Flexibility of HRIM-MS Analysis for Targeted Lipid Profiling: Choose Your Own Adventure!

Importance of the Topic

The structural complexity and high prevalence of isomeric lipid species present significant analytical challenges. Traditional LC-MS often fails to distinguish closely related lipids. High-resolution ion mobility-mass spectrometry (HRIM-MS) offers a powerful solution by separating ions based on their gas-phase conformations, enabling detailed lipid profiling.

Objectives and Study Overview

• Assess the flexibility of HRIM-MS using flow injection analysis (FIA) and liquid chromatography (LC) for targeted ganglioside profiling.
• Compare throughput, sensitivity, and isomer resolution between FIA-HRIM-MS and LC-HRIM-MS workflows.
• Determine collision cross section (CCS) values for a broad range of gangliosides to enhance lipid identification confidence.

Applied Methodology and Instrumentation

Experimental work utilized a porcine ganglioside extract (~100 µg/mL). FIA-HRIM-MS employed a rapid 2-minute infusion to profile abundant species, while LC-HRIM-MS used a 30-minute HILIC gradient for improved separation and reduced ion suppression. Ion mobility data were calibrated using a third-order polynomial derived from MOBEITM TuneMix standards.

Used Instrumentation

• MOBEITM high-resolution ion mobility platform (MOBILion Systems)
• Agilent 6545XT QTOF mass spectrometer
• Agilent 1290 Infinity II Autosampler
• Ascentis Si HILIC column for LC separation

Main Results and Discussion

• FIA-HRIM-MS achieved ≤2-minute analysis, quantifying the most abundant lipids and resolving multiple isomers.
• LC-HRIM-MS reduced ion suppression, enabling quantitation of low-abundance species and detection of approximately six times more isomers compared to FIA alone.
• Collision cross section values were determined for over 40 gangliosides across 12 classes with %RSD below 0.2%, demonstrating high reproducibility.
• Conformational space plots highlighted distinct CCS distributions for d36:1 and d38:1 species, supporting confident lipid identification.

Benefits and Practical Applications

The combined HRIM-MS workflows deliver a versatile platform for targeted lipidomics, offering high throughput and deep structural insights. Applications include biomedical research, quality control in pharmaceutical and food industries, and discovery-driven lipid profiling in complex biological samples.

Future Trends and Application Opportunities

Advancements may include integration of ion mobility with machine learning for CCS prediction, development of untargeted workflows for comprehensive lipidome coverage, and translation into clinical diagnostics for biomarker discovery.

Conclusion

The study demonstrates that HRIM-MS, when paired with FIA or LC, affords a flexible and reproducible approach for targeted lipid profiling. By achieving rapid throughput and high-resolution isomer separation, this methodology enhances the depth and confidence of lipid analyses.