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，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与细胞的通讯来产生大规模的反应。在不同的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，包括有效的生物制造，生物能源转化，新型治疗策略，可持续农业和生物修复。迄今为止，已经鉴定了细菌群落内许多自然发生的相互作用和通信模式，但还没有能力设计合成细菌群落，这些细菌群落在不同的细菌之间具有这些复杂的相互作用和动态响应。该合作项目旨在提高对自然微生物群落中可能发生的种间生化细胞间通信的理解，并使我们能够利用这些系统在合成的多种细菌群落中提供的高度复杂的功能作为可编程的生活设备。该项目将创建合成细菌联合体，用于许多危险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。每年将在马萨诸塞大学阿默斯特分校和波士顿大学为高中生举办实践研讨会，学习研究和工程细菌群落。将创造许多合成生物学研究培训的本科生机会。这些教育活动将增加K-12 STEM教育，帮助解决合成生物学中女性和少数民族代表性不足的问题，并培养下一代科学家和工程师。该项目的目标是建立一个通用的框架，用于设计分布在包含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。最近发现的高丝氨酸内酯介导的群体感应在革兰氏阳性菌的普遍性将确定使用LuxRI型群体感应系统和模型革兰氏阳性菌库。这项工作将产生一套标准化的革兰氏阳性细菌的群体传感器，允许控制不同细菌之间的种间通信。这些群体感应系统的序列-功能关系将使用统计设计和系统诱变来确定。利用这些群体感应器，研究小组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，以单细胞分辨率分析时间信号。该平台将用于开发参数和模型的数据库，以预测这些分布式转录调控网络的信号动力学。这项工作的目的是使研究人员能够创造出具有复杂相互作用、可设计的种间通信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知识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.