Comparison of Full-Scan, Data-Dependent, and Data-Independent Acquisition Modes in Liquid Chromatography-Mass Spectrometry Based Untargeted Metabolomics

被引:214
作者
Guo, Jian [1 ]
Huan, Tao [1 ]
机构
[1] Univ British Columbia, Dept Chem, Fac Sci, 2036 Main Mall, Vancouver, BC V6T 1Z1, Canada
关键词
METABOLITE IDENTIFICATION; TARGETED ANALYSIS; XCMS; DECONVOLUTION; SPECTRA; COMBINATION; STRATEGIES; PRECISION; DISCOVERY; SWATH;
D O I
10.1021/acs.analchem.9b05135
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Full-scan, data-dependent acquisition (DDA), and data-independent acquisition (DIA) are the three common data acquisition modes in high resolution mass spectrometry-based untargeted metabolomics. It is an important yet underrated research topic on which acquisition mode is more suitable for a given untargeted metabolomics application. In this work, we compared the three data acquisition techniques using a standard mixture of 134 endogenous metabolites and a human urine sample. Both hydrophilic interaction and reversed-phase liquid chromatographic separation along with positive and negative ionization modes were tested. Both the standard mixture and urine sample generated consistent results. Full-scan mode is able to capture the largest number of metabolic features, followed by DIA and DDA (53.7% and 64.8% respective features fewer on average in urine than full-scan). Comparing the MS2 spectra in DIA and DDA, spectra quality is higher in DDA with average dot product score 83.1% higher than DIA in Urine(H), and the number of MS2 spectra (spectra quantity) is larger in DIA (on average 97.8% more than DDA in urine). Moreover, a comparison of relative standard deviation distribution between modes shows consistency in the quantitative precision, with the exception of DDA showing a minor disadvantage (on average 19.8% and 26.8% fewer features in urine with RSD < 5% than full-scan and DIA). In terms of data preprocessing convenience, full-scan and DDA data can be processed by well-established software. In contrast, several bioinformatic issues remain to be addressed in processing DIA data and the development of more effective computational programs is highly demanded.
引用
收藏
页码:8072 / 8080
页数:9
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