Reciprocal regulation of metabolic and signaling pathways
Reciprocal regulation of metabolic and signaling pathways
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DOI：
10.1186/1471-2164-11-197
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发表时间：
2010-03-24
期刊：
影响因子：
4.4
通讯作者：
Tomaselli, Gordon F.
中科院分区：
文献类型：
--
作者：
Barth, Andreas S.;Kumordzie, Ami;Tomaselli, Gordon F.
背景资料：通过研究健康和患病组织在广泛的病理生理条件下的全基因组表达模式，DNA微阵列揭示了对复杂疾病的独特见解。然而，高维度的微阵列数据使得异质性基因表达研究的解释本质上是困难的。结果：使用40多个微阵列研究的大规模分析，包括类似的2400哺乳动物组织样本，我们确定了一个共同的主题跨异质性微阵列研究明显的一个强大的全基因组的代谢和细胞信号转导通路的逆调节：我们发现，细胞信号通路的上调总是伴随着细胞代谢转录活性的下调（反之亦然）。一些研究结果表明，这种特征性的基因表达模式代表了哺乳动物转录调控的新原则。首先，这种协调的转录模式发生在各种各样的生理和病理生理条件下，并确定在所有20个人类和动物组织类型的检查。第二，代谢基因表达的差异预测了信号传导和所有其他途径的差异程度，即具有相似代谢转录本表达水平的组织样品在所有其他途径的基因表达中没有显示出任何差异。第三，这种转录模式预测了对蛋白质组的深远影响，分别属于信号传导和代谢途径的蛋白质在结构、稳定性和翻译后修饰方面的差异证明了这一点。我们的数据表明，在广泛的生理和病理生理条件下，基因表达的变化表现出沿沿着转录轴的重复模式，其特征在于主要代谢和细胞信号传导途径的反向调节。鉴于其广泛的发生和其对蛋白质结构，蛋白质稳定性和翻译后修饰的预测影响，我们提出了一个新的原则，在哺乳动物生物学中的转录调控。
Background: By studying genome-wide expression patterns in healthy and diseased tissues across a wide range of pathophysiological conditions, DNA microarrays have revealed unique insights into complex diseases. However, the high-dimensionality of microarray data makes interpretation of heterogeneous gene expression studies inherently difficult.Results: Using a large-scale analysis of more than 40 microarray studies encompassing similar to 2400 mammalian tissue samples, we identified a common theme across heterogeneous microarray studies evident by a robust genome-wide inverse regulation of metabolic and cell signaling pathways: We found that upregulation of cell signaling pathways was invariably accompanied by downregulation of cell metabolic transcriptional activity (and vice versa). Several findings suggest that this characteristic gene expression pattern represents a new principle of mammalian transcriptional regulation. First, this coordinated transcriptional pattern occurred in a wide variety of physiological and pathophysiological conditions and was identified across all 20 human and animal tissue types examined. Second, the differences in metabolic gene expression predicted the magnitude of differences for signaling and all other pathways, i.e. tissue samples with similar expression levels of metabolic transcripts did not show any differences in gene expression for all other pathways. Third, this transcriptional pattern predicted a profound effect on the proteome, evident by differences in structure, stability and post-translational modifications of proteins belonging to signaling and metabolic pathways, respectively.Conclusions: Our data suggest that in a wide range of physiological and pathophysiological conditions, gene expression changes exhibit a recurring pattern along a transcriptional axis, characterized by an inverse regulation of major metabolic and cell signaling pathways. Given its widespread occurrence and its predicted effects on protein structure, protein stability and post-translational modifications, we propose a new principle for transcriptional regulation in mammalian biology.