Abstract
Surface-enhanced Raman scattering (SERS)-based aptasensors display high sensitivity for influenza A/H1N1 virus detection but improved signal reproducibility is required. Therefore, in this study, we fabricated a three-dimensional (3D) nano-popcorn plasmonic substrate using the surface energy difference between a perfluorodecanethiol (PFDT) spacer and the Au layer. This energy difference led to Au nanoparticle self-assembly; neighboring nanoparticles then created multiple hotspots on the substrate. The localized surface plasmon effects at the hot spots dramatically enhanced the incident field. Quantitative evaluation of A/H1N1 virus was achieved using the decrease of Raman peak intensity resulting from the release of Cy3-labeled aptamer DNAs from nano-popcorn substrate surfaces via the interaction between the aptamer DNA and A/H1N1 virus. The use of a Raman imaging technique involving the fast mapping of all pixel points enabled the reproducible quantification of A/H1N1 virus on nano-popcorn substrates. Average ensemble effects obtained by averaging all randomly distributed hot spots mapped on the substrate made it possible to reliably quantify target viruses. The SERS-based imaging aptasensor platform proposed in this work overcomes the issues inherent in conventional approaches (the time-consuming and labor-intensiveness of RT-PCR and low sensitivity and quantitative analysis limits of lateral flow assay kits). Our SERS-based assay for detecting A/H1N1 virus had an estimated limit of detection of 97 PFU mL−1 (approximately three orders of magnitude more sensitive than that determined by the enzyme-linked immunosorbent assay) and the approximate assay time was estimated to be 20 min. Thus, this approach provides an ultrasensitive, reliable platform for detecting viral pathogens.
•SERS-based aptasensor was more sensitive in detecting influenza A/H1N1 virus than ELISA.•A 3D nano-popcorn plasmonic substrate was fabricated to improve reproducibility.•SERS-based aptasensor enabled highly efficient influenza A/H1N1 virus detection.