Analysis of Metabolic Fluxes

Once isolated, the natural H2 producers can be optimized by conventional mutagenesis, and they should be studied so that we can understand those features that make them the best H2 producers. This characterization would involve the analysis of metabolic fluxes (Stephanopoulos and Sinskey 1993 Schuster et al. 1999) and molecular genetics. It would result in new, previously unknown adaptations necessary for improved H2 production, and could provide information on the most important mutations that are required to obtain excellent H2 producers. Information obtained from these experiments should be used in genetic engineering approaches for optimizing H2 producers. Moreover, excellent H2 producers should be used in bioengineering approaches. 

Analysis of metabolic fluxes in non-growing/starved cells... 

Bushell, M.E., Kirk, S., Zhao, H.-J. and Avignone-Rossa, C.A. (2006) Manipulation of the physiology of clavulanic acid biosynthesis with the aid of metabolic flux analysis. Enzyme and Microbial Technology, 39, 149-157. 

A considerable improvement over purely graph-based approaches is the analysis of metabolic networks in terms of their stoichiometric matrix. Stoichiometric analysis has a long history in chemical and biochemical sciences [59 62], considerably pre-dating the recent interest in the topology of large-scale cellular networks. In particular, the stoichiometry of a metabolic network is often available, even when detailed information about kinetic parameters or rate equations is lacking. Exploiting the flux balance equation, stoichiometric analysis makes explicit use of the specific structural properties of metabolic networks and allows us to put constraints on the functional capabilities of metabolic networks [61,63 69]. 

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]. 

K. Raman and N. Chandra, Pathwayanalyser A systems biology tool for flux analysis of metabolic pathways. Nature Precedings, 2008. 

Metabolic control analysis (MCA) is the application of steady-state enzyme networks to the problem of the control of metabolic flux (Fell, 1992 Kacser and Burns, 1995). Consider a pathway ... 

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]. 

Metabolome represents the entire set of low-molecular-weight metabolites that are present in a cell and/or outside the cell under particular conditions [30]. Metabolite profiling allows comparative analysis of physiological states under different conditions e.g., a wild-type vs its mutants, and different culture conditions. Fluxome, the entire set of metabolic fluxes, can also be used for understanding the cellular... 

Fundamentals of Metabolic Flux Analysis Metabolite Balancing... 

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. 

Mathematical optimization deals with determining values for a set of unknown variables x, X2, , x , which best satisfy (optimize) some mathematical objective quantified by a scalar function of the unknown variables, F(xi, X2, , xn). The function F is termed the objective function bounds on the variables, along with mathematical dependencies between them, are termed constraints. Constraint-based analysis of metabolic systems requires definition of the constraints acting on biochemical variables (fluxes, concentrations, enzyme activities) and determining appropriate objective functions useful in determining the behavior of metabolic systems. 

As briefly outlined in Section 6.3, one of the theoretical frameworks in quantitative analysis of metabolic networks is metabolic control analysis. In metabolic control analysis, the enzyme elasticity coefficients provide empirical constraints between the metabolites concentrations and the reaction fluxes. These constraints can be considered in concert with the interdependencies in the J and c spaces that are imposed by the network stoichiometry. If the coefficients elk = (c / Ji)dJi/dck are known, then these values bind the fluxes and concentrations to a hyperplane in the (J, c) space. 

The concept that modules comprise the traditional pathways is gaining more focus as basic functional building blocks (20). Gene expression patterns in pathways and their formation of modules has been an intense topic of study (21, 22). These pathways combined with flux balance analysis have also provided interesting results about the metabolic pathway of yeast (23) and Escherichia coli (24). The latter involves steady-state analysis using reaction stoichiometry information, such as those stored in the KEGG REACTION database, and it is gaining renewed interest for systematic analysis of metabolic networks (6). 

Fig. 3 An example of metabolic flux analysis showing fluxes through the different metabolic pathways of S. cerevisiae under anaerobic growth. (Adapted from Ref.. )...

Cellular Metabolites. - A review of methods for the measurement of ml has been produced with 95 references. It examines the quantitative measurement of ml by mass spectrometry and in vivo NMR. The NMR chemical shifts and /-coupling values of 35 metabolites which can be detected by in vivo or in vitro investigations of the mammalian brain have been published. The principles and recent applications of dynamic nuclear polarisation, which combines the sensitivity to oxygen of EPR and the tractability of NMR imaging, have been reviewed with 244 references. A review of studies of intermediary metabolism, including the use of NMR in the analysis of substrate selection under in vivo conditions, has been produced. A review has been produced, with 74 references, on the study of metabolic flux and subcellular transport of metabolites using NMR. " ... 

F., and Stephanopoulos, G. (2010) Analysis of polyhydroxybutyrate flux limitations by systematic genetic and metabolic perturbations. Metab. Eng, 12, 187-195. 

However, much research remains to be done in this area. The thermodynamics of metabolic flux analysis has not yet been well established and free energy loss analysis based on metabolic flux analysis has only been applied to some particular problems, although there might be room for the development of a systematic methodology. 

Lee SY, Park JM, Kim TY (2011) Application of metabolic flux analysis in metabolic engineering. Methods Enzymol 498 67-93. Elsevier Inc... 

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