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Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip.
Akarapipad, Patarajarin; Kaarj, Kattika; Breshears, Lane E; Sosnowski, Katelyn; Baker, Jacob; Nguyen, Brandon T; Eades, Ciara; Uhrlaub, Jennifer L; Quirk, Grace; Nikolich-Zugich, Janko; Worobey, Michael; Yoon, Jeong-Yeol.
  • Akarapipad P; Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States.
  • Kaarj K; Department of Biosystems Engineering, The University of Arizona, Tucson, AZ, 85721, United States.
  • Breshears LE; Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States.
  • Sosnowski K; Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States.
  • Baker J; Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States.
  • Nguyen BT; Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States.
  • Eades C; Department of Chemistry & Biochemistry, The University of Arizona, Tucson, AZ, 85721, United States.
  • Uhrlaub JL; Department of Immunobiology and Arizona Center on Aging, The University of Arizona College of Medicine, Tucson, AZ, 85724, United States.
  • Quirk G; Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, 85721, United States.
  • Nikolich-Zugich J; Department of Immunobiology and Arizona Center on Aging, The University of Arizona College of Medicine, Tucson, AZ, 85724, United States.
  • Worobey M; Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, 85721, United States.
  • Yoon JY; Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States; Department of Biosystems Engineering, The University of Arizona, Tucson, AZ, 85721, United States; Department of Chemistry & Biochemistry, The University of Arizona, Tucson, AZ, 85721, United State
Biosens Bioelectron ; 207: 114192, 2022 Jul 01.
Article in English | MEDLINE | ID: covidwho-1739563
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biosensing Techniques / Influenza A Virus, H1N1 Subtype / COVID-19 Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Biosens Bioelectron Journal subject: Biotechnology Year: 2022 Document Type: Article Affiliation country: J.bios.2022.114192

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biosensing Techniques / Influenza A Virus, H1N1 Subtype / COVID-19 Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Biosens Bioelectron Journal subject: Biotechnology Year: 2022 Document Type: Article Affiliation country: J.bios.2022.114192