Nonstochastic Protein Counting Analysis for Precision Biomarker Detection: Suppressing Poisson Noise at Ultralow Concentration

Protein counting analysis obtains the quantitative results of specific protein through counting the number of target signals and displays a great value in disease diagnosis. Current protein counting techniques just stochastically count a small portion of the target signal, which causes a considerable information loss and limits the accuracy and precision of the protein assay at ultralow concentration. Here, we present a nonstochastic and ultrasensitive protein counting method through combining multiround evaporation-induced particle sedimentation, grid-assisted multiframe imaging, and microsphere-enhanced high-resolution signals. Using carcinoembryonic antigen (CEA) as the model, the dynamic range was from 5 × 10–18 M (aM) to 5 × 10–16 M, and the limit of detection was 4.9 aM. For CEA-spiked plasma detection, the relative standard deviation and the relative error of CEA concentrations were both lower than 8.0%, and the recoveries reached 92.5% and 98.8% for 20.0 aM and 40.0 aM CEA respectively. Two clinical plasma samples were measured by the standard addition method, and the results showed little deviation with the values provided by the hospital. The established approach suppresses Poisson noise of the stochastic counting, offers ultrahigh sensitivity, and features a remarkable potential in early disease screening.