Berlin Institute of Health Technology Platform Metabolomics, Max-Delbrück-Centrum for Molecular Medicine, Robert-Rössle-Straße 10, 13125 Berlin-Buch, Germany.
Berlin Institute for Medical Systems Biology, Max-Delbrück-Centrum for Molecular Medicine, Robert-Rössle-Straße 10, 13125 Berlin-Buch, Germany.
Anal Chem. 2017 Mar 7;89(5):2986-2994. doi: 10.1021/acs.analchem.6b04456. Epub 2017 Feb 21.
Mass-spectrometry-based lipidomics aims to identify as many lipid species as possible from complex biological samples. Due to the large combinatorial search space, unambiguous identification of lipid species is far from trivial. Mass ambiguities are common in direct-injection shotgun experiments, where an orthogonal separation (e.g., liquid chromatography) is missing. Using the rich information within available lipid databases, we generated a comprehensive rule set describing mass ambiguities, while taking into consideration the resolving power (and its decay) of different mass analyzers. Importantly, common adduct species and isotopic peaks are accounted for and are shown to play a major role, both for perfect mass overlaps due to identical sum formulas and resolvable mass overlaps. We identified known and hitherto unknown mass ambiguities in high- and ultrahigh resolution data, while also ranking lipid classes by their propensity to cause ambiguities. On the basis of this new set of ambiguity rules, guidelines and recommendations for experimentalists and software developers of what constitutes a solid lipid identification in both MS and MS/MS were suggested. For researchers new to the field, our results are a compact source of ambiguities which should be accounted for. These new findings also have implications for the selection of internal standards, peaks used for internal mass calibration, optimal choice of instrument resolution, and sample preparation, for example, in regard to adduct ion formation.
基于质谱的脂质组学旨在从复杂的生物样本中尽可能多地鉴定脂质种类。由于组合搜索空间庞大，明确鉴定脂质种类绝非易事。在直接注射 shotgun 实验中，由于缺少正交分离（例如液相色谱），因此会出现质量模糊。我们利用现有脂质数据库中的丰富信息，生成了一个全面的规则集，描述了质量模糊性，同时考虑了不同质量分析仪的分辨率（及其衰减）。重要的是，我们考虑了常见的加合物物种和同位素峰，它们在由于相同的分子式而导致的完全质量重叠和可分辨的质量重叠中都起着重要作用。我们在高分辨率和超高分辨率数据中确定了已知和未知的质量模糊性，同时还按引起模糊性的倾向对脂质类别进行了排序。基于这组新的模糊规则，我们为实验人员和 MS 和 MS/MS 中可靠的脂质鉴定的软件开发者提出了指导方针和建议。对于该领域的新手研究人员，我们的结果是一个紧凑的模糊来源，应加以考虑。这些新发现还对内部标准的选择、用于内部质量校准的峰、仪器分辨率的最佳选择以及样品制备（例如加合物离子形成）产生影响。
