The control of metabolic pathways

All enzymes exhibit various features that could conceivably be elements in the regulation of their activity in cells. All have a characteristic pH optimum which makes it possible for their catalytic rates to be altered by changes in intracellular pH (e.g. in ribulose diphosphate carboxylase(l7 ). The activities also depend on the concentration of substrates, which may vary according to intracellular conditions. Moreover, many require metal ions or vitamins, and the activity of enzymes may be a function of the concentrations in which such materials are present (e.g. the effect of iron limitation on the citric acid fermentation of Aspergillus niger ). However, over and above these factors, some enzymes have other properties that 

In allosteric enzymes, the activity of the enzyme is modulated by a non-covalently bound metabolite at a site on a protein other than the catalytic site. Normally, this results in a conformational change, which makes the catalytic site inactive or less active. Covalent modulated enzymes are interconverted between active and inactive forms by the action of other enzymes, some of which are modulated by allosteric-type control. Both of these control mechanisms are responsive to changes in cell conditions and typically the response time in allosteric control is a matter of seconds as compared with minutes in covalent modulation. A third type of control, the control of enzyme synthesis at the transcription stage of protein synthesis (see Appendix 5.6), can take several hours to take effect. 

The concept of control of metabolic activity by allosteric enzymes or the control of enzyme activity by ligand-induced conformational changes arose from the study of metabolic pathways and their regulatory enzymes. A good example is the multi-enzymatic sequence catalysing the conversion of L-threonine to L-isoleucine shown in Fig. 5.32. 

The first enzyme in the sequence, L-threonine dehydratase, is strongly inhibited by L-isoleucine, the end product, but not by any other intermediates in the sequence. 

This enzymatic pathway (E, to Es) is inhibited by its product isoleucine at the first step E, 

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Altering the control of metabolic pathways can also be achieved by genetic manipulation. As proteins are generated using the template stored as a fragment of DNA, the structure of the allosteric enzyme may be altered so that there is little or no regulatory control. It is therefore possible to generate mutants that over-produce metabolites, and techniques based on this principle have been most widely exploited in amino-acid and nucleotide production 2 . 

In biological systems the rates of many enzymes are altered by the presence of other molecules such as activators and inhibitors (collectively known as effectors). A common theme in the control of metabolic pathways is when an enzyme early on in the pathway is inhibited by an end-product of the metabolic pathway in which it is involved. This is called feedback inhibition and often takes place at the committed step in the pathway (conversion of A to B in Fig. la). The committed step is the first step to produce an intermediate which is unique to the pathway in question, and therefore normally commits the metabolite to further metabolism along that pathway. Control of the enzyme which carries out the committed step of a metabolic pathway conserves the metabolic energy supply of the organism, and prevents the build up of large quantities of unwanted metabolic intermediates further along the pathway. 

K and h represent a kind of Michaelis constant and the Hill coefficient, respectively. If Vmax is known, these constants can be calculated from the slope and intercept of the Hill plot (eqn [15]). If the Hill coefficient results equal to one, then there is no coope-rativity and the graph is hyperbolic. An increasing value of h will show an increasingly sigmoidal curve with positive cooperativity for the substrate. A value less than one shows negative cooperativity. The reaction rate of these enzymes is easily controlled by allosteric effectors, activators, or inhibitors, this mechanism being of crucial importance for the control of metabolic pathways. Equally important, this mechanism can also be used for the detection of analytes. 

E. Voit, Mathematical Modeling as a Tool for Decoding the Control of Metabolic Pathways , in Glycolysis Regulation, Processes and Diseases, ed. P. N. Lithaw, Nova Science Publishers, Inc. Hauppauge, N. Y., 2009,... 

The development of kinetic schemes for sequences of enzyme reactions contributes to the resolution of two problems. The first of these, the more complex one, concerns the study of the control of metabolic pathways and has been of major interest to biochemists for some time. Two related approaches to the problem have been developed for the interpretation of the behaviour of large assemblies of coupled enzyme reactions. Models can be made which contain the differential equations for the progress of the reactions for all the enzymes of a system. The numerical solutions of this set of equations can be compared with the experimental data for the concentrations of intermediates and their rates of change. Iterative improvements of the model can then be made. Alternatively, if data are only available for a... 

From these various considerations we can now see that a finite number of regulatory principles are involved in the control of metabolic pathways. In theory, when all of the control principles are known, it should be possible to deduce the consequences of failure of these control mechanisms and to determine whether means of correction are possible and what these means should be. 

If the kinetics of the reaction disobey the Michaelis-Menten equation, the violation is revealed by a departure from linearity in these straight-line graphs. We shall see in the next chapter that such deviations from linearity are characteristic of the kinetics of regulatory enzymes known as allosteric enzymes. Such regulatory enzymes are very important in the overall control of metabolic pathways. 

The wide gap between the two opposing theories, replication first and metabolism first , was analysed by Pross from the Ben Gurion University of the Negev (Israel). Pross concludes that replication came first He is convinced that a causality between the two theories can only be established if it is assumed that the replication-first thesis is correct. His analysis also shows that more of the experimental results and theoretical rationales favour the replication thesis. The author finds his assumption justified that life processes are strongly kinetically controlled and that the development of metabolic pathways can only be understood if life is considered as a manifestation of replicative chemistry (Pross, 2004). 

In this chapter we will consider definitions of metabolism the biochemistry-physiology continuum. The concept of metabolic pathways and their organization and control of metabolism are likened to a road map involving flow of substrates but with mechanisms to accelerate or slow down pathways or to direct substrates through alternative routes. 

Glycolysis and the Krebs TCA cycle as models of control of metabolic pathways... 

In the preceding chapter, I emphasized the importance of carbohydrates as sources of metabolic energy. I also introduced the idea of metabolic pathways. Now it is time to pull those two themes together and understand how the pathways for metabolism of carbohydrates yield useful metabolic energy and how these processes are controlled. On the way, we will learn how a number of important drugs for human medicine work their therapeutic magic. 

The activities of metabolic pathways in cells are regulated by control of the activities of certain enzymes. 

The computer simulation is one of the essential means to investigate dynamic and steady-state behavior as well as control of metabolic pathways. A metabolic simulator is a computer program that performs one or several of the tasks including solving the steady state of a metabolic pathway, dynamically simulating a metabolic pathway, or calculating the control coefficient of a metabolic pathway. Its mathematical model generally consists of a set of differential equations derived from rate equations of the enzymatic reactions of the pathway. 

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 ... 

After the series of metabolic pathways had been elucidated for the three model compounds 1-3, these data were implemented into the mathematical model PharmBiosim. The nonlinear system s response to varying ketone exposure was studied. The predicted vanishing of oscillatory behavior for increasing ketone concentration can be used to experimentally test the model assumptions in the reduction of the xenobiotic ketone. To generate such predictions, we employed as a convenient tool the continuation of the nonlinear system s behavior in the control parameters. This strategy is applicable to large systems of coupled, nonlinear, ordinary differential equations and shall together with direct numerical simulations be used to further extend PharmBiosim than was sketched here. This model already allows more detailed predictions of stereoisomer distribution in the products. 

Gene regulation represents the most basic level of metabolic control. Although there are few examples in the alkaloid literature, the post-translational regulation of enzymes can also exert considerable influence over the control of metabolic flux. Recent work in our laboratory suggests that enzymatic controls function of the regulation in alkaloid biosynthesis. (5)-Norcoclaurine is accepted as the central precursor to all BAs produced in plants.6,7 However, NCS was first isolated based on its ability to convert dopamine and 3,4-dihydroxyphenylacetaldehyde (3,4-DHPAA) to the tetrahydroxylated alkaloid (S)-norlaudanosoline.129 The ability of NCS to accept either 4-HPAA or 3,4-DHPAA contributed to the incorrect conclusion that (S)-norlaudanosoline is a common pathway intermediate. However, only (5)-norcoclaurine has been detected in plants. 

Connectivity theorems allow to relate the control coefficients (systemic properties) to the elasticity coefficients (properties of the network s enzymes individually as if in isolation) (Westerhoff and Van Dam 1987 Heinrich and Schuster 1996 Fell 1997). The connectivity theorems have given us a strong insight into the functioning of metabolic pathways. For example, it follows directly from these theorems that enzymes that are very sensitive to the concentrations of metabolites, such as substrates, products and allosteric effectors, tend to have little control over the flux. This is illustrated by overproduction of phosphofructokinase in bakers yeast, an enzyme often referred to textbooks as rate-limiting. Yet, overproduction of phosphofructokinase does not lead to a significant flux increase, since the cell compensates by lowering the level of its allosteric effector fructose 2,6-bisphosphate (Schaaff et al. 1989 Davies and Brindle 1992). 

In addition to regulating the direction of metabolic pathways, cells, especially those in multicellular organisms, also exert control at three different levels allosteric enzymes, hormones, and enzyme concentration. 

The physiological functions of hormones have been broadly categorized into those that (1) affect growth and development, (2) exert homeostatic control of metabolic pathways, and (3) regulate the production, use, and storage of energy. The descriptions below illustrate examples of these functions and mechanisms of control of hormone secretion. 

We focus on the combination of transcriptomics and metabolomics and more specifically on microarray data, which is currently the most used method for gene expression profiling and is used on a routine basis. In the first paragraphs, we briefly revise the extraction of mRNA or metabolites, their measurement, quality control of data, and analysis methods. Afterward two different types of data fusion and recent tools and publications are reviewed, followed by visualization methods for obtained data. Lastly, the metabolite annotation Web server MassTRIX is presented. This Web server allows combined analysis of transcriptomic and metabolomic data in the context of metabolic pathways. We compared the metabolomics part against similar tools and give a short outlook on the next version of MassTRIX, MassTRIX 4. 

An important general principle of metabolism is that biosy ithetic and degradative pathways are almost always distinct. This separation is necessary for energetic reasons, as will be evident in subsequent chapters. It also facilitates the control of metabolism,... 

Aside from the inordinately dominant light of molecular genetics, the new wave in biochemistry today is, what has come to be called, metabolic control analysis (MCA) (Comish-Bowden and Cardenas, 1990). The impetus behind this wave is the desire to achieve a holistic view of the control of metabolic systems, with emphasis on the notion of system. The classical, singular focus on individual, feedback-modulated (e.g., allosteric), rate-limiting enzymes entails a naive and myopic view of metabolic regulation. It has become increasingly evident that control of metabolic pathways is distributive, rather than localized to one reaction. MCA places a given enzyme reaction into the kinetic context of the network of substrate-product connections, effector relationships, etc., as supposedly exist in situ, it shows that control of fluxes, metabolite concentrations, inter alia, is a systemic function and not an inherent property of individual enzymes. Such... 

The 1950s saw a change in emphasis from the analysis of bio-chemistry-as-kinetics to that of biochemistry-as-information. The theoretical rationale for this transition was provided by the growth of the new sciences associated with the development of computers. Theories of control , feedback , and information transfer were collated in 1948 by the American engineer and mathematician Norbert Wiener under the name of cybernetics. As more and more became known about the mechanisms of individual enzymic reactions, about their energy-requirements, and about the workings of series of enzymes in the harmony of metabolic pathways, biochemists seized on these new concepts in order to probe the ways in which the cell controlled and regulated its own metabolism how, so to speak, it decided at any one time... 

The cell achieves its efficiency, stability, and responsiveness through the use of metabolic pathways. A metabolic pathway is a sequence of enzyme-catalyzed reactions in which the product of one reaction is the substrate for the next. Usually, a pathway ends with the production of a particular product, such as an amino acid needed for protein synthesis. A particular starting material, such as glucose, may be used for a variety of purposes. In this case, the metabolic pathways have an initial section that is common to each purpose eventually, each pathway splits off into its own section. At this point, a key enzyme controls the flow of substrate into the specific section of the pathway. This enzyme is controlled allosterically, typically by a product of the pathway, in a negative feedback loop, as described below. This first step on a unique pathway is called the committed step or committed reaction. 

Allosteric enzymes are used by the body to provide feedback control of metabolic pathways and maintain appropriate levels of product. The activity of an allosteric enzyme is modulated by binding substrate and/or nonsubstrate effectors. Allosteric means having an effect at a site different from the one immediately involved. 

Chemotactic behavior and the control of metabolism are examples of complex phenotypes with complicated networks and pathways of signaling and other proteins. In the case of metabolism, the rules describing complex, context-dependent processes depend dir ectly on thermodynamics and kinetics. Analyses of metabolic flux show the principle of distributed control governing the phenotype in mammalian and bacterial systems interacting with the environment, and explain the robust nature of these networks. 

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