ArticleJournal of proteome research2026
Automated Mag-Net Enrichment Unlocks Deep and Cost-Effective LC-MS Plasma Proteomics.
Article in Journal of proteome research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Precision Proteomic Profiling of Systemic Lupus Erythematosus-Correlating Disease Activity and Complement Levels with Clinical Phenotypes.Biomedicines · 2026Article
- Systematic Evaluation of Depletion and Enrichment Technologies for Platelet-Free Plasma Proteomics.Journal of proteome research · 2026Article
- Benchmarking Plasma Proteomics Workflows and Their Correlation to Clinical Routine Protein Assays.Journal of proteome research · 2026Article
- Method Evaluation of Liquid Biopsy Proteomics for Limited Plasma Volume.Molecular & cellular proteomics : MCP · 2026Article
- Blood Matrices and Sample Preparation Influence Blood Marker Discovery.Journal of proteome research · 2026Article
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Authors and funding
4 authors.
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Abstract
Plasma is an ideal material for proteomics due to its diverse protein content reflecting physiological and pathological states and its compatibility with minimally invasive sampling. Deep proteomic profiling of plasma is limited by high-abundant proteins that mask the detection of low-abundant proteins. To overcome this, we compared five plasma protein enrichment methods, Mag-Net, ENRICHplus, ENRICHiST, EasySep, and EXONET, against neat plasma using LC-MS proteomics. All five methods substantially increased protein identifications, with Mag-Net, ENRICHplus, EasySep, and EXONET yielding up to 4200 proteins per sample, over 7-fold more than neat plasma, using a 44 min gradient on the Evosep One and data-independent acquisition on the timsTOF Pro 2. These methods enriched extracellular vesicle-associated proteins while effectively depleting high-abundant proteins. To further enhance performance and scalability, we optimized the Mag-Net protocol by increasing the plasma-to-bead ratio and automated the workflow, including Evotip loading, on the Biomek i5 liquid handler. The automated Mag-Net, combined with the Orbitrap Astral mass spectrometer, yielded up to 4500 proteins per sample with a throughput of 100 samples per day. The workflow demonstrated high reproducibility and a remarkably low total cost of just a few dollars per sample. Newer enrichment methods (Proteonano, P2-iST Plasma, and P2) showed improved plasma proteome coverage compared with Mag-Net but are likely to incur higher costs. The streamlined Mag-Net enrichment strategy enables affordable, scalable, high-throughput LC-MS plasma proteomics, supporting biomarker discovery across large cohorts.
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