Optimizing Collision Energy for Improved Molecular Networking in Non-targeted Lipidomics

초록

Lipidomics, an emerging field, focuses on the comprehensive analysis of lipid species. However, despite its advances, non-targeted lipidomics approaches continue to encounter significant challenges in lipid annotation, primarily due to the limited coverage of publicly available tandem mass spectrometry spectral libraries. Therefore, this study aims to introduce a non-targeted lipidomics approach using molecular networking to enhance neutral lipid identification. Collision energy condi- tions were first optimized using commercial neutral lipid standards and subsequently validated with National Institute of Stan- dards and Technology Standard Reference Material 1950 Metabolites in Frozen Plasma. A normalized collision energy of 30, combined with Global Natural Products Social Molecular Networking parameters (cosine score of 0.7 and a minimum of six matched fragment ions), enabled effective spectral connectivity and improved neutral lipid detection. Among the scan ranges tested, the 600–1000 m/z range was the most effective, facilitating comprehensive detection of diglycerides, triglycerides, and cholesteryl esters. This study presents an optimized molecular networking strategy for non-targeted lipidomics that enhances both lipid annotation and structural characterization.

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