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Updated: Jan 28, 2026

Shotgun Lipidomics of Rodent Tissues
Published on: November 18, 2022
Phospholipid Profiling Established by Structure-Rich Fragments for Molecular Species Level Shotgun Analysis
Rong Chen1, Amber H Jannasch2, Bruce R Cooper2
1Department of Chemistry, Purdue University, West Lafayette, Indiana, USA.
Rationale:
Accurate identification of phospholipid molecular species remains a major challenge in shotgun lipidomics because conventional tandem mass spectrometry typically resolves only one structural moiety at a time. This structural ambiguity limits confident lipid biomarker discovery and biological interpretation. Improving structural specificity without sacrificing analytical speed is therefore critical for lipidomics and disease-related studies.
Methods:
Electrospray ionization tandem mass spectrometry was performed using direct infusion on a triple quadrupole mass spectrometer operated in multiple reaction monitoring (MRM) mode. MRMs were designed based on structure-rich phospholipid fragments containing both the headgroup and one fatty acyl chain. Lipids were extracted from mouse liver and brain tissues and analysed without chromatographic separation, and normal-phase LC was used for lipid headgroup confirmation only.
Results:
Structure-rich MS/MS transitions enabled molecular species identification of both diacyl and ether phospholipids. 15 PUFA-containing phospholipids were identified as candidate biomarkers differentiating healthy and metabolic syndrome mouse livers, revealing opposing regulation among structurally similar species supported by complementary fragmentation and LC evidence. In mouse brains, three ether lipid biomarkers were discovered, including plasmalogens and plasmanyl lipids, with distinct disease-associated trends.
Conclusion:
This study demonstrates that structure-rich MS/MS transitions substantially improve phospholipid structural specificity in shotgun lipidomics while maintaining high throughput. The method enables reliable identification of individual lipid species with minimal isomer interference and is readily compatible with existing workflows. This strategy offers a practical path toward more precise lipid biomarker discovery and mechanistic insight into metabolic disease.
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