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  • Title: A multi-dimensional liquid chromatography/high-resolution mass spectrometry approach combined with computational data processing for the comprehensive characterization of the multicomponents from Cuscuta chinensis.
    Author: Wang M, Xu XY, Wang HD, Wang HM, Liu MY, Hu WD, Chen BX, Jiang MT, Qi J, Li XH, Yang WZ, Gao XM.
    Journal: J Chromatogr A; 2022 Jul 19; 1675():463162. PubMed ID: 35635871.
    Abstract:
    Challenges encountered in plant metabolites characterization by liquid chromatography/mass spectrometry can arise from the insufficient chromatography separation, the lack of specific database, and low reliability of identification because of the ubiquitous isomerism. Herein, we present an integral approach, by combining comprehensive off-line two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), automatic peak annotation, molecular networking, and collision cross section (CCS) prediction, aimed to improve the resolution and reliability in MS-oriented metabolites characterization. Using the seeds of Cuscuta chinensis as a case, the configuration of an XBridge Amide column of hydrophilic interaction chromatography (HILIC) and a Zorbax SB-Aq column of reversed-phase chromatography (RPC), in an off-line mode, showed the orthogonality of 0.73 and effective peak capacity of 4361. Data-independent high-definition MSE (HDMSE) in the negative mode could enable high-coverage MS2 data acquisition and enhance the ions resolution, while computational peak annotation workflows facilitated by UNIFITM and Global Natural Products Social Molecular Network (GNPS) could efficiently characterize the targeted and untargeted compound analogs. A total of 302 compounds were identified or tentatively characterized, and 109 thereof were unreported. Moreover, CCS prediction (www.allccs.zhulab.cn) provided more possibilities to distinguish 12 pairs of isomers in the lack of reference standards. The 2D-LC/IM-QTOF-MS approach enabled the collection of five dimension of data related to each component (tR by HILIC and RPC, CCS, m/z in MS1 and MS2), and the intelligent metabolites characterization with more reliable MS data. Conclusively, the established integral strategy can be utilized in metabolome analysis to support the quality control of herbal medicines.
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