Spontaneous Organization of Phenotypes during Collective Migration

项目摘要 细菌生活在结构化的群落中，在那里个体之间的协调互动往往会导致 有利于公众的集体行为。同时，即使是同基因的细菌也表现出表型 异质性，这使个体行为多样化，并增强了群体在意外情况下的韧性 情况。了解多样性和集体行为的相互作用如何有助于空间组织 细胞群体的功能是细胞生物学中的一个基本问题，一直难以解决 由于难以在多个尺度上测量和建模过程，因此在实验和理论上都是如此。 在这里，我们关注的是运动性和趋化能力的表型多样性如何对空间 细菌种群在不同环境中迁移时的组织和表型组成。 我们的出发点是我们和其他人最近的发现，当追逐引诱剂的旅行前线时 细菌是由它们自己的消耗产生的，它们会自发地沿着旅行的梯度进行排序：高- 执行表型定位在信号(梯度陡度)较弱和性能较低的前端 表型在背部，信号越强，落后的风险就越高。因此，领导者-追随者 表型的组织出现了，即使在同基因的人群中，也是由领导人推动迁移和 追随者脱离并在移动的前线后面殖民空间。 这些观察提出了以下基本问题：1)表型是如何自我重组的 人们遇到了不同的环境，在那里最好的表型现在不同了？什么 这是否告诉我们单个基因作为一个群体在多个环境中导航的能力？ 2)细胞生长在多大程度上可以部分补偿细胞的渗漏，这如何影响 流动人口的表型组成和组织？3)空间分选在多大程度上 运动性和趋化性表型、毒力因子的种子空间组织倾向于共调控？ 为了解决这些问题，我们将开发新的集体细菌迁移的数学模型 包括三个关键因素：表型的连续体、细胞生长和多样化的环境。约束的步骤 模型中，我们将使用大肠杆菌趋化性，因为它有很好的特性，定位于我们发现一般 原理和铜绿假单胞菌，这是一种机会致病菌，具有大肠杆菌趋化性的一些特征 但表达了通过不同环境迁移所必需的两个不同的定子系统。

Project Summary Bacteria live in structured communities where coordinated interactions between individuals often result in collective behaviors beneficial to the population. At the same time, even isogenic bacteria display phenotypic heterogeneity, which diversifies individual behavior and enhances the resilience of the population in unexpected situations. Understanding how the interplay of diversity and collective behavior contributes to spatial organization and function in cell populations is a fundamental problem in cell biology that has been difficult to tackle experimentally and theoretically because of difficulties in measuring and modeling processes at multiple scales. Here we focus on how phenotypic diversity in motility and chemotactic ability contributes to the spatial organization and phenotypic composition of a population of bacteria as it migrates through diverse environments. Our starting point is the recent discovery by us and others that when chasing traveling fronts of attractant generated by their own consumptions, bacteria spontaneously sort themselves along the traveling gradient: high- performing phenotypes localize at the front where the signal (gradient steepness) is weaker and low-performing phenotypes at the back where the signal is stronger but the risk of falling behind is higher. Thus, a leader-follower organization of the phenotypes emerges, even in isogenic populations, with leaders driving the migration and followers falling off and colonizing space behind the moving front. These observations raise the following basic questions: 1) How do phenotypes reorganize themselves when the population encounters a different environment where the most performant phenotype is now different? What does that tell us about the capacity of a single genotype to navigate as a group through multiple environment? 2) To what extent can cell growth partially compensate for the leakage of cells and how does this affect the phenotypic composition and organization of the migrating population? 3) To what extent does the spatial sorting of motility and chemotaxis phenotypes seed spatial organization of virulence factors that tend to be coregulated? To address these questions, we will develop new mathematical models of collective bacterial migration that include three key ingredients: a continuum of phenotypes, cell growth, and diverse environments. To constrain models, we will use E. coli chemotaxis because it is well-characterized, positioning us to discover general principles, and P. aeruginosa, an opportunistic pathogen that shares some features of the E. coli chemotaxis pathway but expresses two different stator systems necessary for migration through different environments.