Rapid identification of Salmonella by infrared spectroscopy (FTIR) and immunomagnetic separation (IMS)
Advisor:Rodriguez-Saona, Luis E.
Contributors:Rodriguez-Romo, L. A.
Yousef, Ahmed E.
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Series/Report no.:Food Science and Technology. Graduate student poster competition, 2007
Despite regulatory efforts and emergence of new processing technologies, food-related illnesses remain a major concern for consumers and producers. Since traditional identification methods for foodborne pathogens are time-consuming, rapid, cost-effective detection techniques are needed. The objective was to evaluate the combined use of immunomagnetic separation (IMS) and Fourier-Transform Infrared (FTIR) spectroscopy for detection and identification of Salmonella serovars. Selected Salmonella enterica serovars (Enteritidis, Typhimurium, Heidelberg, Muenchen, Anatum, and Kentucky), were grown to 109 cfu/ml, bound by anti-Salmonella magnetic beads (IMB) and collected using a magnetic particle concentrator, to specifically isolate and concentrate Salmonella. The bacteria-IMB complex was applied onto ZnSe, vacuum-dried and analyzed by attenuated total reflectance (ATR) FTIR. Spectra were compared by soft independent modeling of class analogy (SIMCA) for Salmonella differentiation. Salmonella bound to IMB had distinctive and reproducible infrared spectra, opposed to unbound IMB. However, the signal of the IMB distorted bacterial bands in the fingerprint region. Sonication and centrifugation lysed the cells, and isolated the cell wall components. Infrared spectra analysis (1300-900 cm-1) of the cell lysate, using SIMCA, permitted the separation of Salmonella into well-defined clusters with differentiation among serovars due to differences in cell envelope lipopolysaccharides (LPS). Application of IMS and IR microspectrometry, in combination with hydrophobic grid membranes allowed identification of Salmonella (103 cfu/ml) within 12 hours of incubation. This technology would allow isolation and identification of pathogenic bacteria in contaminated food matrices, minimizing false-positive results due to cross-reactions, and improving food safety and quality assurance.
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