Kinetic flux profiling for quantitation of cellular metabolic fluxes

241 Carl Icahn Laboratory, Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA.
Nature Protocol (Impact Factor: 9.67). 02/2008; 3(8):1328-40. DOI: 10.1038/nprot.2008.131
Source: PubMed


This protocol enables quantitation of metabolic fluxes in cultured cells. Measurements are based on the kinetics of cellular incorporation of stable isotope from nutrient into downstream metabolites. At multiple time points, after cells are rapidly switched from unlabeled to isotope-labeled nutrient, metabolism is quenched, metabolites are extracted and the extract is analyzed by chromatography-mass spectrometry. Resulting plots of unlabeled compound versus time follow variants of exponential decay, with the flux equal to the decay rate multiplied by the intracellular metabolite concentration. Because labeling is typically fast (t(1/2)<or=5 min for central metabolites in Escherichia coli), variations on this approach can effectively probe dynamically changing metabolic fluxes. This protocol is exemplified using E. coli and nitrogen labeling, for which quantitative flux data for approximately 15 metabolites can be obtained over 3 d of work. Applications to adherent mammalian cells are also discussed.

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    • "More explicitly, the rate of labeling of a metabolite pool is dependent upon the following: (1) the extent of labeling of the precursor substrate molecule(s) as label propagates through the system; (2) the size of the metabolite pool (a large pool will take longer to become fully labeled than a small one); and (3) the rate of conversion of precursor substrate(s) into the metabolite (the desired flux parameter). In the simple case of an irreversible monomolecular reaction, it is possible to estimate the flux by fitting the reactant labeling profiles to the solution of a single differential equation that describes these relationships, in an approach known as kinetic flux profiling (Yuan et al., 2006, 2008). However, in most cases, the complexity of the network increases the number of parameters that must be considered and the equations are no longer analytically solvable. "

    Plant physiology 09/2015; DOI:10.1104/pp.15.01082 · 6.84 Impact Factor
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    • "Relative amounts of metabolites were calculated by summing up all isotopomers of a given metabolite and normalized to the internal standard and cell number. Natural occurring 13 C was accounted for as described by Yuan et al. (2008). "
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    ABSTRACT: We discovered recently that the central metabolite α-ketoglutarate (α-KG) extends the lifespan of C. elegans through inhibition of ATP synthase and TOR signaling. Here we find, unexpectedly, that (R)-2-hydroxyglutarate ((R)-2HG), an oncometabolite that interferes with various α-KG-mediated processes, similarly extends worm lifespan. (R)-2HG accumulates in human cancers carrying neomorphic mutations in the isocitrate dehydrogenase (IDH) 1 and 2 genes. We show that, like α-KG, both (R)-2HG and (S)-2HG bind and inhibit ATP synthase and inhibit mTOR signaling. These effects are mirrored in IDH1 mutant cells, suggesting a growth-suppressive function of (R)-2HG. Consistently, inhibition of ATP synthase by 2-HG or α-KG in glioblastoma cells is sufficient for growth arrest and tumor cell killing under conditions of glucose limitation, e.g., when ketone bodies (instead of glucose) are supplied for energy. These findings inform therapeutic strategies and open avenues for investigating the roles of 2-HG and metabolites in biology and disease. Copyright © 2015 Elsevier Inc. All rights reserved.
    Cell metabolism 07/2015; 22(3). DOI:10.1016/j.cmet.2015.06.009 · 17.57 Impact Factor
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    • "Alternatively, the cells can first be separated from the broth by fast filtration and metabolism can be subsequently quenched in cold liquids such as liquid nitrogen [20] [21] and cold methanol [22] [23]. A derivative procedure developed by Yuan and coworkers [24] involves growing the cells directly on a membrane filter placed on top of the agarose plate and performing quenching by placing the filters in the cold organic solvent mixture. This approach makes it possible to extract labeled metabolic intermediates at the same time as ensuring separation of the extracellular metabolites. "
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    ABSTRACT: The analysis of metabolic intermediates is a rich source of isotopic information for (13)C-metabolic flux analysis ((13)C-MFA) and extends the range of its applications. The sampling of labelled metabolic intermediates is particularly important to obtain reliable isotopic information. The assessment of the different sampling procedures commonly used to generate such data is therefore crucial. In this work, we thoroughly evaluated several sampling procedures for stationary and non-stationary (13)C-MFA using Escherichia coli. We first analysed the efficiency of these procedures for quenching metabolism, and found that procedures based on cold or boiling solvents are reliable, in contrast to fast filtration, which is not. We also showed that separating the cells from the broth is not necessary in isotopic stationary state conditions. On the other hand, we demonstrated that the presence of metabolic intermediates outside the cells strongly affects the transient isotopic data monitored during non-stationary (13)C-labelling experiments. Meaningful isotopic data can be obtained by recovering intracellular labelled metabolites from pellets of cells centrifuged in cold solvent. If the intracellular pools are not separated from the extracellular ones, we showed that accurate flux maps can be established provided the contribution of exogenous compounds is taken into account in the metabolic flux model.
    Analytical Biochemistry 08/2014; 465. DOI:10.1016/j.ab.2014.07.026 · 2.22 Impact Factor
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