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A review of nucleic acid-based detection methods for foodborne viruses: Sample pretreatment and detection techniques
Tai-Yong Kim1, Xiaoning Zhu2, Se-Min Kim3
1Research Group of Food Safety and Distribution, Korea Food Research Institute (KFRI), Wanju-gun, Jeollabuk-do 55365, Republic of Korea.
Abstract:
Viruses are major pathogens that cause food poisoning when ingested via contaminated food and water. Therefore, the development of foodborne virus detection technologies that can be applied throughout the food distribution chain is essential for food safety. A common nucleic acid-based detection method is polymerase chain reaction (PCR), which has become the gold standard for monitoring food contamination by viruses due to its high sensitivity, and availability of commercial kits. However, PCR-based methods are labor intensive and time consuming, and are vulnerable to inhibitors that may be present in food samples. In addition, the methods are restricted with regard to site of analysis due to the requirement of expensive and large equipment for sophisticated temperature regulation and signal analysis procedures. To overcome these limitations, optical and electrical readout biosensors based on nucleic acid isothermal amplification technology and nanomaterials have emerged as alternatives for nucleic acid-based detection of foodborne viruses. Biosensors are promising portable detection tools owing to their easy integration into compact platforms and ability to be operated on-site. However, the complexity of food components necessitates the inclusion of tedious preprocessing steps, and the lack of stability studies on residual food components further restricts the practical application of biosensors as a universal detection method. Here, we summarize the latest advances in nucleic acid-based strategies for the detection of foodborne viruses, including PCR-based and isothermal amplification-based methods, gene amplification-free methods, as well as food pretreatment methods. The principles, strengths/disadvantages, and performance of each method, problems to be solved, and future prospects for the development of a universal detection method are discussed.
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