Metabolomics‐driven quantitative analysis of ammonia assimilation in E. coli

• Published in: Molecular systems biology Vol. 5; no. 1; pp. 302 - n/a
• Main Authors: Yuan, Jie, Doucette, Christopher D, Fowler, William U, Feng, Xiao‐Jiang, Piazza, Matthew, Rabitz, Herschel A, Wingreen, Ned S, Rabinowitz, Joshua D
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 2009; John Wiley & Sons, Ltd; EMBO Press; Nature Publishing Group; Springer Nature
• Subjects: active‐site competition; Ammonia; Ammonia - metabolism; Ammonium; Assimilation; Biological assimilation; Biomass; Catalytic Domain; Chromatography, High Pressure Liquid; Competition; Dehydrogenases; Differential equations; Dynamic response; E coli; EMBO10; EMBO26; Enzymes; Escherichia coli; Escherichia coli - genetics; Escherichia coli - metabolism; flux regulation; Fluxes; Genetic algorithms; Genetic Techniques; Glutamate-ammonia ligase; Glutamine; Glutamine - metabolism; Growth rate; Homeostasis; HPLC‐MS; Intermediates; Ketoglutaric acid; Ketoglutaric Acids - metabolism; Mass Spectrometry - methods; metabolic dynamics; Metabolism; Metabolites; Metabolome; Metabolomics; Metabolomics - methods; Models, Genetic; Nitrogen; Nitrogen - metabolism; Parameter identification; Perturbation; predictive model; Proteins; Quantitative analysis; Quaternary Ammonium Compounds; Substrates; Systems Biology - methods; active‐site competition; predictive model; flux regulation; HPLC‐MS; metabolic dynamics
• ISSN: 1744-4292; 1744-4292
• DOI: 10.1038/msb.2009.60

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, α‐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. Synopsis Although the metabolic pathways converting nutrients to biomass are well known, a quantitative understanding of the relationship between nutrient environment, metabolism, and growth rate is still missing. Furthermore, despite much progress towards quantitatively understanding potential mechanisms for controlling metabolite concentrations and fluxes (as reviewed in Sorribas and Savageau, 1989 ; Heinrich and Schuster, 1996 ; Fell, 1997 ), the most important control mechanisms operating in cells have not been rigorously dissected. This is particularly true for networks containing cycles and branches. Ammonia assimilation in E. coli (Figure 1A ) provides a tractable model network for quantitative analysis of cellular metabolic regulation. This network is composed of two key ammonia assimilating pathways, glutamine synthetase/glutamate synthase (GS/GOGAT) cycle and glutamate dehydrogenase (GDH) pathway, involving three key metabolites (glutamine, glutamate, and α‐ketoglutarate). The enzyme constituents have been explicitly studied biochemically (Miller and Stadtman, 1972 ; Schutt and Holzer, 1972 ; Mantsala and Zalkin, 1976 ; Kustu et al , 1984 ; Alibhai and Villafranca, 1994 ). GS activity is known to be allosterically regulated in response to the intracellular concentrations of glutamine and α‐ketoglutarate (Figure 1B ) (Schutt and Holzer, 1972 ; Senior, 1975 ; Garcia and Rhee, 1983 ; Kustu et al , 1984 ; Atkinson et al , 2002 ; Reitzer, 2003 ; Jiang et al , 2007 ). A strong correlation has been demonstrated between the intracellular pool size of glutamine and growth rate under nitrogen limitation in the closely related organism Salmonella (Ikeda et al , 1996 ). Here we investigate the short‐term (i.e., nontranscriptional) regulation of ammonium assimilation in E. coli using a combination of experiments and computational modeling. We sample the metabolome of ammonium‐limited and ammonium‐replete E. coli and use mass spectrometry to quantify a broad spectrum of cellular metabolites in the resulting extracts (Figure 3 ). We then use data on central nitrogen metabolites to drive the development of a dynamic model that links extracellular ammonium availability to intracellular metabolite concentrations and thereby cellular growth rate. Through this data‐driven modeling process, we demonstrate that competition for enzyme active sites by substrates, products, and inhibitors is an important component regulating cellular nitrogen assimilation fluxes. Thus, even for one of the best studied metabolic subnetworks, combining metabolomic experiments with modeling identified an important but previously overlooked means of flux control. The resulting model quantitatively reproduces the experimentally observed metabolic responses used in model development (Figure 4 ). In addition, it accurately predicts cellular responses to different perturbations (Figure 7 ). This work thereby lays the groundwork for combining metabolomics and modeling to develop larger predictive models of metabolic dynamics. By combining metabolomics and computational modeling, we dissect flux control in a metabolic network involving multiple levels of regulation Metabolome changes induced by nitrogen up‐shift center around metabolites directly involved in nitrogen assimilation Even for the pathway subject to regulation by enzyme covalent modification, active site competition—the fight among metabolites for enzyme active sites—plays a key role in controlling flux in live cells