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Fully Automated Workflow for Integrated Sample Digestion and Evotip Loading Enabling High-Throughput Clinical

Anders H Kverneland1, Florian Harking2, Joel Mario Vej-Nielsen3

  • 1Faculty of Health Sciences, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark; Department of Oncology, National Center of Cancer Immune Therapy, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark.

Molecular & Cellular Proteomics : MCP
|May 22, 2024
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Summary

Automated sample preparation using the Opentrons OT-2 robot significantly speeds up protein analysis for large cohorts. This efficient workflow enhances biomarker discovery by processing up to 192 samples in 6 hours.

Keywords:
biomarker discoverycancer immune therapymass spectrometryplasma proteomicsworkflow automation

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Area of Science:

  • Proteomics
  • Biomarker Discovery
  • Automation in Life Sciences

Background:

  • Protein identification and quantification are crucial for biomarker discovery.
  • High-throughput mass spectrometry requires efficient sample preparation, which is currently a bottleneck for large cohort studies.

Purpose of the Study:

  • To develop and evaluate a fully automated, efficient workflow for protein sample preparation on the Opentrons OT-2 robot.
  • To assess the workflow's performance in terms of speed, reproducibility, sensitivity, and cost-effectiveness for large-scale proteomic analysis.

Main Methods:

  • A novel automated workflow integrating sample digestion, cleanup, and Evotip loading was developed on the Opentrons OT-2 robot.
  • High-throughput analysis was performed using Evosep One coupled with Orbitrap Astral mass spectrometry with narrow-window data-independent acquisition (nDIA).
  • An automated phosphopeptide enrichment step using magnetic titanium-immobilized metal ion affinity chromatography beads was incorporated.

Main Results:

  • The automated workflow processed up to 192 samples in 6 hours, achieving a throughput of 100 samples per day.
  • Consistent identification of ~8000 protein groups and ~130,000 peptide precursors per sample.
  • Demonstrated high sensitivity, reproducibility, and stability with low sample input, optimizing reagent costs.
  • Successful application in evaluating cancer immune therapy effects on plasma proteome in metastatic melanoma patients.

Conclusions:

  • The automated workflow offers a simple, efficient, and scalable solution for high-throughput proteomic sample preparation.
  • This method significantly reduces bottlenecks in sample preparation, enabling large cohort studies and biomarker discovery.
  • The integrated workflow provides high sensitivity for both proteome and phosphoproteome analysis, applicable to clinical research.