LINKING GENOMICS TO FUNCTION VIA METABOLIC PHENOTYPING

通过代谢表型将基因组与功能联系起来

• 批准号: 6224326
• 负责人: GREGORY STEPHANOPOULOS
• 金额: $ 60.42万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-30 至 2002-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6224326
• 关键词: aminoacid metabolism; carbohydrate metabolism; complementary DNA; gas chromatography mass spectrometry; gene expression; gene targeting; genetic transcription; genetically modified animals; genome; glucose transport; hepatocellular carcinoma; laboratory mouse; linkage mapping; lipid biosynthesis; lipid metabolism; liver cells; liver metabolism; method development; microarray technology; neoplastic cell; phenotype; radiotracer; steroid biosynthesis; tissue /cell culture

Recombinant strains with well defined genetic backgrounds are often found to exhibit small functional differences despite specific changes at the genetic level while in other cases, single gene alterations result in profound phenotypic variations. Although a first step in explaining such macroscopic differences is to probe the full detail of the expression phenotype by genome-wide expression measurements, transcription data alone are insufficient to elucidate the actual metabolic state of a cell and its functions. The latter require information about intracellular metabolic fluxes, which constitute fundamental determinants of cell physiology and excellent metrics of cell function. "Metabolic phenotyping" is the process and methods of determining intracellular fluxes as determinants of the cellular metabolic state. Combined with transcription data, the investigators provide a complete framework for analyzing the effect of drugs and studying disease. This application integrates the expertise of three participating laboratories for the purpose of combining metabolic and expression phenotyping to elucidate central carbon and lipid metabolism in model mouse hepatoma and hepatocyte cultures. Determination of intracellular fluxes will follow a systems approach termed metabolic reconstruction whereby the entire metabolic network is configured such as to best represent macroscopic rate and isotopic label distribution measurements made by GC-MS. Of particular attention are issues of observability, redundancy, and solution stability to ensure method feasibility and accuracy of the results. Differential transcription data will be obtained by DNA microarrays for mouse genes involved in central carbon metabolic, gluconeogenic and lipid biosynthetic pathways, as well as for other genes with particular expression variability that will be identified in the course of the research. Bioinformatics methods and programs, developed over the past 12 years will be deployed for this purpose. The general goal of the research is to identify relationships between the metabolic phenotype as defined above and the transcriptional state as defined by expression data of consequence in pathways important to diabetes. Specific aims will focus on flux quantification in mouse hepatoma and hepatocyte cultures to elucidate glutamine metabolism and lipogenesis, other central metabolic pathways and cholesterol synthesis, the effect of nutrients, hormones and drugs like Metformin and finally, pleiotrophic effects generated by altering the normal expression of a single gene, such as over-expressing the truncated verion of sterol-regulatory element binding protein-1a in transgenic mice. The broader contribution of this research is to extend the paradigm of holistic transcriptional investigation introduced by DNA microarray technologies to the study of metabolic level processes by metabolic phenotyping. As such, it holds the promise of identifying most, if not all points in metabolism affected by the action of drugs or genetic modifications thus guiding future programs of drug development and gene therapy.

具有明确遗传背景的重组菌株是 通常发现，尽管有特定的变化， 而在其他情况下，单个基因的改变会导致 深刻的表型变异。虽然解释这种情况的第一步是 宏观差异是探索表达表型的全部细节 通过全基因组的表达测量， 不足以阐明细胞的实际代谢状态及其 功能协调发展的后者需要关于细胞内代谢通量的信息， 其构成细胞生理学的基本决定因素， 细胞功能的度量。“代谢表型分析”是确定代谢表型的过程和方法。 确定细胞内通量作为细胞代谢的决定因素 状态结合转录数据，研究人员提供了一个完整的 分析药物效果和研究疾病的框架。 该应用程序集成了三个参与实验室的专业知识 为了结合代谢和表达表型来阐明 小鼠肝癌模型及肝细胞中心碳脂代谢 cultures.细胞内通量的测定将遵循系统方法 称为代谢重建，由此整个代谢网络被 配置为最好地代表宏观速率和同位素标记 通过GC-MS进行分布测量。特别注意的是以下问题 可观测性、冗余性和解的稳定性，以确保方法的可行性 和结果的准确性。将获得差异转录数据 通过DNA微阵列检测参与中心碳代谢的小鼠基因， 脂质生物合成途径，以及其他基因， 特定的表达变异性，将被确定的过程中， research.生物信息学方法和程序，在过去的12年中发展 将为此目的部署。研究的总体目标是 确定如上定义的代谢表型与代谢表型之间的关系。 转录状态，由途径中结果的表达数据定义 对糖尿病很重要。具体目标将集中在小鼠中的通量定量 肝细胞瘤和肝细胞培养，以阐明谷氨酰胺代谢， 脂肪生成、其他中枢代谢途径和胆固醇合成， 营养素、激素和药物如二甲双胍的作用， 通过改变一个单一基因的正常表达而产生的多效性效应， 基因，如过表达截短的甾醇调节元件 结合蛋白-1a在转基因小鼠中的表达。更广泛的贡献， 研究是为了扩展整体转录研究的范式， 将DNA微阵列技术引入代谢水平的研究 通过代谢表型分析进行的过程。因此，它承诺 确定代谢中受以下作用影响的大多数（如果不是全部）点： 药物或基因修饰，从而指导未来的药物开发计划 和基因治疗。