Patil Kiran Raosaheb, Nielsen Jens
Center for Microbial Biotechnology, BioCentrum-DTU, Technical University of Denmark, Building 223, DK-2800 Kgs. Lyngby, Denmark.
Proc Natl Acad Sci U S A. 2005 Feb 22;102(8):2685-9. doi: 10.1073/pnas.0406811102. Epub 2005 Feb 14.
Cellular response to genetic and environmental perturbations is often reflected and/or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional changes induced by complex regulatory mechanisms coordinating the activity of different metabolic pathways. It is difficult to map such global transcriptional responses by using traditional methods, because many genes in the metabolic network have relatively small changes at their transcription level. We therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic or environmental perturbations. We find that cells respond to perturbations by changing the expression pattern of several genes involved in the specific part(s) of the metabolism in which a perturbation is introduced. These changes then are propagated through the metabolic network because of the highly connected nature of metabolism.
细胞对遗传和环境扰动的反应通常通过代谢变化得以体现和/或介导，因为后者在为生物合成提供吉布斯自由能和前体方面发挥着关键作用。此类代谢变化通常是通过复杂调控机制诱导的转录变化来实现的，这些调控机制协调着不同代谢途径的活性。使用传统方法难以绘制这种全局转录反应图谱，因为代谢网络中的许多基因在转录水平上变化相对较小。因此，我们开发了一种基于假设驱动数据分析的算法，以揭示代谢网络的转录调控结构。通过利用基因组规模代谢重建中代谢网络拓扑结构的信息，我们表明有可能揭示代谢网络中遵循共同转录反应的模式。因此，该算法能够识别所谓的报告代谢物（发生最显著转录变化的代谢物周围）以及一组对遗传或环境扰动具有显著且协调反应的相关基因。我们发现，细胞通过改变参与引入扰动的代谢特定部分的几个基因的表达模式来应对扰动。由于代谢的高度连通性，这些变化随后在代谢网络中传播。
