4.6 Article

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

期刊

FEBS JOURNAL
卷 289, 期 19, 页码 6021-6037

出版社

WILEY
DOI: 10.1111/febs.16459

关键词

enzyme kinetics modeling; nutrient dynamics; pH dependency; progression curve analysis; yeast glycolysis

资金

  1. Netherlands Organization for Scientific Research (NWO) [737.016.001]

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The intracellular pH of Saccharomyces cerevisiae changes during carbon source transitions, affecting the activity of glycolytic enzymes and ultimately cell growth. In this study, the researchers measured the activity of these enzymes under different pH conditions to understand how pH influences glycolysis and ethanol fermentation. The study reveals differential pH dependencies of glycolytic enzymes and highlights the relevance of pH as a key player in metabolic regulation.
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 V-max 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 V-max, but changes in K-m 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.

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