Human respiratory aerosols contain diverse potential biomarkers for early disease diagnosis. Here, we report the direct and label-free detection of SARS-CoV-2 in respiratory aerosols using a highly adsorptive Au-TiO_{2} nanocomposite SERS face mask and an ablation-assisted autoencoder. The Au-TiO_{2} SERS face mask continuously preconcentrates and efficiently captures the oronasal aerosols, which substantially enhances the SERS signal intensities by 47% compared to simple Au nanoislands. The ultrasensitive Au-TiO_{2} nanocomposites also demonstrate the successful detection of SARS-CoV-2 spike proteins in artificial respiratory aerosols at a 100 pM concentration level. The deep learning-based autoencoder, followed by the partial ablation of nondiscriminant SERS features of spike proteins, allows a quantitative assay of the 10^{1}-10^{4} pfu/mL SARS-CoV-2 lysates (comparable to 19-29 PCR cyclic threshold from COVID-19 patients) in aerosols with an accuracy of over 98%. The Au-TiO_{2} SERS face mask provides a platform for breath biopsy for the detection of various biomarkers in respiratory aerosols.
【저자키워드】 SARS-CoV-2, plasmonics, machine-learning, Surface-enhanced Raman spectroscopy, nanocomposite, breath biopsy,