Roberts Joshua A, Radnoff Angela S, Bushueva Aleksandra, Menard Jocelyn A, Wasslen Karl V, Harley Meaghan, Manthorpe Jeffrey M, Smith Jeffrey C
Department of Chemistry, Carleton University, Ottawa, Ontario K1S 5B6, Canada.
Carleton Mass Spectrometry Centre, Carleton University, Ottawa, Ontario K1S 5B6, Canada.
J Am Soc Mass Spectrom. 2024 Dec 4;35(12):3095-3106. doi: 10.1021/jasms.4c00320. Epub 2024 Oct 7.
Lipidomics is a well-established field, enabled by modern liquid chromatography mass spectrometry (LC-MS) technology, rapidly generating large amounts of data. Lipid extracts derived from biological samples are complex, and most spectral features in LC-MS lipidomics data sets remain unidentified. In-depth analyses of commercial triacylglycerol, diacylglycerol, and cholesterol ester standards revealed the expected ammoniated and sodiated ions as well as five additional unidentified higher mass peaks with relatively high intensities. The identities and origin of these unknown peaks were investigated by modifying the chromatographic mobile-phase components and LC-MS source parameters. Tandem MS (MS/MS) of each unknown adduct peak yielded no lipid structural information, producing only an intense ion of the adducted species. The unknown adducts were identified as low-mass contaminants originating from methanol and isopropanol in the mobile phase. Each contaminant was determined to be an alkylated amine species using their monoisotopic masses to calculate molecular formulas. Analysis of bovine liver extract identified 33 neutral lipids with an additional 73 alkyl amine adducts. Analysis of LC-MS-grade methanol and isopropanol from different vendors revealed substantial alkylated amine contamination in one out of three different brands that were tested. Substituting solvents for ones with lower levels of alkyl amine contamination increased lipid annotations by 36.5% or 27.4%, depending on the vendor, and resulted in >2.5-fold increases in peak area for neutral lipid species without affecting polar lipid analysis. These findings demonstrate the importance of solvent selection and disclosure for lipidomics protocols and highlight some of the major challenges when comparing data between experiments.
脂质组学是一个成熟的领域，借助现代液相色谱质谱联用（LC-MS）技术，能快速生成大量数据。生物样品衍生的脂质提取物很复杂，LC-MS脂质组学数据集中的大多数光谱特征仍未得到识别。对商业三酰甘油、二酰甘油和胆固醇酯标准品的深入分析揭示了预期的铵化和钠化离子，以及另外五个强度相对较高的未识别的更高质量峰。通过改变色谱流动相成分和LC-MS源参数来研究这些未知峰的身份和来源。每个未知加合物峰的串联质谱（MS/MS）未产生脂质结构信息，仅产生加合物物种的强离子。未知加合物被鉴定为源自流动相中甲醇和异丙醇的低质量污染物。利用它们的单同位素质量计算分子式，确定每种污染物为烷基化胺类物质。对牛肝提取物的分析鉴定出33种中性脂质以及另外73种烷基胺加合物。对来自不同供应商的LC-MS级甲醇和异丙醇的分析表明，在测试的三个不同品牌中，有一个品牌存在大量烷基化胺污染。根据供应商的不同，用烷基胺污染水平较低的溶剂替代溶剂可使脂质注释增加36.5%或27.4%，并使中性脂质种类的峰面积增加2.5倍以上，同时不影响极性脂质分析。这些发现证明了溶剂选择和披露对脂质组学方案的重要性，并突出了实验间数据比较时的一些主要挑战。
