Ground State Robustness as an Evolutionary Design Principle in Signaling Networks
Ground State Robustness as an Evolutionary Design Principle in Signaling Networks
复制标题
DOI：
10.1371/journal.pone.0008001
复制
发表时间：
2009-12-01
期刊：
影响因子：
3.7
通讯作者：
Ebenhoeh, Oliver
中科院分区：
文献类型：
--
作者：
Kartal, Oender;Ebenhoeh, Oliver
生物体的生存能力取决于它对外界条件的适应能力。除了代谢的多样性和有效的复制，可靠的信号转导是必不可少的。由于信号系统处于永久的进化压力之下，人们可以假设它们的结构反映了某些功能特性。然而，尽管近年来有希望的理论研究，选择性的力量，形状信令网络拓扑结构一般仍然不清楚。在这里，我们提出了一个可能的进化设计原则，防止自动激活。连续动力学模型的通用框架是用来获得拓扑结构的影响，要求一个动态稳定的基态信号系统。为此，应用图论方法。底层有向图的指数是一个关键的拓扑性质，它决定了所谓的动力学基态（或关闭状态）的鲁棒性。动力学鲁棒性仅取决于子图与强连通分量的组合，强连通分量包括网络中的所有正反馈。反馈族中指数最高的分量被证明主导整个网络的动力学鲁棒性，而这些基序的相对大小和周长被强调为分量指数的重要决定因素。此外，根据拓扑特征，当网络面临结构扰动时，鲁棒性的维护也会有所不同。这种结构关闭状态的鲁棒性，定义为网络的邻域的平均动力学鲁棒性，原来是有用的，因为一些结构特征对动力学鲁棒性是中性的，但显示出对结构扰动的支持。其中包括低连通性、高发散性和低路径和。所有的结果进行了测试对真实的信令网络从数据库中获得。分析表明，基态的鲁棒性可能是细胞内信号网络中发现的一些结构特性的基本原理。
The ability of an organism to survive depends on its capability to adapt to external conditions. In addition to metabolic versatility and efficient replication, reliable signal transduction is essential. As signaling systems are under permanent evolutionary pressure one may assume that their structure reflects certain functional properties. However, despite promising theoretical studies in recent years, the selective forces which shape signaling network topologies in general remain unclear. Here, we propose prevention of autoactivation as one possible evolutionary design principle. A generic framework for continuous kinetic models is used to derive topological implications of demanding a dynamically stable ground state in signaling systems. To this end graph theoretical methods are applied. The index of the underlying digraph is shown to be a key topological property which determines the so-called kinetic ground state (or off-state) robustness. The kinetic robustness depends solely on the composition of the subdigraph with the strongly connected components, which comprise all positive feedbacks in the network. The component with the highest index in the feedback family is shown to dominate the kinetic robustness of the whole network, whereas relative size and girth of these motifs are emphasized as important determinants of the component index. Moreover, depending on topological features, the maintenance of robustness differs when networks are faced with structural perturbations. This structural off-state robustness, defined as the average kinetic robustness of a network's neighborhood, turns out to be useful since some structural features are neutral towards kinetic robustness, but show up to be supporting against structural perturbations. Among these are a low connectivity, a high divergence and a low path sum. All results are tested against real signaling networks obtained from databases. The analysis suggests that ground state robustness may serve as a rationale for some structural peculiarities found in intracellular signaling networks.