TY - JOUR
T1 - Correlation between Quality and Geographical Origins of Poria cocos Revealed by Qualitative Fingerprint Profiling and Quantitative Determination of Triterpenoid Acids
AU - Zhu, Li-Xia
AU - Xu, Jun
AU - Wang, Ru-Jing
AU - Li, Hong-Xiang
AU - Tan, Yu-Zhu
AU - Chen, Hu-Biao
AU - Dong, Xiao-Ping
AU - Zhao, Zhong-Zhen
N1 - Publisher copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2018/9
Y1 - 2018/9
N2 - 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.
AB - 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.
KW - Fingerprint
KW - Multivariate statistical analysis
KW - Poria cocos
KW - Quantification
KW - UHPLC-QqQ-MS/MS
KW - UHPLC-QTOF-MS/MS
UR - http://www.scopus.com/inward/record.url?scp=85052663695&partnerID=8YFLogxK
U2 - 10.3390/molecules23092200
DO - 10.3390/molecules23092200
M3 - Journal article
C2 - 30200284
AN - SCOPUS:85052663695
SN - 1420-3049
VL - 23
JO - Molecules
JF - Molecules
IS - 9
M1 - 2200
ER -