4.8 Article

Colorimetric Detection of SARS-CoV-2 Using Plasmonic Biosensors and Smartphones

Journal

ACS APPLIED MATERIALS & INTERFACES
Volume 14, Issue 49, Pages 54527-54538

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsami.2c15407

Keywords

gold nanoparticles; localized surface plasmon resonance; plasmonic coupling; SARS-CoV-2; point-of-care; machine learning; image processing; portable sensor

Funding

  1. CAPES [001]
  2. INEO
  3. CNPq [402816/2020-0, 304431/2020-6, 465389/2014-7, 115857/2022-2, 311757/2019-7]
  4. FAPESP [2018/22214-6, 2014/50867-3, 2019/19235-4, 2021/08387-8, 2017/03879-4]
  5. Edital de projetos integrados de pesquisa em areas estrategicas (PIPAE)

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Low-cost, instrument-free colorimetric tests were developed using plasmonic biosensors with Au nanoparticles functionalized with polyclonal antibodies. The tests showed high sensitivity and accuracy in detecting SARS-CoV-2, and could be used in dynamic light scattering and UV-vis spectroscopy. By processing the images collected from smartphone cameras with image processing and machine learning algorithms, 100% accurate COVID-19 diagnosis for saliva samples could be achieved.
Low-cost, instrument-free colorimetric tests were developed to detect SARS-CoV-2 using plasmonic biosensors with Au nanoparticles functionalized with polyclonal antibodies (f-AuNPs). Intense color changes were noted with the naked eye owing to plasmon coupling when f-AuNPs form clusters on the virus, with high sensitivity and a detection limit of 0.28 PFU mL(-1) (PFU stands for plaque-forming units) in human saliva. Plasmon coupling was corroborated with computer simulations using the finite-difference time-domain (FDTD) method. The strategies based on preparing plasmonic biosensors with f-AuNPs are robust to permit SARS-CoV-2 detection via dynamic light scattering and UV-vis spectroscopy without interference from other viruses, such as influenza and dengue viruses. The diagnosis was made with a smartphone app after processing the images collected from the smartphone camera, measuring the concentration of SARS-CoV-2. Both image processing and machine learning algorithms were found to provide COVID-19 diagnosis with 100% accuracy for saliva samples. In subsidiary experiments, we observed that the biosensor could be used to detect the virus in river waters without pretreatment. With fast responses and requiring small sample amounts (only 20 mu L), these colorimetric tests can be deployed in any location within the point-of-care diagnosis paradigm for epidemiological control.

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