It Is All about MetabolicFluxes

Abstract

In the field of genomics there has been a move towards the development of novel experimental techniques that enable analysis of all components of a certain kind in a biological system, and this has resulted in the appearance of new methods for analyzing the omes. Obviously, in a given cellular system it is attractive to measure all the mRNAs, all the proteins, a large number of the metabolites, a large fraction of protein-protein or protein-DNA interactions, and so on, but a fundamental problem in functional genomics is integration of the information obtained, i.e., how this information can be integrated and lead to new insights into the functioning of cellular processes. Bioinformatics and advanced computer models are continuously supplying new methods for integration of data, and surely progress in the field of systems biology will eventually result in an ability to describe cellular functions in silico. In the race to obtain large amounts of data for phenotypic characterization of different cellular systems, a relatively simple experimental technique for quantitative determination of metabolic fluxes has escaped the attention of a large part of the biological research community; this technique has been used primarily by researchers in the field of metabolic engineering (1). The technique is based on relatively old principles from biochemistry, namely, feeding of specifically 13 C-labeled substrates to the cell for characterization of the metabolism. However, with the development of the necessary mathematical framework for analysis of data obtained from this type of analysis it has become possible to obtain estimates for the fluxes in the different parts of the central carbon metabolism. This information is obviously interesting in connection with improving metabolite production by a given microbial cell, but as demonstrated in a paper in this issue of Journal of Bacteriology (11), it also provides a very powerful tool for functional analysis of different mutant cells. In this short commentary the use of this technique for functional analysis and the advantages and limitations of different techniques for flux quantification are discussed, and some of the underlying methods are reviewed, Finally, some future perspectives are given. METABOLIC NETWORKSCellular metabolism is represented by a large number of metabolic reactions that are involved in the conversion of the carbon source into building blocks needed for macromolecular biosynthesis. Furthermore, there are specific reactions that ensure the constant supply of Gibbs free energy via ATP and redox equivalents (generally in the form of the cofactor NADPH) needed for biosynthesis of macromolecules. This large number of metabolic reactions forms a so-called metabolic network inside the cells, and as a result of reconstruction of the complete metabolic networks in different bacteria (6,17,18) and in the yeast Saccharomyces cerevisiae (8), more insight into the function of complete metabolic networks has been obtained. These reconstructed metabolic networks can b...

Metabolic flux analysis of wild-type Escherichia coli and mutants deficient in pyruvate-dissimilating enzymes during the fermentative metabolism of glucuronate

“…Metabolite balancing (Stephanopoulos et al, 1998;Romeo & Snoep, 2005;Nielsen, 2003), referred to here as in vivo MFA, was used to further investigate the differences between MG1655, Pdh2 and Pfl2. The resulting metabolic flux maps for the three strains during exponential growth are shown in Fig.…”

“…Murarka, J. M. Clomburg and R. Gonzalez of fluxes we used flux balance analysis (Edwards & Palsson, 2000), a technique widely applied to the study of microbial metabolism (Downs, 2006;Romeo & Snoep, 2005;Nielsen, 2003), and referred to here as in silico MFA. To this end, simulations were conducted in different scenarios by selectively relaxing or enforcing redox (R) and ATP (A) constraints (see Table 2 and Supplementary Information for details).…”

Wine Science in the Omics Era: The Impact of Systems Biology on the Future of Wine Research

“…For example, feeding of cells with 13 C-labeled glucose followed by analysis of the 13 C enrichment pattern in different intracellular metabolites establishes an experimental platform for the calculation of real flux estimates (Gombert et al, 2001). The tight connection of the different parts of metabolism means that changes in fluxes in one part of the metabolic network disseminate to many other related parts (Nielsen, 2003). Thus, with the development of the necessary mathematical frameworks, measurement of even a few metabolic fluxes may provide valuable information regarding complete metabolic networks (Wiechert et al, 1997).…”

MetDFBA: incorporating time-resolved metabolomics measurements into dynamic flux balance analysis

“…Unfortunately, intracellular fluxes cannot be measured directly but have to be estimated from concentration measurements. 11,12 Various experimental and associated computational methods have been developed to estimate dynamic fluxes through metabolic networks including kinetic models, 13 13 C-metabolic flux analysis (MFA), [14][15][16] and dynamic flux balance analysis (DFBA). 17,18 The development of kinetic models is hampered by limited availability and accuracy of information about condition-specific (in vivo) kinetic parameters, 19 13 C MFA is expensive and tracer availability is limited.…”