Csikász-Nagy Attila, Soyer Orkun S
Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, Povo (Trento), Italy.
J R Soc Interface. 2008 Aug 6;5 Suppl 1(Suppl 1):S41-7. doi: 10.1098/rsif.2008.0099.focus.
An important step towards understanding biological systems is to relate simple biochemical elements to dynamics. Here, we present the arguably simplest dynamical element in biochemical networks. It consists of a single protein with two states (active and inactive) and an external signal that catalyses the conversion between these two states. Further, there is steady synthesis and degradation of the inactive and active forms, respectively. As this element captures both structural and dynamical features of biochemical networks at the lowest level, we refer to it as a biochemical network unit (BioNetUnit). Using both simulations and mathematical analysis, we find that BioNetUnit shows perfect adaptation that leads to temporal responses to step changes in the incoming signal. Compared with a well-described adaptive system, which is found in bacterial chemotaxis, BioNetUnit has lower sensitivity and its adaptation time is less robust to the base signal levels. We show that these dynamical limitations lead to 'once-and-only-once' responses for certain signal sequences. These findings demonstrate that BioNetUnit is relevant in adaptive and cyclic processes. In particular, it could be seen as a generic representation for ligand-activated receptors that are desensitized upon continuous activation. The analysis of coupled BioNetUnits will show how the presented dynamics at single unit will change upon increased system complexity and how such systems would mediate biological functions.
理解生物系统的一个重要步骤是将简单的生化元素与动力学联系起来。在此,我们展示了生化网络中可以说是最简单的动力学元素。它由一种具有两种状态(活性和非活性)的单一蛋白质以及催化这两种状态之间转换的外部信号组成。此外,非活性和活性形式分别存在稳定的合成和降解过程。由于这个元素在最低层面上捕捉了生化网络的结构和动力学特征,我们将其称为生化网络单元(BioNetUnit)。通过模拟和数学分析,我们发现BioNetUnit表现出完美的适应性,能够对输入信号的阶跃变化产生时间响应。与细菌趋化作用中一个描述详尽的自适应系统相比,BioNetUnit的敏感性较低,其适应时间对基础信号水平的鲁棒性也较差。我们表明,这些动力学限制会导致对某些信号序列产生“一次且仅一次”的响应。这些发现表明BioNetUnit在自适应和循环过程中具有相关性。特别是,它可以被视为持续激活后会脱敏的配体激活受体的一种通用表示。对耦合的BioNetUnit的分析将展示随着系统复杂性增加,单个单元呈现的动力学将如何变化,以及这样的系统将如何介导生物学功能。