J Proteome Res. 2020 Apr 3;19(4):1674-1683. doi: 10.1021/acs.jproteome.9b00845. Epub 2020 Mar 4.
Accurate identification of lipids in biological samples is a key step in lipidomics studies. Multidimensional nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical tool for this purpose as it provides comprehensive structural information on lipid composition at atomic resolution. However, the interpretation of NMR spectra of complex lipid mixtures is currently hampered by limited spectral resolution and the absence of a customized lipid NMR database along with user-friendly spectral analysis tools. We introduce a new two-dimensional (2D) NMR metabolite database "COLMAR Lipids" that was specifically curated for hydrophobic metabolites presently containing 501 compounds with accurate experimental 2D C-H heteronuclear single quantum coherence (HSQC) chemical shift data measured in CDCl. A new module in the public COLMAR suite of NMR web servers was developed for the (semi)automated analysis of complex lipidomics mixtures (http://spin.ccic.osu.edu/index.php/colmarm/index2). To obtain 2D HSQC spectra with the necessary high spectral resolution along both C and H dimensions, nonuniform sampling in combination with pure shift spectroscopy was applied allowing the extraction of an abundance of unique cross-peaks belonging to hydrophobic compounds in complex lipidomics mixtures. As shown here, this information is critical for the unambiguous identification of underlying lipid molecules by means of the new COLMAR Lipids web server, also in combination with mass spectrometry, as is demonstrated for Caco-2 cell and lung tissue cell extracts.
准确识别生物样本中的脂质是脂质组学研究的关键步骤。多维核磁共振(NMR)光谱是一种强大的分析工具,可提供有关脂质组成的原子分辨率的综合结构信息。然而,由于光谱分辨率有限,并且缺乏定制的脂质 NMR 数据库以及用户友好的光谱分析工具,目前复杂脂质混合物的 NMR 光谱的解释受到阻碍。我们引入了一个新的二维(2D)NMR 代谢物数据库“COLMAR Lipids”,该数据库是专门为疏水性代谢物设计的,目前包含 501 种化合物,这些化合物在 CDCl 中具有准确的实验 2D C-H 异核单量子相干(HSQC)化学位移数据。在公共的 COLMAR NMR 网络服务器套件中开发了一个新模块,用于(半)自动分析复杂的脂质组学混合物(http://spin.ccic.osu.edu/index.php/colmarm/index2)。为了在 C 和 H 两个维度上获得具有必要高光谱分辨率的 2D HSQC 光谱,应用了非均匀采样与纯位移光谱学相结合的方法,允许提取复杂脂质组学混合物中属于疏水性化合物的大量独特的交叉峰。如这里所示,这些信息对于通过新的 COLMAR Lipids 网络服务器,也与质谱结合,对潜在的脂质分子进行明确识别是至关重要的,如 Caco-2 细胞和肺组织细胞提取物所示。