pH dependencies of glycolytic enzymes of yeast under in vivo‐like assay conditions

• Published in: The FEBS journal Vol. 289; no. 19; pp. 6021 - 6037
• Main Authors: Luzia, Laura, Lao‐Martil, David, Savakis, Philipp, Heerden, Johan, Riel, Natal, Teusink, Bas
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.10.2022; John Wiley and Sons Inc
• Subjects: Carbon; Carbon - metabolism; Carbon sources; cell growth; Enzymatic activity; enzyme kinetics modeling; Enzymes; Ethanol; Ethanol - metabolism; ethanol fermentation; famine; Fermentation; glucose; Glucose - metabolism; Glyceraldehyde-3-phosphate dehydrogenase; Glycolysis; Hydrogen-Ion Concentration; Metabolism; nutrient dynamics; Original; pH dependency; pH effects; progression curve analysis; Saccharomyces cerevisiae; Saccharomyces cerevisiae - metabolism; Yeast; yeast glycolysis; yeasts; nutrient dynamics; progression curve analysis; pH dependency; yeast glycolysis; enzyme kinetics modeling
• ISSN: 1742-464X; 1742-4658; 1742-4658
• DOI: 10.1111/febs.16459

Under carbon source transitions, the intracellular pH of Saccharomyces cerevisiae is subject to change. Dynamics in pH modulate the activity of the glycolytic enzymes, resulting in a change in glycolytic flux and ultimately cell growth. To understand how pH affects the global behavior of glycolysis and ethanol fermentation, we measured the activity of the glycolytic and fermentative enzymes in S. cerevisiae under in vivo‐like conditions at different pH. We demonstrate that glycolytic enzymes exhibit differential pH dependencies, and optima, in the pH range observed during carbon source transitions. The forward reaction of GAPDH shows the highest decrease in activity, 83%, during a simulated feast/famine regime upon glucose removal (cytosolic pH drop from 7.1 to 6.4). We complement our biochemical characterization of the glycolytic enzymes by fitting the Vmax to the progression curves of product formation or decay over time. The fitting analysis shows that the observed changes in enzyme activities require changes in Vmax, but changes in Km cannot be excluded. Our study highlights the relevance of pH as a key player in metabolic regulation and provides a large set of quantitative data that can be explored to improve our understanding of metabolism in dynamic environments. Under carbon source transitions, S. cerevisiae can experience intracellular pH dynamics. Such fluctuations can potentially affect glycolytic fluxes and therefore growth. This work shows how glucose dynamics affect intracellular pH and how glycolytic and ethanol brunch enzyme activity is influenced by pH. Additionally, we developed a modeling approach to extract additional information from the kinetic profiles that allowed us to elaborate on the origin of the different activities.