The increased incidence of food pathogen outbreaks placed a new emphasis on the requirement of a rapid, sensitive, and reliable detection method for pathogens in food samples. Surface-enhanced Raman spectroscopy (SERS) is a technique that tremendously enhances the weak Raman scattering of an analyte by using a metallic nano-substrate. Herein, we developed an innovative SERS sandwich assay platform which is based on 3-mercaptophenylboronic acid (3-MPBA) or aptamer as a capturer, and 3-MPBA and silver nanoparticles (AgNPs) as the reporter for non-selective and selective detection of bacteria. Both optical and chemical (SERS mapping) imaging were used as mechanisms for bacterial detection and quantification. Using Salmonella enterica and Listeria monocytogenes as the model bacteria, we have identified a unique bacterial SERS signal upon the interaction between the captured bacteria, 3-MBPA and AgNPs, which was used as the base for reliable detection of bacteria using SERS mapping. The non-specific assay also possesses unique optical properties allowing for the enhanced visualization of bacteria at low microscope magnifications (10 and 20x objective lenses). Using 3-MBPA owe achieved sensitive detection and quantification of as low as 102 CFU/mL and a capture efficiency of 92.1% for nonselective detection of Salmonella. The capability of the assay method to detect specific bacteria using an aptamer was also demonstrated. Besides the SERS applications of this assay, it was discovered that the 3-MPBA coated gold chip developed for this assay enhances the visualization of bacteria under a light microscope allowing for facile and rapid detection and quantification. In anticipation for industrial applications, sample preparation methods and strategies were developed for simple and carbohydrate food matrices.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:masters_theses_2-1530 |
| Date | 11 July 2017 |
| Creators | Pearson, Brooke |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses |
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