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Applied and Environmental Microbiology, August 2008, p. 5146-5152, Vol. 74, No. 16
0099-2240/08/$08.00+0     doi:10.1128/AEM.00944-08
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

Group 2 Sigma Factor SigB of Corynebacterium glutamicum Positively Regulates Glucose Metabolism under Conditions of Oxygen Deprivation{triangledown} ,{dagger}

Shigeki Ehira, Tomokazu Shirai, Haruhiko Teramoto, Masayuki Inui, and Hideaki Yukawa*

Research Institute of Innovative Technology for the Earth, 9-2 Kizugawadai, Kizugawa, Kyoto 619-0292, Japan

Received 25 April 2008/ Accepted 16 June 2008


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ABSTRACT
 
The sigB gene of Corynebacterium glutamicum encodes a group 2 sigma factor of RNA polymerase. Under conditions of oxygen deprivation, the sigB gene is upregulated and cells exhibit high productivity of organic acids as a result of an elevated glucose consumption rate. Using DNA microarray and quantitative reverse transcription-PCR (RT-PCR) analyses, we found that sigB disruption led to reduced transcript levels of genes involved in the metabolism of glucose into organic acids. This in turn resulted in retardation of glucose consumption by cells under conditions of oxygen deprivation. These results indicate that SigB is involved in positive regulation of glucose metabolism genes and enhances glucose consumption under conditions of oxygen deprivation. Moreover, sigB disruption reduced the transcript levels of genes involved in various cellular functions, including the glucose metabolism genes not only in the growth-arrested cells under conditions of oxygen deprivation but also in the cells during aerobic exponential growth, suggesting that SigB functions as another vegetative sigma factor.


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INTRODUCTION
 
Corynebacterium glutamicum is a nonpathogenic, GC-rich, gram-positive bacterium that belongs to the order Actinomycetales, which also includes the genera Mycobacterium and Streptomyces. C. glutamicum is used for the industrial production of several amino acids, such as L-glutamate and L-lysine (11, 13, 21). When oxygen is limited during aerobic growth, C. glutamicum excretes several organic acids, including lactate, succinate, and acetate, as fermentation end products (1). Enhanced productivities of organic acids and ethanol from sugars realized by using growth-arrested C. glutamicum strain R cells under conditions of oxygen deprivation (15, 26) have been attributed to an increase in glucose consumption rates, resultant from upregulation of several key enzymes of the glycolytic and organic acid production pathways, encoded by tpi, gapA, pgk, ppc, mdh, and ldhA (17). Regulatory mechanisms of gene expression under conditions of oxygen deprivation still remain to be unraveled.

The initiation of transcription is the pivotal step for gene regulation in eubacteria (41). The sigma factor of RNA polymerase is responsible for promoter recognition and determines the specificity of transcriptional initiation. There are seven genes coding for sigma factors in the genome of C. glutamicum: sigA, sigB, sigC, sigD, sigE, sigH, and sigM (14, 19, 43). Group 1 sigma factor SigA is the primary sigma factor, essential for cell viability and responsible for the transcription of housekeeping genes. The sigB gene encodes a group 2 sigma factor, which shows a high degree of sequence similarity with the primary sigma factor but is nonessential for cell growth. SigC, SigD, SigE, SigH, and SigM are classified into the category of extracytoplasmic function sigma factors, which are divergent from group 1 and 2 sigma factors in amino acid sequence and control the transcription of genes that are involved in response to extracellular environmental signals.

In gram-negative bacteria, such as Escherichia coli, the group 2 sigma factor RpoS is induced during entry into stationary phase and under many stress conditions and plays an important role in cell adaptation by controlling expression of a large set of genes under nonoptimal growth conditions (9, 10). RpoS and the primary sigma factor RpoD of E. coli are known to recognize the same promoter sequence in vitro but have distinct regulons in vivo. Up to 10% of the E. coli genes are under direct or indirect control of RpoS, and RpoS is considered a second vegetative sigma factor with a major impact not only on stress tolerance but also on the whole-cell physiology (39). In C. glutamicum and Mycobacterium tuberculosis, SigB is suggested to play roles similar to those of RpoS, since it is induced during the transition from exponential phase to stationary phase and under some stress conditions, and the sigB disruptant has increased susceptibility to various stress (5, 6, 12, 18, 25). Recently, genes under the control of SigB of C. glutamicum during the transition from exponential phase to stationary phase have been identified by DNA microarray analysis (22). SigB regulates expression of genes involved in various cellular functions, and its promoter sequence is indistinguishable from that of SigA.

We have previously shown that the sigB transcript level is increased under conditions of oxygen deprivation (17). In this study, we found that the glucose consumption rate was lowered in a sigB disruptant under these conditions. DNA microarray and quantitative reverse transcription-PCR (RT-PCR) analyses indicated that SigB positively regulated expression of genes involved in glucose metabolism under conditions of oxygen deprivation. Moreover, sigB disruption had extensive effects on gene expression not only in the growth-arrested cells under conditions of oxygen deprivation but also in cells during aerobic exponential growth. SigB of C. glutamicum is suggested to be a global regulator at various stages of cellular growth.


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MATERIALS AND METHODS
 
Bacterial strains, culture media, and growth conditions.
E. coli strains were grown at 37°C in Luria-Bertani medium (32). C. glutamicum strain R (43) and its derivatives were grown at 33°C in A medium (17) with 4% (wt/vol) glucose on a rotary shaker at 180 rpm. When appropriate, media were supplemented with antibiotics. The final antibiotic concentrations were 50 µg ml–1 of kanamycin and 50 µg ml–1 of chloramphenicol for E. coli and 50 µg ml–1 of kanamycin and 5 µg ml–1 of chloramphenicol for C. glutamicum. Reactions under oxygen deprivation conditions were performed as described previously (17). Briefly, cells grown for 13 h in a jar fermenter were harvested by centrifugation and washed with minimal medium (BT medium), which consists of A medium from which yeast extract and Casamino Acids were removed. The washed cells were suspended to a final dry-cell concentration of 10 g liter–1 in 80 ml of BT medium containing 200 mM sodium bicarbonate, and the cell suspension was incubated at 33°C without aeration, maintaining the pH at 7.5.

Mutant construction.
The sigB coding region was amplified by PCR using the primer pair 1749-F and 1749-R (see Table S1 in the supplemental material) and cloned between the SmaI and Sse8387I sites of pHSG398 (Takara Bio, Shiga, Japan). A kanamycin resistance cassette from pUC4K (GE Healthcare Bio-Science, NJ) was inserted into the unique BamHI site that lay within the sigB gene. The resulting plasmid was transferred by electroporation into C. glutamicum to generate a sigB-disrupted strain, DR1749. Disruption of the sigB gene was confirmed by PCR (data not shown).

For a complementation study, a shuttle vector pCRD600 harboring the sigB gene was constructed. A DNA fragment containing the sigB promoter and coding regions was amplified by PCR using the primer pair sigB-F and sigB-R (see Table S1 in the supplemental material) and was cloned between the PstI and EcoRI sites of pCRB1 (16).

RNA isolation and DNA microarray analysis.
Total RNA was extracted from C. glutamicum cells by using the RNeasy Mini Kit (Qiagen, Hilden, Germany) as described previously (17) and was treated with DNase I (Takara Bio).

Global gene expression analysis was performed with the C. glutamicum R DNA microarray (17). Fluorescently labeled cDNAs were prepared with 10 µg RNA by using the CyScribe cDNA postlabeling kit (GE Healthcare Bio-Science). Synthesis and labeling of cDNA, as well as hybridization, washing and scanning of microarrays, and image analysis followed protocols described previously (17). Microarray analyses were carried out using three sets of RNA samples isolated from independently grown cultures with different combinations of Cy dyes (a dye swap strategy). Since the C. glutamicum R DNA microarray contains two replicates per gene, a total of six replicates per gene were available to determine changes in gene expression. Genes with significantly differential transcript levels (P < 0.01 [Student's t test]) by at least a factor of 2 were determined.

Real-time qRT-PCR.
A one-step real-time quantitative RT-PCR (qRT-PCR) was performed with 7500 Fast Real-Time PCR system (Applied Biosystems, CA) in a 20-µl reaction mixture containing 10 µl Power Sybr green PCR master mix (Applied Biosystems), 0.1 µM each of gene-specific forward and reverse primers (see Table S1 in the supplemental material), 5 U of murine leukemia virus reverse transcriptase (Applied Biosystems), and total RNA. An aliquot of 1 ng of total RNA was used for the experiment with 16S rRNA, and 100 ng of total RNA was used for the others. Reaction conditions were 50°C for 30 min and then 95°C for 10 min, followed by 40 cycles of 95°C for 15 s and 60°C for 30 s. Relative ratios were normalized with the value for 16S rRNA and are represented as means of triplicates.

Enzyme assays.
Cells were harvested by centrifugation at 15,000 x g at 4°C for 5 min, washed once with extraction buffer (50 mM Tris-HCl [pH 7.5], 1 mM dithiothreitol, 2 mM EDTA), and suspended in 1 ml of extraction buffer. The cells were disrupted with a sonicator (Bioruptor UCD-250; Cosmo Bio, Tokyo, Japan) in a water bath at 4°C for 30 min with a 50% duty cycle (on for 5 s and then off for 5 s). Cell debris was removed by centrifugation at 15,000 x g at 4°C for 5 min, and the supernatant was used as a crude extract for enzyme assays. Protein concentrations were determined with a protein assay kit (Bio-Rad, CA) by using bovine serum albumin as the standard.

Enzyme activities, in a final volume of 0.5 ml, were monitored at 340 nm and 33°C with a spectrophotometer (DU800; Beckman Coulter, CA). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) activity was assayed as described previously (27) with some modifications. Assays were performed at pH 7.5 with 5 mM glyceraldehyde-3-phosphate. Fructose-1,6-bisphosphate (FBP) aldolase (FBA) assays were performed in a reaction mixture containing 100 mM Tris-HCl (pH 7.5), 10 mM KCl, 0.1 mM MnCl2, 0.2 mM NADH, 0.5 U triosephosphate isomerase (Roche Diagnostics, Basel, Switzerland), 0.5 U glycerol-3-phosphate dehydrogenase (Roche Diagnostics), and 20 mM FBP. Although GAPDH is encoded by the gapA and gapB genes, gapA is solely responsible for the glycolytic GAPDH activity (27).

Extraction and estimations of intracellular metabolite concentration.
For the measurement of intracellular metabolites, 100 µl of cell suspension was rapidly taken into a sample tube with 1.0 ml cold methanol (–80°C). In this procedure, cell metabolism was stopped quickly and intracellular metabolites were simultaneously extracted to the methanol solution (40). After being incubated for 60 min at –20°C, the sample solution was centrifuged at 15,000 x g at 4°C for 5 min, and 700 µl of the resulting supernatant was mixed vigorously with 700 µl of chloroform and 350 µl of water. An aliquot of the upper methanol-water layer (50 µl) was mixed with 50 µl of water or standard mixture solution (5.0 µM each), was evaporated for 45 min with the integrated SpeedVac system (Thermo Fisher Scientific, MA), and then was redissolved in 100 µl of water. Aliquots (10 µl) were used for analysis with liquid chromatography-tandem mass spectrometry. All analyses were carried out with a Prominence20A high-performance liquid chromatography system (Shimadzu, Kyoto, Japan) coupled with a 4000 Q TRAP linear ion trap mass spectrometer (Applied Biosystems/MDS Sciex). Intracellular metabolites were analyzed by ion-pairing reversed-phase liquid chromatography-electrospray ionization-tandem mass spectrometry with 5 mM dibutylammonium acetate (Tokyo Chemical Industry, Tokyo, Japan) as described by Luo et al. (24).

Analytical methods.
Cell suspensions were centrifuged at 15,000 x g at 4°C for 5 min, and the resulting supernatants were used for analyses of glucose and organic acids. Glucose concentrations were determined by an enzyme electrode glucose sensor (BF-4; Oji Scientific Instruments, Hyogo, Japan). Organic acid concentrations were determined by high-performance liquid chromatography as described previously (20). Cell growth was monitored by measuring the absorbance at 610 nm by using a spectrophotometer (Novaspec II; GE Healthcare Bio-Science).


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RESULTS
 
sigB disruption lowers the glucose consumption rate under conditions of oxygen deprivation.
We investigated physiological functions of SigB under conditions of oxygen deprivation by using a sigB-disrupted strain, DR1749. Figure 1 shows glucose consumption of the wild-type (WT) strain and DR1749 under conditions of oxygen deprivation. The glucose consumption rate was lowered by the sigB disruption. As cell proliferation ceased under oxygen deprivation, cellular mass did not change during the reaction. In comparison to the glucose consumption rate for the WT strain, 6.0 ± 0.3 mmol h–1 g dry cells–1, the rate for DR1749, 4.1 ± 0.5 mmol h–1 g dry cells–1, was 32% lower. By complementation with a plasmid harboring the sigB gene, the glucose consumption rate of DR1749 was restored to the level of the WT strain (i.e., increased to 5.8 ± 0.2 mmol h–1 g dry cells–1). These results indicate that SigB has positive effects on glucose consumption under conditions of oxygen deprivation.


Figure 1
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  		FIG. 1. Time course of glucose consumption of C. glutamicum strain R (filled circles) and the sigB disruptant (open circles) under conditions of oxygen deprivation. Experiments were repeated eight times, and representative data are shown.

Table 1 shows rates of organic acid production in the WT strain and DR1749. Production rates of lactate, succinate, and acetate were lowered by 25%, 36%, and 47%, respectively, accompanied by a decrease of the glucose consumption rate for DR1749. The NADH/NAD+ ratio, which is related to the regulation of the glucose consumption rate under conditions of oxygen deprivation (16), was not affected by the sigB disruption (0.09 ± 0.08 for DR1749 and 0.09 ± 0.06 for the WT).


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  		TABLE 1. Organic acid production rates of C. glutamicum R and the sigB disruptant under conditions of oxygen deprivation

Changes in gene expression in the sigB disruptant under conditions of oxygen deprivation.
Gene expression profiles of the WT and DR1749 under conditions of oxygen deprivation were compared using DNA microarray. The transcript levels of 45 genes were reduced more than twofold at the significance level of 1% in DR1749, and the transcript levels of 30 genes were increased (see Tables S2 and S3 in the supplemental material). These genes are predicted to be involved in various cellular functions, based on COGs (clusters of orthologous groups of proteins) categories (37), although the functions are not verified for most of them. Only the pqo gene (cgR2514), encoding pyruvate:quinone oxidoreductase, out of 29 genes involved in the metabolism of glucose into lactate, succinate, and acetate under conditions of oxygen deprivation, was included among the downregulated genes (see Table S2 in the supplemental material). However, we found that for the WT and DR1749, the transcript levels of 15 genes involved in glucose metabolism showed significant differences (P < 0.01), though ratios for most genes were not different more than twofold (Table 2). Differential transcript levels of these genes were confirmed by qRT-PCR analyses. The transcript levels of nine genes, pfkA, fba, tpi, gapA, pgk, eno, ppc, fum, and pqo, were significantly decreased, and the ptsG, mqo, and sdhCAB genes were upregulated, in DR1749 (Fig. 2).


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  		TABLE 2. sigB disruption-induced changes in expression of genes involved in glucose metabolism


Figure 2
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  		FIG. 2. Glucose metabolism pathway in C. glutamicum under conditions of oxygen deprivation. The depicted scheme was predicted based on the studies of Inui et al. (16) and Yasuda et al. (42) and the KEGG PATHWAY Database (http://www.genome.ad.jp/kegg/pathway.html). Genes and reactions catalyzed by their products are shown. Relative ratios of the transcript levels in DR1749 to WT determined by qRT-PCR analyses are shown under the gene names. Data are means ± standard deviations for three independent experiments. Arrows with bold, solid lines and dotted lines indicate genes upregulated and downregulated by the sigB disruption, respectively. Data of qRT-PCR analyses for the sdhC gene are represented as those for the sdhCAB operon. G6P, glucose-6-phosphate; F6P, fructose-6-phosphate; GAP, glyceraldehyde-3-phosphate; DHAP, dihydroxyacetone phosphate; BPG, 1,3-bisphosphoglycerate; 3PG, 3-phosphoglycerate; 2PG, 2-phosphoglycerate; PEP, phosphoenolpyruvate; PYR, pyruvate; OAA, oxaloacetate; Acetyl-P, acetyl phosphate.

The fba and gapA genes in DR1749 had transcript levels that were reduced more than twofold in comparison to those of the WT (Fig. 2). The specific activities of FBA, which is encoded by the fba gene, and GAPDH, which is encoded by the gapA gene, under conditions of oxygen deprivation were examined. FBA and GAPDH activities in DR1749 (0.25 ± 0.03 µmol min–1 mg protein–1 and 1.57 ± 0.08 µmol min–1 mg protein–1, respectively) were reduced to 56% and 70% of the WT values (0.45 ± 0.04 µmol min–1 mg protein–1 and 2.25 ± 0.30 µmol min–1 mg protein–1, respectively), respectively, suggesting that decreases in the transcript levels by the sigB disruption were followed by decreases in the protein levels.

Accumulation of FBP in the sigB disruptant.
Intracellular concentrations of glycolytic intermediates under conditions of oxygen deprivation were quantified in the WT and DR1749. Table 3 shows the ratio of the concentration of each intermediate in DR1749 to its concentration in the WT. Only the FBP levels of all intermediates quantified in this study were significantly changed by the sigB disruption. The intracellular concentration of FBP increased about threefold in DR1749 (Table 3).


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  		TABLE 3. Effects of the sigB disruption on intracellular concentrations of glycolytic intermediates under conditions of oxygen deprivation

Changes in gene expression in the sigB disruptant during aerobic cultivation.
Effects of sigB disruption on expression of genes involved in glucose metabolism during aerobic cultivation were examined. Figure 3 shows changes in the transcript levels of glucose metabolism genes during aerobic cultivation with a shake flask in the WT and DR1749. sigB disruption did not affect growth (Fig. 3J) or glucose consumption (data not shown) during aerobic cultivation. In the WT, the transcript levels of pfkA and gapA genes increased two- to fivefold at the transition from exponential phase to stationary phase and then decreased back to their exponential-phase levels during stationary phase (Fig. 3A and D). The transcript levels of tpi, pgk, and ppc genes were slightly higher at the transition phase than they were during exponential phase, and then the levels drastically decreased during the stationary phase (Fig. 3C, E, and G). pqo transcript levels increased fivefold at the transition phase, followed by further upregulation (Fig. 3I). The transcript levels of fba, eno, and fum genes gradually decreased during aerobic cultivation (Fig. 3B, F, and H). The transcript levels of glucose metabolism genes in DR1749 were lower than those of WT not only at the transition phase but also during the exponential phase. The growth-phase-dependent changes in expression of genes involved in glucose metabolism were not affected by sigB disruption.


Figure 3
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  		FIG. 3. Changes in the transcript levels of genes involved in glucose metabolism during aerobic cultivation. The relative transcript levels of pfkA (A), fba (B), tpi (C), gapA (D), pgk (E), eno (F), ppc (G), fum (H), and pqo (I) at exponential phase (white bars), at transition from exponential phase to stationary phase (light gray bars), and at stationary phase (dark gray bars) in the WT and DR1749 were determined by qRT-PCR. The transcript levels were determined in triplicate using two independently grown cultures. The transcript level at exponential phase in the WT was taken as 1. (J) Growth curves of C. glutamicum strain R (filled circles) and the sigB disruptant (open triangles) during aerobic cultivation. Cells were harvested at 3 h (exponential phase), 6 h (transition phase), and 12 h (stationary phase). Arrows indicate sampling points.

Global changes in gene expression during exponential growth by sigB disruption were examined by DNA microarray. The transcript levels of 96 genes, including the glucose metabolism genes such as fba, tpi, gapA, pgk, and pqo, were downregulated more than twofold in DR1749, while 39 genes were upregulated (see Tables S4 and S5 in the supplemental material). sigB disruption decreased the transcript levels of 27 genes both during exponential growth and under conditions of oxygen deprivation, while only 2 genes were upregulated under both conditions in DR1749.

Promoter sequences of glucose metabolism genes downregulated by sigB disruption.
We found that nine glucose metabolism genes were downregulated by sigB disruption (Fig. 2 and 3). The promoter sequences of these genes have been determined previously (7, 8, 34, 36, 38). The gapA, pgk, tpi, and ppc genes are cotranscribed from the promoters upstream of the gapA and pgk genes (36). Alignment of the promoter sequences of these genes provides the consensus sequence tAnAAT for the –10 region and cgGCaa for the –35 region (Fig. 4A). The consensus sequence for the –10 region was comparable to that suggested to be recognized by SigA of C. glutamicum (TAtaaT), while the –35 regions were different for promoters recognized by SigB and SigA (ttGcca) (29).


Figure 4
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  		FIG. 4. Promoter sequences of glucose metabolism genes downregulated (A) and not downregulated (B) by the sigB disruption under conditions of oxygen deprivation. The upstream sequences of 50 nt from the transcription initiation site experimentally determined previously (4, 7, 8, 17, 30, 33-36, 38) are indicated. The nucleotides conserved among all and more than 70% of the sequences are shaded in black and gray, respectively. The consensus sequences of –10 and –35 regions are determined by the BioProspector program (23) and are given at the bottom. Consensus sequences where >70% and 50% of nucleotides are conserved are indicated by uppercase and lowercase letters, respectively.


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DISCUSSION
 
In the present study, we found that the glucose consumption rate under conditions of oxygen deprivation was lowered by sigB disruption (Fig. 1). Transcript levels of genes involved in glucose metabolism were decreased for a sigB disruptant (Table 2 and Fig. 2). These results indicate that SigB positively regulates glucose metabolism in C. glutamicum under conditions of oxygen deprivation.

Under conditions of oxygen deprivation, NADH is oxidized to NAD+ by the action of NAD-dependent dehydrogenases, such as lactate dehydrogenase (encoded by ldhA) and malate dehydrogenase (encoded by mdh), and the glucose consumption rate is correlated to the intracellular NADH/NAD+ ratio in C. glutamicum (16). Alteration of metabolic pathways from glucose to organic acids by disruption of a gene involved in the production of either lactate or succinate suppresses NADH oxidation, and the resulting increase in the NADH/NAD+ ratio reduces the GAPDH activity, which is highly susceptible to a high NADH/NAD+ ratio (2), with subsequent reduction of the glucose consumption rate. For the sigB disruptant, the transcript levels of ppc, fum, and pqo, which are involved in succinate and acetate production, were decreased (Fig. 2), and lactate, succinate, and acetate production rates were reduced to different extents (Table 1). Although the metabolic flow from glucose to organic acids was altered by the sigB disruption, the intracellular NADH/NAD+ ratio was not affected. Thus, it is unlikely that the NADH/NAD+ ratio is primarily responsible for the retardation of glucose consumption by the sigB disruption. On the other hand, among the intracellular glucose metabolites examined, the concentration of FBP was significantly increased by disruption of the sigB gene (Table 3), a result which was consistent with the reduced levels of fba transcripts and the FBA activity (Table 2; see Results). We enhanced the FBA activity of DR1749 3.8-fold with a plasmid harboring the fba gene (data not shown). However, the glucose consumption rate of DR1749 with the enhanced FBA activity was 4.2 ± 0.2 mmol h–1 g dry cells–1, which is comparable to that of DR1749 (4.1 ± 0.5 mmol h–1 g dry cells–1). These results indicate that the depressed FBA activity is not solely responsible for the reduced rate of glucose consumption in DR1749. Extensive decreases in the transcript levels of glucose metabolism genes may contribute to the reduced rate of glucose consumption in the sigB disruptant.

The consensus sequences of the –10 and –35 promoter regions of the glucose metabolism genes regulated by SigB were tAnAAT and cgGCaa, respectively (Fig. 4A). Sequences of TA(t/c)nnT for the –10 region and TtnaCA for the –35 region were found within promoter regions of the other glucose metabolism genes (Fig. 4B), and these promoter regions were similar to the promoter sequences suggested to be recognized by SigA of C. glutamicum, TA(c/t)aaT for the –10 region and ttGcca for the –35 region (29). The consensus sequence of the –10 promoter region recognized by SigB is comparable to that recognized by SigA, but the fourth and fifth adenines of the –10 promoter sequences of the SigB-regulated genes are highly conserved. The –10 promoter sequence of the ldhA gene (cgR2812), CATAAT, is similar to that of the SigB-regulated genes (Fig. 4B), and it has been downregulated by sigB disruption during exponential growth (see Table S4 in the supplemental material). SigB would preferentially recognize the –10 promoter sequence with the fourth and fifth adenines. Although the –35 promoter sequence is less conserved, it is likely that the selectivities of the –35 promoter sequence for SigA and SigB differ. However, sigB disruption did not completely eliminate transcription of glucose metabolism genes regulated by SigB but reduced the transcript levels by half (Fig. 2), suggesting that SigA is also capable of directing transcription from these promoters and cooperates with SigB in transcription of glucose metabolism genes.

We identified 114 genes whose transcript levels were decreased by sigB disruption under conditions of oxygen deprivation and during exponential growth (see Tables S2 and S4 in the supplemental material). Twenty-seven genes were downregulated under both conditions. Moreover, only four genes, cgR1219, cgR1581, cgR1849, and cgR2611, were previously shown by Larisch et al. to be SigB regulated (22); in their study, effects of sigB disruption on changes in gene expression between exponential and transition phases were examined. These results suggest that SigB is involved in the regulation of different sets of genes depending on growth conditions in cooperation with specific transcriptional regulators.

It has been thought that the group 2 sigma factor is involved in regulation of gene expression at the transition to stationary phase and in the stress response network (9, 10, 22). RpoS specifically induces the expression of numerous genes at the transition phase and at the same time takes over cellular functions from RpoD by continuing the transcription of genes with promoters recognized by both sigma factors. Recently, RpoS of E. coli was shown to regulate a large set of genes even during exponential growth (3, 31). It has been reported that the group 2 sigma factor SigE of the cyanobacterium Synechocystis sp. PCC 6803 participates in regulation of gene expression during exponential growth and positively regulates sugar catabolic pathways (28). In the present study, we showed that SigB of C. glutamicum positively regulates glucose metabolism genes even during exponential growth, supporting the notion that the group 2 sigma factor should function as another vegetative sigma factor.


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ACKNOWLEDGMENTS
 
We thank Crispinus A. Omumasaba (Research Institute of Innovative Technology for the Earth) for critical reading of the manuscript.

This study was partially supported by a grant from the New Energy and Industrial Technology Development Organization, Japan.


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FOOTNOTES
 
* Corresponding author. Mailing address: Research Institute of Innovative Technology for the Earth, 9-2 Kizugawadai, Kizugawa, Kyoto 619-0292, Japan. Phone: 81-774-75-2308. Fax: 81-774-75-2321. E-mail: mmg-lab{at}rite.or.jp Back

{triangledown} Published ahead of print on 20 June 2008. Back

{dagger} Supplemental material for this article may be found at http://aem.asm.org/. Back


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Applied and Environmental Microbiology, August 2008, p. 5146-5152, Vol. 74, No. 16
0099-2240/08/$08.00+0     doi:10.1128/AEM.00944-08
Copyright © 2008, American Society for Microbiology. All Rights Reserved.



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