|
1
|
Ma Q, Chen X, Zhang K, Yao D, Yang L, Wang H, Bulemasi S, Huang J, Wang J. Chemical Fingerprint Analysis for Discovering Markers and Identifying Saussurea involucrata by HPLC Coupled with OPLS-DA. JOURNAL OF ANALYTICAL METHODS IN CHEMISTRY 2020; 2020:7560710. [PMID: 33014510 PMCID: PMC7520670 DOI: 10.1155/2020/7560710] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 05/27/2020] [Indexed: 06/11/2023]
Abstract
The quality control of Saussurea involucrata has been greatly improved by macroscopic and microscopic identification and chemical profiling described in Chinese Pharmacopoeia since 2005. However, these methods have their own limitations, e.g., their dependence on personal experience and expertise, and it is a huge challenge to identify closely related species that share similar or identical morphological characteristics and chemical profiles. A novel and generally accepted identification strategy is urgently needed as a complement to regulations for protecting the public health interests. In this work, a comprehensive chromatographic fingerprint method was developed and tested on 43 samples from four haplotypes of S. involucrata according to DNA barcoding. Three common patterns consisting of 20, 14, and 7 common peaks were generated by frequency filters of median, upper quartile, and 100%, respectively. Based on two formerly screened patterns, S. involucrata can be effectively identified from its five easily confused snow lotus species, including the most closely related plant (S. orgaadayi) in the orthogonal partial least-squares discriminant analysis (OPLS-DA) models. The model is supported by good R and Q coefficients. In addition, different haplotypes of S. involucrata can be discriminated in the OPLS-DA model using the 20 common peaks. Among them, peaks 9, 11, 16 (zaluzanin C), and 18 (dehydrocostus lactone) have been identified as fingerprint markers of S. involucrata via S-plots and VIP values (>1). Additionally, peaks 19 and 20 were identified as linolenic acid and linoleic acid with anti-inflammatory activity, and they were isolated from the herb for the first time. Collectively, the chromatographic fingerprint of S. involucrata can be an effective and integrated method for the identification of authentic herbs from adulterant species or related plants, and discrimination of its different haplotypes provides an objective and reliable tool for quality control.
Collapse
Affiliation(s)
- Qingdong Ma
- School of Pharmacy, Xinjiang Medical University, Urumqi 830054, China
| | - Xiaoxiang Chen
- College of Pharmacy, Key Laboratory of Xinjiang Phytomedicine Resource and Utilization, Ministry of Education, Shihezi University, Shihezi 832002, China
| | - Ke Zhang
- College of Pharmacy, Key Laboratory of Xinjiang Phytomedicine Resource and Utilization, Ministry of Education, Shihezi University, Shihezi 832002, China
| | - Dahong Yao
- School of Pharmacy, Harbin Medical University, Harbin 150081, China
| | - Lu Yang
- Economic Forest Product Quality Inspection and Testing Center of State Forestry Administration, Xinjiang Academy of Forestry, Urumqi 830052, China
| | - Hangyu Wang
- College of Pharmacy, Key Laboratory of Xinjiang Phytomedicine Resource and Utilization, Ministry of Education, Shihezi University, Shihezi 832002, China
| | - Santai Bulemasi
- State Forestry Administration of Xinjiang Altai Mountain, Altai 836505, China
| | - Jian Huang
- School of Pharmacy, Harbin Medical University, Harbin 150081, China
| | - Jinhui Wang
- School of Pharmacy, Xinjiang Medical University, Urumqi 830054, China
- College of Pharmacy, Key Laboratory of Xinjiang Phytomedicine Resource and Utilization, Ministry of Education, Shihezi University, Shihezi 832002, China
- School of Pharmacy, Harbin Medical University, Harbin 150081, China
| |
Collapse
|