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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality & Safety Assessment Research » Research » Publications at this Location » Publication #333292

Research Project: Develop Rapid Optical Detection Methods for Food Hazards

Location: Quality & Safety Assessment Research

Title: Simultaneous detection and serotyping of Salmonellae by immunomagnetic separation and label-free surface enhanced Raman spectroscopy

Author
item Chen, Jing - Orise Fellow
item Park, Bosoon
item Eady, Matthew

Submitted to: Journal of Food Analytical Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/8/2017
Publication Date: 4/4/2017
Citation: Chen, J., Park, B., Eady, M.B. 2017. Simultaneous detection and serotyping of Salmonellae by immunomagnetic separation and label-free surface enhanced Raman spectroscopy. Journal of Food Analytical Methods. 10:3181-3193.

Interpretive Summary: The food industry and regulatory agencies are consistently seeking rapid and cost-effective methods to replace time-consuming and labor-intensive current standards for pathogen detection. High prevalence of Salmonella enterica in poultry products is one of the major causes of gastrointestinal infections in the United States, resulting in significant public health and economical burdens each year. Timely detection and characterization of Salmonella serotypes are a key measure in prevention and control of Salmonella outbreaks. Label-free methods based on surface enhanced Raman spectroscopy (SERS) have been proposed for rapid detection pathogenic bacteria. However, to move such a strategy forward to actual food testing, obstacles of high detection limits and difficulties in differentiating mixtures must be overcome. In this study we have attempted to resolve these issues with immunomagnetic separation and a reasonable culture period on non-selective agar. Multivariate statistical models were built and validated in sample mixtures using SERS spectra collected on biopolymer encapsulated silver nanoparticle substrates. The potential and limitations of this method have been discussed as well in this paper.

Technical Abstract: Salmonella spp. are one of the leading causes of foodborne outbreaks in the United States and globally. Current detection and characterization techniques for Salmonellae are time consuming and costly, and rapid methods could greatly benefit outbreak investigation, new case prevention and disease treatment. The objective of this study was to evaluate the potential of surface enhanced Raman spectroscopy (SERS) in detection and serotyping of Salmonellae without the use of expensive detection labels. Pathogen cells were first isolated from the matrix by the immunomagnetic separation (IMS) technique, and then cultured overnight to detectable amounts on agar plates. SERS measurements were then carried out, and the collected spectra were analyzed by multivariate statistical analyses, e.g., principle component analysis, linear discriminant analysis and support vector machines for building and validating statistical models using spectra from multiple replicates and experiments. Using pure bacterial culture, the method achieved accuracies of 93%-100% when detecting Salmonella from other bacterial species (E. coli and S. aureus), 87%-100% when identifying four common Salmonella serotypes (Typhimurium, Infantis, Heidelberg, and Enteritidis), and 67%-100% when detection and serotyping were carried out simultaneously. The method was also evaluated with bacterial cocktails consisting of four Salmonella serotypes, E. coli, and S. aureus, and the results were compared with traditional detection/serotyping methods. In this case, prediction accuracies decreased to 65%, with an increased number of misclassifications. Overall, the accuracies achieved by the IMS-SERS method demonstrate potentials in simultaneous detection and serotyping of Salmonellae from food samples inexpensively and within a reasonable period of time. Further improvement in spectral reproducibility is needed to provide higher accuracies and a universal spectral library for faster detection.