Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min
Issued Date
2022-02-22
Resource Type
ISSN
19360851
eISSN
1936086X
Scopus ID
2-s2.0-85123929150
Pubmed ID
35040314
Journal Title
ACS Nano
Volume
16
Issue
2
Start Page
2629
End Page
2639
Rights Holder(s)
SCOPUS
Bibliographic Citation
ACS Nano Vol.16 No.2 (2022) , 2629-2639
Suggested Citation
Leong S.X., Leong Y.X., Tan E.X., Sim H.Y.F., Koh C.S.L., Lee Y.H., Chong C., Ng L.S., Chen J.R.T., Pang D.W.C., Nguyen L.B.T., Boong S.K., Han X., Kao Y.C., Chua Y.H., Phan-Quang G.C., Phang I.Y., Lee H.K., Abdad M.Y., Tan N.S., Ling X.Y. Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min. ACS Nano Vol.16 No.2 (2022) , 2629-2639. 2639. doi:10.1021/acsnano.1c09371 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/84601
Title
Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min
Other Contributor(s)
Abstract
Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes.
