Department of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States.
Department of Mechanical Engineering, University of Washington, Seattle Washington 98195, United States.
J Am Soc Mass Spectrom. 2023 Sep 6;34(9):2016-2024. doi: 10.1021/jasms.3c00181. Epub 2023 Jul 31.
Lipid metabolism is implicated in a variety of diseases, including cancer, cell death, and inflammation, but lipidomics has proven to be challenging due to the vast structural diversity over a narrow range of mass and polarity of lipids. Isotope labeling is often used in metabolomics studies to follow the metabolism of exogenously added labeled compounds because they can be differentiated from endogenous compounds by the mass shift associated with the label. The application of isotope labeling to lipidomics has also been explored as a method to track the metabolism of lipids in various disease states. However, it can be difficult to differentiate a single isotopically labeled lipid from the rest of the lipidome due to the variety of endogenous lipids present over the same mass range. Here we report the development of a dual-isotope deuterium labeling method to track the metabolic fate of exogenous polyunsaturated fatty acids, e.g., arachidonic acid, in the context of ferroptosis using hydrophilic interaction-ion mobility-mass spectrometry (HILIC-IM-MS). Ferroptosis is a type of cell death that is dependent on lipid peroxidation. The use of two isotope labels rather than one enables the identification of labeled species by a signature doublet peak in the resulting mass spectra. A Python-based software, D-Tracer, was developed to efficiently extract metabolites with dual-isotope labels. The labeled species were then identified with LiPydomics based on their retention times, collision cross section, and / values. Changes in exogenous AA incorporation in the absence and presence of a ferroptosis inducer were elucidated.
脂质代谢与多种疾病有关，包括癌症、细胞死亡和炎症，但由于脂质在质量和极性狭窄范围内具有广泛的结构多样性，因此脂质组学一直具有挑战性。同位素标记在代谢组学研究中经常用于跟踪外源性添加标记化合物的代谢，因为它们可以通过与标记相关的质量位移与内源性化合物区分开来。同位素标记在脂质组学中的应用也被探索为跟踪各种疾病状态下脂质代谢的方法。然而，由于在相同质量范围内存在多种内源性脂质，因此很难将单个同位素标记的脂质与脂质组的其余部分区分开来。在这里，我们报告了一种双重同位素氘标记方法的开发，该方法使用亲水相互作用-离子迁移-质谱（HILIC-IM-MS）在铁死亡的背景下跟踪外源性多不饱和脂肪酸（如花生四烯酸）的代谢命运。铁死亡是一种依赖于脂质过氧化的细胞死亡形式。使用两个同位素标记而不是一个，可以通过在所得质谱中出现特征双峰来识别标记的物质。开发了一个基于 Python 的软件 D-Tracer，用于有效地提取具有双重同位素标记的代谢物。然后根据保留时间、碰撞截面和/值，使用 LiPydomics 对标记的物质进行鉴定。阐明了在不存在和存在铁死亡诱导剂的情况下外源性 AA 掺入的变化。
