Exploring linear sequence determinants of inferred Collisional Cross-Sections of unmodified and phosphorylated peptides in an Orbitrap Mass Analyzer

Importance of the topic

Ion collisional cross-section (CCS) measurement provides an additional structural dimension to proteomic analyses, improving peptide discrimination and characterization without requiring dedicated ion mobility hardware.

Objectives and study overview

This work aims to extend a previously reported CCS inference method based on transient signal decay in Fourier-transform analyzers to complex peptide mixtures. By introducing minor modifications to an Orbitrap Exploris 480, the study evaluates high-throughput CCS estimation for unmodified and phosphorylated peptides from standard proteomic workflows.

Methodology and instrumentation

HeLa tryptic digest samples (100 ng) were separated by nanoLC with a 21 min gradient and analyzed on a modified Orbitrap Exploris 480 mass spectrometer under two ultra-high vacuum conditions (3.70×10⁻¹⁰ and 4.33×10⁻⁹ mbar). MS1 transients were acquired at 240 k, 120 k, and 60 k resolution, with MS2 at 15 k. CCS values were inferred from ion transient decay rates using a custom MaxQuant-based software suite.

Main results and discussion

Elevated UHV pressure enhanced transient decay and CCS resolution but decreased spectral quality, highlighting a trade-off. A 120 k MS1 resolution offered the best balance between identification rate and CCS discrimination. Inferred CCS values exhibited strong linear correlation (r² > 0.96) and high reproducibility (Pearson ≈ 0.9–1.0) compared to published IMS data. Sequence-dependent trends showed that higher proline content and internal proline positions yield more compact conformations, histidine near the C-terminus promotes compaction, and phosphorylation induces additional CCS reduction, especially in larger, multi-charged peptides and terminal phosphosite locations.

Benefits and practical applications

The approach enables CCS estimation in routine proteomic experiments without a dedicated ion mobility device, requires only minor hardware adjustments, and enhances peptide characterization by distinguishing post-translationally modified species.

Future trends and applications

Integration of CCS inference into standard FTMS platforms, expansion to diverse post-translational modifications, development of machine learning models for CCS prediction, and potential for real-time structural monitoring during LC-MS analyses.

Conclusion

CCS inference on an Orbitrap Exploris 480 is a robust, reproducible, and high-throughput strategy that yields data comparable to ion mobility measurements, offering valuable structural insights in proteomic workflows with minimal instrument changes.

Instrumentation used

• Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific)
• Ultra-high vacuum conditions at 3.70×10⁻¹⁰ and 4.33×10⁻⁹ mbar
• Nano flow liquid chromatography system with 21 min gradient
• Custom MaxQuant-based data analysis software

References

• Yang F; Voelkel JE; Dearden DV. Collision Cross Sectional Areas from Analysis of Fourier Transform Ion Cyclotron Resonance Line Width: A New Method for Characterizing Molecular Structure. Analytical Chemistry. 2012.
• Sanders JD; Grinfeld D; Aizikov K; Makarov A; Holden DD; Brodbelt JS. Determination of collision cross-sections of protein ions in an orbitrap mass analyzer. Analytical Chemistry. 2018;90(9):5896–5902.
• Meier F; Köhler ND; Brunner AD; Wanka JMH; Voytik E; Strauss MT; Mann M. Deep learning the collisional cross sections of the peptide universe from a million experimental values. Nature Communications. 2021;12(1):1–12.
• Ogata K; Chang CH; Ishihama Y. Effect of phosphorylation on the collision cross sections of peptide ions in ion mobility spectrometry. Mass Spectrometry. 2021;10(1):A0093.