Soyer Orkun S, Pfeiffer Thomas, Bonhoeffer Sebastian
Theoretical Biology Group, Ecology and Evolution, CH 8092, Zürich, Switzerland.
J Theor Biol. 2006 Jul 21;241(2):223-32. doi: 10.1016/j.jtbi.2005.11.024. Epub 2006 Jan 5.
We use a generic model of a network of proteins that can activate or deactivate each other to explore the emergence and evolution of signal transduction networks and to gain a basic understanding of their general properties. Starting with a set of non-interacting proteins, we evolve a signal transduction network by random mutation and selection to fulfill a complex biological task. In order to validate this approach we base selection on a fitness function that captures the essential features of chemotactic behavior as seen in bacteria. We find that a system of as few as three proteins can evolve into a network mediating chemotaxis-like behavior by acting as a "derivative sensor". Furthermore, we find that the dynamics and topology of such networks show many similarities to the natural chemotaxis pathway, that the response magnitude can increase with increasing network size and that network behavior shows robustness towards variations in some of the internal parameters. We conclude that simulating the evolution of signal transduction networks to mediate a certain behavior may be a promising approach for understanding the general properties of the natural pathway for that behavior.
我们使用一种蛋白质网络的通用模型，该模型中的蛋白质可以相互激活或失活，以探索信号转导网络的出现和进化，并对其一般特性有基本的了解。从一组不相互作用的蛋白质开始，我们通过随机突变和选择来进化一个信号转导网络，以完成一项复杂的生物学任务。为了验证这种方法，我们基于一个适应度函数进行选择，该函数捕捉了细菌中趋化行为的基本特征。我们发现，一个只有三种蛋白质的系统可以通过充当“导数传感器”，进化成一个介导类趋化行为的网络。此外，我们发现这种网络的动力学和拓扑结构与天然趋化途径有许多相似之处，响应幅度会随着网络规模的增加而增大，并且网络行为对某些内部参数的变化具有鲁棒性。我们得出结论，模拟信号转导网络的进化以介导某种行为，可能是理解该行为天然途径一般特性的一种有前途的方法。
