Metabolic flux balance analysis applications

Considering a trade-off between knowledge that is required prior to the analysis and predictive power, stoichiometric network analysis must be regarded as the most successful computational approach to large-scale metabolic networks to date. It is computationally feasible even for large-scale networks, and it is nonetheless far more predictive that a simple graph-based analysis. Stoichiometric analysis has resulted in a vast number of applications [35,67,70 74], including quantitative predictions of metabolic network function [50, 64]. The two most well-known variants of stoichiometric analysis, namely, flux balance analysis and elementary flux modes, constitute the topic of Section V. 

An analysis of the right nullspace K provides the conceptual basis of flux balance analysis and has led to a plethora of highly successful applications in metabolic network analysis. In particular, all steady-state flux vectors v° = v(S°,p) can be written as a linear combination of columns Jfcx- of K, such that... 

Despite its widely recognized limitations, flux balance analysis has resulted in a large number of successful applications [35, 67, 72 74], including several extensions and refinements. See Ref. [247] for a recent review. Of particular interest are recent efforts to augment the stoichiometric balance equations with thermodynamic constraints providing a link between concentration and flux in the constraint-based analysis of metabolic networks [74, 149, 150]. For a more comprehensive review, we refer to the very readable monograph of Palsson [50]. 

Flux balance analysis has been used for over 15 yr to study the metabolic flux distribution. Initially, the applications of FBA were primarily educational however, recently, the utility has grown. The FBA has been applied to study the effect of gene deletions, the design of bacterial metabolism for industrial and environmental applications, or for the computational exploration of cellular physiology. Metabolic engineering has been successfully applied to engineer micro-organisms to produce valuable biochemicals... 

Whereas detailed dynamic models can precisely answer questions on cellular behavior, the widespread application of such approaches has been hampered by the lack of kinetic information. In the absence of kinetic information, a method known as flux balance analysis (FBA) has been developed to analyze the metabolic capabilities of a cellular system based on mass balance constraints [Varma and Palsson 1994 Edwards et al. 1999 Edwards and Palsson 2000],... 

The measurement of internal metabolic fluxes is more difficult. The direct measurement of intracellular fluxes is possible with in vivo nuclear magnetic resonance (NMR) spectroscopy. However, the inherent insensitivity of NMR limits its applicability. An improvement over this approach can be found with isotopic tracer techniques [8]. In isotope tracer methods the cells to be studied are provided with a substrate specifically labeled with a detectable isotope (usually or C). The incorporation of label into cellular material and by-products is governed by the fluxes through the biochemical pathways. The quantity and distribution of label is measured and combined with knowledge of the metabolic network to estimate some of the intracellular fluxes. The choices of substrate labeling patterns, as well as which by-products to measure, are guided by careful analysis of the assumed biochemical network. These experiments are usually performed at isotopic steady state so that the flow of isotope into each atom of a metaboHte equals the flux out. For the nth atom of the fcth metabolite the flux balance is [9] ... 

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