National Protein Science Technology Center, Tsinghua University, Beijing 100084, China.
National Protein Science Technology Center, Tsinghua University, Beijing 100084, China; School of Life Sciences, Tsinghua University, Beijing 100084, China.
Talanta. 2018 Feb 1;178:287-293. doi: 10.1016/j.talanta.2017.09.046. Epub 2017 Sep 19.
Untargeted lipidomics is increasingly popular due to the broad coverage of lipid species. Data dependent MS/MS acquisition is commonly used in order to acquire sufficient information for confident lipid assignment. However, although lipids are identified based on MS/MS confirmation, a number of false positives are still observed. Here, we discuss several causes of introducing lipid false identifications in untargeted analysis. Phosphotidylcholines and cholesteryl esters generate in-source fragmentation to produce dimethylated phosphotidylethanolamine and free cholesterol. Dimerization of fatty acid results in false identification of fatty acid ester of hydroxyl fatty acid. Realizing these false positives is able to improve confidence of results acquired from untargeted analysis. Besides, thresholds are established for lipids identified using LipidSearch v4.1.16 software to reduce unreliable results.
由于靶向脂质组学具有广泛的脂质种类覆盖范围，因此越来越受欢迎。为了获得足够的脂质分配信心，通常使用数据依赖型 MS/MS 采集来获取信息。然而，尽管脂质是基于 MS/MS 确认来识别的，但仍会观察到一些假阳性。在这里，我们讨论了在非靶向分析中引入脂质假阳性的几个原因。磷酸胆碱和胆固醇酯会产生内源碎裂，产生二甲氨基乙醇磷酸和游离胆固醇。脂肪酸的二聚化会导致羟基脂肪酸的脂肪酸酯的错误鉴定。意识到这些假阳性可以提高非靶向分析获得的结果的可信度。此外，还为使用 LipidSearch v4.1.16 软件鉴定的脂质建立了阈值，以减少不可靠的结果。
