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基于核磁共振的代谢组学。

NMR-based metabolomics.

作者信息

Reo Nicholas V

机构信息

Department of Biochemistry and Molecular Biology, WSU Magnetic Resonance Laboratory, Cox Institute, 3525 Southern Blvd., Wright State University School of Medicine, Dayton, OH 45429, USA.

出版信息

Drug Chem Toxicol. 2002 Nov;25(4):375-82. doi: 10.1081/dct-120014789.

DOI:10.1081/dct-120014789
PMID:12378948
Abstract

Similar to genomics and proteomics which yield vast amounts of data about the expression of genes and proteins, metabolomics refers to the whole metabolic profile of the cell. The focus of this report concerns the use of nuclear magnetic resonance (NMR) spectroscopy for metabolic analyses and, in particular, its use in toxicology for examining the metabolic profile of biofluids. Examples from the literature will demonstrate how 1H NMR and pattern recognition methods are used to obtain the urinary metabolic profile, and how this profile is affected by exposure to various toxicants. These particular studies which focus on the metabolic profiles of biofluids, specifically urine, are referred to as metabonomics. NMR-based metabonomics provides a means to categorize organ-specific toxicity, monitor the onset and progression of toxicological effects, and identify biomarkers of toxicity. A future challenge, however, is to describe the cellular metabolome for purposes of understanding cellular functions (i.e., metabolomics). Thus the capabilities and advantages of multinuclear NMR to provide metabolic information in cells and tissues will also be discussed. Such information is essential if metabolomics is to provide a complementary dataset which together with genomics and proteomics can be used to construct computer network models to describe cellular functions.

摘要

与基因组学和蛋白质组学相似,它们能产生大量有关基因和蛋白质表达的数据,代谢组学是指细胞的整个代谢概况。本报告的重点是核磁共振(NMR)光谱在代谢分析中的应用,特别是其在毒理学中用于检查生物流体代谢概况的应用。文献中的实例将展示如何使用1H NMR和模式识别方法来获取尿液代谢概况,以及该概况如何受到接触各种毒物的影响。这些专注于生物流体(特别是尿液)代谢概况的特定研究被称为代谢组学。基于NMR的代谢组学提供了一种对器官特异性毒性进行分类、监测毒理学效应的发生和进展以及识别毒性生物标志物的方法。然而,未来的一个挑战是为了理解细胞功能(即代谢组学)而描述细胞代谢组。因此,还将讨论多核NMR在细胞和组织中提供代谢信息的能力和优势。如果代谢组学要提供一个补充数据集,与基因组学和蛋白质组学一起用于构建描述细胞功能的计算机网络模型,这样的信息是必不可少的。

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