Metabolomics-edited transcriptomics analysis of Se anticancer action in human lung cancer cells
Metabolomics-edited transcriptomics analysis of Se anticancer action in human lung cancer cells
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DOI：
10.1007/s11306-005-0012-0
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发表时间：
2005-10-01
期刊：
影响因子：
3.6
通讯作者：
Lane, Andrew N.
中科院分区：
文献类型：
--
作者：
Fan, Teresa W. M.;Bandura, Laura L.;Lane, Andrew N.
转录分析是系统生物学的重要工具，但由于缺乏对基因组功能的全球了解，导致无法将功能不同的基因表达事件联系起来。使用抗癌剂亚硒酸盐和人类肺癌A549细胞作为模型系统，我们证明了这些困难可以通过一种渐进的方法来克服，这种方法利用代谢组学的新兴力量进行转录分析。我们将这种方法命名为代谢组学编辑的转录分析(META)。主要的分析引擎是使用多核二维核磁共振和GC-MS技术相结合的C-13同位素异构体分析。以C-13-葡萄糖为示踪剂，研究了亚硒酸钠对A549细胞中枢代谢网络的多重破坏作用。然后，通过将代谢功能障碍与改变的基因表达谱相结合来实现META：(1)为代谢功能障碍背后的调控网络提供新的见解；(2)能够将不同的基因表达事件组装成功能路径，这是仅通过转录分析无法实现的。线粒体功能障碍与通过AMP-AMPK途径扰乱脂代谢的联系尤其说明了这一点。因此，META产生了广泛和高度具体的工作假说，以供进一步验证，从而加快了复杂生物学问题的解决，如亚硒酸盐的抗癌机制。
Transcriptomic analysis is an essential tool for systems biology but it has been stymied by a lack of global understanding of genomic functions, resulting in the inability to link functionally disparate gene expression events. Using the anticancer agent selenite and human lung cancer A549 cells as a model system, we demonstrate that these difficulties can be overcome by a progressive approach which harnesses the emerging power of metabolomics for transcriptomic analysis. We have named the approach Metabolomics-edited transcriptomic analysis (META). The main analytical engine was C-13 isotopomer profiling using a combination of multi-nuclear 2-D NMR and GC-MS techniques. Using C-13-glucose as a tracer, multiple disruptions to the central metabolic network in A549 cells induced by selenite were defined. META was then achieved by coupling the metabolic dysfunctions to altered gene expression profiles to: (1) provide new insights into the regulatory network underlying the metabolic dysfunctions; (2) enable the assembly of disparate gene expression events into functional pathways that was not feasible by transcriptomic analysis alone. This was illustrated in particular by the connection of mitochondrial dysfunctions to perturbed lipid metabolism via the AMP-AMPK pathway. Thus, META generated both extensive and highly specific working hypotheses for further validation, thereby accelerating the resolution of complex biological problems such as the anticancer mechanism of selenite.