Çakır Tunahan
Gebze Technical University, Department of Bioengineering, 41400, Gebze, Kocaeli, Turkey.
Sci Rep. 2015 Sep 28;5:14563. doi: 10.1038/srep14563.
A systems-based investigation of the effect of perturbations on metabolic machinery is crucial to elucidate the mechanism behind perturbations. One way to investigate the perturbation-induced changes within the cell metabolism is to focus on pathway-level effects. In this study, three different perturbation types (genetic, environmental and disease-based) are analyzed to compute a list of reporter pathways, metabolic pathways which are significantly affected from a perturbation. The most common omics data type, transcriptome, is used as an input to the bioinformatic analysis. The pathways are scored by two alternative approaches: by averaging the changes in the expression levels of the genes controlling the associated reactions (reaction-centric), and by averaging the changes in the associated metabolites which were scored based on the associated genes (metabolite-centric). The analysis reveals the superiority of the novel metabolite-centric approach over the commonly used reaction-centric approach since it is based on metabolites which better represent the cross-talk among different pathways, enabling a more global and realistic cataloguing of network-wide perturbation effects.
基于系统的对扰动对代谢机制影响的研究对于阐明扰动背后的机制至关重要。研究细胞代谢中扰动诱导变化的一种方法是关注途径水平的影响。在本研究中，分析了三种不同的扰动类型（基于基因、环境和疾病）以计算一组报告途径，即受扰动显著影响的代谢途径。最常见的组学数据类型转录组被用作生物信息学分析的输入。通过两种替代方法对途径进行评分：通过平均控制相关反应的基因表达水平的变化（以反应为中心），以及通过平均基于相关基因评分的相关代谢物的变化（以代谢物为中心）。分析揭示了新的以代谢物为中心的方法相对于常用的以反应为中心的方法的优越性，因为它基于能更好地代表不同途径间相互作用的代谢物，从而能够对全网络扰动效应进行更全面和实际的编目。
