STEPHEN QUAKE PRT TIME

斯蒂芬雷克 PRT 时间

• 批准号: 7721919
• 负责人: STEPHEN R QUAKE
• 金额: $ 0.02万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-01 至 2009-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7721919
• 关键词: Acetates; Carbon; Computer Retrieval of Information on Scientific Projects Database; Computer Simulation; Escherichia coli; Funding; Generations; Genes; Glucose; Glycerol; Glycerol Kinase; Grant; Growth; Institution; Malates; Maps; Metabolic; Modeling; Mutation; Point Mutation; Rate; Research; Research Personnel; Resources; Source; Testing; Time; United States National Institutes of Health; malate; mutant

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. A computational model was introduced to predict optimal growth rates of E. coli on several carbon substrates including glucose, glycerol, malate, and acetate (1). Experimental testing of the model showed that E. coli grew optimally on all carbon substrates tested except glycerol. E. coli was subject to growth on glycerol over several generations and it evolved to the optimal predicted growth rate. The metabolic genes were sequenced to identify mutations responsible for the optimized growth rates. In total, eleven different point mutations were identified, and eight of the eleven mutations were in the glycerol kinase gene. The mutations were mapped to highly regulated domains of glycerol kinase. The glycerol kinase mutants have been expressed and structural analysis is underway to determine how these mutations caused an increased growth rate of E. coli on glycerol.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 中心，不一定是研究者的机构。 引入计算模型来预测大肠杆菌在多种碳底物（包括葡萄糖、甘油、苹果酸和醋酸盐）上的最佳生长速率 (1)。 该模型的实验测试表明，大肠杆菌在除甘油之外的所有测试碳底物上生长最佳。 大肠杆菌在甘油中生长了几代，并进化到了最佳的预测生长速率。 对代谢基因进行测序，以确定导致优化生长率的突变。 总共鉴定出十一种不同的点突变，十一种突变中的八种位于甘油激酶基因中。 这些突变被映射到甘油激酶的高度调控域。 甘油激酶突变体已经表达，结构分析正在进行中，以确定这些突变如何导致大肠杆菌在甘油上的生长速率增加。