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Molecules 2018, 23(9), 2200; https://doi.org/10.3390/molecules23092200

Correlation between Quality and Geographical Origins of Poria cocos Revealed by Qualitative Fingerprint Profiling and Quantitative Determination of Triterpenoid Acids

1
Pharmacy College, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
2
School of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong, China
*
Authors to whom correspondence should be addressed.
Received: 14 July 2018 / Revised: 22 August 2018 / Accepted: 28 August 2018 / Published: 31 August 2018
(This article belongs to the Collection Herbal Medicine Research)
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Abstract

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. View Full-Text
Keywords: Poria cocos; fingerprint; UHPLC-QTOF-MS/MS; UHPLC-QqQ-MS/MS; quantification; multivariate statistical analysis Poria cocos; fingerprint; UHPLC-QTOF-MS/MS; UHPLC-QqQ-MS/MS; quantification; multivariate statistical analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhu, L.-X.; Xu, J.; Wang, R.-J.; Li, H.-X.; Tan, Y.-Z.; Chen, H.-B.; Dong, X.-P.; Zhao, Z.-Z. Correlation between Quality and Geographical Origins of Poria cocos Revealed by Qualitative Fingerprint Profiling and Quantitative Determination of Triterpenoid Acids. Molecules 2018, 23, 2200.

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