Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data

被引:4
|
作者
Ross, Dylan H. [1 ]
Guo, Jian [1 ,2 ]
Bilbao, Aivett [1 ]
Huan, Tao [2 ]
Smith, Richard D. [1 ]
Zheng, Xueyun [1 ]
机构
[1] Pacific Northwest Natl Lab, Earth & Biol Sci Directorate, Richland, WA 99354 USA
[2] Univ British Columbia, Fac Sci, Dept Chem, Vancouver Campus,2036 Main Mall, Vancouver, BC V6T 1Z1, Canada
来源
MOLECULES | 2023年 / 28卷 / 08期
基金
加拿大自然科学与工程研究理事会;
关键词
software; ion mobility spectrometry; mass spectrometry; lipidomics; lipid identification; SEPARATIONS; CHROMATOGRAPHY; DIVERSITY; ISOMERS; PEPTIDE;
D O I
10.3390/molecules28083483
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.
引用
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页数:13
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