Systematic evaluation of blood contamination in nanoparticle-based plasma proteomics

Area of Science:

• Proteomics
• Biomarker Discovery
• Nanotechnology

Background:

• Circulating blood proteomics offers minimally invasive biomarker discovery.
• Previous studies using nanoparticle-based plasma proteomics reported varying protein identification numbers (2000-7000), with ambiguity regarding higher protein counts being more informative.

Purpose of the Study:

• To develop an optimized nanoparticle-based workflow for plasma proteomics.
• To assess the impact of contamination on protein identification and quantification.
• To introduce a software tool for contamination assessment in nanoparticle-based plasma proteomics.

Main Methods:

• Development of OmniProt, a silica-nanoparticle workflow, with systematic evaluation of nanoparticle types and protein corona parameters.
• Creation of an Astral spectral library for 10,109 protein groups.
• Utilizing the Astral with high throughput (60 samples/day) for plasma proteomics.
• Controlled contamination experiments to identify contamination biomarkers.
• Development of open-access Baize software for contamination assessment.
• Validation of the pipeline in 193 patients with lung cancer or benign nodules.

Main Results:

• OmniProt identified 3000 to 6000 protein groups from human plasma.
• Platelet, erythrocyte, and coagulation-related contamination were found to artificially inflate protein identifications and compromise quantification accuracy.
• Biomarkers for contamination were identified.
• The Baize software successfully flagged five contaminated samples in the patient cohort.

Conclusions:

• Contamination significantly alters protein identification and quantification in nanoparticle-based plasma proteomics.
• The developed OmniProt workflow and Baize software provide a robust method for contamination assessment, improving the reliability of biomarker discovery from plasma proteomics data.