Research

OpenFLUX: efficient modelling software for ¹³C-based metabolic flux analysis

Lake-Ee Quek¹ , Christoph Wittmann² , Lars K Nielsen¹ and Jens O Krömer¹

¹  Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, QLD 4072, Australia

²  Institute of Biochemical Engineering, Technische Universität Braunschweig, 38106 Braunschweig, Germany

author email corresponding author email

Microbial Cell Factories 2009, 8:25doi:10.1186/1475-2859-8-25

Published:	1 May 2009

Abstract

Background

The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i) tracer cultivation on ¹³C substrates, (ii) ¹³C labelling analysis by mass spectrometry and (iii) mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis.

Results

We have developed OpenFLUX as a user friendly, yet flexible software application for small and large scale ¹³C metabolic flux analysis. The application is based on the new Elementary Metabolite Unit (EMU) framework, significantly enhancing computation speed for flux calculation. From simple notation of metabolic reaction networks defined in a spreadsheet, the OpenFLUX parser automatically generates MATLAB-readable metabolite and isotopomer balances, thus strongly facilitating model creation. The model can be used to perform experimental design, parameter estimation and sensitivity analysis either using the built-in gradient-based search or Monte Carlo algorithms or in user-defined algorithms. Exemplified for a microbial flux study with 71 reactions, 8 free flux parameters and mass isotopomer distribution of 10 metabolites, OpenFLUX allowed to automatically compile the EMU-based model from an Excel file containing metabolic reactions and carbon transfer mechanisms, showing it's user-friendliness. It reliably reproduced the published data and optimum flux distributions for the network under study were found quickly (<20 sec).

Conclusion

We have developed a fast, accurate application to perform steady-state ¹³C metabolic flux analysis. OpenFLUX will strongly facilitate and enhance the design, calculation and interpretation of metabolic flux studies. By providing the software open source, we hope it will evolve with the rapidly growing field of fluxomics.