CAREER: Programmable synthetic microbial consortia for complex multicellular functions

工程混合细胞群在生物制造、细胞治疗和诊断方面具有潜在的应用前景。细菌的代谢是一个高度反应的网络，不同的反应在不同的时间发生。它们由内部和外部产生的信号打开和关闭。通过这种方式，细胞可以通过特定的反应途径对碳源和其他物质的流动做出有效的决定。对细胞群进行工程改造的尝试尚未取得可比的控制效果。这个项目的重点是为混合微生物控制系统的设计制定一个协议。该协议将指导构建有助于实施控制系统的遗传成分。这些成分将在各种生物体中进行评估。该项目的核心目标是教育和指导多样化的未来劳动力。将制定和实施K-12 STEM教育计划，并为代表性不足的群体扩大研究机会。与自然发生的动态途径表达类似，计算动态代谢模型通过离散代谢状态和时间酶激活来预测优化的生物生产。这在生物生产微生物群体中是无法实现的。提出的研究目标是为细菌联合体的自动化设计建立一个通用的平台。用户将能够动态控制新陈代谢，并根据用户定义的时间信号指定协调的多细胞反应。该项目将开发遗传电路组件和电路设计算法，用于在工程细菌群落中划分顺序逻辑电路，并确定合成微生物群落中生物顺序逻辑编程的设计原则。拟议的研究将生产与自动设计算法和细菌细胞间信号的物理质粒兼容的电路元件。这将使研究人员能够利用现成的部件来先验地设计多细胞遗传电路，从而在微生物群体中实现时间转录控制。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。

Engineered mixed cell populations have potential application in biomanufacturing, cell-based therapies, and diagnostics. Bacterial metabolism is a highly reactive network, and different reactions occur at different times. They are turned on and off by signals generated internally and externally. In this way the cell can make effective decisions regarding the flow of carbon sources and other materials through specific reaction pathways. Attempts to engineer cell populations have not achieved comparable control. This project will focus on developing a protocol for the design of control systems for mixtures of microbes. The protocol will guide the construction of genetic components that can help implement the control system. These components will be evaluated in a variety of organisms. A core objective of this project is to educate and mentor a diverse future workforce. Programs for K-12 STEM education and to broaden research opportunities for underrepresented groups will be developed and implemented.Similar to naturally-occurring dynamic pathway expression, computational dynamic metabolic modeling predicts optimized bioproduction by discrete metabolic states and temporal enzyme activation. This has not been achievable within bioproduction microbial consortia. The goal of the proposed research is to establish a generalizable platform for the automated design of bacterial consortia. Users will be able to dynamically control metabolism and specify coordinated multicellular responses to user-defined temporal signals. This project will develop genetic circuit components and a circuit design algorithm for partitioning sequential logic circuits within engineered bacterial communities, and identify design principles for biological sequential logic programming in synthetic microbial consortia. The proposed research will produce circuit components that are compatible with automated design algorithms and physical plasmids for bacterial intercellular signaling. This will enable researchers to utilize off-the-shelf parts for a priori design of multicellular genetic circuits that implement temporal transcription control in microbial consortia.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.