Rochfort Simone
Environmental Health and Chemistry, Department of Primary Industries, Primary Industries Research Victoria--Werribee Centre, Victoria, Australia.
J Nat Prod. 2005 Dec;68(12):1813-20. doi: 10.1021/np050255w.
Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. The analysis of the metabolome is particularly challenging due to the diverse chemical nature of metabolites. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression but also form part of the regulatory system in an integrated manner. Metabolomics has its roots in early metabolite profiling studies but is now a rapidly expanding area of scientific research in its own right. Metabolomics (or metabonomics) has been labeled one of the new "omics", joining genomics, transcriptomics, and proteomics as a science employed toward the understanding of global systems biology. Metabolomics is fast becoming one of the platform sciences of the "omics", with the majority of the papers in this field having been published only in the last two years. In this review metabolomic methodologies are discussed briefly followed by a more detailed review of the use of metabolomics in integrated applications where metabolomics information has been combined with other "omic" data sets (proteomics, transcriptomics) to enable greater understanding of a biological system. The potential of metabolomics for natural product drug discovery and functional food analysis, primarily as incorporated into broader "omic" data sets, is discussed.
代谢组学是对给定条件下一个系统(细胞、组织或生物体)中整体代谢物谱的研究。由于代谢物具有多样的化学性质,对代谢组的分析极具挑战性。代谢物是系统基因组与其环境相互作用的产物,它们不仅是基因表达的最终产物,还以一种整合的方式构成调节系统的一部分。代谢组学起源于早期的代谢物谱分析研究,但如今它本身就是一个迅速发展的科研领域。代谢组学(或代谢物组学)已被列为新的“组学”之一,与基因组学、转录组学和蛋白质组学一道,成为用于理解全球系统生物学的一门科学。代谢组学正迅速成为“组学”中的平台科学之一,该领域的大多数论文都是在过去两年才发表的。在这篇综述中,将简要讨论代谢组学方法,随后更详细地综述代谢组学在综合应用中的使用情况,即在这些应用中,代谢组学信息已与其他“组学”数据集(蛋白质组学、转录组学)相结合,以便更深入地理解生物系统。还将讨论代谢组学在天然产物药物发现和功能性食品分析方面的潜力,主要是作为纳入更广泛“组学”数据集的一部分。