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器。在过去的二十年里，研究人员已经设计了这样的调控RNA，并在细菌中建立了简单的基于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。这个项目涉及开发可推广的设计原则，根据这些原则，简单的基于RNA的遗传电路可以组合在一起，产生复杂的遗传电路。这些复杂电路的效用被工程细菌证明，这些细菌产生对生物经济有贡献的有价值的化学物质。此外，该项目还为学生提供了独特的跨学科培训机会，涉及生物物理、生物化学、分子生物学和工程学。一个外展项目为K-12教师提供了指导学生完成实验室活动的材料，扩大了学生对科学和工程的参与。过去20年，通过自下而上构建更简单的基因电路，在理解复杂的基因调控网络方面取得了显著进展。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(例如，转录和翻译)的不同类型的RNA调节器来构建。因此，基于RNA的电路复杂性是有限的。在这个项目中，研究人员首先建立了基于RNA的基因表达控制器(GEC)，它展示了一致的可预测行为，而不考虑相连的遗传部分。数学建模与实验表征相结合，以便系统地将不同的传感器连接到RNA调节器。接下来，首先通过对集成的遗传程序和单个GEC进行定量描述，然后通过比较它们在集成前后的行为来获得对电路集成规则的洞察。最后，基于收集的设计规则，创建了动态途径控制器来自主调节代谢途径，展示了增强的生化生产。这一跨学科项目为基础研究和生物技术应用提供了统一、标准化的RNA调节工具箱。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.