A Novel Proteomics Magnetic Clean-up Bead for Automated Mass Spectrometry Sample Preparation

Importance of the Topic

Magnetic bead-based sample preparation streamlines proteomics workflows by enabling rapid removal of diverse detergents and contaminants, facilitating automated processing and improving throughput and reproducibility in mass spectrometry analysis.

Study Objectives and Overview

This work evaluates the performance of newly developed Proteomics Magnetic Clean-up Beads across different detergent lysis buffers and sample types (BSA, cultured cells, tissue). The study compares traditional workflows to an automated bead-based protocol, assesses protein and peptide identification metrics, and demonstrates quantitative analysis of human lung tumor versus normal tissue biomarkers.

Methodology and Instrumentation

Samples underwent reduction and alkylation, followed by binding to magnetic beads in 99.5% IPA/0.5% TFA. Beads were washed with acetonitrile and ethanol, digested with trypsin/Lys-C, and peptides eluted in formic acid. Automation was performed on a KingFisher Apex system. Peptide separations used Thermo Scientific Vanquish Neo UPLC with EASY-Spray PepMap Neo columns or IonOpticks Aurora Frontier columns, coupled to Orbitrap Exploris 480 or Orbitrap Astral mass spectrometers (with FAIMS Pro). Data were processed using Spectronaut, DIA-NN, and Proteome Discoverer with CHIMERYS.

Main Results and Discussion

• BSA samples processed in five different lysis buffers achieved >85% sequence coverage, >100 unique peptides, and zero missed cleavages within 5 hours (vs ~48 hours manually).
• Cultured HEK293 cells and mouse kidney tissue yielded comparable protein group and peptide identifications across buffers.
• Human lung tumor and normal tissues showed robust quantitation (CV ~8%, 85% of proteins <20% CV). Volcano analysis highlighted EGFR (1.9-fold increase) and PD-L1 (2.8-fold increase) in tumors.

Benefits and Practical Application of the Method

The bead-based workflow reduces sample preparation time, removes detergents efficiently, supports high-throughput automation, and delivers consistent, high-quality proteomic data across diverse sample types.

Future Trends and Potential Applications

Integration with emerging automation platforms, expansion to challenging sample matrices, coupling with advanced separation and mass spectrometry technologies, and application in clinical biomarker discovery and quantitative proteomics.

Conclusion

The Proteomics Magnetic Clean-up Beads workflow offers a rapid, robust, and automatable solution for MS-based proteomics, significantly enhancing laboratory productivity and data quality across research and clinical applications.

References

1. Mitsudomi T., Yatabe Y. Epidermal growth factor receptor in relation to tumor development. FEBS Journal. 2010;277(2):301–308.
2. Garon E.B., Rizvi N.A., Hui R., et al. Pembrolizumab for the treatment of non-small-cell lung cancer. New England Journal of Medicine. 2015;372(21):2018–2028.