Integrating Ultra-High-Performance Liquid Chromatography-Photodiode Array Detector Coupled to Quadrupole
Zhao Jin1, Hao-Qi He1, Li-Ping Zhang1
1State Key Laboratory for Quality Assurance and Sustainable Use of Dao-di Herbs, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Abstract:
Paeoniae Radix Alba (called Baishao in China, BS), the dried root of Paeonia lactiflora Pall., is a key ingredient in classic Chinese medicine formulas used to treat depression. This study aimed to optimize its cultivation period by integrating analysis of chemical constituents and antidepressant effects. Chemical profiling of 5-year-old roots (BS_5Year) using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry led to the identification of 44 major constituents. Network pharmacology analysis predicted that 12 primary constituents, five monoterpenes (oxypaeoniflorin, albiflorin, paeoniflorin, 6'-O-galloylpaeoniflorin, and benzoylpaeoniflorin) and seven polyphenols (gallic acid, methyl gallate, catechin, 1,3,6-trigalloylglucose, 1,2,3,6-tetragalloylglucose, benzoic acid, and 1,2,3,4,6-pentagalloylglucose) were key contributors to the antidepressant effects. Quantitative analysis by ultra-high-performance liquid chromatography-diode array detection showed that the content of these active constituents in BS_5Year was comparable to that in 4-year-old roots (BS_4Year). Behavioral tests (forced swimming and tail suspension) confirmed no significant difference in antidepressant efficacy between the two groups. These findings indicate that a 4-year growth period is sufficient to achieve the desired quality, thus establishing it as the optimal harvest time. Therefore, this study not only guides the cultivation of P. lactiflora but also highlights the importance of integrating chemical and bioactivity data to determine the optimal harvest time for herbal medicines.


