RUI: Engineered Microbe Colonization and Community Response in a Model Microbial Community

微生物群落生活在人体内和周围，影响环境、食物系统和人类健康。就像稳定的人类群落一样，稳定的微生物群落由许多不同的成员组成。每个成员都追求自己的生存策略，同时以积极和消极的方式与彼此和物理环境互动，创造一个稳定的“邻里”。就像人类社区遭遇自然灾害或士绅化一样，微生物群落经常遇到自然或人为造成的破坏。该项目旨在确定和表征决定微生物群落在被破坏时是否具有弹性或延展性的特征。这个问题将通过创建微生物群落的简化模型来解决，引入新来的微生物或从基因上改变现有社区成员等干扰，然后观察这些干扰如何导致群落组成和行为发生变化。这项研究旨在揭示一般规律，从而能够更准确地预测微生物群落对干扰的反应，从而能够以有利于人类及其环境的方式设计与自然微生物群落的相互作用。这个项目将培养来自不同社会经济和文化背景的本科生。人类微生物区系和人类相互作用的环境中的微生物群落塑造人类生物学和生命。之前的观察性研究已经确定了其中一些群落的组成特征，对这些微生物群落如何与人类相互作用的机械论理解正在开始形成。然而，这些微生物群落中的成员如何相互影响的问题仍然存在。生物工程有可能将基因设计的微生物引入人类和环境社区，以改善和修改它们的功能，但关于微生物群落行为和设备工程的基本问题仍未得到解答。例如，转基因生物能否进入现有社区并成为其成员？管理生物体如何自然进入或离开群落的规则尚不清楚。一旦到了那里，社区将如何影响遗传设备的行为，反之亦然？这些问题将通过首先开发体外微生物群落模型从机械上解决，范围从批次培养中生长的代表生物对到连续培养中生长的复杂环境接种物。与现有的体内模型相比，这些体外模型将允许进行廉价和快速的实验。然后，引入新的微生物，并通过RNA-SEQ识别模式群落组成和基因表达的变化。TN-SEQ筛查将确定成功的新来者微生物在模式群落中建立自己的机制。同时，将构建常用的启动子和报告基因，并在RNA和蛋白质水平上量化它们的表现，并将其与纯培养和社区培养进行比较。这些数据将被用来揭示为微生物群落中的最佳功能而调整的设备的设计规则。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Communities of microbes live in human bodies and all around, impacting the environment, the food system, and human health. Much like stable human communities, stable microbial communities are composed of many different members. Each member pursues their own strategies for survival, while at the same time interacting with each other and the physical environment in positive and negative ways to create a stable “neighborhood.” Like human communities encountering natural disasters or gentrification, microbial communities often encounter natural or human-caused disruption. This project aims to determine and characterize the features that determine if a microbial community can be resilient or malleable to change when disrupted. This question will be addressed by creating simplified models of microbial communities, introducing disruptions like newcomer microbes or genetically altering existing community members, and then seeing how the community composition and behavior changes as a result of these disruptions. This research aims to uncover general rules that will allow more accurate predictions of microbial community responses to disruptions, which will allow for the design of interactions with natural microbial communities in ways that benefit humans and their environments. This project will train undergraduate students from diverse socio-economic and cultural backgrounds.The human microbiota and the microbial communities of the environments that humans interact with shape human biology and lives. Previous observational studies have identified compositional features of some of these communities, and a mechanistic understanding how these microbial communities interact with humans is beginning to take shape. The question of how the members in these microbial communities influence each other, however, remains. Bioengineering has the potential to introduce genetically designed microorganisms to human and environmental communities to improve and modify their functions, but fundamental questions about microbe community behavior and device engineering remain unanswered. For example, can a genetically-modified organism enter an existing community and establish itself as a member? The rules that govern how organisms naturally enter or leave the community are unknown. Once there, how will the community affect the behavior of the genetic device and vice versa? These questions will be addressed mechanistically by first developing in vitro microbial community models ranging from pairs of representative organisms grown in batch culture to complex environmental inocula grown in continuous culture. These in vitro models will allow for inexpensive and rapid experimentation compared to currently existing in vivo models. Then, newcomer microbes will be introduced and changes in model community composition and gene expression will be identified through RNA-seq. Tn-seq screening will identify the mechanism by which successful newcomer microbes establish themselves in the model communities. Concurrently, commonly used promoters and reporter genes will be constructed, and their performance quantified at the RNA and protein levels and compared between pure culture and community culture. This data will be used to uncover rules for designing devices that are tuned for optimal function in microbial communities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.