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Updated: Nov 6, 2025

Shotgun Lipidomics of Rodent Tissues
Published on: November 18, 2022
High Confidence Shotgun Lipidomics Using Structurally Selective Ion Mobility-Mass Spectrometry.
Bailey S Rose1, Katrina L Leaptrot1, Rachel A Harris1
1Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA.
Ion mobility-mass spectrometry (IM-MS) enhances shotgun lipidomics by resolving isomeric lipids. This method uses collision cross section (CCS) values for more confident lipid identification in untargeted analyses.
Area of Science:
- Analytical Chemistry
- Biochemistry
- Lipidomics
Background:
- Shotgun lipidomics is crucial for understanding cellular lipid profiles.
- Liquid chromatography (LC) is a common separation technique but faces challenges with isomeric lipid resolution.
- Ion mobility (IM) offers a complementary or alternative gas-phase separation strategy.
Purpose of the Study:
- To provide an overview of an untargeted ion mobility-mass spectrometry (IM-MS) workflow.
- To demonstrate the utility of IM-MS for high-confidence lipid identification.
- To highlight the role of collision cross section (CCS) values in lipidomics.
Main Methods:
- Utilizing a commercial drift tube ion mobility-quadrupole-time-of-flight mass spectrometer (IM-QTOF).
- Implementing an untargeted IM-MS workflow for lipid analysis.
- Acquiring and analyzing ion mobility and mass spectrometry data.
Main Results:
- Ion mobility separation effectively resolves isomeric lipids.
- Collision cross section (CCS) values serve as valuable molecular descriptors.
- The IM-MS workflow enhances confidence in lipid identification.
Conclusions:
- Ion mobility-mass spectrometry is a powerful tool for untargeted lipidomics.
- Integrating IM into lipidomics workflows improves lipid identification accuracy.
- This approach offers a high-throughput alternative or supplement to traditional LC-based methods.
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