TY - JOUR
T1 - Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip
AU - Akarapipad, Patarajarin
AU - Kaarj, Kattika
AU - Breshears, Lane E.
AU - Sosnowski, Katelyn
AU - Baker, Jacob
AU - Nguyen, Brandon T.
AU - Eades, Ciara
AU - Uhrlaub, Jennifer L.
AU - Quirk, Grace
AU - Nikolich-Žugich, Janko
AU - Worobey, Michael
AU - Yoon, Jeong Yeol
N1 - Publisher Copyright: © 2022 Elsevier B.V.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - 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.
AB - 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.
KW - COVID-19
KW - Capillary action
KW - Particle immunoagglutination
KW - Respiratory virus
KW - Smartphone-based biosensor
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U2 - 10.1016/j.bios.2022.114192
DO - 10.1016/j.bios.2022.114192
M3 - Article
C2 - 35334331
SN - 0956-5663
VL - 207
JO - Biosensors and Bioelectronics
JF - Biosensors and Bioelectronics
M1 - 114192
ER -