A single-step, digital immunoassay based on serial imaging and image processing

Abstract

Single-step immunoassays have attracted much attention compared with conventional multi-step sandwich immunoassays, owing to their user-friendliness, minimization of potential errors (e.g., false signals) arising from multistep procedures, and reduced diagnosis time. However, developing a single-step immunoassay with high sensitivity and accuracy has remained challenging. In this study, we developed a single-step, digital immunoassay by applying an imaging technique to a typical sandwich immunoassay, leading to high sensitivity and accuracy. The imaging technology—composed of serial imaging of a sensing surface, stacking of the obtained images, and particle counting using an algorithm—enabled the differentiation of bound and unbound conjugates (detection antibody-conjugated polystyrene beads) without washing. Stationary bound conjugates became more distinct after stacking over 30 images, while randomly drifting unbound conjugates disappeared, enabling the counting of only individual bound labels. The platform efficiently detected SARS-CoV-2 nucleocapsid protein in the concentration range of 10 pg mL–1 to 1 ng mL–1 (limit of detection, 0.87 pg mL–1), which was 103 times more sensitive than that of a conventional lateral flow immunoassay. This immunoassay could be a promising method for highly sensitive and accurate point-of-care biosensors. © 2024 Elsevier B.V.