LipidMiner: a software for automated identification and quantification of lipids from multiple liquid chromatography/mass spectrometry data files.
LipidMiner: a software for automated identification and quantification of lipids from multiple liquid chromatography/mass spectrometry data files.
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LipidMiner：一种用于从多个液相色谱/质谱数据文件中自动识别和定量脂质的软件。
DOI：
10.1002/rcm.6865
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Lin,Guang
中科院分区：
文献类型：
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作者：
Meng,Da;Zhang,Qibin;Gao,Xiaoli;Wu,Si;Lin,Guang
要全面了解脂质在细胞生理学和病理学中的作用和功能，需要明确地识别和准确地量化各个脂质分子种类。然而，脂类的巨大结构多样性(>；37,000个脂类分子被编目在脂类地图数据库中)。脂图。[1，2]传统上，三重四极杆或四极杆飞行时间(QTOF)质谱仪被用于使用前体离子扫描(PIS)或中性损失扫描(NLS)方法进行脂质分析，这些方法利用脂类特征离子或气相脂质分子离子碰撞诱导解离产生的中性损失碎片。这些方法很容易在直接输液模式(也称为鸟枪式脂质组学[3])下进行，而不需要在线分离脂类，并编写了诸如LIMSA、[4]Lipid Profiler、[5]AMDMS-SL[6]和MS-LAMP[7]等软件工具来专门分析这些类型的数据。最近，从所有可检测到的前体离子中获取全扫描MS/MS光谱的数据相关技术已越来越多地用于脂类分析研究。这种方法主要在离子陷阱、高分辨率QTOF或混合Orbitrap仪器上实现。所获得的光谱可以被认为是在单个分析中同时采集无限数量的产品和中性损失扫描的仿真。因此，用于分析这类数据的工具也在开发中，例如LipidQA，[8]LipidInspector，[9]和LipidXplorer，[10]，主要用于基于直接输液的鸟枪式脂肪组学工作流程(参考文献10中总结了以前的脂肪组学软件工具的共同特征)。最近，开发了一个电子串联质谱库LipidBlast，与实验获得的MS/MS谱图相匹配，[11]这为脂类鉴定提供了一条新的途径。我们和其他人发现，将液相色谱(LC)分离与依赖数据的MS/MS结合起来，可以增加对
Comprehensive understanding of the roles and functions of lipids in cellular physiology and pathology requires unambiguous identification and accurate quantification of individual lipid molecular species. However, the enormous structural diversity of lipids (> 37,000 lipid molecules cataloged in the LIPID MAPS database at www. lipidmaps. org) presents significant challenge in high throughput analysis of lipidomics data.[1, 2] Traditionally, triple quadrupole or quadrupole time of flight (QTOF) mass spectrometers are utilized for lipids analysis using either precursor ion scanning (PIS) or neutral loss scanning (NLS) methods, which exploit lipid class-characteristic ions or neutral loss fragments generated in collisional induced dissociation of gas phase lipid molecular ions. These methods are readily carried out in direct infusion mode (also known as shotgun lipidomics [3]) without on-line chromatographic separation of lipids, and software tools such as LIMSA,[4] Lipid Profiler,[5] AMDMS-SL [6] and MS-LAMP [7] were written to specifically analyze these types of data. Recently, data-dependent acquisition of full scan MS/MS spectra from all detectable precursor ions has gained increasing use in lipid profiling studies. This method is mainly implemented on ion trap, high resolution QTOF or hybrid Orbitrap instruments. The spectra obtained can be considered as the emulation of simultaneous acquisition of an unlimited number of product and neutral loss scans in a single analysis. Accordingly, tools for analyzing this type of data were also being developed, such as LipidQA,[8] LipidInspector,[9] and LipidXplorer,[10] mainly for direct infusion based shotgun lipidomics workflow (Common features of previous lipidomics software tools were summarized in Reference 10). More recently, an in-silico tandem mass spectral database, LipidBlast was developed to match with the experimentally acquired MS/MS spectrum,[11] which provided a new avenue for lipids identification. We and others have found that coupling liquid chromatographic (LC) separation with data-dependent MS/MS adds additional confidence in