Standardized, high-throughput platform for automated, rapid, and extensive plasma proteome characterization

Importance of the Topic

The analysis of plasma proteome is critical due to its potential to reveal biomarkers for disease diagnosis and monitoring. High sample complexity, wide dynamic range and the demand for large cohort studies pose challenges for reproducible and scalable workflows. Automation and rapid processing can overcome these hurdles and support preclinical research and clinical applications.

Objectives and Study Overview

This study aims to develop and validate a fully automated, high-throughput platform for plasma proteomics that matches manual workflows in performance. The workflow integrates PreOmics ENRICH-iST kit with Tecan Fluent and Resolvex A200 automation for sample preparation, followed by short-gradient LC-MS/MS using a nanoElute 2 system coupled to Bruker timsTOF HT in dia-PASEF mode. Performance is assessed on plasma from three healthy donors in quintuplicates, comparing automated and manual protocols.

Methodology and Instrumentation

• Sample Preparation: Automated platform handles 96 samples in about 5 hours, covering bead-based enrichment, lysis, digestion and peptide clean-up based on ENRICH-iST chemistry.
• Automation Hardware: Tecan Fluent liquid handling deck with 8-channel AirFCA pipetting, Robotic Gripper Arm for plate transfers, Resolvex A200 positive pressure module, on-deck heating and shaking, magnetic separation components.
• Liquid Chromatography–Mass Spectrometry: NanoElute 2 nanoflow LC with a 10 cm × 75 µm column and a 20 min acetonitrile gradient; Bruker CaptiveSpray ion source coupled to timsTOF HT.
• Data Acquisition: dia-PASEF scheme using 8 TIMS ramps with three mass windows per ramp (400–1000 m/z, mobility 0.64–1.37 1/K0), cycle time 0.5 s plus one MS1 scan.
• Data Analysis: Spectronaut 17 directDIA+ workflow, library-free search against Human reviewed Uniprot database.

Main Results and Discussion

• Precursor Identifications: Over 19 000 precursors consistently detected per sample for both automated and manual methods.
• Protein Identifications: More than 2 000 protein groups identified with automated workflow, matching manual performance.
• Quantitative Reproducibility: Precursors and proteins showed coefficients of variation below 15 % and 10 %, respectively, across processing modes.
• Overlap and Clustering: >96 % overlap of protein groups between automated and manual for donor 1, >80 % for donor 2 and >99 % for donor 3; principal component and hierarchical clustering confirm that automation preserves biological variability and yields consistent sample grouping.

Benefits and Practical Applications

• Highly scalable sample preparation enabling processing of 96 plasma samples within 5 hours.
• Rapid LC-MS/MS analysis (~45 samples per day) suited for large cohort studies.
• Robust reproducibility and dynamic range compression ensure reliable biomarker discovery workflows.
• Seamless integration of automated protocols reduces manual labor and risk of variability.

Future Trends and Potential Applications

• Automation of peptide concentration measurements and normalization procedures to streamline LC-MS loading.
• Expansion of full automated workflows for additional PreOmics sample preparation chemistries (iST-BCT, iST-PSI, SP3-iST, ENRICH-iST).
• Integration with downstream data processing and reporting pipelines for end-to-end proteomics solutions.

Conclusion

The developed automated platform provides a reliable and efficient solution for extensive plasma proteome characterization. By matching manual workflows in depth and reproducibility while dramatically increasing throughput, this approach enables large-scale studies and accelerates biomarker discovery in clinical and research settings.