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

Laura Luzia, David Lao-Martil, Philipp Savakis, Johan van Heerden, Natal van Riel, Bas Teusink*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)6021-6037
Number of pages17
JournalFEBS Journal
Volume289
Issue number19
Early online date16 Apr 2022
DOIs
Publication statusPublished - Oct 2022

Bibliographical note

Funding Information:
The CEN.PK113‐5D strain was kindly provided by P. Kötter (Institut für Molekulare Biowissenschaften), Euroscarf, Frankfurt. We thank Chrats Melkonian, Frank Bruggeman, and Jurgen Haanstra for fruitful discussions and help with revision. We also acknowledge the financial support from the Netherlands Organization for Scientific Research (NWO), grant nr 737.016.001.

Funding Information:
The CEN.PK113-5D strain was kindly provided by P. Kötter (Institut für Molekulare Biowissenschaften), Euroscarf, Frankfurt. We thank Chrats Melkonian, Frank Bruggeman, and Jurgen Haanstra for fruitful discussions and help with revision. We also acknowledge the financial support from the Netherlands Organization for Scientific Research (NWO), grant nr 737.016.001.

Publisher Copyright:
© 2022 The Authors. The FEBS Journal published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Funding

The CEN.PK113‐5D strain was kindly provided by P. Kötter (Institut für Molekulare Biowissenschaften), Euroscarf, Frankfurt. We thank Chrats Melkonian, Frank Bruggeman, and Jurgen Haanstra for fruitful discussions and help with revision. We also acknowledge the financial support from the Netherlands Organization for Scientific Research (NWO), grant nr 737.016.001. The CEN.PK113-5D strain was kindly provided by P. Kötter (Institut für Molekulare Biowissenschaften), Euroscarf, Frankfurt. We thank Chrats Melkonian, Frank Bruggeman, and Jurgen Haanstra for fruitful discussions and help with revision. We also acknowledge the financial support from the Netherlands Organization for Scientific Research (NWO), grant nr 737.016.001.

Keywords

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

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