Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip
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Final Accepted Manuscript
Author
Akarapipad, PatarajarinKaarj, Kattika
Breshears, Lane E.
Sosnowski, Katelyn
Baker, Jacob
Nguyen, Brandon T.
Eades, Ciara
Uhrlaub, Jennifer L.
Quirk, Grace
Nikolich-Žugich, Janko
Worobey, Michael
Yoon, Jeong-Yeol
Affiliation
Department of Immunobiology and Arizona Center on Aging, The University of Arizona College of MedicineDepartment of Ecology and Evolutionary Biology, The University of Arizona
Department of Biomedical Engineering, The University of Arizona
Department of Biosystems Engineering, The University of Arizona
Department of Chemistry & Biochemistry, The University of Arizona
Issue Date
2022-03
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Elsevier BVCitation
Akarapipad, P., Kaarj, K., Breshears, L. E., Sosnowski, K., Baker, J., Nguyen, B. T., Eades, C., Uhrlaub, J. L., Quirk, G., Nikolich-Žugich, J., Worobey, M., & Yoon, J.-Y. (2022). Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip. Biosensors and Bioelectronics.Journal
Biosensors and BioelectronicsRights
© 2022 Elsevier B.V. All rights reserved.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Respiratory viruses, especially coronaviruses, have resulted in worldwide pandemics in the past couple of decades. Saliva-based paper microfluidic assays represent an opportunity for noninvasive and rapid screening, yet both the sample matrix and test method come with unique challenges. In this work, we demonstrated the rapid and sensitive detection of SARS-CoV-2 from saliva samples, which could be simpler and more comfortable for patients than existing methods. Furthermore, we systematically investigated the components of saliva samples that affected assay performance. Using only a smartphone, an antibody-conjugated particle suspension, and a paper microfluidic chip, we made the assay user-friendly with minimal processing. Unlike the previously established flow rate assays that depended solely on the flow rate or distance, this unique assay analyzes the flow profile to determine infection status. Particle-target immunoagglutination changed the surface tension and subsequently the capillary flow velocity profile. A smartphone camera automatically measured the flow profile using a Python script, which was not affected by ambient light variations. The limit of detection (LOD) was 1 fg/μL SARS-CoV-2 from 1% saliva samples and 10 fg/μL from simulated saline gargle samples (15% saliva and 0.9% saline). This method was highly specific as demonstrated using influenza A/H1N1. The sample-to-answer assay time was <15 min, including <1-min capillary flow time. The overall accuracy was 89% with relatively clean clinical saline gargle samples. Despite some limitations with turbid clinical samples, this method presents a potential solution for rapid mass testing techniques during any infectious disease outbreak as soon as the antibodies become available.Note
No embargo COVID-19ISSN
0956-5663Version
Final accepted manuscriptSponsors
The University of Arizonaae974a485f413a2113503eed53cd6c53
10.1016/j.bios.2022.114192