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从定量数据中学习以了解中心碳代谢。

Learning from quantitative data to understand central carbon metabolism.

机构信息

Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan; RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.

Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.

出版信息

Biotechnol Adv. 2017 Dec;35(8):971-980. doi: 10.1016/j.biotechadv.2017.09.006. Epub 2017 Sep 18.

Abstract

Quantitative analysis of metabolism has been used to identify driver reactions occurring during cancer development and bottleneck reactions in the metabolic engineering of microorganisms. In this review, we compare the advantages and disadvantages of various metabolic analysis methods. We emphasize that metabolic flux analysis based on material balance is a critical method for quantitative investigations into cell metabolism. The absolute determination of metabolite concentration appears to be essential for evaluating the thermodynamic state of metabolism. Obtaining a precise read-out of regulatory mechanisms from the snapshot data remains challenging due to our insufficient knowledge of the control of metabolism.

摘要

代谢的定量分析已被用于鉴定癌症发生过程中的驱动反应和微生物代谢工程中的瓶颈反应。在这篇综述中,我们比较了各种代谢分析方法的优缺点。我们强调,基于物质平衡的代谢通量分析是定量研究细胞代谢的关键方法。绝对测定代谢物浓度对于评估代谢的热力学状态似乎是必不可少的。由于我们对代谢控制的知识不足,从静态数据中获得对调节机制的精确解读仍然具有挑战性。

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