Skyline Support for Proteome-wide Data Analysis of Bruker timsTOF dia-PASEF Acquisition

Importance of the Topic

Proteome-wide data analysis via DIA-PASEF increases throughput, sensitivity, and quantitative accuracy by combining parallel accumulation, ion mobility separation, and quadrupole isolation. This approach enables SRM-like performance at large scale, offering enhanced selectivity over MS1-based extraction.

Study Objectives and Overview

• Incorporate native Bruker timsTOF dia-PASEF data support into Skyline.
• Benchmark proteome-wide performance using a human, yeast, and E. coli mixture.

Methodology and Instrumentation

Sample mixtures from three organisms were fractionated, analyzed in DDA-PASEF mode, and searched with MaxQuant Andromeda. The resulting library of 152,417 unique precursors was imported into Skyline with normalized iRT values. Data acquisition used a fixed 32-window isolation scheme with eight TIMS accumulations across four IMS and quadrupole ranges. Skyline’s ProteoWizard-based 3D IMS model accelerated processing by 50-fold.

• Bruker timsTOF Pro in dia-PASEF mode
• MaxQuant Andromeda for MS/MS search
• Skyline with enhanced 3D IMS data layer
• ProteoWizard data conversion

Main Results and Discussion

The generated library covered 12,717 proteins and 143,335 precursors including standards. Skyline processed over 100,000 precursors in under one hour on a modern i7 workstation. Intra-condition CVs were below 20% for 91.1% of peptides with a median CV of 6.4%. LFQbench evaluation showed median quantitative accuracy within 7% and precision metrics comparable across species. Optimizing IMS resolving power at RP50 maximized peptide detections (>53,000) without compromising precision.

Benefits and Practical Applications

• High-throughput proteome quantification with robust precision
• Enhanced selectivity through combined IMS and quadrupole filtering
• Scalable processing enabling large cohort studies and QA/QC
• Suitable for biomarker discovery and systems biology investigations

Future Trends and Potential Applications

As computational methods and hardware accelerate, real-time and cloud-enabled analysis pipelines will reduce turnaround time. Integration of AI-driven peak detection and library-free approaches may further improve depth and accuracy, extending applications to clinical proteomics and single-cell studies.

Conclusion

Skyline’s native support for Bruker timsTOF dia-PASEF delivers rapid, high-coverage proteome-wide quantification with superior selectivity and reproducibility, positioning it as a powerful tool for modern quantitative proteomics.

References

1. MacLean B., Baker E., et al. JASMS. 2018 Nov;29(11):2182-2188.
2. Meier F., et al. BioRxiv. 2019 doi: https://doi.org/10.1101/656207
3. Navarro P., et al. Nat. Biotech. 2016 Nov;34(11):1130-1136.