Data-driven model of glycolysis identifies the role of allostery in maintaining ATP homeostasis
Abstract
The specific roles of allostery in regulating metabolism are not well understood. Here, we develop a data-driven mathematical model of mammalian glycolysis that uses enzyme rate equations and coupled ordinary differential equations. The key components of our model are the rate equations for allosterically regulated enzymes based on the Monod-Wyman-Changeux model that we derive using a rigorous analysis of thousands ofin vitrokinetic measurements. The resulting model recapitulates the properties of glycolysis observed in live cells and shows that the specific function of allosteric regulation is to maintain high and stable concentrations of ATP, while glycolysis without allosteric regulation is fully capable of producing ATP and ensuring that ATP hydrolysis generates energy. Our data-based modeling approach provides a roadmap for a better understanding of the role of allostery in metabolism regulation.One-Sentence SummaryThe glycolysis model based on allosteric enzyme rate equations recapitulates properties of glycolysis observed in live cells.
Additional Information
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. We thank the students and instructors of the Marine Biological Laboratory course on Physical Biology of the Cell for their comments on the early version of this project; participants of the Kavli Institute for Theoretical Physics workshop on Cellular Energetics for fruitful discussions; Bradley Webb for discussions about PFK regulation; and members of Titov and Phillips labs for helpful suggestions. This research used the Savio computational cluster resource provided by the Berkeley Research Computing program at the University of California, Berkeley (supported by the UC Berkeley Chancellor, Vice Chancellor for Research, and Chief Information Officer). Funding: National Institutes of Health grant DP2 GM132933 (DVT) National Institutes of Health grant 5R35 GM118043-7 (RP) Damon Runyon Cancer Research Foundation Fellowship DRQ 01-20 (TE). Author contributions: Conceptualization: RP, DVT Data curation: MC, TE, DVT Methodology: MC, TE, DVT Investigation: MC, TE, DVT Funding acquisition: RP, DVT Supervision: RP, DVT Writing – original draft: DVT Writing – review & editing: MC, TE, RP, DVT. Data and materials availability: All data are available in the main text or the supplementary materials. The Julia code for the glycolysis model that reproduces all the figures in the main text is deposited at https://github.com/DenisTitovLab/Glycolysis.jl. The authors have declared no competing interest.Attached Files
Submitted - 2022.12.28.522046v2.full.pdf
Supplemental Material - media-1.pdf
Supplemental Material - media-2.xlsx
Supplemental Material - media-3.xlsx
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Additional details
- Eprint ID
- 120160
- Resolver ID
- CaltechAUTHORS:20230316-182632000.47
- DP2 GM132933
- NIH
- 5R35 GM118043-7
- NIH
- DRQ 01-20
- Damon Runyon Cancer Research Foundation
- Created
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2023-03-20Created from EPrint's datestamp field
- Updated
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2023-03-20Created from EPrint's last_modified field
- Caltech groups
- Division of Biology and Biological Engineering