A Fully Automated High-Throughput, Deep-Scale Quantitative Plasma Proteomics Workflow Enables Quantitively Profile More Than 1000 Proteins Per Sample

Significance of the topic

Plasma proteomics enables in-depth molecular profiling of human physiology and disease, supporting biomarker discovery and therapeutic target identification. High reproducibility, deep proteome coverage and high throughput are essential to power large cohort studies while minimizing sample consumption and analytical variability.

Study Objectives and Overview

This work describes the development of a fully automated, high-throughput quantitative plasma proteomics workflow capable of profiling over 1,000 proteins from just 1 µL of human plasma per sample. The aim is to increase statistical power, ensure robust reproducibility and integrate advanced instrumentation and data analysis to support large-scale clinical and research studies.

Methodology and Instrumentation

The workflow combines automated sample preparation, next-generation LC and ion mobility-enabled mass spectrometry with neural network-enhanced data processing:

• Automated Sample Preparation: EasyPep™ 96 MS Sample Prep Kit on a Hamilton liquid‐handling platform, enabling digestion, clean-up and peptide elution from 1 µL plasma in a 96-well format.
• Liquid Chromatography: Thermo Scientific Vanquish™ Neo UHPLC or U3000 system equipped with Easy-Spray™ PepMap™ Neo columns (75 µm × 75 cm for deep profiling or 150 µm × 150 cm for 15 min high-throughput gradients) using 0.1% formic acid in water (A) and 0.1% formic acid in 80% acetonitrile (B).
• Mass Spectrometry: Thermo Scientific Orbitrap Exploris™ 480 with FAIMS Pro interface, using three optimized compensation voltages in a top-speed 3-s cycle over 120 min or 15 min gradients.
• Data Processing: Proteome Discoverer™ 3.0 with Minora Feature Detector, Feature Mapper and Precursor Ion Quantifier nodes; INFERYS deep learning–based rescoring of Sequest HT search results to maximize identification confidence.

Main Results and Discussion

The integrated workflow achieved high reproducibility and depth:

• Identification of 1,014 protein groups from undepleted plasma, with 85% of proteins showing CV<20% across triplicate injections.
• Detection of 82 FDA-approved biomarkers, 66 of which were reproducibly quantified (%CV<20%, n=3).
• Well-to-well and day-to-day peptide recovery assessed by colorimetric assay showed <20% variation across a 96-well plate and multiple days.
• Digestion efficiency metrics (missed cleavages, oxidation and deamidation rates) and MS mass accuracy (<10 ppm) confirmed robust sample processing and data quality.

Benefits and Practical Applications

This workflow provides:

• Ultra-low sample consumption (1 µL) for studies with limited volumes.
• Scalability to large cohorts with automated 96-well processing.
• Rapid turnaround (15 min high-throughput or 120 min deep profiling) without sacrificing data quality.
• Reliable quantification of clinically relevant biomarkers for pharmaceutical research, diagnostics and QA/QC laboratories.

Future Trends and Applications

Emerging opportunities include:

• Integration with artificial intelligence for automated data interpretation and biomarker discovery.
• Further acceleration of LC-MS workflows via multiplexed ion mobility or parallelized chromatography.
• Expansion to other biofluids and tissues to build comprehensive multi-omics profiles.
• Targeted quantitation of low-abundance analytes leveraging FAIMS and advanced acquisition schemes.

Conclusion

The described fully automated plasma proteomics workflow combines sample prep robotics, advanced UHPLC, FAIMS-equipped Orbitrap MS and deep learning–augmented data analysis to deliver reproducible, high-throughput quantification of over 1,000 proteins from minimal sample input. This platform enhances statistical power for large cohort studies and accelerates biomarker research.

Reference

• Zhou Y. et al. A Fully Automated High-Throughput, Deep-Scale Quantitative Plasma Proteomics Workflow Enables Quantitatively Profile More Than 1000 Proteins Per Sample. Thermo Fisher Scientific, 2021.