Nepachalovich Palina, Bonciarelli Stefano, Lombardi Bendoula Gabriele, Desantis Jenny, Eleuteri Michela, Thiele Christoph, Goracci Laura, Fedorova Maria
Center of Membrane Biochemistry and Lipid Research, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Tatzberg 47-49, Dresden, 01307, Germany.
Mass Analytica, Av Cerdanyola 92-94, Sant Cugat del Vallés, 08173, Spain.
Angew Chem Int Ed Engl. 2025 Jul;64(27):e202501884. doi: 10.1002/anie.202501884. Epub 2025 May 2.
Tracing lipid metabolism in mammalian cells presents a significant technological challenge due to the vast structural diversity of lipids involved in multiple metabolic routes. Bioorthogonal approaches based on click chemistry have revolutionized analytical performance in lipid tracing. When adapted for mass spectrometry (MS), they enable highly specific and sensitive analyses of lipid transformations at the lipidome scale. Here, we advance this approach by integrating liquid chromatography (LC) prior to MS detection and developing a software-assisted workflow for high-throughput data processing. LC separation resolved labeled and unmodified lipids, enabling qualitative and quantitative analysis of both lipidome fractions, as well as isomeric lipid species. Using synthetic standards and endogenously produced alkyne lipids, we characterized LC-MS behavior, including preferential adduct formation and the extent of in-source fragmentation. Specific fragmentation rules, derived from tandem MS experiments for 23 lipid subclasses, were implemented in Lipostar2 software for high-throughput annotation and quantification of labeled lipids. Applying this platform, we traced metabolic pathways of palmitic and oleic acid alkynes, revealing distinct lipid incorporation patterns and metabolic bottlenecks. Altogether, here we provide an integrated analytical and bioinformatics platform for high-throughput tracing of lipid metabolism using LC-MS workflow.
由于参与多种代谢途径的脂质具有巨大的结构多样性，追踪哺乳动物细胞中的脂质代谢面临重大技术挑战。基于点击化学的生物正交方法彻底改变了脂质追踪的分析性能。当应用于质谱（MS）时，它们能够在脂质组规模上对脂质转化进行高度特异性和灵敏的分析。在此，我们通过在MS检测之前整合液相色谱（LC）并开发用于高通量数据处理的软件辅助工作流程来推进这种方法。LC分离解析了标记和未修饰的脂质，能够对脂质组部分以及异构体脂质种类进行定性和定量分析。使用合成标准品和内源性产生的炔烃脂质，我们表征了LC-MS行为，包括优先加合物形成和源内碎片化程度。从23种脂质亚类的串联MS实验得出的特定碎片化规则在Lipostar2软件中得以实现，用于对标记脂质进行高通量注释和定量。应用这个平台，我们追踪了棕榈酸和油酸炔烃的代谢途径，揭示了不同的脂质掺入模式和代谢瓶颈。总之，我们在此提供了一个使用LC-MS工作流程进行脂质代谢高通量追踪的综合分析和生物信息学平台。
