In vitro turnover numbers do not reflect in vivo activities of yeast enzymes

Turnover numbers (kcat values) quantitatively represent the activity of enzymes, which are mostly measured in vitro. While a few studies have reported in vivo catalytic rates (kapp values) in bacteria, a large-scale estimation of kapp in eukaryotes is lacking. Here, we estimated kapp of the yeast Saccharomyces cerevisiae under diverse conditions. By comparing the maximum kapp across conditions with in vitro kcat we found a weak correlation in log scale of R2 = 0.28, which is lower than for Escherichia coli (R2 = 0.62). The weak correlation is caused by the fact that many in vitro kcat values were measured for enzymes obtained through heterologous expression. Removal of these enzymes improved the correlation to R2 = 0.41 but still not as good as for E. coli, suggesting considerable deviations between in vitro and in vivo enzyme activities in yeast. By parameterizing an enzyme-constrained metabolic model with our kapp dataset we observed better performance than the default model with in vitro kcat in predicting proteomics data, demonstrating the strength of using the dataset generated here.

Automated summary

In this study, the in vivo catalytic rates of the yeast Saccharomyces cerevisiae under various conditions were estimated and compared with in vitro enzyme activity, revealing a weak correlation and considerable deviations between in vivo and in vitro enzyme activities. The correlation was improved after removing enzymes obtained through heterologous expression, but still not as strong as for bacteria. Parameterizing an enzyme-constrained metabolic model with the kapp dataset showed better performance in predicting proteomics data compared to using in vitro kcat, highlighting the importance of the generated dataset.