Abstract
BackgroundExpression of cell phenotypes highly depends on metabolism that supplies matter and energy. To achieve proper utilisation of the different metabolic pathways, metabolism is tightly regulated by a complex regulatory network composed of diverse biological entities (genes, transcripts, proteins, signalling molecules…). The integrated analysis of both regulatory and metabolic networks appears very insightful but is not straightforward because of the distinct characteristics of both networks. The classical method used for metabolic flux analysis is Flux Balance Analysis (FBA), which is constraint-based and relies on the assumption of steady-state metabolite concentrations throughout the network. Regarding regulatory networks, a broad spectrum of methods are dedicated to their analysis although logical modelling remains the major method to take charge of large-scale networks.ResultsWe present FlexFlux, an application implementing a new way to combine the analysis of both metabolic and regulatory networks, based on simulations that do not require kinetic parameters and can be applied to genome-scale networks. FlexFlux is based on seeking regulatory network steady-states by performing synchronous updates of multi-state qualitative initial values. FlexFlux is then able to use the calculated steady-state values as constraints for metabolic flux analyses using FBA. As input, FlexFlux uses the standards Systems Biology Markup Language (SBML) and SBML Qualitative Models Package (“qual”) extension (SBML-qual) file formats and provides a set of FBA based functions.ConclusionsFlexFlux is an open-source java software with executables and full documentation available online at http://lipm-bioinfo.toulouse.inra.fr/flexflux/. It can be defined as a research tool that enables a better understanding of both regulatory and metabolic networks based on steady-state simulations. FlexFlux integrates well in the flux analysis ecosystem thanks to the support of standard file formats and can thus be used as a complementary tool to existing software featuring other types of analyses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0238-z) contains supplementary material, which is available to authorized users.
Highlights
Expression of cell phenotypes highly depends on metabolism that supplies matter and energy
We have developed FlexFlux, a tool that allows the analysis of both qualitative regulatory networks and genome-scale metabolic networks
In order to illustrate FlexFlux’s capabilities in combining gene regulation and Flux Balance Analysis (FBA), we performed simulation of the biomass production by Escherichia coli in environments composed of lactose and/or D-glucose using the reconstructed genome-scale metabolic model of E. coli [37] and a qualitative model of the lac operon [38, 39] that we translated into Systems Biology Markup Language (SBML)-qual format
Summary
Expression of cell phenotypes highly depends on metabolism that supplies matter and energy. The classical method used for metabolic flux analysis is Flux Balance Analysis (FBA), which is constraint-based and relies on the assumption of steady-state metabolite concentrations throughout the network. A very popular approach to study metabolic networks is the use of a constraint-based method called Flux Balance Analysis (FBA) [2]. Given a biological objective (like growth or metabolite production), the space of optimal solutions for the reaction fluxes can be very quickly solved by linearprogramming computation even for large networks. This calculation only relies on knowing reaction stoichiometry and user-defined input flux values. For a review of differences and specificities of some of these tools, see [10]
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