Femtomolar SARS-CoV-2 Antigen Detection Using the Microbubbling Digital Assay with Smartphone Readout Enables Antigen Burden Quantitation and Tracking

Author:

Chen Hui1,Li Zhao1,Feng Sheng1,Richard-Greenblatt Melissa1,Hutson Emily1,Andrianus Stefen1,Glaser Laurel J1,Rodino Kyle G1,Qian Jianing2,Jayaraman Dinesh2,Collman Ronald G3,Glascock Abigail4,Bushman Frederic D4,Lee Jae Seung1,Cherry Sara1,Fausto Alejandra4,Weiss Susan R4,Koo Hyun56,Corby Patricia M567,Oceguera Alfonso1,O’Doherty Una1,Garfall Alfred L3,Vogl Dan T3,Stadtmauer Edward A3,Wang Ping1

Affiliation:

1. Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA

2. Department of Computer and Information Science and GRASP Lab, University of Pennsylvania, Philadelphia, PA, USA

3. Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

4. Department of Microbiology and Penn Center for Research on Coronavirus and Other Emerging Pathogens, University of Pennsylvania, Philadelphia, PA, USA

5. Department of Orthodontics, Divisions of Pediatric Dentistry and Community of Oral Health, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA

6. Center for Innovation & Precision Dentistry, School of Dental Medicine and School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA

7. Department of Oral Medicine, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA, Center for Clinical and Translational Research, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA

Abstract

Abstract Background High-sensitivity severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen assays are desirable to mitigate false negative results. Limited data are available to quantify and track SARS-CoV-2 antigen burden in respiratory samples from different populations. Methods We developed the Microbubbling SARS-CoV-2 Antigen Assay (MSAA) with smartphone readout, with a limit of detection of 0.5 pg/mL (10.6 fmol/L) nucleocapsid antigen or 4000 copies/mL inactivated SARS-CoV-2 virus in nasopharyngeal (NP) swabs. We developed a computer vision and machine learning–based automatic microbubble image classifier to accurately identify positives and negatives and quantified and tracked antigen dynamics in intensive care unit coronavirus disease 2019 (COVID-19) inpatients and immunocompromised COVID-19 patients. Results Compared to qualitative reverse transcription−polymerase chain reaction methods, the MSAA demonstrated a positive percentage agreement of 97% (95% CI 92%–99%) and a negative percentage agreement of 97% (95% CI 94%–100%) in a clinical validation study with 372 residual clinical NP swabs. In immunocompetent individuals, the antigen positivity rate in swabs decreased as days-after-symptom-onset increased, despite persistent nucleic acid positivity. Antigen was detected for longer and variable periods of time in immunocompromised patients with hematologic malignancies. Total microbubble volume, a quantitative marker of antigen burden, correlated inversely with cycle threshold values and days-after-symptom-onset. Viral sequence variations were detected in patients with long duration of high antigen burden. Conclusions The MSAA enables sensitive and specific detection of acute infections and quantification and tracking of antigen burden and may serve as a screening method in longitudinal studies to identify patients who are likely experiencing active rounds of ongoing replication and warrant close viral sequence monitoring.

Funder

National Institute of Health

National Science Foundation

Penn Center for Research on Coronaviruses and Other Emerging Pathogens

Penn Center for Precision Medicine

Penn Health-Tech and Penn Center for Innovation & Precision Dentistry

Singh Center for Nanotechnology

National Nanotechnology Coordinated Infrastructure Program, which is supported by the National Science Foundation

Amazon Research

General Electric

NEC Laboratories America

CRISPR Therapeutics to institution

Bill & Melinda Gates Foundation

NIH

Burroughs Wellcome Fund

Mercatus Fast Grant

Publisher

Oxford University Press (OUP)

Subject

Biochemistry (medical),Clinical Biochemistry

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