Dynamic Modelling under Uncertainty: The Case of Trypanosoma brucei Energy Metabolism
Dynamic Modelling under Uncertainty: The Case of Trypanosoma brucei Energy Metabolism
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DOI：
10.1371/journal.pcbi.1002352
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发表时间：
2012-01-01
影响因子：
4.3
通讯作者：
Breitling, Rainer
中科院分区：
文献类型：
--
作者：
Achcar, Fiona;Kerkhoven, Eduard J.;Breitling, Rainer
代谢动力学模型需要详细的动力学参数的知识。然而，由于测量误差或缺乏数据，这种知识往往是不确定的。寄生原生动物布氏锥虫的糖酵解模型是定量代谢模型的一个特别好的分析例子，但到目前为止，它只被研究了一组固定的参数。在这里，我们评估参数不确定性的影响。为了定义每个参数的概率分布，收集了关于所有参数的实验来源和置信区间的信息。我们创建了一个基于wiki的网站，专门用于详细记录这些信息：SilicoTryp wiki（http：//silicotryp.ibls.gla.ac.uk/wiki/Glycolysis）。使用维基中收集的信息，我们为模型的所有参数分配了概率分布。这使我们能够对替代模型进行抽样，准确地表示我们的不确定性程度。该模型的一些特性，如甘油和丙酮酸产生分支之间的糖酵解通量的再分配，对这些不确定性是鲁棒的。然而，我们的分析也使我们能够识别导致3-磷酸甘油酸和/或丙酮酸积累的模型的脆弱性。控制系数的分析揭示了考虑参数的不确定性的重要性，因为反应的排名可能会受到很大影响。这项工作现在将形成一个全面的贝叶斯分析和扩展的模型，考虑替代拓扑结构的基础。
Kinetic models of metabolism require detailed knowledge of kinetic parameters. However, due to measurement errors or lack of data this knowledge is often uncertain. The model of glycolysis in the parasitic protozoan Trypanosoma brucei is a particularly well analysed example of a quantitative metabolic model, but so far it has been studied with a fixed set of parameters only. Here we evaluate the effect of parameter uncertainty. In order to define probability distributions for each parameter, information about the experimental sources and confidence intervals for all parameters were collected. We created a wiki-based website dedicated to the detailed documentation of this information: the SilicoTryp wiki (http://silicotryp.ibls.gla.ac.uk/wiki/Glycolysis). Using information collected in the wiki, we then assigned probability distributions to all parameters of the model. This allowed us to sample sets of alternative models, accurately representing our degree of uncertainty. Some properties of the model, such as the repartition of the glycolytic flux between the glycerol and pyruvate producing branches, are robust to these uncertainties. However, our analysis also allowed us to identify fragilities of the model leading to the accumulation of 3-phosphoglycerate and/or pyruvate. The analysis of the control coefficients revealed the importance of taking into account the uncertainties about the parameters, as the ranking of the reactions can be greatly affected. This work will now form the basis for a comprehensive Bayesian analysis and extension of the model considering alternative topologies.