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

Challenges encountered in plant metabolites characterization by liquid chromatography/mass spectrom-etry 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 network-ing, 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 col-umn 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 com-pounds were identified or tentatively characterized, and 109 thereof were unreported. Moreover, CCS pre-diction ( 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. (c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This study presents an integral approach combining 2D-LC/IM-QTOF-MS, automatic peak annotation, molecular networking, and CCS prediction to improve the resolution and reliability in the characterization of plant metabolites. Using Cuscuta chinensis seeds as a case, a total of 302 compounds were identified or tentatively characterized, including 109 that were previously unreported.