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Bioinformatics Advance Access originally published online on July 7, 2005
Bioinformatics 2005 21(17):3558-3564; doi:10.1093/bioinformatics/bti573
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Rapid simulation and analysis of isotopomer distributions using constraints based on enzyme mechanisms: an example from HT29 cancer cells

Vitaly A. Selivanov 1, Ludmilla E. Meshalkina 2, Olga N. Solovjeva 2, Philip W. Kuchel 3, Antonio Ramos-Montoya 1, German A. Kochetov 2, Paul W. N. Lee 4 and Marta Cascante 1,*

1Departamento de Bioquimica i Biologia Molecular, Facultat de Quimica and CERQT at Parc Cientic de Barcelona Barcelona, Catalunya, Spain
2A.N.Belozersky Institute of Physico-Chemical Biology, Moscow State University 199899 Moscow, Russia
3School of Molecular and Microbial Biosciences, University of Sydney NSW, Australia
4Department of Pediatrics, Harbor-UCLA Medical Center, Research and Education Institute Torrance, CA 90502, USA

*To whom correspondence should be addressed.

Motivation: Addition of labeled substrates and the measurement of the subsequent distribution of the labels in isotopomers in reaction networks provide a unique method for assessing metabolic fluxes in whole cells. However, owing to insufficiency of information, attempts to quantify the fluxes often yield multiple possible sets of solutions that are consistent with a given experimental pattern of isotopomers. In the study of the pentose phosphate pathways, the need to consider isotope exchange reactions of transketolase (TK) and transaldolase (TA) (which in past analyses have often been ignored) magnifies this problem; but accounting for the interrelation between the fluxes known from biochemical studies and kinetic modeling solves it. The mathematical relationships between kinetic and equilibrium constants restrict the domain of estimated fluxes to the ones compatible not only with a given set of experimental data, but also with other biochemical information.

Method: We present software that integrates kinetic modeling with isotopomer distribution analysis. It solves the ordinary differential equations for total concentrations (accounting for the kinetic mechanisms) as well as for all isotopomers in glycolysis and the pentose phosphate pathway (PPP). In the PPP the fluxes created in the TK and TA reactions are expressed through unitary rate constants. The algorithms that account for all the kinetic and equilbrium constant constraints are integrated with the previously developed algorithms, which have been further optimized. The most time-consuming calculations were programmed directly in assembly language; this gave an order of magnitude decrease in the computation time, thus allowing analysis of more complex systems. The software was developed as C-code linked to a program written in Mathematica (Wolfram Research, Champaign, IL), and also as a C++ program independent from Mathematica.

Results: Implementing constraints imposed by kinetic and equilibrium constants in the isotopomer distribution analysis in the data from the cancer cells eliminated estimates of fluxes that were inconsistent with the kinetic mechanisms of TK and TA. Fluxes measured experimentally in cells can be used to estimate better the kinetics of TK and TA as they operate in situ. Thus, our approach of integrating various methods for in situ flux analysis opens up the possibility of designing new types of experiments to probe metabolic interrelationships, including the incorporation of additional biochemical information.

Availability: Software is available freely at: http://www.bq.ub.es/bioqint/selivanov.htm

Contact: martacascante{at}ub.edu


Received on April 22, 2005; revised on June 3, 2005; accepted on July 5, 2005

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