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双(单酰甘油)磷酸脂质的无标记定量鸟枪法分析。

Label-free quantitative shotgun analysis of bis(monoacylglycero)phosphate lipids.

作者信息

Wang Lian Y, Derks Rico J E, Brewster Kevin A J, Prtvar Danilo, Tahirovic Sabina, Berghoff Stefan A, Giera Martin

机构信息

Center for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333ZA, The Netherlands.

German Center for Neurodegenerative Diseases (DZNE), Munich, 81377, Germany.

出版信息

Anal Bioanal Chem. 2025 May 9. doi: 10.1007/s00216-025-05890-4.

Abstract

Interest in the role of bis(monoacylglycero)phosphate (BMP) lipids in lysosomal function has significantly grown in recent years. Emerging evidence highlights BMPs as critical players not only in Niemann-Pick disease type C (NPC) but also in other pathologies such as neurodegeneration, cardiovascular diseases, and cancers. However, the selective analysis of BMPs is significantly hindered by isomeric phosphatidylglycerol (PG) lipids. While this can be addressed by chromatographic separation, it poses a significant challenge for shotgun lipidomics approaches. Here, we present a shotgun lipidomics strategy to detect and separate BMPs from PGs using differential fragmentation of sodiated ions. This approach, including isotope correction, is integrated into an existing quantitative shotgun lipidomics workflow (Lipidyzer combined with Shotgun Lipidomics Assistant software) that simultaneously quantifies >1400 lipids. Validation using K-562 cell extracts demonstrated acceptable linearity, trueness, repeatability, and a limit of quantification of 0.12 µM, confirming robust analytical performance. Finally, characteristic accumulation of BMP lipids is shown in bone marrow-derived macrophages from NPC mice, demonstrating its applicability. Our method presents a quantitative, selective, rapid, and robust solution for shotgun-based BMP analysis without the need for extensive chromatographic separation or derivatization. The integration of BMP lipid detection into the Lipidyzer platform, alongside the recently launched iSODA data visualization tool, empowers chemists and biologists to gain deeper insights into BMP lipid biology.

摘要

近年来,人们对双(单酰甘油)磷酸酯(BMP)脂质在溶酶体功能中的作用的兴趣显著增加。新出现的证据表明,BMP不仅是尼曼-匹克病C型(NPC)的关键参与者,也是神经退行性疾病、心血管疾病和癌症等其他病理过程中的关键参与者。然而,异构体磷脂酰甘油(PG)脂质严重阻碍了对BMP的选择性分析。虽然这可以通过色谱分离来解决,但这对鸟枪法脂质组学方法构成了重大挑战。在这里,我们提出了一种鸟枪法脂质组学策略,利用钠化离子的差异裂解从PG中检测和分离BMP。这种方法,包括同位素校正,被整合到现有的定量鸟枪法脂质组学工作流程(Lipidyzer与鸟枪法脂质组学辅助软件相结合)中,该流程可同时定量超过1400种脂质。使用K-562细胞提取物进行的验证表明,该方法具有可接受的线性、准确性、重复性和0.12 µM的定量限,证实了其强大的分析性能。最后,在NPC小鼠骨髓来源的巨噬细胞中显示了BMP脂质的特征性积累,证明了其适用性。我们的方法为基于鸟枪法的BMP分析提供了一种定量、选择性、快速且强大的解决方案,无需广泛的色谱分离或衍生化。将BMP脂质检测整合到Lipidyzer平台中,再加上最近推出的iSODA数据可视化工具,使化学家和生物学家能够更深入地了解BMP脂质生物学。

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