Metabolomics-driven quantitative analysis of ammonia assimilation in E. coli. Mol

Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton University, Princeton, NJ 08544, USA.
Molecular Systems Biology (Impact Factor: 10.87). 02/2009; 5(1):302. DOI: 10.1038/msb.2009.60
Source: PubMed


Despite extensive study of individual enzymes and their organization into pathways, the means by which enzyme networks control metabolite concentrations and fluxes in cells remains incompletely understood. Here, we examine the integrated regulation of central nitrogen metabolism in Escherichia coli through metabolomics and ordinary-differential-equation-based modeling. Metabolome changes triggered by modulating extracellular ammonium centered around two key intermediates in nitrogen assimilation, alpha-ketoglutarate and glutamine. Many other compounds retained concentration homeostasis, indicating isolation of concentration changes within a subset of the metabolome closely linked to the nutrient perturbation. In contrast to the view that saturated enzymes are insensitive to substrate concentration, competition for the active sites of saturated enzymes was found to be a key determinant of enzyme fluxes. Combined with covalent modification reactions controlling glutamine synthetase activity, such active-site competition was sufficient to explain and predict the complex dynamic response patterns of central nitrogen metabolites.

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    • "Biochemical reactions are embedded in complex metabolic networks . The dynamic features of these networks, such as the timedependent regulation of proteins, underlie the capacity of the cell to cope with variable environmental conditions [1] [2] [3], to allocate resources efficiently[4], and to achieve complex adaptive strategies for survival [5]. Several classical studies have addressed the effect of changing enzyme levels on substrate kinetics [6] [7] [8] [9] [10]. "
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    ABSTRACT: The Michaelis-Menten equation for an irreversible enzymatic reaction depends linearly on the enzyme concentration. Even if the enzyme concentration changes in time, this linearity implies that the amount of substrate depleted during a given time interval depends only on the average enzyme concentration. Here, we use a time re-scaling approach to generalize this result to a broad category of multi-reaction systems, whose constituent enzymes have the same dependence on time, e.g. they belong to the same regulon. This "average enzyme principle" provides a natural methodology for jointly studying metabolism and its regulation.
    FEBS letters 07/2013; 587(17). DOI:10.1016/j.febslet.2013.07.032 · 3.17 Impact Factor
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    • "). In model systems, many metabolic enzymes display K m values in vivo that are higher than their corresponding in vitro values and certainly closer to the concentrations of their cosubstrates (Bennett et al., 2009; Yuan et al., 2009). This presumably allows such enzymes to respond to changes in the concentrations of available agonists and antagonists . "
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    ABSTRACT: Chemical modifications of histones and DNA, such as histone methylation, histone acetylation, and DNA methylation, play critical roles in epigenetic gene regulation. Many of the enzymes that add or remove such chemical modifications are known, or might be suspected, to be sensitive to changes in intracellular metabolism. This knowledge provides a conceptual foundation for understanding how mutations in the metabolic enzymes SDH, FH, and IDH can result in cancer and, more broadly, for how alterations in metabolism and nutrition might contribute to disease. Here, we review literature pertinent to hypothetical connections between metabolic and epigenetic states in eukaryotic cells.
    Cell 03/2013; 153(1):56-69. DOI:10.1016/j.cell.2013.03.004 · 32.24 Impact Factor
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    • "Second, we consider the case where two substrates may be simultaneously competing for the active site of a single enzyme. Such competition for the enzymatic active site plays important roles in the behavior of metabolic pathways [23] as well as synthetic biological circuits [24]. Although in both cases the formula relating the boundary conditions of substrate and average enzyme levels is more complicated, it remains true that the average enzyme level entirely determines the final concentration of the substrates given their initial concentration. "
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    ABSTRACT: The Michaelis-Menten equation, proposed a century ago, describes the kinetics of enzyme-catalyzed biochemical reactions. Since then, this equation has been used in countless, increasingly complex models of cellular metabolism, often including time-dependent enzyme levels. However, even for a single reaction, there remains a fundamental disconnect between our understanding of the reaction kinetics, and the regulation of that reaction through changes in the abundance of active enzyme. We revisit the Michaelis-Menten equation under the assumption of a time-dependent enzyme concentration. We show that all temporal enzyme profiles with the same average enzyme level yield identical substrate degradation– a simple analytical conclusion that can be thought of as an invariance principle, and which we validate experimentally using a β-galactosidase assay. The ensemble of all time-dependent enzyme trajectories with the same average concentration constitutes a space of functions. We develop a simple model of biological fitness which assigns a cost to each of these trajectories (in the form of a function of functions, i.e. a functional). We then show how one can use variational calculus to analytically infer temporal enzyme profiles that minimize the overall enzyme cost. In particular, by separately treating the static costs of amino acid sequestration and the dynamic costs of protein production, we identify a fundamental cellular tradeoff. The overall metabolic outcome of a reaction described by Michaelis-Menten kinetics is ultimately determined by the average concentration of the enzyme during a given time interval. This invariance in analogy to path-independent phenomena in physics, suggests a new way in which variational calculus can be employed to address biological questions. Together, our results point to possible avenues for a unified approach to studying metabolism and its regulation. This article was reviewed by Sergei Maslov, William Hlavacek and Daniel Kahn.
    Biology Direct 03/2013; 8(1):7. DOI:10.1186/1745-6150-8-7 · 4.66 Impact Factor
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