Detecting Food‐ and Waterborne Viruses by Surface‐Enhanced Raman Spectroscopy

Fan, Cui; Hu, Zhiqiang; Riley, Lela K.; Purdy, Gregory A.; Mustapha, Azlin; Lin, Mengshi

Abstract: Food‐ and waterborne viruses pose serious health risks to humans and were associated with many outbreaks worldwide. Rapid, accurate, and nondestructive methods for detection of viruses are of great importance to protect public health. In this study, surface‐enhanced Raman spectroscopy (SERS) coupled with gold SERS‐active substrates was used to detect and discriminate 7 food‐ and waterborne viruses, including norovirus, adenovirus, parvovirus, rotavirus, coronavirus, paramyxovirus, and herpersvirus. Virus samples were purified and dialyzed in phosphate buffered saline (8 to 9 log PFU/mL) and then further diluted in deionized water for SERS measurement. After capturing the characteristic SERS spectral patterns, multivariate statistical analyses, including soft independent modeling of class analogy (SIMCA) and principal component analysis (PCA), were employed to analyze SERS spectral data for characterization and identification of viruses. The results show that SIMCA was able to differentiate viruses with and without envelope with >95% of classification accuracy, while PCA presented clear spectral data segregations between different virus strains. The virus detection limit by SERS using gold substrates reached a titer of 10(2). Practical Application: SERS is a simple, rapid, and accurate method for detection of food‐ and waterborne viruses. Our results demonstrate that coupled with gold substrates, SERS was able to rapidly detect and discriminate among different food‐ and waterborne viruses, indicating that SERS can provide rapid, sensitive, and reproducible detection results with minimum sample preparation for virus detection.