Monday, 14 May 2018: 08:55
Room 310 (Washington State Convention Center)
A. Ghuman, Y. Zhou (School of Chemical, Materials and Biomedical Engineering, Nano Electrochemistry Laboratory, University of Georgia), Y. Liu (Department of Chemistry, University of Georgia), L. Mao (School of Electrical and Computer Engineering, University of Georgia), and R. P. Ramasamy (School of Chemical, Materials and Biomedical Engineering, University of Georgia)
Foodborne illnesses caused by pathogenic microorganisms are a major threat to worldwide public health.
Listeria monocytogenes is among the most common pathogens contributing to domestically acquired foodborne illnesses (1). Most foodborne cases of listeriosis present as life-threatening illnesses in the forms of neonatal listeriosis, blood stream infection, and meningoencephalitis. There is a high priority amongst public health officials to identify
Listeria outbreak sources and reduce mortality rates of this disease (2). Since the current methods for bacteria enrichment are time consuming and require sophisticated instruments, they are impossible to reproduce in a non-laboratory setting. There is a growing need to develop field-deployable technologies that are able to rapidly and accurately detect harmful pathogens in complex food matrices such as milk, juice, vegetables, meat, and poultry (3, 4).
This work describes a microfluidic cell sorting device that uses magnetophoresis to detect, separate, and concentrate tagged Listeria monocytogenes from food samples. Bacteriophage-functionalized magnetic particles will be used to isolate the bacteria in a food sample for pre-enrichment, which will allow for more rapid and selective cell sorting followed by impedimetric detection of Listeria in an electrochemical cell. We will report on the effects of flow rate and viscosity of the sample feed on the separation efficiency, as well as the throughput of enriched target bacteria from different food matrices. These enriched samples will be used in various biosensor applications for detection and identification of pathogenic bacteria in food samples.
References
- E. Scallan, R. M. Hoekstra, F. J. Angulo, R. V. Tauxe, M. A. Widdowson, S. L. Roy, J. L. Jones and P. M. Griffin, Emerg Infect Dis, 17, 7 (2011).
- B. Swaminathan and P. Gerner-Smidt, Microbes Infect, 9, 1236 (2007).
- X. Weng and S. Neethirajan, Trends in Food Science & Technology, 65, 10 (2017).
- Y. Jiang, S. Zou and X. Cao, Anal. Methods, 8, 6668 (2016).
