Bioinformatics Center, Kyoto University, Kyoto, Japan.
PLoS One. 2012;7(2):e31345. doi: 10.1371/journal.pone.0031345. Epub 2012 Feb 15.
In this paper we investigate how metabolic network structure affects any coordination between transcript and metabolite profiles. To achieve this goal we conduct two complementary analyses focused on the metabolic response to stress. First, we investigate the general size of any relationship between metabolic network gene expression and metabolite profiles. We find that strongly correlated transcript-metabolite profiles are sustained over surprisingly long network distances away from any target metabolite. Secondly, we employ a novel pathway mining method to investigate the structure of this transcript-metabolite relationship. The objective of this method is to identify a minimum set of metabolites which are the target of significantly correlated gene expression pathways. The results reveal that in general, a global regulation signature targeting a small number of metabolites is responsible for a large scale metabolic response. However, our method also reveals pathway specific effects that can degrade this global regulation signature and complicates the observed coordination between transcript-metabolite profiles.
在本文中,我们研究代谢网络结构如何影响转录物和代谢物谱之间的任何协调。为了实现这一目标,我们进行了两项互补的分析,重点关注代谢对压力的反应。首先,我们研究了代谢网络基因表达和代谢物谱之间关系的一般大小。我们发现,与代谢物谱强烈相关的转录物可以在远离任何目标代谢物的惊人长的网络距离上维持。其次,我们采用一种新的途径挖掘方法来研究这种转录物-代谢物关系的结构。该方法的目的是确定一组最小的代谢物,这些代谢物是显著相关的基因表达途径的靶标。结果表明,一般来说,针对少数代谢物的全局调控特征负责大规模的代谢反应。然而,我们的方法也揭示了特定途径的影响,这些影响可以削弱这种全局调控特征,并使转录物-代谢物谱之间的观察到的协调复杂化。