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Cook KL, Givan EC, Mayton HM, Parekh RR, Taylor R, Walker SL. Using the agricultural environment to select better surrogates for foodborne pathogens associated with fresh produce. Int J Food Microbiol 2017; 262:80-88. [PMID: 28968533 DOI: 10.1016/j.ijfoodmicro.2017.09.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 08/25/2017] [Accepted: 09/24/2017] [Indexed: 01/26/2023]
Abstract
Despite continuing efforts to reduce foodborne pathogen contamination of fresh produce, significant outbreaks continue to occur. Identification of appropriate surrogates for foodborne pathogens facilitates relevant research to identify reservoirs and amplifiers of these contaminants in production and processing environments. Therefore, the objective of this study was to identify environmental Escherichia coli isolates from manures (poultry, swine and dairy) and surface water sources with properties similar to those of the produce associated foodborne pathogens E. coli O157:H7 and Salmonella enterica serotype Typhimurium. The most similar environmental E. coli isolates were from poultry (n=3) and surface water (n=1) sources. The best environmental E. coli surrogates had cell surface characteristics (zeta potential, hydrophobicity and exopolysaccharide composition) that were similar (i.e., within 15%) to those of S. Typhimurium and/or formed biofilms more often when grown in low nutrient media prepared from lettuce lysates (24%) than when grown on high nutrient broth (7%). The rate of attachment of environmental isolates to lettuce leaves was also similar to that of S. Typhimurium. In contrast, E. coli O157:H7, a commonly used E. coli quality control strain and swine isolates behaved similarly; all were in the lowest 10% of isolates for biofilm formation and leaf attachment. These data suggest that the environment may provide a valuable resource for selection of surrogates for foodborne pathogens.
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Affiliation(s)
- Kimberly L Cook
- USDA-ARS, Food Animal Environmental Systems Research Unit, Bowling Green, KY, USA.
| | - Ethan C Givan
- Western Kentucky University, Department of Public Health, Bowling Green, KY, USA.
| | - Holly M Mayton
- University of California, Bourns College of Engineering, Riverside, CA, USA.
| | - Rohan R Parekh
- USDA-ARS, Food Animal Environmental Systems Research Unit, Bowling Green, KY, USA.
| | - Ritchie Taylor
- Western Kentucky University, Department of Public Health, Bowling Green, KY, USA.
| | - Sharon L Walker
- University of California, Bourns College of Engineering, Riverside, CA, USA.
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Hu M, Gurtler JB. Selection of Surrogate Bacteria for Use in Food Safety Challenge Studies: A Review. J Food Prot 2017; 80:1506-1536. [PMID: 28805457 DOI: 10.4315/0362-028x.jfp-16-536] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Nonpathogenic surrogate bacteria are prevalently used in a variety of food challenge studies in place of foodborne pathogens such as Listeria monocytogenes, Salmonella, Escherichia coli O157:H7, and Clostridium botulinum because of safety and sanitary concerns. Surrogate bacteria should have growth characteristics and/or inactivation kinetics similar to those of target pathogens under given conditions in challenge studies. It is of great importance to carefully select and validate potential surrogate bacteria when verifying microbial inactivation processes. A validated surrogate responds similar to the targeted pathogen when tested for inactivation kinetics, growth parameters, or survivability under given conditions in agreement with appropriate statistical analyses. However, a considerable number of food studies involving putative surrogate bacteria lack convincing validation sources or adequate validation processes. Most of the validation information for surrogates in these studies is anecdotal and has been collected from previous publications but may not be sufficient for given conditions in the study at hand. This review is limited to an overview of select studies and discussion of the general criteria and approaches for selecting potential surrogate bacteria under given conditions. The review also includes a list of documented bacterial pathogen surrogates and their corresponding food products and treatments to provide guidance for future studies.
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Affiliation(s)
- Mengyi Hu
- 1 U.S. Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, Food Safety and Intervention Technologies Research Unit, 600 East Mermaid Lane, Wyndmoor, Pennsylvania 19038-8551.,2 Department of Culinary Arts and Food Science, Drexel University, 3141 Chestnut Street, Philadelphia, Pennsylvania 19104-30, USA
| | - Joshua B Gurtler
- 1 U.S. Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, Food Safety and Intervention Technologies Research Unit, 600 East Mermaid Lane, Wyndmoor, Pennsylvania 19038-8551
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Yang X, Noyes NR, Doster E, Martin JN, Linke LM, Magnuson RJ, Yang H, Geornaras I, Woerner DR, Jones KL, Ruiz J, Boucher C, Morley PS, Belk KE. Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain. Appl Environ Microbiol 2016; 82:2433-2443. [PMID: 26873315 PMCID: PMC4959480 DOI: 10.1128/aem.00078-16] [Citation(s) in RCA: 81] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Accepted: 02/09/2016] [Indexed: 11/20/2022] Open
Abstract
Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.
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Affiliation(s)
- Xiang Yang
- Department of Animal Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Noelle R Noyes
- Department of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Enrique Doster
- Department of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Jennifer N Martin
- Department of Animal Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Lyndsey M Linke
- Department of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Roberta J Magnuson
- Department of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Hua Yang
- Department of Animal Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Ifigenia Geornaras
- Department of Animal Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Dale R Woerner
- Department of Animal Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Kenneth L Jones
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver School of Medicine, Aurora, Colorado, USA
| | - Jaime Ruiz
- Department of Computer Science, Colorado State University, Fort Collins, Colorado, USA
| | - Christina Boucher
- Department of Computer Science, Colorado State University, Fort Collins, Colorado, USA
| | - Paul S Morley
- Department of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Keith E Belk
- Department of Animal Sciences, Colorado State University, Fort Collins, Colorado, USA
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