Dynamic modelling under uncertainty: the case of Trypanosoma brucei energy metabolism

Achcar, F., Kerkhoven, E.J., SilicoTryp Consortium, , Bakker, B.M., Barrett, M.P. and Breitling, R. (2012) Dynamic modelling under uncertainty: the case of Trypanosoma brucei energy metabolism. PLoS Computational Biology, 8(1), e1002352. (doi:10.1371/journal.pcbi.1002352)

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Abstract

Kinetic models of metabolism require detailed knowledge of kinetic parameters. However, due to measurement errors or lack of data this knowledge is often uncertain. The model of glycolysis in the parasitic protozoan Trypanosoma brucei is a particularly well analysed example of a quantitative metabolic model, but so far it has been studied with a fixed set of parameters only. Here we evaluate the effect of parameter uncertainty. In order to define probability distributions for each parameter, information about the experimental sources and confidence intervals for all parameters were collected. We created a wiki-based website dedicated to the detailed documentation of this information: the SilicoTryp wiki (http://silicotryp.ibls.gla.ac.uk/wiki/Gl​ycolysis). Using information collected in the wiki, we then assigned probability distributions to all parameters of the model. This allowed us to sample sets of alternative models, accurately representing our degree of uncertainty. Some properties of the model, such as the repartition of the glycolytic flux between the glycerol and pyruvate producing branches, are robust to these uncertainties. However, our analysis also allowed us to identify fragilities of the model leading to the accumulation of 3-phosphoglycerate and/or pyruvate. The analysis of the control coefficients revealed the importance of taking into account the uncertainties about the parameters, as the ranking of the reactions can be greatly affected. This work will now form the basis for a comprehensive Bayesian analysis and extension of the model considering alternative topologies.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Achcar, Dr Fiona and Breitling, Professor Rainer and Kerkhoven, Mr Eduard and Barrett, Professor Michael
Authors: Achcar, F., Kerkhoven, E.J., SilicoTryp Consortium, , Bakker, B.M., Barrett, M.P., and Breitling, R.
College/School:College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
College of Medical Veterinary and Life Sciences > Institute of Molecular Cell and Systems Biology
Journal Name:PLoS Computational Biology
Publisher:Public Library of Science
ISSN:1553-734X
ISSN (Online):1553-7358
Published Online:19 January 2012
Copyright Holders:Copyright © 2012 The Authors
First Published:First published in PLoS ONE 8(1):e100235
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
522081The silicon trypanosome (SilicoTryp)Michael BarrettBiotechnology and Biological Sciences Research Council (BBSRC)BB/I004599/1III - BACTERIOLOGY