Dutta Bhaskar, Kanani Harin, Quackenbush John, Klapa Maria I
Metabolic Engineering and Systems Biology Laboratory, Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, Maryland 20742.
The Institute for Genomic Research (TIGR), Rockville, Maryland 20850.
Biotechnol Bioeng. 2009 Jan 1;102(1):264-279. doi: 10.1002/bit.22036.
The research that aims at furthering our understanding of plant primary metabolism has intensified during the last decade. The presented study validated a systems biology methodological framework for the analysis of stress-induced molecular interaction networks in the context of plant primary metabolism, as these are expressed during the first hours of the stress treatment. The framework involves the application of time-series integrated full-genome transcriptomic and polar metabolomic analyses on plant liquid cultures. The latter were selected as the model system for this type of analysis, because they provide a well-controlled growth environment, ensuring that the observed plant response is due only to the applied perturbation. An enhanced gas chromatography-mass spectrometry (GC-MS) metabolomic data correction strategy and a new algorithm for the significance analysis of time-series "omic" data are used to extract information about the plant's transcriptional and metabolic response to the applied stress from the acquired datasets; in this article, it is the first time that these are applied for the analysis of a large biological dataset from a complex eukaryotic system. The case-study involved Arabidopsis thaliana liquid cultures subjected for 30 h to elevated (1%) CO2 stress. The advantages and validity of the methodological framework are discussed in the context of the known A. thaliana or plant, in general, physiology under the particular stress. Of note, the ability of the methodology to capture dynamic aspects of the observed molecular response allowed for 9 and 24 h of treatment to be indicated as corresponding to shifts in both the transcriptional and metabolic activity; analysis of the pathways through which these activity changes are manifested provides insight to regulatory processes.
在过去十年中，旨在加深我们对植物初级代谢理解的研究不断加强。本研究验证了一个系统生物学方法框架，用于在植物初级代谢背景下分析应激诱导的分子相互作用网络，因为这些网络是在应激处理的最初几个小时内表达的。该框架涉及对植物液体培养物进行时间序列整合全基因组转录组学和极性代谢组学分析。之所以选择后者作为此类分析的模型系统，是因为它们提供了一个可控性良好的生长环境，确保观察到的植物反应仅归因于所施加的扰动。一种改进的气相色谱 - 质谱联用（GC-MS）代谢组学数据校正策略和一种用于时间序列“组学”数据显著性分析的新算法，被用于从获取的数据集中提取有关植物对所施加应激的转录和代谢反应的信息；在本文中，这是首次将这些方法应用于分析来自复杂真核系统的大型生物学数据集。该案例研究涉及对拟南芥液体培养物施加30小时的高浓度（1%）二氧化碳应激。在已知的拟南芥或一般植物在特定应激下的生理学背景下，讨论了该方法框架的优点和有效性。值得注意的是，该方法捕捉观察到的分子反应动态方面的能力，使得能够确定9小时和24小时的处理时间分别对应转录和代谢活性的转变；对这些活性变化所表现的途径进行分析，有助于深入了解调控过程。
