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ERA SynBio: A Unified Nucleic Acid Computation System (UNACS) for Organisms

ERA SynBio: A Unified Nucleic Acid Computation System (UNACS) for Organisms
ERA SynBio:生物体统一核酸计算系统 (UNACS)
批准号:
1541244
负责人:
Andrew Ellington
金额:
$54.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-08-01 至 2019-07-31

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中文摘要
翻译
合成生物学是一门新兴学科,它通过利用工程原理和计算方法来帮助寻找重要生物学问题的答案,并为许多社会需求激发可持续的生物制造解决方案。该项目结合了尖端的专业知识,以创建可编程的,高性能的,基于核酸的调节设备,可以通过对细菌代谢(生命的化学反应)的工作针对特定应用进行优化。这项研究有助于为生物体编程的能力奠定基础,并有望在包括纳米技术、绿色技术和生物经济在内的科学技术领域产生革命性的变化。基于核酸的调控元件通过利用可预测的沃森-克里克碱基配对来控制细胞行为,并通过利用用于预测分子结构及其相互作用的复杂软件工具,为合成生物学中的关键瓶颈问题提供了解决方案。定向蛋白质进化的新发展促使这些技术在活生物体中执行“基于统一核酸的计算”(UNACS)的更广泛适用性的调查。在这项提案中,研究小组提出要确定生物体中基于核糖核酸调节子的计算的基本原理,并展示基于复杂核酸的电路在原核生物和高等生物中代谢物控制的应用。这些工具和方法将为合理设计在生物体中发挥作用的电路元件提供精确的配方,作为生物技术转型的步骤。UNACS适合于标准化、抽象化和扩展。这些都是生物系统真正的“工程”和“重新编程”的重要先决条件,这是合成生物学充分发挥其潜力所必不可少的。该项目由美国国家科学基金会和欧洲资助机构之间的跨国资助机制资助,这些机构是欧洲委员会认可的合成生物学研究领域网络的一部分。该项目的美国部分由系统和合成生物学(生物科学理事会)以及生物技术和生物化学工程(工程理事会)方案共同资助。
英文摘要
Synthetic Biology is an emerging discipline that distinguishes itself by drawing on engineering principles and computational methods to help find the answers to vital biological questions, and to inspire sustainable biomanufacturing solutions for many societal needs. This project combines cutting-edge expertise to create programmable, high-performance, nucleic acid-based regulatory devices that can be optimized for specific applications through work on a bacterium's metabolism (the chemical reactions of life). This research contributes to the groundwork underlying the ability to program living organisms, and is anticipated to produce transformative changes in science and technology encompassing nanotechnology, green technology, and the bioeconomy. Nucleic-acid-based regulatory elements offer a solution to a critical bottleneck problem in synthetic biology by taking advantage of predictable Watson-Crick base pairing to control cell behavior, and by harnessing sophisticated software tools used to predict molecular structures and their interactions. New developments in directed protein evolution prompted this investigation of the broader applicability of these techniques to perform "Unified Nucleic-Acid based Computation" (UNACS) in living organisms. In this proposal, the team proposes to identify the fundamental principles of riboregulator-based computation in living organisms and to demonstrate the application of complex nucleic-acid based circuits for metabolite control in prokaryotes and higher organisms. These tools and approaches will represent a precise recipe for rational design of circuit elements that function in living organisms as steps towards transformation of biotechnology. UNACS lends itself to standardization, abstraction, and scaling. These are all important pre-requisites for genuine "engineering" and "reprogramming" of biological systems, which are essential for synthetic biology to realize its full potential.This project is funded through a transnational funding mechanism between the United States National Science Foundation and European Funding Agencies that are part of the European Commission endorsed Research Area Network in Synthetic Biology. The United States component of this project was co-funded by programs in Systems and Synthetic Biology (Directorate for Biological Sciences) and Biotechnology and Biochemical Bioengineering (Directorate for Engineering).
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SemiSynBio-III: Precision assembly and electronic properties of protein nanowire circuits using DNA origami
  • 批准号:
    2227399
  • 项目类别:
    Standard Grant
  • 资助金额:
    $149.85万
  • 财政年份:
    2022
  • 负责人:
    Andrew Ellington
  • 依托单位:
Collaborative Research: Synthetic and Systems Biology Approaches to Semi-synthetic Cells with Expanded DNA Alphabets
  • 批准号:
    2123996
  • 项目类别:
    Standard Grant
  • 资助金额:
    $129.97万
  • 财政年份:
    2021
  • 负责人:
    Andrew Ellington
  • 依托单位:
RAPID: Development of Rapid Point of Care SARS-CoV-2 Detection System
  • 批准号:
    2027169
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2020
  • 负责人:
    Andrew Ellington
  • 依托单位:
I-Corps: Structure Based Machine Learning Aided Protein Engineering
  • 批准号:
    1929560
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2019
  • 负责人:
    Andrew Ellington
  • 依托单位:
海外基金