Benchmark of Micro-flow Chromatograph for Robust Proteomics Analysis

Importance of the Topic

The development of robust, high-throughput workflows for proteomic analysis is critical for applications ranging from biomarker discovery to quality control in pharmaceutical and clinical research. Micro-flow liquid chromatography-mass spectrometry (LC-MS) offers a promising compromise between the sensitivity of nano-flow systems and the reproducibility and throughput required for large-scale studies. This benchmark evaluates a micro-flow LC-MS platform for both discovery and quantitative proteomics, highlighting its performance, robustness and versatility.

Objectives and Study Overview

This study aimed to assess the reproducibility, identification depth and quantitative accuracy of a micro-flow LC-MS workflow. Key goals were:

• Compare label-free quantification (LFQ) performance across varying sample loads and gradient lengths.
• Evaluate tandem mass tag (TMT11-plex) quantitation accuracy at multiple ratios and loads.
• Demonstrate the robustness of the system through repeated injections and prolonged operation.
• Extend application to gas-phase fractionation (GPF) for in-depth profiling of peripheral blood mononuclear cells (PBMCs) from several species.

Methodology and Instrumentation

The workflow combined a Thermo Scientific Vanquish Neo UHPLC micro-flow system with PepMap C18 2 µm 150 × 1 mm columns and Orbitrap Exploris mass spectrometers. Key elements included:

• Label-free and TMT-labeled HeLa and yeast digest standards at 1 µg, 5 µg, 10 µg and 20 µg loads.
• LC gradients of 30 min and 50 min to assess identification depth versus throughput.
• Data-dependent acquisition on Exploris 240/480 instruments, with optional FAIMS Pro Duo interface for enhanced separation and GPF.
• Data processing in Proteome Discoverer 3.0 using MSPepSearch and the CHIMERYS search engine, with Percolator for 1% FDR.

Main Results and Discussion

Reproducibility and Identification Depth:

• Over 4,300 protein groups and 41,000 peptide groups identified at 10 µg HeLa digest with a 50 min gradient.
• Median coefficient of variation (CV) of protein abundances below 11% across all load and gradient conditions; more than 80% of proteins exhibited CV<20%.

Quantitative Accuracy:

• TMT11-plex standards quantified across 1:10 ratios with minor ratio compression; longer gradients yielded improved accuracy.
• Labeling efficiency exceeded 99.5% for under- and over-labeled peptides, confirming high TMT reaction performance.

GPF-Enhanced Proteome Coverage:

• Gas-phase fractionation on PBMC digests from human, nonhuman primate, canine, porcine, rat and mouse provided deep profiling without offline fractionation.
• Consistent quantitation across over 100 sequential injections, demonstrating platform robustness.

Benefits and Practical Applications

The evaluated micro-flow LC-MS setup offers:

• High throughput: complete dataset acquisition in under four days without offline fractionation.
• Strong reproducibility: suitable for longitudinal studies and quality control.
• Versatility: supports both label-free and multiplexed TMT quantitation with high accuracy.
• Scalability: adjustable gradient lengths and loads to balance depth versus speed.

Future Trends and Potential Applications

Advancements in micro-flow chromatography and ion mobility are expected to further improve proteome coverage and quantitation precision. Emerging opportunities include:

• Integration with real-time search and data-independent acquisition to maximize identifications.
• Expanded use of gas-phase and ion mobility separation for comprehensive multi-omic applications.
• Automation and high-density workflows for clinical proteomics and large cohort studies.

Conclusion

This benchmark demonstrates that a micro-flow LC-MS platform combining Vanquish Neo UHPLC, Orbitrap Exploris mass spectrometers, FAIMS Pro Duo and advanced data processing can achieve high reproducibility, deep proteome coverage and accurate quantitation. The system meets the needs of both discovery and quantitative proteomics, supporting robust, high-throughput applications.