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Enhanced MS/MS coverage for metabolite identification in LC-MS-based untargeted metabolomics by target-directed data dependent acquisition with time-staggered precursor ion list
Wang Y.1; Feng R.1; Wang R.1; Yang F.2; Li P.1; Wan J.-B.1
2017-11-01
Source PublicationAnalytica Chimica Acta
ISSN18734324 00032670
Volume992Pages:67-75
Abstract

Metabolite identification is one of the major bottlenecks in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics owing to the difficulty of acquiring MS/MS information of most metabolites detected. Data dependent acquisition (DDA) has been currently used to acquire MS/MS data in untargeted metabolomics. When dealing with the complex biological samples, top-n-based DDA method selects only a small fraction of the ions for fragmentation, leading to low MS/MS coverage of metabolites in untargeted metabolomics. In this study, we proposed a novel DDA method to improve the performance of MS/MS acquisition in LC-MS-based untargeted metabolomics using target-directed DDA (t-DDA) with time-staggered precursor ion lists (ts-DDA). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment, ion filtration, and ion fusion, the target precursor ion list was generated for subsequent t-DDA and ts-DDA. Compared to the conventional DDA, the ts-DDA exhibits the better MS/MS coverage of metabolomes in a plasma sample, especially for the low abundant metabolites. Even in high co-elution zones, the ts-DDA also showed the superiority in acquiring MS/MS information of co-eluting ions, as evidenced by better MS/MS coverage and MS/MS efficiency, which was mainly attributed to the pre-selection of precursor ion and the reduced number of concurrent ions. The newly developed method might provide more informative MS/MS data of metabolites, which will be helpful to increase the confidence of metabolite identification in untargeted metabolomics.

KeywordData Dependent Acquisition Metabolite Identification Metabolomics Target-directed Dda Time-staggered Precursor Ion List
DOI10.1016/j.aca.2017.08.044
URLView the original
Indexed BySCI
WOS Research AreaChemistry
WOS SubjectChemistry, Analytical
WOS IDWOS:000413241000006
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Cited Times [WOS]:10   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionInstitute of Chinese Medical Sciences
Affiliation1.University of Macau
2.Chongqing University
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Wang Y.,Feng R.,Wang R.,et al. Enhanced MS/MS coverage for metabolite identification in LC-MS-based untargeted metabolomics by target-directed data dependent acquisition with time-staggered precursor ion list[J]. Analytica Chimica Acta,2017,992:67-75.
APA Wang Y.,Feng R.,Wang R.,Yang F.,Li P.,&Wan J.-B..(2017).Enhanced MS/MS coverage for metabolite identification in LC-MS-based untargeted metabolomics by target-directed data dependent acquisition with time-staggered precursor ion list.Analytica Chimica Acta,992,67-75.
MLA Wang Y.,et al."Enhanced MS/MS coverage for metabolite identification in LC-MS-based untargeted metabolomics by target-directed data dependent acquisition with time-staggered precursor ion list".Analytica Chimica Acta 992(2017):67-75.
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