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Bioinformatics Advance Access originally published online on May 19, 2005
Bioinformatics 2005 21(15):3329-3330; doi:10.1093/bioinformatics/bti502
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

MFAML: a standard data structure for representing and exchanging metabolic flux models

Hongseok Yun 1, Dong-Yup Lee 1,2, Joonwoo Jeong 1, Seunghyun Lee 1 and Sang Yup Lee 1,2,*

1Bioinformatics Research Center, Korea Advanced Institute of Science and Technology 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea
2Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering, Department of BioSystems, BioProcess Engineering Research Center, Korea Advanced Institute of Science and Technology 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea

*To whom correspondence should be addressed.


   Abstract
TOP
 Abstract
INTRODUCTION
 SYSTEM OVERVIEW
 METABOLIC FLUX ANALYSIS
 REFERENCES
 

Summary: MFAML is a standard data structure designed for the formal representation and effective exchange of metabolic flux models. It allows for the explicit description of stationary states of a metabolic system by defining environmental/genetic conditions of the system, e.g. flux measurements, balancing constraints and physiological objectives as well as basic information on metabolites and reactions. In addition, a library of MFAML comprising a model parser and a converter provides an open framework for establishing the pipeline from metabolic modeling to metabolic flux analysis.

Availability: MFAML (version 1) is fully described and available at http://mbel.kaist.ac.kr/mfaml/

Contact:leesy{at}kaist.ac.kr


   INTRODUCTION
TOP
 Abstract
 INTRODUCTION
SYSTEM OVERVIEW
 METABOLIC FLUX ANALYSIS
 REFERENCES
 
With the rapid advances in bioinformatics, it is becoming increasingly important to develop information standards to define, share and evaluate computational models of complex biological systems. For this purpose, international communities and research teams have been developing several eXtensible Markup Language (XML)-based modeling languages (Achard et al., 2001). For example, the Systems Biology Markup Language (SBML) (Hucka et al., 2003) is a representative open-standard in the systems biology area, providing several standard structures including a modeling structure for dynamic simulation of the kinetic model. Nevertheless, to our knowledge there is no standard format suitable for implementing metabolic flux analysis (MFA), which is one of the most widely adopted techniques for quantitative analysis of metabolic fluxes (Varma and Palsson, 1994; Edwards et al., 2001). There has recently been an attempt to represent the flux balance model by annotating conditional information on upper and lower flux limits into the existing SBML structure (Segrè et al., 2003). However, it only deals with the information on the flux limits associated with each flux enumerated in ListOfReaction element of SBML schema, and thus is not yet suitable for general use in MFA. In this article, we report a new modeling language, Metabolic Flux Analysis Markup Language (MFAML), for the formal representation and linear programming (LP)-based simulation of metabolic flux models having constraints and objective functions, and present an open framework for the effective exchange of suchmodels.


   SYSTEM OVERVIEW
TOP
 Abstract
 INTRODUCTION
 SYSTEM OVERVIEW
METABOLIC FLUX ANALYSIS
 REFERENCES
 
MFAML provides a platform for modeling of metabolic networks and subsequent flux analyses as outlined in Figure 1. First, a standard data structure and specifications for MFA are defined to unambiguously represent the metabolic flux models. On the basis of this standard, the open MFAML library establishes an integrated environment for constructing, sharing and analyzing the flux models. The parser, with validation, allows the manipulation of the MFAML-based file describing the semantics of the metabolic network and associated flux conditions. Thus, a metabolic flux model can be effectively built and transformed into various formats for metabolic flux analysis by a subsequent converter, thereby rendering the model exchangeable. Finally, each formatted model can be quantitatively analyzed by using various analysis tools and programs.



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  		Fig. 1 A schematic diagram showing the environment for metabolic modeling and metabolic flux analysis via libMFAML. The libMFAML reads, writes and manipulates MFAML and SBML files (Parser) and converts them into various LP formats for flux analysis (Converter). The converted LP files can be imported into various LP solvers for further analysis. Alternatively, MetaFluxNet and other similar program packages can be used to conveniently handle the entire process.

 
Representation of metabolic systems
A standard structure of MFAML mainly consists of four components: Metabolite, Reaction, Condition and Solution. Among them, Metabolite and Reaction are slightly modified from basic model components in SBML (Hucka et al., 2003); the relevant information on reactions and metabolites can be defined in the elements of the existing ListOfReactions and ListOfSpecies structures of SBML to describe the structural properties of a metabolic system, e.g. biochemical reactions, reaction directions, stoichiometry and relevant information on metabolites. The Condition component specifies the stationary state of the metabolic system based on two elements of the ListOfConditions, flux variables (reaction) and balance constraints (metabolite), each of which contains conditional properties (e.g. constraints and objectives) for MFA. These conditional properties are often defined by the measured or desired internal and external (uptake or secretion) fluxes, genetic and environmental conditions, and desired physiological properties. In the Solution component, the solver status and the results of flux distribution under various conditions can be described.

Exchange of metabolic flux models
On the basis of the defined structure of MFAML, we provide the libMFAML which is an open-source library of an application programming interface (API) for reading, writing and manipulating MFAML files (Parser) and for converting them into the respective formats for flux analysis (Converter). They are implemented in C and C++ working on Windows, Linux and Solaris systems. We partially adopted the source codes of libSBML (http://www.sbml.org/libsbml.html) in the MFAML Parser, so that the SBML-based files can also be used. The Parser reads and compiles the input files, thereby checking that the relationships among the reaction–metabolite and reaction–condition, and flux limit rules are appropriately defined according to the MFAML structure. The Converter transforms the resulting representations into various modeling formats for LP standards. The API for converting MFAML or SBML to Mathematical Programming System (MPS), lp_solve (http://groups.yahoo.com/group/lp_solve), LINDO (http://www.lindo.com) or CPLEX (http://www.ilog.com) was partially adopted from the lp_solve 5.0 library. In addition, a MFAML conversion library was developed to convert MFAML or SBML to AMPL (http://www.ampl.com), MATLAB (http://www.mathworks.com) or GAMS (http://www.gams.com). Consequently, the libMFAML helps to establish an integrated environment for efficiently exchanging the metabolic flux models with other analyticaltools (Fig. 1).


   METABOLIC FLUX ANALYSIS
TOP
 Abstract
 INTRODUCTION
 SYSTEM OVERVIEW
 METABOLIC FLUX ANALYSIS
REFERENCES
 
MFA can be carried out using various LP solvers as shown in Figure 1. Alternatively, MetaFluxNet, which is a stand-alone program package for the modeling andsimulation of metabolic pathways (Lee et al., 2003), can be used to handle the entire process. The recent version of MetaFluxNet has incorporated the libMFAML as a module. Valid MFAML files can be loaded into MetaFluxNet, edited, translated into its internal format, exported in various LP formats, and are solved using its internal LP engine. Similarly, other analytical environments can be linked to LP analysis through MFAML. In this way, users can interpret and examine metabolic behaviors and changes in response to genetic and/or environmental modifications which can be explicitly defined in MFAML. In summary, MFAML supports in silico simulations of metabolic pathways in order to understand the metabolic status and to design the metabolic engineering strategies.


   Acknowledgments
 
This work was supported by the Korean Systems Biology Research Program (M10309020000-03B5002-00000) of the MOST and by the BK21 project. Further supports by LG Chem Chair Professorship, Microsoft and IBM-SUR program are greatly appreciated.

Conflict of Interest: none declared.

Received on April 1, 2005; revised on May 6, 2005; accepted on May 13, 2005

   REFERENCES
TOP
 Abstract
 INTRODUCTION
 SYSTEM OVERVIEW
 METABOLIC FLUX ANALYSIS
 REFERENCES
 

    Achard, F., et al. (2001) XML, bioinformatics and data integration. Bioinformatics, 17, 115–125[Abstract/Free Full Text].

    Edwards, J.S., et al. (2001) In silico predictions of Escherichi coli metabolic capabilities are consistent with experimental data. Nat. Biotechnol., 19, 125–130[CrossRef][ISI][Medline].

    Lee, D.-Y., et al. (2003) MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis. Bioinformatics, 19, 2144–2146[Abstract/Free Full Text].

    Hucka, M., et al. (2003) The Systems Biology Markup Language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics, 19, 524–531[Abstract/Free Full Text].

    Segrè, D., et al. (2003) From annotated genomes to metabolic flux models and kinetic parameter fitting. OMICS, 7, 301–316[CrossRef][Medline].

    Varma, A. and Palsson, B.O. (1994) Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technol., 12, 994–998[CrossRef].


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This Article
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