Fuhrer Tobias, Zampieri Mattia, Sévin Daniel C, Sauer Uwe, Zamboni Nicola
Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.
Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
Mol Syst Biol. 2017 Jan 16;13(1):907. doi: 10.15252/msb.20167150.
Metabolism is one of the best-understood cellular processes whose network topology of enzymatic reactions is determined by an organism's genome. The influence of genes on metabolite levels, however, remains largely unknown, particularly for the many genes encoding non-enzymatic proteins. Serendipitously, genomewide association studies explore the relationship between genetic variants and metabolite levels, but a comprehensive interaction network has remained elusive even for the simplest single-celled organisms. Here, we systematically mapped the association between > 3,800 single-gene deletions in the bacterium Escherichia coli and relative concentrations of > 7,000 intracellular metabolite ions. Beyond expected metabolic changes in the proximity to abolished enzyme activities, the association map reveals a largely unknown landscape of gene-metabolite interactions that are not represented in metabolic models. Therefore, the map provides a unique resource for assessing the genetic basis of metabolic changes and conversely hypothesizing metabolic consequences of genetic alterations. We illustrate this by predicting metabolism-related functions of 72 so far not annotated genes and by identifying key genes mediating the cellular response to environmental perturbations.
新陈代谢是人们了解最为深入的细胞过程之一,其酶促反应的网络拓扑结构由生物体的基因组决定。然而,基因对代谢物水平的影响在很大程度上仍然未知,尤其是对于许多编码非酶蛋白的基因而言。机缘巧合的是,全基因组关联研究探索了基因变异与代谢物水平之间的关系,但即使对于最简单的单细胞生物,一个全面的相互作用网络仍然难以捉摸。在这里,我们系统地绘制了大肠杆菌中超过3800个单基因缺失与超过7000种细胞内代谢物离子相对浓度之间的关联。除了在接近被消除的酶活性处预期的代谢变化外,关联图谱还揭示了代谢模型中未体现的基因 - 代谢物相互作用的未知领域。因此,该图谱为评估代谢变化的遗传基础以及反过来推测基因改变的代谢后果提供了独特的资源。我们通过预测72个迄今未注释基因的代谢相关功能以及识别介导细胞对环境扰动反应的关键基因来对此进行说明。