#F.lux free software#
#F.lux free free#

Flux analysis is carried out independently from energy and redox balancing, because the balancing equations only involve the carbon backbone. Redundant pathways that contribute differently to tracer distribution can thus be resolved. There are mainly two different approaches to extract flux information from the labelling patterns: by model-based flux fitting, and by analytical interpretation of flux ratios (both approaches briefly reviewed in ). In such studies, after feeding 13C-labelled substrate(s), one measures the 13C tracer enrichment patterns of metabolites that are rich in flux information, using instruments such as nuclear magnetic resonance spectroscopy (NMR) or mass spectrometry (MS). 13C-based MFA therefore is a powerful extension of MFA.

State-of-art flux analysis today includes the use of stable isotopes to overcome problems such as incomplete resolution of important cellular pathways or the need to rely on stoichiometric parameters with high uncertainty such as ATP yield (Y x/ATP) or P/O ratio which are inherently linked to the purely stoichiometric approaches. Metabolic flux analysis is particular important in rational strain engineering, where we specifically seek to manipulate the metabolic phenotype.ĭue to the high complexity of the examined metabolic network, flux analysis typically involves the use of a stoichiometric model, in which the metabolic reactions available to the cell are parameterized before the fluxes are estimated from experimental data. Metabolic fluxes most closely reflect the underlying metabolic phenotype, whereas other 'omics approaches only yield a sense of metabolic capacities (transcriptomics/proteomics) or thermodynamic driving forces (metabolomics). Metabolic flux analysis (MFA) plays a central role in metabolic engineering and systems biology.

#F.lux free software#

By providing the software open source, we hope it will evolve with the rapidly growing field of fluxomics. OpenFLUX will strongly facilitate and enhance the design, calculation and interpretation of metabolic flux studies. We have developed a fast, accurate application to perform steady-state 13C metabolic flux analysis. It reliably reproduced the published data and optimum flux distributions for the network under study were found quickly (<20 sec).

#F.lux free free#

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. 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. 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 application is based on the new Elementary Metabolite Unit (EMU) framework, significantly enhancing computation speed for flux calculation.

We have developed OpenFLUX as a user friendly, yet flexible software application for small and large scale 13C metabolic flux analysis.

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. 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. 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.