Large-Scale Targeted Protein Quantification Using WiSIM-DIA on an Orbitrap Fusion Tribrid Mass Spectrometer

Significance of the topic

Proteomics has evolved from qualitative mapping to large-scale quantitative analysis in order to decipher protein functions, interactions and biomarkers in complex biological systems. Traditional data-dependent workflows struggle with reproducibility, dynamic range and throughput when interrogating low-abundance targets across replicates. Data-independent acquisition (DIA) strategies address these challenges by systematically capturing all ions for unbiased quantification and identification.

Objectives and overview of the study

This work introduces a novel wide selected-ion monitoring DIA workflow (WiSIM-DIA) on the Thermo Scientific Orbitrap Fusion Tribrid mass spectrometer. The primary goals are to establish a highly sensitive, selective and reproducible platform for large-scale targeted protein quantification, combining high-resolution precursor measurements with rapid, confirmatory MS/MS in a single run.

Methodology and instrumentation

WiSIM-DIA employs three high-resolution (240 000 at m/z 200) SIM scans covering m/z 400–1000 in 200 m/z isolation windows, executed in parallel with 17 sequential rapid CID MS/MS scans (12 m/z isolation) in the linear ion trap. Target proteins are quantified post-acquisition by extracting ion chromatograms (XICs) of 12C and 13C precursor isotopes with a ±5 ppm window, while peptide identity is confirmed via spectral library matching of eight intense b/y fragment ions.

Used Instrumentation

• Orbitrap Fusion Tribrid MS with Q-OT-qIT architecture and EASY-Spray ion source
• Thermo Scientific EASY-nLC 1000 nano-LC system with 75 µm × 50 cm C18 column
• Thermo Scientific Pinpoint software v1.3 for targeted data extraction

Main results and discussion

• SIM acquisitions delivered nearly five-fold increase in signal-to-noise versus full scans, enabling detection limits down to 10 attomoles on column.
• Four orders of linear dynamic range were demonstrated using a 14-peptide dilution series spiked into 500 ng/µL E. coli digest, with CVs below 15% at 100 fmol.
• Six bovine proteins spanned five orders of magnitude in a single run, all quantified with CVs under 10% and reliable sequence confirmation.
• Large-scale quantification compared 250 ng and 500 ng E. coli digests in triplicate, identifying 5923 peptides (1 090 proteins) with p-values <0.1 and achieving a 98% success rate in detecting two-fold expression changes.
• Over 85% of targeted peptides showed CVs ≤15% and pathway analysis covered key metabolic routes with consistent quantitative precision.

Benefits and practical applications

The WiSIM-DIA approach combines high mass resolution for selective precursor quantification with fast CID MS/MS for robust peptide confirmation, eliminating the interference issues of wide-window HRAM MS/MS-only DIA. It offers label-free quantification at attomole sensitivity, broad dynamic range, high throughput and reproducibility, suitable for biomarker verification, QA/QC workflows and systems biology studies.

Future trends and opportunities

Emerging directions include real-time library generation and adaptive acquisition schemes, integration with ion mobility separation, expansion to post-translational modification analysis, and application to metabolomics profiling. Coupling WiSIM-DIA with machine learning for automated target selection and data interpretation may further enhance quantitative accuracy and sample throughput.

Conclusion

The WiSIM-DIA workflow on the Orbitrap Fusion Tribrid MS represents a powerful platform for comprehensive, reproducible and sensitive targeted protein quantification. By leveraging parallel high-resolution SIM and rapid CID MS/MS, it achieves attomole detection limits, extensive dynamic range and reliable identification in a single injection, meeting the demands of modern quantitative proteomics.

References

• Gillet LC, Navarro P, Tate S, et al. Targeted data extraction of MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics. 2012; Manuscript O111.016717.
• Egertson JD, Kuehn A, Merrihew G, et al. Multiplexed MS/MS for improved data-independent acquisition. Nature Methods. 2013;10:744–746.
• Gallien S, Duriez E, Demeure K, Domon B. Selectivity of LC-MS/MS analysis: implication for proteomics experiments. J Proteomics. 2013;81:148–158.
• Prakash A, Tomazela DM, Frewen B, et al. Expediting the development of targeted SRM assays: using data from shotgun proteomics to automate method development. J Proteome Res. 2009;8:2733–2739.