Metabolomics of Medicinal Plants: The Importance of Multivariate Analysis of Analytical Chemistry Data
Metabolomics of Medicinal Plants: The Importance of Multivariate Analysis of Analytical Chemistry Data
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DOI：
10.2174/157340910791760055
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发表时间：
2010-09-01
影响因子：
1.7
通讯作者：
Kanaya, Shigehiko
中科院分区：
文献类型：
--
作者：
Okada, Taketo;Afendi, Farit Mochamad;Kanaya, Shigehiko
代谢组学是对细胞和生物体中产生的各种代谢物进行全面和全面的分析，极大地扩展了代谢物指纹图谱和图谱以及标记代谢物的选择和鉴定。该方法通常使用多变量分析来统计处理由高通量和同时代谢物分析产生的大量分析化学数据。虽然植物代谢组学技术主要是与系统生物学和功能基因组学中的其他后基因组学一起发展起来的，但它独立地应用于药用植物的质量评价，基于非靶标或广泛靶标的代谢物分析的多变量分析所产生的代谢物指纹图谱的多样性。应用代谢组学的一个优点是，对药用植物的评估不仅基于作为药用重要化学物质的有限数量的代谢物，而且还基于次要代谢物和生物活性化学物质的指纹图谱。特别是，分数图和加载图分析，例如主成分分析(PCA)、偏最小二乘判别分析(PLS-DA)和判别图分析，例如批学习自组织映射(BL-SOM)分析，经常被用于减少代谢物指纹和分析样本的分类。根据最近的研究，我们现在认识到代谢组学可以成为综合评价药用植物质量的有效方法。在这篇综述中，我们描述了在药用植物上进行代谢组学研究的实际案例，并讨论了代谢组学在这一研究领域的应用，重点是多变量分析。
Metabolomics, the comprehensive and global analysis of diverse metabolites produced in cells and organisms, has greatly expanded metabolite fingerprinting and profiling as well as the selection and identification of marker metabolites. The methodology typically employs multivariate analysis to statistically process the massive amount of analytical chemistry data resulting from high-throughput and simultaneous metabolite analysis. Although the technology of plant metabolomics has mainly developed with other post-genomics in systems biology and functional genomics, it is independently applied to the evaluation of the qualities of medicinal plants, based on the diversity of metabolite fingerprints resulting from multivariate analysis of non-targeted or widely targeted metabolite analysis. One advantage of applying metabolomics is that medicinal plants are evaluated based not only on the limited number of metabolites that are pharmacologically important chemicals, but also on the fingerprints of minor metabolites and bioactive chemicals. In particular, score plot and loading plot analyses e. g. principal component analysis (PCA), partial-least-squares discriminant analysis (PLS-DA), and discrimination map analysis such as batch-learning self-organizing map (BL-SOM) analysis, are often employed for the reduction of a metabolite fingerprint and the classification of analyzed samples. Based on recent studies, we now understand that metabolomics can be an effective approach for comprehensive evaluation of the qualities of medicinal plants. In this review, we describe practical cases in which metabolomic study was performed on medicinal plants, and discuss the utility of metabolomics for this research field, with focus on multivariate analysis.