Department of GTL Bioenergy and Structural Biology, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
J Am Soc Mass Spectrom. 2010 Sep;21(9):1471-6. doi: 10.1016/j.jasms.2010.04.003. Epub 2010 Apr 12.
Metabolomics is the comprehensive profiling of the small molecule composition of a biological sample. Since metabolites are often the indirect products of gene expression, this approach is being used to provide new insights into a variety of biological systems (clinical, bioenergy, etc.). A grand challenge for metabolomics is the complexity of the data, which often include many experimental artifacts. This is compounded by the tremendous chemical diversity of metabolites. Identification of each uncharacterized metabolite is in many ways its own puzzle (compared with proteomics, which is based on predictable fragmentation patterns of polypeptides). Therefore, effective data reduction/prioritization strategies are critical for this rapidly developing field. Here we review liquid chromatography electrospray ionization mass spectrometry (LC/MS)-based metabolomics, methods for feature finding/prioritization, approaches for identifying unknown metabolites, and construction of method specific 'Metabolite Atlases'.
代谢组学是对生物样本中小分子组成的全面分析。由于代谢物通常是基因表达的间接产物，因此这种方法正被用于为各种生物系统（临床、生物能源等）提供新的见解。代谢组学的一个重大挑战是数据的复杂性，其中通常包括许多实验假象。这是由于代谢物的巨大化学多样性造成的。每个特征不明的代谢物的鉴定在很多方面都是一个谜（与基于多肽可预测的片段模式的蛋白质组学相比）。因此，对于这个快速发展的领域来说，有效的数据减少/优先排序策略是至关重要的。在这里，我们回顾了基于液相色谱-电喷雾电离质谱（LC/MS）的代谢组学、特征发现/优先排序的方法、鉴定未知代谢物的方法以及特定方法的“代谢物图谱”的构建。
