A Genome-Scale Regulated Metabolic Model of Yeast

基因组规模调控的酵母代谢模型

• 批准号: 6921458
• 负责人: BERNHARD O PALSSON
• 金额: $ 56.28万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6921458
• 关键词: Saccharomyces cerevisiae; binding sites; chromatin immunoprecipitation; fungal genetics; gene deletion mutation; gene expression; gene expression profiling; genetic models; genetic transcription; high throughput technology; method development; microarray technology; microorganism culture; microorganism metabolism; model design /development; phenotype; polymerase chain reaction; protein biosynthesis; transcription factor

DESCRIPTION (provided by applicant): The goal of this research program is to develop a genome-scale in silico model of metabolism, its regulation, and macromolecular synthesis in Saccharomyces cerevisiae using existing genetic/biochemical literature and data as well as experimental data generated within the program. The model will also be used to drive prospective experimental designs, and these experiments will be performed to interrogate the model. Genomics and various high-throughput technologies are generating large volumes of molecular data on living cells. This data and the complexity of cellular processes are now demanding the construction of large-scale (ultimately genome-scale) in silico models in order to interpret the data in the context of the full cellular function of an organism. The proposed research program is comprised of three specific aims: #1 to build a genome-scale model of yeast that describes metabolism and its regulation along with the protein synthesis process based on data available on the individual cellular components; #2 to generate high-throughput functional genomics data to expand and validate the model in an on-going fashion; and #3 to perform modeldriven targeted phenotyping of knock-out strains to validate or refute the model. The data types that will be used to reconstruct the network in Aim #2 are genome-wide transcription profiling and DNA-binding site identification (location analysis) data. These experiments will be designed in a model-driven fashion to allow efficient validation and extension of the existing model. Finally, the model will be validated by performing both high-throughput and detailed phenotyping experiments designed to optimally probe the model for inconsistencies or inaccuracies. S. cerevisiae is an important eukaryotic model organism for basic medical research and of great industrial significance. A genome-scale model of this organism is expected to have wide impact on the development of systems biology and be of broad practical use. The proposed program would result in the development of the first genome-scale integrated model of a eukar-yotic organism and would serve as a stepping stone for building similar models of higher eukaryotes including mouse and human.

描述（由申请人提供）： 该研究计划的目标是利用现有的遗传/生物化学文献和数据以及该计划内生成的实验数据，开发一个基因组规模的代谢、调节和酿酒酵母大分子合成的计算机模型。该模型还将用于驱动前瞻性实验设计，并将进行这些实验以询问模型。基因组学和各种高通量技术正在产生关于活细胞的大量分子数据。这些数据和细胞过程的复杂性现在要求构建大规模（最终是基因组规模）的计算机模型，以便在生物体的完整细胞功能的背景下解释数据。拟议的研究计划包括三个具体目标：#1建立一个基因组规模的酵母模型，描述代谢及其调控沿着蛋白质合成过程的基础上，对个别细胞成分的数据; #2产生高通量功能基因组学数据，以扩大和验证模型在一个持续的方式;和#3进行敲除菌株的模型驱动的靶向表型分析以验证或反驳模型。目标2中用于重建网络的数据类型是全基因组转录谱和DNA结合位点识别（位置分析）数据。这些实验将以模型驱动的方式设计，以有效验证和扩展现有模型。最后，将通过执行高通量和详细的表型实验来验证模型，这些实验旨在最佳地探测模型的不一致性或不准确性。S.酿酒酵母是一种重要的真核生物模式生物，用于基础医学研究，具有重要的工业意义。这种生物体的基因组规模模型预计将对系统生物学的发展产生广泛的影响，并具有广泛的实际用途。该计划将导致真核生物的第一个基因组规模整合模型的开发，并将作为建立包括小鼠和人类在内的高等真核生物类似模型的垫脚石。