Rapid and background-free detection of avian influenza virus in opaque sample using NIR-to-NIR upconversion nanoparticle-based lateral flow immunoassay platform
- Rapid and background-free detection of avian influenza virus in opaque sample using NIR-to-NIR upconversion nanoparticle-based lateral flow immunoassay platform
- 표희수; 김승기; 이석; 이관희; 김상경; 이준석; 이효진; 김재영; 권정훈; 장진영; 한영기; 송창선
- Issue Date
- Biosensors and bioelectronics
- VOL 112-215
- Rapid and sensitive on-site detection of avian influenza virus (AIV) is the key for achieving near real-time surveillance of AIV and reducing the risk of dissemination. However, unlike the laboratory-prepared transparent buffer solutions containing a single type of influenza virus, distinction between real- and false-positive outputs and detection of low concentrations of AN in stool specimens or cloacal swabs are difficult. Here, we developed a rapid and background-free lateral flow immunoassay (LFA) platform that utilizes near-infrared (NIR)-to-NIR upconversion nanoparticles (UCNPs) to yield a sensor that detects AIV nucleoproteins (NPs) from clinical samples within 20 min. Ca2+ as a heterogeneous dopant ion in the shell enhanced the NIR-to-NIR upconversion photoluminescence (PL) emission without inducing significant changes in the morphology of the UCNPs. In a mixture of opaque stool samples and gold nanoparticles (GNPs), which are components of commercial AN LFA, the background signal of the stool samples masked the absorption peak of GNPs. However, UCNPs dispersed in the stool samples still show strong emission centered at 800 nm when excited at 980 nm, which enables the NIR-to-NIR upconversion nanoparticle-based lateral flow immunoassay (NNLFA) platform to detect 10-times lower viral load than a commercial GNP-based MV LFA. The detection limit of NNLFA for LPAI H5N2 and HPAI H5N6 viruses was 10(2) and 10(3.5) EID50/mL, respectively. Moreover, the viruses were successfully detected within dark brown-colored samples using the NNLFA but not the commercial AN LFA. Therefore, the rapid and background free NNLFA platform can be used for sensitive on-site detection of MV.
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