Integrated strategy for widely targeted metabolome characterization of Peucedani Radix

化学 代谢组 色谱法 分析物 亲水作用色谱法 代谢组学 对映体 质谱法 高效液相色谱法 立体化学
作者
Xingcheng Gong,Wenjing Liu,Yan Cao,Rong-Ye Wang,Nai-Yun Liang,Libo Cao,Jun Li,Pengfei Tu,Yuelin Song
出处
期刊:Journal of Chromatography A [Elsevier BV]
卷期号:1678: 463360-463360 被引量:6
标识
DOI:10.1016/j.chroma.2022.463360
摘要

Herbal medicines (HMs) are widely recognized as extremely complicated matrices, resulting in a great challenge for the existing analytical approaches to characterize the widely targeted metabolome. The primary obstacles include high-level structural diversity, broad concentration range, large polarity span, insufficient authentic compounds and frequent occurrences of isomers, even enantiomers. Here, we aimed to propose an integrated strategy being able to circumvent the technical barriers, and a well-known HM namely Peucedani Radix was employed to illustrate and justify the applicability. Regarding qualitative analysis, the hydrophilic metabolites were detected with HILIC-predictive multiple-reaction monitoring mode, and structurally identified by matching predefined identities with authentic compounds or information archived in relevant databases. After RPLC-MS/MS measurement, full collision energy ramp-MS2 spectrum in combination with quantum structural calculation was applied to confirmatively identify those less polar components, mainly angular-type pyranocoumarins (APs). For quantitative analysis, achiral-chiral RPLC/HILIC was configured for chromatographic separations because the analytes spanned a large polarity range and involved many enantiomers. A quasi-content concept was employed for comprehensively relative quantitation through constructing a so-called universal metabolome standard (UMS) sample and building calibration curves by assaying serial diluted UMS solutions. Consequently, high-confidence structural annotation and relatively quantitative analysis were achieved for 103 compounds, in total. After multivariate statistical analysis, some APs, e.g., (3'S)-praeruptorin A, (3'S)-praeruptorin B, (3'S)-praeruptorin E, as well as several primary metabolites were screened out as the prominent contributors for inter-batch variations. Together, current study shows a promising strategy enabling widely targeted metabolomics of, but not limited to, HMs.
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