Optimized bead-based enrichment workflow for high-throughput detection of low-abundant proteins for plasma proteomics

Significance of the topic

The plasma proteome is a prime source of biomarkers relevant to diagnosis, prognosis and therapeutic monitoring because it reflects both systemic and tissue-derived biology and is accessible by routine blood collection. However, the extreme dynamic range of plasma proteins—dominated by a small number of highly abundant proteins—greatly limits detection and quantification of low-abundance species (cytokines, signaling proteins, tissue leakage markers) that are often the most diagnostically informative. Reliable, high-throughput enrichment strategies that increase detectability of low-abundance proteins while preserving reproducibility are therefore critical for large-scale translational proteomics and biomarker discovery.

Objectives and overview of the study

This study aimed to develop and validate an optimized, bead-based enrichment workflow for human plasma that: increases detection depth for low-abundance proteins; is compatible with high-throughput processing (manual, tip/plate formats, and automated KingFisher workflows); and provides reproducible protein and peptide identifications suitable for large-scale DIA (data-independent acquisition) analyses. Key performance metrics included total protein IDs, coefficients of variation (CV) across technical replicates, robustness to different input volumes and bead-to-sample ratios, and compatibility with downstream sample-prep and LC–MS platforms.

Methodology and experimental workflow

The optimized pipeline consists of: enrichment of low-abundance proteins from 20–100 µL human plasma using a commercial magnetic bead workflow; denaturation, reduction and alkylation; enzymatic digestion (EasyPep MS sample-prep); peptide quantitation with a fluorometric assay; peptide desalting (tip or plate formats); and LC–MS/MS analysis by DIA. Key LC–MS conditions included nanoLC on a Thermo Vanquish Neo UPLC with 50 cm or 15 cm C18 EASY-Spray PepMap Neo columns and gradients (3% to 28% ACN over 35 min, then to 35% over 12 min) at 300 nL/min. Mass spectrometers used were Thermo Orbitrap Eclipse Tribrid and Orbitrap Astral Zoom. Spectronaut 20.5 was used for DIA data analysis. Performance was probed across different bead-to-sample ratios, plasma input volumes, bead lots and manual versus automated (KingFisher) processing.

Used instrumentation

• Thermo Scientific Orbitrap Astral Zoom mass spectrometer
• Thermo Scientific Orbitrap Eclipse Tribrid mass spectrometer
• Thermo Scientific Vanquish Neo UPLC
• Thermo Scientific EASY-Spray PepMap Neo columns (50 cm and 15 cm)
• Thermo Scientific EasyPep MS sample-prep kit
• Thermo Scientific Pierce Quantitative Fluorometric Peptide Assay
• Thermo Scientific KingFisher automated magnetic-bead platform
• Spectronaut 20.5 software for DIA data analysis

Main results and discussion

• Proteome depth and reproducibility: The optimized bead-based enrichment enabled consistent identification of approximately 5,500–5,600 protein IDs in enriched plasma with excellent reproducibility across technical replicates. Reported median protein CV was 8% and median peptide CV 15%, with ~84% of proteins and ~63% of peptides quantified with CVs below 20%.
• High-confidence quantitation: A substantial fraction of proteins and peptides were quantified with CVs below 10% (majority) and many with CVs below 5% in technical replicates, indicating strong quantitative precision suitable for comparative studies.
• Robustness across lots and inputs: Across multiple bead lots the workflow identified ~5,600 protein IDs with <1% CV in identifications, demonstrating lot-to-lot reproducibility. Performance was consistent across plasma inputs from 20 to 100 µL, yielding >3,600 protein IDs with CVs below 1% for tip/plate formats and >3,600–4,100 protein IDs on different platforms.
• Bead-to-sample ratio effects: Bead-to-sample ratios at or above 1:2 provided robust enrichment, consistently delivering >4,000 protein IDs with CVs below 1%, indicating reliable capture of low-abundance proteins without excessive bead usage.
• Automation compatibility: Implementation on a KingFisher automated platform reduced manual handling and operator variability while maintaining comparable or improved depth (~3,900–4,100 protein IDs and ~38,000–39,000 peptide IDs) and CVs below 10% compared with manual processing.
• Proteome composition: Gene ontology enrichment showed the enriched proteome was biased toward secretory and trafficking pathways, consistent with expected plasma contents and indicating successful enrichment of extracellular and tissue-derived protein signals.

Benefits and practical applications of the method

• Enhanced detection of low-abundance, biologically and clinically relevant proteins that are often masked by high-abundance plasma constituents.
• High throughput and scalability: compatible with manual, plate/tip formats and automated KingFisher workflows to support large-cohort studies.
• Reproducibility: low CVs across replicates, lots and input volumes facilitate reliable quantitation for biomarker discovery and longitudinal studies.
• Workflow integration: direct compatibility with standard sample-prep kits, nanoLC configurations and DIA acquisition and analysis pipelines enables straightforward adoption in proteomics laboratories.
• Reduced turnaround and operator variability when automated, beneficial for clinical-translational labs and core facilities processing many samples.

Future trends and potential applications

• Integration with deeper fractionation or orthogonal enrichment strategies to further extend detection of ultra-low-abundance proteins (e.g., cytokines, growth factors) for immuno-oncology and immunology research.
• Coupling with targeted DIA/PRM assays for verification and clinical validation of discovered biomarkers.
• Optimization for small-volume or dried blood spot inputs to enable population-scale screening or remote sampling workflows.
• Application in longitudinal and multi-center studies where automation and reproducibility are essential to control pre-analytical variability.
• Potential extension to multi-omics workflows (e.g., parallel metabolomics or lipidomics sample handling) for integrated biomarker panels.

Conclusions

The presented bead-based enrichment workflow substantially improves detection of low-abundance plasma proteins while preserving high reproducibility and scalability. It routinely achieves several thousand protein identifications (>4,000–5,600 depending on configuration) with low technical variation and is compatible with automated platforms, making it well suited for large-scale biomarker discovery and translational proteomics. The method balances depth, throughput and robustness and can serve as a practical upstream enrichment step prior to DIA-based LC–MS analysis.

Reference

• Amarjeet Flora, Jared Deyarmin, Qingling Li, Stephanie Samra, Bhavin Patel. Optimized bead-based enrichment workflow for high-throughput detection of low-abundant proteins for plasma proteomics. Thermo Fisher Scientific, application note (2026).