Collaborative Research: RUI: Broadening the Application of Programmed Evolution for Metabolic Engineering

代谢工程中的设计考虑一直基于对作用于工程菌群体的进化力量的不完全理解。这个项目通过利用而不是对抗进化来逆转新陈代谢工程范式。研究人员开发了一种代谢工程的进化方法，使细菌能够整合他们的生长环境和他们的工程代谢。这种方法被称为编程进化，因为细菌种群是用DNA软件编程来计算代谢途径优化问题的解决方案，而进化是用来引导细菌种群走向最优解决方案。该项目的目标是通过开发一种新的发现核糖开关的新方法，使用新的核糖开关以最佳方式表达产生新化合物所需的酶，并开发数学模型和计算工具来支持这两个过程，从而扩大编程进化。这些方法将降低代谢工程细菌生产有用化合物的成本，用于能源、制药和生物修复。该项目将增加科学教育的多样性，为具有竞争力和科学素养的劳动力做出贡献，并有可能提高美国的经济竞争力。在本科生提出研究问题、开发可检验的假设、收集和分析数据以及交流结果时，该项目响应了《愿景与变革》中对更真实的本科生研究体验的呼吁。随着他们学习如何为代谢工程规划细菌的进化，本科生将学习如何作为有科学素养的公民、教育工作者和研究科学家规划他们自己未来的课程。编程进化是一个用于优化细菌中正交代谢途径的模块系统。它使用组合学、适应性和生物传感器模块，这些模块可以单独开发和测试，组合使用，并在研究小组之间共享。程序化进化的一个关键组成部分是核糖开关，它将代谢输出转化为适合性基因表达和选择优势。大多数用于代谢工程的核糖开关结合了通过指数富集法进行配体系统进化的体外过程中发现的RNA适配子。然而，在体外发现的适体很少在体内发挥作用。研究人员建议开发基于细胞的指数浓缩作为一种新的体内方法，以发现在细菌细胞中具有可预测功能的核糖开关。这种新方法在核糖开关中引入遗传变异来产生文库，应用负选择和正选择，并表征新核糖开关的表型和基因型。新方法的重要性来自于它有潜力促进对自然发生的核糖开关的了解，并发现新的核糖开关在能源、制药和生物修复方面的应用。

Design considerations during metabolic engineering have been based on incomplete understanding of the evolutionary forces acting upon populations of engineered bacteria. This project inverts the metabolic engineering paradigm by harnessing evolution instead of fighting it. The investigators developed an evolutionary approach to metabolic engineering that enables bacteria to integrate their growth environment and their engineered metabolism. The approach is called Programmed Evolution because a population of bacteria is programmed with DNA software to compute solutions to a metabolic pathway optimization problem, and evolution is used to direct the bacterial population toward optimal solutions. The goal of this project is to expand Programmed Evolution by developing a new method for new riboswitch discovery, using the new riboswitches optimally express the enzymes necessary for e the production of new compounds, and developing mathematical models and computational tools to support both processes. These approaches will reduce the cost of producing useful compounds in metabolically engineered bacteria for applications in energy, pharmaceuticals, and bioremediation. This project will increase diversity for science education, contribute to a competitive and scientifically literate workforce, and has the potential to improve American economic competitiveness. This project responds to the call in Vision and Change for more authentic undergraduate research experiences as undergraduates pose research questions, develop testable hypotheses, collect and analyze data, and communicate results. As they learn how to program the evolution of bacteria for metabolic engineering, undergraduate research students will learn how to program the course of their own futures as science literate citizens, educators, and research scientists.Programmed Evolution is a modular system for the optimization of orthogonal metabolic pathways in bacteria. It uses combinatorics, fitness, and biosensor modules that can be developed and tested separately, used in combinations, and shared among research groups. A key component of Programmed Evolution is the riboswitch that transduces metabolic output into fitness gene expression and selective advantage. Most riboswitches used in metabolic engineering incorporate RNA aptamers discovered by the in vitro process of Systematic Evolution of Ligands by Exponential enrichment. However, aptamers discovered in vitro rarely function in vivo. The investigators propose to develop Cell-based Exponential enrichment as a new in vivo method of discovering riboswitches that function predictably in bacterial cells. The new method introduces genetic variation in a riboswitch to produce a library, applies negative and positive selection, and characterizes the phenotype and genotype of new riboswitches. The significance of the new approach derives from its potential to advance knowledge of naturally occurring riboswitches and to discover new riboswitches for applications in energy, pharmaceuticals and bioremediation.