Visualization and Comparison of SYNAPT G2-S LC/MS Data with Scaffold Software

Importance of the Topic

Large‐scale label‐free proteomic analysis has become indispensable for profiling complex biological mixtures with high sensitivity and reproducibility. The ability to visualize and validate LC/MS datasets with low false discovery rates is vital for confident protein identification and downstream biological interpretation.

Study Objectives and Overview

This work presents an integrated workflow for qualitative proteomics, combining high‐definition data independent acquisition (HDMSE) on the SYNAPT G2‐S system with advanced informatics. Using a 100 ng Escherichia coli digest spiked with known protein standards, the study evaluates the depth of protein coverage and confidence in peptide identifications.

Methodology

The experimental design involved on‐column injection of 100 ng E. coli peptides, chromatographic separation by nanoUPLC, and HDMSE acquisition at >20,000 FWHM resolution. Data processing employed ProteinLynx Global SERVER for database searching, with automated export of search results via a dedicated plug‐in.

Used Instrumentation

• nanoACQUITY UPLC System for peptide separation
• SYNAPT G2‐S mass spectrometer operating in LC/HDMSE mode
• ProteinLynx Global SERVER v3.0 for spectrum matching
• Scaffold v3.6 for data visualization and validation

Main Results and Discussion

Applying filtering criteria such as minimum protein probability, peptide count, and peptide probability, the workflow reliably identified numerous E. coli proteins, including low‐abundance species. Gene ontology annotation provided insight into protein functions. Representative MS/MS spectra of a CLPB chaperone peptide demonstrated full sequence coverage and high confidence. Retention time plots revealed co‐eluting species, supporting detailed peptide characterization.

Benefits and Practical Applications

The described approach offers several advantages:

• High confidence in protein and peptide identifications at low false discovery rates
• Reproducible label‐free qualitative profiling of complex samples
• Streamlined data export and filtering within a unified informatics environment

Future Trends and Opportunities

Advancements in ion mobility, faster scan speeds, and machine learning–driven data analysis are expected to deepen proteome coverage and accelerate discovery. Integration with quantitation workflows and cloud‐based platforms will further enhance throughput and accessibility.

Conclusion

The combination of HDMSE acquisition on the SYNAPT G2‐S system with ProteinLynx Global SERVER and Scaffold software yields a robust qualitative proteomics workflow. It enables sensitive detection of low‐abundance proteins and provides clear visualization and validation tools for large‐scale studies.

References

1. Li et al. Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. Proteomics. 2009 Mar;9(6):1696-719.
2. Searle BC. Scaffold: a bioinformatic tool for validating MS/MS-based proteomic studies. Proteomics. 2010 Mar;10(6):1265-9.