Salem Mohamed A, Giavalisco Patrick
Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
Department of Pharmacognosy, Faculty of Pharmacy, Cairo University, Cairo, Egypt.
Methods Mol Biol. 2018;1778:137-155. doi: 10.1007/978-1-4939-7819-9_10.
In recent years, multiple mass-spectrometric methods have been developed to tackle fundamental analytical questions in the field of biology and biochemistry. One essential approach relies on the use of liquid chromatography (LC), for efficient compound separation, coupled to high-resolution mass spectrometry (HR-MS). Even though these techniques are highly sensitive allowing for the reliable measurement of several thousand mass features, the major bottleneck is to convert the measured masses into annotated lipid species. To overcome this problem, we present a simple, example-based workflow, which provides an introduction to basic strategies for the manual validation of LC-MS-based lipidomic data. The whole strategy makes use of a data-independent acquisition (DIA) method, where alternating MS measurement cycles using high and low-energy scans are used. This measurement strategy allows to reliably annotate lipids, based on the exact mass measurements of intact, but also fragmented lipids from continuously recorded spectra.
近年来，已经开发出多种质谱方法来解决生物学和生物化学领域的基本分析问题。一种基本方法依赖于使用液相色谱（LC）进行高效化合物分离，并与高分辨率质谱（HR-MS）联用。尽管这些技术具有很高的灵敏度，能够可靠地测量数千个质量特征，但主要瓶颈在于将测得的质量转化为注释的脂质种类。为了克服这个问题，我们提出了一个简单的、基于示例的工作流程，该流程介绍了基于液相色谱-质谱的脂质组学数据手动验证的基本策略。整个策略使用了一种数据非依赖采集（DIA）方法，其中使用高能量和低能量扫描交替进行质谱测量循环。这种测量策略能够基于连续记录光谱中完整脂质以及碎片化脂质的精确质量测量，可靠地注释脂质。
