BIOMERIT Research Centre, Department of Microbiology, University College Cork, Cork, Ireland
Received 25 March 2006/ Returned for modification 30 May 2006/ Accepted 12 July 2006
| ABSTRACT |
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| INTRODUCTION |
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F508, and it has also been shown that CFTR can serve as a receptor for P. aeruginosa (46). The P. aeruginosa genome consists of 6.3 million bp, 8% of which are predicted to be involved in gene regulation (56). Such a substantial proportion of regulation-associated genes is thought to have important consequences for the tightly controlled production of a diverse set of virulence factors (reviewed in reference 52). Strict control over the selected production of appropriate virulence determinants is essential to allow the organism to effectively colonize the host during different stages of infection. Regulation of gene expression in P. aeruginosa is accomplished by a number of signal transduction systems, including the two-component system GacS/GacA (16, 49) and two recently described hybrid sensor kinases, RetS and LadS (11, 60). These environmental sensors have been shown to coordinate gene expression by modulating the expression of the untranslated RNA RsmZ, which subsequently alleviates the effects of the small RNA-binding protein RsmA (2, 11, 18, 45, 60).
In P. aeruginosa, posttranscriptional regulation of a number of genes involved in virulence is mediated by RsmA. RsmA negatively affects the production of hydrogen cyanide, extracellular enzymes, and the quorum-sensing molecules C4- and 3-oxo-C12-homoserine lactone, PvdS synthesis, and antibiotic resistance (2, 18, 41, 45). However, RsmA exerts a positive regulatory effect on motility, rhamnolipid synthesis, vfr transcription, and Pseudomonas quinolone signal biosynthesis in P. aeruginosa (2, 18, 41).
Recent work in this laboratory has shown that RsmA played an important role in the interaction between P. aeruginosa and human airway epithelial cells in a cell culture model (41). An rsmA mutant failed to cause actin depolymerization and cytotoxicity in epithelial cells but displayed significantly increased invasion into epithelial cells (41). Subsequently, the rsmA mutant was demonstrated to have decreased transcription of several regulators of the type III secretion system (TTSS) and failed to secrete proteins essential for a functional TTSS (41).
The TTSS is used by a number of different animal and plant pathogens to produce and deliver bacterial effector proteins directly into the cytoplasm of eukaryotic cells (reviewed in reference 21). P. aeruginosa is known to secrete four effector proteins termed exoenzymes (Exo). The prevalence of genes encoding ExoS, ExoT, ExoU, and ExoY in isolates of P. aeruginosa has been investigated by a number of groups, and it has generally been shown that the presence of exoS and that of exoU are mutually exclusive in the same strain (5, 51). The reason for this is unclear, although P. aeruginosa PA14, which lacks a gene encoding ExoS, was recently shown to encode ExoU on a pathogenicity island (15).
ExoS and ExoT are related proteins which have N-terminal GTPase-activating protein (GAP) activity and C-terminal ADP-ribosyltransferase (ADPRT) activity (9, 10, 25, 30, 43). While the GAP activities of ExoS and ExoT act on the same set of host proteins, the ADPRT activity of ExoS inhibits intracellular signaling by acting on human Ras-related proteins (7, 17, 36, 61) and is distinct from that of ExoT, which acts on host proteins such as Crk-I and Crk-II (57). ExoU exerts phospholipase activity (53) and is a potent cytotoxic factor for a number of cell types in vitro, including epithelial cells and macrophages (6, 14). ExoY, an adenylate cyclase, elevates the intracellular concentration of cyclic AMP by interacting with an unidentified eukaryotic factor (64). Recently, ExoY was shown to cause actin depolymerization of epithelial cells and to influence invasion (3).
Because P. aeruginosa RsmA influences a number of epithelial cell phenotypes associated with the TTSS (41), we sought to investigate the role of RsmA on the global transcriptional response of human airway epithelial cells to infection with P. aeruginosa. Using such an approach, it was hypothesized that the activation/repression of host processes elicited by bacterial components under the control of RsmA would be identified. Here we characterize the genome-wide response of epithelial cells to P. aeruginosa and show that the specific induction of two members of the Kruppel-like factor (KLF) family of transcription regulators is RsmA dependent. These human transcription factors play key roles in cellular proliferation, the response to tissue injury, the regulation of immune cells, and lung development (28, 29, 31, 32, 62, 63). Induction of these genes in response to PAO1, but not the rsmA mutant, led us to identify the specific bacterial components responsible for the induction of KLF2 and KLF6. Increased expression of KLF2 was dependent on bacterial expression of ExoS, while elevated expression of KLF6 required the production of both ExoS and ExoY. These data suggest an important role for RsmA-mediated regulation of specific effector proteins of the TTSS in activating host transcription factors during the infection of airway epithelial cells with P. aeruginosa.
| MATERIALS AND METHODS |
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F508 mutation of CFTR and were derived from human tracheobronchial epithelium (13). Cells were cultured on bovine serum albumin-collagen-fibronectin-coated plastic, using minimum essential medium supplemented with 10% fetal bovine serum (FBS), 2 mM L-glutamine, 100 units/ml penicillin, and 100 µg/ml streptomycin. Cells were incubated at 37°C in a humidified 5% CO2 atmosphere. All cell culture reagents were supplied by Sigma, unless stated otherwise.
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Epithelial cell infection studies using bacterially conditioned cell-free supernatant, heat-killed bacteria, or LPS. Epithelial cells and bacterial strains were cultured as described above. For the generation of bacterially conditioned cell-free supernatant (bacterial supernatant), bacterial cells (after 4 h of subculture) were pelleted by centrifugation (4,000 x g), and the supernatant was subsequently filter sterilized (0.02 µm). To prepare heat-killed bacteria, bacterial strains (after 4 h of subculture) were pelleted by centrifugation in a plastic container which was placed in boiling water for 30 min. In each case, preparations were confirmed to be free of viable bacteria by plating aliquots of the samples on LB agar. Preparations of bacterial supernatant or heat-killed bacteria were added to the cells to reflect an MOI of 50:1. Lipopolysaccharide (LPS; diluted in infection medium) from P. aeruginosa (serotype 10) or Escherichia coli (O26:B6) (both supplied by Sigma) was added to epithelial cells at a final concentration of 10 µg/ml. Epithelial cells were harvested as described above.
RNA isolation and array sample preparation. Total RNA was isolated from epithelial cells by using an RNeasy kit (QIAGEN) according to the manufacturer's instructions. Genomic DNA was removed by using DNA-free (Ambion), and the samples were confirmed by PCR to be free of DNA prior to cDNA synthesis. Biological samples from two independent infection experiments were used in two independent array experiments, as outlined below. Isolated RNAs were used in the preparation of fragmented cRNAs for array hybridization according to the manufacturer's protocol (Affymetrix). Briefly, 8.5 µg of RNA was converted to double-stranded cDNA by reverse transcription, using a Superscript cDNA synthesis kit (Invitrogen) and an oligo(dT) primer containing a T7 RNA polymerase site added 3' of the poly(T) (Affymetrix). After second-strand synthesis, cDNAs were converted to biotin-labeled cRNAs by in vitro transcription (Enzo). The labeled cRNAs were purified using a Genechip clean-up module (QIAGEN). Total cRNA quality and yield were measured using a GeneQuant spectrophotometer, and 20 µg of cRNA was fragmented at 94°C for 35 min in fragmentation buffer (40 mM Tris-acetate, pH 8.1, 100 mM potassium acetate, 30 mM magnesium acetate). Full-length and fragmented cRNA sample integrity was assessed by electrophoresis on a 1% agarose-Tris-borate-EDTA gel, with visualization by staining with SYBR green. Fragmented cRNAs were sent to Geneservice (Cambridge, United Kingdom) for assessment of RNA quality, using a Bioanalyzer (Agilent), before hybridization to a human genome U133A array (Affymetrix). The arrays were washed and stained in a fluidic station and then scanned according to the manufacturer's protocols (Affymetrix). For the six array samples, the 3'/5' ratio of the control probe sets did not reach a value of >3, indicating that sample preparation was not compromised in our study.
Microarray data analysis. Raw image analysis was performed using Microarray Suite v5.0 software (Affymetrix). Downstream data analysis was performed using GeneSight software, version 2.7 (Biodiscovery). For all analyses, the signal intensities from two independent infection and array experiments were used. To filter the array data, analysis of variance for comparison between multiple groups of samples (uninfected cells or PAO1- or rsmA mutant-infected cells) was used to investigate significant differences (P < 0.05) in gene expression between samples. Using the filtered data, a series of Student's t tests was employed to determine significant differences (P < 0.05) in gene expression between two particular samples.
For subsequent analysis, a 1.5-fold cutoff was applied between two samples to identify different levels of gene expression.
Investigation of biological processes with significant alterations postinfection. Expression Analysis Systematic Explorer (EASE; http://david.niaid.nih.gov/david/ease.htm) was used to facilitate the biological interpretation of lists of transcripts derived from the array analysis. The EASE score measures the statistical significance of changes in regulation of a biological process or molecular function by comparing the number of genes changed experimentally to the total number of genes spotted on the array that are annotated for that process, thus identifying categories of genes that are overrepresented under the experimental conditions. Categories with P values of <0.05 compared to uninfected control cells were considered significantly altered. Gene Ontology (http://www.geneontology.org) annotations were used to categorize the lists of biological processes.
Real-time reverse transcription-PCR analysis. RNAs were isolated and genomic DNA was removed as described above. Five hundred nanograms of total RNA was reverse transcribed using oligo(dT) and Expand reverse transcriptase (Roche) as recommended by the manufacturer. Contaminating bacterial cDNAs were not detected using species-specific primers. cDNA standards were prepared, and real-time reverse transcription-PCR analysis was carried out using a Light Cycler apparatus (Roche) as previously described (42). MgCl2 concentrations and thermocycling conditions were optimized for each primer set (available upon request), and melting curve analysis confirmed the specificity of the reaction, as described previously (48). Normalization of gene expression between samples was carried out using hypoxanthine phosphoribosyltransferase (HPRT) as a control (4), as its expression was not significantly altered, as determined by array analysis (data not shown).
Quantification of cell cytotoxicity by measuring LDH release. The release of lactate dehydrogenase (LDH) into culture supernatants was measured using an LDH cytotoxicity detection kit (Roche) according to the manufacturer's instructions. FBS was omitted from the infection medium, as the inclusion of FBS resulted in high background levels of LDH activity. Infection of epithelial cells was carried out as described above, using an MOI of 50:1, and allowed to proceed for the indicated times postinfection.
Microarray accession number. The entire array data set has been deposited in the Gene Expression Omnibus (GEO) database at NCBI (http://www.ncbi.nlm.nih.gov/geo/) under GEO accession number GSE4485.
| RESULTS |
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The identification of transcripts with significantly altered expression levels was performed by using a combination of statistical approaches, as described in Materials and Methods. Infection with PAO1 was responsible for 241 transcripts with increased expression levels and 112 transcripts with decreased expression levels compared to those in uninfected cells at 1.5 h postinfection (see Table S1 in the supplemental material). By comparison, infection with the rsmA mutant resulted in 151 and 123 transcripts with increased and decreased transcription levels, respectively, compared to those in uninfected cells (see Table S2 in the supplemental material).
In the current study, the rsmA mutant failed to significantly alter the expression of a number of transcripts which were significantly increased following infection with PAO1. A number of these PAO1-regulated transcripts were also identified by other investigators following infection of epithelial cells with P. aeruginosa. These included PAO1-induced expression of the phosphatases DUSP1 (37) and DUSP10 (23) and the Rho protein RHOB (37). McMorran et al. (37) showed that infection with P. aeruginosa PA103 caused induction of the transcriptional regulator NR4A1, while in the current study, PAO1 infection resulted in the detection of elevated expression levels of the related nuclear receptor NR4A2 (see Table S1 in the supplemental material). Additionally, PAO1 infection increased the expression of the transcriptional regulator Jun (see Table S1 in the supplemental material), as previously observed in three separate studies (22, 24, 50). In our study, infection with PAO1 increased the expression of two related transcriptional regulators, KLF2 and KLF6 (see Table S1 in the supplemental material). In supplementary material provided by Hybiske et al. (22), increased expression of KLF6, but not KLF2, was observed following infection of a CF nasal cell line with P. aeruginosa PAK.
To differentiate between the responses of epithelial cells to infections with PAO1 and the rsmA mutant, significantly altered transcripts (relative to those in uninfected control cells) were grouped so as to distinguish those that were similarly (see Table S3 in the supplemental material), differentially (see Table S4 in the supplemental material), and reciprocally (see Table S5 in the supplemental material) regulated by PAO1 and the rsmA mutant (Fig. 1). Fourteen percent of the total number of significantly altered transcripts were regulated in a similar manner by PAO1 and the rsmA mutant compared to those in uninfected cells (71 and 18 transcripts with increased and decreased transcription levels, respectively) (Fig. 1; see Table S3 in the supplemental material). Those with increased transcription levels included two members of the solute carrier family (SLC13A3 and SLC26A3). Infection with PAO1 and the rsmA mutant resulted in decreased expression of the cell surface receptor CD44, which is involved in the activation of cytotoxic T cells (38).
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Infection with PAO1 resulted in 144 and 83 transcripts with increased and decreased transcription levels, respectively, which were not significantly altered by infection with the rsmA mutant (Fig. 1; see Table S4 in the supplemental material). These transcripts included those for the transcription factors KLF2 and KLF6 (PAO1 induced), the immunity-related surface receptor HLA-DRB1 (PAO1 repressed), and the chemokine CCL19 (PAO1 repressed). In contrast, infection with the rsmA mutant resulted in 60 and 88 transcripts with increased and decreased transcription levels, respectively, which were not significantly altered by infection with PAO1 (Fig. 1; see Table S4 in the supplemental material). Included in this list were the genes for INFA8 (rsmA induced), which is known to be a target of the transcriptional regulator IRF5, and the cell adhesion molecules CCL11, ICAM2, ISLR, and LAMA1 (rsmA repressed).
The second group of differentially regulated transcripts, which were significantly altered by both strains but showed significant differences in the levels of expression between the two infected samples, was made up of 17 and 8 transcripts with increased and decreased transcription levels, respectively, compared to those in uninfected cells (Fig. 1; see Table S4 in the supplemental material). Included in this group were the genes for the signal transduction molecule MAP2K1, which was induced to a higher level as a result of infection with PAO1 than that in rsmA mutant-infected cells, and the cytokine interleukin-2, which showed a lower level of transcription as a result of infection with the rsmA mutant than that in PAO1-infected cells.
A small number of transcripts exhibited reciprocal regulation when cells were infected with PAO1 or the rsmA mutant (Fig. 1; see Table S5 in the supplemental material). Included in the list of nine transcripts shown to be PAO1 induced but rsmA repressed compared to those in uninfected cells were transcripts involved in the regulation of transcription (RORA, SMARCA2, and HOXA9). The three transcripts which were PAO1 repressed but rsmA induced were those for DAPK1, KCNJ5, and SAMD4, all of which are involved in ion transport.
Infection with PAO1 or the rsmA mutant alters a distinct set of biological processes. EASE software (http://david.niaid.nih.gov/david/ease.htm) with Gene Ontology annotations (http://www.geneontology.org) was employed to investigate the biological processes (Table 2) that were significantly altered during infection of epithelial cells with PAO1 or the rsmA mutant. This statistical analysis revealed clear differences in the biological processes that were altered as a result of infections of epithelial cells with PAO1 and the rsmA mutant. PAO1, but not the rsmA mutant, caused significant alterations in biological processes such as cell growth, positive regulation of cell proliferation, and immune cell and lymphocyte activation. Furthermore, PAO1 infection resulted in significant changes in pathways related to transcription and the regulation of transcription at 1.5 h postinfection which were not changed after infection with the rsmA mutant (Table 2). Additionally, genes involved in immune and defense responses were overrepresented among the genes that were significantly altered postinfection with PAO1 but not with the rsmA mutant. In contrast, the rsmA mutant was responsible for the alteration of processes involving cell communication and the metabolism of lipids, aromatic amino acids, and amino acid derivatives (Table 2).
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PAO1 caused increased expression of Jun at 1.5, 3, and 6 h postinfection, with maximal induction of approximately 20-fold (compared to the case in uninfected cells) observed at 6 h postinfection. In contrast, the rsmA mutant failed to increase the expression level of Jun more than 3.3-fold at 6 h postinfection (Fig. 2). Increased expression (sixfold) of FGF18 was only observed at 6 h postinfection with PAO1, while the rsmA mutant failed to increase the expression of FGF18 compared to that in uninfected cells (Fig. 2). Increased expression of KLF2 was detected as early as 1.5 h postinfection with PAO1. Maximal induction of KLF2, to a level approximately 25-fold higher than that in uninfected cells, was observed at 3 h postinfection (Fig. 2). KLF6 expression levels also increased in response to PAO1, with the most induction (21-fold) observed at 6 h postinfection (Fig. 2). In contrast, the rsmA mutant failed to alter the expression of either of these transcription factors more than 2.4-fold compared to that in uninfected cells for up to 6 h postinfection (Fig. 2).
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Cell-associated or secreted factors are insufficient to alter the expression of KLF2 or KLF6. Gene expression analysis was conducted to identify if cell-associated or secreted factors were capable of increasing the expression of KLF2 or KLF6. Exposure of epithelial cells for 3 h to bacterially conditioned cell-free supernatant, heat-killed bacteria, or LPS from P. aeruginosa or E. coli was insufficient to alter the expression of either gene (Fig. 3). In the same assay, infection with PAO1, but not the rsmA mutant, resulted in increased expression of both genes compared to that in uninfected cells, as previously observed (Fig. 3). These data showed that gene expression of KLF2 and KLF6 was regulated in a more specific manner.
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| DISCUSSION |
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Microarray analysis demonstrated the significance of RsmA in modulating the host response to infection. RsmA influenced the expression of a large number of epithelial transcripts in a distinct manner. This was evident in the number of differentially regulated transcripts uniquely regulated by PAO1 or the rsmA mutant. The rsmA mutant failed to alter transcripts involved in controlling a number of biological processes relevant to microbial infection, including immune and defense responses and immune cell and lymphocyte activation. Mining of the array data also pointed to the importance of genes involved in the regulation of transcription at 1.5 h postinfection. Temporal expression analysis confirmed the array data, which showed increased expression of Jun, FGF18, KLF2, and KLF6 in response to PAO1 but not in response to the rsmA mutant. PAO1-induced expression of KLF2 and KLF6 was also observed in a non-CF tracheal epithelial cell line (our unpublished data). However, since this was not an isogenically derived cell line, we cannot conclude definitively regarding the significance of this result.
As members of the KLF transcription factor family, KLF2 and KLF6 play important roles in cell proliferation and the host response to tissue injury. KLF2 prevents apoptosis of T lymphocytes (32) and has been shown to be important for the development of blood vessels, as KLF2 knockout mice die at embryonic day 12 due to hemorrhage (31). KLF6 binding has been shown to alter the transcription of a number of genes with roles in cell proliferation, development, and tissue repair (28, 29, 63). Increased expression of KLF2 following infection of murine macrophages with Yersinia enterocolitica has been reported (1, 19, 54). Additionally, induction of both KLF2 and KLF6 has been documented following infection of tracheal epithelial cells with Staphylococcus aureus (40). While P. aeruginosa-mediated induction of KLF6 has previously been reported as supplementary data by Hybiske et al. (22), to our knowledge this is the first report indicating increased expression of KLF2 in response to P. aeruginosa infection and the first to identify the specific bacterial component(s) responsible for the induction of KLF2 and KLF6.
KLF2 and KLF6 expression was significantly induced in response to infection with PAO1, but not the rsmA mutant, indicating a role for downstream targets of RsmA in eliciting this specific host response. Subsequent investigations indicated that live bacterial infection was required for the induction of KLF2 and KLF6, as bacterially conditioned cell-free supernatant, heat-inactivated bacteria, or LPS was insufficient for the induction of KLF2 or KLF6. These data, in conjunction with our recent data showing the absence of a functional TTSS in the rsmA mutant (41), prompted us to investigate whether the type III effectors were possible modulators of KLF2 and KLF6 expression.
Elevated transcriptional expression of KLF2 was observed only in response to infections with strains capable of secreting ExoS. Since the ADPRT, but not GAP, activities of ExoS and ExoT differ in terms of substrate specificity, this suggests that the ADPRT activity of ExoS was responsible for the observed increase in gene expression of KLF2 during infection. It has also been shown that the ADPRT activity of ExoS, not that of ExoT, is required to induce cytotoxicity (44) and apoptosis (26, 27) in cultured mammalian cells. Recently, it was shown that the ADPRT activity of ExoS is essential for virulence in a mouse model of acute pneumonia (55). To clarify the specific roles of these domains, expression analysis of KLF2 in response to ExoS with a mutated GAP and/or ADPRT domain would be necessary. Induction of KLF6 was detected only in response to strains capable of secreting ExoS in combination with ExoY. This suggested that the specific ADPRT activity of ExoS, in combination with bacterial production of ExoY, was required for the induction of KLF6, although this has not yet been investigated. Synergistic effects between the type III effector proteins in eliciting a distinct host transcriptional response to P. aeruginosa infection were shown recently (23). However, the study by Ichikawa et al. did not highlight synergy, specifically that between ExoS and ExoY, in influencing the host response to infection, as seen with KLF6 in our study. While differential expression of KLF2 or KLF6 was not detected (23), this may be attributable to the use of different cell lines, P. aeruginosa strains, and infection conditions.
Epithelial cell death due to the presence of ExoS but not ExoU was associated with elevated gene expression of KLF2 and KLF6. Three clinical isolates of P. aeruginosa, including PA14, failed to increase the expression of either KLF2 or KLF6, and this was attributed to the lack of production of both ExoS and ExoY by these strains. However, we cannot rule out the possibility that these strains did not fail in their ability to increase the expression of these genes, but rather acted to suppress induction, a condition which may ultimately favor the bacterium. Whether the induction of KLF2 and KLF6 is a mechanism of host defense or serves to benefit the bacterium is not currently known. This issue is the subject of current investigations.
In this study, we have shown that regulation of the TTSS mediated by the posttranscriptional regulator RsmA has important effects on the host transcriptional response to P. aeruginosa infection. Significant alterations in the expression of genes involved in the regulation of transcription were observed early in the infection process. ExoS and ExoY were shown to specifically increase the expression of selected human transcription factors, and this increased gene expression was associated with ExoS-mediated cytotoxicity in epithelial cells. The host transcription factors KLF2 and KLF6 have important roles in the regulation of genes associated with cell proliferation, lung development, and tissue injury. Delineation of the molecular mechanisms by which ExoS and ExoY influence the expression of these genes may help to identify the importance of exoenzyme-mediated modulation of host gene expression during infection with P. aeruginosa.
| ACKNOWLEDGMENTS |
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This work was supported in part by grants awarded by the Higher Education Authority of Ireland (PRTLI programs to F.O.), The Science Foundation of Ireland (SFI 02/IN.1/B1261, 04/BR/B0597 to F.O.), the European Commission (QLK3-CT-2000-31759, QLTK3-CT-2001-0010, and QLK5-CT-2002-0091 to F.O.), and the Health Research Board (RP76/2001 and RP/2004/145 to F.O.).
| FOOTNOTES |
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Supplemental material for this article may be found at http://iai.asm.org/. ![]()
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