Abstract
DNA microarrays are promising high-throughput tools for multiple pathogen detection. Currently, the performance and cost of this platform has limited its broad application in identifying microbial contaminants in foods. In this study, an optimized custom DNA microarray with flexibility in design and content for foodborne pathogen detection was developed through the systematic evaluation of spotting buffers, probe lengths, scanning conditions, and nucleic acid amplification and labeling strategies. Briefly, by robotic contact printing, a spotting solution of 50 % dimethylsulfoxide produced uniform and high-quality spots on UltraGAPS glass slides coated with aminopropyl silane. The use of 60 % photomultiplier tube gain in scanning ∼70-mer oligonucleotide probes resulted in strong signals and low background. For sample preparation, multiplex PCR amplification coupled with fluorescent labeling of DNA using the Klenow fragment and random hexamers achieved higher specificity than whole genome random amplification. To minimize the cost of the assay, the quantities of probes, Klenow fragment, and Cy5 were substantially reduced in each assay without noticeably affecting the detection efficiency. Applying the optimized microarray assay to 26 fresh meat samples, three different isolates of Escherichia coli O157:H7 were found in four individual packages, demonstrating that the assay has a great potential for identifying and genotyping multiple pathogens in a real food system.
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Acknowledgments
We would like to acknowledge the US Department of Agriculture, Agricultural Research Service (USDA-ARS), the National Natural Science Foundation of China (grant No. U1204331), and the Science and Technology Department of Henan Province (grant No. 122102310310) for supporting this research. Mention of trade names or commercial products is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. The USDA is an equal opportunity provider and employer.
Conflict of Interest
Biao Suo declare no conflict of interest. Yiping He declare no conflict of interest. Peter Irwin declare no conflict of interest. Andrew Gehring declare no conflict of interest. This article does not contain any studies with human or animal subjects.
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Suo, B., He, Y., Irwin, P. et al. Optimization and Application of a Custom Microarray for the Detection and Genotyping of E. coli O157:H7 in Fresh Meat Samples. Food Anal. Methods 6, 1477–1484 (2013). https://doi.org/10.1007/s12161-013-9639-z
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DOI: https://doi.org/10.1007/s12161-013-9639-z