Systematic evaluation of blood contamination in nanoparticle-based plasma proteomics

Circulating blood proteomics enables minimally invasive biomarker discovery. Nanoparticle-based circulating plasma proteomics studies have reported varying number of proteins (ca 2000–7000), but it remains unclear whether a higher protein number is more informative. Here, we first develop OmniProt—a silica-nanoparticle workflow optimized through a systematic evaluation of nanoparticle types and protein corona formation parameters. Next, we present an Astral spectral library for 10,109 protein groups. Using the Astral with 60 sample-per-day throughput, OmniProt identifies ca 3000 to 6000 protein groups from human plasma. Platelet/erythrocyte/coagulation-related contamination artificially inflates protein identifications and compromises quantification accuracy in nanoparticle-enriched samples. Through controlled contamination experiments, we identified biomarkers for platelet/erythrocyte/coagulation-related contamination in nanoparticle-based plasma proteomics. We developed open-access software Baize for contamination assessment. We validated the pipeline in 193 patients with CT-indistinct benign nodules or early-stage lung cancers, flagging five contaminated samples. This study reveals that contamination alters protein identification/quantification in nanoparticle-based plasma proteomics and presents Baize software to evaluate it. In mass spectrometry-based plasma proteomics, blood platelet and erythrocyte contamination artificially inflates protein identification and compromises quantification. An open-source software, Baize, is developed to systematically evaluate this critical issue. In mass spectrometry-based plasma proteomics with nanoparticle enrichment, blood platelet and erythrocyte contamination artificially inflates protein identification and compromises quantification. The open-source software Baize is developed to systematically evaluate this critical issue.