Metabolomics approach reveals annual metabolic variation in roots of Cyathula officinalis Kuan based on gas chromatography-mass spectrum

• Published in: Chinese medicine 2017-05, Vol.12 (1), p.12-12, Article 12
• Main Authors: Tong, Kai, Li, Zhao-Ling, Sun, Xu, Yan, Shen, Jiang, Mei-Jie, Deng, Meng-Sheng, Chen, Ji, Li, Jing-Wei, Tian, Meng-Liang
• Format: Article
• Language: English
• Subjects: Arthritis; Cellobiose; Chemical composition; Chinese medicine; Chromatography; Cultivation techniques; Cyathula officinalis; Discriminant analysis; Fatty acids; Gas chromatography; GC–MS; Gluconic acid; Harvest; Harvest time; Herbal medicine; Herbs; Lactic acid; Least squares method; Mannose; Mass spectrometry; Metabolism; Metabolites; Metabolomics; Multivariate analysis; Oxalic acid; PCA; PLS-DA; Principal components analysis; Quality control; Quality standards; Scientific imaging; Variance; Variance analysis; Xylitol
• ISSN: 1749-8546; 1749-8546
• DOI: 10.1186/s13020-017-0133-1

Herbal quality is strongly influenced by harvest time. It is therefore one of crucial factors that should be well respected by herbal producers when optimizing cultivation techniques, so that to obtain herbal products of high quality. In this work, we paid attention on one of common used Chinese herbals, Kuan. According to previous studies, its quality may be related with growth years because of the variation of several main bioactive components in different growth years. However, information about the whole chemical composition is still scarce, which may jointly determine the herbal quality. samples were collected in 1-4 growth years after sowing. To obtain a global insight on chemical profile of herbs, we applied a metabolomics approach based on gas chromatography-mass spectrum. Analysis of variance, principal component analysis, partial least squares discriminant analysis and hierarchical cluster analysis were combined to explore the significant difference in different growth years. 166 metabolites were identified by using gas chromatography-mass spectrum method. 63 metabolites showed significant change in different growth years in terms of analysis of variance. Those metabolites then were grouped into 4 classes by hierarchical cluster analysis, characterizing the samples of different growth ages. Samples harvested in the earliest years (1-2) were obviously differ with the latest years (3-4) as reported by principal component analysis. Further, partial least squares discriminant analysis revealed the detail difference in each growth year. Gluconic acid, xylitol, glutaric acid, pipecolinic acid, ribonic acid, mannose, oxalic acid, digalacturonic acid, lactic acid, 2-deoxyerythritol, acetol, 3-hydroxybutyric acid, citramalic acid, -carbamylglutamate, and cellobiose are the main 15 discrimination metabolites between different growth years. Harvest time should be well considered when producing In order to boost the consistency of herbal quality, is recommended to harvest in 4th growth year. The method of GC-MS combined with multivariate analysis was a powerful tool to evaluate the herbal quality.