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Updated: Jan 8, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Automated Mag-Net Enrichment Unlocks Deep and Cost-Effective LC-MS Plasma Proteomics.

Erkka Järvinen1, Xiaonan Liu1, Markku Varjosalo1

  • 1Institute of Biotechnology, Helsinki Institute of Life Science HiLIFE, University of Helsinki, 00014 Helsinki, Finland.

Journal of Proteome Research
|December 21, 2025
PubMed
Summary

Five plasma protein enrichment methods were compared for deep proteomic profiling. Optimized Mag-Net achieved high throughput and low cost for scalable plasma proteomics and biomarker discovery.

Keywords:
BiomekDIA-NNEXONETMag-Netautomationdia-PASEFextracellular vesicles (EVs)mass spectrometryneat plasmaplasma proteomics

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Area of Science:

  • Proteomics
  • Biomarker Discovery
  • Analytical Chemistry

Background:

  • Plasma proteomics offers insights into physiological and pathological states.
  • High-abundance proteins in plasma limit the detection of low-abundance proteins.
  • Minimally invasive plasma sampling is ideal for deep proteomic profiling.

Purpose of the Study:

  • To compare five plasma protein enrichment methods for LC-MS proteomics.
  • To optimize a cost-effective and scalable method for high-throughput plasma proteomics.
  • To enhance biomarker discovery through improved plasma proteome coverage.

Main Methods:

  • Comparison of Mag-Net, ENRICHplus, ENRICHiST, EasySep, and EXONET against neat plasma using LC-MS proteomics.
  • Optimization of the Mag-Net protocol, including automation on the Biomek i5 liquid handler.
  • Evaluation of newer methods like Proteonano, P2-iST Plasma, and P2 for proteome coverage.

Main Results:

  • All five methods significantly increased protein identifications (up to 4200 proteins/sample), over 7-fold more than neat plasma.
  • Optimized and automated Mag-Net yielded up to 4500 proteins/sample with a throughput of 100 samples/day at low cost.
  • Newer methods showed improved coverage but potentially higher costs compared to Mag-Net.

Conclusions:

  • Streamlined Mag-Net enrichment enables affordable, scalable, high-throughput LC-MS plasma proteomics.
  • The optimized workflow supports biomarker discovery in large patient cohorts.
  • Mag-Net effectively enriches extracellular vesicle-associated proteins while depleting high-abundance ones.