Image from vecstock on Magnific

Human blood plasma is one of the most diagnostically valuable biological samples available, yet its extreme protein dynamic range — spanning up to 10¹² — has long limited conventional mass spectrometry (MS)-based discovery to only a few hundred proteins. NP-based enrichment technologies have already expanded plasma proteomics into the thousands of quantified proteins by improving access to lower-abundance species, but until now no rigorous head-to-head comparison had evaluated their performance, reproducibility, or susceptibility to preanalytical variability under consistent conditions.

To address this, Völlmy et al. directly compared six plasma proteomics workflows: Neat plasma, Top14 immunodepletion, ENRICH-iST, Mag-Net, P2, and Proteograph XT, using global quantitative proteomics via DIA on an Orbitrap Astral. Peptide separation was performed on a Vanquish Neo coupled to an Aurora® Elite™ 15×75 C18 UHPLC column. The technology-focused benchmarking found that P2 achieved the greatest depth at 4,636 unique protein groups, followed closely by Proteograph XT at 4,402 – compared to 584 for Neat plasma.

The researchers from the Bantscheff lab demonstrated that the high protein identifications achieved by NP-based methods are substantially driven by cellular contamination, including platelets, erythrocytes, and cellular debris, rather than solely by extracellular vesicle (EV) enrichment as previously claimed. Secreted plasma proteins remained quantitatively stable even under stringent ultracentrifugation, suggesting the soluble plasma proteome can be reliably measured when appropriate preanalytical controls are applied.

These findings provide the field with a clear, evidence-based framework for selecting plasma proteomics workflows, with direct implications for biomarker discovery and clinical study design.

Publication
Journal of Proteome Research

Authors

Franziska Völlmy, Prashant Kaushik, Stephan Eckert, Christoph Paschen, Shahrzad Tavalaei, Justine Fidelin, Stefan Weiser, & Marcus Bantscheff;

Title

Comparison of common plasma proteomics workflows reveals distinct preanalytical biases by sample preparation and nanoparticle enrichment