Kang Li-Ping, Huang Yuan-Yuan, Zhan Zhi-Lai, Liu Da-Hui, Peng Hua-Sheng, Nan Tie-Gui, Zhang Yuan, Hao Qing-Xiu, Tang Jin-Fu, Zhu Shou-Dong, Yang Guang, Guo Lan-Ping, Chen Min, Huang Lu-Qi
State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijng, 100700, PR China.
State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijng, 100700, PR China; School of Pharmacy, Anhui University of Chinese Medicine, Hefei, Anhui, 230012, PR China.
J Pharm Biomed Anal. 2017 Aug 5;142:252-261. doi: 10.1016/j.jpba.2017.05.019. Epub 2017 May 11.
This study aimed to distinguish the rhizomes of Paris polyphylla var. yunnanensis (Franch) Hand Mazz (PPY) and Paris veitnamensis (Takht.) H. Li (PV) using metabolomics-based ultra high-performance liquid chromatography coupled with quadrupole time-of-fligh mass spectrometry (UHPLC/Q-TOF MS). First, the UHPLC/Q-TOF MS approach was optimized for metabolite profiling. Then, the MS data were processed using UNIFI™ combined with an in-house library to automatically characterize the metabolites. Based on the exact mass information, the fragmentation characteristics, and the retention time of compounds, and the fragmentation mechanism and retention behavior of steroidal glycosides in the references, the structures identified by UNIFI were further verified. Overall, 146 metabolites, including 42 potential new compounds, were identified or tentatively identified. Pattern recognition analysis of the PPY and PV MS data revealed that they were clearly separated, and 15 potential biomarkers for differentiating between them were selected. These biomarkers were subsequently used to successfully predict the genus of PPY and PV samples. These results indicated that metabolite profiling by UHPLC/Q-TOF MS is an effective, robust approach for determining the characteristic biomarkers that differentiate between TCM species with multiple botanical origins.
本研究旨在利用基于代谢组学的超高效液相色谱-四极杆飞行时间质谱联用技术（UHPLC/Q-TOF MS）区分滇重楼（Paris polyphylla var. yunnanensis (Franch) Hand Mazz, PPY）和越南重楼（Paris veitnamensis (Takht.) H. Li, PV）的根茎。首先，对UHPLC/Q-TOF MS方法进行优化以进行代谢物谱分析。然后，使用UNIFI™结合内部自建库对质谱数据进行处理，以自动鉴定代谢物。基于化合物的精确质量信息、裂解特征、保留时间以及参考文献中甾体苷的裂解机制和保留行为，对UNIFI鉴定出的结构进行进一步验证。总体而言，共鉴定或初步鉴定出146种代谢物，其中包括42种潜在新化合物。对PPY和PV的质谱数据进行模式识别分析，结果显示二者能够明显区分开，并筛选出15种区分二者的潜在生物标志物。这些生物标志物随后被成功用于预测PPY和PV样本的种类。这些结果表明，UHPLC/Q-TOF MS代谢物谱分析是一种有效、可靠的方法，可用于确定区分多种植物来源的中药品种的特征生物标志物。
