Exploring Ion Mobility Data File Conversions to Leverage Existing Tools and Enable New Workflows

Significance of the Topic

Adding ion mobility to LC-MS experiments introduces an orthogonal separation dimension that enhances the analysis of complex mixtures. By converting LC-IM-MS data into formats compatible with established LC-MS workflows, researchers can leverage existing informatics tools to extract deeper insights from lipidomics, PFAS profiling, and other applications.

Objectives and Study Overview

• Enable traditional LC-MS data analysis workflows to process LC-IM-MS files through novel data conversions.
• Integrate mapping of ion mobility (IM) axis to chromatographic axis and conversion of All Ions IM/MS fragmentation into data-dependent acquisition (DDA) spectra.
• Evaluate an automated high-resolution demultiplexing (HRdm) workflow for improved spectral clarity.
• Explore conversion of comprehensive 2D-LC MS data into LC-IM-MS format for four-dimensional analysis.

Methodology and Instrumentation

• Instrumentation: Agilent 6560 IM-QTOF coupled to 1290 Infinity II LC for both 1D and 2D separations.
• Samples: NIST SRM 1950 human plasma lipid extract and ITA-70 PFAS standard.
• Software Tools: PNNL PreProcessor for data conversion, IM-MS Browser for ion mobility feature extraction, MassHunter Qual, Lipid Annotator, Mass Profile, and MS-DIAL for downstream analysis.
• Conversion Workflows: Two PNNL PreProcessor modes – Workflow 1 maintains chromatographic elution, Workflow 2 treats drift time as retention time in output DDA files.

Main Results and Discussion

• All Ions IM/MS-to-DDA Conversion:
    • Converted files yielded the highest number of lipid identifications by capitalizing on the improved duty cycle of All Ions acquisition.
    • Mirror‐plot comparisons showed expectedly lower dot‐product similarity versus quadrupole isolation but better fragment coverage for smaller lipid fragments.
• Isomer Treatment:
    • Workflow 1 generated separate spectra per isomer when stepped collision energy was applied, but overlapping fragments could complicate interpretation.
    • Workflow 2 fully resolved IM isomers into distinct DDA events, yielding two unique spectra for LPC 20:3 in downstream analysis (MassHunter Qual and MS-DIAL).
• High-Resolution Demultiplexing (HRdm):
    • The new HRdm 3.0 workflow integrates interpolation, demultiplexing, feature finding, and deconvolution in a single automated step.
    • This reduces user handling of multiple software packages and streamlines the conversion to DDA format.
• Single Pulse vs Multiplexed Acquisition:
    • Multiplexed All Ions data processed with automated HRdm increased lipid IDs in both Lipid Annotator and MS-DIAL compared to single pulse.
    • Triacylglycerol lipids, which often have broader fragment bands, benefited from HRdm deconvolution.
• 2D-LC MS to LC-IM-MS Conversion:
    • Conversion of PFAS standard set via PNNL PreProcessor allowed four-dimensional feature extraction, detecting 12 of 14 standards in both native LC-IM-MS and converted datasets.
    • Ongoing work focuses on assessing mass accuracy and applying IM peak detection to chromatographic peak shapes.

Benefits and Practical Applications

• Maximized lipid and small molecule identifications through improved duty cycles and deconvolution.
• Ability to resolve and analyze IM isomers as separate spectral events.
• Streamlined workflow reduces software dependencies and simplifies data conversion.
• Compatibility with existing LC-MS tools extends capabilities to four-dimensional datasets in lipidomics, environmental analysis, and QA/QC.

Future Trends and Applications

• Expansion of PNNL PreProcessor capabilities for seamless conversion of comprehensive 2D-LC datasets into LC-IM-MS format.
• Integration of enhanced mass calibration and alignment routines for improved accuracy in converted files.
• Advanced feature detection algorithms to exploit four-dimensional separation for novel biomarker discovery.
• Potential for automated workflows combining IM conversion, HRdm, and downstream identification in a single pipeline.

Conclusion

Data file conversions provided by the PNNL PreProcessor enable existing LC-MS workflows to harness the full potential of ion mobility separations. Automated high-resolution demultiplexing and IM-to-DDA transformations yield richer spectral data, increase identification rates, and simplify processing. Converting 2D-LC MS to LC-IM-MS formats further broadens analytical capability, paving the way for comprehensive four-dimensional studies.

References

1. Bilbao A., Mejía E., et al. Journal of Proteome Research 2022;21(3):798-807.
2. Tsugawa H., Cajka T., et al. Nature Methods 2015;12(6):523-526.
3. Wright J., et al. Agilent Technologies Technical Overview 2022.