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Cady NC, Tokranova N, Minor A, Nikvand N, Strle K, Lee WT, Page W, Guignon E, Pilar A, Gibson GN. Multiplexed detection and quantification of human antibody response to COVID-19 infection using a plasmon enhanced biosensor platform. Biosens Bioelectron 2021; 171:112679. [PMID: 33069957 PMCID: PMC7545244 DOI: 10.1016/j.bios.2020.112679] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 09/30/2020] [Accepted: 10/01/2020] [Indexed: 12/18/2022]
Abstract
The 2019 SARS CoV-2 (COVID-19) pandemic has illustrated the need for rapid and accurate diagnostic tests. In this work, a multiplexed grating-coupled fluorescent plasmonics (GC-FP) biosensor platform was used to rapidly and accurately measure antibodies against COVID-19 in human blood serum and dried blood spot samples. The GC-FP platform measures antibody-antigen binding interactions for multiple targets in a single sample, and has 100% selectivity and sensitivity (n = 23) when measuring serum IgG levels against three COVID-19 antigens (spike S1, spike S1S2, and the nucleocapsid protein). The GC-FP platform yielded a quantitative, linear response for serum samples diluted to as low as 1:1600 dilution. Test results were highly correlated with two commercial COVID-19 antibody tests, including an enzyme linked immunosorbent assay (ELISA) and a Luminex-based microsphere immunoassay. To demonstrate test efficacy with other sample matrices, dried blood spot samples (n = 63) were obtained and evaluated with GC-FP, yielding 100% selectivity and 86.7% sensitivity for diagnosing prior COVID-19 infection. The test was also evaluated for detection of multiple immunoglobulin isotypes, with successful detection of IgM, IgG and IgA antibody-antigen interactions. Last, a machine learning approach was developed to accurately score patient samples for prior COVID-19 infection, using antibody binding data for all three COVID-19 antigens used in the test.
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Affiliation(s)
- Nathaniel C Cady
- College of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA.
| | - Natalya Tokranova
- College of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA
| | - Armond Minor
- College of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA
| | - Nima Nikvand
- College of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA
| | - Klemen Strle
- Wadsworth Center, New York State Department of Health, Albany, NY, USA and School of Public Health, University at Albany, Albany, NY, USA
| | - William T Lee
- Wadsworth Center, New York State Department of Health, Albany, NY, USA and School of Public Health, University at Albany, Albany, NY, USA
| | | | | | | | - George N Gibson
- Ciencia, Inc., East Hartford, CT, USA; University of Connecticut, Storrs, CT, USA
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