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: 7093466
• 负责人: BERNHARD O PALSSON
• 金额: $ 56.33万
• 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/7093466
• 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）： 该研究计划的目的是使用现有的遗传/生化文献和数据以及该计划中产生的实验数据来开发代谢模型，其调节和大分子合成的基因组规模。该模型还将用于推动前瞻性实验设计，并将执行这些实验以询问模型。基因组学和各种高通量技术正在生成大量有关活细胞的分子数据。现在，这些数据和细胞过程的复杂性要求在计算机模型中构建大规模（最终基因组规模），以便在有机体的完整细胞功能的背景下解释数据。拟议的研究计划由三个特定目的组成：＃1建立一个基因组规模模型的酵母模型，该模型根据单个细胞成分可用的数据来描述代谢及其调节以及蛋白质合成过程； ＃2生成高通量功能基因组学数据，以持续的方式扩展和验证模型；和＃3执行敲除菌株的模型靶向表型来验证或反驳模型。在AIM＃2中将用于重建网络的数据类型是全基因组转录分析和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，以允许对现有模型的有效验证和扩展。最后，该模型将通过执行高通量和详细的表型实验来验证，旨在最佳地探测模型的不一致或不准确性。酿酒酵母是一种重要的真核模型生物体，具有基础医学研究，具有重要的工业意义。预计该生物体的基因组规模模型将对系统生物学的发展产生广泛的影响，并具有广泛的实际使用。拟议的程序将导致开发Eukar-yotic有机体的第一个基因组规模综合模型，并将作为垫脚石，用于构建包括小鼠和人类在内的高等真核生物的类似模型。