Rate of isotope exchange in enzyme-catalyzed reactions

Yagil, Gad; Hoberman, Henry D.

doi:10.1021/bi00829a049

Cited by 52 publications

(12 citation statements)

References 24 publications

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“…2 to Equation 7, using the rate constants in Table 1 LDH and V MCT is the equilibrium exchange velocity for the monocarboxylate transporters. Although this equation was derived for trace isotope exchange (20) it has also been shown to apply to bulk isotope exchange (21), as is the case here. The reaction is expected to be near to chemical equilibrium because only a very small fraction of pyruvate needs to undergo net conversion to lactate to achieve chemical equilibrium, whereas the whole pyruvate pool must exchange to achieve isotopic equilibrium.…”

Section: Dependence Of the Rate Ofmentioning

confidence: 98%

Kinetic Modeling of Hyperpolarized 13C Label Exchange between Pyruvate and Lactate in Tumor Cells

Witney¹,

Kettunen

Brindle

2011

Journal of Biological Chemistry

136

203

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Measurements of the kinetics of hyperpolarized 13 C label exchange between [1-13 C]pyruvate and lactate in suspensions of intact and lysed murine lymphoma cells, and in cells in which lactate dehydrogenase expression had been modulated by inhibition of the PI3K pathway, were used to determine quantitatively the role of enzyme activity and membrane transport in controlling isotope flux. Both steps were shown to share in the control of isotope flux in these cells. The kinetics of label exchange were well described by a kinetic model that employed rate constants for the lactate dehydrogenase reaction that had been determined previously from steady state kinetic studies. The enzyme showed pyruvate inhibition in steady state kinetic measurements, which the kinetic model predicted should also be observed in the isotope exchange measurements. However, no such pyruvate inhibition was observed in either intact cells or cell lysates and this could be explained by the much higher enzyme concentrations present in the isotope exchange experiments. The kinetic analysis presented here shows how lactate dehydrogenase activity can be determined from the isotope exchange measurements. The kinetic model should be useful for modeling the exchange reaction in vivo, particularly as this technique progresses to the clinic.Magnetic resonance spectroscopy is a powerful tool for the non-invasive investigation of cellular metabolism, in systems ranging from isolated cells, through perfused organs (1), and small animals to humans (2, 3). A fundamental limitation of magnetic resonance spectroscopy has been a lack sensitivity, which limits temporal resolution to the minute time scale and spatial resolution to 1-10 cm 3 , depending on the magnetic field strength and nucleus detected (4). The recent introduction of dissolution dynamic nuclear polarization (5), which can increase the sensitivity of the magnetic resonance experiment by more than 10,000-fold, has had a significant impact on the field (reviewed in Refs. 6 and 7), dramatically increasing the temporal resolution to the second time scale and the spatial resolution to the millimeter scale. With this technique the 13 C nucleus, in a 13 C-labeled cell metabolite, is hyperpolarized and then injected into the biological system, where this may be an intravenous injection into a small animal or human. The gain in sensitivity, due to hyperpolarization of the 13 C nucleus, means that there is now sufficient signal to image the distribution of the labeled metabolite in the body and, more importantly, its metabolism and conversion into other cellular metabolites. The main limitation is the relatively short lifetime of the polarization, which in the 13 C-labeled metabolites, which have been used to date, is between 10 and 30 s. This means that spectroscopic imaging must be accomplished within 2-3 min and the labeled molecule must be taken up by cells and metabolized very rapidly for a significant labeling of other cell metabolites within the lifetime of the polarization. Although other nuclei ca...

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Section: Dependence Of the Rate Ofmentioning

confidence: 98%

Kinetic Modeling of Hyperpolarized 13C Label Exchange between Pyruvate and Lactate in Tumor Cells

Witney¹,

Kettunen

Brindle

2011

Journal of Biological Chemistry

136

203

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“…Notably, flux balance analysis (FBA) (8)(9)(10)(11), a method for studying the capabilities of metabolic networks at steady state, constitutes an example of how the knowledge of a restricted set of parameters in a system, combined with the application of fundamental thermodynamic and evolutionary principles, can generate quantitative predictions and testable hypotheses. In FBA, the constraints imposed by stoichiometry in a chemical network at steady state are treated analogously to Kirchoff's law for the balance of currents in electric circuits (2,12). Thus, for each of M metabolites in a network, the net sum of all production and consumption fluxes, weighted by their stoichiometric coefficients, is zero:…”

mentioning

confidence: 99%

Analysis of optimality in natural and perturbed metabolic networks

Segrè

Vitkup

Church

2002

Proc. Natl. Acad. Sci. U.S.A.

1,250

1,170

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An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism.

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“…The experimental points lie approximately on a hyperbola characterized by a 'Km' of about 4,UM. It is possible to derive an equation describing the methyl-group equilibration rate across lactate dehydrogenase (Silverstein & Boyer, 1964;Yagil & Hoberman, 1969). We may write the mechanism thus (Borgmann et al, 1974):…”

Section: Resultsmentioning

confidence: 99%

Studies of lactate dehydrogenase in the purified state and in intact erythrocytes

Simpson¹,

Brindle²,

Brown³

et al. 1982

Biochemical Journal

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Lactate dehydrogenase in intact erythrocytes was studied by observing isotope exchange between lactate and pyruvate by p.m.r. The inhibition of the enzyme in intact cells by both oxalate and pyruvate was found to be similar to that of the purified enzyme. The activity of the enzyme in intact cells indicates that the free solution NAD+ + NADH concentration in erythrocytes is about 10 microM whereas the total extractable NAD+ + NADH is about 80 nmol/ml of cell water.

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Rate of isotope exchange in enzyme-catalyzed reactions

Cited by 52 publications

References 24 publications

Kinetic Modeling of Hyperpolarized 13C Label Exchange between Pyruvate and Lactate in Tumor Cells

Kinetic Modeling of Hyperpolarized 13C Label Exchange between Pyruvate and Lactate in Tumor Cells

Analysis of optimality in natural and perturbed metabolic networks

Studies of lactate dehydrogenase in the purified state and in intact erythrocytes

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