A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes

Kieran Smallbone; Hanan L Messiha; Kathleen M Carroll; Catherine L Winder; Naglis Malys; Warwick B Dunn; Ettore Murabito; Neil Swainston; Joseph O Dada; Farid Khan; Pınar Pir; Evangelos Simeonidis; Irena Spasić; Jill Wishart; Dieter Weichart; Neil W Hayes; Daniel Jameson; David S Broomhead; Stephen G Oliver; Simon J Gaskell; John E G McCarthy; Norman W Paton; Hans V Westerhoff; Douglas B Kell; Pedro Mendes

doi:10.1016/j.febslet.2013.06.043

A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes

Kieran Smallbone, Hanan L Messiha, Kathleen M Carroll, Catherine L Winder, Naglis Malys, Warwick B Dunn, Ettore Murabito, Neil Swainston, Joseph O Dada, Farid Khan, Pınar Pir, Evangelos Simeonidis, Irena Spasić, Jill Wishart, Dieter Weichart, Neil W Hayes, Daniel Jameson, David S Broomhead, Stephen G Oliver, Simon J GaskellJohn E G McCarthy, Norman W Paton, Hans V Westerhoff, Douglas B Kell, Pedro Mendes

Research output: Contribution to journal › Article › peer-review

71 Citations (Scopus)

Abstract

We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a "cycle of knowledge" strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought.

Original language	English
Pages (from-to)	2832-41
Number of pages	10
Journal	FEBS Letters
Volume	587
Issue number	17
DOIs	https://doi.org/10.1016/j.febslet.2013.06.043
Publication status	Published - 2 Sept 2013

Keywords

Computer Simulation
Glycolysis
Isoenzymes
Kinetics
Metabolic Networks and Pathways
Models, Biological
Saccharomyces cerevisiae
Saccharomyces cerevisiae Proteins
Systems Biology

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10.1016/j.febslet.2013.06.043

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Smallbone, K., Messiha, H. L., Carroll, K. M., Winder, C. L., Malys, N., Dunn, W. B., Murabito, E., Swainston, N., Dada, J. O., Khan, F., Pir, P., Simeonidis, E., Spasić, I., Wishart, J., Weichart, D., Hayes, N. W., Jameson, D., Broomhead, D. S., Oliver, S. G., ... Mendes, P. (2013). A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes. FEBS Letters, 587(17), 2832-41. https://doi.org/10.1016/j.febslet.2013.06.043

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abstract = "We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a {"}cycle of knowledge{"} strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought.",

keywords = "Computer Simulation, Glycolysis, Isoenzymes, Kinetics, Metabolic Networks and Pathways, Models, Biological, Saccharomyces cerevisiae, Saccharomyces cerevisiae Proteins, Systems Biology",

author = "Kieran Smallbone and Messiha, {Hanan L} and Carroll, {Kathleen M} and Winder, {Catherine L} and Naglis Malys and Dunn, {Warwick B} and Ettore Murabito and Neil Swainston and Dada, {Joseph O} and Farid Khan and Pınar Pir and Evangelos Simeonidis and Irena Spasi{\'c} and Jill Wishart and Dieter Weichart and Hayes, {Neil W} and Daniel Jameson and Broomhead, {David S} and Oliver, {Stephen G} and Gaskell, {Simon J} and McCarthy, {John E G} and Paton, {Norman W} and Westerhoff, {Hans V} and Kell, {Douglas B} and Pedro Mendes",

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doi = "10.1016/j.febslet.2013.06.043",

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Smallbone, K, Messiha, HL, Carroll, KM, Winder, CL, Malys, N, Dunn, WB, Murabito, E, Swainston, N, Dada, JO, Khan, F, Pir, P, Simeonidis, E, Spasić, I, Wishart, J, Weichart, D, Hayes, NW, Jameson, D, Broomhead, DS, Oliver, SG, Gaskell, SJ, McCarthy, JEG, Paton, NW, Westerhoff, HV, Kell, DB & Mendes, P 2013, 'A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes', FEBS Letters, vol. 587, no. 17, pp. 2832-41. https://doi.org/10.1016/j.febslet.2013.06.043

TY - JOUR

T1 - A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes

AU - Smallbone, Kieran

AU - Messiha, Hanan L

AU - Carroll, Kathleen M

AU - Winder, Catherine L

AU - Malys, Naglis

AU - Dunn, Warwick B

AU - Murabito, Ettore

AU - Swainston, Neil

AU - Dada, Joseph O

AU - Khan, Farid

AU - Pir, Pınar

AU - Simeonidis, Evangelos

AU - Spasić, Irena

AU - Wishart, Jill

AU - Weichart, Dieter

AU - Hayes, Neil W

AU - Jameson, Daniel

AU - Broomhead, David S

AU - Oliver, Stephen G

AU - Gaskell, Simon J

AU - McCarthy, John E G

AU - Paton, Norman W

AU - Westerhoff, Hans V

AU - Kell, Douglas B

AU - Mendes, Pedro

PY - 2013/9/2

Y1 - 2013/9/2

N2 - We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a "cycle of knowledge" strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought.

AB - We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a "cycle of knowledge" strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought.

KW - Computer Simulation

KW - Glycolysis

KW - Isoenzymes

KW - Kinetics

KW - Metabolic Networks and Pathways

KW - Models, Biological

KW - Saccharomyces cerevisiae

KW - Saccharomyces cerevisiae Proteins

KW - Systems Biology

U2 - 10.1016/j.febslet.2013.06.043

DO - 10.1016/j.febslet.2013.06.043

M3 - Article

C2 - 23831062

SN - 0014-5793

VL - 587

SP - 2832

EP - 2841

JO - FEBS Letters

JF - FEBS Letters

IS - 17

ER -

A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes

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Keywords

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