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Development of a Label-Free Sers Mapping Based Platform for Multi-Bacterial Dete

Investigators
He, Lili
Institutions
University of Massachusetts - Amherst
Start date
2015
End date
2018
Objective

The overall goal of this project is to develop a platform for pathogen detection in foods that is superior to the current detection methods, in terms of analytical time, sensitivity, and accuracy, which is based ona novel label-free surface enhanced Raman scattering (SERS) mapping technique. With the developed SERS platform, we expect to concentrate, identify and quantify multiple bacterial cells from food samples before them being distributed further. This will improve the long-range sustainability of U.S. agriculture and food systems by reducing the economic loss due to the product recalls and minimizing the health risk caused by food pathogens.Objectives:Determine the best capturers for bacteria concentration and SERS identification.Optimize the SERS mapping method for cell quantification.Evaluate and optimize sample pretreatments for bacterial capture and SERS identification.Fabricate SERS slides for multi-bacterial detection in food samples.

More information

Determine the best capturers for bacteria concentration and SERS identification. Salmonella enterica and Listeria monocytogenes will be used as the targets. Selective capturers (antibodies and aptamers) and nonselective capturers (antibiotics and antimicrobial peptides) will be conjugated onto silver dendrites and their performance will be evaluated. Capture capacity will be tested using the traditional plate count methods. SERS identification capacity will be evaluated by principal component analysis. Both live and dead cells (thermal inactivated) will be tested for SERS identification. The best capturers will be determined for each bacterium and bacterial mixture.Optimize the SERS mapping method for cell quantification. Different parameters of mapping will be applied and optimized for rapid and accurate quantification.Evaluate and optimize sample pretreatments for bacterial capture and SERS identification. Milk (an example of liquid food) and ground beef (an example of solid food) will be tested in this study. The sample pretreatments (purification and/or enrichment) will be evaluated and optimized for the best detection.Fabricate SERS slides for multi-bacterial detection in food samples. SERS slides with capturer functionalized silver dendrites will be fabricated and evaluated for detection of a mixture of Salmonella and Listeria from food samples after the optimized pretreatments.

Funding Source
Nat'l. Inst. of Food and Agriculture
Project source
View this project
Project number
MASW-2014-03641
Accession number
1005211
Categories
Salmonella
Listeria