Reaction metabolic flux analysis

The following chapter shows the application of MS to metabolic flux analysis with different examples. Whereas some of them focus on flux quantification of only a single or a few selected reactions, others aim at the analysis of larger parts of the metabohsm. The overview given should illustrate the broad application potential of MS for metabohc flux analysis by examples from different fields of research. The majority of studies belongs to the medical field, whereas so far only few examples can be found in the area of biochemical engineering. 

Metabolic flux analysis Cellular metabolites and metabolic fluxes can be combined into a series of balance equations, not unlike a series of (bio)chemical reactions in a kinetic model. Metabolic flux analysis is the description of the components and their connections in a metabolic network. 

Like the examples mentioned above, most examples of metabolic flux analysis by metabolite balancing have redox balances as a central constraint used in the determination of the flux distribution. However, the redox balance is, especially under aerobic conditions, subject to uncertainties which make it less suitable for estimation of the fluxes. Part of the reason for this is to be found in futile cycles, e. g., oxidation of sulfides to disulfides, where reductive power is needed to reduce the disulfides. The net result of this reaction is reduction of molecular oxygen to water, and oxidation of NADPH to NADP+. Since the consumption rate of oxygen of these specific reactions is impossible to measure, the result may be that the NADPH consumption is underestimated. This is in accordance with the finding that when the NADPH-producing reactions are estimated independently of the NADPH-consuming reactions, there is usually a large excess of NADPH that needs to be oxidized by reactions not included in the network, e. g., futile cycles [11-13]. 

As we shall see, linear algebraic constraints arising from steady state mass balance form the basis of metabolic flux analysis (MFA) and flux balance analysis (FBA). Thermodynamic laws, while introducing inherent non-linearities into the mathematical description of the feasible flux space, allow determination of feasible reaction directions and facilitate the introduction of reactant concentrations to the constraint-based framework. 

Identifying constraints on reaction directions is essential for applications of metabolic flux analysis. However, in many applications the procedure used for determining reaction directions is not concretely defined. Typically, a subset of the reactions in a model is assigned as irreversible and the feasible directions are assigned based on information in pathway databases [59], In these applications, by treating certain reactions as implicitly unidirectional, biologically reasonable results can often be obtained without considering the system thermodynamics as outlined above. 

Analyses of Importance of Anaplerotic Reactions During Glutamate Overproduction Based on "C Metabolic Flux Analysis... 

Metabolic flux analysis (MFA) is a powerful tool used in the field of metabolic engineering to understand cellular metabolism and to quantitatively evaluate the effects of metabolic engineering. Metabolic flux is defined as the rate of metabolic reaction per unit cell mass. In MFA, a metabolic reaction model, including the metabolic reactions of interest, that is, equations expressing the material balances of each metabolite of the metabolic reactions, is constructed and the distribution of metabolic fluxes are determined based on the measurement of intracellular and extracellular metabolites [74]. 

However, FBA in itself is not sufficient to uniquely determine intracellular fluxes. In addition to the ambiguities with respect to the choice of the objective function, flux balance analysis is not able to deal with the following rather common scenarios [248] (i) Parallel metabolic routes cannot be resovled. For example, in the simplest case of two enzymes mediating the same reaction, the optimization procedure can only assign the sum of a flux of both routes, but not the flux of each route, (ii) Reversible reaction steps can not be resolved, only the sum of both directions, that is, the net flux, (iii) Cyclic fluxes cannot be resolved as they have no impact on the overall network flux, (iv) Futile cycles, which are common in many organisms, are not present in the FBA solution, because they are usually not optimal with respect to any optimization criterion. These shortcomings necessitate a direct experimental approach to metabolic fluxes, as detailed in the next section. 

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