YEAST METABOLOMICS BY TWO-DIMENSIONAL GAS CHROMATOGRAPHY AND MASS SPECTROMETRY

通过二维气相色谱和质谱法进行酵母代谢组学

• 批准号: 8171287
• 负责人: Sara J Cooper
• 金额: $ 4.42万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8171287
• 关键词: Amino Acids; Biological; Collaborations; Computer Retrieval of Information on Scientific Projects Database; Data; Funding; Gas Chromatography; Gene Expression; Gene Expression Regulation; Genes; Grant; Human; Individual; Institution; Mass Fragmentography; Mass Spectrum Analysis; Measures; Metabolic; Metabolism; Methods; Proteomics; Protocols documentation; Research; Research Personnel; Resources; Sampling; Source; Technology; United States National Institutes of Health; Variant; Yeasts; member; metabolomics; small molecule; tissue culture; two-dimensional

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. Metabolomics is the unbiased study of small molecules in biological samples. We have previously generated methods for targeted metabolite profiling of amino acids and other classes of small molecules in yeast. Now we have focused our efforts on using two-dimensional gas chromatography with mass spectrometry for an untargeted metabolomics approach in yeast. We have optimized these protocols for the quantification of approximately 150-200 different small molecule metabolites found in yeast. We are applying these methods for the characterization of natural variation in wild yeast strains. In collaboration with other members of the yeast resource center, we are measuring metabolic profiles for 38 individual strains grown under chemostat controlled conditions. Our data in combination with gene expression and proteomics data could provide a more complete network of gene regulation, gene expression and cellular metabolism differ among these strains. This project is just one example of the applications for this technology which can easily be applied to human biofluids and tissue culture samples.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 代谢组学是对生物样品中小分子的无偏研究。我们以前已经产生了针对酵母中氨基酸和其他类别小分子的靶向代谢物分析的方法。 现在，我们已经把我们的努力集中在使用二维气相色谱质谱法在酵母中的非靶向代谢组学方法。 我们已经优化了这些方案，用于定量酵母中发现的约150-200种不同的小分子代谢物。我们正在应用这些方法来表征野生酵母菌株的自然变异。与酵母资源中心的其他成员合作，我们正在测量在恒化器控制条件下生长的38个单独菌株的代谢谱。我们的数据结合基因表达和蛋白质组学数据可以提供一个更完整的基因调控网络，基因表达和细胞代谢在这些菌株之间的差异。该项目只是该技术应用的一个例子，该技术可以很容易地应用于人类生物流体和组织培养样品。