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황순홍Charles S H Hwang

KAIST

ACS Appl. Mater. Interfaces, 2022 Dec 14;14(49):54550-54557 | https://doi.org/10.1021/acsami.2c16446 Highly Adsorptive Au-TiO2 Nanocomposites for the SERS Face Mask Allow the Machine-Learning-Based Quantitative Assay of SARS-CoV-2 in Artificial Breath Aerosols

Charles S H Hwang ^1,2, Sangyeon Lee ¹, Sejin Lee ^1,2, Hanjin Kim ¹, Taejoon Kang ^3,4, Doheon Lee ¹, Ki-Hun Jeong ^1,2

¹Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea.
²KAIST Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea.
³Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-gu, Daejeon 34141, Korea.
⁴School of Pharmacy, Sungkyunkwan University, Suwon 16419, Korea.

C.S.H.H. and S.L. contributed equally to this work.
Corresponding Authors : Doheon Lee, Ki-Hun Jeong

Abstract

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-TiO₂ nanocomposite SERS face mask and an ablation-assisted autoencoder. The Au-TiO₂ 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-TiO₂ 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 10¹-10⁴ 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-TiO₂ SERS face mask provides a platform for breath biopsy for the detection of various biomarkers in respiratory aerosols.

논문정보

형식Research article
게재일2022년 12월 (BRIC 등록일 2023-03-06)
연구진국내 연구진
분야 바이오·의료융합 > 바이오센싱 및 나노바이오물질

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