2020年
Modeling Invasion of Campylobacter jejuni into Human Small Intestinal Epithelial-Like Cells by Bayesian Inference
Applied and Environmental Microbiology
- ,
- ,
- 巻
- 87
- 号
- 1
- 記述言語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1128/AEM.01551-20
- 出版者・発行元
- American Society for Microbiology
<title>ABSTRACT</title>
Current approaches used for dose-response modeling of low-dose exposures of pathogens rely on assumptions and extrapolations. These models are important for quantitative microbial risk assessment of food. A mechanistic framework has been advocated as an alternative approach for evaluating dose-response relationships. The objectives of this study were to investigate the invasion behavior of <named-content content-type="genus-species">Campylobacter jejuni</named-content>, which could arise as a foodborne illness even if there are low counts of pathogens, into Caco-2 cells as a model of intestinal cells and to develop a mathematical model for invading cell counts to reveal a part of the infection dose-response mechanism. Monolayer-cultured Caco-2 cells and various concentrations of <named-content content-type="genus-species">C. jejuni</named-content> in culture were cocultured for up to 12 h. The numbers of <named-content content-type="genus-species">C. jejuni</named-content> bacteria invading Caco-2 cells were determined after coculture for different time periods. There appeared to be a maximum limit to the invading bacterial counts, which showed an asymptotic exponential increase. The invading bacterial counts were higher with higher exposure concentrations (maximum, 5.0 log CFU/cm2) than with lower exposure concentrations (minimum, 0.6 log CFU/cm2). In contrast, the ratio of invading bacteria (number of invading bacteria divided by the total number of bacteria exposed) showed a similar trend regardless of the exposure concentration. Invasion of <named-content content-type="genus-species">C. jejuni</named-content> into intestinal cells was successfully demonstrated and described by the developed differential equation model with Bayesian inference. The model accuracy showed that the 99% prediction band covered more than 97% of the observed values. These findings provide important information on mechanistic pathogen dose-response relationships and an alternative approach for dose-response modeling.
<bold>IMPORTANCE</bold> One of the infection processes of <named-content content-type="genus-species">C. jejuni</named-content>, the invasion behavior of the bacteria in intestinal epithelial cells, was revealed, and a mathematical model for prediction of the cell-invading pathogen counts was developed for the purpose of providing part of a dose-response model for <named-content content-type="genus-species">C. jejuni</named-content> based on the infection mechanism. The developed predictive model showed a high accuracy of more than 97% and successfully described the <named-content content-type="genus-species">C. jejuni</named-content> invading counts. The bacterial invasion predictive model of this study will be essential for the development of a dose-response model for <named-content content-type="genus-species">C. jejuni</named-content> based on the infection mechanism.
Current approaches used for dose-response modeling of low-dose exposures of pathogens rely on assumptions and extrapolations. These models are important for quantitative microbial risk assessment of food. A mechanistic framework has been advocated as an alternative approach for evaluating dose-response relationships. The objectives of this study were to investigate the invasion behavior of <named-content content-type="genus-species">Campylobacter jejuni</named-content>, which could arise as a foodborne illness even if there are low counts of pathogens, into Caco-2 cells as a model of intestinal cells and to develop a mathematical model for invading cell counts to reveal a part of the infection dose-response mechanism. Monolayer-cultured Caco-2 cells and various concentrations of <named-content content-type="genus-species">C. jejuni</named-content> in culture were cocultured for up to 12 h. The numbers of <named-content content-type="genus-species">C. jejuni</named-content> bacteria invading Caco-2 cells were determined after coculture for different time periods. There appeared to be a maximum limit to the invading bacterial counts, which showed an asymptotic exponential increase. The invading bacterial counts were higher with higher exposure concentrations (maximum, 5.0 log CFU/cm2) than with lower exposure concentrations (minimum, 0.6 log CFU/cm2). In contrast, the ratio of invading bacteria (number of invading bacteria divided by the total number of bacteria exposed) showed a similar trend regardless of the exposure concentration. Invasion of <named-content content-type="genus-species">C. jejuni</named-content> into intestinal cells was successfully demonstrated and described by the developed differential equation model with Bayesian inference. The model accuracy showed that the 99% prediction band covered more than 97% of the observed values. These findings provide important information on mechanistic pathogen dose-response relationships and an alternative approach for dose-response modeling.
<bold>IMPORTANCE</bold> One of the infection processes of <named-content content-type="genus-species">C. jejuni</named-content>, the invasion behavior of the bacteria in intestinal epithelial cells, was revealed, and a mathematical model for prediction of the cell-invading pathogen counts was developed for the purpose of providing part of a dose-response model for <named-content content-type="genus-species">C. jejuni</named-content> based on the infection mechanism. The developed predictive model showed a high accuracy of more than 97% and successfully described the <named-content content-type="genus-species">C. jejuni</named-content> invading counts. The bacterial invasion predictive model of this study will be essential for the development of a dose-response model for <named-content content-type="genus-species">C. jejuni</named-content> based on the infection mechanism.
- リンク情報
- ID情報
-
- DOI : 10.1128/AEM.01551-20
- ISSN : 1098-5336
- ISSN : 0099-2240
- eISSN : 1098-5336
- ORCIDのPut Code : 92050741
- SCOPUS ID : 85098474765