Dataset Information

Correlation between Quality and Geographical Origins of Cortex Periplocae, Based on the Qualitative and Quantitative Determination of Chemical Markers Combined with Chemical Pattern Recognition.

ABSTRACT: Quality assessment of Cortex Periplocae remains a challenge, due to its complex chemical profile. This study aims to investigate the chemical components of Cortex Periplocae, including its non-volatile and volatile constituents, via liquid chromatograph-mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS) assays. The established strategy manifested that Cortex Periplocae from different producing areas was determined by identifying 27 chemical markers with ultra-high-performance liquid chromatography, coupled with quadrupole tandem time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS), including four main groups of cardiac glycosides, organic acids, aldehydes, and oligosaccharides. These groups' variable importance in the projection (VIP) were greater than 1. Simultaneously, the samples were divided into four categories, combined with multivariate statistical analysis. In addition, in order to further understand the difference in the content of samples from different producing areas, nine chemical markers of Cortex Periplocae from 14 different producing areas were determined by high performance liquid chromatography coupled with mass spectrometry (HPLC-MS/MS), and results indicated that the main effective constituents of Cortex Periplocae varied with places of origin. Furthermore, in GC-MS analysis, samples were divided into three groups with multivariate statistical analysis; in addition, 22 differential components whose VIP were greater than 1 were identified, which were principally volatile oils and fatty acids. Finally, the relative contents of seven main volatile constituents were obtained, which varied extremely with the producing areas. The results showed that the LC-MS/MS and GC-MS assays, combined with multivariate statistical analysis for Cortex Periplocae, provided a comprehensive and effective means for its quality evaluation.

SUBMITTER: Gao M

PROVIDER: S-EPMC6804018 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Correlation between Quality and Geographical Origins of Cortex Periplocae, Based on the Qualitative and Quantitative Determination of Chemical Markers Combined with Chemical Pattern Recognition.

Gao Mengyuan M Jia Xiaohua X Huang Xuhua X Wang Wei W Yao Guangzhe G Chang Yanxu Y Ouyang Huizi H Li Tianxiang T He Jun J

Molecules (Basel, Switzerland) 20191008 19

Quality assessment of Cortex Periplocae remains a challenge, due to its complex chemical profile. This study aims to investigate the chemical components of Cortex Periplocae, including its non-volatile and volatile constituents, via liquid chromatograph-mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS) assays. The established strategy manifested that Cortex Periplocae from different producing areas was determined by identifying 27 chemical markers ...[more]

PMID: 31597295

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Project description:Poria cocos (Schw.) Wolf (PC) is a well-known saprophytic fungus, and its sclerotium without the epidermis (PCS) is widely used in traditional Chinese medicine and as a functional food in many countries. PCS is normally collected from multiple geographical regions, but whether and how the quality of PCS correlates with where it grows have not been determined. This correlation could be significant both for quality control and optimum utilization of PCS as a natural resource. In this study, a qualitative fingerprint profiling method performed by ultra-performance liquid chromatography (UHPLC) with diode array detection (DAD) combining quadrupole time-of-flight-mass spectrometry (QTOF-MS/MS) and a quantitative UHPLC coupled with triple quadrupole mass spectrometry (QqQ-MS/MS) approach were established to investigate whether and how the quality of PCS correlates with its collection location. A standard fingerprint of PCS was generated by median simulation of 25 tested samples collected from four main producing areas of China, and similarity analysis was applied to evaluate the similarities between the fingerprints of samples and the standard fingerprint. Twenty three common peaks occurring in the fingerprint were unequivocally or tentatively identified by UHPLC-QTOF-MS/MS. Meanwhile, principal component analysis (PCA), supervised orthogonal partial least squares-discriminate analysis (OPLS-DA) and hierarchical cluster analysis (HCA) were employed to classify 25 batches of PCS samples into four groups, which were highly consistent with the four geographical regions. Ten compounds were screened out as potential markers to distinguish the quality of PCS. Nine triterpene acids, including five compounds that played important roles in the clusters between different samples collected from the four collection locations, were simultaneously quantified by using the multiple reaction monitoring (MRM) mode of UHPLC-QqQ-MS/MS. The current strategy not only clearly expounded the correlation between quality and geographical origins of PCS, but also provided a fast, accurate and comprehensive qualitative and quantitative method for assessing the quality of PCS.

Dataset Information

Correlation between Quality and Geographical Origins of Cortex Periplocae, Based on the Qualitative and Quantitative Determination of Chemical Markers Combined with Chemical Pattern Recognition.

Publications

Correlation between Quality and Geographical Origins of <i>Cortex</i> <i>Periplocae</i>, Based on the Qualitative and Quantitative Determination of Chemical Markers Combined with Chemical Pattern Recognition.

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