Abstract
Cycling of co-substrates, whereby a metabolite is converted among alternate forms via different reactions, is ubiquitous in metabolism. Several cycled co-substrates are well known as energy and electron carriers (e.g. ATP and NAD(P)H), but there are also other metabolites that act as cycled co-substrates in different parts of central metabolism. Here, we develop a mathematical framework to analyse the effect of co-substrate cycling on metabolic flux. In the cases of a single reaction and linear pathways, we find that co-substrate cycling imposes an additional flux limit on a reaction, distinct to the limit imposed by the kinetics of the primary enzyme catalysing that reaction. Using analytical methods, we show that this additional limit is a function of the total pool size and turnover rate of the cycled co-substrate. Expanding from this insight and using simulations, we show that regulation of these two parameters can allow regulation of flux dynamics in branched and coupled pathways. To support these theoretical insights, we analysed existing flux measurements and enzyme levels from the central carbon metabolism and identified several reactions that could be limited by the dynamics of co-substrate cycling. We discuss how the limitations imposed by co-substrate cycling provide experimentally testable hypotheses on specific metabolic phenotypes. We conclude that measuring and controlling co-substrate dynamics is crucial for understanding and engineering metabolic fluxes in cells.
Original language | English |
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Journal | eLife |
Volume | 12 |
DOIs | |
State | Published - 17 Feb 2023 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2023, West, Delattre et al.
Funding
This project is funded by the Biotechnology and Biological Sciences Research Council (BBSRC) (grant BB/T010150/1). EF acknowledges funding from the Novo Nordisk Foundation (grant NNF18OC0052483), while OSS acknowledges support from the Gordon and Betty Moore Foundation (grant https://doi.org/10.378 We would like to thank Wenying Shou for constructive comments on an earlier version of this manuscript, and Dan Davidi for his help with datasets of reaction fluxes and enzyme abundances.
Funders | Funder number |
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Gordon and Betty Moore Foundation | |
Biotechnology and Biological Sciences Research Council | BB/T010150/1 |
Novo Nordisk Fonden | NNF18OC0052483 |
Keywords
- A. thaliana
- E. coli
- S. cerevisiae
- computational biology
- human
- systems biology