Evidence map›Paper›PMID 41422412›Full record

ArticleJournal of proteome research2026

Automated Mag-Net Enrichment Unlocks Deep and Cost-Effective LC-MS Plasma Proteomics.

Erkka Järvinen, Xiaonan Liu, Markku Varjosalo, Salla Keskitalo

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Erkka JärvinenInstitute of Biotechnology, Helsinki Institute of Life Science HiLIFE, University of Helsinki, 00014 Helsinki, Finland.
Xiaonan LiuInstitute of Biotechnology, Helsinki Institute of Life Science HiLIFE, University of Helsinki, 00014 Helsinki, Finland.
Markku VarjosaloInstitute of Biotechnology, Helsinki Institute of Life Science HiLIFE, University of Helsinki, 00014 Helsinki, Finland.ORCID 0000-0002-1340-9732
Salla KeskitaloInstitute of Biotechnology, Helsinki Institute of Life Science HiLIFE, University of Helsinki, 00014 Helsinki, Finland.ORCID 0000-0001-5555-1975

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Blood ProteinsProteomeProteomicsChromatography, LiquidCost-Benefit AnalysisHumansLiquid Chromatography-Mass SpectrometryMass SpectrometryTandem Mass SpectrometryBlood ProteinsProteomeautomationBiomekDIA-NNdia-PASEFEXONETextracellular vesicles (EVs)Mag-Netmass spectrometryneat plasmaplasma proteomics

Identifiers

PMID41422412
PMCPMC12887985

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.