Bioinformatics Advance Access published online on July 7, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti573
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1 Departamento de Bioquimica i Biologia Molecular, Facultat de Quimica and CERQT at Parc Cientic de Barcelona, Barcelona, Catalunya, Spain
* 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 provides a unique method for assessing metabolic fluxes in whole cells. However, due 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 with other biochemical information. Method: We present software that integrates kinetic modeling with isotopomer distribution analysis. It solves the ordinary differential equations (ODEs) 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 (Selivanov et al., 2004), 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 available free from: http://www.bq.ub.es/bioqint/selivanov.htm.
Received April 22, 2005
Revised June 3, 2005
Accepted July 5, 2005
Article
Rapid simulation and analysis of isotopomer distributions using constraints based on enzyme mechanisms: an example from HT29 cancer cells
2 A.N.Belozersky Institute of Physico-Chemical Biology, Moscow State University, 199899, Moscow, Russia
3 School of Molecular and Microbial Biosciences, University of Sydney, NSW, Australia
4 Department of Pediatrics, Harbor-UCLA Medical Center, Research and Education Institute, Torrance, CA, 90502, USA
Marta Cascante, E-mail: martacascante{at}ub.edu
Abstract 
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  R. J. Gillies, I. Robey, and R. A. Gatenby Causes and Consequences of Increased Glucose Metabolism of Cancers J. Nucl. Med., June 1, 2008; 49(Suppl_2): 24S - 42S. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 V. A. Selivanov, S. Marin, P. W. N. Lee, and M. Cascante Software for dynamic analysis of tracer-based metabolomic data: estimation of metabolic fluxes and their statistical analysis Bioinformatics, November 15, 2006; 22(22): 2806 - 2812. [Abstract] [Full Text] [PDF]
|
|