Abstract

Since the foodborne pathogenic bacteria cause serious diseases and socio-economic losses throughout the world, the molecular diagnosis of foodborne poisoning pathogen in the early stage is essential for preventing excessive damages. In this study, a colorimetric based foodborne pathogen detection on the centrifugal microdevice was demonstrated in a high throughput manner. The developed centrifugal microdevice consists of a sample reservoir, a spiral shaped sample injection microchannel, 24 aliqouting chambers (2.5μL each), cross capillary valves, and 24 reaction chambers on a single device. Once the sample was loaded, the rotation speed at 850rpm allowed the sample solution to be divided into 24 aliqouting chambers. Then, the samples loaded in the aliqouting chambers could be injected into the reaction chambers at 5000rpm evenly. The centrifugal device was placed in an oven at 66°C for target gene amplification. As a gene amplification method, loop mediated isothermal amplification (LAMP) was used in which specific primer sets targeting three kinds of foodborne pathogens (Escherichia coli O157:H7, Salmonella typhimurium, and Vibrio parahaemolyticus) were included. The presence of each pathogen was identified by Eriochrome Black T (EBT)-mediated colorimetric change from purple to sky blue with the naked eye, and the color of each reaction chamber was analyzed by a ratiometric image processing method. Green/Red (G/R) and Blue/Red (B/R) ratios were set as the criteria to differentiate negative results from positive ones. The threshold values for G/R (0.915<G/R<1.098) and B/R (B/R=1.2723) ratios were determined from 216 experimental data (84 negative and 132 positive) using the RGB-based image processing method. The entire genetic analytical process was completed on the high-throughput centrifugal microdevice within 1h. The extracted DNA of each pathogen was successfully amplified and detected at a 500 copy level. Furthermore, the bacterial cell could be directly used as a sample and analyzed at a 100 cell level, thereby demonstrating the great potential for the sample-to-answer generic analysis of pathogens on a chip even in resource limited environments.

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