Max Planck Institute of Molecular Plant Physiology, Am Muehlenberg 1, 14476 Potsdam-Golm, Germany.
INRA, University of Bordeaux, UMR 1332 Fruit Biology and Pathology, F-33883 Villenave d'Ornon, France.
Trends Plant Sci. 2014 Apr;19(4):256-65. doi: 10.1016/j.tplants.2013.11.003. Epub 2013 Dec 11.
Information about the abundance and biological activities of proteins is essential to reveal how genes affect phenotypes. Over the past decade, mass spectrometry (MS)-based proteomics has revolutionized the identification and quantification of proteins, and the detection of post-translational modifications. Interpretation of proteomics data depends on information about the biological activities of proteins, which has created a bottleneck in research. This review focuses on enzymes in central metabolism. We examine the methods used for measuring enzyme activities, and discuss how these methods provide information about the kinetic and regulatory properties of enzymes, their turnover, and how this information can be integrated into metabolic models. We also discuss how robotized assays could enable the genetic networks that control enzyme abundance to be analyzed.
蛋白质丰度和生物学活性的信息对于揭示基因如何影响表型至关重要。在过去的十年中，基于质谱（MS）的蛋白质组学已经彻底改变了蛋白质的鉴定和定量，以及翻译后修饰的检测。蛋白质组学数据的解释取决于蛋白质生物学活性的信息，这在研究中造成了瓶颈。本文重点介绍中心代谢中的酶。我们检查了用于测量酶活性的方法，并讨论了这些方法如何提供关于酶的动力学和调节特性、周转率的信息，以及如何将这些信息整合到代谢模型中。我们还讨论了如何通过机器人化测定来分析控制酶丰度的遗传网络。
