Spectral Image Contrast Based Flow Digital Nanoplasmon-metry For Ultrasensitive Antibody Detection

Abstract Background: Gold nanoparticles (AuNPs) have been widely used as local surface plasmon resonance (LSPR) immunoassay for biomolecule sensings. It is primarily based on two conventional methods - absorption spectra and colorimetric. While the low figure of merit (FoM) of the LSPR and high-concentration AuNPs requirement restrict their limit of detection (LOD), which is around ng to μg per mL in antibody detection if there is no other signal or analytes amplification. By now, the improvement of sensitivity has bogged down for years. It also reveals a great challenge of the current LSPR immunoassay in biosensing - pushing the boundary of the current LOD. Results: In this work, we developed a spectral image contrast-based flow digital nanoplasmon-metry(FDNM) to push the LOD boundary. Comparing the scattering image brightness of AuNPs in two neighboring wavelength bands near the LSPR peak, the signal of peak shift is extremely amplified and quickly detected. Introducing the digital analysis, the FDNM provides an ultra-high signal-to-noise ratio and less sample volume requirement. Compared to conventional analog LSPR immunoassay, FDNM has a LOD down to 1 pg mL -1 within only a 15-minute detection time and 500 μL sample volume. Antibody against spike proteins of SARS-CoV-2 in artificial saliva that contained various proteins was also conducted to validate the detection of FDNM in complicated samples. Of the detection, FDNM shows significant discrimination with a LOD of 10 pg mL -1 and a broad dynamic detecting range of five orders of magnitude. Conclusion: Together with the quick readout time and simple operation, this work outstandingly demonstrated the high sensitivity and selectivity of the developed FDNM in rapid antibody detection. The spectral image contrast and digital analysis further provide a new generation LSPR immunoassay of AuNPs.