Analysis of Plasma Proteome for a Respiratory Disease Cohort Using SONAR on a SYNAPT XS Mass Spectrometer

Importance of Topic

Plasma proteome analysis is crucial for understanding disease mechanisms and identifying biomarkers in respiratory conditions such as COPD and asthma. Reliable, high throughput mass spectrometry methods enhance specificity and quantitative accuracy, supporting translational research and clinical studies.

Study Goals and Overview

This study applied the SONAR data independent acquisition method on a SYNAPT XS mass spectrometer to characterize the plasma proteome of three pooled patient cohorts: healthy controls, chronic obstructive pulmonary disease, and asthma. Objectives included improving peptide identification confidence, sequence coverage, and reproducibility.

Methodology and Used Instrumentation

• Sample preparation involved tryptic digestion of undepleted human plasma pooled into three working samples (n=6 each).
• Chromatographic separation employed an ACQUITY UPLC M Class system with a Peptide CSH C18 column (300 μm I D x 100 mm) and a 45 minute gradient from 1 to 40 percent acetonitrile at 50 μL per minute.
• Mass spectrometry was performed on a SYNAPT XS instrument operating in SONAR mode to collect fast scanning quadrupole data for both precursor and fragment ions.
• Data processing and protein identification used Progenesis QI for Proteomics with searches against the UniProt reviewed human database, applying carbamidomethyl C as a fixed modification, methionine oxidation variable modifications, and a false discovery rate threshold of 1 percent.

Main Results and Discussion

• A total of 349 proteins were identified across all cohorts with substantial overlap between conditions.
• Median sequence coverage ranged from 18 to 25 percent across groups, demonstrating detailed proteome mapping.
• Technical reproducibility was high, with median coefficients of variation below three percent for normalized protein abundance.
• Linear dynamic range spanned three to four orders of magnitude within each cohort, enabling quantification of both high and low abundance proteins.
• The scanning quadrupole dimension in SONAR provided enhanced selectivity, resolving coeluting peptides and improving spectral clarity.
• Data integration with Skyline software confirmed quantitative accuracy, showing multiple transitions and more than ten points per chromatographic peak for example peptides.

Benefits and Practical Applications

The SONAR workflow on a SYNAPT XS platform offers:

• Improved specificity and reduced interference in complex plasma samples
• High throughput compatible with fast chromatography
• Robust quantification with low technical variation
• Flexibility to integrate with third party informatics tools

These attributes support applications in biomarker discovery, clinical proteomics, QA QC in biopharma, and multiomic investigations.

Future Trends and Opportunities

• Expansion of SONAR-based DIA approaches into metabolomics and lipidomics for comprehensive multiomic studies
• Integration with advanced bioinformatics and machine learning pipelines for deeper data mining
• Development of open access spectral libraries and customized workflows for personalized medicine
• Implementation in clinical laboratories for rapid biomarker screening and outcome monitoring

Conclusion

This work demonstrates that SONAR acquisition on a SYNAPT XS mass spectrometer delivers high specificity, broad dynamic range, and reproducible protein identification in plasma proteome analysis of respiratory disease cohorts. The method is well suited for diverse applications in research and clinical settings.

References

1 Gethings LA et al Rapid Commun Mass Spectrom 2017 31 1599–1606
2 Moseley AM et al J Proteome Res 2017 17 770–779