EAGER: Systematic Approach to Improve Probability of Metabolic Engineering Success

EAGER：提高代谢工程成功概率的系统方法

• 批准号: 1448657
• 负责人: Mattheos Koffas
• 金额: $ 14.99万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-15 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1448657&HistoricalAwards=false
• 关键词: EAGER; Systematic; Approach; Improve; Probability

The field of metabolic engineering continues to excel at producing specialty and commodity chemicals from simple, renewable feedstocks, but focus on the field's successes in literature and media neglect the larger picture: many metabolic engineering efforts produce industrially irrelevant titers in the early stages of research and sometimes throughout the duration of the project. This EAGER award will address the question of whether there are fundamental steps that can be taken early in metabolic engineering projects to maximize their success rates. The PI will address his hypothesis that the regulation of the amount of cofactors (small molecules that enable certain enzymes to function) is central to the ability to control metabolic pathways in cells in such a way as to enable the production of useful biochemicals for biomanufacturing purposes. In addition, the PI will train graduate and undergraduate students in interdisciplinary research and expose high school students to cutting edge research in this field.Technical description: The investigator will apply a broadly applicable, systematic approach to improve the success rate of metabolic engineering endeavors by performing a rigorous case study of the production of a complex biochemical in E. coli. The PI hypothesizes that the dynamic regulation of cofactor biosynthesis is key to metabolic engineering success, and will use the CRISPR interference (CRISPRi) system to achieve dynamic cofactor expression control in order to test his hypothesis. He will examine the fate of accumulating cofactor and cellular response via pulse-chase metabolic analysis and quantification with LC-MS/MS. Cellular response to cofactor accumulation will be monitored using comparative RNA-seq (transcriptomic) and iTRAQ (proteomic) analysis between wild-type and engineered strains. The PI will then use results from this case study to begin to generalize rules concerning co-factor regulation and impacts on metabolic engineering success.

代谢工程领域继续擅长于从简单的可再生原料生产特种和商品化学品，但专注于该领域在文献和媒体上的成功，忽视了更大的图景：许多代谢工程努力在研究的早期阶段产生了与工业无关的滴度，有时在整个项目期间。EAGER奖将解决代谢工程项目早期是否可以采取基本步骤以最大限度地提高成功率的问题。PI将阐述他的假设，即辅因子（使某些酶发挥作用的小分子）的量的调节对于控制细胞中代谢途径的能力至关重要，从而能够生产用于生物制造目的的有用生物化学品。 此外，PI还将培养研究生和本科生进行跨学科研究，并让高中生接触该领域的前沿研究。技术描述：研究员将通过对E.杆菌PI假设辅因子生物合成的动态调节是代谢工程成功的关键，并将使用CRISPR干扰（CRISPRi）系统来实现动态辅因子表达控制，以验证他的假设。 他将通过脉冲追踪代谢分析和LC-MS/MS定量来检查累积辅因子和细胞反应的命运。将使用野生型和工程菌株之间的比较RNA-seq（转录组学）和iTRAQ（蛋白质组学）分析来监测细胞对辅因子累积的反应。 然后，PI将使用本案例研究的结果，开始推广有关辅因子调节和对代谢工程成功的影响的规则。