Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.
OMICS. 2010 Jun;14(3):261-74. doi: 10.1089/omi.2010.0010.
The integrated analysis of omics datasets covering different levels of molecular organization has become a central task of systems biology. We investigated the transcriptional and metabolic response of yeast exposed to increased (37 degrees C) and lowered (10 degrees C) temperatures relative to optimal reference conditions (28 degrees C) in the context of known metabolic pathways. Pairwise metabolite correlation levels were found to carry more pathway-related information and to extend to farther distances within the metabolic pathway network than associated transcript level correlations. Metabolites were detected to correlate stronger to their cognate transcripts (metabolite is reactant of the enzyme encoded by the transcript) than to more remote or randomly chosen transcripts reflecting their close metabolic relationship. We observed a pronounced temporal hierarchy between metabolic and transcriptional molecular responses under heat and cold stress. Changes of metabolites were most significantly correlated to transcripts encoding metabolic enzymes, when metabolites were considered leading in time-lagged correlation analyses. By applying the concept of Granger causality, we detected directed relationships between metabolites and their cognate transcripts. When interpreted as substrate-to-product directions, most of these directed Granger causality pairs agreed with the KEGG-annotated preferred reaction direction. Thus, the introduced Granger causality approach may prove useful for determining the preferred direction of metabolic reactions in cellular systems. The metabolites glutamic acid and serine were identified as central causative metabolites influencing transcript levels at later time points. Selected examples are presented illustrating the intertwined relationships between metabolites and transcripts in the yeast temperature stress adaptation process.
在系统生物学中，整合分析涵盖不同分子组织层次的组学数据集已经成为一项核心任务。我们研究了酵母在高于（37°C）和低于（10°C）最佳参考条件（28°C）的温度下暴露时的转录和代谢反应，这是在已知代谢途径的背景下进行的。我们发现，成对代谢物相关水平比相关转录水平相关更具有途径相关信息，并在代谢途径网络内延伸到更远的距离。与更远程或随机选择的转录物相比，代谢物与它们同源的转录物（代谢物是由转录物编码的酶的反应物）相关性更强，反映了它们密切的代谢关系。我们观察到在热和冷应激下，代谢和转录分子反应之间存在明显的时间层次结构。当考虑代谢物在时间滞后相关分析中起主导作用时，代谢物的变化与编码代谢酶的转录物最显著相关。通过应用格兰杰因果关系的概念，我们检测到代谢物与其同源转录物之间存在有向关系。当解释为底物到产物的方向时，这些有向格兰杰因果关系对中的大多数与 KEGG 注释的首选反应方向一致。因此，所提出的格兰杰因果关系方法可能有助于确定细胞系统中代谢反应的首选方向。谷氨酸和丝氨酸等代谢物被确定为影响转录物水平的核心因果代谢物，在稍后的时间点。本文呈现了一些示例，说明了在酵母温度应激适应过程中代谢物和转录物之间相互交织的关系。
