Improved dia-PASEF isolation window schemes for proteomics measurements

Importance of the Topic

Data-Independent Acquisition combined with trapped ion mobility separation (dia-PASEF) represents a major advance in proteomics workflows. By integrating ion mobility into the acquisition scheme, complex peptide mixtures can be fractionated in an additional dimension, improving sensitivity, reproducibility and depth of proteome coverage. This is particularly important for low-input samples such as single-cell digests, where maximizing ion utilization and discrimination against background noise is critical.

Study Objectives and Overview

This work aimed to design and evaluate improved dia-PASEF isolation window schemes for enhanced proteome analysis. Key goals included:

• Optimizing window width and distribution across both mass and mobility dimensions.
• Assessing the trade-off between selectivity and sensitivity at varying TIMS scan times.
• Quantifying protein and precursor identifications from ultra-low and standard sample loads.

Methodology and Instrumentation Used

Peptides from a tryptic digest of K562 cells were prepared at concentrations ranging from 100 ng/μL down to 0.25 ng/μL, with 0.015% DDM added to mitigate surface adsorption. Separation and detection were performed as follows:

• Liquid chromatography: nanoElute system with a 25 cm × 75 μm ID Aurora Ultimate column (IonOpticks), 22-minute gradient (5–35% ACN, 0.1% FA) at 250 nL/min.
• Ion source: CaptiveSpray ultra emitter.
• Mass spectrometry: timsTOF Ultra instrument operated in dia-PASEF mode.
• Window design: initial schemes generated with py_diAID, manually refined to cover a broad m/z-mobility range in 24 windows (3×8 per TIMS scan).
• Data processing: dia-NN 1.8.1 with a 560,000-precursor library, including Match Between Runs for enhanced second-pass identification.

Main Results and Discussion

Optimized window schemes achieved a balance between narrow isolation widths (high selectivity) and sufficient accumulation time (high sensitivity). Key findings:

• At 0.25 ng input, up to 5,400 protein groups and >47,000 precursors were consistently identified in triplicate runs.
• At 100 ng input, extending the library with MBR yielded 8,500 protein groups and >105,000 precursors.
• Shorter TIMS ramps with more windows increased selectivity but required trade-offs in sensitivity when cycle time approached chromatographic peak widths.

Benefits and Practical Applications

This optimized dia-PASEF approach delivers:

• Exceptional proteome depth from sub-nanogram samples, enabling single-cell studies.
• High throughput with 22-minute gradients, suitable for large-scale projects.
• Robust quantitation without extensive method fine-tuning, facilitating routine QA/QC and biomarker discovery.

Future Trends and Possibilities of Applications

Emerging directions include:

• Automated window scheme generation driven by machine learning to adapt to sample complexity.
• Integration with single-cell platforms for detailed cell heterogeneity studies.
• Extension to post-translational modification mapping by tailoring window placement around enriched m/z ranges.

Conclusion

Refined dia-PASEF isolation window designs, combined with TIMS, offer a powerful strategy for ultra-sensitive, high-throughput proteomics. By fine-tuning window widths and scan times, researchers can maximize both depth and quantitative precision across a broad range of sample inputs.

References

Skowronek J., et al. Mol Cell Proteomics. 2022;21(9):100279.