Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee 37235, United States.
J Am Soc Mass Spectrom. 2022 Jul 6;33(7):1229-1237. doi: 10.1021/jasms.2c00067. Epub 2022 Jun 2.
Structures for lossless ion manipulation-based high-resolution ion mobility (HRIM) interfaced with mass spectrometry has emerged as a powerful tool for the separation and analysis of many isomeric systems. IM-derived collision cross section (CCS) is increasingly used as a molecular descriptor for structural analysis and feature annotation, but there are few studies on the calibration of CCS from HRIM measurements. Here, we examine the accuracy, reproducibility, and practical applicability of CCS calibration strategies for a broad range of lipid subclasses and develop a straightforward and generalizable framework for obtaining high-resolution CCS values. We explore the utility of using structurally similar custom calibrant sets as well as lipid subclass-specific empirically derived correction factors. While the lipid calibrant sets lowered overall bias of reference CCS values from ∼2-3% to ∼0.5%, application of the subclass-specific correction to values calibrated with a broadly available general calibrant set resulted in biases <0.4%. Using this method, we generated a high-resolution CCS database containing over 90 lipid values with HRIM. To test the applicability of this method to a broader class range typical of lipidomics experiments, a standard lipid mix was analyzed. The results highlight the importance of both class and arrival time range when correcting or scaling CCS values and provide guidance for implementation of the method for more general applications.
基于无损离子操控的高分辨离子淌度（HRIM）与质谱联用的结构已成为分离和分析许多同分异构体系统的强大工具。IM 衍生的碰撞截面（CCS）越来越多地被用作结构分析和特征注释的分子描述符，但关于 HRIM 测量的 CCS 校准的研究很少。在这里，我们检查了广泛的脂质亚类的 CCS 校准策略的准确性、重现性和实际适用性，并开发了一种简单且可推广的方法来获得高分辨率 CCS 值。我们探索了使用结构相似的定制校准剂集以及脂质亚类特异性经验衍生校正因子的效用。虽然脂质校准剂集将参考 CCS 值的整体偏差从约 2-3%降低到约 0.5%，但将子类特异性校正应用于使用广泛可用的通用校准剂集校准的值会导致偏差 <0.4%。使用这种方法，我们生成了一个包含超过 90 个脂质 HRIM 值的高分辨率 CCS 数据库。为了测试该方法在脂质组学实验中更广泛的典型类范围的适用性，我们分析了一个标准脂质混合物。结果突出了在校正或缩放 CCS 值时类和到达时间范围的重要性，并为更通用的应用实施该方法提供了指导。
