Li Hao, Jiang Ying, He Fu-Chu
State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China.
Yi Chuan. 2008 Apr;30(4):389-99. doi: 10.3724/sp.j.1005.2008.00389.
In the post-genomic era, systems biology is central to the biological sciences. Functional genomics such as transcriptomics and proteomics can simultaneous determine massive gene or protein expression changes following drug treatment or other intervention. However, these changes can't be coupled directly to changes in biological function. As a result, metabonomics and its many pseudonyms (metabolomics, metabolic profiling, etc.) have exploded onto the scientific scene in the past several years. Metabonomics is a rapidly growing research area and a system approach for comprehensive and quantitative analysis of the global metabolites in a biological matrix. Analytical chemistry approach is necessary for the development of comprehensive metabonomics investigations. Fundamentally, there are two types of metabonomics approaches: mass-spectrometry (MS) based and nuclear magnetic resonance (NMR) methodologies. Metabonomics measurements provide a wealth of data information and interpretation of these data relies mainly on chemometrics approaches to perform large-scale data analysis and data visualization, such as principal and independent component analysis, multidimensional scaling, a variety of clustering techniques, and discriminant function analysis, among many others. In this review, the recent development of analytical and statistical techniques used in metabonomics is summarized. Major applications of metabonomics relevant to clinical and preclinical study are then reviewed. The applications of metabonomics in study of liver diseases, cancers and other diseases have proved useful both as an experimental tool for pathogenesis mechanism re-search and ultimately a tool for diagnosis and monitoring treatment response of these diseases. Next, the applications of metabonomics in preclinical toxicology are discussed and the role that metabonomics might do in pharmaceutical research and development is explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology (COMET), and the concept of pharmacometabonomics as a way of predicting an individual's response to treatment is highlighted. Finally, the role of metabonomics in elucidating the function of the unknown or novel enzyme is mentioned.
在后基因组时代,系统生物学是生物科学的核心。诸如转录组学和蛋白质组学等功能基因组学能够同时确定药物治疗或其他干预后大量基因或蛋白质表达的变化。然而,这些变化无法直接与生物学功能的变化联系起来。因此,代谢组学及其众多别称(代谢物组学、代谢谱分析等)在过去几年里迅速登上了科学舞台。代谢组学是一个快速发展的研究领域,是一种对生物基质中全局代谢物进行全面定量分析的系统方法。分析化学方法对于全面开展代谢组学研究是必不可少的。从根本上讲,代谢组学方法有两种类型:基于质谱(MS)的方法和核磁共振(NMR)方法。代谢组学测量提供了丰富的数据信息,对这些数据的解释主要依赖于化学计量学方法来进行大规模数据分析和数据可视化,例如主成分分析和独立成分分析、多维标度分析、各种聚类技术以及判别函数分析等等。在这篇综述中,总结了代谢组学中使用的分析和统计技术的最新进展。接着回顾了代谢组学在临床和临床前研究中的主要应用。代谢组学在肝脏疾病、癌症和其他疾病研究中的应用已证明,它既是一种用于发病机制研究的实验工具,最终也是一种用于这些疾病诊断和监测治疗反应的工具。接下来,讨论了代谢组学在临床前毒理学中的应用,并特别参考代谢组学毒理学联盟(COMET)的目标和成果,解释了代谢组学在药物研发中可能发挥的作用,同时强调了药物代谢组学作为预测个体治疗反应方式的概念。最后,提到了代谢组学在阐明未知或新型酶功能方面的作用。