Conventional lipidomics provides a rich snapshot of the molecular architecture of lipid metabolism. However, it lacks a dynamic perspective. Temporal organization and regulation of lipid metabolism are essential for understanding metabolic flux, transformation, and pathway-level organization. To uncover these hidden dynamics, we employ a biorthogonal labelling strategy based on click chemistry, which enables resolution of the temporal organization of lipid metabolism.

Cells uptake alkyne fatty acids, incorporate them into endogenous lipids, and shuttle them through anabolic and catabolic pathways. These labelled lipids can then be selectively tagged using azide-based mass reporters. We extended this methodology to LC–MS/MS, enabling the simultaneous analysis of clicked and unlabelled lipidomes with isomer-level resolution.

Importantly, we performed comprehensive analytical characterization of clicked lipids, including preferential adduct formation, in-source fragmentation, and detailed fragmentation rules. These features are now fully integrated into the Lipostar2 software, which supports lipid metabolic tracing experiments through an end-to-end bioinformatics pipeline. Method development and validation details are described in “LC-MS and High-Throughput Data Processing Solutions for Lipid Metabolic Tracing Using Bioorthogonal Click Chemistry” ( Nepachalovich P. et al., Angew. Chem. Int. Ed., 2025).