Label-free detection and serotyping of Salmonellae by surface enhanced Raman spectroscopy with immunomagnetic separation

Journal of Lasers, Optics & Photonics

ISSN: 2469-410X

Open Access

Label-free detection and serotyping of Salmonellae by surface enhanced Raman spectroscopy with immunomagnetic separation

5th International Conference and Exhibition on Lasers, Optics & Photonics

November 28-30, 2016 Atlanta, USA

Bosoon Park

USDA - Agricultural Research Service, Athens, USA

Posters & Accepted Abstracts: J Laser Opt Photonics

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 rapid methods could greatly benefit outbreak investigation, new case prevention and disease treatment. In this presentation, the potential of surface enhanced Raman spectroscopy (SERS) in label-free detection and serotyping of Salmonella will be discussed. Immunomagnetic separation (IMS) with anti-Salmonella antibody coated paramagnetic beads can capture target bacterial samples in a cell level. SERS methods are used by applying single colony suspensions on polyvinyl alcohol stabilized biopolymer encapsulated silver nano-substrates. Spectra from multiple colonies and experiments are collected and analyzed by chemometric analysis for classification. The detection accuracies are evaluated in real mixture samples. IMS-SERS coupled with classification models yielded accuracies of between 86.7% and 99.8% for detecting Salmonella. However, when validated in mixture samples consisting of six bacteria samples including S. typhimurium, S. Infantis, S. Kentucky, S. enteritidis, E. coli, and S. aureus, prediction accuracies decreased. The potential of simultaneous detection and characterization of multiple foodborne pathogens and serotypes using label-free SERS coupled with IMS has the potential as a new bio-sensing method, which provides an inexpensive and rapid alternative method. However, further improvement in spectral reproducibility and classification accuracy are needed, particularly for characterization of Salmonella serotypes in food matrices.

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