关于细菌逃避中性粒细胞追逐的最优策略研究

项目名称： 关于细菌逃避中性粒细胞追逐的最优策略研究

项目编号： No.11504399

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 数理科学和化学

项目作者： 傅雄飞

作者单位： 中国科学院深圳先进技术研究院

项目金额： 21万元

中文摘要： 追逐与逃逸是最常见一对矛盾体之一。在自然界中，追与逃的策略关系到捕食者的狩猎成败与被掠食者的生死。中性粒细胞与细菌两种细胞通过感知对方分泌的趋化因子浓度梯度实现追逐与逃逸。不同于中性粒细胞通过自身极化实现定向运动，细菌的逃逸是以有偏向性的随机游动形式实现的趋化运动。以往关于细菌趋化运动的定量研究常局限于相对稳定的简单外界环境中。然而，细菌在逃避的中性粒追逐的过程所面对的外界浓度梯度是一个由追踪者时空位置决定的动态场。对于细菌采取何种逃逸策略, 仍然是个迷团。本课题拟围绕中性粒细胞与细菌追与逃的过程，通过光学轨迹跟踪，调控趋化能力等手段分析细菌逃避策略。另外，我们还将构建描述中性粒细胞和细菌的信号传导及相互作用的模型，分析细菌的最优逃避策略。本研究不仅会加深对细菌与免疫细胞的相互作用的认识，还将有助于博弈论、最优化等领域对追逐与逃逸策略的研究。

中文关键词： 定量生物学；趋化运动；最优化；基于主体的模型；追逐与逃逸

英文摘要： Pursuit and evasion are a common pair of exclusive behaviors. In nature, the strategy of pursuit-evasion play a critical role in predator foraging, prey survival. In the pursuit and evasion behaviors of neutrophil and bacteria, each side can sense the gradient of chemotactic signal secreted by the other side. Unlike the directional motion of neutrophil which is realized by polarization of its body, bacteria can only adopt biased run-and-tumble random walks to perform chemotaxis away from the neutrophil. Previous quantitative studied about bacterial chemotaxis were always assumed stable and simple external signal environments. However, when the bacteria evades away from the neutrophil, the gradient it faces is a dynamical field determined by the spatiotemporal position of the neutrophil. The strategy how the bacteria escape is still a mystery. In this project, we will focus on the pursuit and evasion behaviors between neutrophil and bacteria, and analyze evasion strategy of bacteria by optical tracing, genetic control of chemotactic ability, etc. Besides, we will also build agent-based models by using the knowledge of signal transductions and the interaction between the two types of cells, so as to analyze the optimal strategy to evade. This project will not only enable us tackle problems related to interaction between bacteria and immune cells, but also help the pursuit-evasion strategy study in game theory, optimization, and other fields.

英文关键词： Quantitative biology;Chemotaxis;Optimization;Agent-based model;Pursuit and evasion