thesis

Development of label-free detection systems targeting food-borne pathogens

Abstract

Food-borne pathogens and food safety-related outbreaks have come to the forefront over recent years. Estimates on the annual cost of sicknesses, hospitalizations, and deaths run into the billions of dollars. There is a large body of research on the subject of detection of food-borne pathogens, however, the widely accepted current systems are limited by high reagent costs, lengthy time to completion, and expensive equipment. This work has been developed with the goal of focusing on minimizing the time and reagent cost of two of the most common types of rapid, food-borne pathogen detection systems, i.e. immunoassays and real-time polymerase chain reaction assays. The first aim was to develop the proof-of-concept methodology for a label-free immunoassay technique utilizing photonic crystal biosensors targeting bacteria, specifically E. coli O157:H7. In this project, it is shown that detergent-lysing of the cells and extraction of their membrane antigens allows for the detection of down to 1E7 CFU/mL. Optimization of the blocking scheme takes the assay one step further and allows for specific detection of E. coli O157:H7 over E. coli K12. The second aim was to develop a label-free method for determining changes in DNA concentration as it relates to food-borne pathogen-targeted polymerase chain reaction assays. For this goal, impedance spectroscopy studies were carried out to characterize the system???s capability in determining changes in concentration of purified DNA in DI water. To adequately measure the change in DNA concentration in a PCR solution, it was necessary to go through a purification and precipitation step to minimize the effects of primers, PCR reagents, and especially excess salts. It was shown that the purification and precipitation of the fully amplified PCR reaction showed a similar trend to the pure DNA in DI water characterization tests. In developing the two versions of label-free detection systems, this work has brought cheaper, faster, smaller biosensors one step closer to reality

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