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首页> 外文期刊>Philosophical Transactions of the Royal Society of London, Series B. Biological Sciences >Subcellular metabolic organization in the context of dynamic energy budget and biochemical systems theories
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Subcellular metabolic organization in the context of dynamic energy budget and biochemical systems theories

机译:动态能量收支和生化系统理论背景下的亚细胞代谢组织

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The dynamic modelling of metabolic networks aims to describe the temporal evolution of metabolite concentrations in cells. This area has attracted increasing attention in recent years owing to the availability of high-throughput data and the general development of systems biology as a promising approach to study living organisms. Biochemical Systems Theory (BST) provides an accurate formalism to describe biological dynamic phenomena. However, knowledge about the molecular organization level, used in these models, is not enough to explain phenomena such as the driving forces of these metabolic networks. Dynamic Energy Budget (DEB) theory captures the quantitative aspects of the organization of metabolism at the organism level in a way that is nonspecies- specific. This imposes constraints on the sub-organismal organization that are not present in the bottom-up approach of systems biology. We use in vivo data of lactic acid bacteria under various conditions to compare some aspects of BST and DEB approaches. Due to the large number of parameters to be estimated in the BST model, we applied powerful parameter identification techniques. Both models fitted equally well, but the BST model employs more parameters. The DEB model uses similarities of processes under growth and no-growth conditions and under aerobic and anaerobic conditions, which reduce the number of parameters. This paper discusses some future directions for the integration of knowledge from these two rich and promising areas, working top-down and bottom-up simultaneously. This middle-out approach is expected to bring new ideas and insights to both areas in terms of describing how living organisms operate.
机译:代谢网络的动态建模旨在描述细胞中代谢物浓度的时间演变。由于高通量数据的可获得性和系统生物学作为研究活生物体的一种有前途的方法的全面发展,近年来该领域引起了越来越多的关注。生化系统理论(BST)提供了一种准确的形式主义来描述生物动力学现象。但是,在这些模型中使用的有关分子组织水平的知识不足以解释诸如这些代谢网络的驱动力之类的现象。动态能量预算(DEB)理论以非物种特定的方式捕获了生物体一级新陈代谢组织的定量方面。这对自下而上的系统生物学方法不存在的亚有机组织施加了限制。我们使用乳酸菌在各种条件下的体内数据来比较BST和DEB方法的某些方面。由于在BST模型中需要估计大量参数,因此我们应用了功能强大的参数识别技术。两种模型均拟合得很好,但BST模型采用了更多参数。 DEB模型使用生长和无生长条件以及有氧和厌氧条件下的过程相似性,从而减少了参数数量。本文讨论了这两个丰富而有前途的领域(自上而下和自下而上)同时进行的知识集成的未来方向。从描述活生物体的运作方式来看,这种中间化方法有望为这两个领域带来新的想法和见解。

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