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: $ 94万
• 依托单位: University of California-Irvine
• 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: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328145&HistoricalAwards=false
• 关键词: Collaborative; Research; Enabling; Scalable; Redox

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，商品化学品，燃料和药物的生物合成，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和能源效率。然而，自然界中存在的生物合成逻辑通常不会以最大的碳或能源效率运行。这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以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，并导致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，该项目改善了生物制造，以更好地满足国家对能源，食品，商品和医药的需求，并同时有助于STEM的本科和研究生教育。该项目计划通过参与实践科学的实践经验，激励K-12学生从事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，而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，引入了非自然的热力学驱动力。这个提议开发了非自然的辅因子来部署比自然更强大的热力学驱动力。总体目标是将比NAD（P）更有效的还原剂的非天然氧化还原辅因子引入大肠杆菌代谢，并使用它们为商品化学品的碳效率生物制造提供动力。这是通过设计关键酶来实现的，以通过集成的设计-构建-测试-学习工作流来利用这些非天然辅因子，该工作流跨越基因组挖掘，具有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。更好地全面了解辅因子的结构可塑性如何被酶所耐受，在进化过程中超越自然选择的能力，并为蛋白质开辟新的设计空间。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，环境和运输系统这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。