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Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments
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Exploring Ion Mobility Mass Spectrometry Data File Conversions to Leverage Existing Tools and Enable New Workflows.
Sarah M Stow1, Bryson C Gibbons2, Leonard C Rorrer Iii3
1Agilent Technologies, Santa Clara, California 95051, United States.
Journal of the American Society for Mass Spectrometry
|July 26, 2024
Summary
This study introduces data conversion tools to simplify ion mobility mass spectrometry (IM-MS) analysis. These tools adapt complex IM-MS data into standard LC-MS formats, enabling broader software compatibility for lipidomics and proteomics.
Area of Science:
- Analytical Chemistry
- Mass Spectrometry
- Biochemistry
Background:
- Ion mobility (IM) coupled with LC-MS enhances complex sample analysis by adding a separation dimension.
- Current data analysis workflows often struggle to fully utilize the rich information from LC-IM-MS data.
- The full dimensionality of LC-IM-MS data is not always necessary for extracting valuable sample insights.
Purpose of the Study:
- To develop data file conversion tools for simplifying the analysis of IM-MS data.
- To enable the use of existing LC-MS software for analyzing IM-MS datasets.
- To reduce the complexity associated with processing and analyzing IM-MS data.
Main Methods:
- Development of data file conversion tools within the PNNL PreProcessor software.
- Implementation of three specific data transformations: IM axis to LC axis mapping, drift time to CCS/z conversion, and IM/MS fragmentation data to LC-MS DDA format.
- Demonstration of these transformations using lipidomics and proteomics workflows.
Main Results:
- Successful adaptation of IM-MS data into standard LC-MS formats.
- Demonstrated utility of the PNNL PreProcessor tools in lipidomics and proteomics analyses.
- Enabled leveraging of existing LC-MS analysis software for previously complex IM-MS datasets.
Conclusions:
- The developed data conversion tools significantly reduce the complexity of IM-MS data analysis.
- These transformations allow researchers to benefit from IM separation while utilizing established LC-MS analysis pipelines.
- The approach broadens the accessibility and application of IM-MS data in fields like lipidomics and proteomics.
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