Multiplexed and High-Throughput Label-Free Detection of RNA/Spike Protein/IgG/IgM Biomarkers of SARS-CoV-2 Infection Utilizing Nanoplasmonic Biosensors

Abstract

To tackle the COVID-19 outbreak, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an unmet need for highly accurate diagnostic tests at all stages of infection with rapid results and high specificity. Here, we present a label-free nanoplasmonic biosensor-based, multiplex screening test for COVID-19 that can quantitatively detect 10 different biomarkers (6 viral nucleic acid genes, 2 spike protein subunits, and 2 antibodies) with a limit of detection in the aM range, all within one biosensor platform. Our newly developed nanoplasmonic biosensors demonstrate high specificity, which is of the upmost importance to avoid false responses. As a proof of concept, we show that our detection approach has the potential to quantify both IgG and IgM antibodies directly from COVID-19-positive patient plasma samples in a single instrument run, demonstrating the high-throughput capability of our detection approach. Most importantly, our assay provides receiving operating characteristics, areas under the curve of 0.997 and 0.999 for IgG and IgM, respectively. The calculated p-value determined through the Mann-Whitney nonparametric test is <0.0001 for both antibodies when the test of COVID-19-positive patients (n = 80) is compared with that of healthy individuals (n = 72). Additionally, the screening test provides a calculated sensitivity (true positive rate) of 100% (80/80), a specificity (true negative rate) >96% (77/80), a positive predictive value of 98% at 5% prevalence, and a negative predictive value of 100% at 5% prevalence. We believe that our very sensitive, multiplex, high-throughput testing approach has potential applications in COVID-19 diagnostics, particularly in determining virus progression and infection severity for clinicians for an appropriate treatment, and will also prove to be a very effective diagnostic test when applied to diseases beyond the COVID-19 pandemic.