Fan Teresa W-M, Higashi Richard M, Lane Andrew N
James Graham Brown Cancer Center, University of Louisville, Louisville, Kentucky 40202, USA.
Drug Metab Rev. 2006;38(4):707-32. doi: 10.1080/03602530600959599.
Transcriptomics provides the tool for deciphering gene expression networks, and proteomics links these networks to protein products. The third crucial partner is metabolomics, which defines the metabolic network(s) linked to gene expression. NMR and mass spectrometry enable the broad screen analysis of the metabolome and its transformation pathways, transcending classical targeted metabolic studies. These tools were combined to investigate the anticancer mechanisms of different selenium forms in human lung cancer cells. Using 2-D NMR and tandem-MS, we mapped perturbations of 13C labeling patterns in numerous metabolites induced by selenite and selenomethionine. This information was used to interpret selenite-induced changes in gene expression networks. Linking metabolic dysfunctions to altered gene expression profiles provided new insights into the regulatory network underlying the metabolic dysfunctions, enabled the assembly of discrete gene expression events into functional pathways, and revealed protein targets for proteomic analysis.
转录组学为破译基因表达网络提供了工具，而蛋白质组学则将这些网络与蛋白质产物联系起来。第三个关键伙伴是代谢组学，它定义了与基因表达相关的代谢网络。核磁共振（NMR）和质谱分析能够对代谢组及其转化途径进行广泛的筛查分析，超越了传统的靶向代谢研究。我们将这些工具结合起来，研究不同硒形态在人肺癌细胞中的抗癌机制。利用二维核磁共振和串联质谱，我们绘制了亚硒酸盐和硒代蛋氨酸诱导的多种代谢物中13C标记模式的扰动情况。这些信息被用于解释亚硒酸盐诱导的基因表达网络变化。将代谢功能障碍与改变的基因表达谱联系起来，为代谢功能障碍背后的调控网络提供了新的见解，使离散的基因表达事件能够组装成功能途径，并揭示了蛋白质组学分析的蛋白质靶点。
