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Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens

Different techniques are available for assessing differences in virulence of bacterial foodborne pathogens. The use of animal models or human volunteers is not expedient for various reasons; the use of epidemiological data is often hampered by lack of crucial data. In this paper, we describe a stati...

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Autores principales: Wijnands, Lucas M., Teunis, Peter F. M., Kuijpers, Angelina F. A., Delfgou-Van Asch, Ellen H. M., Pielaat, Annemarie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5491934/
https://www.ncbi.nlm.nih.gov/pubmed/28713334
http://dx.doi.org/10.3389/fmicb.2017.01139
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author Wijnands, Lucas M.
Teunis, Peter F. M.
Kuijpers, Angelina F. A.
Delfgou-Van Asch, Ellen H. M.
Pielaat, Annemarie
author_facet Wijnands, Lucas M.
Teunis, Peter F. M.
Kuijpers, Angelina F. A.
Delfgou-Van Asch, Ellen H. M.
Pielaat, Annemarie
author_sort Wijnands, Lucas M.
collection PubMed
description Different techniques are available for assessing differences in virulence of bacterial foodborne pathogens. The use of animal models or human volunteers is not expedient for various reasons; the use of epidemiological data is often hampered by lack of crucial data. In this paper, we describe a static, sequential gastrointestinal tract (GIT) model system in which foodborne pathogens are exposed to simulated gastric and intestinal contents of the human digestive tract, including the interaction of pathogens with the intestinal epithelium. The system can be employed with any foodborne bacterial pathogens. Five strains of Salmonella Heidelberg and one strain of Salmonella Typhimurium were used to assess the robustness of the system. Four S. Heidelberg strains originated from an outbreak, the fifth S. Heidelberg strain and the S. Typhimurium strain originated from routine meat inspections. Data from plate counts, collected for determining the numbers of surviving bacteria in each stage, were used to quantify both the experimental uncertainty and biological variability of pathogen survival throughout the system. For this, a hierarchical Bayesian framework using Markov chain Monte Carlo (MCMC) was employed. The model system is able to distinguish serovars/strains for in vitro infectivity when accounting for within strain biological variability and experimental uncertainty.
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spelling pubmed-54919342017-07-14 Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens Wijnands, Lucas M. Teunis, Peter F. M. Kuijpers, Angelina F. A. Delfgou-Van Asch, Ellen H. M. Pielaat, Annemarie Front Microbiol Microbiology Different techniques are available for assessing differences in virulence of bacterial foodborne pathogens. The use of animal models or human volunteers is not expedient for various reasons; the use of epidemiological data is often hampered by lack of crucial data. In this paper, we describe a static, sequential gastrointestinal tract (GIT) model system in which foodborne pathogens are exposed to simulated gastric and intestinal contents of the human digestive tract, including the interaction of pathogens with the intestinal epithelium. The system can be employed with any foodborne bacterial pathogens. Five strains of Salmonella Heidelberg and one strain of Salmonella Typhimurium were used to assess the robustness of the system. Four S. Heidelberg strains originated from an outbreak, the fifth S. Heidelberg strain and the S. Typhimurium strain originated from routine meat inspections. Data from plate counts, collected for determining the numbers of surviving bacteria in each stage, were used to quantify both the experimental uncertainty and biological variability of pathogen survival throughout the system. For this, a hierarchical Bayesian framework using Markov chain Monte Carlo (MCMC) was employed. The model system is able to distinguish serovars/strains for in vitro infectivity when accounting for within strain biological variability and experimental uncertainty. Frontiers Media S.A. 2017-06-30 /pmc/articles/PMC5491934/ /pubmed/28713334 http://dx.doi.org/10.3389/fmicb.2017.01139 Text en Copyright © 2017 Wijnands, Teunis, Kuijpers, Delfgou-Van Asch and Pielaat. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Wijnands, Lucas M.
Teunis, Peter F. M.
Kuijpers, Angelina F. A.
Delfgou-Van Asch, Ellen H. M.
Pielaat, Annemarie
Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens
title Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens
title_full Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens
title_fullStr Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens
title_full_unstemmed Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens
title_short Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens
title_sort quantification of salmonella survival and infection in an in vitro model of the human intestinal tract as proxy for foodborne pathogens
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5491934/
https://www.ncbi.nlm.nih.gov/pubmed/28713334
http://dx.doi.org/10.3389/fmicb.2017.01139
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