Collaborative Research: Model-guided design of bacterial interspecies interactions and trans-organismic communication in living intercellular circuits

环境中的细菌生活在多物种群落中，具有动态相互作用，可以带来复杂的集体行为。细菌通过可扩散分子和基因调控元件利用生化细胞间通讯来产生大规模反应。在不同细菌群落中可预测地设计多细胞反应的能力将具有广泛的应用，包括高效的生物制造、生物能源转换、新颖的治疗策略、可持续农业和生物修复。迄今为止，已经确定了细菌群落内许多自然发生的相互作用和通讯模式，但还没有能力设计出在不同细菌之间具有这些复杂的相互作用和动态响应的合成细菌群落。该合作项目旨在提高对天然微生物群落中可能发生的种间生化细胞间通讯的理解，并使我们能够利用合成多样化细菌群落中这些系统提供的高度复杂的功能作为可编程生命设备。该项目将创建合成细菌群落，用于许多有害水污染物的生物传感和生物修复，包括一些最危险的饮用水和水生生态系统污染物。该项目将为众多 K-12、本科生和研究生提供教育和研究培训。麻省大学阿默斯特分校和波士顿大学每年都会举办实践研讨会，供高中生学习如何研究和改造细菌群落。将创造许多合成生物学研究培训的本科机会。这些教育活动将增加 K-12 STEM 教育，帮助解决合成生物学领域女性和少数族裔代表性不足的问题，并培训下一代科学家和工程师。该项目的目标是建立一个通用框架，用于设计分布在含有革兰氏阴性和革兰氏阳性细菌的细菌群落内的多细胞转录调控网络。最近发现的革兰氏阳性细菌中高丝氨酸内酯介导的群体感应的普遍性将使用 LuxRI 型群体感应系统和模型革兰氏阳性细菌的文库来确定。这项工作将为革兰氏阳性细菌生成一套标准化群体传感器，从而控制不同细菌之间的种间通讯。这些群体感应系统的序列-功能关系将通过统计设计和系统诱变来确定。使用这些群体传感器，该团队将测试有关细菌群体感应进化的基本问题。将开发用于研究和维护细菌群落的高通量多层微流体平台，以分析单细胞分辨率的时间信号。该平台将用于开发参数和模型数据库，以预测这些分布式转录调控网络的信号动态。这项工作旨在使研究人员能够创建具有复杂相互作用、可设计的种间通讯和规定的动态响应的多样化细菌群落。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Bacteria in the environment live in multispecies communities with dynamic interactions that can bring about complex collective behaviors. Bacteria use biochemical cell-to-cell communication via diffusible molecules and gene regulatory elements to bring about large-scale responses. The ability to predictably design multicellular responses in diverse bacterial communities would have a wide range of applications including efficient biomanufacturing, bioenergy conversion, novel therapeutic strategies, sustainable agriculture, and bioremediation. To date, numerous naturally occurring interactions and modes of communication within bacterial communities have been identified, yet there is not the ability to engineer synthetic bacterial communities that have these complex interactions and dynamic responses among diverse bacteria. This collaborative project aims to improve understanding of interspecies biochemical cell-cell communication that can occur in natural microbial communities and allow us to leverage the highly complex functions afforded by these systems within synthetic diverse bacterial communities as programmable living devices. This project will create synthetic bacterial consortia for biosensing and bioremediation of many hazardous water contaminants, including some of the most dangerous drinking water and aquatic ecosystem contaminants. This project will provide education and research training for numerous K-12, undergraduate, and graduate students. Hands-on workshops will be run at UMass Amherst and Boston University each year for high school students to learn about studying and engineering bacterial communities. Many undergraduate opportunities for synthetic biology research training will be created. These educational activities will increase K-12 STEM education, help address the underrepresentation of women and minorities in synthetic biology, and train the next generation of scientists and engineers. The goal of this project is to establish a generalizable framework for the design of multicellular transcriptional regulatory networks distributed within bacterial communities containing gram-negative and gram-positive bacteria. The universality of recent discoveries of homoserine lactone-mediated quorum sensing in gram-positive bacteria will be determined using libraries of LuxRI-type quorum sensing systems and model gram-positive bacteria. This work will generate a set of standardized quorum sensors for gram-positive bacteria that allow for controlling interspecies communication between diverse bacteria. The sequence-function relationship for these quorum sensing systems will be determined using statistical design and systematic mutagenesis. Using these quorum sensors, the team will test fundamental questions about the evolution of quorum sensing in bacteria. A high-throughput multilayer microfluidics platform for studying and maintaining bacterial communities will be developed to analyze temporal signaling at single-cell resolution. This platform will be used to develop a database of parameters and models to predict the signaling dynamics of these distributed transcriptional regulatory networks. This work aims to enable researchers to create diverse bacterial communities that have complex interactions, designable interspecies communication, and prescribed dynamic responses.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.