Location: Quality & Safety Assessment ResearchTitle: Label-Free Detection and Serotyping of Salmonellae by Surface Enhanced Raman Spectroscopy with Immunomagnetic Separation
|CHEN, JING - US Department Of Agriculture (USDA)|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/19/2016
Publication Date: 11/28/2016
Citation: Park, B., Chen, J. 2016. Label-Free Detection and Serotyping of Salmonellae by Surface Enhanced Raman Spectroscopy with Immunomagnetic Separation. Meeting Abstract. Vol. 3, Issue 3 (Suppl), 103. https://www.omicsgroup.org/journals/conference-proceedings/2469-410X.C1.009_0
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 Salmonella 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 polyvinylalcohol stabilized biopolymer encapsulated silver nanosubstrates. 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 biosensing 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.