Improving the Accuracy, Robustness, and Dynamic Range of Digital Bead Assays

We report methods that improve the quantification of digital bead assays (DBA)-such as the digital enzyme-linked immunosorbent assay (ELISA)-that have found widespread use for high sensitivity measurement of proteins in clinical research and diagnostics. In digital ELISA, proteins are captured on beads, labeled with enzymes, individual beads are interrogated for activity from one or more enzymes, and the average number of enzymes per bead (AEB) is determined based on Poisson statistics. The widespread use of digital ELISA has revealed limitations to the original approaches to quantification that can lead to inaccurate AEB. Here, we have addressed the inaccuracy in AEB due to deviations from Poisson distribution in a digital ELISA for A beta-40 by changing the AEB calculation from a fixed threshold between digital counting and average normalized intensity to a smooth, continuous combination of digital counting and intensity. We addressed issues with determining the average product fluorescence intensity from single enzymes on beads by allowing outlier, high intensity arrays to be removed from average intensities, and by permitting the use of a wider range of arrays. These approaches improved the accuracy of a digital ELISA for tau protein that was affected by aggregated detection antibodies. We increased the dynamic range of a digital ELISA for IL-17A from AEB similar to 25 to similar to 130 by combining long and short exposure images at the product emission wavelength to create virtual images. The methods reported will significantly improve the accuracy and robustness of DBA based on imaging-such as single molecule arrays (Simoa)-and flow detection.

Automated summary

This study presents methods to improve the quantification of digital bead assays (DBA), such as digital enzyme-linked immunosorbent assay (ELISA), which are widely used for highly sensitive protein measurement in clinical research and diagnostics. By changing the calculation method for the average number of enzymes per bead (AEB) and improving the determination of average product fluorescence intensity, the accuracy and robustness of DBA can be significantly improved.