Ion Mobility-Derived Collision Cross Section As an Additional Measure for Lipid Fingerprinting and Identification

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• 作者：Giuseppe Paglia ; Peggi Angel ; Jonathan P. Williams ; Keith Richardson ; Hernando J. Olivos ; J. Will Thompson ; Lochana Menikarachchi ; Steven Lai ; Callee Walsh ; Arthur Moseley ; Robert S. Plumb ; David F. Grant ; Bernhard O. Palsson ; James Langridge ; Scott Geromanos ; Giuseppe Astarita
• 刊名：Analytical Chemistry
• 出版年：2015
• 出版时间：January 20, 2015
• 年：2015
• 卷：87
• 期：2
• 页码：1137-1144
• 全文大小：518K
• ISSN：1520-6882

文摘

Despite recent advances in analytical and computational chemistry, lipid identification remains a significant challenge in lipidomics. Ion-mobility spectrometry provides an accurate measure of the molecules鈥?rotationally averaged collision cross-section (CCS) in the gas phase and is thus related to ionic shape. Here, we investigate the use of CCS as a highly specific molecular descriptor for identifying lipids in biological samples. Using traveling wave ion mobility mass spectrometry (MS), we measured the CCS values of over 200 lipids within multiple chemical classes. CCS values derived from ion mobility were not affected by instrument settings or chromatographic conditions, and they were highly reproducible on instruments located in independent laboratories (interlaboratory RSD < 3% for 98% of molecules). CCS values were used as additional molecular descriptors to identify brain lipids using a variety of traditional lipidomic approaches. The addition of CCS improved the reproducibility of analysis in a liquid chromatography-MS workflow and maximized the separation of isobaric species and the signal-to-noise ratio in direct-MS analyses (e.g., 鈥渟hotgun鈥?lipidomics and MS imaging). These results indicate that adding CCS to databases and lipidomics workflows increases the specificity and selectivity of analysis, thus improving the confidence in lipid identification compared to traditional analytical approaches. The CCS/accurate-mass database described here is made publicly available.