The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics.
The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics.
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DOI：
10.1371/journal.pcbi.0030059
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发表时间：
2007-04-20
影响因子：
4.3
通讯作者：
Gerstein, Mark
中科院分区：
文献类型：
--
作者：
Yu, Haiyuan;Kim, Philip M.;Sprecher, Emmett;Trifonov, Valery;Gerstein, Mark
寻找蛋白质网络的拓扑性质与功能特征之间的关系是系统生物学长期追求的目标。然而，网络研究的大部分焦点都集中在高度连接的蛋白质(“中枢”)上。作为一种补充概念，可以将瓶颈定义为具有高度介数中心性的蛋白质(即具有许多经过它们的“最短路径”的网络节点，类似于公路地图上的主要桥梁和隧道)。事实上，瓶颈是具有惊人功能和动态特性的关键连接蛋白。特别是，它们更有可能是必不可少的蛋白质。事实上，在监管和其他定向网络中，中间性(即“瓶颈性”)是比程度(即“中枢”)更重要的重要指标。此外，瓶颈对应于交互网络的动态组件--它们与邻居的协同表达明显不如非瓶颈，这意味着表达动态连接到网络拓扑中。网络是由多个节点组成的图，这些节点之间有边连接。近年来，网络模型被广泛应用于生物系统。这里，我们主要对两种类型的生物网络感兴趣：相互作用网络，其中节点是蛋白质，边连接相互作用的伙伴；调控网络，其中节点是蛋白质，边连接转录因子及其靶标。介数是网络最重要的拓扑性质之一。它测量通过某个节点的最短路径的数量。因此，介数最高的节点控制着网络中的大部分信息流，代表着网络的关键点。因此，我们将这些节点称为网络的“瓶颈”。在这里，我们关注蛋白质网络中的瓶颈。我们发现，在有明确信息流概念的调控网络中，蛋白质瓶颈确实有更高的趋势成为必需基因。在这种类型的网络中，介数是一个很好的预测重要性的指标。因此，生物研究人员可以将介数作为另一个特征来选择潜在的目标进行详细分析。
It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins (“hubs”). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many “shortest paths” going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., “bottleneck-ness”) is a much more significant indicator of essentiality than degree (i.e., “hub-ness”). Furthermore, bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks, implying that expression dynamics is wired into the network topology. A network is a graph consisting of a number of nodes with edges connecting them. Recently, network models have been widely applied to biological systems. Here, we are mainly interested in two types of biological networks: the interaction network, where nodes are proteins and edges connect interacting partners; and the regulatory network, where nodes are proteins and edges connect transcription factors and their targets. Betweenness is one of the most important topological properties of a network. It measures the number of shortest paths going through a certain node. Therefore, nodes with the highest betweenness control most of the information flow in the network, representing the critical points of the network. We thus call these nodes the “bottlenecks” of the network. Here, we focus on bottlenecks in protein networks. We find that, in the regulatory network, where there is a clear concept of information flow, protein bottlenecks indeed have a much higher tendency to be essential genes. In this type of network, betweenness is a good predictor of essentiality. Biological researchers can therefore use the betweenness as one more feature to choose potential targets for detailed analysis.
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酵母蛋白相互作用网络中的高比分蛋白。
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