Unifying synthetic small regulatory RNAs

RNA通常被认为是携带来自DNA的遗传指令的信使，然而，许多小RNA充当控制基因表达的调节剂。在过去的二十年里，研究人员已经设计了这种调控RNA，并在细菌中构建了简单的基于RNA的遗传电路，然而，构建复杂的基于RNA的遗传电路仍然具有挑战性。该项目涉及开发可推广的设计原则，通过这些原则，可以将简单的基于RNA的遗传电路结合起来，生成复杂的遗传电路。这些复杂电路的实用性通过工程细菌来证明，这些细菌产生有助于生物经济的有价值的化学物质。此外，该项目为学生提供了独特的跨学科培训机会，涉及生物物理学，生物化学，分子生物学和工程学。一个推广计划为K-12教师提供材料，引导学生通过实验室活动，扩大学生对科学和工程的参与。过去二十年，通过自下而上构建更简单的遗传电路，在理解复杂的基因调控网络方面取得了显着进展。然而，基于RNA的遗传电路很少通过整合控制基因表达的多个步骤的不同类型的RNA调节剂（例如，转录和翻译）。因此，基于RNA的电路复杂性是有限的。在这个项目中，研究人员首先构建了基于RNA的基因表达控制器（GECs），这些控制器表现出一致的可预测行为，而不管连接的遗传部分如何。数学建模与实验表征相结合，以系统地将不同的传感器连接到RNA调节器。接下来，首先通过定量表征集成的遗传程序和单个GEC，然后通过比较它们集成前后的行为来深入了解电路集成规则。最后，基于收集的设计规则，创建动态通路控制器来自主调节代谢通路，从而展示增强的生化生产。这个跨学科的项目为研究界提供了一个统一的、标准化的RNA调节工具箱，用于基础研究和生物技术应用。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。

RNA is generally known as a messenger to carry genetic instructions from DNA, however, many small RNAs act as regulators controlling gene expression. Over the past two decades, researchers have engineered such regulatory RNAs and have built simple RNA-based genetic circuits in bacteria, nevertheless, the construction of complex RNA-based genetic circuits remains challenging. This project involves developing generalizable design principles by which simple RNA-based genetic circuits can be combined to generate complex genetic circuits. The utility of these complex circuits is demonstrated by engineering bacteria that produce valuable chemicals that contribute to the bioeconomy. In addition, this project provides unique interdisciplinary training opportunities for students, involving biophysics, biochemistry, molecular biology and engineering. An outreach program provides K-12 teachers with the materials to lead their students through lab activities, broadening student participation in science and engineering.The past two decades have witnessed remarkable progress in understanding complex gene regulatory networks by building simpler genetic circuits from the bottom-up. However, RNA-based genetic circuits have seldom been built by integrating different types of RNA regulators that control multiple steps of gene expression (e.g., both transcription and translation). Consequently, RNA-based circuit complexity is limited. In this project, the investigators first build RNA-based gene expression controllers (GECs) that demonstrate consistently predictable behaviors regardless of connected genetic parts. Mathematical modeling is combined with experimental characterization in order to systematically connect different sensors to RNA regulators. Next, insights into the circuit integration rule are obtained first by quantitatively characterizing both integrated genetic programs and individual GECs then by comparing their behaviors before and after integration. Finally, based on the gathered design rules, dynamic pathway controllers are created to autonomously modulate metabolic pathways, demonstrating enhanced biochemical production. This interdisciplinary project provides the research community with a unified, standardized RNA regulator toolbox for fundamental research and biotechnological applications.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.