Enhanced pseudotargeted analysis using a segment data dependent acquisition strategy by liquid chromatography–tandem mass spectrometry for a metabolomics study of liquiritin in the treatment of depression. Issue 11 (7th April 2020)

• Record Type: Journal Article
• Authors: Yang, Jina; Jin, Wenbin; Liu, Danyang; Zhong, Qisheng; Zhou, Ting
• Is Part Of: Journal of separation science. Volume 43:Issue 11(2020)
• Page Start: 2088
• Page End: 2096
• Publication Date: 2020-04-07
• Subjects: depression -- liquiritin -- pseudotargeted method -- segment data dependent acquisition; Separation (Technology) -- Periodicals; Chromatographic analysis -- Periodicals; 543.089
• DOI: 10.1002/jssc.202000107
• Languages: English
• ISSNs: 1615-9306

Abstract

Abstract: An enhanced pseudotargeted method using a segment data‐dependent acquisition mode based on ultra‐high performance liquid chromatography–tandem mass spectrometry was developed. This segment data dependent acquisition‐based pseudotargeted method could improve the detection of co‐eluted ions and extend the coverage of analytes. A set of 502 multiple reaction monitoring channels were obtained by this segment strategy, which was twice the number created by the traditional data‐dependent acquisition mode. Compared with the untargeted method, the pseudotargeted profiling demonstrated higher sensitivity and higher precision. More than 90% of the metabolites detected by the enhanced pseudotargeted method had relative standard deviations less than 15%. The segment data dependent acquisition‐based pseudotargeted method was successfully applied to the metabolomics study of the depressed rats with the treatment of liquiritin. Forty‐seven differential metabolites were screened and five metabolic pathways were found to be related to depression including retinol metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, terpenoid backbone biosynthesis, and lysine degradation. The segment data dependent acquisition‐based pseudotargeted method widened the coverage of metabolites with good sensitivity and precision, which exhibited great potential in the discovery of differential metabolites in metabolomics studies.