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Trans-omics Analysis of Yeast Central Carbon Metabolism by Integration of Metabolome, Proteome and Fluxome Data

机译:代谢物,蛋白质组和浮动数据集成酵母中央碳代谢的转常常调分析

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The central carbon metabolism is an old frontier of biology, but recently revisited with the mass spectrometry-based trans-omics analysis to investigate the cancer-specific metabolism and a microbial cell factory producing biomaterials. Although the central metabolic pathways, intermediates, and enzymes in an eukaryotic cell model, Saccharomyces cerevisiae, have been well characterized, a system-level understanding of the regulation network requires a quantitative description of those complex behaviors. Recent progress in mass spectrometry-based bioanalysis techniques enabled to produce the required amount of quantitative data from S. cerevisiae. In this study, a trans-omics dataset including metabolome, proteome and fluxome data was obtained from the 11 single-deletion strains of S. cerevisiae by the ion-pairing liquid chromatography-mass spectrometry (LC-MS), the targeted proteome analysis using the fast scanning speed of LC-ultra-fast mass spectrometry (LC-UFMS), and the ~(13)C-metabolic flux analysis (MFA) using GC-MS.
机译:中央碳代谢是生物学的古老前沿,但最近通过基于质谱的转铁族分析检测,研究癌症特异性代谢和产生生物材料的微生物细胞厂。尽管在真核细胞模型中的中间体代谢途径,中间体和酶,但已经很好地表征了对调节网络的系统级别了解,但是对这些复杂行为的定量描述需要定量描述。基于质谱的生物分析技术的最近进展使得从S.Cerevisiae产生所需的定量数据量。在本研究中,通过离子配对液相色谱 - 质谱(LC-MS)从11个单缺失菌株获得包括代谢物,蛋白质组和血液数据的反式蛋白酶数据集,从属于离子配对液相色谱 - 质谱(LC-MS),靶向蛋白质组分析使用GC-MS的LC超快速质谱(LC-UFMS)的快速扫描速度和〜(13)C-代谢通量分析(MFA)。

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