Österlund Tobias, Bordel Sergio, Nielsen Jens
Novo Nordisk Foundation Center for Biosustainability, Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-41296 Göteborg, Sweden.
Integr Biol (Camb). 2015 May;7(5):560-8. doi: 10.1039/c4ib00247d. Epub 2015 Apr 9.
Transcriptional regulation is the most committed type of regulation in living cells where transcription factors (TFs) control the expression of their target genes and TF expression is controlled by other TFs forming complex transcriptional regulatory networks that can be highly interconnected. Here we analyze the topology and organization of nine transcriptional regulatory networks for E. coli, yeast, mouse and human, and we evaluate how the structure of these networks influences two of their key properties, namely controllability and stability. We calculate the controllability for each network as a measure of the organization and interconnectivity of the network. We find that the number of driver nodes nD needed to control the whole network is 64% of the TFs in the E. coli transcriptional regulatory network in contrast to only 17% for the yeast network, 4% for the mouse network and 8% for the human network. The high controllability (low number of drivers needed to control the system) in yeast, mouse and human is due to the presence of internal loops in their regulatory networks where the TFs regulate each other in a circular fashion. We refer to these internal loops as circular control motifs (CCM). The E. coli transcriptional regulatory network, which does not have any CCMs, shows a hierarchical structure of the transcriptional regulatory network in contrast to the eukaryal networks. The presence of CCMs also has influence on the stability of these networks, as the presence of cycles can be associated with potential unstable steady-states where even small changes in binding affinities can cause dramatic rearrangements of the state of the network.
转录调控是活细胞中最关键的调控类型，转录因子（TFs）控制其靶基因的表达，而TF的表达则由其他TF控制，从而形成高度互联的复杂转录调控网络。在此，我们分析了大肠杆菌、酵母、小鼠和人类的九个转录调控网络的拓扑结构和组织，并评估了这些网络的结构如何影响其两个关键特性，即可控性和稳定性。我们计算每个网络的可控性，以此作为衡量网络组织和互联性的指标。我们发现，控制大肠杆菌转录调控网络的整个网络所需的驱动节点数量nD占TFs的64%，相比之下，酵母网络仅为17%，小鼠网络为4%，人类网络为8%。酵母、小鼠和人类网络具有较高的可控性（控制该系统所需的驱动节点数量较少），这是因为其调控网络中存在内部回路，其中TFs以循环方式相互调控。我们将这些内部回路称为循环控制基序（CCM）。与真核生物网络不同，没有任何CCM的大肠杆菌转录调控网络呈现出转录调控网络的层次结构。CCM的存在也会影响这些网络的稳定性，因为循环的存在可能与潜在的不稳定稳态相关，即使结合亲和力的微小变化也可能导致网络状态的剧烈重排。
