Peptide Mapping Using Intelligent Data Capture on Vion IMS QTof

Importance of the topic

Liquid chromatography–mass spectrometry is widely used for detailed characterization of biomolecules. However, standard peptide mapping workflows produce extensive data files and background noise, which can overload storage systems and delay data analysis.

Goals and study overview

This work demonstrates the benefits of enabling Waters Intelligent Data Capture (IDC) on the Vion IMS QTof mass spectrometer. The study uses a reduced, alkylated, tryptic digest of NIST monoclonal antibody injected in triplicate under conditions with IDC disabled and enabled at thresholds of 5, 10, and 20 counts.

Methodology and instrumentation

Reversed-phase LC–MS/MS experiments were performed using a data-independent acquisition method (LC-MS^E) featuring alternating low- and high-collision energy scans. The experimental design compares total ion chromatograms, file sizes, percentage reduction, and data processing times across the four conditions.

Used instrumentation

• Waters Vion IMS QTof mass spectrometer
• Waters UNIFI Scientific Information System
• Standard reversed-phase LC system configured for peptide mapping

Main results and discussion

Enabling IDC at a threshold of 5 counts reduced raw data file size by nearly 50% without altering total ion chromatogram profiles. Sequence coverage for light and heavy antibody chains remained constant at 92% and 90%, respectively. Analysis of a low-abundance oxidized peptide (~2% relative abundance) showed consistent identification across all IDC settings, with a notable reduction in spectral noise at higher thresholds.

Benefits and practical application

• Substantially lowered data storage requirements and faster data processing
• Maintained full analytical performance and sequence coverage
• Cleaner spectra facilitate reliable peak picking and identification

Future trends and applications

Real-time noise reduction algorithms such as IDC are expected to integrate with advanced data analytics and machine learning workflows. Broader adoption may extend to other omics platforms, support cloud-based data management, and enable more automated method development.

Conclusion

Intelligent Data Capture significantly enhances LC–MS peptide mapping efficiency by halving dataset sizes and reducing spectral noise, all while preserving data integrity and analytical outcomes.

Reference

Mortishire-Smith R.; Richardson K.; Denny R.; Hughes C. Intelligent Data Capture: Real-Time Noise Reduction for High Resolution Mass Spectrometry. Waters White Paper, 720006567EN (2019).