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Responses of the Central Metabolism in Escherichia coli to Phosphoglucose Isomerase and Glucose-6-Phosphate Dehydrogenase Knockouts

Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0017,¹ Research and Education Center for Genetic Information, Nara Institute of Science and Technology, Ikoma 630-0101,² Department of Biochemical Engineering & Science, Kyushu Institute of Technology, Iizuka 820-8502, Japan³

Received 10 June 2003/ Accepted 18 September 2003

	ABSTRACT

Top Abstract Introduction Materials and Methods Results Discussion Appendix References

 
The responses of Escherichia coli central carbon metabolism to knockout mutations in phosphoglucose isomerase and glucose-6-phosphate (G6P) dehydrogenase genes were investigated by using glucose- and ammonia-limited chemostats. The metabolic network structures and intracellular carbon fluxes in the wild type and in the knockout mutants were characterized by using the complementary methods of flux ratio analysis and metabolic flux analysis based on [U-¹³C]glucose labeling and two-dimensional nuclear magnetic resonance (NMR) spectroscopy of cellular amino acids, glycerol, and glucose. Disruption of phosphoglucose isomerase resulted in use of the pentose phosphate pathway as the primary route of glucose catabolism, while flux rerouting via the Embden-Meyerhof-Parnas pathway and the nonoxidative branch of the pentose phosphate pathway compensated for the G6P dehydrogenase deficiency. Furthermore, additional, unexpected flux responses to the knockout mutations were observed. Most prominently, the glyoxylate shunt was found to be active in phosphoglucose isomerase-deficient E. coli. The Entner-Doudoroff pathway also contributed to a minor fraction of the glucose catabolism in this mutant strain. Moreover, although knockout of G6P dehydrogenase had no significant influence on the central metabolism under glucose-limited conditions, this mutation resulted in extensive overflow metabolism and extremely low tricarboxylic acid cycle fluxes under ammonia limitation conditions.

	INTRODUCTION

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The central carbon pathways constitute the backbone of cell metabolism by providing energy, building blocks, and reducing power for biomass synthesis. Due to the extensive redundancy and the presence of isozymes, most single-gene knockout mutations in central metabolism do not block cell growth on glucose (13, 18). To reveal gene-phenotype relationships, it is important to gain insight into the complex responses of the metabolic network in its entirety to these mutations. The most important properties of biochemical networks are the per se nonmeasurable in vivo reaction rates, which may be estimated by metabolic flux analysis (41).

The most common approach is based on flux balancing of extracellular uptake and secretion rates within a stoichiometric reaction model (26, 45). This approach usually requires assumptions about redox or energy balances, and the validity of these assumptions strongly affects the flux estimates. To increase the reliability and resolution of such flux balance analyses, additional information may be obtained from ¹³C labeling experiments (43, 48). In this approach, the isotope labeling patterns of intracellular metabolites are analyzed by either nuclear magnetic resonance (NMR) or mass spectrometry. The data are then used for identification of the metabolic network structure or for quantification of the intracellular carbon fluxes.

Direct analytical interpretation of ¹³C labeling patterns may provide direct evidence for a particular flux or reaction (24, 34). Recently, a more general method of flux ratio analysis has been developed based on biosynthetically directed fractional ¹³C labeling by cofeeding of unlabeled glucose and [U-¹³C]glucose (30, 44). The resulting ¹³C labeling patterns of metabolic intermediates are analyzed by two-dimensional NMR spectroscopy of the anabolic products (e.g., amino acids) synthesized from these intermediates. The observed ¹³C-¹³C scalar coupling multiplet intensities are then transformed into the relative abundance of intact carbon fragments originating from a single glucose source molecule. Since alternative pathways leading to the same metabolites yield different intact fragments, flux ratio analysis enables identification of active pathways in a bioreaction network and the ratios of some intracellular fluxes.

The ¹³C labeling data in combination with biomass composition and extracellular flux data may also be used to quantify the intracellular fluxes in a metabolic network (7, 35, 39). Based on the balances of metabolites and isotopomers, a mathematical framework relating the metabolic fluxes to the ¹³C labeling data is constructed. The intracellular flux distribution is then estimated by finding a best fit for all the available data in an iterative fitting procedure. Since the flux distribution represents the mathematically best estimate for the given biochemical reaction network, the validity of the network itself may affect the flux result. To avoid this, the bioreaction network identified by flux ratio analysis may be used for flux quantification. Consequently, the flux ratio analysis and metabolic flux analysis methods are highly complementary. Flux ratio analysis provides insight into which enzymes are active and which enzymes are not active and if there is an unknown reaction taking place in cells. This method can identify the metabolic network structure for metabolic flux analysis. The intracellular flux distribution estimated by metabolic flux analysis provides a holistic view of cellular metabolism. The result can be used for quantitative comparison of cells grown under different environmental conditions or for comparison of different mutant strains (9, 21, 37, 47). Moreover, as these two methods are very different, flux ratio analysis may provide an independent verification of the flux estimates (14).

In this study, we used a combination of flux ratio analysis and metabolic flux analysis to quantitatively investigate how Escherichia coli metabolism responds to knockout of phosphoglucose isomerase or glucose-6-phosphate (G6P) dehydrogenase in glucose- and ammonia-limited chemostat cultures. Phosphoglucose isomerase and G6P dehydrogenase are located at the first juncture of the two important routes of central carbon metabolism, the Embden-Meyerhof-Parnas (EMP) and pentose phosphate (PP) pathways (Fig. 1). Estimation of the relative contributions of the EMP and PP pathways to glucose catabolic flux has received considerable attention (4, 12) due to the variability with environmental conditions and the relevance for NADPH metabolism. Glucose limitation and ammonia limitation represent bioenergetically very different regimens that have profound effects on cellular physiology and carbon fluxes, including the PP pathway flux (10, 33). The PP pathway is used for production of NADPH, which is mainly used in anabolic reactions and may also play an important role in the antioxidant system (3).

View larger version (76K): [in this window] [in a new window]   FIG. 1. Bioreaction network of E. coli central carbon metabolism. The arrows indicate the physiological directions of reactions. Fluxes to biomass building blocks are indicated by gray arrows. Abbreviations: F6P, fructose 6-phosphate; T3P, triose 3-phosphate; 3PG, 3-phosphoglycerate; PYR, pyruvate; ACoA, acetyl coenzyme A; 6PG, 6-phosphogluconate; S7P, seduheptulose 7-phosphate; OAA, oxaloacetate; ICT, isocitrate; AKG, -ketoglutarate; SUC, succinate; FUM, fumarate; MAL, malate; GOX, glyoxylate; EPS, extracellular polysaccharide; ETH, ethanol; ACE, acetate; ex, extracellular.

	MATERIALS AND METHODS

Top Abstract Introduction Materials and Methods Results Discussion Appendix References

Chemostat cultivation was performed at 37°C in a 2-liter bioreactor (BMJ-02PI; Able Co.,Tokyo, Japan) with a working volume of 1 liter. The culture medium was continuously fed to the bioreactor at a dilution rate of 0.1 h^-1, and the working volume was kept constant by withdrawing culture broth through a continuously operating pump. The pH of the culture was maintained at 7.0 by addition of 2.0 M NaOH. Agitation at 450 rpm and a constant airflow of 1.0 liter/min ensured that the dissolved oxygen concentration was above 60% saturation. The oxygen and carbon dioxide concentrations in the bioreactor effluent gas were monitored with an exhaust gas analyzer (Off-Gas Jr. DEX-2562; Able Co.).

Labeling experiments were started after the cultures reached the steady state; we assumed that the steady state was reached when the optical density at 600 nm and the exhaust gas analysis results remained constant for at least three volume changes. The unlabeled feed was replaced by an identical medium containing 4.5 g of unlabeled glucose per liter and 0.5 g of [U-¹³C]glucose (>98% ¹³C; Isotech, Miamisburg, Ohio) per liter. Biomass samples for NMR analysis were taken after two volume changes, so that 86% of the biomass was ¹³C labeled, which was calculated based on the first-order washout kinetics.

Analytical methods. Cell growth during cultivation was monitored by measuring the optical density at 600 nm. Cell dry weight was determined from cell pellets of 100-ml culture aliquots that were centrifuged for 10 min at 4°C and 8,000 x g, washed once with distilled water, and dried at 85°C until the weight was constant.

For extracellular metabolite analysis, culture samples were centrifuged for 5 min at 4°C and 20,000 x g to remove the cells. Glucose, ammonia, and ethanol concentrations were determined with enzymatic test kits (Roche Molecular Biochemicals, Mannheim, Germany). Organic acids were detected by high-pressure liquid chromatography with a model 2695 instrument (Waters, Milford, Mass.) equipped with an Inertsil ODS-3V column (4.6 by 250 mm; GL Sciences Inc., Tokyo, Japan) and a Waters 2487 UV detector. A mobile phase consisting of 50 mM NH₄H₂PO₄ at a flow rate of 1.0 ml/min was used, and the column was operated at 40°C. Acetate, formate, pyruvate, D-lactate, -ketoglutarate, succinate, and fumarate concentrations were also determined enzymatically with Roche test kits or by using standard protocols (49). The extracellular polysaccharide concentration was determined by the phenol-sulfuric acid method by using glucose for calibration (23). The relative contributions of protein, RNA, and glycogen to the macromolecular biomass composition were determined as described previously (51).

In vitro enzyme activities were determined in crude cell extracts from 10-ml culture aliquots that were centrifuged at 4°C and 8,000 x g for 10 min. The cell pellets were then washed and resuspended in disruption buffer, which contained 200 mM Tris-HCl (pH 7.6), 4 mM MgCl₂, and 2 mM dithiothreitol. Cell disruption was achieved by sonication with an ultrasonic disruptor (UD-201; Tomy, Tokyo, Japan), and the cell debris was removed by centrifugation for 15 min at 4°C and 20,000 x g. The supernatant was used for determination of enzyme activities and the protein concentration (29). Phosphoglucose isomerase activity was measured by monitoring the increase in the NADPH concentration by using G6P dehydrogenase as a coupling enzyme (19). The activities of NADP⁺-dependent G6P dehydrogenase (11), 6-phosphogluconate dehydrogenase (19), and isocitrate dehydrogenase (20) were determined by monitoring the increase in the amount of NADPH. The change in the amount of NADPH was monitored fluorimetrically by using an excitation wavelength of 355, an emission wavelength of 460 nm, and a dual-scanning microplate spectrofluorometer (SPECTRAmax GEMINI XS; Molecular Devices Co., Sunnyvale, Calif.). Isocitrate lyase activity was assayed by the phenylhydrazine method (31).

NMR spectroscopy. At the end of the labeling experiment, 400-ml portions of culture samples were harvested by centrifugation for 10 min at 4°C and 8,000 x g. The cell pellets were washed three times with 20 mM Tris-HCl (pH 7.6) and resuspended in 24 ml of 6 M HCl. Each mixture was then separated into two fractions. The first fraction was 6 ml for the glucose-limited chemostat and 12 ml for the ammonia-limited chemostat, and the second fraction was 18 ml for the glucose-limited chemostat and 12 ml for the ammonia-limited chemostat. The first fraction was hydrolyzed for 12 h at 105°C and used to determine the labeling patterns of amino acids and glycerol. In the resulting hydrolysate there were 16 proteinogenic amino acids, since cysteine and tryptophan were oxidized and asparagine and glutamine were deaminated during the acid hydrolysis. The second fraction was hydrolyzed for only 30 min at 105°C and used to determine the labeling state of glucose. The hydrolysates from both fractions were filtered through a 0.2-µm-pore-size filter and evaporated to dryness. The dried material was then dissolved in 650 µl of 20 mM ²HCl in ²H₂O, filtered, and used for the NMR measurements.

The labeling patterns of amino acids, glycerol, and glucose in the hydrolysates were determined by NMR spectroscopy. The measurements were obtained at 30°C and 400 MHz with a Bruker Avance 400 spectrometer (Bruker, Karlsruhe, Germany). Two-dimensional proton-detected heteronuclear ¹³C-¹H correlation ([¹³C, ¹H]-COSY) spectra were recorded. For each labeling experiment, the following three spectra were measured: one spectrum for the aliphatic carbons of amino acids and glycerol with the ¹³C carrier concentration set to 45 ppm, one spectrum for the aromatic rings of amino acids with the ¹³C carrier concentration set to 125 ppm, and one spectrum for the carbons of glucose with the ¹³C carrier concentration set to 65 ppm. For NMR analyses in each labeling experiment, the measurement times were 15.5 h (data size, 3,072 x 1,024 complex points; t_1max = 249 ms; t_2max = 128 ms; scan number, 8) for aliphatic spectra, 10.5 h (data size, 2,048 x 1,024 complex points; t_1max = 360 ms; t_2max = 128 ms; scan number, 8) for aromatic spectra, and 15.5 h (data size, 1,536 x 1,024 complex points; t_1max = 124 ms; t_2max = 128 ms; scan number, 16) for glucose spectra. Before Fourier transformation, the time domain data were multiplied in t₁ and t₂ with sine-bell windows shifted by /2. The digital resolutions along ₁ after linear prediction and zero filling were 0.86 Hz/point for aliphatic spectra, 1.47 Hz/point for aromatic spectra, and 1.72 Hz/point for glucose spectra.

The overall degree of ¹³C labeling in the sample (P₁) was determined from the satellites of well-separated peaks in one-dimensional ¹H-NMR spectra (acquisition time, 1.024 s; interscan delay, 8 s) and was confirmed by analysis of the scalar coupling fine structure of leucine C^ß. P₁ was 0.096 in all cases.

All NMR data processing was performed by using the Bruker XWINNMR software. The ¹³C-¹³C scalar coupling fine structures were extracted from the cross sections taken along the ¹³C axis in a two-dimensional NMR spectrum. After manual baseline correction, the individual multiplet components of the scalar coupling fine structures were integrated to quantify the relative contributions of singlet, doublet, and doublet-of-doublets signals. This evaluation procedure is valid only if strong ¹³C-¹³C scalar coupling effects are negligible. Thus, in glucose spectra, only C-4 of ß-glucose was evaluated, because there was strong coupling for the other carbons of glucose. For C-4 of ß-glucose, the scalar coupling constant for the adjacent carbons was much smaller than the corresponding chemical shift difference, so the strong coupling could be neglected.

Flux ratio analysis. Forty-eight ¹³C-¹³C scalar coupling fine structures for the 16 amino acids, glycerol, and glucose present in the hydrolysates were determined from the two-dimensional NMR spectra. The observed relative multiplet intensities (I values) were used to calculate the relative abundances of intact carbon fragments (f values) with equations A1 and A2 (see Appendix). The denotations of f are shown in the Appendix (see Table A1). The f values for the following carbon atom positions provided information on the metabolic origins of their precursors: ß-glucose C-4 for G6P; His-, His-ß, and His-² for pentose 5-phosphate (P5P); Tyr-^x and Tyr-^x for erythrose 4-phosphate (E4P); glycerol C-1/C-3 and glycerol C-2 for triose 3-phosphate; Ser-, Ser-ß, and Gly- for 3-phosphoglycerate; Phe-, Phe-ß, Tyr-, and Tyr-ß for phosphoenolpyruvate (PEP); Ala-, Ala-ß, Val-, Val-¹, Val-², Leu-ß, Leu-¹, Leu-², and Ile-² for pyruvate; Leu- for acetyl-coenzyme A; Lys-ß, Lys-, Lys-, and Lys- for pyruvate and oxaloacetate; Asp-, Asp-ß, Met-, Thr-, Thr-ß, Thr-, Ile-, Ile-¹, and Ile- for oxaloacetate; and Glu-, Glu-ß, Glu-, Pro-, Pro-ß, Pro-, Pro-, Arg-ß, Arg-, and Arg- for -ketoglutarate.

(i) Oxaloacetate formed via the glyoxylate shunt. If the glyoxylate shunt is inactive, the intact C-1-C-2 and C-3-C-4 fragments in the oxaloacetate (OAA) pool originate from -ketoglutarate and PEP, yielding equations 1.

(1)

In equations 1, X^exch, which is the fraction of oxaloacetate molecules that were reversibly interconverted to fumarate at least once, can be calculated from 2f⁽³⁾(Asp-ß)/[f⁽³⁾(Asp-) + f⁽³⁾(Asp-ß)]. X^ppc, the fraction of oxaloacetate stemming from anaplerotic carboxylation of PEP, can be calculated with equation 2.

(2)

Equations 1 are used to identify the activity of the glyoxylate shunt. If the glyoxylate shunt is inactive, equations 1 are satisfied within experimental error, while the active glyoxylate shunt results in obviously higher values of f^(2b)(Asp-) and f^(2b)(Asp-ß) than the values calculated with equations 1.

If the glyoxylate shunt is active under the conditions investigated, excess intact C-1-C-2 and C-3-C-4 connectivities in oxaloacetate are introduced via the glyoxylate shunt. Thus, the fraction of oxaloacetate molecules formed via the glyoxylate shunt, X^glo, can be obtained by using equations 3.

(3)

or

(ii) Pyruvate formed via the ED pathway. If the ED pathway is active, excess intact C-1-C-2-C-3 fragments may be introduced into the pyruvate pool via the ED pathway, yielding equation 4.

(4)

In equation 4, X^ME, the fraction of pyruvate derived from malate via the malic enzyme, can be calculated with equations 5.

(5)

where lb and ub indicate the lower and upper boundaries, respectively. Since the interconversion of oxaloacetate to malate leads to the introduction of intact C-1-C-2-C-3 fragments into the malate pool, f⁽³⁾(Asp-ß) f⁽³⁾(malate C-2) f⁽³⁾(Asp-) is obtained. Thus, the lower and upper boundaries for the fraction of pyruvate molecules formed via the ED pathway, X^ED,lb and X^ED,ub, can be assessed by using equations 6 and 7, respectively.

(6)

(7)

The G6P pool is assessable via glucose; i.e., f⁽ⁱ⁾(G6P C-2) = f⁽ⁱ⁾(glucose C-2). Equations 6 and 7 are used to identify the activity of the ED pathway when f⁽³⁾(G6P C-2) is larger than f⁽³⁾(Phe-).

(iii) P5P and E4P synthesized via the nonoxidative PP pathway. If P5P and E4P are synthesized from triose 3-phosphate and fructose 6-phosphate via the nonoxidative part of the PP pathway, equations 8 are obtained.

(8)

Metabolic flux analysis. For quantification of carbon fluxes in the central metabolism of E. coli, a bioreaction network was constructed, as shown in Fig. 1. This network includes the reactions of the EMP, PP, and ED pathways, as well as the tricarboxylic acid (TCA) cycle and the glyoxylate shunt. The reactions catalyzed by PEP carboxylase (v₁₉), PEP carboxykinase (v₂₀), and malic enzyme (v₂₁) were also included. The networks of active pathways identified by flux ratio analysis were used for flux quantification (see Results). The following enzyme reactions were considered reversible: phosphoglucose isomerase (v₂), transketolase (v₁₀ and v₁₂), transaldolase (v₁₁), the sequence of glycolytic reactions leading from triose 3-phosphate to PEP (v₄ and v₅), succinate dehydrogenase (v₁₆), fumarase (v₁₇), and malate dehydrogenase (v₁₈).

The reversible transfer of reducing equivalents between NAD(H) and NADP(H) was included in the bioreaction network, because the pyridine nucleotide transhydrogenase has been shown to be active in E. coli (2). The malic enzyme in E. coli may be NAD⁺ or NADP⁺ dependent (32). While our analysis could not distinguish between fluxes through the two isoenzymes, the only influence of the enzyme was its influence on the flux of reducing equivalents via transhydrogenase. The flux distribution was calculated by assuming that the NAD⁺- and NADP⁺-dependent malic enzymes were equally active, and the influence of this assumption on the transhydrogenase flux was investigated.

Metabolic flux analysis was based on three different data sets: (i) substrate uptake and product formation rates; (ii) macromolecular biomass composition; and (iii) relative intensities of the ¹³C multiplet components of the aforementioned 48 carbon positions in amino acids, glycerol, and glucose determined by two-dimensional [¹³C, ¹H]-COSY. The precursor requirements for biomass formation were derived from the biochemical information concerning biosynthetic pathways in E. coli (36) and the experimentally determined macromolecular composition.

The carbon flux distribution in the bioreaction network was then determined as a best fit to the three data sets by using a least-squares parameter-fitting approach in the mathematical framework, as described previously (52). Exchanges fluxes via reversible reactions were quantitatively considered in the flux calculation. Initially, the isotopomer balances of all metabolites in the bioreaction network were calculated from a randomly chosen flux distribution. Relative ¹³C multiplet intensities were then simulated from this isotopomer distribution and compared to the experimentally determined values. The quality of the fit was judged by the ² (error) value. Through an iterative process of data fitting, a flux solution corresponding to the minimal ² value was sought. To verify the global error minimum of the flux solution, multiple calculations were performed from different random starting points, and the best solution that was reproducibly attained was presented as the estimated result of flux distribution. A statistical error analysis of the estimated fluxes was included in the calculations. Moreover, the flux estimates were compared with the independently calculated flux ratios from flux ratio analysis to verify the reliability of flux estimates.

	RESULTS

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Growth parameters. To investigate quantitatively the effects of pgi or zwf gene deletion on E. coli physiology, we grew E. coli wild-type strain W3110, strain BW25113, the phosphoglucose isomerase knockout (Pgi) mutant JWK3985, and the G6P dehydrogenase knockout (Zwf) mutant JWK1841 in aerobic chemostats at a dilution rate of 0.1 h^-1 under glucose- or ammonia-limited conditions. The experimentally determined growth parameters are summarized in Table 2. The parent strain for the knockout mutants, BW25113, exhibited almost the same growth parameters as W3110 (data not shown). Under glucose-limited conditions, all the strains converted glucose completely to biomass and CO₂ without any by-product formation, and the biomass yields on glucose were similar.

To obtain accurate information on the specific precursor requirements for subsequent flux analysis, we determined the relative fractions of the major biomass components of E. coli: protein, RNA, and glycogen (Table 3). As expected, the reserve carbohydrate glycogen content was markedly increased under ammonia-limited conditions. The remaining fraction of biomass was assigned to minor macromolecules, such as DNA, lipids, or peptidoglycan (8).

View larger version (34K): [in this window] [in a new window]   FIG. 2. 13C-13C scalar coupling multiplets observed for aspartate from glucose-limited chemostat cultures of E. coli W3110 (left) and the Pgi mutant (right). The signals were extracted from the 1(13C) cross sections in the [13C,1H]-COSY spectra. (A) Asp-; (B) Asp-ß. As indicated in panel A, the multiplets consist of a singlet (s), a doublet with a small coupling constant (Da), a doublet split by a larger coupling constant (db), and a doublet of doublets (dd). Aspartate corresponds directly to its metabolic precursor, oxaloacetate (OAA).

The glyoxylate shunt consisting of isocitrate lyase and malate synthase was found to be inactive in W3110. This result was obtained based on analysis of the intact carbon fragments for Asp-, Asp-ß, Phe-, Glu-ß, and Glu- (f values are shown in Table 5), which were derived from C-2 and C-3 of oxaloacetate, C-2 of PEP, and C-3 and C-4 of -ketoglutarate, respectively. The f values for these carbon positions were found to satisfy the relationship shown in equations 1 within experimental error, demonstrating that oxaloacetate was synthesized exclusively from the TCA cycle and the anaplerotic carboxylation of PEP. Identification of the ED pathway activity by using equations 6 and 7 required the labeling data for G6P C-2 that could be assessed by using glucose C-2. Unfortunately, the ¹³C multiplet pattern of glucose C-2 could not be evaluated because of strong ¹³C-¹³C scalar coupling effects. Thus, in this analysis we could not exclude the possibility that the ED pathway makes a minor contribution to glucose catabolism in W3110. Because the ED pathway has been shown to be inactive in wild-type E. coli grown with glucose in many studies (17, 19), it was not considered in the metabolic network used for W3110.

Identification of network structure in the Pgi mutant. The flux ratio analysis of the Pgi mutant revealed the absence of G6P molecules derived from fructose 6-phosphate through the phosphoglucose isomerase reaction (Table 4). This information was obtained from direct interpretation of the ¹³C-¹³C scalar coupling fine structure of glucose C-4 in the [¹³C, ¹H]-COSY spectra. As Fig. 3 shows, the scalar coupling multiplets of glucose C-4, which was used to assess the labeling pattern of G6P, showed that the doubletwas not present in the Pgi mutant, demonstrating the lack of C-3-C-4 and C-4-C-5 carbon bond cleavage in G6P. However, in wild-type E. coli, a significant fraction of the C-3-C-4 carbon bonds in fructose 6-phosphate were cleaved due to the action of the PP pathway, and this carbon bond cleavage was introduced into the G6P pool by the phosphoglucose isomerase reaction. Hence, a significant contribution of the doublet to the multiplets of glucose C-4 was observed for W3110 (Fig. 3), reflecting the cleavage of C-3-C-4 bonds in G6P introduced by the active phosphoglucose isomerase reaction. This result indicated that in the Pgi mutant, the phosphoglucose isomerase was inactive in vivo, and the labeled substrate, glucose, was the sole source of G6P. The in vitro enzyme activity measurements also confirmed that no phosphoglucose isomerase could be detected in the crude extract of the Pgi mutant.

View larger version (19K): [in this window] [in a new window]   FIG. 3. 13C-13C scalar coupling multiplets observed for C-4 of glucose from ammonia-limited chemostat cultures of E. coli W3110 (left) and the Pgi mutant (right). The signals were extracted from the 1(13C) cross sections in the [13C,1H]-COSY spectra. As glucose C-4 exhibits scalar coupling constants identical to those of the adjacent carbons, the multiplets consist of a singlet (s), a doublet (d), and a triplet (t). The labeling data for glucose represent the labeling patterns of G6P.

The glyoxylate shunt was found to be active in the Pgi mutant by flux ratio analysis (Table 4). Visual inspection of the scalar coupling fine structures of Asp- and Asp-ß revealed a surprisingly high abundance of the doublet split by a larger coupling constant for the Pgi mutant (Fig. 2). The analysis of the intact carbon fragments from Asp-, Asp-ß, Phe-, Glu-ß, and Glu- (f values are shown in Table 5) showed that the f^(2b)(Asp-) and f^(2b)(Asp-ß) values were significantly higher than the values calculated for f^(2b)(Phe-), f⁽²⁾(Glu-ß), and f^(2b)(Glu-) with equations 1. This indicated that the intact C-1-C-2 and C-3-C-4 fragments in the oxaloacetate pool could not be derived entirely from the TCA cycle and PEP carboxylation and that excess intact C-1-C-2 and C-3-C-4 connectivities were introduced via the glyoxylate shunt. Therefore, the flux ratio analysis provided evidence of the in vivo activity of the glyoxylate shunt, which is normally required for growth on carbon sources, such as acetate or fatty acids, and is generally considered to be repressed in E. coli grown on glucose (5). Consistently, in vitro enzyme activity analysis also confirmed that no isocitrate lyase could be detected in wild-type E. coli, while the Pgi mutant exhibited an isocitrate lyase activity of 197 nmol mg of protein^-1 min^-1. By calculating with equations 3 and the f values of Asp-, Asp-ß, Phe-, Glu-ß, Glu-, and Leu- (Table 5), we found that more than one-half of the oxaloacetate molecules were formed via the glyoxylate shunt in the glucose-limited culture of the Pgi mutant (Table 4).

The flux ratios in the Pgi mutant also showed that the ED pathway made a minor contribution to glucose catabolism (Table 4). Three carbon positions carry the information necessary to identify the activity of the ED pathway (Table 6): Phe- is derived from C-2 of PEP, and Ala- and Val- are derived from C-2 of pyruvate. The f values of Ala- and Val- fulfill the following relationship: f^(2b)(Val-) = f^(2b)(Ala-) + f⁽³⁾(Ala-). Using equations 6 and 7 for identification of the ED pathway activity required the f values for G6P C-2 and the flux via the malic enzyme. As described above, the G6P molecules in the Pgi mutant originated solely from the labeled substrate, glucose, so that f⁽³⁾(G6P C-2) = 1. The flux through the malic enzyme was negligible in the Pgi mutant (Table 4). Thus, according to equations 6 and 7, the ED pathway was found to account for about 6 and 11% of the pyruvate molecules synthesized in the glucose- and ammonia-limited Pgi mutant, respectively (Table 4).

View larger version (18K): [in this window] [in a new window]   FIG. 4. 13C-13C scalar coupling multiplets observed for Asp- from ammonia-limited chemostat cultures of E. coli W3110 (left) and the Zwf mutant (right). The signals were extracted from the 1(13C) cross sections in the [13C,1H]-COSY spectra. See the legend to Fig. 2 for definitions of multiplet components. Aspartate corresponds directly to its metabolic precursor, oxaloacetate (OAA).

The intracellular fluxes determined represent estimates for in vivo enzyme activities. BW25113 and W3110 exhibited very similar flux distributions (data not shown). The intracellular flux distributions in wild-type E. coli were found to depend strongly on the limiting nutrient (Fig. 5A and B). Changing the limiting nutrient from glucose to ammonia resulted in a reduced flux through the oxidative branch of the PP pathway, so that the contribution of the EMP pathway to glucose catabolism was increased. This result is consistent with the flux ratio analysis results and previous findings (14, 38). Moreover, the gluconeogenic flux from oxaloacetate to PEP via the PEP carboxykinase was significantly lower, whereas the malic enzyme flux from malate to pyruvate was higher under ammonia-limited conditions than under glucose-limited conditions.

View larger version (139K): [in this window] [in a new window]   FIG. 5. Metabolic flux distribution in chemostat cultures of E. coli W3110 under glucose-limited conditions (A) and ammonia-limited conditions (B), the Pgi mutant under glucose-limited conditions (C) and ammonia-limited conditions (D), and the Zwf mutant under glucose-limited conditions (E) and ammonia-limited conditions (F). The chemostats were operated at a dilution rate of 0.1 h-1. The numbers in rectangles are the net fluxes determined. The flux values are expressed relative to the specific glucose uptake rate, which is indicated in parentheses (in millimoles per gram [dry weight] per hour). The arrows indicate the directions of the fluxes determined. The numbers in ellipses are the fluxes for withdrawal of precursor metabolites for biomass formation. For abbreviations, see the legend to Fig. 1.

As Fig. 5C and D show, the glyoxylate shunt was activated, and the flux through the isocitrate dehydrogenase in the TCA cycle was significantly lower in the Pgi mutant than in W3110 under both limiting conditions investigated. In wild-type E. coli, isocitrate was metabolized exclusively in the TCA cycle to generate energy and reducing power (Fig. 5A and B). In the Pgi mutant, however, a significant fraction of isocitrate entered the glyoxylate shunt; 59% of the isocitrate was funneled into the glyoxylate shunt, and 41% was converted to -ketoglutarate by the isocitrate dehydrogenase under glucose-limited conditions (Fig. 5C). The malate formed by the glyoxylate shunt served to replenish the carbon skeletons withdrawn from the TCA cycle for biosynthesis. The flux through the anaplerotic PEP carboxylase, which served solely to replenish the TCA cycle in wild-type E. coli (Fig. 5A and B), was decreased remarkably in the Pgi mutant (Fig. 5C and D). These results indicated that disruption of the phosphoglucose isomerase in E. coli resulted in alterations in cellular anaplerotic metabolism.

In the Pgi mutant, the ED pathway accounted for 5 and 13% of the glucose catabolic flux under glucose- and ammonia-limited conditions, respectively (Fig. 5C and D). Hence, the ED pathway was used to a limited extent, and the PP pathway was the primary route for glucose catabolism. A similar observation was made with other phosphoglucose isomerase-deficient E. coli strains (2, 16, 19). The transhydrogenase flux converting NADPH to NADH was found to be significantly higher in the Pgi mutant than in W3110 (Fig. 5C and D), suggesting that the transhydrogenase played an important role in redox metabolism in this mutant.

The flux distributions in the glucose- and ammonia-limited Zwf mutant are shown in Fig. 5E and F. The constraint on the flux through G6P dehydrogenase was included in the flux calculations, because the flux ratio analysis provided direct evidence of the inactivation of this enzyme in vivo in the Zwf mutant. Under both limiting conditions investigated, G6P dehydrogenase deficiency resulted in exclusive glucose catabolism through the EMP pathway, synthesis of P5P and E4P via the nonoxidative PP pathway, and the transhydrogenase flux converting NADH to NADPH. The fluxes through other parts of metabolism were remarkably similar in the glucose-limited cultures of the Zwf mutant and W3110 (Fig. 5E). However, under ammonia-limited conditions, the inactivation of G6P dehydrogenase drastically altered the flux distribution (Fig. 5F). Most strikingly, the TCA cycle flux was reduced to an extremely low level, and a reverse flux through the malate dehydrogenase converted oxaloacetate to malate. Moreover, the ammonia-limited Zwf mutant exhibited surprisingly high fluxes of secretion of acetate and pyruvate. In addition, the flux through the PEP carboxykinase was negligible, while the malic enzyme flux was increased in the ammonia-limited Zwf mutant.

The flux estimates in Fig. 5 were obtained from at least 10 independent flux calculations, which were initiated from different random starting points. The independently calculated flux solutions turned out to be very similar, and the flux solutions with the lowest ² values are shown in Fig. 5; under glucose- and ammonia-limited conditions, these ² values were 62 and 136, respectively, for W3110, 76 and 185, respectively, for the Pgi mutant, 132 and 89, respectively, for the Zwf mutant. Since the 95% confidence level of the ² value in this type of experiments is around 120 (7), these ² values are remarkably good for analysis of a biological system. Therefore, the flux distributions determined can provide a reliable description of the behavior of the E. coli metabolic network.

The flux solutions were also subjected to statistical error analysis based on Monte Carlo simulations (40, 52). For most fluxes we obtained 90% confidence intervals that were less than 8% of the estimated flux, but the 90% confidence intervals for the oxidative PP and ED pathway fluxes were less than 25%. The transhydrogenase flux was obtained by assuming that the NAD⁺- and NADP⁺-dependent malic enzymes were equally active. For an entirely NAD⁺-dependent malic enzyme, the transhydrogenase flux would be decreased. However, when the transhydrogenase reaction was omitted from the network, the ² values of the corresponding flux solution increased remarkably, indicating that the transhydrogenase flux was indeed present in E. coli metabolism. Finally, the flux estimates were verified with the flux ratios that were independently calculated in the flux ratio analysis. For example, from the estimated flux distribution in the glucose-limited Pgi mutant (Fig. 5C), the fraction of oxaloacetate originating from PEP and the fraction of oxaloacetate formed via the glyoxylate shunt were calculated to be 29 and 58%, respectively. These values were in very good agreement with the flux ratio results shown in Table 4, providing further evidence of the reliability of our flux estimates.

	DISCUSSION

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The primary objective of this study was to quantitatively elucidate metabolic flux responses of E. coli to knockout mutations in the entrance to the EMP or PP pathway, phosphoglucose isomerase or G6P dehydrogenase. To do this, complementary methods, flux ratio analysis and metabolic flux analysis, based on [U-¹³C]glucose labeling experiments and two-dimensional NMR spectroscopy were used. The results showed that the split ratio of the PP pathway to the EMP pathway was about 29% in glucose-limited wild-type E. coli, and ammonia limitation induced a significant reduction in this split ratio (Fig. 5A and B). Disruption of phosphoglucose isomerase led to use of the PP pathway as the primary route of glucose catabolism (Fig. 5C and D). On the other hand, G6P dehydrogenase-deficient E. coli catabolized glucose exclusively through the EMP pathway and synthesized the two biosynthetic precursors, P5P and E4P, via the nonoxidative PP pathway (Fig. 5E and F). However, additional, unexpected flux responses to the knockout mutations were also found, which provided new insights into the behavior of the metabolic network in its entirety.

The glyoxylate shunt was unexpectedly activated upon knockout of phosphoglucose isomerase (Table 4; Fig. 5C and D). In the glucose-limited Pgi mutant, only a minor fraction of isocitrate was converted to -ketoglutarate by isocitrate dehydrogenase in the TCA cycle, while the majority was metabolized via the glyoxylate shunt (Fig. 5C). This result is surprising because the glyoxylate shunt is generally considered to be inactive in E. coli grown on glucose. The activation of the glyoxylate shunt in the Pgi mutant can be explained based on the analysis of intracellular redox metabolism.

The flux results presented above provide a holistic perspective on intracellular metabolism and thus provide unique insight into the generation and consumption of the anabolic reducing power, NADPH (Fig. 6). In wild-type E. coli, the isocitrate dehydrogenase reaction was the major producer of NADPH, accounting for more than 60% of the NADPH production. In the Pgi mutant, the PP pathway, which was used as the primary glucose catabolic pathway, generated a large amount of NADPH. Overproduction of NADPH is deleterious, as a limited capacity for reoxidation of NADPH is one reason for the low growth rate of phosphoglucose isomerase-deficient E. coli (2). The Pgi mutant bypassed the isocitrate dehydrogenase reaction by redirecting carbon flow through the glyoxylate shunt, so that the amount of NADPH produced by the isocitrate dehydrogenase reaction was markedly decreased (Fig. 6). This reaction contributed to less than 20% of the NADPH production in the Pgi mutant. Therefore, activation of the glyoxylate shunt could reduce significantly the production of excess NADPH in the Pgi mutant that was limited in reoxidizing NADPH. NADPH and NADP⁺ have been identified as effectors that regulate the reversible phosphorylation or inactivation of isocitrate dehydrogenase in E. coli (25).

View larger version (52K): [in this window] [in a new window]   FIG. 6. Specific rates of NADPH production and consumption in glucose (C)- and ammonia (N)-limited chemostat cultures of E. coli W3110, the Pgi mutant, and the Zwf mutant. NADPH production was contributed to by the oxidative PP pathway (solid bars), isocitrate dehydrogenase (cross-hatched bars), transhydrogenase (hatched bars), and malic enzyme (stippled bars). NADPH was consumed via biomass formation(stippled bars) and the transhydrogenase reaction (hatched bars).

The strong increase or decrease in the PP pathway flux in the Pgi and Zwf mutants apparently disturbed the balance of NADPH (Fig. 6). Hence, high transhydrogenase fluxes are needed to balance the reducing equivalents NADPH and NADH. In the Pgi mutant, a significant fraction of NADPH was converted to NADH by the transhydrogenase reaction. Thus, it appears that the transhydrogenase reaction plays an important role in maintaining the NADPH balance in phosphoglucose isomerase-deficient E. coli. Consistently, phosphoglucose isomerase knockout mutants of Saccharomyces cerevisiae, in which the transhydrogenase is absent, are blocked for growth on glucose (15). The reaction converting NADPH to NADH may be catalyzed by the soluble transhydrogenase UdhA, since a physiological role of this enzyme is the reoxidation of NADPH (1, 2). In the Zwf mutant, NADPH could not be supplied by the oxidative PP pathway (Fig. 6). The transhydrogenase reaction thus converted NADH to NADPH to satisfy the NADPH requirement for biomass formation. This reaction may be catalyzed by the membrane-bound energy-coupled transhydrogenase PntAB, as one of its metabolic functions is to provide NADPH for biosynthesis (46).

Disruption of G6P dehydrogenase was counteracted by local flux rerouting via the EMP and nonoxidative PP pathways under glucose-limited conditions (Fig. 5E). However, additional, significant flux changes in response to this knockout mutation were observed under ammonia-limited conditions (Fig. 5F). The ammonia-limited Zwf mutant exhibited extensive overflow metabolism and extremely low TCA cycle fluxes. The flux through the malate dehydrogenase was even reversed, which was usually encountered in anaerobic cultures. This flux response could have resulted from the cellular response to oxidative stress. For wild-type E. coli, the specific oxygen uptake rate was higher under ammonia-limited conditions than under glucose-limited conditions (Table 2), indicating that ammonia limitation induced the increased respiration activity. Because the respiration activity is linearly related to the rate of production of hydrogen peroxide (H₂O₂) in E. coli (22), the cells in an ammonia-limited culture are likely to encounter oxidative stress. In the Zwf mutant, the oxidative PP pathway could not produce NADPH, an essential reducing equivalent for the antioxidant system. Thus, the Zwf mutant was probably sensitive to oxidative stress, a phenomenon that has also been described for isocitrate dehydrogenase-deficient E. coli and G6P dehydrogenase-deficient S. cerevisiae (3, 27). The activities of the TCA cycle and respiration were reduced to extremely low levels, which could have decreased significantly the production of reactive by-products of oxygen in the ammonia-limited Zwf mutant.

	APPENDIX

Top Abstract Introduction Materials and Methods Results Discussion Appendix References

 
The abundances of intact carbon fragments originating from a single glucose source molecule (f values) were calculated from the observed relative ¹³C multiplet intensities (I values). Equation A1 was used for a terminal carbon atom, and equation A2 was used for the central carbon in a C₃ fragment.

(A1)

(A2)

The components in the K_term and K_central matrices were calculated with the probabilistic expressions described by Szyperski (42). The denotations of f are shown in Table A1.

	ACKNOWLEDGMENTS

 
Q. Hua and C. Yang contributed equally to this work.

We thank the reviewers for their helpful suggestions concerning the manuscript.

This work was supported by a grant from the New Energy and Industrial Technology Development Organization (NEDO) of the Ministry of Economy, Trade and Industry of Japan (Development of a Technological Infrastructure for Industrial Bioprocess Project).

	FOOTNOTES

 
* Corresponding author. Mailing address: Metabolome Unit, Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0017, Japan. Phone: 81-235-29-0527. Fax: 81-235-29-0530. E-mail: huaq{at}sfc.keio.ac.jp.

For a commentary on this article, see page 7031 in this issue.

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