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J Bacteriol. Nov 2006; 188(22): 7742–7758.
PMCID: PMC1636327

Influence of the Two-Component System SaeRS on Global Gene Expression in Two Different Staphylococcus aureus Strains

Abstract

The two-component system SaeRS consisting of the histidin kinase SaeS and the response regulator SaeR is known to act on virulence gene expression in Staphylococcus aureus. In order to get a more comprehensive picture on SaeR-regulated genes, we studied the contribution of the two-component system on global gene expression by using both the proteomic and transcriptomic approach. Altogether, a loss of SaeRS resulted in a decreased amount of at least 17 extracellular proteins and two cell surface-associated proteins, among them several important virulence factors such as HlgA, HlgB, HlgC, LukF, and LukM. SaeRS activates the expression of these genes at the transcriptional level. The amount of the five proteins Aur, SspA, SsaA, Plc, and GlpQ was negatively influenced by SaeRS. However, the transcription of the corresponding genes was not affected by the two-component system. SaeRS had also no measurable influence on the transcription of the regulatory genes agr, sarA, arlRS, and sigB that contribute to the regulation of SaeRS-dependent virulence factors identified in this investigation. Our results clearly show that SaeRS is strongly involved in the tight temporal control of virulence factor expression in S. aureus. Its precise role within the regulatory network remains to be determined.

Staphylococcus aureus is a gram-positive bacterium that colonizes the anterior nares of at least one-third of the human population but also causes a variety of infections ranging from superficial lesions, such as wound infections and abscesses, to severe systemic infections such as bacteremia, endocarditis, pneumonia, and osteomyelitis. The pathogenicity of this organism largely depends on the successful adaptation to the human host and the environmentally coordinated expression of virulence factors. The expression of virulence factors in S. aureus is regulated during the growth cycle by a network of interacting regulators (for a review, see reference 41). The best-characterized virulence-associated regulons thus far are the agr regulon (accessory gene regulator), the SarA regulon (staphylococcal accessory regulator), the σB regulon (alternative sigma factor), the Rot regulon (regulator of toxins), and the ArlRS regulon (autolysis-regulated locus) (7, 15, 20, 37, 47, 60, 61).

The sae locus was first described by Giraudo et al. (27) following the characterization of a Tn551 insertional mutant of S. aureus RC161. sae is a regulatory locus that consists of four open reading frames, two of them encode the response regulator and the sensor kinase, respectively (23). Two additional open reading frames coding for hypothetical proteins are probably important for the functionality of the sae operon (42, 56). The two-component system SaeRS itself activates the expression of several virulence factors such as serine protease SspA, thermonuclease Nuc, coagulase Coa, alpha-hemolysin Hla, beta-hemolysin Hlb, extracellular adherence protein Eap, extracellular matrix binding protein Emp, protein A, and fibronectin binding protein FnbA (24, 27-30, 42). In contrast, the expression of the cap operon is repressed by SaeRS (56). The transcription of the sae operon is influenced by environmental signals such as pH, salt, and glucose concentrations or subinhibitory concentrations of antibiotics (42, 35). Moreover, the transcription of sae is controlled by other virulence-associated regulators (24, 42). It has been shown that agr might influence the transcription of sae, which would explain the concomitant influence of both regulators on the synthesis of extracellular proteins (25, 28, 42). In contrast, an sae mutation has no effect on the expression of agr and sarA (24). Therefore, it has been suggested that SaeRS regulates the synthesis of extracellular proteins downstream of agr and might modify quorum sensing-dependent regulation by sensing of additional signals. Whether or not SaeR interacts with other regulators is largely unknown.

Furthermore, there are data indicating that the sae locus is essential for virulence gene expression under in vivo conditions (28, 29, 45). Consequently, the virulence of the sae mutant, assayed by the intraperitoneal injection in mice, was significantly lower than that of the parental strain (45). The importance of SaeRS for the virulence of S. aureus was also emphasized in two whole-genome screens for the identification of genes required for full virulence (1, 4).

To date, only a few genes are known to be regulated by the two-component system. Therefore, we used transcriptomic and proteomic approaches to define the SaeRS regulon structure in two different S. aureus strains: COL and Newman. Transcriptome analyses with a full genome DNA array of S. aureus provided information on the role of SaeR as a global transcriptional regulator, whereas the proteomic approach allows the investigation of the influence of SaeRS on the amount of proteins within and outside the cells. Since the extracellular proteome of S. aureus represents a reservoir of virulence factors, we focused especially on this subproteome.

MATERIALS AND METHODS

Bacterial strains and culture conditions.

The bacterial strains used in the present study are listed in Table Table1.1. The mutated saeS gene of NCTC8325-4 saeS::Tn917 (29) was transduced into the wild-type strain COL by using phage 85 (5), resulting in an isogenic saeS mutant strain. The insertion event was confirmed by PCR using oligonucleotides specific for saeS and Tn917 (saeS and tn917) (Table (Table2).2). Bacterial cultures were inoculated with an overnight culture to an optical density at 540 nm (OD540) of 0.05 into tryptic soy broth (TSB), followed by incubation with agitation at 37°C. For all cultures, a flask-to-medium ratio of 5:1 was used. Bacterial growth was monitored by measuring the OD540.

TABLE 1.
Strains used in this study
TABLE 2.
Oligonucleotides used in this study

Preparation of protein extracts.

For the preparation of extracellular protein extracts, bacteria were grown in TSB. At different optical densities (OD540), the extracellular proteins from 100 ml of supernatant were precipitated, washed, dried, and resolved as described previously (60).

Cytoplasmic proteins were prepared from bacteria grown in TSB medium to different optical densities (OD540s of 1, 6, and 10). In each case, cells from 50 ml of culture were used to isolate cytoplasmic proteins as described by Kohler et al. (34).

The protein concentration was determined by using Roti-Nanoquant according to the manufacturer's instructions (Carl Roth GmbH & Co., Karlsruhe, Germany).

Analytic and preparative 2D-PAGE.

Preparative two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) was performed by using the immobilized pH gradient (IPG) technique described by Bernhardt et al. (6). The protein samples were separated on 2D gels using linear IPG strips (GE-Healthcare, Little Chalfont, United Kingdom) in the pH range of 3 to 10. The resulting protein spots were stained with silver nitrate or with colloidal Coomassie brilliant blue G-250 (8, 10). For protein identification by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS), 350-μg portions of protein extracts were separated on 2D gels, and the proteins were stained with colloidal Coomassie brilliant blue (10). Coomassie blue-stained protein spots were cut from gels by using the spot cutter Proteome Work (GE-Healthcare) with a picker head of 2 mm and transferred into 96-well microtiter plates. Digestion with trypsin and subsequent spotting of the peptide solutions onto the MALDI targets were performed automatically in the Ettan Spot Handling Workstation (GE-Healthcare) using a protocol described by Eymann et al. (18). MALDI-TOF-MS analyses of spotted peptide solutions were carried out on a Proteome-Analyzer 4700 (Applied Biosystems, Foster City, CA). The spectra were recorded in reflector mode in a mass range from 900 to 3,700 Da with a focus mass of 2,000 Da. For one main spectrum, 25 subspectra with 100 spots per subspectrum were accumulated by using a random search pattern. Automatic or manual calibration was performed as described by Eymann et al. (18). After calibration, the peak lists were created by using the “peak-to-mascot” script of the 4700 Explorer software. The resulting peak lists were analyzed by using the mascot search engine (Matrix Science, London, United Kingdom) and the genome sequence of S. aureus COL (22) and Mu50 (36).

Quantitation of protein spots.

For quantitation of extracellular proteins, the Ettan-fluorescence difference gel electrophoresis (DIGE) technique was used (GE-Healthcare). Protein extracts were labeled with CyDye DIGE Cy2, Cy3, or Cy5 (GE-Healthcare) prior to separation on 2D gels as described by Ziebandt et al. (60). Cy2-, Cy3-, and Cy5-labeled proteins were detected by using a Typhoon laser scanner 9400 (GE-Healthcare). The unfixed gels were scanned according to the Ettan DIGE user manual (GE-Healthcare) with 254-dpi resolution. The resulting images were compared, and spots were quantified by using Delta2D Software from Decodon GmbH (Greifswald, Germany). Only volume ratios of ≥2 or ≤0.5 and a probability value α of ≤5% were defined as significant changes between the different strains.

Transcriptional analyses.

Total RNA from S. aureus was isolated by using the acid-phenol method (21). Digoxigenin-labeled RNA probes were prepared by in vitro transcription with T7 RNA polymerase by using the Dig-RNA labeling mixture (Roche, Indianapolis, IN) and appropriate PCR fragments as templates. The PCR fragments were generated by using chromosomal DNA of S. aureus COL isolated with the chromosomal DNA isolation kit (Promega, Madison, WI) according to the manufacturer's recommendations and the respective oligonucleotides (Table (Table2).2). Reverse primers contain the T7 RNA polymerase recognition sequence at the 5′ end (33). Northern blot analyses were carried out as previously described (57). Before hybridization, each RNA blot was stained with methylene blue in order to check RNA loading and blotting. Only blots showing equal amounts of 23S rRNA and 16S rRNA for each sample loaded onto the respective gel were used for hybridization experiments. The digoxigenin-labeled RNA marker I (Roche) was used to calculate the sizes of the transcripts. The hybridization signals were detected by using a Lumi-Imager (Roche) and analyzed by using the software package LumiAnalyst (Roche).

For DNA microarray analyses, sciTRACER S. aureus N315 full genome microarrays (Scienion, Berlin, Germany) containing PCR products corresponding to 2,334 genes derived from the genome sequence of S. aureus N315 were used. The integrity of RNA was ensured by gel electrophoresis and by analysis with the Agilent 2100 Bioanalyzer (Agilent Technologies, Waldbronn, Germany). Fluorescent probes were prepared by reverse transcription of 10 μg of total RNA from S. aureus COL, S. aureus Newman, and their isogenic saeS mutants. Synthesis, purification, and hybridization of fluorescence-labeled cDNAs, as well as the washing of slides, were carried out as recommended by the manufacturer (Scienion). Each slide was hybridized competitively with cDNAs of the wild type and its isogenic saeS mutant labeled with Cy3 and Cy5, respectively.

Slides were scanned by using a ScanArray scanner (PE Biosystems, Weiterstadt, Germany), and the obtained images were quantified with ScanArrayExpress software (version 3.0; PE Biosystems) using “adaptive threshold” as the quantitation method. All subsequent calculations were performed using R2.2.1 (44) and Limma 2.4.7 (52, 53). Prior to all further analysis steps, the reproducibility of the data was determined as follows. The raw spot intensities from the two identical adjacent probes (designated by 1 and 2 in the following formulae) were compared by calculating the log2(G1/G2) in the green channel and log2(R1/R2) in the red channel, respectively. Furthermore, the reproducibility of the ratio between the red and green channel intensities of the spot pairs was compared by calculating the log2[(R1/G1)/(R2/G2)]. For spot pairs with a good reproducibility, all of these values tend toward 0. From the lists of the red, green, and red-green reproducibility scores, respectively, all extremes were removed arraywise by iterative calculation and removal of the outliers according to Chauvenet's criterion (11) until no further outliers could be detected. The methods implemented in limma allow for weighting the impact of every datum on the calculations for normalization and linear modeling by assigning every spot intensity a spotweight. Spotweights for calculations with limma functions were attributed by giving weights 0 to all spots that were determined to be outliers with respect to at least one of the reproducibility criteria. Furthermore, all control spots were assigned weight 0 for the subsequent calculations. Moreover, all signals corresponding to genes not encoded in the S. aureus COL genome as revealed by a nucleotide/nucleotide BLAST (E-value cutoff of 10e-50) with the S. aureus N315 open reading frames against the COL genomic sequence were omitted from the COL/COLΔsae data set by assigning a spotweight of 0. The most stringent upper and lower limits of all single arrays were used as the overall spot reproducibility threshold for the whole data set. All spots failing these defined limits were given a spotweight of 0.1. The remaining spots meeting all three reproducibility criteria were assigned a spotweight of 1. The overall spot reproducibility measures are shown in Table S1 in the supplemental material. Table S2 in the supplemental material displays the percentage of spots meeting the different criteria (not included in this percentages are empty and control spots). Before a linear model was calculated, the data were normalized within arrays by using the Loess function (13) and subsequently normalized between arrays using the method Aquantile (55). Simultaneously with within-array normalization, the background correction as proposed by Edwards (17) and implemented in limma (55) was performed. A linear model was calculated from the normalized data according to the guidelines of the limma users guide (17 December 2005 version). The linear model fitted with the limma functions accounts for dye effects and considers the duplicate spots as technical replicates (54). All spots with a P value of <0.05 and induced or repressed at least 2.5-fold were considered to be significantly regulated.

RESULTS

Differential transcription of the sae-operon during growth in TSB medium in S. aureus COL and S. aureus Newman.

Northern blot experiments using an saeR-specific RNA probe revealed three transcripts of about 3.0, 2.4, and 2.0 kb. As already published by Steinhuber et al. (56), saeR and saeS are cotranscribed with orf3 and orf4 upstream of saeR (Fig. (Fig.1).1). Whereas the 3.0-kb transcript comprises all four open reading frames, the 2.4- and 2.0-kb transcripts are initiated from internal promoters in front of orf3 and saeR, respectively (56). All three transcripts were differentially expressed during growth. In S. aureus COL, sae transcription was almost nondetectable at low optical densities but strongly increased at an OD540 of 4 (Fig. (Fig.1).1). In contrast, in exponentially growing cells of S. aureus Newman, the transcriptional level of sae was significantly higher than in S. aureus COL. Only a very slight increase of sae transcription at high optical densities could be observed in strain Newman. Very similar observations were done by other groups comparing the expression of sae in S. aureus Newman with that of either SH1000 or 8325-4 (30). Therefore, both S. aureus Newman and S. aureus COL were used to study SaeRS-dependent gene expression in S. aureus. In both strains the 2.4-kb transcript starting in front of orf3 was the most abundant transcript (Fig. (Fig.1).1). When RNA of the saeS mutant strains was used, no saeR-specific RNA could be detected (data not shown; see also reference 56). These results strongly imply the loss of both the sensor kinase SaeS and the response regulator SaeR in the saeS mutant strains used in the present study.

FIG. 1.
Transcriptional analysis of the sae operon. (A) Northern blot analysis of the sae operon. RNA was isolated from S. aureus COL and S. aureus Newman grown in TSB medium at 37°C. The membrane was hybridized with digoxigenin-labeled RNA probes specific ...

Extracellular proteome of S. aureus COL and S. aureus Newman.

The differences between the extracellular protein patterns of strain COL and strain Newman were striking (Fig. (Fig.2).2). In all, 42 proteins were identified from S. aureus COL and 47 were identified from S. aureus Newman (Table (Table3).3). The proteins of both strains were assigned to the open reading frame numbers defined in the S. aureus COL genome sequencing project (22) or in the Mu50 and N315 genome sequencing project (36). Superantigen proteins were named according to the nomenclature suggested by Lina et al. (38). At least 49 of the identified proteins both in COL and Newman showed signal sequences typical for Sec-translocated proteins (Table (Table3).3). The remaining proteins were of cytoplasmic origin. The presence of these proteins in the supernatant might be due to cell lysis.

FIG. 2.
Comparison of the extracellular protein pattern of S. aureus COL with the extracellular protein pattern of S. aureus Newman. False-colored dual-channel image of 2D gels of extracellular proteins of S. aureus COL (red) and S. aureus Newman (green). Proteins ...
TABLE 3.
Extracellular proteins identified from 2D gels of S. aureus COL and S. aureus Newman

A comparison of the list of potentially Sec-translocated proteins identified in S. aureus COL with those identified in S. aureus Newman showed an overlap of 21 proteins (Table (Table3).3). Among these are the metalloprotease Aur, the cysteine proteases SspA and SspB, and the serine protease SplA. Furthermore, we found the gamma-hemolysin components HlgA, HlgB, HlgC, LukF, LukE, and LukM; the alpha-hemolysin HlY; the lipases Lip, GlpQ, and Plc; the thermonuclease Nuc; and proteins such as Aly, IsaA, Sbi, and SsaA. Although all of these proteins were detectable in both strains, some of them differed significantly in amount. For instance, Nuc, Sbi, LukF, LukE, LukM, HlgB, HlgC, and HlgA were present at a higher level in strain Newman, whereas the amounts of SspA, Aur, and SplABCF were increased in strain COL.

Twelve Sec-translocated proteins were unique for S. aureus COL, and 16 were only detectable in S. aureus Newman (Table (Table33 and Fig. Fig.2).2). There are two possible explanations for this: (i) the proteins are not encoded in the genome of S. aureus COL or Newman, respectively, or (ii) the proteins are synthesized in very low amounts and thus remained below the detection limit. For S. aureus COL, it was possible to discriminate between these two possibilities, since the genome sequence is available. Surprisingly, only the genes for SEA and Ssl7 were missing in S. aureus COL. The reason for the absence of a particular protein in the S. aureus Newman strain is not as easily determined because its genome has not been sequenced. However, by using the PCR technique we could demonstrate the presence of the gene coding for Hlb in S. aureus Newman. The absence of Hlb on 2D gels of S. aureus Newman might be due to the presence of an hlb-converting bacteriophage. This notion is supported by the observation that the phage-encoded SEA was detectable in strain Newman (Table (Table3)3) (14). Genes coding for SEB, SEI (also SElQ), SEK, and Ear could not be detected in strain Newman (data not shown). Since all of these genes are localized on pathogenicity island vSa1, this genetic element might be absent in strain Newman. Finally, Pls was found only in S. aureus COL. The protein is known to be encoded on mec cassette type I (32), which is missing in strain Newman.

Influence of a mutation in saeS on the amount of extracellular proteins in S. aureus COL and S. aureus Newman.

The differential proteome display can also be used to visualize the entire set of extracellular proteins in the wild type in comparison with a regulatory mutant. In order to quantify changes in the level of extracellular proteins, we used the Ettan-fluorescence DIGE technique (GE-Healthcare). To investigate the influence of a mutation in saeS on the extracellular proteome of S. aureus COL, the extracellular protein pattern at OD540s of 6 and 10 of the respective wild-type strain was compared to those of the isogenic saeS mutant (Fig. (Fig.3A).3A). Eight proteins were found in higher amounts in the wild-type strain than in the saeS mutant (Fig. (Fig.3A3A and Table Table4),4), among them the hemolysins Hlb and HlY, the thermonuclease Nuc, the leucocidin component LukF, the enterotoxin SEB, and the serine proteases SplA and SplC, which are described to play a role as virulence factors. Furthermore, the amount of the pathogenicity island protein Ear was also positively influenced by SaeRS. Enterotoxin B, alpha-hemolysin, and beta-hemolysin are among the most abundant proteins.

FIG.3.FIG.3.
Extracellular proteome of S. aureus COL and Newman in comparison to the extracellular proteome of their isogenic saeS mutants. False-colored dual-channel images of 2D gels illustrate the differences in the protein pattern of the wild type (red) and the ...
TABLE 4.
Genes the expression of which is influenced by SaeRS in S. aureus COL and S. aureus Newman

Because of the aforementioned high level of sae-specific mRNA in S. aureus Newman, the influence of the two-component system on the expression of extracellular proteins was also analyzed in this strain. Here we could show that the amount of at least 15 proteins was decreased by a mutation in saeS (Fig. (Fig.3B3B and Table Table4).4). Five of these proteins (HlY, LukF, SplA, SplC, and Nuc) were positively influenced by SaeRS also in S. aureus COL. The other 10 SaeRS dependently expressed proteins (Coa, SACOL0479, SACOL0859, Sbi, HlgA, HlgB, HlgC, LukM, Ssl11, and Ssl7) could be identified to be influenced by SaeRS only in strain Newman. Three proteins (Hlb, SEB, and Ear) were influenced by SaeRS in strain COL but not encoded in strain Newman (Table (Table44).

Besides the positive effect of SaeRS on the amount of extracellular proteins, the amount of five proteins (Aur, SspA, GlpQ, Plc, and SsaA) was negatively influenced by this regulatory system: Aur and SspA were influenced by SaeRS in strain Newman, whereas the levels of GlpQ, Plc, and SsaA were influenced only in strain COL.

To confirm that saeS mutation was responsible for changes in the extracellular protein pattern of S. aureus, we inserted the wild-type sae operon into the geh locus of the saeS mutant of strain Newman. In this way the extracellular protein pattern could be restored to the wild-type phenotype, suggesting that the observed changes in extracellular protein expression can be attributed to the mutation in saeS (data not shown).

Finally, we compared the cytoplasmic proteome of the wild-type strains COL and Newman with those of their isogenic saeS mutants grown in TSB medium to an OD540 of 1, 6, or 10. There was no significant influence of SaeRS on this subproteome (data not shown). This identifies SaeRS as an important regulatory system for classical virulence factors, which directly interacts with the host.

Genomewide expression profiling of SaeRS-dependent genes using DNA microarrays.

For a global view on the role of SaeRS in gene regulation/expression, DNA microarray studies were carried out. Since the proteomic approach seemed to show that SaeRS affects the amounts of both early and late virulence factors, transcriptional analyses were performed at OD540s of 1 and 6. In S. aureus COL, the transcription of 12 genes was positively influenced by SaeRS (Table (Table4).4). Among these were six genes encoding extracellular proteins and five genes encoding cytoplasmic proteins. The transcription of one gene belonging to the sae operon itself that probably codes for a lipoprotein seems to be also affected by SaeRS. Whether the transcription of the sae operon is influenced by SaeRS itself or the loss of the sae transcript is only due to the mutation event is not entirely clear. Three of six of the extracellular proteins were detected in the supernatant of S. aureus COL, and the abundance of two of them (HlY and Hlb) was affected by SaeRS. Interestingly, we observed no differences in the transcription of the serine protease genes splA and splC and of nuc between the S. aureus COL wild type and its saeS mutant, although there was a strong negative influence at the protein level (Table (Table44 and Fig. Fig.3).3). SEB, Ssl11, SACOL0479, and the pathogenicity island protein Ear were also strongly induced at the protein level in the saeS mutant (Fig. (Fig.33 and Table Table4).4). Since these genes were not included in the microarray, no transcriptional data are available. Surprisingly, no genes were found whose transcription was upregulated in the saeS mutant. Obviously, SaeRS does not inhibit gene transcription in S. aureus COL.

In strain Newman, the transcriptional level of 29 genes was reduced in the saeS mutant (Table (Table4).4). Thirteen genes probably code for extracellular proteins, four code for membrane proteins, three code for cell wall associated proteins, one codes for a lipoprotein, and eight code for cytoplasmic proteins. Among the 13 genes encoding extracellular proteins, 5 were also shown to be affected by SaeRS at the protein level (Ssl11, SACOL0859, Nuc, Sbi, and HlgC). The remaining eight gene products have not been identified in the supernatant of S. aureus Newman to date. In contrast to S. aureus COL, the transcription of four genes was inhibited by SaeRS in strain Newman. However, none of these codes for a protein whose expression was negatively influenced by SaeRS at the protein level.

Eight genes were identified whose transcription was positively influenced by SaeRS both in strain COL and Newman: sbi, efb, hlb, the SACOL1169 and SACOL0480 genes, sae orf4, saeR, and saeS. The transcription of four genes (the SACOL0773, SACOL0776, and SACOL0777 genes and hly) was positively influenced by SaeRS only in COL, and the transcription of 21 genes (the SA0076, SA1784, SA1801, SACOL1849, SACOL1952, and SA1755 genes; geh; the SACOL0859 gene; hlgC; coa; empb; ent; fnbA; fnbB; map; nuc; the SACOL0199, SACOL0769, and SACOL1167 genes; and lrgA) was exclusively affected by the two-component regulatory system in strain Newman (Table (Table4).4). Only four of these are missing from the S. aureus COL genome sequence (the SA0076, SA1784, SA1801, and SA1755 genes).

As expected, during the exponential growth phase, differences in gene transcription between the wild-type strain and the saeS mutant were observed almost exclusively in strain Newman (Table (Table4),4), which shows high levels of sae message at low optical densities. In strain COL, differences became apparent only at higher cell densities. This finding also correlates with transcription of the sae operon (Fig. (Fig.11).

In contrast to published results (27, 42, 56), we did not find any influence of SaeRS on the transcription of the cap operon and the spa gene encoding protein A either in strain COL or in strain Newman.

Detailed transcriptional analyses of SaeRS-dependent genes.

To validate the SaeRS dependency of the expression of genes identified in our DNA microarray experiments, we performed Northern blot investigations (Fig. (Fig.4).4). Based on the data obtained by the 2D gel and DNA microarray analyses, the proteins of the SaeRS regulon can be divided into two gene groups: (i) genes whose expression are influenced at the transcriptional level, and (ii) genes whose expression might be influenced at the posttranscriptional level. We selected genes from both groups for Northern blot analyses and investigated 29 open reading frames in detail. These transcriptional analyses confirmed the findings in our microarray experiments in most cases. In addition, the analyses revealed the SaeRS dependence of eight genes (hly, hlgB, hlgC, lukM, lukF, nuc, the SA0859 gene, and map), whereas the microarray data did not show significant differences between the wild type and the saeS mutant. A common theme of these genes is a relatively low transcription level that might account for the failure to be detected as significantly influenced by SaeRS in the array approach.

FIG.4.FIG.4.FIG.4.
Northern blot analyses of SaeRS-dependent genes. RNA was isolated from S. aureus COL and S. aureus Newman and their respective saeS mutants (Δ) grown in TSB medium at 37°C (OD540 = 1 [lanes 1] and OD540 = 6 [lanes 6]). ...

Moreover, the transcription of four genes (seb, ssl11, the SACOL0479 gene, and ear) that were not present on the microarray was also analyzed by Northern blot experiments. The obtained data revealed that their transcription was positively influenced by SaeRS (Fig. (Fig.44).

Taken together, our data show that SaeRS seems to activate transcription of the respective genes rather than to inhibit transcription. The negative effect of SaeRS on the amount of Aur, GlpQ, Plc, SsaA, and SspA probably occurs at the posttranscriptional level, since the transcription of the corresponding genes was not influenced by the mutation in saeS during growth in TSB medium (shown for OD540s of 1 and 6 in Fig. Fig.44).

Influence of SaeRS on the transcription of regulatory genes involved in virulence gene expression.

Most of the genes whose expression appears to be influenced by SaeRS are also affected by agr, SarA, and σB (7, 15, 60, 61). To determine whether the observed effects of the mutation in saeS on the expression of these genes might be mediated by these regulators, the potential influence of SaeRS on the transcription of sigB, sarA, the agrA and RNAIII genes, and arlRS was investigated by Northern blotting. Similar to sae transcription, differences in the growth phase dependence of the transcription of sigB, the agrA and RNAIII genes, and sarA between both wild-type strains could be observed. Whereas in S. aureus Newman the transcript levels of all of these genes were largely constant, their transcription in S. aureus COL was strongly dependent on the growth phase. Here the transcription of the agrA and RNAIII genes was upregulated at higher optical densities (OD540 of 6), whereas the transcripts of sigB, arlRS, and sarA disappeared simultaneously. Importantly, SaeRS did not influence the regulation of these genes (Fig. (Fig.55).

FIG. 5.
Transcriptional analysis of virulence-associated regulatory genes. RNA was isolated from S. aureus COL and S. aureus Newman and their respective saeS mutants (Δ) grown in TSB medium at 37°C (OD540 = 1 [lanes 1] and OD540 = ...

DISCUSSION

In addition to host factors (e.g., the immune response of healthy or immunocompromised individuals), the pronounced diversity of the species S. aureus in its equipment with virulence factors might be responsible for the wide variety of clinical symptoms that are characteristic for infections with this microorganism. Most genes encoding virulence factors are located on highly variable regions of the staphylococcal genome, such as pathogenicity islands, lysogenic bacteriophages, or even on plasmids (2, 39, 40). Interestingly, some virulence-associated genes, such as spa, aur, hla, lip, clfAB, map/eap, fnbA, and coa, also belong to the core genome (31, 43). The expression of virulence factors in S. aureus is regulated by a very complex network of regulators such as DNA-binding proteins, two-component systems, and the alternative sigma factor σB. However, the contribution of each regulator on virulence gene expression, their regulatory mechanisms, and their mutual interference within this regulatory network are not well understood. To elucidate the role of the two-component system SaeRS in S. aureus virulence gene expression, we combined proteomic and transcriptomic approaches. Both techniques are excellent tools to reveal whether individual virulence genes (i) are expressed at all and, if so, (ii) in what quantities and (iii) under which environmental conditions. The study was initiated in strain COL, where the genome sequence became available in 2005 (22). S. aureus Newman was later included in the present study because this strain is characterized by an unusually high level of sae-specific mRNA.

Extracellular proteins constitute a reservoir of virulence factors and have important roles in the pathogenicity of bacteria. Therefore, besides the elucidation of virulence factor regulation, the comprehensive analysis of the extracellular proteome of S. aureus may lead to the discovery of new virulence factors. In our study, the amount of eight extracellular proteins in S. aureus COL and 15 in S. aureus Newman was influenced by the two-component system SaeRS. Among these were known SaeRS-dependent proteins such as Nuc, HlY, Hlb, Eap (Map), and Emp (Empbp) (27-30, 42), which confirms the validity of our experimental approach. In addition, 13 new extracellular proteins which likely are under SaeRS control could be identified. Interestingly, most of the proteins whose amount was influenced by SaeRS play a role in immune evasion (for a review, see reference 19). These are Map, Eap, Efb, HlgA, HlgB, HlgC, LukF, LukM, Ent, SEB, Sbi, and Aur. Others are especially involved in adhesion to host cells (FnbA and FnbB), or they can damage host cell membranes (Hlb and HlY). We also discovered proteins of unknown function in the SaeRS regulon. These are SACOL0479, SACOL0480, SACOL0859, and SACOL1169. Their presence in virulence-associated regulons makes it very likely that they play a role in the interaction of S. aureus with its host, probably in immune evasion or adhesion. Interestingly, SACOL1169 shows similarity to fibrinogen-binding proteins. The elucidation of the precise function of the putative virulence factors will be a challenging task for the future. The amounts of four virulence factors were similarly influenced by SaeRS in strain COL and in strain Newman. Interestingly, in strain Newman, more extracellular proteins were positively influenced by the two-component system, in particular proteins expressed at the early phase of growth.

To distinguish between the effects of SaeRS at the transcriptional level and those due to changes at the protein level, we complemented our proteome data with transcriptome analyses using a full genome DNA microarray corresponding to the genome sequence of S. aureus N315. In this way we could clearly show that the positive control of genes by SaeRS occurred at the transcriptional level. In contrast, the expression of genes coding for proteins, the amount of which was negatively influenced by SaeRS (SsaA, Plc, SspA, and GlpQ) was not affected by the two-component system at the mRNA level. Although the aforementioned proteins were identified in both strains, the proteases Aur and SspA accumulated only in the saeS mutant of strain Newman, whereas the lipases GlpQ and Plc, as well as SsaA, accumulated solely in the saeS mutant of strain COL.

The transcriptomic approach further allowed the investigation of the transcriptional regulation of genes encoding surface-associated and membrane proteins that escape proteome analyses focusing on extracellular and cytoplasmic proteins. S. aureus Newman produces significant amounts of surface-associated proteins leading to exceptionally strong adhesion of this strain to host cells and extracellular matrix (59). Interestingly, the expression of genes encoding Coa, FnbB, and FnbA was shown to be positively influenced by SaeRS at low optical densities. The same phenomenon was observed for the SACOL0199, SACOL0769, and SACOL1167 genes and lrgA, which code for proteins with membrane-spanning domains. At high optical densities, however, the transcription of all of these genes was repressed despite the presence of SaeRS. In contrast to the positive effect of SaeRS, the agr quorum-sensing system inhibits the expression of coa, fnbB, and fnbA, indicating that RNAIII might act as an antagonist of SaeRS (24, 48, 58, 59).

In contrast to the genes encoding FnbA, FnbB, and Coa, most other genes of the SaeRS regulon, however, are positively coregulated both by RNAIII and by SaeRS (9, 15, 24, 26, 30, 46, 51, 60). RNAIII appears to synergize with the positive effect of SaeRS on gene expression at higher optical densities either directly or indirectly by enhancing SaeR activity (25, 28, 42). Furthermore, the expression of most SaeRS-dependent genes appears to be positively affected by SarA and negatively by the alternative sigma factor σB (7, 9, 12, 15, 28-30, 46, 49, 60, 61). For nine SaeRS-dependent genes (ear; efb; ent; the SACOL0479, SACOL0480, SACOL0859, and SACOL1169 genes; ssl11; and ssl7) identified in the present study, an influence of agr, SarA, σB, ArlSR, or Rot on their transcription has not yet been observed (7, 15, 37, 47). However, the published data were obtained with other S. aureus strains and under very different conditions. Nevertheless, the effect of SaeRS seems to be restricted to virulence gene regulation, which is only a subset of the many genes described to be regulated by the other regulators such as agr or SarA.

The present study provides clear evidence that although some virulence-associated genes are present in strain COL and in strain Newman the expression of these genes varied between these strains. Whereas some of these virulence factors were synthesized in different amounts, other virulence factors are not expressed at all in one of the two strains (Fig. (Fig.2).2). There are two possible explanations for this: (i) the activity of virulence-associated regulators differs between the strains and/or (ii) there are differences between the regulatory regions of the respective genes. The comparison of the two S. aureus strains revealed a correlation between the transcription of regulatory genes and the expression of virulence-associated genes. We observed differences in the amount of transcripts of regulatory genes such as agr, sarA, sigB, and saeRS between COL and Newman. However, the differences in the transcriptional regulation were most at the sae and the agr loci. Very similar observations for the sae operon were reported by other groups (30, 56) that observed reduced sae transcription in derivatives of 8325 compared to strain Newman. Moreover, the fact that S. aureus Newman shows an extraordinary behavior in regulation of gene expression is also supported by the finding that mutations in sarA and agrA did not affect biofilm formation, as observed for many other strains (3). Analysis of the SaeRS regulon structure in strain COL and strain Newman grown under nearly identical conditions reveals remarkable differences. Consequently, for a thorough understanding of the complex interaction of S. aureus regulators and their function in the virulence of S. aureus, the global role of these regulators in gene expression must be analyzed systematically in various strains with different clinical behaviors and under strictly defined conditions. However, the present study is limited since the genome sequence of S. aureus Newman has not been available to date. Therefore, for a more comprehensive analysis of differences in global virulence gene expression in various S. aureus strains, only sequenced strains should be used in order to determine whether the respective genes are present and whether there are sequence variations particularly in the regulatory regions of these genes or within regulatory genes.

The genomewide expression profiling of SaeRS-dependent genes revealed that the regulator SaeR might act as an activator of transcription. SaeR is a typical response regulator that is expected to be activated by phosphorylation and then able to bind to a specific region of the DNA in front of its target genes. Clearly, SaeRS is involved in the tight control of the temporally coordinated expression of virulence factors in S. aureus. However, its role within the regulatory network is not yet entirely clear. SaeRS did not affect the transcription of other regulatory genes, suggesting that SaeR might be an essential downstream effector molecule within the regulatory network. Whether SaeR directly regulates its target genes remains to be determined. A comparison of the upstream sequences of all SaeRS-dependent genes, however, did not reveal a consensus sequence that might serve as a binding site of SaeR. Gel shift experiments are currently under way to determine whether SaeR directly binds to the promoter region of the SaeRS-dependent genes.

In conclusion, we have identified SaeRS as an important regulatory system of staphylococcal virulence gene expression. Many SaeRS-dependent genes are also regulated by agr, SarA, and/or σB. According to the function of SaeRS-dependent genes, the two-component system might be crucial for the complex interactions of S. aureus with the eukaryotic immune system via expression of proteins involved in adhesion and immune evasion. The signals that are responsible for the activation of SaeRS under in vivo conditions remain to be elucidated.

Supplementary Material

[Supplemental material]

Acknowledgments

We thank Silva Holtfreter for helpful discussion on SAg nomenclature and Birgit Voigt, Haike Henkel, and Dirk Albrecht for support in protein digestion and identification. We are grateful to Thomas Meier and Anita Harang for excellent technical assistance. We also thank Decodon GmbH (Greifswald, Germany) for providing Delta2D software.

This study was supported by grants of the BMBF (031U107A/-207A, 031U213B), the DFG (GK212/3-00, WO578/5-1), the Land MV, and the Fonds der Chemischen Industrie to M.H., C.W., and S.E.

Footnotes

Supplemental material for this article may be found at http://jb.asm.org/.

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