Related Experiment Video
Updated: Jan 14, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Multiplexed Nanoparticle Protein Corona Enables Accurate and Precise Deep Plasma Proteomics
Ting Huang1, Jian Wang1, Alexey Stukalov1
1Seer, Inc, Redwood City, California 94065, United States.
Abstract:
The Proteograph Product Suite, a multiplexed nanoparticle (NP) protein corona-based workflow, substantially improves the depth of detection of proteins by mass spectrometry (MS) by compressing the dynamic range of protein abundances. Here, we evaluate its quantitative performance and suitability for large-scale studies. Using multispecies spike-in experiments, we assessed fold change accuracy, linearity, precision, and the lower limit of quantification (LLOQ) across multiple MS platforms. Combined with the Orbitrap Astral MS, the Proteograph XT assay enabled identification of more than 7,000 plasma proteins. In mixed-species dilution experiments, fold change accuracy was preserved, with Proteograph quantifying 3.5 times more proteins than the Neat plasma workflow at the same fold change error threshold. Similar accuracy was observed with the Orbitrap Exploris 480 MS, and we also demonstrate that different proteome backgrounds do not impact the accuracy. Data produced with NPs from the four distinct NP batches (each supporting >100,000 assays) showed only a 4% increase in protein intensity CV across batches. Together, these results demonstrate that the Proteograph Product Suite provides depth as well as quantitative accuracy and precision to power new biomarker discovery and biological understanding in population-scale plasma proteomics cohorts.
More Related Videos
07:54Capillary Electrophoresis Mass Spectrometry Approaches for Characterization of the Protein and Metabolite Corona Acquired by Nanomaterials
Published on: October 27, 2020
10:02Standardized SDS-PAGE Workflow for Personalized Protein Corona Profiling in Early Cancer Detection
Published on: December 19, 2025