Scalable Workflows for standardized proteomics

Scalable workflows are no longer a nice‑to‑have in proteomics, they’re essential.

In this upcoming webinar series, we explore how standardized, automated proteomics workflows are enabling reproducible results at scale—from discovery to translational and applied research. Hear directly from experts and users as they share practical insights on building robust, high‑throughput workflows that keep pace with growing sample volumes, increasing complexity, and real‑world laboratory demands.

Join us to learn how scalable proteomics workflows are moving from promise to practice.

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

• Salla Keskitalo, PhD, LSRI Director Viikki Proteomics Unit, University of Helsinki

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-minute 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 automated Mag-Net enrichment strategy enables affordable, scalable, high-throughput LC-MS plasma proteomics, supporting biomarker discovery across large cohorts.

Topic to be announced

• Joachim Smollich, PhD Student, Faculty of Biology, Department of Molecular Cell Biology, Weizmann institute of science