Collaborative Research: Enabling Scalable Redox Reactions in Biomanufacturing

生物制造，即大宗化学品、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，存在于自然界的生物合成逻辑往往不能以最大的碳或能源效率运行。之所以会出现这种情况，是因为碳需要以二氧化碳的形式释放，而能量必须以热量的形式浪费，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。该项目提供了一套非自然的化学工具，以低还原电位还原等价物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，该项目改善了生物制造，以更好地满足国家对能源，食品，商品和药品的需求，并同时为STEM的本科和研究生教育做出贡献。该项目计划开展活动，通过参与实践科学的实践经验，激励K-12学生在STEM领域从事职业。目前的生物制造工艺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，引入了非自然热力学驱动力。这个建议发展了非自然的辅因子来部署比自然更强的热力学驱动力。总体目标是将比NAD(P)更有效的还原试剂非自然氧化还原辅助因子引入大肠杆菌代谢，并利用它们为商品化学品的低碳生物制造提供动力。这是通过集成的设计-构建-测试-学习工作流程来实现的，该工作流程跨越基因组挖掘，高通量酶发现与定向进化，工程酶的结构和生物物理研究，以及基于机器学习的数据解释，以提取控制蛋白质-辅因子相互作用的一般设计原则。更全面地了解辅因子的结构可塑性是如何被酶所耐受的，这将使蛋白质的能力超越自然在进化过程中选择的能力，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、环境和运输系统部的细胞和生化工程项目共同资助。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

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.