Large Scale Targeted Protein Quantification Using HR/AM Selected Ion Monitoring with MS/MS Confirmation on the Orbitrap Fusion Tribrid MS

Importance of the Topic

The accurate and sensitive quantification of targeted proteins in complex biological samples is essential for biomarker validation, clinical research, and industrial quality control. Traditional full scan methods often suffer from limited sensitivity and interference from coeluting species. Implementing a high resolution, accurate mass selected ion monitoring workflow with parallel MS/MS confirmation addresses these challenges by improving selectivity and lowering detection limits.

Objectives and Study Overview

This study introduces a novel data independent acquisition workflow on the Orbitrap Fusion Tribrid mass spectrometer that combines high resolution accurate mass (HR/AM) selected ion monitoring (SIM) with sequential collision-induced dissociation MS/MS scans. The goals were to evaluate the method’s detection limits, dynamic range, reproducibility, and its ability to quantify both low-abundance target peptides and a large number of proteins in a single experiment.

Methodology and Instrumentation

Methodology

• Three overlapping HR/AM SIM windows (400–600, 600–800, 800–1000 m/z) at 240 000 resolving power were acquired per cycle using 200 amu isolation. In parallel, each window triggered 17 sequential CID MS/MS scans with 12 amu isolation for sequence confirmation.
• Targeted peptides were quantified by extracting ion chromatograms (XICs) at 5 ppm tolerance. MS/MS fragment matching against a spectral library provided specificity and confidence filtering at p < 0.1.

Instrumentation

• Mass Spectrometer: Thermo Scientific Orbitrap Fusion Tribrid MS equipped with EASY-Spray source (capillary 275 °C, 1800 V).
• Nano-LC: Thermo Scientific EASY-nLC 1000 with EASY-Spray PepMap C18 column (75 μm × 50 cm, 2 μm); gradient 5 %–35 % acetonitrile over 120 min at 300 nL/min.

Main Results and Discussion

• Detection limits of 10 amol on column and a linear dynamic range spanning four orders of magnitude were achieved for seven yeast peptides spiked into E. coli digest.
• Six bovine proteins spiked at levels from 10 amol to 1 pmol in a 500 ng E. coli matrix were quantified with ≥ 90 % of peptides showing CV < 10 % across triplicates.
• Data files used for the six-protein study were further processed to quantify 172 E. coli metabolic proteins, resulting in 771 peptides with 69 % of CVs < 10 % and all CVs < 20 %. This demonstrates high throughput capability for large protein sets.

Benefits and Practical Applications of the Method

• Enhanced sensitivity and selectivity through HR/AM SIM reduces chemical interferences.
• Parallel MS/MS confirmation via targeted data extraction ensures peptide identity and quantitation confidence.
• Unified workflow allows simultaneous quantification of low-abundance biomarkers and larger protein panels in a single run, increasing laboratory throughput.

Future Trends and Potential Applications

Advances in spectral library generation and automated data processing will expand the applicability to clinical proteomics and biopharmaceutical monitoring. Combining HR/AM SIM with ion mobility separation or real-time library matching may further improve selectivity for highly complex samples. Integration into regulated workflows could support biomarker qualification and high-throughput QC in drug development.

Conclusion

This work presents a unique DIA strategy on the Orbitrap Fusion Tribrid system that collects high resolution SIM scans in parallel with rapid CID MS/MS. The approach achieves attomole sensitivity, four orders of linear dynamic range, and excellent reproducibility for targeted peptides and protein sets in complex matrices, making it a powerful tool for large-scale targeted proteomics.

Reference

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• Egertson JD, Kuehn A, Merrihew G, et al. Multiplexed Data Independent Acquisition for Comparative Proteomics. ASMS Poster, 2012.
• Gallien S, Duriez E, Demeure K, Domon B. Selectivity of LC-MS/MS analysis: Implication for proteomics experiments. J Proteomics. 2013;81:148–158.