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MobiLipid:一种通过内标法增强离子淌度-质谱脂质组学 CCS 质量控制的工具。

MobiLipid: A Tool for Enhancing CCS Quality Control of Ion Mobility-Mass Spectrometry Lipidomics by Internal Standardization.

机构信息

Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Str. 38, 1090 Vienna, Austria.

Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Waehringer Str. 42, 1090 Vienna, Austria.

出版信息

Anal Chem. 2024 May 14;96(19):7380-7385. doi: 10.1021/acs.analchem.4c01253. Epub 2024 May 1.

Abstract

Ion mobility-mass spectrometry (IM-MS) offers benefits for lipidomics by obtaining IM-derived collision cross sections (CCS), a conditional property of an ion that can enhance lipid identification. While drift tube (DT) IM-MS retains a direct link to the primary experimental method to derive CCS values, other IM technologies rely solely on external CCS calibration, posing challenges due to dissimilar chemical properties between lipids and calibrants. To address this, we introduce MobiLipid, a novel tool facilitating the CCS quality control of IM-MS lipidomics workflows by internal standardization. MobiLipid utilizes a newly established CCS library for uniformly (U)C-labeled lipids, derived from a UC-labeled yeast extract, containing 377 CCS values. This automated open-source R Markdown tool enables internal monitoring and straightforward compensation for CCS biases. It supports lipid class- and adduct-specific CCS corrections, requiring only three UC-labeled lipids per lipid class-adduct combination across 10 lipid classes without requiring additional external measurements. The applicability of MobiLipid is demonstrated for trapped IM (TIM)-MS measurements of an unlabeled yeast extract spiked with UC-labeled lipids. Monitoring the CCS biases of CCS values compared to CCS library entries utilizing MobiLipid resulted in mean absolute biases of 0.78% and 0.33% in positive and negative ionization mode, respectively. By applying the CCS correction integrated into the tool for the exemplary data set, the mean absolute CCS biases of 10 lipid classes could be reduced to approximately 0%.

摘要

离子淌度-质谱(IM-MS)通过获得离子淌度衍生的碰撞截面(CCS),为脂质组学提供了益处,CCS 是离子的条件特性,可以增强脂质的鉴定。虽然漂移管(DT)IM-MS 保留了与衍生 CCS 值的主要实验方法的直接联系,但其他 IM 技术仅依赖于外部 CCS 校准,由于脂质和校准剂之间的化学性质不同,这带来了挑战。为了解决这个问题,我们引入了 MobiLipid,这是一种新的工具,通过内部标准化促进 IM-MS 脂质组学工作流程的 CCS 质量控制。MobiLipid 利用一个新建立的 UC 标记酵母提取物衍生的(U)C 标记脂质 CCS 库,包含 377 个 CCS 值。这个自动化的开源 R Markdown 工具可以实现内部监测和 CCS 偏差的直接补偿。它支持脂质类别和加合物特异性 CCS 校正,仅需在 10 个脂质类别中对每个脂质类别-加合物组合使用三种 UC 标记的脂质,而无需进行额外的外部测量。MobiLipid 的适用性通过对未标记酵母提取物中 UC 标记脂质进行捕获 IM(TIM)-MS 测量得到了证明。利用 MobiLipid 监测 CCS 值与 CCS 库条目相比的 CCS 偏差,在正离子和负离子模式下分别导致平均绝对偏差为 0.78%和 0.33%。通过应用集成到工具中的 CCS 校正对示例数据集进行校正,可以将 10 个脂质类别的平均绝对 CCS 偏差降低到约 0%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1990/11099887/f9145b7e31dd/ac4c01253_0001.jpg

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