Abstract
Recent worldwide foodborne outbreaks emphasize the need for the development of rapid and accurate method for pathogen detection. To address such issues, a new colony based label-free detection method working on the principles of elastic light scattering was introduced. In order to build libraries of scattering images for bacterial pathogens, it is pertinent to determine the effect of preparation and storage of the agar media on the scatter patterns. Scatter patterns of three Escherichia coli serovars (O26, O111 and O157) were studied and used in a model system, after growth on Sorbitol-MacConkey agar plates that were prepared and stored at different conditions in the laboratory. Quantitative image processing software was used to analyze variation in scatter patterns of the same serovar on media prepared under various standard laboratory conditions and to generate a cross-validation matrix for comparison. Based on the results, it was determined that attention should be given during preparation of media so that the agar plates are not air-dried more than 10 - 20 min after solidification at room temperature. The plates could be stored in sealed bags in cold room (4oC - 10oC) for up to a month before use. The findings of this study should provide guidelines in preparation, storage, and handling of media for generation of reproducible scatter patterns of bacterial colonies with the light scattering sensor for pathogen detection.
Highlights
Today a large amount of our food is being processed and sold as ready-to-eat product on the shelves of the grocery stores worldwide
Effects of the preparation and storage conditions of SMAC agar plate on scatter patterns of E. coli serovars O157, O111 and O26 are presented in two groups: 1) effect of air-drying agar plates on the scatter patterns; and 2) effect of agar plate storage on the scatter patterns
The results were tabulated with three distinctive parameters; the condition of drying or storage used in the experiment; the representative Bacterial Rapid Detection using Optical scattering Technology (BARDOT) scatter image obtained under given parameter; and the cross validation matrix obtained with the classification software, where highest off-diagonal values for false positives and false negatives were set as the Maximum Confusion Factor (MCF) (Table 1)
Summary
Today a large amount of our food is being processed and sold as ready-to-eat product on the shelves of the grocery stores worldwide. To maintain food quality and safety, scientists apply various quality control strategies; lack of rapid, user-friendly and high through put techniques delays quality assurance in food production and processing practices. Such constraints may increase the risk of foodborne outbreaks [2,3]. Food products are highly susceptible to contaminations if they are not processed under good manufacturing practices (GMP) or following HACCP plans [4,5]. The detection of foodborne pathogens is vital and critical for the food industry to deliver and maintain food safety [6]. Recent E. coli O104-outbreak in Europe [7] in 2011 and Salmonella in the United States [8] emphasize the need for an improvement of current culture-based and direct detection techniques of analysis; and development of new technologies to mitigate foodborne outbreaks and resulting economic damages
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