Sensitivity and dynamic range of massively parallel single-molecule protein quantitation using protein identification by short-epitope mapping (PrISM)

Many biological processes in the cell are driven by protein abundance changes across the full complement of the cellular proteome. Detection of those changes requires a proteomic measurement capable of detecting minute changes in protein abundance simultaneously with high-abundance protein changes. Protein Identification by Short-epitope Mapping (PrISM) is a novel single-molecule based proteome analysis approach that may enable identification and quantification of nearly the entire human proteome in a single experiment.

Here we assess the dynamic range associated with the PrISM approach utilizing a simple mixture of standard proteins. Two proteins from a twenty-one protein standard mixture were deposited in separate control lanes on the flow cell and in a sample lane as part of the twenty-one protein mixture. In a second set of lanes, the two proteins were varied over multiple orders of magnitude. PrISM data were acquired on the flow cell using 150 sequential incubate/rinse/image/remove cycles with 50 multi-affinity probes. Frequency of binding of the probes to the standard proteins in the control lanes compounded over multiple cycles of measurement provided the basis for confident identification and quantification of the two proteins in the sample lane. The results indicate that the two standard proteins were reproducibly quantified over multiple orders of magnitude in the presence of the mixture with one standard varying as much as one million fold vs the other standard. We also demonstrate that the protein decoding signal has a wider dynamic range than quantitation from any single multi-affinity probe due to the ability of the decode algorithm to increase the fidelity of quantitation by accumulating information across multiple multi-affinity probes measurement events. Furthermore, we demonstrate assay sensitivity into the yoctomole range. These attributes showcase the platform's robust capability for precise and sensitive quantification of protein variations in complex biological samples.