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
基本信息
- 批准号:2328145
- 负责人:
- 金额:$ 94万
- 依托单位:
- 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
- 起止时间:2023-09-01 至 2026-08-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
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.
生物制造,即商品化学品、燃料和药品的生物合成,是一个快速增长的行业,在美国的收入超过 1500 亿美元。为了继续扩大规模和经济可行性,生物制造必须提高其碳效率和能源效率。然而,自然界中存在的生物合成逻辑通常不能以最大碳或能源效率运行。之所以如此,是因为需要以二氧化碳的形式释放碳,并且必须以热量的形式浪费能量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。该项目提供了一套非自然的化学工具,以低还原电位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、商品和医药的需求,同时为 STEM 本科和研究生教育做出贡献。该项目计划开展活动,激励 K-12 学生通过参与实用科学的实践经验来从事 STEM 职业。当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通常不能在最大碳或能量效率下运行,因为碳需要以二氧化碳的形式释放,能量需要以热量的形式浪费,以提供强大的热力学驱动力。为了克服这一挑战,引入了非自然热力学驱动力。该提案开发了非自然辅助因子来部署比自然更强的热力学驱动力。总体目标是将非天然氧化还原辅助因子(比 NAD(P) 更有效的还原剂)引入大肠杆菌代谢中,并利用它们为商品化学品的碳高效生物制造提供动力。这是通过设计关键酶来利用这些非天然辅因子来实现的,通过集成的设计-构建-测试-学习工作流程,涵盖基因组挖掘、高通量酶发现与定向进化、工程酶的结构和生物物理研究以及机器学习基于数据解释,提炼出控制蛋白质-辅因子相互作用的一般设计原则。更好地全面了解酶如何耐受辅因子的结构可塑性,提高了超出自然在进化过程中选择的能力,并为蛋白质开辟了新的设计空间。该奖项由系统与合成生物学项目共同资助化学、生物工程、环境和运输系统部门的分子和细胞生物科学以及细胞和生物化学工程项目该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值进行评估,被认为值得支持以及更广泛的影响审查标准。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Han Li其他文献
Hierarchical Graph Networks for 3D Human Pose Estimation
用于 3D 人体姿势估计的分层图网络
- DOI:
- 发表时间:
2021-11-23 - 期刊:
- 影响因子:0
- 作者:
Han Li;Bowen Shi;Wenrui Dai;Yabo Chen;Botao Wang;Yu Sun;Mingzhe Guo;Chenlin Li;Junni Zou;H. Xiong - 通讯作者:
H. Xiong
Foreign Direct Investment, Environmental Regulation and Environmental Pollution
外商直接投资、环境规制与环境污染
- DOI:
- 发表时间:
2024-09-14 - 期刊:
- 影响因子:0
- 作者:
Han Li - 通讯作者:
Han Li
The Design and Construction of the Roof Greening in the Building Energy Efficiency Demonstration Project
建筑节能示范工程屋顶绿化设计与施工
- DOI:
10.1016/j.compag.2020.105840 - 发表时间:
2024-09-14 - 期刊:
- 影响因子:0
- 作者:
Han Li - 通讯作者:
Han Li
Novel high-purity struvite crystallization method for phosphate recovery from simulated swine wastewater using activated talcum
使用活性滑石从模拟猪废水中回收磷酸盐的新型高纯度鸟粪石结晶方法
- DOI:
10.1016/j.jclepro.2024.142133 - 发表时间:
2024-04-01 - 期刊:
- 影响因子:11.1
- 作者:
Linlong Li;Han Li;Haiming Huang;Xiaotong Kuang;Leyao Tao;Caiying Zhu - 通讯作者:
Caiying Zhu
A wide-beam NCS algorithm for multi-receiver SAS based on azimuth spectrum superposition
基于方位谱叠加的多接收机SAS宽波束NCS算法
- DOI:
10.3389/fmars.2023.1253105 - 发表时间:
2023-10-24 - 期刊:
- 影响因子:3.7
- 作者:
Mingqiang Ning;Heping Zhong;Han Li;Mengbo Ma;Lili Dai;Jinsong Tang - 通讯作者:
Jinsong Tang
Han Li的其他文献
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{{ truncateString('Han Li', 18)}}的其他基金
A Dynamical Systems Weekend Conference at Wesleyan
卫斯理学院动力系统周末会议
- 批准号:
2000176 - 财政年份:2020
- 资助金额:
$ 94万 - 项目类别:
Standard Grant
CAREER: Engineering redox metabolism using unnatural cofactors
职业:使用非天然辅助因子工程氧化还原代谢
- 批准号:
1847705 - 财政年份:2019
- 资助金额:
$ 94万 - 项目类别:
Standard Grant
Group Actions, Homogeneous Dynamics, and Number Theory
群作用、齐次动力学和数论
- 批准号:
1700109 - 财政年份:2017
- 资助金额:
$ 94万 - 项目类别:
Continuing Grant
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