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Keywords:

  • CRP/FNR family;
  • DNA microarray;
  • gene regulation;
  • stress response;
  • thermophile;
  • transcription factor

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The stationary phase-dependent regulatory protein (SdrP) from the extremely thermophilic bacterium, Thermus thermophilus HB8, a CRP/FNR family protein, is a transcription activator, whose expression increases in the stationary phase of growth. SdrP positively regulates the expression of several genes involved in nutrient and energy supply, redox control, and nucleic acid metabolism. We found that sdrP mRNA showed an increased response to various environmental or chemical stresses in the logarithmic growth phase, the most effective stress being oxidative stress. From genome-wide expression pattern analysis using 306 DNA microarray datasets from 117 experimental conditions, eight new SdrP-regulated genes were identified among the genes whose expression was highly correlated with that of sdrP. The gene products included manganese superoxide dismutase, catalase, and excinuclease ABC subunit B (UvrB), which plays a central role in the nucleotide excision repair of damaged DNA. Expression of these genes also tended to increase upon entry into stationary phase, as in the case of the previously identified SdrP-regulated genes. These results indicate that the main function of SdrP is in the oxidative stress response.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Bacteria are exposed to various stresses in nature, including nutrient availability, osmolarity, redox, pH, temperature, antibiotic, and toxic heavy metal stresses. In order to adapt quickly and to survive an abrupt environmental change, bacteria have developed an environmental response system that controls the expression of various proteins for defense against various stresses, and repairs the damaged cellular components. Bacterial stress responses are mainly controlled at the transcription level, i.e., alternative σ factors and/or transcription factors are involved in the expression of stress response genes (Stock et al., 2000; Raivio & Silhavy, 2001; Helmann, 2002; Hengge-Aronis, 2002; Gruber & Gross, 2003; Marles-Wright & Lewis, 2007; Hengge, 2008). In many cases, various stress response genes are under the control of the same transcription factor (Storz & Imlay, 1999; Hengge-Aronis, 2002). In fact, the response to a certain stress is often accompanied by seemingly unrelated responses. For example, glucose- or nitrogen-starved cultures of Escherichia coli exhibit enhanced resistance to heat, H2O2, or osmotic challenge (Jenkins et al., 1988; Jenkins et al., 1990); furthermore, when bacteria are challenged with high osmolarity, they acquire increased resistance to high temperature and oxidative stresses (Tesone et al., 1981; Hengge-Aronis et al., 1993; Canovas et al., 2001; Gunasekera et al., 2008). Elucidation of bacterial stress responses will facilitate understanding of bacterial physiology.

The stationary phase-dependent regulatory protein (SdrP) is a CRP/FNR family transcriptional regulator from Thermus thermophilus HB8 (Agari et al., 2008), which is an extremely thermophilic bacterium isolated from the water at a Japanese hot spring. Thermus thermophilus HB8 can grow at 47–85 °C, and its optimum temperature range is from 65 to 72 °C (Oshima & Imahori, 1974). Previously, we demonstrated that sdrP mRNA increases upon entry into the stationary phase, and SdrP positively regulates the expression of several kinds of genes, which are possibly involved in nutrient and energy supply, redox control, and polyadenylation of mRNA (Agari et al., 2008). Transcriptional activation occurs independently of any added effector molecule, which is supported by the observation that the three-dimensional structure of apo-SdrP is similar to that of the DNA-binding form of E. coli CRP (Agari et al., 2008). In this study, to gain further insight into the cellular function of SdrP, we developed a new approach to identify novel genes whose expression was regulated by SdrP.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Reverse transcriptase (RT)-PCR analysis

The T. thermophilus wild-type and csoR gene-deficient (ΔcsoR) strains (Sakamoto et al., 2010) were cultured at 70 °C in a rich or synthetic medium (Supporting Information, Table S1). The details of the culture conditions are given in the NCBI Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/projects/geo/), the accession numbers being GSE21433 [for N,N,N′,N′-tetramethylazodicarboxamide (diamide) treatment], GSE21430 (for H2O2 treatment), GSE20900 (for ZnSO4 treatment), GSE21432 (for tetracycline treatment), GSE21289 (for NaCl treatment), GSE21435 (for ethanol treatment), GSE19508 (for CuSO4 treatment of the wild-type strain), and GSE19509 (for CuSO4 treatment of the ΔcsoR strain). Total RNA was isolated from each strain, as described previously (Shinkai et al., 2007). Using the RNA (1 μg) as a template, RT-PCR was performed in 20 μL reaction mixtures with a PrimeScript RT-PCR kit (Takara Bio. Inc.) according to the manufacturer's instructions. The reverse transcription reaction was performed at 42 °C for 20 min. Using 1 μL of the reaction mixture as a template, PCR was performed in the presence of 0.2 μM each of the forward and reverse primes in a 25 μL reaction mixture. After the reaction, samples were analyzed on a 2% agarose gel, followed by staining with ethidium bromide and photography. The primers used are listed in Table S2.

DNA microarray analysis

The experimental conditions are given in the NCBI GEO website, and the accession numbers are given in Table 1 and in Table S1. Briefly, crude RNA was extracted from each sample, and then cDNA was synthesized, followed by fragmentation and labeling with biotin–dUTP using DNA-labeling reagents from Affymetrix Inc. (Santa Clara) or ENZO Life Sciences Inc. (Farmingdale) according to the manufacturer's instructions, as described previously (Shinkai et al., 2007; Agari et al., 2008). The 3′-terminal-labeled cDNA was hybridized to a TTHB8401a520105F GeneChip (Affymetrix Inc.), and then the array was washed, stained, and scanned as described previously (Agari et al., 2008). The raw intensity data were summarized as 2266 ORFs using genechip operating software version 1.4 (Affymetrix Inc.).

Table 1.   Expression of sdrP and its target genes under various stress conditions
Gene name*Spearman's correlation coefficientDiamideH2O2ZnSO4TetracyclineNaClEthanolCuSO4 (wild type)CuSO4csoR)Stationary phase
  • The expression level in cells after treatment with 2 mM diamide for 30 min, 10 mM H2O2 for 5 min, 1 mM ZnSO4 for 30 min, 50 mM tetracycline for 10 min, 1.5% NaCl for 30 min, 5% ethanol for 30 min, or 1.25 mM CuSO4 for 30 min, relative to untreated cells, is shown. The expression level in the stationary phase is the relative value compared with that in the logarithmic phase. Gray background indicates that the q-value is >0.05. The details of these experiments are given in the NCBI GEO website under GEO series accession numbers described under ‘RT-PCR analysis’. For the stationary phase data, that is GSE21290.

  • *

    The nucleotide sequences and deduced amino acid sequences can be found in the NCBI website accessible under GenBank accession numbers AP008226, AP008227, and AP008228. The genes identified in this study are indicated by bold letters.

  • The expression level after cultivation for 680 min relative to that for 300 min is shown, except in the case of the TTHA0425 gene, the expression level of which is relative to that for 480 min (Agari et al., 2008).

sdrP1.0027108.16.15.65.22.11822
TTHA11280.91101.33.01.92.52.21.37.95.7
TTHA09860.83122.52.70.81.71.11.27.87.6
TTHA05700.812.91.22.11.51.40.91.14.53.0
TTHA00290.806.21.62.61.31.72.51.25.52.8
TTHA16350.774.11.41.95.71.21.81.23.08.0
TTHA06370.773.71.41.60.61.31.01.12.72.3
TTHA06360.754.21.61.80.71.31.11.02.91.9
TTHA05570.723.51.51.62.21.31.00.93.72.9
TTHA12150.712.51.91.80.71.61.41.22.12.0
TTHA18920.703.53.02.20.80.91.81.12.43.2
TTHB1320.672.61.82.01.40.81.31.11.74.0
TTHA16250.672.71.71.52.20.71.00.93.24.4
TTHA06540.673.91.71.70.31.60.91.23.42.0
TTHA06340.664.81.61.80.61.11.01.03.01.9
TTHA06350.664.01.61.60.61.11.21.03.31.7
TTHA06380.662.11.91.20.81.51.01.01.92.6
TTHA07690.652.02.31.20.41.31.60.82.02.8
TTHA07700.655.21.91.60.41.21.20.93.54.6
TTHA03370.511.92.00.61.21.11.01.02.81.5
TTHA06550.512.61.51.70.51.50.81.12.61.5
TTHA10280.481.71.30.71.41.40.71.02.61.4
TTHA04250.416.32.41.60.85.60.71.77.32.7
Comparative expression analysis

The datasets were normalized through the following normalization steps using the Subio Platform (Subio Inc.), i.e. shifting of low signals <1.0 to 1.0, log-based transformation of the data, and global normalization [normalized as to 75 percentile (third quartile)]. The data for chemically treated cells were normalized using the data for the nontreated cells as a control. The t-test P-value of the observed differences in the normalized intensities was calculated using the Subio Platform, and then from the value, the false discovery rate (q-value), which is useful for measuring statistical significance in multiple-hypothesis testing (Storey & Tibshirani, 2003), was calculated using r (http://www.R-project.org). In this study, we arbitrarily considered the q-value threshold to be 5%, a well-used significant threshold value, which means that q-values ≤0.05 provide significant genes for differential expression, whereas values >0.05 do not, but still may not be false.

Expression pattern analysis

Three hundred and six datasets from 117 experimental conditions were used for the analysis (Table S1). Normalization of the datasets was performed as described above except that the normalization to the mean value for each gene was performed after the global normalization. Spearman's correlation coefficients, between the sdrP gene and each of 2266 genes, were calculated using the Subio Platform.

The microarray data used in this study have been summarized and deposited in the GEO database, and are accessible through GEO series accession number GSE21875.

In vitro transcription assays

Preparation of templates

The regions upstream of the TTHA0029, TTHA0557, TTHA1128, TTHA1215, TTHA1625, TTHA1635, TTHA1892, TTHB132, and TTHA0987 genes were amplified by genomic PCR using the primers listed in Table S2. The amplified fragments were digested with BamHI and EcoRI, and then cloned into pUC19 (Merck). Using each plasmid as the template, PCR was performed with primers P21 and P22 (Table S2) to prepare template DNAs for the transcription assay. The amplified fragments were excised from a 0.8% agarose gel, extracted with phenol and ether, and then precipitated with ethanol. The DNA fragments were used for the following assays.

Run-off transcription

Assays were performed in 15-μL reaction mixtures in the absence or presence of 2 μM T. thermophilus SdrP by basically the same process as that described previously (Shinkai et al., 2007). The template DNA was preincubated with or without SdrP at 55 °C for 5 min. Thermus thermophilus RNA polymerase-σA holoenzyme purified as described previously (Vassylyeva et al., 2002) was added, and then the mixture was further incubated for 5 min. Transcription was initiated by the addition of 1.5 μCi [α-32P]CTP and unlabeled ribonucleotide triphosphates. After further incubation for 10 min, the reaction was stopped, and the sample was analyzed on a 10% polyacrylamide gel containing 8M urea, followed by autoradiography.

Identification of the in vitro transcriptional start site

Primer extension analysis with RNA transcribed in vitro was performed by basically the same method as that described previously (Shinkai et al., 2007). The nucleotide sequence of the template DNA was determined by the dideoxy-mediated chain termination method (Sanger et al., 1977). Samples were analyzed on an 8% polyacrylamide gel containing 8M urea, followed by autoradiography.

Other methods

A blast search was performed at http://blast.ncbi.nlm.nih.gov/Blast.cgi.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Environmental stresses that induce expression of the sdrP gene

In the previous study, we observed that the growth of an sdrP gene-deficient (ΔsdrP) strain was more significantly affected by diamide treatment, which forms non-native disulfide bonds (Leichert et al., 2003; Nakunst et al., 2007), in comparison with that of the wild type (Agari et al., 2008). In order to determine whether oxidative stress induces expression of the sdrP gene, we treated the wild-type T. thermophilus HB8 strain in the logarithmic growth phase with diamide or H2O2. RT-PCR analysis showed that expression of the sdrP gene increased with the addition of a final concentration of 2 mM diamide or 10 mM H2O2 (Fig. 1), which was supported by DNA microarray analysis results that showed that expression of the gene increased 27-fold (q-value=0.00) and 11-fold (q-value=0.00) in response to diamide and H2O2 treatment, respectively (Table 1). Next, we examined whether other environmental or chemical stresses, such as heavy metal ion (ZnSO4 and CuSO4), antibiotic (tetracycline), high-salt (NaCl), and organic solvent (ethanol) stresses, induce expression of the sdrP gene. RT-PCR (Fig. 1) and DNA microarray (Table 1) analyses indicated that expression of the sdrP gene was induced by all of these stresses. In the ΔcsoR strain, in which excess Cu(I) ions may accumulate due to a significant decrease in the expression of the probable copper efflux P-type ATPase gene copA (Sakamoto et al., 2010), the effect of excess CuSO4 on expression of the sdrP gene was more significant than that in the wild-type strain (Fig. 1 and Table 1).

image

Figure 1.  RT-PCR analysis was performed to detect sdrP mRNA for total RNA isolated from the Thermus thermophilus wild-type (lanes 2–9) and ΔcsoR (lanes 10 and 11) strains cultivated in the absence (lanes 2 and 10) or presence of 2 mM diamide for 30 min (lane 3), 10 mM H2O2 for 5 min (lane 4), 1 mM ZnSO4 for 30 min (lane 5), 50 mM tetracycline for 10 min (lane 6), 1.5% NaCl for 30 min (lane 7), 5% ethanol for 30 min (lane 8), or 1.25 mM CuSO4 for 30 min (lanes 9 and 11), respectively, and samples were analyzed on a 2% agarose gel, followed by staining with ethidium bromide and photography. The PCR analysis involved 20 cycles of 98°C for 1 min, 65°C for 1 min, and 72°C for 1 min. Lane 1, 100-bp DNA ladder markers.

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Screening of SdrP-related genes by genome-wide expression pattern analysis

We found that expression of sdrP drastically changed depending on the environmental conditions. Because SdrP does not require any added effector molecule to induce transcription of target genes in vitro (Agari et al., 2008), the cellular responses via SdrP most likely depend on the expression level of the sdrP gene, and not post-translational modification of the protein. In order to find novel genes regulated by SdrP, we performed expression pattern analysis using the 306 DNA microarray datasets derived with 117 experimental conditions, which were obtained for time-dependent expression analysis of the wild-type strain in a rich or synthetic medium (91 samples with 40 experimental conditions), expression analysis of a gene-disruptant strain (95 samples with 35 experimental conditions), expression analysis after chemical or physical treatment, or phage infection (87 samples with 29 experimental conditions), and a combination of gene-disruption with chemical or physical treatment, or with phage infection (33 samples with 13 experimental conditions) (Table S1). As a result, 40 genes whose expression was strongly positively correlated with that of the sdrP gene were selected, their Spearman's correlation coefficients being ≥0.65 (Fig. S1 and Tables S3 and S4). Among them, the proportion of genes belonging to COGs (clusters of orthologous groups of proteins) code O (post-translational modification, protein turnover, chaperones) and code C (energy production and conversion) were higher (Tables S3 and S4). Ten of the 14 SdrP-regulated genes identified previously (Agari et al., 2008) were included in these 40 genes (Table 1 and Table S3).

On the other hand, expression of 16 genes was strongly and negatively correlated with that of the sdrP gene, with Spearman's correlation coefficients≤−0.65 (Tables S3 and S5). Among them, the proportion of genes belonging to COGs code H (coenzyme transport and metabolism) was the highest, suggesting that some specific metabolism was inversely correlated with the stress response via SdrP.

Identification of novel SdrP-regulated genes

In order to determine whether novel SdrP-regulated genes are included in the 40 genes that showed Spearman's correlation coefficients of ≥0.65, we searched for SdrP-binding sites upstream of these genes. We found that sequences upstream of the TTHA0029, TTHA0557, TTHA1128, TTHA1215, TTHA1625, TTHA1635, TTHA1892, and TTHB132 genes were homologous to that of a putative consensus SdrP-binding site (Fig. 2a) (Agari et al., 2008). The DNA fragments containing the putative binding sites were cloned and used as templates for in vitro run-off transcription assays. We found that all of the genes were transcribed by T. thermophilus RNA polymerase-σA holoenzyme in an SdrP-dependent manner, as in the cases of the SdrP-regulated genes identified previously (Fig. 3) (Agari et al., 2008). SdrP did not enhance transcription of the DNA fragment containing upstream of the TTHA0987 gene (Spearman's correlation coefficient=0.64) (Fig. 3), or those containing other genes derived from T. thermophilus HB8 (Agari et al., 2008), indicating that SdrP does not nonspecifically bind DNA under these experimental conditions. We found that the in vitro transcription start sites of the novel SdrP-regulated genes were 6–7 bp downstream from the predicted −10 hexamers of their promoters and around 40 bp downstream of the putative SdrP-binding sites, as in the cases of the previously identified SdrP-regulated genes (Fig. 2a and Fig. S2) (Agari et al., 2008). We investigated the sequence conservation of the putative binding-sequences of 16 SdrP-regulated promoters including those identified in the previous study (Agari et al., 2008) (Fig. 2a and b). The results indicate that the left arm of the putative binding-sites is relatively conserved as TTGTG, but the right arm is not except for two C bases (Fig. 2b).

image

Figure 2.  (a) Nucleotide sequence alignment of predicted SdrP-dependent promoters found in the sequence upstream of the TTHA0557 (TTHA0557_up), TTHA0029 (TTHA0029_up), TTHA1128 (TTHA1128_up), TTHA1215 (TTHA1215_up), TTHA1625 (TTHA1625_up), TTHA1635 (TTHA1635_up), TTHA1892 (TTHA1892_up), and TTHB132 (TTHB132_up). The putative Thermus thermophilus SdrP-binding sites are indicated. Possible −10 hexamer sequences of the promoters are indicated by bold italic letters. The in vitro transcriptional start sites (see Fig. S2) are indicated by bold capital letters. The numerals represent the positions from the transcriptional start site. (b) Sequence conservation at the putative SdrP-binding site. The sequence logos (Schneider & Stephens, 1990) of the 16 putative SdrP-binding sites including those identified previously (Agari et al., 2008) were created by WebLogo (Crooks et al., 2004).

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image

Figure 3.  Run-off transcription assays performed with the templates containing the sequences shown in Fig. 2 and upstream of TTHA0987 (TTHA0987_up) in the absence (−) or presence (+) of Thermus thermophilus SdrP. After the reaction, equivalent volumes of samples were analyzed by polyacrylamide gel electrophoresis, followed by autoradiography. Lane 1, [α-32P]dCTP-labeled MspI fragments of pBR322.

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Table 2 summarizes the eight genes that are under the control of the SdrP-dependent promoter found in this study. The gene products include manganese superoxide dismutase (TTHA0557) (Ludwig et al., 1991; Peterson et al., 1991) and catalase (TTHA1625) (Rehse et al., 2004), which are involved in the oxidative stress response, and excinuclease ABC subunit B (UvrB) (TTHA1892) (Nakagawa et al., 1999), which plays a central role in the nucleotide excision repair of damaged DNA. According to blast searches, the functions of the other gene products were predicted to be in redox control (TTHA1215, TTHA1635, and TTHB132), protein degradation (TTHA1128), and transcriptional regulation (TTHA0029). Expression of the genes also tended to increase upon entry into the stationary phase, as in the case of the previously identified SdrP-regulated genes (Table 1). We could not find the predicted SdrP-binding sequence close to the promoter regions of the 16 genes whose expression showed strong negative correlation with that of the sdrP gene, suggesting that SdrP does not act as a transcription repressor. Thus, including the 14 previously identified genes, a total of 22 genes have been identified as SdrP-regulated genes.

Table 2.   Genes under the control of the SdrP-dependent promoters identified in this study
Gene nameConserved domain*e-valueAnnotation of productPossible cellular roleReference
  • *

    The domain was identified in a blast search.

  • This value is for the amino acid sequence of the conserved domain.

  • The C-terminal domain of the TTHA0029 protein showed homology to that of Meiothermus silvanus ZP_04036762 annotated as a transcriptional regulatory protein, the e-value being 3e-20.

TTHA0029Hypothetical proteinTranscriptional regulation 
TTHA0557COG06058e-73Manganese superoxide dismutaseRedox controlLudwig et al. (1991); Peterson et al. (1991)
TTHA1128COG15062e-21PeptidaseProtein quality control; Nutrient supply 
TTHA1215COG04922e-30Thioredoxin reductaseRedox control 
TTHA1625TIGR035627e-54Osmotically inducible protein OsmCRedox controlRehse et al. (2004)
TTHA1635TIGR000498e-41Iron−sulfur cluster biosynthesis protein IscARedox controlZheng et al. (1998); Yang et al. (2006)
TTHA1892COG05561e-180Excinuclease ABC subunit B (UvrB)DNA repairNakagawa et al. (1999)
TTHB132PRK000582e-72Methionine sulfoxide reductase A (MsrA)Protein repairEzraty et al. (2005)

We analyzed the altered expression profiles of the 22 SdrP-regulated genes in cells perturbed by the various stresses, and found that the expression of most genes increased with these perturbations (Table 1). The altered expression profile caused by 2 mM diamide treatment was the most similar to that upon entry into the stationary growth phase (Table 1). The expression level did not always correlate with that of the sdrP gene, especially in response to perturbation by 50 mM tetracycline, in which the expression of 13 genes was significantly decreased (Table 1). These results suggest that depending on the stress, not only the signal via SdrP, but also other signal(s) are transmitted to the cells to alter expression of the SdrP-regulated genes.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Using expression pattern analysis of a large amount of DNA microarray data, we found eight new SdrP-regulated genes that were not identified in previously studies using comparative expression analysis of the wild-type and ΔsdrP strains (Agari et al., 2008). These genes were not identified as SdrP-regulated genes in the previous study for the following reasons. Although the expression levels of the eight genes were 0.17–0.63-fold in the ΔsdrP strain relative to that in wild type, their q-values except that of TTHA1128 were 0.061–0.242, which were greater than the threshold value used in the experiment (0.06). As for TTHA1128, identification of a SdrP-binding site in the promoter region was missed in the previous study. Conversely, expression of four out of 14 SdrP-regulated genes identified in the previous study showed lower correlation to that of sdrP (Spearman's correlation coefficients≤0.51). Some unknown factors such as promoter activity and affinity of SdrP to DNA in vivo, and unidentified transcriptional regulator(s) that might act together with SdrP, might influence the results of the experimental screenings for SdrP-regulated genes. Thus, a combination of comparative expression analysis and expression pattern analysis was appropriate for screening of SdrP-regulated genes.

Among the environmental and chemical stresses examined in this study, the diamide and H2O2 stresses were the most effective in enhancing the expression of sdrP and its target genes in the wild-type strain. Furthermore, an excess amount of CuSO4 was a strong inducer of sdrP gene expression in the ΔcsoR strain, in which excess Cu(I) ions may accumulate (Sakamoto et al., 2010). In this strain, excess Cu(I) ions, which have the potential to drive oxidation/reduction to form free radicals (Touati, 2000; Imlay, 2002), may trigger expression of sdrP. As for the possible cellular functions of the 22 SdrP-regulated gene products, at least nine, i.e. TTHA0425, TTHA0557, TTHA0654, TTHA0986, TTHA1028, TTHA1215, TTHA1625, TTHA1635, and TTHB132, are possibly involved in redox control (Table 2) (Agari et al., 2008). UvrB (TTHA1892) may be involved in the repair of oxidized DNA. The altered expression levels of sdrP and its target genes in the stationary growth phase were similar to those caused by diamide treatment. These results suggest that the main inducer of sdrP expression is oxidative stress, and support the previous finding that SdrP functions in the response to oxidative stress. Because SdrP does not have a cysteine residue or cofactor that could be a sensor of an oxidative signal [unlike in the case of other oxidative stress-responsive transcriptional regulators such as OxyR, PerR, and SoxR (Storz & Imlay, 1999; Pomposiello & Demple, 2001; Lee & Helmann, 2006)], and it does not require any effector molecule for its transcriptional activation (Agari et al., 2008), there may be some unidentified factor(s) sensing oxidative stress and causing induced expression of SdrP. It has been demonstrated that the bacterial response to a specific stress can increase the resistance to other stresses, probably because stresses are not encountered in isolation in nature (Tesone et al., 1981; Jenkins et al., 1988; Jenkins et al., 1990; Hengge-Aronis et al., 1993; Storz & Imlay, 1999; Canovas et al., 2001; Hengge-Aronis, 2002; Gunasekera et al., 2008). Because expression of the sdrP gene was also enhanced by other stresses, cross-protection may occur via SdrP in T. thermophilus HB8.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We wish to thank Keiko Sakamoto for the RT-PCR analysis. We also thank Noriko Nakagawa, Aiko Kashihara, Emi Ishido-Nakai, Miwa Ohmori, Kenji Fukui, Takushi Ooga, Toshiko Miyazaki, and Keiko Sakamoto for their excellent support in the GeneChip analysis, and Kazuko Agari for the excellent support with preparation of the templates for the in vitro transcription assays.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Fig. S1. Expression pattern analysis using DNA microarray data.

Fig. S2. Identification of the transcriptional start site.

Table S1. GEO accession numbers and experimental conditions for the DNA microarray dataset.

Table S2. Oligonucleotides used in this study.

Table S3. Number of genes correlated with sdrP gene in each COGs category.

Table S4. Genes exhibiting Spearman's correlation coefficients, as to the sdrP gene, of ≥0.50.

Table S5. Genes exhibiting Spearman's correlation coefficients as to the sdrP gene, of ≤-0.50.

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