Data collection, analysis and development of a peri-harvest quantitative microbial risk assessment (QMRA) for Shiga toxin-producing Escherichia coli (STEC) in beef production

Date

2017-12-01

Journal Title

Journal ISSN

Volume Title

Publisher

Kansas State University

Abstract

Shiga-toxin-producing Escherichia coli (STEC), of which enterohemorrhagic E. coli (EHEC) are a pathogenic sub-group, are foodborne pathogens of significant public health importance in the United States. STEC belong to the family Enterobacteriaceae commonly found in the large intestine of humans and other warm-blooded animals. EHEC harbors shiga toxin (stx1 and/or stx2) and eae genes which confers the ability to cause human illnesses. The U.S. Department of Agriculture Food Safety and Inspection Service declared seven STEC (O26, O45, O103, O111, O121, O145, and O157) as adulterants in ground beef and non-intact beef products to reduce/eliminate the burden of the pathogens in the beef production chain. STEC control efforts in the U.S. include the development of quantitative microbial risk assessment (QMRA) to identify mitigation strategies that are effective and economical in reducing exposure and reduce occurrence and public health risk from STEC in the beef chain. Collection of accurate and unbiased data is critical for the development of a QMRA that is valid for decision making. Determining the prevalence and concentration of the seven STEC in the different cattle types and seasons is valuable for the development a valid QMRA for STEC in beef production in the U.S. Our systematic review and meta-analysis study of the prevalence and concentration of E. coli O157 along the beef production chain indicated differences in the fecal prevalence of E. coli O157 among cattle types and seasons, revealed decreasing prevalence and concentration of E. coli O157 on cattle hides and carcass surfaces from pre-evisceration to the final chilled carcass stage, and identified study setting, detection method, hide or carcass swab area, and study design as significant sources of heterogeneity among studies reporting prevalence of E. coli O157 along the beef production chain. Bayesian estimation of the diagnostic performance of three laboratory methods (culture, conventional PCR [cPCR], and multiplex quantitative PCR [mqPCR]) used for the detection of the seven STEC in the feces of cattle is necessary to estimate true prevalence of EHEC in cattle. The analysis revealed highest sensitivity of mqPCR, followed by cPCR, and culture for the detection of E. coli O157; the cPCR and mqPCR had comparable specificity, but specificity of mqPCR method was heavily dependent on prior specification. The mqPCR method was the most sensitive for the detection O26, O45, and O103 serogroups. The cPCR method was more sensitive than the culture method for serogroups O26, and O121, but comparable for serogroups O45, O103, O111, and O145. The cPCR method showed higher specificity than mqPCR within serogroups O45, O121, and O145 but no apparent differences within serogroups O26, O103, and O111. A second order quantitative microbial risk assessment was developed to quantify the prevalence and concentration of the seven STEC on pre-evisceration beef carcasses and evaluate the impact of peri-harvest interventions. Simulation scenarios of current industry peri-harvest intervention practices showed variable effectiveness in reducing STEC contamination on pre-evisceration beef carcass, however, a scenario of increased adoption of peri-harvest interventions was more effective at reducing STEC contamination. Fecal-to-hide transfer and hide-to-carcass transfer had a large effect on prevalence and concentration of STEC on pre-evisceration carcasses.

Description

Keywords

Quantitative microbial risk assessment, Shigatoxin, Escherichia coli, Peri-harvest beef production, Data collection, Bayesian analysis

Graduation Month

December

Degree

Doctor of Philosophy

Department

Department of Diagnostic Medicine/Pathobiology

Major Professor

Michael W. Sanderson

Date

2017

Type

Dissertation

Citation