The detection of single protein molecules1,2 in blood could help identify many new diagnostic protein markers. We report an approach for detecting hundreds to thousands of individual protein molecules simultaneously that enables the detection of very low concentrations of proteins. Proteins are captured on microscopic beads and labeled with an enzyme, such that each bead has either one or zero enzyme-labeled proteins. By isolating these beads in arrays of 50-femtoliter reaction chambers, single proteins can be detected by fluorescence imaging. By singulating molecules in these arrays, ~10–20 enzymes can be detected in 100 μL (~10−19 M). Single molecule enzyme-linked immunosorbent assays (digital ELISA) based on singulation of enzyme labels enabled the detection of clinically-relevant proteins in serum at concentrations (<10−15 M) much lower than conventional ELISA3-5. Digital ELISA detected prostate specific antigen in all tested sera from patients who had undergone radical prostatectomy, down to 14 fg/mL (0.4 fM).

We report a method for combining the detection of single molecules (digital) and an ensemble of molecules (analog) that is capable of detecting enzyme label from 10 −19 M to 10 −13 M, for use in high sensitivity enzyme-linked immunosorbent assays (ELISA). The approach works by capturing proteins on microscopic beads, labeling the proteins with enzymes using a conventional multi-step immunosandwich approach, isolating the beads in an array of 50-femtoliter wells (Single Molecule Array, SiMoA), and detecting bead-associated enzymatic activity using fluorescence imaging. At low concentrations of proteins, when the ratio of enzyme labels to beads is less than ∼1.2, beads carry either zero or low numbers of enzymes, and protein concentration is quantified by counting the presence of "on" or "off" beads (digital regime) 1 . At higher protein concentrations, each bead typically carries multiple enzyme labels, and the average number of enzyme labels present on each bead is quantified from a measure of the average fluorescence intensity (analog regime). Both the digital and analog concentration ranges are quantified by a common unit, namely, average number of enzyme labels per bead (AEB). By combining digital and analog detection of singulated beads, a linear dynamic range of over 6 orders of magnitude to enzyme label was achieved. Using this approach, an immunoassay for prostate specific antigen (PSA) was developed. The combined digital and analog PSA assay provided linear response over approximately four logs of concentration ([PSA] from 8 fg/mL -100 pg/mL or 250 aM -3.3 pM). This approach extends the dynamic range of ELISA from picomolar levels down to subfemtomolar levels in a single measurement.

Disease detection at the molecular level is driving the emerging revolution of early diagnosis and treatment. A challenge facing the field is that protein biomarkers for early diagnosis can be present in very low abundance. The lower limit of detection with conventional immunoassay technology is the upper femtomolar range (10 −13 M). Digital immunoassay technology has improved detection sensitivity three logs, to the attomolar range (10 −16 M). This capability has the potential to open new advances in diagnostics and therapeutics, but such technologies have been relegated to manual procedures that are not well suited for efficient routine use. We describe a new laboratory instrument that provides full automation of single-molecule array (Simoa) technology for digital immunoassays. The instrument is capable of single-molecule sensitivity and multiplexing with short turnaround times and a throughput of 66 samples/h. Singleplex and multiplexed digital immunoassays were developed for 16 proteins of interest in cardiovascular, cancer, infectious disease, neurology, and inflammation research. The average sensitivity improvement of the Simoa immunoassays versus conventional ELISA was >1200-fold, with coefficients of variation of <10%. The potential of digital immunoassays to advance human diagnostics was illustrated in two clinical areas: traumatic brain injury and early detection of infectious disease.

Methods for accurately quantifying the concentration of a particular analyte in solution are all based on ensemble responses in which many analyte molecules give rise to the measured signal. In this paper, single molecules of beta-galactosidase were monitored using a 1 mm diameter fiber optic bundle with 2.4 x 10(5) individually sealed, femtoliter microwell reactors. By observation of the buildup of fluorescent products from single enzyme molecule catalysis over the array of reaction vessels and by application of a Poisson statistical analysis, a digital concentration readout was obtained. This approach should prove useful for single molecule enzymology and ultrasensitive bioassays. More generally, the ability to determine concentration by counting individual molecules offers a new approach to analysis of dilute solutions.

Individual enzyme molecules have been observed to possess discrete and different turnover rates due to the presence of long-lived activity states. These stable activity states are thought to result from different molecular conformations or post-translational modifications. The distributions in kinetic activity observed in previous studies were obtained from small numbers of single enzyme molecules. Due to this limitation, it has not been possible to fully characterize the different kinetic and equilibrium binding parameters of single enzyme molecules. In this paper, we analyze hundreds of single beta-galactosidase molecules simultaneously; using a high-density array of 50,000 fL-reaction chambers, we confirm the presence of long-lived kinetic states within a population of enzyme molecules. Our analysis has isolated the source of kinetic variability to kcat. The results explain the kinetic variability within enzyme molecule populations and offer a deeper understanding of the unique properties of single enzyme molecules. Gaining a more fundamental understanding of how individual enzyme molecules work within a population should provide insight into how they affect downstream biochemical processes. If the results reported here can be generalized to other enzymes, then the stochastic nature of individual enzyme molecule kinetics should have a substantial impact on the overall metabolic activity within a cell.