LAUSR

A sensor capable of quantifying both anti-SARS-CoV-2 spike receptor-binding domain (RBD) antibody levels and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in saliva and serum was developed. This was accomplished by exploiting the enzymatic reaction of maltose and orthophosphate (PO43–) in the presence of maltose phosphorylase to generate an equivalent amount of glucose that was detected using a commercial glucometer test strip and a potentiostat. Important for this approach is the ability to generate PO43– in an amount that is directly related to the concentration of the analytes. RBD-modified magnetic microparticles were used to capture anti-SARS-CoV-2 spike RBD antibodies, while particles modified with anti-SARS-CoV-2 nucleocapsid antibodies were used to capture SARS-CoV-2 nucleocapsid protein from inactivated virus samples. A magnet was used to isolate and purify the magnetic microparticles (with analyte attached), and alkaline phosphatase-conjugated secondary antibodies were bound to the analytes attached to the respective magnetic microparticles. Finally, through enzymatic reactions, specific amounts of PO43– (and subsequently glucose) were generated in proportion to the analyte concentration, which was then quantified using a commercial glucometer test strip. Utilizing glucose test strips makes the sensor relatively inexpensive, with a cost per test of ∼US $7 and ∼US $12 for quantifying anti-SARS-CoV-2 spike RBD antibody and SARS-CoV-2, respectively. Our sensor exhibited a limit of detection of 0.42 ng/mL for anti-SARS-CoV-2 spike RBD antibody, which is sensitive enough to quantify typical concentrations of antibodies in COVID-19-infected or vaccinated individuals (>1 μg/mL). The limit of detection for the SARS-CoV-2 virus is 300 pfu/mL (5.4 × 106 RNA copies/mL), which exceeds the performance recommended by the WHO (500 pfu/mL). In addition, the sensor exhibited good selectivity when challenged with competing analytes and could be used to quantify analytes in saliva and serum matrices with an accuracy of >94% compared to RT-qPCR.