Department of Biology and Biological Engineering, Chalmers University of Technology, SE412 96 Gothenburg, Sweden.
Department of Biology and Biological Engineering, Chalmers University of Technology, SE412 96 Gothenburg, Sweden;
Proc Natl Acad Sci U S A. 2021 Aug 10;118(32). doi: 10.1073/pnas.2108391118.
Turnover numbers ( values) quantitatively represent the activity of enzymes, which are mostly measured in vitro. While a few studies have reported in vivo catalytic rates ( values) in bacteria, a large-scale estimation of in eukaryotes is lacking. Here, we estimated of the yeast under diverse conditions. By comparing the maximum across conditions with in vitro we found a weak correlation in log scale of = 0.28, which is lower than for ( = 0.62). The weak correlation is caused by the fact that many in vitro values were measured for enzymes obtained through heterologous expression. Removal of these enzymes improved the correlation to = 0.41 but still not as good as for , suggesting considerable deviations between in vitro and in vivo enzyme activities in yeast. By parameterizing an enzyme-constrained metabolic model with our dataset we observed better performance than the default model with in vitro in predicting proteomics data, demonstrating the strength of using the dataset generated here.
周转率数值(值)定量表示酶的活性,这些酶主要在体外进行测量。虽然有少数研究报道了细菌的体内催化速率(值),但缺乏对真核生物的大规模估计。在这里,我们估计了酵母在不同条件下的。通过比较条件下的最大与体外我们发现对数标度的相关性较弱,为 = 0.28,低于(= 0.62)。弱相关性是由于许多体外值是通过异源表达获得的酶测量得到的。去除这些酶提高了相关性至 = 0.41,但仍不如,这表明酵母中体外和体内酶活性之间存在相当大的偏差。通过用我们的数据集参数化一个受酶限制的代谢模型,我们观察到在预测蛋白质组学数据方面,使用这里生成的数据集的性能优于默认模型的体外,这证明了使用该数据集的优势。