, distribution

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