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。细菌通过扩散分子和基因调控元件进行细胞间的生化交流，从而产生大规模的反应。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范围，包括高效的生物制造、生物能源转换、新型治疗策略、可持续农业和生物修复。迄今为止，已经确定了细菌群落中许多自然发生的相互作用和交流模式，但还没有能力设计出具有这些复杂相互作用和不同细菌之间动态响应的合成细菌群落。该合作项目旨在提高对自然微生物群落中可能发生的物种间生物化学细胞-细胞通信的理解，并允许我们利用这些系统在合成不同细菌群落中提供的高度复杂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。马萨诸塞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，让高中生学习研究和设计细菌群落。将为合成生物学研究培训创造许多本科生机会。这些教育活动将增加K-12 STEM教育，帮助解决女性和少数民族在合成生物学领域代表性不足的问题，并培养下一代科学家和工程师。该项目的目标是为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中的多细胞转录调控网络建立一个可推广的框架。最近在革兰氏阳性细菌中发现的同丝氨酸内酯介导的群体感应的普遍性将通过luxri型群体感应系统和模型革兰氏阳性细菌的文库来确定。这项工作将产生一套标准化的革兰氏阳性细菌群体传感器，允许控制不同细菌之间的种间交流。这些群体感应系统的序列-函数关系将通过统计设计和系统诱变来确定。利用这些群体传感器，研究小组将测试细菌群体感应进化的基本问题。一个用于研究和维持细菌群落的高通量多层微流体平台将被开发，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节网络的信号动力学。这项工作旨在使研究人员能够创造不同的细菌群落，这些细菌群落具有复杂的相互作用、可设计的种间交流和规定的动态响应。该奖项反映了美国国家科学基金会的法定使命，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.