Proteograph™, a multi-nanoparticle platform, enables plasma proteomics profiling at scale and speed, significantly improving coverage and scalability versus traditional deep fractionation methods Shadi Ferdosi1, Taher Elgierari1, Patrick A. Everley1, Matthew McLean1, Martin Goldberg1, Juan Cruz Cuevas1, John E. Blume1, Omid C. Farokhzad1 and Daniel Hornburg1 1 Seer Inc. 3200 Bridge Parkway - Suite 102 Redwood CIty - CA 94065 U.S.A. Blood plasma, which comprises signals from most tissues, is a rich source of protein biomarkers for disease detection, but its large dynamic range of protein concentrations necessitates complex workflow trade-offs between throughput, scalability, coverage, and precision. We developed a deep, high-throughput quantitative proteome profiling platform, Proteograph, which leverages the selective protein-nanosurface interactions of nanoparticles engineered with distinct physicochemical properties to provide broad coverage of the plasma proteome at scale. In a pilot study we compared the Proteograph to common deep plasma proteome workflows in terms of depth, dynamic range, coverage, throughput, and precision and demonstrated reproducible quantification of approximately 2,000 proteins (Blume et al., Nat Commun 11, 3662 (2020)). We also performed a head-to-head comparison of the Proteograph to typical workflows, including combined abundant protein-immunodepletion and high-pH peptide fractionation, using a pooled common EDTA plasma sample. Samples processed with each method were analyzed by micro LC-MS/MS interfaced to a Sciex 6600+ mass spectrometer (MS) operating in data-independent mode. MS data were processed using Spectronaut (1% peptide and protein false discovery rate). Coverage, depth, precision, and workflow efficiency were evaluated, with all statistical analyses performed in R. Proteograph identified more than 1,600 protein groups in this common sample, spanning nearly the full range of protein abundance in plasma. Compared to standard fractionation workflows, Proteograph captured proteins on average at 10-times lower abundance, outperforming the identification rate of high-pH fractionation fivefold for the two lowest orders of magnitude. In terms of time and resources, the Proteograph workflow upstream of the MS requires only 7 hours with only 30 minutes of hands-on time and has better precision compared to depletion and fractionation methods, which require multiple days. Proteograph demonstrates superior performance on the measures evaluated, distinguishing it as a robust and efficient platform for unbiased, deep, rapid, large-scale proteomics to quantify thousands of proteins across large numbers of samples.