Bacterial food contamination is an increasingly major problem in society, causing food poisoning and other foodborne diseases. Foodborne pathogens currently affect approximately 50 million people each year in the United States alone. Furthermore, public demand for organic, nonpasteurized food products is inducing pressure on the food industry to provide high quality and safe products. One of the most prevalent foodborne pathogens associated with recalls and illness is Listeria monocytogenes, which causes the infection Listeriosis, the third leading cause of death from foodborne illness. There is a pressing need to develop low cost, rapid biosensors that can discriminate L. monocytogenes in a wide range of food environments with the same level of reliability as traditional methods. The goal of this research is to develop rapid, low cost L. monocytogenes biosensors based on composites of stimuli-responsive polymer nanobrushes and aptamers on laser scribed graphene (LSG) electrodes. We are engineering LSG electrodes utilizing a low cost, low power, millisecond-pulsed UV laser. Electrodes were optimized through electrochemical testing, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), of LSG carbonized at various laser energy densities. Holes (1mm diameter) are drilled into the working electrode so that fluid can be pulled through the sensor to process realistic samples (225 mL according to FDA standards). After forming carbonized electrodes with holes for sample processing, the LSG electrodes are then modified with nanoplatinum deposition to increase sensor performance and conductivity, and functionalized with InlA-specfic DNA aptamers. Using impedance spectroscopy, we are able to detect L. monocytogenes in food matrices at levels as low as 10 CFU/mL in approximately 20 minutes for sample volumes of 225 mL. The sample volume is extremetly important, as microfluidic samples have major limitations when processing food samples according to the standard methodology, which requires enrichment of a 225 mL sample. This work is a major step toward enrichment-free sample analysis of food products, and we are currently working toward further improved limits of detection to facilitate enrichment free testing. This sensor platform has potential impacts beyond food detection and has potential applications in hospitals, disease tracking, and pathogen detection in envirionmental samples.

Laser scribed graphene sensors for point of use detection of Listeria monocytogenes

2019 Fall National Meeting

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