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Journal of Bacteriology, July 2007, p. 5142-5152, Vol. 189, No. 14
0021-9193/07/$08.00+0 doi:10.1128/JB.00203-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
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Department of Environmental Protection, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, C/ Prof. Albareda, 1, E-18008 Granada, Spain,1 Institute for Molecular Systems Biology, ETH, CH-8093 Zurich, Switzerland2
Received 7 February 2007/ Accepted 29 April 2007
| ABSTRACT |
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| INTRODUCTION |
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In addition to the above-mentioned pathway for the conversion of glucose into 6-phosphogluconate, another pathway has been described in other species of the genus Pseudomonas. Pseudomonas aeruginosa can use the glucokinase pathway, in which glucose is phosphorylated to glucose-6-phosphate, which is subsequently oxidized to 6-phosphogluconate by glucose-6-phosphate dehydrogenase (8, 16, 18, 19, 20, 30, 39, 40, 45). Failure to detect glucokinase activity in several P. putida strains growing on glucose led several groups to propose that the glucose-6-phosphate pathway was nonfunctional in P. putida (12, 23, 27, 36, 37, 48, 49).
In different species of the genera Bacillus, Oceanobacillus, Staphylococcus, Geobacillus, and others (Swiss Prot/ErEMBL), the synthesis of 6-phosphogluconate has been shown to also occur through direct phosphorylation of the gluconate formed by glucose oxidation in a reaction catalyzed by gluconokinase (14, 38, 41). This reaction has been proposed to be of minor, if any, importance in P. putida KT2440 (47).
Based on the genome annotation of P. putida KT2440 (29, 32, 51), Velázquez et al. (47) proposed the metabolic pathways potentially available for the use of glucose, identifying a single open reading frame (ORF) in the database of The Institute of Genomic Research (TIGR) (http://www.tigr.org) for each of the reactions summarized in Fig. 1. The first and most remarkable feature of the network of transformations that results from projecting the genomic data of KT2440 is that, in principle, it does not fit with the earlier proposal for glucose metabolism in different strains of P. putida (15, 21, 28, 36, 48, 49), because up to three pathways to transform glucose into 6-phosphogluconate were identified in silico: (i) the glucose kinase pathway, in which glucose-6-phosphate is the intermediate (Fig. 1); (ii) the direct phosphorylation of gluconate mediated by gluconokinase (Fig. 1); and (iii) the ketogluconate loop, which involves the oxidation of gluconate to 2-ketogluconate (Fig. 1).
This study was undertaken to shed light on the initial steps of glucose metabolism in the soil bacterium P. putida KT2440 (25) by generating and characterizing mutants in each of the potential branches leading to 6-phosphogluconate. Growth analysis, metabolic fluxes from glucose in wild-type and isogenic mutant strains, and biochemical and gene expression analysis led us to conclude that P. putida KT2440 uses multiple peripheral pathways to convert glucose into the key pathway intermediate, 6-phosphogluconate.
| MATERIALS AND METHODS |
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Analytical procedures and physiological parameters. Cell growth was monitored by measuring the turbidity of the cultures at 660 nm. Glucose and acetate concentrations were determined enzymatically with commercially available kits (Boehringer Mannheim). Gluconate and 2-ketogluconate were determined at 210 nm after separation of products by high-pressure liquid chromatography (Perkin-Elmer) using a Supercogel C8 (4.6 x 250 mm) high-pressure liquid chromatography column. The liquid phase was 5 mM sulfuric acid, and the flow rate was 0.6 ml/min at 60°C. To determine the cell dry weight (CDW), 10-ml cell suspensions were harvested by centrifugation at 15,800 x g in a centrifuge using predried and weighed 10-ml tubes. The pellets were washed with 0.9% (wt/vol) NaCl and dried at 105°C for 24 h to a constant weight.
The following physiological parameters were determined by regression analysis during the exponential growth phase in batch cultures (35): maximum specific growth rate, biomass yield on glucose, specific glucose consumption, and by-product formation rates.
Sample preparation and gas chromatography-mass spectrometry analysis. Cell aliquots were harvested in precooled tubes (4°C) during mid-exponential growth by centrifugation of 7 to 10 ml of the culture broth at 1,200 x g and 4°C for 20 min. The pellet was washed twice with 1 ml of 0.9% (wt/vol) NaCl, hydrolyzed in 1.5 ml 6 M HCl for 24 h at 110°C in sealed 2-ml Eppendorf tubes, and desiccated overnight in a heating block at 85°C under a constant air stream. The hydrolysate was dissolved in 50 µl 99.8% pure dimethyl formamide and derivatized with N-methyl-N-(tert-butyldimethylsilyl)-trifluoroacetamide as described previously (5, 10, 26). One microliter of the derivatized sample was injected into a Hewlett-Packard series 8000 gas chromatographer combined with a model MD 800 mass spectrometer (Fisons Instruments) and analyzed as described previously (5, 10, 26).
METAFoR analysis. For metabolic-flux ratio (METAFoR) analysis, the mass spectra of the derivatized amino acids alanine, glycine, valine, leucine, isoleucine, proline, serine, threonine, phenylalanine, aspartate, glutamate, histidine, and tyrosine were corrected for the natural abundances of all stable isotopes and unlabeled biomass from the inoculum. Lysine and methionine are not required for the METAFoR analysis used in this study, whereas arginine, asparagine, cysteine, glutamine, and tryptophan are not detectable (42). The amino acids are synthesized from one or more metabolic intermediates, and the mass isotopomer distribution vector of these metabolites was derived from the mass isotopomer distribution vector of the amino acids and used to calculate the fractional contribution of a given pathway or reaction to a target metabolite pool (metabolic-flux ratios) by using a set of algebraic equations implemented in the MATLAB-based program Fiat Flux (26, 55).
Net-flux analysis and master reaction network. The metabolic models used for net-flux analysis were based on the master reaction network, which included 45 reactions and 33 metabolites. Respiration, biomass formation, and a transhydrogenase reaction were included as additional reactions, and ATP and the cofactors NADH and NADPH were included as additional metabolites. Net fluxes were then calculated using (i) the stoichiometric reaction matrix, (ii) the METAFoR analysis-derived flux ratios, (iii) physiological data, and (iv) precursor requirements for biomass synthesis, as described previously (11, 13, 26). Specifically, the following flux ratios were used: pyruvate derived through the ED pathway, oxaloacetate (OAA) originating from phosphoenolpyruvate or pyruvate, the lower and upper bounds of pyruvate originating from malate, and the upper bound of phosphoenolpyruvate derived through the pentose phosphate pathway. The stoichiometric matrix was then solved with the MATLAB-based program by minimizing the sum of the weighted-square residuals of the constraints from both metabolite balances and flux ratios to obtain estimated net fluxes (55).
DNA techniques. Preparation of plasmid and chromosomal DNA, digestion with restriction enzymes, ligation, electrophoresis, and Southern blotting were done by standard methods (2).
Preparation of RNA and reverse transcriptase (RT)-PCR. P. putida KT2440 cells were grown overnight in M9 medium with glucose. The cells were then diluted to reach a turbidity at 660 nm of 0.05 in fresh M9 medium with glucose as the sole carbon source and were incubated until the culture reached a turbidity of 1.0 at 660 nm. Then, 15 ml of the cultures was harvested by centrifugation at 7,000 x g for 5 min. Total bacterial RNA was isolated as described by Marqués et al. (24). Extracts were treated with RNase-free DNase I (10 U/µl) in the presence of an RNase inhibitor cocktail (RNaseOUT; 40 U/µl).
RT-PCR was done with 0.5 µg RNA in a final volume of 20 µl using the Titan OneTube RT-PCR system according to the manufacturer's instructions (Roche Laboratories). The annealing temperature used for RT-PCR was between 50°C and 58°C, and the cycling conditions were as follows: 94°C for 10 s, 50 to 58°C for 30 s, and 68°C for 30 s. Positive controls (with DNA as the template and Taq polymerase) and negative controls (with RNA as the template and Taq polymerase) were included in all the assays.
Mini-Tn5 mutagenesis of P. putida strain KT2440.
Mini-Tn5 transposon mutagenesis was carried out by performing triparental mating between P. putida KT2440R (Rifr), E. coli CC118
pir (pUT-Km), and the helper strain E. coli HB101(pRK600), as described by Duque et al. (7). After 4 h of conjugation, the transconjugants were selected as Rifr Kmr clones on M9 medium with citrate as a carbon source. Among the set of transconjugants, we searched for mutants unable to grow on M9 medium with glucose as a carbon source. This allowed us to identify mutants with insertions in the edd and eda genes (see below). Other mutants, with insertions in the gcd, gnuK, kguK, and kguD genes, were obtained from the Pseudomonas Reference Culture Collection (7). The transposon insertion site in each of the mutants was confirmed by DNA sequencing (7).
Site-specific homologous inactivation of glk.
To construct a mutant strain bearing an inactivated chromosomal version of the glk gene, we generated the corresponding knockout using the appropriate derivative of pCHESI
Km. Plasmid pCHESI
Km is based on pUC18 and bears the origin of transfer oriT of RP4 and the
-Km interposon of plasmid pHP45
Km cloned as a HindIII fragment (22). To generate the desired mutation, an internal fragment (540 bp) of the target gene was amplified by PCR with primers provided with EcoRI and BamHI sites and subsequently cloned between the EcoRI and BamHI sites of pCHESI
Km in the same transcriptional direction as the lacp promoter. The recombinant plasmid was mobilized from E. coli CC118
pir into P. putida KT2440 by triparental mating with the E. coli HB101(pRK600) helper strain (33). P. putida KT2440 transconjugants bearing a cointegrate of the plasmid in the host chromosome were selected on M9 minimal medium with benzoate (15 mM) as the sole carbon source and kanamycin (33). The nature of the mutation in a few randomly chosen Kmr clones was confirmed by PCR using a primer based on the Kmr gene and another primer that was complementary to the glk gene. One correct clone was randomly chosen, and the nature of the mutation was confirmed by Southern blotting (not shown).
Preparation of cell extracts. Cells were grown in batch in M9 medium with glucose or citrate as the carbon source until the culture reached a turbidity of around 0.8 at 660 nm. The cells were then harvested by centrifugation at 8,000 x g for 7 min, washed twice in 50 mM phosphate buffer (pH 7.0), and frozen at 20°C. To prepare cell extracts, cells were resuspended in 1 ml buffer (100 mM Tris-HCl, pH 7.5, 5 mM MgCl2, 2 mM dithiothreitol, and protease inhibitor Cocktail Tabs Complete, EDTA free). The cells were disrupted in a French press at 120 MPa. Whole cells and debris were removed by centrifugation at 11,180 x g (45 min; 4°C). The clear supernatant was considered the cell extract. The protein concentration in the cell extract was determined by the Bradford method, using bovine serum albumin as the standard.
Enzyme assays. Enzyme assays were performed at 30°C, and the formation of NAD(P)H was monitored at 340 nm in a Shimadzu UV-160A spectrophotometer. The reaction assays for glucokinase and gluconokinase were as described earlier (18, 44). Specific activities were calculated based on an NAD(P)H extinction coefficient of 6.3 mM1·cm1.
P. putida microarrays.
The genome-wide DNA chip used in this work (printed by Progenika Biopharma) was described in detail previously (54). It consists of an array of 5,539 oligonucleotides (50-mer) spotted in duplicate onto
-aminosilane-treated slides and covalently linked by UV light and heat. The oligonucleotides represent 5,350 of the 5,421 predicted ORFs annotated in the P. putida KT2440 genome (29, 54). The chips are also endowed with homogeneity controls consisting of oligonucleotides for the rpoD and rpoN genes spotted at 20 different positions, as well as duplicate negative controls at 203 predefined positions.
Microarray hybridization and data analysis.
RNA isolation and preparation of labeled cDNA were done exactly as described by Duque et al. (7). To this end, P. putida KT2440 cells were grown on M9 medium with glucose or citrate as the carbon source. Prior to the hybridization process, the microarray slides were blocked by immersion in 5x SSC (1x SSC is 0.15 M NaCl, 15 mM sodium citrate, pH 7), 0.1% (wt/vol) sodium dodecyl sulfate (SDS), 1% (wt/vol) bovine serum albumin for 1 h at 42°C. Then, the slides were washed by two successive immersions in MilliQ water at room temperature, followed by a final wash with isopropanol. The slides were spin dried by centrifugation at 1,500 x g for 5 min and used within the next hour. Equal amounts of Cy3- and Cy5-labeled cDNAs, one of them corresponding to the control and the other one to the problem to be analyzed, were mixed, dried in a Speed-Vac, and reconstituted in 35 µl hybridization buffer (5x SSC, 25% [vol/vol] formamide, 0.5% [wt/vol] SDS, 5x Denhardt's solution, 5% [wt/vol] dextran sulfate) preheated to 42°C. The labeled probe was denatured at 98°C for 3 min, applied to the microarray slide, and covered with a glass coverslip. The slide was then placed in a humidified hybridization chamber (AHC ArrayIt hybridization cassette; Telechem International, Inc.) and incubated for 18 to 20 h in a water bath at 42°C in the dark. After hybridization, the microarrays were washed by gentle agitation in 2x SSC, 0.1% [wt/vol] SDS at 42°C for 5 min, followed by a 5-min wash at room temperature in 1x SSC, two 5-min washes in 0.2x SSC, and a final 5-min wash in 0.1x SSC. Finally, the slides were spin dried in a centrifuge at 1,500 x g for 5 min and scanned on a GenePix 4100A scanner (Axon Instruments, Inc.). Images were acquired at a 10-µm resolution, and the background-subtracted median spot intensities were determined with GenePix Pro 5.1 image analysis software (Axon Instruments, Inc.). The signal intensities were normalized by the LOWESS intensity-dependent normalization method and analyzed with Almazen System statistical software (Alma Bioinformatics S. L.). To ensure appropriate statistical analysis of the results, RNA preparations from at least four independent cultures were tested for each strain (4). P values were calculated by Student's t test. A particular ORF was considered differentially expressed if (i) the change was
2.0-fold and (ii) the P value was 0.05 or lower.
| RESULTS |
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To further investigate glucose catabolism in P. putida KT2440, we decided to compare the growth rates in M9 minimal medium with 16 mM glucose as the sole carbon source of the wild-type strain and mutants in each of three potential peripheral pathways that yield 6-phosphogluconate. Mutants deficient in either of the initial enzymes (Glk or Gcd) exhibited significantly decreased growth rates (0.41 ± 0.01 h1 and 0.45 ± 0.01 h1) compared to that in the wild-type strain (0.56 ± 0.02 h1) (Table 2). This indicated that 6-phosphogluconate was produced simultaneously from glucose-6-phosphate and gluconate. The reduced growth rate could not be due only to initially reduced catabolism but also to the metabolic readjustment to produce fructose-6 phosphate. Gluconate can also be directly phosphorylated to 6-phosphogluconate or converted into this compound via the 2-ketogluconate loop. A mutant deficient in 2-ketogluconate metabolism, i.e., with kguD knocked out, grew at a lower rate (0.44 ± 0.01 h1) than a mutant deficient in GnuK (0.54 ± 0.02 h1). A mutant deficient in kguK also grew more slowly than the parental strain and the gnuK mutant. This was interpreted as evidence that metabolism via 2-ketogluconate is more efficient than the direct phosphorylation of gluconate.
During growth on glucose, P. putida KT2440 accumulated only relatively low extracellular concentrations of gluconate (the maximal accumulation was 1.75 ± 0.36 mM) and 2-ketogluconate (the maximal accumulation was 0.53 ± 0.02 mM), which were eventually consumed. As expected, the mutant deficient in glucose dehydrogenase (Gcd) did not accumulate gluconate (Table 2). The KguD mutant accumulated the highest concentrations of 2-ketogluconate (3.46 ± 1.36 mM) and gluconate (2.0 ± 0.14 mM), as expected from the limited operation of the 2-ketogluconate loop, whereas the inactivation of GnuK led to gluconate accumulation at levels similar to those found with the parental strain (Table 2). This set of results supports the notion that KT2440 can assimilate gluconate both via direct phosphorylation to 6-phosphogluconate and through the 2-ketogluconate loop (Fig. 1).
KT2440 exhibits inducible glucokinase and gluconokinase activity. To obtain unequivocal support for the notion that 6-phosphogluconate can be simultaneously synthesized from both glucose-6-phosphate and gluconate, we decided to determine the levels of glucokinase activity, involved in the direct phosphorylation of glucose, and gluconokinase activity, involved in the direct phosphorylation of gluconate. To this end, wild-type cells were grown with citrate or with glucose as the sole source of carbon, and enzymatic activities were determined in cell extracts. Relatively low levels of glucokinase and gluconokinase activity were detected in cells growing on citrate, which increased around 10-fold in cells growing on glucose (Table 3). This indicated that both enzymes were induced in response to glucose in KT2440.
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In the gcd mutant, gluconokinase activities were equally low in cells growing on citrate and glucose. However, in the rest of the mutant strains, we found that gluconokinase activity was induced when cells were grown on glucose (Table 3). These results supported the idea that GnuK is an inducible activity.
Net fluxes from glucose in the wild type and mutants in the early steps of glucose metabolism.
The above-mentioned results suggested that KT2440 metabolizes glucose through three initial pathways that converge at the level of 6-phosphogluconate and that their simultaneous operation is necessary to achieve maximal growth rates. To assess whether the use of different combinations of these initial pathways further impacts on the central carbon metabolism, we used metabolic-flux analysis based on 13C-labeling experiments (10, 26, 42). For this purpose, batch cultures were initiated with mid-exponential-phase cultures at a low inoculum density (less than 1% of the final culture volume) in medium containing 80% natural-abundance glucose and 20% [U-13C6]glucose and, in another series, with 100% [1-13C]glucose. Because we could not resolve fluxes through the three initial pathways, they were lumped for P. putida KT2440 as the total carbon uptake rate. The rate of carbon uptake by the wild-type strain was estimated to be 6.31 ± 0.05 mmol g1 h1 for the parental strain, with a biomass yield of 0.44 g biomass/g carbon used (Table 2). A complete net-flux distribution for the wild-type strain is depicted in Fig. 2, and the relevant fluxes for the wild-type anaplerosis and gluconogenesis in P. putida KT2440 and its isogenic mutants are given in Table 4. As expected, we found that most pyruvate was produced primarily via the ED pathway. Flux data also revealed that over 80% of the tricarboxylic acid (TCA) cycle carbon flux occurs through the so-called pyruvate shunt, which bypasses malate dehydrogenase in the TCA cycle. This was deduced from the higher fraction of OAA originating from pyruvate than from malate (Table 4) using the mathematical formula q(6-phosphogluconate
glyceraldehyde-3-phosphate + pyruvate)/q(total carbon uptake), where q is rate. Consequently, P. putida should exhibit an as-yet-unidentified malic enzyme that converts malate into pyruvate. These results are in agreement with a proposal made by Fuhrer et al. (13) for Pseudomonas fluorescens.
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Somewhat surprising results were obtained for yields and metabolic fluxes with the kguD and gnuK mutants. Both mutants exhibited lower carbon uptake rates (around 5.3 mmol g1 h1) than the parental strain; however, yields (around 0.45 g biomass/g carbon used) were similar to those of the parental strain: in both mutants, the pyruvate shunt was enhanced, since the total amount of OAA from pyruvate represented almost 90% of the total flux. The higher yield in the kguD and gnuK mutants versus the gcd and glk mutants might be due to redirection of the excess of OAA and NADPH to biomass biosynthesis.
Global analysis of the genes involved in glucose metabolism. (i) Gene organization and transcriptional architecture of the peripheral glucose catabolic genes. We have analyzed the annotated sequence of KT2440 to study in greater detail the physical organization of the genes of the glucose peripheral and convergent pathways to gain further insights into the metabolism of the sugar. We have also determined the operon organization of the genes with an RT-PCR approach. The gcd gene corresponded to ORF PP1444, and it was found to be in a cluster of five genes that are transcribed in the same direction (Fig. 3B). The long intergenic distance (295 bp) between the end of ORF PP1446 and the start of the second ORF, encoding a putative porin B (PP1445), suggested that transcription of the ORF encoding PP1446 occurs independently. The distance (203 nucleotides) between gcd (the third gene) and the fourth ORF also suggested that the ORF encoding PP1443 is not transcribed with gcd. The cluster is therefore likely to be made up of three transcriptional units. It should be noted that the gene in 5' with respect to gcd encodes a porin B family protein that might be involved in the entry of glucose into the periplasmic space (34, 43). Distal with respect to gcd are the genes encoding the subunits of gluconate dehydrogenase (PP3382 and PP3383), involved in the conversion of gluconate into 2-ketogluconate. These two genes form an operon (Fig. 3C).
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The gene encoding gluconokinase (gnuK) is adjacent to a gene involved in the transport of gluconate (PP3417). Divergent with respect to gnuK is a gene encoding a transcriptional repressor that belongs to the LacI family (Fig. 3D). We found that the kguK and kguD genes were located in the same operon with kguE and a gene encoding a putative transporter for 2-ketogluconate (Fig. 3C).
Another interesting finding was that one of the alleles encoding glucose-6-phosphate dehydrogenase (zwf-1) was in a cluster with the eda gene. Upstream from zwf-1 and transcribed in the opposite direction was a gene encoding a transcriptional regulator called HexR (Fig. 3A). It is worth noting that the edd/glk and zwf-1/eda gene clusters are vicinal and that between them lies a set of genes that encode a porin-like protein (PP1019) and an ABC transport system involved in glucose uptake, based on glucose uptake assays (T. del Castillo, E. Duque, and J. L. Ramos, unpublished results).
The physical organization of the genes involved in glucose metabolism suggested that some of them might form operons. This was tested by isolating total RNA from cells growing with glucose in the mid-exponential growth phase and by carrying out RT-PCR analysis. The edd and glk genes are part of an operon that was transcribed with the gltR2 gene (Fig. 4). The overlapping gene encoding the sensor kinase PP1013 was also part of this operon (not shown). The following gene, whose function is unknown; the set of genes encoding porin OprB-1; and the ABC transport system made up of PP1015 through PP1019 are also part of this long operon (not shown). The zwf-1, pgl, and eda genes form another operon. Therefore, a relevant feature is the cotranscription of the glk and edd genes and of the zwf-1 and eda genes, which indicates that the glucose-6-phosphate pathway is induced simultaneously with the ED enzymes.
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(ii) Global transcriptomic analysis of KT2440 in response to glucose.
Because the number of straightforward enzymatic assays for peripheral glucose catabolic-pathway enzymes is limited and because the organization of glucose pathway genes is relatively complex (with clustering of certain genes and scattering over the chromosome of other sets of genes), we decided to study the global response of strain KT2440 to glucose by comparing glucose-grown cells versus citrate-grown cells at the transcriptomic level. As indicated in Materials and Methods, we centered our attention on
2.0-fold changes and P values of
0.05.
Interestingly, we observed a significant induction of two outer membrane porins, OprB1 (PP1019) and OprB2 (PP1445), that have been proposed to be necessary for glucose to enter the periplasmic space. This finding agrees with previous reports that in P. aeruginosa and P. putida, oprB mutants grow deficiently in minimal medium with glucose (53). All genes involved in the oxidation of glucose to gluconate (PP3382, PP3383, PP3376, and PP3378) were induced to significant levels (Table 5). Gluconokinase involved in the phosphorylation of gluconate (PP3416) was induced almost fourfold. The reactions from glucose to gluconate and from gluconate to 2-ketogluconate are known to take place in the periplasm, and entry into the cytoplasm of the oxidation products requires a gluconate-specific transport system (PP3417), as well as a 2-ketogluconate transporter (PP3377). These two transporters were also induced slightly more than twofold (Table 5). In addition, since pseudomonads use the glk pathway, glucose itself has to be transported to the cytoplasm. In connection with this, we found that the operon containing ORFs PP1015, PP1016, PP1017, PP1018, and PP1019, which encode a putative ABC glucose uptake system, was also induced at a high level. Therefore, the corresponding gene products most likely constitute a glucose transport system. We found that expression of the glk (PP1011) gene increased around 2.0-fold concomitantly with the induction of zwf-1, which encodes the most active glucose-6-P-dehydrogenase (PP1022). This enzyme converts glucose-6-phosphate into 6-phosphogluconate.
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Of the five regulators in the vicinity of the catabolic enzymes, hexR, the lacI family, ptxS, gltR-2, and ORF PP1013 encoding a sensor kinase, we found that three, namely, GltR (PP1012), PtxS (PP3380), and a LacI-like regulator (PP3415), also increased their expression in response to glucose (Table 5). This suggests that these regulators control their own expression, which is well documented for repressors belonging to different families (31).
In addition to the genes that are directly involved in glucose catabolism, a limited number of genes that in principle have no obvious connection with glucose metabolism were also induced. No annotation is available for six of these genes; for the other three, the annotation suggests that the corresponding gene products encode an OAA decarboxylase (PP5346; oadA), an acetyl-coenzyme A (CoA) carboxylase, and a methyl-accepting chemotaxis receptor (PP3555). Induction of oadA coincides with the functioning of the pyruvate shunt reported above. This suggests that OAA in the wild-type strain growing on glucose may be produced in excess in the TCA cycle and scavenged via OAA decarboxylase.
To test the potential roles of the other gene products in glucose metabolism, we rescued mutants from the Pseudomonas Reference Culture Collection and tested growth on M9 minimal medium with glucose. All mutants, except for PP5347, exhibited growth characteristics similar to those of the wild-type strain in terms of growth kinetics, growth rates, and yields (not shown). The exception was mutant PP5347, which grew at a relatively low rate (growth rate [µ] = 0.22 ± 0.02 h1), exhibited low yields (0.21 ± 0.01 g/g glucose), and accumulated large amounts of gluconate and 2-ketogluconate.
The set of downregulated genes is provided as supplemental material (see Table S1 in the supplemental material). Among the downregulated genes was, as expected, a set of genes involved in citrate metabolism, including two citrate uptake systems (PP0147 and PP0171), the TCA transport TctC protein (PP1418), the outer membrane copper receptor PP4838, and a series of transporters, porins, and metabolic enzymes probably involved in citrate, but not glucose, metabolism (see Table S1 in the supplemental material).
| DISCUSSION |
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Glucose catabolism enzymes in all peripheral pathways are inducible. Enzymatic determinations and microarray analyses showed that enzymes involved in glucose metabolism via gluconate and glucose-6-phosphate were inducible. Although glucose is probably the true inducer of gcd, gluconate seems to be the inducer of gluconokinase activity, since, in a gcd mutant growing on glucose, the level of this enzyme was 1/10 of that in the wild type (Table 3). Glucokinase and gluconokinase activities were expressed at a low basal level in cells grown with citrate, and these activities increased about 10-fold when the cells were grown on glucose. This is in agreement with the increase in glk, gcd, and gnuK expression observed in microarrays. Therefore, the transcriptional and enzymatic assays indicated that the glucokinase pathway and the enzymes for the direct phosphorylation of gluconate and the 2-ketogluconate loop enzymes are all inducible.
Further insights helping to understand the pattern of gene expression of these convergent pathways were obtained from the bioinformatic analysis of the physical localization of the genes, which showed that glucose catabolism genes in P. putida are organized in a series of clusters, that the glk gene forms an operon with the edd gene, and that the zwf-1 gene forms an operon with the eda gene. Because the edd and eda gene products are the sine qua non for 6-phosphogluconate metabolism, the physical and genetic organization of the edd/glk and eda/zwf-1 genes explains why this pathway is operational in P. putida KT2440 (46).
On the other hand, it is notable that the physical and transcriptional organization of genes for the metabolism of gluconate indicated that the catabolic enzymes, along with the set of specific porins and transporters, form single transcriptional units (Fig. 3). This structure points toward coevolution of the uptake system and the catabolic enzyme, which seems to guarantee the efficient entry and metabolism of the corresponding metabolites.
Our results also indicate that OprB1 could be a specific porin for the entry of glucose into the periplasmic space and to transport it to the cytoplasm via an ABC transport system made up of PP1015, PP1016, PP1017, and PP1108 (Fig. 3). This set of genes forms an operon independent of that in which the glucokinase gene (glk) is present. Therefore, although the genes for the uptake of glucose and its metabolism to 6-phosphogluconate are clustered, up to three different operons can be distinguished.
Global metabolic changes. 13C-based flux analysis was used to identify network operation and responses as a consequence of different entry pathways for glucose. These analyses revealed some novel insights into the global metabolic networks that operate in P. putida during glucose metabolism. Our findings showed that in the wild-type KT2440 strain, a major fraction of the TCA flux occurred through the pyruvate shunt instead of the malate dehydrogenase, which is similar to other Pseudomonas species but contrasts with net TCA fluxes in E. coli and Bacillus subtilis (13). This set of results indicates that in P. putida, excess C is removed via this shunt.
Fluxome analysis revealed that the operation of the TCA cycle was similar in the glk- or gcd-deficient mutants and in the parental strain, although the total amount of carbon taken up by the mutant strains was lower than that consumed by the parental strain, which probably results in a lower µmax for the mutant strains. In these mutants, the pyruvate shunt operated at a level similar to that in the wild-type strain (Table 4). Net-flux analysis also confirmed the results of previous studies that showed that the pentose phosphate pathway does not contribute to glucose catabolism in Pseudomonas.
How are the glucose catabolic genes organized in other Pseudomonas species? Our unexpected results regarding glucose metabolism and the bioinformatics projection in P. putida led us to examine the gene organization for glucose catabolism in other Pseudomonas species for which the complete genome is available. We found that all key enzymes for the synthesis of 6-phosphogluconate from glucose via glucose-6-phosphate or via gluconate are present in P. fluorescens Pf-5, Pseudomonas syringae DC3000, and P. aeruginosa PAO1. BLAST analysis revealed a high degree of sequence conservation for all gene products, ranging from 70% to 95% similarity. The organization shown for porin B and the gcd gene in Fig. 3B is conserved in P. aeruginosa and P. fluorescens, but not in P. syringae.
The organization of the edd/glk operon and the divergent gap-1 gene of P. putida (Fig. 3A) is also conserved in the other three Pseudomonas species. We propose that glucose-6-phosphate represents a compulsory pathway for glucose metabolism, regardless of the functioning of the gluconate pathways, in all of these strains. The organization of gnuK and the corresponding gluconate transporter of P. putida are also maintained in all three species. The kgu cluster is very similarly organized in P. aeruginosa and P. fluorescens, whereas in P. syringae, the genes are not present. Finally, the gad genes (PP3383 and PP3384) involved in the oxidation of gluconate to 2-ketogluconate have highly homologous genes in the genomes of P. fluorescens and P. aeruginosa, with very similar patterns of gene organization. In contrast, the gene homologs are not present in P. syringae. The bioinformatics analysis suggests that different species of the genus Pseudomonas use the ED pathway for glucose metabolism and that, in principle, all can synthesize the key intermediate 6-phosphogluconate through a series of converging peripheral pathways.
In summary, our study revealed that initial glucosea source of carbon in the plant rhizosphere (3)catabolism in the genus Pseudomonas occurs through a series of pathways that converge at the level of 6-phosphogluconate and that function simultaneously. This guarantees the efficient assimilation of a carbon source that is abundant in niches occupied by pseudomonads. Moreover, we have shown that, with glucose as a carbon source, malate produced in the TCA cycle is channeled mainly to OAA via the pyruvate shunt.
| ACKNOWLEDGMENTS |
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We thank Ana Hurtado for DNA sequencing and Jesus de la Torre for help in the selection of mutants. We also thank C. Lorente and M. Fandila for secretarial assistance and K. Shashok for improving the use of English in the manuscript.
| FOOTNOTES |
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Published ahead of print on 4 May 2007. ![]()
Supplemental material for this article may be found at http://jb.asm.org/. ![]()
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