Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism

Files in This Item:
File Description SizeFormat 
Paper86.pdf305.16 kBAdobe PDFDownload
Title: Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism
Authors: Fleming, R.M.T.
Thiele, I.
Provan, G.
et al.
Permanent link: http://hdl.handle.net/10197/4994
Date: Jun-2010
Abstract: The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in Escherichia coli and compare favourably with in silico prediction by flux balance analysis.
Type of material: Journal Article
Publisher: Elsevier
Copyright (published version): 2010 Elsevier
Keywords: Systems biology;Constraint-based modelling;Linear polytope;Logarithmic polytope;Algebraic geometry
DOI: 10.1016/j.jtbi.2010.02.044
Language: en
Status of Item: Peer reviewed
Appears in Collections:SBI Research Collection

Show full item record

SCOPUSTM   
Citations 10

33
Last Week
0
Last month
checked on Jun 23, 2018

Page view(s) 50

41
checked on May 25, 2018

Download(s) 50

147
checked on May 25, 2018

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.