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Collaborative Research: Enabling Scalable Redox Reactions in Biomanufacturing

Collaborative Research: Enabling Scalable Redox Reactions in Biomanufacturing
合作研究:在生物制造中实现可扩展的氧化还原反应
批准号:
2328145
负责人:
Han Li
金额:
$94.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2026-08-31

项目摘要

项目成果

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中文摘要
翻译
生物制造,即商品化学品、燃料和药品的生物合成,在美国代表着一个快速增长的行业,收入超过1500亿美元。为了在规模和经济可行性上继续增长,生物制造必须提高其碳和能源效率。然而,自然界中存在的生物合成逻辑往往不能以最高的碳或能源效率运行。情况之所以如此,是因为碳的释放需要以二氧化碳的形式存在,而能量必须以热的形式浪费,才能提供强大的热力学驱动力。克服这一挑战的一种方法是引入非自然的热力学驱动力。该项目贡献了一套非自然的化学工具,以低还原势能还原当量的形式部署比自然更强的热力学驱动力。这些工具增强了生物系统的自然能力,并导致将可再生资源转化为有价值的产品。通过综合研究和推广活动,该项目改进了生物制造,以更好地满足国家对能源、食品、大宗商品和药品的需求,并同时为STEM的本科生和研究生教育做出贡献。该项目计划通过参加实践性科学实践经验来激励K-12学生在STEM追求职业生涯的活动。目前的生物制造过程面临着一个根本性的挑战:自然界中存在的生物合成逻辑往往不能以最大的碳或能源效率运行,因为碳需要以二氧化碳的形式释放,能量需要作为热量浪费,以提供强大的热力学驱动力。为了克服这一挑战,引入了非自然的热力学驱动力。这一提议开发了非自然的辅因,以部署比自然更强的热力学驱动力。总体目标是将比NAD(P)更有效的非天然氧化还原辅因子引入到大肠杆菌的新陈代谢中,并使用它们来推动商品化学品的碳高效生物制造。这是通过设计关键酶以利用这些非天然辅因子来实现的,方法是通过跨越基因组挖掘的集成设计-构建-测试-学习工作流程,通过定向进化的高通量酶发现,工程酶的结构和生物物理研究,以及基于机器学习的数据解释,以提取管理蛋白质-辅因子相互作用的一般设计原则。该奖项由分子和细胞生物科学部的系统和合成生物学项目以及化学、生物工程、环境和运输系统部门的细胞和生化工程项目共同资助。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。
英文摘要
Biomanufacturing, the biosynthesis of commodity chemicals, fuels, and medicines, represents a fast-growing industry with over $150 billion in revenue in the US. To continue to grow in scale and economic viability, biomanufacturing must increase its carbon and energy efficiency. However, biosynthetic logics that exist in Nature often do not operate at maximal carbon or energy efficiency. This is the case because release of carbon is required as carbon dioxide and energy has to be wasted as heat to afford a robust thermodynamic driving force. One way to overcome this challenge is to introduce unnatural thermodynamic driving forces. This project contributes a suite of unnatural, chemical tools to deploy stronger-than-Nature thermodynamic driving forces in the form of low reduction-potential reducing equivalents. These tools augment the natural capability of biological systems and lead to the conversion of renewable resources into valuable products. Through the integrated research and outreach activities, the project improves biomanufacturing to better meet the Nation's needs for energy, food, commodities, and medicine and concomitantly contributes to undergraduate and graduate education in STEM. The project plans activities to motivate K-12 students to pursue a career in STEM by participating in hands-on experiences in practical science. Current biomanufacturing processes face a fundamental challenge: biosynthetic logics that exist in Nature often do not operate at maximal carbon or energy efficiency, because carbon needs to be released as carbon dioxide and energy needs to be wasted as heat to afford a robust thermodynamic driving force. To overcome this challenge, unnatural thermodynamic driving forces are introduced. This proposal develops unnatural cofactors to deploy stronger-than-Nature thermodynamic driving forces. The overall objectives are to introduce unnatural redox cofactors that are more potent reducing reagents than NAD(P) into Escherichia coli metabolism and use them to power carbon-efficient biomanufacturing of commodity chemicals. This is achieved by engineering key enzymes to utilize these unnatural cofactors through an integrated Design-Build-Test-Learn workflow spanning genome mining, high-throughput enzyme discovery with directed evolution, structural and biophysical study of the engineered enzymes, as well as machine learning-based data interpretation to distill general design principles that govern protein-cofactor interactions. A better overall understanding of how structural plasticity of the cofactors is tolerated by enzymes, advances capability beyond what Nature selected for during evolution and opens new design space for proteins.This award is co-funded by the Systems and Synthetic Biology program in the Division of Molecular and Cellular Biosciences and the Cellular and Biochemical Engineering program in the Division of Chemical, Bioengineering, Environmental and Transport SystemsThis 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.
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A Dynamical Systems Weekend Conference at Wesleyan
  • 批准号:
    2000176
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.6万
  • 财政年份:
    2020
  • 负责人:
    Han Li
  • 依托单位:
CAREER: Engineering redox metabolism using unnatural cofactors
  • 批准号:
    1847705
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.22万
  • 财政年份:
    2019
  • 负责人:
    Han Li
  • 依托单位:
Group Actions, Homogeneous Dynamics, and Number Theory
  • 批准号:
    1700109
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $14.4万
  • 财政年份:
    2017
  • 负责人:
    Han Li
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)