Demirkıran Gökhan, Kalaycı Demir Güleser, Güzeliş Cüneyt
Department of Electrical-Electronics Engineering, Yaşar University, Bornova, İzmir, 35100, Turkey.
The Graduate School of Natural and Applied Sciences, Dokuz Eylül University, Buca, İzmir, 35160, Turkey.
IET Syst Biol. 2018 Aug;12(4):138-147. doi: 10.1049/iet-syb.2017.0077.
p53 network, which is responsible for DNA damage response of cells, exhibits three distinct qualitative behaviours; low state, oscillation and high state, which are associated with normal cell cycle progression, cell cycle arrest and apoptosis, respectively. The experimental studies demonstrate that these dynamics of p53 are due to the ATM and Wip1 interaction. This paper proposes a simple two-dimensional canonical relaxation oscillator model based on the identified topological structure of ATM and Wip1 interaction underlying these qualitative behaviours of p53 network. The model includes only polynomial terms that have the interpretability of known ATM and Wip1 interaction. The introduced model is useful for understanding relaxation oscillations in gene regulatory networks. Through mathematical analysis, we investigate the roles of ATM and Wip1 in forming of these three essential behaviours, and show that ATM and Wip1 constitute the core mechanism of p53 dynamics. In agreement with biological findings, we show that Wip1 degradation term is a highly sensitive parameter, possibly related to mutations. By perturbing the corresponding parameters, our model characterizes some mutations such as ATM deficiency and Wip1 overexpression. Finally, we provide intervention strategies considering our observation that Wip1 seems to be an important target to conduct therapies for these mutations.
负责细胞DNA损伤反应的p53网络呈现出三种不同的定性行为:低状态、振荡和高状态,它们分别与正常细胞周期进程、细胞周期停滞和细胞凋亡相关。实验研究表明,p53的这些动态变化是由于ATM和Wip1的相互作用。本文基于所确定的ATM和Wip1相互作用的拓扑结构,提出了一个简单的二维规范弛豫振荡器模型,该拓扑结构是p53网络这些定性行为的基础。该模型仅包含具有已知ATM和Wip1相互作用可解释性的多项式项。所引入的模型有助于理解基因调控网络中的弛豫振荡。通过数学分析,我们研究了ATM和Wip1在形成这三种基本行为中的作用,并表明ATM和Wip1构成了p53动态变化的核心机制。与生物学发现一致,我们表明Wip1降解项是一个高度敏感的参数,可能与突变有关。通过扰动相应参数,我们的模型表征了一些突变,如ATM缺陷和Wip1过表达。最后,考虑到我们观察到Wip1似乎是针对这些突变进行治疗的重要靶点,我们提供了干预策略。