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

Autor:	Chen H; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Li Z; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Feng S; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Wang A; Bioengineering Graduate Program, University of Pennsylvania, Philadelphia, PA., Richard-Greenblatt M; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Hutson E; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Andrianus S; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Glaser LJ; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Rodino KG; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Qian J; Department of Computer and Information Science and GRASP Lab, University of Pennsylvania, Philadelphia, PA., Jayaraman D; Department of Computer and Information Science and GRASP Lab, University of Pennsylvania, Philadelphia, PA., Collman RG; Department of Medicine, University of Pennsylvania, Philadelphia, PA., Glascock A; Department of Microbiology and Penn Center for Research on Coronavirus and Other Emerging Pathogens, University of Pennsylvania, Philadelphia, PA., Bushman FD; Department of Microbiology and Penn Center for Research on Coronavirus and Other Emerging Pathogens, University of Pennsylvania, Philadelphia, PA., Lee JS; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Cherry S; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Fausto A; Department of Microbiology and Penn Center for Research on Coronavirus and Other Emerging Pathogens, University of Pennsylvania, Philadelphia, PA., Weiss SR; Department of Microbiology and Penn Center for Research on Coronavirus and Other Emerging Pathogens, University of Pennsylvania, Philadelphia, PA., Koo H; Department of Orthodontics, Divisions of Pediatric Dentistry and Community of Oral Health, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA.; Center for Innovation & Precision Dentistry, School of Dental Medicine and School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA., Corby PM; Center for Innovation & Precision Dentistry, School of Dental Medicine and School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA.; Department of Oral Medicine, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA.; Center for Clinical and Translational Research, University of Pennsylvania, Philadelphia, PA., O'Doherty U; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA., Garfall AL; Department of Medicine, University of Pennsylvania, Philadelphia, PA., Vogl DT; Department of Medicine, University of Pennsylvania, Philadelphia, PA., Stadtmauer EA; Department of Medicine, University of Pennsylvania, Philadelphia, PA., Wang P; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA.; Bioengineering Graduate Program, University of Pennsylvania, Philadelphia, PA.
Jazyk:	angličtina
Zdroj:	MedRxiv : the preprint server for health sciences [medRxiv] 2021 Mar 26. Date of Electronic Publication: 2021 Mar 26.
DOI:	10.1101/2021.03.17.21253847
Abstrakt:	Background: Little is known about the dynamics of SARS-CoV-2 antigen burden in respiratory samples in different patient populations at different stages of infection. Current rapid antigen tests cannot quantitate and track antigen dynamics with high sensitivity and specificity in respiratory samples. Methods: We developed and validated an ultra-sensitive SARS-CoV-2 antigen assay with smartphone readout using the Microbubbling Digital Assay previously developed by our group, which is a platform that enables highly sensitive detection and quantitation of protein biomarkers. A computer vision-based algorithm was developed for microbubble smartphone image recognition and quantitation. A machine learning-based classifier was developed to classify the smartphone images based on detected microbubbles. Using this assay, we tracked antigen dynamics in serial swab samples from COVID patients hospitalized in ICU and immunocompromised COVID patients. Results: The limit of detection (LOD) of the Microbubbling SARS-CoV-2 Antigen Assay was 0.5 pg/mL (10.6 fM) recombinant nucleocapsid (N) antigen or 4000 copies/mL inactivated SARS-CoV-2 virus in nasopharyngeal (NP) swabs, comparable to many rRT-PCR methods. The assay had high analytical specificity towards SARS-CoV-2. Compared to EUA-approved rRT-PCR methods, the Microbubbling Antigen Assay demonstrated a positive percent agreement (PPA) of 97% (95% confidence interval (CI), 92-99%) in symptomatic individuals within 7 days of symptom onset and positive SARS-CoV-2 nucleic acid results, and a negative percent agreement (NPA) of 97% (95% CI, 94-100%) in symptomatic and asymptomatic individuals with negative nucleic acid results. Antigen positivity rate in NP swabs gradually decreased as days-after-symptom-onset increased, despite persistent nucleic acid positivity of the same samples. The computer vision and machine learning-based automatic microbubble image classifier could accurately identify positives and negatives, based on microbubble counts and sizes. Total microbubble volume, a potential marker of antigen burden, correlated inversely with Ct values and days-after-symptom-onset. Antigen was detected for longer periods of time in immunocompromised patients with hematologic malignancies, compared to immunocompetent individuals. Simultaneous detectable antigens and nucleic acids may indicate the presence of replicating viruses in patients with persistent infections. Conclusions: The Microbubbling SARS-CoV-2 Antigen Assay enables sensitive and specific detection of acute infections, and quantitation and tracking of antigen dynamics in different patient populations at various stages of infection. With smartphone compatibility and automated image processing, the assay is well-positioned to be adapted for point-of-care diagnosis and to explore the clinical implications of antigen dynamics in future studies.
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu