Flux-dependent graphs for metabolic networks.
Flux-dependent graphs for metabolic networks.
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DOI：
10.1038/s41540-018-0067-y
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发表时间：
2018
影响因子：
4
通讯作者：
Barahona M
中科院分区：
文献类型：
--
作者：
Beguerisse-Díaz M;Bosque G;Oyarzún D;Picó J;Barahona M
细胞适应它们的代谢流以响应环境的变化。我们提出了一个框架的系统建设的通量为基础的图表来自生物体范围内的代谢网络。我们的图通过代表代谢物从源反应到目标反应的流动的边缘编码代谢流的方向性。该方法可以应用在没有特定的生物背景下，通过模拟通量概率，或可以定制不同的环境条件下，通过结合通量分布计算，通过基于约束的方法，如通量平衡分析。我们说明了我们的方法对大肠杆菌的中心碳代谢和人类肝细胞的代谢模型。在各种环境条件和遗传扰动下的通量依赖图在其拓扑和群落结构中表现出系统性变化，这捕获了代谢流的重新路由以及特定反应和途径的不同重要性。通过整合网络科学中基于约束的模型和工具，我们的框架允许在标准途径描述之外的系统水平上研究特定于环境的代谢反应。细胞代谢是一组高度纠缠的生化反应的结果，这些反应自然适合于基于图形的分析。然而，有多种方法可以从任何给定的代谢模型构建图形表示。在这里，一个由英国和西班牙科学家组成的国际研究小组提出了一种原则性的方法，通过网络科学的透镜来研究代谢模型。他们提出了一个框架来构建基因组规模的代谢模型，解决各种挑战，如合并池代谢物，代谢流的方向性的保存，并结合特定的通量信息的能力。该方法可以集成到管道流量平衡分析的基础上，并提供了一个系统的框架，以探索网络连接的变化，由于环境的变化或遗传扰动。因此，该框架允许询问超出标准途径描述的背景特异性代谢反应。作者通过分析大肠杆菌在不同生长条件下的核心代谢以及影响人类肝细胞的罕见代谢疾病来说明这种方法。
Cells adapt their metabolic fluxes in response to changes in the environment. We present a framework for the systematic construction of flux-based graphs derived from organism-wide metabolic networks. Our graphs encode the directionality of metabolic flows via edges that represent the flow of metabolites from source to target reactions. The methodology can be applied in the absence of a specific biological context by modelling fluxes probabilistically, or can be tailored to different environmental conditions by incorporating flux distributions computed through constraint-based approaches such as Flux Balance Analysis. We illustrate our approach on the central carbon metabolism of Escherichia coli and on a metabolic model of human hepatocytes. The flux-dependent graphs under various environmental conditions and genetic perturbations exhibit systemic changes in their topological and community structure, which capture the re-routing of metabolic flows and the varying importance of specific reactions and pathways. By integrating constraint-based models and tools from network science, our framework allows the study of context-specific metabolic responses at a system level beyond standard pathway descriptions. Cellular metabolism is the result of a highly enmeshed set of biochemical reactions that is naturally amenable to graph-based analyses. Yet there are multiple ways to construct a graph representation from any given metabolic model. Here an international research team of UK and Spain scientists presents a principled approach to study metabolic models through the lens of network science. They propose a framework to construct graphs for genome-scale metabolic models that resolve various challenges, such as the incorporation of pool metabolites, the preservation of the directionality of metabolic flows, and the capability to incorporate specific flux information. The method can be integrated into pipelines based on flux balance analysis and provides a systematic framework to explore changes in network connectivity as a result of environmental shifts or genetic perturbations. The framework thus allows to interrogate context-specific metabolic responses beyond standard pathway descriptions. The authors illustrate the approach through the analysis of Escherichia coli's core metabolism in different growth conditions, as well as a rare metabolic disease affecting human hepatocytes.
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影响因子：
16.6
作者：
Amor, B. R. C.;Schaub, M. T.;Yaliraki, S. N.;Barahona, M.
通讯作者：
Barahona, M.
影响因子：
5.4
作者：
Feist, Adam M.;Palsson, Bernhard O.
通讯作者：
Palsson, Bernhard O.
影响因子：
4.3
作者：
Bacik KA;Schaub MT;Beguerisse-Díaz M;Billeh YN;Barahona M
通讯作者：
Barahona M
影响因子：
4.3
作者：
King ZA;Dräger A;Ebrahim A;Sonnenschein N;Lewis NE;Palsson BO
通讯作者：
Palsson BO
影响因子：
5.6
作者：
Croes, D;Couche, F;van Helden, J
通讯作者：
van Helden, J