Marquez-Lago Tatiana T, Leier André
Department of Biosystems Science and Engineering, ETH Zurich, Universitätsstrasse 6, CH-8092 Zurich, Switzerland.
BMC Syst Biol. 2011 Feb 3;5:22. doi: 10.1186/1752-0509-5-22.
In cell signaling terminology, adaptation refers to a system's capability of returning to its equilibrium upon a transient response. To achieve this, a network has to be both sensitive and precise. Namely, the system must display a significant output response upon stimulation, and later on return to pre-stimulation levels. If the system settles at the exact same equilibrium, adaptation is said to be 'perfect'. Examples of adaptation mechanisms include temperature regulation, calcium regulation and bacterial chemotaxis.
We present models of the simplest adaptation architecture, a two-state protein system, in a stochastic setting. Furthermore, we consider differences between individual and collective adaptive behavior, and show how our system displays fold-change detection properties. Our analysis and simulations highlight why adaptation needs to be understood in terms of probability, and not in strict numbers of molecules. Most importantly, selection of appropriate parameters in this simple linear setting may yield populations of cells displaying adaptation, while single cells do not.
Single cell behavior cannot be inferred from population measurements and, sometimes, collective behavior cannot be determined from the individuals. By consequence, adaptation can many times be considered a purely emergent property of the collective system. This is a clear example where biological ergodicity cannot be assumed, just as is also the case when cell replication rates are not homogeneous, or depend on the cell state. Our analysis shows, for the first time, how ergodicity cannot be taken for granted in simple linear examples either. The latter holds even when cells are considered isolated and devoid of replication capabilities (cell-cycle arrested). We also show how a simple linear adaptation scheme displays fold-change detection properties, and how rupture of ergodicity prevails in scenarios where transitions between protein states are mediated by other molecular species in the system, such as phosphatases and kinases.
在细胞信号传导术语中,适应性是指系统在短暂响应后恢复到平衡状态的能力。为实现这一点,网络必须既敏感又精确。也就是说,系统在受到刺激时必须显示出显著的输出响应,随后再回到刺激前的水平。如果系统稳定在完全相同的平衡状态,则称适应性为“完美”。适应性机制的例子包括温度调节、钙调节和细菌趋化性。
我们在随机环境中提出了最简单的适应性架构模型,即双态蛋白质系统。此外,我们考虑了个体适应性行为与集体适应性行为之间的差异,并展示了我们的系统如何呈现倍数变化检测特性。我们的分析和模拟突出了为何需要从概率角度而非严格的分子数量来理解适应性。最重要的是,在这个简单的线性环境中选择合适的参数可能会产生表现出适应性的细胞群体,而单个细胞却不会。
不能从群体测量结果推断单细胞行为,而且有时也无法从个体确定集体行为。因此,适应性很多时候可被视为集体系统的一种纯粹涌现特性。这是一个明显的例子,说明不能假定生物遍历性,就如同细胞复制速率不均匀或取决于细胞状态的情况一样。我们的分析首次表明,在简单的线性例子中遍历性也不能被想当然地认为成立。即使将细胞视为孤立的且缺乏复制能力(细胞周期停滞)时也是如此。我们还展示了一个简单的线性适应性方案如何呈现倍数变化检测特性,以及在蛋白质状态之间的转变由系统中的其他分子种类(如磷酸酶和激酶)介导的情况下遍历性的破坏是如何普遍存在的。