Glycosyl inositol phospho ceramides (GIPCs) are the major sphingolipids on earth, as they account for a considerable fraction of the total lipids in plants and fungi, which in turn represent a large portion of the biomass on earth. Despite their obvious importance, GIPC analysis remains challenging due to the lack of commercial standards and automated annotation software. In this work, we introduce a novel GIPC glycolipidomics workflow based on reversed-phase ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry. For the first time, automated GIPC assignment was performed using the open-source software Lipid Data Analyzer (LDA), based on platform-independent decision rules. Four different plant samples (salad, spinach, raspberry, and strawberry) were analyzed and the results revealed 64 GIPCs based on accurate mass, characteristic MS2 fragments and matching retention times. Relative quantification using lactosyl ceramide for internal standardization revealed GIPC t18:1/h24:0 as the most abundant species in all plants. Depending on the plant sample, GIPCs contained mainly amine, N-acetylamine or hydroxyl residues. Most GIPCs revealed a Hex-HexA-IPC core and contained a ceramide part with a trihydroxylated t18:0 or a t18:1 long chain base and hydroxylated fatty acid chains ranging from 16 to 26 carbon atoms in length (h16:0–h26:0). Interestingly, four GIPCs containing t18:2 were observed in the raspberry sample, which was not reported so far. The presented workflow supports the characterization of different plant samples by automatic GIPC assignment, potentially leading to the identification of new GIPCs. For the first time, automated high-throughput profiling of these complex glycolipids is possible by liquid chromatography-high-resolution tandem mass spectrometry and subsequent automated glycolipid annotation based on decision rules.

中文翻译：

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追逐地球上的主要鞘脂：糖脂组学对植物糖基肌醇磷酸神经酰胺的自动注释。

糖基肌醇磷酸神经酰胺（GIPC）是地球上的主要鞘脂，因为它们占植物和真菌中总脂质的相当一部分，而脂质又代表了地球上生物质的很大一部分。尽管具有明显的重要性，但由于缺乏商业标准和自动注释软件，GIPC分析仍然具有挑战性。在这项工作中，我们介绍了一种基于反相超高压液相色谱与高分辨率质谱联用的新型GIPC糖脂组学工作流程。第一次，基于平台无关的决策规则，使用开源软件Lipid Data Analyzer（LDA）执行了GIPC自动分配。分析了四种不同的植物样品（沙拉，菠菜，覆盆子和草莓），结果显示，基于准确的质量，有64种GIPC，特有的MS2片段和匹配的保留时间。使用乳糖基神经酰胺进行内部标准化的相对定量显示，GIPC t18：1 / h24：0是所有植物中最丰富的物种。取决于植物样品，GIPCs主要包含胺，N-乙酰胺或羟基残基。大多数GIPC都显示了Hex-HexA-IPC核心，并含有神经酰胺部分，该部分具有三羟基化的t18：0或t18：1长链碱基，且羟基化的脂肪酸链的长度为16至26个碳原子（h16：0–h26： 0）。有趣的是，在覆盆子样品中观察到了四个含有t18：2的GIPC，目前尚未报道。提出的工作流程支持通过自动GIPC分配来表征不同的植物样品，从而有可能导致识别新的GIPC。首次，