噬菌体感染细菌调控网络的构建与分析

One of the most important frontier scientific issues is to study self-organized phenomena of biology from the aspect of nonlinear dynamics and nonequilibrium thermodynamics. The project is going to systematically study the regulatory network of bacteria infected by phage. Firstly, we will use nonlinear differential equations to construct the model of gene regulatory network of Escherichia coli infected by lambda phage. We will focus on the regulatory mechanism of early regulatory proteins from infection to lysogeny or lysis and the influence to lysis/lysogeny switch by proteins CII, CIII, Q and N. Secondly, from the thermodynamic perspective, we will detailed study the entropy and the entropy production rate of the network regulated by regulators for providing a thermodynamic foundation of this network. Finally, we will generalize the models to other network of bacteria infected by phage and compare the regulatory mechanisms. Based on these studies, a set of models to study regulatory network will be constructed. The regulatory mechanisms of the infection system chosen different fate will be revealed. The project is of great significance for studying gene regulatory network quantitatively and qualitatively.

从非线性动力学和非平衡热力学角度研究生物体的非线性自组织现象是重要的前沿科学问题。本项目拟对被噬菌体感染的细菌溶源/裂解调控网络进行系统的研究。首先，我们拟从动力学角度，利用非线性微分方程对被Lambda噬菌体感染的大肠杆菌调控网络进行建模，重点研究调控早期蛋白对"感染"到"溶源态"建立的调控机制，和CII、CIII、Q、N蛋白对溶源/裂解调控的影响；其次，拟从热力学角度，对该调控网络的热力学熵和熵产生率进行研究，给出网络稳态和热力学基础；最后，将模型推广到其它类型噬菌体侵染细菌的调控网络，并比较不同网络的调控机制。通过以上研究，将建立一套研究相关调控网络的模型，并揭示噬菌体侵染细菌选择不同生存途径的调控机制。该项目的实施对定性、定量研究基因调控网络具有重要的科学意义。

从非线性动力学和非平衡热力学角度研究生物体的非线性自组织现象是重要的前沿科学问题。本项目拟对被噬菌体感染的细菌溶源/裂解调控网络进行系统的研究。首先，我们从动力学角度，利用非线性微分方程对被 Lambda 噬菌体感染的大肠杆菌调控网络进行建模，重点研究调控早期蛋白对“感染”到“溶源态”建立的调控机制；其次，从热力学角度，对该调控网络的热力学熵进行研究，给出网络稳态和热力学基础；最后，将模型推广到突变型噬菌体侵染细菌的调控网络，并比较了不同网络的调控机制。此外，基于机器学习算法，我们构建了预测模型来识别噬菌体特殊功能蛋白，并推广到其它蛋白质和DNA调控元件的识别中。该项目的实施对定性、定量研究基因调控网络具有重要的科学意义。