TY - JOUR
T1 - Novel, accurate pathogen sensors for fast detection of SARS-CoV-2 in the aerosol in seconds for a breathalyzer platform
AU - Shi, Xiaoling
AU - Sadeghi, Pardis
AU - Lobandi, Nader
AU - Emam, Shadi
AU - Seyed Abrishami, Seyed Mahdi
AU - Martos-Repath, Isabel
AU - Mani, Natesan
AU - Nasrollahpour, Mehdi
AU - Sun, William
AU - Rones, Stav
AU - Kwok, Joshua
AU - Shah, Harsh
AU - Charles, Joseph
AU - Khan, Zulqarnain
AU - Pagsuyoin, Sheree
AU - Rojjanapinun, Akarapan
AU - Liu, Ping
AU - Chae, Jeongmin
AU - Ferreira Da Costa, Maxime
AU - Li, Jianxiu
AU - Sun, Xin
AU - Yang, Mengdi
AU - Li, Jiahe
AU - Dy, Jennifer
AU - Wang, Jennifer
AU - Luban, Jeremy
AU - Chang, Ching Wen
AU - Finberg, Robert
AU - Mitra, Urbashi
AU - Cash, Sydney
AU - Robbins, Gregory
AU - Hodys, Cole
AU - Lu, Hui
AU - Wiegand, Patrick
AU - Rieger, Robert
AU - Sun, Nian X.
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2023/9
Y1 - 2023/9
N2 - Rapid and accurate detection of the pathogens, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for COVID-19, is critical for mitigating the COVID-19 pandemic. Current state-of-the-art pathogen tests for COVID-19 diagnosis are done in a liquid medium and take 10–30 min for rapid antigen tests and hours to days for polymerase chain reaction (PCR) tests. Herein we report novel accurate pathogen sensors, a new test method, and machine-learning algorithms for a breathalyzer platform for fast detection of SARS-CoV-2 virion particles in the aerosol in 30 s. The pathogen sensors are based on a functionalized molecularly-imprinted polymer, with the template molecules being the receptor binding domain spike proteins for different variants of SARS-CoV-2. Sensors are tested in the air and exposed for 10 s to the aerosols of various types of pathogens, including wild-type, D614G, alpha, delta, and omicron variant SARS-CoV-2, BSA (Bovine serum albumin), Middle East respiratory syndrome–related coronavirus (MERS-CoV), influenza, and wastewater samples from local sewage. Our low-cost, fast-responsive pathogen sensors yield accuracy above 99% with a limit-of-detection (LOD) better than 1 copy/μL for detecting the SARS-CoV-2 virus from the aerosol. The machine-learning algorithm supporting these sensors can accurately detect the pathogens, thereby enabling a new and unique breathalyzer platform for rapid COVID-19 tests with unprecedented speeds.
AB - Rapid and accurate detection of the pathogens, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for COVID-19, is critical for mitigating the COVID-19 pandemic. Current state-of-the-art pathogen tests for COVID-19 diagnosis are done in a liquid medium and take 10–30 min for rapid antigen tests and hours to days for polymerase chain reaction (PCR) tests. Herein we report novel accurate pathogen sensors, a new test method, and machine-learning algorithms for a breathalyzer platform for fast detection of SARS-CoV-2 virion particles in the aerosol in 30 s. The pathogen sensors are based on a functionalized molecularly-imprinted polymer, with the template molecules being the receptor binding domain spike proteins for different variants of SARS-CoV-2. Sensors are tested in the air and exposed for 10 s to the aerosols of various types of pathogens, including wild-type, D614G, alpha, delta, and omicron variant SARS-CoV-2, BSA (Bovine serum albumin), Middle East respiratory syndrome–related coronavirus (MERS-CoV), influenza, and wastewater samples from local sewage. Our low-cost, fast-responsive pathogen sensors yield accuracy above 99% with a limit-of-detection (LOD) better than 1 copy/μL for detecting the SARS-CoV-2 virus from the aerosol. The machine-learning algorithm supporting these sensors can accurately detect the pathogens, thereby enabling a new and unique breathalyzer platform for rapid COVID-19 tests with unprecedented speeds.
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U2 - 10.1016/j.biosx.2023.100369
DO - 10.1016/j.biosx.2023.100369
M3 - Article
AN - SCOPUS:85164705255
SN - 2590-1370
VL - 14
JO - Biosensors and Bioelectronics: X
JF - Biosensors and Bioelectronics: X
M1 - 100369
ER -