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An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics
Wang, Yang1; Feng, Ruibing1; He, Chengwei1; Su, Huanxing1; Ma, Huan2; Wan, Jian-Bo1
2018-08-05
Source PublicationJOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
ISSN0731-7085
Volume157Pages:171-179
Abstract

The narrow linear range and the limited scan time of the given ion make the quantification of the features challenging in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics with the full-scan mode. And metabolite identification is another bottleneck of untargeted analysis owing to the difficulty of acquiring MS/MS information of most metabolites detected. In this study, an integrated workflow was proposed using the newly established multiple ion monitoring mode with time-staggered ion lists (tsMIM) and target-directed data-dependent acquisition with time-staggered ion lists (tsDDA) to improve data acquisition and metabolite identification in UHPLC/Q-TOF MS-based untargeted metabolomics. Compared to the conventional untargeted metabolomics, the proprosed workflow exhibited the better repeatability before and after data normalization. After selecting features with the significant change by statistical analysis, MS/MS information of all these features can be obtained by tsDDA analysis to facilitate metabolite identification. Using time-staggered ion lists, the workflow is more sensitive in data acquisition, especially for the low-abundant features. Moreover, the metabolites with low abundance tend to be wrongly integrated and triggered by full scan-based untargeted analysis with MSE acquisition mode, which can be greatly improved by the proposed workflow. The integrated workflow was also successfully applied to discover serum biosignatures for the genetic modification of fat-1 in mice, which indicated its practicability and great potential in future metabolomics studies. (C) 2018 Elsevier B.V. All rights reserved.

KeywordTime-staggered Ion List Tsmim Tsdda Metabolomics
DOI10.1016/j.jpba.2018.05.020
URLView the original
Indexed BySCI
Language英语
WOS Research AreaChemistry ; Pharmacology & Pharmacy
WOS SubjectChemistry, Analytical ; Pharmacology & Pharmacy
WOS IDWOS:000438169400019
PublisherELSEVIER SCIENCE BV
The Source to ArticleWOS
Fulltext Access
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Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionInstitute of Chinese Medical Sciences
Affiliation1.State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, 999078, China
2.Cardiac Rehabilitation Department, Guangdong Cardiovascular Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
First Author AffilicationInstitute of Chinese Medical Sciences
Recommended Citation
GB/T 7714
Wang, Yang,Feng, Ruibing,He, Chengwei,et al. An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics[J]. JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS,2018,157:171-179.
APA Wang, Yang,Feng, Ruibing,He, Chengwei,Su, Huanxing,Ma, Huan,&Wan, Jian-Bo.(2018).An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics.JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS,157,171-179.
MLA Wang, Yang,et al."An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics".JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS 157(2018):171-179.
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