Dataset Information

Chemical Fingerprint Analysis for Discovering Markers and Identifying Saussurea involucrata by HPLC Coupled with OPLS-DA.

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.

SUBMITTER: Ma Q

PROVIDER: S-EPMC7520670 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Chemical Fingerprint Analysis for Discovering Markers and Identifying <i>Saussurea involucrata</i> by HPLC Coupled with OPLS-DA.

Ma Qingdong Q Chen Xiaoxiang X Zhang Ke K Yao Dahong D Yang Lu L Wang Hangyu H Bulemasi Santai S Huang Jian J Wang Jinhui J

Journal of analytical methods in chemistry 20200919

The quality control of <i>Saussurea involucrata</i> 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 ...[more]

PMID: 33014510

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Project description:(1)Objective: In this study, a quantitative analysis of chemical groups (the triterpenoids, water-soluble polysaccharides, and acidic polysaccharides) and quantitative high liquid performance chromatography (HPLC) fingerprint of Poria cocos (Schw.) Wolf (PC) for quality control was developed. (2)&nbsp;Methodology: First, three main chemical groups, including triterpenoids, water-soluble polysaccharides, and acidic polysaccharides, in 16 batches of PC were evaluated by ultraviolet spectrophotometry. Afterward, the quantitative fingerprint of PC was established, and the alcohol extract of PC was further evaluated. The method involves establishing 16 batches of PC fingerprints by HPLC, evaluating the similarity of different batches of PC, and identifying eight bioactive components, including poricoic acid B (PAB), dehydrotumulosic acid (DTA), poricoic acid A (PAA), polyporenic acid C (PAC), 3-epidehydrotumulosic acid (EA), dehydropachymic acid (DPA), dehydrotrametenolic acid (DTA-1), and dehydroeburicoic acid (DEA), in PC by comparison with the reference substance. Combined with the quantitative analysis of multi-components by a single marker (QAMS), six bioactive ingredients, including PAB, DTA, PAC, EA, DPA, and DEA, in PC from different places were established. In addition, the multivariate statistical analyses, such as principal component analysis and heatmap hierarchical clustering analysis are more intuitive, and the visual analysis strategy was used to evaluate the content of bioactive components in 16 batches of PC. Finally, the analysis strategy of three main chemical groups in PC was combined with the quantitative fingerprint strategy, which reduced the error caused by the single method. (3)&nbsp;Results: The establishment of a method for the quantification of chemical groups and quantitative HPLC fingerprint of PC was achieved as demonstrated through the quantification of six triterpenes in PC by a single marker. (4)&nbsp;Conclusions: Through qualitative and quantitative chemical characterization, a multi-directional, simple and efficient routine evaluation method of PC quality was established. The results reveal that this strategy can provide an analytical method for the quality evaluation of PC and other Chinese medicinal materials.

Dataset Information

Chemical Fingerprint Analysis for Discovering Markers and Identifying Saussurea involucrata by HPLC Coupled with OPLS-DA.

Publications

Chemical Fingerprint Analysis for Discovering Markers and Identifying <i>Saussurea involucrata</i> by HPLC Coupled with OPLS-DA.

Similar Datasets

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